Increasing the detail of European land use/cover data by combining heterogeneous data sets

References

• Antoniou, V., C. Fonte, L. See, J. Estima, J. Arsanjani, F. Lupia, and S. Fritz. 2016. “Investigating the Feasibility of Geo-Tagged Photographs as Sources of Land Cover Input Data.” ISPRS International Journal of Geo-Information 5 (5): 64. doi: 10.3390/ijgi5050064
   Web of Science ®Google Scholar
• Aubrecht, C., D. Özceylan Aubrecht, J. Ungar, S. Freire, and K. Steinnocher. 2017. “VGDI - Advancing the Concept: Volunteered Geo-Dynamic Information and its Benefits for Population Dynamics Modeling.” Transactions in GIS 21 (2): 253–276. doi: 10.1111/tgis.12203
   Web of Science ®Google Scholar
• Batista e Silva, F., C. Lavalle, and E. Koomen. 2013. “A Procedure to Obtain a Refined European Land Use/Cover Map.” Journal of Land Use Science 8 (3): 255–283. doi: 10.1080/1747423X.2012.667450
   Google Scholar
• Batista e Silva, F., K. Rosina, M. Schiavina, M. Marin, S. Freire, M. Craglia, and C. Lavalle. 2017. “Spatiotemporal Mapping of Population in Europe: The ‘ENACT’ Project in a Nutshell.” Proceedings of the 57th European Regional Science Association (ERSA) Congress, Groningen, The Netherlands, 17 p.
   Google Scholar
• Ben-Asher, Z., H. Gilbert, H. Haubould, G. Smith, and G. Strand. 2013. HELM-Harmonised European Land Monitoring: Findings and Recommendations of the HELM Project. Tel-Aviv: The HELM Project.
   Google Scholar
• Bossard, M., J. Feranec, and J. Oťaheľ. 2000. CORINE Land Cover Technical Guide – Addendum 2000. Technical Report 40. Copenhagen: European Environment Agency. http://www.eea.europa.eu/publications/tech40add.
   Google Scholar
• Breiman, L. 2001a. “Random Forests.” Machine Learning 45 (1): 5–32. doi: 10.1023/A:1010933404324
   Web of Science ®Google Scholar
• Breiman, L. 2001b. “Statistical Modeling: The Two Cultures (with Comments and a Rejoinder by the Author).” Statistical Science 16 (3): 199–231. doi: 10.1214/ss/1009213726
   Web of Science ®Google Scholar
• Büttner, G. 2014. “CORINE Land Cover and Land Cover Change Products.” In Land Use and Land Cover Mapping in Europe, edited by I. Manakos and M. Braun, 55–74. Dordrecht: Springer.
   Google Scholar
• Cruickshank, M. M., R. W. Tomlinson, and S. Trew. 2000. “Application of CORINE Land-Cover Mapping to Estimate Carbon Stored in the Vegetation of Ireland.” Journal of Environmental Management 58 (4): 269–287. doi: 10.1006/jema.2000.0330
   Web of Science ®Google Scholar
• Diaz-Pacheco, J., and J. Gutiérrez. 2014. “Exploring the Limitations of CORINE Land Cover for Monitoring Urban Land-Use Dynamics in Metropolitan Areas.” Journal of Land Use Science 9 (3): 243–259. doi: 10.1080/1747423X.2012.761736
   Google Scholar
• Dorn, H., T. Törnros, and A. Zipf. 2015. “Quality Evaluation of VGI Using Authoritative Data—A Comparison with Land Use Data in Southern Germany.” ISPRS International Journal of Geo-Information 4 (3): 1657–1671. doi: 10.3390/ijgi4031657
   Web of Science ®Google Scholar
• EEA (European Environment Agency). 2007. “CLC2006 Technical Guidelines.” EEA Technical Report No 17/2007. 66 p. ISSN 1725–2237.
   Google Scholar
• Estima, J., and A. Painho. 2015. “Investigating the Potential of OpenStreetMap for Land Use/Land Cover Production: A Case Study for Continental Portugal.” In OpenStreetMap in GIScience, edited by J. Jokar Arsanjani, A. Zipf, P. Mooney, and M. Helbich, 273–293. Cham: Springer International Publishing.
   Google Scholar
• European Commission. 2011. “Mapping Guide for a European Urban Atlas [2006].” 30 p. https://www.eea.europa.eu/data-and-maps/data/urban-atlas/mapping-guide/urban_atlas_2006_mapping_guide_v2_final.pdf.
   Google Scholar
• European Commission. 2016. “Mapping Guide for a European Urban Atlas v4.7 [2012].” 39 p. http://land.copernicus.eu/user-corner/technical-library/urban-atlas-2012-mapping-guide-new.
   Google Scholar
• Eurostat. 2008. NACE Rev. 2 – Statistical Classification of Economic Activities in the European Community. Luxemburg: Office for Official Publications of the European Communities.
   Google Scholar
• Fan, H., A. Zipf, Q. Fu, and P. Neis. 2014. “Quality Assessment for Building Footprints Data on OpenStreetMap.” International Journal of Geographical Information Science 28 (4): 700–719. doi: 10.1080/13658816.2013.867495
   Web of Science ®Google Scholar
• Feick, R., and C. Robertson. 2015. “A Multi-Scale Approach to Exploring Urban Places in Geotagged Photographs.” Computers, Environment and Urban Systems 53: 96–109. doi: 10.1016/j.compenvurbsys.2013.11.006
   Web of Science ®Google Scholar
• Ferri, S., V. Syrris, A. Florczyk, M. Scavazzon, M. Halkia, and M. Pesaresi. 2014. “A New Map of the European Settlements by Automatic Classification of 2.5 m Resolution SPOT Data.” 2014 IEEE Geoscience and Remote Sensing Symposium, 1160–1163.
   Google Scholar
• Fisher, P., A. Comber, and R. Wadsworth. 2005. “Land Use and Land Cover: Contradiction or Complement.” In Re-Presenting GIS, edited by D. J. U. Peter Fisher, 85–98. Chichester: John Wiley and Sons.
   Google Scholar
• Fonte, C., M. Minghini, J. Patriarca, V. Antoniou, L. See, and A. Skopeliti. 2017. “Generating Up-to-Date and Deled Land Use and Land Cover Maps Using OpenStreetMap and GlobeLand30.” ISPRS International Journal of Geo-Information 6 (4): 125. doi: 10.3390/ijgi6040125
   Web of Science ®Google Scholar
• Frias-Martinez, V., and E. Frias-Martinez. 2014. “Spectral Clustering for Sensing Urban Land use Using Twitter Activity.” Engineering Applications of Artificial Intelligence 35: 237–245. doi: 10.1016/j.engappai.2014.06.019
   Web of Science ®Google Scholar
• Gallego, F., F. Batista, C. Rocha, and S. Mubareka. 2011. “Disaggregating Population Density of the European Union with CORINE Land Cover.” International Journal of Geographical Information Science 25 (12): 37–41. doi: 10.1080/13658816.2011.583653
   Web of Science ®Google Scholar
• Jacobs-Crisioni, C., V. Diogo, C. Perpiña Castillo, C. Baranzelli, F. Batista e Silva, K. Rosina, B. Kavalov, and C. Lavalle. 2017. The LUISA Territorial Reference Scenario 2017: A Technical Description. Luxembourg: Publications Office of the European Union. ISBN 978-92-79-73866-1.
   Google Scholar
• Jacobs-Crisioni, C., P. Rietveld, E. Koomen, and E. Tranos. 2014. “Evaluating the Impact of Land-Use Density and Mix on Spatiotemporal Urban Activity Patterns: An Exploratory Study Using Mobile Phone Data.” Environment and Planning A 46 (11): 2769–2785. doi: 10.1068/a130309p
   Web of Science ®Google Scholar
• Janssen, S., G. Dumont, F. Fierens, and C. Mensink. 2008. “Spatial Interpolation of air Pollution Measurements Using CORINE Land Cover Data.” Atmospheric Environment 42 (20): 4884–4903. doi: 10.1016/j.atmosenv.2008.02.043
   Web of Science ®Google Scholar
• Jiang, S., A. Alves, F. Rodrigues, J. Ferreira, and F. C. Pereira. 2015. “Mining Point-of-Interest Data from Social Networks for Urban Land Use Classification and Disaggregation.” Computers, Environment and Urban Systems 53: 36–46. doi: 10.1016/j.compenvurbsys.2014.12.001
   Web of Science ®Google Scholar
• Jokar Arsanjani, J., M. Helbich, M. Bakillah, J. Hagenauer, and A. Zipf. 2013. “Toward Mapping Land-use Patterns from Volunteered Geographic Information.” International Journal of Geographical Information Science 27 (12): 2264–2278. doi: 10.1080/13658816.2013.800871
   Web of Science ®Google Scholar
• Jokar Arsanjani, J., L. See, and A. Tayyebi. 2016. “Assessing the Suitability of GlobeLand30 for Mapping Land Cover in Germany.” International Journal of Digital Earth 9 (9): 873–891. doi: 10.1080/17538947.2016.1151956
   Web of Science ®Google Scholar
• Jokar Arsanjani, J., and E. Vaz. 2015. “An Assessment of a Collaborative Mapping Approach for Exploring Land Use Patterns for Several European Metropolises.” International Journal of Applied Earth Observation and Geoinformation 35: 329–337. doi: 10.1016/j.jag.2014.09.009
   Web of Science ®Google Scholar
• Kunze, C., and R. Hecht. 2015. “Semantic Enrichment of Building Data with Volunteered Geographic Information to Improve Mappings of Dwelling Units and Population.” Computers, Environment and Urban Systems 53: 4–18. doi: 10.1016/j.compenvurbsys.2015.04.002
   Web of Science ®Google Scholar
• Landis, J. R., and G. G. Koch. 1977. “The Measurement of Observer Agreement for Categorical Data.” Biometrics 33 (1): 159–174. doi: 10.2307/2529310
   PubMed Web of Science ®Google Scholar
• Langanke, T., G. Büttner, H. Dufourmont, D. Iasillo, M. Probeck, M. Rosengren, A. Sousa, P. Strobl, and J. Weichselbaum. 2016. GIO Land (GMES/Copernicus Initial Operations Land) High Resolution Layers (HRLs) – Summary of Product Specifications, Version 13. EEA Copenhagen.
   Google Scholar
• Lavalle, C., F. Batista e Silva, C. Baranzelli, C. Jacobs-Crisioni, I. Vandecasteele, A. L. Barbosa, and S. Vallecillo. 2016. “Land Use and Scenario Modeling for Integrated Sustainability Assessment.” In European Landscape Dynamics, edited by J. Feranec, T. Soukup, G. Hazeu, and G. Jaffrain, 237–262. Boca Raton, FL: CRC Press.
   Google Scholar
• Liu, Y., X. Liu, S. Gao, L. Gong, C. Kang, Y. Zhi, and L. Shi. 2015. “Social Sensing: A New Approach to Understanding Our Socioeconomic Environments.” Annals of the Association of American Geographers 105 (3): 512–530. doi: 10.1080/00045608.2015.1018773
   Web of Science ®Google Scholar
• Lloyd, A., and J. Cheshire. 2017. “Deriving Retail Centre Locations and Catchments from Geo-Tagged Twitter Data.” Computers, Environment and Urban Systems 61: 108–118. doi: 10.1016/j.compenvurbsys.2016.09.006
   Web of Science ®Google Scholar
• Mack, B., P. Leinenkugel, C. Kuenzer, and S. Dech. 2017. “A Semi-Automated Approach for the Generation of a new Land use and Land Cover Product for Germany Based on Landsat Time-Series and Lucas in-Situ Data.” Remote Sensing Letters 8 (3): 244–253. doi: 10.1080/2150704X.2016.1249299
   Web of Science ®Google Scholar
• Marin Herrera, M., F. Batista e Silva, A. Bianchi, R. Barranco, and C. Lavalle. 2015. “A Geographical Database of Infrastructures in Europe – A Contribution to the Knowledge Base of the LUISA Modelling Platform.” JRC Technical Report. EUR 27671 EN.
   Google Scholar
• Pazúr, R., and J. Bolliger. 2017. “Enhanced Land use Datasets and Future Scenarios of Land Change for Slovakia.” Data in Brief 14: 483–488. doi: 10.1016/j.dib.2017.07.066
   PubMed Web of Science ®Google Scholar
• Pei, T., S. Sobolevsky, C. Ratti, S.-L. Shaw, T. Li, and C. Zhou. 2014. “A New Insight into Land Use Classification Based on Aggregated Mobile Phone Data.” International Journal of Geographical Information Science 28 (9): 1988–2007. doi: 10.1080/13658816.2014.913794
   Web of Science ®Google Scholar
• Pesaresi, M., D. Ehrlich, S. Ferri, A. Florczyk, S. Freire, M. Halkia, and V. Syrris. 2016. Operating Procedure for the Production of the Global Human Settlement Layer from Landsat Data of the Epochs 1975, 1990, 2000, and 2014. Luxembourg: Publications Office of the European Union.
   Google Scholar
• Pesaresi, M., G. Huadong, X. Blaes, D. Ehrlich, S. Ferri, L. Gueguen, M. Halkia, et al. 2013. “A Global Human Settlement Layer from Optical HR/VHR RS Data: Concept and First Results.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6 (5): 2102–2131. doi: 10.1109/JSTARS.2013.2271445
   Web of Science ®Google Scholar
• Ríos, S. A., and R. Muñoz. 2017. “Land Use Detection with Cell Phone Data Using Topic Models: Case Santiago, Chile.” Computers, Environment and Urban Systems 61: 39–48. doi: 10.1016/j.compenvurbsys.2016.08.007
   Web of Science ®Google Scholar
• Schmit, C., M. D. Rounsevell, and I. La Jeunesse. 2006. “The Limitations of Spatial Land use Data in Environmental Analysis.” Environmental Science & Policy 9 (2): 174–188. doi: 10.1016/j.envsci.2005.11.006
   Web of Science ®Google Scholar
• Schultz, M., J. Voss, M. Auer, S. Carter, and A. Zipf. 2017. “Open Land Cover from OpenStreetMap and Remote Sensing.” International Journal of Applied Earth Observation and Geoinformation 63 (July): 206–213. doi: 10.1016/j.jag.2017.07.014
   Google Scholar
• Spyratos, S., D. Stathakis, M. Lutz, and C. Tsinaraki. 2017. “Using Foursquare Place Data for Estimating Building Block use.” Environment and Planning B: Urban Analytics and City Science 44 (4): 693–717.
   Google Scholar
• Stathopoulou, M., and C. Cartalis. 2007. “Daytime Urban Heat Islands from Landsat ETM+ and Corine Land Cover Data: An Application to Major Cities in Greece.” Solar Energy 81 (3): 358–368. doi: 10.1016/j.solener.2006.06.014
   Web of Science ®Google Scholar
• Stevens, F. R., A. E. Gaughan, C. Linard, and A. J. Tatem. 2015. “Disaggregating Census Data for Population Mapping Using Random Forests with Remotely-Sensed and Ancillary Data.” PLoS ONE 10 (2): e0107042. doi: 10.1371/journal.pone.0107042
   PubMed Web of Science ®Google Scholar
• Stewart, J. S. 1998. “Combining Satellite Data with Ancillary Data to Produce a Refined Land-Use/Land-Cover Map.” Water Resources Investigations Report 97-4203, United States Geological Survey, 11 pp.
   Google Scholar
• Theobald, D. M. 2014. “Development and Applications of a Comprehensive Land Use Classification and Map for the US.” PLoS ONE 9 (4): e94628. doi: 10.1371/journal.pone.0094628
   PubMed Web of Science ®Google Scholar
• Tomlin, C. D. 1990. Geographical Information Systems and Cartographic Modeling. Englewood Cliffs, NJ: Prentice Hall.
   Google Scholar
• Verburg, P. H., J. Steeg, A. Veldkamp, and L. Willemen. 2009. “From Land Cover Change to Land Function Dynamics: A Major Challenge to Improve Land Characterization.” Journal of Environmental Management 90: 1327–1335. doi: 10.1016/j.jenvman.2008.08.005
   PubMed Web of Science ®Google Scholar
• Yao, Y., X. Li, X. Liu, P. Liu, Z. Liang, J. Zhang, and K. Mai. 2017. “Sensing Spatial Distribution of Urban Land Use by Integrating Points-of-Interest and Google Word2Vec Model.” International Journal of Geographical Information Science 31 (4): 825–848. doi: 10.1080/13658816.2016.1244608
   Web of Science ®Google Scholar