TY - GEN
T1 - Exploratory analysis of OpenStreetMap for land use classification
AU - Estima, Jacinto
AU - Painho, Marco
N1 - Estima, J., & Painho, M. (2013). Exploratory analysis of OpenStreetMap for land use classification. In GEOCROWD 2013 - Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information (pp. 39-46). (GEOCROWD 2013 - Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information). Association for Computing Machinery. https://doi.org/10.1145/2534732.2534734
PY - 2013/1/1
Y1 - 2013/1/1
N2 - 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.
AB - 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.
KW - GIS
KW - land use
KW - OpenStreetMap
KW - volunteered geographic information
UR - http://www.scopus.com/inward/record.url?scp=84889667874&partnerID=8YFLogxK
U2 - 10.1145/2534732.2534734
DO - 10.1145/2534732.2534734
M3 - Conference contribution
AN - SCOPUS:84889667874
SN - 9781450325288
T3 - GEOCROWD 2013 - Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information
SP - 39
EP - 46
BT - GEOCROWD 2013 - Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information
PB - ACM - Association for Computing Machinery
T2 - 2nd ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information, GEOCROWD 2013
Y2 - 5 November 2013 through 5 November 2013
ER -
