Canopy leaf water content estimated using terrestrial LiDAR

Xi Zhu, Tiejun Wang, A.K. Skidmore, R. Darvishzadeh, K.O. Niemann, Jing Liu

Research output: Contribution to journalArticleAcademicpeer-review

29 Citations (Scopus)

Abstract

Leaf water content (LWC) within a plant canopy plays an important role in light penetration and scattering, thus affecting reflectance simulation with radiative transfer models. It is also of key importance for the distribution of other plant biochemical parameters, fire propagation simulation and habitat suitability evaluation. Although passive remote sensing techniques have been widely applied to estimate LWC, they are unable to retrieve the LWC vertical distribution within a canopy. In this paper we investigated the applicability of the full-waveform terrestrial laser scanning data (TLS) to estimate the LWC vertical distribution within the canopy of individual plants. A modified skewed Gaussian function that accommodates the nonlinear nature of the system was proposed to perform a decomposition on the full-waveform data. The amplitude, the backscatter cross-section, and the backscatter coefficient were assessed to estimate LWC, respectively. Our results showed that the backscatter coefficient had the strongest correlation with LWC (R2 = 0.66) for four plant species after an incidence angle correction. Good agreements were achieved between the predicted vertical profile of LWC and the measured vertical profile of LWC with a mean RMSE (root mean square error) value of 0.001 g/cm2 and a mean MAPE (mean absolute percent error) value of 4.46%. However, the performance of LWC vertical profile estimation varied across species, suggesting the influence of leaf structure other than LWC on waveform features, which should be considered in future studies. Nevertheless, our study successfully demonstrated the feasibility of retrieving LWC vertical distribution within plant canopy from a full-waveform terrestrial laser scanner.
Original languageEnglish
Pages (from-to)152-162
JournalAgricultural and forest meteorology
Volume232
DOIs
Publication statusPublished - 2017

Keywords

  • METIS-317781
  • ITC-ISI-JOURNAL-ARTICLE

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