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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. -
Brochure, flyer, fact-sheetA rapid geospatial analysis of the flood impacts on crops in KwaZulu-Natal province of South Africa in 2022 2023
Also available in:
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 RC) water body data (2020). Sentinel 1 SAR was used to assess flood extent. -
Book (stand-alone)Wood-energy supply/demand scenarios in the context of poverty mapping
A Wisdom case study in Southeast Asia for the years 2000 and 2015
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No results found.Current (2000) and projected (2015) woodfuel consumption patterns and supply potentials in continental Southeast Asia are analysed and mapped applying the Woodfuel Integrated Supply/Demand Overview Mapping (WISDOM) methodology. Combined with poverty data, the study helps define areas where poor rural and suburban populations that depend primarily on woodfuels for their subsistence energy supply are likely to suffer severe shortages, adding an indicator to the mapping of extreme poverty a nd a new tool for poverty alleviation policies and forestry and energy development planning. Integrating several cartographic layers with multi-source field data provides maps of woody biomass stocking and potential sustainable productivity in 2000 and 2015 at a spatial resolution of less than 1 km. Woody biomass consumption maps matching the resolution of supply maps, coupled with likely population distribution in 2015 and model projections of woodfuel consumption, give future consump tion scenarios. Combining these yields balance maps of woodfuel deficit and surplus areas. This study is a starting point for expanding work in the agro-energy sector, which can benefit from the approach, the GIS analytical environment, the additional thematic layers and the nexus with forestry, energy and poverty alleviation issues.
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