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LULC system in India exhibits high degree of spatial and temporal variability due to the influence of climate and local land use practices on agriculture, compositional and phenological variability of natural vegetated systems like forests, grasslands. In order to precisely capture these variabilities, multi-temporal Resourcesat-1 Advanced Wide Field Sensor (AWiFS) data acquired during August- May of each calendar year (kharif, rabi, and zaid seasons) were used. In some of the areas, where the quality of AWiFS datasets was not satisfactory due to presence of cloud cover, Indian Remote Sensing Satellite (IRS-1C/1D Wide Field Sensor (WiFS)/Moderate Imaging Spectrometer (MODIS) images were used as supplementary datasets. The multi-temporal datasets were geo-referenced to LCC projection and WGS 84 datum. Planimetric accuracy of maps in plain area is around 1 pixel (±60m) and in hilly areas it is 2 pixels (±120m).
LULC classification scheme (legend) amenable to digital classification was adopted in order to generate LULC maps rapidly. Hierarchical decision tree (See 5), maximum likelihood and interactive classification techniques were adopted for classification of the data. The legacy datasets on forest cover, type, wastelands and limited ground truth were used as inputs for classification and accuracy assessment. Geo-database standards were developed to address the issues of retrieval and storage of different data inputs and outputs, designing metadata elements relevant to different types of data, automated output production and interactive querying.
Process-based Quality Assurance Scheme (QAS) was implemented to regulate the data flows and outputs as per the standards. The detailed methodology followed is available is described in the manual.
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