Remote sensing images are recorded in digital forms and then processed by the computers to produce images for interpretation purposes. The remote sensing data products are available to the users in the forms of
· Photographic products such as paper prints, film negatives, diapositives of black and white, and false colour composite (FCC) on a variety of scales, and
· Digital form as computer compatible tape (CCT), CD after necessary correction.
The size of the photographic products can vary depending on the enlargement needed. When we say color photographic products, it generally means false color composites (FCC). FCC are generated by combining the data contained in 3 different spectral bands into one image by assigning blue, green and red colors to the data in three spectral bands respectively during the exposure of a color negative. The choice of band combinations can be determined depending upon the application.
Visual image interpretation is a process of identifying what we see on the images FCC and communicate the information obtained from these images to others for evaluating and performing image interpretation to extract thematic information for subsequent input to GIS. Visual interpretation techniques have certain disadvantages and may require extensive training and are labor intensive. In this technique, the spectral characteristics are not always fully evaluated because of limited ability of the eye to discern total values and analyze the spectral changes. If the data are in digital mode, the remote sensing data can be analyzed using digital image processing techniques and the resultant database can be used in raster GIS. In applications where spectral patterns are more informative, it is preferable to analyze digital data rather than pictorial data.
In a most generalized way, a digital image is a two-dimensional i.e. matrix of numbers depicting spatial distribution of certain field parameters such as reflectivity of EM radiation, emissivity, temperature or some geophysical or topographical elevation. Digital image consists of discrete picture elements called pixels. Associated with each pixel is a number represented as DN (Digital Number) that depicts the average radiance of relatively small area within a scene. A particular part of scene reflecting more energy will appear bright while a different part of the same scene that reflecting less energy will appear black .The range of DN values is normally 0 to 255. The size of this area effects the reproduction of details within the scene. As the pixel size is reduced more scene detail is preserved in digital representation.
Image Processing can be defined as the "act of classifying images for the
purpose of identifying objects and judging their significance". Remotely
sensed data is of matrix form and is subjected to logical process in detecting,
identifying, classifying, measuring and evaluating the significance of physical
and cultural objects, their patterns and spatial relationships. This classified
data are important input for developing Spatial Decision Support Systems in
agricultural research and development.
2Remote Sensing Applications
The following are some of the Remote Sensing applications by ISRO,
· National land use
/ cover mapping
· Drought Monitoring:
· Flooded area mapping
· Crop acreage and production estimation
· Mapping of Saline/Alkaline Soils of India
· Wasteland mapping
· Biennial monitoring of vegetation / forest cover
· Nationwide Grassland Mapping
· Urban Land use change monitoring
· Mulberry crop inventory / sericulture
· Coastal wetland mapping for inland fisheries
· Ground water potential zone mapping
· Watershed prioritization
· Water management in command areas
· Marine Fisheries