4.7 Article

Improved DisTrad for Downscaling Thermal MODIS Imagery over Urban Areas

Journal

REMOTE SENSING
Volume 9, Issue 12, Pages -

Publisher

MDPI AG
DOI: 10.3390/rs9121243

Keywords

land surface temperature; downscaling; disaggregation; impervious percentage; DisTrad; MODIS; Landsat 7 ETM+

Funding

  1. ERASMUS MUNDUS Scholarship programme based on the bilateral agreement between Al-AQSA University (Palestine)
  2. EU
  3. Belgian Science Policy Office [SR/00/105]

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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 (R-2 = 0.48) with the observed temperatures than the original DisTrad (R-2 = 0.43) and a lower mean absolute error (MAE = 1.88 degrees C) than the original DisTrad (MAE = 2.07 degrees 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.

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