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Research Paper | December 6, 2022

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Crop yield estimation with irrigation system using remote sensing and machine learning, A case study of Bahawalpur and Rahimyar Khan

Sumaira Hafeez, Saira Akram, Hassan Hafeez, Waqas Ejaz, Sajid Rashid Ahmad

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Int. J. Agron. Agri. Res.21(6), 18-27, December 2022

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IJAAR 2022 [Generate Certificate]

Abstract

Different datasets can be used to calculate the cropped areas. These datasets range from Statistical to Physical Measurements and Remotely Sensed. In this study, remotely sensed images were used to identify the cropped areas. RS GIS based Google Earth platform as a mechanical meeting is implemented to sign in unique id regard at each perception area Normalized Difference Vegetation Index (NDVI) the use of Reflectance and intensity of specific limits of data and data collecting instruments Photo-misleadingly Active Radiation (PAR), Fractional Absorbed PAR (fPAR), Absorbed Photo Synthetically in Bahawalpur and Rahim yar khan. The effects are differentiated this observe hopes to convert into the laying out for development of collect assessment from cautious and quantifiable to far flung spotting techniques in Pakistan.

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Crop yield estimation with irrigation system using remote sensing and machine learning, A case study of Bahawalpur and Rahimyar Khan

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