global -scale analysis of earth observation data

Global-scale analysis of Earth observation data

Dave [email protected]

The Google Earth Engine

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Google Earth Engine - [email protected] - TWDG – September 28, 2010

Who are we?

- Technology-Driven Philanthropy.

Goal: Use Google's strengths in information and technology to address global challenges.

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Google’s StrengthsData management, processing, Storage, indexing & delivery.Making things simple, at scale.

Global ChallengesClimate changePandemic diseasePoverty

RE<C and RechargeITDeveloping utility scalerenewable energy cheaper than coal (RE<C) and accelerating the commercialization of plug-in vehicles (RechargeIT)

Google Power MeterGoogle PowerMeter is a home energy monitoringtool that gives you theinformation you need touse less electricity andsave money.

Google Flu TrendsGoogle Flu Trends uses aggregated Google search data to estimate flu activity in near real-time in 20 countries.

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Motivation

UNEP: "Atlas of our Changing Environment"

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Rondonia, BrazilJune 1975

Rondonia, BrazilJuly 1989

Rondonia, BrazilSeptember 2001


Challenges and GoalsAccess to Datao Cost, availability & licensing of petabyteso Raw data requires preprocessing Why should each user have to solve this on their own?

Access to Software, Algorithms, and Hardwareo What algorithms are available and where to find them?o I don’t have a cluster, what do I do?

Non-technical Challengeso Open, transparent, verifiableo Privacy and sovereignty concerns

Non-Goals• Doing global monitoring ourselves• Scientific algorithm research

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The Plan

Developing a platform for processing at scale• Inherently parallel system• Instant visualization• Promote transparency, reproducibility, reuse

Getting expertise from the experts• Avoid reinventing the (scientific) wheel• Partner with academic institutions, NGOs, indigenous people…

Providing a place to publish (or not)• Let users curate their own datasets and algorithms• Help others to find them• Or keep everything private

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Google Earth Engine - [email protected] - TWDG – September 28, 201013Demo


Very fast computation of scientific map products• Using arbitrary (user-supplied) algorithms

With some nice features • APIs for algorithm development and Web front ends• Access control, versioning, provenance• Online and Desktop versions (open source desktop version)• TIFF / KML / Fusion Tables / Google Maps

On a lot of data• Stored in their native projection• Every available Landsat scene• Every MODIS scene• Commercial datasets with cost pass-thru• User supplied data

Details

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Android phones+OpenDataKit Training: Tanzania Village Forest Monitors, TZ Forestry and Beekeeping Division, Jane Goodall Institute, Nov 2009


Each point: GPS-tagged photo, tree info, plot info, more….


…more data collected for each in-situ sample point


Dataset fromBrianHeidorn

Image from AnimalBiodiversityWeb


Niche Modeling

River health

Your Ideas

Biodiversity and Conservation

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Prediction for Triatoma barberiPeterson, et al. 2002

Upper MississippiFrom USGS


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global -scale analysis of earth observation data

Documents