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
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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.
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.
引文
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[11]杨劲松,姚荣江,邹平,等.海涂区不同植被类型下土壤盐渍剖面及其电磁感应响应特征[J].应用生态学报,2008,19(10):2117-2124.
[12]王飞,丁建丽,伍漫春.基于NDVI—SI特征空间的土壤盐渍化遥感模型[J].农业工程学报,2010,26(8):168-173.
[13]侯春玲.基于BP神经网络的黄河三角洲典型盐渍区遥感监测研究[D].青岛:中国石油大学(华东),2010.
[2]李潭潭.黄河三角洲典型盐渍区遥感监测研究[D].青岛:中国石油大学(华东),2015.
[3]Sandholt I,Rasmussen K,Andersen J.A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status[J].Remote Sensing of Environment,2002,79(2):213-224.
[4]詹志明,秦其明,阿布都瓦斯提·吾拉木,等.基于NIRRed光谱特征空间的土壤水分监测新方法[J].中国科学·D辑:地球科学,2006,36(11):1020-1026.
[5]杨曦,武建军,闫峰,等.基于地表温度—植被指数特征空间的区域土壤干湿状况[J].生态学报,2009,29(3):1205-1216.
[6]曾永年,向南平,冯兆东,等.Albedo-NDVI特征空间及沙漠化遥感监测指数研究[J].地理科学,2006,26(1):75-82.
[7]王飞.基于特征空间的土壤盐渍化遥感应用研究[D].乌鲁木齐:新疆大学,2010.
[8]哈学萍,丁建丽,塔西甫拉提·特依拜,等.基于SI-Albedo特征空间的土壤盐渍化遥感监测指数研究[J].土壤学报,2009,46(4):698-672.
[9]Khan N M,Sato Y.Monitoring hydro-salinity status and its impact in irrigated semi-arid areasusing IRS-1B LISS-II data[J].Asian J.Geoinform,2001,1(3):63-73.
[10]哈学萍,丁建丽,塔西甫拉提·特依拜,等.基于SI-Albedo特征空间的干旱区盐渍化土壤信息提取研究:以克里雅河绿洲为例[J].土壤学报,2009,46(3):382-385.
[11]杨劲松,姚荣江,邹平,等.海涂区不同植被类型下土壤盐渍剖面及其电磁感应响应特征[J].应用生态学报,2008,19(10):2117-2124.
[12]王飞,丁建丽,伍漫春.基于NDVI—SI特征空间的土壤盐渍化遥感模型[J].农业工程学报,2010,26(8):168-173.
[13]侯春玲.基于BP神经网络的黄河三角洲典型盐渍区遥感监测研究[D].青岛:中国石油大学(华东),2010.