Abstract
Quantifying and mapping heavy metals’ concentrations in the soil are important in monitoring and managing heavy metal pollution in the mining areas. However, the cover on the soil acts as a balk when retrieving information from soil. In order to retrieve heavy metal pollution precisely and quickly from hyperspectral images, this study presents a new method to remove non-soil information based NDVI from hyper-spectral and multi-spectral images. The method assumed that the mixed objects in each pixel of remote sensing images are composed only of soil and vegetation-based non-soil end-generational endmembers, then, the soil information of each pixel can be compensated with the non-soil information removed based on its NDVI. Thus, the soil DN value can be corrected to retrieve soil information more precisely. The method has been used on the Hyperion image in June 8, 2002 and the Gaofen-2 (GF-2) image in February 14, 2016 to retrieve the heavy metals’ contents in Bai-ma and De-sheng mining areas, Miyi County, Sichuan Province. From the non-soil information removed images, the R2 and RMSE of the models of estimating Cr, Ag, Cu and Ba in soil are 0.68, 0.724, 0.71, 0.695 and 75.96, 0.03, 52.88, 284.70 respectively. From the original images, the R2 and RMSE of the models of estimating Cr, Ag, Cu and Ba in soil are 0.67, 0.385, 0.425, 0.406 and 80.11, 0.18, 53.43, 396.49 respectively. The retrieval results show that the non-soil information removed images are superior to original images in soil heavy metals’ contents retrieval. This indicates that this method is feasible, and it can be used in soil information retrieval.
Highlights
In order to retrieve heavy metal pollution precisely and quickly from hyperspectral images, this study presents a new method to remove non-soil information based NDVI from hyper-spectral and multi-spectral images
The method assumed that the mixed objects in each pixel of remote sensing images are composed only of soil and vegetation-based non-soil end-generational endmembers, the soil information of each pixel can be compensated with the non-soil information removed based on its NDVI
This paper presented a fast and convenient method based on NDVI to remove the vegetation-based non-soil information from the soil surface of the Hyperion and GF-2 images in the mining area
Summary
The traditional method of estimating the heavy metals by collecting sampling points and analyzing in the laboratory is time-consuming and expensive. New methods are needed for monitoring and managing heavy metal pollution in the mining areas. With the improvement in remote sensing technology, the new method of establishing inversion models with the heavy metals’ concentrations and the feature spectra from hyperspectral and high spatial resolution images are popular to monitor heavy metal in soil [4] [5] [6] [7]. Many studies have shown that the Visible and Near-infrared spectra of soil obtained from remote sensing images were effectively used for retrieving real-time heavy metals’ concentrations in large mining areas [3] [8] [9]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Data Analysis and Information Processing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
