Applying earth observation, geospatial analysis, machine learning, and AI to environmental and societal challenges.
KELP works across earth observation, spatial analysis, machine learning, and the domains where they apply, connecting the right methods and tools around each problem.
Analysing satellite imagery to monitor environmental conditions across space and time. Water quality, vegetation, land cover, ecosystem health, tracked from orbit and validated on the ground.
Integrating spatial datasets to find patterns, assess risk, and support location-based decisions. From national projections down to asset level.
Statistical modelling, deep learning, and AI used where they earn their place. Predictive modelling, image classification, anomaly detection, and scenario forecasting.
Turning analysis into interactive maps, dashboards, and reproducible code, built so decision makers can act on the findings without reading the methodology.
The first comprehensive vulnerability forecast in the UK water sector. Spatial Priority Services Register mapping, demographic projections, now informing investment and regulatory submissions across two service areas covering around two million customers.
Read the case →Scientific publications from the founder's academic research underpin KELP's methods. Peer-reviewed work across leading earth observation and environmental science journals, plus LAQUA, an open-source satellite water quality tool designed for water managers.
Read research →