Comparing different profiles to characterize the atmosphere for three MODIS TIR bands

Abstract Accurate land surface temperature (LST) retrievals from sensors aboard orbiting satellites are dependent on the corresponding atmospheric correction, especially in the thermal infrared (TIR) spectral domain (8–14 μm). To remove the atmospheric effects from at-sensor measured radiance in the TIR range it is needed to characterize the atmosphere by means of three specific variables: the upwelling path and the hemispherical downwelling radiances plus the atmospheric transmissivity. Those variables can be derived from the previous knowledge of vertical atmospheric profiles of air temperature and relative humidity at different geo-potential heights and pressures. In this work, the above mentioned atmospheric variables were analyzed for three specific weather station sites located in Spain, at three different altitudes. These variables were calculated with atmospheric profiles retrieved from three different sources: The National Centers for Environmental Prediction (NCEP) web-tool atmospheric profiles calculator, the MODIS (MOD07) product and the radiosoundings available on the web of the University of Wyoming (WYO), which are launched by the Agencia Estatal de Meteorologia (AEMET), in the particular case of Spain. Atmospheric profiles from 2010 to 2013 were obtained to carry out the present study. Results from comparison of these three different atmospheric profiles show that the NCEP profiles characterize the atmosphere in a better manner than MOD07. Average result values of the three MODIS spectral bands 29, 31 and 32 show a BIAS of 0.06 Wm − 2  μm − 1  sr − 1 and RMSE of ± 0.2 Wm − 2  μm − 1  sr − 1 for upwelling radiance, a BIAS of 0.13 Wm − 2  μm − 1  sr − 1 and RMSE of ± 0.3 Wm − 2  μm − 1  sr − 1 for the donwelling radiance and a BIAS of − 0.008 and RMSE of ± 0.03 for the atmospheric transmissivity. In terms of simulated LST, these errors yield a deviation of ± 0.9 K when applying a single-channel method.

[1]  V. Caselles,et al.  Comparison between different sources of atmospheric profiles for land surface temperature retrieval from single channel thermal infrared data , 2012 .

[2]  Juan de la Riva,et al.  Assessment of Methods for Land Surface Temperature Retrieval from Landsat-5 TM Images Applicable to Multiscale Tree-Grass Ecosystem Modeling , 2014, Remote. Sens..

[3]  Hua Li,et al.  Evaluation of the NCEP and MODIS Atmospheric Products for Single Channel Land Surface Temperature Retrieval With Ground Measurements: A Case Study of HJ-1B IRS Data , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[4]  V. Caselles Determination of the surface temperature by remote sensing , 2010 .

[5]  G. Hulley,et al.  Thermal-based techniques for land cover change detection using a new dynamic MODIS multispectral emissivity product (MOD21) , 2014 .

[6]  José Luis Sánchez,et al.  Synoptic environment, mesoscale configurations and forecast parameters for hailstorms in Southwestern Europe , 2013 .

[7]  García-Santos Determination of the surface temperature by remote sensing , 2010 .

[8]  Geng-Ming Jiang,et al.  Retrieval of Sea and Land Surface Temperature From SVISSR/FY-2C/D/E Measurements , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Ji Zhou,et al.  Intercomparison of methods for estimating land surface temperature from a Landsat-5 TM image in an arid region with low water vapour in the atmosphere , 2012 .

[10]  V. Caselles,et al.  Estimation of atmospheric water vapour content from direct measurements of radiance in the thermal infrared region , 2012 .

[11]  John R. Schott,et al.  Validation of a web-based atmospheric correction tool for single thermal band instruments , 2005, SPIE Optics + Photonics.

[12]  H. Huntrieser,et al.  Comparison of Traditional and Newly Developed Thunderstorm Indices for Switzerland , 1997 .

[13]  Juan C. Jiménez-Muñoz,et al.  Atmospheric correction of optical imagery from MODIS and Reanalysis atmospheric products , 2010 .

[14]  Eva Rubio,et al.  Assessing crop coefficients of sunflower and canola using two-source energy balance and thermal radiometry , 2014 .

[15]  R. López-Urrea,et al.  Determining water use of sorghum from two-source energy balance and radiometric temperatures , 2011 .