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Remote Sens. 2016, 8(11), 952; doi:10.3390/rs8110952

Using Landsat, MODIS, and a Biophysical Model to Evaluate LST in Urban Centers

1
Universities Space Research Association at NASA Marshall Space Flight Center, National Space Science and Technology Center, Huntsville, AL 35805, USA
2
Earth Science Office at NASA Marshall Space Flight Center, National Space Science and Technology Center, Huntsville, AL 35805, USA
3
Biospheric Sciences Laboratory, NASA’s Goddard Space Flight Center, Greenbelt, MD 20771, USA
4
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20742, USA
5
Science System Applications Inc., Lanham, MD 20706, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Janet Nichol, James Campbell, Richard Müller and Prasad S. Thenkabail
Received: 13 August 2016 / Revised: 23 September 2016 / Accepted: 19 October 2016 / Published: 16 November 2016
(This article belongs to the Special Issue Multi-Sensor and Multi-Data Integration in Remote Sensing)
View Full-Text   |   Download PDF [8288 KB, uploaded 16 November 2016]   |  

Abstract

In 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 model’s 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. View Full-Text
Keywords: land surface temperature; Landsat; MODIS; SiB2 model land surface temperature; Landsat; MODIS; SiB2 model
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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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MDPI and ACS Style

Al-Hamdan, M.Z.; Quattrochi, D.A.; Bounoua, L.; Lachir, A.; Zhang, P. Using Landsat, MODIS, and a Biophysical Model to Evaluate LST in Urban Centers. Remote Sens. 2016, 8, 952.

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