| 光谱解混下耕地土壤铬含量GMDH模型反演 |
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| 引用本文： | 郭云开,章琼,张思爱,谢晓峰.光谱解混下耕地土壤铬含量GMDH模型反演[J].测绘通报,2021,0(5):73-76. |
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| 作者姓名： | 郭云开 章琼 张思爱 谢晓峰 |
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| 作者单位： | 1. 广州城建职业学院建筑工程学院, 广东 广州 510925;2. 长沙理工大学测绘遥感应用技术研究所, 湖南 长沙 410076 |
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| 基金项目： | 国家自然科学基金(41671498;41471421) |
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| 摘 要： | 针对遥感影像反射率与重金属元素间的光谱响应弱,土壤重金属经典反演模型精度较低等问题,本文以Sentinel-2号遥感影像为数据源,利用像元二分模型进行影像光谱解混,筛选出相关性较高的特征光谱作为光谱参量,构建基于像元线性解混和不同光谱变换下土壤反射率与重金属Cr含量的PLS模型和GMDH模型。研究结果表明,解混后的光谱与重金属Cr含量间的显著相关波段数增多,相关性增强。基于解混后的土壤光谱与重金属Cr含量构建的GMDH模型,其模型稳定性较好,预测能力更强,精度更好。该方法拓展了传统的利用遥感影像进行反演的思路,可为大范围监测土壤重金属的污染状况提供有益参考。
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| 关 键 词： | 光谱解混 影像土壤反射率 PLS模型 GMDH模型 重金属Cr |
| 收稿时间： | 2020-07-28 |
| 修稿时间： | 2020-09-28 |
GMDH model inversion of Cr content in cultivated soil under spectral unmixing |
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| GUO Yunkai,ZHANG Qiong,ZHANG Siai,XIE Xiaofeng.GMDH model inversion of Cr content in cultivated soil under spectral unmixing[J].Bulletin of Surveying and Mapping,2021,0(5):73-76. |
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| Authors: | GUO Yunkai ZHANG Qiong ZHANG Siai XIE Xiaofeng |
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| Institution: | 1. School of Architectural Engineering, Guangzhou City Construction College, Guangzhou 510925, China;2. Institute of Surveying and Mapping Remote Sensing Applied Technology, Changsha University of Science and Technology, Changsha 410076, China |
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| Abstract: | Aiming at the problems of weak spectral response between remote sensing image reflectivity and heavy metal elements, and low accuracy of soil heavy metal classical inversion models.In this study, Sentinel-2 remote sensing image is used as the data source, and the dimidiate pixel model is used for image spectral unmixing. The characteristic spectra with high correlation are selected as spectral parameters. PLS model and GMDH model of soil reflectance and heavy metal Cr content under different spectral transformations and pixel linear unmixing are constructed.The results show that there is a significant correlation between the spectra and the content of Cr, and the number of bands is increased and the correlation is enhanced.The GMDH model constructed based on the unmixed soil spectrum and the heavy metal Cr content has better model stability, stronger predictive ability and better accuracy.This research method expands the traditional method of remote sensing image inversion, and can provide a useful reference for monitoring soil heavy metal pollution in a large scale. |
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| Keywords: | spectral unmixing image soil reflectance PLS model GMDH model heavy metal Cr |
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