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See when and where elevated wildfire risk occurs.
Year-round spectral data identifies vegetation stress earlier, providing more insight for prioritized vegetation and asset inspections.
Not a hypothetical model, not NDVI.
Indices like NDVI do not detect vegetation stress as early or precisely as Raster Report's patent-pending analysis.
NDVI
Above: Pre-ignition conditions over 100 days before the Mountain Fire started on November 6th, 2024. The difference between Raster Report's analysis and indices like NDVI is compelling. This is not gambling with a hypothetical scenario, these are actual spectral signatures showing where elevated fire risk is highest at a specific time.
Covering large areas, seeing results at local scales.
Monitoring your entire system with actionable results delivered at the asset level.
Precision within High-Fire-Threat Districts.
When elevated fire risk is at regional scales all the time, make informed decisions with current state data at the asset level.
Source: CPCU High Fire Threat District (HFTD), www.cpcu.ca.gov California Public Utilities Commission, 03_01_2025
Lowering your enterprise expenditures.
Enable your asset and vegetation inspection cycles to be more cost effective by sending the right resources to the right locations at the right time.
Strengthening your grid reliability.
A stronger grid is a safer grid. Treat easements and harden assets first in locations of elevated wildfire risk.
Informing Operational and Planning decisions.
Historical and current data analyses inform day to day and long-term decisions for vegetation and asset management, new construction, and strategic deployment of weather stations, cameras and sensors.
Refining fire behavior models.
Dynamic spectral vegetation data inputs make risk/behavior/consequence scenarios more spatially and temporally relevant.
Improving mid-cycle inspections.
When high resolution imagery or lidar finds thousands to millions of encroachments, know which ones to address first.
Lower O&M costs from Day 1.
No new software.
No integrations.
No new training.
Multiple deliverable options to best suit your needs.
There is no need to implement new software or conduct extensive training, which minimizes the growing pains of organizational change management.
Reducing aerial inspection costs.
LiDAR, drone, and fixed wing fly overs and other airborne inspection methods can cost millions of dollars, especially in large service territories. Prioritize where those flights go by knowing where the highest fire risk locations are.
01 / Gather
The most recent spectral satellite imagery is collected and configured for geospatial analysis.
02 / Process
Vegetation data analytics are conducted to identify specific locations of elevated vegetation stress throughout the year.
03 / Deliver
Concise, easy to interpret results are provided in a format that best suits your needs.
Making Your Sensor Investment Worthwhile
Our long-term analysis ensures that every sensor—be it cameras, weather stations, or other devices—is deployed in the most strategic location.
By deploying sensors to the most elevated fire risk areas, you gather vital data where it matters most.
This targeted approach maximizes the effectiveness of your investment, ensuring optimal performance and reliability for your projects while protecting lives and property.
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