DeepGlobe Land Cover Classification Dataset

Automatic categorization and segmentation of land cover is of great importance for sustainable development, autonomous agriculture, and urban planning. DeepGlobe Land Cover Classification Challenge introduces the challenge of automatic classification of land cover types. This problem is defined as a multi-class segmentation task to detect areas of urban, agriculture, rangeland, forest, water, barren, and unknown.

土地覆盖自动分类与分割对于可持续发展、自主农业及城市规划均具有重要价值。DeepGlobe土地覆盖分类挑战赛（DeepGlobe Land Cover Classification Challenge）发起了土地覆盖类型自动分类的任务挑战。该问题被界定为一项多类别分割任务，需识别城市、农业用地、牧场、森林、水域、裸地及未知区域的地块范围。