Remote sensing clustering analysis based on object-based interval modeling

Hui He, Tianheng Liang, Dan Hu, Xianchuan Yu

Abstract: Highlights•Accurate descriptions of object features are important in object-based clustering.•The interval-valued data model describes the object-based clustering prototype features more appropriately.•Increasing separability between classes will increase the classification accuracy.•Novel object-based adaptive interval-valued fuzzy clustering method makes higher flexibility and efficiency.•Applied to high-resolution, multiband, remote sensing data for land cover classification, can also be applied in wider areas.