Adrijana CAR - Josef STROBL - Robert VOGLER - Gerald GRIESEBNER (Eds.)


GI_Forum 2021, Volume 9, Issue 2




ISSN 2308-1708
Online Edition

ISBN 978-3-7001-9183-4
Online Edition
doi:10.1553/giscience2021_02_
GI_Forum 2021,  Volume 9,  Issue 2 
 
Open access


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

GI_Forum publishes high quality original research across the transdisciplinary field of Geographic Information Science (GIScience). The journal provides a platform for dialogue among GI-Scientists and educators, technologists and critical thinkers in an ongoing effort to advance the field and ultimately contribute to the creation of an informed GISociety. Submissions concentrate on innovation in education, science, methodology and technologies in the spatial domain and their role towards a more just, ethical and sustainable science and society. GI_Forum implements the policy of open access publication after a double-blind peer review process through a highly international team of seasoned scientists for quality assurance. Special emphasis is put on actively supporting young scientists through formative reviews of their submissions. Only English language contributions are published.


Starting 2016, GI_Forum publishes two issues a Year.
Joumal Information is available at: GI-Forum

GI_Forum is listed on the Directory of Open Access Journals (DOAJ)

In the 2021-2 issue, the following three thematic areas are addressed: Advances in GIScience, Geo-Social Analytics, and Learning and Education with Geomedia. The contributions, for example, evaluate modes of generalization in animated choropleth maps; investigate different Convolutional Neural Networks (CNNs) architectures for monitoring wildlife in complex natural habitats; introduce an Augmented Reality learning environment for Geoinformatics education; investigate pedestrian infrastructure in a city considering the COVID-19 restrictions; or propose a customised workflow for place extraction from social media text and subsequent geocoding; or address various mobility issues for sustainable cities.

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GI_Forum 2021, Volume 9, Issue 2

ISSN 2308-1708
Online Edition

ISBN 978-3-7001-9183-4
Online Edition



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Austrian Academy of Sciences Press
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doi:10.1553/giscience2021_02_s82



Thema: geography
Adrijana CAR - Josef STROBL - Robert VOGLER - Gerald GRIESEBNER (Eds.)


GI_Forum 2021, Volume 9, Issue 2




ISSN 2308-1708
Online Edition

ISBN 978-3-7001-9183-4
Online Edition
doi:10.1553/giscience2021_02_
GI_Forum 2021,  Volume 9,  Issue 2 
 
Open access


Sabine Hennig
PDF Icon  Orchard Meadow Trees: Tree Detection Using Deep Learning in ArcGIS Pro ()
S.  82 - 93
doi:10.1553/giscience2021_02_s82

Verlag der Österreichischen Akademie der Wissenschaften


doi:10.1553/giscience2021_02_s82
Abstract:
‘Orchard meadows’ refers to the combination of extensively managed fruit trees in combination with fields and pastures. In many regions, among others in Germany, Austria and Switzerland, they are a landscape-defining element and of particular ecological, economic and social importance. However, the numbers of orchard meadows and fruit trees have been decreasing for quite some time. Current and detailed data that allow for the identification of suitable countermeasures to maintain this cultural landscape element are often missing. Such data can be obtained through deep learning. Various deep learning frameworks can now be used in the context of ArcGIS Pro. But what exactly does the use of deep learning involve, in the context of ArcGIS Pro, to get an insight into the stocks of orchard meadow trees? What are the challenges? Initial analyses were carried out using selected areas in Franconian Switzerland (Northern Bavaria) as an example. The results confirm the potential of the approach, but also that training data, model and output data must be refined.

Keywords:  cultural landscape, machine learning, monitoring, landscape maintenance
Published Online:  2021/12/28 12:08:03
Object Identifier:  0xc1aa5576 0x003d25e8

GI_Forum publishes high quality original research across the transdisciplinary field of Geographic Information Science (GIScience). The journal provides a platform for dialogue among GI-Scientists and educators, technologists and critical thinkers in an ongoing effort to advance the field and ultimately contribute to the creation of an informed GISociety. Submissions concentrate on innovation in education, science, methodology and technologies in the spatial domain and their role towards a more just, ethical and sustainable science and society. GI_Forum implements the policy of open access publication after a double-blind peer review process through a highly international team of seasoned scientists for quality assurance. Special emphasis is put on actively supporting young scientists through formative reviews of their submissions. Only English language contributions are published.


Starting 2016, GI_Forum publishes two issues a Year.
Joumal Information is available at: GI-Forum

GI_Forum is listed on the Directory of Open Access Journals (DOAJ)

In the 2021-2 issue, the following three thematic areas are addressed: Advances in GIScience, Geo-Social Analytics, and Learning and Education with Geomedia. The contributions, for example, evaluate modes of generalization in animated choropleth maps; investigate different Convolutional Neural Networks (CNNs) architectures for monitoring wildlife in complex natural habitats; introduce an Augmented Reality learning environment for Geoinformatics education; investigate pedestrian infrastructure in a city considering the COVID-19 restrictions; or propose a customised workflow for place extraction from social media text and subsequent geocoding; or address various mobility issues for sustainable cities.



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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