Editorial for the Special Issue "Forestry Applications of Unmanned Aerial Vehicles (UAVs)"

被引:4
作者
Matese, Alessandro [1 ]
机构
[1] Natl Res Council CNR, Inst BioEcon IBE, Via Caproni 8, I-50145 Florence, Italy
关键词
unmanned aerial vehicles (UAV); precision forestry; forestry applications; image processing; machine learning; RGB imagery;
D O I
10.3390/f11040406
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Unmanned aerial vehicles (UAVs) are new platforms that have been increasingly used in the last few years for forestry applications that benefit from the added value of flexibility, low cost, reliability, autonomy, and capability of timely provision of high-resolution data. This special issue (SI) collects nine papers reporting research on different forestry applications using UAV imagery. The special issue covers seven Red-Green-Blue (RGB) sensor papers, three papers on multispectral imagery, and one further paper on hyperspectral data acquisition system. Several data processing and machine learning methods are presented. The special issue provides an overview regarding potential applications to provide forestry characteristics in a timely, cost-efficient way. With the fast development of sensors technology and image processing algorithms, the forestry potential applications will growing fast, but future work should consider the consistency and repeatability of these novel techniques.
引用
收藏
页数:3
相关论文
共 9 条
[1]   Robinia pseudoacacia L. in Short Rotation Coppice: Seed and Stump Shoot Reproduction as well as UAS-based Spreading Analysis [J].
Carl, Christin ;
Lehmann, Jan R. K. ;
Landgraf, Dirk ;
Pretzsch, Hans .
FORESTS, 2019, 10 (03)
[2]   An Automatic UAV Based Segmentation Approach for Pruning Biomass Estimation in Irregularly Spaced Chestnut Orchards [J].
Di Gennaro, Salvatore Filippo ;
Nati, Carla ;
Dainelli, Riccardo ;
Pastonchi, Laura ;
Berton, Andrea ;
Toscano, Piero ;
Matese, Alessandro .
FORESTS, 2020, 11 (03)
[3]   The Use of Low-Altitude UAV Imagery to Assess Western Juniper Density and Canopy Cover in Treated and Untreated Stands [J].
Durfee, Nicole ;
Ochoa, Carlos G. ;
Mata-Gonzalez, Ricardo .
FORESTS, 2019, 10 (04)
[4]   Detection of Coniferous Seedlings in UAV Imagery [J].
Feduck, Corey ;
McDermid, Gregory J. ;
Castilla, Guillermo .
FORESTS, 2018, 9 (07)
[5]   Evaluating the Effectiveness of Unmanned Aerial Systems (UAS) for Collecting Thematic Map Accuracy Assessment Reference Data in New England Forests [J].
Fraser, Benjamin T. ;
Congalton, Russell G. .
FORESTS, 2019, 10 (01)
[6]   Characterizing Seedling Stands Using Leaf-Off and Leaf-On Photogrammetric Point Clouds and Hyperspectral Imagery Acquired from Unmanned Aerial Vehicle [J].
Imangholiloo, Mohammad ;
Saarinen, Ninni ;
Markelin, Lauri ;
Rosnell, Tomi ;
Nasi, Roope ;
Hakala, Teemu ;
Honkavaara, Eija ;
Holopainen, Markus ;
Hyyppa, Juha ;
Vastaranta, Mikko .
FORESTS, 2019, 10 (05)
[7]   Automatic Segmentation of Mauritia flexuosa in Unmanned Aerial Vehicle (UAV) Imagery Using Deep Learning [J].
Morales, Giorgio ;
Kemper, Guillermo ;
Sevillano, Grace ;
Arteaga, Daniel ;
Ortega, Ivan ;
Telles, Joel .
FORESTS, 2018, 9 (12)
[8]   Application of UAV Photogrammetric System for Monitoring Ancient Tree Communities in Beijing [J].
Qiu, Zixuan ;
Feng, Zhong-Ke ;
Wang, Mingming ;
Li, Zhenru ;
Lu, Chao .
FORESTS, 2018, 9 (12)
[9]   Using UAV Multispectral Images for Classification of Forest Burn Severity-A Case Study of the 2019 Gangneung Forest Fire [J].
Shin, Jung-il ;
Seo, Won-woo ;
Kim, Taejung ;
Park, Joowon ;
Woo, Choong-shik .
FORESTS, 2019, 10 (11)