European Journal of Remote Sensing (Dec 2022)

Preliminary verification of hyperspectral LiDAR covering VIS-NIR-SWIR used for objects classification

  • Haibin Sun,
  • Zhen Wang,
  • Yuwei Chen,
  • Wenxin Tian,
  • Wenjing He,
  • Haohao Wu,
  • Huijing Zhang,
  • Lingli Tang,
  • Changhui Jiang,
  • Jianxin Jia,
  • Zhiyong Duan,
  • Hui Zhou,
  • Eetu Puttonen,
  • Juha Hyyppä

DOI
https://doi.org/10.1080/22797254.2022.2056519
Journal volume & issue
Vol. 55, no. 1
pp. 291 – 303

Abstract

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Hyperspectral LiDAR (HSL) has been utilised as an efficacious technique in objects classification and recognition based on its synchronously obtaining spectral and spatial information. However, the spectral information obtained by most of the developed HSL was in the visible and near-infrared range (VNIR, 400–1000 nm). Whereas spectral information in a longer wavelength range showed more useful for classification and detection, such as detecting vegetation water content. This paper proposed and tested an eight-channel HSL prototype covering visible to near-infrared and even short-wavelength infrared (VIS-NIR-SWIR, 450–1460 nm) based on a Super-continuum (SC) laser. System calibration, range precision and spectral profiles experiments were carried out to test the HSL prototype. The spectral profiles collected by the HSL are consistent with those acquired by the commercial spectrometer (SVC© HR-1024). And these spectral profiles of plants, textiles, camouflage objects, and ore samples collected by the HSL, especially those in the SWIR range, can effectively reveal the health status of the plants, and classify the manufacturing materials and ore species. The unique characteristics of spectral profiles covering VIS-NIR-SWIR promote the HSL shows the potential applications on objects classification related to vegetation, mining and surveillance.

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