How Can Artificial Intelligence Help Curb Deforestation in the Amazon?

Adriana Erthal Abdenur
2020
#Agriculture and food
#Mining
#Environment and climate change
#Sustainability standards
#Latin America

Deforestation has traditionally been viewed as an environmental issue, but, increasingly, illegal logging in rainforests is being understood as an issue of transnational organized crime. Forests cover 31 percent of the planet, are home to 80 percent of the world’s terrestrial species of animals and plants, and provide for the livelihoods of 1.6 billion people. Yet rising deforestation rates are destroying their rich biodiversity in several parts of the world. In the Amazon basin, forest destruction is driven primarily by illegal activities such as land invasions, induced forest fires (usually set to clear land for agriculture, ranching, and land speculation), and illegal mining and logging. Part of the problem is a lack of adequate forest monitoring, which is complicated by the challenges to obtaining accurate and consistent spatial data on deforestation. Even when greater accuracy and reliability are achieved — for instance, with the support of satellite technologies that allow for real-time tracking and increasingly detailed surveillance of forest canopies — filtering large amounts of data can be slow, labor intensive, and expensive. The enormous troves of data that can now be gathered through the deployment of drones pose similar challenges. Some of the most promising innovations for enhancing the monitoring of forests involve artificial intelligence (AI) and associated technologies, such as deep learning and machine learning. So-called “earth-friendly AI” has been touted as a way to vastly enhance data collection and analysis for environmental conservation. Some of these new technologies are being developed and applied elsewhere in the world, but they may be adaptable to the Amazon basin through adequate government support, robust policy frameworks, and international cooperation.

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