EJERS, European Journal of Engineering Research and Science Vol. 4, No. 6, June 2019 Analysis of Forest Vegetal Characteristics of Akure Forest Reserve from Optical Imageries and Unmanned Aerial Vehicle Data Isaac A. Gbiri, Isaac A. Idoko, Michael O. Okegbola, and Latifat O. Oyelakin which earmarked at the beginning of the 20th century. Abstract—Forest vegetal characteristics monitoring has a References [11] and [19] estimated 285 hectares as the long tradition records with a success rate ranging from low to average annual rate of deforestation in Nigeria between medium or high depends on the application at the hands. 1976 and1980, increasing into an estimated 400 hectares by Details information about the indication of association of the year 2000. Reference [9] reported Nigeria has lost 55.7% phenomena as forest indicators, such forest gap, estate and forest status, provides high spatial resolution images. The aim of its primary forest to logging, subsistence agriculture, of this study focuses on combining unmanned Aerial Vehicles collection of fuel wood and other agents between 2000 and (UAVs) and satellite multispectral imaging along side by side to 2005. details forest parameter during the seasons. UAVs image at The same patterns had been experienced in the tropics and 0.15m appeared more detailed of having features such as rock, sub-tropics Africa. For instance, the East African region lost road, bare ground, riparian trees among others than that of about 10% of its forest cover to deforestation between 1990 Landsat OLI image, though the features such as rock, road, bare ground, and riparian forest were also seen on the image and 2000, with Uganda recorded the highest rate [8]. In the but it was poorly seen due to the coarse spatial resolution of 30 humid tropical rainforest region of Cameroon, about m. The 3-Dimensional of UAVs, relief pattern and contour 200,000 hectares of forest reported to be degraded annually from Shuttle Radar Topography Mission was also compared due to high rate of exploitation. Such clearance has been and this study further demonstrated on the advantages of observed and documented from almost of four decades Unmanned Aerial Vehicle data over established remotely through land cover change detection based on Landsat-1-4 sensed data which includes flying blow the cloud, high spatial resolution, flexibility, inexpensive of data acquisition, time MSS, Landsat-5 Thematic Mapper (TM), Landsat-7 effective, using video footage to detect human activities such as Enhanced TM (ETM+) and Landsat -8 OLI data and has tree flora, burning and logging. resulted in extensive losses of forest and such discoveries in assessing deforestation has generated a lot of questions on Index Terms—Forest Vegetal Characteristics, Monitoring, the validity of data. Among the technical issues in question, Unmanned Aerial Vehicles (UAVs), Satellite Multispectral. the most challenging is that there was no consensus in the literature on the rate of deforestation in most of existing forest reserves globally and regionally often because of I. INTRODUCTION coarse resolution of the optical remote sensors. Early work on forest plantation in Nigeria commences at Recently, technologies such as GPS, miniaturized drones the beginning of the 20th century especially in the south- (UAVs) were initially developed for military use, but are west which practically involved on the economical increasingly being deployed in civilian applications important indigenous tree species [7], ever since Nigeria including mapping, monitoring and managing habitats and settlement after independent, over half of nation`s forests natural resources [14]. Although miniaturized drones are not and woodlands have been progressively cleared subsistence used widely in environmental applications yet, their use is agriculture [17]. Despite recognition of the factors likely to increase rapidly as their prices decrease and the associated with their clearance, deforestation rates technology becomes easier to use [5]. Although [12] cited accelerated in the uncontrollable manner [17]. Much of the [16], [5] in their reports that some initial attempts were clearance in south-west occurred in the more productive made to employ small drones in environmental research in forest ecosystems. Reference [2] revealed the remaining the 1990s and early 2000s, researchers have begun serious status of the tropical rainforest in Nigeria at only 10% of investigation on the use of drones over the last seven to tropical rainforest area as against 25% tropical rainforest eight years. The development of environmental remote sensing technologies and aerial drone has been closely Published on June 17, 2019. related to the study of forests [10]. Although, the bulk of I. A. Gbiri is with Geographic Information Systems (GIS) Department Federal School of Surveying, P. M. B. 1024, Oyo State, Nigeria (e-mail: academic research into the use of miniaturized drones has [email protected]). been greatly geared toward precision agriculture [21] and I. A. Idoko is with Survey and Geoinformatics Department Federal [18]. School of Surveying, P. M. B. 1024, Oyo State, Nigeria (e-mail: [email protected]). M. O. Okegbola is with Survey and Geoinformatics Department Federal School of Surveying, P. M. B. 1024, Oyo State, Nigeria (e-mail: II. GEOGRAPHIC LOCATION OF THE STUDY [email protected]). o o L.O. Oyelakin is with Survey and Geoinformatics Department Federal It lies between latitudes7 16`and 7 18` N of the Equator School of Surveying, P. M. B. 1024, Oyo State, Nigeria (e-mail: and longitudes 5o 9`and 5o11`E of the Greenwich Meridian. [email protected]). DOI: http://dx.doi.org/10.24018/ejers.2019.4.6.1340 57 EJERS, European Journal of Engineering Research and Science Vol. 4, No. 6, June 2019 Akure forest reserve is geographically located in rainforest Radar Topography Mission (SRTM) 30 m spatial zone of Akure South Local government area of Ondo State, resolution(2017) and Landsat 2017 OLI. Nigeria. It was constituted as a reserve in 1936 and covered A. Data Processing 69.93 km2 but 2.463 km2 was selected for the study. The relief pattern is low lying, elevation ranges from 216 to This process involves restructuring the available data and 504(m) and gently undulating in southern part while the creating sequence order of proceeding or cartographic model northern part is hilly rock outcrops occurring at close required for data analyses. Basically, raster and vector intervals. The underlying rock is crystalline and gneiss. It is models are usually involved and they were employed. slightly neutral; pH of 6.7–7.3 and sandy-loam in nature. B. Primary data The dry season lasts from November to March while the wet X, Y locational coordinates of prominent settlements in season commences from April and ends in October with the the Akure Forest Reserve (AFR) were captured as points highest rainfall records between July and August [3] 0 0 with the Garmin eTrex20 GPS device. The dilution of Average daily temperature ranges between 21 C and 29 C precision (DoP), geometric dilution of precision (GDoP) and almost throughout the year [1]. The mean annual rainfall datum was set to zone 31 North Hemisphere 1984. After the varies from 2000m in southern area to –1500m in northern setting, the GPS was allowed to resolve and connect to at area with relative humidity of 80–85% annually experienced least minimum of four satellites before the data capture for in south-west [15]. Politically, it lies in Ondo State in the settlements. We gridded the Topographical map and Southwestern Nigeria and shares border with Osun State in coordinates were obtained from the edges of the map and the Northeast, being surrounded by five Local Government coordinates were pre-loaded into Quadcopter drone through Areas in Ondo State namely: Ile Oluji ,Oke-Igbo, Ifedore, the designed path i.e. traverse from the origin to destination. Akure south, Idanre and Ondo East. Aponmu and Owena 300 m altitude was chosen to fly due to trees obstructions Yoruba speaking communities owned the forest, though, it for the drone when it moves around, the drone speed was set also had minor settlements surrounded the forest included at 3m/s, and 16.1 mega pixels integrated camera was Ipogun, Kajola/ Aponmu, Kajola, Ago Petesi, Akika Camp, onboard for the field of view (FOV) of 28.940 look angles. Owena Town, Ibutitan/Ilaro Camp, Elemo Igbara Oke Camp Images were captured in panchromatic mode of (RGB) with and Owena Water New Dam. shutter capture speed at 1/1000s. It covered 2.463 km2 / 246.284 ha / 608.897 acres Also UAVs imageries was processed through the drone2map software by the conversion of flight lines and points into points, clouds, Poisson surface reconstruction, Ortho generate Digital Surface Model, and orthomosaic of 2-dimension (2D) and 3-dimension (3D). Then after the stacking of the image, it was imported into ArcGIS environment through add data tool on the ArcGIS interface. C. Secondary Data The Digital Image Processing (DIP) Techniques is necessitated by having imageries in digital format. Landsat 8 Fig. 1: Map of the study area OLI-TIRS (2017) were sourced through Path 190/Row 055 (Source: Author, 2019 Map of Study area) and downloaded from GLCF/USGS in digital format into the computer via earth explorer window and then it was imported into ERDAS Imagine 9.2 version through classic III. MATERIALS AND METHODS viewer. Landsat 8, 2017 OLI-TIRS alone was sourced for Methodology employs various techniques and approaches the sensor that acquired image on the 23rd of March 2017 to integrate this study. Such techniques and approaches downloaded because it was exactly the times that drone focus on data acquisition, data processing and data image was acquired. The images noise was filtered through presentation. It commences with database design, radiometric enhancement. The ground truthing, visual image conceptual, logical and schema.