Joe Flasher

As the world population expands and food insecurity reaches record levels, the collective need for agriculture to produce more output with fewer resources is critical. Using Earth observation data brings insights to agriculture and helps inform improved practices and outcomes in farms from Africa to Brazil and beyond.

Across the commercial and public sectors, companies are working with large geospatial datasets. We take a look at how to use various services including Amazon Simple Storage Service (Amazon S3), Amazon Simple Storage Service Glacier, Amazon Athena, AWS Step Functions, and AWS Batch to store, process, and get insights into your large geospatial datasets.

SpaceNet, a nonprofit LLC focusing on solving geospatial problems such as mapping road network routes after a natural disaster, has open-sourced more than 6,500 square kilometers of high-resolution satellite imagery with approximately 800,000 building footprint labels and 8,000 square kilometers of road network labels. Join us for a discussion on how to use this data to train machine learning...