Field Strength Distribution-Based Sample Selection Method

In the process of spectral modeling, the representativeness of samples to the overall space determines the modeling efficiency. A commonly used unsupervised sample selection method is based on the maximum–minimum distance of selected samples. However, this approach selects samples based solely on a single distance metric, which introduces a degree of randomness. Inspired by the spatial field strength distribution law of multiple point charges, we propose a novel sample selection method based on field strength. In this method, each sample point is treated as a point charge that generates an electric field in its vicinity. The field strength at any given position is the sum of the contributions from all point charges at that location, with a higher field strength indicating that the point is already well represented. By calculating the total field strength exerted by each selected sample on the candidate points and incorporating the point with the minimum field strength into the calibration set, the method maximizes the coverage of field strength in the calibration space. Sequentially selecting and adding points with the lowest field strength yields a highly representative sample set. This approach enables efficient and unsupervised selection of modeling samples.