| Journal: | Boletim de ciencias geodesicas |
| Database: | PERIÓDICA |
| System number: | 000456634 |
| ISSN: | 1413-4853 |
| Authors: | Elias, Elias Nasr Naim1 Amorim, Fabricio Rosa1 Schmidt, Marcio Augusto Reolon1 Camboim, Silvana Philippi1 |
| Institutions: | 1Universidade Federal do Paraná, Programa de Pós-Graduação em Ciências Geodésicas, Curitiba, Paraná. Brasil 2Universidade do Estado do Rio de Janeiro, Departamento de Engenharia Cartográfica, Rio de Janeiro. Brasil |
| Year: | 2023 |
| Volumen: | 29 |
| Number: | 2 |
| Country: | Brasil |
| Language: | Inglés |
| Document type: | Artículo |
| Approach: | Analítico, descriptivo |
| English abstract | The potential of intrinsic parameters to estimate geospatial data quality on Voluntary Geographic Information (VGI) platforms is a recurrent theme in Cartography. The spatial-temporal distribution in these platforms is very heterogeneous, depending on several factors such as input availability, number, and motivation of volunteers, especially in developing countries. The most recent approaches have been aiming to detail temporal patterns as an additional measure of quality in VGI. This research proposes a methodology to identify and analyze the behavior of the contribution parameters over time (2007-2022) of the OSM platform and differentiates the influences that affect its growth. Part of the Metropolitan region of Curitiba was the study area, subdivided into 1 x 1 km cells. The cumulative growth of contributions was calculated and later adjusted using a Logistic Regression. The obtained parameters made it possible to identify abruptly growing cells caused by external data import, mass contributions, or collective mapping activities. In addition, heterogeneity in the growth of the data available in OSM over time was evident. Furthermore, the proposed methodology promoted the investigation of a new indicator of intrinsic quality based on modelling the spatiotemporal evolution of OSM feature insertions |
| Disciplines: | Geociencias, Geografía |
| Keyword: | Geodesia, Cartografía, Calidad de datos geoespaciales, Mapas colaborativos, Parámetros intrínsecos, Regresión logística |
| Keyword: | Geodesy, Cartography, Geospatial Data Quality, Collaborative Maps, Intrinsic Parameters, Logistic Regression |
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