文献类型：期刊文献

中文题名：基于主成分分析法的戈壁地表砾石粒径遥感估测模型研究

英文题名：Remote-sensing Model for Estimating the Size of Gobi Surface Gravel Based on Principal Components Analysis

作者：姚爱冬[1] 曹晓阳[1] 冯益明[1]

第一作者：姚爱冬

机构：[1]中国林业科学研究院荒漠化研究所

年份：2014

卷号：0

期号：5

起止页码：1215-1221

中文期刊名：中国沙漠

外文期刊名：Journal of Desert Research

收录：CSTPCD;;北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；

基金：国家自然科学基金项目(31370708)资助

语种：中文

中文关键词：戈壁;砾石粒径;主成分分析;遥感;哈密

外文关键词：gobi;;size of gravel;;principal components analysis;;remote sensing;;Hami

分类号：P931.3

摘要：戈壁地表砾石粒径与遥感多光谱数据、植被指数及地学因子存在相关关系,但这些因子间可能存在着多重相关性,如利用这些因子直接建模估测戈壁地表砾石粒径,则可能出现病态模型。利用主成分分析法筛选因子,既可保留多个相关因子的主要信息,又可避免因子间共线性的问题,达到降维、简化模型的效果。因此,本文以新疆哈密市境内山前洪积扇戈壁地表砾石为研究对象,以2010年Landsat TM遥感影像及30m分辨率DEM为基本数据源,采用主成分分析法,从选择的43个遥感及地学因子(主要包括影像各波段信息、DEM、NDVI、GEMI,影像经K-T变换得到SBI、GVI、WVI三个分量,通过纹理分析得到的各个波段的均值、方差、信息熵、相关性及对比度等纹理因子,以及利用DEM提取的粗糙度等)中,筛选提取其主成分。结果表明,第一主成分至第五主成分的累计贡献率达98.0%,以前5个主成分作为自变量,借助SPSS软件中的多元回归分析功能,建立戈壁地表砾石粒径估测的回归模型,模型经方差分析及相关性检验,达到显著相关水平。基于建立的估测模型,进行了戈壁地表砾石粒径估测,经验证,实测值与估算值紧密相关。研究可帮助我们了解戈壁的特征,为戈壁区改造利用,认识沙粒迁移、沙漠扩展提供技术支持。
The size of gobi surface gravel is correlated to the factors such as multispectral remote sensing data,vegetation indexes and geological factors.However,these factors are usually strongly correlative.The size of gobi surface gravel model will become an ill-posed one if the model is built directly with the factors.The principal components(PCs)for those factors are obtained by principal components analysis(PCA).In that case,not only the main information of these factors can be reserved in the model,the multicolliearity problem of the factors can also be avoided.Moreover,the number of the variables decreases and the model is optimized.Based on the data obtained from Landsat TM images of 2010 and 30 m DEM at a alluvial-fan in Hami,Xinjiang,China,the paper analyzes the PCs by PCA for the 43 factors,which include 6 multi-spectral bands,2 kinds of vegetation index of NDVI and GEMI,surface roughness generated from DEM,mean,variance,entropy,correlation and contrast extracted from texture analysis.The results show that the accumulative ratio of contribution of the first 5 PCs is 98.0%.Then the size of gobi surface gravel model is set up by regression analysis of SPSS 18 based on these first 5 PCs.F test examination shows that the size of gobi surface gravel is correlated significantly to these first 5 PCs.Finally,the study estimates the size of gobi surface gravel based on the model,and the precision is above 80%.We could learn about the gobi characteristics,cognize the laws of sand grain move and desert extension by studying the grain size of gobi surface gravel.