| 基于多源数据的新疆人居环境质量评价 |
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| 引用本文： | 庞瑞秋,胡宁,魏冶.基于多源数据的新疆人居环境质量评价[J].地理科学,2021,41(12):2127-2137. |
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| 作者姓名： | 庞瑞秋 胡宁 魏冶 |
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| 作者单位： | 东北大学江河建筑学院,辽宁沈阳110000;东北师范大学地理科学学院,吉林长春130024 |
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| 基金项目： | 国家自然科学基金项目(41971202) |
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| 摘 要： | 针对区域人居环境质量缺乏从自然和人文因子组合综合评价分析的现状，利用遥感影像、站点监测、交通网络等多源数据，获取与人居环境质量密切相关的自然和人文因素共17个影响因子。应用熵权法、GIS空间分析及现代大数据等方法，定量研究新疆人居环境质量综合评价指数的空间分异及其与经济、人口分布的协调性关系。结果表明：① 新疆自然环境本底受水资源及植被覆盖情况影响较大，自然环境本底评价指数高值区域的空间分布特征与绿洲分散分布的特点具有极大的相似性，县域尺度的高质量区聚集分布在天山北坡的伊犁河谷等地，低质量区和一般质量区大面积集中连片地分布在新疆南部和东部。② 人文环境受交通通达程度及基础支撑完善度影响较大，地级市、县级市优于其他县级地区，人文环境质量基本呈现以各地级市、县级市为中心向外辐射递减的空间分异规律。③ 人居环境质量综合评价指数空间分异显著，呈现出以乌鲁木齐、昌吉市等点为中心的局部圈层式递减的空间分异规律。木垒?皮山分界线东南部与西北部人居环境质量的平均水平相差悬殊。④ 整体人居环境质量水平较低，人口分布与人居环境质量综合评价指数空间分布的匹配度不足，一般质量区和低质量区的县域土地面积占比高达84.90%，分布了47.74%的人口，低质量区仍有较大的提升潜力。⑤ GDP水平与人居环境质量保持较高的匹配性，环境经济协调型县市数量较少，环境经济滞后型县市数量最多，经济发展与人居环境相互掣肘，制约着新疆的可持续性发展。
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| 关 键 词： | 人居环境质量 多源数据 熵值法 空间分异 协调性 新疆 |
| 收稿时间： | 2021-01-01 |
| 修稿时间： | 2021-04-06 |
Evaluation of Quality for Human Settlement in Xinjiang Based on Multi-source Data |
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| Pang Ruiqiu,Hu Ning,Wei Ye.Evaluation of Quality for Human Settlement in Xinjiang Based on Multi-source Data[J].Scientia Geographica Sinica,2021,41(12):2127-2137. |
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| Authors: | Pang Ruiqiu Hu Ning Wei Ye |
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| Institution: | 1. Jiangho Architecture College, Northeastern University, Shenyang 110000, Liaoning, China
2. School of Geographical Sciences, Northeast Normal University, Changchun 130024, Jilin, China |
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| Abstract: | In view of the lack of comprehensive evaluation and analysis of the quality of regional human settlements from the combination of natural and human multi-dimensional factors, this paper uses remote sensing images, site monitoring, transportation network data and other multi-source data to obtain a total of 17 natural and human factors closely related to the quality of human settlements. Apply entropy method, GIS spatial analysis methods and big data processing methods to quantitatively study the spatial differentiation of Xinjiang’s human settlements quality composite index and its coordinated relationship with economic and population distribution. The results show that: 1) The quality of natural environment in Xinjiang is greatly affected by water resources and vegetation coverage. The spatial distribution characteristics of high-value areas at the regional scale are very similar to the scattered distribution of oases, and high-quality areas are concentrated in the Ili River Valley on the northern slope of the Tianshan Mountains, and the low quality areas and the average quality areas at county scale are concentrated in the southern and eastern parts of Xinjiang. 2) The quality of human environment is greatly affected by convenient transportation and basic support. The scores of prefecture-level cities and county-level cities are higher than other county-level areas. And it basically presents a spatial differentiation law with the prefecture-level cities and county-level cities as the center and radiating outward. 3) The human settlements quality composite indexpresents a spatial differentiation law with local circle layer decreasing centering on Urumqi and Changji. There is a great difference in the average level of human settlement quality between the northwest and southeast of the Mulei-Pishan boundary. 4) The overall quality of human settlement is low, and the matching degree between population distribution and the distribution of human settlements quality composite indexis insufficient. The land area of the general quality and the low quality is as high as 84.9%, distributed 47.74% of the population. The low quality areas still have great potential to improve their quality. 5) The GDP level and the quality of human settlements maintain a high similarity. The number of counties and cities with coordinated environment and economy is relatively small, while the number of counties and cities with lagged environment and economy is the largest.Economic development and human settlement environment restrict each other, which restricts the sustainable development of Xinjiang. |
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| Keywords: | quality of human settlement environment multi-source data entropy value method spatial differentiation coordination Xinjiang China |
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