干旱区生态环境知识资源中心(Arid): Invasive buffelgrass detection using high-resolution satellite and UAV imagery on Google Earth Engine

Arid

DOI	10.1002/rse2.116
	Invasive buffelgrass detection using high-resolution satellite and UAV imagery on Google Earth Engine
	Elkind, Kaitlyn; Sankey, Temuulen T.; Munson, Seth M.; Aslan, Clare E.
通讯作者	Sankey, TT (corresponding author), No Arizona Univ, Sch Informat Comp & Cyber Syst, 1295 S Knoles Dr, Flagstaff, AZ 86011 USA.
来源期刊	REMOTE SENSING IN ECOLOGY AND CONSERVATION
EISSN	2056-3485
出版年	2019
卷号	5 期号:4 页码:318-331
英文摘要	Methods to detect and monitor the spread of invasive grasses are critical to avoid ecosystem transformations and large economic costs. The rapid spread of non-native buffelgrass(Pennisetum ciliare) has intensified fire risk and is replacing fire intolerant native vegetation in the Sonoran Desert of the southwestern US. Coarse-resolution satellite imagery has had limited success in detecting small patches of buffelgrass, whereas ground-based and aerial survey methods are often cost prohibitive. To improve detection, we trained 2 m resolution DigitalGlobe WorldView-2 satellite imagery with 12 cm resolution unmanned aerial vehicle (UAV) imagery and classified buffelgrass on Google Earth Engine, a cloud computing platform, using Random Forest (RF) models in Saguaro National Park, Arizona, USA. Our classification models had an average overall accuracy of 93% and producer's accuracies of 94-96% for buffelgrass, although user's accuracies were low. We detected a 2.92 km(2) area of buffelgrass in the eastern Rincon Mountain District (1.07% of the total area) and a 0.46 km(2) area (0.46% of the total area) in the western Tucson Mountain District of Saguaro National Park. Buffelgrass cover was significantly greater in the Sonoran Paloverde-Mixed Cacti Desert Scrub vegetation type, on poorly developed Entisols and Inceptisol soils and on south-facing topographic aspects compared to other areas. Our results demonstrate that high-resolution imagery improve on previous attempts to detect and classify buffelgrass and indicate potential areas where the invasive grass might spread. The methods demonstrated in this study could be employed by land managers as a low-cost strategy to identify priority areas for control efforts and continued monitoring.
英文关键词	Cloud computing drone non-native species random forest classification Sonoran Desert UAS WorldView-2
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000587566900003
WOS关键词	UNMANNED AERIAL VEHICLES ; BIOLOGICAL INVASIONS ; GRASS ; VEGETATION ; FUTURE ; PLANTS
WOS类目	Ecology ; Remote Sensing
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing
来源机构	United States Geological Survey
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/369499
作者单位	[Elkind, Kaitlyn; Sankey, Temuulen T.] No Arizona Univ, Sch Informat Comp & Cyber Syst, 1295 S Knoles Dr, Flagstaff, AZ 86011 USA; [Munson, Seth M.] US Geol Survey, Southwest Biol Sci Ctr, Flagstaff, AZ 86001 USA; [Aslan, Clare E.] No Arizona Univ, Landscape Conservat Initiat, Flagstaff, AZ 86011 USA
推荐引用方式 GB/T 7714	Elkind, Kaitlyn,Sankey, Temuulen T.,Munson, Seth M.,et al. Invasive buffelgrass detection using high-resolution satellite and UAV imagery on Google Earth Engine[J]. United States Geological Survey,2019,5(4):318-331.
APA	Elkind, Kaitlyn,Sankey, Temuulen T.,Munson, Seth M.,&Aslan, Clare E..(2019).Invasive buffelgrass detection using high-resolution satellite and UAV imagery on Google Earth Engine.REMOTE SENSING IN ECOLOGY AND CONSERVATION,5(4),318-331.
MLA	Elkind, Kaitlyn,et al."Invasive buffelgrass detection using high-resolution satellite and UAV imagery on Google Earth Engine".REMOTE SENSING IN ECOLOGY AND CONSERVATION 5.4(2019):318-331.