多源遥感对宁夏干湿季土壤含盐量敏感性分析与定量反演

doi:10.13292/j.1000-4890.202309.006

生态学杂志 ›› 2023, Vol. 42 ›› Issue (9): 2286-2295.doi: 10.13292/j.1000-4890.202309.006

多源遥感对宁夏干湿季土壤含盐量敏感性分析与定量反演

王怡婧¹,贾萍萍²,陈睿华¹,张俊华^3,4,5*

（¹宁夏大学地理科学与规划学院，银川 750021； ²南京信息工程大学地理科学学院，南京 210044； ³宁夏大学生态环境学院，银川 750021； ⁴西北退化生态系统恢复与重建教育部重点实验室，银川 750021； ⁵西北土地退化与生态恢复国家重点实验室培育基地，银川 750021）

出版日期:2023-09-10 发布日期:2023-09-05

Sensitivity analysis and quantitative inversion of multi-source remote sensing to soil salt content in dry and wet seasons in Ningxia.

WANG Yijing¹, JIA Pingping², CHEN Ruihua¹, ZHANG Junhua^3,4,5*

(¹College of Geographical Sciences and Planning, Ningxia University, Yinchuan 750021, China; ²College of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China; ³College of Ecology and Environmental Science, Ningxia University, Yinchuan 750021, China; ⁴Key Laboratory for Restoration and Reconstruction of Degraded Ecosystem in Northwestern China of Ministry of Education, Ningxia University, Yinchuan 750021, China; ⁵Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwestern China, Ningxia University, Yinchuan 750021, China).

Online:2023-09-10 Published:2023-09-05

摘要/Abstract

摘要： 快速准确反演干旱地区土壤盐渍化程度是有效防止盐渍化扩张的前提。为探讨地面高光谱和Landsat 8 OLI影像数据针对干湿季土壤含盐量敏感性分析与定量反演的问题，本研究以宁夏银北平罗县干季（4月）和湿季（10月）表层土壤（0～20 cm）含盐量、地面高光谱和Landsat 8 OLI影像为数据源，利用线性和非线性函数检验2种光谱数据及其对应盐分指数对研究区土壤含盐量的敏感性。采用偏最小二乘回归（PLSR）、支持向量机（SVM）和反向传播神经网络模型（BPNN）构建地面高光谱和Landsat 8 OLI影像的盐分估算模型。结果表明：干、湿季土壤含盐量平均值分别为6.17和4.28 g·kg^-1，土壤盐渍化较为严重；不同季节地面高光谱和影像光谱对土壤含盐量敏感的波段和盐分指数不同，地面高光谱经重采样波段和盐分指数与土壤含盐量敏感性均表现为极显著；干、湿季土壤含盐量的BPNN估算模型稳定性和预测能力均优于PLSR和SVM模型；干、湿季均以高光谱-BPNN模型效果最佳，其决定系数R²分别为0.739和0.819，RPD分别为1.49和1.95；经重采样地面高光谱模型校正后的干季影像模型精度R²从0.685提升到0.844；湿季影像模型精度R²从0.654提升到0.788，有效提高了较大尺度下的土壤含盐量估算精度。本研究实现了遥感监测土壤含盐量由点向面的空间转换，为宁夏银北地区土壤盐渍化的识别和防治提供了科学参考。

关键词: 盐渍化, 盐分指数, 地面高光谱, Landsat 8 OLI影像, 模型

Abstract: Rapid and accurate inversion of soil salinity in arid areas is the premise to effectively prevent the expansion of salinization. To address sensitivity analysis and quantitative inversion of soil salt content in dry and wet seasons by means of ground hyperspectra and Landsat 8 OLI images, we obtained data of topsoil (0-20 cm) salt content, ground hyperspectra and Landsat 8 OLI image in the dry season (April) and wet season (October) in Pingluo County, Ningxia. Linear and nonlinear functions were used to test the sensitivity of the spectral data and corresponding salinity index. We established the models to estimate soil salt content based on ground hyperspectral and image data using partial least squares regression (PLSR), support vector machine (SVM), and back propagation neural network model (BPNN). The average soil salt content in dry and wet seasons was 6.17 and 4.28 g·kg-1, respectively, indicating serious soil salinization. The sensitive bands and salinity index of ground hyperspectra and image spectra to soil salinity differed among seasons. The resampling band and salinity index of ground hyperspectra showed extremely high sensitivity to soil salinity. The stability and prediction ability of BPNN estimation model of soil salt content were better than those of PLSR and SVM. Hyperspectral-BPNN in dry and wet seasons was the best estimation model, with the prediction accuracy of 0.739 and 0.819, and the relative analytical errors of 1.49 and 1.95, respectively. After calibrated by the resampled measured spectrum model, the estimation accuracy of the image spectra based model increased from 0.685 to 0.844 in the dry season and from 0.654 to 0.788 in the wet season, which effectively enhanced the accuracy in estimating soil salt content at large scale. We successfully made the spatial transformation of soil salt content from small to large scale. The results provided a scientific reference for identification and prevention of soil salinization in Yinbei of Ningxia.

Key words: salinization, salinity index, ground hyperspectrum, Landsat 8 OLI image, model.

王怡婧, 贾萍萍, 陈睿华, 张俊华. 多源遥感对宁夏干湿季土壤含盐量敏感性分析与定量反演[J]. 生态学杂志, 2023, 42(9): 2286-2295.

WANG Yijing, JIA Pingping, CHEN Ruihua, ZHANG Junhua. Sensitivity analysis and quantitative inversion of multi-source remote sensing to soil salt content in dry and wet seasons in Ningxia.[J]. Chinese Journal of Ecology, 2023, 42(9): 2286-2295.

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多源遥感对宁夏干湿季土壤含盐量敏感性分析与定量反演

Sensitivity analysis and quantitative inversion of multi-source remote sensing to soil salt content in dry and wet seasons in Ningxia.

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