-
121por Aron, Moses Banda, Kachimanga, Chiyembekezo, Kreuels, Benno, Mailosi, Bright, Sambani, Clara, Matanje, Beatrice Lydia, Blessmann, Joerg, Chunga, Mwayi, Momba, Grace, Ndarama, Enoch, Kambalame, Dzinkambani Moffat, Connolly, Emilia, Rosenthal, Anat, Munyaneza, Fabien“…Using "shapefiles" from Open Street Maps, we mapped villages with snakebite cases. …”
Publicado 2022
Enlace del recurso
Enlace del recurso
Enlace del recurso
Online Artículo Texto -
122“…Spatial information comprise parks represented through OpenStreetMaps polygons and census tracts from the 2010 decennial US Census. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso
Online Artículo Texto -
123por Bender, Max Ernst, Edwards, Suzanne, von Philipsborn, Peter, Steinbeis, Fridolin, Keil, Thomas, Tinnemann, Peter“…Open-access tools were used for data cleaning and scientometrics (OpenRefine), geocoding (OpenStreetMaps) and to create (Table2Net), visualise and analyse co-authorship networks (Gephi). …”
Publicado 2015
Enlace del recurso
Enlace del recurso
Enlace del recurso
Online Artículo Texto -
124por Bauleo, Lisa, Giannini, Simone, Ranzi, Andrea, Nobile, Federica, Stafoggia, Massimo, Ancona, Carla, Iavarone, Ivano“…For the 7903 Italian municipalities (1 January 2020—ISTAT), 44 variables were identified, collected, and grouped into five information dimensions a priori defined: (i) geographic characteristics of the municipality, (ii) demographic and anthropogenic characteristics, (iii) mobility, (iv) socio-economic-health area, and (v) healthcare offer (source: ISTAT, EUROSTAT or Ministry of Health, and further ad hoc elaborations (e.g., OpenStreetMaps)). Principal component analysis (PCA) was carried out for the five identified dimensions, with the aim of reducing the large number of initial variables into a smaller number of components, limiting as much as possible the loss of information content (variability). …”
Publicado 2022
Enlace del recurso
Enlace del recurso
Enlace del recurso
Online Artículo Texto