Quantitative Model Based on Field-Derived Spectral Characteristics to Estimate Soil Salinity in Minqin County, China (SCI)

CORC > 寒区旱区环境与工程研究所 > 中科院寒区旱区环境与工程研究所（未分类） > 期刊论文

	Quantitative Model Based on Field-Derived Spectral Characteristics to Estimate Soil Salinity in Minqin County, China (SCI)
	Pang G. J. ; Wang T. ; Liao J. ; Li S.
刊名	Soil Science Society of America Journal
	2014
卷号	78 期号:2 页码:546-555
英文摘要	Soil salinization, which is one of the most important land degradation problems in arid and semiarid regions, has a significant impact on ecological equilibrium. Hyperspectral remote sensing, with a large number of measured wavelength bands and a high resolution, has gradually become a popular technology to investigate soil salinization. In this study, a model based on field-derived spectra was developed for soil salinity and the quantitative relationships between the soil spectrum and vegetation spectrum with the soil salt content (SSC) and soil electrical conductivity (EC). A field study was performed in Minqin County, China. A genetic algorithm (GA), partial least squares regression (PLS), and back-propagation neural network (BPNN) were used for modeling. The results showed that GA has a relatively strong ability for band selection. After the selection, the predictive ability of the GA-PLS model was better than the PLS model based on the full spectra. The BPNN model built by selected bands (GA-BP) was superior to the GA-PLS linear model. The models built using the soil spectrum after band selection have a high predictive ability. The R-2 and ratio of prediction to deviation (RPD) for SSC were 0.68 and 1.76 for GA-PLS and 0.72 and 1.89 for GA-BP, respectively. There were no significant correlational relationships between the normalized difference vegetation index and SSC or EC. The GA-BP model fitted using the vegetation spectrum was superior to a single vegetation index model, whereas the predictive ability of SSC (0.56 for R-2 and 1.47 for RPD) was not high due to influences such as plant species differences and vegetation coverage.
收录类别	SCI
公开日期	2015-12-24
内容类型	期刊论文
源URL	[http://ir.casnw.net/handle/362004/24916]
专题	寒区旱区环境与工程研究所_中科院寒区旱区环境与工程研究所（未分类）_期刊论文
推荐引用方式 GB/T 7714	Pang G. J.,Wang T.,Liao J.,et al. Quantitative Model Based on Field-Derived Spectral Characteristics to Estimate Soil Salinity in Minqin County, China (SCI)[J]. Soil Science Society of America Journal,2014,78(2):546-555.
APA	Pang G. J.,Wang T.,Liao J.,&Li S..(2014).Quantitative Model Based on Field-Derived Spectral Characteristics to Estimate Soil Salinity in Minqin County, China (SCI).Soil Science Society of America Journal,78(2),546-555.
MLA	Pang G. J.,et al."Quantitative Model Based on Field-Derived Spectral Characteristics to Estimate Soil Salinity in Minqin County, China (SCI)".Soil Science Society of America Journal 78.2(2014):546-555.