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Stratification is a procedure for subdividing the heterogeneous population into subpopulations which are internally homogeneous. Spectral stratification, i.e. stratification based on spectral characteristics can be used for classification of multispectral remotely sensed data. In this paper an approach is suggested for estimating the areas under different cover types by taking samples from spectral strata. The basis of spectral stratification i s the multidimensional frequency information from the data. The size of a sampling unit is decided by the coefficient of variation within the data and the size of the samples can be obtained either from the allowable error or the level of significance. The samples are allocated on the basis of the proportional geographical area in each stratum. The samples from each stratum are classified using an unsupervised method namely, the Iterative Self Organizing Clustering system and the area under each class is estimated. The procedure is tested with the Indian Space Research Organization-MSS data for two test sites each covering approximately 20 Sq. kms. One test site pertains to a planned agricultural research farm and the other belongs to a normal agricultural area. Areas under different cover types are obtained for both the test sites. These results are compared with the results obtained by a supervised approach on pixel by pixel basis using maximum likelihood quadratic discriminant function. In the majority of the classes the results are in agreement where as there are little discrepancies in few cases.

Bhaskara, the first Indian Earth Observations Satellite was launched on June 7, 1979. The two primary payloads onboard the Bhaskara satellite were two Television cameras (TV Camera) and two frequency Satellite Microwave Radiometers (SAMIR). The salient features of the TV camera and SAMIR payloads are summarised and given in Table 1. Since the Bhaskara TV data is having a low resolution and as the data was acquired in only one band, namely, 0.54-0. 66 µm, the utility of the data from the point of view of information extraction on earth resources is limited. Moreover, because of its orbital characteristics the data is acquired at different times of the day and thus under various illumination conditions. This note discusses an approach that is designed to increase the scope of utilisation of this data. This approach is developed using both digital and photographic techniques with a view to arrive at a standard set of keys for analysing and interpreting the TV data. The basis of the digital technique is the frequency distribution of gray tones (reflectance values) for identifying major cover types, classifying them and generation of three new data sets by assigning pseudo grey codes to the classified data. The pseudo gray coded data is then used to generate photographically colour codes for each of the cover type. Each pseudo data set is turned into a photographic film transparency and is assigned the colours red, green and blue respectively. The colour composite made using these transparencies is the new colour coded thematic ground cover picture from Bhaskara.