Abstract
In view of the problems of low precision, high energy consumption, and poor flexibility of the spatial characteristics analysis and vulnerability evaluation methods of agricultural land use environment, a principal component analysis–based spatial characteristics analysis and vulnerability evaluation method of agricultural land use environment is proposed. The remote sensing image of agriculture land was corrected. According to the Cartesian moments before and after image transformation, the scale factor, rotation angle, and translation parameters of image transformation are calculated, and these parameters are used to correct the agricultural land use image. The environment information data is obtained from the corrected image. On this basis, the dynamic degree of single and compound land use types is calculated. Two dynamic values are used to get the spatial characteristic values of agricultural land use. According to the eigenvalue, the evaluation index of land use vulnerability is calculated. Through principal component analysis, the comprehensive index of agricultural land vulnerability was obtained. Compare the index with the evaluation index to judge the level of land use vulnerability. The experimental results show that the method has high accuracy, low energy consumption, and the highest sensitivity coefficient of 0.99.
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Funding
This research was supported by Hunan Provincial Department of Education (12th Five-Year) Key Subject Funding Projects (No. 2011-76) and The State Forestry Administration focuses on Discipline (No. Lin Ren Fa [2016] 21).
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This article is part of the Topical Collection on Geological Modeling and Geospatial Data Analysis
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Chen, J., Hu, Y., Hu, Y. et al. Spatial characteristics analysis and vulnerability evaluation of agricultural land use environment. Arab J Geosci 13, 587 (2020). https://doi.org/10.1007/s12517-020-05597-z
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DOI: https://doi.org/10.1007/s12517-020-05597-z