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July 8, 2026Remote Sensing0 citationsOpen Access

Spatiotemporal Evolution of Ecological Environment Quality and Driving Factors in the Loess Plateau of Northern Shaanxi

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RTRuize TangZLZ L LiSZShuangcheng Zhang

Key Points

  • The aim is to systematically assess the spatiotemporal evolution of ecological environment quality on the Loess Plateau from 2000 to 2024.
  • Constructed a remote sensing ecological index model to assess ecological environment quality.
  • Employed Theil–Sen estimator, Mann–Kendall test, and Hurst exponent to analyze changes and predict trends.
  • Used Geodetector model to explore driving factors influencing ecological environment quality.
  • Ecological environment quality showed an upward trend, with mean remote sensing ecological index increasing from 0.376 in 2000 to 0.545 in 2024.
  • A spatial distribution pattern indicated higher quality in the south, lower in the north, and the lowest in the northwest.
  • 91.21% of the area showed an improving trend, primarily influenced by geomorphological types.

Abstract

Accurately assessing the spatiotemporal evolution of ecological environment quality (EEQ) on the Loess Plateau of Northern Shaanxi is of great significance for consolidating the ecological security barrier of the Yellow River Basin. Most of the existing research focuses on a single ecological theme, which does not reflect the overall ecological status of the region. In this study, a remote sensing ecological index (RSEI) model was constructed to systematically assess the EEQ from 2000 to 2024. The Theil–Sen estimator, Mann–Kendall test, and Hurst exponent were jointly employed to detect change significance and predict future trends, while the Geodetector model was applied to explore driving factors. The results were as follows: (1) EEQ exhibited a fluctuating but overall upward trend, with the mean RSEI rising from 0.376 in 2000 to 0.545 in 2024—an average annual increase of approximately 0.00569. (2) Spatially, a distinct pattern of “higher in the south, lower in the north and the lowest in the northwest” was observed. Over the 25-year period, the combined proportion of “excellent” and “good” grades increased by roughly 20 percentage points, and the “moderate” grade expanded from 13.61% to 47.12%. (3) Areas showing an improving trend accounted for 91.21% of the total area and highly overlapped with those projected to improve in the future. (4) Single-factor detection revealed that geomorphological type exerted the greatest influence on the spatial heterogeneity of EEQ, with a multi-year mean q-value of 0.701. Interaction detection further indicates that the geomorphology–land use interaction may continue to shape the regional EEQ’s spatial distribution. These findings provide a scientific basis for precise ecological restoration planning and spatial optimization on the Loess Plateau of Northern Shaanxi.

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Cite This Study

Tang et al. (2026) studied this question.

synapsesocial.com/papers/6a4de804d2ea289ef6282e52https://doi.org/10.3390/rs18132219
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