ASSESSMENT OF VEGETATION DYNAMICS AND FOREST LOSS USING GOOGLE EARTH ENGINE AND MULTI-TEMPORAL SENTINEL-2 IMAGERY

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Date

2022-04

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Publisher

Faculty of Agriculture, University of Nigeria, Nsuka

Abstract

This study evaluated regional vegetation dynamics and changes between 2015 and 2020 using Google earth engine (GEE) platform and normalized difference vegetation index (NDVI) derived from the multi-petabyte catalogue of sentinel-2 imageries. Using the computational capability of GEE, yearly mean NDVI from 2015 to 2020 were computed using level C-1 product. Subsequently, each of the NDVI images was classified into four land cover classes; water bodies, non-vegetated, grassland/cropland/shrubs, and forest using NDVI threshold values of < 0.01, 0.01-0.20, 0.20-0.30 and > 0.30, respectively. The classified maps allowed for the assessment of yearly variation in vegetation and changes between 2015 and 2020. Result showed that nonvegetated area increased from 18.53% in 2015 to 42.56% in 2020 (~ 25.00% gain), the forest area reduced to 6.78% in 2020 compared to 23.76% measured in 2015 (~ 17.00% loss in forest); whereas water bodies and grassland/cropland/shrubs remained relatively constant (0.21 and ~ 50.00%, respectively) across the years studied. Presently, the forest land was estimated to be about 2, 371.131 km2 (~ 6.70%) of the total land mass, grassland/cropland/shrubs occupied 17, 770.79 km2 (~ 50.07%), non-vegetated area was slightly less than half with 15, 274.85 km2 (~ 43.04%) and water bodies occupied 75.68 km2 (~ 0.21%).

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Keywords

NDVI, tropical savannah, vegetation dynamics, sentinel-2, desertification, Kwara

Citation

Omar D., Idrees M., Ahmadu H., Yusuf A., Ipadeola O., Babalola A. and Abdulyekeen A. (2022). Assessment of vegetation dynamics and forest loss using Google earth engine and multi-temporal sentinel-2 imagery. Agro-Science, 21 (2), 85-94

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