R2SFCA — Reconciled 2SFCA
A reconciled two-step floating catchment area model for measuring spatial accessibility to healthcare, services, and amenities.
Paper: Reconciling 2SFCA and i2SFCA via distance decay parameterization — IJGIS, 2025.
Products · PlaceXAI Toolkit
PlaceXAI Toolkit
Open-source Python packages for accessibility, service-area modeling, and explainable geospatial machine learning — all on PyPI and GitHub.
PG-MST — Physics-informed GNN + MST
A physics-informed graph neural network with minimum spanning trees for network-based service-area delineation.
Paper: Physics-informed graph learning for spatially contiguous, capacity-constrained hospital service areas — CEUS, 2026.
XGeoML — Explainable Geospatial ML
Train spatial machine-learning models with built-in, place-aware interpretability and feature attribution.
Paper: An ensemble framework for explainable geospatial machine learning models — IJAEOG, 2024.