Forestry applications of UAVs in Europe: a review

By C. Torresan, A. Berton, F. Carotenuto, S. F. Di Gennaro, B. Gioli, A. Matese, F. Miglietta, C. Vagnoli, A. Zaldei, Luke Wallace. 2017

455 citations recorded by the source corpus.

Subfields: Environmental Engineering, Geology, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/34d1cddd68e9e141d8e63fe0641fbf866d9fca03

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Xiaowei Yu
2. Juha Hyyppä
3. Olli Nevalainen
4. Lin Cao
5. Antonio Maria Garcia Tommaselli
6. Honghua Ruan
7. Keiko Fukumoto
8. Andrew M. Cunliffe

In Geology

1. Lin Cao
2. Andrew M. Cunliffe
3. Xiaoyu Chen
4. Rongjun Qin
5. H. Yao

In Global and Planetary Change

1. Juha Hyyppä
2. Xiaoyu Chen
3. Rongjun Qin
4. Xiaowei Yu
5. H. Yao

Citations in the corpus

• Vegetation monitoring using multispectral sensors – best practices and lessons learned from high latitudes (2018, background): “…structure and chlorophyll content influence the spectral signatures of plants, and VIs transform spectra-specific variability into single variables that can be related to other measures of vegetation productivity and leaf area index (LAI) (Tucker 1979, Guay et al. 2014, e.g. see Aasen et al. 2015).”
• Comparison of UAV LiDAR and Digital Aerial Photogrammetry Point Clouds for Estimating Forest Structural Attributes in Subtropical Planted Forests (2019, background): “Unmanned aerial vehicles (UAVs) have advantages of cost effectiveness and widespread availability [30,31], and are increasingly being used as an alternative remote sensing platform to acquire high-spatial- and temporal-resolution data [32]; thus, UAVs were applied in EFIs in recent years [31,33,34].”
• A compilation of UAV applications for precision agriculture (2020, unknown): “Therefore, in conclusion, this situation results in a complicated regulatory framework at the European level with many ambiguities and limitations [72,74] .”
• Unmanned Aerial Vehicle for Remote Sensing Applications - A Review (2019, background): “These practices are often developed through a learn-by-doing process, and there exist a few papers that review current works of domain-specific urban and environmental applications [2–4], as well as methodologies (e.g., feature extraction and classification for specific objects) [4–6].”
• Forest Structure Estimation from a UAV-Based Photogrammetric Point Cloud in Managed Temperate Coniferous Forests (2017, background): “In particular, lightweight UAVs are sometimes equipped with consumer-grade digital cameras and inexpensive global navigation satellite system (GNSS), which may lead to distortions or positioning errors, respectively [17,18].”
• Accuracy of Photogrammetric UAV-Based Point Clouds under Conditions of Partially-Open Forest Canopy (2017, unknown): “[1] focused on the use of UAVs within the European region in the field of forestry, reporting that RGB (red, green, blue) imaging is the most adopted technology used in combination with UAVs.”
• Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging (2017, background): “The development of low-weight hyperspectral imaging sensors is likely to increase the use of spectral data collected from UAVs in forestry applications [34].”