Counting trees from space with artificial intelligence - EIN News
Researchers have developed an AI system that counts trees worldwide using high-resolution satellite imagery, revealing far more trees than previously estimated.
- AI model counts individual trees globally using high-resolution satellite imagery, outperforming traditional remote sensing methods.
- Initial findings suggest global tree populations may be higher than previously estimated.
- The system enables real-time tracking of deforestation, reforestation, and ecosystem health.
- Breakthrough could transform forestry management, climate modeling, and conservation strategies.
A team of scientists has created an artificial intelligence model capable of counting trees across the globe by analyzing high-resolution satellite images. The system, trained on millions of tree samples, identifies individual trees even in dense forests and arid regions where manual counting is impractical. Initial results suggest the planet may host significantly more trees than previously believed, challenging existing estimates of global forest coverage.
The AI leverages deep learning techniques to distinguish trees from other vegetation and terrain features, achieving accuracy rates that surpass traditional remote sensing methods. This development could revolutionize forestry management, climate modeling, and conservation efforts by providing real-time, scalable data on tree populations. Researchers emphasize the model's potential to track deforestation, reforestation, and ecosystem health with greater precision than ever before.
Source: Counting trees from space with artificial intelligence - EIN News. Read the full piece at the source.
Opportunity to build on open-source AI models for environmental monitoring and geospatial analysis.
Companies in forestry, agriculture, and climate tech can leverage this data for sustainability reporting and resource management.
Potential for new markets in AI-driven environmental monitoring and data services.
Provides critical insights into global forest health and climate change mitigation.
- deep learning
- A subset of machine learning using neural networks with many layers to analyze complex patterns in data.
- remote sensing
- The science of obtaining information about objects or areas from a distance, typically using satellites or aircraft.
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