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Data fusion for improving thermal emissivity separation from hyperspectral data

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

2 Zitate (Scopus)

Abstract

Land Surface Temperature (LST) and Land Surface Emissivity (LSE) are common retrievals from thermal hyperspectral imaging. However, their retrieval is not a straightforward procedure because the mathematical problem is ill-posed. This procedure becomes more challenging in an urban area where the spatial distribution of temperature varies substantially in space and time. In this study we propose a new method which integrates 3D surface information from LIDAR data in an attempt to improve the temperature and emissivity separation (TES) procedure for thermal hyperspectral scene. The experimental results prove the high accuracy of the proposed method in comparison to another conventional TES model.

OriginalspracheEnglisch
Titel2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten2955-2958
Seitenumfang4
ISBN (elektronisch)9781479979295
DOIs
PublikationsstatusVeröffentlicht - 10 Nov. 2015
VeranstaltungIEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Milan, Italien
Dauer: 26 Juli 201531 Juli 2015

Publikationsreihe

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Band2015-November

Konferenz

KonferenzIEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
Land/GebietItalien
OrtMilan
Zeitraum26/07/1531/07/15

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