Remote Sensing (Dec 2020)

Improvement and Impacts of Forest Canopy Parameters on Noah-MP Land Surface Model from UAV-Based Photogrammetry

  • Ming Chang,
  • Shengjie Zhu,
  • Jiachen Cao,
  • Bingyin Chen,
  • Qi Zhang,
  • Weihua Chen,
  • Shiguo Jia,
  • Padmaja Krishnan,
  • Xuemei Wang

DOI
https://doi.org/10.3390/rs12244120
Journal volume & issue
Vol. 12, no. 24
p. 4120

Abstract

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Taking a typical forest’s underlying surface as our research area, in this study, we employed unmanned aerial vehicle (UAV) photogrammetry to explore more accurate canopy parameters including the tree height and canopy radius, which were used to improve the Noah-MP land surface model, which was conducted in the Dinghushan Forest Ecosystem Research Station (CN-Din). While the canopy radius was fitted as a Burr distribution, the canopy height of the CN-Din forest followed a Weibull distribution. Then, the canopy parameter distribution was obtained, and we improved the look-up table values of the Noah-MP land surface model. It was found that the influence on the simulation of the energy fluxes could not be negligible, and the main influence of these canopy parameters was on the latent heat flux, which could decrease up to −11% in the midday while increasing up to 15% in the nighttime. Additionally, this work indicated that the description of the canopy characteristics for the land surface model should be improved to accurately represent the heterogeneity of the underlying surface.

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