Page 232 - India Insurance Report 2023- BIMTECH

220 India Insurance Report - Series II

Leveraging Remote Sensing and

Data Analytics in Agriculture

Insurance Solutions

- Malay Poddar
26 Former Chairman-and-Managing Director,
Agriculture Insurance Company of India Ltd, New Delhi

1. Introduction

Modern remote sensing technology is characterized by freely available analysis-ready satellite data
sets with higher frequency and spatial resolution. When this availability is combined with UAV/ Mobile
phone-based crop survey data, otherwise known as ground truthing, one can derive useful biophysical
parameters leading to scientific crop assessment. The adoption of these technologies reduces information
gaps and information asymmetries for enhancing the efficiency and sustainability of a crop insurance
system. These technologies generate a huge amount of data, and therefore, data analytics is key to the
success of such big data applications. Spatial analytics, data mining, data engineering, evidence-based
tools, etc., could only churn out useful information products from the large pool of data.

Even for the ongoing season, these technologies can generate digital crop area maps with reasonably
good accuracy, which are vital inputs for proactive crop risk management, disaster relief, and production
estimates useful for developing customized insurance solutions. Since historical data on crops for a
reasonable number of past years are now available, these datasets are very useful for investigating the
associations, establishing relationships, quantifying historical losses, and predicting crop health and risk
occurrence during the ongoing crop season.

Governments can adopt a collaborative approach in a PPP mode with the reputed professional
firms having longstanding and proven expertise in this speciality and niche domain.

2. Global Perspectives – Some Examples

The Copernicus Programme of the European Space Agency started a new era of remote sensing by
providing an unprecedented amount of free data from its Sentinel series of satellites. Data of multiple
spectral channels representing optical and microwave regions, moderate spectral resolutions of 10-20 meters,
covering large areas once in 5-12 days, are made available in the public domain in the least possible turnaround
time. The problem of cloud cover in the monsoon season is overcome with microwave data. The synergistic
use of multiple datasets has enabled close monitoring of crops and capturing multiple crop risks.