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

Simple item page
dc.contributor.authorOmar, D.
dc.contributor.authorIdrees, M
dc.contributor.authorAhmadu, H.
dc.contributor.authorYusuf, A
dc.contributor.authorIpadeola, O.
dc.contributor.authorBabalola, A
dc.contributor.authorAbdulyekeen, A.
dc.date.accessioned2023-01-04T11:30:31Z
dc.date.available2023-01-04T11:30:31Z
dc.date.issued2022-04
dc.description.abstractThis 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%).en_US
dc.identifier.citationOmar 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), 85-94en_US
dc.identifier.issn1119-7455
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/8104
dc.language.isoen_USen_US
dc.publisherFaculty of Agriculture, University of Nigeria, Nsukaen_US
dc.relation.ispartofseriesVolume 21;No. 2
dc.subjectNDVI, tropical savannah, vegetation dynamics, sentinel-2, desertification, Kwaraen_US
dc.titleASSESSMENT OF VEGETATION DYNAMICS AND FOREST LOSS USING GOOGLE EARTH ENGINE AND MULTI-TEMPORAL SENTINEL-2 IMAGERYen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
227211-Article Text-553387-1-10-20220622_2.pdf
Size:
408.45 KB
Format:
Adobe Portable Document Format
Description:
main article
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections