干旱区生态环境知识资源中心(Arid): A Method of Extracting Mining Disturbance in Arid Grassland Based on Time Series Multispectral Images

Arid

DOI	10.3964/j.issn.1000-0593(2019)12-3788-06
	A Method of Extracting Mining Disturbance in Arid Grassland Based on Time Series Multispectral Images
	Li Jing; Deng Xiao-juan; Yang Zhen; Liu Qian-long; Wang Yuan; Cui Lu-yuan
通讯作者	Li, J (corresponding author), China Univ Min & Technol Beijing, Coll Geosci & Surveying Engn, Beijing 100083, Peoples R China.
来源期刊	SPECTROSCOPY AND SPECTRAL ANALYSIS
ISSN	1000-0593
出版年	2019
卷号	39 期号:12 页码:3788-3793
英文摘要	Surface mining will completely change the original landscape pattern of land use, directly destroy the local ecological environment, and even affect the production and life of the nearby residents; therefore, more and more scholars have begun to pay attention to mining disturbance. Previous studies on extracting mining disturbances from temporal multispectral images focused on forest areas with single disturbance form. However, most surface mines in China are concentrated in grassland areas, and in the grassland mining areas in northeastern China, mining disturbances are more difficult to be identified because of their fragile ecological environment and the existence of various other forms of disturbance. In order to clarify the mining disturbance of grassland open stope in ecologically fragile areas in northeastern China, the authors taking Shengli mining area as an example, firstly employs 27 Landsat multi-spectral remote sensing images from 1986 to 2017, and bases the study on the long time series trajectory change characteristics of NDVI (normalized difference vegetation index). (In order to remove the effects of phenology, cloud and shadow on time series multispectral images, BISE-WT filter is used to filter the original NDVI time series to effectively remove the noise in the time series NDVI data and retain the effective information at the same time). After sample point training, CV threshold (Coefficient of Variation) and Max vegetation threshold are obtained. The Max vegetation threshold (vegetation threshold) is then used to construct the CV-Max disturbance recognition model and extract the disturbance distribution in the study area. Furthermore, using vegetation threshold, NDVI time series trajectory is analyzed to obtain disturbance interannual information and reconstruct disturbance history map. Then, by analyzing the spectral characteristics of typical terrain in the study area, bare coal extraction rules are constructed to extract the distribution of hare coal in the study area. Finally, the topological relationship between bare coal and disturbance area is constructed and a spatial topological overlay analysis is conducted to obtain mining disturbance information. The accuracy verification reveals the extraction accuracy of mining disturbance is 93. 17% (Kappa coefficient= 0. 85) and the extraction accuracy of disturbance interannual information is 83. 35% (Kappa coefficient= 0. 81) respectively. The results show that during the study period, the mining disturbance area accounts for 8. 90% of the total area of the study area in space; in terms of time, the occurrence of mining disturbance concentrated in 2000-2009, during which the mining disturbance pixels accounted for 76. 70% of the total mining disturbance pixels; the years from 1988 to 1998 witness the initial period of land destruction, and in 2000-2005, land destruction increased in the mining area, and in 2006-2009, the land destruction the mining area reached the peak. The proportion trend of mining disturbance pixels in 2010-2017 is relatively flat and continues to be at a low level, and the scope of land damage in mining area is basically stable. In view of the ecologically fragile grassland mining area in northeastern China, the method of extracting mining disturbance information by using NDVI and hare coal spectral features based on time series multispectral images is feasible. The research results can provide data and theoretical method support for the sustainable development of arid and semi-arid grassland surface mining area.
英文关键词	Landsat multi-temporal NDVI Spectral features Mining disturbance CV-Max model
类型	Article
语种	中文
收录类别	SCI-E
WOS记录号	WOS:000510806200022
WOS类目	Spectroscopy
WOS研究方向	Spectroscopy
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/369692
作者单位	[Li Jing; Deng Xiao-juan; Yang Zhen; Liu Qian-long; Wang Yuan; Cui Lu-yuan] China Univ Min & Technol Beijing, Coll Geosci & Surveying Engn, Beijing 100083, Peoples R China
推荐引用方式 GB/T 7714	Li Jing,Deng Xiao-juan,Yang Zhen,et al. A Method of Extracting Mining Disturbance in Arid Grassland Based on Time Series Multispectral Images[J],2019,39(12):3788-3793.
APA	Li Jing,Deng Xiao-juan,Yang Zhen,Liu Qian-long,Wang Yuan,&Cui Lu-yuan.(2019).A Method of Extracting Mining Disturbance in Arid Grassland Based on Time Series Multispectral Images.SPECTROSCOPY AND SPECTRAL ANALYSIS,39(12),3788-3793.
MLA	Li Jing,et al."A Method of Extracting Mining Disturbance in Arid Grassland Based on Time Series Multispectral Images".SPECTROSCOPY AND SPECTRAL ANALYSIS 39.12(2019):3788-3793.