“Each place has its own way of supporting its own inhabitants[1].”As the Chinese proverb indicates,geographic environments have great influences on human behavior,and humans are also gradually adapting to these envi...“Each place has its own way of supporting its own inhabitants[1].”As the Chinese proverb indicates,geographic environments have great influences on human behavior,and humans are also gradually adapting to these environments.This relationship is even more prominent in the rapidly changing present world(e.g.,urbanization,climate change,and interregional communication).展开更多
Building,as an integral aspect of human life,is vital in the domains of urban management and urban analysis.To facilitate large-scale urban planning applications,the acquisition of complete and reliable building data ...Building,as an integral aspect of human life,is vital in the domains of urban management and urban analysis.To facilitate large-scale urban planning applications,the acquisition of complete and reliable building data becomes imperative.There are a few publicly available products that provide a lot of building data,such as Microsoft and Open Street Map.However,in East Asia,due to the more complex distribution of buildings and the scarcity of auxiliary data,there is a lack of building data in these regions,hindering the large-scale application in East Asia.Some studies attempt to simulate large-scale building distribution information using incomplete local buildings footprints data through regression.However,the reliance on inaccurate buildings data introduces cumulative errors,rendering this simulation data highly unreliable,leading to limitations in achieving precise research in East Asian region.Therefore,we proposed a comprehensive large-scale buildings mapping framework in view of the complexity of buildings in East Asia,and conducted buildings footprints extraction in 2,897 cities across 5 countries in East Asia and yielded a substantial dataset of 281,093,433 buildings.The evaluation shows the validity of our building product,with an average overall accuracy of 89.63%and an F1 score of 82.55%.In addition,a comparison with existing products further shows the high quality and completeness of our building data.Finally,we conduct spatial analysis of our building data,revealing its value in supporting urban-related research.The data for this article can be downloaded from https://doi.org/10.5281/zenodo.8174931.展开更多
基金supported by the National Natural Science Foundation of China(42242102).
文摘“Each place has its own way of supporting its own inhabitants[1].”As the Chinese proverb indicates,geographic environments have great influences on human behavior,and humans are also gradually adapting to these environments.This relationship is even more prominent in the rapidly changing present world(e.g.,urbanization,climate change,and interregional communication).
基金supported in part by the National Key R&D Program of China under Grant 2022YFB3903402National Natural Science Foundation of China under Grant 42222106+1 种基金National Natural Science Foun-dation of China under Grant 61976234Fundamental Research Funds for the Central Universities,Sun Yat-sen University under Grant 22lgqb12.
文摘Building,as an integral aspect of human life,is vital in the domains of urban management and urban analysis.To facilitate large-scale urban planning applications,the acquisition of complete and reliable building data becomes imperative.There are a few publicly available products that provide a lot of building data,such as Microsoft and Open Street Map.However,in East Asia,due to the more complex distribution of buildings and the scarcity of auxiliary data,there is a lack of building data in these regions,hindering the large-scale application in East Asia.Some studies attempt to simulate large-scale building distribution information using incomplete local buildings footprints data through regression.However,the reliance on inaccurate buildings data introduces cumulative errors,rendering this simulation data highly unreliable,leading to limitations in achieving precise research in East Asian region.Therefore,we proposed a comprehensive large-scale buildings mapping framework in view of the complexity of buildings in East Asia,and conducted buildings footprints extraction in 2,897 cities across 5 countries in East Asia and yielded a substantial dataset of 281,093,433 buildings.The evaluation shows the validity of our building product,with an average overall accuracy of 89.63%and an F1 score of 82.55%.In addition,a comparison with existing products further shows the high quality and completeness of our building data.Finally,we conduct spatial analysis of our building data,revealing its value in supporting urban-related research.The data for this article can be downloaded from https://doi.org/10.5281/zenodo.8174931.
