Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회지)

Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회)
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Downscaling of MODIS Land Surface Temperature to LANDSAT Scale Using Multi-layer Perceptron

  • Choe, Yu-Jeong (Dept. of Geoinformation Engineering, Sejong University) ;
  • Yom, Jae-Hong (Dept. of Geoinformation Engineering, Sejong University)
  • Received : 2017.08.01
  • Accepted : 2017.08.29
  • Published : 2017.08.31
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Abstract

Land surface temperature is essential for monitoring abnormal climate phenomena such as UHI (Urban Heat Islands), and for modeling weather patterns. However, the quality of surface temperature obtained from the optical space imagery is affected by many factors such as, revisit period of the satellite, instance of capture, spatial resolution, and cloud coverage. Landsat 8 imagery, often used to obtain surface temperatures, has a high resolution of 30 meters (100 meters rearranged to 30 meters) and a revisit frequency of 16 days. On the contrary, MODIS imagery can be acquired daily with a spatial resolution of about 1 kilometer. Many past attempts have been made using both Landsat and MODIS imagery to complement each other to produce an imagery of improved temporal and spatial resolution. This paper applied machine learning methods and performed downscaling which can obtain daily based land surface temperature imagery of 30 meters.

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References

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