干旱区生态环境知识资源中心(Arid): 黄河黑山峡无植被区的地表组成物质遥感信息模型

Arid

	黄河黑山峡无植被区的地表组成物质遥感信息模型
其他题名	Research on mass ingredient model based on remote sensing technology in non-vegetation area of Heishan Gorge basin
	王树东 1; 杨胜天 2; 温志群 3; 曾红娟 4; 王玉娟 5
ISSN	1000-0585
出版年	2009
卷号	28 期号:4 页码:1128-1135
中文摘要	下垫面物质组成是土壤侵蚀模型最主要的输入参数.应用遥感技术提取无植被地区下垫面物质组成信息对于研究大面积土壤侵蚀是非常重要的.黄河黑山峡地区地形复杂,加之裸土、沙漠和岩石光谱的相似性与复杂性,使遥感技术在该地区的应用受到限制,但是由于地形起伏、岩石风化及表面粗糙度等因素的影响,石质山地纹理明显.综合了光谱和纹理信息特征,本文提出光谱归一化方法,并将归一化的光谱与纹理信息相结合构建了石质山地指数(RMI),应用归一化光谱进一步得到沙漠指数(DI),实现石质山地、沙漠与裸土分离.结果表明,该方法提高了信息提取的精度.
英文摘要	It is very important to extract various kinds of underlying surfaces for soil erosion model because of various contributions of soil, vegetation, desert and rock under the same natural condition. Currently, traditional classification and information extraction methods based on remote sensing data have been widely applied in eco-hydrologic process field. But due to similarity and complexity of spectrums of soil, rock and desert, it was hard to dis-tinguish soil, desert and rock in the same area. Rock land mountain, desert and soil moun-tain are widely distributed in the middle and upper reaches of Yellow River basin. In this paper, real spectrums of rock, soil and desert measured in lab using ASD (Analysis Spec-trum Device) are analyzed, the result indicates that they could be well distinguished. On account of complex topographic changes and underlying surface roughness, spectrums from Landsat TM 5 become more complex and uncertain, but characteristics of surface texture of the rock land mountain are obvious and could be well differentiated from that of soil mountain and desert. For problem-solving of spectral complexity, normalized spectral index (NSI) is presented: NSI=(R4 + R3 + R2 - 3R1)/ (R5- R1)(R1, R2, R3.,R4 and R5 individually refer to reflectance of the Langsat TM bands from 1 to 5). Then, the rock land mountain index (RMI) is presented according to the characteristics of normalized spectral index and texture: RMI = (R4 + R3 + R2 - 3 R1 )/(R5 - R1) + Rt (Rt refers to homogeneity index of texture), and the result indicates that information extraction preci-sion of rock land mountain is 82. 7% through set of threshold. Finally, we analyze spectral normalized spectral information of desert and soil and establish desert-exposed soil differ-ence model (DS-Def): = DS- Def = (R4-R1) / (R5-R1) + R1+R2, and the result indi-cates that desert information extraction precision is 73.1%, and that of exposed soil is 72.8%. The above results indicate that the information extraction precision is higher than that by methods of traditional classification.
中文关键词	下垫面类型 ; 光谱与纹理 ; 遥感模型 ; 土壤侵蚀
英文关键词	heterogeneous underlying surface spectrum and texture remote sensing mod-el soil erosion
语种	中文
国家	中国
收录类别	CSCD
WOS类目	FORESTRY
WOS研究方向	Forestry
CSCD记录号	CSCD:3575934
来源机构	北京师范大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/223384
作者单位	1.北京师范大学,地理学与遥感科学学院, 北京 100875, 中国; 2.北京师范大学, 遥感科学国家重点实验室, 北京 100875, 中国; 3.北京师范大学, 北京市环境遥感与数字城市重点实验室, 北京 100875, 中国; 4.北京师范大学,GIS与遥感中心, 北京 100875, 中国; 5.北京师范大学
推荐引用方式 GB/T 7714	王树东,杨胜天,温志群,等. 黄河黑山峡无植被区的地表组成物质遥感信息模型[J]. 北京师范大学,2009,28(4):1128-1135.
APA	王树东,杨胜天,温志群,曾红娟,&王玉娟.(2009).黄河黑山峡无植被区的地表组成物质遥感信息模型.,28(4),1128-1135.
MLA	王树东,et al."黄河黑山峡无植被区的地表组成物质遥感信息模型".28.4(2009):1128-1135.