AI-Based Solutions are Crucial for Forest Management
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AI-Based Solutions are Crucial for Forest Management

By CIOReview | Thursday, July 25, 2019

AI-driven solutions can prove to be the game-changer for assessment and protection of forest cover.

FREMONT, CA: When it comes to understanding and protecting the natural resources, humans are not moving at the right pace and direction in spite of a wealth of statistics. It is a major challenge on how to fight climate change while also keeping up with the growing demands of the ever-increasing population. Agriculture is still the largest industry that employs more than a billion people and generates over $1.3 trillion worth of food per annum. However, production is getting difficult with increasing population and extreme climatic conditions that affect the crops. On the other hand, the increased demand for land for agriculture and infrastructure purposes is leading to a decrease in the forest cover at a drastic pace.

The loss of green cover is more than just a loss of ecosystem, natural resources, and biodiversity. It is also affecting climatic change and accounts for almost 25 percent of the world’s entire greenhouse emissions. Saving these resources enhances the well-being of the entire planet. Moreover, better management of such resources can also help feed a growing population and reduce carbon emissions simultaneously. However, to address the issues, we need a better picture of the current state. Artificial intelligence (AI) driven solutions can have a great application to deal with such complexities.

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AI for Forest Management

Microsoft developed AI for Earth that equips those working in the areas of water, biodiversity, agriculture, and climate change with its expertise and technology. The technology will bring their solutions to scale and enhance sustainability throughout the world. Forest inventory processes haven't changed much which requires the teams to go into the woods and measure various metrics such as height, diameter, and species of each tree in several sample plots to understand the forest as a whole.

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With the use of technologies such as AI and satellite imagery, conventional methods can be replaced by more accurate solutions. For instance, AI-based algorithms greatly offset the amount of fieldwork required for the accurate assessment of the forests and are leading to what is termed as "precision forestry". The goal is to develop a data library and powerful AI tools that will enable updated data over forest covers and other such details.

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