Project Case Study

Aerial GPR Geospatial Intelligence

Geospatial analytics platform combining aerial and subsurface sensing data.

Role
Platform Architect
Domain
Geospatial Intelligence
Stack
6 technologies
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01 — Problem

The Challenge

Survey data was hard to correlate across geospatial and operational systems.

02 — Solution

Solution Approach

Built geospatial pipelines with PostGIS-backed APIs and visualization services.

03 — Architecture

Architecture Decisions

Spatially aware architecture with map tile rendering, geospatial query indexing, and API endpoints tuned for large geodata payloads.

  • PostGIS spatial indexing tuned for large geodata payloads and proximity queries.
  • Tile-based map rendering keeps the survey explorer responsive at scale.
  • Versioned endpoints emit map-ready GeoJSON to minimize client-side transforms.

04 — Stack

Technologies Utilized

Cloud

  • AWS

Backend

  • Django

DevOps

  • Docker

Geospatial

  • Mapbox
  • PostGIS

Database

  • PostgreSQL

05 — Outcome

Measurable Outcomes

Enabled faster investigation cycles with improved geospatial insight quality.

+35% Interpretation accuracy
−50% Reporting cycle time
1 Unified survey workflow

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