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[Spatio-temporal Monitoring and Driving Factor Analysis of Eco-environment Quality in the Loess Plateau of Northern Shaanxi]

  • 0School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China.
Huan Jing Ke Xue= Huanjing Kexue +

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July 18, 2025

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July 18, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

The Loess Plateau

Area Of Science

  • Ecological monitoring and environmental science.
  • Remote sensing applications in environmental assessment.
  • Spatio-temporal analysis of ecological factors.

Context

  • The Loess Plateau in Northern Shaanxi faces significant ecological challenges including soil erosion, desertification, and salinization.
  • Effective eco-environment protection necessitates comprehensive, quantitative monitoring of spatio-temporal changes and driving factors.
  • Existing ecological indices require adjustment to accurately capture the specific environmental conditions of the region.

Purpose

  • To develop an adjusted remote sensing ecological index (RSEI_A) incorporating salinity and desertification indices.
  • To dynamically monitor and analyze the eco-environment quality changes in the Loess Plateau of Northern Shaanxi from 2000 to 2020.
  • To investigate the spatial distribution characteristics and driving factors of eco-environment quality using advanced analytical models.

Summary

  • An adjusted remote sensing ecological index (RSEI_A) was developed using Google Earth Engine, integrating the Composite Salinity Index (CSI) and Desertification Difference Index (DDI).
  • Eco-environment quality in the study area showed a distinct improvement trend over two decades, with a significant increase in good/excellent quality areas and a decrease in poor quality areas.
  • The Normalized Difference Vegetation Index (NDVI) was identified as the most influential factor on RSEI_A, followed by precipitation, highlighting key drivers of environmental change.

Impact

  • The study provides a robust methodology for assessing eco-environment quality in ecologically fragile regions.
  • Findings offer crucial data for informing regional eco-environment protection strategies and sustainable land management practices.
  • The developed RSEI_A demonstrates broad applicability for comprehensive regional ecological evaluations.

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