| Title | A multi-window texture classification and object-oriented feature extraction method with airborne LiDAR products |
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| Author | Zhu, X; Toutin, T |
| Source | IEEE International Geoscience and Remote Sensing Symposium proceedings 6049941, 2011 p. 3370-3373, https://doi.org/10.1109/IGARSS.2011.6049941 |
| Year | 2011 |
| Alt Series | Natural Resources Canada, Contribution Series 20181552 |
| Publisher | IEEE |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Subjects | geophysics; remote sensing |
| Program | Canada Centre for Remote Sensing Divsion |
| Released | 2011 07 01 |
| Abstract | High accurate airborne Light Detection and Range (LiDAR) is widely accepted as one kind of survey data sources. However, with the LiDAR products including Digital Elevation Model (DEM), Digital Surface
Model (DSM) and intensity image, land use classifications and feature extractions were generally combined with optical images including satellite images or aerial photos using relative segmentations and feature extraction algorithms. In this paper, a
multi-window texture classification and object-oriented feature extraction method is proposed using only airborne LiDAR products. Based on the experimental analysis and accuracy statistics, it is an efficient attempt in land cover classification with
airborne LiDAR products. |
| GEOSCAN ID | 311907 |
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