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Data fusion for improving thermal emissivity separation from hyperspectral data

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdragepeer review

2 Citaten (Scopus)

Samenvatting

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.

Originele taal-2Engels
Titel2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings
UitgeverijInstitute of Electrical and Electronics Engineers Inc.
Pagina's2955-2958
Aantal pagina's4
ISBN van elektronische versie9781479979295
DOI's
StatusGepubliceerd - 10 nov. 2015
EvenementIEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Milan, Italië
Duur: 26 jul. 201531 jul. 2015

Publicatie series

NaamInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2015-November

Congres

CongresIEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
Land/RegioItalië
StadMilan
Periode26/07/1531/07/15

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