Prospect inversion for indirect estimation of leaf dry matter content and specific leaf area

Abebe Mohammed Ali, Roshanak Darvishzadeh, Andrew K. Skidmore, Iris van Duren, Uta Heiden, Marco Heurich

Research output: Contribution to journalConference paperpeer-review

7 Citations (Scopus)
42 Downloads (Pure)

Abstract

Quantification of vegetation properties plays an indispensable role in assessments of ecosystem function with leaf dry mater content (LDMC) and specific leaf area (SLA) being two important vegetation properties. Methods for fast, reliable and accurate measurement of LDMC and SLA are still lacking. In this study, the inversion of the PROSPECT radiative transfer model was used to estimate these two leaf parameters. Inversion of PROSPECT traditionally aims at quantifying its direct input parameters rather than identifying the parameters which can be derived indirectly from the input parameters. The technique has been tested here to indirectly model these parameters for the first time. Biophysical parameters such as leaf area, as well as fresh and dry weights of 137 leaf samples were measured during a field campaign in July 2013 in the mixed mountain forests of the Bavarian Forest National Park, Germany. Reflectance and transmittance of the leaf samples were measured using an ASD field spec III equipped with an integrating sphere. The PROSPECT model was inverted using a look-up table (LUT) approach for the NIR/SWIR region of the spectrum. The retrieved parameters were evaluated using their calculated R2 and normalized root mean square error (nRMSE) values with the field measurements. Among the retrieved variables the lowest nRMSE (0.0899) was observed for LDMC. For both traits higher R2 values (0.83 for LDMC and 0.89 for SLA) were discovered. The results indicate that the leaf traits studied can be quantified as accurately as the direct input parameters of PROSPECT. The strong correlation between the estimated traits and the NIR/SWIR region of the electromagnetic spectrum suggests that these leaf traits could be assessed at canopy and in the landscape by using hyperspectral remote sensing data.

Original languageEnglish
Pages (from-to)277-284
Number of pages8
JournalThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
VolumeXL-7/W3
DOIs
Publication statusPublished - 2015
Externally publishedYes
EventInternational Symposium on Remote Sensing of Environment (36th : 2015) - Berlin, Germany
Duration: 11 May 201515 May 2015
Conference number: 36th

Bibliographical note

Copyright the Author(s) 2015. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • Rradiative transfer model
  • PROSPECT
  • LDMC
  • SLA

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