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基于多源数据的长三角人居适宜性综合评价与分析

Comprehensive Evaluation and Analysis of Human Settlements' Suitability in the Yangtze River Delta Based on Multi-Source Data.

机构信息

School of Geography, Liaoning Normal University, Dalian 116029, China.

School of Resource and Environmental Sciences, Quanzhou Normal University, Quanzhou 362000, China.

出版信息

Int J Environ Res Public Health. 2023 Jan 11;20(2):1354. doi: 10.3390/ijerph20021354.

DOI:10.3390/ijerph20021354
PMID:36674110
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9859550/
Abstract

The suitability of human settlements is critical for quality of life and regional development. As comprehensive evaluations and research on the suitability of human settlements are lacking, a comprehensive evaluation of human settlements in the Yangtze River Delta (YRD) was carried out in 2020 by combining natural and human environmental elements based on multi-source data such as digital elevation models, Landsat remote sensing images, meteorological station data, and points of interest, other multi-source data, and constructions of the human settlements' suitability indexes. The results showed the following: (1) The spatial suitability of the natural environment in the YRD is significantly affected by the topographic conditions and distance from the sea, showing an increasing spatial differentiation from southwest to northeast, with Shanghai and Yancheng having the best natural environment suitability. (2) The suitability of the human environment in urban areas is better than that in non-urban areas and shows a decreasing trend from the south to the north circle. Shanghai, Zhoushan, and Huaibei have the best human environment suitability. (3) The comprehensive suitability of human settlements includes both the spatial differentiation characteristics of the suitability of natural and human environments. Shanghai and Zhoushan have the mosy comprehensive suitability for human settlements, while Huaibei and Xuzhou have the worst. (4) Land with a comprehensive suitability for human settlements of greater than 0.580 accounts for 23.60% of the total and contains 30.08% of the population and 32.31% of the economy, indicating that areas with a high suitability index have been fully utilized, and the populations and economies with human settlements suitability have a high degree of matching.

摘要

人类住区的适宜性对生活质量和区域发展至关重要。由于缺乏对人类住区适宜性的综合评价和研究,因此,2020 年结合多源数据(如数字高程模型、Landsat 遥感影像、气象站数据和兴趣点等)对长三角地区(YRD)的人类住区适宜性进行了综合评价,构建了人类住区适宜性指标体系。结果表明:(1)YRD 自然环境的空间适宜性受地形条件和距海距离的影响显著,从西南到东北呈现出空间分异程度逐渐增加的趋势,其中上海和盐城具有最佳的自然环境适宜性。(2)城区人类环境的适宜性优于非城区,且从南到北的圈域呈逐渐降低的趋势,其中上海、舟山和淮北具有最佳的人类环境适宜性。(3)人类住区的综合适宜性既包括自然环境和人类环境适宜性的空间分异特征,又包括两者之间的相互作用。上海和舟山的人类住区综合适宜性最好,而淮北和徐州的最差。(4)综合适宜性大于 0.580 的人类住区土地占比 23.60%,但承载了 30.08%的人口和 32.31%的经济,这表明高适宜性指数的区域已得到充分利用,且具有人类住区适宜性的人口和经济具有高度的匹配性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/6a1759ea234b/ijerph-20-01354-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/03c18771b633/ijerph-20-01354-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/1975b6635bf1/ijerph-20-01354-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/354617b47adf/ijerph-20-01354-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/c2ae9b529dcb/ijerph-20-01354-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/e66870f43d81/ijerph-20-01354-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/95138b016f04/ijerph-20-01354-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/7e2c38f3bdc1/ijerph-20-01354-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/6a1759ea234b/ijerph-20-01354-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/03c18771b633/ijerph-20-01354-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/1975b6635bf1/ijerph-20-01354-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/354617b47adf/ijerph-20-01354-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/c2ae9b529dcb/ijerph-20-01354-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/e66870f43d81/ijerph-20-01354-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/95138b016f04/ijerph-20-01354-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/7e2c38f3bdc1/ijerph-20-01354-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c4/9859550/6a1759ea234b/ijerph-20-01354-g008.jpg

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