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The ability to quickly and non-destructively monitor the cadmium (Cd) content in agricultural crops is the basic premise of effective prevention and control of Cd contamination in agricultural products. Hyperspectral technology provides a solution for this issue. The potential capability for the spectral prediction of the Cd content in the leaves of pepper and eggplant in the field was explored, and a spectral prediction model of the Cd content in these leaves was established. In this study, based on the indoor spectrum, the sensitive wavebands for predicting the Cd content in leaves were determined preliminarily by correlation analysis. Partial least squares regression (PLSR) and support vector machine regression (SVMR) were used to establish spectral prediction models, and the final sensitive wavebands were determined by the size of the model index. The results show that the SVMR model exhibited higher prediction accuracy than the PLSR model. The RPDp (relative percent different of prediction set) values of the best SVMR prediction models for the pepper leaves and the eggplant leaves were 1.82 and 1.49, respectively. The values of Rp2 (coefficient of determination of prediction set), which can quantitatively estimate the Cd content in leaves, were 0.897 (p < 0.01) and 0.726 (p < 0.01), respectively. This study demonstrated that the leaf spectra of pepper and eggplant in the field can be used to predict the Cd content in leaves, providing a reference for monitoring the Cd content in the fruits of pepper and eggplant in the future.

How to explicitly understanding the soil erosion intensity change in different geomorphological types is one of key issues in the field of soil and water conservation. According to classification criterion of soil erosion intensity of China, the spatial soil erosion data with the resolution of 10 m×10m in Guizhou Province were obtained by combing with the multi-resolution remote sensing data of ALOS, ZY-3, GF-1, Landsat and GDEMV2, and 2762 field sampling data in 2010 and 2015, respectively. a spatial analysis model of soil erosion was improved to analyze the spatiotemporal change of soil erosion intensity in karst and non karst area of Guizhou province, which involved the spatial soil erosion data and different geomorphological type data of Guizhou province. The results show that the soil erosion intensity decreased by 6468.13km 2 in Guizhou Province from 2010 to 2015. The dynamic change intensity in the high-altitude area is larger than in the low-altitude area. The soil change intensity in karst area is higher than in non karst area, especially in the high and middle elevation area in Guizhou province. Moreover, the decreasing ratio of soil erosion intensity in karst area is generally larger than in non karst area, which can be used to explain that the ecological restoration projects and water soil conservation polices carried out in karst area has a good effect, especially in western of Guizhou province from 2010 to 2015, one the other hand, the soil erosion in non karst area should also be focused by local government in the future.

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