China's State Council has decided to conduct the first national comprehensive risk survey of natural disasters from 2020 to 2022. In view of the problems such as large data base and extraction difficulty of disaster bearing bodies in the census work,a complete disaster bearing body extraction workflow which combines big data with deep learning technol-ogies is explored and practiced based on the Domestic MAP-GIS software platform,and an applicable deep learning disas-ter bearing body extraction tool is formed. Thus,it further strengthens the interpretation and analysis ability of complex data in spatial information field.To provide authoritative disas-ter risk information and scientific decision-making basis for ef-fectively carrying out natural disaster prevention and emergen-cy management,and ensuring sustainable socio-economic de-velopment.
维普
万方数据