Flood Vulnerability Mapping: A Case Study of Okoko Basin, Osogbo

This study employed Geographic Information System (GIS) and remote sensing approach to analyze the flood vulnerability areas in the Okoko basin area of Osogbo in Osun state, Southwestern Nigeria. High-resolution imageries, a Topographic map of the study area and a TCX software program (Version 2.0) were integrated using ArcGis (10.7). Some of the causative factors for flooding in the watershed were taken into account which are: Land use, Distance of buildings to drainage, Digital Elevation Model, and Slope. This study aimed at mapping the flood-vulnerable areas along the Okoko basin of Osogbo. In developing a flood risk/flood hazard map of the study area, and determining the level of expected disaster, a multi-criteria analysis was utilized. The factors considered were ranked in five classes with the highly vulnerable areas having the highest score of “5”. These factors were weighed according to the estimated significance of causing flooding. The study revealed that the study area has an estimated area of 17.85 km2 of which 14.2 km2 falls within the vulnerable areas while 3.6 km2 is on the least vulnerable areas. Moreover, out of 16,829 buildings in the study area, 8204 buildings were found susceptible to flood disasters. This research attempts to equip decision-makers to make accurate decisions and also serves as a mitigation measure for flood disaster management.

Street Mapping of Ife Metropolis, Osun State, Nigeria

The importance of Remote Sensing and Geographic Information System in map making cannot be overemphasized because of its ability to integrate spatial data with non-spatial data and also communicate the resulting information in a way that everyone would understand. Several works have taken advantage of the abilities of these technologies to produce street maps using High Resolution Images. The increase in development in Ile Ife, Osun State, Nigeria, has brought about navigation challenge and associated difficulties. This work intends to produce a street map that will ease navigation within the study area and help in road network analysis, site suitability analysis etc. Aerial Photographs, captured in the year 2009 and GeoEye1 Satellite Image of 2011 were used to extract the road network of Ife Metropolis. The image was imported into ArcGIS environment, where the database was created having feature datasets such as roads and special features. To have all the elements in vector format, the image was digitized. The street names collected from the field work was inputted into the database and then subjected to cartographical processes. 512 Roads were captured within four classes of Road Network namely Express road (5), Secondary Road (25), Primary Roads (22) and Street Road (460). This field work revealed that a larger percentage of the roads were not paved, while most of the paved ones have deteriorated and the newly constructed ones were not documented. It also showed that some of the roads were not named according to the standard and some were not named at all. From this study, we recommend that the naming system should be standardized across the study area. It is also recommended that provision should be made for street map revision on a yearly basis so as to account for changes.