At Azavea, interacting with and contributing to the geospatial community is a perpetual highlight of our work. For many years, Twitter has represented a hub of activity within the professional geospatial sphere, and we’ve enjoyed interacting with community members and sharing our work through the platform. In light of the uncertain future of Twitter, both…
At Azavea, interacting with and contributing to the geospatial community is a perpetual highlight of our work. For many years, Twitter has represented a hub of activity within the professional geospatial sphere, and we’ve enjoyed interacting with community members and sharing our work through the platform. In light of the uncertain future of Twitter, both…
To generate a printable document that is well-formatted, we break down the implementation process to print a Mapbox map to a PDF in React.
Azavean Rachele Morino outlines her career transition from baking to software engineering, and where the two professions overlap.
Reviewing model architectures for building footprint extraction including naive approaches, model improvement strategies, and recent research.
In the second part of our Automated Building Footprint Extraction series, we review some evaluation metrics for building footprint extraction.
In the first installment of this three-part blog series, we summarize some of the latest research on automated building footprint extraction.
A recap of Azavea’s partnership with the Philadelphia Water Department to support stormwater management through Philadelphia’s Green City, Clean Waters plan.
Two weeks ago, right before SatSummit, we hosted a “Satellite Tasking API Sprint” at our office in Alexandria. The goal was to initiate a conversation around standardizing how users submit tasking requests to data providers. The companies attending, made up of data providers, analytics users, and developers, represented a wide and deep knowledge base around…
We outline our 10% time program in detail, highlight some notable examples and themes, and describe the impact of the program.
In this blog we demonstrate how an active learning approach can boost machine learning model performance with the human-in-the-loop workflow.