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Remote Sens. 2017, 9(12), 1243;

Improved DisTrad for Downscaling Thermal MODIS Imagery over Urban Areas

Geospatial Data Center for Education, Research and Development (GDC), Al-Aqsa University, Gaza Strip 0970, Palestine
Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel, Pleinlaan 2, BE-1050 Brussels, Belgium
IHE Delft Institute for Water Education, Westvest 7, 2611 AX Delft, The Netherlands
National Centre for Groundwater Research and Training (NCGRT), College of Science and Engineering, Flinders University, Sturt Road, Bedford Park South Australia 5042, GPO Box 2100, Adelaide, SA 5001, Australia
Author to whom correspondence should be addressed.
Received: 22 October 2017 / Revised: 20 November 2017 / Accepted: 26 November 2017 / Published: 1 December 2017
(This article belongs to the Special Issue Remote Sensing Image Downscaling)
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Spaceborne thermal sensors provide important physical parameters for urban studies. However, due to technical constraints, spaceborne thermal sensors yield a trade-off between their spatial and temporal resolution. The aims of this study are (1) to downscale the three originally low spatial resolution (960 m) Moderate Resolution Imaging Spectroradiometer (MODIS/Terra) land surface temperature image products (MOD11_L2, MOD11A1 and MOD11A2) to resolutions of 60, 90, 120, 240 and 480 m; and (2) to propose an improved version of the DisTrad method for downscaling the MODIS/Terra land surface temperature products over urban areas. The proposed improved DisTrad is based on a better parameterization of the original DisTrad residuals in urban areas. The improved resampling technique is based on a regression relationship between the residuals of the temperature estimation and the impervious percentage index. Validation of the improved DisTrad, the original DisTrad, and the uniformly disaggregated MODIS land surface temperature images (UniTrad) are performed by comparative analysis with a time-coincident Landsat 7 ETM+ thermal image. Statistical results indicate that the improved DisTrad method shows a higher correlation (R2 = 0.48) with the observed temperatures than the original DisTrad (R2 = 0.43) and a lower mean absolute error (MAE = 1.88 °C) than the original DisTrad (MAE = 2.07 °C). It is concluded that the improved DisTrad method has a stronger capability to downscale land surface temperatures in urban areas than the original DisTrad. View Full-Text
Keywords: land surface temperature; downscaling; disaggregation; impervious percentage; DisTrad; MODIS; Landsat 7 ETM+ land surface temperature; downscaling; disaggregation; impervious percentage; DisTrad; MODIS; Landsat 7 ETM+

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Essa, W.; Verbeiren, B.; Van der Kwast, J.; Batelaan, O. Improved DisTrad for Downscaling Thermal MODIS Imagery over Urban Areas. Remote Sens. 2017, 9, 1243.

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