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Hany Abo-El-Wafa Kumelachew Yeshitela Stephan Pauleit 《Geografisk tidskrift / udgivet af Bestyrelsen for Det Kongelige danske geografiske selskab》2017,117(2):68-81
AbstractThe built-up area of Addis Ababa and its surrounding towns is expanding into the peri-urban region leading to high losses of farmland, directly influencing the food production for the urban population. This paper investigates the patterns of settlement growth in the region surrounding Addis Ababa and their impact on peri-urban agriculture using an urban spatial scenario design model. The effects of two population density scenarios are explored within the framework of a proposed master plan. The model output was used to estimate areas of different suitability levels that would be lost to the modelled settlement expansion. The settlement area in 2038 would represent 29% of the case study’s total area in the low-density scenario but only 19% in the high-density scenario. Compared to the low-density scenario, the high-density scenario would only require a third of the agricultural land transformed into settlement areas. Settlement development would contribute to higher losses of land suitable for cultivating important export products, high nutritional value and import-substituting products. The scenario approach can support sustainable regional planning for settlement expansion that conserves valuable farmland in the peri-urban area and contributes to building capacity for strategic planning of the city regions of sub-Saharan Africa. 相似文献
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GeoJournal - Land-use and land-cover (LULC) changes have been recognized universally as fundamental constituents of global biodiversity and ecosystem services change driver. The objectives of this... 相似文献
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Fatemeh Jalayer Raffaele De Risi Francesco De Paola Maurizio Giugni Gaetano Manfredi Paolo Gasparini Maria Elena Topa Nebyou Yonas Kumelachew Yeshitela Alemu Nebebe Gina Cavan Sarah Lindley Andreas Printz Florian Renner 《Natural Hazards》2014,73(2):975-1001
Identifying urban flooding risk hotspots is one of the first steps in an integrated methodology for urban flood risk assessment and mitigation. This work employs three GIS-based frameworks for identifying urban flooding risk hotspots for residential buildings and urban corridors. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas and urban corridors [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. A maximum likelihood method (MLE) is employed for estimating the threshold used for identifying the flood-prone areas (the TWI threshold) based on the inundation profiles calculated for various return periods within a given spatial window. Furthermore, Bayesian parameter estimation is employed in order to estimate the TWI threshold based on inundation profiles calculated for more than one spatial window. For different statistics of the TWI threshold (e.g. MLE estimate, 16th percentile, 50th percentile), the map of the potentially flood-prone areas is overlaid with the map of urban morphology units, identified as residential and urban corridors, in order to delineate the urban hotspots for both UMT. Moreover, information related to population density is integrated by overlaying geo-spatial census datasets in order to estimate the number of people affected by flooding. Differences in exposure characteristics have been assessed for a range of different residential types. As a demonstration, urban flooding risk hotspots are delineated for different percentiles of the TWI value for the city of Addis Ababa, Ethiopia. 相似文献
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