Deforestation has been an ongoing problem for many years. Whilst technology has advanced, offenders have held the advantage because there’s simply an excessive amount of land to cover — until now. Could artificial intelligence be the important thing to putting an end to illegal deforestation? Each its potential and real-world use cases show promise.
1. Discover Optimal Reforestation Areas
Although deforestation rates fluctuate, more trees are lost yearly. It increased by 4% from 2021 to 2022, amounting to over 6.6 million hectares of forest lost. Even when all illegal logging, mining and agriculture operations stop today, those critical environments will still be at an obstacle.
If this trend continues unchecked, the world will see temperatures rise, wildlife flee and native ecosystems weaken. An unstoppable dieback process triggers at that time, meaning healthy trees’ conditions progressively deteriorate. This might result in a domino effect where tens of millions more hectares of forest are lost despite no human-led deforestation.
With AI, activists and native governments can speed up reforestation, helping forests return to how they were before human intervention. The model can pinpoint areas where replanting could be simplest. It could also discover fast-growing, native tree species proof against pests and drought. Once the saplings are planted, it could possibly monitor growth in real time.
2. Analyze Satellite Imagery for Forest Loss
For many years, analyzing satellite imagery was one in every of the few ways to discover deforestation in motion other than the less efficient word-of-mouth or boots-on-the-ground strategies. Nonetheless, since there are over 3 trillion trees on the planet, there’s loads of ground to cover. While manually going through these images is impractical, traditional software misses critical details.
AI-powered image recognition technology can detect early indicators of forest loss, including latest roads, smoke and latest clearings. It could actually report any positive hit to a human in real time, enabling them to review and report back to local law enforcement agencies. Teams may even use AI-powered drones for up-close aerial views.
3. Differentiate Between Legal and Illegal Operations
Sometimes, deforestation is legal. Local governments approve those operations so firms can proceed doing business. Nonetheless, what starts as a sanctioned motion doesn’t all the time stay that way. There are various cases where individuals encroach into protected territory with the understanding that it is best to hunt forgiveness than ask permission.
In truth, cropland expansion accounts for nearly 50% of deforestation worldwide, closely followed by livestock grazing at 38.5%. With satellite imagery alone, differentiating between legal, semi-legal and illegal deforestation is complicated. AI fills within the gaps by analyzing the colour, texture and extent of tree cover, eliminating the guesswork.
4. Analyze Sounds That Signal Deforestation
What does deforestation sound like? Revving chainsaws, falling logs, roaring excavators, distressed wildlife and burning brush. Unfortunately, the noise from heavy machinery, power tools, pickup trucks and conversations between employees is quickly dampened in densely forested areas, making pinpointing those operations difficult.
AI-enabled Web of Things (IoT) surveillance systems powered by miniature solar panels for acoustic monitoring will be placed nearly anywhere, so that they can pick up those audio cues. Plus, since animals flee, entering areas they normally wouldn’t because the offenders burn or cut down trees, those cameras may discover potential human interference before logging begins.
5. Trace Illegal Operations to the Source
The Bureau of Investigative Journalism recently discovered beef from farmers was making its way into global supply chains — including those who supply two of the world’s largest meat firms — after they were accused of illegal deforestation and subsequently punished. Despite embargoes, business continued as usual. Some even seemingly continued deforesting.
Illegal deforestation is commonly driven by local sawmills, refineries and farms. Whether employees need to expand their cropland, sell more products or feed their herds for affordable, they contribute to significant forest loss. Unfortunately, tracing these activities back to their source is difficult. That’s, unless people use AI.
AI can track heavy machinery because it moves from newly created clearings back to its base station, helping investigators narrow their search. Alternatively, it could possibly employ facial recognition technology to uncover the identities of those involved. Doing so helps local law enforcement agencies discover repeat offenders, shrinking the gap between assigning and enforcing punishment.
6. Analyze Unarchived Legacy Data
Although data on deforestation stretches back many years, much stays inaccessible to this present day. That’s since it is barely accessible via unarchived, physical sources like field notes, cassette tapes, written correspondence and preserved biological specimens. This evidence exists in silos, hidden away from traditional tools that scrape online resources.
With AI image recognition, language detection and automatic transcription, researchers can finally secure these invaluable insights. This allows them to discover forest loss drivers and reveal repeat offenders. Advanced models can consider context, maintaining accuracy even when offending entities change their names or localities’ borders shift.
7. Enable Proactive Intervention
Although satellite image clarity has been improving for many years — professionals can now pinpoint deforestation with unparalleled precision — this strategy continues to be reactive. Forest loss still happens even in the event that they immediately intervene upon getting an alert. With AI, they will finally achieve proactive intervention, identifying at-risk areas before clearing begins.
AI can analyze aspects like local topography, distance from roads and industrialization rates to find out which areas are most in danger. It could actually even consider complex elements just like the geopolitical climate or the worldwide timber market. Such a tool isn’t any longer hypothetical — one joint research team has developed it.
Researchers on the World Wildlife Fund collaborated with computer scientists to develop an AI called Forest Foresight. It could actually predict forest loss as much as six months prematurely with upwards of 80% accuracy. When it recognizes potential illegal operations, it could possibly alert local authorities, stopping deforestation before it starts.
8. Use Sensors to Discover Illegal Activity
Whether illegal deforestation operations use heavy machinery to chop down trees, move livestock into protected territory or start wildfires to clear land, their actions produce some form of emission. As an example, a single cow produces as much as 264 kilos of methane annually — a complete herd’s gas could be noticeable.
AI-enabled IoT sensors strategically placed in high-risk forests can track methane, carbon monoxide and carbon dioxide emissions. In the event that they suddenly spike, teams can investigate further. This approach might be uniquely effective since the model can consider context, enabling it to filter out false positives and make investigations easier.
9. Provide an Anonymous Tip Line
Up to now, activists and law enforcement agencies largely relied on word of mouth to uncover illegal logging operations. While they moved away from that approach once satellite imagery became widely available, it isn’t any less useful. In the event that they were to leverage AI-powered chatbots in affected areas, they may receive insightful anonymous tips about potential forest loss.
Deploying AI for this use case is good because a single model can hold dozens — if not a whole bunch or 1000’s — of conversations directly. Those interacting with it don’t have to wait for business hours or be placed on hold, incentivizing them to send a message. This technology can even analyze semantics, pull keywords and summarize reports for his or her human counterparts.
Could AI Put an End to Deforestation Once and for All?
Truth be told, AI isn’t a silver bullet. It might do all the legwork, but many other moving parts exist. Ending deforestation requires buy-in from local politicians, collaboration between investigative groups and publicly available resources. That said, this technology could still be a game-changer, reducing forest loss rates to levels never before seen.
