Presented by Allison Lieber, Program Manager for Google Earth Outreach with Google, at the the 2017 GIS Working Group Annual Meeting.

1. Confidential + Proprietary
Google Earth Engine: Cloud-
based Geospatial Data
Analysis for Everyone
Allie Lieber, Google
allieber@google.com

2. EARTH OUTREACH
We work with
nonprofits,
indigenous groups,
educators,
scientists, and
journalists
to foster the use of
Geo tools to address
the world’s most
pressing problems.
Build Geo knowledge in the international community
A Trainer Network
An annual Geo For Good User Summit
Create lighthouse examples
Tackle a huge issue at Google scale
Premium Geo products (Maps API) to qualified orgs
Scale presence to the globe
Training & Knowledge
High-profile partner
projects
Software Grants
Online Resources

3. Google Earth Earth Engine
My Maps Tour Builder
Street View Fusion Tables
Open Data Kit
Google Maps API
THE TOOLS

4. HEALTH
Collecting georeferenced data on-the-ground
through surveillance activities and resource
deployment
Communicating health information and summary
statistics to policy and funding decision makers
Analyze climate and environmental information
along with disease data.
Teaching, planning, ...
Mobile Data Collection
Visualizations
Analysis
Others?

5. SOLUTIONS DEPEND ON
Epidemiology
Entymology
Infectious, noncommunicable
Vaccines
IRS
Sources
HTC
Burden of disease
Healthcare system
Capacity
Funding
Disease
Intervention
Context

6. Where are the highest priority
location for interventions?

7. Disease Risk Mapping Framework
Ostfeld et al 2005, TRENDS in Ecology and Evolution Vol.20 No.6

8. *
Environment
Climate
Population
Infrastructure Disease Data
Analysis &
Modeling
Decisions

9. Swaziland National Malaria Control Program/
UCSF Global Health Group
Automated Malaria Risk Mapping

11. 5/3/16

13. 6/7/15
DiSARM malaria

20. DiSARM malaria

22. 5/3/16DiSARM malaria

33. www.disarm.io

36. Google Earth Visualizations

37. 2013: Global Landsat Forest Extent and Change, 2000–2012

38. Source: NASA

40. “Often it turns out to be more efficient to move
the questions than to move the data.”
- Jim Gray
The Fourth Paradigm:
Data-Intensive Scientific Discovery

41. > 200 public datasets
MODIS
Daily, LST, NDVI ...
Terrain
SRTM, GTOPO, NED, ...
Atmospheric
CHIRPS, NOAA, ...
Land Cover
GlobCover, NLCD, ...
The Earth Engine Public Data Catalog
> 4000 new images every day
> 5 million images > 5 petabytes of data
Landsat 4, 5, 7, 8
Raw, TOA, SR, ...
… and population (world pop & GPWv4?)
... and many more, updating daily!

44. CENSUS, ~20 million road segments

45. Import your own raster & vector datasets

46. Request datasets

48. The Economist

50. Malaria
Collaborations with:
World Health Organization,
Ministries of Health in Africa,
PMI USAID

51. Schistosomiasis
Collaboration with:
World Health Organization,
Ministries of Health in Africa,

52. Schistosomiasis(a)
(d)(c)
(b)
Predicted snail habitat suitability for two snail species in Ndumo area of uMkhanyakude
district, South Africa (a) Bulinus globosus in winter (b) Biomphalaria pfeifferi in winter (c)
Bulinus globosus in spring (d) Bulinus globosus in autumn (Manyangadze et al., 2016)

53. Leishmaniasis
Collaborations with:
Médecins Sans Frontières,
South Sudan

54. Leishmaniasis
Collaborations with:
Médecins Sans Frontières,
South Sudan

55. Trypanosomiasis
Collaborations with:
World Health Organization,
Nelson Mandela University
Masai village in Tanzania affected by trypanosomiasis
John Hargrove providing expertise on tsetse
fly

56. Monitoring Tsetse Habitats for Targeting Controls

57. Dengue

59. Explore Earth Engine

60. The Earth Engine Data Catalog
code.earthengine.google.com/datasets

61. Data Catalog | CHIRPS

62. CHIRPS | What is it?
● U.S. Geological Survey (USGS) Earth Resources Observation and Science
(EROS) Center in order to deliver reliable, up to date, and more complete
datasets for a number of early warning objectives.
● Spans 50°S-50°N (and all longitudes)
● Started in 1981 to Feb 2016
● Incorporates 0.05° resolution satellite imagery with in-situ station data to
create gridded rainfall time series for trend analysis and seasonal drought
monitoring.
● Learn more: chg.geog.ucsb.edu/data/chirps/

63. Precipitation for Africa CHIRPS (FEWS Net) daily data set
from 1981 to present at 5km spatial resolution

64. CHIRPS | Background
Developed for
● Assessing precipitation at national, regional and local scale
● Evaluating the seasonality of precipitation
● Identifying regions where precipitation have increased or decreased
(precipitation anomalies)
Not for
● Predicting precipitation in the coming season/year
● Investigating disasters caused by factors other than the distribution of
precipitation.

65. Let’s view it in the code editor
code.earthengine.google.com

66. The Earth Engine Code Editor
Your Scripts &
Example Scripts
API Docs
Your Assets Search Your Code Data Inspector
Batch Tasks
Output Console
Drawing Tools Output Map
code.earthengine.google.com

67. Load and Filter CHIRPS Data
● Search “chirps” and hover over the result “CHIRPS: Climate
Hazards Group InfraRed Precipitation with Station data (version
2.0 final)”
● Click “import >>”

68. Name your variable
● Rename the variable chirps

69. Inspect it

70. CHIRPS | Inspecting
● What is the spatial scale?
● What is the temporal cadence / sampling period?
● How many bands?
● Where can you find out more?

71. Filter and Map CHIRPS Data
Filter chirps ImageCollection to only the 2016 calendar year
//Load and filter chirps data
var chirpsYear = chirps.filterDate(‘2016-01-01’, ‘2016-12-31’);
//Add it to the map, labeled chirpsYear
Map.addLayer(chirpsYear, {}, ‘chirpsYear’);
This is called camelCase

72. Use “Inspector” tab to Inspect Image Data

73. CHIRPS | Visualizations

74. Temperature
● Air Temperature
● Land Temperature
● Daytime
● Nighttime

75. MODIS Land Surface Temperature | Background
● The Moderate Resolution Imaging Spectroradiometer (MODIS) is an instrument
carried by NASA’s Aqua and Terra satellites.
● It captures images of Earth’s surface in 1-2 day intervals in 36 spectral bands.
● The spatial resolution is 1000m, and the data extends from March 5, 2000 to
the present.
● MODIS images can be used to analyze land surface changes over time,
including land surface temperature.
Limitations: The Terra and Aqua satellites were launched in 1999 and 2002,
respectively. Therefore, the tool can only be used for analyzing temperature data
from March 5, 2000 to the present, with about a month delay between satellite
imaging and availability of data. It cannot be used for future temperature

78. Time of overpass for Aqua
0 to 2 am
2.30 to 6 am

79. Time of overpass for Terra
2 to 4 am
4 to 6 am 1 to 6 am

80. Temperature | Inspecting
● Select “000 Inspecting Temperature”
● Hit “Run”
● Use the inspector
● Change visualizations parameters on
the two layers

81. Vegetation | NDVI
NDVI = Normalized Difference Vegetation Index
● NIR channel: Cell walls reflect NIR → high reflectance values = high quantity of
biomass
● Red channel: Chlorophyll absorbs Red (photosynthesis) → lower Red
reflectance and greener vegetation
Normalize the difference (NIR - Red) between them to determine NDVI

82. Confidential + Proprietary
NDVI = 0.1
NDVI = 0.1

84. Confidential + Proprietary
NDVI =
(Near Infrared - Red)
(Near Infrared + Red)

85. NDVI | Isoline

86. NDVI | Tropical Forest
High NIR reflectance
Low Red reflectance

87. Less chlorophyll
Higher
Biomass
NDVI | .1 could be sparse veg or bright soil

88. Other examples

89. Population

90. Global Accessibility Map (under review)

91. Image credit: New York Times

93. Image of JRC water map
Find locations of Iran and Himalayans

94. Image of JRC water map
Find locations of Iran and Himalayans

95. http://www.sciencedirect.com/science/article/pii/S0034425715001637

101. Confidential + Proprietary
earthengine.google.com/signup
Thank you!
allieber@google.com