A Tailings Pond Identification Method Based on Spatial Combination of Objects

doi:10.1109/JSTARS.2019.2904297

	A Tailings Pond Identification Method Based on Spatial Combination of Objects
	Liu, Kun 1,2,3,4; Liu, Ronggao 2,3; Liu, Yang 2,3
刊名	IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
	2019-08-01
卷号	12 期号:8 页码:2707-2717
关键词	Context information object-based classification spatial combination tailings pond
ISSN号	1939-1404
DOI	10.1109/JSTARS.2019.2904297
通讯作者	Liu, Ronggao(liurg@igsnrr.ac.cn)
英文摘要	Tailings ponds pose a significant risk to the safety of the surrounding residents and the local ecological environment. Therefore, it is necessary to efficiently and accurately monitor tailings ponds. However, the internal structures of tailings ponds are heterogeneous, and they are typically identified through manual interpretation. In this paper, an identification method for four main structures of tailings ponds, namely, starter dams, embankments, deposited beach, and water body, is proposed based on the spatial combinations among them. First, hierarchy objects were established based on GaoFen-2 imagery. Then, candidate objects (such as embankment-like) were identified using the spectral features and the number of parallel lines. Subsequently, rural settlement-like objects were eliminated as interfering objects based on their shapes and distributions. Finally, four structures of tailings ponds could be identified based on their spatial combination. Six cases of tailings ponds were selected for validation. Interference categories were eliminated step by step (79.64%, 38.21%, and 39.75% for case A), and all four structures were identified. The overall identification accuracies were 88.14%-96.21%. The average accuracy is 32.02% higher than that of comparison experiments using the random forest. The method was proved to be applicable to the automatic identification of mining areas, which is of great significance for efficient and accurate supervision of mining safety.
资助项目	Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19080303] ; Youth Innovation Fund Program of AGRS[2016YFL11] ; National Key Research and Development Program of China[2016YFA0600201]
WOS关键词	IMAGE-ANALYSIS ; CLASSIFICATION ; FEATURES ; EXTRACTION
WOS研究方向	Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000487530100011
资助机构	Strategic Priority Research Program of the Chinese Academy of Sciences ; Youth Innovation Fund Program of AGRS ; National Key Research and Development Program of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/129617]
专题	中国科学院地理科学与资源研究所
通讯作者	Liu, Ronggao
作者单位	1.Minist Nat Resources PR China, Land Satellite Remote Sensing Applicat Ctr, Beijing 100048, Peoples R China 2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.Univ Chinese Acad Sci, Coll Resource & Environm, Beijing 100049, Peoples R China 4.Minist Land & Resources, Key Lab Airborne Geophys & Remote Sensing Geol, Beijing 100083, Peoples R China
推荐引用方式 GB/T 7714	Liu, Kun,Liu, Ronggao,Liu, Yang. A Tailings Pond Identification Method Based on Spatial Combination of Objects[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2019,12(8):2707-2717.
APA	Liu, Kun,Liu, Ronggao,&Liu, Yang.(2019).A Tailings Pond Identification Method Based on Spatial Combination of Objects.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,12(8),2707-2717.
MLA	Liu, Kun,et al."A Tailings Pond Identification Method Based on Spatial Combination of Objects".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 12.8(2019):2707-2717.