How Will Rwandan Land Use/Land Cover Change under High Population Pressure and Changing Climate?
Source abstract
Abstract
In recent decades, population growth and economic development have greatly influenced the pattern of land use/land cover (LULC) in Rwanda. Nevertheless, LULC patterns and their underlying change mechanisms under future climate conditions are not well known. Therefore, it is particularly important to explore the direction of LULC transfer in the study area, identify the factors driving the transfer of different types of LULC and their changes, and simulate future LULC patterns under future climate conditions. Based on LULC analyses of Rwanda in 1990, 2000, 2010, and 2015, the LULC pattern of Rwanda in the next 30 years was simulated using an LULC transition matrix, random forest sampling, the Markov chain model, and the PLUS model. The results showed that LULC change in the study area primarily comprised a decrease in forest area and expansion of cropland area, accompanied by a small increase in grassland area and an annual increase in urban land area. Prior to 2000, the LULC in Rwanda was mainly converted from forest and grassland to cropland, with the ratio being 0.72:0.28. After 2010, the LULC was mainly converted from forest to grassland and cropland, with the ratio being 0.83:0.17. Changes in forests, grasslands, and cropland are driven by multiple factors, whereas changes in wetlands, water, urban land, and unused land are more likely to be driven by a single factor. The existing trend of LULC change will continue for the next 30 years, and the future LULC pattern will exhibit a trend in which cropland area will increase in the west and grassland area will decrease, whereas grassland area will increase in the east and cropland area will decrease.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Land Use and Ecosystem Services · Conservation, Biodiversity, and Resource Management · Remote Sensing in Agriculture
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Soil and Water Conservation, Northwest A&F University, Yangling, Xianyang 712100, China
Funding
International Cooperation and Exchange Program of the National Natural Science Foundation of China
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