Grid Based Raster Selection and Vector Extraction

Abstract

The increased volume of raster imagery necessitates the development of methods to efficiently retrieve data associated with it. The use of digital imagery is ever increasing for GIS applications due to enabling technology to integrate digital imagery with other land related digital data. Integration of imagery with vector data is now a necessity for a full-featured GIS system. Imagery was once thought to be the exclusive domain of image processing systems, but is now often required as a backdrop for vector, or other data types. This research addresses the limited capability of current GIS (Geographical Information System) applications while working with Raster images. It proposes a method of giving the user more control over raster images and be able to retrieve data associated with it. The current GIS tools provide various ways to select vector data interactively by the user. However selecting raster data from the GIS application is still the area to be explored by researchers. In this thesis we propose an effective grid based approach to select Area of Interest (AoI) on the raster image and extract vector data out of it. The new contribution of this work combines the design of a customized GIS application that lets the user to select raster image cells and able to retrieve vector data that falls into the geography of selected cells. The proposed method of selecting raster data cells and able to retrieve vector data for the selected cells has been successfully implemented and tested. ArcObjects is the development platform used for this research work in conjunction with ArcGIS family of application such as ArcMap. A customized ArcMap application is created that provides a grid based approach to select AoI on the raster image and extract vector data for it.