A dataset of inland water distribution in Hainan province based on remote sensing (2013-2017)

Inand water distribution is an indispensable component of global water resource security and management, climate research and ecological environment dynamic monitoring. Based on GF-1 data and Landsat8 OLI data, we used the minimum-redundancy maximum-relevancy(mRMR) feature selection algorithm and the object-oriented knowledge rule set to automatically extract the land water distribution of Hainan province during 2013-2017. Then assisted by high-resolution remote sensing images and Google Earth images to verify the classification accuracy. Results show a Kappa coefficient of 84.67%，85.98%，80.61%，88.66% and 90.66% for the subsets, respectively, demonstrating a high accuracy of the classification results. This dataset can be directly used to study the spatial and temporal distribution of land surface water. It also provides data basis for water environment research, such as water body studies and water resource safety assessment.