干旱区生态环境知识资源中心(Arid): Ultra-high spatial resolution fractional vegetation cover from unmanned aerial multispectral imagery

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DOI	10.1016/j.jag.2019.01.013
	Ultra-high spatial resolution fractional vegetation cover from unmanned aerial multispectral imagery
	Melville, Bethany 1; Fisher, Adrian 2,3; Lucieer, Arko 4
通讯作者	Fisher, Adrian
来源期刊	INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
ISSN	1569-8432
EISSN	1872-826X
出版年	2019
卷号	78 页码:14-24
英文摘要	Vegetation cover is a key environmental variable often mapped from satellite and aerial imagery. The derivation of ultra-high spatial resolution fractional vegetation cover (FVC) based on multispectral imagery acquired from an Unmanned Aerial System (UAS) has several applications, including the potential to revolutionise the collection of field data for calibration/validation of satellite products. In this study, abundance maps were derived using three methods, applied to data collected in a typical Australian rangeland environment. The first method used downscaling between Landsat FVC maps and UAS images with Random Forest regression to predict bare ground, photosynthetic vegetation and non-photosynthetic vegetation cover. The second method used spectral unmixing based on endmembers identified in the multispectral imagery. The third method used an object-based classification approach to label image segments. The accuracy of all UAS FVC and Landsat FVC products were assessed using 20 field plots (100 m diameter star transects), as well as from 138 ground photo plots. The classification method performed best for all cover fractions at the 100 m plot scale (12-13% RMSE), with the downscaling approach only able to accurately predict photosynthetic cover. The downscaling and unmixing generally over-predicted non-photosynthetic vegetation associated with Chenopod shrubs. When compared with the high-resolution photo plot data, the classification method performed the worst, while the downscaling and unmixing methods achieved reasonable accuracy for the photosynthetic component only (12-13% RMSE). Multispectral UAS imagery has great potential for mapping photosynthetic vegetation cover in rangelands at ultra-high resolution, though accurately separating non-photosynthetic vegetation and bare ground was only possible when the data was scaled-up to coarser resolutions.
英文关键词	Unmanned aerial systems Downscaling Spectral unmixing Fractional vegetation cover
类型	Article
语种	英语
国家	Germany ; Australia
收录类别	SCI-E
WOS记录号	WOS:000463131700002
WOS关键词	RANDOM FOREST ; GREEN VEGETATION ; REGRESSION TREE ; ARID REGIONS ; SOIL ; REFLECTANCE ; INDEXES ; SURFACE ; RETRIEVALS ; MODEL
WOS类目	Remote Sensing
WOS研究方向	Remote Sensing
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/216341
作者单位	1.Rhein Waal Univ Appl Sci, Fac Commun & Environm, Friederich Heinrich Allee 25, Kamp Linifort, Germany; 2.Univ Queensland, Sch Earth & Environm Sci, Joint Remote Sensing Res Program, Brisbane, Qld 4072, Australia; 3.Univ New South Wales, Ctr Ecosyst Sci, Sch Biol Earth & Environm Sci, Sydney, NSW 2052, Australia; 4.Univ Tasmania, Sch Technol Environm & Design, Geog & Spatial Sci Discipline, Private Bag 78, Hobart, Tas 7001, Australia
推荐引用方式 GB/T 7714	Melville, Bethany,Fisher, Adrian,Lucieer, Arko. Ultra-high spatial resolution fractional vegetation cover from unmanned aerial multispectral imagery[J],2019,78:14-24.
APA	Melville, Bethany,Fisher, Adrian,&Lucieer, Arko.(2019).Ultra-high spatial resolution fractional vegetation cover from unmanned aerial multispectral imagery.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,78,14-24.
MLA	Melville, Bethany,et al."Ultra-high spatial resolution fractional vegetation cover from unmanned aerial multispectral imagery".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 78(2019):14-24.