Journal
LAND
Volume 11, Issue 7, Pages -Publisher
MDPI
DOI: 10.3390/land11071080
Keywords
ecological carrying capacity (ECC); Yellow River Basin in Shaanxi (YRBS); geographical detector model; remote sensing evaluation
Categories
Funding
- Shaanxi Provincial Forestry Science and Technology Innovation Program Special Project [SXLK2020-0102]
- China Association for Science and Technology 2020 Postgraduate Science Popularization Ability Improvement Project [kxyjs202034]
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Ecological carrying capacity (ECC) is an important index for assessing the sustainability of ecosystems. This study used GIS and RS techniques to evaluate the ECC of the Yellow River Basin in Shaanxi and identify the influencing factors. A calculation method combining RS and GIS data was used to estimate the net primary productivity (NPP) of each land type and calculate the ECC of the watershed. The geographical detector model was applied to study the influencing factors of ECC, providing a scientific basis for ecological management policies.
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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