Airborne dual-wavelength LiDAR data for classifying land cover

Cheng Kai Wang, Yi Hsing Tseng, Hone Jay Chu

研究成果: Article

29 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)700-715
頁數16
期刊Remote Sensing
6
發行號1
DOIs
出版狀態Published - 2013 十二月 1

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)

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