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Remote Sens. 2014, 6(1), 700-715;

Airborne Dual-Wavelength LiDAR Data for Classifying Land Cover

Department of Geomatics, National Cheng Kung University, Tainan 701, Taiwan
Author to whom correspondence should be addressed.
Received: 8 October 2013 / Revised: 16 December 2013 / Accepted: 31 December 2013 / Published: 8 January 2014
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This study demonstrated the potential of using dual-wavelength airborne light detection and ranging (LiDAR) data to classify land cover. Dual-wavelength LiDAR data were acquired from two airborne LiDAR systems that emitted pulses of light in near-infrared (NIR) and middle-infrared (MIR) lasers. The major features of the LiDAR data, such as surface height, echo width, and dual-wavelength amplitude, were used to represent the characteristics of land cover. Based on the major features of land cover, a support vector machine was used to classify six types of suburban land cover: road and gravel, bare soil, low vegetation, high vegetation, roofs, and water bodies. Results show that using dual-wavelength LiDAR-derived information (e.g., amplitudes at NIR and MIR wavelengths) could compensate for the limitations of using single-wavelength LiDAR information (i.e., poor discrimination of low vegetation) when classifying land cover. View Full-Text
Keywords: dual-wavelength; LiDAR; land cover classification; support vector machine (SVM) dual-wavelength; LiDAR; land cover classification; support vector machine (SVM)
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Wang, C.-K.; Tseng, Y.-H.; Chu, H.-J. Airborne Dual-Wavelength LiDAR Data for Classifying Land Cover. Remote Sens. 2014, 6, 700-715.

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