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Using ArcMap, R, and Adobe Illustrator to Create Data Driven Infographics
Learn to create a series of data-driven infographics in the context of a project that evaluates bus performance in each Philadelphia City Council District.
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Using ArcMap, R, and Adobe Illustrator to Create Data Driven Infographics
Learn to create a series of data-driven infographics in the context of a project that evaluates bus performance in each Philadelphia City Council District.
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How Evictions Correspond to Past Divestment in New Orleans
We worked with Jane Place Neighborhood Sustainability Initiative as part of the 2018 Summer of Maps program to analyze evictions data in New Orleans.
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Digitizing Maps Using Remote Sensing Techniques in ArcMap and R
Learn how to use image processing and remote sensing techniques in R and ArcGIS to digitize spatial data from image or PDF files.
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Creating Leaflet Tiles from Open Data using PostGIS and QGIS
A guide to transforming open geospatial data into slippy map tiles to display in Leaflet or OpenLayers using PostGIS, QGIS, and QTiles.
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Engineer Onboarding with Breakable Toy
My experience joining the Operations Team at Azavea. This was the first time my colleagues used the Breakable Toy apprenticeship pattern.
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Preparing Data for MaxEnt Species Distribution Modeling Using R
How to use R to turn disparate environmental data into clean, usable raster data that can be fed into a MaxEnt species distribution model.
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Evaluating Machine Learning Models in R: Predicting Marine Debris
Evaluating machine learning models in R with a focus on how to handle biased and imperfect data, specifically volunteer collected marine debris data.
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Three (Earth) Observations from Sat Summit 2018
Here are our key takeaways from SatSummit and some thoughts to help drive innovation related to earth observation data toward impactful solutions.
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Public Redlining Exhibit Showcases Azavea’s Data Analysis Work
In September 2018, a free exhibit opened to the public on the history of redlining in Philadelphia. Read about how our Data Analytics team was involved.
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Cleaning Philadelphia Campaign Finance Data with R
How to categorize, clean, filter, and prepare Philadelphia’s campaign finance data for analysis, mapping, and visualization.
