Browsing by Author "Luwa, Justine Kilama"

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    Impacts of land use and land cover change in response to different driving forces in Uganda: evidence from a review
    (African Geographical Review, 2021) Luwa, Justine Kilama; Bamutaze, Yazidhi; Mwanjalolo, Jackson-Gilbert Majaliwa; Waiswa, Daniel; Petter, Pilesjö; Mukengere, Espoir Bagula
    This reviewe of Land Use Land Cover Change (LULCC) studies in Uganda indicates agriculture, forest, grassland, and woodland as the major land use and land cover types. Central Uganda is the most studied region (15%), followed by western (14), eastern (10), and northern Uganda (3). District scale studies were (48%), catchment (19%), forest (17%), national (10%), and park (7%). Landsat 30 m and remote sensing was most used (93%) . Population is the leadingdrivers of LULCC. The impacts of LULCC are site specific and includes reduction of: tree cover and species composition; water quality and quantity; and soil quality.
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    Variability and Changes in Climate in Northern Uganda
    (East African Nature and Science Organization, 2024-03-18) Oriangi, George; Mukwaya, Paul Isolo; Luwa, Justine Kilama; Menya, Emmanuel; Malinga, Geoffrey Maxwell; Bamutaze, Yazidhi
    Variability and changes in climate are generally expected to occur. However, there remain gaps on dynamics of expected regional variations in climatic changes. This study assessed historic and projected climatic conditions up to the year 2033. The study hypothesized that temperature rather than rainfall significantly increased for the period 1980-2010 and rainfall rather than temperature is likely to decrease significantly by 2033 for Gulu District in northern Uganda. To determine historic climatic trends, rainfall and temperature data were obtained from Uganda National Meteorological Authority (UNMA) while for future climate, the PRECIS (Providing Regional Climates for Impact Studies) modelled data based on projected conditions at a 50 km spatial resolution was used. These data sets were subjected to trend analysis and the differences in means were detected at a 95% confidence level. Contrary to the evidences from other empirical studies, results generally indicated decreasing rainfall for the period 1980-2010. However, the decrease was not significant (P > 0.05) while both historic mean annual maximum and minimum temperature trends showed a statistically significant increase (P<0.05). Projections for 2033 reveal a significant decrease in rainfall (P < 0.05) while both maximum and minimum temperature will remain quasi uniform