Download PDFOpen PDF in browserRural Landscape Vulnerability Assessment Method Incorporating Human Disturbance Factors: the Case of a Autonomous Prefecture in Southwestern ChinaEasyChair Preprint 668013 pages•Date: September 24, 2021AbstractThis study Addressed the inadequacy of traditional landscape vulnerability measurement methods in considering human disturbance factors, added the population pressure index, to constructs a rural landscape vulnerability measurement model of "landscape sensitivity index (LSI) - landscape adaptability index (LAI) - population pressure index (PPI)" by combining rural landscape vulnerability characterization.Based on the land use cover data from 2005 to 2015 in Liangshan Yi Autonomous Prefecture,we constructed a rural landscape vulnerability evaluation system and took empirical analysis. we found that :(1) the evaluation model has good feasibility to portray the vulnerability of rural landscape in the study area, and the research findings reflect the actual situation to a certain extent, which can provide a reference for the study of rural landscape vulnerability measurement. (2) During the period of 2005-2015, the unevenness of rural landscape vulnerability in each district and county of the study area is significant, showing the characteristics of circles; the spatial structure of landscape vulnerability level changes significantly, the area of high vulnerability area has experienced the process of first increasing and then decreasing, and gradually changing to medium and low vulnerability areas, and the overall situation of landscape vulnerability has been optimized. (3) Natural environmental factors have a continuous influence on the fragility of rural landscape, while socio-economic and urban-rural construction and other anthropogenic disturbance factors have a transformative influence on the spatial and temporal differentiation of rural landscape fragility, and administrative force is another major influencing factor. Keyphrases: Spatial and temporal evolution, driving forces, landscape adaptability index (LAI), landscape pattern, landscape sensitivity index(LSI), landscape vulnerability index(LVI), population pressure index(PPI)
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