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An attempt has been made to understand the potential of temporal Advanced Wide Field Sensor (AWiFS) data aboard IRS-P6 (Resourcesat) to generate the land use land cover information along with the net sown area. The temporal data sets were georeferenced, converted to top of atmosphere reflectance and classified using decision tree classifier, See5. Results indicate that the temporal data set could give a better definition of training sites thereby resulting in good overall kappa (kappa = 0.8651) as well as individual classification accuracies. However, co-registration of temporal datasets accuracies also has got a significant influence on the classification accuracy. Temporal variation in cloud infestation and availability of appropriate data sets within the season (before harvest of the crop) has also affected the classification accuracy.  相似文献   
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This paper presents a method called SACRS2, a scheme for atmospheric correction of RS2-AWiFS (Resourcesat2-Advanced Wide Field Sensor) data. The SACRS2 is a computationally fast scheme developed from a physics-based detailed radiative transfer model 6SV for correcting large amount of data from the high-repetivity AWiFS sensor. The method is based on deriving a set of equations with coefficients which depend on the spectral bands of the RS2-AWiFS sensor through forward signal simulations by 6SV. Semi-empirical formulations provided in the SMAC method with a few improvements have been used to describe various atmospheric interactions. A total of 112 coefficients for different equations are determined using the best fit equations against the computations of the 6SV. After the specific coefficients for the RS2-AWiFS spectral bands are determined, the major inputs of the scheme are raw digital numbers recorded by RS2-AWiFS sensor, atmospheric columnar water vapour content, ozone content, aerosol optical thickness at 550 nm and viewing-illumination conditions. Results showed a good performance of the SACRS2 with a maximum relative error in the SACRS2 simulations ranged between 1% for a reflectance of 0.5 and 8.6% for reflectance of 0.05 with respect to 6SV computations. Validation of retrieved surface reflectance using the SACRS2 scheme with respect to in-situ measurements at two sites indicated a capability of this scheme to determine the surface reflectance within 10%. This is a first of its kind scheme developed for the atmospheric correction of any Indian Remote Sensing satellite data. A package containing the SACRS2 software is available on the MOSDAC website for the researchers.  相似文献   
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