All stakeholders in agriculture sector, whether he is the farmer himself, Government, agricultural insurance companies, agribusiness firms or local traders have always been in the need of ‘information’ on accurate estimation and forecast on crops on ground including their health, likelihood of losses, actual losses, among others to take ‘informed decisions’ in their domain.
The world is now living in an ‘information world’ where electronics, computers and mobile phones have changed the way we live, think and act. Integration of satellite, mobile and ground-based information together can resolve the ‘information darkness’ in agriculture sector and can provide all the information that is sought by different stakeholders.
Low altitude platform-based solutions hold huge potential when it comes to localised problem solving. One of the prominent solution among these is UAV (unmanned aerial vehicle) or DRONE (Dynamic Remotely Operated Navigation Equipment) technology that has caught attention of large farmers, crop insurance companies and Government as it can provide 'farm–specific' information on crop condition, losses to farmers and in reaching the right kind of benefits to right people. With flying just at 150 metre - 200 metre above ground level, this makes it as one unique platform.
The sensors that can be placed on board on any of these three platforms -- regular satellite, nano-satellites and Drones -- are largely the same and can provide comparable information with varying level of details.
While the medium resolution satellites score on their capabilities of covering large areas, the Nano-satellites and Drones based images capture very detailed pictures of ground.
Following are the areas where Drones can immediately offer solutions
The Drones flying over farmers field can reveal whether conditions for delayed sowing prevail on ground or sowing was done based on other sources of irrigation.
2.Area sown validation
Since every farm land can be identified and sown crop can be mapped at crop field level, a 100 percent correct statistic for sown crops in a village or multiple villages can be determined and compared with that derived through traditional way (Patwari's assessment).
UAVs provide a complete perspective view of crop field along with a detailed close-up view, so it becomes quite easy to provide digital proof of whether the field was inundated or not. It also helps in estimating the extent of damage suffered by crop and its spatial extent.
4.Field level data for yield estimation
Crop simulation models require very detailed information of crop fields in order to accurately forecast yield. With UAVs, the crop insurance companies can get additional information as compared to satellites such as tentative sowing date, planting density, row spacing, well managed or poorly managed, irrigation source, precise health among other information from the field.
5.Crop Cutting Experiment (CCE) location validation
Another major issue faced by insurance companies is the manipulation of CCE location sites wherein the crop cutting experiment is conducted at a different location than selected by random sampling method.
6. Fraud detection in loss reporting
It was often talked about that farmers actually sow different crops than what they had committed to crop insurance agencies at the time of insurance policy issued to them, but there was no hard evidence to prove the same. Thanks to UAV, Geographic Information System (GIS) and Cadastral map data, it is now possible to correlate every policy to the sown crop and validate whether the compliance level is complete or there are flaws.
(With inputs from FICCI-Skymet Weather report on Accelerating Agriculture Insurance)
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