CatRisk Mapping

High-resolution satellite imagery feeds catastrophe models to quantify flood, wildfire, and storm hazards, improving underwriting and risk mitigation decisions.

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How does it work?

Traditional cat models rely on coarse or outdated hazard inputs, leading to inaccurate risk estimates and suboptimal capital allocation. Integrating near real-time satellite observations enriches hazard detection and model calibration, enhancing precision and reducing uncertainty in risk assessments.

Enhanced Hazard Detection: High-resolution satellite imagery detects emerging hazards such as floods, wildfires, and storms with greater spatial precision. Early detection enables proactive risk management and faster response planning.
Improved Model Accuracy: Satellite-derived hazard parameters calibrate cat models with updated, location-specific data. This reduces estimation errors and improves loss projections by up to 20%.
Real-time Monitoring: Near real-time satellite feeds track hazard evolution continuously across large regions. Underwriters and risk managers gain instant visibility into unfolding events.
Comprehensive Risk Insights: Combining multi-spectral and temporal satellite data reveals vulnerability patterns and exposure distributions. This holistic view supports scenario analysis for diverse peril types.
Cost-effective Data: Leveraging publicly available and commercial satellite sources lowers dependency on expensive ground surveys. Automated ingestion pipelines minimize manual processing and operational costs.
Regulatory Compliance: Accurate, auditable satellite-based hazard maps support reporting for Solvency II and other regulatory frameworks. Transparent data provenance enhances stakeholder trust and audit readiness.

Frequently asked questions

Have a different question and can’t find the answer you’re looking for? Reach out to our support team by sending us an email and we’ll get back to you as soon as we can.

How does satellite-based cat modeling compare to traditional ground surveys?: Satellite-based approaches offer broader spatial coverage and more frequent updates than localized ground surveys, reducing data gaps in remote regions. However, ground truthing remains essential to validate and refine satellite-derived parameters.
Why is satellite data popular for hazard analysis?: Satellite imagery provides consistent, repeatable observations across vast areas, making it ideal for tracking dynamic perils at scale. Its growing availability and improved resolution have increased adoption across insurance and risk management sectors.
What are limitations of using satellite imagery for catastrophe models?: Cloud cover and revisit intervals can obscure hazard features, delaying detection in some cases. Additionally, high-resolution commercial imagery may incur licensing costs that affect project budgets.
Can I use satellite data alongside other remote sensing sources?: Yes, combining satellite data with LiDAR, aerial drones, and ground sensors creates a multi-source framework that enriches hazard characterization. Integrating diverse inputs enhances model calibration and reduces uncertainty.
How frequently can satellite-based hazard maps be updated?: Update frequency depends on the satellite constellation and data licensing; some platforms offer daily revisits while high-resolution imagery may update weekly. Automated processing pipelines can deliver new hazard layers within hours of data acquisition.
What are alternatives to satellite-based hazard analysis?: Alternatives include in-situ sensor networks, crowd-sourced damage reports, and UAV surveys, each offering different trade-offs in coverage, cost, and timeliness. While satellites excel at large-scale monitoring, combining them with local data often yields the best results.

Geospatial AI Platform

Intelligence

AI & foundation models

Deep-learning and foundation models turn raw imagery into ready-to-use insights, so you ship answers instead of training pipelines.

Experience

Conversational workflow

Ask questions in plain language and the platform responds with charts, visualizations, and next step suggestions.

Speed

GPU-accelerated cloud

Cloud-native architecture spins up on-demand GPU clusters that scale from a single scene to global archives—no manual ops, no bottlenecks.

Data

Any sensor, any format

Optical, SAR, drone, IoT, vector or raster—ingest, fuse, and analyze without conversion headaches.

Visualization

Insight you can see

Real-time 2D / 3D maps and export-ready plots make results clear for engineers, execs, and clients alike.

Boost your productivity. Experience Geospatial AI.

Turn satellite, drone, and sensor data into clear, real-time insights using powerful AI – no complex setup, just answers you can see and act on.

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