Building a Geospatial Analytics Team In-House:
A Guide for Linear Infrastructure Owners and Operators
As critical infrastructure evolves under the pressure of aging assets, regulatory demands, and environmental risks, geospatial analytics is no longer a “nice-to-have” – it’s a strategic necessity.
From vegetation management to climate resilience planning to regulatory compliance and more, the ability to turn asset-specific spatial data into actionable insight is key to ensuring asset reliability, safety, and sustainability.
But here’s the question:
Should you build a geospatial analytics team in-house or outsource to specialized providers while maintaining strong GIS systems and data management in-house?
Download the Guide
This Guide Helps You Decide
Inside the guide, we unpack what it takes to successfully build and manage an internal geospatial analytics team tailored for electric utilities, pipeline operators, transportation networks, and beyond. You’ll discover:
✅ Key roles and responsibilities — from GIS Analysts to Remote Sensing Specialists to Data Scientists
✅ Infrastructure and tools required to support in-house analytics
✅ Collaboration within the team to transform raw spatial data into operational insights
✅ Strategic considerations when choosing between in-house, outsourced or hybrid approaches
This Guide Looks at the Make-up of a Successful Team
📌 Geospatial Team Lead: Coordinates resources, defines KPIs, manages data providers, and aligns analytics with business goals.
📌 Remote Sensing / Earth Observation Specialist: Selects appropriate sensors, preprocesses imagery, and extracts insight from multi-sensor data sources.
📌 GIS Analyst: Manages geodatabases, visualizes spatial datasets, and ensures data integrity.
📌 Data Scientist: Trains AI/ML models, applies statistical methods, and helps detect, classify, and predict patterns.
📌 Software Developer: Builds custom geospatial apps and integrates analytics into operational workflows.
and more
