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Problem-solving by asking questions
The first in a two-part series, this blog post details how we solved a design problem by asking questions in building our climate adaptation planning app.
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Problem-solving by asking questions
The first in a two-part series, this blog post details how we solved a design problem by asking questions in building our climate adaptation planning app.
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AWS Enables Temperate
We recently released Temperate: A new climate adaptation planning companion for cities. This blog explores how AWS, and the data they host, fueled this app.
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E84 Lab Notes: Machine Learning with SageMaker
In a previous post we showed how the E84 R&D team used RoboSat by Mapbox to prepare training data, train a machine learning model, and run predictions on new satellite imagery. In this example, we’re going to use the same imagery source and label data as a proxy for data produced by our AWS disaster…
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Six Ways we Fund Innovation
Without outside funding and given our commitment to openly sharing our knowledge, people often ask: How do you fund your innovation? We outline 6 main ways.
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Temperate: Your Climate Adaptation Planning Companion
Azavea rolled out Temperate, a climate adaptation planning app, in 2018. Get the details here.
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E84 Lab Notes: Machine Learning with RoboSat
Recently, the E84 R&D team has been experimenting with machine learning pipelines and identifying potential use cases. There are a lot of new and exciting tools out there and we’re interested in exploring what’s available, particularly tools related to satellite and aerial imagery (one of our specialties). Mapbox‘s RoboSat was released earlier this year and…
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Enhancing the Pangeo Community with NASA Earth Observing System (EOS) Data
One of our main missions at Element 84 is to help reduce the amount of time that researchers (scientific and corporate, alike) spend wrangling, downloading, cleaning, and prepping data in pursuit of their primary research question. A recent NASA study put that number at around 60%–leaving less than half of a scientist’s time available for…
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Raster Vision: A New Open Source Framework for Deep Learning on Satellite and Aerial Imagery
Azavea is pleased to announce the release of Raster Vision, a new open source framework for deep learning on satellite and aerial imagery.
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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.
