Yaohuan Huang

Abstract High-precision global river datasets are crucial for hydrology and environmental research. Although several global river datasets have been developed and widely adopted, they often suffer from significant deviations from actual river distributions in many areas. In this study, we propose a multi-source vector river data fusion framework to generate a high spatial accuracy global river dataset with topological information, named GSriver.

3. Results and Discussion Based on the proposed methodology, a rooftop potential assessment was conducted. The results of classification, PV rooftop extraction and PV potential, were presented and discussed in this section. 3.1. Results Classification The classifications were performed, and the results were labelled TP, FP, and missed building pixels FN, as illustrated in Figure 4. According to the results, the optimized approach was highly robust and convincing.

Open AccessEditorial by Yaohuan Huang 1,2, Yesen Liu 3,*, Runhe Shi 4 and Hongyan Ren 1 1 State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China 2 College of Resource and Environment, University of Chinese Academy of Sciences, Beijing 100049, China 3 State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water...