Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolu...Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolution,high spatial resolution,and high spectral resolution.To the best of our knowledge,however,no satellite owns all the above character-istics.Thus,it is necessary to coordinate data from existing remote sensing satellites to meet the needs of urban observation.In this study,we abstracted the urban remote sensing observation process and proposed an urban spatio-temporal-spectral observation model,filling the gap of no existing urban remote sensing framework.In this study,we present four applications to elaborate on the specific applications of the proposed model:1)a spatiotemporal fusion model for synthesizing ideal data,2)a spatio-spectral observation model for urban vegetation biomass estimation,3)a temporal-spectral observation model for urban flood mapping,and 4)a spatio-temporal-spectral model for impervious surface extraction.We believe that the proposed model,although in a conceptual stage,can largely benefit urban observation by providing a new data fusion paradigm.展开更多
基金This work is supported by the National Key Research and Development Program of China[grant number 2018YFB2100501]the Key Research and Development Program of Yunnan province in China[grant number 2018IB023]+2 种基金the Research Project from the Ministry of Natural Resources of China[grant number 4201⁃⁃240100123]the National Natural Science Foundation of China[grant numbers 41771452,41771454,41890820,and 41901340]the Natural Science Fund of Hubei Province in China[grant number 2018CFA007].
文摘Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolution,high spatial resolution,and high spectral resolution.To the best of our knowledge,however,no satellite owns all the above character-istics.Thus,it is necessary to coordinate data from existing remote sensing satellites to meet the needs of urban observation.In this study,we abstracted the urban remote sensing observation process and proposed an urban spatio-temporal-spectral observation model,filling the gap of no existing urban remote sensing framework.In this study,we present four applications to elaborate on the specific applications of the proposed model:1)a spatiotemporal fusion model for synthesizing ideal data,2)a spatio-spectral observation model for urban vegetation biomass estimation,3)a temporal-spectral observation model for urban flood mapping,and 4)a spatio-temporal-spectral model for impervious surface extraction.We believe that the proposed model,although in a conceptual stage,can largely benefit urban observation by providing a new data fusion paradigm.