OpenStreetMap : crowd sourcing client
Location-based mobile services/applications are becoming more and more popular both on the web and in the mobile phones, according to research firm Gartner. The demand for accurate maps is rapidly growing and the possibility for the user to contribute to add details to the maps.
openaire +1 more source
Development and application of a geospatial index of urban playability for young children. [PDF]
Gemmell E +6 more
europepmc +1 more source
Mukara: A deep learning alternative to the four-step travel demand model with a case study on interurban highway traffic prediction in the UK. [PDF]
Li Y, Chen S, Jin Y.
europepmc +1 more source
A spatially disaggregated dataset of workplace locations in Warsaw for 2015 and 2025. [PDF]
Goliszek S.
europepmc +1 more source
Identifying and modeling built environment factors influencing cultural perception in metro stations: Evidence from central Shanghai. [PDF]
Feng H, Xiao X, Cheng Y, Mu R, Xiong L.
europepmc +1 more source
A unified deep learning framework integrating OpenStreetMap for multi-domain urban planning tasks. [PDF]
Chen Y, Afandi WS, Gura D, Kosenok Y.
europepmc +1 more source
Editorial: Localization and scene understanding in urban environments
Augusto Luis Ballardini +3 more
doaj +1 more source
The Spatial Distribution and Distance-Based Regulatory Compliance of Private Medicine Outlets in Two Urban Districts of Dar es Salaam, Tanzania. [PDF]
Manyanga VP +7 more
europepmc +1 more source
Fieldtrip GB: Creating a customisable mapping and data capture app for the HEFE community [PDF]
Butchart, Ben +5 more
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