Abstract
Visible and near-infrared (VNIR) spectroscopy technology for soil heavy metal (HM) concentration prediction has been widely studied. However, its spectral response characteristics are still uncertain. In this study, a near standard soil Cd samples (NSSCd) spectra enhanced modeling strategy was developed in order to to reveal the soil cadmium (Cd) spectral response characteristics and predict its concentration. NSSCd were produced by adding the quantitative Cd solution into background soil. Then, prior spectral bands (i.e., the bands with higher variable importance in projection (VIP) score in NSSCd spectra) were used for predicting Cd concentration in soil samples collected from the Hengyang mining area and Baoding agriculture area. The partial least squares (PLS) and competitive adaptive reweighted sampling-partial least squares (CARS-PLS) were used for validation. Compared to using entire VNIR spectral ranges, the new modeling strategy performed very well, with the coefficient of determination (R2) and the ratio of prediction to deviation (RPD) showing an improvement from 0.63 and 1.72 to 0.71 and 1.95 in Hengyang and from 0.54 and 1.57 to 0.76 and 2.19 in Baoding. These results suggest that NSS prior spectral bands are critical for soil HM prediction. Our results represent an exciting finding for the future design of remote sensing sensors for soil HM detection.
Highlights
Soil is a fundamental medium for material and energy circulation in terrestrial ecological systems
Soil HM contamination has gradually emerged as a serious problem all over the world [4,5,6], especially in China where in 2014 it was reported that about 19.4% of farmlands were polluted by heavy metals [7,8]
near standard soil Cd samples (NSSCd) prior spectral bands are extracted by the variable importance in projection (VIP) method, and these spectral ranges are used to predict Cd concentration in naturally contaminated soil samples (NCS) collected from the two case areas with both the competitive adaptive reweighted sampling (CARS)-partial least squares (PLS) and PLS model
Summary
Soil is a fundamental medium for material and energy circulation in terrestrial ecological systems. With rapid urbanization and industrialization, soils have been contaminated by heavy metal (HM) due to various smelting, mining, dust settlement, agricultural, and industrial producing activities [1,2,3]. Soil HM causes soil health degradation and imposes significant harm on organisms by accumulating in the food chain. Soil HM contamination has gradually emerged as a serious problem all over the world [4,5,6], especially in China where in 2014 it was reported that about 19.4% of farmlands were polluted by heavy metals [7,8]
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