Urban Surface Temperature Time Series Estimation at the Local Scale by Spatial-Spectral Unmixing of Satellite Observations

Remote Sensing

Zina Mitraka²  Nektarios Chrysoulakis¹  Georgia Doxani⁴  Fabio Del Frate²  Michael Berger⁴  Zhao-Liang Li³  Jose A. Sobrino³  Xiaoning Song³  Clement Atzberger³  Richard Müller³ 

[1] Foundation for Research and Technology Hellas, N.Plastira 100, Vassilika Vouton, 70013 Heraklion, Greece; E-Mail:;DICII, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy; E-Mail:;DICII, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy; E-Mail;European Space Agency, Via Galileo Galilei, 00044 Frascati, Italy; E-Mails:

关键词: land surface temperature;    local scale;    urban surface emissivity;    urban climate;    spatial-spectral unmixing;    downscaling;   

DOI  :  10.3390/rs70404139

来源: mdpi

【 摘 要 】

The study of urban climate requires frequent and accurate monitoring of land surface temperature (LST), at the local scale. Since currently, no space-borne sensor provides frequent thermal infrared imagery at high spatial resolution, the scientific community has focused on synergistic methods for retrieving LST that can be suitable for urban studies. Synergistic methods that combine the spatial structure of visible and near-infrared observations with the more frequent, but low-resolution surface temperature patterns derived by thermal infrared imagery provide excellent means for obtaining frequent LST estimates at the local scale in cities. In this study, a new approach based on spatial-spectral unmixing techniques was developed for improving the spatial resolution of thermal infrared observations and the subsequent LST estimation. The method was applied to an urban area in Crete, Greece, for the time period of one year. The results were evaluated against independent high-resolution LST datasets and found to be very promising, with RMSE less than 2 K in all cases. The developed approach has therefore a high potential to be operationally used in the near future, exploiting the Copernicus Sentinel (2 and 3) observations, to provide high spatio-temporal resolution LST estimates in cities.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.