Many studies have unveiled the importance of variation in residential property values overtime, but failed to cover different types of residential property value and location. The aim of this research is therefore to model residential property rental value in Bida from 2015 to 2020 with the aid of Geographic Information System (GIS). The study focused on the rental values of the residential property and rental value variation across space. Data collected for this paper includes residential rental values and geographic coordinates from 196 residential properties in the study area, comprising 101 one-bedroom, 80 two-bedroom and 15 three-bedroom apartments. Inverse Distance Weighted (IDW) interpolation tool of ArcGIS was employed in analysing the data. It was found out that the core areas of the town commands lower rental values while the southern part of the town commands higher rental values. It was also found out that one bedroom apartment is the most dominant residential rental property followed by the two bedroom apartments and three bedroom apartments respectively. Geospatial database was produced for each model in a bid to ascertain the level of changes with time. The benefits associated with the application of GIS technology were established by this research and recommends its application to other property values modelling.

Geostatistical tools are considered to be very imperative in achieving the Sustainable Development Goals (SDGs), most especially in the distribution of facilities. Studies on the application of geostatistics such as Average Nearest Neighbour (ANN) in the spatial distribution of sustainable water supply facilities are often very rare. This study, therefore, explores the critical importance of the ANN analytical tool of ArcGIS to examine the spatial distribution of public water supply facilities in Lapai, Nigeria. The ANN sets the null hypothesis that there is no difference between the random distribution and the distribution of public water facilities in the study area, where the z-score and p-value results are both measures of statistical significance which explains whether the null hypothesis should be accepted or rejected. The results obtained indicate a similar spatial distribution pattern for all water facilities in the study area, as they are dispersedly distributed from the global view. The method will allow more proactive decision making in the provision of sustainable public water supply facilities to better the wellbeing of urban dwellers.

The study aimed at examining the spatial pattern of residential densification in housing submarkets of Bida, an ancient traditional town in Nigeria. The study adopted the 2015 standard residential density of Niger State Urban Development Board to determine the level of residential density and occupancy rates of the various submarkets of the town. The study also adopted primary method of data collection through the use of satellite images, handheld GPS and georeferencing of demarcated areas and the buildings, using point features and vector approach in ArcGIS environment to achieve the area coverage, number of buildings and buildings per hectare (ha) in the housing submarkets. The finding of the study reveals that in 2008 Town housing submarket has the highest area coverage, followed by the Project Quarters and then GRA, but in terms of residential density, four housing submarkets of Town, Rahmatu Dangana, Gbazhi and Wadata have high densities above the other seven submarkets. The study further reveals that in the year 2013, additional eight housing submarkets have high residential densities, GRA medium density while Eyagi and Prject Quarters had low densities respectively. It was therefore recommended that there is the need for rational densification (planned densification) for urban development in order to check the increasing unplanned residential density that reduces the green and open spaces in urban environment.