Global Roads Data: A Strategy for Development

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Global Roads Data A Strategy for Development

• Results of the Global Roads Workshop, 1-3 October
  2007 Lamont Campus of Columbia University,
  Palisades, NY
• Alex de Sherbinin
• Center for International Earth Science
  Information Network (CIESIN)
• The Earth Institute at Columbia University

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Outline

1. The goal
2. The need
3. Approaches to data development
4. A new global product
5. CODATA working group
6. Questions for APAN participants

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1. The goal

• A global roads data base that has
• improved geographic and temporal coverage,
• consistent coding of road types, and
• good documentation of sources
• Available free-of-charge on an attribution only
  basis (i.e., public commons)
• Nominal scale of 1250,000

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Example of a 1250k product
Source ViaMichelin at http//www.viamichelin.com/
viamichelin/int/dyn/controller/Maps
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The ideal product
1250k scale Major travel routes only. Not
urban streets Attributes for road type,
surface, and road use Metadata on sources,
purpose, timeliness and restrictions Verificatio
n of accuracy Consistent classes between
countries Connectivity between
borders/tiles Update frequency at least every 5
years, and preferably on rolling basis
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2. The need

• There is currently no globally consistent,
  reasonably complete, roads data product available
  to the development, disaster response, health,
  conservation, and research communities
• Best available is VMAP, produced by the U.S.
  National Geospatial Intelligence Agency (NGA)
• Covers only 25-30 of the global roads network
• Little documentation of sources or verification
  of spatial accuracy
• More data exist but no release is anticipated

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VMAP0 vs. Intl Road Statistics
/ road network (IRF) coverage, km per country
VMAP 0
Source Andy Nelson, JRC
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VMAP0 vs. Intl Road Statistics
/ road network (IRF) coverage, km per country
VMAP 0
Source Andy Nelson, JRC
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VMAP1 publicly released data
- complete or almost complete countries
VMAP 1
22 / 4
Source Andy Nelson, JRC
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International Steering Committee for Global
Mapping (ISCGM) has completed the following
Source Andy Nelson, JRC
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User needs

• Pre- and post-disaster planning
• Economic development
• Environment and land use
• Research community
• Private sector

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Disaster response
The map at left of travel time costs owing to a
major flood in 2006 in the Horn of Africa region
shows the value of combining road network data
with digital elevation models (DEMs), flood
remote sensing or meteorological data in order to
plan for flood response, or to allocate
additional travel time in the event of floods
coupled with some other emergency. Bad road data
will affect the validity of the results.
Produced by Paul Bartel, HIU, US State Dept.
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Development policy
The map at left represents an accessibility map
based on low resolution/poor quality roads data,
and the map at right represents an accessibility
map for the same region based on high
resolution/high quality roads data. Allocation of
development resources based on the roads data at
left would not yield optimal results, since some
of the apparently most inaccessible regions
actually have dense road networks.
Source Glenn Hyman, CIAT
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Biodiversity conservation
Road expansion and improvement increases the farm
gate price of commodities such as beef, soybeans
and palm oil, and is a powerful economic
incentive for the expansion of plantations on the
forest frontier. These products are also under
increasing global demand as food products and
biofuel feed stocks. Conservation planning with
better knowledge of road networks can diminish
the cost of trade-offs between biodiversity
conservation and the expansion of livelihood
opportunities in agriculture and forestry.
Source Vera-Diaz et al. (forthcoming).
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3. Approaches to developing the data

• Mix-and-match approach
• Buy from private sector
• Military sources (e.g., NIMA)
• Crowd sourcing, e.g. OpenStreetMap
• Create a new data product

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Mix-and-match approach

• Pros
• Can be accomplished quickly at relatively little
  cost
• Cons
• Lack of consistent coverage among countries
• Problems with matching networks at borders
• CIESINs SEDAC plans to develop a catalog and to
  carry out preliminary evaluation of available data

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Mix and match approachCombining available
national-level data
Total 105 countries, 67 by area, 59 by
population
Multiple sources including VMAP1, Global Map,
CGIAR, World Bank DEC-RC, FAO Geonetwork, and
others found by Andy Nelson
105/59
Source Andy Nelson, JRC
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Buy from private sector

• Held conversations with Teleatlas
• Willing to engage in data development
  partnerships with a limited number of users
• Unwilling to sell a skeletal map or earlier
  version without restrictions on further use
• Data for developing countries are still
  relatively sparse
• Economist risk of digital map monopoly by
  Navteq Teleatlas in the navigation map arena

Economist, Location, Location, Location,
October 4, 2007
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Military sources

• Main obstacle is military/intelligence community
  is not committed to public commons approach
• Portions of their data which are available (e.g.
  VMAP1 tiles) may be useful for validation

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Crowd sourcing

• Pros
• Many hands make light work
• Openstreetmap a successful model of this
  approach
• Cons
• Poor quality control
• Fewer inputs in low income countries

www.openstreetmap.org
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Create a new product

• Pros
• Develop a consistent, well documented product
• Methods for integrating multiple source data have
  been developed by Georigin for data-poor Africa
• Build on top of this for future updates
• Cons
• The cost will likely be gt US1million
• Bringing the approach to scale

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Georigin approach
Example form Nigeria A Russian 1200 000
topographic map at left (georeferenced, cropped,
datum shifted to WGS84) can be integrated with
data from Landsat 7 (geometrically enhanced with
GPS ground control points) and GPS tracks at
right to produce a road map. Source John Dann,
Georigin, Ltd.
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4. Specifications for a new global product

• Terminology and Classification
• Data model building on on UN Spatial Data
  Infrastructure specifications.
• Each road segment will include information on its
  provider, its collection date as well as an
  indication of data quality and reliability.
• Initially, only information on primary, secondary
  and tertiary roads will be collected.
• Database structure and functionality
• The database would be structured so as to allow
  basic network analysis and routing functions in
  addition to cartographic representation.
• This implies ensuring topological consistency in
  the data, as well as the ability to establish
  connectivity with external data layers such as
  settlements and other transportation networks.
• The database would be structured in order to
  allow versioning and maintenance of a historical
  archive of the evolution of global road networks.

These would include deriving macro and
meso-level transport costs, optimal routes
between population centers, contingency plans in
case of shocks to the network and optimized road
rehabilitation investment decisions.
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Data model
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Approach proposed at first Global Roads Workshop
October 2007

• A combination of the following data sets will be
  used to manually digitize roads and attributes
  according to the data model described above.
• Scanned 1200,000 paper maps developed by the
  Russian military (ranging in dates from the late
  1960s to the early 1980s) and the US Joint
  Operations Graphic (JOG) navigation maps.
• Geocover Landsat pansharpened 15m imagery
  baselined to the year 2000, which are
  orthorectified and are available free of charge.
  
• GPS tracks wherever available to add the most
  recent routes.
• Roads will be manually digitized and attributes
  assigned according to a data model.
• Digitization could occur anywhere assuming a
  suitable tool and management structure is
  developed

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5. CODATA working group

• A working group has been proposed under ICSUs
  Committee on Data (CODATA)
• This group will oversee quality control and move
  the process forward
• Representatives of CIESIN (myself) and UN Joint
  Logistics Centre (Olivier Cottray) serve as
  co-chairs

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CODATA working group members
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6. Questions for the APAN participants

• Let us know how you might be able to contribute
• Improved methodologies
• National roads data sets for inclusion in the
  catalog
• Funding opportunities
• Suggestions regarding low cost but reliable/well
  managed click worker shops in Asia

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For more information on the Global Roads Data
workshop and the overall strategy, visit

• http//www.ciesin.columbia.edu/confluence/display/
  roads