Journal
REMOTE SENSING
Volume 12, Issue 6, Pages -Publisher
MDPI
DOI: 10.3390/rs12061046
Keywords
sensing payloads; forest inventory; fire monitoring; post-fire monitoring; tree species classification; forest health monitoring; photogrammetry; LiDAR
Categories
Funding
- European Regional Development Fund (ERDF) through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 under the PORTUGAL 2020 Partnership Agreement
- European Regional Development Fund (ERDF) through Portuguese National Innovation Agency (ANI) [33113]
- FCT-Portuguese Foundation for Science and Technology [PD/BD/150260/2019, PD/00122/2012, SFRH/BD/139702/2018, SFRH/BD/137968/2018/J567573bYgFF]
- Fundação para a Ciência e a Tecnologia [PD/BD/150260/2019] Funding Source: FCT
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Currently, climate change poses a global threat, which may compromise the sustainability of agriculture, forestry and other land surface systems. In a changing world scenario, the economic importance of Remote Sensing (RS) to monitor forests and agricultural resources is imperative to the development of agroforestry systems. Traditional RS technologies encompass satellite and manned aircraft platforms. These platforms are continuously improving in terms of spatial, spectral, and temporal resolutions. The high spatial and temporal resolutions, flexibility and lower operational costs make Unmanned Aerial Vehicles (UAVs) a good alternative to traditional RS platforms. In the management process of forests resources, UAVs are one of the most suitable options to consider, mainly due to: (1) low operational costs and high-intensity data collection; (2) its capacity to host a wide range of sensors that could be adapted to be task-oriented; (3) its ability to plan data acquisition campaigns, avoiding inadequate weather conditions and providing data availability on-demand; and (4) the possibility to be used in real-time operations. This review aims to present the most significant UAV applications in forestry, identifying the appropriate sensors to be used in each situation as well as the data processing techniques commonly implemented.
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