Uncertainties of LAI Estimation from Satellite Imaging due to Atmospheric Correction

Mannschatz, Theresa, Borg, Erik, Pflug, Bringfried, Feger, Karl-Heinz and Dietrich, Peter, (2014). Uncertainties of LAI Estimation from Satellite Imaging due to Atmospheric Correction. Remote Sensing of Environment, 153 24-39

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  • Sub-type Journal article
    Author Mannschatz, Theresa
    Borg, Erik
    Pflug, Bringfried
    Feger, Karl-Heinz
    Dietrich, Peter
    Title Uncertainties of LAI Estimation from Satellite Imaging due to Atmospheric Correction
    Appearing in Remote Sensing of Environment
    Volume 153
    Publication Date 2014-10
    Place of Publication Oxford
    Publisher Elsevier Inc.
    Start page 24
    End page 39
    Language eng
    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.
    Keyword LAI estimation
    Hydrological modelling
    Uncertainty analysis
    Sensitivity analysis
    Satellite imaging
    Atmospheric correction
    Copyright Holder Elsevier Inc. 
    Copyright Year 2014
    Copyright type All rights reserved
    ISSN 00344257
    DOI 10.1016/j.rse.2014.07.020
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    Created: Mon, 14 Sep 2015, 22:08:41 JST by Claudia Matthias on behalf of UNU FLORES