One of the most exciting advancements in regenerative agriculture programs is the marriage of remote sensing and artificial intelligence (AI). Together, these technologies are transforming our ability to monitor the management of row crops. Modern programs focused on regenerative farming, Scope 3 emissions reduction, and carbon sequestration require reliable insights about on-the-ground management practices. Historically, this information was collected through time-consuming surveys or disrupting interviews with farmers. While valuable, the time needed to undertake these efforts made it impossible to scale them up and cover the entire country. Now, with satellite-based remote sensing and AI, these insights are delivered instantly, at scale, at high resolution, and, importantly, without disrupting farmers.
Remote sensing measures crop growth throughout the year so that the growers can analyze conditions based on the data and take action that will have a positive influence on the harvest outcome. But what exactly is remote sensing? In this recorded webinar, the CIBO team will share an overview of remote sensing, ways to use the data and how remote sensing data can be used for decision-making among the agriculture and food security communities.
- Remote sensing 101
- Where remote sensing data comes from and how to use it
- Updates to CIBO’s remote sensing capabilities
Ernesto Brau, Lead Computer Vision Scientist
Ernesto Brau is the Lead Computer Vision Scientist at CIBO. Prior to CIBO, he worked on computer vision for AiBee Inc., Intel Corporation, and Hewlett-Packard Laboratories. He holds a Bachelor of Science in Computer Science from the Universidad de Sonora in Mexico, along with an MS and PhD in Computer Science from the University of Arizona.
Subhash Bylaiah, Senior Data Scientist
Subhash Bylaiah is a Data Scientist at CIBO. He holds a Bachelors of Engineering from the Malnad College of Engineering and a Master of Science in Data Science from Indiana University Bloomington.
Pankaj Bhambhani, Data Scientist
Pankaj Bhambhani is a Data Scientist at CIBO. He holds a B.Tech in Information and Communication Technology from Dhirubhai Ambani Institute of Information and Communication Technology and a Masters in Computer Science from the University of Massachusetts Amherst.
Guided Learning Path – Regenerative Ag Verification 101
Growers are looking for guidance through deeper engagement from businesses when trying to implement and verify regenerative agriculture practices. Businesses want to collect more data that has purpose and meaning to their sustainability goals, and they want to utilize this data to improve the way they operate their business. Discover how businesses can become growers’ trusted advisors in regard to verifying regenerative ag.
Computer Vision and Remote Sensing: Agricultural Information in the 21st Century
By Ernesto Brau
This blog post will explore how CIBO is focused on providing actionable information and insights regarding farmland, and the many different sources of data we use to do so. Some of this data is available from public sources. Some we derive from our proprietary modeling technology. And other data comes to us from tens of thousands of miles in the air, via satellites soaring around the earth.
How Remotely Sensed Performance Zone Maps Improve Agriculture Assessments
By Pankaj Bhambhani
Understanding how farmland behaves is tricky because it’s not just about historical yield, type of soil and weather conditions. We often think of a field as a single unit, but in reality, every field has variability: differences in soil type, texture, and slope mean that different parts of the field show obvious differences in yield. To deeply understand a field, we need to know how these parts perform relative to each other.