Evaluation of COVID-19 Cases and Vaccinations in the State of Georgia, United States: A Spatial Perspective

This study evaluates the distribution of COVID-19 cases and mass vaccination campaigns from January 2020 to April 2023. There are over 235,000 COVID-19 cases and over 733,000 vaccinations across the 159 counties in the state of Georgia. Data on COVID-19 was acquired from usafact.org while the vaccination records were obtained from COVID-19 vaccination tracker. The spatial patterns across the counties were analyzed using spatial statistical techniques which include both global and local spatial autocorrelation. The study further evaluates the effect of vaccination and selected socio-economic predictors on COVID-19 cases across the study area. The result of hotspot analysis reveals that the epicenters of COVID-19 are distributed across Cobb, Fulton, Gwinnett, and DeKalb counties. It was also affirmed that the vaccination records followed the same pattern as COVID-19 cases’ epicenters. The result of the spatial error model performed well and accounted for a considerable percentage of the regression with an adjusted R squared of 0.68, Akaike Information Criterion (AIC) 387.682 and Breusch-Pagan of 9.8091. ESDA was employed to select the main explanatory variables. The selected variables include vaccination, population density, percentage of people that do not have health insurance, black race, Hispanic and these variables accounted for 68% of the number of COVID-19 cases in the state of Georgia during the study period. The study concludes that both COVID-19 cases and vaccinated individuals have spatial peculiarities across counties in Georgia state. Lastly, socio-economic variables and vaccination are very important to reduce the vulnerability of individuals to COVID-19 disease.

Effects of RapidEye Imagery's Red-edge Band and Vegetation Indices on Land Cover Classification in an Arid Region

Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was effective for vegetation identification and could improve LCC accuracy. However, there has been no investigation of the effects of RapidE ye images' red-edge band and vegetation indices on LCC in arid regions where there are spectrally similar land covers mixed with very high or low vegetation coverage information and bare land. This study focused on a typical inland arid desert region located in Dunhuang Basin of northwestern China. First, five feature sets including or excluding the red-edge band and vegetation indices were constructed. Then, a land cover classification system involving plant communities was developed. Finally, random forest algorithm-based models with different feature sets were utilized for LCC. The conclusions drawn were as follows: 1) the red-edge band showed slight contribution to LCC accuracy; 2) vegetation indices had a significant positive effect on LCC; 3) simultaneous addition of the red-edge band and vegetation indices achieved a significant overall accuracy improvement(3.46% from 86.67%). In general, vegetation indices had larger effect than the red-edge band, and simultaneous addition of them significantly increased the accuracy of LCC in arid regions.

Effects of climate change on phenology and primary productivity in the desert steppe of Inner Mongolia

Variations in temperature and precipitation affect local ecosystems. Considerable spatial and temporal heterogeneity exists in arid ecosystems such as desert steppes. In this study, we analyzed the spatiotemporal dy- namics of climate and vegetation phenology in the desert steppe of Inner Mongolia, China using meteorological data （1961-2010） from 11 stations and phenology data （2004-2012） from 6 ecological observation stations. We also estimated the gross primary production for the period of 1982-2009 and found that the annual mean tem- perature increased at a rate of 0.47~C/decade during 1961-2010, with the last 10 years being consistently warmer than the 50 years as an average. The most significant warming occurred in winters. Annual precipitation slightly decreased during the 50-year period, with summer precipitation experiencing the highest drop in the last 10 years, and spring precipitation, a rise. Spatially, annual precipitation increased significantly in the northeastern and eastern central areas next to the typical steppe. From 2004 to 2012, vegetation green-up and senescence date advanced in the study area, shortening the growing season. Consequently, the primary productivity of the desert steppe de- creased along the precipitation gradient from southeast to northwest. Temporally, productivity increased during the period of 1982-1999 and significantly decreased after 2000. Overall, the Last decade witnessed the most dramatic climatic changes that were likely to negatively affect the desert steppe ecosystem. The decreased primary produc- tivity, in particular, decreases ecosystem resilience and impairs the livelihood of local farmers and herdsmen.

Geography of Talent in China During 2000-2015:An Eigenvector Spatial Filtering Negative Binomial Approach

The increase in China’s skilled labor force has drawn much attention from policymakers,national and international firms and media.Understanding how educated talent locates and re-locates across the country can guide future policy discussions of equality,firm localization and service allocation.Prior studies have tended to adopt a static cross-national approach providing valuable insights into the relative importance of economic and amenity differentials driving the distribution of talent in China.Yet,few adopt longitudinal analysis to examine the temporal dynamics in the stregnth of existing associations.Recently released official statistical data now enables space-time analysis of the geographic distribution of talent and its determinants in China.Using four-year city-level data from national population censuses and 1%population sample surveys conducted every five years between 2000 and 2015,we examine the spatial patterns of talent across Chinese cities and their underpinning drivers evolve over time.Results reveal that the spatial distribution of talent in China is persistently unequal and spatially concentrated between 2000 and 2015.It also shows gradually strengthened and significantly positive spatial autocorrelation in the distribution of talent.An eigenvector spatial filtering negative binomial panel is employed to model the spatial determinants of talent distribution.Results indicate the influences of both economic opportunities and urban amenities,particularly urban public services and greening rate,on the distribution of talent.These results highlight that urban economic-and amenity-related factors have simultaneously driven China’s talent’s settlement patterns over the first fifteen years of the 21st century.

A Multi-Layer Based Assessment of Wetland Changes in the Southern Iraqi Marshlands Using Remotely Sensed Data

Marshlands are important ecosystem for living organisms. The Southern Iraqi Marshland is the central habitat for freshwater fish, provides habitat for important populations of wildlife and serves as a source of income for native economies through reed harvesting. Studies have shown that variability in climate and human-induced factors affects the spatial dynamics of marsh ecosystems. This study assessed wetland changes in the Southern Iraqi Marshlands using Remotely Sensed Data from 1986 to 2019 using Landsat satellite imagery for four epochs: 1986, 2000, 2010 and 2019. To achieve this, thirty (30) pixels were obtained in selected land cover theme and their signatures were merged into one class. Furthermore, the selected pixels were recoded and merged into ten (10) land cover classes. The multi-layer classes created were shallow water, deep water, dense marsh, medium marsh, sparse marsh, dense vegetation, medium vegetation, sparse vegetation, dry soil and wet soil. The areal extents of the land cover types were calculated for 1986, 2000, 2010 and 2019. Normalized Difference Vegetation Index (NDVI) differencing was also carried in order to highlight trends in vegetation from 1986 to 2019. The study correlated historical trends of human activities as a central factor in the degradation of marshland (by 16.25%) from 1986 to 2000. However, by the year 2000 to 2010, there was an 11.36% increase in the total marshland area, which remained almost unchanged between 2010 and 2019. In 1986, NDVI was relatively stable at 0.73 in the Al-Hammar and Al-Hwaizeh Marsh. However, by 2000, the areas of dense vegetation cover reduced drastically by over 90%. In 2010, the NDVI index indicated trends of increasing water body and an outward cluster of healthier vegetation continuing to 2019.

Tropical forest canopies and their relationships with climate and disturbance： results from a global dataset of consistent field-based measurements

Background： Canopy structure, defined by leaf area index （LAI）, fractional vegetation cover （FCover） and fraction of absorbed photosynthetically active radiation （fAPAR）, regulates a wide range of forest functions and ecosystem services. Spatially consistent field-measurements of canopy structure are however lacking, particularly for the tropics. Methods： Here, we introduce the Global LAI database： a global dataset of field-based canopy structure measurements spanning tropical forests in four continents （Africa, Asia, Australia and the Americas）. We use these measurements to test for climate dependencies within and across continents, and to test for the potential of anthropogenic disturbance and forest protection to modulate those dependences. Results： Using data collected from 887 tropical forest plots, we show that maximum water deficit, defined across the most arid months of the year, is an important predictor of canopy structure, with all three canopy attributes declining significantly with increasing water deficit. Canopy attributes also increase with minimum temperature, and with the protection of forests according to both active （within protected areas） and passive measures （through topography）. Once protection and continent effects are accounted for, other anthropogenic measures （e.g. human population） do not improve the model. Conclusions： We conclude that canopy structure in the tropics is primarily a consequence of forest adaptation to the maximum water deficits historically experienced within a given region. Climate change, and in particular changes in drought regimes may thus affect forest structure and function, but forest protection may offer some resilience against this effect.

Geotechnical and GIS-based environmental factors and vulnerability studies of the Okemesi landslide,Nigeria

Landslide is a geological hazard typically associated with extreme events such as earthquakes,heavy rainfall,volcanic eruptions,changes in groundwater level,etc.This study was carried out in Okemesi-Ekiti(also known as Okemesi),Southwest Nigeria,with the purpose of using remote sensing and GIS technologies to analyze the environmental factors(grain size,direct shear strength resistance,rainfall data,wet density,surface,and slope)resulting in the occurrence of the Okemesi landslide.The study also aimed to conduct a vulnerability analysis in the study area to identify regions with a probability of landslide occurrence.The grain size analysis of the soil in the Okemesi landslide area showed that slope materials comprised 17.14%gravel,59.31%sand,and 19.48%fines,thus the soil type could be classified as poorly graded gravely sand with a high possibility of landslide occurrence.The geomorphic characteristics of the study area was characterized by slopes ranging from 0.00°to 49.00°,while most slopes in the area were less than 8.00°.The slope aspect direction was mainly in south(157.51°–202.50°),southwest(202.51°–247.50°),west(247.51°–292.50°),and north(0.00°–22.50°and 337.51°–360.00°).The highlands were primarily bounded by the slope directions of north(0.00°–22.50°and 337.51°–360.00°),northeast(22.51°–67.50°),east(67.51°–112.51°),and southeast(112.51°–157.50°),which indicated the potential direction of mass movement.The study area can be divided into three vulnerability zones:high,medium,and low,with the area percentages of 9.00%,61.80%,and 29.20%,respectively.The analysis suggested that the Okemesi landslide was likely triggered by rainfall,which might have weakened the physical structure of slope materials.Understanding the causes and impacts of landslides is crucial for policymakers to implement measures to mitigate landslide hazards,protect infrastructure,and prevent the loss of life in the landslide-prone regions.

Landscape spatial structure for predicting suitable habitat: The case of <i>Dalea villosa</i>in Saskatchewan

Prediction of potentially suitable habitat is important for the recovery of species protected by federal laws. Therefore, the objective of this research was to study the relationship between habitat configuration and hairy prairie-clover occurrence in order to predict suitable and unsuitable bare sand habitat across the study site. Bare sand patches were extracted from a land cover classification of the study site and several patch scaled metrics were calculated to characterize habitat spatial structure. Binary logistic regression was used to determine which metrics were significantly correlated with hairy prairie-clover occurrences. The logistic regression equation was subsequently used to predict suitable and unsuitable bare sand habitat for hairy prairie-clover based on the probability of occupancy. Results showed that about 29% of the variation in bare sand patch occupancy could be explained by the size, shape, and degree of isolation of a sand patch as well as the amount of vegetation on a sand patch in the early growing season. Based on these variables, 18.8% of bare sand patches in the study site were predicted to be unsuitable hairy prairie-clover habitat, 45.7% were predicted to be marginally unsuitable, 32.7% were predicted to be suitable, and 2.8% were predicted to be marginally suitable.

The Impact of Climate Change on Sustainable Food Supply and Environmental Safety in Ekiti State, Nigeria

The resultant climate change on sustainable food supply has greatly affected agricultural production by the level of great volumes of gasses emitted into the atmosphere by human activities. The human factors that emit large amount of green house gases include industrialization, burning of fossil fuel and gas flaring. Increase in air temperature and consequent increase in the rates of evaporation also affect the level of food supply. Data for this study were collected from primary and secondary sources. Primary source were collected through field investigation and structured questionnaire. A total of 450 questionnaires were administered. Results revealed that varieties of crops ranging from tree crops to cereals were cultivated within the study area. The effect of climate change on food supply has resulted into change in crop yields, change in rainfall pattern, soil loss and has greatly affected planting period and harvesting. The study therefore recommended awareness campaigns on the causes and consequences of global climate change on food production, environmental education and afforestation campaign programmes on sustainable food supply and environmental safety must be intensified.

Spatial Assessment of Flood Vulnerability in Aba Urban Using Geographic Information System Technology and Rainfall Information

This study investigated the relationship between topographic information and trends in rainfall in Aba urban, South Eastern Nigeria. GIS data were applied to generate topographical information on?runoff characteristics, the slope, the contour, the aspect and the digital elevation model. The Mann-Kendall Trend was applied to the rainfall data to show if a monotonic increase, decrease or stability trend exist for the rainfall data of Aba metropolis for the period 2000-2010. Results showed that virtually all parts of Aba were liable to floods expect Ogbor hill axis. The flood vulnerability map indicated that 71.65% of the study area was vulnerable to flood. Rainfall trend showed a decrease in six out of the ten year period. Since within this period, flood intensity had generally remained the same, we concluded that topography, poor drainage infrastructure and non-compliance with building, planning and environmental regulations rather than rainfall trend were the key cause of flood problem in the study area.

A Longitudinal Analysis of Environment and Risk of Obesity in the US

Obesity is a fast-growing global health crisis and the epidemic is about to get worse. Environment has been shown to influence physical activity and people’s body weight. Utilizing Centers for Disease Control and Prevention 2004-2010 waves of the continuous obesity data, this study conducted longitudinal analyses to examine neighborhood built environment and obesity risk controlling for the effects of socio-demographic characteristics. This study presents a comprehensive effort to understand the relationship between the environment and physical inactivity and obesity across the entire contiguous US. When constructing measures of the built environment, Geographic Information Systems (GIS) were used to calculate street connectivity, walk score and food environment. In addition to the built environment, the natural environment, which was represented by the annual number of extreme weather events from 2004-2010, was taken into account in explaining variation of physical inactivity and obesity across the contiguous US. Results show that higher street connectivity and walk score are related to lower physical inactivity and obesity rates, while the ratio of fast-food restaurants and number of extreme weather events are positively related to physical inactivity and obesity. The results are believed to provide policy-makers and planners with useful insights into the dynamics between the environment and obesity epidemic. Further, the significant effects of extreme weather invite more studies to investigate the relationship between the natural environment and obesity.

Comparative Geospatial Planning Model for “Location Specific” Intervention and Continuous Improvement Strategy

Sustainable development can only be achieved by conscious planning and implementation of action plans. Decision making requires a careful selection of the right conceptual framework and models for planning and implementation processes. Planning process models dictate in very clear terms what must be done and how it is done to achieve a successful completion of a process of activity [1]. Since about 80% of data used to support decisions are geographically related [3], it is necessary to put Geographic Information Systems (GIS) at the core of the planning and implementation model. There exists a great disparity in a heterogeneous world. The locational disparity in achieving sustainable development, therefore, necessitates a planning model that is “location specific” i.e. identifies areas (locations) requiring intervention and areas (locations) requiring continuous improvement strategies. This was achieved in this study by reviewing Bell’s Information System Strategic Planning Model and Kaufman’s Strategic Planning Model, and the designing of new model to overcome the limitation of existing models. Practical application of the new model was carried out in education planning and administration in order to achieve the global goals for sustainable development 4 (quality education). Finding shows that the Comparative Geospatial Planning Model for “Location Specific” Intervention and Continuous Improvement Strategy is useful to support the achievement of sustainable development goals in multidisciplinary, multi-sector applicable instances.

Stand Structure,Allometric Equations,Biomass and Carbon Sequestration Capacity of Acacia mangium Wild.(Mimosaceae)in Cote d’Ivoire

In addition to bioenergy production, Acacia magium, a fast growing species, plays a major role in climate change mitigation through carbon sequestration from the atmosphere. The objective of this study was to improve estimates of aboveground biomass of 3, 7 and 11 years old stands of Acacia mangium set up through natural regeneration at Anguédédou in C?te d’Ivoire. Tree measurements were done in circular plots of 615 m2 located at the center of each stand. 24 trees of circumference at breast height (cbh) between 31 and 116 cm were felled, weighed and measured. Multiple linear regressions were used to develop allometric equations linking aboveground biomass of trees to cbh and/or height. The carbon stock and sequestration capacity of each stand was assessed using these predictive models. The average cbh was 39.4 cm, 73.5 cm and 91.4 cm respectively for 3, 7 and 11 years old stands with a density ranging between 845 trees·ha-1 and 553 trees·ha-1. The allometric equations for biomass estimation were Btotal aboveground = exp(-3.455 + 2.081 × ln(C)), Btrunk = exp (-5.153 + 1.681 × ln(C) + 1.056 × ln(H)), Bbranches = exp(-2.005 + 0.498 × ln(C2 × H)), Bleaves = exp(-2.415 + 1.339 × ln(C)). Total height had no influence on total and leaf biomass but increased precision of trunk and branch biomass. The carbon sequestration capacity of aboveground biomass was highest in Acacia mangium stand of 7 years old with 45.14 teqCO2·ha-1·year-1 and lowest in the 3-year stand with 33.90 teqCO2·ha-1·year-1.

Spatial distribution and potential ecological and health risks associated with heavy metals in the Ijero-Ekiti mining site,Nigeria

Artisanal gold mining,a labor-intensive and antiquated technique,is a growing industry and the source of income for rural communities all over the world.However,artisanal gold mining has potential negative and long-term effects on economy,environment,and society.This study collected soil samples from 16 sample points including a control point to examine the pollution degrees and spatial distribution of heavy metals,as well as ecological and health risks associated with heavy metal pollution in the Ijero-Ekiti mining site,Nigeria.Geographical Information System(GIS)and remote sensing technologies were used to identify regions with high concentrations of heavy metals and assess the environmental impact of gold mining activities.The results show that the mean heavy metal concentrations of 16 soil pointa are 8.94(±5.97)mg/kg for As,0.18(±0.54)mg/kg for Cd,0.11(±1.06)mg/kg for Co,14.32(±3.43)mg/kg for Cr,6.89(±0.64)mg/kg for Cu,48.92(±11.77)mg/kg for Fe,135.81(±30.75)mg/kg for Mn,5.92(±0.96)mg/kg for Ni,5.72(±1.66)mg/kg for Pb,and 13.94(±1.38)mg/kg for Zn.The study reveals that heavy metal concentration in soils follows the order of Mn>Fe>Cr>Zn>As>Cu>Ni>Pb>Co>Cd.An analysis of soil samples indicates that 3 principal components(PCs)account for 70.008%of the total variance and there are strong positive correlations between various pairs of heavy metals.The total potential ecological risk index(309.599)in the study area is high.Non-carcinogenic risk suggests that there may be long-term health impacts on people who work in the mining areas due to chronic exposure to the environment.Based on the study,the hazard index of carcinogenic health risks associated with heavy metals through ingestion is 520.00×10^(–4).Dermal contact from As and Cr also increases the risk of cancer,with the highest hazard index value of 18.40×10^(–4).The lowest exposure pathway,with the hazard index value of 0.68×10^(–4),indicates that the inhalation of heavy metals has a comparatively low risk of cancer.This study recommends the formulation of policies to monitor the Ijero-Ekiti mining site and other regions in Nigeria where indiscriminate artisanal gold mining activities exist.

Coping with the Impact of Climate Change: A Dive into Precision Agriculture in the United States

With the continued increase in the number of people that are food insecure globally, which could be increasing because of the ongoing Ukraine-Russia war, leading to reduction in international agribusinesses, coupled with drastic climate change exacerbating the problem of food insecurity, there is a constant need to come up with innovative approaches to solve this global issue. In this article, we articulated how precision agriculture can be a tool for ensuring food security in the United States. This study aims to reiterate the significance of precision agriculture in solving global food insecurity.

Bank erosion in an Andean páramo river system: Implications for hydro-development and carbon dynamics in the neotropical Andes

The páramo of the Northern Andes provide critically important ecosystem services to the Northern Andean region in the form of water provisioning and carbon sequestration, both of which are a result of the páramo?s organic-rich soils. Little is known, however, about the hydro-geomorphic characteristics of the rivers that drain these ecosystems. With impending plans for widespread hydro-development and increasing implementation of carbon-sequestering compensation for ecosystem services programs in the region it is imperative that we develop a thorough understanding of the hydrogeomorphic role that rivers play in this unique ecosystem. The objective of this study was to quantify bank erosion along an Amazonian headwater stream draining a small, relatively undisturbed páramo catchment to gain a better understanding of the natural erosion regime and the resulting sediment contributions from this unique ecosystem. This study implemented a combination of field, laboratory, and Geographic Information Systems techniques to quantify bank erosion rates and determine a bank erosion sediment yield from the Ningar River, a small páramo catchment(22.7 km^2) located in the eastern Andean cordillera of Ecuador. Results show that bank erosion rates range from 3.0 to ≥ 390.0 mm/yr, are highly episodic, and yield at least 487 tons of sediment annually to the Ningar River. These results imply that 1) páramo ecosystems substantially contribute to the sediment load of the Amazon River basin; 2) bank erosion is a potentially significant flux component of basin-scale carbon cycles in páramo ecosystems; and 3) hydrologic alteration campaigns(dam building) will likely critically alter these contributions and concomitantly disconnect a critical source of sediment and nutrients to downstream ecosystems.

Effective Instructions in Design Process of Urban Public Spaces to Promote Sustainable Development

Public spaces in cities have long been the basis used for the expression of cultural values and social relations. Cultural and social systems have an old two-sided relation. This means that the establishment and continuity of social relationships strengthen the values and norms;on the other hand, culture determines the conditions and the formation of social relationships. Therefore, to create a bonding connection between people and the city, urban public spaces are the focal points which still need to be noticed more effectively by designers and managers. There are components which help the designers design more efficient urban public spaces and, as a consequence, there will be more vitality in cities. In today conditions, sustainability issues, as the solutions of having better future conditions, can considerably affect these components and give the society the opportunity of having more capable public spaces. Sum of studies in the field of sustainability and the subsequent sustainable public spaces researches mainly express three components of environment, economy and society, among which environment section is more significant than two others, so that the importance of climatic design components has been tangibly noted in public space designing. The aim of this paper is reviewing urban public spaces and sustainability notions and, as the result, reaching to some instructions for designing sustainable urban public spaces which have important impacts on these types of places. By doing this, not only the possibility of getting closer to the identity of cities, but also the necessary ground for the strong presence of sustainable urban public spaces in cities, are provided. The research method is descriptive-analytic and library research method is used for data collecting.

Environmental Impact of Climate Change on Agricultural Production in Ekiti State, Nigeria

Climate change will impact agriculture and food production around the world due to the effects of elevated CO2 in the atmosphere, higher temperature, altered precipitation and transpiration regimes, increased frequency of extreme events, and modified weed, pest and pathogen pressure. Data of this study were collected from primary and secondary sources. Primary sources of data were collected using two sets of structured questionnaires. A total number of three hundred （300） questionnaires were administered on categories of respondents in this study. Results of this study revealed that food crops are the major crops cultivated in the study area, and the effects of climate change on agricultural production results in soil loss, plant nutrient loss, textural change, increase in pest and diseases and poor yield germination etc.. This study therefore recommended that cover trees should be planted, which will provide shade and reduce heat, due to climate change and the preservation of underground water.

GIS as a Tool in Analyzing Flood Occurrence and Its Impact on Ikere Ekiti, Ekiti State Nigeria

Flood is any flow of water, which overflows the natural or artificial banks of a body of water. Flooding is one of the fundamental environmental challenges that results from interaction between man and his environment. In Nigeria, Flooding is one of the most common environmental hazards and there is increasing vulnerability of populations and infrastructure to flooding and flood related hazards. This study used GIS as a tool to analyze the cause and the impact of flooding in the study area. The study used both primary and secondary data, through a questionnaire, geographic information system and remote sensing. The result showed that the nature of the basin in the study area resulted to the high volume of water in the major river (River Osun) during raining season, which resulted to overflow across its bank. Fieldwork shows that the river overflows its bank at 500 meters to the north and the south and the GIS analysis shows that over 1000 houses get affected at any point of flooding occurrences, hence the width of the river is less than 8 meters and the depth on the average in less than 10 meter over the bridge of the River Osun. The study recommends methods by which flooding could be controlled in the study area through regular dredging, effective waste management and drainage control.

Assessment of Heavy Metals Pollution in Sediments from Ologe Lagoon, Agbara, Lagos, Nigeria

This study was carried out to assess the level of heavy metals pollution in Ologe Lagoon, Agbara, Lagos, Nigeria. The Lagoon receives effluents from industries in the Agbara Industrial Estate. Cored Soft sediments were retrieved from six random sampling points within the Lagoon and labeled (S1, S2, S3, S4, S5 and S6). Subsamples of the sediments were prepared and analyzed for heavy metal concentration. The result from the heavy metal analysis of the sediments shows that average concentration of Mn, Zn, Cr, Ni, Cr, Ni, Co, Cu and Pb in the samples was 278.1 ppm, 21.7 ppm, 14.2 ppm, 6.6 ppm, 6.4 ppm, 6.4 ppm and 4.4 ppm, respectively. The correlation between the heavy metals varies from 0.71 to 0.98 shows that they have a strongly positive degree of association which suggests that they are from the same source. The geo-accumulation values for Cu in all stations ranged between (1 - 2.8 ppm) and it can be deduced that the sediments are moderately to strongly polluted. Pb varies between 1 and 2.1 suggesting that the sediments are moderately polluted. Zn exhibits strong pollution levels with a range from 2.5 and 3.5 ppm. Co is moderately polluted with 1.5 - 2.4 while Mn shows the highest level of pollution in all stations with Igeo values ranging between 4.1 and 5.8. This study showed that the Lagoon accumulates heavy metals as a result of anthropogenic activities evident in the dumping of municipal, sewage, industrial waste in the environment and domestic activities such as auto mobile transportation and mechanic repair workshop. Based on sediment quality guidelines, the Ologe Lagoon level of pollution ranged from Cu > Pb > Zn > Ni > Co > Mn > Cr > Al with Mn having the highest level of pollution.