Agriculture was invented by humans in 8000 B.C., and has come a long way since. In the 21st century, it continues to play a key role in the economy of developing nations and can make or break the food supply of a whole nation.
In India, the agricultural sector employs about 42% of the Indian population, yet it contributes to just 16% of the GDP (source: Statista). This glaring gap gives rise to the question – why have we still not unlocked the potential of the ‘lifeline’ of India? One problem area that emerges is the limited access to technological farm solutions for all. More than 80% of farmers have small or marginal farms, and most of the solutions available at present are expensive, sensor-based, and ground-staff heavy.
To provide technological access to all the farmers, including the 130+ million small and marginal farmers, agritech and agricultural legacy companies need to introduce inexpensive, scalable solutions that do not rely heavily on ground-staff or sensors. This is where satellite-based solutions can be used to fill in the gaps.
At Kawa Space, we don’t want anyone to be left behind. To empower agriculture companies and help them serve millions of farmers, we are making universally accessible satellite-based solutions to empower agriculture companies and help them serve millions of farmers. We have built a geospatial technological infrastructure for agritech and agriculture legacy companies, so they could focus on what matters the most – providing insights to farmers and making sure that they progress.
We have released geospatial APIs, which focus on all aspects of farming – boundary detection, crop growth and health, soil, and weather. We have curated the necessary infrastructure to enable companies to serve farmers at scale.
How are we doing that? That’s where it gets interesting.
Digitizing farm boundaries at scale
“During conversations with multiple companies in the agriculture domain, we realized that the most pressing problem they face is being stuck to a macro-level view of their customers – the reason for which is the lack of digitization of individual farmlands. Currently, they have to deploy ground resources to individually map farm boundaries, which is labor-intensive, expensive, and not scalable.”
We, at Kawa, are making this process easy, accurate, and scalable.
We have created a farm boundary detection solution, with a resolution as high as 1m. All a user has to do, is provide a pair of coordinates, and it will identify all the visible farm boundaries in the area of interest.
Demarcation of farm boundaries has given our users a micro-level view of their farmers. Market Linkage Cos are combining farm boundary detection and vegetation index APIs to facilitate their procurement process.
Shown below is the output of our farm boundary detection model, with the original input on the side. Clearly, the solution works and looks vibrant while doing so.
Identification of a farm boundary is the first step to decode any farm and provide farm-specific crop, soil, and weather insights.
API to monitor crop growth across the year
During a pilot project in Indonesia, we identified the limitations of the multi-spectral vegetation index. Being a passive sensor-based index, it was not able to capture crop health data because of cloud cover during 200+ rainy days in Indonesia.
To tackle this issue, we’ve developed a radar-based vegetation index that can provide crop-health data across the year, irrespective of the weather conditions.
Given the scope of the solution in India, we have released the API focusing on Indian farmlands.
Just as an example of how our index is different from the multi-spectral vegetation index, the graph below shows how the SAR-based index managed to give insights during the months of June to September, while the multi-spectral index was on vacation. Also, note how the results from both indices wherever available are in synchrony, a testament to the accuracy of the SAR insights.
Replacing soil moisture sensors with an API
For irrigation, advisory, and input management companies, understanding the soil moisture content of their customer’s farms is important. To make this process easy, accurate, and scalable, we have introduced the soil moisture API, which can help them analyze the moisture content of the farms without investing in ground sensors.
One of the ways our API is being deployed into the field is for the evaluation of the performance of a company’s water retention enhancement product. They have been able to successfully quantify the impact of their product, gain farmer’s trust and provide better irrigation advisory. Check the results out for yourselves!
An inexpensive weather stations for your farmers
Given the expensive nature of weather stations, agriculture companies have faced major roadblocks in delivering timely and accurate weather insights to their farmers at scale.
We are trying to replace these costly setups with our weather API.
Agritech companies have integrated our weather API in their call center advisory services, and are providing real-time and hyperlocal weather forecast updates to their farmers.
There’s more where all that came from. We have several other agricultural offerings in the pipeline. Currently, we are focussing on crop classification and nutritional mapping, which we plan to release in the next 2-3 quarters.
Our aim at Kawa Space is to power agriculture with intelligence from space. We are excited for companies to use our APIs, and to help them provide their services to millions of farmers, at scale. To enable developers and PMs of companies of all sizes to test out our services, Kawa Space offers a pay-as-you-go model, removing the CAPEX dependency.
Please visit agriculture.kawa.space to know more, and we would love to connect with you.