3D Habitat Mapping Using High-Resolution Optical Satellite and Lidar Data
Meisam Amani (Wood Environment and Infrastructure Solutions)
Fatemeh Foroughnia (TU Delft - Geo-engineering)
Armin Moghimi (Leibniz University of Hannover)
Sahel Mahdavi (Wood Environment and Infrastructure Solutions)
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Abstract
Remote sensing datasets are great resources to map habitat types. In this study, 3D habitat maps were generated using high-resolution multispectral imagery and a LiDAR-derived digital surface model (DSM). Two study areas in the United Kingdom (UK) were selected to investigate the potential of the developed models in habitat classification. The overall classification accuracies for the two study areas were high (91% and 82%), indicating the satisfactory performance of the developed approach for habitat mapping in the study areas. Overall, it was observed that a synergy of high-resolution multi-spectral imagery and LiDAR data could provide reliable 3D information on habitat types.