Treffer: Towards Intelligent Forestry: Big Data, Machine Learning, and Sustainable Management Strategies.

Data-driven, precision forest management exemplifies a shift from traditional practices to big-data analytics, which leverages advanced computational technologies while addressing complex environmental challenges. Research has shown how big data analytics has become an important enabler for sustainable forest management and provides unprecedented opportunities for monitoring, analysis, and decision-making at every step. Remote sensing technology, Internet of Things (IoT) sensors, machine learning algorithms, cloud computing platforms, and block chain systems are some of the key technologies being deployed in this market. Results indicate an increase of the accuracy of forest classification applications to 85-98% with significant improvement in operation efficiency and cost reduction. However, the data integration problems, system interoperability, technical ability, and economic accessibility still exist. This review provides a comprehensive framework for the transformation potential that big data analytics can add to the solution of contemporary challenges in forestry, including minimizing climate change adaptation, biodiversity conservation, sustainable resource utilization, and supply chain transparency. [ABSTRACT FROM AUTHOR]