19 Jul Leaf leverages Japanese satellite technology
Partnership with Japan-based Sagri will bring solutions to help develop sustainable farming ecosystem
Indian agricultural services company Lawrencedale Agro Processing India (Leaf), has partnered with Japan-based Sagri improve harvest estimations and productivity using satellite technology.
Leaf and Sagri are aligning to disrupt the field of information sourced from satellites and making it meaningful for marginalised tribal farmers who are struggling to increase their productivity.
Sagri’s Satoshi Nagata said his company specialises harnessing satellite data and using artificial intelligence, machine learning, and mapping technology to solve problems plaguing the agriculture sector.
“Since satellite data can be obtained over a wide area and in a homogeneous manner, its usefulness is expected,” said Nagata.
“However, on the other hand, it is difficult for end users to directly utilise satellite data. It is this gap that Leaf-Sagri partnership will address and provide information appropriately.”
Palat Vijayaraghavan, founder and chief executive of Leaf, said the partnership was about more than just collecting data.
“Leaf’s strategic alignment with Sagri leverages the developments in satellite technology, analyses the vegetation index acquired from satellite data and uses machine learning technology to solve the major agricultural issues,” said Vijayaraghavan.
“It is not just an app that provides data that can be obtained from satellites, but an algorithm that connects to the solution.”
The solution uses satellite imagery to calculate the Normalised Difference Vegetation Index (NDVI) of the farmland over a period of time. In other words, NDVI is a measure to calculate farm production and productivity. With this wealth of information about farmland and with its proprietary technology, Leaf-Sagri team helps farmers increase their harvest quality and yields.
“We use satellite imagery to calculate the NDVI of the farmland over a period of time. This is further helped by additional data such as area of farmland, distance of the farmland from the main road, water supply and weather or climate within that region,” added Vijayaraghavan.
“When we can predict the quality of the produce along with the yield, it gives the farming ecosystem with much needed confidence to come with multiple services such as access to organised farm credit and farm insurance.”