Assessment of vegetation dynamics and forest loss using google earth engine and multi-temporal sentinel-2 imagery

  • Omar D
  • Idrees M
  • Ahmadu H
  • et al.
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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 non-vegetated 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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APA

Omar, D., Idrees, M., Ahmadu, H., Yusuf, A., Ipadeola, O., Babalola, A., & 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. https://doi.org/10.4314/as.v21i2.10

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