[Spatiotemporal Evolution and Driving Forces of Landscape Ecological Risk in Harbin City Based on Interpretable...

Investigating landscape ecological risk in Harbin is of great significance for ecological protection and sustainable development in the northeastern old industrial base. Based on land cover data from 2003 to 2023， this research employed landscape ecological risk assessment models， trajectory analysis， and XGBoost-SHAP interpretable machine learning to analyze the spatial and temporal variation of landscape types， risk distribution and dynamics， and driving mechanism. The results showed that cropland and forest land were predominant， with an increase of 859.14 km² in built-up areas being the primary factor of landscape pattern changes. The overall ecological risk level in Harbin remained low， with more than 96% of the area classified as low or very low risk； high and very high-risk zones accounted for only 0.79%， mainly concentrated in core urban districts such as Daoli and Nangang. Risk transfer analysis indicated that regions with stable risk levels dominated， whereas areas experiencing risk increase or decrease demonstrated dynamic shifts. Trajectory analysis revealed diverse risk development modes， with the stable maintenance type accounting for 61.8%， while risk-increasing fluctuation and risk-decreasing fluctuation accounted for 22.9% and 14.6%， respectively. Fluctuation-reversion and cross-over fluctuation accounted for only 0.6% and 0.1%. The analysis of driving factors showed that elevation （SHAP value 0.014 3） and NDVI （SHAP value 0.004 19） were the primary natural factors influencing the distribution of landscape ecological risk patterns， whereas population density （SHAP value 0.009 05） and GDP （SHAP value 0.003 4） exhibited negative effects in core urban areas such as Daoli， Nangang， and Xiangfang， reflecting infrastructure development's role in alleviating ecological risks. These findings provide scientific references for ecological conservation and territorial spatial planning in Harbin.