Assessing the Spatio-Temporal Pattern of Land Use and Land Cover Changes in Osun Drainage Basin, Nigeria

Abstract

Over the years, Osun drainage basin has witnessed tremendous increase in population, and urbanization that have changed the landscape of the area. This study evaluated the spatio-temporal pattern of land use/land cover change (LULC) in the study area, and made hydrological inferences. Landsat imageries were acquired from USGS-EROS satellite image database for the period 1984, 2000 and 2015, while the Digital Elevation Model (DEM) was obtained from Shuttle Radar Topography Mission (SRTM) of the National Aeronautics and Space Agency (NASA). Supervised image classification using the Maximum Likelihood Algorithm in Erdas Imagine was adopted to classified the land use/land cover of the study area into seven classes. Elevation, aspect and slope of the study area were processed from DEM using ArcGIS. Modules for Land Use Change Evaluation (MOLUSCE) plugin in QGIS was used to simulate the basin future LULC change, using change driving factors of population, elevation, aspect and slope of the study area. There was about 234% increase in built up areas and 89.22% in crop/shrubs between 1984 and 2015. The most significant decrease in LULC occurred in forest (58.75%) and wetland (84.69%) during this period. The predicted future LULC change suggests that only about 12% of the basin will remain under forest cover by the year 2046. The results underscored the increasing anthropogenic activities in the basin that influenced recharge rate, surface runoff, incidences of soil erosion, etc., in Osun drainage basin. The planting of the lost native trees was recommended for the sustainability of the basin’s ecosystem.

Comprehensive review on land use/land cover change classification in remote sensing

“…Many researchers around the world have carried out LU/LC change analysis research over many years. Some of the study areas for LU/LC analysis have been North-eastern Latvia, 1 forests, 7 Northern Ethiopia, 9 Mexico, 14 Germany, 18 China, 23 Iran, 25 Egypt, 27 United Arab Emirates, 31 India, 32 Iraq, 37 Malaysia, 41 south-western Australia, 44 Eastern Region of Ghana, 50 Dubai, 52 south-western Nigeria, 54 Indonesia, 55 Pakistan 56 and Sri Lanka. 57 The main objective of researchers in choosing their study area depends on the causes of LU/LC change ( Figure 2), and their work assists government, forest departments, land resource and urban planners in taking the necessary actions to protect the Earth's environment.…”

“…Researchers use image enhancement techniques to reduce the dimensionality of the satellite data: PCA, MNF, Independent Component Analysis (ICA) and wavelet dimensionality reduction. 9,19,25,29,30,34,46,47,51,53,54,56,[61][62][63]67,80,82 Frequently used atmospheric correction methods are Dark Object Subtraction (DOS), Quick Atmospheric Correction (QUAC), FLAASH, Apparent Reflectance Model (ARM) and the F mask method. [7][8][9]12,15,[18][19][20]23,28,29,33,35,37,40,41,45,49,[61][62][63]66,67,70,74,75,79 Geometric corrections include Orthorectification, Geo-referencing, Image Registration, ASCII Coordinate Conversion and Resampling.…”

“…6,7,26,35,55 QGIS is an open-source tool that helps in analysing LU/LC changes across the world. 43,54 Evaluation metrics…”

“…Image Enhancement 9,19,25,29,30,34,46,47,51,53,54,56,[61][62][63]67,80,82 This method helps in reducing the dimensionality and enhancing the contrast of the satellite image.…”

Effect of Land Use/Land Cover Change on Groundwater Recharge in Osun Drainage Basin, Nigeria

“…The classified LULC maps of the study area for the period 1984, 2000 and 2015 were adopted for this study (Ashaolu, 2019). Seven land use/land cover classes such as bare surfaces, built up area, crops/shrubs, forest, rock outcrops, water bodies and wetland were adopted.…”