Using the Google Earth Engine cloud-computing platform to assess the long-term spatial temporal dynamics of land use and land cover within the Letaba watershed, South Africa

被引:7
作者
Mashala, Makgabo Johanna [1 ,2 ]
Dube, Timothy [2 ]
Ayisi, Kingsley Kwabena [3 ]
Ramudzuli, Marubini Reuben [1 ]
机构
[1] Univ Limpopo, Dept Geog & Environm Studies, Sovenga, South Africa
[2] Univ Western Cape, Inst Water Studies, Dept Earth Sci, Bellville, South Africa
[3] Univ Limpopo, Risk & Vulnerabil Sci Ctr RVSC, Sovenga, South Africa
关键词
Catchment health; cloud computing; ecosystem system; environmental security; land resources; population growth; RIVER CATCHMENT; DRIVING FORCES; IMPACTS; QUALITY; MANAGEMENT; BIOMASS; UTILITY; SENSOR;
D O I
10.1080/10106049.2023.2252781
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Population growth and environmental shifts have elevated the pressure on land use and cover (LULC), necessitating vital management and adaptive strategies to preserve the balance between ecosystem services and human well-being in watersheds. It's pivotal to understand the implications of human-induced shifts from natural to human-dominated surroundings This study utilized Google Earth Engine (GEE) to analyze 31 years of LULC changes in Letaba watershed. Using GEE's random forest, LULC classes were mapped with 93% to 99% accuracy across four timeframes (1990, 2000, 2010, and 2021). Trends revealed declining water bodies (-4%), bare surfaces (-2%), natural forest (-3%), and grassland (-3%), while shrublands, plantations, and built-up areas increased at annual rates of 41%, 24%, and 47% respectively. This transformation reflects population-driven shifts, necessitating adaptive strategies. Given the importance of plantations for income, embracing climate-smart agriculture could ensure long-term food and environmental security, thus addressing the evolving dynamics in Letaba watershed.
引用
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页数:20
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