Using Worldview-2 Vis-NIR Multispectral Imagery to Support Land Mapping and Feature Extraction Using Normalized Difference Index Ratios

Multispectral imagery (MSI) provides information to support decision making across a growing number of private and industrial applications. Among them, land mapping, terrain classification and feature extraction rank highly in the interest of those who analyze the data to produce information, reports, and intelligence products. The 8 nominal band centers of WorldView-2 allow us to use non-traditional means of measuring the differences which exist in the features, artifacts, and surface materials in the data, and we can determine the most effective method for processing this information by exploiting the unique response values within those wavelength channels. The difference in responses across select bands can be sought using normalized difference index ratios to measure moisture content, indicate vegetation health, and distinguish natural features from man-made objects. The focus of this effort is to develop an approach to measure, identify and threshold these differences in order to establish an effective land mapping and feature extraction process germane to WorldView-2 imagery.