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Use of satellite mapping and drone-based data gathering in estimating yield of paddy and wheat — having a combined 40 per cent share in total insured areas — for the purpose of crop insurance under the Pradhan Mantri Fasal Bima Yojana (PMFBY) is likely to be made compulsory from kharif 2022.
With high accuracy level in crop cutting experiments (CCEs), technology adoption may eliminate data tampering possibility and build trust in the crop insurance model.
“Currently, CCEs are done in the pre-identified field in the presence of farmers, insurance company’s representatives and State officials. Though the results of CCEs are supposed to be uploaded immediately in an app developed for the purpose, very often it does not happen and States take months to share the data, resulting in delays in claim settlement,” an official source told BusinessLine.
Precise results
By adopting the technology, the Agriculture Ministry has already roped in services of many private companies including agri start-ups who have invested in this segment. From the pilot projects done during last two seasons on wheat and paddy crop, the accuracy level of CCEs is between 80 and 95 per cent depending on technology used, sources said.
While farmers allege that the manually done CCEs favour insurance companies by showing inflated yield than actual, insurers also claim that state officials reduce the yield to provide higher claims to farmers.
During kharif 2019, pilot studies were conducted through 12 agencies in 64 districts of 15 States for nine crops envisaging innovative technologies such as High Resolution Satellite data (Optical and microwave), Unmanned Aerial Vehicle (UAV), Advanced multi-parameter crop models, Mobile Applications for Field Data Collection, Artificial intelligence/Machine learning approach, Sensor Networks, Internet of Things, Field based digital photographs, Hand held instruments and Scientifically designed Sampling Plans, said Union Agriculture Minister Narendra Singh Tomar recently in the Lok Sabha.
These approaches were validated in rabi 2019-20 in 15 blocks of six States, he said, adding the pilot studies were scaled up to 100 districts for paddy and wheat in 2020-21. The agencies who did the CCEs have already submitted the technical reports to Mahalanobis National Crop Forecast Centre (MNCFC), who also independently gathered data using satellite imagery for testing purpose.
Attracting private insurers
The transition is essential for the government to retain the interest of private insurance companies after some of them exited from the crop insurance business, while no one participated during bids (for premium) in some clusters recently citing high claims ratio.
“We have collected huge amount of data and have been conducting experiments for the government, banks and insurance companies. We have employed drones and artificial intelligence/machine learning (AI/ML), besides satellite imagery with very high resolution which helped us to provide yield estimates with high accuracy for field crops like paddy, wheat, cotton, soyabean and maize,” said Jatin Singh, Managing Director of Skymet Weather Services.
Many experts said noise-free data and availability of that at hyperlocal level are indispensable for generating precise yield insights. Effective use of advance imaging technologies such as Multispectral, Hyperspectral and Thermal is possible with UAVs (drones) and this will help in analysing different aspects of crop physiology accurately.
Navneet Ravikar, Chairman and Managing Director of Noida-based Leads Connect Services, said technology intervention in CCEs will be instrumental in nullifying aberrations to a significant level. Inconsistencies due to human error or bias are always a possibility, which can now be done away with technology providing near to accurate post-harvest yield estimates, Ravikar said.
Leads Connect, which has developed and tested its smart crop CCE framework in Uttar Pradesh, Haryana and Rajasthan on pilot basis using Drone-AI analytics during kharif 2019 and rabi 2020, has expanded its work by partnering with Assam and Odisha governments.
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