Band selection procedure for multispectral scanners
John C. Price
Abstract
John C. Price
Abstract
Advances in high spectral resolution sensors and in data handling capabilities are enabling development of greatly improved remote-sensing devices for resource monitoring, so that design trade-offs are required. A methodology for optimizing selection of spectral bands for multispectral instruments such as those on the LANDSAT series of satellites is described. The method is applied to a collection of laboratory and outdoor spectra of natural and artificial materials. These reflectance spectra represent the visible and near-infrared spectral ranges at high (0.01-μm) spectral resolution. For most natural materials 15-25 spectral bands appear to be sufficient to describe spectral variability, whereas description of minerals and some artificial substances may require double this number of bands.
OpenAlex reports 49 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Advances in high spectral resolution sensors and in data handling capabilities are enabling development of greatly improved remote-sensing devices for resource monitoring, so that design trade-offs are required. A methodology for optimizing selection of spectral bands for multispectral instruments such as those on the LANDSAT series of satellites is described. The method is applied to a collection of laboratory and outdoor spectra of natural and artificial materials. These reflectance spectra represent the visible and near-infrared spectral ranges at high (0.01-μm) spectral resolution. For most natural materials 15-25 spectral bands appear to be sufficient to describe spectral variability, whereas description of minerals and some artificial substances may require double this number of bands.
Key concepts: Multispectral image, Remote sensing, Spectral bands, Spectral resolution, Hyperspectral imaging, Spectral imaging, Optics, Multispectral pattern recognition