D08

Research Abstracts on Spatial Information Science
CSIS DAYS 2016

Development of web-based GIS platform for measuring urbanization
Hao Gong and Yuji Murayama
Graduate School of Life and Environment Sciences, University of Tsukuba
Email: <hiro.gonghao@gmail.com>(1) Motivation: In connection with the exponential
increase of big data, the Internet and distributed
computing provide the technical framework forprocessing geospatial data. Web-based GIS provides agateway to explore and access geographic WEB
services, which help to visualize and analyze thegeographic data for GIS users. In particular, tomeasure and compare the urban growth process of big
cities in multidimensional way, the Web-GIS caninspire and assist to understand the urbanization
process in a more comprehensive manner (Gong andMurayama, 2015).
(2) Approach: In the first phase (data mining): the distributed GIS
data processing part. GIS data analyzing specialists
collect and process the spatial data based on theirexpertise and knowledge through the integrated local
data and cloud storage. We used the supervisedclassification method for raster image data,
employing the maximum likelihood algorithm fortraining the target areas into LULC map of 8categories. On the other hand, because of the flexibleof cloud geospatial analysis, the major vector spatial
analysis was processed in the cloud based on theopen cloud-based vector data.
 For the second phase: the web platform framework
development. The framework of front-end system iscomposed of four vital components: Google Maps
API (basic web-GIS services and cloud storage
topological layer), Google Charts API (visualizationfor statistics table data), Google Fusion Tables API(spatial information analysis and visualization forvector data) and DataTables plug-in (table view ofstatistics data). All of the processed local-based andcloud-based geospatial data in first phase will beembedded into the integrated platform.
(3) Data: Both geospatial data (three kinds of opticalimage data, cloud-based vector data) and statistical
data are utilized to extract the indicators. The opticalimaged data utilized are listed below:
 Land use / cover (LULC) map: Landsat TM/ ETM+/
OLI satellite imagery.
 Energy consumption intensity map: DMSP-OLS
nighttime imagery.
 Population data: ORNL's LandScan global
population distribution data.
(4) Results: With the web-based GIS services, it could
assist that a spatial planner has a quantifiable map
during the future decision-making and visualize thegeographic data in a more comprehensive manner(Fig.1). GIS users can check the classified LULC map,
high-resolution satellite image, terrain map, spatialinformation (administrate units, road network, realtime traffic information), and statistics data ofmultidimensional indicators through this platform.
Furthermore, people can do the advanced spatial
analysis in the website.
(5) References:Gong, H., and Murayama, Y. (2015) WEB-GIS forvisualizing land use/cover change in mega-cities indeveloping countries. Tsukuba Geoenvironmental
Sciences, 11, 21-25.

Fig.1: Screenshot for demo city in web-based GIS prototype platform. (Left) LULC map for demo city in 2000,(Right) LULC change map for demo city (2000-2015).

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