Change in the Scape

Time lapse exploration of the past 30 years through satellite imagery via Google Map platform.

This project is a collaboration between Google’s Earth Engine team, Carnegie Mellon University’s CREATE Lab, and TIME Magazine.

1. Nearly a petabyte of historical record from USGS’s and NASA’s Landsat satellites

2. Algorithms (and associated/expected resulting interpolation) to remove the well-known stripe problem with Landsat 7

3. Carnegie Mellon CREATE Lab’s open-source “Time Machine” software

4. Multi-year interpolation for cloud-removal


Straight from the horse’s mouth: article by Randy Sargent, Google/Carnegie Mellon University; Matt Hancher and Eric Nguyen, Google; and Illah Nourbakhsh, Carnegie Mellon University

“Using Earth Engine, we first built annual global mosaics at a resolution of 30 meters per pixel for each year from 1984 through 2012. We started with a total of 2,068,467 scenes from the Landsat 4, 5, and 7 satellites, comprising 909 terabytes of data. The Earth’s atmosphere is a constantly-shifting sea of clouds, so in order to assemble a seamless cloud-free view of each year we analyzed all the images available at each location and used a simple cloud model to separate out the clouds from the ground. To help correct for atmospheric and seasonal effects, we used an additional 20TB of data from the MODIS MCD43A4 product to build a cloud-free low-resolution model of the Earth over time. We combined all this to produce a statistical estimate of the color of each pixel for every year for which data was available. Producing the final 29 global mosaics took a bit less than a day and consumed approximately 260,000 core-hours of CPU… Time-lapse Earth sets a new record for giant videos: each frame of the video is a global Mercator-projected map with a resolution of 30 meters per pixel at the equator, for a total of 1.78 trillion pixels per frame. That’s about a million times larger than a standard HD video stream. In order to scale to such large videos, we needed to integrate Time Machine’s data production pipeline into Earth Engine and the rest of Google’s infrastructure. Encoding the final video tiles consumed approximately 1.4 million core-hours of CPU in Google’s data centers over the course of about a day.”


Margaret Spyker

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