干旱区生态环境知识资源中心(Arid): Using Full and Partial Unmixing Algorithms to Estimate the Inundation Extent of Small, Isolated Stock Ponds in an Arid Landscape

Arid

DOI	10.1007/s13157-019-01201-7
	Using Full and Partial Unmixing Algorithms to Estimate the Inundation Extent of Small, Isolated Stock Ponds in an Arid Landscape
	Jarchow, Christopher J.; Sigafus, Brent H.; Muths, Erin; Hossack, Blake R.
通讯作者	Jarchow, CJ
来源期刊	WETLANDS
ISSN	0277-5212
EISSN	1943-6246
出版年	2020
卷号	40 期号:3 页码:563-575
英文摘要	Many natural wetlands around the world have disappeared or been replaced, resulting in the dependence of many wildlife species on small, artificial earthen stock ponds. These ponds provide critical wildlife habitat, such that the accurate detection of water and assessment of inundation extent is required. We applied a full (linear spectral mixture analysis; LSMA) and partial (matched filtering; MF) spectral unmixing algorithm to a 2007 Landsat 5 and a 2014 Landsat 8 satellite image to determine the ability of a time-intensive (i.e., more spectral input; LSMA) vs. a more efficient (less spectral input; MF) spectral unmixing approach to detect and estimate surface water area of stock ponds in southern Arizona, USA and northern Sonora, Mexico. Spearman rank correlations (r(s)) between modeled and actual inundation areas less than a single Landsat pixel (< 900 m(2)) were low for both techniques (r(s)range = 0.22 to 0.62), but improved for inundation areas >900 m(2)(r(s)range = 0.34 to 0.70). Our results demonstrate that the MF approach can model ranked inundation extent of known pond locations with results comparable to or better than LSMA, but further refinement is required for estimating absolute inundation areas and mapping wetlands <1 Landsat pixel.
英文关键词	Remote sensing Spectral mixture analysis Matched filtering Stock ponds Wetlands
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000558519300010
WOS关键词	SPECTRAL MIXTURE ANALYSIS ; SURFACE-WATER ; LAND-COVER ; WETLANDS ; CLASSIFICATION ; BIODIVERSITY ; COUNTY
WOS类目	Ecology ; Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
来源机构	University of Arizona ; United States Geological Survey
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/325552
作者单位	[Jarchow, Christopher J.] Univ Arizona, Biosyst Engn, 1177 E 4th St, Tucson, AZ 85719 USA; [Sigafus, Brent H.] Univ Arizona, Southwest Biol Sci Ctr, US Geol Survey, 520 N Pk Ave, Tucson, AZ 85719 USA; [Muths, Erin] US Geol Survey, Ft Collins Sci Ctr, 2150 Ctr Ave,Bldg C, Ft Collins, CO 80526 USA; [Hossack, Blake R.] US Geol Survey, Northern Rocky Mt Sci Ctr, 800 E Beckwith Ave, Missoula, MT 59801 USA
推荐引用方式 GB/T 7714	Jarchow, Christopher J.,Sigafus, Brent H.,Muths, Erin,et al. Using Full and Partial Unmixing Algorithms to Estimate the Inundation Extent of Small, Isolated Stock Ponds in an Arid Landscape[J]. University of Arizona, United States Geological Survey,2020,40(3):563-575.
APA	Jarchow, Christopher J.,Sigafus, Brent H.,Muths, Erin,&Hossack, Blake R..(2020).Using Full and Partial Unmixing Algorithms to Estimate the Inundation Extent of Small, Isolated Stock Ponds in an Arid Landscape.WETLANDS,40(3),563-575.
MLA	Jarchow, Christopher J.,et al."Using Full and Partial Unmixing Algorithms to Estimate the Inundation Extent of Small, Isolated Stock Ponds in an Arid Landscape".WETLANDS 40.3(2020):563-575.