Assessment of Landscape Ecological Risks Driven by Land Use Change Using Multi-Scenario Simulation: A Case Study of Harbin, China

Yang Li, Jiafu Liu (), Yue Zhu and Chunyan Wu
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Yang Li: School of Geographical Sciences and Tourism, Jilin Normal University, Siping 136000, China
Jiafu Liu: School of Geographical Sciences and Tourism, Jilin Normal University, Siping 136000, China
Yue Zhu: School of Geographical Sciences and Tourism, Jilin Normal University, Siping 136000, China
Chunyan Wu: School of Geographical Sciences and Tourism, Jilin Normal University, Siping 136000, China

Land, 2025, vol. 14, issue 5, 1-23

Abstract: An evaluation of regional landscape ecological risk (LER) in Harbin, a key center city in Northeast China, is crucial for the long-term sustainability of its ecological and economic development. This study aims to (1) assess the spatiotemporal patterns of LER in Harbin from 2000 to 2020, (2) identify the key natural and human driving factors influencing LER, and (3) project future landscape ecological risk trends under multiple land use scenarios. To achieve these objectives, land use data from 2000, 2010, and 2020 were analyzed using landscape pattern indices to characterize ecological risk patterns. GeoDetector was applied to quantify the spatial differentiation and factor contributions to LER. Furthermore, the PLUS model was employed to simulate land use change and assess future LER patterns under three scenario settings. Moran’s I was used to evaluate spatial autocorrelation. The results indicate the following: (1) Between 2000 and 2020, cultivated land and woodland were the two most prevalent land types in Harbin, with the majority of land use shifts occurring between these two groupings. The main changes to the landscape were a continuous increase in development land and a steady decrease in unused area. (2) The overall LER in Harbin has been trending downward over the last 20 years, primarily falling within the medium-risk range. Marked spatial heterogeneity in LER was observed, displaying a distribution pattern of “high in the west and north, low in the east and south”. The majority of the riskiest regions were concentrated around bodies of water. (3) The Moran’s I indices for LER in Harbin were 0.798, 0.828, and 0.852, respectively, indicating significant spatial autocorrelation. The local clustering patterns were mainly defined by “High–High” and “Low–Low” agglomeration patterns. (4) Among natural factors, DEM exhibited the greatest explanatory strength for LER in Harbin, and the interaction between DEM and annual precipitation was recognized as the dominant force driving spatial disparities in LER. (5) Among the three projected scenarios for 2030, the ecological priority scenario showed a slower rate of decrease in ecological land, suggesting that this scenario is an effective approach for improving landscape ecological conditions. The findings offer a theoretical foundation and scientific guidance for LER management in Harbin and similar regions.

Keywords: landscape pattern; multi-scenario simulation; GeoDetector; Harbin (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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