DOI: 10.5194/tc-10-511-2016
Scopus记录号: 2-s2.0-84960120882
论文题名: Using a fixed-wing UAS to map snow depth distribution: An evaluation at peak accumulation
作者: De Michele C ; , Avanzi F ; , Passoni D ; , Barzaghi R ; , Pinto L ; , Dosso P ; , Ghezzi A ; , Gianatti R ; , Vedova G ; D
刊名: Cryosphere
ISSN: 19940416
出版年: 2016
卷: 10, 期: 2 起始页码: 511
结束页码: 522
语种: 英语
英文关键词: aerial survey
; alpine environment
; digital elevation model
; mapping method
; measurement method
; remote sensing
; sampling
; snow
; vertical distribution
英文摘要: We investigate snow depth distribution at peak accumulation over a small Alpine area (∼0.3 km2) using photogrammetry-based surveys with a fixed-wing unmanned aerial system (UAS). These devices are growing in popularity as inexpensive alternatives to existing techniques within the field of remote sensing, but the assessment of their performance in Alpine areas to map snow depth distribution is still an open issue. Moreover, several existing attempts to map snow depth using UASs have used multi-rotor systems, since they guarantee higher stability than fixed-wing systems. We designed two field campaigns: during the first survey, performed at the beginning of the accumulation season, the digital elevation model of the ground was obtained. A second survey, at peak accumulation, enabled us to estimate the snow depth distribution as a difference with respect to the previous aerial survey. Moreover, the spatial integration of UAS snow depth measurements enabled us to estimate the snow volume accumulated over the area. On the same day, we collected 12 probe measurements of snow depth at random positions within the case study to perform a preliminary evaluation of UAS-based snow depth. Results reveal that UAS estimations of point snow depth present an average difference with reference to manual measurements equal to -0.073 m and a RMSE equal to 0.14 m. We have also explored how some basic snow depth statistics (e.g., mean, standard deviation, minima and maxima) change with sampling resolution (from 5 cm up to ∼100 m): for this case study, snow depth standard deviation (hence coefficient of variation) increases with decreasing cell size, but it stabilizes for resolutions smaller than 1 m. This provides a possible indication of sampling resolution in similar conditions. © Author(s) 2016. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75177
Appears in Collections: 影响、适应和脆弱性 气候变化与战略
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作者单位: Politecnico di Milano, Department of Civil and Environmental Engineering, Piazza Leonardo da Vinci 32, Milan, Italy; University of Genova, Department of Civil, Chemical and Environmental Engineering, Via Montallegro 1, Genoa, Italy; Studio di Ingegneria Terradat, Paderno Dugnano, Italy; A2a Group, Grosio, Italy
Recommended Citation:
De Michele C,, Avanzi F,, Passoni D,et al. Using a fixed-wing UAS to map snow depth distribution: An evaluation at peak accumulation[J]. Cryosphere,2016-01-01,10(2)