Vulnerability assessment of agro-ecological environment in Karst mountain based on set pair analysis model of grey trigonometrically whitening weight

doi:10.13287/j.1001-9332.202008.014

Abstract

Abstract: Ecological vulnerability is a hot issue in the study of global change and sustainable development. Understanding the vulnerability of agro-ecological environment is conducive to rational utilization of regional agricultural resources, which could put forward effective measures for prote-cting agro-ecological environment. Given that the evaluation of agricultural eco-environment vulnerability generally does not consider the relationships among different indicators in different evaluation levels, we used the grey trigonometrically whitening weight set pair analysis (SPA) model to evaluate the vulnerability of agricultural eco-environment in Karst mountain by selecting 11 indicators such as population density, per capita arable land area and per capita afforestation area from the external vulnerability of ecological environment. The results showed that the vulnerability degree of agro-ecological environment in the study area was very high, mainly at the extreme, high and medium vulnerability grades. The proportion of extremely, highly, moderately, mildly and slightly vulnerable areas was 32.4%, 14.1%, 17.7%, 23.6% and 12.2% respectively. This result was consistent with the status of agricultural ecological environment vulnerability in the study area. It was feasible to evaluate the vulnerability of agro-ecosystem with the SPA Model of grey trigonometrically whitening weight, which provided a new method for evaluating agricultural ecological environment vulnerability.

Key words: vulnerability of agro-ecological environment, set pair analysis model, grey trigonometri-cally whitening weight function, Karst mountain

SHU Ying-ge, PENG Wen-jun, ZHOU Peng-peng. Vulnerability assessment of agro-ecological environment in Karst mountain based on set pair analysis model of grey trigonometrically whitening weight[J]. Chinese Journal of Applied Ecology, 2020, 31(8): 2680-2686.

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