Are AI deep learning models the future of environmental conservation?
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Chesapeake Conservancy's research team has developed an advanced deep-learning model that uses AI and satellite imagery to map ground-mounted solar arrays. The model shows the rapid growth of solar capacity in DC, Maryland, and other states, with solar arrays primarily replacing agricultural fields and avoiding natural land covers like forests and wetlands.
The Chesapeake Conservancy's research team has made significant strides in environmental conservation through the use of AI deep learning models. They have developed an advanced model that utilizes satellite imagery to automatically map ground-mounted solar arrays, providing valuable insights into the rapid growth of solar capacity in DC, Maryland, and other states. The model reveals that solar arrays have primarily replaced agricultural fields, avoiding the conversion of natural land covers such as forests and wetlands. This trend is encouraging from a conservation perspective, as it presents an opportunity to restore biodiversity and ecosystem services in the watershed. The team's research also includes predicting patterns of solar energy development and its potential impact on biodiversity conservation, providing valuable information for future planning and decision-making.
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