Applicability of advanced remote sensing technologies to support forest management

Tese de Doutoramento - Engenharia Florestal e dos Recursos Naturais - Instituto Superior de Agronomia

Forest ecosystems provide multiple wood and non-wood forest products and services that are crucial for the socio-economic development of rural areas. In this context, current methods of estimating variables of interest in forest ecosystems should be improved due to new demands for information related to sustainable forest management. Advanced remote sensing (RS) technologies provide data that will address the increasing demands for information and support the subsequent development of prediction models. Airborne laser scanning (ALS) has emerged as one of the most promising RS technologies for characterizing tree canopies and other biophysical characteristics essential for forest inventories. The use of 3D data acquired from Digital Aerial photography (DAP) is a useful alternative to ALS-based forest variable estimation. The rapid development of Unmanned Aerial Vehicles (UAVs) (drones) fitted with digital aerial cameras and the use of SfM (Structure from Motion) techniques together provide new possibilities for efficient mapping of forest variables. Combining ALS and DAP technologies with UAV platforms will probably have a strong impact on forest inventory practices in the next decade, leading to more accurate characterization of forest stands, as well as for monitoring forest growth. The overall aim of all of the five studies included in this doctoral thesis is to evaluate the capacity of two advanced RS technologies (ALS and DAP) to provide methods and tools that support forest management at different scales ranging from stand level to individual tree level

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