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Remote Sens. 2016, 8(4), 274; doi:10.3390/rs8040274

Assessing the Capability of a Downscaled Urban Land Surface Temperature Time Series to Reproduce the Spatiotemporal Features of the Original Data

1
Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Athens GR-15236, Greece
2
School of Chemical Engineering, National Technical University of Athens, Athens GR-15780, Greece
3
Center for Earth System Research and Sustainability, University of Hamburg, Hamburg DE-20146, Germany
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: James A. Voogt, Simone Kotthaus, Richard Müller and Prasad S. Thenkabail
Received: 21 January 2016 / Revised: 3 March 2016 / Accepted: 21 March 2016 / Published: 25 March 2016
View Full-Text   |   Download PDF [6190 KB, uploaded 25 March 2016]   |  

Abstract

The downscaling of frequently-acquired geostationary Land Surface Temperature (LST) data can compensate the lack of high spatiotemporal LST data for urban climate studies. In order to be usable, the generated datasets must accurately reproduce the spatiotemporal features of the coarse-scale LST time series with greater spatial detail. This work concerns this issue and exploits the high temporal resolution of the data to address it. Specifically, it assesses the accuracy, correct pattern formation and the spatiotemporal inter-relationships of an urban three-month-long downscaled geostationary LST time series. The results suggest that the downscaling process operated in a consistent manner and preserved the radiometry of the original data. The exploitation of the data inter-relationships for evaluation purposes revealed that the downscaled time series reproduced the smooth diurnal cycle, but the autocorrelation of the downscaled data was higher than the original coarse-scale data. Overall, the evaluation process showed that the generation of high spatiotemporal LST data for urban areas is very challenging, and to deem it successful, it is mandatory to assess the temporal evolution of the urban thermal patterns. The results suggest that the proposed tests can facilitate the evaluation process. View Full-Text
Keywords: thermal remote sensing; urban heat island; land surface temperature; LST downscaling; evaluation; diurnal evolution; hotspots; MSG-SEVIRI; MODIS thermal remote sensing; urban heat island; land surface temperature; LST downscaling; evaluation; diurnal evolution; hotspots; MSG-SEVIRI; MODIS
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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

Sismanidis, P.; Keramitsoglou, I.; Kiranoudis, C.T.; Bechtel, B. Assessing the Capability of a Downscaled Urban Land Surface Temperature Time Series to Reproduce the Spatiotemporal Features of the Original Data. Remote Sens. 2016, 8, 274.

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