Quantifying the Effect of Aerial Imagery Resolution in Automated Hydromorphological River Characterisation

被引:18
作者
Casado, Monica Rivas [1 ]
Ballesteros Gonzalez, Rocio [2 ]
Wright, Ros [3 ]
Bellamy, Pat [1 ]
机构
[1] Cranfield Univ, Sch Energy Environm & Agrifood, Cranfield MK43 0AL, Beds, England
[2] Reg Ctr Water Res UCLM, Ctra Penas Km 3-2, Albacete 02071, Spain
[3] Environm Agcy, Natl Fisheries Serv, Threshelfords Business Pk,Inworth Rd, Feering CO6 1UD, Essex, England
基金
英国工程与自然科学研究理事会;
关键词
unmanned aerial vehicle; photogrammetry; resolution; comparison; hydromorphology; river management; PRECISION AGRICULTURE; ECOLOGICAL ASSESSMENT; ATLANTIC SALMON; ACCURACY; SYSTEMS; IDENTIFICATION; TOPOGRAPHY; KAPPA;
D O I
10.3390/rs8080650
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Existing regulatory frameworks aiming to improve the quality of rivers place hydromorphology as a key factor in the assessment of hydrology, morphology and river continuity. The majority of available methods for hydromorphological characterisation rely on the identification of homogeneous areas (i.e., features) of flow, vegetation and substrate. For that purpose, aerial imagery is used to identify existing features through either visual observation or automated classification techniques. There is evidence to believe that the success in feature identification relies on the resolution of the imagery used. However, little effort has yet been made to quantify the uncertainty in feature identification associated with the resolution of the aerial imagery. This paper contributes to address this gap in knowledge by contrasting results in automated hydromorphological feature identification from unmanned aerial vehicles (UAV) aerial imagery captured at three resolutions (2.5 cm, 5 cm and 10 cm) along a 1.4 km river reach. The results show that resolution plays a key role in the accuracy and variety of features identified, with larger identification errors observed for riffles and side bars. This in turn has an impact on the ecological characterisation of the river reach. The research shows that UAV technology could be essential for unbiased hydromorphological assessment.
引用
收藏
页数:19
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