Spatio-temporal-spectral observation model for urban remote sensing

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.

Spatio-temporal-spectral-angular observation model that integrates observations from UAV and mobile mapping vehicle for better urban mapping

In a complex urban scene,observation from a single sensor unavoidably leads to voids in observations,failing to describe urban objects in a comprehensive manner.In this paper,we propose a spatio-temporal-spectral-angular observation model to integrate observations from UAV and mobile mapping vehicle platform,realizing a joint,coordinated observation operation from both air and ground.We develop a multi-source remote sensing data acquisition system to effectively acquire multi-angle data of complex urban scenes.Multi-source data fusion solves the missing data problem caused by occlusion and achieves accurate,rapid,and complete collection of holographic spatial and temporal information in complex urban scenes.We carried out an experiment on Baisha Town,Chongqing,China and obtained multi-sensor,multi-angle data from UAV and mobile mapping vehicle.We first extracted the point cloud from UAV and then integrated the UAV and mobile mapping vehicle point cloud.The inte-grated results combined both the characteristics of UAV and mobile mapping vehicle point cloud,confirming the practicability of the proposed joint data acquisition platform and the effectiveness of spatio-temporal-spectral-angular observation model.Compared with the observation from UAV or mobile mapping vehicle alone,the integrated system provides an effective data acquisition solution toward comprehensive urban monitoring.