TITLE:
Assessment of Land Use and Land Cover Change in Southwest Mauritania, Remote Sensing and GIS Approach
AUTHORS:
Amadou Hamadi Diallo, Temitayo Abayomi Ewemoje, Sidatt Zeine El Abidine
KEYWORDS:
Land-Use-Land-Cover, Remote Sensing, Geographic Information System, Maximum Likelihood Classifier, Southwest Mauritania
JOURNAL NAME:
Advances in Remote Sensing,
Vol.11 No.4,
December
30,
2022
ABSTRACT: Most countries’ land use and land cover (LULC) are changing dramatically today. Most of these changes are related to the way humans and the environment interact. Various methodologies and data sources have been used in conjunction with remote sensing (RS) to categorize and map changes in LULC. This study used RS and Geographic Information System (GIS) tools to analyze LULC change and transitions from 1984 to 2022 in a tropical forested landscape in southwest Mauritania. Using a suitable and high-quality collection of Landsat satellite images. For the classification and creation of LULC maps for the selected periods, the supervised technique using a maximum likelihood classifier was used. The results indicated that there was a remarkable change in all classes of LULC, with an increase in all classes, except barren land, which had a tremendous decrease of −68.58% for the total study area. Therefore, for the total study area, an increase in agricultural land (221%), water bodies (118.46%), vegetation (57.50%), and built-up areas (14.65%) was observed. We believe that by informing policymakers, environmental managers, and the general public about the current changes, our study will help the region to establish appropriate land use rules that may lead to policy document development.