Arid
DOI10.1016/j.rse.2016.05.019
Ultra-fine grain landscape-scale quantification of dryland vegetation structure with drone-acquired structure-from-motion photogrammetry
Cunliffe, Andrew M.1; Brazier, Richard E.1; Anderson, Karen2
通讯作者Cunliffe, Andrew M.
来源期刊REMOTE SENSING OF ENVIRONMENT
ISSN0034-4257
EISSN1879-0704
出版年2016
卷号183页码:129-143
英文摘要

Covering 40% of the terrestrial surface, dryland ecosystems characteristically have distinct vegetation structures that are strongly linked to their function. Existing survey approaches cannot provide sufficiently fine-resolution data at landscape-level extents to quantify this structure appropriately. Using a small, unpiloted aerial system (UAS) to acquire aerial photographs and processing theses using structure-from-motion (SfM) photogrammetry, three-dimensional models were produced describing the vegetation structure of semi-arid ecosystems at seven sites across a grass-to shrub transition zone. This approach yielded ultra-fine (<1 cm(2)) spatial resolution canopy height models over landscape-levels (10 ha), which resolved individual grass tussocks just a few cm(3) in volume. Canopy height cumulative distributions for each site illustrated ecologically-significant differences in ecosystem structure. Strong coefficients of determination (r(2) from 0.64 to 0.95) supported prediction of above-ground biomass from canopy volume. Canopy volumes, above-ground biomass and carbon stocks were shown to be sensitive to spatial changes in the structure of vegetation communities. The grain of data produced and sensitivity of this approach is invaluable to capture even subtle differences in the structure (and therefore function) of these heterogeneous ecosystems subject to rapid environmental change. The results demonstrate how products from inexpensive UAS coupled with SfM photogrammetry can produce ultra-fine grain biophysical data products, which have the potential to revolutionise scientific understanding of ecology in ecosystems with either spatially or temporally discontinuous canopy cover. (C) 2016 The Authors. Published by Elsevier Inc.


英文关键词Semi-arid Rangeland Grassland Shrubland Vegetation Biophysical Biomass UAV UAS SfM Canopy height model
类型Article
语种英语
国家England
收录类别SCI-E
WOS记录号WOS:000382345400011
WOS关键词UNMANNED AERIAL VEHICLES ; SEMIARID ECOSYSTEMS ; ABOVEGROUND BIOMASS ; OVERLAND-FLOW ; ALLOMETRIC MODELS ; FOREST BIOMASS ; DESERT GRASSES ; CARBON CONTENT ; TREE COVER ; SOIL
WOS类目Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/196005
作者单位1.Univ Exeter, Geog, Amory Bldg, Exeter, Devon, England;
2.Univ Exeter, Environm & Sustainabil Inst, Exeter, Devon, England
推荐引用方式
GB/T 7714
Cunliffe, Andrew M.,Brazier, Richard E.,Anderson, Karen. Ultra-fine grain landscape-scale quantification of dryland vegetation structure with drone-acquired structure-from-motion photogrammetry[J],2016,183:129-143.
APA Cunliffe, Andrew M.,Brazier, Richard E.,&Anderson, Karen.(2016).Ultra-fine grain landscape-scale quantification of dryland vegetation structure with drone-acquired structure-from-motion photogrammetry.REMOTE SENSING OF ENVIRONMENT,183,129-143.
MLA Cunliffe, Andrew M.,et al."Ultra-fine grain landscape-scale quantification of dryland vegetation structure with drone-acquired structure-from-motion photogrammetry".REMOTE SENSING OF ENVIRONMENT 183(2016):129-143.
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