干旱区生态环境知识资源中心(Arid): 离子吸附型稀土矿区地表荒漠化遥感监测方法比较

Arid

	离子吸附型稀土矿区地表荒漠化遥感监测方法比较
其他题名	Comparison of Remote Sensing Monitoring Methods for Land Desertification in Ion-adsorption Rare Earth Mining Areas
	李迎双; 李恒凯; 徐丰
来源期刊	稀土
ISSN	1004-0277
出版年	2021
卷号	42 期号:1 页码:9-20
中文摘要	离子吸附型稀土由于特殊的开采方式及红壤背景,导致矿区大面积土地退化及荒漠化,准确快速提取荒漠化信息是矿区环境治理的前提。以定南县岭北矿区为研究样区,以Landsat-8的影像作为数据源,分别用Albedo- NDVI特征空间理论、线性光谱像元解析(Linear Spectral Mixture Model,LSMM)两种方法对稀土矿区荒漠化信息进行提取,并随机取样,利用同年同月的Google高分影像,对研究区荒漠化信息提取结果进行精度验证、对比分析。结果表明,通过两种方法反演得到的荒漠化土地分级结果与各地物类型的空间分布基本一致,但是在对比分析中发现,基于Albedo-NDVI 特征空间理论提取的矿区土地荒漠化信息更能明显地反映离子型稀土矿区的荒漠化状况,使不同荒漠化类型土地得到有效区分,在定量评价中分级总体精度为87% ,Kappa系数为83.42%,整体而言, Albedo-NDVI特征空间理论方法对于离子型稀土矿区荒漠化信息提取具有更高的适用性。
英文摘要	Due to the special mining method and red soil background of ion-adsorption rare earth mines,large-area land degradation and desertification in mining areas are brought about. Accurate and rapid extraction of desertification information is the premise of environmental management in mining areas. In this paper,Lingbei mining area in Dingnan County is taken as the research sample area,Landsat-8 image is taken as the data source,Albedo-NDVI characteristic space theory and Linear Spectral Mixture Model (LSMM) are respectively used to extract desertification information in rare earth mining area,and random sampling is carried out. Google high-score image in the same month of the same year is used to verify and compare the accuracy of the extraction results of desertification information in the research area. The results show that the inversion results of desertification classification of land obtained by the two methods are basically consistent with the spatial distribution of various species types. However,in the comparative analysis,it is found that the desertification information extracted from the mining area based on Albedo-NDVI characteristic space theory can more clearly reflect the desertification status of the ionic rare earth mining area and effectively distinguish different desertification types of land. In the quantitative evaluation,the overall classification accuracy is 87%,and the Kappa coefficient is 83.42%. Overall,Albedo-NDVI characteristic space theory method has high applicability for the extraction of desertification information from the ion-adsorption rare earth mining area.
中文关键词	稀土矿区 ; 土地荒漠化 ; Albedo-NDVI特征空间 ; 线性光谱像元解析
英文关键词	rare earth mining area land desertification Albedo-NDVI space LSMM
类型	Article
语种	中文
收录类别	CSCD
WOS类目	Remote Sensing
CSCD记录号	CSCD:6899718
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/354502
作者单位	李迎双, 江西理工大学土木与测绘工程学院, 赣州, 江西 341000, 中国. 李恒凯, 江西理工大学土木与测绘工程学院, 赣州, 江西 341000, 中国. 徐丰, 江西理工大学土木与测绘工程学院, 赣州, 江西 341000, 中国.
推荐引用方式 GB/T 7714	李迎双,李恒凯,徐丰. 离子吸附型稀土矿区地表荒漠化遥感监测方法比较[J],2021,42(1):9-20.
APA	李迎双,李恒凯,&徐丰.(2021).离子吸附型稀土矿区地表荒漠化遥感监测方法比较.稀土,42(1),9-20.
MLA	李迎双,et al."离子吸附型稀土矿区地表荒漠化遥感监测方法比较".稀土 42.1(2021):9-20.