The Role of Remote Sensing in Tackling Crop Insurance Anomalies

In the year 2022, the surface temperature of the Earth was 1.55 Degrees Fahrenheit warmer than the average of 57 Degrees Fahrenheit (NOAA,2023). As the world warms, the frequency and intensity of climate change related disasters amplify, posing a significant risk. Heatwaves, Droughts, Hurricanes, and typhoons have caused havoc across every area, leaving no continent unaffected by their destructive impacts (UN,2019).

This inadvertently threatens global food security due to its inevitable impacts on agriculture. Natural hazards tend to challenge food production since the field relies heavily on the environment and weather conditions. In 2007, global economic losses because of the impacts of climate change on wheat, maize and barley were estimated at 5 billion USD (Lobell et al 2007), this amount has increased owing to the level of uncertainties.

The US EPA (Environmental Protection Agency) lists down four major areas impacted by natural disasters, in view of the agricultural system –

Contamination of water sources: For instance, flooding in an area causes the water to gather unwanted pollutants/contaminants along the way, ending up in nearby water bodies. When this water is used for irrigation, it can harbour risks to plants and even human health.

Loss of produce: Strong, unseasonal winds can cause lodging in certain crops, such as wheat. Lodging is the displacement of the crop, causing them to bend towards the ground. Susceptibility to diseases: Sudden weather events can cause physical damage to plants. Plants have natural defence mechanisms that prevent pathogen entry, like thick cuticles/thorns. Once a plant is wounded, the entry of these pathogens becomes easy, making them vulnerable to diseases.

Destruction of Agricultural infrastructure: Natural disasters can cause widespread devastation, impacting the elements needed to support agriculture.

The heavy amounts of risk associated with agriculture call for efficient Agriculture Insurance policies, which are still lagging in some parts of the world, leaving farmers at the mercy of unpredictable disasters. If farmers’ Crop loss is not covered, they fail to collect money for the next sowing season, causing a disturbance in the entire supply chain and eventually challenging our global food security. This is where high resolution satellite imagery can be used for problem solving.

India, “a global powerhouse of agriculture” (World Bank, 2012) is the leading producer of some of the major crops today. With nearly three-quarters of India’s families depending on this sector, it plays a crucial role in the country’s GDP. However, over the last six years the country has lost 33.9 million hectares of the sown area due to heavy rains and an additional 35 million due to drought (ANN, 2023) and in such situations, crop insurance becomes the only safety net for farmers. But the major question is, do the current insurance policies cover these losses efficiently?

NAIS, or National Agriculture Insurance Scheme is the oldest agriculture scheme in India, covering a majority of food and horticulture crops. Premium rates are set differently for each crop, additionally, small and marginal farmers are also entitled to a subsidy on the premium rate which is shared equally by the central and state governments. Over the years, necessary modifications have been made. The most recent scheme launched in 2016 – Pradhan Mantri Fasal Bima Yojna has replaced the previous schemes by integrating the best features and addressing the pain points.

Since the system caters to a multitude of farmers, the scope for potential discrepancies expands. Challenges include unawareness, lack of interest and most importantly settlement of claims. Data from 2018 shows that between 70 to 100 percent of farmers who made claims did not receive their payouts. Post the introduction of the PMFBI (Pradhan Mantri Fasal Bima Yojna) this percentage was improved, however, there was a delay in the payments.

From a broader perspective, the issues faced are area discrepancies and time-consuming, manual crop-cutting experiments to assess yield.

An area discrepancy is when the amount of area insured is greater than that of the area that is cultivated, at times farmers show their whole land to insurance companies but grow crops only in a small area. This is done to get a higher amount of insurance than required. Furthermore, crop-cutting experiments are traditional methods of Yield estimation. They involve a manual workforce to collect field samples and make further predictions. This is necessary to determine the claims that should be paid to the farmers however, with large areas the process tends to cause a delay in the settlement of claims.

How can we make our Agri insurance process more robust?

The answer lies in the appropriate usage of Geospatial Technology. Satellite Remote sensing is a growing field and has currently been introduced into the crop insurance cycle, to tackle the above issues. 3d Satellite images can procure data regarding the sown area on the field, thereby reducing the scope for discrepancies.

A practical application of GIS Mapping was seen in Churu village, Rajasthan where the net sown area was estimated using a satellite map. These images were geo-referenced and clipped according to boundaries, masking the open area. Pixels showing chlorophyll were identified. This gave the government an idea of the net sown area of gram crops in the region. The results showed 2.34 Lakh Hectares of sown area vs 5.38 Lakh Hectares that was insured. Latest satellite images give agencies the updated version of the status on the field.

Another effort of the Government of India is underway, as a partnership with private players to incorporate technology-based crop-cutting experiments. Artificial intelligence is used to identify sample plots and following that satellite images and predictive analyses are used for assessing the ideal sample for the region. Crop acreage and estimating yields using technology saves the government resources and money, eventually leading to faster settlement of claims.

Thus, there is huge scope for the incorporation of remote sensing to ensure a smooth and farmer-friendly insurance system which is the need of the hour for the farmers as well as the food security of the nation.