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Brochure, flyer, fact-sheetA rapid geospatial analysis of the flood impacts on crops in KwaZulu-Natal 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 RC) water body data (2020). Sentinel 1 SAR was used to assess flood extent. -
Book (stand-alone)A rapid geospatial analysis of the flood impacts on crops in KwaZulu-Natal and Eastern Cape provinces of South Africa in 2022 2022
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No results found.South Africa is the southern most country on the African continent with the 121 309 ha of land area and highly dependent on agriculture sector (79 percent of agricultural land area) for food, income, and employment. Natural disasters like drought, floods, storms, cyclones etc. causes significant socio-economic damages and losses, as well as negatively impacting the agricultural sector. From 11–13 April 2022, heavy rainfall caused severe flooding and landslides affecting the south and south-eastern part of South Africa. Particularly, in the Provinces of KwaZulu-Natal and Eastern Cape, authorities reported loss of lives, infrastructure damages and inundated cropland. Disaster Charter 755 was activated for South Africa. From 19–20 April, moderate rainfall waa forecast over north-eastern South Africa, while no heavy rainfall was expected over the already affected Provinces. In this context, the Food and Agriculture Organization of the United Nations (FAO) Geospatial Unit of the Land and Water Division (NSL) with support from SFS REOSA conducted a rapid geospatial assessment on crops and the exposure of rural people during the period 10–20 April 2022. This assessment provides information at the district, local municipalities and ward levels in the area of interest (AOI). This analysis combines Sentinel 1 (S1) Synthetic Aperture Radar (SAR) and Sentinel 2 (S2) imagery (both at a 10 m spatial resolution) with Planet imagery (5 m spatial resolution) and 2020 population data from Worldpop (100 m spatial resolution) to determine: (1) flood extent; (2) cropland area; (3) flooded crop area; and (4) exposure of population to flooded cropland. The results are provided in the form of maps by administrative units and tabular with descriptive statistics for the aforementioned indicators. With recent advances in geospatial and information technologies and updated land cover maps, crop specific information adapted to national conditions with tailored field campaigns have the potential to better support response programmes and agricultural development in the future. The key findings from this rapid assessment are that for Area of Interest (AOI): 1) total flooded area in the Province of Eastern Cape is 373 868 ha and in the Province of KwaZulu-Natal is 137 601 ha; 2) total cropland area estimated in Area of Interest is 1 386 941 ha; 3) overall inundated cropland is 51 601 ha (4 percent of the total land in AOI); and 4) the most affected districts in respect to people exposure to floods are Cacadu (54 616). -
BookletA rapid geospatial analysis of the impact of the Tropical Cyclone Gombe in Mozambique in 2022 2022
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No results found.Mozambique was hit by Tropical Storm Ana on 24 January 2022 and Tropical Cyclone Gombe on 11 March 2022. These extreme weather events caused floods, damages to infrastructure (including roads and electricity poles), the evacuation of several thousands of people to temporary shelters, and the deaths of dozens of people. Furthermore, agriculture in these areas of the country was significantly impacted. Since the beginning of the rainy season up till now, it is reported that a total 220 425 hectares of crops have been lost (OCHA, 2022d). This analysis builds on FAO experience in assessing impacts from natural hazards to the agricultural sector and highlights the importance to of regularly updating geospatial information for vulnerability and impact assessments in support to preparedness and response programs. The accuracy of the results provided can be improved by combining additional information, such as agricultural statistics, and field data.
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