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. India is one of the world’s largest producers of rice, accounting for 20% of all world rice production. Rice crop occupies nearly 27.6% of the India’s arable land with average consumption per capita/year was ~68.2 kg milled rice. Being a staple food it is crucially important for policy makers, planners and researchers to have an accurate estimate before the harvest of crop. Timely and accurate statistics helps planners, and decision makers in formulating policies in regard to import/export in the event of shortfall and/or surplus. In the present study it is tried to evaluate the applicability of the remote sensing for yield estimation of major rice growing states of India. Recent advances on the resolutions (i.e., spectral, spatial, radiometric, and temporal) and availability of remote sensing imagery allowed us timely collection of information. This study developed an intermediate method called semi-physical method using remote sensing and the physiological concepts such as the Photo-synthetically Active Radiation and the fraction of PAR absorbed by the crop. Net Primary Product was computed using the Monteith model. Rice yield was computed using the actual NPP, Radiation use efficiency and Harvest index. The study was carried in kharif season 2018–19. Although model gives slight difference of yield with respect to actual and the estimated yield and DES yields within the range of ± 10%, which confirms the utility of model and can be used for the operational estimates of rice crop.

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

ASSESSMENT OF RICE BIOMASS PRODUCTION AND YIELD USING SEMI-PHYSICAL APPROACH AND REMOTELY SENSED DATA