A case study in Maharashtra
Timely, accurate, and local historical along with near real time weather information is required to support pricing of premiums and identification of valid claims. Three barriers constrain growth of access to WBCIS products.
Over a 4 -year period (2012-2016), with initial funding from SwissRe followed by a public- private partnership with the State of Maharashtra, a team led by Niruthi with support from AICI (Agricultural Insurance Corporation of India), CRIDA (Central Research Institute for Dryland Agriculture), GoM (Government of Maharashtra) and SwissRe assessed technological solutions that can bring crop insurance to individual villages and potentially individual farmers in the future
TOPS technology developed by NASA scientists integrates satellite data, ground-based weather data with crop simulation models for estimating location-specific climate, crop condition and yield at spatial resolutions ranging from 30m to 1000m. Niruthi deploys the TOPS platform that uses an array of technologies – satellite measurements, ground observations, crowd sourcing, and cloud computing to provide robust, integrated solutions to the insurance industry.
Generate village specific historical and current weather data derived from TOPS, and evolve science based objective approaches for assessing climate risks.
Formulate relations between crop yields vs Remote Sensing (RS) and weather data at sub-district level to use to predict yields at gram panchayat level (GP- level).
Creating village virtual weather stations in order to address the problems related to the lack of historical climate data at village-level
Conducting such a large number of CCEs is expensive, time-consuming and logistically difficult to deliver on time.
We addressed this question using a photo-to-yield approach based on machine learning technology that is widely used in face-recognition
We used an android-based app called CropSnap to obtain geo-located images of crops acquired under specific guidelines