Search

This article examined the spectral interference by heavy metal on the spectral signal of moisture content of heavy metal contaminated soils. Soil samples were collected from an abandoned mine area, and the chemical analysis revealed extremely high contamination amount of copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd), and lead (Pb). The mineralogical analysis showed that the spectral signature of the heavy metal contaminated soils was manifested by secondary minerals. Water content suppressed the spectral reflectance of the soil samples but increased the absorption depths. Although a regression model can predict moisture content using the magnitude of the water absorption feature, the accuracy was much lower when the heavy metal concentration was extremely high. It indicates that geochemical reactions between the heavy metal cation and iron oxide/clay minerals may have affected the spectral responses of the contaminated soils at the water absorption bands. Our model also showed that there was a shift of the absorption features of moisture content if the heavy metal contamination level went up. Unlike normal soils, the absorption features of clay minerals and ferric iron were not able to accurately predict moisture in highly contaminated soils. Given the fact that the spectral bands selected in this article were associated with water absorption, the findings from this article may only be useful to a drone-based low-altitude remote sensing of soil moisture content. [ABSTRACT FROM AUTHOR]

This paper investigated the spectral characteristics of heavy metal contaminated soils of a hydrothermal ore deposit developed in carbonate host rock associated with heavy metal concentration and mineral composition. The results showed that spectral response of heavy metal contaminated soils was statistically correlated with zinc, cadmium, and lead concentrations. Empirical equations for predicting zinc, cadmium, and lead concentrations were derived. Spectral characteristics of the soils were expressed by smectite, chlorite, tremolite, and talc which resulted from hydrothermal alteration and weathering products of the parent rocks. The stepwise multiple linear regression (SMLR) model of zinc, cadmium, and lead was statistically satisfactory with $R^{2}$ greater than 0.7. The SMLR results indicated that the spectral response to cadmium and zinc concentration was sensitive to reflectance at 1850 nm and first derivative at ~950 and 2154 nm corresponding to the smectite absorption features. On the other hand, lead concentration is closely related to first derivatives at 1453, 2316, and 2337 nm, which are absorption features of chlorite, tremolite, and talc. These results revealed that the spectral bands sensitive to the heavy metal concentration varied with the geochemical absorption mechanism between specific minerals and heavy metal elements. Therefore, the geological setting of the soils is one of the major controlling factors associated with spectral response to heavy metal contamination. Given the fact that a hydrothermal ore deposit is one of the most widely distributed types, the laboratory result of this paper may be applied to the real-world cases with similar geological environments. [ABSTRACT FROM AUTHOR]

We study the power allocation problem for maximizing the sum rate in orthogonal frequency-division multiplexing systems, where multiple point-to-point links share a set of subcarriers. This problem is hard to solve, in general, due to its nonconvexity. In this letter, we characterize the conditions for the problem to be convex, in which case the problem can be solved efficiently using known algorithms such as gradient projection method. We validate our analysis through simulations. [ABSTRACT FROM PUBLISHER]