6 research outputs found
Refugee settlement induces accelerated land use/cover change in Northern Uganda
ABSTRACTThe establishment of refugee settlements has caused profound segmented impacts on the coverage of land use/cover types. Few studies have computed the spatial drivers of land use/cover changes in Refugee prone areas. This study explored how refugee settlements induced geo-changes in land use/cover in Bidi-Bidi refugee settlement in Uganda. Sentinel-2B images (2015, 2017 and 2020) were used to assess and predict (2030 and 2040) the spatial areal extent of land use/cover changes. The images were classified using Supervised algorithm (Maximum-likelihood) and used CA-Markov model to generate transitions into the future. A Binary Logistic regression was used to compute the spatial drivers of geo-changes. Our results reveal that the settlements triggered more geo-changes in built-up (0.6%), refugee settlements (4.1%), and subsistence farmlands (7.0%) at the expense of woodlands (−0.3%), wetlands (−2.9%), and grasslands (−8.3%). The same trajectory will also be expected between 2030 and 2040. The most critical spatial drivers of these changes are as follows: population growth, increased temperatures, precipitation variation, distance to water sources, distance to roads, distance to police posts, and distance to trading centres. To reduce the acceleration of changes in land use/cover types, this study agitates for equal spatial establishment of woodlots, promotion of alternative sources of energy and livelihoods, and settlement construction materials
Malaria patterns across altitudinal zones of Mount Elgon following intensified control and prevention programs in Uganda
CITATION: Siya, A., et al. 2020. Malaria patterns across altitudinal zones of Mount Elgon following intensified control and prevention programs in Uganda. BMC Infectious Diseases, 20:425, doi:10.1186/s12879-020-05158-5.The original publication is available at https://bmcinfectdis.biomedcentral.comBackground: Malaria remains a major tropical vector-borne disease of immense public health concern owing to its debilitating effects in sub-Saharan Africa. Over the past 30 years, the high altitude areas in Eastern Africa have been
reported to experience increased cases of malaria. Governments including that of the Republic of Uganda have
responded through intensifying programs that can potentially minimize malaria transmission while reducing
associated fatalities. However, malaria patterns following these intensified control and prevention interventions in
the changing climate remains widely unexplored in East African highland regions. This study thus analyzed malaria
patterns across altitudinal zones of Mount Elgon, Uganda.
Methods: Times-series data on malaria cases (2011–2017) from five level III local health centers occurring across
three altitudinal zones; low, mid and high altitude was utilized. Inverse Distance Weighted (IDW) interpolation
regression and Mann Kendall trend test were used to analyze malaria patterns. Vegetation attributes from the three
altitudinal zones were analyzed using Normalized Difference Vegetation Index (NDVI) was used to determine the
Autoregressive Integrated Moving Average (ARIMA) model was used to project malaria patterns for a 7 year period.
Results: Malaria across the three zones declined over the study period. The hotspots for malaria were highly
variable over time in all the three zones. Rainfall played a significant role in influencing malaria burdens across the
three zones. Vegetation had a significant influence on malaria in the higher altitudes. Meanwhile, in the lower
altitude, human population had a significant positive correlation with malaria cases.
Conclusions: Despite observed decline in malaria cases across the three altitudinal zones, the high altitude zone
became a malaria hotspot as cases variably occurred in the zone. Rainfall played the biggest role in malaria trends.
Human population appeared to influence malaria incidences in the low altitude areas partly due to population
concentration in this zone. Malaria control interventions ought to be strengthened and strategically designed to
achieve no malaria cases across all the altitudinal zones. Integration of climate information within malaria
interventions can also strengthen eradication strategies of malaria in such differentiated altitudinal zones.https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-020-05158-5Publisher's versio
Land Use and Land Cover Change Dynamics and Perceived Drivers in Rangeland Areas in Central Uganda
Sustainable rangeland management requires understanding the nature of human-ecosystem interactions and local communities’ perspectives regarding evolving changes. This study integrated perceptions from the local community and remote sensing to characterize the extent and drivers of land use and land cover (LULC) changes in the rangelands of Nakasongola district in Central Uganda. The aim of the study was to determine the perceived drivers of land use and land cover change in of Nakasongola district in the Central Uganda district to support decision making for present and future rangeland management. Satellite imagery for 1985, 1995, 2005, 2015 and 2021 were obtained from the United States Geological Survey (USGS) and analyzed to determine the LULC dynamics. Key informant interviews and focus group discussions (FGDs) were conducted to obtain perceived drivers of LULC. Results showed that by 1985 grassland covered 31.7%, wetlands 26.4%, woodland 11.5% and farmland 7.2% of the total land area. However, by 2021, farmland covered 35.8% of the total land area, wetland 21.6% and had reduced to grassland 18.5 percent. Future LULC projections using a Markov chain model showed that farmland cover will increase by 13.85% while grassland cover will further decline by 9.89% in 2040. Wood fuel extraction, subsistence farming, population growth and overgrazing were perceived as key drivers of LULC change. Both remote sensing techniques and local perceptions were in agreement with the identification of patterns and perceived drivers revealing the inherent value of tacit knowledge resident within the community. This knowledge in addition to remotely sensed information can thus be tapped by the decision leaders to better guide interventions aimed at securing better rangeland health and management
Land Use and Land Cover Change Dynamics and Perceived Drivers in Rangeland Areas in Central Uganda
Sustainable rangeland management requires understanding the nature of human-ecosystem interactions and local communities’ perspectives regarding evolving changes. This study integrated perceptions from the local community and remote sensing to characterize the extent and drivers of land use and land cover (LULC) changes in the rangelands of Nakasongola district in Central Uganda. The aim of the study was to determine the perceived drivers of land use and land cover change in of Nakasongola district in the Central Uganda district to support decision making for present and future rangeland management. Satellite imagery for 1985, 1995, 2005, 2015 and 2021 were obtained from the United States Geological Survey (USGS) and analyzed to determine the LULC dynamics. Key informant interviews and focus group discussions (FGDs) were conducted to obtain perceived drivers of LULC. Results showed that by 1985 grassland covered 31.7%, wetlands 26.4%, woodland 11.5% and farmland 7.2% of the total land area. However, by 2021, farmland covered 35.8% of the total land area, wetland 21.6% and had reduced to grassland 18.5 percent. Future LULC projections using a Markov chain model showed that farmland cover will increase by 13.85% while grassland cover will further decline by 9.89% in 2040. Wood fuel extraction, subsistence farming, population growth and overgrazing were perceived as key drivers of LULC change. Both remote sensing techniques and local perceptions were in agreement with the identification of patterns and perceived drivers revealing the inherent value of tacit knowledge resident within the community. This knowledge in addition to remotely sensed information can thus be tapped by the decision leaders to better guide interventions aimed at securing better rangeland health and management