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Environmental Monitoring in Northern Aksu, China Based on Remote Sensing Ecological Index Model

Environmental Monitoring in Northern Aksu, China Based on Remote Sensing Ecological Index Model

作     者:Yun Zhang Liangjun Zhao Kai Niu Asiya Manlike Yun Zhang;Liangjun Zhao;Kai Niu;Asiya Manlike

作者机构:Computer Science and Engineering of Sichuan University of Science and Engineering Yibin China Grassland Research Institute Xinjiang Academy of Animal Sciences Urumchi China 

出 版 物:《Open Journal of Applied Sciences》 (应用科学(英文))

年 卷 期:2022年第12卷第5期

页      面:757-768页

学科分类:08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 081102[工学-检测技术与自动化装置] 

主  题:Aksu China Ecological Environment Quality Principal Component Analysis Remote Sensing Ecological Index 

摘      要:In order to understand the development status of ecological environment quality in the Aksu region of China, to effectively adjust the ecological environment quality, so as to promote the sustainable development of its social economy and ecological environment protection. This paper selects the Landsat series remote sensing images of the northern Aksu region in 2013, 2016, and 2019, and uses the tools such as ENVI5.3 and ArcGIS 10.8.1 to process the image data accordingly. The principal component analysis method is used to calculate the Remote Sensing Ecological Index (RSEI) of the northern Aksu region. The data show that: 1) The ecological environment quality index in the northern Aksu region in 2013, 2016, and 2019 was 0.706087, 0.25243 and 0.362991 respectively;2) The areas where the ecological environment quality declined significantly in the northern Aksu region were the human settlements and the Gobi, fan-shaped land and other special terrain areas;3) The humidity index and the heat index are the two factors that have the greatest impact on the ecological environment quality in the northern Aksu area. The data as a whole show that the ecological environment in the northern part of the Aksu region has deteriorated seriously, and the severely deteriorated area is close to the human living area.

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