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Urban Land Cover Classification With Airborne Hyperspectral Data: What Features to Use?

, , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 7 (10): 3998-4009 (2014)

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Automated Subpixel Surface Water Mapping from Heterogeneous Urban Environments Using Landsat 8 OLI Imagery., , , , and . Remote Sensing, 8 (7): 584 (2016)A New Genetic Method for Subpixel Mapping Using Hyperspectral Images., , , , , , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 9 (9): 4480-4491 (2016)Urban Land Cover Classification With Airborne Hyperspectral Data: What Features to Use?, , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 7 (10): 3998-4009 (2014)Precision and Bias Comparison Between Laser and Radar Altimetry Data in the Amundsen Sea Embayment and the Lambert-Amery System of Antarctica., , , , , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 12 (11): 4342-4350 (2019)Positional accuracy improvement: a comparative study in Shanghai, China., , , and . Int. J. Geogr. Inf. Sci., 25 (7): 1147-1171 (2011)An Improved Surface Slope Estimation Model Using Space-Borne Laser Altimetric Waveform Data Over the Antarctic Ice Sheet., , , , , , and . IEEE Geosci. Remote. Sens. Lett., (2022)An Anchor-Free Network With Density Map and Attention Mechanism for Multiscale Object Detection in Aerial Images., , , , , and . IEEE Geosci. Remote. Sens. Lett., (2022)LASDU: A Large-Scale Aerial LiDAR Dataset for Semantic Labeling in Dense Urban Areas., , , , , , , , and . ISPRS Int. J. Geo Inf., 9 (7): 450 (2020)Optimized Sample Selection in SVM Classification by Combining with DMSP-OLS, Landsat NDVI and GlobeLand30 Products for Extracting Urban Built-Up Areas., , , , , and . Remote. Sens., 9 (3): 236 (2017)A Multi-Scale Superpixel-Guided Filter Feature Extraction and Selection Approach for Classification of Very-High-Resolution Remotely Sensed Imagery., , , , , , and . Remote. Sens., 12 (5): 862 (2020)