While it is anticipated that there would be some similarities amongst spectral Vegetation Indices (VIs) because the majority of the indices use the red and NIR bands, it is also expected that there would be some variances. The NDVI, derived earlier by Rouse (1973), and is the commonly used VI, there have meagre understanding of the relationship between the NDVI and another VIs. Similarly, investigations on the correlation between LST and other VIs (other than NDVI) in both dry and raining seasons have not been adequately explored. This motivated the study to determine the seasonal correlation of some spectral VIs against the NDVI and LST over the forest reserve area. The study investigated two categories of VIs: slope-based and distance-based. It derived spectral VIs from Landsat 8 images for dry (January) and raining (August) seasons; and estimated LST from MODIS. The findings showed that the ARVI, GNDVI and TVI not only showed resemblance in appearance with the NDVI in both seasons, but also had a high coefficient of correlation: ARVI = 0.973, 0.964; GNDVI = 0.919, 0.879; TVI = 0.779, 0.716. Based on this finding, the ARVI, GNDVI and TVI can be used to supplant the NDVI for biomass related studies in the study area. The study further revealed that the LST-VIs relationship was negative for both dry and rainy seasons, except for the distance-based VIs (DVI, SAVI, MSAVI) that specifically had a positive correlation with the LST. The LST was strongly correlated with the GNDVI, TVI, NDVI, ARVI (0.664 ? r ? 0.598). However, the strength of the correlation for the LST-VIs in the raining season was very weak (0.003 ? r ? 0.245). The study concluded that the correlation of the LST versus the ARVI, GNDVI, NDVI, and TVI can be used for climate related studies.

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The effect of improper waste disposal on man’s health and environment due to the closeness of solid waste dumpsites to underground water sources in some parts of the world has raised issues of serious concern. This study thus sought to examine groundwater quality dependence on the spatial proximity of dumpsites in Samaru, Kaduna state-Nigeria. The coordinates of 10 solid waste dumpsites in proximity to groundwater sources (boreholes) in the study area were acquired for spatial analyses with a GPS-enabled smartphone. Ten groundwater samples from boreholes in relation to dumpsites were collected for testing and analyses of 11 physical and chemical parameters of water quality based on the Canadian Council of Ministers of the Environment (CCME) and World Health Organisation (WHO) standard limits. Thereafter, the water quality index (WQI) for all the locations was calculated. The results of the spatial proximity analyses carried out revealed that the requirement for locating dumpsites was not met as specified by the Environmental Protection Agency (EPA) regarding the minimum safe distance from groundwater sources as a majority (about 80%) of the dumpsites were located too close to the boreholes. The results of the study, however, revealed that the majority (about 80%) of the groundwater samples met the conditions for good drinking water (suitable for drinking water) even with their closeness to the dumpsites based on the computed WQI values and ratings. Meanwhile, only Calcium, Dissolved Oxygen, and Biochemical Oxygen Demand concentrations were significantly affected (p < 0.05 at the 95% significance level) by the closeness of the solid waste dumpsites to the boreholes with very strong (R2 = 86%) and strong (R2 = 79%) relationships, respectively. Suggestions were nonetheless made for the monitoring of land use activities in the areas surrounding groundwater sources to prevent groundwater contamination.

The focus of this study is to determine the relationship between land use and water quality in the River Mu drainage basin for effective water quality management. Various land uses in the study area were identified and mapped using Landsat 8 OLI of 2016. Water samples were also collected from 112 sample sites using Stratified Random Sampling methods. The samples were analysed in terms of physicochemical parameters using standard methods. The results of land use and water quality parameters were regressed using Geographically Weighted Regression (GWR) to determine whether there exist spatially varying relationships. The results revealed that the local R2 values varied between 0.0 and 0.5, indicating a weak relationship between land use and water pollution, except for mixed forest and pH which recorded local R2 values of 0.7 towards the western region of the study area. This shows that the relationship between the two variables varied spatially across the drainage basin. The one-sample Kolmogorov Smirmov test-p<0.05 revealed that there were significant differences in pH (0.00), EC (0.00), turbidity (0.001), TDS (0.048), DO (0.003), NH4+ (0.002), Ca2+ (0.00), Cl- (0.036), Fe3+ (0.00) and Cr2+ (0.039) across the different sample points, whereas K+ (0.134), PO43- (0.715) and NO3- (0.501) were not significantly different across the different sample points. The study recommended that the procedure for water management be localized to sub-catchment and basin levels, to provide adequate attention to each sub-catchment depending on the level and nature of pollution identified.

Human variables such as population increase and distribution, as well as economic expansion, have a strong impact on land usage. Zaria and Sabon Gari local government areas are endowed with various types of institutions that attract people from far and near to its space for studies and employments. This in turn leads to increase in population growth and the expansion of residential land use (LU). Thus, this study assessed the Land Consumption Rate (LCR) and Land Absorption Coefficient (LAC) of the residential and educational LUs using geospatial technique. The study analyzed Landsat imagery of 1987, 1999, 2006, and 2018. The study utilized a combination of quantitative (pixel-based) and qualitative (digitizing) methods of image classification for classifying the residential and educational LUs and biophysical covers. Quantitative assessment of the LU dynamics was achieved by the post-classification computation of LU dynamics, LCR, and LAC. The results revealed that residential LU occupied an area of 2594.25ha in 1987, 2815.15ha in 1999, 4042.54ha in 2006, and 8033.19ha in 2018. In the same vein, the educational LU occupied area of 2623.41ha in 1987, 2991.87ha in 1999, 3021.10ha in 2006, and 3093.75ha in 2018. The LCR values for residential LU were 0.555%, 0.468%, 0.579%, and 0.803% for the years 1987, 1999, 2006, and 2018 respectively. The LCR reduced from 1987 to 1999 and then increased from 1999 to 2018. The LAC values for the residential LU increased across the period of the study. The study concluded that the exploitation of the new lands for residential and educational LUs could be as a result of the demographic and institutional drivers of LU. The study suggested that the urban planning authority should develop planning measures that will regulate the already crowded residential LU in the study area.was transformation of rocky surface and waterbody into urban area, which was caused by population growth, human and agricultural activities in Zuru metropolis.