Integrate Geospatial Data from Google Places API and OpenStreetMap for Gas Station Mapping in Hanoi, Vietnam

Visualizing the spatial distribution of gas stations supports the assessment of service coverage, optimization of fuel supply, urban planning, and environmental impact control related to the emission of hazardous gases during fuel distribution. This study focuses on mapping the distribution of gas stations across Hanoi by integrating data from Google Places API and OpenStreetMap into a Geographic Information System (GIS). Using Python programming, data were collected, cleaned, and processed to determine the location, density, and spatial distribution of gas stations throughout the city. The results reveal that in 2024, Hanoi had a total of 382 gas stations, with an average density of 0.11 stations per km² and 0.05 stations per 1,000 inhabitants. The spatial distribution varies significantly between urban and suburban districts. This approach is scalable to other cities and provides a foundation for estimating vapor emissions and other pollutants generated during fuel distribution, contributing to improved energy management and sustainable development toward net-zero emissions in the future.

Authors

Institutions

Publication Details

Journal
VNU Journal of Science Earth and Environmental Sciences
Published
2025-11-15
DOI
https://doi.org/10.25073/2588-1094/vnuees.5429
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrate Geospatial Data from Google Places API and OpenStreetMap for Gas Station Mapping in Hanoi, Vietnam

Thanh Viet Nguyen, Hoàng Anh Lê, Duong Thi Phuong
VNU Journal of Science Earth and Environmental Sciences
Atmospheric and Environmental Gas Dynamics
article

Integrate Geospatial Data from Google Places API and OpenStreetMap for Gas Station Mapping in Hanoi, Vietnam

Thanh Viet Nguyen, Hoàng Anh Lê, Duong Thi Phuong
article en

Abstract

Visualizing the spatial distribution of gas stations supports the assessment of service coverage, optimization of fuel supply, urban planning, and environmental impact control related to the emission of hazardous gases during fuel distribution. This study focuses on mapping the distribution of gas stations across Hanoi by integrating data from Google Places API and OpenStreetMap into a Geographic Information System (GIS). Using Python programming, data were collected, cleaned, and processed to determine the location, density, and spatial distribution of gas stations throughout the city. The results reveal that in 2024, Hanoi had a total of 382 gas stations, with an average density of 0.11 stations per km² and 0.05 stations per 1,000 inhabitants. The spatial distribution varies significantly between urban and suburban districts. This approach is scalable to other cities and provides a foundation for estimating vapor emissions and other pollutants generated during fuel distribution, contributing to improved energy management and sustainable development toward net-zero emissions in the future.

VNU Journal of Science Earth and Environmental SciencesVol. 41(2S)
VNU University of Science (VN)
Openalex Percentile: Top 68%
Atmospheric and Environmental Gas Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.