ABSTRACTIn this paper, we introduced major challenges in mapping croplands, settlements, water and wetlands, and discussed challenges in the use of multi-temporal and multi-sensor data. We then summarized some of the on-going efforts in improving qualities of global land cover maps. Existing technologies provide sufficient data for better map making if extra efforts can be made instead of harmonizing and integrating various global land cover products. Developing and selecting better algorithms, including more input variables (new types of data or features) for classification, having representative training samples are among conventional measures generally believed effective in improving mapping accuracies at local scales. We pointed out that data were more important in improving mapping accuracies than algorithms. Finally, we proposed a new paradigm for global land cover mapping, which included a view of vegetation classes based on their types and form, canopy cover and height. The new paradigm suggests t...
['Peng Gong', 'Le Yu', 'Congcong Li', 'Jie Wang', 'Lu Liang', 'Xuecao Li', 'Luyan Ji', 'Yuqi Bai', 'Yuqi Cheng', 'Zhiliang Zhu']
A new research paradigm for global land cover mapping