Million clandestine gravesites over southeastern China’s land surfaces revealed by satellite images

• Various deep learning models are used to detect prevailing informal gravesites in southeastern China. • A large-scale high-resolution grave detection database over a substantial spatial extent is created. • Nearly one million clandestine gravesites are detected over the highly vegetated land surfaces. • Attribution analysis using machine learning reveals complicated socioeconomic and geographic factors. Gravesite occupies a nonnegligible fraction of land resources with growing population in China. Apart from public cemeteries, the clandestine gravesites built by local residents distributed over various land surfaces are yet not to be understood. Here, we use high-resolution satellite images and deep learning methods to detect prevailing informal gravesites in highly vegetated land surfaces of southeastern China. The deep learning gravesite detection model is trained, validated and tested using 20,349 manually labeled samples and achieves an average precision (AP) of 0.905 during the testing stage (precision = 0.830, recall = 0.840, F1 score = 0.835). Using 31 million satellite image tiles, we detect nearly one million (996,074) clandestine gravesites over the land surfaces of Zhejiang, Fujian and Guangdong provinces, especially in forests and croplands. Further spatial attribution analysis suggests that the detected mass informal gravesites are closely related to gross domestic product (GDP) per capita, elevation, vegetation cover, climatic factors and the distances to rivers and coastlines. These findings and conclusions may provide meaningful references for gravesite occupied land use monitoring and management at regional to national scales.