I delve into the strategic use of historical accident data to identify high-risk zones. This session showcases how the Bangkok Metropolitan Administration has employed GIS analysis on historical accident data to pinpoint areas with a higher incidence of accidents. The insights derived from this analysis inform targeted physical improvements, contributing to a safer urban environment. Additionally, I investigate the power of analyzing retrospective traffic data to identify congestion hotspots. By examining historical traffic patterns, we pinpoint road segments experiencing the highest congestion. This granular understanding enables informed decision-making in urban planning and traffic management, offering practical solutions to alleviate congestion. These insights are derived from GIS and Map API.
Bringing data from surveys and public data through a reliable analysis process. There are various theories supporting every step of the analysis in order to get the accuracy and precision results and forward them to the team that develops for design master plans and implements. Including bringing the analysis results to be displayed on the platform for ease of use.
OpenStreetMap (OSM) is a well-known crowdsourced map collaboratively created by global communities. The data production of OSM relies on a geographical data model enabling volunteers to collaboratively contribute their data on the single platform. The data production mechanism of OSM actually gets attention from map authorities which attempt to move towards a collaboration-based framework. However, the data production of map authorities is required to be compatible with institutional policies and standards. The top-down approach of map authorities is actually different from the bottom-up approach of OSM. There is a gap between OSM’s collaborative model and the institutional model of map authorities. To embed the OSM framework into the production mechanism of map authorities, the research starts with investigation of the differences in feature models between OSM and the map authority of Taiwan. According to the investigation of the feature models, data transformation tools have been designed to transfer institutional data to OSM. The data transformation enables the institutional data providers to contribute their data on the OSM-based map platform. The institutional data providers can be surveyors of the map authority or other agencies taking charge of geographic data such as river, land covers, forest, etc. This OSM-based collaboration model is actually created for instructional data contribution but not for crowdsourced data contribution. Moreover, the insertion of the OSM mechanism in map authorities certainly has impacts and conflicts with institutional data production. This research analyzes the possible impacts and conflicts. It would be valuable for map authorities to adopt the collaborative model for their data production.
Embark on a three-year exploration through Northern Thailand’s remote landscapes in this 25-minute talk at FOSS4G Thailand and State of the Map ASIA 2023. Using an off-road motorcycle and software, I’ll unveil how innovative tools have reshaped outdoor mapping in challenging terrains.
Discover how our mapping methodologies evolved, leading to significant enhancements in road and outdoor trail coverage. This journey showcases technology’s potential to capture accurate data where traditional methods fall short.
Explore the transformation of Thailand’s highway classification system, powered by collaborative insights. Engage with the practice of community-driven mapping as I share practical approaches for nurturing an outdoor mapping community in Northern Thailand.
Join me in this journey of exploration, collaboration, and the boundless opportunities that outdoor mapping presents.