BackgroundThe aim of this study was to determine if remotely sensed data and Digital Elevation Model (DEM) can test relationships between Culex quinquefasciatus and Anopheles gambiae s.l. larval habitats and environmental parameters within Internally Displaced People (IDP) campgrounds in Gulu, Uganda. A total of 65 georeferenced aquatic habitats in various IDP camps were studied to compare the larval abundance of Cx. quinquefasciatus and An. gambiae s.l. The aquatic habitat dataset were overlaid onto Land Use Land Cover (LULC) maps retrieved from Landsat imagery with 150 m × 150 m grid cells stratified by levels of drainage. The LULC change was estimated over a period of 14 years. Poisson regression analyses and Moran's I statistics were used to model relationships between larval abundance and environmental predictors. Individual larval habitat data were further evaluated in terms of their covariations with spatial autocorrelation by regressing them on candidate spatial filter eigenvectors. Multispectral QuickBird imagery classification and DEM-based GIS methods were generated to evaluate stream flow direction and accumulation for identification of immature Cx. quinquefasciatus and An. gambiae s.l. and abundance.ResultsThe main LULC change in urban Gulu IDP camps was non-urban to urban, which included about 71.5 % of the land cover. The regression models indicate that counts of An. gambiae s.l. larvae were associated with shade while Cx. quinquefasciatus were associated with floating vegetation. Moran's I and the General G statistics for mosquito density by species and instars, identified significant clusters of high densities of Anopheles; larvae, however, Culex are not consistently clustered. A stepwise negative binomial regression decomposed the immature An. gambiae s.l. data into empirical orthogonal bases. The data suggest the presence of roughly 11% to 28 % redundant information in the larval count samples. The DEM suggest a positive correlation for Culex (0.24) while for Anopheles there was a negative correlation (-0.23) for a local model distance to stream.ConclusionThese data demonstrate that optical remote sensing; geostatistics and DEMs can be used to identify parameters associated with Culex and Anopheles aquatic habitats.

The study was conducted in Busoro Sub County in Kabarole District to assess the physical and economic suitability of the land for Tea, Maize and Bananas. Physical suitability was evaluated using a soil map of the study area. Soil types with their parameters of Cation Exchange Capacity, base saturation, pH, organic matter, nitrogen, potassium, and phosphorous were studied. The climate of the area was studied using annual monthly rainfall and temperature values for the area for more than thirty years. Production costs, market prices and annual yields per hectare for tea, maize and bananas were computed. Using Net Present Value approach, the economic suitability of each crop was computed. The economic and physical parameters were entered into a model built in Automated Land Evaluation System (ALES) software using the decision trees. Overall suitability evaluation results were produced for each of the respective crops. The results of the study indicated that different soil types (management units) had varying suitability among the three crops. Tea registered higher overall economic suitability followed by Bananas and then Maize. However, Bananas presented a higher overall physical suitability on all soil types followed by Tea and Maize. The study recommends conducting a mini agro-ecological zonation in planning and decision for maximum utilization of the land resources for a potential LUT is an important tool in ensuring improved agricultural livelihoods and household income.

Realizing sustainable livelihood and food security in refugee situations is often an overwhelming challenge. The focus of this study was on ensuring food self-reliance in Kiryandongo refugee settlement in Uganda. The study employed a multimethod approach, that is both qualitative and quantitative methods were used. A cross sectional survey design was used and primary data was collected using questionnaires and in-depth interview. Experimental method was used in analyzing soil samples for soil organic matter content, soil moisture and soil depth. Suitability classes were derived for each of the assessed variables separately and a generalized suitability was later obtained. Suitability classes were ranked as S1 (highly suitable), S2 (moderately suitable) and S3 (marginally suitable). Each sampling unit was chosen on the basis of soil colour, slope and soil type and crop history. Each sampling unit was captured by the use of GPS and results interpolated to depict the situation and mapping of the entire refugee settlement. The results indicate that areas of high suitability S1 devoted for maize yielded a production level and would ensure food security. Using mean comparative test for average yields, the study established that there was a strong relationship between maize production and land suitability. Areas of marginal suitability experienced the threat of food insecurity. The study recognized the relevance of land suitability evaluation for planning purposes and in ensuring that land resources are put to maximum use. The study recommended site selection for refugee settlements to undertake land suitability evaluation prior to any allocation for settlement.

Realizing sustainable livelihood and food security in refugee situations is often an overwhelming challenge. The focus of this study was on ensuring food self-reliance in Kiryandongo refugee settlement in Uganda. The study employed a multimethod approach, that is both qualitative and quantitative methods were used. A cross sectional survey design was used and primary data was collected using questionnaires and in-depth interview. Experimental method was used in analyzing soil samples for soil organic matter content, soil moisture and soil depth. Suitability classes were derived for each of the assessed variables separately and a generalized suitability was later obtained. Suitability classes were ranked as S1 (highly suitable), S2 (moderately suitable) and S3 (marginally suitable). Each sampling unit was chosen on the basis of soil colour, slope and soil type and crop history. Each sampling unit was captured by the use of GPS and results interpolated to depict the situation and mapping of the entire refugee settlement. The results indicate that areas of high suitability S1 devoted for maize yielded a production level and would ensure food security. Using mean comparative test for average yields, the study established that there was a strong relationship between maize production and land suitability. Areas of marginal suitability experienced the threat of food insecurity. The study recognized the relevance of land suitability evaluation for planning purposes and in ensuring that land resources are put to maximum use. The study recommended site selection for refugee settlements to undertake land suitability evaluation prior to any allocation for settlement.