2 results about "Band ratio" patented technology

This invention provides a method, apparatus, and device for identifying water bodies on a single orbit of a polar-orbiting meteorological satellite, comprising: acquiring first-band data, first-positioning information data, and second-band data, second-positioning information data, and product data at a first spatial resolution from a polar-orbiting meteorological satellite; sampling the data at the second spatial resolution to obtain second-band data, second-positioning information data, and product data at the first spatial resolution; acquiring high-quality binary classification data; training a decision tree model based on the first-band data, second-band data, normalized index data, band difference data, and band ratio data at the first spatial resolution corresponding to high-quality water body pixels and high-quality non-water body pixels within the target area, to obtain a target decision tree model; and obtaining the single-orbit water body identification area based on the target decision tree model. The solution of this invention accurately identifies water bodies in complex background conditions, improving monitoring accuracy and applicability.

This application relates to the field of metal mining technology and proposes a method, apparatus, equipment, and medium for estimating the heavy metal content in soil. The method includes: collecting soil samples from a target area and determining the content of multiple heavy metal elements; acquiring visible-near-infrared hyperspectral reflectance data and X-ray fluorescence spectral data of the soil samples; calculating the competition coefficients between heavy metal elements using the L-V competition model to determine the set of competing elements for the target heavy metal element; constructing a multi-objective optimization function based on the band importance of random forests, with the goal of maximizing the spectral response differences of the target heavy metal element and minimizing the spectral response differences of its competing elements; combining wavelength spacing constraints; using the NSGA-II algorithm to select the optimal set of band ratio features; training a machine learning regression model; and estimating the heavy metal content in the soil of the target area. This scheme significantly improves the inversion accuracy and stability of the model.