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Crowd sourcing and high resolution satellite imagery in public health Chris Grundy [email protected] Improving health worldwide www.lshtm.ac.uk

Crowd sourcing and high resolution satellite imagery in public health

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Page 1: Crowd sourcing and high resolution satellite imagery in public health

Crowd sourcing and high

resolution satellite

imagery in public health

Chris [email protected]

Improving health worldwide

www.lshtm.ac.uk

Page 2: Crowd sourcing and high resolution satellite imagery in public health

Screen grab of Google maps around LSHTM

Page 3: Crowd sourcing and high resolution satellite imagery in public health

Screen grab of Google maps in Tanzania

Page 4: Crowd sourcing and high resolution satellite imagery in public health

Crowd source mapping

Using people around the world to collect

and map features of interest into a

central location

• OpenStreetMap (OSM) & HOT

• Missing maps

Page 5: Crowd sourcing and high resolution satellite imagery in public health

Haiti earthquake 2010

Page 6: Crowd sourcing and high resolution satellite imagery in public health

Ebola: BRC online ebola map

Source: simonbjohnson.github.io

Page 7: Crowd sourcing and high resolution satellite imagery in public health

Benefits of OpenStreetMap

• Free, simple software to map area

• Shared workload

• Speed

• Meeting “open data” requirements

Page 8: Crowd sourcing and high resolution satellite imagery in public health

Satellite imagery

• Increasing in resolution

– Very high resolution imagery (VHR) now 30cm

• Costs reducing – free in emergencies

• Widely available

Page 9: Crowd sourcing and high resolution satellite imagery in public health

It is only with local knowledge and

previous experience that we can fully

generate datasets from satellite images.

Page 10: Crowd sourcing and high resolution satellite imagery in public health

What are the features in this image

Page 11: Crowd sourcing and high resolution satellite imagery in public health
Page 12: Crowd sourcing and high resolution satellite imagery in public health

Estimating populations using

satellite images

Page 13: Crowd sourcing and high resolution satellite imagery in public health

Am Timan, Chad, 2012

Stratum 1

Stratum 2

Stratum 3

Page 14: Crowd sourcing and high resolution satellite imagery in public health

Manual structure count

• Structures located by eye

• Type of structure determined by user

– Traditional hut

– Small building

– Large building

• Grid used to ensure

systematic counting

• Count checked

– Missed features / errors

Page 15: Crowd sourcing and high resolution satellite imagery in public health

Population estimates

Page 16: Crowd sourcing and high resolution satellite imagery in public health

Experience and being systematic are

vital when producing dataset from

satellite images.

Page 17: Crowd sourcing and high resolution satellite imagery in public health
Page 18: Crowd sourcing and high resolution satellite imagery in public health

Good image

Page 19: Crowd sourcing and high resolution satellite imagery in public health

Poor image

Page 20: Crowd sourcing and high resolution satellite imagery in public health

Dispersed population

Page 21: Crowd sourcing and high resolution satellite imagery in public health

Landing site

Page 22: Crowd sourcing and high resolution satellite imagery in public health

Population Density

Area

X

Population

density

Page 23: Crowd sourcing and high resolution satellite imagery in public health

Example of sensitivity analysis

Density 1 Density 2 Variable

Uganda 370,803 311,812 316,301

Kenya 152,128 138,575 139,767

Tanzania 555,177 429,689 473,575

Total 1,078,108 880,076 929,643

Density 1: 33,874 people per km

Density 2: 28,895 people per km

High density villages: 35,598 people per km

Low density Villages: 19,533 people per km

Page 24: Crowd sourcing and high resolution satellite imagery in public health

How to avoid main problems

• Know your software

• Experience counts

• Factor problems into proposal

• Two heads are better than one

• Be systematic

• Validate the method

Page 25: Crowd sourcing and high resolution satellite imagery in public health

Thank you.