User Manual - pancroma

The idea is to adjust the included pixels to entirely cover ground features that areknown by ground truthing or other means. When the match is close, it is likelythat all other instances of that feature in the image will be closely identified. Inthe case of the snow pack example, the snow is easily identified visually. Byadjusting the Distance Fraction TM , an accurate snow pack coveragemeasurement can be taken.Spectral Angle AnalysisSAAis an alternative method for matching image pixel reflectances with target spectra.As in Euclidean Distance analysis, SAA also considers each image reflectance valueand the target spectrum as an n-dimensional vector, where n is the number ofmultispectral bands. The algorithm determines the spectral similarity between eachimage reflectance vector and the target vector by calculating the angle between eachimage reflectance and the target. As in Euclidean Distance comparisons, target spectraused by SAA can come from ASCII files or spectral libraries, or you can extract themdirectly from an image using the Point Spectrum Generator TM .Spectral Angle comparisons can often be more discriminating and can yield moreaccurate matches than corresponding Euclidean Distance analyses. This is because,when used with calibrated reflectance data, Spectral Angle comparisons are relativelyinsensitive to illumination and albedo effects that can confound Euclidean Distanceanalyses.In order to use the method for Landsat 7 data, open six or seven Landsat multispectralband files. Then select ‘Spectral Analysis’ | ‘Landsat Spectral Analyzer’ | ‘Six/Seven 8-Bit DN Bands’ | ‘Spectral Angle’. (Or alternatively, if you are using Landsat 7 reflectancedata choose the corresponding ‘Six/Seven 16-Bit Reflectance Bands’ submenuselection.258