[OSM-Science] Call for papers: IJGIS special issue on Climate change adaptation using Crowdsourced Geospatial Information

[Yair Grinberger]

*Apologies for cross-posting*

Dear Colleagues and Friends,

We are happy to share with you a call for papers for a Special Issue of the
International Journal of Geographic Information Science on "Climate change
adaptation using Crowdsourced Geospatial Information: Understanding
Human-environment interactions" [1]. The submission deadline was now
extended to 31 Dec 2023.

We are looking for original studies or reviews relating to the use of
crowdsourced geoinformation for supporting human-environment interactions
issues. Relevant themes include, but are not limited to, the following:
* Applying CGI to analyse various human-environment interactions
* Theories, models for CGI data processing, knowledge production and
communication to support climate change adaptation
* Developing methods utilizing CGI resources to assess communities’
vulnerability and enhance their resilience
* Using spatial approaches to detect and screen biases, rumours, and fake
news in geo-social data related to climate-induced phenomena and urban
environments
* Identifying and addressing ethical issues arising from the use of CGI in
community-based projects
* Identifying temporal and spatial trends and phenomena that are reflected
in CGI systems and their implications for producing valid assessments of
preparedness and resilience

If you are working on a relevant topic, we would be thrilled to receive
your submission. Please feel free to approach us with any questions.

Best wishes,
The guest editors:
Motti Zohar - motti.zohar at univ.haifa.ac.il
Carolin Klonner - c.klonner at uni-heidelberg.de
Peter Mooney - Peter.Mooney at mu.ie
Yair Grinberger - yair.grinberger at mail.huji.ac.il

[1]
https://think.taylorandfrancis.com/special_issues/climate-change-adaptation-science/?utm_source=TFO&utm_medium=cms&utm_campaign=JPG15743&_gl=1*1efsseb*_ga*MTYyMTQ5NTU4Mi4xNjg3MDc3NzU4*_ga_0HYE8YG0M6*MTY4NzA3Nzc1OC4xLjEuMTY4NzA3ODQ2Ny4wLjAuMA..&_ga=2.59627428.829545995.1687077758-1621495582.1687077758
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