Earth observation for practical decisions

Terrave

Terrave uses earth observation data and geospatial intelligence to map and monitor crops, vegetation, land use, and environmental change.

Practical advice on data, validation, modelling risk, and delivery pathways for agriculture and environmental monitoring projects.

Abstract satellite-derived terrain and land-cover signal
Land intelligence from above Evidence that can be checked, explained, and used.
What Terrave Helps With

Clear advice before major spend, and practical delivery when the evidence supports it.

Terrave works where satellite imagery, field context, spatial data, and machine learning need to become a defensible decision pathway.

01

Feasibility and data suitability

Assess whether available imagery, labels, timing, resolution, and field context can support the decision you need to make.

02

Validation and model-risk review

Review sampling, accuracy claims, uncertainty, edge cases, and failure modes before a model becomes operational evidence.

03

Land-use and land-cover mapping

Design mapping workflows for vegetation, land condition, production landscapes, change detection, and monitoring questions.

04

Monitoring workflow delivery

Build repeatable geospatial workflows, review outputs, and handover pathways that can be rerun and explained.

05

Proposal and tender technical review

Strengthen EO, AI, and geospatial project scopes with grounded assumptions, realistic delivery pathways, and validation language.

How The Work Runs

Start with the decision, then work back to the data.

The useful question is rarely "can we map this?" It is whether the evidence will be good enough, repeatable enough, and clear enough to support a real-world decision.

  1. Frame the decision Clarify the land, conservation, monitoring, or investment question the spatial evidence needs to support.
  2. Test the evidence path Check data sources, labels, timeframes, uncertainty, validation options, and practical delivery risk.
  3. Deliver a usable workflow Build or review the repeatable process, outputs, documentation, and handover needed for confident use.
About Andy

Led by Dr Andy Clark.

Andy is a remote sensing and geospatial machine-learning specialist with 20+ years of applied experience across government, research, private-sector, agriculture, environment, and validation-heavy spatial products.

Terrave brings that experience into focused advisory and delivery work: clear technical judgement, practical workflows, and spatial evidence that can stand up to review.

20+ years applied experience

Remote sensing, geospatial machine learning, operational spatial workflows, and practical project judgement.

Environmental and land systems

Experience across land-use, land-cover, vegetation, production landscapes, monitoring, and spatial validation.

Independent technical advice

Data suitability, validation design, model risk, delivery pathways, and review before major investment.

Start With A Project Email

Send the question, the landscape, and the decision you need to support.

A useful first email usually includes the place or region, the decision the work needs to support, available data or field information, timing, and what would make the project useful.

Email Andy about a project