GI_Forum 2015, Volume 3 Journal for Geographic Information Science
Geospatial Minds for Society
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Verlag der Österreichischen Akademie der Wissenschaften Austrian Academy of Sciences Press
A-1011 Wien, Dr. Ignaz Seipel-Platz 2
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400 https://verlag.oeaw.ac.at, e-mail: verlag@oeaw.ac.at |
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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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GI_Forum 2015, Volume 3 Journal for Geographic Information Science
Geospatial Minds for Society ISSN 2308-1708 Online Edition ISBN 978-3-87907-558-4 Print Edition ISBN 978-3-7001-7826-2 Online Edition
doi:10.1553/giscience2015
GI_Forum, 2015Volume 3 2015, 645 pages Print edition is available at Wichmann-Verlag, Berlin
Ana Gonzalez Quintairos,
Jochen Bühler,
Birgit Kleinschmit,
Matthias Resch
S. 220 - 224 doi:10.1553/giscience2015s220 Verlag der Österreichischen Akademie der Wissenschaften
Abstract: The present study as part of the joint research project “Smart-Power-Flow”1 (at Reiner Lemoine Institute for Renewable Energies) focuses on modelling PV systems´ distribution in German rural communities. Although solar power energy systems in Germany have been increasing exponentially for the last 20 years (WRITH 2014), the majority of literature on PV potential has focused on rooftop PV systems in urban regions, and a small number of publications consider the typology of small rural communities. These areas, although less populated than cities, are where the highest PV potential in Germany is expected (DENA 2010), and, at the same time, where the availability of laser scanning data is highly incomplete, or not affordable for small administrations or projects. Several authors have used remotely-sensed imagery to quantify the PV potential on a regional scale, but only few authors (KJELLSSON 2000, BERGAMASCO & ASINARI 2011, JO & OTANICAR 2011) have attempted to use high-resolution images to quantify the suitable rooftop surface on a building basis, and none of them have addressed the particularities of rural communities. The aim of this study is to create a methodology, which predicts the size and location of future photovoltaic systems on rooftops, based on generally accessible data, and that is easily reproducible on a building scale for other rural villages. The methodology’s input data comprises high-resolution aerial imagery, GIS building footprints from the Landregister map, and the Bavarian database of photovoltaic systems. In addition, the method is tested using two types of images: a) official orthophotos from the Bavarian Land-survey Office, and b) Google Earth™ orthophotos, to assess the accuracy of freely available data to the project. The results are compared in the discussion section. Published Online: 2015/06/29 07:51:32 Object Identifier: 0xc1aa5576 0x00324a7f Rights:https://creativecommons.org/licenses/by-nd/4.0/
The Journal for Geographic Information Science issue 1-2015 presents peer-reviewed papers
presented at the Geoinformatics
Forum (www.gi-forum.org), held in Salzburg from July 7-10,
2015. The annual GI_Forum symposium provides a platform for dialogue among geospatial minds
in an ongoing effort to support the creation of an informed GISociety.
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Verlag der Österreichischen Akademie der Wissenschaften Austrian Academy of Sciences Press
A-1011 Wien, Dr. Ignaz Seipel-Platz 2
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400 https://verlag.oeaw.ac.at, e-mail: verlag@oeaw.ac.at |