Abdelrahman Medhat Saleh, M. Abd-Elwahed, Y. Metwally, S. Arafat
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引用次数: 0
摘要
当前研究的目的是研究从高光谱数据中估计土壤盐度的机会，并确定用于估计的最有信息的光谱区。从埃及toshka收集的90个表层土壤样品(0-30 cm)的电导率(EC)测量结果作为数据集。采用分析光谱装置采集土壤样品的反射光谱特征。线性回归和HSD Tukey的分析均表明，SWIR1和SWIR2区最适合预测土壤盐分，而蓝色、绿色和近红外区最不适合预测土壤盐分。土壤含盐量较低(0 ~ 2 dS m -1)时，EC的估算效果优于土壤含盐量较高(8本文章由计算机程序翻译，如有差异，请以英文原文为准。
CAPABILITIES OF HYPERSPECTRAL REMOTE SENSING DATA TO DETECT SOIL SALINITY
: The objectives of the current study were to investigate the oppor-tunity of estimating soil salinity from hyperspectral data and identifying the most informative spectral zones for estimation. Electrical conductivity (EC) measurements of ninety topsoil samples (0–30 cm) collected fromToshka, Egypt, were used as data set. Analytical spectral device was employed to collect the reflectance spectral signatures of soil samples. Both linear regression and HSD Tukey’s analyses displayed that the SWIR1 and SWIR2 zones are the most suitable for soil salinity prediction while, blue, green and NIR were the wickedest. Moreover, EC estimation was better in case of lower soil salinity (0-2 dS m -1 ) than higher levels (8
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