干旱区生态环境知识资源中心(Arid): Estimating food resource availability in arid environments with Sentinel 2 satellite imagery

Arid

DOI	10.7717/peerj.9209
	Estimating food resource availability in arid environments with Sentinel 2 satellite imagery
	Funghi, Caterina 1,2; Heim, Rene H. J.2,3; Schuett, Wiebke 1,4,5; Griffith, Simon C.2,5; Oldeland, Jens 3
通讯作者	Funghi, Caterina
来源期刊	PEERJ
ISSN	2167-8359
出版年	2020
卷号	8
英文摘要	Background. In arid environments, plant primary productivity is generally low and highly variable both spatially and temporally. Resources are not evenly distributed in space and time (e.g., soil nutrients, water), and depend on global (El Nino/Southern Oscillation) and local climate parameters. The launch of the Sentinel2-satellite, part of the European Copernicus program, has led to the provision of freely available data with a high spatial resolution (10 m per pixel). Here, we aimed to test whether Sentinel2-imagery can be used to quantify the spatial variability of a minor tussock grass (Enneapogon spp.) in an Australian arid area and whether we can identify different vegetation cover (e.g., grass from shrubs) along different temporal scenarios. Although short-lasting, the Enneapogon grassland has been identified as a key primary food source to animals in the arid environment. If we are able to identify and monitor the productivity of this species remotely, it will provide an important new tool for examining food resource dynamics and subsequent animal responses to them in arid habitat. Methods. We combined field vegetation surveys and Sentinel2-imagery to test if satellite spectral data can predict the spatial variability of Enneapogon over time, through GLMMs. Additionally, a cluster analysis ('gower' distance, 'complete' method), based on Enneapogon seed-productivity, and total vegetation cover in October 2016, identified three clusters: bare ground, grass dominated and shrub dominated. We compared the vegetation indices between these different clusters from October 2016 to January 2017. Results. We found that MSAVI(2) and NDVI correlated with the proportion of Enneapogon with seeds across the landscape and this relationship changed over time. Both vegetation indices (MSAVI(2) and NDVI) were higher in patches with high seed-productivity of Enneapogon than in bare soil, but only in October, a climatically-favorable period during which this dominant grass reached peak seed-productivity. Discussion. MSAVI(2) and NDVI provided reliable estimates of the heterogeneity of vegetation type across the landscape only when measured in the Austral spring. This means that grass cover is related to seed-productivity and it is possible to remotely and reliably predict food resource availability in arid habitat, but only in certain conditions. The lack of significant differences between clusters in the summer was likely driven by the short-lasting nature of the vegetation in the study and the sparseness of the grass-dominated vegetation, in contrast to the shrub vegetation cluster that was particularly well measured by the NDVI. Conclusions. Overall, our study highlights the potential for Sentinel2-imagery to estimate and monitor the change in grass seed availability remotely in arid environments. However, heterogeneity in grassland cover is not as reliably measured as other types of vegetation and may only be well detected during periods of peak productivity (e.g., October 2016).
英文关键词	Arid environment Remote sensing Vegetation survey Sentinel 2 Behavioral ecology
类型	Article
语种	英语
国家	Germany ; Australia ; England
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:000535415100015
WOS关键词	VEGETATION INDEX NDVI ; ZEBRA FINCHES ; RAINFALL ; AUSTRALIA ; ZONE ; ECOLOGY ; CLIMATE ; BIRDS ; WATER ; BUST
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/319178
作者单位	1.Univ Hamburg, Inst Zool, Hamburg, Germany; 2.Macquarie Univ, Dept Biol Sci, Sydney, NSW, Australia; 3.Univ Hamburg, Inst Plant Sci & Microbiol, Hamburg, Germany; 4.Univ Sussex, Sch Life Sci, Brighton, E Sussex, England; 5.Univ New South Wales, Dept Biol Earth & Environm Sci, Sydney, NSW, Australia
推荐引用方式 GB/T 7714	Funghi, Caterina,Heim, Rene H. J.,Schuett, Wiebke,et al. Estimating food resource availability in arid environments with Sentinel 2 satellite imagery[J],2020,8.
APA	Funghi, Caterina,Heim, Rene H. J.,Schuett, Wiebke,Griffith, Simon C.,&Oldeland, Jens.(2020).Estimating food resource availability in arid environments with Sentinel 2 satellite imagery.PEERJ,8.
MLA	Funghi, Caterina,et al."Estimating food resource availability in arid environments with Sentinel 2 satellite imagery".PEERJ 8(2020).