Tata Consultancy Services Limited

Mariappan Sakkan

Srinivasu Pappula

Jayantrao Mohite

Suryakant Ashok Sawant

Ankur Pandit

Sanat Sarangi

Vaibhav Sadashiv Lonkar

Ravinkumar Sivalingam

This disclosure relates generally to assessing soil carbon sequestration. One of the driving factors for climate change and global warming is emission of greenhouse gas emissions. Of the possible ways to reduce climate change and global warming adoption, sustainable agricultural practices will enable efficient soil carbon sequestration thereby reducing the greenhouse gases as well as increasing the crop yield. The disclosure is a method and a system for real time assessing soil carbon sequestration of farm based on remote sensing. The soil carbon sequestration of farm is assessed by continuously monitoring the farm at real time based on remote sensing using a plurality of satellite data and a plurality of farming data using several techniques. The several techniques utilized for assessing soil carbon sequestration includes machine learning, a carbon sequestration estimation technique, estimating a crop health index and an adoption index and computing a set of carbon sequestration parameters.

Method and system for assessing soil carbon sequestration of a farm based on remote sensing

Agriculture is impacted due to various parameters that results into heavy losses to the crops. Existing methods rely on manual inventories from fields and statistical results are prone to errors thus classification of crops may not be accurate. Present disclosure provides systems and methods for detection and prediction of disguised and potential non-performing assets (NPAs) in agriculture. Disguised NPAs detection involves, obtaining satellite data from sources and natural calamity, detecting of crop for past years, crop growth, estimating yields, market prices for individual years, AC zones, etc. wherein a generate performance score is generated for each field for classifying crop as disguised NPA. Predicting potential NPAs includes obtaining current season satellite data, data received from the fields via sensors, determining crop protocol being followed, forecast weather, estimating cumulative growth, feedback received from fields, projected yield, estimating crop losses, and then performance score is generated for predicting crops as potential NPA.

Systems and methods for detecting disguised non-performing assets (NPAs) and predicting potential NPAs in agriculture

The disclosure herein relates to identification of agro-phenological zones. Further the disclosed method and system also shares techniques for updating of the identified/existing agro-phenological zones. In a diverse geographical domain (like India), in order to maximize the crop production (avoid crop failures) from the available resources and prevailing diverse climatic conditions it necessary to use the resources and technology to infer the best agriculture approach on an individual location. The invention enables identification of the agro-phenological zones based on satellite image, weather data, soil data and cloud free historical satellite data using several techniques that includes machine learning, time series analysis, heuristic time series analysis technique and clustering. Further the invention also discloses techniques to update the identified/existing agro-phenological zones using historic data of agro-phenological zones of satellite image.

Method and system for identification of agro-phenological zones and updation of agro-phenological zones

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Chennai, India

Mariappan Sakkan