Software Engineering
<- Return to all blogs
-
Color Correction in Space and at Sea
A common theme with projects at Element 84 is bridging the gap between data collection and its presentation to end-users. With satellite imagery, there is a pipeline of processing steps used to transform raw data into the imagery we see on our computers, phones and tablets. Basic Color Correction One of the important steps in…
-
Color Correction in Space and at Sea
A common theme with projects at Element 84 is bridging the gap between data collection and its presentation to end-users. With satellite imagery, there is a pipeline of processing steps used to transform raw data into the imagery we see on our computers, phones and tablets. Basic Color Correction One of the important steps in…
-
Give The Gift of a Tech Debt Sprint This Agile Holiday Season
Holidays can be a challenging time in software development. How can you make the most of your velocity and energize the team at the same time? The holiday challenge For a lot of teams, the holidays are a time of year when a large amount of peope take off after saving their PTO for the…
-
3 Ways to Analyze the Results of a Supervised Machine Learning Model
How accurate are our supervised machine learning models and what are they really doing? We offer 3 tips to help you better understand these models.
-
Modeling State with TypeScript
Working with frontend state can be challenging. With TypeScript, thoughtfully constructed types can help prevent bugs by making bad states unrepresentable. Let’s explore a common use case and examine how to do this effectively in TypeScript.
-
Ethical Machine Learning for Disaster Relief: Rage for Machine Learning
ML’s predictive powers are driving a rage for deep learning in the crisis management and disaster relief industries. How can these powers be harnessed for ethical machine learning?
-
Ethical Machine Learning for Disaster Relief: Avoiding the Second Disaster
Machine learning on satellite imagery is revolutionizing disaster relief. What does ethical machine learning mean in this field?
-
Betting Big on the Spatiotemporal Asset Catalog (STAC) Standard
We’re investing heavily in the STAC specification – including building a STAC-compatible Python library and server as well contributing to the Label Extension. We’re hoping this work will help accelerate adoption across the geospatial engineering community more broadly.
-
Introducing PySTAC: A Core Library for SpatioTemporal Asset Catalogs
PySTAC is a Python library for reading, writing, and manipulating SpatioTemporal Asset Catalogs. PySTAC 0.3 is now released and ready to use!
-
GeoTrellis 3.0 Release
GeoTrellis 3.0 includes feature additions and improvements that make it easier to read raster data from a variety of formats and sources, and support COG’s.
-
Mapping with Leaflet and React
Mapping is hard, but spinning up a new app that renders maps doesn’t have to be. Here’s how you can easily get started working with maps in a new React app. Not that AAA map under your car seat Maps have been around for thousands of years, but they’ve become more complex and powerful within…