Spatio-Temporal Distribution of the Black Rhino (Diceros bicornis L.) in the Midlands Black Rhino Conservancy, Zimbabwe

Abstract

Geographic Information System (GIS) and Remote Sensing (RS) technologies have many attributes that are beneficial in detecting, mapping, and, monitoring change in Land use/Land cover (LULC). This study used the technology with the aim to evaluate the Spatio -temporal impacts of Land use/Land cover Changes (LULCC) on Black Rhino distribution in Midlands Black Rhino Conservancy (MBRC), Zimbabwe. The study used time series satellite data. Landsat images were downloaded for the month of May at five-year intervals from 2000 to 2020. LULC and Normalized Differences Vegetation Index (NDVI) maps obtained were used in change detection. The images were classified using QGIS software on the maximum likelihood classifier algorithm. Presents and absence data for Black Rhino was used for distribution mapping. Quantum Geographic Information System (QGIS) and, R studio software were used for analysis. Results indicated that, a big percentage cover change was the bare land which increased by over 160%. Woodland decreased by about 46% within the same space of time. LULCC showed a significant positive relationship with black rhino distribution (p = 0.0381). MOLUSCE plugin was used for Prediction of LULCC for the year 2030, results indicated the highest increase in bare land 16.59%.