Impact of Atmospheric Correction Methods Parametrization on Soil Organic Carbon Estimation Based on Hyperion Hyperspectral Data

被引:6
作者
Mruthyunjaya, Prajwal [1 ]
Shetty, Amba [1 ]
Umesh, Pruthviraj [1 ]
Gomez, Cecile [2 ,3 ]
机构
[1] Natl Inst Technol Karnataka, Dept Water Resources & Ocean Engn, Surathkal 575025, India
[2] INRA, IRD, UMR LISAH, IRD SupAgro, F-34060 Montpellier, France
[3] Indian Inst Sci, Indo French Cell Water Sci, IRD, Bangalore 560012, Karnataka, India
关键词
Hyperion; hyperspectral imagery; atmospheric corrections; soil organic carbon; ATCOR; FLAASH; mapping; SURFACE REFLECTANCE; NIR SPECTROSCOPY; PREDICTION; QUALITY; MATTER; PARAMETERS;
D O I
10.3390/rs14205117
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Visible Near infrared and Shortwave Infrared (VNIR/SWIR, 400-2500 nm) remote sensing data is becoming a tool for topsoil properties mapping, bringing spatial information for environmental modeling and land use management. These topsoil properties estimates are based on regression models, linking a key topsoil property to VNIR/SWIR reflectance data. Therefore, the regression model's performances depend on the quality of both topsoil property analysis (measured on laboratory over-ground soil samples) and Bottom-of-Atmosphere (BOA) VNIR/SWIR reflectance which are retrieved from Top-Of-Atmosphere radiance using atmospheric correction (AC) methods. This paper examines the sensitivity of soil organic carbon (SOC) estimation to BOA images depending on two parameters used in AC methods: aerosol optical depth (AOD) in the FLAASH (Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes) method and water vapor (WV) in the ATCOR (ATmospheric CORrection) method. This work was based on Earth Observing-1 Hyperion Hyperspectral data acquired over a cultivated area in Australia in 2006. Hyperion radiance data were converted to BOA reflectance using seven values of AOD (from 0.2 to 1.4) and six values of WV (from 0.4 to 5 cm), in FLAASH and ATCOR, respectively. Then a Partial Least Squares regression (PLSR) model was built from each Hyperion BOA data to estimate SOC over bare soil pixels. This study demonstrated that the PLSR models were insensitive to the AOD variation used in the FLAASH method, with R-cv(2) and RMSEcv of 0.79 and 0.4%, respectively. The PLSR models were slightly sensitive to the WV variation used in the ATCOR method, with R-cv(2) ranging from 0.72 to 0.79 and RMSEcv ranging from 0.41 to 0.47. Regardless of the AOD values, the PLSR model based on the best parametrization of the ATCOR model provided similar SOC prediction accuracy to PLSR models using the FLAASH method. Variation in AOD using the FLAASH method did not impact the identification of bare soil pixels coverage which corresponded to 82.35% of the study area, while a variation in WV using the ATCOR method provided a variation of bare soil pixels coverage from 75.04 to 84.04%. Therefore, this work recommends (1) the use of the FLAASH AC method to provide BOA reflectance values from Earth Observing-1 Hyperion Hyperspectral data before SOC mapping or (2) a careful selection of the WV parameter when using ATCOR.
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页数:24
相关论文
共 78 条
[1]  
Adler-Golden S., 1988, P 7 ANN JPL AIRB EAR, VVolume 97, P9
[2]  
[Anonymous], 2014, INT J AGR SCI
[3]  
[Anonymous], 2013, ATMOSPHERIC TOPOGRAP
[4]  
Ayoubi Shamsollah, 2011, Biomass and Remote Sensing of Biomass, P181
[5]   STANDARD NORMAL VARIATE TRANSFORMATION AND DE-TRENDING OF NEAR-INFRARED DIFFUSE REFLECTANCE SPECTRA [J].
BARNES, RJ ;
DHANOA, MS ;
LISTER, SJ .
APPLIED SPECTROSCOPY, 1989, 43 (05) :772-777
[6]  
BARTHOLOMEUS H, 2012, APPL ENVIRON SOIL SC, V2012, DOI DOI 10.1155/2012/241535
[7]   Influence of aerosol and surface reflectance variability on hyperspectral observed radiance [J].
Bassani, C. ;
Cavalli, R. M. ;
Antonelli, P. .
ATMOSPHERIC MEASUREMENT TECHNIQUES, 2012, 5 (06) :1193-1203
[8]   Critical review of chemometric indicators commonly used for assessing the quality of the prediction of soil attributes by NIR spectroscopy [J].
Bellon-Maurel, Veronique ;
Fernandez-Ahumada, Elvira ;
Palagos, Bernard ;
Roger, Jean-Michel ;
McBratney, Alex .
TRAC-TRENDS IN ANALYTICAL CHEMISTRY, 2010, 29 (09) :1073-1081
[9]   Quality assessment of several methods to recover surface reflectance using synthetic imaging spectroscopy data [J].
Ben-Dor, E ;
Kindel, B ;
Goetz, AFH .
REMOTE SENSING OF ENVIRONMENT, 2004, 90 (03) :389-404
[10]   The reflectance spectra of organic matter in the visible near-infrared and short wave infrared region (400-2500 nm) during a controlled decomposition process [J].
BenDor, E ;
Inbar, Y ;
Chen, Y .
REMOTE SENSING OF ENVIRONMENT, 1997, 61 (01) :1-15