Ko Ko Lwin
University of Tokyo
32 Papers
95 Citations
Ko Ko Lwin is an academic researcher from University of Tokyo. The author has contributed to research in topics: Geospatial analysis & Population. The author has an hindex of 10, co-authored 30 publications. Previous affiliations of Ko Ko Lwin include National Institute of Information and Communications Technology & University of Tsukuba.
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Papers
Modelling of urban green space walkability: Eco-friendly walk score calculator
Ko Ko Lwin,Yuji Murayama +1 more
TL;DR: An integrated methodology (Remote Sensing, GIS and Spatial Web Technology) is proposed to model urban green space walkability, which enables local residents to make informed decisions that will improve their living conditions and physical health related to the neighbourhood environmental quality.
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A GIS Approach to Estimation of Building Population for Micro-spatial Analysis
Ko Ko Lwin,Yuji Murayama +1 more
TL;DR: A GIS approach using the Areametric and Volumetric methods for estimating building population based on census tracts and building footprint datasets is discussed and a standalone GIS tool for generating new building footprint with population attribute information based on user-defined criteria is implemented.
City Geospatial Dashboard: IoT and Big Data Analytics for Geospatial Solutions Provider in Disaster Management
Ko Ko Lwin,Yoshihide Sekimoto,Wataru Takeuchi,Koji Zettsu +3 more
- 01 Dec 2019
TL;DR: Establishment of a City Geospatial Dashboard, which can collect, share and visualise geospatial data collected from satellites, IoT devices, and other big data is discussed, and geovisualisation of big data analytical results such as near-real-time rainfall profiler is explained.
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Space–time multiple regression model for grid-based population estimation in urban areas
TL;DR: A space-time multiple regression model is built to estimate grid-based (500 m × 500 m) spatial resolution at multi-temporal scale (30-min intervals) population data based on the space- time relationship among geospatially enabled person trip (PT) survey data and incorporate both mobile call and geotagged Twitter (GT) data.
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Estimation of Building Population from LIDAR Derived Digital Volume Model
Ko Ko Lwin,Yuji Murayama +1 more
- 01 Jan 2011
TL;DR: In this paper, the authors discuss new dasymetric mapping technique based on GIS estimated building population which was computed from building footprints, census tract and LIDAR derived Digital Volume Model DVM.
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