Mr. Pravin Kolhe will present his APS as per the details below:
Date: 24 September 2025
Time: 1230 hrs.
Venue: C-TARA Conference Room No.1
Supervisor: Prof. Pennan Chinnasamy
External Supervisor: Dr. Sanjay Belsare
RPC Members: Prof. Priya Jadhav and Prof. Raaj Ramsankaran
Title: "Synergized Mapping™ of Agriculture Area and Crops Using Satellites, Drones and Crowd Sourcing -A case study in Maharashtra"
Abstract:
The agriculture sector in India consumes nearly 84% of total water resources, and hence monitoring water use is crucial for sustainable management. For this purpose, data related to area irrigated, crop type, and crop yield becomes essential for stakeholders such as Government agencies, private industry, consumers, academicians, and policy makers. In the 1st Annual Progress Seminar (APS), various approaches for crop and area mapping were discussed. Their advantages and limitations were analyzed, and it was concluded that remote sensing, drone surveys, and crowd sourcing are effective tools for agricultural mapping. It was further decided to develop a methodology for synergizing these methods to enhance accuracy and applicability. In the 2nd APS, the study site was finalized based on a nine-point analysis. Among the shortlisted villages—Bhigwan, Loni Devkar, Malthan, and Rajegaon—it was found that Loni Devkar village satisfied the required criteria and was selected for detailed research. In the 3rd APS, three sets of data were collected: Government data, Drone survey data, and Crowd-sourced data. In the 4th APS, the satellite-based data for Loni Devkar village was collected, processed, and prepared for result presentation.
In the 5th APS, the analysis of all datasets will be presented. The results indicate that drone-based data provides the highest accuracy for crop mapping, but it is expensive, requires significant storage capacity, and poses challenges for large-scale distribution. Government data shows representation issues, which were verified through ground truthing. The comparative analysis suggests the need for a methodology that ensures accurate crop mapping while minimizing input requirements and resource use. Accordingly, in this APS an introduction to a synergized crop mapping methodology is presented. This approach combines multi-sourced datasets—satellite imageries, drone survey data, crowd-sourced information, and Government records to achieve effective, reliable, and resource-efficient crop mapping.