Evaluation of Ecological Carrying Capacity and Identification of Its Influencing Factors Based on Remote Sensing and Geographic Information System: A Case Study of the Yellow River Basin in Shaanxi

被引:12
|
作者
Zhu, Zhiyuan [1 ,2 ]
Mei, Zhikun [1 ,2 ]
Li, Shilin [1 ,2 ]
Ren, Guangxin [1 ,2 ]
Feng, Yongzhong [1 ,2 ]
机构
[1] Northwest A&F Univ, Coll Agron, Xianyang 712100, Peoples R China
[2] Res Ctr Recycle Agr Engn & Technol Shaanxi Prov, Xianyang 712100, Peoples R China
关键词
ecological carrying capacity (ECC); Yellow River Basin in Shaanxi (YRBS); geographical detector model; remote sensing evaluation; NORTHERN SHAANXI; LOESS PLATEAU; FOOTPRINT; ENVIRONMENT; AREAS; PROVINCE; TOURISM; DEMAND; EVOLUTION; REGION;
D O I
10.3390/land11071080
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Ecological carrying capacity (ECC), which requires simple scientific evaluation methods, is an important evaluation index for assessing the sustainability of ecosystems. We integrate an innovative research method. Geographic information systems (GIS) and remote sensing (RS) were used to evaluate the ECC of the Yellow River Basin in Shaanxi (YRBS) and to identify the underlying factors that influence it. A calculation method that combines RS and GIS data to estimate ECC based on net primary productivity (NPP) was established. The Carnegie-Ames-Stanford approach model was applied to estimate NPP. The NPP of each land type was used as an indicator to determine the yield factors. The ECC of the watershed was calculated with the carrying capacities of each land-use type. The geographical detector model was used to study the influencing factors of ECC, which provides a scientific basis for the formulation of ecological management policies in YRBS. The results show that from 2000 to 2010, it first decreased by 45.46%, and then increased by 37.06% in 2020, an overall decrease of 13.49 x 10(5) wha in 20 years. Precipitation is the dominant factor that affects ECC, while the impact of human activities on ECC was significantly enhanced during the study period. The developed method based on RS data serves as a reference for ecological evaluation in other similar regions.
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页数:17
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