1. 中国科学院 水利部 水土保持研究所, 陕西 杨凌,712100
2. 中国科学院大学,北京,100049
纸质出版:2022
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邱高峯, 马波. 卢旺达共和国土地利用变化特征及其驱动因子[J]. 水土保持通报, 2022,42(3):263-273.
Qiu Gaofeng, Ma Bo. Land Use Change Characteristics and Their Driving Factors in Republic of Rwanda[J]. Bulletin of Soiland Water Conservation, 2022, 42(3): 263-273.
邱高峯, 马波. 卢旺达共和国土地利用变化特征及其驱动因子[J]. 水土保持通报, 2022,42(3):263-273. DOI: 10.13961/j.cnki.stbctb.2022.03.034.
Qiu Gaofeng, Ma Bo. Land Use Change Characteristics and Their Driving Factors in Republic of Rwanda[J]. Bulletin of Soiland Water Conservation, 2022, 42(3): 263-273. DOI: 10.13961/j.cnki.stbctb.2022.03.034.
[目的] 探究卢旺达共和国(以下简称“卢旺达”)1992—2019年土地利用状况,为该国土地利用规划和土地资源可持续利用提供参考。[方法] 本研究利用1992—2019年欧洲航天局全球陆地覆盖数据(ESA GlobCover),基于GIS空间统计分析及地理探测器等方法分析了卢旺达土地利用时空变化特征及其关键驱动力。[结果] ①卢旺达1992—2019年土地利用类型以农地和林地为主。城镇用地面积增加4.5倍,灌木林地和水域面积分别增加0.28%和2.65%。农地、林地、草地和湿地面积分别减少0.38%,1.46%,44.24%和0.27%。1992—2000年综合土地利用动态度最大,为0.19%。各地类空间分布表现出集聚性。②各驱动因子对各地类的驱动作用差异较大。各驱动因子独立作用q值解释力小于两因子间的交互作用。[结论] 短期内,社会经济指标对卢旺达土地利用类型变化起决定性作用。因此,未来应当考虑土地使用的长期利益,最大限度地促进土地的有效管理。
[Objective] The land use status of the Republic of Rwanda (hereinafter referred to as Rwanda) during 1992-2019 was analyzed in order to provide a reference for land use planning and sustainable use of land resources in Rwanda.[Methods] The spatial and temporal land use change characteristics of Rwanda were analyzed and their key driving factors were determined based on GIS spatial statistical analysis and geographic probes using global land cover data (ESA GlobCover) of European Space Agency from 1992-2019.[Results] ① Rwanda's land use types from 1992-2019 were dominated by agricultural and forest land. The area of urban land increased by 4.5 times
while the area of shrubland and watersheds increased by 0.28% and 2.65%
respectively. The area of agricultural land
forest land
grassland
and wetland decreased by 0.38%
1.46%
44.24%
and 0.27% respectively. From 1992-2000 had the largest comprehensive land use movement attitude of 0.19%. The spatial distribution of each land class showed agglomeration. ② The driving effect of each driving factors on each land class varied greatly. The explanatory power of the q-value of each driving factors acting independently was less than the interaction between the two factors.[Conclusion] Socio-economic indicators played a decisive role in land use type changes in the study area over the short term. Therefore
the long-term benefits of land use should be considered in the future to maximise the effective management of land.
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