Time-series Analysis of Vegetation Cover in the Southwest Nigeria using Remote Sensing and GIS

Thomas U. Omali¹

Section:Research Paper, Product Type: Journal-Paper
Vol.8 , Issue.7 , pp.36-42, Jul-2022

Online published on Jul 31, 2022

Copyright © Thomas U. Omali . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Dependable mapping and assessment of vegetation cover are essential for planning a sustainable ecosystem in the face of current global change. Satellite-based analysis of vegetation cover is an effective alternative to the costly ground-based surveys. Thus, this study is focused on monitoring the long–term modification in the vegetation cover of Southwest Nigeria from 2000 to 2020 using Time-series MODIS–NDVI datasets. The major plus for using MODIS–NDVI is its sufficient spatial, spectral, and temporal resolutions to identify distinct multi-temporal signatures for vegetation to distinguish vegetation from other land covers. For this study, MODIS–NDVI datasets covering Southwest Nigeria were acquired for 2000, 2010, and 2020. This was followed by image reprojection to WGS 84 and clipping of Southwest Nigeria. Also, the clipped images were classified and subjected to accuracy assessment using field-verified referenced data. Also, the change detection was conducted on the classified images. The result is a map of Southwest Nigeria showing non–vegetation, savanna, and forest areas. Furthermore, the overall image classification accuracies are 80 %, 82 %, and 83 %, for 2000, 2010, and 2020, respectively, while the kappa coefficients are 0.696, 0.728, and 0.731 for 2000, 2010, and 2020, respectively.

Key-Words / Index Term :
Ecosystem, forest, global change, mapping, satellite imageries, savanna

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