摘要：In Anthropocene, Earth’s social-ecological systems are experiencing intense pressure as a result of human-induced resource over-exploitation at a magnitude never seen before. Consequently, land use and cover change (LUCC) dynamics have implications for environment through the resultant land degradation. This study focuses on understanding the spatio-temporal dynamics associated with mining activities in Zambia’s Solwezi copper mining district. Landsat-5 (TM), Landsat-8 (OLI and TIRS) satellite images were classified using Supervised Classification and Maximum Likelihood Approach in ERDAS Imagine 2015 for the LUCC detection between 1995 and 2019. The images were categorized into six different classes: water body, mine, agriculture, built-up, barren and forest areas. The results show a rapid reduction of forest cover and water body from 82.32% and 1.88% to 54.14% and 0.47% in 1995 and 2019, respectively. Built-up area on the other hand increased from 2.04% in 1995 to 4.9% in 2019. Mine area increased from 0.02% in 1995 to 1.43% in 2019. Barren and agriculture areas both gradually increased from 8.24% and 5.5% to 19.52% and 19.53% in 1995 and 2019, respectively. Thus, there was progressive LUCC with increase in the mining activities in the study area. The results obtained from this study proffer lessons that will benefit policy and environmental management strategies applicable to mining-dominated landscapes. We suggest that multiple stakeholders make use of such baselines to guide conservation planning and mitigation measures in resource-rich and mining-dominated landscapes.
关键词：Change detection Maximum likelihood classification Mining Multi-use landscape Sustainable land management Zambia
