ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume X-1-2024
09 May 2024
 | 09 May 2024

Land Cover Classification Based on Multimodal Remote Sensing Fusion

Wei Chen, Jiage Chen, Yuewu Wan, Xining Liu, Mengya Cai, Jingguo Xu, Hongbo Cui, and Mengdie Duan

Keywords: Land cover data, deep learning, Multi source image fusion

Abstract. Global high-precision and high timeliness land cover data is a fundamental and strategic resource for global strategic interest maintenance, global environmental change research, and sustainable development planning. However, due to difficulties in obtaining control and reference information from overseas, a single data source cannot effectively cover, and surface coverage classification faces significant challenges in information extraction. Based on this, this article proposes an intelligent interpretation method for typical elements based on multimodal fusion, starting from the characteristics of domestic remote sensing images. It also develops an optical SAR data conversion and complementarity strategy based on convolutional translation networks, as well as a typical element extraction algorithm. This solves the problems of sparse remote sensing images, limited effective observations, and difficult information recognition, thereby achieving automation of typical element information under dense observation time series High precision extraction and analysis.