Estimation of subpixel MODIS water temperature near coastlines using the SWTI algorithm

Abstract Satellite derived water surface temperature maps are widely used in many environmental studies and applications. The Moderate Resolution Imaging Spectroradiometer (MODIS) is among the widely used sensors in this field and sea surface temperature (SST) is one of the standard quantities derived from MODIS imagery. However, MODIS SST maps have limited applications in near-shore and coastal environments due to inadequate spatial resolution of 1 km. This problem means that the MODIS pixels closer than 1 km from the shore are mixed pixels, i.e. they include by both water and land, and must be discarded from the SST map. In this work SWTI (Sharpening Water Thermal Imagery) methods were applied to MODIS thermal imagery for the first time. The information required by SWTI regarding cover fractions and perpendicular vegetation index was obtained from the MODIS images in the Visible–Near Infrared bands at a spatial resolution of 250 m. In this way, the SST MODIS maps were extended to a minimum distance of 250 m from the shore. The SWTI results were evaluated using as a reference the SST computed from two ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) images acquired simultaneously to the MODIS images and covering the same areas. The applied validation methodology provides an evaluation of the deviations introduced by SWTI separated from the pre-existing differences between MODIS SST and ASTER SST upscaled to 250 m. For sea coast environments, SWTI was able to compute the SST of more than 80% of the pixels close to the shore at a spatial resolution of 250 m. This represents an increase of 67% compared to the number of pixels obtainable using a simple downscaling method based on polynomial interpolation; in areas with lagoons and estuaries the increases were + 70% and + 60% respectively. The ASTER SST comparison showed that the SST bias and the unsystematic deviation introduced by SWTI were ∆S ≤ 0.45 K and σ(ϵS) ≤ 0.88 K respectively, corresponding to a total deviation TD ≤ 0.97 K. SWTI is written in the IDL language and could be adapted for automatic application to MODIS images.

[1]  Paul V. Zimba,et al.  Remote Sensing Techniques to Assess Water Quality , 2003 .

[2]  Simon J. Hook,et al.  Generating Consistent Land Surface Temperature and Emissivity Products Between ASTER and MODIS Data for Earth Science Research , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Sergio Teggi,et al.  Inspecting MIVIS capability to retrieve chemical–mineralogical information: evaluation and analysis of VNIR–SWIR data acquired on a volcanic area , 2004 .

[4]  A. Huete A soil-adjusted vegetation index (SAVI) , 1988 .

[5]  V. Klemas Remote Sensing Techniques for Studying Coastal Ecosystems: An Overview , 2010 .

[6]  Martha C. Anderson,et al.  Upscaling ground observations of vegetation water content, canopy height, and leaf area index during SMEX02 using aircraft and Landsat imagery , 2004 .

[7]  Ruiliang Pu,et al.  Estimation of Subpixel Land Surface Temperature Using an Endmember Index Based Technique: A Case Examination on ASTER and MODIS Temperature Products Over a Heterogeneous Area , 2011 .

[8]  Dimitar Ouzounov,et al.  Terra and Aqua MODIS products available from NASA GES DAAC , 2004 .

[9]  William P. Kustas,et al.  A vegetation index based technique for spatial sharpening of thermal imagery , 2007 .

[10]  Joan M. Galve,et al.  Temperature and emissivity separation from ASTER data for low spectral contrast surfaces , 2007 .

[11]  Paul D. Colaizzi,et al.  Utility of thermal sharpening over Texas high plains irrigated agricultural fields , 2007 .

[12]  R. Richter,et al.  Correction of satellite imagery over mountainous terrain. , 1998, Applied optics.

[13]  L. Wald,et al.  Fusion of satellite images of different spatial resolutions: Assessing the quality of resulting images , 1997 .

[14]  Simon J. Hook,et al.  Sub-pixel water temperature estimation from thermal-infrared imagery using vectorized lake features , 2008 .

[15]  R. Schowengerdt,et al.  Early results on the characterization of the Terra MODIS spatial response , 2002 .

[16]  Shuichi Rokugawa,et al.  A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images , 1998, IEEE Trans. Geosci. Remote. Sens..

[17]  Douglas C. Montgomery,et al.  Applied Statistics and Probability for Engineers, Third edition , 1994 .

[18]  F. Despini,et al.  Analysis of temperature maps of waterbodies obtained from ASTER TIR images , 2013 .

[19]  A. J. Richardsons,et al.  DISTINGUISHING VEGETATION FROM SOIL BACKGROUND INFORMATION , 1977 .

[20]  Sergio Teggi,et al.  Improvement of the spatial resolution of MODIS coastal waters thermal mapping , 2011, Remote Sensing.

[21]  X. Song,et al.  Study on component temperatures inversion using satellite remotely sensed data , 2007 .

[22]  K. Masuda,et al.  Emissivity of pure and sea waters for the model sea surface in the infrared window regions , 1988 .

[23]  Martha C. Anderson,et al.  Estimating subpixel surface temperatures and energy fluxes from the vegetation index-radiometric temperature relationship , 2003 .

[24]  Yasushi Yamaguchi,et al.  Scaling of land surface temperature using satellite data: A case examination on ASTER and MODIS products over a heterogeneous terrain area , 2006 .

[25]  Simon J. Hook,et al.  Absolute Radiometric In-Flight Validation of Mid Infrared and Thermal Infrared Data From ASTER and MODIS on the Terra Spacecraft Using the Lake Tahoe, CA/NV, USA, Automated Validation Site , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[26]  Sergio Teggi,et al.  A technique for spatial sharpening of thermal imagery of coastal waters and of watercourses , 2012 .

[27]  Ji Zhou,et al.  Disaggregation of remotely sensed land surface temperature: Literature survey, taxonomy, issues, and caveats , 2013 .

[28]  Sergio Teggi,et al.  TM and IRS-1C-PAN data fusion using multiresolution decomposition methods based on the 'a tròus' algorithm , 2003 .

[29]  Hermann Kaufmann,et al.  On the application of the MODTRAN4 atmospheric radiative transfer code to optical remote sensing , 2009 .

[30]  Martha C. Anderson,et al.  Utility of thermal image sharpening for monitoring field‐scale evapotranspiration over rainfed and irrigated agricultural regions , 2008 .