基于HJ-1A高光谱影像的盐渍化土壤信息提取——以渭干河-库车河绿洲为例

doi:10.7522/j.issn.1000-694X.2013.00156

摘要/Abstract

摘要：

以环境小卫星高光谱影像为主要数据源，在野外实测样本的支持下进行光谱反射率及其变换形式与土壤含盐量的相关性分析，筛选盐渍化土壤响应敏感波段，利用曲线回归分析方法，建立基于高光谱影像的新疆渭干河-库车河绿洲土壤含盐量定量反演模型。结果表明：研究区土壤含盐量的影像响应波段基本位于近红外波段，其中以780~924 nm波长范围最佳，相关系数R≈0.8；反射率对数的倒数一阶微分土壤含盐量预测模型精度最高，回归方程为Y=-4.152-27.735X+769.813X2，模型及其检验的决定系数都在0.88以上，均方根误差约为3。该模型的建立可为区域盐渍化土壤信息的提取及监测提供参考。

关键词: HSI, 盐渍化, 曲线回归分析, 渭干河-库车河绿洲

Abstract:

Soil salinization is a major land degradation problem in Xinjiang, China. Remote sensing has been found to be useful in detection, mapping and monitoring of salt-affected soils. A curvilinear regression model was proposed in this paper to assess the degree of soil salinization, based on correlation between soil salinity and the hyper spectral imaging (HSI) reflectance variation and screening sensitive wavebands on soil salinity of HSI images. The results showed that: the most sensitive HSI images waveband on soil salt content was Near-infrared band, in which 780-924 nm wavelength was the best band with a correlation coefficient of 0.8; the model using the reciprocal of HSI reflectance logarithm in first order differential could get the best result (regression equation: Y=-4.152-27.735X+769.813X2), as the coefficient determination R2 was higher than 0.88 and the root mean square error was about 3. The model might provide a reference for information extraction and monitoring of remote sensing on a large scale soil salinization area.

Key words: HSI, soil salinization, curve regression model, Oasis of Ugan and Kuqa

中图分类号:

X833

雷磊，塔西甫拉提·特依拜，丁建丽，江红南，张飞，姚远，阿尔达克·克里木. 基于HJ-1A高光谱影像的盐渍化土壤信息提取——以渭干河-库车河绿洲为例[J]. 中国沙漠, 2013, 33(4): 1104-1109.

LEI Lei, TIYIP Tashpolat, DING Jian-li, JIANG Hong-nan, ZHANG Fei, YAO Yuan, KELIMU Ardak. Soil Salinization Information Extraction by Using Hyperspectral Data of HJ-1A HSI： A case study in the Oasis of Ugan & Kuqa, Xinjiang, China[J]. JOURNAL OF DESERT RESEARCH, 2013, 33(4): 1104-1109.

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