Software Engineering
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Predicting Land Use in the Amazon using Deep Learning
Learn about our methods and results leveraging our RasterVision deep learning project to predict land use in satellite images of the Amazon.
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Predicting Land Use in the Amazon using Deep Learning
Learn about our methods and results leveraging our RasterVision deep learning project to predict land use in satellite images of the Amazon.
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Weighing Scalaz vs Cats Scala Libraries for GeoTrellis
After a thorough research period that compared the Scalaz and Cats libraries in depth, GeoTrellis has decided to use the Cats library. Find out why…
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GeoTrellis 1.2 Release: New Features & Optimizations
LocationTech GeoTrellis, library that enables distributed processing of geospatial raster data, reached a new milestone in the development timeline.
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A Terraform Module for Amazon Elastic MapReduce
We encapsulated all resources required to launch an Amazon EMR cluster into a reusable Terraform module to leverage for batch GeoTrellis workflows with Apache Spark.
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Serving Tiles with GeoTrellis, Lambda, and API Gateway
Have this open source serverless tile server built with the Serverless framework, AWS Lambda, AWS API Gateway, and GeoTrellis up and running in minutes.
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How to Run GeoPySpark in a GeoNotebook with Docker
Walk through the easiest path to enable the use of GeoPySpark, a Python library for geoprocessing big data, interactively in a GeoNotebook with Docker.
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Introducing GeoPySpark, a Python Binding of GeoTrellis
GeoTrellis is a Scala library for working with geospatial data in a distributed environment. While powerful, it has a limited user base due to the geospatial community’s preference for other languages such as Python and R. Bringing GeoTrellis to another language has thus been a requested feature of the community. Well, after nine months of…
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Video: Using Convolutional Neural Networks to Automatically Analyze Aerial and Satellite Imagery
In this recording of our most recent Technical Staff Meeting, we walk through our team’s work on Raster Vision, a set of open source tools for automatically analyzing aerial and satellite imagery using convolutional neural networks. As part of Raster Vision, we have implemented approaches to tagging (predicts a set of tags for each image)…
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Reading and Visualizing NetCDF Climate Data with GeoTrellis
This blog post contains an example project that demonstrates how to read NetCDF climate projection data from S3 or a local filesystem into a Spark/Scala program using NetCDF Java and how to manipulate the data using GeoTrellis. We are interested in reading datasets stored as NetCDF because it is a common format for storing large, global climate…
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Deep Learning for Semantic Segmentation of Aerial and Satellite Imagery
This post describes how to use deep learning to do semantic segmentation on aerial and satellite imagery, experiments on the ISPRS Potsdam dataset, and how to visualize model predictions on a map.
