Remote Sensing is unique in that it can be used to collect data, unlike other techniques, such as thematic cartography, geographic information systems, or statistics that must rely on data that are already available. Remote sensing data derived may then be transformed into information using analog or digital image processing techniques if appropriate logic and methods are used.
Remote sensing derived information is critical to the successful modeling and monitoring of numerous natural (e.g., watershed run off) and cultural processes (e.g., land use conversion at the urban fringe). In fact, for successful execution of many models- that rely on spatially distributed information- remote sensing is must.
The principal advantages of remote sensing are the speed at which data can be acquired from large areas of the earth’s surface, and the related fact that comparatively inaccessible areas may be investigated in this way.
The major advantages of this technique over ground-based methods are summmarized as follows:
Remote sensing process facilitates the study of various earths’ surface features in their spatial relation to each other and helps to delineate the required features and phenomena.
The remote sensing satellites provide repetitive coverage of the earth and this temporal information is very useful for studying landscape dynamics, phenological variations of vegetation and change detection analysis.
Remote sensing process made it possible to gather information about the area when it is not possible to do ground survey like in mountainous areas and foreign areas.
Since information about a large area can be gathered quickly, the techniques save time and efforts of human. It also saves the time of fieldwork.
Remote sensing especially when conducted from space, is an intrinsically expensive activity. Nevertheless, cost-benefit analysis demonstrates its financial effectiveness, and much speculation or developmental remote sensing activity can be justified in this way. It is a cost-effective technique as again and again fieldwork is not required and also a large number of users can share and use the same data.