Python in Science Conferences

Harmful algal blooms pose major health risks to human and aquatic life. CyFi is an open-source Python package that enables detection of cyanobacteria in inland water bodies using 10-30m Sentinel-2 imagery and a computationally efficient tree-based machine learning model.

The increasing volume of research data in fields such as astronomy, biology, and engineering necessitates efficient distributed data management. This paper presents the Librarian, a custom framework designed for data transfer in large academic collaborations, designed for the Simons Observatory.

Water column sonar data collected by echosounders are essential for fisheries and marine ecosystem research, enabling the detection, classification, and quantification of fish and zooplankton from many different ocean observing platforms. We introduce Echostack, a suite of open-source Python software packages that leverage existing distributed computing and cloud-interfacing libraries to support intuitive and scalable data access, processing, and interpretation.

In recent years, leveraging satellite imagery with deep learning architectures has become an effective approach for environmental monitoring tasks, including forest wildfire detection. This paper presents a Python-based methodology for gathering and using a labeled high-resolution satellite imagery dataset for forest wildfire detection.