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Using Landsat, MODIS, and a Biophysical Model to Evaluate LST in Urban CentersIn this paper, we assessed and compared land surface temperature (LST) in urban centers using data from Landsat, MODIS, and the Simple Biosphere model (SiB2). We also evaluated the sensitivity of the models LST to different land cover types, fractions (percentages), and emissivities compared to reference points derived from Landsat thermal data. This was demonstrated in three climatologically- and morphologically-different cities of Atlanta, GA, New York, NY, and Washington, DC. Our results showed that in these cities SiB2 was sensitive to both the emissivity and the land cover type and fraction, but much more sensitive to the latter. The practical implications of these results are rather significant since they imply that the SiB2 model can be used to run different scenarios for evaluating urban heat island (UHI) mitigation strategies. This study also showed that using detailed emissivities per land cover type and fractions from Landsat-derived data caused a convergence of the model results towards the Landsat-derived LST for most of the studied cases. This study also showed that SiB2 LSTs are closer in magnitude to Landsat-derived LSTs than MODIS-derived LSTs. It is important, however, to emphasize that both Landsat and MODIS LSTs are not direct observations and, as such, do not represent a ground truth. More studies will be needed to compare these results to in situ LST data and provide further validation.
Document ID
20170003281
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Al-Hamdan, Mohammad Z.
(Universities Space Research Association Huntsville, AL, United States)
Quattrochi, Dale A.
(NASA Marshall Space Flight Center Huntsville, AL United States)
Bounoua, Lahouari
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Lachir, Asia
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Zhang, Ping
(Maryland Univ. College Park, MD, United States)
Date Acquired
April 7, 2017
Publication Date
November 16, 2016
Publication Information
Publication: Remote Sensing
Publisher: MDPI
Volume: 8
Issue: 11
e-ISSN: 2072-4292
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN41093
Funding Number(s)
CONTRACT_GRANT: NNX17AE79A
CONTRACT_GRANT: NNM13AA43C
Distribution Limits
Public
Copyright
Other

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