Integration of remote sensing data with geographic information system (gis): Applications and Change Detection Techniques

Remote Sensing and Geographic information System together comprise of Geographic Information Science (GIScience) which is a core research field that tries to emphasis on advanced geographic concepts in Geographic Information System and examines the impact of GIS on individuals and society as a whole and re-examines the themes with incorporation of most recent cognitive and Information Science. The Geographic Information System can be defined as a Computer based system and a tool, both hardware, software and procedures, which manages geospatial data, solves spatial problems, and supports collection, storage, transformation, analyzing, retrieving and display of data in a well desired manner. The integration of GIS and Remote Sensing is a field of research and several implementations have been developed to gain the maximum throughput out of these collective fields as these techniques have their own data analysis and data representation methods. The application domain of remote sensing is from a base layer for GIS to the development of thematic datasets, obtaining and extracting data from imagery and generation of unique spatial datasets. In my paper I have focused on the integration of both the fields along with its usage in Analysis and Modelling and also some models of error sources due to the integration of interface of the two techniques. The paper also describes some error sources while integration as GIS and remote sensing both are subject to errors and uncertainty. The paper has discussed some Change Detection Techniques used in the modern sciences with their comparison. In GIS all the images positioned should be accurate and correctly positioned. All the data layers should be described correctly, must be registered to one another and must be Georeferenced to a specific map projection and coordinate system. Base maps are the frame of reference for positioning and mapping. Remote sensing is the source of thematic data especially data on land use, land cover characteristics and surface elevation. So deriving thematic geospatial data through remote sensing is a big task. The images taken from remote sensing has spatial displacements of objects and variations. Such displacements should be removed in order to create orthorectified image. So for this purpose the data required should be imported from GIS only. Hence they have to be integrated with each other. So for further analysis the output data is fed back into the GIS system and used for other purposes