Reporting Forest Fires from Space in 7 Minutes
The importance of generating near real-time space intelligence to detect forest fires and how can we achieve this within 7 minutes.
Image: NASA (Source: CNN)
As a person deeply entrenched in the world of space intelligence, I find myself increasingly drawn to the pressing problem of forest fires. We are all aware of the profound value that forests offer to us. Regrettably, these critical ecosystems are under siege from wildfires, with 9.3 million hectares of tree cover loss globally. In 2021 alone, fires scorched over 4.6 million hectares of forest in the United States, marking the third-largest wildfire season on record. This devastation isn't just about the environment - in Indonesia alone, nearly 10 million children are at risk from air pollution caused by forest fires.
We have been using traditional methods like improved fire management techniques and community education for some time now, but these approaches haven't been as effective as we'd hoped, and their implementation demands significant resources.
But here at Little Place Labs, we're exploring a promising approach to halting these fires - leveraging the power of space intelligence.
One significant development has been the capacity to generate near real-time space intelligence. By processing satellite imagery in orbit and only downlinking useful analytics, we can detect forest fires with unprecedented speed and accuracy. Regarding forest fires, the swifter the detection, the more effective the response.
Our mission at Little Place Labs is to detect these fires as swiftly as possible. We aim to reduce the detection time to just 7 minutes, enabling immediate action and minimizing potential damage.
So, how does this system work?
STEP-1: (1 minute)
Satellites equipped with sensors, such as thermal or infrared ones, collect data by scanning the Earth's surface. A satellite in low earth orbit (LEO) can scale a length of 500 km in just over 1 minute (approx 65 seconds). Depending on the onboard sensors, a typical amount of raw data generated could be somewhere between 2GB to 10 GB. This is a lot of data created in approx 1 minute.
STEP-2: (5 minutes)
This data is processed in orbit using complex data analytics techniques to look for wildfires, burnt areas and nearby water bodies. Only the imagery where events of interest are spotted is preserved. The rest is discarded. The aim is to carry out by a constellation of satellites so that the temporal resolution (revisit rate) is high. Data processing takes several minutes to crunch through several gigabytes of raw data using only the compute available on a satellite powered by solar panels (~50 watts). Little Place Labs specialises in building super-optimal Machine Learning applications which require substantially less compute resources.
STEP-3: (1 minute)
Following the analysis, alerts are generated and passed on to the relevant authorities and emergency responders in the corresponding geography. This is done using inter-satellite links such as LEO-GEO-Ground for persistent connectivity. This information is invaluable in making decisions about resource allocation, evacuation planning, and firefighting strategies.
STEP-1 + STEP-2 + STEP-3 = 7 minutes
Global reach: Satellites can cover vast areas on Earth where monitoring terrestrially could be impossible or too expensive. Once a solution works in a given geography, it can be easily scaled to another geography with little tweaks.
Muti- Use Case: The supported constellation of satellites described above not only can support wildfire detection but can also be used for several other detection, segmentation and monitoring activities in near real-time such as near-real-time maritime monitoring, urban activities and more.
Here at Little Place Labs, we're looking to demonstrate this system soon, and once proven, this technology will be scaled up to several satellites on several platforms. We're running several experiments to bring intelligence to satellites and building industry partnerships to address this challenge more effectively.
We're also encouraged by initiatives like XPRIZE Wildfire, a global competition offering $11 million in prize money for teams that can develop fully-autonomous capabilities to detect and extinguish wildfires.
As I reflect on our mission, I am convinced that using near real-time space intelligence is a critical step forward in our efforts to combat wildfires and lessen their impact. By providing early warnings and essential information to authorities and firefighters, space intelligence becomes a reliable ally in mitigating wildfires' devastating effects. Each fire it prevents helps protect not only lives and property but also the delicate balance of ecosystems and the biodiversity within our forests.
I invite you to join us in our journey, using near real-time space intelligence to ensure a future where forests teem with life, not fire.
To understand how you can access these upcoming near real-time intelligence information, reach out to Little Place Labs at firstname.lastname@example.org