Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019WR025251 |
Quantifying Uncertainties in Snow Depth Mapping From Structure From Motion Photogrammetry in an Alpine Area | |
Goetz, Jason; Brenning, Alexander | |
2019-09-09 | |
发表期刊 | WATER RESOURCES RESEARCH
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ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2019 |
卷号 | 55期号:9页码:7772-7783 |
文章类型 | Article |
语种 | 英语 |
国家 | Germany |
英文摘要 | Mapping snow conditions in alpine areas is crucial for monitoring local hydrology to support water resource management decisions. Recently, the use of structure-from-motion multiview stereo 3-D reconstruction (or SFM photogrammetry) to derive high-resolution digital elevation models (DEMs) has become popular for mapping snow depth in alpine areas. In this study, methods for communicating spatial uncertainties in snow depth calculated from SFM-derived DEMs are presented using a case study in the French Alps. A spatially varying snow depth precision estimate was determined using an error propagation model based on the precision of the acquired SFM DEMs, which was obtained from repeated unmanned aerial vehicle flights. Spatially varying snow depth detection limits were determined using Student's t distribution. It was found that snow depths as shallow as 1 to 5 cm could be detected with high confidence for most of the study area. Areas of high uncertainties were generally related to where the extent of the ground control coverage did not match in the snow-on and snow-off surveys and in areas with higher surface roughness. A map of the snow depth detection threshold was found to be useful for identifying areas with high uncertainties and potential biases in the SFM snow depths, such as errors due to changes in topography between DEM acquisition dates and poor SFM reconstruction. |
英文关键词 | remote sensing of snow structure from motion unmanned aerial vehicle snow depth uncertainty analysis high spatial resolution |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000487409700001 |
WOS关键词 | TOPOGRAPHIC SURVEYS ; GROUND-CONTROL ; GRAVEL-BED ; LOW-COST ; GLACIER ; TERRAIN ; CLIMATE ; SURFACE ; MODELS ; ROCK |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/186973 |
专题 | 资源环境科学 |
作者单位 | Friedrich Schiller Univ Jena, Dept Geog, Jena, Germany |
推荐引用方式 GB/T 7714 | Goetz, Jason,Brenning, Alexander. Quantifying Uncertainties in Snow Depth Mapping From Structure From Motion Photogrammetry in an Alpine Area[J]. WATER RESOURCES RESEARCH,2019,55(9):7772-7783. |
APA | Goetz, Jason,&Brenning, Alexander.(2019).Quantifying Uncertainties in Snow Depth Mapping From Structure From Motion Photogrammetry in an Alpine Area.WATER RESOURCES RESEARCH,55(9),7772-7783. |
MLA | Goetz, Jason,et al."Quantifying Uncertainties in Snow Depth Mapping From Structure From Motion Photogrammetry in an Alpine Area".WATER RESOURCES RESEARCH 55.9(2019):7772-7783. |
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