Multi-scale GIS based Satellite Image Mapping

Remotely sensed imagery has an enhanced capability of extracting information about small image structures (both artificial and natural objects). Fast, low cost, accurate and spatially rich data can be acquired via remote sensing technology. For this reason, satellite image mapping is quite common technique and image maps provide a great contribution to cartography and Geographic Information Systems as data sources. However, there are several remote sensing satellites with various kinds of spectral and spatial resolution and they detect different regions of electromagnetic spectrum. One needs to know which satellite image is suitable for which kind of mapping. On the other hand, image mapping which is based on resolution is a procedure including information extraction from pixels. While pixel algorithms and processing methods are suitable for medium and low resolution images, pattern recognition is suitable for high resolution images. Thus, there is a need to evaluate maps according to scale and satellites according to resolution level and see if they are matching or not. This paper aims to examine the possibilities of map production by using remote sensing imagery, to set out representation criteria for map features and to discuss the results by means of efficiency, accuracy, consistency and usability. In this context, first of all, the map concept was examined in terms of scale and content of the map. A requirement matrix was produced in order to execute the requirement analysis on the content of each map type based on the scale. Secondly, remote sensing images, having different spatial and spectral characteristics, were examined in a similar approach and a requirement matrix was formed for determining the data extraction level of remote sensing imagery based on spatial and spectral characteristics. Finally, these two matrices were evaluated in order to assess the use of the remote sensing images in terms of mapping.