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Detecting the Severity of Socio-Spatial Conflicts Involving Wild Boars in the City Using Social Media Data

The encroachment of wild boars into urban areas is a growing problem. The occurrence of wild boars in cities leads to conflict situations. Socio-spatial conflicts can escalate to a varied degree. Assessments of these conflicts can be performed by analyzing spatial data concerning the affected locati...

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Autores principales: Dudzińska, Małgorzata, Dawidowicz, Agnieszka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8703761/
https://www.ncbi.nlm.nih.gov/pubmed/34960305
http://dx.doi.org/10.3390/s21248215
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author Dudzińska, Małgorzata
Dawidowicz, Agnieszka
author_facet Dudzińska, Małgorzata
Dawidowicz, Agnieszka
author_sort Dudzińska, Małgorzata
collection PubMed
description The encroachment of wild boars into urban areas is a growing problem. The occurrence of wild boars in cities leads to conflict situations. Socio-spatial conflicts can escalate to a varied degree. Assessments of these conflicts can be performed by analyzing spatial data concerning the affected locations and wild boar behaviors. The collection of spatial data is a laborious and costly process that requires access to urban surveillance systems, in addition to regular analyses of intervention reports. A supporting method for assessing the risk of wild boar encroachment and socio-spatial conflict in cities was proposed in the present study. The developed approach relies on big data, namely, multimedia and descriptive data that are on social media. The proposed method was tested in the city of Olsztyn in Poland. The main aim of this study was to evaluate the applicability of data crowdsourced from a popular social networking site for determining the location and severity of conflicts. A photointerpretation method and the kernel density estimation (KDE) tool implemented in ArcGIS Desktop 10.7.1 software were applied in the study. The proposed approach fills a gap in the application of crowdsourcing data to identify types of socio-spatial conflicts involving wild boars in urban areas. Validation of the results with reports of calls to intervention services showed the high coverage of this approach and thus the usefulness of crowdsourcing data.
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spelling pubmed-87037612021-12-25 Detecting the Severity of Socio-Spatial Conflicts Involving Wild Boars in the City Using Social Media Data Dudzińska, Małgorzata Dawidowicz, Agnieszka Sensors (Basel) Article The encroachment of wild boars into urban areas is a growing problem. The occurrence of wild boars in cities leads to conflict situations. Socio-spatial conflicts can escalate to a varied degree. Assessments of these conflicts can be performed by analyzing spatial data concerning the affected locations and wild boar behaviors. The collection of spatial data is a laborious and costly process that requires access to urban surveillance systems, in addition to regular analyses of intervention reports. A supporting method for assessing the risk of wild boar encroachment and socio-spatial conflict in cities was proposed in the present study. The developed approach relies on big data, namely, multimedia and descriptive data that are on social media. The proposed method was tested in the city of Olsztyn in Poland. The main aim of this study was to evaluate the applicability of data crowdsourced from a popular social networking site for determining the location and severity of conflicts. A photointerpretation method and the kernel density estimation (KDE) tool implemented in ArcGIS Desktop 10.7.1 software were applied in the study. The proposed approach fills a gap in the application of crowdsourcing data to identify types of socio-spatial conflicts involving wild boars in urban areas. Validation of the results with reports of calls to intervention services showed the high coverage of this approach and thus the usefulness of crowdsourcing data. MDPI 2021-12-08 /pmc/articles/PMC8703761/ /pubmed/34960305 http://dx.doi.org/10.3390/s21248215 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Dudzińska, Małgorzata
Dawidowicz, Agnieszka
Detecting the Severity of Socio-Spatial Conflicts Involving Wild Boars in the City Using Social Media Data
title Detecting the Severity of Socio-Spatial Conflicts Involving Wild Boars in the City Using Social Media Data
title_full Detecting the Severity of Socio-Spatial Conflicts Involving Wild Boars in the City Using Social Media Data
title_fullStr Detecting the Severity of Socio-Spatial Conflicts Involving Wild Boars in the City Using Social Media Data
title_full_unstemmed Detecting the Severity of Socio-Spatial Conflicts Involving Wild Boars in the City Using Social Media Data
title_short Detecting the Severity of Socio-Spatial Conflicts Involving Wild Boars in the City Using Social Media Data
title_sort detecting the severity of socio-spatial conflicts involving wild boars in the city using social media data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8703761/
https://www.ncbi.nlm.nih.gov/pubmed/34960305
http://dx.doi.org/10.3390/s21248215
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