Uso de inteligencia artificial para la identificación de especies forestales a través de imágenes satelitales

Abstract

Artificial intelligence (AI) and satellite imagery are transforming forest management by improving species identification and monitoring, contributing to biodiversity conservation and sustainable ecosystem management. This study explores the applications, benefits and challenges of these technologies, using a document review methodology based on recent literature, with emphasis on case studies and relevant findings. The results show that AI allows optimizing species classification through advanced algorithms, generating distribution maps in remote areas and monitoring changes in biodiversity with improved accuracy, complementing its implementation with drones. In addition, integrated technologies reduce operating costs, increase spatial coverage and provide real-time information, facilitating strategic decisions. However, limitations are faced such as restricted access to high resolution data, insufficient representative datasets, lack of trained personnel and risks associated with technology dependence. The discussion highlights the need to overcome these challenges through international collaboration, inclusive policies and specialized training, ensuring a balance between technological innovation and sustainability. We conclude that these emerging tools have significant potential, but require comprehensive efforts to maximize their impact on forest conservation.