Effect of the Continuum Removal in Predicting Soil Organic Carbon with Near Infrared Spectroscopy (NIRS) in the Senegal Sahelian Soils

Spectroscopy plays a major role in the access of the analytical parameters of the soil. It tends to substitute the conventional laboratory analysis because hyperspectral data were least expensive and easier to obtain. The objective of this study was to evaluate the effect of the continuum removal (CR) in the validation of the accurate prediction model of the soil properties with Vis-NIR spectroscopy data. Few studies using Vis-NIR reflectance spectroscopy have well focused the calculation of the CR method;its effect in the calibration of the accurate models was also not well emphasized. In this study, we used the remote sensing software ENVI 4.7 to compute the CR function where the value of the continuum for each sample and for each spectral wavelength was obtained by dividing the reflectance values of the full spectrum (FS) with those of the continuum curve (CC). The partial least square regression (PLSR) model was applied in the spectral data from the soil of the Senegal Sahelian region. It was calibrated with both data from the full spectrum (FS) and those obtained after the application of the continuum removal. With the application of the CR, ultraviolet wavelengths (350 - 429 nm) and those of near infrared (2491 - 2500 nm) were removed from the explanatory variables of PLSR model. With the FS, all wavelengths between 350 and 2500 nm were taken into account in predicting soil properties. Our findings show a positive effect of the application of CR in the estimation of soil organic carbon. In calibration, the R2 increased up to 10% with the continuum removal in the model of 12 components (CP). In terms of validation, it’s the 15-component model which is the most accurate with the same range in calibration between the FS and the CR. The lowest RMSE ranged from 0.04 with the FS to 0.03 with the application of the CR in calibration and validation. These results show that the interest of this study as soil organic carbon is recognized as a key indicator of fertility of the soil in Sahelian-African regions. For future studies, it’s important to apply the model of neural networks to better evaluate the effect of continuum removal in predicting soil properties from the spectral data and other methods of preprocessing like the multiplicative scatter correction (msc).

Analysis on Reflectance Spectral Characteristics of Typical Saline Soil in Arid Area

The spectral characteristic of geography objects is not only the important content of remote sensing mechanism, but also the important basis for remote sensing application. The reflectance spectral characteristics reflect the physiochemi-cal properties of saline soil. With 3 kinds of typical saline soils in the arid area as the study objects, the reflectance spectrums of soils with different salt contents and soil moistures were measured, and the spectral characteristics of the spectrums were analyzed. The results showed that under dry condition, the reflectance of the three kinds of saline soils presented obvious high-low patterns, while under damp condition, there was no obvious pattern. With continuum removed ,the three kinds of saline soils showed significant difference in reflectance spectral characteristics. There was significant difference in the absorption depth of the two absorption val eys un-der dry and damp conditions, which could be used to identify these 3 saline soils. The result of this research can be used for the parametric inversion and classifica-tion of saline soil retrieval and classification, as wel as for the remote sensing monitoring on saline soil.

Detection of Acid Rain Stress Effect on Plant Using Hyperspectral Data in Three Gorges Region,China

This paper aims to use hyperspectral data to detect the spectral change caused by acid stress to a native forest type in the Three Gorges region of China. For this purpose, a ground-based hyperspectral experiment was conducted at the Three Gorges region to detect acid deposition that caused Masson pine (Pinus massoniana) forest degra-dation. Continuum removal method was used to isolate wavebands more responsive to stress in wavelengths 450-750nm. The differences in chlorophyll concentrations and needle thickness caused by acidic stress are found to be explicable to the different spectral reflectance patterns in the visible and near-infrared wavelengths. Two new chlorotic indices were utilized to explain the stress-caused leaf chlorosis. The comparison of simulated vegetation indices and principal component analysis (PCA) results suggests that it would be possible to monitor acid rain stress effect on forest ecosystem from some wider spectral regions.

Characterization of the Rice Canopy Infested with Brown Spot Disease Using Field Hyperspectral Data

Based on the field hyperspectral data from the analytical spectral devices （ASD） spectrometer, we characterized the spectral properties of rice canopies infested with brown spot disease and selected spectral regions and bands sensitive to four severity degrees （severe, moderate, light, and healthy）. The results show that the curves＇ variation on the original and the first- and second-order de- rivative curves are greatly different, but the spectral difference in the near-infrared region is the most obvious for each level. Specifically, the peaks are located at 822, 738, and 793 nm, while the valleys are located at 402, 570, and 753 run, respectively. The sensitive regions are between 430-520, 530-550, and 650-710 nm, and the bands are 498, 539, and 673 nm in the sensitivity analysis, while they are in the ranges of 401-530, 550-730 as well as at 498 nm and 678 nm in the continuum removal.