ESTIMATION OF CHICKPEA YIELD IN THE DEDIAPADA BLOCK USING REMOTE SENSING AND GIS
Keywords:
CHICKPEA YIELDAbstract
Crop yield estimation in various countries is based on traditional data collection techniques for crop and yield estimation, which include on-the-ground field visits and reports. These reports are frequently subjective and take more time and money to complete. They are prone to large errors due to insufficient ground observations, which leads to inaccurate crop yield and production estimates [Bhattacharyay et. al., 2020; Gummadi et al., 2022]. Crop yield estimation also can be done by using remote sensing data. Yield estimation using remote sensing is done by using statistical methods, like regression analysis and modelling in GIS and excels, including classification and estimation. With the advent of remote sensing and GIS technologies, it has come possible to estimate crop yields using various methodologies. In tropical regions, chickpea is cultivated as a winter crop and in temperature clines, as a spring or summer crop [Frimpong et al., 2009]. Chickpeas are grown across 59 nations in an area of 14.8 Mha, producing 15.1 million tons annually [FAOSATAT Crops. 2021]. In India, chickpea has played a significant role in the 'Pulse Revolution', making the country self-sufficient in pulses. From a level of seven 75.9 lakh tonnes in 2014-15, chickpea production rose to an all-time high of 126.1 lakh tones during 2020-21. Main food grain crops cultivated in Dediapada are Wheat, Jowar and Maize, Paddy while major oil seeds grown in the district are Groundnut and Castor, where as the main crop cultivated in Dediapada are cotton and Gram.
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