Analysis of Changes and Driving Forces in Landscape Ecological Pattern of Land Use: A Case Study of Sanmenxia Section in the Yellow River Basin

This is the authors' abstract. We don't add key points for this paper.

The sustainable management of land resources and the formulation of land policies are closely linked to the stability and health of terrestrial ecological systems, which in turn underpin sustainable regional economic, social, and environmental development. However, land use change has a time effect on the environment and requires long-term observation to discover its impact on landscape patterns. The Yellow River Basin functions as a critical ecological barrier in northern China, where land use changes are particularly intense in the transitional zone between its middle and lower reaches. Using Landsat imagery as the data source, this study adopts the Random Forest (RF) algorithm to classify eight sets of sequential data covering a 35-year period from 1990 to 2025 in the study area. Landscape pattern metrics and transfer matrices are employed to conduct qualitative and quantitative analyses of the spatiotemporal dynamics of land use changes. Additionally, land expansion analysis strategies and the RF algorithm are applied to identify the relative importance of different driving factors. The results show that: (1) The classification accuracy based on the Google Earth Engine (GEE) cloud platform remains consistently high, exceeding 90% across all phases. (2) Patch density decreases significantly, while the largest patch index continues to decline; the Shannon diversity index shows a fluctuating upward trend, and the aggregation index exhibits a slight increase. (3) Mutual conversions among farmland, forest, and grassland are the dominant processes driving land use changes in the region. (4) The Digital Elevation Model (DEM), construction land area distribution, and distance to primary roads are the key factors influencing land use patterns, with human activities acting as the primary driver of land use type transformations in the area.