When one thinks of tropical forests, images of vast, lush green canopies come to mind. Yet, beneath these canopies, particularly in mangroves, lies a daunting challenge: How do we determine the carbon stock of such vast regions, especially when they're hard to navigate and assess? Enter drones and the power of Artificial Intelligence (AI).
Mapping Mangroves with Modern Technology
Mangrove forests, known for storing vast amounts of CO2 and other greenhouse gases in their biomass and soils, play a pivotal role in our fight against climate change. Astonishingly, they harbor between four to 20 billion tons of organic carbon globally. But, given their remote nature and challenging terrain, obtaining precise carbon estimates for these tidal forests has been a tough nut to crack.
Traditional methods involve physically measuring a tree's height and diameter on-site, often amid mosquito swarms and murky, waist-deep sediment. And yet, these efforts could yield only rough estimates due to the forests' inherent variability.
Desiring a comprehensive and efficient solution, scientists from the Leibniz Center for Tropical Marine Research (ZMT) decided to leverage modern technology.
“We were looking for new techniques to cover the entire forest area and enable regular monitoring,” reveals Daniel Schürholz, the study's lead author. “The more detailed the information about the trees in a forest, the more precise the calculation of stored carbon.”
A Game-Changing Approach in Utría National Park
The team's focus shifted to Utría National Park on Colombia's Pacific coast, home to vast mangrove forests. With assistance from park rangers and researchers from Colombia's Universidad del Valle, they deployed drones to capture aerial images of the forest canopy.
Navigating a mangrove forest near Bragança in Brazil can be quite challenging. Photo by Martin Zimmer, Leibniz Centre for Tropical Marine Research.
These high-resolution images were transformed into detailed mosaics back at ZMT in Bremen, outshining even the clarity of satellite imagery. The real magic, however, lay in the team's application of AI.
Schürholz shares, “Given the current advances in artificial intelligence, we decided to test cutting-edge techniques to automatically detect individual trees in the forest.”
The result? An AI workflow that could pinpoint individual trees, gauge their height, and assess the canopy's diameter. The outcomes were impressive.
“Using our AI workflow, we calculated, for example, that there are 19,717 trees of the endemic mangrove species Pelliciera rhizophorae in the area studied,” says Arjun Chennu, a ZMT habitat mapping expert.
Achieving such precision manually would have been almost impossible.
The Broader Implications and Future Endeavors
But it's not just about counting trees. Chennu points out that this fusion of Drone Technology and AI could also track illegal logging, detect invasive species, or monitor changes in animal and plant communities.
Their findings have broader implications: equipping conservationists with reliable data to bolster mangrove protection efforts. Schürholz is reportedly optimistic about the future.
“The current hype around cutting-edge AI algorithms should also be applied to environmental issues to improve our understanding of the natural world,” he advocates.
He envisions AI revealing intricate details about nature, enhancing our protective and sustainable management efforts. This method could transcend mangroves.
“We are providing a good blueprint for a system that can be used around the globe,” Schürholz notes.
From coral reefs to temperate forests, and even tracking animals, the potential applications are vast, promising a brighter future for environmental research and conservation.
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