The sciences, technologies, and practices of remote sensing and of geographic information systems (GIS), arose separately, developed in parallel, intersected, and are now inextricably linked. Nearly all the features in most GIS are collected by means of satellite imagery or aerial photogrammetry, and GIS is the application where this imagery is most commonly visualized. \u201cAll the foundation elements of GIS come from remote sensing: cultural features, roads, buildings, water features, topography, terrain, soils, slopes, geology, and many more,\u201d points out Lawrie Jordan, Director of Imagery at Esri.<\/p>\n
It was not always this way. In the 1970s, 1980s, and early 1990s, remote sensing and image processing, on the one hand, and GIS, on the other, were separate worlds \u2014 each with its own culture and software. The former stored data in a raster format and used multispectral classification, the latter stored data in a vector format and used topology. Software vendors specialized in one or the other \u2014 even though their customers were acquiring and using both types of data. Until recently, in a GIS context, imagery was thought of only as a background or a base map to the information that was being analyzed.<\/p>\n
Over the last decade, however, remote sensing and GIS have become increasingly integrated. \u201cNow people are seeing imagery as a source of a lot of GIS information,\u201d says Jennifer Stefanacci, Director of Product Management at Exelis. \u201cSo, the analysis workflows that our users are doing incorporate both analysis of the imagery and analysis of their GIS data.\u201d While GIS gives you the information about where, through information extraction routines remote sensing gives you the information about what, explains Mladen Stojic, V.P. of Geospatial at Intergraph, \u201cBy merging the two, we now have the opportunity to do modeling with raster data, vector data, and, on top of that, terrain data.\u201d<\/p>\n