干旱区生态环境知识资源中心(Arid): Identifying Vegetation in Arid Regions Using Object-Based Image Analysis with RGB-Only Aerial Imagery

Arid

DOI	10.3390/rs11192308
	Identifying Vegetation in Arid Regions Using Object-Based Image Analysis with RGB-Only Aerial Imagery
	Silver, Micha; Tiwari, Arti; Karnieli, Arnon
通讯作者	Silver, Micha
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2019
卷号	11 期号:19
英文摘要	Vegetation state is usually assessed by calculating vegetation indices (VIs) derived from remote sensing systems where the near infrared (NIR) band is used to enhance the vegetation signal. However VIs are pixel-based and require both visible and NIR bands. Yet, most archived photographs were obtained with cameras that record only the three visible bands. Attempts to construct VIs with the visible bands alone have shown only limited success, especially in drylands. The current study identifies vegetation patches in the hyperarid Israeli desert using only the visible bands from aerial photographs by adapting an alternative geospatial object-based image analysis (GEOBIA) routine, together with recent improvements in preprocessing. The preprocessing step selects a balanced threshold value for image segmentation using unsupervised parameter optimization. Then the images undergo two processes: segmentation and classification. After tallying modeled vegetation patches that overlap true tree locations, both true positive and false positive rates are obtained from the classification and receiver operating characteristic (ROC) curves are plotted. The results show successful identification of vegetation patches in multiple zones from each study area, with area under the ROC curve values between 0.72 and 0.83.
英文关键词	segmentation classification vegetation arid regions gray-level co-occurrence matrix texture object-based image analysis threshold optimization
类型	Article
语种	英语
国家	Israel
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000496827100122
WOS关键词	RANDOM FOREST ; NEGEV DESERT ; CLASSIFICATION ; INDEXES ; PRODUCTIVITY ; ALGORITHMS ; FEATURES
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
EI主题词	2019-10-01
来源机构	Ben-Gurion University of the Negev
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/310168
作者单位	Ben Gurion Univ Negev, Jacob Blaustein Inst Desert Res, Remote Sensing Lab, IL-84105 Beer Sheva, Israel
推荐引用方式 GB/T 7714	Silver, Micha,Tiwari, Arti,Karnieli, Arnon. Identifying Vegetation in Arid Regions Using Object-Based Image Analysis with RGB-Only Aerial Imagery[J]. Ben-Gurion University of the Negev,2019,11(19).
APA	Silver, Micha,Tiwari, Arti,&Karnieli, Arnon.(2019).Identifying Vegetation in Arid Regions Using Object-Based Image Analysis with RGB-Only Aerial Imagery.REMOTE SENSING,11(19).
MLA	Silver, Micha,et al."Identifying Vegetation in Arid Regions Using Object-Based Image Analysis with RGB-Only Aerial Imagery".REMOTE SENSING 11.19(2019).