Comparison of a hyperspectral classification method implemented in two remote sensing software packages

Abstract

This paper presents a study that aims at applying, comparing and characterizing a proven method for hyperspectral land use classification that is currently integrated in two different remote sensing software packages. Recently a great deal of advances in the Geomatica Hyperspectral Analysis Package (HAP) has been made. The Spectral Angle Mapper (SAM) algorithm was used in both Geomatica and ENVI for this study and a hyperspectral dataset from the European sensor CHRIS onboard the platform PROBA-1 served as a test case. The study showed that, despite of many differences in the workflow of the two software packages, the two land use classification results of SAM turned out to be identical