Using ICT for remote sensing, crowdsourcing, and big data to unlock the potential of agricultural data

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cg.authorship.typesCGIAR single centreen
cg.contributor.crpPolicies, Institutions, and Markets
cg.contributor.donorBill & Melinda Gates Foundationen
cg.creator.identifierCindy Cox: 0000-0003-4837-969X
cg.creator.identifierJawoo Koo: 0000-0003-3424-9229
cg.identifier.projectIFPRI - Environment and Production Technology Division
cg.identifier.publicationRankNot ranked
cg.identifier.urlhttps://hdl.handle.net/10986/27526en
cg.placeWashington, DCen
cg.reviewStatusInternal Reviewen
dc.contributor.authorWoodard, Joshen
dc.contributor.authorAndriessen, Mechtelden
dc.contributor.authorCohen, Courtneyen
dc.contributor.authorCox, Cindy M.en
dc.contributor.authorFritz, Steffenen
dc.contributor.authorJohnson, Drewen
dc.contributor.authorKoo, Jawooen
dc.contributor.authorMcLean, Morvenen
dc.contributor.authorSee, Lindaen
dc.contributor.authorSpeck, Taraen
dc.contributor.authorSturn, Tobiasen
dc.date.accessioned2024-06-21T09:25:07Zen
dc.date.available2024-06-21T09:25:07Zen
dc.identifier.urihttps://hdl.handle.net/10568/148583
dc.titleUsing ICT for remote sensing, crowdsourcing, and big data to unlock the potential of agricultural dataen
dcterms.abstractBy 2050, the global population is projected to reach approximately 9 billion. Population growth will be concentrated in poorer countries, particularly the low-income countries of Sub-Saharan Africa. By some estimates, agricultural productivity will need to double to meet everyone’s needs for food (Foley 2014). For instance, if current trends continue, yields of the world’s foremost food crops—maize, rice, wheat, and soybeans, which supply roughly two-thirds of calories consumed globally—appear likely to grow significantly more slowly than required to meet the projected global demand in 2050 (Ray et al. 2013). Some productivity growth will come from using more of the world’s arable land for agriculture, but most of the available arable land is unevenly distributed, and about half of it is found in only seven countries.en
dcterms.accessRightsOpen Access
dcterms.bibliographicCitationWoodard, Josh; Andriessen, Mechteld; Cohen, Courtney; Cox, Cindy M.; Fritz, Steffen; Johnson, Drew; Koo, Jawoo; McLean, Morven; See, Linda; Speck, Tara; and Sturn, Tobias. 2017. Using ICT for remote sensing, crowdsourcing, and big data to unlock the potential of agricultural data. In ICT in Agriculture (Updated Edition) : Connecting Smallholders to Knowledge, Networks, and Institutions, World Bank. Section 4: Improving Public Service Provision, Module 15, pp. 401-431. Washington, DC: World Bank. https://hdl.handle.net/10986/27526en
dcterms.issued2017
dcterms.languageen
dcterms.licenseCC-BY-3.0-IGO
dcterms.publisherWorld Banken
dcterms.replaceshttps://ebrary.ifpri.org/digital/collection/p15738coll5/id/5898en
dcterms.subjectinformation technologyen
dcterms.subjectagricultural growthen
dcterms.subjecttelecommunicationsen
dcterms.subjectagricultureen
dcterms.subjectagricultural developmenten
dcterms.subjectinformation and communication technologiesen
dcterms.typeBook Chapter

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