干旱区生态环境知识资源中心(Arid): Mapping vegetation types in semi-arid riparian regions using random forest and object-based image approach: A case study of the Colorado River Ecosystem, Grand Canyon, Arizona

Arid

DOI	10.1016/j.ecoinf.2018.12.006
	Mapping vegetation types in semi-arid riparian regions using random forest and object-based image approach: A case study of the Colorado River Ecosystem, Grand Canyon, Arizona
	Uyen Nguyen 1; Glenn, Edward P.1; Thanh Duc Dang 2; Pham, Lien T. H.3
通讯作者	Uyen Nguyen
来源期刊	ECOLOGICAL INFORMATICS
ISSN	1574-9541
EISSN	1878-0512
出版年	2019
卷号	50 页码:43-50
英文摘要	Riparian regions are essential habitats for wildlife and play a vital role in agricultural production, but they are highly dynamic environments impacted by fluctuations of water levels. Monitoring vegetation types along narrow river corridors is complicated and requires high-resolution imagery and advanced remote sensing techniques due to the mixture of vegetation and other types of land covers. The primary aim of this paper is to develop a framework using airborne imagery, object-based image approach (OBIA), hyper-spectral analysis and Random Forest to classify vegetation along narrow, semi-arid riparian corridors via a case study of the Grand Canyon, the Colorado River. By analyzing hyper-spectral and field data with Random Forest, we found that the bandwidths from 642 to 682 nm and 750 to 870 nm were useful for vegetation classification in this case study. As a result, the red and near-infrared bands of aerial photos were used with ancillary data for species classification, and the overall accuracy (OA) of classification with these images reached up to 94.8% with a Kappa's coefficient of 0.93. The similarity of vegetation phonology caused most of the misclassified cases. Low cost unmanned aerial vehicles should be used to acquire more frequent data, which is essential to understand how vegetation patterns change over time.
英文关键词	Airborne imagery OBIA Random Forest Grand Canyon Vegetation classification
类型	Article
语种	英语
国家	USA ; Vietnam
收录类别	SCI-E
WOS记录号	WOS:000461401800005
WOS关键词	CLASSIFICATION ; RESTORATION ; MECHANISMS ; WETLANDS ; SCIENCE ; INDEXES ; BASIN
WOS类目	Ecology
WOS研究方向	Environmental Sciences & Ecology
来源机构	University of Arizona
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/215220
作者单位	1.Univ Arizona, Dept Soil Water & Environm Sci, Tucson, AZ 85721 USA; 2.Thuy Loi Univ, Inst Water & Environm Res, Ho Chi Minh City, Vietnam; 3.Vietnam Natl Univ Ho Chi Minh City, Univ Sci, Fac Environm, Ho Chi Minh City, Vietnam
推荐引用方式 GB/T 7714	Uyen Nguyen,Glenn, Edward P.,Thanh Duc Dang,et al. Mapping vegetation types in semi-arid riparian regions using random forest and object-based image approach: A case study of the Colorado River Ecosystem, Grand Canyon, Arizona[J]. University of Arizona,2019,50:43-50.
APA	Uyen Nguyen,Glenn, Edward P.,Thanh Duc Dang,&Pham, Lien T. H..(2019).Mapping vegetation types in semi-arid riparian regions using random forest and object-based image approach: A case study of the Colorado River Ecosystem, Grand Canyon, Arizona.ECOLOGICAL INFORMATICS,50,43-50.
MLA	Uyen Nguyen,et al."Mapping vegetation types in semi-arid riparian regions using random forest and object-based image approach: A case study of the Colorado River Ecosystem, Grand Canyon, Arizona".ECOLOGICAL INFORMATICS 50(2019):43-50.