Review of the available remote sensing tools, products, methodologies and data to improve crop production forecasts

dc.creatorErick Khamala
dc.date2023-04-27T11:18:46Z
dc.date2023-04-27T11:18:46Z
dc.date2017
dc.date2017-08-14T10:16:15.0000000Z
dc.date.accessioned2026-06-27T22:01:00Z
dc.descriptionTimely and reliable agricultural production forecasts are critical to make informed food policy decisions and to enable rapid responses to emerging food shortfalls. Agricultural forecasts are increasingly important in national planning in sub-Saharan Africa (SSA) due to highly variable yield, production and consumption trends, which are in turn occasioned by high climate variability and change, rapidly increasing populations, and limited financial capacity to cope with frequent food insecurity c rises. This review examines the current status of the remote sensing (RS) tools, products, methodologies and data that can help to improve agricultural crop production forecasting systems. The review is structured in three parts: A description of the methodology used for this review; A literature review that covers four core areas, namely: an overview of the application of RS in crop production forecasting; the RS methodologies currently used in crop production forecasting; insight into the avai lable geoportals and RS data and products on crop production forecasting; and an analysis of the national agencies mandated to generate crop production statistics in the three pilot countries of Kenya, Senegal and Zimbabwe; A discussion on the key findings and the conclusions.
dc.format94 p.
dc.formatapplication/pdf
dc.identifier978-92-5-109840-0
dc.identifierhttps://openknowledge.fao.org/handle/20.500.14283/i7569en
dc.identifierhttp://www.fao.org/3/a-i7569e.pdf
dc.identifier.urihttp://hdl.handle.net/123456789/240674
dc.languageEnglish
dc.publisherFAO ;
dc.rightsFAO
dc.titleReview of the available remote sensing tools, products, methodologies and data to improve crop production forecasts
dc.titleReview of the available remote sensing tools, products, methodologies and data to improve crop production forecasts
dc.typeBook (stand-alone)

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