The increasing human settlements around protected areas is a significant cause of the shrinking size of conservation areas globally. This is an alarming situation, especially in countries where protected areas significantly contribute to the National economy. The use of new tools to solve Land use conflicts that exist around protected areas is needed. This study employed the weighted overlay analysis using ecological, social and economic factors to model suitability for developing settlements in Chobe District, an international tourist destination in Northern Botswana, using ArcGIS spatial analyst. The majority of the land (83.4%) in Chobe is not suitable for settlement, while suitable areas that could for settlement remain relatively small (0.3% of the land). This study suggests that more land for settling the increasing population be created out of Chobe District to avoid encroachment on the conservation areas. The study demonstrated that ArcGIS spatial analyst model builder could be integrated into the land resource planning process of protected areas, making it a handy tool for the analysis and the identification of ecological, economic and social factors, thus establishing an excellent area for further research, especially for sustainable management of protected areas.

Fire is a critical tool for managing rangeland ecosystems; however, the increasing wildfire occurrence poses a considerable danger to rangeland ecosystem continuity. Predicting fire occurrence and mapping wildfire danger is critical in managing highly flammable rangelands. To identify potential remotely sensed variables for wildfire prediction, this study employed a Random Forest (RF) classifier using selected environmental variables to assess their possible use for wildfire prediction in Kgalagadi District, Botswana. The study used 107,883 active fire points from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor from 2015 to 2021. Datasets of remotely sensed Dry Matter Productivity (DMP), Soil Moisture (SM), Land Surface Temperature (LST), Live Fuel Moisture Content (LFMC), and Dead Fuel Moisture Content (DMFC) were analysed in ArcMap 10.7 Esri©. The RF model developed gave an Out of Bag (OOB) error of 9.91% and an overall accuracy of 90.15% for classifying fires and non-fire points using the test dataset. The results also showed a Kappa coefficient of 0.803, with 88.25% and 91.76% producer and user accuracies, respectively, for classifying fire points. The DMP was the most significant variable with Mean Decrease Accuracy (MDA)= 1,055.20 and Mean Decrease Gini (MDG)= 9.328.62), followed by SM (MDA= 828.39 and MDG= 15,745). The LFMC and DMFC were found to be weak in detecting fires. It is recommended that field studies be carried out in the study area to calibrate these to improve their contribution to accurate fire prediction, as most literature shows that they are significant in fire prediction.

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This study evaluated the impact of irrigation and cropping on soil physicochemical properties at Kyekide small scale irrigation farm in Jinja district, eastern Uganda. Treatments included Land-use systems under perennial and annual cropping with and without irrigation for over 20 years. The hypothesis was that there were insignificant differences in physicochemical properties of the soil under irrigated and non-irrigated cropping systems. Soil physical properties except hydraulic conductivity was not significantly different with irrigation and cropping. The pH of the soils ranged from moderately acidic to neutral pH (5.17-7.40), with irrigated soils tending to be more neutral than non-irrigated soils. SOM content was higher in the irrigated soils and perennial soils than in the non-irrigated and annual soils. The soils were moderately deficient in N and severely deficient in P (mean values =0.175% N and 1.183mg kg-1 P) compared with the critical of 0.2% and 15 mg kg-1, respectively. Irrigated soils had a significantly higher Na+ content than non-irrigated soils, with a mean value of 2.985cmol/kg. The K+, Ca2+, and Mg2+ contents were higher in irrigated and perennial soils than non-irrigated and annual soils. The study suggested monitoring the soils under an irrigation scheme to prevent degradation due to increased salt accumulation or chemical fertility decline. Overall, monitoring of soil quality is vital in irrigation schemes to monitor the impacts of water on the environment.

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