Semantic Scholar Open Access 2020 234 sitasi

Forestry Remote Sensing from Unmanned Aerial Vehicles: A Review Focusing on the Data, Processing and Potentialities

Nathalie Guimarães L. Pádua P. Marques Nuno Silva Emanuel Peres +1 lainnya

Abstrak

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.

Topik & Kata Kunci

Penulis (6)

N

Nathalie Guimarães

L

L. Pádua

P

P. Marques

N

Nuno Silva

E

Emanuel Peres

J

J. Sousa

Format Sitasi

Guimarães, N., Pádua, L., Marques, P., Silva, N., Peres, E., Sousa, J. (2020). Forestry Remote Sensing from Unmanned Aerial Vehicles: A Review Focusing on the Data, Processing and Potentialities. https://doi.org/10.3390/rs12061046

Akses Cepat

Lihat di Sumber doi.org/10.3390/rs12061046
Informasi Jurnal
Tahun Terbit
2020
Bahasa
en
Total Sitasi
234×
Sumber Database
Semantic Scholar
DOI
10.3390/rs12061046
Akses
Open Access ✓