Overview and Current Status of Remote Sensing Applications Based on Unmanned Aerial Vehicles (UAVs)

Gonzalo Pajares

Abstract Remotely Piloted Aircraft (RPA) is presently in continuous battery or energy system’s capabilities. There are vehicles with development at a rapid pace. Unmanned Aerial Vehicles the ability to fly at medium and high altitudes with flight dura- (UAVs) or more extensively Unmanned Aerial Systems (UAS) tions ranging from minutes to hours, i.e., from five minutes are platforms considered under the RPAs paradigm. Simulta- to 30 hours. The horizontal range of the different platforms neously, the development of sensors and instruments to be is also limited by the power of the communications system, installed onboard such platforms is growing exponentially. which should ensure contact with a ground station, again These two factors together have led to the increasing use of ranging from meters to kilometers. Communications using sat- these platforms and sensors for remote sensing applications ellite input can also be used, expanding the operational range. with new potential. Thus, the overall goal of this paper is There are several different categorizations for unmanned aerial to provide a panoramic overview about the current status platforms depending on the criterion applied (Nonami et al., of remote sensing applications based on unmanned aerial 2010). Perhaps the most extensive and current classifications platforms equipped with a set of specific sensors and instru- can be found in Blyenburgh (2014) with annual revisions. ments. First, some examples of typical platforms used in An auto platform or remotely controlled platform through remote sensing are provided. Second, a description of sensors a remote station together with a communication system, and technologies is explored which are onboard instruments including the corresponding protocol, constitutes what is specifically intended to capture data for remote sensing ap- known an Unmanned Aircraft System (UAS) (Gertler, 2012). plications. Third, multi-UAVs in collaboration, coordination, According to Yan et al. (2009) and Gupta et al. (2013), UAS and cooperation in remote sensing are considered. Finally, are considered as the full system, including the aircraft, the a collection of applications in several areas are proposed,Delivered by Ingentaremote control station and all of the ground support elements, where the combination of unmannedIP: 192.168.39.151platforms and sensors, On: Sat, 25communication Sep 2021 13:24:12 links, air traffic control, and launching and together with methods, Copyright:algorithms, Americanand procedures Society provide for Photogrammetry recovery system, and Remote as may beSensing required (this is the opinion of the overview in very different remote sensing applications. the Civil Aviation Authority (CAA, 2015)). Unmanned Aerial This paper presents an overview of different areas, each inde- Vehicles (UAVs) are included in the category of UAS, i.e., they pendent from the others, so that the reader does not need to can fly autonomously, although they can be also remotely read the full paper when a specific application is of interest. controlled (The UAV, 2015). From the standpoint of remote sensing, the equipment of UAS is required for capturing information, which is later conveniently handled (processed, Introduction analyzed, or stored), but the term “UAV” is commonly used in Remote sensing refers to the technique of capturing informa- remote sensing. Therefore, in this paper, we will refer to UAVs tion at a distance (remotely) by specific instruments (sen- under the perspective of remote sensing operations, includ- sors). Traditionally, remote sensing has been associated with ing drones, gliders, (quad-, hexa-, octo-) copters, helicopters, satellites or manned aircraft with a set of airborne sensors. In balloon-launched gliders, airships, or stratospheric balloon the last decade, the increasing developments and improve- systems and more broadly, any unmanned vehicle with the ments in unmanned platforms, together with the development ability to fly auto-controlled using processors onboard, re- of sensing technologies installed onboard of such platforms, motely controlled with human supervision based on a ground provide excellent opportunities for remote sensing applica- station (remotely piloted aircraft; RPA) or through another aeri- tions. Indeed, they can offer high versatility and flexibility, as al vehicle under coordination. Certainly, from a strict point of compared to airborne systems or satellites, and can oper- view, all these systems should be considered as RPA systems, ate rapidly without planned scheduling. In remote sensing because they need human supervision; full autonomy is not operations with high human risk, lives can be safeguarded. generally yet achieved. Nevertheless, as mentioned earlier, Additionally, they can fly at low altitudes and slowly, with throughout this paper we will refer to them as UAVs. This the ability of acquiring spatial and temporal high resolution overview is focused on remote sensing applications based on data, representing important advantages against conventional small UAVs of different categories flying at relatively low alti- platforms that have been broadly used over the years. tudes with different take-off and landing systems, including Watts et al. (2012), Dalamagkidis et al. (2012), and Ander- Vertical-Take-Off-and-Landing (VTOL), where UAVs operate in son and Gaston (2013) provided a classification and use of different scenarios and situations. The potential use of UAVs platforms where an important issue that determines this clas- sification is the altitude they can fly, ranging from a few meters up to 9,000 m or more. Micro- and nano- air vehicles can fly Photogrammetric Engineering & Remote Sensing at low attitudes with limited flight duration because of their Vol. 81, No. 4, April 2015, pp. 281–329. 0099-1112/15/281–329 Department of Software Engineering and Artificial Intelligence, © 2015 American Society for Photogrammetry Faculty of Informatics, University Complutense of Madrid, and Remote Sensing Madrid 28040, Spain ([email protected]). doi: 10.14358/PERS.81.4.281

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 281 in remote sensing has been reported in many works with high with a set of specific sensor technologies and also with performance exploring areas of different sizes, sometimes several UAVs working in concert with each other. With such hazardous, with assumable costs as compared to traditional purpose, as far as it has been possible, we have collected most airborne or satellite systems (Jardin and Jensen, 2013). The recent technological advances, especially in the last decade, range of applications makes UAVs suitable tools in remote where the boom has occurred. Nevertheless, apologies to au- sensing with an apparent market, which is to be consolidated, thors or possible references if some of them were not cited. when UAVs are widespread, which will likely be the turning Different worldwide international associations and forums point in remote sensing, as pointed out by Esler (2010) and have emerged related to UAVs, providing ideas, information Hardin and Jensen (2011) several years ago. and opportunities for members, users, and researchers while UAVs must navigate to perform the remote sensing mission; they cover most fields and application areas, including any re- for this reason they are equipped with different instruments lated to remote sensing. Commercial benefits are also consid- and sensors, such as, Global Positioning Sensors (GPS), Inertial ered without ruling out the use of all available resources for Navigation Sensors (INS), Micro-Electro-Mechanical Systems immediate humanitarian interventions protection or search (MEMS) gyroscopes and accelerometers, Altitude Sensors (AS) and rescue in disasters. Additional member relations, oppor- (Quinchia et al., 2013) or even camera-based sensors, among tunities, and training are offered, where remote sensing is an others (Shabayek et al., 2011; Bristeau et al., 2011), where important activity (UAS Vision, 2015; UAVa, 2015; UAVc, 2015; multisensory fusion techniques are required (Oh, 2010). Obvi- UAPA, 2015, UAVS, 2015; AUVSI, 2015). Also, local associations, ously, UAVs are generally configured with control strategies for at the country or region level, become more or less active autonomous navigation that must follow a previously planned from the remote sensing point of view. path, with the ability to make autonomous decisions. Obstacle In 2006, the NASA Civil UAV Assessment Team (Yuhas, avoidance is also required during navigation. Ultrasonic sen- 2006), defined Earth observation missions forUAVs , based sors (Bristeau et al., 2011) or 3D laser scanners (Holz, 2013) on user-defined needs to determine technologies, platform are sometimes also used for safe navigation, where they can capabilities, and a comprehensive civil UAV roadmap. Later, be used for detecting other UAVs around them. Also, dynamic Colomina et al. (2008) established some fundamental issues strategies for positioning, landing, and take-off, including of UAV-based photogrammetry and remote sensing as a para- VTOL, as part of the full path planning, is necessary in normal digm, identifying challenges and specific advantages. and adverse environmental conditions, where aircraft control Many institutions, research centers and companies world- in wind conditions is essential. Moreover, UAVs require ad- wide have addressed the challenge of designing and develop- ditional logistic resources to be permanently operative, such ing UAS, with the aim of performing different missions, includ- as battery recharging or refueling. ing remote sensing: NASA (2015a), INTA (2015), NOAA (2015), Also, in recognition of technological developments and USGS (2015a). The list can be completed through the websites, advances in communications, significant progress is being where specific remote sensing missions can be found. Here, made in applications involving multiple UAVs in collaboration flight regulations must be considered for effective use ofUAVs or even between UAVs and ground systems, including UnDelivered- byin Ingentadifferent applications (Rango and Laliberte, 2012). manned Ground Vehicles (UGVs) or unmannedIP: 192.168.39.151 marine Surface On: Sat, 25Regarding Sep 2021 the state13:24:12 of the art of UAVs in remote sensing, Vehicles (USVs). CollaborationsCopyright: between American UAVs and SocietyUGVs can for be PhotogrammetryHaarbrink (2011) and provided Remote information Sensing and perspectives about found in Martínez-de-Dios et al. (2011) and Maza et al. (2011), this issue. A survey is also proposed in Ma et al. (2013) estab- and between UAVs and USVs in Sánchez-Benítez et al. (2011). lishing a framework with three levels (data acquisition, data Some studies about indices of effectiveness of UAVs have been processing, and applications). In the data acquisition level, proposed in Samkov and Silkov (2012). flight, autonomy, and trajectory were addressed. Data process- From the approach of remote sensing, navigation and all ing included photography, image matching, and mosaicking issues mentioned above, mission programming and flight and classification and finally, the applications, were catego- strategies are excluded and not specifically considered in rized as: environment and agriculture, terrain extraction, 3D this overview, unless they are essential with high degree of visualization and monitoring of hazards. Colomina and Molina involvement in remote sensing tasks. (2014) reviewed the use of UAVs in photogrammetry and re- Navigation, communication, mission programming and mote sensing (PaRS). This last work is structured according to flight strategies have been widely discussed in the scientific the following sections: (a) Introduction, where topics, names and industrial communities with abundant publications and and acronyms, pioneers, literature evolution are revised; (b) work. Being aware of this, we intentionally excluded all top- Early developments, starting at the end of 19th century with ics related with power sources, communication, navigation balloons; (c) Unmanned aerial systems and unmanned aerial (including obstacle avoidance), path planning, flight control systems for PaRS, establishing the principles for classifying systems, evasive maneuvering, landing, take-off, autonomous the different platforms; what is considered an aircraft, ground flight, fueling and refueling or localization, including Simulta- control station, communication to command and control neous Localization and Mapping (SLAM). The Ground Control the aircraft and mission planning; (d) Regulatory bodies and Stations (GCS), required by some systems, are also excluded; regulations, involving national and international agencies and this is because these specific operations are not considered as organizations; and (e) Navigation, orientation and sensing pay- specific from the remote sensing point of view, although they loads, covering autopilots, navigation and orientation systems, are absolutely necessary for conducting successful remote sensing payloads. This last including visible-band, near-infra- sensing missions. Nevertheless, some of them could be of red, multi-spectral and hyperspectral cameras, thermal imag- interest in remote sensing because they can be considered as ing, laser scanners and synthetic aperture radar; (f) Processing, the starting point for other remote sensing-based approaches. image orientation, camera calibration and surface reconstruc- By example, Pearre and Brown (2012) capture path gathering tion; (g) Unmanned aerial systems PaRS applications and geo- information, using wireless link, from sensors on the ground matic markets, agricultural and environmental applications, for path planning, but this method can be used for recovering intelligence, surveillance, reconnaissance, aerial monitoring information from sensors installed on dynamical structures in engineering, and cultural heritage. Shahbazi et al. (2014) or elements, such as glaciers or rivers with moving elements, reported on different applications including: (a) Precision ag- where methods above can be useful for remote sensing. riculture and rangeland monitoring with challenges and future Thus, the overall goal of this paper is to provide an over- perspectives, including land-cover mapping and classification, view of remote sensing applications based on UAVs equipped crop health monitoring, biophysical modeling attributes, soil

282 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING (a)

Figure 1. rpa system with the remote control system (Image cour- tesy of iscar-ucm Group, Madrid, Spain). characteristics; (b) Natural disaster management explaining advantages, including thermal disasters, ground displace- ment, floods; (c) Aquatic ecosystems management, mapping and monitoring species, characterization of water bodies; (d) Wildlife, bird and mammal detection. Whitehead and Hugen- holtz (2014) described the progress and challenges in the use of small UAVs in different environmental applications, includ- (b) ing photogrammetry, multispectral and hyperspectral imaging, thermal, and synthetic aperture radar and lidar. Considering the above classifications, paradigms and topics, this paper provides a new point of view. Indeed, as mentioned before, the overall goal is to provide an overview of remote sensing applications based on UAVs equippedDelivered with by Ingenta specific sensor-based technologies.IP: With192.168.39.151 such a purpose, On: Sat, 25 Sep 2021 13:24:12 the paper is structured asCopyright: follows. TheAmerican next section Society includes for Photogrammetry and Remote Sensing aircrafts and x-copters, where ‘x’ can be quad, six, octo, and heli, as typical platforms of UAVs used in remote sensing applications. Different sensors and technologies, onboard UAVs, are also briefly described as instruments required for such specific applications. Next, some remote sensing issues related to collaboration, coordination, and cooperation as the main topics in multi-UAVs for remote sensing applications, fol- lowed by a wide set of remote sensing applications, becoming an important contribution of this overview. Finally, the last section contains the conclusions and future trends. The paper is structured so that applications are independent; readers interested in a specific area do not need to read the full paper. The large number of references included in this overview (c) provides a suggestion of the importance and use of UAVs in Figure 2. uav multi-rotors: (a) quad-copter (Image courtesy of different application areas. We have preferred to provide Cartouav, La Coruña, Spain); (b) hexa-copter (Image courtesy of extensive references, so that the readers are provided with a Airrobot GmbH & Co., Arnsberg, Germany) and (c) quad-copter variety of topics of interest. (Image courtesy of eDroniX, Madrid, Spain)

UAVs and Sensors: Onboard Capabilities and Technologies Spain). Figures 2 (a) and (b) display two multi-rotors fly- The conjunction of unmanned platforms equipped with ing; they are a quad-copter (courtesy of CartoUAV, La Coruña, sensors onboard allows for the realization of remote sensing Spain) (CartoUAV, 2015) and a hexa-copter, respectively, missions with applications in different areas. The Unmanned (courtesy of AirRobot GmbH, Arnsberg, Germany) (AirRobot, Aerial Platforms Section displays typical platforms used 2015), used for weed patches detection in agriculture in the for such purpose. The Sensors and Technologies Section context of the RHEA (2015) project. Figure 2(c) displays a quad- describes different sensor-based technologies specifically rotor equipped with a multipurpose visible camera (courtesy designed for remote sensing tasks. of eDroniX, Madrid, Spain) (eDronix, 2015). Figure 3 displays Unmanned Aerial Platforms two fixed-wing UAVs, the Cropsight and Viewer (courtesy of Figure 1 displays a quad-copter on the ground, with its remote QuantaLab-IAS-CSIC, Cordoba, Spain) equipped with multispec- radio control system, used in collaborative missions together tral and hyperspectral, including thermal, sensors and used in airborne campaigns for biomass analysis, based on chlorophyll with USVs (Courtesy of ISCAR-UCM Group (2015), Madrid, or carotenoids content, in vineyard, citrus, peach and olive

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 283 (a) (b)

Figure 3. uav: (a) Cropsight, and (b) Viewer (Images courtesy of QuantaLab-ias-csic, Cordoba, Spain).

(a) (b)

Figure 4. (a) Helicopter hero equipped with gps, visual and infrared cameras on the pan and tilt unit, and the required hardware, and (b) Sensor system detail (Images courtesy of J.R. Martínez-de-DiosDelivered and A. by Ollero; Ingenta Robotics, Vision, and Control Group, University of Seville, Seville Spain). IP: 192.168.39.151 On: Sat, 25 Sep 2021 13:24:12 Copyright: American Society for Photogrammetry and Remote Sensing Table 1. Sensors Onboard UAVs: Auxiliary and Specific Auxiliary Specific • GPS • Video cameras (visible spectrum): EOS, • Ultraviolet spectrometer • IMU stereoscopic, omnidirectional, fish eye lens. • Multi-gas detector • Gyroscopes • Thermal cameras • Sonar • Accelerometers • Infrared cameras • Smartphone • Altimeters • FLIR • Particle counters (optical, condensation) • Video stabilizer • LIDAR (Laser scanner) • Photometer, aethalometer • Image transmitter • Multi-Hyperspectral (HyperUAS) • Aerosol sampling • Communication antennas • Irradiance • Probes (temperature, humidity, pressure) • (VHF, UHF) • Radar/SAR • Cloud droplet spectrometer • Communication modems • Radiometer (multi-frequency) • Pyranometer • Infrared spectroscopy • Electrostatic collector • Electronic nose • Radiation gauge • VCSEL • Magnetic sensor • WMS • Ultraviolet flame detector • Gas/smoke detector orchards, always related with the photosynthesis (Zarco-Tejada affecting the attributes of the remote sensing application. et al., 2013a and 2013b). However, an advantage is that small platforms require fewer Figure 4a displays the helicopter HERO equipped with GPS, logistics, unlike larger platforms. and the sensor system consisting of visual and infrared cam- Payload limits onboard UAVs represent a handicap in the eras installed on a pan and tilt unit, the hardware enclosure is use of sensors. Under this assumption new challenges appear: also displayed. Figure 4b displays the structure and detail of the sensors must be adapted to the platform or vice versa. the sensor system. (Images courtesy of J.R. Martínez-de-Dios Sensors onboard the platform should not be a serious im- and A. Ollero; Robotics, Vision, and Control Group, University pediment for maneuverability. In this regard several research of Seville, Seville, Spain). The HERO platform has been used subjects have been opened, where recent advances in MEMS for early fire detection (Martínez-de-Dioset al., 2007). are currently in continuous progress from the point of view of From the point of view of sensors onboard UAVs, payload systems engineering. and logistic requirements are two important issues to be con- As reported in Dziubana et al. (2012) and previously in sidered to ensure the success of remote sensing missions. The Everaerts (2008), UAVs are equipped with different sensors smaller platform will be more limited for payload, directly that can exceed twenty in number. Some of them are used affecting the types of sensors that can be transported and thus to capture data with the exclusive aim of controlling the

284 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING platform during navigation. Some of these sensors are speed The need to cover large areas of vision led to the develop- or pressure gauges, inertial/angular measurement devices, and ment of systems equipped with capabilities such as omnidi- also imaging sensors for SLAM. Thus, considering that such rectional vision systems (Fraś et al., 2013; Haus et al., 2013). sensors are specifically dedicated to navigation, they are no A commercial model with a CCD-based sensor is used with longer considered part of the remote sensing system, although an adjustable shutter speed ranging in 10 µs to 10 s, with ap- they are critical for successful PaRS operations. proximately a 45º Field of View (FOV). The camera rotational Additionally in remote sensing, different sensors work to- speed is 125 rpm capturing views of 360º. gether as required for the application. Indeed, UAVs equipped Omnidirectional systems are suitable for surveillance ap- with accelerometers, magnetometers, gyroscopes (most times plications. In this regard, Gurtner et al. (2009) investigated the embedded in an Inertial Measurement Unit, IMU), GPS, altim- use of fish-eye lenses to increase the angle of view in aerial eters and cameras (optical, thermal, multispectral, or hyper- photography, an application broadly used in remote sens- spectral) associate each image with the corresponding GPS ing. The lens distortion should be examined for its use with location, altitude of the UAV, and orientation (pitch, roll, and low-quality cameras. The full suite of equipment has been yaw angles), with the aim of obtaining geometric products, installed onboard mid- and small-sized (<10 kg) platforms. i.e., 3D mapping, geo-referenced images, and orthophotos. The underlying concept is its use with small UAVs for remote Franceschini et al. (2010) designed a flexible architecture sensing tasks that cannot be achieved by satellites, such as for for UAVs, aimed to enhance performance of large-scale metrol- monitoring of power lines or pipeline corridors. ogy instruments. Portability, flexibility, ease-to-use, and met- Kim et al. (2010) designed an electro-optical system (EOS) rological performance are required of different technologies for small UAVs, able to track objects and recover 3D measure- onboard UAVs, including: optical and acoustic instruments, ments from these objects. The EOS consists of commercial mechanical/electromagnetic and inertial tracking systems. image acquisition systems integrated with the corresponding Table 1 summarizes different sensors and instruments for servo-motors for pan and tilt orientation and stabilization. A remote sensing onboard UAVs. Auxiliary sensors are identified as ground control station (GCS) sends signals and receives infor- the instruments onboard UAVs required to complete tasks or ap- mation to and from the EOS. The datasheet for EOS indicates a plications dedicated to specific sensors, which are also identified. weight of about 3.5 kg with a size of 178 × 178 × 269 mm. It is Sensors and instruments are in continuous improvement installed onboard a platform with 2,050 mm wingspan, 79.5 and development, including the emergence of new technolo- dm2 wing area with an empty weight of 3.3 kg. gies. This means that in the near future most of the existing Li and Yang (2012) proposed the design of a UAV-based in- systems will change, becoming more effective. In this over- telligent photography system able to capture image and video view they are described as technologies with their capabilities. stabilized sequences with any digital camera. The fixed-wing Most of these technologies have been used in real-world UAV incorporated the following parameters, among others: remote sensing applications as outlined later in the Applica- span = 3,360 mm; load = 4 kg; ceiling = 4.5 km. The images tions Section. However, some other applications are waiting are transmitted to a GCS. In the same way, Hodgson et al. for specific relevance, and are envisaged for potentialDelivered future by Ingenta(2013) used commercial video-cameras, where the images are applications. IP: 192.168.39.151 On: Sat, 25transmitted Sep 2021 in 13:24:12 real-time to a GCS. Copyright: American Society for PhotogrammetryUndesired and vibrations Remote orSensing rotations (pitch, roll, yaw) in UVA, Sensors and Technologies not detected by the IMU and affecting the image acquisition, Video Cameras in the Visible Spectrum are compensated by developing software-based methods Video cameras are systems broadly used in UAVs for remote for video stabilization, Fowers et al. (2007) and Wang et al. sensing. This subsection deals with generic aspects related to (2012) used relevant features in the images (corners, lines) vision-based, onboard UAVs, operating in the spectral visible for such purpose. This application was also addressed in range, i.e., from wavelengths from approximately 390 nm to Buyukyazi et al. (2013) where the images are transmitted and 700 nm. Specific video systems are also considered in the Ap- processed in a ground station. This was also the approach de- plications Section. Blyenburgh (2014) provided a review re- veloped in Walha et al. (2013) based on point extraction and garding imaging and range sensors, and Colomina and Molina matching techniques between consecutive frames. (2013) provided a representative list of small and medium Feifei et al. (2012) proposed a system with four cameras for formats for visible band cameras. 3D modeling based on triangulation from the overlapped images, Nawrat and Kuś (2013), inside the editorial of the Part II which are captured under different angles of view. The combi- related to the “construction of images acquisition devices used nation can reach 130°. Grenzdörffer et al. (2012) also proposed a in UAV applications,” addressed the problem associated with four-vision camera system, with weights of 80 g including lenses image video acquisition related to the adverse flight condi- with focal length of 9.65 mm. The radiometric and geometric tions derived from operations in day or night, adverse tem- calibration problem (including inter calibration of the four cam- peratures, engines producing high frequencies and vibrations, eras) is addressed with the system onboard a quad-rotor. and unexpected UAV rotations because of wind variability Thermal Infrared Video Sensors or gusts. It is suggested that the design of systems be robust Differences between thermal and infrared sensors are due to enough to deal with such situations, as well as proper systems emitted and reflected energy, respectively. An infrared thermal to be installed onboard the UAVs, i.e., with appropriate weight sensor detects radiant energy, based on the assumption that and power consumption and with sufficient resistance against objects with temperatures above absolute zero emit infrared ra- adverse conditions. In addition, mechanical video stabiliza- diation as a function of wavelength and temperature. Accord- tion devices are to be considered ensuring that the camera ing to ISO 20473, the wavelengths of the spectral bands range video system always points toward to the direction of interest approximately as follows (Robles-Kelly and Huynh, 2013): (Bereska et al., 2013). Stability analysis and geometric calibra- 0.78 µm to 3 µm (near-infrared), 3 µm to 50 µm (middle-infra- tion of off-the-shelf digital cameras was addressed in Habib red), and 50 µm to 1000 µm (far-infrared). Some of these spec- and Morgan (2005). Figure 4 depict a visible camera, onboard tral ranges can be integrated into multispectral or hyperspec- the helicopter HERO, as part of the sensor system installed on tral sensors together with visible spectral ranges, considered a pan and tilt unit for stabilizing and targeting in the correct below. Colomina and Molina (2014) provided a representative direction. The objectives of this configuration are fire preven- list of thermal cameras in UAVs. Infrared and thermal cameras tion, detection, and monitoring (Martínez-de-Dios et al., 2007). are devices capable of operating in adverse weather conditions

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 285 Lens distortion correction methods were proposed for improving thermal imaging quality, making thermal systems more accurate for remote sensing (Yahyanejad et al., 2011). Bendig et al. (2012) equipped an octo-copter (<5 kg and payload between 0.2 to 1.5 kg) with a thermal sensor (weight of 300 g) with a mechanical trigger. Infrared cameras together with visual cameras were used in Martínez-de-Dios et al. (2007 and 2011) for surveillance in forest fire detection, at times together with ground stations for image controlling purposes. Figure 4 displays an infrared camera, onboard the helicopter HERO, as part of the sensor sys- tem on such a platform. Regarding the quality of near-infrared (NIR) images, Ariff et al. (2013) reported about the findings of quality of the captured video from a NIR imaging system pro- totype for night-time surveillance, with potential use in UAVs. UAV operations have been considered in indoor environ- ments by using active systems based on infrared sensors. This is the approach proposed in Lange et al. (2012) where the Kinect RGB-D sensor is used to obtain dense color and depth information in an indoor corridor, where the information is further processed on-board. Plate 1 displays a thermal image of a field area where each color represents a different temperature value; red colors represent higher temperature values and black ones lower values. The remaining colors represent intermediate values of temperature. Scholtz et al. (2011) equipped a fixed-wingUAV , with a wingspan of 2 m and take-off weight (TOW) of 7 kg includ- ing 1.5 kg of payload, with an infrared camera (with spectral range 800 nm - 1200 nm, and weigh = 200 g) and a multispec- tral camera with 12 channels. Forward looking infrared (FLIR, 2015) systems are adjusted and developed to be installed onboard UAVs with sizes about Delivered by22 Ingenta × 22 × 12 mm and weights up to 28 g with a lens of 35 mm, IP: 192.168.39.151 On: Sat,including 25 Sep analog 2021 13:24:12and digital video formats. Copyright: American Society for PhotogrammetryKohoutek and and Eisenbeiss Remote Sensing(2012) used a Time-of-Flight (ToF) device with 870 nm of illumination wavelength and weight of 1370 g onboard an unmanned helicopter to obtain 3D images representing surface structures. Emery et al. (2014) developed a calibrated radiometer, with a total weight of 1.36 kg, for infrared measurements of sea surface temperature from UAVs. The sensor is designed with a Plate 1. Thermal image: each color represents a value of tem- 2D microbolometer array that acquires infrared images in the perature (Image courtesy of QuantaLab-ias-csic, Cordoba, Spain). 8 µm - 12 µm range as the UAV flies forward. Lidar or low illumination, including observations during the night. Light Detection and Ranging (lidar) devices are used to mea- In Bieszczad et al. (2013) and PRlog (2013), small thermal sure distances by exploring the scene with the light (gener- cameras were designed to be installed onboard UAVs with the ally pulses emitted by a laser) projected on the targets. These aim of carrying out data acquisition in remote sensing opera- systems have been adapted for UAVs, achieving lightweight tions under adverse conditions. The spectral bands range systems useful for surveillance or mapping natural and artifi- from 8 µm to 12 µm and 7.5 µm to 14 µm, respectively. The cial structures with important improvements. Colomina and weights of the model proposed in PRlog (2013) depend on the Molina (2014) provided a representative list of laser scanners. optical system, being less than 380 g with a lens of 60 mm. Its Nagai et al. (2004) integrated a laser with a camera onboard a size is 57 × 71 × 38.5 mm plus the length of the optical sys- UAV for digital surface and feature extraction. tem. It contains analog and digital video output interfaces. Zhou et al. (2012a) presented the advance of a premature Thermal and infrared imagers were identified by Rufino flash lidar, including a complete laser emitting system (diode, and Moccia (2005) to be useful for fire detection onboard a conic lens, alignment, divergence angle) and pulse generator fixed wing vehicle (wingspan 2.75 m and length 1.7 m). The to be installed onboard a UAV. Simulated experiments were spectral response band in the thermal camera was 7.5 µm to conducted and the results reported. 13 µm, with a weight less than 120 g. The vehicle was also Wallace et al. (2012) used a multi-rotor UAV (octo-copter) equipped with a spectral sensor covering the range of 430 nm with maximum payload of 2.8 kg. It is equipped with an Ibeo - 900 nm, and a weight of 500 g. LUX laser scanner with maximum range of 200 m and scan- Sheng et al. (2010) described the design of a platform with ning at 12.5 Hz with angular resolutions of 0.25°. The remain- wingspan of 1,828 mm, weight about 3.7 kg, and equipped ing sensors within the payload are an inertial measurement with thermal cameras as a payload. Three thermal cameras unit (IMU) for positioning and orientation, a dual frequency re- with the spectral band of 7 µm to 14 µm are used, with ceiver GPS, a lightweight antenna, and a high-resolution video weights of 150 g with lens or 108 g and 97 g without lenses. camera. This system was also used in Wallace et al. (2014b). Analog and digital outputs are allowed.

286 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING Plate 2. Data captured with an altm Gemini laser scanner onboard an uav: vertical view and profiles (Image courtesy of Luke Wallace and Arko Lucieer, University of Tasmania, Australia).

Plate 2 displays data captured at 40 m from an UAV above Bendig et al. (2012) equipped a mini octo-copter (<5 kg ground level (AGL). The airborne laser scanning (ALS) data and payload between 0.2 to 1.5 kg) with a multispectral was captured with an Airborne Laser Terrain MapperDelivered (ALTM) by Ingentasystem consisting in a multiple camera array (MCA) sensor Gemini laser scanner with a pulse rateIP: 192.168.39.151frequency of 70 kHz On: and Sat, 25with Sep a total2021 weight 13:24:12 of about 720 g and mechanical trigger. It an on ground laser footprintCopyright: of 0.2 m. American The plot Societyis in a forestry for Photogrammetry contains four and arrays Remote with Sensing spectral filters of 550, 671, 800, and plantation, close to Geeveston in southeast Tasmania, Australia. 950 nm corresponding to the green and red visible bands and two bands of NIR. It was used together with a thermal system Multispectral and Hyperspectral Sensors previously described. Multispectral and hyperspectral sensors have been widely Honkavaara et al. (2013) used and described a multispec- used in UAVs-based applications for multiple purposes. The tral camera developed by the Technical Research Center of difference between these sensors and others is the number of Finland based on a Fabry-Perot interferometer with the capa- spectral bands and the wavelength range covered, including bility of selecting different spectral bands with wavelengths the visible spectrum. As hyperspectral sensors are based on ranging in 400 nm - 1000 nm. The full system is also equipped line scanning through the movement of the UAV, they require with irradiance sensors to measure different levels of this sufficient stabilization to build coherent images. Sometimes magnitude together with a GPS. The above interferometer was these systems require geometric correction using specific fea- previously described in Saari et al. (2011) and Mäkynen et tures and ground control points (Jensen et al., 2009 and 2011). al. (2011). Different tests conducted by Nackaerts et al. (2010) Multispectral sensors are non-scanning, and they, in general, and Honkavaara et al. (2012) demonstrated its performance provide lower image resolutions compared to hyperspectral for UAVs, including the processing for radiometric corrections sensors. Ren et al. (2013) presented a strategy for spectral re- (Honkavara et al., 2012) and considering irradiance values calibration (spectral response function, central wavelength, and (Hakala et al., 2013). This system was also used in Pölönen et bandwidth) using man-made ground targets. The CCD-based al. (2012) for precision agriculture and Kaivosoja et al. (2013) camera with four channels (blue: 420 nm–520 nm; green: 520 for building raster maps for a precision fertilizer application. nm–600 nm; red: 630 nm–690 nm; NIR: 760 nm–900 nm) was Mäkeläinen et al. (2013) described the use of a 2D frame mounted onboard an UAV with the targets on the ground surface. camera operating in the RGB and NIR for orthomosaicking and Multispectral and hyperspectral sensors are often used DEM production. It is built with a CMOS-based technology and together with other sensors with proven high performance to based on the Fabry-Perot interferometer. increase the remote sensing capabilities of the UAV. Colomina Kelcey and Lucieer (2012a and 2012b) used a six-band and Molina (2014) provided two lists of representative multi- multispectral sensor, which is improved based on radiometric and hyper-spectral sensors. and spatial correction techniques in order to achieve noise Achteren et al. (2007) described the MEDUSA multispectral reduction (based on dark offset imagery), sensor-based modi- instrument, ranging in 400 nm - 650 nm with weight of 2 kg fication of incoming radiance (based on spatially/spectrally and two frame sensors (panchromatic and RGB), designed to dependent correction factors), and lens distortion (through be installed in a high altitude, long endurance UAV. the Brown-Conrady Model). These corrections improved the Jensen et al. (2008) used two multispectral cameras, cover- quality of the raw multispectral imagery, facilitating subse- ing the visible and NIR spectral bands, installed onboard a quent quantitative image analysis. fixed wingUAV , with wingspan of 122 cm and weight of 454 g, Duan et al. (2013) evaluated the in-flight performance in for georeferencing. terms of signal-to-noise ratio of a new hyperspectral sensor

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 287 onboard an UAV. The sensor was a pushbroom scanner with them. Colomina and Molina (2014) provided a list of rep- linear CCD arrays operating in the spectral range of 350 nm - resentative SAR systems. Zaugg and Long (2008), Xing et al. 1030 nm with 128 bands and 5 nm of spectral resolution and (2009) and later Zhang et al. (2012) developed robust motion 1,024 pixels per line. A field campaign was conducted over compensation approaches for UAV SAR imagery, as appropriate the Baotou test site in China deploying portable reference for highly precise imaging for UAV SAR, which are also valid reflectance targets. for platforms equipped with only a low-accuracy inertial A radiometric calibration based on the vicarious method navigation system. was proposed in Pozo et al. (2014) with the aim of adjusting the Ouchi (2013) provided specifications ofSAR systems involved parameters to better collect the information provided onboard UAVs operating at X (7 - 12.5 GHz) and Ku (12 to 18 by the sensor. The multispectral sensor is a CMOS-based with GHz) bands. Koo et al. (2012) proposed a SAR-based system six channels, weight of 1025 g, and geometric resolution of operating at the C-Band (ranging from 3.7 to 4.2 GHz and 5.9 1280 × 1024 pixels in size. This system was installed onboard to 6.4 GHz) and single VV polarization. It was designed for an octo-copter with weight of 2,420 g including the battery. monitoring soil resources, crops, and trees in agriculture and Imaging spectrometers were designed with high technolo- forestry. Wang et al. (2009), Saldaña and Martinez (2007), or gy to work as hyperspectral devices onboard the UAVs (Hruska González-Partida et al. (2009) designed and developed SAR et al., 2012). The integration of these devices with IMU and systems working at the millimeter-wave band with the aim of GPS allows obtaining direct imaging georeferencing after im- transmitting large bandwidth, i.e., high spatial resolution. Al- age processing. Additional efforts for spectral calibration of though this band could represent a problem caused by motion hyperspectral data observed from a hyperspectrometer have errors, that could be larger than the UAV operation resolution, been reported in Liu et al. (2014). they can be compensated with algorithms such as the Range The ability of UAVs to fly at low altitudes, equipped with Migration Algorithm or using an IMU to align target responses specific technologies, allows the acquisition of images with (González-Partida et al., 2009). Two SAR-based instruments, both, ultra-high spatial and spectral resolutions. Lucieer et al. operating in the C- and X-bands, were described in Aguasca (2014b) described the design and operability of a new hyper- et al. (2013). They are based on dual receiving channels with spectral UAS (HyperUAS), a multi-rotor helicopter carrying the ability to work in interferometric and polarimetric modes a pushbroom spectroradiometer in conjunction with a dual and equipped with a motion compensation unit to avoid also frequency GPS and an IMU. The HyperUAS prototype acquires motion errors. hyperspectral images with 324 spectral bands and 2 to 5 cm Nouvel et al. (2007 and 2009) developed a low-cost radar spatial resolutions after spectral and radiometric calibration system to enable avoidance of shading effects produced by SAR and atmospheric correction. Burkart et al. (2014) developed a systems in mountains or urban areas with high density of trees. hyperspectral measurement system for UAVs, operating in the With the aim of minimizing the above effects, Weiss et al. (2007) spectral range of 350 nm - 800 nm, based on the Ocean Optics proposed the 3D ARTINO (Airborne Radar for Three-dimensional STS microspectrometer with a weight of 216 g. Imaging and Nadir Observation) imaging radar system. Suomalainen et al. (2014) designed a lightweight hyperDelivered- by IngentaA radiometer operating in the L-band at 1.4 GHz was de- spectral system, with off-the-shelf components,IP: 192.168.39.151 for rotor-based On: Sat,signed 25 Sep in Acevo-Herrera 2021 13:24:12 et al. (2010) and installed on an UAV, UAVs with weight of 2 kg. It Copyright:consists of threeAmerican elements: Society a push for- Photogrammetrytogether with a and GPS Remoteand an IMU Sensing. broom spectrometer with spectral range of 400 nm - 950 nm The SARVANT platform is a fixed-wing aerial vehicle with and spectral resolution of 9 nm, a photogrammetric camera, a six-meter wingspan and a payload weight of 45 kg (Remy and a GPS/Inertial Navigation System. Geometric and radiomet- et al, 2012; Molina et al., 2013). SARVANT is equipped with a ric procedures are designed for DSM production in agriculture. dual-band (X and P) interferometric SAR, where the P-band Zarco-Tejada and Berni (2012) equipped a fixed-wing enables the topographic mapping of densely tree-covered vehicle with a micro hyperspectral imaging sensor for vegeta- areas, providing terrain profile information. The combination tion monitoring. These authors and co-workers in the research of X- and P-band data can be used for biomass estimations. It group QuantaLab-IAS-CSIC (2015) have also used multispectral is also equipped with a double optical system to cover visible and hyperspectral sensors for different purposes, mainly in and NIR spectrum. agriculture and forestry, as described later. Plate 3 displays a Schulz (2011) and Essen et al. (2012) developed two mil- multispectral image in Plate 3a and a hyperspectral image in limeter wave radar, both operating at 94 GHz, to be integrated Plate 3b, both courtesy of QuantaLab-IAS-CSIC, Cordoba, Spain. onboard two unmanned helicopters with payloads of 30/35 kg Some Color Infrared (CIR) cameras are designed with four and maximum weight of 125/85 kg (with fuel), respectively. spectral channels covering the three R, G, B spectral bands and The design of radars was based on the Frequency Modulated the infrared band, i.e., they belong to the category of multispec- Continuous Wave (FMCW) principle, to get the highest possible tral systems. Plate 4 displays four strips built with a CIR system. average transmission power with the best range of performance. The left and right strips represent RGB images; the left central strip represents a Digital Surface Model (DSM) with the associ- Chemical Sensors ated color-bar representing surface heights (in meters); the Right Berman et al. (2012) described the design and adaptation of the Off-Axis Integrated Cavity Output Spectroscopy (Off-Axis central strip represents the RGB plus the IR channel. These im- ICOS) for UAVs, primarily described in Paul et al. (2001) and ages are courtesy of QuantaLab-IAS-CSIC, Cordoba, Spain. Baer et al. (2002), with an operating principle based on in-

Radar/SAR frared spectroscopy for measuring water vapor (H2O), carbon Synthetic Aperture Radar (SAR) systems have been installed dioxide (CO2), and methane (CH4). This sensor fulfills the onboard UAVs with successful results. Rosen et al. (2006) payload requirements for the UAV provided by NASA (Sensor proposed the design of a polarimetric SAR system with a range Integrated Environmental Remote Research Aircraft, SIERRA), bandwidth of 80 MHz for UAVs. Wang at al. (2009) developed which is midsize with 6.1 m wingspan, 3.6 m long, and 1.4 m an operative system based on a technology that combines high with a cruising speed of 28 m/s and a maximum alti- millimeter-wave frequency-modulated continuous-wave and tude of 3,600 m. SIERRA can carry a 40 kg payload measuring SAR. The transmission power required is feasible in UAVs. This 40.5 cm × 40.5 cm × 30.5 cm and can provide up to 200 W of system appears to be an active image sensor, which can be aircraft power. used in remote sensing applications, similar to SAR onboard A biologically inspired electronic nose is deployed and satellites, where land cover for texture analysis is one of installed on an UAV in Bermúdez i Badia et al. (2007) based

288 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING (a) (b)

Plate 3. (a) Multispectral image, (b) hyperspectral image (Images courtesy of QuantaLab-ias-csic, Cordoba, Spain).

Delivered by Ingenta IP: 192.168.39.151 On: Sat, 25 Sep 2021 13:24:12 Copyright: American Society for Photogrammetry and Remote Sensing

Plate 4. Four strips obtained from a cir system: Left and right strips represent rgb images; left central strip is a dsm, with the associated color- bar representing heights; right central strip represents the rgb plus the ir channel. (Image courtesy of QuantaLab-ias-csic, Cordoba, Spain) on thin-metal oxide technology, for humanitarian demin- mass excluding payload of approximately 4.7 kg. Malaver et ing, which is sensitive to different volatile compounds. This al. (2015) integrated a solar powered UAV (3 kg payload) with device is installed onboard a blimp built with a hull filled wireless sensor networks (WSN) to measure concentrations of with helium. It is 4.5 m long, with 1.2 m diameter, and 6 m3 CH4 and CO2 in greenhouses. The UAV was equipped with a of volume, with a payload of approximately 3 kg. gas sensing system based on nanostructured metal oxide and Gas emissions come from different activities. Indeed, non-dispersive infrared sensors. greenhouse is an emerging activity in agriculture with gas Volcanic gases were measured at La Fossa crater, Vul- emission. Methane is a gas flowing in gasification plants or cano Island (Italy) by McGonigle et al. (2008) with an UAV refineries. Regarding gas detection withUAVs , Khan et al. flying through the plume and equipped with an ultraviolet

(2012a and 2012b) proposed a VCSEL (vertical cavity surface spectrometer for the SO2 flux and a multi-gas sensor system emitting laser) sensor for measuring H2O, CO2, and CH4 in consisting in a non-dispersive CO2-H2O infrared spectrometer, greenhouses based on Wavelength Modulation Spectroscopy an electrochemical SO2-H2S sensor, and a H2 semi-conductor. (WMS); the device is installed onboard a helicopter with Different ratios of CO2/SO2 are measured. This multi-gas sen- payload capacity of up to 5 kg. The UAV is 133 cm long, 41 sor technology was also installed onboard an UAV for analyz- cm high, has a main rotor diameter of 156 cm, with a flying ing volcanic gas compositions of Shinmoedake, Kirishima

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 289 volcano, Japan (Shinohara, 2013). The weights of such issue, involving positioning, coverage, throughput, or channel systems vary from 1.5 to 3 kg. The UAV used in Shinohara modeling among others (Zhan et al., 2006 and 2011, Burda- (2013) was a helicopter with a fuel engine and 710 mm stan- kov, 2010; Li and Zhang, 2010; Xin et al., 2010; Olsson et al., dard carbon fiber blades; its weight is 5.2 kg. The helicopter 2010; Yanmaz et al., 2011; Lin et al., 2011, Yanmaz, 2012; dimensions were 1410 × 465 × 190 mm. Zhou et al., 2012b; Rohde et al., 2013). Krüll et al. (2012) used sensors for gas and smoke detec- tion based on semiconductor technology. Hydrogen produced Atmospheric Instrumentation Corrigan and Ramanathan (2008a) introduced a set of atmo- in open fires and also hydrocarbons CxHx, generated during the fire evolution are detected. They are also able for dis- spheric instruments specifically designed forUAVs , specifical- ly: (a) optical and condensation particle counters for detecting criminating among dust, mist, or other aerosols. The UAV is a quad-copter with a diameter of about 1vm, a weight of about particles in the atmosphere above 10 nm; (b) aethalometer for 1 kg. Data are transmitted to a ground control station though measuring the concentration of particles based on the absorp- tion of a beam of light; (c) sampling of aerosols; (d) probe for wireless local area network (WLAN). temperature and relative humidity; (e) cloud droplet spec- Sonars trometer between 1 and 50 µm; (f) pyranometer for measuring Misnan et al. (2012a and 2012b) experimented with 2D sonar solar irradiance; (g) photosynthetically available radiation (400 and the associated analytical process for ranging and mapping nm - 700 nm); (h) liquid water content probe for measuring the surfaces with an UAV flying at low altitudes. The transmitter water in the clouds; and (i) video camera for cloud detection. and receiver are placed close among them to achieve maxi- Corrigan et al. (2008b) described the use of several devices mum accuracies. This technology, based on sound waves, is for data air analysis, including a meteorological system (pres- rarely used in UAVs for remote sensing, but is used widely in sure, temperature, and relative humidity), an optical particle navigation where ultrasonic sensors are useful in UAVs for col- counter, and an aerosol absorption photometer. These systems lision avoidance during navigation. are installed onboard an UAV with a maximum takeoff weight of 27 kg, a wingspan of 2.6 m and an overall length of 1.9 Communications/Data Transmission m. The aircraft can lift a 5 kg payload in a 12 l compartment In remote sensing applications, communications become while carrying 8 l of fuel. of special interest either for coordination and collaboration Bates et al. (2013) measured vertical distribution of aerosols between UAVs or for data transmission. With such motivation, on Svalbard, Norway. The UAV was equipped with: (a) one GPS and VHF/UHF antennas were integrated into UAVs (Strojny mixing condensation particle counter;(b) one three-wavelength and Rojas, 2009). absorption photometer, a Multi-Channel Chemical Filter The data acquired in UAVs must be transferred for process- Sampler (MCCFS) consisting of eight, off-the shelf filter hold- ing or for integration with other systems or data. High-speed ers with 13 mm of diameter and a magnetically driven, rotary modems were designed for high-speed wireless data transmis- valve manifold to distribute the vacuum/flow from one central sion, suitable for surveillance or reconnaissance tasks (Rupar pump to each of the separate sampling channels; and (c) two et al., 2009). Delivered byprobes Ingenta of temperature and relative humidity to collect data at Bhaskaranand and Gibson (2011) developedIP: 192.168.39.151 a low-com- On: Sat,different 25 Sep atmospheric 2021 13:24:12 layers. The aircraft weighs 16.3 kg with- plexity encoding approach Copyright:for high speed American data transmission. Society for Photogrammetryout payload and and fuel Remote (27.7 kg Sensing maximum takeoff weight). The Data transmission represents a challenge particularly with the wingspan is 2.7 m, height is 0.62 m, and length is 1.92 m. growing interest for its use in real-time applications, includ- A spectrometer probe and an electrostatic collector for aero- ing those that send real-time video for monitoring events. sol measurements, size and distribution, were the instruments Municipalities and other institutions are demanding high adapted for UAVs in addition to temperature and humidity performance surveillance services, where video strips must be relative probes for measurements (Claussen et al., 2013). transmitted to a GCS for monitoring purposes (Israel, 2011). Pressure, temperature, and relative humidity are atmo- Embedded or blade antennas are elements onboard UAVs spheric variables that can be measured with specific instru- for transmission or reception. The embedded operational ments onboard UAVs. In Mayer (2011) and Reuder et al. (2009), a systems preserve the aerodynamic characteristics of the air- SUMO (Small Unmanned Meteorological Observer) system with craft (Patrovsky and Sekora, 2010). Abdelkader et al. (2013) wingspan 0.80 m, length 0.75 m, height 0.23 m, and TOW of 580 used antennas to identify lagrangian micro-sensors drifting in g was the system equipped with such sensors with the ability of flooded areas to monitor the evolution of the flooding. capturing data at 2 Hz. Cook et al. (2013) used a probe, onboard The Smartphone proposed in Yun et al. (2012) and Kim et a wing-fixed UAV, with humidity and temperature sensors for al. (2013) uses 3G internet accesses for communication with the coastal atmospheric research in New Zealand. ability to become a remote server for storing images and data. Brown et al. (2011) described the upgrading, for the deploy- Radio communications, including UHF, are feasible for im- ment on the Global Hawk UAV platform, of the existing high- age transmission, after compression, achieving ranges of 2 to 5 altitude monolithic microwave integrated circuit sounding km with low and high directivity antennas (Wada et al., 2015). radiometer, with a 25-channel cross-track scanning microwave As an intrinsic element in communications, UAVs can be sounder with channels near the 60 and 118 GHz oxygen lines used as nodes in WSN, establishing links to other nodes which and the 183 GHz water-vapor line. The upgrading consisted of can be fixed or moving, including otherUAVs (Antonio et al., the addition of a front-end, low-noise amplifier developed by 2012). Additionally, the UAV can serve as a sink of data col- JPL, to the 183 GHz channel. This instrument was used in three lection to be sent to other nodes. Also in the context of WSN, hurricane field campaigns for atmospheric observations, in- Tuna et al. (2012 and 2014) proposed a team of UAVs, tested cluding temperature, water-vapor, cloud-liquid water, convec- with helicopters, for establishing an effective communica- tive intensity, precipitation, and 3D storm structure. tion system considered as essential after natural disasters for rescue operations. The proposed system is a post-disaster so- Radiation Instruments lution where each UAV in the team has an onboard computer Some nuclear and radiation accidents and incidents (Wikipe- which runs three main subsystems responsible for end-to-end dia, 2015) have motivated the design and development of radi- communication, formation control and autonomous naviga- ation sensors onboard UAVs; one of which was the instrument tion in communication with a GCS. Different works addressed proposed by Towler et al. (2012) onboard a helicopter with the wireless communication problem where the experiments 20 kg of weight, together with imagery sensors. The sensor is were conducted for testing some problems related to this a lightweight sodium-iodide scintillating crystal to convert

290 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING gamma rays to visible light photons. A photomultiplier am- Zhou and Reichle (2010) proposed a mathematical model plifies the flashes in the crystal to voltage levels, which are for multi-sensor data integration consisting of video stream, supplied to an electronic device to convert the analog signal to GPS, a three-axis magneto-inductive magnetometer, and a spectral information and finally transferred to a ground station high-performance two-axis tilt sensor (inclinometer), for both computer. Several processing techniques are also proposed for photogrammetry tasks and navigation. gathering measures and mapping the radiation effect. The use of Smartphones can be considered as multisen- A ranger fixed-wing unmanned aerial vehicle was designed sory devices. They have been proposed for photogrammetry in Kurvinen et al. (2005) and equipped with three different applications onboard UAVs (Yun et al., 2012; Kim et al., 2013). radiation detector types to locate plumes with different activi- Smart phones can operate in broad areas under 3G telecom- ties and also to avoid saturations in some detectors, namely: (a) munication networks, they are equipped with MEMS sensors, a dose rate meter, GM; (b) a cintillation detector, NaI(Tl), and (c) including accelerometer, magnetometer, gyroscope, and GPS, a compound semiconductor detector, CdZnTe. These sensors to- which allows image acquisitions with the required informa- gether with a visual camera were conveniently encapsulated and tion to generate photogrammetric products. installed on an UAV. Pöllänena et al. (2009) using a commercial With the aim of obtaining direct georeferenced images, CsI detector in the area of (137) Cs and (131) I, which were able captured from an octo-copter (1.5 kg of payload and 4.8 kg to detect radioactive particles during the flies on boardUAVs . total weight), Rehak et al. (2013) integrated a consumer-grade MacFarlane et al. (2014) developed a new instrument to digital camera, a geodetic-grade RTK-GPS/Glonass/Galileo provide rapid and high spatial resolution assessment of radionu- multi-frequency receiver at 10 Hz sampling frequency, and four clide contamination. The full system consists of an unmanned MEMS-IMU chips with a Field Programmable Gate Array (FPGA). hexa-copter equipped with a gamma ray spectrometer, a micro- Data fusion is required for combining the information controller, GPS, and lidar. The goal is to rapidly and remotely provided by different sensors. With such purpose, Jutzi et al. detect ground-based radiation anomalies with a high spatial (2014) proposed a method that weights the data captured with resolution. Source samples used within this study were speci- both a visual camera and a lightweight line laser scanner for mens collected from the Cornubian batholith, Southwest UK. 3D mapping production. A multisensory system has been integrated onboard a Magnetic Sensors quadrotor in Roldán et al. (2015) to measure temperature, A high-resolution 3-axis magnetic sensor has been mounted humidity, luminosity, and CO2 concentration in a green- on a helicopter to generate detailed magnetic maps and to house. The integration has been carried out in the Raspberry identify various ferrous objects in the soil in the work of Eck Pi device because its performance. and Imbach (2011). The specifications of the helicopter are: main rotor diameter of 3.20 m, payload weight of approxi- mately 30 kg including 10 l. UAVs in Collaboration, Coordination, and Cooperation Multisensor Technologies Collaboration, coordination, and cooperation are relevant Although generally speaking, UAVs are equipped withDelivered various by Ingentaconcepts when several UAVs are programmed to achieve a sensors for both navigation and detection.IP: 192.168.39.151 Here we address On: Sat, 25remote Sep 2021sensing 13:24:12 goal. Some years ago, Ollero and Maza (2007) multisensor technologiesCopyright: from the pointAmerican of view Society of remote for Photogrammetry noted that aand multiple Remote UAV Sensing-based approach increases the sensing applications providing insights. spatial coverage, improves the reliability due to redundancy, MAVIS (Massive Airspace Volume Instrumentation System) allows the simultaneous intervention in different places, and project addresses specifically the design of multisensory tech- makes possible the teaming of specialized UAVs. Coopera- nologies (Sobester, 2011 and 2014). tion of UAVs for different tasks has recently received special Vierling et al. (2006) designed a multisensory system on- attention. Each vehicle has assigned a portion of the goal and board a tethered balloon with the following equipment: a dual all collaborate to achieve the global goal with the maximum channel spectro-radiometer with wavelengths from 350 mn - performance and accuracy as possible. This is an added value 1050 nm, an RGB micro-video camera, a thermal infrared sensor for these concepts in remote sensing, where technologies and sensitive to the spectral range of 7.6 μm to 18 μm, a GPS receiver, research must be united for effective actuations (Chao and tilt sensors, an analog compass sensor, a wireless video trans- Chen, 2012). Obviously, the systems included in this section mission device, meteorological sensors for measuring relative are designed for specific missions and applications. Because humidity, temperature, barometric pressure, and wind speed. of the special characteristics, they have been included in this Some areas of application have been identified, including section, although some of them appear later in the Applica- canopy vegetation analysis, atmospheric data collection, trace tions Section, under specific applications. Table 2 displays gas flux measurements or aquatic remote sensing among other. different strategies applied under collaboration in coordina- Martínez-de-Dios et al. (2007) used a fleet of three UAVs tion and cooperation for remote sensing missions and perfor- in cooperation for fire detection. OneUAV (Helivision-GRVC) mance. Different applications, where cooperation becomes is equipped with infrared and visual cameras; Figure 4b efficient are also reported. displays details of this system. The second UAV (Marvin) Distributed systems architecture and control-based strate- is equipped with an ultraviolet flame detector, provided gies are critical in UAVs formations, networking, and collabo- by Hamamatsu. This device is based on the photoelectric rations for effective performance (Maza et al., 2010; Richert effect of metal and gas multiplication and operates on the and Cortés, 2013). Maza et al. (2011) proposed a multi-UAV wavelengths range of 185 nm - 260 nm. Finally, the third distributed architecture where each vehicle is in charge of a UAV (Karma) contains a stereoscopic system with two visual task or set of tasks. This architecture has been validated in cameras for 3D mapping. several applications, including: surveillance, wireless sensor Multisensory systems for disaster monitoring and man- distribution, and fire detection and extinguishing. agement are designed in Choi et al. (2009) and Choi and Lee In most cases, early intervention is crucial, particularly in (2011). In the latter, a rotary-wing UAV is equipped with two emergencies; cooperation and collaboration can be the solution. digital cameras (470 g and 115 g), a laser scanner (7 kg), GPS Cooperative control strategies in UAVs for detection and track- (75 g), IMU (3.4 kg), and a communication system, based on a ing are assigned to each vehicle an area, element, or specific RF link with a ground control station. A computer, a gimbal, task. This approach is described in Pack et al. (2009) for track- and a power supply are elements on-board for data process- ing ground mobile units emitting intermittently radio frequen- ing, compression, and transmission. cy signals. Tracking means that they must fly in coordination to

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 291 Table 2. Collaboration: Strategies and Applications Strategies Applications • Distributed architectures • Surveillance • Search and rescue • Multi-agent systems • Visual perception • Wireless sensor distribution • Data fusion • Tracking (ground mobile units, contaminant clouds) • Nuclear radiation detection (simulation) • Multiple UAVs • Fire (prevention, detection, tracking, extinguishing) • Disaster monitoring • UAVs/USVs in collaboration increase the reliability of the team where identification among the units plays an important role (Heredia et al., 2009). Col- laboration of multiple UAVs allows for data sharing, including images between the different vehicles (Quaritsch et al., 2011). In order to improve performance in remote sensing mis- sions, an important issue concerning collaboration between UAVs consists of the anticipation of anomalies in some units within the fleet. Bethkeet al. (2008) proposed a method to deal with these effects under the framework of multi-agent systems. Cooperative visual perception, from heterogeneous multi- UAVs, was soon identified as useful because of its potential in visual perception tasks (Merino et al. 2006a and 2007). A fleet of heterogeneousUAVs (one airship and two helicopters), equipped with various sensors (infrared, visual cameras, and fire detectors), cooperate in automatic forest fire detection and localization tasks using a distributed architecture based on the blackboard communication system (BBCS). Research has pointed out that heterogeneity increases the complexity of the problem, but also provides several advantages such as the possibility to exploit the complementarities of different UAV platforms with different mobility attributes and also different sensor and perception functionalities. Merino et al. (2015) proposed a decision and control architecture for multi-UAVs teams in forest firefighting. Different techniques derived from infrared and visual imagery were applied. A fleet of UAVs is proposed in Jensen et al. (2009) underDelivered by Ingenta the assumption that redundancy and distributedIP: 192.168.39.151 information On: Sat, 25 Sep 2021 13:24:12 are more profitable. TheUAV Copyright: fleet is used American for measuring Society windfor Photogrammetry Figure 5. Mosaic and built Remote with more Sensing than five hundred images from dif- speeds and acquiring data for 3D photogrammetry. ferent uavs (Image courtesy of J.R. Martínez-de-Dios and A. Ollero; Zheng-Jie and Wei (2013) proposed a strategy to achieve Robotics, Vision, and Control Group, University of Seville, Spain). maximum coverage in surveillance missions when multiple UAVs are involved. In this way, Cook et al. (2013) proposed a such as ground or marine. Here, distributed architecture control learning-based strategy for target tracking in urban areas, becomes again critical for resolving conflicts, tasks allocation, where the goal is to achieve maximum coverage with three UAVs. and their distribution or sensor data fusion coming from all Motion estimation and relative displacements between vehicles or systems. Maza et al. (2011) proposed a distributed several UAVs in collaboration also represents a challenge. Im- architecture for autonomous cooperation involving UAVs, wire- age matching, with blob-based and estimation of homography less sensor/actuator networks, and ground camera networks. between images obtained from different UAVs was addressed Murphy et al. (2008) used aerial and sea surface vehicles in Merino et al. (2006b). The images are aligned by reducing in cooperation for monitoring and analysis disaster for the the global alignment error leading to a refined homography re- Hurricane Wilma. sulting in a mosaic built with more than five hundred images Based on simulation and statistical analysis, Lanillos et al. acquired from different UAVs. Figure 5, adapted from Merino (2014) studied the advantages of using the expected observa- et al. (2006b), displays a mosaic obtained by the method de- tion heuristic in multi-vehicle coordination for search. Coor- scribed by the authors. dination of a team of autonomous sensor platforms search- A cooperative UAVs-based system for monitoring and tracking ing for lost targets under uncertainty is studied. A real-time forest fires was explored in Casbeeret al. (2005 and 2006). Coop- receding horizon controller was developed in continuous eration for surveillance in fire detection with a fleet of three het- action space based on a decentralized gradient-based optimi- erogeneous UAVs was studied in Martínez-de-Dios et al. (2007). zation algorithm and by using the expected observation as an Multi-UAVs systems are designed, as appropriate, for rapid estimate of future returns, which is an estimate of the possible intervention when the remote sensing task is urgent. Han et cumulative rewards that are obtainable in the future. al. (2013) proposed this type of systems for nuclear radiation A team of UAVs is used for patrolling and surveillance of a detection, where two scenarios are simulated with the aim of network of roads in Las Fargeas et al. (2015). A cooperative mapping the contour of actuation. surveillance task is formulated as a NP-hard problem based on a Sinha et al. (2009) tested a coordinated strategy for track- heuristic approach analyzed with completeness and complexity. ing a contaminant cloud in urban environments where multi- The cooperation between UAVs and UGVs (Tokekar et al., UAVs work together under a simulated scenario. 2013) and USVs also becomes an important challenge; Figure Mase (2013) proposed the cooperation of electrical and fueled 6a displays a quad-rotor onboard a patented landing platform (gas, oil) vehicles to cover non-overlapped areas in disasters. (Cruz et al., 2015), specifically designed for precise approxi- Cooperation and collaboration is not only limited to air ve- mation with full orientation during the landing operation, hicles themselves, but can also involve other types of vehicles two USVs and the UAV are all in cooperation for search and

292 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING (a) (b)

Figure 6. (a) Quad-rotor landed onboard a usv (boats property of Distance University of Spain, uned), and (b) Landing platform (Images courtesy of ISCAR-UCM Group, University Complutense of Madrid, Madrid, Spain)

Table 3. Applications: Areas and Topics Areas and topics • Agriculture and forestry • Vegetation • Crops and weeds • Coverage • Trees in forestry • Development • Forests • Soil and others • Disaster monitoring • Photogrammetry • Hurricanes, typhoons and tornados • Digital elevation models and 3D mapping • Earthquakes • Mosaicking, ortho and geo-rectification • Fire • Measurements • Nuclear leaks • Cadastral applications • Spills detection • Floods • Atmospheric • Avalanches • Observation • Epidemiology Delivered by •Ingenta Air analysis and pollution IP: 192.168.39.151 On: Sat, 25 Sep 2021 13:24:12 • Humanitarian • Cultural • LocalizationCopyright: American Society for Photogrammetry• Heritage and Remote Sensing • Rescue • Archeology • Surveillance • Wildlife: inventories and monitoring • Traget detection • Fauna • Tracking • Flora • Environmental monitoring • Urban environments • Volcanic inspections • Surveillance • Soils • Tracking • Aquatic environments • Road information • Canopy • Urban configuration • Rural roads and geological infrastructures • Facades analyisis • Urban terrain reconstruction rescue missions in marine environments (Sánchez-Benítez et agricultural forestry and fisheries (environmental monitoring, al., 2011). Figure 6b displays the same landing platform with crop dusting, optimizing use of resources); (e) earth observa- the quad-rotor, from CartoUAV (2015) company, onboard with tion and remote sensing (climate monitoring, aerial photogra- an enlarged level of detail. The use of the landing platform phy, mapping and surveying, seismic events, major incident, can be extended to different scenarios and environments. pollution monitoring); and (f) communications and broadcast- ing (Very High Altitude-Long Endurance (VHALE) platforms as proxy-satellites and Medium Altitude-Long Endurance (MALE), Applications or Small and Mini-Unmanned Aerial Systems (S/MUAS) as The number of applications where UAVs become useful tool short-term, local communications coverage). Nowadays, seems almost unlimited and is continually growing. We have many developments have followed these lines with success- considered different applications grouped under major topics. ful results. The overview about the current state carried out in Then, when appropriate, we break them down in other subtop- this paper focuses on a set of applications classified under the ics. Obviously, this does not mean they are exclusive and surely, specific topics displayed in Table 3 for various areas. This di- other applications not covered here could be also relevant. vision is established considering the main application, taking The European Commission (2007) identified a set of cur- into account that some type of overlapping among them may rent and potential UAV procurements, including: (a) govern- occur. Indeed, when a disaster occurs, humanitarian localiza- ment (police, civil security, border security, coastguard); tion and rescue are tasks to be executed immediately. Pho- (b) fire-fighting (forest fires, emergency rescue, other major togrammetry (mosaics, ortho-rectification) is an application incidents); (c) energy sector (oil and gas industry distribution useful with great relevance in agriculture, cultural heritage, infrastructure, electricity grids, distribution networks); (d) and archeology or urban environments, among others.

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 293 Agriculture and Forestry estimations, herbicide applications, and pesticide control Remote sensing is a classical and traditional approach widely resulting in cost savings and minimal environmental impact. applied in agriculture and agronomy for different purposes The wider use of UAVs in this area consists on the acquisi- (Atzberger, 2013). Farmers have expressed some requests to tion of information using sensors onboard, to serve as inputs monitor crop conditions in their fields usingUAVs . In Zhang to other agricultural systems, such as tractors, that apply agri- et al., (2014) a quad-copter equipped with optical and near- cultural treatments. Nevertheless, an exception is the system infrared imagery has been used to monitor fertilizer trials, described in Huang et al. (2009) where a low volume spray conduct crop scouting, and map field tile drainage in Ontario, system is designed to be installed and integrated onboard an Canada. The results of a preliminary investigation into the use unmanned helicopter to apply crop specific treatments. A of aerial surveillance techniques to estimate weed-patch areas helicopter, powered by two gasoline engines, with rotor diam- were presented very early by Thornton et al. (1990) using a eter of 3 m and maximum payload of 22.7 kg, was equipped low-altitude helium balloon based on imagery for mapping with the sprayer system consisting of boom tubing and the wild oat distribution in a wheat field. This platform was nozzles, spray pump, control box, and spray tank for chemi- later used in Jensen et al. (2007) for detecting attributes in cal with a total weight of approximately 11 kg. The sprayer on wheat crops. the UAV was designed to spray 14 ha of land on a single load Since the beginning of the development of new generations at a low volume spray rate of 0.3 L/ha. of UAVs, these platforms were considered a well suited tool, Despite this standalone application, this overview is under different configurations, in agriculture and forestry focused on the first type, i.e., UAVs equipped with sensors because of their potential (size, weight, flight speed, altitude) onboard that provide data for subsequent analysis and treat- (Grenzdörffer et al., 2008; Gay et al., 2009). Currently, they ments when required. continue offering new opportunities as well as new chal- Many applications in crops are oriented to the genera- lenges (SARS, 2014). Herwitz et al. (2004) and Furfaro et al. tion of maps for monitoring weed infestations and coverage, (2005) used early-unmanned aerial platforms in a plantation biomass estimation, yield prediction, or crop stress. Imaging of Kauai Coffee Company in Hawaii, equipped with multi- maps are commonly georeferenced and ortho-rectified, where spectral imagery and a local area network for camera control positioning accuracy becomes an important consideration in and downlinking images. UAVs are recently becoming part of map generation. remote sensing applications in agriculture and forestry with In this regard, Sugiura et al. (2005) developed a system very different and diverse applications; some of them gaining based on an unmanned helicopter for precise mapping in in performance while being inexpensive compared to tradi- maize fields. They applied geometric corrections based on a tional platforms. Zhang and Kovacs (2012) and Stefanakis et real-time kinematic global positioning system (RTK-GPS), an al. (2013) identified a research agenda to developUAV systems INS, and a geomagnetic direction system (GDS). An imaging and define methods for precision agriculture. In this regard, sensor installed under the fuselage captures images. The large Urbahs and Jonaite (2013) proposed the main features for us- errors of the GDS data, due to a geomagnetic warp surrounding ing UAVs in agriculture applications, including weight,Delivered flight bythe Ingenta helicopter, are corrected based on the parallel crop rows duration, flight altitude, payload, andIP: engine. 192.168.39.151 On: Sat,after 25 imagery Sep 2021 was 13:24:12 collected. A categorization of mobileCopyright: platforms American and resulting Society research for Photogrammetry Cross-pollenization and Remote in maize Sensing crops was studied in Vo- applications were reported in Zecha et al. (2013) where UAVs’ gler et al. (2009) because of the importance to achieve the design and characterization are focused on their use for agri- coexistence of conventional and genetically modified maize cultural tasks. More specific works dealing with the develop- with the aim of achieving acceptable yields. The impact of ment and testing of a UAV aerial platform for agricultural tasks elevation differences between adjacent donor and receptor equipped with multispectral cameras can be found in Link et fields on rates of cross-pollenization was analyzed using a al. (2013). An overview of works involving the development Geographic Information System (GIS). Digital images were of technologies, systems, and methods for UAVs are examined captured with a digital still-video camera mounted on an and studied for agricultural production management in Huang unmanned helicopter. et al. (2013), where limitations of current UAVs for agricultural Quantification of nitrogen status of rice and winter wheat tasks are reported, as well as future needs and suggestions for were studied in Zhu et al. (2009) and Yunxia et al. (2005), development and application of UAVs in agriculture. respectively, to avoid under/over fertilization. Hyperspectral In the context of agricultural and forestry, the control of imagery was used for computing chlorophyll content to char- biophysical variables is of special interest for various pur- acterize spatial and temporal variation in crop production. poses, such as chlorophyll and biomass determination for site Øvergaard et al. (2010) used three radiometers as sensors specific treatments or forest stands. Several methods and strat- to estimate yield in wheat fields and also grain quality. Two of egies have been developed for the control of such biophysical these instruments are point spectroradiometers covering wave- variables, as described below. Specifically, Grenzdörffer and lengths ranging from 485 nm - 1650 nm and 350 nm - 2500 nm, Niemeyer (2011) have used the bidirectional reflectance distri- respectively. The third instrument is a hyperspectral imaging bution function (BRDF) for computing bidirectional reflectance system with wavelengths in the range of 400 nm - 1000 nm. properties of plant surfaces. A quad-copter equipped with A spatial stratified random sampling method was applied four vision-based cameras carefully configured is designed to for crop area estimation using medium spatial resolution and cover a field of view from four different perspectives. UAV imagery, which is useful for subsequent regional distribu- Salamí et al. (2014) provide a review of UAVs used for sens- tion in specific areas (Panet al., 2011). ing vegetated areas, including precision agriculture, forest, Agüera et al. (2011) used two digital compact cameras for and rangeland applications, where sensors, tools, payloads, acquisition of RGB and NIR images onboard a quad-rotor. The and platforms are considered with their categorization. Ap- NIR images were acquired with a camera equipped with an plication areas of UAVs in agriculture and forestry are quite optical filter that allows the radiation with wavelength greater diverse, whereas the topics considered in the next section than 920 nm, these systems weigh 130 and 250 g, respective- provide an overview of this. ly. The aim of this work was to compare an NDVI related with sunflower nitrogen status based on greenness determination Crops and Weeds derived from the leaf chlorophyll content. Crops and weed management in precision agriculture are Costa et al. (2012) described an architectural design based two key activities for different purposes, such as yield on UAVs which can be used in agricultural systems for specific

294 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING (a) (b)

Figure 7. (a) uav flying a maize crop field to detect weeds patches for site-specific herbicide treatments, and (b) Weed density map obtained from uav images with three levels of weed infestation (Images courtesy of F. López-Granados and J.M. Peña, Institute for Sustainable Agriculture, csic-Córdoba, Spain; adapted from Peña et al., 2013). applications where UAVs are used for spraying chemicals on monitoring for prevention and cure when infestation has oc- crops controlled by a WSN deployed on the crop field. curred were studied and addressed in Yue et al. (2012). Samseemoung et al. (2012) designed a low altitude remote Figure 7a shows an UAV quad-rotor, from the CartoUAV sensing (LARS) helicopter, with 6 kg and payload capacity of 5 (2015) company, flying a maize crop field to detect weed kg, equipped with a commercial true color camera (RGB) and patches in order to design site-specific herbicide treatments. a color-infrared digital camera (G-R-NIR) for monitoring crop The images are conveniently mosaicked and segmented for growth and weed infestation in a soybean plantation flying at crop row identification and crop versus weeds discrimination altitudes up to 15 m. Also a LARS system based on a helicop- with the aim of building density maps of crops and weeds ter, with weight of 6 kg and payload of 5 kg, equipped with coverage. Figure 7b shows a map obtained from UAV images a multispectral imaging system was proposed in Swain et al. showing three levels of weed infestation (low, moderate, and (2010) and Swain and Zaman (2012) to determine theDelivered crop rice by Ingentahigh, in an ascending greyscale), crop rows (in grey) and free- coverage with the aim of predictingIP: rice 192.168.39.151 yield for planning On: and Sat, 25weed Sep zones 2021 (in 13:24:12 white). The image displayed in Figure 7b is expectation. Bendig et al.Copyright: (2013a and American 2013b) obtained Society crop for Photogrammetrysur- adapted from and Peña Remote et al. (2013).Sensing face models in rice fields based on stereo images with the aim Honkavaara et al. (2013) used a multispectral system (see of analyzing crop growth and health status. The platform is an the Multispectral and Hyperspectral Subsection) for biomass octo-copter with payload of 1 kg equipped with a true color estimation. Different vegetation densities in wheat and barley RGB sensor with a weight of 400 g. In the context of corn yield crops were obtained according to the amounts of seeds and prediction, Geipel et al. (2014) used a hexa-copter, equipped fertilizers applied, which allowed for determination of the with standard navigation sensors (IMU, GNSS) to acquire RGB effect of these quantities in the health and growth stage of imagery, which was later ortho-rectified with production of crops. Different experiments were also conducted by Jannoura DEMs and maps leading to the computation of vegetation indi- et al. (2015) to monitor crop biomass based on RGB images ces. Rice paddies were characterized in Uto et al. (2013) based captured by a true color camera onboard a hexa-copter. on a miniature hyperspectral system onboard an UAV. Rabatel et al. (2014a) proposed various methods to obtain Torres-Sanchez et al. (2013a, 2013b, and 2014), Peña- simultaneously visible and NIR bands for agricultural applica- Barragán et al. (2012a and 2012b), and Peña et al. (2013) used tions, including weed monitoring. Red (R) and NIR data were a quad-copter, with payload of 1.25 kg, with a lightweight obtained from a uniquely modified still camera, which was 700 g CMOS multispectral sensor with six individual digital achieved by removing the blocking internal NIR filter in the channels and sometimes a commercial high-resolution RGB camera, inserting a red long-pass filter in front of the lens and true color camera. Both cameras can be installed separately getting Red and NIR as linear combinations of the raw channel onboard for deriving vegetation indices for crop and weed data. In a second system, in the context of the RHEA project detection for generating weed coverage maps with the aim of and its associated second conference (RHEA, 2015), R and NIR site-specific treatments in maize crops. The images, stored in bands are obtained by a couple of compact still cameras, one SD and CF cards, are preprocessed for correct channel align- of them being modified as before. A specific image registration ment suitable for accurate ortho-rectification and mosaicking procedure was developed for such purpose (Rabatel and Lab- purposes before the map generation. A set of georeferenced bé, 2014b). Aerial images of wheat were acquired by a camera ground control points (GCP) is used for such purpose. Small onboard the UAV from AirRobot (2015) company, Figure 2b, as changes in flight altitudes can produce important differences part of the activities in the RHEA project with the aim of pro- in the ortho-images resolutions. A study about accuracy in ducing georeferenced maps for follow-up, site-specific treat- wheat fields infested by broad-leaved and grass weeds was ments in wheat fields. Huntet al. (2010 and 2011) replaced carried out in Gómez-Candón et al. (2014), where precision the internal hot-mirror filter with a red-light-blocking filter to mapping for farm applications are built using a quad-copter get data in the near-infrared, green, and blue bands, i.e., CIR equipped with a device providing CIR images. Different bands. Leaf area and green normalized difference vegetation studies were conducted in Peña et al. (2015) quantifying the indices were correlated in fertilized wheat crops. efficacy and limitations of remote images acquired with an Aerial reflectance measurements were conducted in Link- UAV for detection and discrimination of weeds affected by Dolezal et al. (2010 and 2012) in winter wheat for crop moni- the spectral, spatial and temporal resolutions. Crop pests and toring purposes based on georeferenced images. The UAV, with

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 295 wingspan of 2000 mm with payload of 1.3 kg, was equipped orchards. They used a micro-hyperspectral imaging system, with a multispectral sensor with weight less than 1 kg. 2.7 kg weight, with six-bands and configurable filters with Monitoring of wheat crops was evaluated and quantified different wavelengths centers (490 nm to 800 nm), which is in Lelong et al. (2008) based on the computation of different synchronized with an IMU for ortho-rectification. Also, a ther- vegetation indices from images acquired in the visible and mal (FLIR) camera, weighing 1.7 kg with spectral responses near-infrared spectral bands. The work of Perry et al. (2012) ranging in 7.3 µm to 1.3 µm, is used for measuring differences was the focus in this line for determining phenotyping traits. of temperature between the ground and the crowns of trees. Wal et al. (2013) used UAV for crop monitoring to overcome the The UAV is an auto-piloted helicopter with a fuel engine. problem of using satellite in areas with a high density of clouds, García-Ruiz et al. (2013) used a six-narrow-band multispec- improving performance. An effective example is a lidar system tral camera equipped with filter arrays at several wavelength onboard a helicopter working together with a camera operating centers. Its weight is 700 g, and is installed onboard a six-copter in the visible spectrum for infrastructure inspections and crop with a weight about 2,000 g. They compute vegetation indices, monitoring in unfamiliar scenarios (Merz and Chapman, 2011). which allow the analysis of loss of greenness in citrus trees. Sullivan et al. (2007) used a thermal infrared sensor, with A multi-spectral camera, acquiring high-resolution images bands 7 µm to 14 µm, onboard a UAV to assess the water at 10 nm bandwidth in the visible and near-infrared, onboard stress in cotton canopy. Meron et al. (2013) analyzed different an UAV, was used in Guillen-Climent et al. (2012) to model technologies for crop stress detection based on measures of the fraction of active radiation in citrus and peach orchards temperature in foliage. The data were captured from thermog- with unstructured rows, being useful in applications for pre- raphy sensors. cision agriculture. Córcoles et al. (2013) used a quad-rotor to determine the Yield estimation in citrus (orange trees) was obtained with leaf area index with a digital RGB camera onboard. Leaf area a mini-helicopter and a machine vision system (MacArthur et index was studied in Duan et al. (2014) for three typical row al., 2006). crops (maize, potatoes, and sunflowers). Data were acquired Berni et al. (2008) applied the factor known as “crown leaf in-situ and from a UAV equipped with a 128-band hyperspec- area index” in olive trees for chlorophyll content analysis tral imaging sensor ranging from 350 nm to 1030 nm with a 5 based on two camera-based instruments: (a) a multispectral nm bandwidth. system (2.7 kg) with six individual sensors with interchange- Verger et al. (2014) described an algorithm for determining able optical filters; and (b) a thermal camera (1.7 kg) with the green area index in wheat and rapeseed crops. A fixed- spectral response in the range 7.5 µm - 13 μm. These sensors wing UAV with 2 kg of weight, including the payload, was were installed onboard a rotary wing UAV with 7 kg of payload used and equipped with a four CMOS-based system to acquire and in a fixed wing UAV with payload of 5.5 kg. images in four spectral bands based on interferential filters Health canopy in olive orchards was studied in Zarco- operating at 550 nm (green), 660 nm (red), 735 nm (red edge), Tejada et al. (2013d) based on reflectance and fluorescence and 790 nm (NIR) with well-defined sensitivities. analysis. Different vegetation indices are obtained through Saberioon et al. (2014) studied the status of nitrogenDelivered and byhyperspectral Ingenta cameras with spatial resolution of 30 cm and chlorophyll content in rice leaf by analyzingIP: 192.168.39.151 the visible bands On: Sat,260 25 spectral Sep 2021 bands 13:24:12 ranging in 400 nm to 900 nm. from images. In-situ ground-basedCopyright: results American were checked Society against for Photogrammetry Vineyards and and grape Remote vines Sensing have been crops of special inter- the images captured with an integrated camera fixed-wingUAV . est very early (Johnson et al., 2003). Different sensors are used Faiçal et al. (2014) designed a control strategy to apply for determining measures related to: chlorophyll function pesticides in crops involving UAVs and WSN deployed in the and photosynthesis activity, leaf area indices, or plant health ground. status among others. Hung et al. (2014) apply a learning-based approach for Berni et al. (2009a) used high-resolution thermal images to classifying three invasive weed species on the north-west obtain the tree canopy conductance and the crop water stress in- slopes of New South Wales, Australia. A filter bank was used dex in olive orchards. A hyperspectral scanner with 80 spectral for feature extraction, and an explanation of the images cap- bands in the 0.43 µm to 12.5 μm spectral range was used on- tured was acquired with a high resolution commercial true board an airborne system. Also an UAV was developed to carry a color camera onboard a hexa-copter with 1.5 kg of weight. thermal device in the infrared (FLIR) and a multispectral imaging Burkart et al. (2015) used a hyperspectral flying goniometer sensor (ranging in 7.5 µm to 13 μm). Calderón et al. (2013) system, based on an octo-copter equipped with a spectrom- used multispectral (six-bands), thermal and hyper-spectral (260 eter mounted on an active gimbal for collecting multi-angular bands) imagery for computing some indices (xanthophyll, chlo- hyperspectral data over wheat fields for vegetation indices rophyll, carotenoids and blue/green/red) for determining the analysis based on BRDF. water stress in olive trees caused by soil-borne fungus in some regions. The UAV used for the multispectral and thermal acquisi- Trees in Forestry tion had a 2 m wingspan for a fixed-wing platform at 5.8 kg TOW. Important trees in forestry, where UAV-based applications Hyperspectral images were acquired with a larger UAV with a 5 have been of interest with significant performances are citrus, m wingspan for a fixed-wing platform having 13.5 kgTOW . peach, olive, vineyards, and pistachio. Nevertheless, the ap- Relations between chlorophyll fluorescence and photo- plications reported in this overview can be easily extended to synthesis were analyzed by Zarco-Tejada et al. (2013a) in other different kinds of trees. Biophysical parameters can be vineyards. The results are validated against other terrestrial estimated using different vegetation indices. Based on these systems, such as infrared gas analyzers sensors. An auto-pilot- parameters, several image-based products can be obtained: ed 2 m wingspan and fixed-wing platform at 5.8 kgTOW was leaf area index, chlorophyll content, water stress detection, used to carry thermal and multispectral sensors and a wing- health of plants, canopy analysis, photosynthesis, mapping of span fixed-wing platform with up to three-hour endurance at areas (including 3D), or soil analysis among others. 13.5 kg TOW. Zarco-Tejada et al. (2013c) used hyper-spectral Stress on citrus fruit due to water content was monitored imagery to determine the carotenoid content in vineyards in Stagakis et al. (2012); they applied structural and physi- related to the photosynthesis. A six-band multispectral cam- ological indices for such purpose, obtained from a multi- era and a micro-hyperspectral imager with 260 bands are the spectral camera operating in the visible and near-infrared sensors used onboard the platforms. spectrum. Zarco-Tejada et al. (2009, 2012, and 2013e) and The structure from motion was explored in Mathews and Berni et al. (2009b) determined water stress, leaf biomass, and Jensen (2013) to determine canopy in vineyard with a RGB chlorophyll content of the canopy in citrus, peach, and olive

296 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING commercial digital camera. Leaf area index measurements Wallace et al. (2012a) used a lidar scanner, together with were also obtained with successful performance results, com- an IMU, GPS, and high-resolution visible video cameras parable to the ones obtained by lidar technologies. onboard an octo-copter for tree height estimation and forest Turner et al. (2011) provided a method for mapping vine- inventory. A very high-density point cloud (up to 62 points yards based on visible, multispectral and thermal imagery. per m2) is achieved for the measurement of tree location, as Efficient water use regulating the irrigation schedule and well as height and crown width, which were assessed over determining results of special interest for efficiency concerning individual isolated trees. Lidar was also the technology used plant bio-physical parameters and physiological status are stud- in Wallace et al. (2011, 2012b, 2014a, and 2014b) for forest ied in forestry. In this regard, Baluja et al. (2012) analyzed the inventories based on change-detection analysis with high per- water status variability in vineyards based on multispectral im- formance, including error assessment. The stability of canopy ages (six-bands from 580 nm - 800 nm), including visible and NIR maps in forested areas was analyzed in Wallace (2013) based bands. Gonzalez-Dugo et al. (2013) computed a crop water stress on a lidar system onboard an UAV. Wallace et al. (2014b and index (CWSI) for determining the water status in an orchard with 2014c) used laser-based technology onboard an octo-copter an UAV, 2 m wingspan, fixed-wing and 5.8 kgTOW equipped in a four-year-old Eucalyptus globulus stand for determining with a thermal camera. Gago et al. (2014) computed leafs water stage of growth and the rate of pruning, respectively, with the stress in an experimental vineyard with an UAV hexa-copter aim of achieving high quality timber. The laser consists of equipped with a thermal camera and an additional RGB camera. four parallel scanning layers each with a scan frequency of 12 Zarco-Tejada et al. (2013b) computed the CWSI in vine- Hz, being capable of recording up to three returns per pulse yards, with the aim of determining different irrigation levels, with a transversal beam divergence of 0.8°. using both a multispectral and a thermal camera on board a Hernández-Clemente et al. (2012) used multi (hyper) spec- 2 m wingspan, fixed-wing platform, with a 5.8 kgTOW . The tral imagery to obtain biochemical (chlorophylls, carotenoid, spectral band-set center comprises wavelengths between 530 xanthophyll) measurements in forest canopies with conifers. nm and 800 nm. CWSI was also computed in Bellvert et al. The UAV was a 2 m fixed-wing platform capable of carrying a (2014) based on canopy temperatures measured with infrared 3.5 kg payload. The camera consisted of six independent im- temperature-based sensors placed on top of grapevines to age sensors and optics with user configurable spectral filters. map the spatial variability in water deficits in a “Pinot Noir” Tree height canopy measurements were obtained in Zarco- vineyard. CWSI was correlated with leaf water potential in Zar- Tejada et al. (2014) from a RGB camera manipulated to capture co-Tejada et al. (2012). This correlation was also tested using the near-infrared spectral band, i.e., a CIR device previously thermal imagery captured with a sensor with spectral range of introduced. 8 µm - 12 µm onboard an UAV. Dandois and Ellis (2010 and 2013) obtained high-resolu- Primicerio et al. (2012) used a hexa-copter for site-specific tion 3D maps in forestry vegetation from RGB images captured vineyard management based on canopy analysis from NDVI with an UAV. They achieved similar performance as was and equipped with a multi-spectral CMOS-based camera, with obtained with lidar systems. In this regard, Tao et al. (2010) weight of 200 g and wavelengths of 520 nm to 600 Deliverednm (green), by Ingentacomputed dense point clouds from images captured with UAVs 630 nm to 690 nm (red), and 760 µmIP: to192.168.39.151 900 nm (NIR). On: Sat, 25for Sep 3D mapping 2021 13:24:12 purposes. A helicopter carryingCopyright: an imaging American payload of Society approximately for Photogrammetry A mini- UAVand-borne Remote lidar Sensing system was constructed in Lin et 1 kg was used in Nebiker et al. (2008) for deriving plant al. (2011). The UAV is a helicopter with weight of 4.5 kg, being health, based on the computation of the percentage of dam- able to transport a payload of about 7 kg. It is equipped with aged leaves within a grape vine. NDVI values are obtained by laser scanners of 1.2 and 1.6 kg for assessing its validity in RGB (CMOS-based) and NIR (CCD-based) sensors. The RGB and high-resolution 3D mapping for tree height estimation. NIR images are captured on different flights for subsequent Fritz et al. (2013) used an octo-copter for tree stem detec- geo-referencing and ortho-rectification. tion in open stands. The UAV is equipped with a consumer Gonzalez-Dugo et al. (2015) conducted different studies in camera fixed on a flexible mount, which enables tilting the a commercial pistachio orchard located in Madera County, camera vertically and horizontally. In five steps, a dense point California to determine the spatial variability in water status cloud is generated: Scale Invariant Feature Transform (SIFT) and irrigation needs based on thermal imagery computing the operator for generate tie points, image matching of SIFT fea- CWSI. The UAV platform used is described in Zarco-Tejada et tures, bundle adjustment to estimate camera parameters, clus- al. (2012 and 2013b). tering the image, and dense reconstruction. The method was Plate 3 displays a plot, corresponding to a forestry plantation, validated against point clouds from terrestrial laser scanners. obtained with an ALTM Gemini laser scanner, described above. Chisholm et al. (2013) used a quad-copter equipped with a lidar operating at 10 Hz with 1,081 beams per scan, with scan- Forests ning angle of 270° and range of 30 m for below-canopy surveys. In forest or forested areas, UAVs are also useful. They allow A map of horizontal cross section of the forest was reconstruct- flying over the forest stand for different purposes. Canopy ed and the diameter-at-breast-height of 12 trunks estimated. analysis, including gap patterns, and 3D mapping are two Fallen trees are surveyed from an unmanned helicopter in relevant areas where UAVs are used. Inoue et al. (2014) in a deciduous broadleaved forest in east- Dunford et al. (2009) proposed a classification approach, ern Japan as a key factor in biodiversity and biogeochemical based on imaging analysis, to quantify riparian areas and cycling. The UAV was equipped with a consumer-grade digital vegetation in the Mediterranean region, where standing dead camera a GPS and a laser range finder for the production of DEMs. trees are identified as well as unhealthy or dead canopy. Some potential and limitations were also reported, such as typical Other Applications problems derived from sizes and payloads of UAVs or illu- Soil monitoring in agriculture becomes an important task be- mination or vibrations/undesired movements in the sensor cause yield can be estimated based on its evaluation, wherein during flight. Advanced technologies have been designed for UAVs can play an important role. Biasio et al. (2010) used minimizing such effects, including cameras with auto-iris, multispectral imagery (a device with three visible and two gimbals, or three-axis stabilized platforms. infrared channels) to monitor the soil composition in agricul- Whalin (2012) proposed the analysis of tree canopies to de- tural fields to estimate crop yields based on the computation tect the health based on infrared analysis. This allows detect- of vegetation indices in farmlands. ing and fighting beetle pests as well as other diseases affecting Corbane et al. (2012) addressed the study of soil surface forests, which can also be monitored. characteristics in vineyards with the aim of determining

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 297 infiltration and runoff with hydrological multitemporal clas- improvements, the different technologies were integrated in sification. Part of the data were collected around solar noon the UAV, including: communication, control, sensing, image with a commercial visual RGB camera onboard an UAV. processing, and networking. Thanks to all these technologies, Aquatic weed surveillance was described in Göktogan et the UAVs can provide communication links where terrestrial al. (2010). The UAV is a rotary-wing vehicle with length of 2 areas are damaged. m, maximum TOW of 15 kg, and a fuel engine equipped with Li et al. (2011) proposed a method for image rectification a 3-CCD video camera. The images were captured and stored and mosaicking without control points in earthquake disaster for subsequent treatment and analysis. areas with the aim of early intervention. A CCD imaging sensor Geipel et al. (2013) proposed a software-based framework was installed onboard a UAV with payload of 4.5 kg. for connecting sensors and processor(s) onboard during the flight; this is intended with the aim of exploiting this poten- Fire tial against platforms that only store information for follow-up The use of UAVs, equipped with sensory technologies, was ground processing. They deployed a prototype for microcli- early identified for its potential use in fire detection (Am- mate monitoring equipped with low-cost sensors, includ- brosia et al., 2003, 2009, and 2011; Ambrosia and Wegener, ing temperature, humidity, and imaging sensors specifically 2009; Ollero et al. 2006; Rufino and Moccia, 2005; Wu and adapted or designed for agriculture applications. Zhou, 2006a and 2006b; Wu et al., 2007). UAVs progressed to more sophisticated and precise technologies and methods Disaster Monitoring with high performance, including the design of an effective Regarding disaster monitoring it is worth to consider two architecture (Pastor et al., 2011). During crisis management in relevant aspects, the first related to prevention and the second fires, it is essential the coordination between fire brigades is to response after the event has occurred. According to this critical for extinguishing the fire. Persieet al. (2011) proposed category, pre- and post-emergency topics are to be considered. an integrated GIS where all relevant geospatial information is Several years ago, Bendea et al. (2008) identified the need automatically distributed to all levels of the organization. and usefulness of UAVs for operations in disaster areas conve- During years 2006 to 2010, NASA and US Forest Service niently equipped with advanced sensors and technologies. Its conducted several missions over different forest where the use in National Parks for surveillance was also considered as NASA Ikhana UAS capabilities were demonstrated and verified convenient in prevention tasks (Restas, 2006). for processing multi-spectral data onboard the UAV (Ambrosia Hurricanes, typhoons, tornados, earthquakes, fires, nuclear et al., 2011), including fire monitoring. The great possibilities incidents, spills in the ocean, floods, and avalanches are clear for using thermal imaging cameras in firefighting were defined causes of disaster where UAVs can play an important role. in Hinkley and Zajkowski (2011) thanks to the collabora- These are manmade or natural events where UAVs have been tion of the two institutions mentioned above. Forest wildfire applied, but they are not exclusive and can serve as founda- monitoring was also addressed in Zhou and Cheng (2005). tions for future applications in disasters. Deployment of UAVs Martínez-de-Dios et al. (2007) used a fleet of three hetero- to build a network of sensors has been considered useful in geneous UAVs (Helivision-GRVC, Marvin and Karma) for fire disaster management applications (Quaritsch et al., 2010).Delivered bydetection. Ingenta The fire is detected by means of histogram analysis IP: 192.168.39.151 On: Sat,using 25 learning-basedSep 2021 13:24:12 strategies. These UAVs explore different Hurricanes, Typhoons, and TornadosCopyright: American Society for Photogrammetryareas in cooperative and Remote surveillance; Sensing if a fire is detected, they UAVs in the Hurricane and Severe Storm Sentinel (HS3) pro- provide positioning of this incident using to the system’s gram launched by NASA (2015b), were equipped with different GPS. Maza et al. (2011) proposed a distributed architecture of high-tech instruments to monitor hurricane formation and its multi-UAVs with this identical purpose, where fire detection evolution. A multisensory technology was used including a tasks have been carried out and tested under the proposed radar scanner and wind lidar, both based on the Doppler Effect, approach. Figure 8 displays a fire monitoring sequence at multi-frequency radiometer based on interferometry, and a different levels of detail, where the polygons surrounding the microwave sounder. One UAV “catches” data inside the storm active flames identifies its position and extension. In the se- (winds and precipitation) and a second one “explores” the en- quence of the four images in the bottom partion of this Figure, vironment. A hurricane post-disaster assessment was conduct- one can see its expansion and evolution at different times. ed in Adams et al. (2010) based on imagery analysis captured Martínez-de Dios et al. (2011) and Merino et al. (2010 and by a RGB camera with a weight of 250 g onboard a helicopter. 2012) designed and tested three UAVs (two helicopters and Chou et al. (2010) applied imagery technologies with a com- one blimp) equipped with infrared (non-thermal, operating in mercial camera with weight of 1.2 kg onboard a helicopter with the far-infrared band) and visual cameras in combination with 8.5 kg of weight and payload of 5.5 kg. This system was used cameras distributed on ground stations. Fire measurements to analyze changes take for disaster monitoring following the and remotely sensed locations are supplied for the interces- MORAKOT typhoon. Rescue operations were studied in DeBusk sion of the response brigades for resource planning against (2010) for follow-up analysis caused by the tornado Alley. the fire. Figure 9 displays the Interface Human Machine IHM( ) Earthquakes in the GCS, where visible and infrared images are visualized. Seismic hazards were evaluated in the old city center of Positioning coordinates and other dynamic parameters are L’Aquila, Italy after an earthquake with an octo-copter (Domi- also displayed, including the UAV trajectory and a tele-opera- nici et al., 2012) capturing high quality images on roofs and tion connection. facades of structures with a reflex digital camera. Baiocchiet The system used in Krüll et al. (2012) for early fire de- al. (2013) used stereoscopic techniques for 3D reconstruction tection, described in the Chemical Sensors subsection, is of buildings for determining possible damage in such build- designed for detecting component of gases that identify the ings in the same city for post seismic analysis. The platform existence of fire. is equipped with two cameras operating in the visible and Nuclear Leaks infrared spectrum, respectively, and a GPS. Nuclear leaks represent a very high-risk event, with a great After the Tohoku, Japan earthquake in 2011, important hazard at all levels, often at a great distance distances from efforts were made for the NEC (Wada et al., 2015), where UAVs, the event, where immediate action in post-disaster effort is an equipped with optical sensors, provided a rapid interven- immediate priority. tion with abundant information during several imaging-based In this regard, Han et al. (2013) simulated a nuclear di- surveillance tasks. After subsequent developments and saster for rapid intervention with the aim of delimiting the

298 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING Figure 8. Fire monitoring with flame identification and its expansion over time (Images courtesy of J.R. Martínez-de-Dios and A. Ollero; Robotics, Vision, and Control Group, University of Seville, Seville Spain)

Delivered by Ingenta IP: 192.168.39.151 On: Sat, 25 Sep 2021 13:24:12 Copyright: American Society for Photogrammetry and Remote Sensing

Figure 9. Interface Human Machine in the gcs: visible and infrared images, dynamic parameters, trajectory, and tele-operation (Image courtesy of J.R. Martínez-de-Dios and A. Ollero; Robotics, Vision, and Control Group, University of Seville, Seville Spain). extent of the affected area. A set of UAVs in cooperation was the proposed model also considers weather forecasting for the the proposed system. Also, simulated experiments were car- purpose of replacing stationary sensor networks. ried out in Smídl and Hofman (2013) to model the tracking of Post-disaster surveillance with measurements after radio- a plume of air contaminated by a nuclear leak based on UAVs; active leaks is possible for monitoring the disaster and its

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 299 development (Towler et al. 2012). Siminski (2014) reported Humanitarian Localization and Rescue regarding the monitoring of the Fukushima, Japan plant’s When a disaster has occurred, people risk their own lives to radiation with an UAV; this post-disaster intervention with rescue others trapped due to the consequences of the event. persistent observation minimizes the threat and hazard to the As mentioned before, disasters involve people requiring inhabitants and response personnel. urgent rescue. Tsunamis, earthquakes, shipwrecks, fires, or nuclear leaks are typical examples of these events. Simulated Oil Spill Detection and real scenarios are used for experimentation with UAVs. Oil slicks and perhaps other pollutants on the sea surface are Rapid intervention is crucial in the early hours of the event becoming more prevalent creating large contaminated areas. for effective search and rescue. With such purpose, Naidoo et The field-of-view of the camera-based systems onboardUAVs al. (2011) designed and simulated a stable UAV quad-copter rarely covers the entire area. To address this problem with platform equipped with three main modules, each with a single UAV equipped with a camera, Lanillos et al. (2009) different sensors onboard: (a) communication (wireless and proposed a strategy for boundary detection of a surface that radio controller); (b) vision system (cameras and sonar range is partially imaged with the camera. Each image contains a finders); and (c) attitude and heading reference system (GPS, segment of the oil spill extent, and the UAV is used to search magnetometer, accelerometer, and gyroscope). This system for joining consecutive segments to close the full boundary. was successfully simulated. A simulated scenario is used for testing and an optimization Molina et al. (2012) used an unmanned helicopter strategy is selected for closing the complete contour. equipped with thermal and optical cameras for search and res- The oil slick detection problem was addressed in Muttin cue, considering that operations could be conducted at night. (2011), where the UAV guides a ship for subsequent oil conten- In search and rescue tasks, the time is a critical parameter tion and recovery, based on a non-linear dynamic model for for the survival of the trapped or missing persons. Search the aerial umbilical including variable length domain and strategies in UAVs equipped with camera-based systems must material elasticity using different numerical examples. be optimized, so that the search is done focusing on areas Floods and Avalanches of maximum probability in minimum time. Cameras with Some years ago, nanotechnologies were seen as useful for sufficient field-of-view for recognition, combined with ef- weather observation (Manobianco et al., 2008). Now these ficient path planning strategies are suitable for such purpose, technologies are proposed for monitoring flash floods from such as the methods proposed in Lin and Goodrich (2009), UAVs. During the first phase, a number of transmitter sensors where different simulated scenarios were used for testing. In are deployed inside the potential area where the flood could this way, Lanillos (2013) proposed a minimum time-based occur, and then UAVs, equipped with receiving antennas, search strategy for moving targets in simulated scenarios with identify each sensor position and build a distribution map. uncertainty. Several agents (UAVs) collect information from Abdelkader et al. (2013) used lagrangian (mobile) micro- the sensors onboard for target identification and location. A sensors emitting a unique identifier ID( ), similar to the radio- flight path planning process based on a probabilistic Bayesian frequency identifiers (RFID). When transmitters are dropped,Delivered byframework Ingenta was established for early actuation. UAVs track their movements using passiveIP: 192.168.39.151 receiving antennas. On: Sat, 25Multiple Sep 2021 simulated 13:24:12 observations, based on different alti- This application is very appropriateCopyright: for American multiple UAVsSociety in col for- Photogrammetrytudes and sensor and configurations Remote Sensing were studied in Waharte and laboration to build a map of the transmitters. Symington (2010) to assess the robustness of the target detec- In post emergency situations, Weng et al. (2011) used UAVs tion for the purpose of covering the full area to be examined. for monitoring debris flow in Zhouqu County area in China; a A camera with birds-eye view, onboard a quad-copter, was collection of high-resolution images was acquired to evaluate used for search and rescue in Symington et al. (2010), where a the disaster. tracking approach is proposed for a static target. Image video SAR-based systems onboard UAVs were considered to be sequences were used for training, where key-points invari- used for detecting and studying temporal evolution of wet ant to translations, rotations, and scale changes are used for snow in avalanche prone areas (Malnes et al., 2015). recognizing the target (persons) on the image. This goal was A new research topic emerged to study the feasibility of achieved by applying image-based similarity measurements utilizing 4G-LTE signals in combination with UAVs for search and different parameters from the observation model to up- and rescue of avalanche victims (Wolfe, 2014). date a recursive Bayesian estimator. Rudol and Doherty (2008) combined thermal and color Epidemiology imagery to locate areas with high probability of presence of Fornace et al. (2014) have used a commercially available UAV humans to be rescued. The thermal camera, mounted on a for mapping landscapes with the aim of detecting potential pan-tilt-unit, discriminates temperatures and locates human areas for future human infections with the zoonotic malarial temperature ranges; the CCD color camera at a later stage veri- parasite Plasmodium knowlesi. The flights were conducted in fies the presence of persons. The UAV platform was a helicop- two study sites in Sabah, Malaysia and one site in Palawan, ter with total length of 3.6 m, including the main motor and a The Philippines. Spatial information to integrate movements maximum TOW of 95 kg. of human and macaque was recovered and analyzed to local- Coyle (2014) described some cases where UAVs have been ize the focus of epidemiology infections. used for early rescue in snow avalanches. Fixed-wing aircraft Jones (2014) provides a review about trends in plant virus or rotary-wing copters, equipped with video cameras and epidemiology, focusing on new or improved technologies ap- infrared imagery sensors, are mentioned. plied to research in this topic. UAVs, equipped with different Mardell et al. (2014) have applied simulation techniques to sensors, are considered useful tools for the future to acquire compare the performance of image inspection modes for visual sufficient knowledge of different types of plant epidemics, search and rescue tasks in wilderness areas based on an UAV re- their development, and how they could be controlled. mote sensing system.. Live video and serial visual image analy- Barasona et al. (2014) have used UAVs to capture informa- sis (a static image remains in view until replaced by a new image tion about the spatial epidemiology distribution of tuberculo- rate) captured from a downward facing camera were analyzed. sis in the ungulate community in the Doñana National Park in Southwestern Spain). Surveillance: Target Detection and Tracking Surveillance is an important issue in UAVs applications; most tasks described above involve this application. For example,

300 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING Desikan et al. (2013) used several UAVs to avoid un-authorized desert environments from images acquired with a commercial entry in aquatic ecosystem (park) to enhance the conservation camera onboard an autonomous helicopter. Ruangwiset (2009) of endangered aquatic species in its natural habitat. introduced a path planning strategy for target tracking from Specifically, target detection and tracking are two impor- UAVs. A chaotic biogeography-based optimization approach to tant challenges in surveillance: often with partial information, target detection has been proposed in Zhang and Duan (2014) because the target could be only partially observed due to large where the chaotic strategy, the dynamic ergodicity popula- areas not covered by the onboard sensors on. This challenge tion and global searching avoid local optimal solutions during occurs when tracking is conducted with sensors having a evolution. An inter-row tree tracking technique was applied limited field of view, such as camera-based or lasers. In image- in Thamrin et al. (2012) based on Structure from Motion (SfM). based applications, the key issue in target tracking is the object matching between successive frames, so that an object can be Environmental Monitoring located from one frame to the next. This analysis is not with- Environmental monitoring operations are an interesting area out significant problems in outdoor environments, such as the inside remote sensing, where UAV technology has much to ones reported in Kwon et al. (2013), where sunlight reflections contribute. Research in this field is one of the key pillars on water surfaces become confused with objects. Relevant fea- (Hardin and Hardin, 2010). Anderson and Gaston (2013) tures of objects must be extracted to be matched; in this regard, provided a broad revision of UAV-based applications covering super-resolution techniques have been applied in video sur- several areas, where ecology is one of the most relevant. A veillance for improving images quality (Camargo et al. 2010). review was conducted under the United Nations Environment Al-Helal and Sprinkle (2010) and Siam and ElHelw (2012) Programme (UNEP, 2013) where drones are used to work in a proposed a solution for tracking a target moving in the ground broad variety of ecosystems. based on visual detection, where significant features, such as The topics addressed under the environmental monitoring corners or specific lines are used for guiding the process. topic include: volcanic inspections, soil erosion, landslides or Hong et al. (2008) applied a continuous wavelet-based ap- rocky surfaces, aquatic environments, canopy in the understo- proach for target tracking in video sequences for surveillance rey, rural roads, and geological hazard analysis. purposes. They converted target trajectories in a spatial- Volcanic Inspections temporal domain into target energy volumes in the frequency Volcanic inspections and monitoring are risky activities domain where different motion parameters were integrated to where UAVs are appropriate tools (Smith et al., 2009). The obtain three target energy densities, which then serve as cost experiments carried out in volcanic areas are intended for functions for estimating target trajectories and sizes. predicting eruptions and for issuing possible warning to resi- Vehicle detection, traffic tracking, and monitoring are top- dents. These explorations are on-going, (McGarry, 2005). NASA (2015c) flew modified Dragon-eye drones, fixed-wing, ics of special interest in surveillance, where UAVs can play an important role. Coifman et al. (2006) proposed a roadway with a weight of 2.7 kg and payload of 500 g, for monitoring the Turrialba Volcano in Costa Rica with the aim to study gas monitoring approach form UAVs. Kanistrasy et al. (2013) emissions and ash clouds inside the volcanic plume (Wil- provided a survey on this area with additional referencesDelivered to by Ingenta related topics, including road and moving vehicle detection, liams, 2014). Pieri et al. (2014) described how to acquire IP: 192.168.39.151 On: Sat, 25different Sep 2021 measurements, 13:24:12 including gases (CO , CH , H S, He) vehicle counting, traffic flow and behavior. Liuet al. (2012) 2 4 2 Copyright: American Society for Photogrammetryand aerosols and liquid Remote (H SO Sensing, HCl) at the same time atmospheric used UAVs for moving vehicle detection and tracking based on 2 4 similarity measurements between consecutive frames in the data (temperature, humidity, pressure, wind velocity) are video stream. Skoglar et al. (2012) proposed a method to track obtained with UAVs in the Turrilba Volcano, Costa Rica. In several vehicles on roads based on vision sensor with gimbal this line are focused the works described in Mondragón et al. capabilities. All targets are monitored with simultaneous ac- (2015) for volcano inspections and hydrothermal alterations tive search, and also for identifying new targets. The vision at mountains of Poas and Irazu (Costa Rica) with a multi-rotor sensor is oriented towards the field of interest. UAV equipped with thermal and visible cameras. McGonigle Xiao et al. (2008) and Miller et al. (2008) proposed sev- et al. (2008) conducted different experiments to measure eral techniques for tracking persons in video sequences from volcanic gases at La Fossa crater, Vulcano Island, Italy with a multi-gas sensor (see the Chemical Sensors subsection). This UAVs. The first work used video cameras for tracking ground vehicles and the second one used infrared images. device was used in Shinohara (2013) for analyzing gas emis- A target tracking approach, based on a monocular camera sions in Shinmoedake, Kirishima Volcano, Japan. Amici et al. (2013) described the inspection of the Le Sa- (pinhole model), for determining ranges from UAVs to objects was the approach proposed in Choi and Kim (2014). A guid- linelle, Italian mud volcano on the lower South West flank of ance law is also proposed for such purpose. the Etna Volcano. The UAV is configured as a hexa-copter with Different transformations and approaches have been a 1.7 kg payload, equipped with a lightweight thermal system of 67 g and spectral response in the range at 2 µm to 14 µm proposed for target detection and tracking. SIFT and variants and a PAL video camera with weight of 600 g. such as the Mean SIFT, were proposed with the aim of match- ing objects in successive frames (Fang et al., 2011; Chao-Jian Soils and San-Xue, 2011). Gleason et al. (2011) described a method Soil erosion analysis, hazard monitoring, reflectance proper- based on Mean SIFT for vehicle detection and tracking in rural ties, and 3D modeling are motivating applications where UAVs areas with the aim of detecting potential threats in oil and gas can play an important role. pipelines with extension to other applications in these kinds Frankenberger et al. (2008) evaluated the feasibility of us- of environments. Automatic aerial surveillance systems in ing low-altitude (100 m) photogrammetry to assess ephemeral buried gas and oil pipelines based on UAVs were considered in gully erosion at agricultural fields after rainfall events.DEMs Zaréa et al. (2014). were built for analysis from surface images acquired with Fang et al. (2011) proposed particle filtering based on the a commercial camera onboard an UAV and checked against mean-shift algorithm captured with an UAV. Rodríguez-Canosa ground-based systems, such as terrestrial lidar. et al. (2012) described a compensated optical flow-based Hazard monitoring, for rockslides in Randa (Wallis, Swiss approach between consecutive frames for tracking objects, Alps), was addressed in Eisenbeiss (2009). The images were where low frequency vibrations caused by the UAV are con- acquired with a still video camera on-board an unmanned veniently balanced. Lin and Saripalli (2012) applied a Hough helicopter. transform-based approach for road detection and tracking in

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 301 Land reflectance (bidirectional reflectance factor) has been was to study discharges and sediment-transport capacities to studied and different measures obtained in Hakala et al. estimate the efficiency of weathering and runoff.SfM was used (2010). The UAV is a quad-rotor with 55 cm from side-to-side as a photogrammetric technique for subsequent DEM produc- and payload around 300 g. A set of images were acquired with tion. UAVs imagery and georeferencing was applied in Barreiro a CCD commercial camera with weight of 200 g, from multiple et al. (2014) to obtain topographic information regarding the views for subsequent analysis. runoff due to water flow during extreme rain events utilizing A quad-copter equipped with a commercial digital camera photogrammetry. Simulation results defining how water can was used in Carvajal et al. (2011) to characterize landslides, flow into a close road was carried out. with sufficient accuracy, located on the size of a road in the Templeton et al. (2014) combined an environmental sen- Abla municipality in Almeria, Spain. sor network and UAV-based imagery for studying hydrologic In the context of temporal image analysis, object change de- processes in semiarid watersheds exhibiting a high degree of tection is the problem addressed in Shi et al. (2011) where an spatial heterogeneity and seasonal evolution in land surface area in Guangzhou, China was studied by applying image pro- characteristics from DTMs, derived from UAV images captured cessing and classification techniques including principal com- with a consumer-grade camera. ponent analysis, Mean-Shift, and K-Means. The georeferenced As reported in Chen et al. (2014) the China Institute of images were acquired from an UAV. A time series analysis, over Geological Environment Monitoring conducted a research on four years, was used in Turner et al. (2015) for studying land- the characterization of the landslide at Daguangbao, which slides dynamics from high-resolution images captured with was induced by the 2008 Wenchuan earthquake. The damage a RGB consumer-grade camera onboard an octo-copter (with pattern was analyzed by combining the pre-seismic remote payload capacity of 2 kg). They applied SfM to create DSMs. sensing image interpretation of QuickBird and SPOT5 satellite Niethammer et al. (2011 and 2012) used a quad-rotor imagery data, with post-seismic aerial imagery of the land- equipped with a digital camera for monitoring hazards in slide area collected by airborne instrumentation in an UAV. areas affected by landslides (Super-Sauze landslide on the Geological structures of rocky surfaces at Piccaninny Point north-face in the Barcelonnette Basin in Southern French on the east coast of Tasmania, Australia were studied in Alps), where temporal and spatial imaging changes are ana- Vasuki et al. (2014) for detecting faults, joints, and fractures lyzed and DTM built for analysis. Landslide dynamics were based on imaging analysis. Images were captured with a digi- also investigated in Stumpf et al. (2012 and 2013) building tal commercial camera onboard an octo-copter, where SfM is maps from images and also in Huang et al. (2011) for warn- the approach applied for 3D structure determination. ing and emergency purposes in highway design in China. SfM Soil erosion was also addressed by the USGS unmanned was applied in Lucieer et al. (2014a) to obtain a 3D model of aerial system program in USGS (2015b), more specifically a landslide in southeast of Tasmania based on multi-view im- referred to monitoring the shoreline of the Missouri River on age frames obtained from an octo-copter with approximately the Lower Brule Reservation. Bioerosion, caused by burrow- 80 cm in diameter and TOW of 3 kg. It is equipped with an ing parrots on a cliff in Bahía Blanca (Argentina), was studied autopilot, navigation-grade GPS receiver, and a commercialDelivered byin IngentaGenchi et al. (2015) using a hexa-copter to evaluate the standard camera. Rau et al. (2011) usedIP: a 192.168.39.151fixed-wingUAV with On: Sat,applicability 25 Sep 2021 of the 13:24:12 3D model based on SfM. 3 kg of payload for landslideCopyright: detection Americanin Taiwan, Society equipped for Photogrammetry and Remote Sensing with a consumer digital camera, a flight control computer, Aquatic Environments Aquatic environments are of particular relevance in terms of a Garmin GPS receiver, and an attitude heading reference system. An automatic algorithm was proposed based on the their protection and study because they generate ecosystems, object-based image analysis in advance and applying aerial providing protection to different species of fauna and flora. In triangulation, ortho-image generation, and mosaicking. A this regard, UAVs were identified to play an important role. Ob- servation of rivers for detecting water pollution and green algae fixed-wingUAV with 2.4 m wingspan used in Lin et al. (2010) for monitoring mountain hazards. coverage or monitoring river boundaries, bridges, and coast- Soil monitoring was carried out in d’Oleire-Oltmanns lines is another relevant issue in such environments. Monitor- (2012) in the Souss Basin, Morocco in order to determine ing of such spaces represents a high priority challenge to detect the possible impact on soil erosion due to land leveling for changes in aquatic conditions for early response or monitoring. new land use. A fixed-wing aircraft with wingspan of 163 Rathinam et al. (2007) used a fixed wing UAV equipped with cm, length of 120 cm, and 2.3 kg of weight is employed; it is visible and NIR imagery collection systems for identifying and equipped with a digital camera with 550 g. mapping a river structure, including bridges. Liu et al. (2009) Morillas et al. (2013) studied the surface energy balance developed an UAV equipped with multispectral imagery system in Mediterranean dry-lands, considering soil and vegetation for quick-response when drinking-water pollution occurs. All components, and under water stress conditions. Part of this sensors are integrated onboard the UAV, and the CCD-based cam- eras were calibrated and tested along a river. Wawrzyniak et al. study was carried out with an UAV, 2 m wingspan fixed-wing (2013) used thermal imagery for water temperature prediction in with 5.8 kg TOW, equipped with a thermal camera with spec- tral response in the range of 8 μm - 12 μm. braided rivers. Flynn and Chapra (2014) used a RGB commercial The identification of agricultural terraces was addressed in digital camera installed on a quad-rotor (with payload of 200 g) Diaz-Varela et al. (2014) based on the assumption that these to analyze the spatial and temporal distribution of filamentous areas are specific ecosystems. They applied a classification green algae on the Clark Fork River in western Montana. approach based on the computation of ortho-rectified digital Coastal areas in the Campania (Italy) have been scanned in Lega and Napoli (2010) through a FLIR system onboard dif- surface models. The UAV carries a modified camera fromRGB ferent platforms, including an ultra-light machine, a tethered to CIR by removing the internal NIR filter. TheUAV platform is a 2 m wingspan fixed-wing platform with up to one-hour balloon, and two types of UAV: a conventional shape mini- blimp and a Hybrid LTA (Lighter than Air) vehicle. endurance at 5.8 kg TOW. Experimental analysis based on simulated rainfall and Fresh water wetlands areas were identified in Liet al. gully mapping were conducted by Peter et al. (2014). (2010) with an imaging system onboard of an airship, from Haas et al. (2014) have integrated ground surveys for which different mosaics were produced. textural and morphological patterns at an alluvial fan surface Surveillance for tagging free drifting icebergs was proposed by McGill et al. (2011) using video cameras, where the access through a lightweight (1.1 kg) UAV, with a wingspan of 1.2 m to hidden areas in the iceberg provides excellent potential for and equipped with a RGB consumer-grade camera. The goal

302 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING observation. Two UAVs with 2.0 and 2.8 m wing-span, fuel engine, Vegetation: Classification, Coverage, and Development and payload of 2.27 kg were used for their high stability. They Vegetation analysis, including classification and identification were equipped with a video system with a small overlay board. (Ishihama et al., 2012), coverage, and development are also an RGB, NIR, and thermal mosaicked images were analyzed application area where UAVs can be used successfully. Even in Jensen et al. (2012) for determining the temperature in at some point, kites and balloons, equipped with commercial streams, once the land is separated out in the image mosaics. cameras, have been used for monitoring vegetation in perigla- They used an UAV (AggieAir, 2015) for this application. This cial areas in Alaska (Boike and Yoshikawa, 2003). Ecology is fixed-wing platform was designed for riparian and wetlands an area highly benefited by the use ofUAVs where the versatil- applications (Jensen et al., 2011) and was also used in Zaman ity and maneuverability of such vehicles, equipped with dif- et al. (2011) to quantify the spread of invasive grass species, ferent sensors, offer researchers and end users and excellent Phragmites australis, in a large and important wetland in opportunity (Anderson and Gaston, 2013). northern Utah. Vegetation analysis in agriculture, forestry, and forest map- Sediments, oil spills, or other pollutants can be also de- ping is excluded here, as it was considered in the Agriculture tected and tracked in aquatic environments. This task is car- and Forestry Section. ried out in Zang et al. (2012) with a fixed-wing UAV with the Reid et al. (2011) and Bryson et al. (2010) applied texture following specifications: airframe length of 1.8 m, wingspan descriptors to classify vegetation in natural and farmland of 2.8 m, maximum TOW of 15 kg, and payload 3 -3.55 kg. The environments from images captured with a machine vision UAV is equipped with a digital RGB commercial camera and a system installed on a fixed-wingUAV . multispectral device in the spectral range of RGB and NIR. Rangeland ecosystems cover large areas for different uses Monitoring of swamps was carried out in Lechner et al. including natural habitat, recreational opportunities, or cattle (2012); the purpose is to protect species sensitive to changes in forage. UAVs were early identified for applications in this con- hydrological conditions. Object-based image analysis methods text (Hardin and Jackson, 2005). McGwire et al. (2013) used were applied to characterize swamp land-cover on the Newnes NDVI for comparing spatial variability in green leaf cover Plateau in the Blue Mountains near Sydney, Australia. A fixed- of semi-arid rangeland areas based on images captured with wing UAV with 2 m wingspan weighing approximately 3.9 kg UAVs and Landsat Thematic Mapper with 2 cm and 30 m reso- was the platform used. It is equipped with a commercial cam- lution, respectively. The UAV was a 1.4 m length with a main era with the spectral range coverage modified by a NIR filter. rotor span of 1.58 m and tail rotor span of 27 cm equipped Monitoring of Eriophorum vaginatum at Mer Bleue peat- with a CMOS imaging chip, capturing images in wavelengths land was carried out by Kalacska et al. (2013) because of its ranges of green, red, and NIR comparable to CIR images and TM relevance in methane exchanges in large areas. A rotorcraft bands 2, 3, and 4. 1.2 m long with a main rotor diameter of 1.3 m was used. From the point of view of the classification paradigm, La- Video images were recorded in RGB to generate georeferenced liberte et al. (2011) proposed imagery to obtain orthorectified mosaics. The content of each mosaic was classified to identify mosaics with radiometric calibration for rangeland vegetation E. vaginatum tussock cover using a supervised classificationDelivered by Ingentaclassification based on rule-based approaches. A fixed-wing approach based on multi-distance IP:cluster 192.168.39.151 analysis. On: Sat, 25aircraft Sep 2021with wingspan13:24:12 of 1.8 kg and 10 kg is the platform Ouédraogo et al. (2014)Copyright: determined American micro-topography Society for Photogrammetryused, which and was Remote equipped Sensing with three sensors: a forward look- changes in watersheds with high agricultural activity. This ing color video camera, a digital RGB camera installed on the study was based on the analysis of agricultural structures wing, and a multispectral (700 g) sensor on the nose, consist- (crops, furrows, ridges) affecting the topography through the ing of six individual CMOS digital cameras, arranged in a 2 × 3 generation of high precision DEMs. array and using filters with center wavelengths from 450 nm - 850 nm. Rango et al. (2009), Laliberte and Rango (2009 and Biodiversity Analysis 2011), and Laliberte et al. (2010) proposed an image texture- From the point of view of biodiversity analysis, Getzin et al. based method for determining the coverage of rangelands with (2012) determined the floristic diversity in the forest under- different textures by applying several scales in ortho-rectified storey. This application is environmental monitoring where mosaics. The platform was also the one used in Laliberte et gaps in the canopy are analyzed with the goal of preserving al. (2011), and the classification approach used was: object- structural diversity and niche differences within habitats for based, rule-based, and textured-based (homogeneity, con- stabilizing species coexistence, which was achieved utilizing trast, dissimilarity, entropy, angular second moment, mean, the high-resolution RGB images captured with a fixed-wing standard deviation, correlation, entropy). Later, Laliberte et al. UAV. Later, Getzin et al. (2014) have studied gap distributions (2011) analyzed different geometric errors of image mosaics in forest canopies to determine the regeneration of trees based and classification accuracies at different levels of detail in on statistical analysis, which was achieved using high spatial rangelands with the platform and sensors described above. resolutions (7 cm/pixel) based on RGB ortho-rectified images Different types of vegetation were classified in Arnoldet al. acquired from a UAV with weight of 6 kg and wing span of 2 m. (2012 and 2013), through vegetation indices, based on an im- Also regarding biodiversity analysis, land-use change agery multi-spectral system, consisting of three visible bands monitoring is an important application to control greenhouse (400 nm - 590 nm, 500 nm - 590 nm, 590 nm - 670 nm) and gas emissions and biodiversity loss (Wich and Koh, 2012). two infrared bands (670 nm - 850 nm, 850 nm - 1000 nm). The Rural Roads and Geological Infrastructures images were acquired simultaneously with multiple CCD arrays Unpaved roads in rural environments were monitored with where the incoming light is projected with specially designed the aim of identification and surface inspection (Zhang, 2014). dichroic-coated prisms to single monochrome CCDs. The multi- The platform used was a helicopter with payload of 680 g spectral system was mounted on an unmanned helicopter. equipped with a digital commercial camera together with a Kelcey and Lucieer (2013) applied different texture de- navigation system (GPS/INS). Also, rural roads were monitored scriptors for describing both vegetation and non-vegetation in Zhang (2014), where stereo-based techniques are applied to areas based on the co-occurrence descriptor and the random obtain 3D orientation with a RGB camera onboard a helicopter forest machine-learning technique in ortho-mosaics. Knoth as an UAV. Geological hazard analysis is considered in Qian et et al. (2013) classified four different types of vegetation using al. (2012) to early detection of anomalies and to prevent disas- NIR imagery for monitoring restoration in cutover bogs. ters on infrastructure such as roads or bridges. Regarding the coverage analysis, Breckenridge et al. (2011) and Breckenridge and Dakins (2011) used a camera based

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 303 system onboard a fixed-wing and a helicopter to analyze vegeta- Bueren et al. (2015) tested and compared four (visible, vis- tion coverage in bare ground. The data provided by the UAVs ible + IR, multispectral, and hyperspectral) sensors onboard were compared against field estimates, showing good agree- two octo-copters to capture the reflectance from grasslands. ment for the measurement of bare ground, particularly with the Their challenges and limitations were discussed. helicopter. Breckenridge et al. (2012) estimated the percentage Feng et al. (2015) have analyzed urban vegetation using of coverage in six different types of vegetative (live and dead random forest and texture analysis. Off-the-shelf RGB digital shrub, grass, forbs, litter, and bare ground). The final goal in the cameras, onboard a fixed-wing UAV with 2.5 m wingspan and above three works was to analyze the ecosystem sustainability. a length 0f 1.58 m, were used. Suzuki et al. (2010) determined the vegetation coverage through visible and infrared cameras on-board a fixed-wing Photogrammetry Photogrammetry is a traditional topic in combination with UAV that allows building images mosaics with the help of the remote sensing. UAVs equipped with sufficient sensor tech- GPS and the IMU. Strecha et al. (2012) proposed the combina- nologies are able to obtain remote measurements from images, tion of NIR and visible images to produce orthoimages and which are conveniently processed in order to produce: 3D DEMs with machine vision systems installed on UAVs. The goal was to build vegetation maps to monitor different species. terrain mapping with Digital Elevation Models (DEMs) or DSMs An unmanned helicopter, with 0.57 kg weight capable with shapes, surface reconstruction, elevation contours, or of lifting an 11.5 kg payload with a fuel engine, was used in features. All these products are useful for cartography and Xiang and Tian (2011) to monitor turf grass glyphosate appli- topography, where ortho-images are also final or intermedi- ate products. Generally, photogrammetry is the support for cation based on multi-spectral CMOS sensor consisting of three bands (green, 520 nm - 620 nm, red 620 nm - 750 nm, and other applications. Sometimes, the quality of photogram- metric products, such as orthophotos, is not always achieved NIR 750 nm - 950 nm). The UAV was equipped with additional successfully because of the movement of the UAV or due to sensors: GPS, IMU, video-transmitter, wireless router, single board computer, and flight controller. overlapping errors that require special treatments (Samad et The third topic considered is vegetation development al., 2013). In this regard, studies conducted toward validation of measurements with robust processing methods are useful from different points of view. Imagery-based data from UAVs, combined with satellite information, were used for studying to determine and obtain sufficient quality (Riekeet al., 2011; vegetation development in braided areas in the French Alps. Mesas-Carrascosa et al., 2014, Ai et al. 2015). The flow of rivers and wind are relevant for the transport of Figure 10 displays a DSM built from images captured with seeds (Hervouet, 2011). a visible camera (Courtesy of QuantaLab-IAS-CSIC, Cordoba, Lucieer et al. (2010, 2011, 2012, and 2014c) and later Spain). The goal of photogrammetry with respect to UAVs is to Turner et al. (2014a) in a broad and extensive research, com- achieve similar or higher accuracies to the ones obtained with airborne-based systems (Haala et al., 2011; Remondino et al., piled in such references, applied SfM and SIFT techniques for 2011; Strecha, 2011; Liu et al., 2011) where rapid rotational 3D mapping of moss beds in Antarctica to determine their or translation movements in UAVs increase the difficulty of extent along the terrain. They also obtained a thematicDelivered map by Ingenta of moss health derived from the multispectral mosaic using a image orientation for subsequent processing, requiring precise IP: 192.168.39.151 On: Sat,registration 25 Sep 2021 or matching 13:24:12 techniques. Colomina and Molina Modified Triangular VegetationCopyright: Index American(MTVI) and anSociety indicative for Photogrammetry and Remote Sensing map of moss surface temperature. For these tasks, they used (2014) provide an extensive review related to data processing techniques considering that, in the context of photogramme- two UAVs depending on the goal to be achieved: (a) an electric helicopter capable of lifting 1.5 kg; and (b) an autopilot octo- try from UAVs, their performance is similar to products from copter with payload of 1 to 1.5 kg. Three sensors which were piloted, airborne-based systems. In this regard, the revision used sometimes individually and sometimes all together: (a) is focused on three main topics: (a) image orientation for visible digital camera weighing approx. 355 g; (b) multispec- navigation and camera calibration to cope with the problem tral six-band sensor with wavelengths at 530 nm, 550 nm, of irregularity of frames acquired from UAVs, where computer 580 nm, 670 nm, 700 nm, and 800 nm, determined by 10 nm vision techniques provide some solutions, such as SfM or automatic tie point generation based on point detection and filters; and (c) aFLIR thermal sensor. A motion compensated gimbal mount stabilizes these devices. In addition, the vigor descriptors with sufficient accuracies likeSIFT , their variants of these moss beds was addressed in Lucieer et al. (2014b) and many others; and (b) surface reconstruction, to obtain DSM and ortho-photos with sufficient accuracies in point using the HyperUAS (see the Multispectral and Hyperspectral subsection). This was achieved by studying the photosyn- cloud generation and densification, including multi-view thetic activity based on the ability to acquire images with stereopsis techniques. high spatial and spectral resolutions. Different experiments In the context of photogrammetry, some National Mapping were conducted to assess the performance in georeferencing and Cadastral agencies have considered and acquired UAVs to and ortho-rectification that allows the generation of precise develop some activities and products within its competence (Cramer et al., 2013). A brief list of some examples is as fol- mosaics and DSMs. This HyperUAS allows the quantification of chlorophyll content and biomass in pasture and barley crop lows: spatial data infrastructures, geodesy, GIS, cartography, by computing optical vegetation indices with relevant traits, topographic mapping, cadastral applications, mapping for emergencies, erosion, or change detection. In this regard, Eyn- namely: NDVI, transformed chlorophyll absorption in reflec- dt and Volkmann (2013) reported that UAVs suitably equipped tance index (TCARI), and optimized soil-adjusted vegetation can accomplish these tasks well. Also, Mesas-Carrascosa et al. index (OSAVI). Negative impact analysis relating to the invasion of grass- (2014) analyzed the potential use of very high resolution UAV land by woody shrubs was addressed in Rango et al. (2011) imagery to measure the area of land plots to monitor land pol- with the aim of reversing this situation to the original one by icies. The fixed-wing UAV, with a 2 m wingspan and TOW 5.8 kg was operated by people of the QuantaLab-IAS-CSIC (2014) analyzing historical data. In this application, UAVs turn out to be an excellent tool where ranchers and scientists have ex- team and equipped with a six-band multispectral camera. Object reconstruction and modeling are also feasible from ploited their abilities. A fixed-wingUAV was used, equipped with a consumer visual digital camera in the wing and a remotely sensed data. An important issue addressed in pho- togrammetry is the validation of measurements from images video camera in the nose. The UAV is catapult launched using a gasoline engine. for achieving the maximum accuracy possible (Gini et al., 2013). Feature detectors (SIFT) and image matching techniques

304 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING Figure 10. Digital Surface Model built from images captured with a visible light camera (Image courtesy of QuantaLab-ias-csic, Cordoba, Spain).

(least-squares) were evaluated in Lingua et al. (2009) for DSM Harwin and Lucieer (2012a and 2012b) applied multi- generation. The images were acquired with an off-the-shelf view stereovision (MVS) techniques to obtain 3D structure visible light camera. from overlapping imagery captured from multiple angles. An Progress related to machine learning-based techniques for octo-copter with approximate payload limit of 1 kg is the UAV DSMs generation has reinforced its use for images acquired used. It was equipped with a stabilized camera mount to carry from UAVs (Rosnell et al. 2011). different sensors, including a commercial digital camera. A Virtual reality is another issue closely related to pho- very dense point cloud was produced with sufficient accura- togrammetry. In this way, Linkugel and Schilling (2013)Delivered by Ingentacy. Accuracy is a central issue in photogrammetry as reported proposed a simulation system whereIP: a192.168.39.151 micro-UAV is used On: Sat, 25in SepKüng 2021 et al. 13:24:12(2011a) and Vallet et al. (2011), where different for computing 3D measuresCopyright: for virtual American reality purposes.Society for The Photogrammetry experiments and have Remote been carried Sensing out with light UAVs, weighing mathematical model was described, including all aerodynam- less than 500 g with maximum payload of 125 g. Different ic parameters of the UAV toward the definition of the geomet- methods and strategies for point cloud generation from digital ric modeling based on different sensors. images captured with UAVs flying at relatively low altitudes Digital elevation models and 3D mapping with DSM or DTM were also addressed in Siebert and Teizer (2014) for 3D map- production together with mosaicking with geo- and ortho- ping in mapping earthwork projects. rectification are two main topics inside photogrammetry; Regarding digital surface models, a laser scanner, two CCD- both are considered separated here, although they are closely based digital cameras (with weights of 500 g each) and two related. infrared devices (NIR sensitivity with 500 g) were integrated together with an IMU and GPS in Nagai et al. (2009) for such a 3D Mapping, Digital Surface, Elevation, and Terrain Models purpose. A 3D shape is obtained by the laser scanner as point Nex and Remondino (2014) and Remondino et al. (2011) cloud data, texture information is acquired by the digital cam- provided a review with new insights and proposal for differ- eras, and vegetation indexes are acquired by the IR cameras ent photogrammetry-based applications, including 3D digital simultaneously. The UAV is a helicopter with weight of 330 kg terrain or 3D textured models. Photogrammetric approaches, in- and payload of 100 kg with two main rotors (4.8 m diameter) cluding topographic maps with slopes, have been described in and two tail rotors (diameter of 0.8 m). Tahar et al. (2011 and 2012) oriented to landslides applications. High-resolution surface models are possible by using UAVs Hugenholtz et al. (2013) evaluated the accuracy in DTM flying at low altitudes. Manciniet al. (2013) developed a production using a fixed-wing UAV that weighs less than 6.2 kg method based on SfM to build such models in unstructured and equipped with an off-the-shelf CCD-based visible camera. coastal environments. An electric hexacopter was the UAV Different works have been proposed for 3D model genera- used, with a 1 m diameter and total weight of approximately tion. In this regard, point cloud generation is a task of interest 5 kg, and equipped with a digital camera. Walker (2012) also for 3D mapping accuracy, a procedure for such a purpose was addressed the topic of coastal management applications. proposed in Rosnell and Honkavaara (2012) with two RGB- In Delacourt et al. (2009) DEMs and orthorectified images, based digital still CCD-cameras. Two quad-copters were used, acquired from and helicopter, are built with high spatial which were able to carry 300 g and 1.2 kg payload, equipped resolutions (<5 cm). The system was tested on the beach of with cameras weighing 180 g and 448 g, respectively. Porsmillin (French Brittany) for the quantification of morpho- Neitzel et al. (2011) used an octo-copter (1.2 kg net weight sedimentary changes of the coastal fringe, including cross- or TOW 2 kg with camera) for 3D mapping landfills with the shore and long-shore sediment transport. aim of determining its volume and quantity based on point Imagery change detection techniques for topographical cloud computation. 3D building models are obtained in Jizhou reconstruction were applied in Xuan (2011), where DSMs et al. (2004) using a fixed-wingUAV equipped with a CCD-based were built from the remotely sensed data based on different camera. They captured oblique images to obtain relevant parts techniques, including: triangulation, DEM generation, ortho- of buildings instead of using a pair of images as usual. imaging, and mosaicking. Two types of UAVs were used: (a)

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 305 three blimps of nylon with helium bottles for inflating with landscapes was also carried out in Wundram and Loffler lengths of 12.4 m to 18.3m and payload between 6 to 15 kg; (2008) based on DEM production. and (b) three fixed-wing models, with lengths of 2.0 m to 2.8 m with a payload between 2 to 5 kg. Mosaicking, Ortho- and Geo-rectification Whitehead et al. (2013) measured surface motion and Images acquired with UAVs cover relatively small land areas; elevation changes of an Arctic glacier based on image process- hence, automatic mosaicking and rectification are required for covering larger areas when required. Most applications ing techniques. They used UAVs and then a piloted helicopter. described above were based on mosaic and ortho-rectified A DEM and an ortho-mosaic were generated with accuracies images. Here, only specific aspects regarding both topics are comparable to those obtained from a fixed-wing UAV with payload of approx. 0.5 kg. addressed. Bathymetry measurements, obtained with very high spatial Mosaicking and ortho-rectification are products obtained in real-time from video streams (Zhou, 2009), where the UAV resolution imagery sensors onboard UAVs, were obtained for platform has 1.53 m (length) × 1.53 m (height), with wingspan producing DEMs and studying the riverbed of the Ain and the Drôme rivers in France (Lejot et al. 2007). of 2.44 m, weight of 10 kg and payload of 2.3 kg. Different Aerial photography was combined with mobile lidar on efficient methods have been proposed for accuracy in the gen- eration of such products, including SIFT for matching (Xing the ground for obtaining a seamless DTM with the purpose of studying changes in river channels and their floodplains et al., 2010a and 2010b; Xing, 2010; Yang et al., 2013). The (Flener et al. 2007). efficiency in the generation of these products withUAVs , with Yun et al. (2012) and Kim et al. (2013) proposed the use of relatively high ease of use, has led to considerable advances from the point of view of remote sensing in the last few years a 3G Smart phone onboard a fixed-wingUAV , with all devices previously calibrated, including the camera for photogram- (Zhao et al., 2006). SIFT is also the method used in Zhang et metric purposes. The system was programmed based on the al. (2011) with overlapped images captured from UAVs to pro- Android operating system. duce photogrammetric products. Matsuoka et al. (2012) applied photogrammetry-based Feature matching and SfM were used in Turner et al. (2012) techniques for deformation measurements, with sufficient for geometric correction and mosaicking. The images were accuracy, of a large-scale solar power plant. They used im- processed to create three-dimensional point clouds, which are ages acquired with a calibrated, non-digital camera onboard a used to build DTMs; then, images are mosaicked. An octo-cop- quad-copter and based on a sufficient number of ground con- ter, with a digital commercial camera, is the UAV used with trol points. Control points are relevant features in photogram- payload limit of approximately 1 kg. metry for product generation as tested in Chiang et al. (2012). Turner et al. (2014a) applied a direct georeferencing tech- nique by synchronizing the camera exposure time with the An UAV with wingspan of 5 m and payload of 25 kg was used. position of each airframe recorded by a GPS. Image processing Manyoky et al. (2011) reported that UAVs were tested for capturing geodata and compared with conventional acqui- techniques were used to eliminate blurry images and images sition methods for cadastral applications. Two different with excessive overlapping. They compared three different Delivered bysoftware Ingenta methods using an octo-copter with payload capability methods (tachymetry/GNSS and an UAVIP:) were 192.168.39.151 applied in two On: Sat, 25 Sep 2021 13:24:12 test areas in Switzerland: (a) a mountainous area in Krattigen; of up to 2 kg, equipped with a commercial and stabilized digi- Copyright: American Society for Photogrammetrytal camera. Direct and image Remote georeferencing Sensing using the UAVs georef- and (b) a suburban area in Campus Science City ETH Zurich. erencing was previously tested in Bláha et al. (2011) using and Regarding the UAV, an octo-copter with payload of 500 g was octo-copter with payload of 500 g and equipped with a camera, used. It was equipped with a GNSS, a barometric height sensor, three magnetometers, a barometric altimeter, an INS and a GPS. a compass, an IMU, and a commercial camera weighing 265 g. Cadastral surveys were carried out by Cunningham et al. In the context of agriculture, an automatic image-based (2011) in rural areas in Alaska for generating orthomosaics, UAV system was developed in Xiang and Tian (2011) to obtain georeferenced images for mosaicking and ortho-rectification. from an UAV-mounted camera, with the purpose of testing The system was a helicopter, a CMOS multispectral camera other sensors (lidar, SAR) also for cadastral mapping. Hinsberg ranging from 520 nm to 950 nm, an IMU, a differentially-cor- et al. (2013) used images acquired from an UAV for boundary identification, obtaining sufficient accuracies in the experi- rected GPS, a single board computer (SBC), a flight controller, a ments carried out in Austerlitz and the City of Nunspeet, pulse-width modulation switch, a wireless router, and a video transmitter. Netherlands. DEMs quality represents a challenge for cadastral applications. In this regard, Berteška and Ruzgienė (2013) Mayr (2011) reported on the applicability of a 1.1 kg fixed wing UAV in photogrammetry for building ortho-mosaics and have analyzed this issue using a fixed-wingUAV platform with wingspan of 1.8 m and a take-off weight around 4 kg, DSMs through several examples, and Gülch, (2012) for photo- grammetric measurements using different software packages. equipped with an off-the-shelf CCD-based camera. Regarding the orthorectification, Mesas-Carrascosaet al. Immerzeel et al. (2014) applied stereovision and SfM to de- (2014) have studied the positional quality of orthophotos rive highly detailed ortho-mosaics and DEMs by using a fixed- obtained with an off-the-shelf commercial digital camera wing UAV with a wingspan of 80 cm and a take-off capacity of 0.5 kg. It is equipped with a digital camera triggered by the onboard a quad-copter with maximum payload of 1.2 kg. autopilot system. The goal was the observation of debris-cov- Aerial triangulation, DSM generation, and mosaicking were the ered tongue of the Lirung Glacier in Nepal before and after the processing techniques applied. melt and monsoon season. Stereovision is also the technique Because of the large amount of data provided by UAVs equipment, Stødle et al. (2014) proposed a system for 3D data applied in Stefanik et al. (2011) for terrain 3D mapping. The stabilized stereovision system consisted of two gray cameras visualization based on raster maps and topography with high performance. with a baseline of 1.5 m plus an IMU with total weight of 28 kg onboard an autonomous helicopter with payload of 94 kg. Atmospheric: Observation, Air Analysis, and Pollution DSMs products were also obtained, with accuracy and New challenges in atmospheric observations are now steadily precision, in Tonkin et al. (2014) from a large glacial circle at growing within the area of UAVs, where some vehicles and Cwm Idwal, North Wales, by applying SfM to images acquired sensors have been specifically designed for such purpose. with a hexa-copter equipped with a digital RGB commer- Air concentrations of gases, aerosols, ozone concentrations, cial camera. High-resolution spatial analysis of mountain temperature, humidity, pressure, wind fields are the most important data collected.

306 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING Under the ASTRA (Atmospheric Science Through Robotic how transport distances vary between seasons from potential Aircraft) umbrella, the MAVIS project is in development with inoculum sources. the aim to equip a fleet of gliders with atmospheric instru- ments (Sobester et al., 2011 and 2012). Gliders are released Cultural: Heritage and Archeology at high altitudes and during the auto-piloted descent, they Cultural heritage and archeology are two topics, sometimes recover data for different purposes: weather forecasting, pol- very close to each other and sometimes indistinguishable. lution, aerosol monitoring, wind speed, temperature, and Both are related to human activity in the past. UAVs are con- turbulences among others. sidered useful tools for inspection in heritage and archeologi- Atmospheric measurements, including temperature, cal applications. Yan et al. (2012) discussed advantages and humidity, and pressure were captured for data analysis in shortcomings of photogrammetry at low altitudes from UAVs Corrigan et al. (2008b) along an atmospheric profile at differ- in architectural heritage applications. They assumed that the ent altitudes. The system was described in the Atmospheric complexity of architectural heritages determines the particu- Instrumentation subsection. These data were combined with larity of aerial photogrammetry. Also Remondino et al. (2012) other data sets coming from an aerosol analyzer and a particle concluded that, in cultural heritage, SfM methods suffer from counter that provided measurements of albedo, atmospheric lack of reliability and repeatability when complex and long solar absorption, heating rates in the visible (0.4 µm - 0.7 µm) sequences of data are processed. and broadband (0.3 µm - 2.8 µm) spectral regions using verti- Cultural Heritage cally stacked multiple lightweight UAVs (Ramana et al., 2007). Eisenbeiss et al. (2005 and 2006), and Eisenbeiss and Zhang Finn and Franklin (2011) described a technique for moni- (2006) analyzed the generation of DSM in the cultural heritage toring the air temperature and wind fields in areas close to site of Pinchango Alto, Peru, based on multi-image matching the ground surface. Sound signals emitted by its engine were and registration techniques in overlapped images. The images transmitted using radio communications. Additionally, re- were acquired with an autonomous helicopter equipped with ceivers placed on the ground captured signals coming directly a commercial digital camera, and the results compared against from the UAV. Differences based on the Doppler effect of both a laser-based ground technique. signals allow for the temperature and wind measurements. A quad-rotor, with empty weight of 585 g, maximum In an agricultural context, the potato late-blight pathogen payload capacity of 200 g and equipped with a CMOS-based in the atmosphere has been tracked in Aylor et al. (2011) by sensor, was the platform used in Hendrickx et al. (2011) for using a 3 m wing-span UAV, engine powered, equipped with heritage documentation, based on photogrammetry, in the sporangia samplers mounted under the wings. Aerial concen- Tuekta area, in the Russian Altay Mountains. The goal was trations of plant pathogenic spores at various distances from to obtain two types of products: photogrammetric (DEMs and a source of inoculum have been quantified to determine the ortho-images) and archaeological datasets (3D visualisation potential spread of a plant disease. and volume estimations). Berman et al. (2012) used the Off-Axis ICOS device to mea- Gini et al. (2012) used two digital compact cameras for suring in-situ H2O, CO2, and CH4 air concentrations,Delivered primarily by Ingentaacquisition of RGB and NIR images onboard a quad-rotor; the for greenhouse locations and influencedIP: 192.168.39.151 areas, with the On: pos -Sat, 25last Sep one 2021 modified 13:24:12 with a filter that allows the radiation with sibility of its applicationCopyright: to large forest American and remote Society locations. for Photogrammetry wavelength and greater Remote than 830Sensing nm, with weights of 130 g and The fully assembled UAV device measures approximately 30.5 250 g, respectively, for 3D modeling and tree classification in cm × 30.5 cm × 28 cm and weighs 19.5 kg. the Parco Adda Nord, (Italy). Kroonenberg et al. (2012) measured the structure param- Brumana et al. (2013) presented a work oriented to build eter of temperature in the lower convective boundary layer panoramic images for heritage simulation purposes in areas of with a mini-UAV. The UAV was a wingspan of 2 m and a maxi- interest. Images acquired from the UAV were combined with mum TOW of 6 kg. data from ground sensors with the aim of forming the pan- Xie et al. (2013) proposed a monitoring atmospheric en- oramic setup. The UAV platform was a helicopter with an over- vironment framework based on UAVs for emergency applica- all weight of 7.3 kg, main rotor diameter 1,564 mm, and a 7 kg tions. They described the platform, instruments functions, payload. A digital camera installed on a mechanical stabilizer. and procedures to carry-out such missions. Candigliota and Immordino (2013a and 2013b) described Gyongyosi et al. (2013) described a weather prediction sys- some technological issues for data acquisition in real-time tem based on a statistical model and learning-based methods. for monitoring cultural heritage. Three applications were ad- The UAV, with a wingspan of 3.7 m, length 1.7 m, maximum dressed: landslide of a hill affecting a historic village center, TOW 17 kg and payload about 4 kg captures actual climatolog- knowledge acquisition of a historical building for restoration, ical data around an area and the forecast is provided accord- and damage evaluation after the Emilia-Romagna earthquake. ing to the data and the model. Weather research and predic- They used a helicopter and a quad-copter equipped with tion is documented in the report provided by Darack (2012) stabilized platforms to hold the camera. where several aircrafts and sensors are mentioned. Koutsoudis et al. (2014) evaluated the performance of the In the project described in Daehler (2014), an UAS was SfM and dense multi-view 3D reconstruction techniques for equipped with a radar unit operating in HF and VHF ranges high building 3D models. An UAV was equipped with a three for collecting data from the air and the surface of the ice in axis pan-tilt-roll remote controlled digital camera head. The Antarctica and Greenland. SfM approach was applied to the reconstruction of an Ottoman Lin and Chen (2014) proposed the use of an autopilot monument located in the region of Xanthi, Greece and com- helicopter to study aerosol and ozone concentrations at low pared against a time-of-flight terrestrial 3D range scanner. altitudes. Atmospheric concentrations of spores of fungi belonging to Archaeology the genus Fusarium were studied in Lin et al. (2014) by using Early on, the use of UAVs in archaeology was considered as both a terrestrial system and UAVs. The fixed-wingUAVs ex- promising (Schlitz, 2004). In archaeological explorations, plored the atmosphere in an agricultural ecosystem flying 100 photogrammetric techniques are commonly used for analysis m above ground level and equipped with aerobiological sam- and inventories, where 3D models (DSMs and DTMs), mapping, pling devices containing large plates of 9 cm diameter similar mosaics or ortho-images are typical photogrammetric prod- to the ones used in Schmale et al. (2008) and Lin et al. (2013). ucts of special interest in archaeology. In addition, thermogra- The goal was to study variations with height and season and phy was applied in this application.

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 307 Sauerbier and Eisenbeiss (2010) proposed the use of UAVs Italy. They integrated 3D recording techniques, photogrammetry, and photogrammetric techniques for documenting excavations and terrestrial laser scanner techniques. A quad-rotor was used in archaeology under the assumption that inventories are for the acquisition of aerial images with payload of 1.2 kg and suitable and necessary, because objects continuously change. equipped with a commercial color camera. Three case studies were documented: (a) large archaeologi- Casana et al. (2014) described a technique based on cal site in Bhutan, explored by a quad-copter with TOW of up thermography for discovering undocumented architectural to 5 kg; (b) excavation of a smaller site in the Nasca region in remains in the subsurface at the Chaco-era Blue J Community, Peru, containing ancient tombs with uncovered objects, with New Mexico. The UAV was an octo-copter that can lift around a helicopter; and (c) a Maya site of Copán in Honduras, using 2 kg of payload, with cameras mounted on an independently a helicopter with petrol engine, payload of 5 kg and main operated gimbal suspended below the UAV. The gimbal is ca- rotor of 2 m. Photogrammetric techniques were applied in (a) pable of a full 360º of motion, enabling cameras to be pointed and (c) for 3D modeling of buildings and their remains. In (b) in a predetermined direction or at a specific point regardless only the aerial images are directly analyzed. Later, the same of the motion of the UAV. authors in Eisenbeiss and Sauerbier (2011) reported about the use of similar UAVs platforms in the Bhutan and Honduras Wildlife Conservation, Inventories, and Monitoring sites plus two additional sites in Pinchango Alto and Pernil Conservation and preserving ecosystems where wildlife exists Alto in Peru. Commercial cameras were the sensors used. is a crucial issue. The use of UAVs for this purpose has at- Chiabrando et al. (2011) applied computer vision-based tracted the interest of researchers for several years. More than a decade ago, Jones et al. (2006) studied during 2002 and 2003 techniques, including ortho-rectification, to buildDSMs in two the use of a 1.5 m wingspan UAV equipped with autonomous archaeological sites of the Piedmont region in Italy. Two UAVs, both equipped with commercial cameras, were tested for this control and video equipment to test the potential usefulness of type of works: (a) helicopter in the Reggia di Venaria Reale such an aircraft for wildlife research applications in Florida. site; and (b) fixed-wing plane in the Augusta Bagiennorum. Chabot (2013) studied specifications and features of anUAV for wildlife monitoring and survey applications. In sensitive Mosaics, DSMs, and overlaid contours based on RGB com- mercial digital cameras were obtained in Remondino et al. ecosystems, they avoid having to walk the terrain, leading (2011) in two archaeological areas: (a) Veio and Pava (Italy) to severe damage, with footprints or ground vehicle tracks. with a quad-rotor, and (b) a Maya site in Copan (Honduras) Biologists have an excellent tool for many of their activities, with an unmanned helicopter. where specific designs of UAVs have been considered (Schiff- man, 2014; Humle, 2014; Luo, 2014). Kite aerial photography Mészáros (2011) used a fixed wing UAV, with 1.8 m wing- has been used in intertidal ecosystems for mapping of plants span and weight of 0.9 kg, equipped with a RGB commercial pocket camera (37 g) for ortho-mosaic generation in an undis- (micro-and macro-algae) and animals (gastropods) assemblag- covered archaeological site, signed by a crop-mark in moun- es at different spatial and temporal scales (Bryson et al., 2013). tain Pilis, Hungary. From the remote sensing point of view, two main topics are Grün et al. (2012) integrated images of different resolutions addressed for wildlife inventories and monitoring, specifi- Delivered bycally: Ingenta fauna and flora. (satellite, UAV, and terrestrial) to obtainIP: a 192.168.39.151textured 3D model On: Sat, 25 Sep 2021 13:24:12 (DTM) of the Buddhist fortressCopyright: Drapham American Dzong located Society in forthe PhotogrammetryFauna and Remote Sensing Bumthang District, Bhutan. Large terrestrial and marine animals (elephants, rhinoceros, Mozas-Calvache et al. (2012) proposed a method for pho- bison, lions, sea lions, manatees, dugongs, bears, deer, foxes, or togrammetric survey with a tethered helium balloon (2.5 m whales) and bird colonies (geese, gulls) have been surveyed and diameter) in an archaeological site from the Tartessic epoch monitored using UAVs. An important role played by UAVs is that in Southern Spain. They considered the undesired effects of “aerial guardians” for the prevention of poaching. Currently, produced in the photography acquired by these platforms major efforts are being made in this regard, particularly for derived from uncontrolled factors, such as wind or lack of wildlife conservation (Yeld, 2013) and illegal fishing activities. flight control. Large herbivores were monitored in the Gonarezhou Na- Brutto et al. (2012) presented DSMs and ortho-images re- tional Park in Zimbabwe, with the plan of studying trends, sults of the survey of the archaeological site of Himera in Sic- behaviors, and changes in their populations Dunham (2012). ily (Italy), from images obtained through a quad-copter with Elephants have been monitored and surveyed in Burkina load capacity of 0.2 kg, weight 0.9 kg, and diameter of 70 cm Faso with UAVs, where the aim consisted in determining equipped with a commercial camera with a CCD of 7.6 mm × UAV system’s parameters (maximum altitude for discrimi- 5.7 mm. In addition, DSMs and ortho-images were used in Rin- nation, camera system geometry) for discriminating single audo et al. (2012) and tested on a Roman villa archaeological animals or groups at the same time the animal’s behavior was site located in Aquileia (Italy), a well-known UNESCO World studied when the UAV flies above (Vermeulenet al., 2013). Heritage list site. A hexa-copter, weighing approximately 650 The UAV was a wing fixed system (catapulted through an g and maximum payload of 1 kg, equipped with a visible elastic launcher) with wingspan of 100 cm and weight 2 kg, CMOS sensor was used. The same products were obtained equipped with a commercial still digital camera. Prevention with a quad-rotor (700 g of payload) in Seitz and Altenbach of elephant deaths by trains is to be addressed by using UAVs (2011) in two sites: (a) the excavation of a wooden Roman fort for tracking their movements with the aim of alerting the train in Neuhofen, Germany; and (b) the Daramsala, “House of the drivers (Bala, 2014). Guests” in Banteay Chhmar, Cambodia. Different thermal (FLIR-based) and RGB images are used A fixed-wing UAV (RPA) with wingspan of 1,960 mm and in Brumana et al. (2013) for documenting the archaeological a maximum take-off weight of 2 kg with a 350 g payload site of Isola Comacina (Comacina Island), in the Lago di Como equipped with radio control and three different types of cam- (Italy) where rock structures partially buried were studied. eras (still, video, and thermal) was used to verify its ability for The UAV is an octo-copter, size of 70 cm × 60 cm, and weight rhinoceros anti-poaching tasks in cooperation with security of 2 kg. A FLIR sensor was used in Poirier et al. (2013) for the companies working in the KwaZulu-Natal province of South detection of archaeological buried structures onboard an octo- Africa (Mulero-Pázmány et al., 2014). copter with wingspan of about 80 cm and payload of 3 kg. Wilkinson (2007) described different methods for image Fiorillo et al. (2013) developed reality-based 3D digital georeferencing, acquired from UAVs, with the aim of invento- models and ortho-images of the archaeological area of Paestum, ries of bison as part of the wildlife.

308 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING The prestigious National Geographic magazine reported Flora about the use of UAVs (drones) to photography the daily life Components and current capabilities of small UAVs have been and behavior of lions (Thurston, 2014). Animals are not dis- developed specifically for wildlife and ecological surveys that turbed, because they did not consider these devices as threats. is currently in field use for a variety of applications (Wattset Israel (2011) proposed a technology based on geo-refer- al., 2010). enced thermal images for detecting fawns in areas where they Monitoring vegetation and flora in rainforest areas is of graze to avoid undesired damage. Monitoring was carried out special interest to control the vegetation status. This research from a base station where the strips of video imagery were was carried out in Koh and Wich (2012) with a fixed-wing received from an octo-copter. UAV weighing 650 g approx., equipped with a commercial still But, not only wildlife on the savannah or the jungle are CMOS camera. The study site and the national park are part of monitored with UAVs; these platforms have been used for a broader Leuser Ecosystem that contains the last few contigu- remote monitoring marine mammals. Some reasons to use ous lowland rainforests in Sumatra. Additionally, thanks to UAVs for this purpose were reported in Hodgson (2015). the high camera resolution, large mammals are also surveyed Indeed, surveillance of large marine mammals was carried (elephants and orangutans). out in Koski et al. (2009) with an UAV of 3.1 m wingspan, 1.2 Georeferenced images were acquired and processed for m long, and 18 kg maximum gross weight, equipped with monitoring vegetation strips classified as shrubs, woody, and a video camera. Surveys of sea lions for counting popula- tree savannah (Lisein et al., 2013). An autopilot fixed wing tions and other observations were carried out on the coast of with a 1 m wingspan and weight of 2 kg was the platform used. the Aleutian Islands (Walker, 2012). Because of the adverse environmental conditions, several platforms (rotary and fixed Urban Environments and Infrastructure In complex urban environments, some challenges for UAVs wing, including hand and catapult launching) were tested are surveillance, tracking, traffic control, car counting, illegal and evaluated for this type of environment. construction, or building observation. These scenarios are es- Martin et al. (2012) developed statistical models to esti- sentially complex including occluded areas where even UAVs mate the distribution of some hidden organisms that appear equipped with a unique camera cannot reach or have difficult when some factor affects the environment. They first mod- access. Different efforts have been made to solve these kinds eled the statistical distributions with tennis balls including a of problems, including multi-UAV systems (Semsch, 2009). known number of them with high probability to be occluded. Qin et al. (2013) reported on the difficulties found in urban The underlying idea is to establish a relation between a gradi- environments for mapping and modeling. Georeferencing and ent and the distribution. With this approach, they proposed to processing were carried out with an octo-copter equipped know the relationship between the distribution of manatees, with a RGB camera assessing its validity against commercial based on georeferenced images, and the water temperature, and non-commercial software packages. This octo-copter was which is measured in-situ and related with the captured im- also used in Küng et al. (2011b) where automatic image pro- ages. An electric powereded UAV used was a hand-launched, cessing was proposed to generate building models for a final 2.7 m wingspan aircraft weighing 4.5 kg, equipped with an Delivered by Ingentamanual editing and refinement. The procedure was based on off-the-shelf commercial digital camera. IP: 192.168.39.151 On: Sat, 25the Sep generation 2021 13:24:12 of a 3D point cloud (dense matching) which Hodgson et al. (2013) surveyed dugongs in their marine Copyright: American Society for Photogrammetrywas projected and on Remote the z-axis Sensing to detect the building facades and habitat at different flight heights at inaccessible areas avoid- compute the primary directions in the buildings. Driveway ing unnecessary human risks. This UAV is fuel powered, 3.11 surveillance and control represents an urban application m wingspan weighing 13.1 kg, with maximum TOW 20.0 kg, where UAVs have been used (Cummings, 2013). equipped with a commercial digital camera. Visual-based tracking and control in urban areas is an Bears, deer, and foxes were surveyed in the snow in important issue addressed in Campoy et al. (2009). Often, the northwestern Miyagi, Japan (Oishi and Matsunaga, 2014). GPS signal is lost during navigation in such urban areas; it is Registered aerial images were captured from an unmanned necessary to develop strategies to overcome this problem in helicopter for automatic detection and identification based on remote sensing applications. Three platforms were tested: two relevant moving points. gas powered helicopters and one electrically powered rotor- Belugas and other baleen whales species were monitored motion UAV. All were equipped were with visual cameras. with a turret-based stabilized, low-cost multispectral imaging Road information detection is another area of interest system onboard UAVs (Schoonmaker et al., 2008). where UAVs can play an important role for traffic monitoring Automatic bird detection techniques based on pattern rec- and control in Salvo et al. (2014), where a VTOL quad-rotor ognition analysis from images captured with an UAV were ap- with a payload of 300 g is the platform used. Street detection plied as remote sensing approaches in Abd-Elrahman (2005), based on video strips using color images is another applica- where spectral similarities were exploited. tion proposed in Candamo et al. (2009). Sarda-Palomera et al. (2012) monitored temporal changes Image-based change detection techniques are useful for in breeding population size in a black-headed gull colony identifying new configurations of urban areas caused by legal from UAVs that allows for observation in barren or bleak areas or illegal constructions; UAVs are suitable for early detection without disturbance. The UAV was a fixed-wing with a 1 m and actuation (Walker, 2012). wingspan, weighing 2 kg, and equipped with an electric Roca et al. (2013) proposed the use of an autopilot octo- brushless 250 W pusher propeller. Take-off was achieved us- copter for the inspection of outdoor facades in buildings for ing a catapult launcher. both structural and energy considerations. They argued that Evaluation of an off-the-shelf UAV for surveying flocks of these platforms are especially useful when facades are of dif- Canada Geese and Snow Geese was carried out in Chabot ficult access making unfeasible the full D3 characterization. and Bird (2012), where the goal was comparing photographic They used an UAV equipped with a Microsoft Kinect sensor counts from repeated flybys of geese. for the generation of 3D point clouds. Automatic bird counting of a common gull colony was Bulatov et al. (2011) proposed a four-step procedure (ori- used in Grenzdörffer (2013) with two UAVs, a quad-copter and entation, dense reconstruction, urban terrain modeling, and an octo-copter with payloads of 1200 g and 400 g, respective- geo-referencing) for obtaining georeferenced 3D urban models ly. Each was equipped with individual commercial, stabilized from video sequences, where DTM extraction, segregation of cameras. A supervised classification approach, based on the buildings from vegetation and tree modeling were the most size of birds, was the method used.

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2015 309 relevant operations. Automatic detection of heat loss in win- According to Hambling (2014), the future outlook for dows by using autonomous and teleoperated helicopters was the development of UAVs is in cooperation with rapid and addressed in Martinez-de-Dios and Ollero (2006). efficient operations. This aspect is of particular interest for Wefelscheid et al. (2011) used an octo-copter (1.5 kg weight disaster monitoring, where the main goal is to cover the larg- and payload of 500 g) for 3D reconstruction of buildings through est area as possible. Surveillance, monitoring, crop pollina- a consumer camera with prime lens and weight of 285 g. tion, and traffic control appear as promising areas, all from Moranduzzo and Melgani (2014a and 2014b) used an UAV the remote sensing point of view. Apart from the above, new for automatic detection of cars in visible images, captured by insights and perspectives are continuously appearing as re- a commercial camera. Feature extraction and machine learn- ported in Handwerk (2013). ing based on support vector machines were the approaches Miniaturization of UAVs can be a part of some roles, from used. Hierarchical image processing operations were applied the point of view of remote sensing, there are some opportu- expedite the car identification process. nities oriented to the development of very small UAVs, like the Regarding applications in man-made infrastructures, Feng ones imitating birds (Betriu, 2014), equipped with legs that et al. (2009) applied image processing techniques to identify a can perch on branches in the trees. Micro-drones (µ-drones) road and its geometry from an unmanned fixed-wing platform or micro-air vehicles (MAVs) are insect-sized “aircrafts” with weight of 40 kg, equipped with transmission and storage which are being included in the new era of remote sensing. capabilities. Metni and Hamel (2007) described the dynamic They were proposed several years ago with promising expec- of UAVs for monitoring of structures and maintenance of tations (Nonami, 2007). bridges based on simulation results. Nevertheless, industrial development will occur in both, Rodriguez-Gonzalvez et al. (2014) proposed a methodol- platforms and associated elements, to form the full UAV ogy for a 3D reconstruction of complex scenarios applied to system (remote control station, communication links or air electrical substations and demonstrating that camera-based traffic control) and integrated in the national airspace systems systems onboard UAVs can compete with laser-based scanners. (Lasica, 2013). An octo-copter was used for such purpose, equipped with a Mass-media and general media are contributing positively stabilized platform for a visual commercial camera. in the dissemination of UAVs as future systems in several ap- plications, including remote sensing. The Guardian (Napoli, 2012), Reuters (Krishnamurthy, 2013), El Mundo (Treceño, Conclusions and Future Trends 2013), Antena3 TV (2015), and Expansión (2015) are some This work provides an overview of papers and publications examples of general newspapers, news agencies, and TVs. on the status of remote sensing applications based on UAVs: Specific sites can be found at Energy Global (Rehn, 2014), extensively UAS, as special RPA systems. Over 600 studies, Gunderson (2014), or James (2014). coming from peer-reviewed works and relevant websites have As a result, the population is becoming aware of UAVs, been reviewed to provide this overview. The proliferation of contributing new ideas according to the needs expressed or repositories and databases containing links to papers, Deliveredproj- bydetected, Ingenta while companies are taking on new initiatives and ects, and publications is overwhelming;IP: the 192.168.39.151 amount of mate On:- Sat,undertaking 25 Sep 2021 new 13:24:12challenges with impact on the economy rial they contain makes it almostCopyright: impossible American for a Societycomplete for Photogrammetry(Hall and Coyne, and 2014). Remote Sensing referencing (Science.gov Alliance, 2015). Based on some existing studies (GAU, 2014), the compound The progress made in recent years regarding this topic annual growth rate (CAGR) in the UAV remote sensing market to create this overview becomes clear. Indeed, an important is 5.39 percent over the period 2013 to 2018. Due to this in- number of proposals have been studied and international crease, it is expected the advent of new applications in remote events are held periodically on this topic (ARSS, 2014). This sensing with UAVs, as well as the improvement and outperfor- overview starts with a brief description of platforms and its mance of the existing ones (Zhang and Wu, 2014). use in remote sensing. Sensors technologies, instruments, and their abilities for capturing information for remote sensing purposes have also been presented. An extensive review was Acknowledgments and Disclaimer carried out through different applications in a variety of areas Thanks to the following persons, companies and institutions where these systems are being adapted to traditional remote that kindly and selflessly have provided the material exhib- sensing applications. ited in the different figures included in this review, allowing Some conclusions can be considered after this overview. for the illustration of unmanned platforms and results derived First, platforms and sensors are converging towards each oth- from the remote sensing applications. er to accommodate an ever increasing demand for use. Sen- They are listed in the order they appear in the paper: (a) ISCAR- sors and platforms are being matched in every way; an similar UCM Group Madrid, Spain, with special thanks to active mem- example of this fusion can be found in the remotely control bers J.M. Cruz, J.A. López-Orozco, and E. Besada in the project applications based on Smart phones (Parrot, 2015). More and entitled Autonomous System for Locating and Acting in the more areas of application appear demonstrating where UAVs Face of Sea Pollutants (DPI2013-46665-C1), funded by the become efficient. Second, this technology has allowed for the Spanish Ministry of Economy and Competition, where UAVs development of numerous methods, procedures, and strate- and UGVs work together and in collaboration; (b) CartoUAV, La gies specifically adapted for these systems from a unique Coruña, Spain; (c) AirRobot GmbH & Co. KG, Arnsberg, Ger- perspective of the problem to be solved. Third, successes many; (d) QuantaLab-IAS-CSIC, Cordoba, Spain; (e) A. Arjonilla; obtained together with economical aspects derived from their eDroniX, Madrid, Spain; (f) J.R. Martínez-de-Dios and A. Olle- relatively low cost are enhancing their use and extending the ro; Robotics, Vision, and Control Group, University of Seville, range of performance and applications. Seville, Spain; (g) L. Wallace and A. Lucieer, University of For over a decade, Petrie (2001) said the future of UAVs Tasmania, Australia; and (h) F. López-Granados and J.M. Peña; looked promising in remote sensing, confirmed more recently Institute for Sustainable Agriculture, CSIC-Córdoba, Spain. by Tully (2013). In this regard, the relative low cost with Also this document was prepared with economic support respect to the benefits obtained provides a promising future of the European Community, the European Union and projection. AUVSI (2015) reported on the economic impact of CONACYT under Grant No. FONCICYT 93829. UAVs integration in the United States based on potential mar- Special thanks to referees for their help, constructive criti- kets, including precision agriculture, safety, and many others. cism, and suggestions on the original version of this paper.

310 April 2015 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING In this overview references to papers, authors, products, Ambrosia, V., S. Buechel, S. Wegener, D. Sullivan, F. Enomoto, E. organizations, institutions, companies, associations, trade- Hinkley, and T. Zajkowski, 2011. Unmanned airborne systems marks, newspapers, news agencies, TVs and others, do not supporting disaster observations: Near-real-time data needs, mean author’s endorsement or the University Complutense of International Archives of the Photogrammetry, Remote Sensing Madrid where the author is employed. There is no discrimi- and Spatial Information Sciences, 144:1–4. nation in any case, since the author has made an exhaustive Ambrosia, V.G., S. Wegener, T. Zajkowski, D.V., Sullivan, S. Buechel, search from all available sources of information on the topics F. Enomoto, E.A. Hinkley, B. Lobitz, and S. Schoenung, 2011. The Ikhana UAS western states fire imaging missions: From con- unmanned aerial vehicles (systems) or remotely piloted sys- cept to reality (2006-2010), Geocarto International, 26(2):85–101. tems involved in remote sensing areas and tasks. It has been Amici, S., S. Turci, S. Giammanco, L. Spampinato, and F. Giulietti, researched in preference over the last decade and especially 2013. UAV thermal infrared remote sensing of an Italian mud in the most recent years where there have been significant ad- volcano, Advances in Remote Sensing, 2:358–364. vances in remote sensing based on unmanned aerial platforms Anderson, K., and K.J. Gaston, 2013. Lightweight unmanned aerial Apologize, once again, for any omission. vehicles will revolutionize spatial ecology, Frontiers in Ecology and the Environment, 11(3):138–146. Antena3 TV, 2015. Aviones no tripulados, la próxima revolución References aeronáutica (Drones aircraft, the next revolution), URL: http:// Abdelkader, M., M. Shaqura, C.G. 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Appendix A - List of Acronyms AGL Above Ground Level MALE Medium Altitude-Long Endurance ALS Airborne Laser Scanning MAVIS Massive Airspace Volume Instrumentation System ALTM Airborne Laser Terrain Mapper MAVs Micro Air Vehicles AS Altitude Sensors MCCFS Multi-Channel Chemical Filter Sampler ASTRA Atmospheric Science Through Robotic Aircraft MEMS Micro-Electro-Mechanical Systems AUVSI Association for Unmanned Vehicle MTVI Modified riangularT Vegetation Index Systems International Delivered by IngentaMVS Multi-View Stereovision BBCS Blackboard communicationIP: 192.168.39.151 system On: Sat, 25NASA Sep 2021National 13:24:12 Aeronautics and Space Administration CAGR Compound AnnualCopyright: Growth American Rate Society for PhotogrammetryNDVI Normalizedand Remote Difference Sensing Vegetation Index BRDF Bidirectional Reflectance Distribution Function NEC Nippon Electric Company CCA Civil Aviation Authority NIR Near Infra-Red CCD Charge Coupled Device NOAA National Oceanic and Atmospheric Administration CF Compact Flash OSAVI Optimized Soil-Adjusted Vegetation Index CIR Color Infrared RFID Radio Frequency Identifiers CMOS Complementary Metal-Oxide-Semiconductor RPAs Remotely Piloted Aircrafts CSIC Spanish National Research Council RTKGPS: Real-Time Kinematic Global Positioning System CWSI Crop Water Stress Index SAR Synthetic Aperture Radar DEM Digital Elevation Model SBC Single Board Computer DSM Digital Surface Model SD Secure Cards DTM Digital Terrain Model SfM Structure from Motion EOS Electro-Optical-System SIFT Scale Invariant Feature Transform FLIR Forward Looking Infrared SLAM Simultaneous Localization and Mapping FMCW Frequency Modulated Continuous Wave S/MUAS Small and Mini-Unmanned Aerial Systems FOV Field of View TCARI Transformed Chlorophyll Absorption FPGA Field Programmable Gate Array in Reflectance Index GCP Ground Control Points TOW Take-Off Weight GCS Ground Control Station (System) UAVs Unmanned Aerial Vehicles GDS Geomagnetic Direction System UASs Unmanned Aerial Systems GPS Global Positioning System UCM University Complutense of Madrid GNSS Global Navigation Satellite System UGVs Unmanned Ground Vehicles GIS Geographic Information System UHF Ultra High Frequency HS3 Hurricane Severe Storm Sentinel UNEP United Nations Environment Programme IAS Institute for Sustainable Agriculture USGS U.S. Geological Survey ICOS Integrated Cavity Output Spectroscopy USVs Unmanned marine Surface Vehicles IHM Interface Human Machine VCSEL Vertical Cavity Surface Emitting Laser IMU Inertial Measurement Unit VHALE Very High Altitude-Long Endurance INS Inertial Navigation Sensors VHF Very High Frequency INTA National Institute for Aerospace Technology VTOL Vertical-take-off-and-landing ISCAR System Engineering, Control, WLAN Wireless Local Area Network Automation and Robotics WMS Wavelength Modulation Spectroscopy LARS Low Altitude Remote Sensing WSN Wireless Sensor Networks

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