基于植被指数-盐分指数特征空间的黄河三角洲盐渍化遥感监测研究  

Remote Sensing Monitoring Model of Soil Salinization in the Yellow River Delta Zone based on Vegetation Index- Salt Index Feature Space

作　　者：樊彦国[1] 张维康 刘敬一 

机构地区：[1]中国石油大学(华东)地球科学与技术学院,山东青岛266580

出　　处：《山东农业科学》2016年第5期137-141,共5页Shandong Agricultural Sciences

基　　金：山东省科技攻关项目"盐渍化遥感监测及暗管改碱与节水集成技术及其应用"(2008GG10009018)

摘　　要：受地理位置影响,黄河三角洲地区土壤盐渍化现象比较严重,已经影响到当地农业和经济的可持续发展。遥感为盐渍化监测提供了一种简单高效的手段。本研究依据特征空间理论,采用植被指数和盐分指数构建二维特征空间,对黄河三角洲地区的盐渍化现象进行分析,构建遥感监测模型,并结合实测含盐量数据进行精度验证。结果表明,该模型虽然可以模拟盐渍化的整体趋势,但精度还有待提高,究其原因,可能与混合像元的影响有关,后续需进一步研究以提高模型精度。Affected by geographical location,the soil salinization phenomenon in the Yellow River Delta region is quite severe. And it has affected the sustainable development of local agriculture and economy. Remote sensing provides a simple and efficient method for soil salinization monitoring. Based on the theory of feature space,the two- dimensional feature space was built in this paper using normalized difference vegetation index and salt index to analyze the salinization phenomenon in the Yellow River Delta. Then the remote sensing monitoring model was established,and its accuracy was verified combined with measured salinity data.The results showed that this model could simulate the whole trend of salinization,but its accuracy still needed to be improved. It might be associated with the effects of mixed pixel. Further researches were required to improve the accuracy of this model.

关 键 词：盐渍化 特征空间 植被指数 盐分指数 黄河三角洲 

分 类 号：S156.4[农业科学—土壤学]