Opportunities and Challenges for Remote Sensing in Agricultural Applications of Data Science

  • Climate and Water

This presentation provides an overview of curent developments in the analysis of multi-temporal, multi-scale, and multi-sensor remotely sensed data, which presents potential and challenges for data science. The author highlights that the development of technologies to support increased food production throughout the supply chain is necessary due to the problems posed by climate change and a growing global population. She presents recent advancements in computing platforms and data analytics, as well as remote sensing developments from space-based, aerial and proximate platforms. Finally, she identifies some of the key challenges in the field and outlines the way forward.

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Author: Melba Crawford, College of Engineering, Purdue University