Sustainable Forestry Management and Technologies

Dear Colleagues,

The growth of technology in recent decades has ushered in a new era of sustainable forest management. This is due to the significant number of tools that have been created, new methodologies that have emerged, and the wealth of information and data available for incorporation into decision-making processes. This growth has, for example, contributed to the adoption of a new paradigm for forest inventory using active sensors such as ALS or TLS, marking the onset of the big data era in forest management.

Furthermore, the increasing availability of diverse data sources, like satellite data, has made it easier to monitor forests and has opened new possibilities for obtaining spatial and temporal information. However, this framework implies that forest managers must require more knowledge in handling big data to achieve the results they seek. In this context, the development of tools facilitates the exchange of knowledge among users, regardless of their level of technological expertise.

In this context, artificial intelligence is not merely a concept for the future, it is already part of the present. Several tools and methods offer robust assessments of big data, leading to extraordinary results in areas such as species recognition, land use cover changes, and pest prediction, among many others. However, the applications extend beyond land monitoring. For instance, we are witnessing the emergence of future applications like unmanned forest machinery, which could be a game-changer in forest management and harvesting.

The present and the future hold great promise, and this Special Issue aims to compile recent research results and studies in this field. It will explore how these advances contribute to our understanding of forest sustainability and their practical applications. Original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

• Artificial intelligence applications with sustainable forest management purposes;
• Forest monitoring tools based on active and passive sensor data;
• Forest tools and decisions support systems developments for sustainable forest management;
• Parametric and non-parametric modeling to describe and predict forest characteristics;
• Hardware improvements of passive and active sensors and their applications in forest;
• New forest measures technology and software.

We look forward to receiving your contributions.

Prof. Dr. Francisco Rodríguez-Puerta
Dr. Fernando Pérez-Rodríguez
Dr. Juan Picos
Dr. Esteban Gómez-García
Guest Editors

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• big data
• remote sensing
• forest decision support systems
• computing
• artificial intelligence
• forest sustainability
• forest inventory
• forest monitoring