Quantifying Error in Training Data for Mapping and Monitoring the Earth System - A Workshop on “Quantifying Error in Training Data for Mapping and Monitoring the Earth System” was held on January 8-9, 2019 at Clark University, with support from Omidyar Network’s Property Rights Initiative, now PlaceFund.

1. Sources of Map Error
in Public Health Activities
and Operations Research
Victoria M Gammino
Radiant Earth Foundation
8 January 2019

2. About Us
Key facts
 Non-profit organization, founded in 2016 with funding
from Omidyar Network and Gates Foundation
 Back-end infrastructure for global development
organizations providing open source imagery and ML
tools
 Neutral convener
 Collaborative & Sector-agnostic

3. Core Public Health Functions Investigative Activities
- Disease surveillance &
detection
- Outbreak /emergency
response
- case-finding
Link To/ Provide Care
- Service delivery
- population estimation
- supply chain logistics

4. CASE STUDY: Polio Eradication
Four-part strategy
- Routine immunization coverage
- (x4 in 14 weeks)
- Laboratory surveillance/case detection
- Outbreak response (targeted campaigns)
- 80% coverage all kids < 5
- House-to-house
- Strategic public places
- Mass immunization coverage
o Population size
o Location
o Terrain

5. Role of Satellite Imagery & GIS
Satellite Imagery
 Facilitates feature extraction to identify settlements and temporary
encampments missed in « manual » microplanning based on local
knowledge
 Visualize jurisdictional boundaries
 Increase awareness of environment to improve logistical efficiency
based on terrain and distance
Direct Impact on Microplanning
 Assure that all settlements incorporated into written plans
 Advocacy to assure adequate resources

6. in the absence of census data & current shp files

7. Mapping in the Polio Context
(and its relationship to groundtruthing)
Logistical plans for field operations crafted
at the lowest level of health service
administration and data aggregated
upwards
However,
Field operations are implemented at the
lowest administrative level
Systematic bias
Behavioral bias

9. Rationale: “not our area”

10. Systematic Errors

11. Sakwaya Ward
Kachi Ward
J/Tsada Ward
Missed Settlements
Map/data credit: Vince Seaman

12. “Border Settlements”
~40% cases

13. 13
o Literacy/numeracy
o Redundancy
o Map reading
Qualitative | Behavioral | Perceptual
Non-systematic Bias
| Perceptual
o POIs measurement bias
(distance, movement)

14. o Fear
o Insider knowledge-- > wrong KIs?
o [Consensus analytics to validate
intra-cultural knowledge a.k.a,
“expert opinion”]
Large surveys
o Response bias (e.g., opportunity
cost or cost implications)
Non-systematic Bias (2)

15. Discrimination|otherness
Quantified:
2 vs 14 settlements
68 vs ~1200
Saliency/ social construction
“no man’s land”

16. Visual balance (benign); “canvas compliance”

17. 17
Intentional “balancing”
-Concerns about
equity and pay

18. This is a photo of the map that was used in an exercise to gather
village location information. The map has very little detailed
information for reference to place new village locations. The new
locations are shown written in pencil.
The map is improved by adding detailed data. This map shows
Facebook grid data (red) lining up with more detailed road
data (black), which improves accuracy in placing points. The
written in points are shown in purple and are now aligned with
the more detailed data.
Imagery was also used to verify the presence of structures,
in addition to the Facebook grid data. The image also
shows the new road data (in black) aligning to the road in
the image.
Mozambique vDPV2 outbreak, 2017

19. Context, context, context
In emergency, bang for buck
Solutions from Anthro/ Sociology/Other disciplines
Consensus Analytics for KIs
Hybrid methods
Grand Tour / Transects
Mnemonic prompts
Communicating w/ visuals and analogies

20. More about Radiant Earth Foundation
Additional References | Info

21. Why we exist
DISCOVERY
1
COMPLEXITY2
COSTS
3
Problem
Our Solution
Opportunity
• Increase in imagery and
tools
• New technologies such as
machine learning and
cloud computing
Facilitating access to imagery
and data analytics to enable
the global development
community to address
challenges
Global Development
Community needs
data and tools but
often has the least
access to it

22. Vision & Mission
 Open Geospatial Data for Positive Global Impact
 Connecting people globally to Earth Imagery, geospatial data, tools and knowledge
to meet the world’s most critical challenges

23. Mission Critical Support
Food Security &
Agriculture
Property Rights
Humanitarian
Response
Global Health
Conservation,
Forestry &
Environment
WaterPoverty Reduction Climate Change
Transparency &
Journalism

24. What we do
Provide Open Access to Earth Imagery &
Tools
Provide Education on Geospatial Data &
Tools
Provide Remote Sensing Use Case
Analytical Support & Advise of
Procurement of Commercial Products
Technology Platform Community Development Consultancy

25. 25
Polio Campaign Dashboard
2011-2013 WHO, NPHCDA AND NSTOP
Expanded use of GPS tracking to quantify SIA
performance (%%)
Barau, et al, 2014 J Infect Dis. (2014) 210 (suppl 1): S102-S110
http://vts.eocng.org/GeoCoverage/Lga?campaignId=26&day=7&lgaCode=804

26. Hybrid: Grand Tour/Transect
Interactive technique using interviews and guided tour to document community features and or
boundaries with photographs and geotags according to key informant priorities, or systematically
by identifying and maintaining a pre-determined pathway through the community.
+ Combines geotagged data with key informant-identified
Priorities
+ More accurate than hand-drawn
- Vulnerable to key informant bias in determining “what’s
important”
- Limited by informants’ knowledge of the community and
Terrain

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