Identification and Restoration of Forest Degradation Areas in Shaanxi Province Based on the LandTrendr Algorithm

Qianqian Tian, Bingshu Zhao, Chenyu Xu, Han Wang, Siwei Chen () and Xuhui Wang
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Qianqian Tian: College of Landscape Architecture and Art, Northwest Agriculture and Forestry University, Xianyang 712100, China
Bingshu Zhao: College of Landscape Architecture and Art, Northwest Agriculture and Forestry University, Xianyang 712100, China
Chenyu Xu: College of Landscape Architecture and Art, Northwest Agriculture and Forestry University, Xianyang 712100, China
Han Wang: College of Landscape Architecture and Art, Northwest Agriculture and Forestry University, Xianyang 712100, China
Siwei Chen: College of Landscape Architecture and Art, Northwest Agriculture and Forestry University, Xianyang 712100, China
Xuhui Wang: College of Landscape Architecture and Art, Northwest Agriculture and Forestry University, Xianyang 712100, China

Sustainability, 2025, vol. 17, issue 13, 1-31

Abstract: As an important ecological barrier in Northwest China, the health of forest ecosystems in Shaanxi Province is crucial to regional ecological balance and sustainable development. However, forest degradation has become increasingly prominent in recent years due to both natural and anthropogenic pressures. This study aims to identify the spatio-temporal pattern of forest degradation in Shaanxi Province, construct an ecological network, and propose targeted restoration strategies. To this end, we first built a structural-functional forest degradation (SFD) assessment system and used the Landsat-based detection of trends in disturbance and recovery (LandTrendr) algorithm to identify degraded areas and types; subsequently, we used morphological spatial pattern analysis (MSPA) and the minimum cumulative resistance (MCR) model to construct a forest ecological network and identify key restoration nodes. Finally, we proposed a differentiated restoration strategy for near-natural forests based on the Miyawaki method as a conceptual framework to guide future ecological recovery efforts. The results showed that (1) in 1991–2020, the total area of forest degradation in Shaanxi Province was 1010.89 km 2 , which was dominated by functional degradation (98%) and structural degradation (87.15%), with significant regional differences; (2) the constructed ecological network contained 189 ecological source sites, 189 ecological corridors, 89 key nodes, and 50 urgently restored; and (3) specific restoration measures were proposed for different degradation conditions (e.g., density regulation and forest window construction for functional light degradation and maintenance of the status quo or full reconstruction for structural heavy degradation). This study provides key data and systematic methods for the accurate monitoring of forest degradation, the optimization of ecological networks, and scientific restoration in Shaanxi Province, which holds great practical significance for establishing a robust ecological barrier in Northwest China.

Keywords: forest degradation; ecological restoration; LandTrendr algorithm; forest ecological networks (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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