基于热红外光谱的干旱区土壤盐分监测研究

干旱区地理 ›› 2017, Vol. 40 ›› Issue (1): 181-187.

基于热红外光谱的干旱区土壤盐分监测研究

买买提·沙吾提^1,2, 吐尔逊·艾山^1,3, 塔西甫拉提·特依拜^1,2, 如则麦麦提·米吉提^1,2, 麦尔耶姆·亚森^1,2, 依力亚斯江·努尔麦麦提^1,2

1 新疆大学资源与环境科学学院, 新疆乌鲁木齐 830046;
2 新疆大学绿洲生态教育部重点实验室, 新疆乌鲁木齐 830046;
3 新疆维吾尔自治区农业资源区划办公室, 新疆乌鲁木齐 83000

收稿日期:2016-07-10 修回日期:2016-10-01 出版日期:2017-01-25
作者简介:买买提·沙吾提,男(维吾尔族),新疆喀什人,副教授,博士,主要从事资源环境及遥感应用研究.Email:korxat@xju.edu.cn
基金资助:
国家自然科学基金项目（41361016，40901163）；新疆维吾尔科技厅基金（2014KL005）

Salt content monitoring on thermal infrared emissivity in arid area

Mamat SAWUT^1,2, Tuerxun AISHAN^1,3, Tashpolat TIYIP^1,2, Ruzimaimaiti MIJITI^1,2, Maieryemu YASEN^1,2, Ilyas NURMEMET^1,2

1 College of Resources and Environmental Sciences, Xinjiang University, Urumqi 830046, Xinjiang, China;
2 Ministry of Education Key Laboratory of Oasis Ecology at Xinjiang University, Urumqi 830046, Xinjiang, China

Received:2016-07-10 Revised:2016-10-01 Online:2017-01-25

摘要/Abstract

摘要： 土壤盐渍化是新疆最常见的土地退化过程，已经严重威胁到了当地的农业生产、生态稳定和经济发展。通过对渭库绿洲土壤含盐量和土壤热红外光谱分析，探讨了土壤含盐量与热红外发射率之间的定量关系。结果表明：（1）盐渍化土壤的发射率随着含盐量的变化而发生变化，当土壤盐分增加时，发射率也随之增大。（2）土壤含盐量与热红外发射率光谱数据相关性在8.5～9.5 μm波段范围内表现尤为显著，相关系数超过0.8，最高为0.90，对应波段范围9.259～9.271 μm。（3）运用回归模型一阶导数变换形式下建模效果和预测精度都是最优的，R²达到了0.899，RMSE最小为1.734。热红外光谱技术可以反演土壤含盐量，为利用热红外遥感识别土壤盐分信息提供技术支撑。

关键词: 土壤含盐量, 热红外遥感, 发射率光谱, 数据变换, 多元回归

Abstract: Soil salinity is a critical problem in many arid and irrigated agricultural areas. It reduces soil quality and limits the growing of crops. Monitoring soil salinity is important for controlling this problem. During the last decades, many researches aim to develop methods for assessing, mapping, and monitoring salt-affected soils using remote sensing data in combination with field measurements. The methods were classified as visual interpretation of satellite imagery, digital analysis of multispectral remote sensing data, quantitative analysis of hyperspectral imagery and integrated modeling. The main objective of this study is to assess the usefulness of the thermal infrared (TIR)emissivity for predicting salt content. For this purpose, soil samples were collected from the field for laboratory determination in this study. And spectral data was acquired from Fourier Transform spectrometer (102F), predicting model was developed using a Regression Model. The spectral results show that different salt contents in soil exhibited different emissivity. The emissivity were extremely sensitive to salt content in the 8.5-9.5 μm region, with a high correlation value (0.8 in the 9.259-9.271 μm region), holding a great promise for prediction of salt content; the Stepwise Multiple Regression Mode performed well (R²=0.899, RMSE=1.734) based on the first derivative spectral pre-treatment. The results of this study indicate that infrared thermal data provide a useful tool for predicting salt content in soil that commonly occurs in aid region.

Key words: salt content, Thermal Infrared Remote Sensing, Soil emissivity spectra, Stepwise multiple regression(SMR)

中图分类号:

TP722.5

买买提·沙吾提, 吐尔逊·艾山, 塔西甫拉提·特依拜, 如则麦麦提·米吉提, 麦尔耶姆·亚森, 依力亚斯江·努尔麦麦提. 基于热红外光谱的干旱区土壤盐分监测研究[J]. 干旱区地理, 2017, 40(1): 181-187.

Mamat SAWUT, Tuerxun AISHAN, Tashpolat TIYIP, Ruzimaimaiti MIJITI, Maieryemu YASEN, Ilyas NURMEMET. Salt content monitoring on thermal infrared emissivity in arid area[J]. , 2017, 40(1): 181-187.

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