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Poverty Mapping in Uganda: An Analysis Using Remotely Sensed and Other Environmental Data










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    Poverty mapping in Uganda: Extrapolating household expenditure data using environmental data and regression technique 2011
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    This ‘Working Paper’ series pulls together different strands of work on the wide range of topics covered by the Animal Production and Health Division with the aim of providing ‘fresh’ information on developments in various regions of the globe, some of which is hoped may contribute to foster sustainable and equitable livestock sector development.The work described in this paper follows directly on from earlier attempts to develop a novel approach to mapping poverty using environmental data. The aim was to get closer to understanding some of the underlying causes of poverty – something that is unlikely to be feasible using approaches based only on socio-economic data such as the traditional small area estimate (SAE) techniques. The environmental poverty mapping technique involved modelling geo-registered household expenditure estimates in Uganda, available from household surveys, using discriminant analysis of a range of environmental data – mostly derived from satellite remote sensing. This analysis was successful, resulting in a series of poverty maps and lists of environmental variables that were strongly correlated with poverty at different spatial resolutions.
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    Groundwater search by remote sensing: A methodological approach 2003
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    In the framework of the technical assistance provided to the Groundwater Unit (GWU) of the FAO-implemented IRAQ/SCR/986 "Three-year Agricultural Programme" for the three Iraqi Northern Governorates, a comprehensive remote sensing/GIS methodology was developed to identify potential sites for groundwater exploitation. The approach used in the study was a development of the traditional standard sequence of drainage, landforms, cover and lineaments analyses, to which several improvements and addit ions were made, such as: (1) all data were in digital format and stored in a geo-database as GIS layers; (2) all analyses and interpretations were performed directly from the computer screen; (3) on the basis of a previous positive experience, thermal lineaments analysis was performed; (4) a comprehensive geo-database was created including all GIS layers which were considered of interest for the study; (5) by using the potentiality of GIS software, which allows stacking of georeferenced data f or comparison and integration and data query for subsetting the needed information, selected layers of the database were superimposed on the Landsat image kept as background and a logical series of observations was made, leading to a well-substantiated set of interpretation assumptions. The creation of a GIS database, including the data format and entry, is a time-consuming and laborious exercise, as high accuracy is definitely mandatory. However, once the database is complete, interpretation of features leading to selection of promising sites for groundwater search is carried out easily and quickly. This as a result of data availability of all needed information in a GIS environment. Thirty test areas, selected by the field team, were investigated and 198 promising sites were identified for further ground survey and subsequent drilling.
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    Remote sensing for space-time mapping of smog in Punjab and identification of the underlying causes using geographic information system (R-SMOG) 2020
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    Food and Agriculture Organization of the United Nations, Pakistan initiated the Technical Cooperation Programme on Remote Sensing for Spatio-Temporal mapping of Smog (R-SMOG)   upon the request of the Government of Punjab. The R-SMOG evaluates the relationship between Smog and the rice residue burning practices by farmers in the Rice belt of Punjab. It is a comprehensive geospatial research which integrates Spatio-temporal mapping of smog viz-a-viz climatological modelling, study of seasonal trends and dynamics and estimates an inventory of sectoral emissions. The findings of the R-SMOG will assist to generate scientific evidences to study the causes of Smog in Punjab and to adopt adequate mitigation and adaptation strategies.

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