Abstract
This work is linked to the future Indian–French high spatio-temporal TRISHNA (Thermal infraRed Imaging Satellite for High-resolution natural resource Assessment) mission, which includes shortwave and thermal infrared bands, and is devoted amongst other things to the monitoring of urban heat island events. In this article, the performance of seven empirical thermal unmixing techniques applied on simulated TRISHNA satellite images of an urban scenario is studied across spatial resolutions. For this purpose, Top Of Atmosphere (TOA) images in the shortwave and Thermal InfraRed (TIR) ranges are constructed at different resolutions (20 m, 40 m, 60 m, 80 m, and 100 m) and according to TRISHNA specifications (spectral bands and sensor properties). These images are synthesized by correcting and undersampling DESIREX 2008 Airborne Hyperspectral Scanner (AHS) images of Madrid at 4 m resolution. This allows to compare the Land Surface Temperature (LST) retrieval of several unmixing techniques applied on different resolution images, as well as to characterize the evolution of the performance of each technique across resolutions. The seven unmixing techniques are: Disaggregation of radiometric surface Temperature (DisTrad), Thermal imagery sHARPening (TsHARP), Area-To-Point Regression Kriging (ATPRK), Adaptive Area-To-Point Regression Kriging (AATPRK), Urban Thermal Sharpener (HUTS), Multiple Linear Regressions (MLR), and two combinations of ground classification (index-based classification and K-means classification) with DisTrad. Studying these unmixing techniques across resolutions also allows to validate the scale invariance hypotheses on which the techniques hinge. Each thermal unmixing technique has been tested with several shortwave indices, in order to choose the best one. It is shown that (i) ATPRK outperforms the other compared techniques when characterizing the LST of Madrid, (ii) the unmixing performance of any technique is degraded when the coarse spatial resolution increases, (iii) the used shortwave index does not strongly influence the unmixing performance, and (iv) even if the scale-invariant hypotheses behind these techniques remain empirical, this does not affect the unmixing performances within this range of resolutions.
Highlights
In the context of urban spread, 68% of the world population is projected to live in urban areas by 2050 according to the United Nations, and climate change is very likely to increase both the frequency and intensity of heat waves, the need for methodologies to monitor urban climates and UHI becomes critical
Classification-unmixing method has been tested with two different ground classifications and Disaggregation of radiometric surface Temperature (DisTrad) applied on each class
We modelled, from Airborne Hyperspectral Scanner (AHS) data of Madrid at 4 m resolution obtained during the DESIREX 2008 campaign, the corresponding data as would be obtained by four different multispectral satellites with the same spectral configuration and spatial resolution in the shortwave optical domain and different resolution in the Thermal InfraRed (TIR) range
Summary
In the context of urban spread, 68% of the world population is projected to live in urban areas by 2050 according to the United Nations, and climate change is very likely to increase both the frequency and intensity of heat waves, the need for methodologies to monitor urban climates and UHI (urban heat islands) becomes critical. Disaggregation methods based on combining low resolution TIR data with high resolution data in the Visible and Near InfraRed (VNIR) domain have been developed to derive high resolution products in the TIR [4,5,6]. All these methodologies rely on the hypothesis of conservation at finer resolution of relationships established at coarser resolution between temperature and a feature estimated using the VNIR bands. From our knowledge this study has not been performed for the other empirical techniques used in the present work
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
