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Estimating leaf functional traits by inversion of PROSPECT: Assessing leaf dry matter content and specific leaf area in mixed mountainous forest

Mohammed Ali, Abebe and Darvishzadeh, Roshanak and Skidmore, Andrew and van Duren, Iris and Heiden, Uta and Heurich, Marco (2016) Estimating leaf functional traits by inversion of PROSPECT: Assessing leaf dry matter content and specific leaf area in mixed mountainous forest. International Journal of Applied Earth Observation and Geoinformation, 45 (A), pp. 66-76. Elsevier. DOI: 10.1016/j.jag.2015.11.004 ISSN 0303-2434

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Official URL: http://www.sciencedirect.com/science/article/pii/S0303243415300507

Abstract

Assessments of ecosystem functioning rely heavily on quantification of vegetation properties. The search is on for methods that produce reliable and accurate baseline information on plant functional traits. In this study, the inversion of the PROSPECT radiative transfer model was used to estimate two functional leaf traits: leaf dry matter content (LDMC) and specific leaf area (SLA). Inversion of PROSPECT usually aims at quantifying its direct input parameters. This is the first time the technique has been used to indirectly model LDMC and SLA. Biophysical parameters of 137 leaf samples were measured in July 2013 in the Bavarian Forest National Park, Germany. Spectra of the leaf samples were measured using an ASD FieldSpec3 equipped with an integrating sphere. PROSPECT was inverted using a look-up table (LUT) approach. The LUTs were generated with and without using prior information. The effect of incorporating prior information on the retrieval accuracy was studied before and after stratifying the samples into broadleaf and conifer categories. The estimated values were evaluated using R2 and normalized root mean square error (nRMSE). 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 in the pooled samples. The use of prior information improved accuracy of the retrieved traits. 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 level by using remotely sensed data.

Item URL in elib:https://elib.dlr.de/110397/
Document Type:Article
Title:Estimating leaf functional traits by inversion of PROSPECT: Assessing leaf dry matter content and specific leaf area in mixed mountainous forest
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Mohammed Ali, AbebeFaculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500 AE Enschede, The NetherlandsUNSPECIFIED
Darvishzadeh, Roshanakr.darvish (at) utwente.nlUNSPECIFIED
Skidmore, Andrewa.k.skidmore (at) utwente.nlUNSPECIFIED
van Duren, IrisFaculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500 AE Enschede, The NetherlandsUNSPECIFIED
Heiden, UtaDLR OberpfaffenhofenUNSPECIFIED
Heurich, Marcobavarian forest national park, department of researchUNSPECIFIED
Date:March 2016
Journal or Publication Title:International Journal of Applied Earth Observation and Geoinformation
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:45
DOI :10.1016/j.jag.2015.11.004
Page Range:pp. 66-76
Publisher:Elsevier
ISSN:0303-2434
Status:Published
Keywords:Functional leaf traits; Radiative transfer model; PROSPECT; LDMC; SLA
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Fernerkundung der Landoberfläche (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface
Deposited By: Heiden, Dr.rer.nat. Uta
Deposited On:11 Jan 2017 10:39
Last Modified:06 Sep 2019 15:16

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