Algorithm & Data Architecture
Understanding the science behind TerraIQ's site readiness scoring system.
Data Sources
TerraIQ integrates five primary data layers to provide comprehensive site analysis. Each layer is continuously updated and validated against authoritative sources.
OpenStreetMap (OSM)
Road networks, building footprints, POIs, and land use classifications.
US Census Bureau
Demographics, income levels, population density, and employment data.
FEMA Flood Maps
Flood zone designations, risk assessments, and historical flood data.
Satellite Imagery
Land cover analysis, vegetation indices, and change detection.
Proprietary Datasets
Traffic patterns, utility infrastructure, and zoning regulations.
Scoring Model
Weighted Linear Combination (WLC)
The core scoring algorithm uses a Weighted Linear Combination model that aggregates normalized factor scores according to user-defined weights:
Distance-Decay Functions
Proximity-based factors utilize distance-decay functions to model the diminishing influence of amenities and infrastructure:
H3 Hexagonal Aggregation
Scores are computed at H3 resolution 9 (hexagons ~174m edge length) and can be aggregated to coarser resolutions for regional analysis. The hexagonal grid ensures uniform distance relationships and eliminates edge effects common in square grids.
Technology Stack
Our architecture is optimized for real-time spatial queries and interactive visualization at scale.
PostGIS
Spatial database with advanced geometric operations and indexing.
FastAPI
High-performance Python backend for spatial computations.
Next.js
React framework for the interactive mapping interface.
H3 Library
Uber's hexagonal hierarchical spatial index for grid analysis.