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Urban green volume is an important indicator for analyzing urban vegetation structure, ecological evaluation, and green-economic estimation. This paper proposes an object-based method for automated estimation of urban green volume combining three-dimensional (3D) information from airborne Light Detection and Ranging (LiDAR) data and vegetation information from high resolution remotely sensed images...
Greenhouse gas data collected by different institutions throughout the world have significant scientific values for global climate change studies. Due to the diversity of data formats and different specifications of data access interfaces, most of those data should be first downloaded onto a local machine before they can be used. To overcome this limitation, we present a geospatial web portal for...
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