Mitteilungen der Österreichischen Geographischen Gesellschaft Annals of the Austrian Geographical Society Band 161 (Jahresband), Wien 2019
Volume 161 (Annual volume), Vienna 2019
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DATUM, UNTERSCHRIFT / DATE, SIGNATURE
BANK AUSTRIA CREDITANSTALT, WIEN (IBAN AT04 1100 0006 2280 0100, BIC BKAUATWW), DEUTSCHE BANK MÜNCHEN (IBAN DE16 7007 0024 0238 8270 00, BIC DEUTDEDBMUC)
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Mitteilungen der Österreichischen Geographischen Gesellschaft Annals of the Austrian Geographical Society Band 161 (Jahresband), Wien 2019
Volume 161 (Annual volume), Vienna 2019
ISSN 0029-9138
Print Edition ISSN 0029-9138 Online Edition ISBN 978-3-901313-32-5 Print Edition ISBN 978-3-7001-8551-2 Online Edition
Christian Bauer ,
Katharina Kern ,
Wolfgang Sulzer
S. 271 - 290 doi:10.1553/moegg161s271 doi:10.1553/moegg161s271
Abstract: This paper focuses on the automatic detection of hot spots on heterogenic roofscapes in high resolution airborne thermal imagery. Previous approaches to detect hot spots required either emissivity corrected TIR-data or are only applicable to roofscapes with uniform roof materials. Here we present an automatic detection process using TIR-data without emissivity correction. To achieve this, every single roof and every roof material in the study area has to be acquired from remotely sensed imagery. This is obtained by using an object-based image classification approach based on orthophotos (RGB / IR) with sub-meter spatial resolution and a digital surface model. The hot spot detection is based on a two-step statistical criterion for every previously detected roof envelopes and roofing material. Firstly, the hottest spots on a roof are located by using a peak detection and secondly, a focal neighbourhood function is used to delimit thermal anomalies. The developed method was applied to TIR-data from the Thermal Airborne Broadband Imager (TABI-1800) with a spatial resolution of 0.6m x 0.6m. The results demonstrate that the developed method is applicable for heterogenic roofscapes, whereas the detection process highly depends on the roofscape complexity. Keywords: Airborne thermal imagery, TABI-1800, roof heat loss detection, hot spots, object based classification Published Online: 2020/03/24 13:51:04 Object Identifier: 0xc1aa5576 0x003b613c Rights: .
Die Fachzeitschrift "Mitteilungen der Österreichischen Geographischen Gesellschaft" (früher "Mitteilungen der k.k. Geographischen Gesellschaft in Wien")
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epub.oeaw – Institutionelles Repositorium der Österreichischen Akademie der Wissenschaften epub.oeaw – Institutional Repository of the Austrian Academy of Sciences
A-1011 Wien, Dr. Ignaz Seipel-Platz 2
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400 http://epub.oeaw.ac.at, e-mail: epub@oeaw.ac.at |