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Transforming Rural Livelihoods through Location Intelligence: The Quiet Revolution in Socializing Geospatial Science Stanley Wood, IFPRI Global Coordinator: CGIAR Consortium on Spatial Information (CSI) Co-PI: HarvestChoice Steering Committee Member: AGCommons ICTs transforming agricultural science, research & technology generation Science Forum Workshop Theme 3

Transforming Rural Livelihoods through Location Intelligence: The Quiet Revolution in Socializing Geospatial Science Stanley Wood, IFPRI Global Coordinator:

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Transforming Rural Livelihoods through Location Intelligence:

The Quiet Revolution in SocializingGeospatial Science

Stanley Wood, IFPRI

Global Coordinator: CGIAR Consortium on Spatial Information (CSI)Co-PI: HarvestChoice

Steering Committee Member: AGCommons

ICTs transforming agricultural science, research & technology generation

Science Forum Workshop Theme 3

Definitions & Examples• Location Intelligence: The place-specific insights gained by

organizing and analyzing complex phenomena using geographic attributes and relationships found in all information.

By combining geographic- and location-related data with HH data, rural poor (especially) can gain new insights, make better decisions, and fine tune important processes and applications.

Examples: best varieties & planting windows; best practices; local prices; input availability; marketing opportunities (product, land, machine, labour); infrastructure siting & design, investment targeting

Driving Forces• Rapid growth in converging & mutually supporting

infrastructure/hardware platforms: $1 GPS chips; low-power rugged PDAs; cell phone networks; fiber-optic cable; nanotechnologies; private & developing country RS expansion; resolution, spectral, repeat, processing & access; advanced servers & cloud/grid computing.

• Explosion of “neogeography” business & consumer-oriented, geospatial applications & tools: Google, Bing; FOSS & OpenGIS; Satnav & visualization tools, “Mash-ups”, links to, e.g., photo/doc data & models. Web-based spatial data sharing, value-addition, e.g., Geo commons.

• Socializing of Geography; GPS ubiquity; Web 2.0 linkages; increasingly spatially-aware public as GIS/RS technicians/consumers, crowdsourcing (Openstreetmap)

Development Opportunities• Enhanced two-way flow of timely, highly-targeted, location-

specific and location-intelligent information, e.g., use of CG outputs in “last 10km”

• Value-addition by integration/synthesis/modeling services & delivery of location-intelligence

• Validation and expert elicitation of local data• ‘Public as sensors’ lay data collection, e.g., Kenya: cell phone

a/c credited for delivered data points• More RS for land use, production, environmental systems,

infrastructure, M&E (change detection), statistics (crop system area & yield detection).

• Value chain spatial tracking (safety, certification)

Science & Development Issues• Critical gaps in understanding current and potential location-specific

& time-specific user information needs. • Licensing strategies to promote public goods sharing & attribution,

& promote innovation by public & private sector• Protocols for respecting privacy of individuals and households• Cell/web access limits (coverage/bandwidth) in rural areas• ICT access impacts on power structures (PPGIS lessons)• Integration of socio-economic data (especially with rapidly changing

administrative boundaries)• Enabling local institutional capacity for service provision• Quality assurance strategies with crowd-sourced data• Business models for sustainable location-intelligence service

provision

Location Intelligence & CGIAR MPs• Enabling Environment: Critical need for support for awareness &

capacity development, sustain internal CoP linked to key partners, foster the harmonization & sharing of data, tools, protocols. Assess need to develop and sustain shared spatial infrastructure (Actors include; CSI, ICT/KM, AGCommons)

• Cross-cutting Geospatial Service Provision: “Plug and P(l)ay” geospatial service modules/capacities supporting individual MPs; map visualization, strategic geographic targeting, spatial sampling design, location-intelligent value adding services, scaling-up/out location-specific research

• Advanced Location-intelligent Research Methods: Increased embedding of spatial analysis tools into the general research armoury of MP researchers to improve robustness and significance of research findings.

More Information• [email protected]

• CGIAR Centre Representatives

• www.agcommons.org

• www.harvestchoice.org

• www.geocommons.com

• (http://csi.cgiar.org/index.asp) under reconstruction