Fusing Earth Observation, Volunteered Geographic Information and Artificial Intelligence for improved Land Management

The ever-growing availability of Earth Observation (EO) data is demonstrating a wide range of potential applications in the realm of land management. On the other hand, large volumes of data need to be handled and analysed to extract meaningful information and Geomatics coupled with new approaches...

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Autores principales: Vyron Antoniou, Flavio Lupia
Formato: article
Lenguaje:EN
IT
Publicado: mediaGEO soc. coop. 2020
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VGI
Acceso en línea:https://doaj.org/article/ce1372e7b0364dd686fb41d61fa2647e
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spelling oai:doaj.org-article:ce1372e7b0364dd686fb41d61fa2647e2021-11-09T17:42:27ZFusing Earth Observation, Volunteered Geographic Information and Artificial Intelligence for improved Land Management10.48258/geo.v1i3.17271128-81322283-5687https://doaj.org/article/ce1372e7b0364dd686fb41d61fa2647e2020-09-01T00:00:00Zhttps://www.mediageo.it/ojs/index.php/GEOmedia/article/view/1727https://doaj.org/toc/1128-8132https://doaj.org/toc/2283-5687 The ever-growing availability of Earth Observation (EO) data is demonstrating a wide range of potential applications in the realm of land management. On the other hand, large volumes of data need to be handled and analysed to extract meaningful information and Geomatics coupled with new approaches such as Artificial Intelligence (AI) and Machine Learning (AI) will play a pivotal role in the years to come. Training datasets need to be developed to use these new models and Volunteered Geographic Information can be one of the promising sources for EO processing. Among the various applications, agriculture may benefit from the large dataset availability and AI processing. However, several issues remain unsolved and further steps should be taken in the near future by researchers and policy makers. Vyron AntoniouFlavio LupiamediaGEO soc. coop.articleEarth observationVGImachine learningdeep learningdigital agricultureland managementCartographyGA101-1776Cadastral mappingGA109.5ENITGEOmedia, Vol 24, Iss 3 (2020)
institution DOAJ
collection DOAJ
language EN
IT
topic Earth observation
VGI
machine learning
deep learning
digital agriculture
land management
Cartography
GA101-1776
Cadastral mapping
GA109.5
spellingShingle Earth observation
VGI
machine learning
deep learning
digital agriculture
land management
Cartography
GA101-1776
Cadastral mapping
GA109.5
Vyron Antoniou
Flavio Lupia
Fusing Earth Observation, Volunteered Geographic Information and Artificial Intelligence for improved Land Management
description The ever-growing availability of Earth Observation (EO) data is demonstrating a wide range of potential applications in the realm of land management. On the other hand, large volumes of data need to be handled and analysed to extract meaningful information and Geomatics coupled with new approaches such as Artificial Intelligence (AI) and Machine Learning (AI) will play a pivotal role in the years to come. Training datasets need to be developed to use these new models and Volunteered Geographic Information can be one of the promising sources for EO processing. Among the various applications, agriculture may benefit from the large dataset availability and AI processing. However, several issues remain unsolved and further steps should be taken in the near future by researchers and policy makers.
format article
author Vyron Antoniou
Flavio Lupia
author_facet Vyron Antoniou
Flavio Lupia
author_sort Vyron Antoniou
title Fusing Earth Observation, Volunteered Geographic Information and Artificial Intelligence for improved Land Management
title_short Fusing Earth Observation, Volunteered Geographic Information and Artificial Intelligence for improved Land Management
title_full Fusing Earth Observation, Volunteered Geographic Information and Artificial Intelligence for improved Land Management
title_fullStr Fusing Earth Observation, Volunteered Geographic Information and Artificial Intelligence for improved Land Management
title_full_unstemmed Fusing Earth Observation, Volunteered Geographic Information and Artificial Intelligence for improved Land Management
title_sort fusing earth observation, volunteered geographic information and artificial intelligence for improved land management
publisher mediaGEO soc. coop.
publishDate 2020
url https://doaj.org/article/ce1372e7b0364dd686fb41d61fa2647e
work_keys_str_mv AT vyronantoniou fusingearthobservationvolunteeredgeographicinformationandartificialintelligenceforimprovedlandmanagement
AT flaviolupia fusingearthobservationvolunteeredgeographicinformationandartificialintelligenceforimprovedlandmanagement
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