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Uncertainties of LAI estimation from satellite imaging due to atmospheric correction

Mannschatz, Theresa and Pflug, Bringfried and Borg, Erik and Feger, K.-H. and Dietrich, P. (2014) Uncertainties of LAI estimation from satellite imaging due to atmospheric correction. Remote Sensing of Environment, 153, pp. 24-39. Elsevier. DOI: 10.1016/j.rse.2014.07.020 ISSN 0034-4257

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Official URL: http://www.sciencedirect.com/science/article/pii/S0034425714002697

Abstract

Leaf area index (LAI) is a plant development indicator that as an input parameter strongly influences several relevant hydrological processes represented in Soil–Vegetation–Atmosphere-Transfer (SVAT) models. Generally, temporal measurement or monitoring of LAI is challenging or even impossible in remote areas. High-temporal resolution remote sensing imaging can be used to estimate LAI from vegetation indices calculated from band ratios. This paper shows the sensitivity of LAI estimation from satellite imaging to atmospheric correction (with ATCOR) and evaluates the effects of LAI uncertainty on water balance modelling. LAI as a SVAT model input parameter was estimated based on the empirical relationship between field measurements, and the vegetation indices NDVI (Normalized-Difference Vegetation Index), SAVI (Soil-Adjusted Vegetation Index) and SARVI (Soil–Atmosphere Resistant Vegetation Index) for six RapidEye images obtained between 2011 and 2012. In summary, we found that the ATCOR parameter ‘visibility’ has the strongest influence on LAI estimation. Likewise, atmospherically corrected successive images gathered from around the same time period had low LAI differences (mean absolute difference of 0.09 ± 0.08) on overlapping image areas. This uncertainty is negligible in SVAT modelling in most cases, thereby allowing mosaicked successive atmospherically corrected images to be used. We showed that LAI uncertainties arising from atmospheric correction (ATCOR 3) can translate into small (LAI ± 0.1 ≈ evapotranspiration ± 0.9%, interception ± 2.5%, evaporation ± 3.3%, transpiration ± 0.7%) to moderate (LAI ± 0.3 ≈ evapotranspiration ± 4.1%, interception ± 7.5%, evaporation ± 9.9%, transpiration ± 2.4%) SVAT model uncertainty.

Item URL in elib:https://elib.dlr.de/90580/
Document Type:Article
Title:Uncertainties of LAI estimation from satellite imaging due to atmospheric correction
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Mannschatz, TheresaUNU-FLORES, GermanyUNSPECIFIED
Pflug, Bringfriedbringfried.pflug (at) dlr.deUNSPECIFIED
Borg, Erikerik.borg (at) dlr.deUNSPECIFIED
Feger, K.-H.TU DresdenUNSPECIFIED
Dietrich, P.UFZ, GermanyUNSPECIFIED
Date:August 2014
Journal or Publication Title:Remote Sensing of Environment
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:153
DOI :10.1016/j.rse.2014.07.020
Page Range:pp. 24-39
Editors:
EditorsEmail
Bauer, MarvinUniversity of Minnesota, St. Paul, Minnesota, USA
Publisher:Elsevier
ISSN:0034-4257
Status:Published
Keywords:LAI estimation; Hydrological modelling; Uncertainty analysis; Sensitivity analysis; Satellite imaging; Atmospheric correction; ATCOR
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), R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Berlin-Adlershof , Neustrelitz
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
German Remote Sensing Data Center > National Ground Segment
Deposited By:INVALID USER
Deposited On:22 Sep 2014 08:41
Last Modified:31 Jul 2019 19:47

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