Spatial Mapping of Abandoned Mines and Land Use–Land Cover Changes in Kamtonga and Mkuki of Kenya: A Remote Sensing and GIS Approach
Peter Sholo *
Taita Taveta University, Kenya.
Mika Siljander
University of Helsinki, Finland.
James Ochieng
Taita Taveta University, Kenya.
*Author to whom correspondence should be addressed.
Abstract
Following mining activities, rehabilitation is essential to restore sites to their original condition. This study employed Geographic Information System (GIS) and remote sensing techniques to analyze land use–land cover (LULC) changes in Kamtonga and Mkuki, Kenya. Specifically, satellite imagery from 2014 and 2017 was processed using supervised classification and the Normalized Difference Vegetation Index (NDVI). The results revealed significant LULC changes: vegetation cover decreased by 40%, bare rock by 75.4%, and scrubland by 15.26%, while built-up areas increased by 41.8%. Open land accounted for 92.3% of the study area. NDVI values showed a mean of 0.66 in 2014, indicating high vegetation cover, and −0.28 in 2017, reflecting a sharp decline. These findings suggest that mining activities have led to substantial alterations in LULC patterns, with an increase in built-up areas likely driven by population growth and settlement expansion. Urban encroachment has contributed to the loss of shrubs and vegetation, resulting in more open land. Furthermore, spatial overlay of abandoned mines on the LULC map revealed that they are predominantly situated in areas classified as shrubland, bare rock, and open land. These insights offer a critical foundation for policymakers and relevant institutions to design and implement effective mine rehabilitation strategies. However, further research is needed to validate the reliability of the identified indicators.
Keywords: Remote sensing, GIS, land use–land cover change, NDVI, rehabilitation, bandoned mines