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Book (series)Geospatial datasets and analyses for an environmental approach to African trypanosomiasis 2009
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No results found.Geospatial datasets and analysis techniques based on geographic information systems (GIS) have become indispensable tools in the planning, implementation and evaluation of a wide range of development programmes, including actions addressing sustainable agriculture and rural development. The growing volume of spatially explicit environmental information, combined with the widening utilization of GIS, allows ecological and socioeconomic factors to be integrated more fully into the decision-making process, thus laying the foundation for a holistic approach to development. This publication provides a cross-section of actual and potential applications of GIS in the context of interventions against tsetse and trypanosomiasis (T&T). It aims to promote the sharing of knowledge and harmonization of methodologies among the wide range of actors concerned with the T&T problem. In the first section, a selection of geospatial datasets available in the public domai n is reviewed through the lens of their possible use within T&T interventions. This review is followed by three case studies from two countries affected by trypanosomiasis (Burkina Faso and Botswana). The case studies provide examples of the application of GIS in operational scenarios and pay particular attention to data collection, management and analysis in the context of area-wide integrated management of tsetse and trypanosomiasis. -
MeetingRegional Conference for Africa - Information Document on “The Programme against African Trypanosomiasis”(PAAT)
Cairo, Egypt, 4-8 February 2002
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Brochure, flyer, fact-sheetA rapid geospatial analysis of the flood impacts on crops in Eastern Cape province of South Africa in 2022 2023
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No results found.An analysis to assess the impacts of floods on cropland in KwaZulu-Natal province was performed using existing data, GIS and remote sensing. The crop mask was derived from the South African National Land Cover map (SANLC, 2018). The water mask was derived from the Joint Research Centre (JRC) water body data (2020). Sentinel 1 SAR was used to assess flood extent.
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