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Exploratory analysis of OpenStreetMap for land use classification

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Presented at the 2nd ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information (GEOCROWD) 2013

Presented at the 2nd ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information (GEOCROWD) 2013

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  • - research fields: LULC monitoring and modeling, monitoring of tropical deforestation, climate changes, among many others
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    • 1. Exploratory analysis of OpenStreetMap for land use classification Jacinto Estima and Marco Painho Jacinto.estima@gmail.com; painho@isegi.unl.pt www.isegi.unl.pt 2nd International Workshop on Crowdsourced and Volunteered Geographic Information (GEOCROWD) 2013 21st International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2013) November 5 - 8, 2013 — Orlando, Florida, USA 05-11-2013 Nome e/ou Título e/ou Outros 1
    • 2. Agenda • Introduction • Objective • Related work: – Volunteered Geographic Information – VGI Initiatives (examples) – Research using VGI • Material and Methods • Results and Discussion • Conclusions 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 2
    • 3. Introduction • • • VGI has become exponentially available over the web in the last years An inventory made by Elwood in 2009 identified 99 VGI initiatives running Research has already been conducted in some areas: – – – – • emergency response Navigation Land Use/Cover validation etc. To our best knowledge, no study using OSM in the production of Land Use/Cover databases exists 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 3
    • 4. Objective • Objective: – Conduct an exploratory analysis of the OSM database for land use/cover production, using Corine Land Cover (CLC) as reference data • Contributions: – Establish a tentative to relate both nomenclatures – Evaluate the quality of OSM land use classification over continental Portugal taking CLC as reference data, to assess if it can be used as ground truth for LULC validation in the future 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 4
    • 5. Volunteered Geographic Information • • “Spatial” type of User Generated Content (UGC) contributed by volunteers Has been exponentially growing since 2005: – Evolution of important technologies (Web 2.0, GPS, etc.) – Willingness of private citizens to contribute • • 70% of the initiatives counted by Elwood started after 2005 (when Google Maps was launched) Issues: – heterogeneity, absence of formal structures and quality control procedures, absence of metadata • Advantages: – Quantity, temporal coverage, and the local knowledge of its contributors 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 5
    • 6. VGI initiatives (examples) • • • • • • • HD Traffic TM from TomTom (real-time traffic data) OpenStreetMap (OSM) (aims to provide free geographic data for free to anyone) Wikimapia (based in Google Maps) Flickr (Kisilevich downloaded a total of 86,314,466 geotagged photos in 2010) Map Tube (“Place to put maps”) “Did you feel it” (USGS initiative for earthquake mapping) Etc. 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 6
    • 7. Research using VGI • • • • Fritz et al. developed a plattform that uses a global network of volunteers to help improving the quality of global land cover maps Leung and Newsam (2010) conducted some experiments to automatically derive maps of what-is-where from large collections of georeferenced photos (they achieved around 75% of classification accuracy) Estima and Painho (2013) explored the possibility of using Flickr photos as a source of truth data to help in the accuracy assessment phase of land use/cover production OSM: – Over et al. (2010) studied, for the first time, the possibility of generating interactive 3D City Models based on free geo-data available from OSM, and public domain height information provided by the Shuttle Radar Topography Mission – Al-Bakri and Fairbairn (2012) used OSM and Ordnance Survey (OS) to give one step towards the integration of geospatial datasets from varied sources (focus on semantic and structural similarities) 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 7
    • 8. Study area and Datasets (1) • Study area – The study area is Continental Portugal – The land cover is mainly composed by agricultural and forest areas (around 95%) • Datasets – OSM database (only polygon datasets were used to quantify areas): • Buildings, Landuse and Natural Areas datasets – Corine Land Cover (CLC) database for the CLC2006 inventory version 16 (04/2012) – vector format – Portuguese official administrative boundaries database - “Carta Administrativa Oficial de Portugal” (CAOP) – vector format 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 8
    • 9. a) b ) c) Study area and Datasets (2) • CLC nomenclature • OSM nomenclature available from http:// wiki.openstreetmap.org/wiki/Map_Features • Assumptions: – We assume the time difference between CLC and OSM databases (2006 for CLC and 2013 for OSM) would not represent a major issue, Considering a yearly average change value of land cover in Europe of 0.23% 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 9
    • 10. Methods 1. Analysis of OSM datasets (nomenclature and area of coverage) 2. Analysis and establishment of a relationship between the nomenclatures (OSM and CLC) 3. Analysis of the coverage of each OSM class using CLC level 1 as reference 4. Analysis of the matching degree between related classes 5. Analysis of the OSM spatial distribution 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 10
    • 11. 1. Analysis of OSM datasets Areas of coverage of OSM datasets Dataset Area (Ha) Country coverage (%) Natural areas 140006.95 1.57% Landuse 144350.23 1.62% Buildings 7057.61 0.08% Total 3.27% Overlapping areas - 0.03% Total 3.24% 05-11-2013 Existing classification differences (overlapping areas) Natural areas Landuse Buildings Area dataset dataset dataset (Ha) Forest Military None 5.24 Residential Reservoir_cover 0.02 Recreation_ground Hospital 0.25 Park Commercial None 0.01 Residential Museum 0.39 Cafe 0.05 Chapel 0.01 Church 0.00 House 0.03 Library 0.03 Museum 0.08 Public 0.02 Public_building 0.37 Restaurant 0.03 Roof 0.01 Theatre 0.03 Toilets 0.00 Yes 0.01 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 11
    • 12. 2. OSM and CLC relationship nomenclatures CLC classes Level 3 Level 2 Level 1 Landuse dataset Abutters 111-112-121 11-12 1 Allotments 242 24 2 Basin 512 51 5 Beach 331 33 3 Brownfield 133 13 1 Cemetery 111-112 11 1 Commercial 121 12 1 Conservation 313-312-311 31 3 Construction 133 13 1 Farm 222-231-241-242 22-23-24 2 Farmland 222-231-241-242 22-23-24 2 Farmyard 222-231-241-242 22-23-24 2 Field ? ? ? Garages 122 12 1 Garden 142 14 1 Grass 231-321 23-32 2-3 OSM classes 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 12
    • 13. 3. Coverage analysis of OSM datasets 1. Gave to each OSM class got its correspondent CLC level1 2. Dissolve by CLC level1 class 3. Removed overlapping areas (not deducted) – 1.39% of the total OSM area Coverage areas from CLC level 1 and OSM CLC classes unclassified 1 2 3 4 5 05-11-2013 Area from CLC Area from OSM Class coverage (Ha) (Ha) (%) --7036.75 --309716.89 62407.48 20.15 4199177.27 34309.93 0.82 4259642.22 98536.62 2.31 28777.11 64.59 0.22 110906.66 82621.61 74.50 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 13
    • 14. 4. Matching degree between classes (areas) Confusion matrix of CLC vs. OSM classifications Classification accuracy Classification Class accuracy (%) 1 84.3% 2 46.6% 3 83.5% 4 1.2% 5 99.5% Global 76.7% 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 14
    • 15. 5. OSM spatial distribution Spatial distribution of OSM classified areas over continental Portugal Distribution of classes’ coverage areas by continental Portuguese districts 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 15
    • 16. Conclusions • Tentative to relate OSM and CLC • Determined the accuracy of classification of OSM polygon features based on CLC level 1 classes • Analyzed OSM spatial distribution • Results show that might be worth to study OSM with the more detailed CLC levels 1 and 2 • Classification accuracy of 76.7% (23.3% need further investigation): – Not all the classes have similar accuracy – We believe that it might be used, for instance, as another source of ground truth data in the validation process of LULC databases 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 16
    • 17. Conclusions (2) • Further investigation needed: – Correspondence between OSM and the 3 levels of CLC – Ways to avoid “not_known” class and classes without description – The cause of discrepancies between both classifications (errors or just different views?) – Understand the real effect of conflicting overlapping areas (1.39%) (level of contributors trust to decide which one is correct?) 05-11-2013 GEOCROWD 2013 • ACM SIGSPATIAL GIS 2013 November 5 - 8, 2013 — Orlando, Florida, USA 17
    • 18. Thank you for your attention Jacinto Estima and Marco Painho Jacinto.estima@gmail.com; painho@isegi.unl.pt www.isegi.unl.pt 2nd International Workshop on Crowdsourced and Volunteered Geographic Information (GEOCROWD) 2013 21st International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2013) November 5 - 8, 2013 — Orlando, Florida, USA 05-11-2013 Nome e/ou Título e/ou Outros 18