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Spatial Planning Science Lab
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A lab that uses data on when and where things happen to build a foundation for discussing the future of regions.
AboutAbout the lab
Better regional management through spatiotemporal data.
The Spatial Planning Science Lab develops methods for analyzing data tagged with time and location.
Data recording social and economic activity increasingly retains detailed information on when and where events occurred.
From such data, the lab reads the reality of people's activities and creates material for discussing the future of regions.
The lab works on themes that shape how regions function, such as real estate prices, crime, and disaster risk.
Key terms
- Spatiotemporal data
- Data tagged with time and location information, recording when and where something occurred
- Spatial heterogeneity
- The phenomenon in which the same event occurs differently, or has different causes, from place to place
- Interpolation
- Estimating values at locations or points in time with no observations, based on values observed nearby
ResearchResearch themes
From large volumes of data tagged with time and geographic location, the lab reads the reality of people's activities at the scale of nations, regions, cities, and even smaller districts. By developing analytical methods, it aims to create an environment in which the future of a region can be discussed on the basis of an analysis of its current state.
*Illustrative imageAnalyzing differences from place to place
The lab develops methods for analyzing how the same phenomenon occurs differently from place to place (spatial heterogeneity). It applies them to uncovering the factors behind real estate prices, which differ from district to district, and to identifying areas where crime occurs frequently.
*Illustrative imageFilling in real estate prices across space and time
Using the property of spatiotemporal data that observations close in time or place tend to be similar, the lab estimates (interpolates) real estate prices at locations and points in time where no data exist. The aim is to make price information available for any place and any time.
*Illustrative imageHow disaster risk affects regions
The lab investigates how the presence of disaster risk, and the measures taken to reduce it, have affected regions. It clarifies these effects by analyzing real estate prices observed over time and space.
MembersFaculty
- Associate ProfessorRyo Inoue
- Project Assistant ProfessorZhan Peng
VoicesStudent voices
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Report an errorAbout the images
For images provided to us or used with permission, the source is listed on each line. Wikimedia Commons images are illustrative and were not taken at the lab (they are cropped). Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Aerial view of suburban housing in Blacklick, Ohio, October 2024” Pi. / CC BY-SA 4.0 (cropped)
- Analyzing differences from place to place: “View from Tokyo Skytree 04” ume-y / CC BY 2.0 (cropped)
- Filling in real estate prices across space and time: “View from Tokyo Skytree 01” ume-y / CC BY 2.0 (cropped)
- How disaster risk affects regions: “Flooded houses, Chertsey (geograph 3812479)” Alan Hunt / CC BY-SA 2.0 (cropped)
- Related lab (Transport Control Lab): “Waru Interchange and City of Tomorrow Superblocks, bordering with Surabaya and Sidoarjo (July 2018).” consigliere ivan from Bontang, Indonesia / CC BY 2.0 (cropped)
- Related lab (Advanced Computational Mechanics Lab): “Sediment Flow Simulation” 東北大学 先進計算力学研究室 / 研究室からの
提供 (cropped) - Related lab (IT Communication Design Lab): “Central Library, Indianapolis Public Library, The Learning Curve” MSwierenga / CC0 (cropped)
- Related lab (Disaster Geoinformatics Lab): “Mapping flood with Envisat's radar” Envisat satellite / CC BY-SA 3.0 igo (cropped)
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