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

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Presentation on theme: "Transforming Rural Livelihoods through Location Intelligence: The Quiet Revolution in Socializing Geospatial Science Stanley Wood, IFPRI Global Coordinator:"— Presentation transcript:

1 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

2 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

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

4 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-intelligencemodeling services Validation and expert elicitation of local dataexpert elicitation ‘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)

5 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

6 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.

7 More Information s.wood@cgiar.org CGIAR Centre Representatives www.agcommons.org www.harvestchoice.org www.geocommons.com (http://csi.cgiar.org/index.asp) under reconstructionhttp://csi.cgiar.org/index.asp


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