SDC Lab creates regional data and proposes spatial alternatives with AI.

Problem

Existing park accessibility research only looks at 'parks'. However, the green spaces that urban residents actually use include riversides, tree-lined streets, school playgrounds, and greenery within apartment complexes. Measuring only parks means seeing only half of green space equity.

SDC Lab Approach

• •Building an integrated evaluation system for park + non-park green spaces
• •Extracting actual green spaces by combining NDVI satellite imagery + land cover maps
• •Precise measurement of accessibility differences by population group and transportation mode using G2SFCA (Gaussian-based 2-Step Floating Catchment Area)
• •Deriving policy priorities by combining with environmental justice framework

Differentiation

We don't stop at 'measuring' accessibility. Who is excluded, why, and where should we invest— we produce data that serves as policy evidence.

Problem

Analyzing urban environments requires field surveys. However, it's impossible for humans to directly evaluate the entire street environment of Seoul. Satellite imagery only shows from above and lacks on-the-ground perspective.

SDC Lab Approach

• •Automatic extraction of green view index, pedestrian environment, and street tree status through Google Street View image Semantic Segmentation
• •Development of Deep Learning-based urban green space quality prediction models
• •Comparative analysis of "greenest route" vs "fastest route" through Multi-objective Route Optimization
• •Building spatial analysis pipelines that directly query images through VQA (Visual Question Answering)

Differentiation

We design analysis systems tailored to landscape questions, not general-purpose image analysis. We don't ask "how much green space is there" but "what does this green space mean to whom."

Problem

With the enforcement of the Rural Spatial Restructuring Act, all cities and counties must establish rural spatial plans. However, data that serves as the basis for planning is insufficient. It's difficult to identify where and what residents find inconvenient, and which facilities are in accessibility blind spots.

SDC Lab Approach

• •Settlement satisfaction survey design and spatial data conversion
• •Life service facility accessibility analysis (medical, education, commercial)
• •Village-level population change simulation
• •GIS visualization of resident participation workshop data
• •Development of Shrinking Design scenarios

Differentiation

We don't stop at "collecting resident opinions." We convert opinions into data, combine them with spatial analysis, and derive actionable plans. We create decision support systems, not just planning documents.