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  • CN 62-1070/P
  • ISSN 1000-694X
  • 双月刊 创刊于1981年
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生物与土壤

新疆典型绿洲土壤电导率和pH值的光谱响应特征

  • 赵振亮 ,
  • 塔西甫拉提·特依拜 ,
  • 丁建丽 ,
  • 张 飞 ,
  • 雷 磊 ,
  • 买买提·沙吾提
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  • 新疆大学 资源与环境科学学院/绿洲生态教育部重点实验室, 新疆 乌鲁木齐 830046

收稿日期: 2012-06-19

  修回日期: 2012-08-13

  网络出版日期: 2012-08-13

Characteristics of Spectral Responding to Soil Electrical Conductivity and pH in the Typical Oasis of Xinjiang

  • ZHAO Zhen-liang ,
  • TASHPOLAT Tiyip ,
  • DING Jian-li ,
  • ZHANG Fei ,
  • LEI Lei ,
  • MAMAT Sawut
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  • College of Resources and Environment Science/Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China

Received date: 2012-06-19

  Revised date: 2012-08-13

  Online published: 2012-08-13

摘要

土壤理化性质影响土壤质量,直接决定作物的产量,极易受到灌溉的影响。选择新疆典型绿洲——渭干河-库车河三角洲绿洲作为靶区,利用土壤光谱反射率预测土壤的电导率、pH值。首先,对土壤光谱反射率做变换,得到18种形式的反射率;其次,对18种形式的反射率与土壤电导率、pH值进行相关与回归分析,得到预测方程;最后,验证预测方程的精度,并确定最佳方程。结果显示:可以用土壤的光谱反射率预测土壤电导率、pH值,土壤电导率的预测方程为反射率的一阶导数微分形式,均方根误差为0.184;土壤pH值的预测方程为倒数的二阶导数微分形式,均方根误差为0.278。快速预测土壤电导率、pH值可以为土壤质量的评价提供数据基础,有利于正确有效地指导农业生产。

本文引用格式

赵振亮 , 塔西甫拉提·特依拜 , 丁建丽 , 张 飞 , 雷 磊 , 买买提·沙吾提 . 新疆典型绿洲土壤电导率和pH值的光谱响应特征[J]. 中国沙漠, 2013 , 33(5) : 1413 -1419 . DOI: 10.7522/j.issn.1000-694X.2013.00136

Abstract

The soil physical and chemical properties, which are extremely influenced by irrigation, have impacts on the quality of soil, and determine the crop yields directly. There is a large drought agricultural region in Xinjiang, so, to study the soil physical and chemical properties is essential. The author selected a delta oasis between the Ugan River and the Kuqa River as objects. The aim of this study was how to use spectral of soil to obtain the properties of soil rapidly and efficiently. Firstly, we transformed the spectral reflectance to 18 kinds of forms of reflectance. Secondly, correlation analysis and multiple regression analysis were done to these kinds of reflectance and the properties of soil. Finally, we used the data to validate the predictive accuracy and determined the best prediction equations of the properties of soil. The results showed that these equations were good. The prediction equation of soil electrical conductivity was the first derivative differential form, the root mean square error was 0.184. The best prediction equation of soil pH was the second derivative differential forms of the reciprocal, the root mean square error was 0.278. It could be a feasible way to use the spectral reflectance to predict soil EC and pH. The study also provides data base for the land quality assessment and sustainable development of the soil and guides the agricultural production correctly and effectively.

参考文献

[1]汪媛媛,杨忠芳,余芳.土壤质量评价研究进展[J].安徽农业科学,2011,39(36):22617-22652,22657.

[2]李法虎.土壤物理化学[M].北京:水利电力出版社,2006:207-216.

[3]Metternicht G,Alfred Zinck J.Remote Sensing of Soil Salinization Impact on Land Management[M].New York:CRC Press,2009:63-113.

[4]Domsch H,Giebel A.Estimation of soil textural features from soil electrical conductivity recorded using the EM38[J].Precision Agriculture,2004,5:389-409.

[5]Corwin D,Lesch S.Application of soil electrical conductivity to precision agriculture[J].Agronomy Journal,2003,95(3):455-471.

[6]崔耀平,王让会,刘彤,等.基于光谱混合分析的干旱荒漠区植被遥感信息提取研究——以古尔班通古特沙漠西缘为例[J].中国沙漠,2010,30(2):334-341.

[7]李晓松,李增元,高志海,等.基于NDVI与偏最小二乘回归的荒漠化地区植被覆盖度高光谱遥感估测[J].中国沙漠,2011,31(1):162-167.

[8]赵金,陈曦,古丽加·帕尔.塔里木河荒漠植被光谱可分析模拟[J].中国沙漠,2009,29(2):270-278.

[9]孙小艳,常学礼,张宁,等.不同取样单元对干旱区绿洲小麦地上生物量光谱估算模型的影响[J].中国沙漠,2012,32(2):568-571.

[10]夏学齐,季峻峰,陈骏,等.土壤理化参数的反射光谱分析[J].地学前缘,2009,16(4):354-362.

[11]吴亚坤,杨劲松,李晓明.基于光谱指数与EM38 的土壤盐分空间变异性研究[J].光谱学与光谱分析,2009,29(4):1023-1027.

[12]张芳,熊黑钢,栾福明,等.土壤碱化的实测光谱响应特征[J].红外与毫米波学报,2011,30(1):55-60.

[13]霍金炜,杨德刚,张新焕.基于农业节水的干旱区绿洲可持续发展研究——以渭干河流域为例[J].中国沙漠,2013,33(1):295-301.

[14]乔冬梅,齐学斌,庞鸿滨,等.地下水作用下微咸水灌溉对土壤及作物的影响[J].农业工程学报,2009,25(1):55-61.

[15]黄翠华,薛娴,彭飞,等.不同矿化度地下水灌溉对民勤土壤环境的影响[J].中国沙漠,2013,33(2):590-596.

[16]Goldman S.Vibration Spectrum Analysis:A Practical Approach[M].New York:Industrial Press Inc,1999:12-19.

[17]高荣强,范世福,严衍禄,等.近红外光谱的数据预处理研究[J].光谱学与光谱分析,2004,24(12):1563-1565.

[18]童庆禧,张兵,郑兰芬.高光谱遥感的多学科应用[M].北京:电子工业出版社,2006:32-41.

[19]浦瑞良,宫鹏.高光谱遥感及其应用[M].北京:高等教育出版社,2003:53-55.

[20]徐元进,胡光道,张振飞.包络线消除法及其在野外光谱分类中的应用[J].地理与地理信息科学,2005,21(6):11-14.

[21]Tsai F,philpot W D.A derivative-aided hyperspectral image analysis system for land-cover classification[J].IEEE Transaction on Geoscience and Remote Sensing,2002,10(2):416-425.

[22]周英豪,范翠玲,时伟,等.新编统计学[M].北京:北京大学出版社,2006:215-221.

[23]黄林,陈斌.现代统计学原理[M].广州:暨南大学出版社,2005:120-138.

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