Remote Sensing and Landscape Metrics-Based Forest Physical Degradation: Two-Decades Assessment in Gishwati-Mukura Biological Corridor in Rwanda, East-Central Africa

Abstract

The management of forest corridors and related ecology is one of the effective strategies to minimize the adverse effects of forest degradation. It controls the connectivity of inhabitant species and the connection of the isolated patches. This study analyzed spatial and temporal forest physical degradation based on forest cover change and forest fragmentation in the Gishwati-Mukura biological corridor from 1990-2019. Remotely sensed datasets, Geographical Information System (GIS) and FRAGSTATS software were used to analyze the spatial and temporal physical degradation and changes in forest cover. The results indicated that the Gishwati-Mukura corridor experienced massive deforestation where approximately 7617.1 ha (64.22%) of forest cover was completely cleared out, which implies an annual forest loss of 262.6 ha·year-1 (2.21%) during 1990-2019. The forest cover transitions patterns and geostatistical analysis indicated that extensive deforestation was associated with intensive agriculture. The results demonstrated that agriculture has dramatically increased from 29.46% in 1990 to 57.22% in 2019, with an annual increase of 1.97%. Since Gishwati-Mukura has changed to National Park (NP), it lacks diversified scientific studies addressing the analysis of the remote and spatial patterns to investigate its physical degradation and landscape dynamics. This research study will serve as remote forest analysis gap-filling and as the cornerstone of numerous other research that will contribute to the improvement of the connectivity assessments along the Gishwati-Mukura corridor and other related ecosystems.