Aim: To identify settlements that are vulnerable to flooding within River Rima floodplain in Birnin Kebbi Local Government Area of Kebbi State, Nigeria. Study Design: A flood vulnerability test was conducted by observing the relationship between the locations of settlements on the floodplain and elevation data, considering previous flooding events. Place and Duration of Study: The study covers Birnin Kebbi Local Government Area of Kebbi State, Nigeria. Methodology: This study uses Digital Elevation Model DEM obtained by The Shuttle Radar Topography Mission (SRTM). The Geographical Information System (GIS) technique (Map Overlay) was used where DEM was overplayed by settlement location (point data). Similarly, 3D view was used to confirm the result. Conclusion: The result shows that 12 settlements in Birnin Kebbi LGA were located at the lower altitude (<207m) with close proximity from the river channel. Therefore, the settlements and the surrounding farmlands become vulnerable to flooding. Recommendations: It was recommended that the settlements should be relocated to higher ground for safety. Local farmers should use species of rice that can survive longer time when submerged by water. The Environmental Monitoring Agencies should include detailed images showing affected areas in their publications.

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Generally, vegetation change through the conversion of the world’s forest land to other uses has assumed an increasing scale due to the unprecedented growth of the human population which increases the demand for food and land. Some believed that decrease in vegetation in the area is attributed to oil exploration and exploitation activities only. This study aimed to find out the nature of the vegetation change in the region from 2000 to 2020. The data used was remotely sensed images as Enhanced Vegetation Index (EVI) observed by Terra-MODIS, downloaded via United States Geological Survey (USGS). The Simple Image Differencing was performed on two images (February 18, 2000 and February 18, 2020) using IDRISI software. The result shows that all the states in the Niger Delta region experience both positive and negative change in vegetation cover. The positive change was observed around locations where agricultural plantations exists and within urban areas followed by oil and gas exploration and exploitation that damage the natural forest cover, while negative change was observed around farms where intensive rainy season farming takes place. It was recommended that deforested areas in the region should be reclaimed by planting economic trees as plantation to enhance greenness and maintain balance of the ecosystem. If intensive farming is necessary, it should be practiced sustainably to save the environment.

Many researchers used gauge data from weather stations for rainfall estimate across Africa. Since Africa lies within the tropics, there is possibility for variations in rain received from place to place. Therefore, there is need for excessive density of the gauges for accurate estimate of Africa’s rainfall. Due to numerous challenges, these cannot be achieved. This necessitates the application of remote sensing and GIS to detect changes in rainfall amount in Africa between 1999 and 2018. The data used was obtained from remote sensing satellite (TRMM) and analyzed using GIS application (IDRISI Taiga). The Simple Image Differencing was performed on the two annual mean images covering January to December, 1999 and January to December, 2018. This provides reliable information on rainfall estimate that can complement sparsely and unevenly distributed rain gauge network in Africa. The analysis shows that latitudinal locations, to some extent, determine spatial distribution of rainfall in Africa. It is also observed that significant changes in rainfall rate are mainly found around coastal regions. It was recommended that adequate ground data it needed to confirm these findings. African countries should provide adequate and justly distributed weather stations with on-net database for easy access to the data.

Previous researchers reported that vegetation is one of the natural resources that are constantly changing. These changes are mostly found in an area affected by human activities. Those researchers study vegetation using holistic approach without identifying the locations affected and species of plant that withstand the prevailing conditions. The aim of this research was to find out the locations where these changes are mostly affected. This was achieved using Coefficient of Variation analysis on MODIS-EVI dataset, supported by the field observation. The result shows that high CV areas are mostly around farmlands and around the nomadic routes, while low CV areas are around the floodplains of Rivers Sokoto and Rima. The identified plant species that can survive in the high CV areas are Gueira senegalensis (Sabara), Combretum micranthum (Geza) and Piliostigma thonningii (Kalgo). It was recommended that the dominant plant species in the area should be domesticated and used for afforestation programme in the region. Government should provide adequate grazing reserves and animal routes to avoid indiscriminate grazing activities in the area.