Late detection of remote wildfires heavily contributes to global warming as they emit tonnes of CO2 into the atmosphere. Most of the damage caused by fires is due to extreme wildfire events, which account for about 2% of the total fires. Prevention, quick detection, and real-time monitoring of wildfires are therefore essential.
Existing non-space solutions for wildfire detection (watchtowers, camera systems, drones, helicopters, and wireless sensors) are often inadequate and financially unviable, especially for monitoring larger forest areas. Space-based solutions could theoretically close this gap, but available solutions on the market suffer from a lack of accessibility, usability, and data sources.
We identified a clear need on the market for an all-in-one global wildfire detection, alert, and monitoring service based on all available data sources (space and non-space). This led us to develop the so-called Wildfire System (WFS), a progressive Web App, that is already on the market and incorporates more satellite data sources than any other system and offers multiple overlays (e.g., weather, terrain, wind) based on customers’ demand. The WFS does not only enable the early detection of extreme wildfire events but also of minor fires all around the globe.
However, existing satellite data sources are only partly sufficient, primarily due to data gaps in the afternoon, where many fires ignite. This leads to the need for more thermal-infrared satellite data, especially at local afternoon times, to close this gap. The ongoing miniaturization of satellites and their payloads offers the right solution to address this problem. Therefore we want to close current thermal-infrared satellite data gaps by placing our miniaturized thermal-infrared imager in low-earth orbit to complement the existing satellite data sources. This activity brings us closer to our mid-term goal of launching our so-called minimum viable constellation of about 14 nanosatellites, placed in a sun-synchronous orbit at local afternoon time to close a gap of around 6 hours, where currently no space-based wildfire data exists. This gap is critical for our customers, as the occurrence of wildfires peaks exactly at that time. This minimum viable constellation can then be complementary to existing larger missions.
Wildfires’ environmental, economic, and societal problems show a clear need for an all-in-one downstream service for wildfire management based on all available data (space and non-space). New satellite data is needed to address the problem of insufficient revisit times and resolution. We believe that our end-to-end solution strongly addresses this problem and can be the solution globally.
The key customer segments targeted by our product are in the B2G (public) and B2B (private) sectors. Governments, fire services, commercial forestry companies, insurances, and environmental organizations are among the most important users of WFS.
In B2G (business to governmental), the problems and needs of wildfire services are already well understood by OroraTech, as we already have paying customers within this segment. Besides having more accurate short-term fire risk assessments, early fire detection and a real-time overview of fire spread are two needs identified in this group.
In B2B (business to business), commercial forestry has been the early adopter of our system. Faced with similar challenges as the public sector, commercial wood and pulp producers usually have a denser network of fire detection technologies and staff in place. Costs of each hectare lost to fires can directly be translated into willingness to pay for enhanced prevention measures and faster early detection.
One of the most promising sectors is the insurance industry (direct insurers, insurance brokers, re-insurers) with a specific demand for high-quality data, reliability, and proven track records. Active fire monitoring is regarded as less of an issue compared to sophisticated fire risk analyses and improvements for more efficient damage evaluations.
Wildfires are a global problem therefore we want to provide our Global Wildfire Warning system to any potential customer in any country around the world.
Our goal is for WFS to offer the lowest latency for wildfire detection and monitoring on the market and incorporate the additional data of one own developed nanosatellite. This can be translated into a significant improvement in our offer for customers: We can prove the quality of our data from space and, in general, demonstrate the viability of using nanosatellites for low-cost supplementation of thermal-infrared data from space.
Our current wildfire service aggregates the most satellite data sources on a global scale, standing out in comparison to existing publicly available downstream service solutions. As a result, detection times are lower, and monitoring capabilities are higher.
Direct fast alerts and updates are automatically sent to users for their area of interest, enabling them to deploy fire suppression resources optimally. Innovative features like the hotspot-fusion of all gathered data and the easy-to-use overlays of wind, weather, and other data differentiate us from what is available on the market. Unlike other solutions, we also incorporate non-space data sources from our customers, like automated cameras and other sensors. All our development is thereby closely coupled to the feedback of our customers and pilot users and thus really answers the demand on the market (co-creation concept).
Concerning solutions on the market that build upon non-space data sources, we can offer higher scalability and more cost-efficient coverage of larger areas. Each of the existing solutions can only cover a very small part of Earth’s land and thus, is inadequate and financially unviable when it comes to larger areas, like countries, or even the whole planet.
Furthermore, there are also several areas of innovation for our patent-pending multispectral thermal infrared imager: it is miniaturized for the volumetric constraints of a CubeSat. It can sense mid-wave as well as long-wave infrared radiation, which makes it the ideal choice for detecting high-temperature events like wildfires. As data delay is significant for our customers, we have developed a GPU-based processing module for on-orbit wildfire detection (classical and AI algorithms possible). Another key-innovation of our R&D development complements this: an inter-satellite modem, which allows the near-real-time downlink of key parameters of the detection, cutting down the delay of wildfire alert dissemination from several hours to minutes.
As of today, the WFS aggregates the most satellite data sources on a global scale, standing out in comparison to existing publicly available downstream service solutions. Data from 21 existing satellites and non-space sensors in our proprietary platform are processed, merged, evaluated, and made available on a user-friendly interface. This significantly accelerates, digitizes, and simplifies the process of wildfire detection and monitoring. Updates and new functionalities for our platform are prioritized according to the extensive feedback we get from pilot users and existing customers.