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 Philadelphia’s Green City, Clean Waters plan.
In this blog we demonstrate how an active learning approach can boost machine learning model performance with the human-in-the-loop workflow.
Benchmarking Zarr and Parquet Data Retrieval using the National Water Model (NWM) in a Cloud-native environment
In order to benchmark efficiency, we take a deep dive into Zarr and Parquet data retrieval to compare performance on various time scales.
A recent project required us to implement an interactive map of the United States with a custom counties layer. This is what we learned.