Blog
The latest news from Google AI
An Inside Look at Google Earth Timelapse
Wednesday, June 5, 2019
Posted by Paul Dille, Senior Software Developer, Carnegie Mellon University CREATE Lab, and Chris Herwig, Geo Data Engineer, Google Earth Outreach
Six years ago, we first introduced
Google Earth Timelapse
, a global, zoomable time-lapse video that lets anyone explore our changing planet’s surface—from the global scale to the local scale. Earth Timelapse consists of 83 million multi-resolution overlapping video tiles, which are made interactively explorable through the open-source
Time Machine
client software developed at Carnegie Mellon University’s
CREATE Lab
. At its core, Google Earth Timelapse is an example of how organizing information can make it more accessible and useful, turning petabytes of satellite imagery into an interactive experience that shows the dynamic changes occurring across space and time.
In April, we
introduced several updates
to Timelapse, including two additional years of imagery to the time-series visualization, which now spans from 1984 to 2018, with
visual upgrades
that make exploring more accessible and intuitive. We are especially excited that this update includes support for mobile and tablet devices, which are quickly overtaking desktop computers as the dominant source of app traffic.
Building the Global Visualization
Making a planetary-sized time-lapse video required a significant amount of pixel crunching in
Earth Engine
, Google's cloud platform for petabyte-scale geospatial analysis. The new release followed a process similar to
what we did in 2013
, but at a significantly greater scale—turning 15 million satellite images acquired over the last three and a half decades from the USGS/NASA
Landsat
and European
Sentinel
programs into 35 cloud-free 4-terapixel images of the planet—one for each year from 1984 to 2018.
At its native resolution, the Timelapse visualization is a 4 terapixel video (that's four trillion pixels), which would take about 12 days to download on a 95 Mb/s internet connection. Most computers would have difficulty playing a video of this size, let alone with an interactive, zoomable interface. The problem is even more severe for a mobile device.
A solution was pioneered by Google Maps in 2004 with the
map pyramiding technique
. Before that time, navigating a map required the use of directional arrows to pan and zoom, with each step requiring the page to reload. The map pyramiding technique assembles the full map image displayed on-screen from tens of small 256x256 pixel non-overlapping image tiles in an array, with new tiles fetched as needed at an appropriate resolution as the user pans and zooms across the map.
A traditional Mercator map pyramid contains non-overlapping image tiles.
This works very well for maps made of static images, but less so for pyramids of video tiles, such as those used by Timelapse, since it requires a web browser to keep up to 16 videos in sync while interacting with the visualization. The solution is embodied in CREATE Lab’s
open source Time Machine software
: create much larger video tiles that can cover the entire screen and only show one whole-screen tile at a time. The tiles create a pyramid, where sibling tiles overlap with their neighbors to provide a seamless transition between tiles while panning and zooming. Though the overlapping tiles require the use of about 16x more videos, this pyramid structure enables the use of Timelapse on mobile devices by minimizing the amount of data required for visualization.
In our newest release, the global video pyramid consists of 83 million videos across 13 zoom levels, which required about 2 million CPU hours distributed across thousands of machines in Google Cloud to generate.
Earth Timelapse uses a pyramid of overlapping video tiles.
Time Travel, Wherever You Are
Prior to April's update, ~30% of visitors to the Timelapse visualization were on mobile devices and didn't actually experience the visualization; instead they saw a
YouTube playlist
of locations in Timelapse. Until recently, the hardware and CPUs for phones and tablets could not decode videos fast enough without significant delays when someone attempted to zoom in or pan across a video, making mobile exploration unpleasant, if not impossible. In addition, in order for the visualization to be smooth as you pan and zoom, each video that is loaded must sync to the previously playing video and begin playing automatically. But, until only recently, mobile browser vendors had disabled video autoplay at the browser level for bandwidth reasons.
Now that
mobile browser vendors have re-enabled video autoplay
, we are able to take advantage of current mobile hardware and CPU capabilities, while leveraging the pyramid mapping technique’s efficient use of data, to enable Timelapse on mobile.
Redesigning Timelapse for Exploration Across Devices
Timelapse is a tool for exploration, so we designed for immersiveness, devoting as much real estate as possible to the map. On the other hand, it's not just a map, but a map of videos. So we kept controls visible, like pausing and restarting the timeline or choosing highlights, by leveraging
Material Design
with simple, clean lines and clear focal areas.
Navigate with Google Maps using the new "Maps Mode" toggle.
To explore, you need to know where you are or where somewhere else is, so the new interface includes a new "Maps Mode" toggle that lets the user navigate with Google Maps. We also built in scalability to the timeline element of the UI, so that new features added in the future, such as lengthening the time-lapse or adding options for different time increments, won’t break the design. The timeline also allows the user to go backwards in time—an interesting way to compare the present with the past.
For desktop browsers supporting WebGL, we also added a new WebGL viewer to the open source project, which loads and synchronizes multiple videos to fill the screen at optimal resolution. The aesthetic improvement of this is nontrivial, with >4x better resolution.
What's next
We're excited about the
abundance
of freely available, openly licensed satellite imagery and remote sensing data available, enabling new visualizations across time, space, and the visual and non-visual spectrum. We've found it's often the data combined with supplemental layers, such as the
World Database on Protected Areas (WDPA) boundaries
, that can spark new insights. For example, seeing the visual connection between declining home ownership and
shifts in the city of Pittsburgh's racial makeup
tells a story about inequality that numbers on a page simply cannot.
Visual evidence
can transcend language and cultural barriers and, we hope, generate productive conversations about our global challenges.
Acknowledgements
Randy Sargent, Senior Systems Scientist, Carnegie Mellon University CREATE Lab and the Google Earth Engine team
Labels
2018
accessibility
ACL
ACM
Acoustic Modeling
Adaptive Data Analysis
ads
adsense
adwords
Africa
AI
Algorithms
Android
Android Wear
API
App Engine
App Inventor
April Fools
Art
Audio
Augmented Reality
Australia
Automatic Speech Recognition
AutoML
Awards
BigQuery
Cantonese
Chemistry
China
Chrome
Cloud Computing
Collaboration
Compression
Computational Imaging
Computational Photography
Computer Science
Computer Vision
conference
conferences
Conservation
correlate
Course Builder
crowd-sourcing
CVPR
Data Center
Data Discovery
data science
datasets
Deep Learning
DeepDream
DeepMind
distributed systems
Diversity
Earth Engine
economics
Education
Electronic Commerce and Algorithms
electronics
EMEA
EMNLP
Encryption
entities
Entity Salience
Environment
Europe
Exacycle
Expander
Faculty Institute
Faculty Summit
Flu Trends
Fusion Tables
gamification
Gboard
Gmail
Google Accelerated Science
Google Books
Google Brain
Google Cloud Platform
Google Docs
Google Drive
Google Genomics
Google Maps
Google Photos
Google Play Apps
Google Science Fair
Google Sheets
Google Translate
Google Trips
Google Voice Search
Google+
Government
grants
Graph
Graph Mining
Hardware
HCI
Health
High Dynamic Range Imaging
ICCV
ICLR
ICML
ICSE
Image Annotation
Image Classification
Image Processing
Inbox
India
Information Retrieval
internationalization
Internet of Things
Interspeech
IPython
Journalism
jsm
jsm2011
K-12
Kaggle
KDD
Keyboard Input
Klingon
Korean
Labs
Linear Optimization
localization
Low-Light Photography
Machine Hearing
Machine Intelligence
Machine Learning
Machine Perception
Machine Translation
Magenta
MapReduce
market algorithms
Market Research
Mixed Reality
ML
ML Fairness
MOOC
Moore's Law
Multimodal Learning
NAACL
Natural Language Processing
Natural Language Understanding
Network Management
Networks
Neural Networks
NeurIPS
Nexus
Ngram
NIPS
NLP
On-device Learning
open source
operating systems
Optical Character Recognition
optimization
osdi
osdi10
patents
Peer Review
ph.d. fellowship
PhD Fellowship
PhotoScan
Physics
PiLab
Pixel
Policy
Professional Development
Proposals
Public Data Explorer
publication
Publications
Quantum AI
Quantum Computing
Reinforcement Learning
renewable energy
Research
Research Awards
resource optimization
Robotics
schema.org
Search
search ads
Security and Privacy
Semantic Models
Semi-supervised Learning
SIGCOMM
SIGMOD
Site Reliability Engineering
Social Networks
Software
Sound Search
Speech
Speech Recognition
statistics
Structured Data
Style Transfer
Supervised Learning
Systems
TensorBoard
TensorFlow
TPU
Translate
trends
TTS
TV
UI
University Relations
UNIX
Unsupervised Learning
User Experience
video
Video Analysis
Virtual Reality
Vision Research
Visiting Faculty
Visualization
VLDB
Voice Search
Wiki
wikipedia
WWW
Year in Review
YouTube
Archive
2019
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2018
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2017
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2016
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2015
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2014
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2013
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2012
Dec
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2011
Dec
Nov
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2010
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2009
Dec
Nov
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2008
Dec
Nov
Oct
Sep
Jul
May
Apr
Mar
Feb
2007
Oct
Sep
Aug
Jul
Jun
Feb
2006
Dec
Nov
Sep
Aug
Jul
Jun
Apr
Mar
Feb
Feed
Follow @googleai
Give us feedback in our
Product Forums
.
