干旱区地理2024，Vol.47Issue(2)：248-259,12.DOI:10.12118/j.issn.1000-6060.2023.162
基于基线遥感生态指数的鄂尔多斯市生态质量分析
Ecological quality analysis of Ordos City based on the baseline remote sensing ecological index
摘要
Abstract
Ordos City is an important steppe desert and agropastoral ecotone in the Yellow River Basin,China.Studying the changes in ecological quality in Ordos City is important for supporting the ecological conservation and high-quality development of the Yellow River Basin.Herein,the remote sensing imagery of a moderate-reso-lution imaging spectroradiometer was used as a data source to calculate the baseline remote sensing ecological in-dex(B_RSEI)of Ordos City by improving the conventional normalization and principal component analysis.This study also analyzes the characteristics of ecological quality changes from 2001 to 2019.The results indicate the following:(1)B_RSEI exhibits stable directionality and integrity,offering an enhanced reflection of long-term changes in ecological quality.From 2001 to 2019,B_RSEI of Ordos City showed a fluctuating increase and a spatial differentiation of higher in the east and lower in the west.(2)The surface water content index(SWCI)is the primary factor promoting B_RSEI and serves as the main factor explaining the B_RSEI distribution.The land surface temperature(LST)is the main factor inhibiting B_RSEI,with its most substantial interaction.(3)The eco-logical quality of Ordos City has improved,covering 67.13%of the total area,with notable ecological manage-ment effects in the Jungar Banner,Kangbashen District,and Ejin Horo Banner areas.This study demonstrates an overall improvement in the ecological quality of Ordos City,emphasizing the usefulness of B_RSEI in analyzing interannual changes.This could provide a reference for the ecological governance of the Ordos City and high-quality development of the Yellow River Basin.关键词
生态质量/基线遥感生态指数/主成分分析/鄂尔多斯市Key words
ecological quality/B_RSEI/principal component analysis/Ordos City引用本文复制引用
薛华柱,袁茜,董国涛,姚楠,张晴..基于基线遥感生态指数的鄂尔多斯市生态质量分析[J].干旱区地理,2024,47(2):248-259,12.基金项目
国家自然科学基金(51779099) （51779099）
国家重点研发计划项目(2016YFC0402400) （2016YFC0402400）
河南省科技攻关项目(232102320247)资助 （232102320247）
