# Spatiotemporal Variation of Ecological Quality in the Yinshan Mountains Detected by MODIS Remote Sensing Indicators

## TL;DR

This study uses satellite data to assess ecological quality changes in the Yinshan Mountains, identifying key factors like vegetation, water, and grazing that influence the region's sustainability.

## Contribution

A new MODIS-based ecological indicator (MODIS RSEI) is introduced, integrating multiple environmental factors for improved ecological assessment in arid and semiarid regions.

## Key findings

- The MODIS RSEI showed a spatial pattern of 'low in the west and high in the east' with temporal fluctuations in ecological quality.
- 62.53% of the MODIS RSEI in the Yinshan Mountains exhibited sustainable stability according to the Hurst index.
- NPP, precipitation, and grazing intensity were the main factors affecting ecological quality, with interactions between factors being more significant than individual effects.

## Abstract

Arid and semiarid regions constitute the primary distribution areas of desert ecosystems, and the long‐term, multifactor dynamic assessments of ecological quality can provide a scientific basis for the regional construction and sustainable development of desertified steppe ecosystems. To address the ecological vulnerability and monitoring needs of the Yinshan Mountains, we constructed a new MODIS‐based Remote Sensing Ecological Indicator (MODIS RSEI) based on MODIS data from 2001 to 2023. This indicator integrates greenness (SAVI, Soil Adjusted Vegetation Index), humidity (SWCI, Surface Water Capacity Index), dryness (NDBBI, Normalized Difference Bareness and Built‐up Index), heat (LST, Land Surface Temperature), as well as a salinity index (CSI, Comprehensive Salinity Index). Additionally, an optimal parameter geographic detector (OPGD) was employed to analyze the driving factors affecting ecological quality and their interactions. The results show that (1) the MODIS RSEI in the Yinshan Mountains exhibited a spatial pattern of “low in the west and high in the east,” fluctuating temporally between poor (0.20–0.40), moderate (0.40–0.60), and good (0.60–0.80) levels; (2) analysis of the Hurst index indicated that 62.53% of the MODIS RSEI in the Yinshan Mountains exhibited sustainable stability; and (3) single‐factor detection based on the OPGD showed that the spatial differentiation of MODIS RSEI was mainly affected by NPP (q = 0.837), precipitation (q = 0.474), and grazing intensity (q = 0.416). The interaction of multiple factors was significant, and the interaction of any two driving factors was greater than the influence of a single driving factor on the spatial differentiation of the Yinshan Mountains. This study provides a methodological framework and empirical evidence to support ecological conservation planning in the Yinshan Mountains, with potential applications in other arid and semiarid regions.

A comprehensive ecological index MRSEI based on MODIS was proposed.The new indicators of greenness, humidity, and dryness are more applicable to the ecological evaluation of the desertification steppes.The introduction of comprehensive salinity index can effectively reflect the issue of soil salinization.FROM‐TO vector transformation can effectively express the direction of gradient change.The partitioning effect of explanatory variables can be optimized using the optimal parameter geo‐detector model.

A comprehensive ecological index MRSEI based on MODIS was proposed.

The new indicators of greenness, humidity, and dryness are more applicable to the ecological evaluation of the desertification steppes.

The introduction of comprehensive salinity index can effectively reflect the issue of soil salinization.

FROM‐TO vector transformation can effectively express the direction of gradient change.

The partitioning effect of explanatory variables can be optimized using the optimal parameter geo‐detector model.