isprs archives XLI B3 167 2016
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In this paper, the performances of biomass estimation using airborne LiDAR and Hyperspectral data will be explored in a sub-tropical forest of Southwest China.. STUDY SITE AND DATA
We extract the feature by the Caffenet from semantic regions cropped from LIDAR intensity images, and we select top K similar regions cropped from training
• was shown to match the North, East and Down position computed using the ASB network Carrier Phase DGNSS processing for 100 airborne data sets to an accuracy of 0.021m, 0.020
While in image matching method, filtering DSM to obtain DTM using LIDAR processing approach in photogrammetric processes, especially when meet heavy forestry area,
Urban scene classification based on aerial LiDAR points can guide surface reconstruction techniques in urban modeling, piecewise planar surfaces are used for precise
KEY WORDS: lidar, multispectral imagery, fusion, feature extraction, supervised classification, energy minimisation, forest stand delineation, tree
The workflow of airborne LiDAR point cloud data and synchronous digital image co-registration based on combined adjustment is shown in Figure. 1) Point cloud
In object-based classification, the meaningful features are based on similar spectral or spatial properties of the remotely sensed imagery or the LiDAR data.. Applying an
