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Hyperspectral lidar in non-destructive 4D monitoring of climate variables

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives (2014) 40(7) 109-111
DOI: 10.5194/isprsarchives-XL-7-109-2014
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Abstract

The first applications of a prototype 8-channel full waveform active hyperspectral lidar (HSL) show a possibility to determine various target 3D characteristics with remote observations. The results open up a prospect for four-dimensional (4D - a three dimensional target representation with time as a fourth dimension) monitoring of important climate variables, such as those related to tree physiology or snow pollution.

Figures

  • Figure 1. The pine sample before the measurement in April 2013. The white spherical reference targets visible in the image were used for the co-registration of scans.
  • Figure 4. A 3D distribution of the Modified Triangular Vegeation Index 2 (MTVI2) over the pine sample. This index is correlated to the leaf area index (LAI).
  • Figure 2. HSL time series (growing season 2013) of NDVI plotted over the HSL point cloud shows the new growth in spring as well as dying and falloff of the old parts.
  • Figure 3. A 3D distribution of Modified Chlorophyll Absorption Ratio Index (MCARI) over the pine sample.

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CITATION STYLE

APA

Kaasalainen, S., Hakala, T., Nevalainen, O., Puttonen, E., & Anttila, K. (2014). Hyperspectral lidar in non-destructive 4D monitoring of climate variables. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives (Vol. 40, pp. 109–111). International Society for Photogrammetry and Remote Sensing. https://doi.org/10.5194/isprsarchives-XL-7-109-2014

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