基于生态敏感性分析的江川区土地利用空间格局优化配置

    Optimization of land use spatial pattern in Jiangchuan district based on ecological sensitivity analysis

    • 摘要: 为优化江川区土地利用空间格局,促进土地可持续发展,该文以云南省玉溪市江川区为研究区,将CLUE-S(conversion of land use and its effects at small region extent)模型和生态敏感性分析应用于江川区土地利用空间格局优化配置。以高度敏感区为CLUE-S模型中区域约束文件,突出研究区生态保护重点区域,并以综合生态敏感性分区为影响研究区土地利用变化的驱动力因子,提出一种将生态敏感性融入土地利用空间格局优化配置的过程和结果中的土地利用情景模拟方法,并借助2006年和2016年土地利用数据对江川区自然发展情景和土地生态优化情景2种模式下2025年的土地利用空间格局进行优化配置,并基于生态敏感性分区对优化配置模拟结果进行对比分析。结果表明:2种情景下2025年江川区土地利用格局既有共同特征也存在差异。在2种情景下均有效的保护了原有林地、耕地、未利用地和建设用地格局,但新增林地、草地等空间分布格局不同。根据2025年2种情景与2016年土地利用现状在不同敏感性区内主要土地利用类型分布情况表明,情景二土地利用空间格局优于自然发展情景和2016年土地利用现状。研究结果认为土地生态优化情景更为合理,该结果可为江川区生态保护和城镇发展提供参考。

       

      Abstract: In order to optimize the spatial pattern of land use and promote the sustainable development of the land, taking the Jiangchuan District of Yuxi City, Yunnan Province as the research area, in this paper, we adopted the CLUE-S (The Conversion of Land Use and its effects at Small Region Extent) and ecological sensitivity analysis methods that were applied to the optimal allocation of land use spatial pattern in Jiangchuan District. We took the highly sensitive region as the regional constraint document in the CLUE-S model to highlight the key areas of ecological protection in the studied area. Based on the comprehensive ecological sensitivity zoning as the driving force factor affecting the land use change in the study area, a land use scenario simulation method was proposed in which the ecological sensitivity was integrated into the land use spatial pattern optimization configuration process and results. With the use of land use data in 2006 and 2016, the land use spatial pattern of 2025 in the two modes of natural development scenarios and land ecological optimization scenarios in Jiangchuan District would be optimized. The simulation results of optimized configuration were analyzed and validated based on ecological sensitivity partition. The results showed that by selecting five secondary indicators of soil erosion intensity, land use type, vegetation coverage, distance from water source and disaster susceptibility, we constructed a watershed ecological sensitivity evaluation index system. Jiangchuan District's ecological sensitivity was mainly moderate or above sensitivity, and the area was 57 111.37 hm2, accounting for 70.91% of the total area of Jiangchuan District. According to the results of ecological sensitivity assessment, Jiangchuan District was divided into highly sensitive, moderately sensitive, mildly sensitive and non-sensitive, and it was divided into ecological protection core area, control development area and suitable development area. In addition, based on the 2006 land use data, and use of the CLUE-S model, the spatial pattern of land use in Jiangchuan District in 2016 was simulated. Compared with the land use data in 2016, the correct raster number of the simulation results accounted for 81.59% of the total number of grids. The Kappa coefficient was 0.779 1, and the CLUE-S model can be used to simulate the spatial pattern of land use in Jiangchuan District in 2025. Moreover, in the two scenarios, the land use pattern of Jiangchuan District in 2025 had both common features and differences. In the two scenarios, the original forest land, farmland, unused land and urban and residential land pattern were effectively protected, but the spatial distribution patterns of newly added forest land and grassland were different. The results of the optimal allocation of land use spatial pattern in Jiangchuan District in 2025 were verified. According to the distribution of major land use types in different sensitive areas in 2025 and the land use status in 2016, the spatial pattern of land use in Scenario 2 was better than natural development scenarios and the status of land use in 2016. The research results showed that the land ecological optimization scenario was more reasonable, which not only could reduce the area of cultivated land, but also consider the needs of ecological protection and urban development.

       

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