Azavea Open Source Fellows Release Completed Projects

September 27th, 2018

In addition to welcoming three Azavea Summer of Maps fellows to our office for the past few months, we were fortunate to be able to host three software engineering fellows.

This second group of fellows worked closely with mentors as part of our Azavea Open Source Fellowship Program, a 12-week professional training fellowship that matches software engineering fellows with open source projects.

Applicants requested to work on Project Opportunities that were created by our team of mentors and we accepted three fellows to work on three separate projects as part of the 2018 program.

Summer 2018 projects

Open Source Fellows wrote blog posts detailing their project, including background information about the problem they were aiming to solve and a description of the solution. Click on an image or project title below to read about their work.

Editable schema

Grout: a Flexible-Schema Framework for Geospatial Apps

Fellow: Jean Cochrane
Mentors: Derek Dohler and Kathryn Killebrew

Grout is an open source framework that empowers non-technical administrative users to directly define and modify data at the core of their application. This framework for geospatial apps allows clients to edit not only the data, but the schema itself as they adapt the app for needs overtime.

Serverless tile rendering

Tilegarden: Serverless Tile Rendering with AWS Lambda

Fellow: Matt DelSordo
Mentors: Klaas Hoekema and Matt McFarland

Tilegarden enables serverless Lambda-based raster and vector tile generation from PostGIS data. This project builds upon a proof of concept project, Lambnik, that was created to take advantage of more robust map tiling libraries.

Ongoing work

Raster Vision – Deep Neural Networks for Satellite and Aerial Imagery

Nathan Holeman joined us later in the summer and continues to work on, Raster Vision, our library for deep learning for aerial and satellite imagery. This open source library is designed to easily extend to new data sources, machine learning tasks, and machine learning implementations.

On the horizon

If you’re interested in applying for a fellowship position for the 2019 Azavea Open Source Fellowship Program, sign up for our mailing list.

If you would like more information about the Azavea Open Source Fellowship Program or about ways you can get involved, contact fellowship@azavea.com.