Need for an Orchestration Platform to Unlock the Potential of Remote Sensing Data for Agriculture

Abstract

Satellites, drones, and on-ground sensors are essential in providing data for the digital ecosystem for agriculture innovation. Usually, all three modes of data collection are executed in isolation; however, they should work in coordination to leverage the strength of remote sensing. For example, making a classification model using remote sensing and ground data is mandatory. The current approach is to collect data through mobile phones by field officers at a specific time of crop harvesting. However, a more efficient method would be using an on-ground sensor to provide ground truth data continuously. Frequent training of the machine learning model will produce a time-sensitive digital crop signature on the ground. It will significantly impact how we do crop classification and yield estimation. This chapter evaluates and proposes a reference architecture for the orchestration platform that provides a coordination mechanism for the data collected from on-ground sensors, drones, and remote sensing satellites. The benefits of agriculture are examined through several use cases in this chapter.