Classification algorithm for land use in the giant panda habitat of Jiajinshan based on spatial case-based reasoning - Xia, Wanlu; Zhang, Wen; Wu, Sen (Frontiers in Environmental Science, 2024)
The Jiajin Mountain, where the giant pandas reside, is an essential nature reserve in China. To comprehend the land use classification of the habitat, this article proposes a remote sensing interpretation algorithm based on spatial case reasoning, and is named Spatial Case-Based Reasoning (SCBR). The algorithm incorporates specific spatial factors into its framework，and doesn't require an extensive amount of domain knowledge and eliminates the need for a complex model training process, making it capable of completing land-use classification in the study area. SCBR comprises a spatial case expression model and a spatial case similarity reasoning model. The paper conducted comparative experiments between the proposed algorithm and SVM, Unet, ViT, Trans-Unet, and the results demonstrate that spatial case-based reasoning produces superior classification outcomes. The land use classification experiment based on spatial case-based reasoning at the Jiajinshan Giant panda habitat produced satisfactory experimental results. In the comparative experiments, the overall accuracy of SCBR classification reached 95%, and the Kappa coefficient reached 90%. The paper further analyzed the changes in land use classification from 2018 to 2022, and the average accuracy consistently exceeds 80%. We discovered that the ecological environment in the region where the giant pandas reside has experienced significant improvement, particularly in forest protection and restoration. This study provides a theoretical basis for the ecological environment protection of the area.