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Spatial Planning Science Lab
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The lab develops methods for analyzing spatiotemporal data to create an environment where people can discuss the future of their region.
AboutAbout the lab
Analyzing spatiotemporal data to contribute to community development.
The Spatial Planning Science Lab develops methods for analyzing data on socioeconomic activities that carry time and location information.
Analyzing such spatiotemporal data may make it possible to extract information on how people actually act in a region, as well as information that can serve as a basis for discussing its future.
Based on analyses of current conditions, the lab aims to create an environment where people can discuss the future of their region and to contribute to better community development.
Methods for analyzing spatial heterogeneity are applied to, for example, identifying the factors behind real estate prices that differ from district to district and locating areas with frequent crime.
Key terms
- Spatiotemporal data
- Data with time and geographic location attached. In this lab, it refers to recorded observations of socioeconomic activities.
- Spatial heterogeneity
- The property that the process generating a spatial phenomenon differs from place to place.
- Interpolation
- A method of estimating values at any location or point in time based on known data.
ResearchResearch themes
The lab develops methods for analyzing data on socioeconomic activities that carry time and location information (spatiotemporal data). Based on analyses of current conditions using spatiotemporal data, it aims to create an environment where people can discuss the future of their region.
*Illustrative imageMethods for analyzing spatial heterogeneity
The lab develops methods for analyzing how the process that generates a spatial phenomenon differs from place to place. These are applied to identifying the factors behind real estate prices that differ from district to district and to locating crime hotspots.
*Illustrative imageInterpolating real estate prices using spatiotemporal correlation
To provide real estate price information for any location and any point in time, the lab conducts analyses that make use of a property of spatiotemporal data: data close in time or place tend to be similar.
*Illustrative imageEffects of disaster risk and risk reduction measures on regions
The lab uses analyses of real estate prices observed across space and time to clarify how the existence of disaster risk, and its reduction, has affected regions.
MembersFaculty
- Associate ProfessorRyo Inoue
- Project Assistant Professor (Research)Peng Peng
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “PANO-X GIS BASED 360 PANORAMIC AUTOMATION SYSTEM” Panoramicweb / CC BY-SA 4.0 (cropped)
- Methods for analyzing spatial heterogeneity: “Crime hotspots - STAC Ellipses” Roach006 / CC BY-SA 3.0 (cropped)
- Interpolating real estate prices using spatiotemporal correlation: “Apartment buildings on the bank of East River, Manhattan, New York City” Jakub Hałun / CC BY 4.0 (cropped)
- Effects of disaster risk and risk reduction measures on regions: “Lancaster New City Cavite Southern Barangay Navarro Flood Hazard map” Ervin Malicdem / CC BY-SA 4.0 (cropped)
- Related lab (Political Communication Lab): “Historical documents in the Swedish National archives” OlesiaLukaniuk (WMUA) / CC BY-SA 4.0 (cropped)
- Related lab (Linguistic Text Analysis Lab): “Tree diagram for "How kind you are"” Brett / CC BY-SA 4.0 (cropped)
- Related lab (Language Informatics Lab): “Data center infrastructure in the United States” DOE/National Renewable Energy Laboratory (NREL) / Public domain (cropped)
- Related lab (Cognitive Psychology and Informatics Lab): “Optical Illusion (67183712)” Dennis Sylvester Hurd / CC BY 2.0 (cropped)
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