Spectrum spatial structure characteristic analysis of remote sensing alteration information and interference factors

Abstract

Based on the statistical characteristics of remote sensing data, the spatial geometric structure characteristics of spectral data and distribution of background, interference and alteration information in characteristic space were researched through the analysis of two-dimensional and three-dimensional scatter diagrams. The results indicate that the hyper-space of remote sensing multi-data aggregation belongs to low-dimensional geometric structure, i.e. hyperplane form, and anomalous point groups including alteration information usually dissociate out of hyperplane. Scatter diagrams of remote sensing data band are mainly presented as two distribution forms of single-ellipse and dual-ellipse. Clarifying the relations of three objects of background, disturbance and alteration information in remote sensing images provides an important technical thought and guidance for accurately detecting and extracting remote sensing alteration information.

Integrating Data of ASTER and Landsat-8 OLI (AO) for Hydrothermal Alteration Mineral Mapping in Duolong Porphyry Cu-Au Deposit, Tibetan Plateau, China

“…When a high linear correlation is observed between the two bands, their two-dimensional spectral spaces are generally presented as a single ellipse type. Such a distribution shows that the spectral features of various surface objects are similar and that the spectral curve shape is also similar though only certain differences for spectral value exist [64]. Figure 3b,c are the two-dimensional scatterplots of O3 and A1, as well as O4 and A2.…”