Application of remote sensors and artificial intelligence in the management and conservation of forests in the face of climate change in Mexico
Application of remote sensors and artificial intelligence in the management and conservation of forests in the face of climate change in Mexico
DOI:
https://doi.org/10.32870/e-cucba.vi21.332Keywords:
Artificial Intelligence, forest monitoring, forest management, forecasting, biodiversity conservationAbstract
The present review focuses on remote sensors and artificial intelligence (AI) are key tools for monitoring forests and understanding climate change. These sensors provide detailed information about the structure and status of forests, including the detection of deforestation, diseases, and pests, as well as the estimation of stored carbon. The combination of remote sensors with AI has revolutionized forest management, enabling soil classification, change detection, and forecasting the effects of climate change. They have also been valuable for biodiversity conservation, identifying areas of high diversity, monitoring ecosystems, and supporting the planning of conservation strategies. Advanced technologies such as drones, planes, satellite imagery, and LiDAR have also proven effective in environmental monitoring. Drones are versatile and cost-effective, planes cover large areas, satellites provide global data, and LiDAR is useful for characterizing forest structure. However, in Mexico overall, there is a lack of application and utilization of these technologies due to the absence of updated data and limited integration of AI. Investment in technological infrastructure and the promotion of collaboration between institutions are needed to overcome this gap and fully harness the potential of these tools in environmental decision-making.
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