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Drilling Detection with Machine Learning Part 3: Making and mapping predictions

SkyTruth Technical Program Director Ry Covington, PhD explains challenges to generating meaningful predictions from the machine learning model, and outlines solutions.

This is the final post in a 3-part blog series describing SkyTruth’s effort to automate the detection of oil and gas well pads around the world using machine learning. We hope that this series – and the resources we’ve provided throughout – will help other developers and scientists working on conservation issues to learn from our experience and build their own exciting tools. 

2017 Frackfinder update

We’re excited to announce the 2017 update to our Pennsylvania FrackFinder data set.  Using the USDA’s most recent high-resolution aerial imagery for Pennsylvania, we’ve again updated our maps of the state’s drilling sites and wastewater impoundments.  Our revised maps show Pennsylvania’s drilling sites and wastewater impoundments as of October 2017.   Our previous Pennsylvania FrackFinder […]

Using machine learning to map the footprint of fracking in central Appalachia

Fossil fuel production has left a lasting imprint on the landscapes and communities of central and northern Appalachia.  Mountaintop mining operations, pipeline right-of-ways, oil and gas well pads, and hydraulic fracturing wastewater retention ponds dot the landscapes of West Virginia and Pennsylvania.  And although advocacy groups have made progress pressuring regulated industries and state agencies […]