Potential and constraints of Unmanned Aerial Vehicle technology for the characterization of Mediterranean riparian forest

被引:171
作者
Dunford, R. [1 ,2 ]
Michel, K. [2 ]
Gagnage, M. [2 ]
Piegay, H. [2 ]
Tremelo, M. -L. [2 ]
机构
[1] Univ Durham, Dept Geog, Durham DH1 3LE, England
[2] Univ Lyon, CNRS, UMR 5600, F-69342 Lyon 07, France
基金
英国经济与社会研究理事会;
关键词
REMOTELY-SENSED DATA; IMAGERY; RIVER; CLASSIFICATION; PHOTOGRAPHY; BATHYMETRY; PATTERNS; BASIN;
D O I
10.1080/01431160903023025
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Unmanned Aerial Vehicle (UAV) technology provides potential for very high spatial resolution (<25 cm) mapping of relatively large areas at a user-defined re-survey frequency. In a riparian context, UAV technology provides a mechanism for riparian managers to (a) quantify riparian terrain and vegetation units and (b) identify standing dead wood and canopy mortality. In this study a paraglider UAV was used to survey 174 ha at 6.8-21.8 cm ground resolution. Pixel-based and object-oriented classification approaches were used at the scale of a single image and a channel mosaic. Significant potential was demonstrated: vegetation units were classified with an accuracy of kappa = 0.79 and standing dead wood units were identified with an average accuracy with respect to omission and commission errors of 80% and 65%, respectively. Work across multiple images identified that major constraints currently result from factors such as illumination conditions and sensor movement during flight, which create variations in spatial resolution and radiometry. It is expected that with further methodological refinement and more complex methods of automated radiometric correction UAV technology can provide the flexibility to rapidly produce very high resolution map products to aid riparian management.
引用
收藏
页码:4915 / 4935
页数:21
相关论文
共 33 条
[31]   Estimating forest uniformity in Eucalyptus spp. and Pinus taeda L. stands using field measurements and structure from motion point clouds generated from unmanned aerial vehicle (UAV) data collection [J].
Hentz, Angela M. K. ;
Silva, Carlos A. ;
Dalla Corte, Ana P. ;
Netto, Sylvio P. ;
Stager, Michael P. ;
Klauberg, Carine .
FOREST SYSTEMS, 2018, 27 (02)
[32]   Application of Unmanned Aerial Vehicle (UAV)-Acquired Topography for Quantifying Typhoon-Driven Landslide Volume and Its Potential Topographic Impact on Rivers in Mountainous Catchments [J].
Chang, Kuo-Jen ;
Tseng, Chun-Wei ;
Tseng, Chih-Ming ;
Liao, Ta-Chun ;
Yang, Ci-Jian .
APPLIED SCIENCES-BASEL, 2020, 10 (17)
[33]   Forest Burn Severity Mapping Using Multispectral Unmanned Aerial Vehicle Images and Light Detection and Ranging (LiDAR) Data: Comparison of Maximum Likelihood, Spectral Angle Mapper, and U-Net Classifiers [J].
Lee, Boknam ;
Kim, Bomi ;
Woo, Choongshik ;
Jung, Geonhwi ;
Kwon, Gyeongwon ;
Park, Joowon .
SENSORS AND MATERIALS, 2022, 34 (12) :4599-4614