Arid
DOI10.1016/j.jag.2019.01.013
Ultra-high spatial resolution fractional vegetation cover from unmanned aerial multispectral imagery
Melville, Bethany1; Fisher, Adrian2,3; Lucieer, Arko4
通讯作者Fisher, Adrian
来源期刊INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
ISSN1569-8432
EISSN1872-826X
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.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Melville, Bethany]的文章
[Fisher, Adrian]的文章
[Lucieer, Arko]的文章
百度学术
百度学术中相似的文章
[Melville, Bethany]的文章
[Fisher, Adrian]的文章
[Lucieer, Arko]的文章
必应学术
必应学术中相似的文章
[Melville, Bethany]的文章
[Fisher, Adrian]的文章
[Lucieer, Arko]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。