Performance Evaluation of Lora 920 Mhz Frequency Band in a Hilly Forested Area

electronics

Article Performance Evaluation of LoRa 920 MHz Frequency Band in a Hilly Forested Area

Bilguunmaa Myagmardulam 1,*, Ryu Miura 2, Fumie Ono 3, Toshinori Kagawa 4, Lin Shan 2, Tadachika Nakayama 1, Fumihide Kojima 2 and Baasandash Choijil 5

1 Extreme Energy-Density Research Institute, Nagaoka University of Technology, 1603-1 Kamitomioka, Nagaoka, Niigata 940-2188, Japan; [email protected] 2 Wireless Network Research Center, Wireless Systems Laboratory, National Institute of Information and Communications Technology, Yokosuka-shi, Kanagawa 239-0847, Japan; [email protected] (R.M.); [email protected] (L.S.); [email protected] (F.K.) 3 Global Strategy Bureau, Ministry of International Affairs and Communication, 1-2 Kasumigaseki 2-chome, Chiyoda-ku, Tokyo 100-8926, Japan; [email protected] 4 Central Research Institute of Electronic Power Industry, 2-11-1, Iwato-Kita, Komae-shi, Tokyo 201, Japan; [email protected] 5 Graduate School of Business, Mongolian University of Science and Technology, Sukhbaatar District, Ulaanbaatar 14191, Mongolia; [email protected] * Correspondence: [email protected]; Tel.: +81-0258-46-6000

Abstract: Long-range (LoRa) wireless communication technology has been widely used in many Internet-of-Things (IoT) applications in industry and academia. Radio wave propagation characteristics in forested areas are important to ensure communication quality in forest IoT applications. In this study, 920 MHz band propagation characteristics in forested areas and tree canopy openness were investigated in the Takakuma experimental forest in Kagoshima, Japan. The aim was to evaluate the Citation: Myagmardulam, B.; Miura, performance of the LoRa 920 MHz band with spreading factor (SF12) in a forested hilly area. The R.; Ono, F.; Kagawa, T.; Shan, L.; Nakayama, T.; Kojima, F.; Choijil, B. received signal strength indicator (RSSI) was measured as a function of the distance between the Performance Evaluation of LoRa transmitter antenna and ground station (GS). To illustrate the effect of canopy openness on radio 920 MHz Frequency Band in a Hilly wave propagation, sky view factor (SVF) and a forest canopy height model were considered at each Forested Area. Electronics 2021, 10, location of a successfully received RSSI. A positive correlation was found between the RSSI and SVF. 502. https://doi.org/10.3390/ It was found that between the GS and transmitter antenna, if the canopy height is above 23 m, the electronics10040502 signal diffracted and RSSI fell to −120 to −127 dBm, so the presence of the obstacle height should be considered. Further research is needed to clarify the detailed tree density between the transmitter Academic Editor: Joao Ferreira and ground station to propose an optimal propagation model for a forested environment.

Received: 24 December 2020 Keywords: LoRa technology; sky view factor; canopy height map Accepted: 11 February 2021 Published: 20 February 2021

Publisher’s Note: MDPI stays neutral 1. Introduction with regard to jurisdictional claims in published maps and institutional affil- Long-range (LoRa) communication technology plays an essential role in many Internet- iations. of-Things (IoT) applications in industry and academia. Currently, approximately 31 billion IoT devices exist, such as home appliances that are connected to the Internet, and approximately 75 billion IoT devices are forecast to be connected to the Internet by 2025 [1]. The main characteristics of the LoRa technology fulfill the IoT requirements for using better wireless communication over long distances, low data rates, and low power consumption Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. for batteries [2]. The LoRa technology operates in the unlicensed industrial, scientific, and This article is an open access article medical (ISM) radio band, which allows for a much faster uptake of technology worldwide. distributed under the terms and The ISM band is different depending on the region; the 920 MHz frequency band is used conditions of the Creative Commons for LoRa applications in Japan [3]. Attribution (CC BY) license (https:// It is essential to understand the accurate LoRa technology performance characteristics creativecommons.org/licenses/by/ in complex environments to develop models and simulations and to plan high-performance 4.0/). communication networks. Mountains, hills, and trees are well known natural obstacles that

Electronics 2021, 10, 502. https://doi.org/10.3390/electronics10040502 https://www.mdpi.com/journal/electronics Electronics 2021, 10, 502 2 of 12

interrupt radio wave propagation across almost the entire frequency range in a complex propagation environment. This is because the irregular structure of leaves, twigs, branches, and tree trunks of the forest environment can cause signal attenuation, scattering and diffraction as well as absorption of the propagated waves [4]. Many simulations and experimental studies have been conducted to evaluate the performance characteristics of forests. The most common evaluation method is the measured received signal strength indicator (RSSI) values compared with the well-known path loss models such as the Weissberger- modified exponential decay model [5], International Telecommunication Union Sector recommendation (ITU-R) model [6], and COST235 model [7]. Studies of LoRa technology performance and coverage evaluation in forested areas have employed various measurements for field testing [8–13]. Lova et al. [8] performed experiments in mountain and urban environments using the European ISM band (868 MHz). It has been reported that the signal decreased because of temperature variation and the existence of hills and vegetation. Khairol et al. [9] carried out experiments using a Malaysian ISM band (433 MHz) in a tropical environment. The results evaluated the RSSI value measurement and comparison of the spreading factor (SF) of 7 and 12 MHz. It was shown that path loss in tropical foliage is unstable owing to the parameter configuration and vegetation. Pablo et al. [10] carried out experiments using an American ISM band (915 MHz) of SF (from 7 to 10 MHz) in a riparian forest. The results were evaluated using the measured RSSI and signal noise ratio (SNR). Based on the RSSI and SNR, a fitting curve was proposed. Mariana et al. [11] conducted a field experiment in a forest and a dense urban environment using a Brazilian ISM band (915 MHz) and a European ISM band (868 MHz) of LoRa SF12. The experimental results were evaluated by measuring the RSSI with distance. In the forest environment, the established communication link reached a distance of 800 m in Portugal and 230 m in Brazil. Ana et al. [12] performed experiments in urban, suburban, and forest environments using a 915 MHz frequency band. The results obtained varied greatly depending on the environment. LoRa SF12 was evaluated based on RSSI, packet delivery ratio (PDR), and SNR in a forest environment. The average RSSI was −100 dBm in the forested area, and the maximum communication range was 250 m. It has been reported that the presence of vegetation affects communication performance and that the experimental communication range is shorter than the theoretical range. Malevich et al. [13] performed measurements in the 10 GHz frequency band with an antenna located in front of, and within, a mixed forest. The receiver’s antenna-height-dependent signal was attenuated. If the receiving antenna was in front of the forest, the signal level increased at some points. The authors noted that the signal level changed because of gaps in the branches and leaves between the transmitter and the receiver antenna. This paper covers the interdisciplinary field of remote sensing and wireless communication. The main motivation of this work is to characterize LoRa SF12 modulation technology features to design a high-performance communication network in a hilly forested area. As a first step, a theoretical propagation characteristic model over distance was compared to real experimental data. In the second step, canopy openness was calculated from 360◦ panoramic image data. To better understand the experimental propagation environment, the image data were captured from the beginning until the end of the experiment. In the third step, the global forest canopy height model 2019 was examined to determine the obstacle height between the transmitter and the receiver. The main contributions of this work are as follows: an experiment into the communication ability of a LoRa SF12 configuration in a hilly forest area is presented. The effect of canopy openness on radio wave propagation is explored. The obstacles (tree height and terrain elevation) are discussed. However, to the best of our knowledge this is the first study to present the effect of canopy openness on LoRa communication technology in a hilly forest environment. Electronics 2021, 10, 502 3 of 12

2. Materials and Methods 2.1. Principle of LoRa Technology The LoRa technology is generally divided into two different layers: the physical layer, which uses the chirp spread spectrum (CSS) and is called the LoRa modulation technique, and the medium access control (MAC) layer, which is called the long-range wide-area network (LoRaWAN) protocol. The LoRa physical layer modulation patent is owned by the Semtech Corporation [14]. For the LoRa modulation, three parameters can be customized depending on the device and purpose: bandwidth (BW), spreading factor (SF), and coder rate (CR). The basic principle of LoRa technology is based on a spread-spectrum modulation techniques that use CSS. A chirp is a signal with a frequency that moves up or down at different speeds. The speed of the chirp is determined by the spreading factor. The chirp rate depends only on the bandwidth: one chirp per second per Hertz of bandwidth. This means that an increase in one of the spreading factors will divide the frequency span of a chirp by two because two SF chirps covering the entire bandwidth will multiply the duration by two [15]. This is why the spreading factor (SF) is an important parameter in CSS modulation. The higher the SF modulation, the wider is the wireless communication range. The SF value ranged from SF7 to SF12. The LoRa wireless communication distance can be extended to more than 30 km [16].

2.2. Theoretical Data The free-space path loss model gives the theoretical data that predicts radio wave propagation path loss in free space without obstructing objects over distance. This model considers only the frequency and propagation distance. It does not consider radio wave propagation effects such as reﬂection, refraction, diffraction, or absorption. Path loss expresses the loss in signal strength as a function of distance. The link budget calculates the signal strength in the receiver, accounting for all gains and losses in a transmission system [17]. Free space path loss model equation:

L (dB) = 20log10 (4πd/λ). (1)

Link budget equation:

Pr (dBm) = Pt + Gr + Gt − L, (2)

where L is the free space path loss in dB, d is the distance between receiver and transmitter antenna in meters; λ is the frequency in MHz; Pr is the received power expressed in dBm; Pt is the transmitter power in dBm; Gr is the receiver antenna gain in dB; and Gt is the transmitter antenna gain in dB.

2.3. Sky View Factor Calculation (SVF) The sky view factor (SVF) is the ratio of visible sky area to a hemisphere centered over a location. SVF is widely used as an important parameter in research fields like geography, geomorphology, cartography, hydrology, glaciology, forestry, and disaster management [18]. It can be used in engineering to calculate urban heat and predict the availability of Global Positioning System (GPS) signals in urban areas. Many methods have been developed to estimate an SVF [19], which ranges between 0 and 1:0 indicates no sky view from a given location and the maximum influence of the surroundings, whereas 1 indicates a clear sky view from a given location and no influence of the surroundings. If the SVF is low, the tree cover can cause a shadowing effect in the radio wave propagation path and RSSI is expected to be weak. The degree to which canopy openness affects LoRa’s communication performance between the transmitter and receiver is yet to be answered. The experimental area of the video image was acquired using a Garmin VIRB-360 video camera, which was mounted on the roof of the transmitter vehicle. The following steps were completed to calculate the Electronics 2021, 10, x FOR PEER REVIEW 4 of 13

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SVF. The captured video images were automatically corrected and extracted using Gar- min VIRBSVF. 5.4.3.0 The capturedvideo editing video software. images were The automaticallyresolution of correctedthe video andimages extracted was 3840 using × Garmin 2160, withVIRB a frame 5.4.3.0 rate video of 30 editing fps. A software.flowchart Theof the resolution SVF calculation of the video is presented images in was Figure 3840 × 2160, 1. The firstwith step a frame is from rate the of 30extracted fps. A flowchart image to ofa the360° SVF field-of-view calculation image is presented generated in Figure by 1. The cylindricalfirst projection. step is from The the next extracted step is image from to the a 360 generated◦ field-of-view 360° field-of-view image generated image by cylindricalto fisheye imageprojection. generation The next by stepequisolid is from angle the generatedprojection. 360 The◦ field-of-view third step is imageto convert to fisheye the image fisheye imagegeneration into a by binary equisolid image. angle The projection. last step Theinvolves third counting step is to convertthe sky thepixels fisheye from image a into binary image.a binary The image. R program The last of stepthe SVF involves calculation counting procedures the sky pixels was developed from a binary by [20] image. The and is Rshown program in of thethe SVF following calculation URL: procedures (https://github.com/honjo7777/theta2svf, was developed by [20] and is shown in the eqdist2eqsolid)following (accessed URL: ( https://github.com/honjo7777/theta2svfon 15 June 2020). , eqdist2eqsolid) (accessed on 15 June 2020).

Figure 1. Flowchart of sky view factor (SVF) calculation.

2.4. Global Forest Canopy Height Map Figure 1. FlowchartNASA’s Global of sky view Ecosystem factor (SVF) Dynamics calculation. Investigation (GEDI) generated the first high- resolution, laser-ranging observations of the 3D structure of the Earth that can reveal precise 2.4. Globalmeasurements Forest Canopy ofHeight the vertical Map forest canopy height, surface elevation, major carbon and NASA’swater Global cycling Ecosystem processes, Dy biodiversity,namics Investigation and habitat (GEDI) [21]. GEDI generated was launched the first tohigh- the interna- resolution,tional laser-ranging space station observations (ISS) on December of the 3D 5, structure 2018, and of vegetation the Earth structurethat can reveal data collection pre- has cise measurementsbeen conducted of the since vertical April forest 2019. Thecanopy GEDI height, instrument surface consists elevation, of three major light carbon detection and and waterranging cycling (LIDAR) processes, laser biodiversity, systems that and produce habitat eight [21]. parallel GEDI trackswas launched of observations. to the in- Each laser ternationalfires space 242 timesstation per (ISS) second on December and illuminates 5, 2018, a and 25 m vegetation spot (a footprint) structure on data the surface,collec- which tion has includesbeen conducted the measurement since April of the 2019. 3D Th structuree GEDI on instrument the Earth. Theconsists global of forest three canopy light height detectionmap and 2019 ranging was (LIDAR) developed laser by systems integrating that the produce LIDAR eight forest-structure parallel tracks measurements of obser- with vations. theEach Landsat laser fires analysis-ready 242 times per data second time and series illuminates [21]. The a global 25 m spot forest (a canopyfootprint) height on model the surface,2019 which with 30includes m resolution the measurement was downloaded of the 3D from structure https://glad.umd.edu/dataset/gedi on the Earth. The global . It forest canopyis important height tomap illustrate 2019 was the developed path loss for by the integrating height of the the LIDAR canopy forest-structure between the GS and the measurementstransmitter with car.the Landsat analysis-ready data time series [21]. The global forest canopy height model 2019 with 30 m resolution was downloaded from 2.5. Experimental Setup https://glad.umd.edu/dataset/gedi. It is important to illustrate the path loss for the height of the canopyThe between field experimentthe GS and the was transmitter conducted car. in February 2020 at Takakuma Experimental Forest (31.5◦ N, 130.7◦ E) of Kagoshima University, Tarumizu City, Kagoshima Prefecture.

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Electronics 2021, 10, 502 5 of 12 2.5. Experimental Setup The field experiment was conducted in February 2020 at Takakuma Experimental TheForest details (31.5° of N, the 130.7° measurement E) of Kagoshima setup Univ are shownersity, inTarumizu Figure2 .City, A map Kagoshima of Japan Prefecture. is shown inThe Figure details2a, of where the measurement the dark-blue setup colored are areashown is Kagoshimain Figure 2.prefecture; A map of Japan in Figure is shown2b, the in expansionFigure 2a, where of the dark-bluethe dark-blue area colored is the Takakuma area is Kagoshima experimental prefecture; forest area,in Figure and the2b, redthe squareexpansion is the of locationthe dark-blue of the experimentalarea is the Taka areakuma in this experimental study. The experimentforest area, wasand carriedthe red outsquare by installingis the location a ground of the station experimental (GS) antenna area in to this the study. summit The of experiment Mt. Takatouge was (722carried m high),out by asinstalling shown ina ground Figure2 stationc. The (GS) height an oftenna the to GS the is approximatelysummit of Mt. 2.5Takatouge m. Figure (7222d m showshigh), as a transmittershown in Figure antenna 2c. The mounted height toof the roofGS is of approximately a vehicle approximately 2.5 m. Figure 2 2d m aboveshows ground.a transmitter The measurementsantenna mounted were to performedthe roof of a in vehicle good weather approximately conditions. 2 m above Table1 ground. shows theThe experimentalmeasurements parameter were performed conﬁguration. in good weather conditions. Table 1 shows the experimental parameter configuration.

(a) (b)

FigureFigure 2.2. Experimental setup: setup: (a (a) )Map Map of of Japan; Japan; (b ()b Experimental) Experimental area; area; (c) ( cGround) Ground station station located located at Mt. at Mt. Takatouge; Takatouge; (d) (Transmittingd) Transmitting station station mounted mounted on onthe the roof roof of ofvehicle. vehicle.

Table 1. Experimental conﬁguration parameters.

Description Value Receiver (Rx) height 2.5 m Transmitter (Tx) power +20 mW Antenna Gain (dB) 0 Spreading Factor (sf) 12

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Table 1. Experimental configuration parameters.

Description Value Receiver (Rx) height 2.5 m Transmitter (Tx) power +20 mW Antenna Gain (dB) 0 Spreading Factor (sf) 12 Electronics 2021, 10, 502 6 of 12 3. Results 3.1. Propagation Measurement of 920 MHz Band 3. ResultsIn our experiment, we collected data from the ground station every time the trans- mitter3.1. Propagation car sent data. Measurement The RSSI of was 920 MHzmeasur Banded. The propagation environment was sur- roundedIn ourby experiment,a mixed forest we collectedwith hilly data areas. from RSSI the groundcommunication station every was timesuccessfully the transmit- re- ceivedter car up sent to data.a distance The RSSI of 3.2 was km. measured. For a distance The propagation greater than environment 3.2 km from was the surroundedGS, where theby direct a mixed signal forest path with was hilly obstructed areas. RSSI by communicationthe mountain, there was was successfully no signal received received. up The to a experimentaldistance of 3.2 communication km. For a distance map greateris shown than in Figure 3.2 km 3. from The the plots GS, indicate where thethe directmovement signal trajectoriespath was obstructedof the transmitter by the car. mountain, The successf thereul was RSSI no values signal indicated received. by The the experimentalcolored dots andcommunication the red triangle map is isthe shown location in Figure of the3 GS. The and plots received indicate RSSI the ranging movement between trajectories −24 and of −the128 transmitterdBm at the GS, car. as The shown successful in Figure RSSI 3. values Communication indicated byloss the occurred colored from dots 1.8 and to the 2 km red becausetriangle the is thetransmitter location ofcar the was GS running and received behind RSSI the ranging hilly mountain, between which−24 and has− a128 height dBm of at 532the m. GS, as shown in Figure3. Communication loss occurred from 1.8 to 2 km because the transmitter car was running behind the hilly mountain, which has a height of 532 m.

Figure 3. Experimental measured data on a map. Figure 3. Experimental measured data on a map. The measurement attenuation characteristics at 920 MHz are shown in Figure4. The solidThe black measurement line in the ﬁgureattenuation shows characteristics the theoretical at value 920 MHz of the are free-space shown in path Figure loss 4. model, The solidand black the red line dots in the show figure the shows measured the theoreti valuescal of thevalue received of the free-space power. From path Figure loss model,4, the andresults the showred dots that show the measured the measured path loss values is higher of the than received the theoretical power. From path loss.Figure The 4, RSSIthe resultsvalue changesshow that over the the measured distance path between loss is the higher receiver than and the transmitter theoretical andpath the loss. surrounding The RSSI valueenvironment. changes over For the example, distance the between RSSI received the receiver from and−90 transmitter to −120 dBm and from the surrounding a distance of environment.500 m to 1 km. For This example, is because the RSSI of the received terrain from effect, −90 vegetation to −120 dBm scattering, from a distance diffraction, of 500 and mabsorption to 1 km. ofThis radiation. is because At aof distance the terrain of 500 effect, m to vegetation 1 km, the transmitter scattering, cardiffraction, ran through and a forested mountainside area of Mt. Takatouge.

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Electronics 2021, 10, 502 7 of 12 absorption of radiation. At a distance of 500 m to 1 km, the transmitter car ran through a forested mountainside area of Mt. Takatouge.

Figure 4. Propagation characteristics of 920 MHz band in distance: Experimental and theoretical Figuredata versus4. Propagation distance. characteristics of 920 MHz band in distance: Experimental and theoretical data versus distance. As predicted, the experimental and theoretical values do not perfectly match because of theAs predicted, environmental the experimental radio wave and propagation theoretical effect. values Figure do not5a perfectly shows the match difference because in ofsignal the environmental power between radio the wave experimental propagation data effect. and theoretical Figure 5a datashows as the indicated difference by RSSI. in signalThe differencepower between between the theexperimental theoretical data and experimentaland theoretical data data was as approximatelyindicated by RSSI. 10 to The52 difference dB at distances between of up the to theoretical 1 km, 9 to and 40 dB expe at 2rimental km and data 11 to was 42 dBapproximately at 3 km. Theoretically, 10 to 52 dBsignal at distances strength of decreases up to 1 km, exponentially 9 to 40 dB at with 2 km distance, and 11 butto 42 in dB the at experimental 3 km. Theoretically, results in signalFigure strength5a, the decreases distance of exponentially 1 km revealed with more distance, signal attenuationbut in the experimental occurred than results at 2 km.in FigureWe assume 5a, the thatdistance from of 2 to1 km 3.2 revealed km there more is a high signal possibility attenuation of distance-dependentoccurred than at 2 km. path Weloss assume and the that existence from 2 ofto the3.2 hillykm there area is and a high canopy. possibility The difference of distance-dependent plotted map is shownpath lossin and Figure the5 b.existence The largest of the difference hilly area between and canopy. the experimental The difference and plotted theoretical map valuesis shown at a indistance Figure 5b. of upThe to largest 1, 2, and difference 3 km were between 52, 40, th ande experimental 42 dB, respectively. and theoretical For data transmissionvalues at a distancedistances of up of to up 1, to 2, 1and km, 3 akm higher were signal52, 40, attenuationand 42 dB, respectively. occurred than For at data 2 km. transmission Until 1 km, distancesthere was of largeup to signal 1 km, attenuationa higher signal because attenuation of the terrain occurred effect than and at the 2 km. canopy. Until By 1 visualkm, thereinspection was large of thesignal comparison attenuation among because the differentof the terrain values, effect there and was the more canopy. signal By decrease visual inspectionin the nearby of the tall comparison deciduous among trees andthe diff behinderent the values, hilly there areas. was This more can signal be explained decrease by inconsidering the nearby thetall environmentaldeciduous trees conditions and behind of the the scenario. hilly areas. To investigate This can be the explained reason for by the consideringlarge attenuation the environmental values of the conditions measurement of the data, scenario. the SVF To investigate and forest canopythe reason height for the map are examined in the next section.

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Electronics 2021, 10, 502 8 of 12 large attenuation values of the measurement data, the SVF and forest canopy height map are examined in the next section.

(a) (b)

FigureFigure 5. 5.ComparisonComparison between between measurement measurement data data and and theoretical data: ((aa)) differencedifference betweenbetween distance distance up up to to 1, 1, 2, 2, and and 3 km;3 km;(b )(b Difference) Difference of receivedof received signal signal strength strength on on the the map. map.

3.2.3.2. Correlation Correlation analysis Analysis between between Sky Sky View View Factor Factor Calculation Calculation (SVF) (SVF) and and RSSI RSSI ToTo understand understand the the effect effect of of tree tree canopy canopy openness openness on on radio radio wave wave propagation, propagation, this this studystudy analyzed analyzed the the correlation correlation between between each each RS RSSISI and and the the corresponding corresponding SVF SVF distance distance up up toto 800 800 m. m. For For correlation correlation analysis, analysis, distances distances of up toto 800800 mm sitessites were were selected selected based based on on the thefollowing following criteria: criteria: 1. 1. AA higher higher signal signal attenuation attenuation was was observed observed compared compared to to the the theoretical theoretical value. value. 2. 2. AA large large number number of of data data was was received. received. 3. 3. TheThe transmitter transmitter car car was was moving moving through through mountainside. mountainside. FigureFigure 6 6shows shows that that up up to todistances distances of of800 800 m, m,the the RSSI RSSI had had a significant a signiﬁcant correlation correlation to theto SVF the with SVF a with coefficient a coefﬁcient R2 = 0.6. R2 For= 0.6. distances For distances up to 800 up m tothe 800 theoretical m the theoretical value was value−77 dBmwas and−77 the dBm experimental and the experimental value was − value99 to − was120 dBm.−99 to The−120 received dBm. signal The received near the signal de- ciduousnear the trees deciduous had a lower trees SVF. had aThis lower is be SVF.cause This the is deciduous because the trees deciduous were irregularly trees were shapedirregularly and broad-leaved. shaped and broad-leaved. However, at a However, distance up at ato distance 800 m, the up RSSI to 800 and m, SVF the RSSIshow and a positiveSVF show correlation a positive and, correlation in the case and, of over in theall experimental case of overall data, experimental it was not data,dependent it was on not thedependent SVF. This onis because the SVF. trees This grow is because randomly trees and grow are randomlydifferent from and each are different other. Therefore, from each weother. selected Therefore, a sample we point selected to examine a sample the point forest to canopy examine height the forestin the canopyradio wave height propa- in the radio wave propagation path between the GS and the transmitter at a distance up to 800 m. gation path between the GS and the transmitter at a distance up to 800 m. 3.3. Forest Canopy Height Map The forest canopy height map and received RSSI results at the GS are plotted in Figure7 . The forest canopy height ranged from 4.2 to 30 m in this experimental area. Color denotes the height of the canopy. The light-green and dark-green colors indicate low and high canopy heights, respectively. The forest canopy height map spatial resolution was 30 m and covered an area of approximately 1 km2.

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Figure 6. Correlation analysis between received signal strength indicator (RSSI) and Sky View Factor (SVF).

3.3. Forest Canopy Height Map The forest canopy height map and received RSSI results at the GS are plotted in Fig-

ure 7. The forest canopy height ranged from 4.2 to 30 m in this experimental area. Color FiguredenotesFigure 6. Correlation 6.theCorrelation height analysis of the analysis between canopy. between received The light-gr receivedsignal strengtheen signal and indicator strengthdark-green indicator(RSSI) colors and (RSSI) Skyindicate View and low Sky and View FactorhighFactor (SVF). canopy (SVF). heights, respectively. The forest canopy height map spatial resolution was 30 m and covered an area of approximately 1 km2. 3.3. Forest Canopy Height Map The forest canopy height map and received RSSI results at the GS are plotted in Fig- ure 7. The forest canopy height ranged from 4.2 to 30 m in this experimental area. Color denotes the height of the canopy. The light-green and dark-green colors indicate low and high canopy heights, respectively. The forest canopy height map spatial resolution was 30 m and covered an area of approximately 1 km2.

Figure 7. Forest Canopy height map. Figure 7. Forest Canopy height map. To distinguish tree height, the canopy height map color is re-classiﬁed in Figure8a. As shown in Figure8, a selected sampling point is used to examine the tree height effect between the GS and the transmitter. Among the sampling points, the weakest signal was RSSI = −122. From the GS location to the weakest signal’s location, the topographic proﬁle

white arrow is examined in Figure8a. In Figure8b, the yellow line represents the terrain Figureproﬁle, 7. Forest and Canopy the greenheight linemap. is the canopy height model proﬁle from GS to the sampling point location. In the case of the weakest signal location, as shown in Figure8 , detailed

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Electronics 2021, 10, 502 To distinguish tree height, the canopy height map color is re-classified in Figure 8a. 10 of 12 As shown in Figure 8, a selected sampling point is used to examine the tree height effect between the GS and the transmitter. Among the sampling points, the weakest signal was RSSI = −122. From the GS location to the weakest signal’s location, the topographic proﬁle ◦ informationwhite arrow is theis examined following: in Figure elevation 8a. In Figu = 555re 8b, m; the elevation yellow line angle represents = 11 the; andterrainSVF = 0.36 (Figureprofile,9c). and However, the green atline this is the sampling canopy height point, model the canopyprofile from openness GS to the value sampling SVF = 0.36, whichpoint was location. the weakest In the case among of the the weakest sampling signal points. location, The as sceneshown ofin theFigure tree 8, canopydetailed coverage situationinformation photo is taken the following: by Garmin elevation is shown = 555 m; in elevation Figure9 .angle The sampling𝜃 = 11°; and point SVF = proﬁle0.36 from the GS(Figure to the 9c). transmitterHowever, at this car sampling location point, is shown the canopy inFigure openness8b. value The SVF canopy = 0.36, heightwhich at this was the weakest among the sampling points. The scene of the tree canopy coverage situ- − site rangedation photo from taken 9 to by 25 Garmin m. The is shown RSSI decreasedin Figure 9. toThe sampling122. The point large profile attenuation from the values at this siteGS to were the transmitter because of car the location canopy is shown height in between Figure 8b. the The GS canopy and the height transmitter at this site car. From Figureranged8, the from weakest 9 to 25 RSSIm. The = RSSI−121 decreased and −122 to − were122. The both large received attenuation near values a canopy at this height of 25 msite (pink were colored). because of Signal the canopy attenuation height betw occurredeen the GS near andtaller, the transmitter thicker coniferouscar. From Fig- trees than nearure deciduous 8, the weakest trees. RSSI If the= −121 radio and wave−122 were propagation both received path near canopy a canopy height height is of between 25 m 23 to 25 m,(pink there colored). is a higher Signal possibilityattenuation occurred of signal near diffraction taller, thicker at theconiferous top of trees the treethan andnear the RSSI deciduous trees. If the radio wave propagation path canopy height is between 23 to 25 m, decreases from −120 to −127. The signal attenuation tended to increase with tree height there is a higher possibility of signal diffraction at the top of the tree and the RSSI de- up tocreases 23–25 from m. The−120 attenuationto −127. The signal near attenuation trees is believed tended to to increase decrease with as tree the height height up increases becauseto 23–25 of the m. The shadowing attenuation effect nearof trees the is trees. believed to decrease as the height increases because of the shadowing effect of the trees.

(a) (b) ElectronicsFigure 8.2021 Sampling, 10, x FOR sites; PEER ( aREVIEW) sampling points, (b) sample of profile between ground station (GS) to transmitter. 11 of 13 Figure 8. Sampling sites; (a) sampling points, (b) sample of proﬁle between ground station (GS) to transmitter.

(b)

(a) (c)

Figure 9. LocationFigure of the9. Location weakest of the signal weakest received signal received sampling sampling point point (a) ( Samplea) Sample of of 11 grid cell cell of oftree tree height height map; map;(b) Image (b) Image taken by Garmin; (c) Generated fisheye image. taken by Garmin; (c) Generated ﬁsheye image. 4. Discussion In this study, the LoRa 920 MHz frequency band performance was evaluated in a forest environment. Evaluations based on the measured RSSI, canopy openness and tree height were examined. The discussion of the obtained results are as follows: First, the successfully reached communication range is much longer than the cited studies that followed a standard device-to-gateway communication model in a forest environment. However, measurements in the forest had an extremely short range compared to theory. The maximum communication range was 3.2 km for SF12. The quality of a signal greatly depended on the environment. For instance, at distances of up to 1 km the communication quality was greatly reduced. For a distance range within 2 km, the signal appeared to be more stable than at a distance of 1 km. This was because for distances greater than 1 km, the transmitter car was moving out of the forest area. The variations in the RSSI in the signal attenuation were because of the existence of hills and different canopy heights. Sec- ond, this is the first study to examine the effect of canopy openness on LoRa signal transmission in the context of operational LoRa performance. Signal attenuation occurred near deciduous trees compared to coniferous trees with lower SVF values. Because deciduous trees have more discrete surfaces, the signal can scatter on branches and leaves. Third, when designing communication links, we should consider the obstacles between the transmitter and the receiver. With these results, there is a higher possibility that signals will be decreased or blocked by obstacles such as trees and hills if they are of a height of 23 m or 532 m, respectively.

Electronics 2021, 10, 502 11 of 12

4. Discussion In this study, the LoRa 920 MHz frequency band performance was evaluated in a forest environment. Evaluations based on the measured RSSI, canopy openness and tree height were examined. The discussion of the obtained results are as follows: First, the successfully reached communication range is much longer than the cited studies that followed a standard device-to-gateway communication model in a forest environment. However, measurements in the forest had an extremely short range compared to theory. The maximum communication range was 3.2 km for SF12. The quality of a signal greatly depended on the environment. For instance, at distances of up to 1 km the communication quality was greatly reduced. For a distance range within 2 km, the signal appeared to be more stable than at a distance of 1 km. This was because for distances greater than 1 km, the transmitter car was moving out of the forest area. The variations in the RSSI in the signal attenuation were because of the existence of hills and different canopy heights. Second, this is the ﬁrst study to examine the effect of canopy openness on LoRa signal transmission in the context of operational LoRa performance. Signal attenuation occurred near deciduous trees compared to coniferous trees with lower SVF values. Because deciduous trees have more discrete surfaces, the signal can scatter on branches and leaves. Third, when designing communication links, we should consider the obstacles between the transmitter and the receiver. With these results, there is a higher possibility that signals will be decreased or blocked by obstacles such as trees and hills if they are of a height of 23 m or 532 m, respectively.

5. Conclusions In the present study, 920 MHz band propagation characteristics in forested areas and tree canopy coverage and heights were investigated for the Takakuma experimental forest in Kagoshima. The aim was to evaluate the performance of the LoRa 920 MHz band (SF 12) in a forested environment. Canopy openness affects the signal quality but does not block the signal completely. According to the results, it can be concluded that the LoRa signal quality greatly depends on the environment and obstacle height, such as the hill and trees between the transmitter and receiver, which are more important than canopy- openness. The results were obtained from real experiments, and we expect that our results could provide information for developing a real IoT application using LoRa technology in a hilly forested environment. Further research is required to clarify the detailed tree density between the transmitter and receiver paths, and based on the results an optimal propagation model for the forested environment is proposed.

Author Contributions: Conceptualization, B.M.; methodology, B.M., R.M. and F.O.; software, B.M.; validation, B.M., T.N., R.M. and F.O.; formal analysis, B.M.; investigation, B.M., R.M., and F.O.; data cu- ration, R.M., F.O., T.K., L.S., F.K., and B.C.; writing—original draft preparation, B.M.; writing—review and editing, B.M., T.N.; supervision, R.M., and T.N.; project administration, R.M., T.N and B.C.; funding acquisition, T.N. All authors have read and agreed to the published version of the manuscript. Funding: This research was supported by SCOPE project, Ministry of Internal Affairs and Communi- cations of Japan and the APC was funded by Tadachika Nakayama. Acknowledgments: This paper is based on results obtained from a project commissioned by the Forest-ICT project of Kagoshima University and the Japanese National Institute of Information and Communications Technology (NICT). This experiment was conducted in cooperation with NICT. We would like to acknowledge the part of the project “Research and development of highly reliable wireless transmission technology that contributes to the utilization of next-generation UAVs” the SCOPE project, the Aerospace and Environmental Engineering Education Sky-infra in Mongolia project, and the Mongolian-Japanese Engineering Education Development Project (MJEED). In addition, we would like to thank our colleagues at the lab Wiff Verdugo Juan Paulo for the discussion and consultations. Conﬂicts of Interest: The authors declare no conﬂict of interest. Electronics 2021, 10, 502 12 of 12

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