research-article

Exploratory analysis of OpenStreetMap for land use classification

Authors:

Jacinto Estima,

Marco PainhoAuthors Info & Claims

GEOCROWD '13: Proceedings of the Second ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information

Pages 39 - 46

https://doi.org/10.1145/2534732.2534734

Published: 05 November 2013 Publication History

Abstract

In the last years, volunteers have been contributing massively to what we know nowadays as Volunteered Geographic Information. This huge amount of data might be hiding a vast geographical richness and therefore research needs to be conducted to explore their potential and use it in the solution of real world problems. In this study we conduct an exploratory analysis of data from the OpenStreetMap initiative. Using the Corine Land Cover database as reference and continental Portugal as the study area, we establish a possible correspondence between both classification nomenclatures, evaluate the quality of OpenStreetMap polygon features classification against Corine Land Cover classes from level 1 nomenclature, and analyze the spatial distribution of OpenStreetMap classes over continental Portugal. A global classification accuracy around 76% and interesting coverage areas' values are remarkable and promising results that encourages us for future research on this topic.

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Cited By

Yang DFu CHerrero HSouthworth JBinford M(2023)Linking forest management to surrounding lands: a citizen-based approach towards the regional understanding of land-use transitionsFrontiers in Remote Sensing10.3389/frsen.2023.11975234Online publication date: 13-Jul-2023
https://doi.org/10.3389/frsen.2023.1197523
Huang XLi XYang DZou L(2023)Crowdsourced geospatial data in human and Earth observations: opportunities and challengesGeoinformatics for Geosciences10.1016/B978-0-323-98983-1.00007-7(109-129)Online publication date: 2023
https://doi.org/10.1016/B978-0-323-98983-1.00007-7
Ulrich VSchultz MLautenbach SZipf A(2023)Carbon fluxes related to land use and land cover change in Baden-WürttembergEnvironmental Monitoring and Assessment10.1007/s10661-023-11141-9195:5Online publication date: 27-Apr-2023
https://doi.org/10.1007/s10661-023-11141-9
Show More Cited By

Index Terms

Exploratory analysis of OpenStreetMap for land use classification
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Geographic visualization
2. Information systems
  1. Information systems applications
    1. Spatial-temporal systems

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Published In

cover image ACM Conferences

GEOCROWD '13: Proceedings of the Second ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information

November 2013

102 pages

ISBN:9781450325288

DOI:10.1145/2534732

Editors:
Dieter Pfoser
George Mason University
,
Agnès Voisard
Freie Universität Berlin and Fraunhofer FOKUS, Germany

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 05 November 2013

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SIGSPATIAL'13

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SIGSPATIAL'13: 21st SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 5, 2013

Florida, Orlando

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GEOCROWD '13 Paper Acceptance Rate 12 of 20 submissions, 60%;

Overall Acceptance Rate 17 of 30 submissions, 57%

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Cited By

Yang DFu CHerrero HSouthworth JBinford M(2023)Linking forest management to surrounding lands: a citizen-based approach towards the regional understanding of land-use transitionsFrontiers in Remote Sensing10.3389/frsen.2023.11975234Online publication date: 13-Jul-2023
https://doi.org/10.3389/frsen.2023.1197523
Huang XLi XYang DZou L(2023)Crowdsourced geospatial data in human and Earth observations: opportunities and challengesGeoinformatics for Geosciences10.1016/B978-0-323-98983-1.00007-7(109-129)Online publication date: 2023
https://doi.org/10.1016/B978-0-323-98983-1.00007-7
Ulrich VSchultz MLautenbach SZipf A(2023)Carbon fluxes related to land use and land cover change in Baden-WürttembergEnvironmental Monitoring and Assessment10.1007/s10661-023-11141-9195:5Online publication date: 27-Apr-2023
https://doi.org/10.1007/s10661-023-11141-9
Rashevskiy NParygin DShcherbakov AShlyannikov NShlyannikov V(2023)Using Generative Design Technologies to Create Park Area Layouts for Urban ImprovementCreativity in Intelligent Technologies and Data Science10.1007/978-3-031-44615-3_39(549-567)Online publication date: 14-Oct-2023
https://doi.org/10.1007/978-3-031-44615-3_39
Liu Z(2021)Identifying urban land use social functional units: a case study using OSM dataInternational Journal of Digital Earth10.1080/17538947.2021.1988161(1-20)Online publication date: 14-Oct-2021
https://doi.org/10.1080/17538947.2021.1988161
Qiao ZYuan X(2021)Urban land-use analysis using proximate sensing imagery: a surveyInternational Journal of Geographical Information Science10.1080/13658816.2021.191968235:11(2129-2148)Online publication date: 3-May-2021
https://doi.org/10.1080/13658816.2021.1919682
Singh SSingh J(2020)Intrinsic Parameters based Quality Assessment of Indian OpenStreetMap Dataset using Supervised Learning Technique2020 Indo – Taiwan 2nd International Conference on Computing, Analytics and Networks (Indo-Taiwan ICAN)10.1109/Indo-TaiwanICAN48429.2020.9181313(52-57)Online publication date: Feb-2020
https://doi.org/10.1109/Indo-TaiwanICAN48429.2020.9181313
Prokudin DLevit GHossfeld U(2020)Selection Methods for Geodata Visualization of Metadata Extracted from Unstructured Digital Data for Scientific Heritage StudiesDigital Transformation and Global Society10.1007/978-3-030-37858-5_46(542-553)Online publication date: 3-Jan-2020
https://doi.org/10.1007/978-3-030-37858-5_46
Zhang HMalczewski J(2019)Quality Evaluation of Volunteered Geographic InformationCrowdsourcing10.4018/978-1-5225-8362-2.ch058(1173-1201)Online publication date: 2019
https://doi.org/10.4018/978-1-5225-8362-2.ch058
Yang D(2019)Mapping Regional Landscape by Using OpenstreetMap (OSM)Environmental Information Systems10.4018/978-1-5225-7033-2.ch033(771-790)Online publication date: 2019
https://doi.org/10.4018/978-1-5225-7033-2.ch033
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