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, PeterTitle 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
ATCORCopyright 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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