Open Synergy Land Cover Series

We put forward a cost-effective open and synergy framework for combining
supervised classification with training samples and aggregating existing multisource
land cover datasets. With this framework, novel global land cover maps with a
spatial resolution of 30 m every 5 years from 1990 to 2015 have been developed. The dataset was made into 1 km percentage due to the upload limit.

本研究提出了一种高性价比的开放协同框架，该框架将监督分类（supervised classification）与训练样本相结合，并聚合现有多源土地覆盖数据集。基于该框架，本研究构建了1990年至2015年间每5年一期、空间分辨率为30米的新型全球土地覆盖地图。受上传限制影响，本数据集被处理为1千米分辨率的百分比格网形式。