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Article

Comparative Assessment of UAV and Sentinel-2 NDVI and GNDVI for Preliminary Diagnosis of Habitat Conditions in Burunge Wildlife Management Area, Tanzania

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School of Life Sciences and Bio-Engineering (LISBE), Nelson Mandela African Institution of Science and Technology, Arusha P.O. Box 447, Tanzania
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College of Forestry, Wildlife and Tourism (CFWT), Sokoine University of Agriculture (SUA), Morogoro P.O. Box 3009, Tanzania
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Aridlands, LLC, Grand Junction, CO 81507, USA
4
Tanzania Wildlife Research Institute (TAWIRI), Arusha P.O. Box 661, Tanzania
*
Author to whom correspondence should be addressed.
Academic Editors: Gianluca Groppelli and Tien Yin Chou
Earth 2022, 3(3), 769-787; https://doi.org/10.3390/earth3030044
Received: 7 May 2022 / Revised: 9 June 2022 / Accepted: 12 June 2022 / Published: 28 June 2022
(This article belongs to the Special Issue Applications of Remote Sensing for Resources Conservation)
Habitat condition is a vital ecological attribute in wildlife conservation and management in protected areas, including the Burunge wildlife management areas in Tanzania. Traditional techniques, including satellite remote sensing and ground-based techniques used to assess habitat condition, have limitations in terms of costs and low resolution of satellite platforms. The Normalized Difference Vegetation Index (NDVI) and Green NDVI (GNDVI) have potential for assessing habitat condition, e.g., forage quantity and quality, vegetation cover and degradation, soil erosion and salinization, fire, and pollution of vegetation cover. We, therefore, examined how the recently emerged Unmanned Aerial Vehicle (UAV) platform and the traditional Sentinel-2 differs in indications of habitat condition using NDVI and GNDVI. We assigned 13 survey plots to random locations in the major land cover types: three survey plots in grasslands, shrublands, and woodlands, and two in riverine and mosaics cover types. We used a UAV-mounted, multi-spectral sensor and obtained Sentinel-2 imagery between February and March 2020. We categorized NDVI and GNDVI values into habitat condition classes (very good, good, poor, and very poor). We analyzed data using descriptive statistics and linear regression model in R-software. The results revealed higher sensitivity and ability of UAV to provide the necessary preliminary diagnostic indications of habitat condition. The UAV-based NDVI and GNDVI maps showed more details of all classes of habitat conditions than the Sentinel-2 maps. The linear regressions results showed strong positive correlations between the two platforms (p < 0.001). The differences were attributed primarily to spatial resolution and minor atmospheric effects. We recommend further studies to test other vegetation indices. View Full-Text
Keywords: remote sensing; Unmanned Aerial Vehicle; vegetation indices; wildlife habitats; satellite platforms; ecological monitoring remote sensing; Unmanned Aerial Vehicle; vegetation indices; wildlife habitats; satellite platforms; ecological monitoring
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MDPI and ACS Style

Mangewa, L.J.; Ndakidemi, P.A.; Alward, R.D.; Kija, H.K.; Bukombe, J.K.; Nasolwa, E.R.; Munishi, L.K. Comparative Assessment of UAV and Sentinel-2 NDVI and GNDVI for Preliminary Diagnosis of Habitat Conditions in Burunge Wildlife Management Area, Tanzania. Earth 2022, 3, 769-787. https://doi.org/10.3390/earth3030044

AMA Style

Mangewa LJ, Ndakidemi PA, Alward RD, Kija HK, Bukombe JK, Nasolwa ER, Munishi LK. Comparative Assessment of UAV and Sentinel-2 NDVI and GNDVI for Preliminary Diagnosis of Habitat Conditions in Burunge Wildlife Management Area, Tanzania. Earth. 2022; 3(3):769-787. https://doi.org/10.3390/earth3030044

Chicago/Turabian Style

Mangewa, Lazaro J., Patrick A. Ndakidemi, Richard D. Alward, Hamza K. Kija, John K. Bukombe, Emmanuel R. Nasolwa, and Linus K. Munishi. 2022. "Comparative Assessment of UAV and Sentinel-2 NDVI and GNDVI for Preliminary Diagnosis of Habitat Conditions in Burunge Wildlife Management Area, Tanzania" Earth 3, no. 3: 769-787. https://doi.org/10.3390/earth3030044

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