Geographic Information System Mapping Research Articles

Hydroclimatic projection: statistical learning and downscaling model for rainfall and runoff forecasting

Abstract The study is carried out to investigate the surface runoff depth with changing precipitation due to climate change in the study area where sandy loam and loamy soil are dominant. In this study, future rainfall is projected by a statistical downscaling model (SDSM) using a set of predictors derived from a Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate model (GCM) [the Norwegian Earth System Model (NorESM)] with updated scenarios SSP 4.5 and SSP 8.5. Daily rainfall values for the observed period (1981 to 2014) are validated using statistical learning and evaluated with matrices, namely, root mean square error (RMSE), coefficient of correlation, and Nash–Sutcliffe efficiency (NSE), which are found to be valid for further predictions. Rainfall projections show a decrease in rainfall trend of 50% from 2030 to 2040 for scenario SSP 4.5 and an increase of 7% from 2040 to 2050. Predicted rainfall for scenario SSP 8.5 shows a similar trend of decreasing rainfall of 24% for the period 2030–2040 and an increase of 19% in the period 2040–2050. Furthermore, these rainfall values are spatially modelled in a geographic information system (GIS) and rainfall maps are obtained. The obtained rainfall map, land-use map, and soil map are overlaid to compute curve numbers and runoff depths. A similar trend of decrease in runoff is observed for the period 2030–2050. The overall trend of climate change shows a water-stressed scenario.

Impact of current anthropogenic activities on Blesbokspruit wetland microbiome and functions

Till present, natural wetlands have been continuously subjected to intensive pollution stress in recent years, mainly because of the rapidly growing industrialization and urbanization that are associated with a myriad of anthropogenic activities and land use practices. These man-made sources of pollution change the chemical properties of the natural wetlands, which in turn alter their microbial ecological biodiversity and functions. For the first time, the impact of the current anthropogenic activities and land use practices on the Blesbokspruit wetland chemical status and their consequential effect on the microbial structure and functions were investigated. Sites of high pollution intensity were identified using geographic information systems mapping (GISMapping) and the wetland microbiome and functional profile were studied through the use of high throughput shotgun metagenomics sequencing analysis. The predominant phyla that stemmed along the Blesbokspruit wetland were found to be Proteobacteria which was more dominant in water (93 %) than in the sediments (89 %), followed by firmicutes which was more abundant in sediments (9 %) than in water (6 %), and Bacteroidetes were relatively low in abundance within both the sediments (2 %) and the overlying water (1 %). The genera Klebsiella (70.4 %–28.2 %), Citrobacter (52.0 %–30.6 %), Escherichia (51.0 %–8.4 %), and Lynsinibacillus (9.3 %–1.5 %) were observed in most water and sediment samples. Within the six polluted sites, Site 2 was found to be the most highly polluted site in the Blesbokspruit wetland with very high COD (900 mg/L), TOC (11.60 mg/L), NO3− (39.74 mg/L), NO2− (12.64 mg/L), PO43 (4.14 mg/L), Fl− (143.88 mg/L), Cl− (145.95 mg/L) concentrations recorded in the water and high levels of TOC (0.37 mg/L), TC (6.92 %), TN (1.82 %), TS (0.53 %) in sediments. The microbial community structure and functions were found to be strongly influenced by the high organic content from the intense agricultural activities and sewage spillages and heavy metals from the mining activities nearby.

The Risk-Informed Asset-Centric (RIACT) Urban Resilience Enhancement Process: An Outline and Pilot-Case Demonstrator for Earthquake Risk Mitigation in Portuguese Municipalities

This study introduces the Risk-Informed Asset-Centric (RIACT) process, a novel approach aimed at enhancing the safety and resilience of urban infrastructures against natural and man-made disasters. The RIACT method stands out for its comprehensive analysis of potential disruptions to urban areas, encompassing their susceptibility to disasters, vulnerability factors, and recovery capabilities. This study’s primary focus is on Portugal’s 308 municipalities, assessing their preparedness and ability to recover from earthquake events. Methodologically, the study involved employing geographic information system (GIS) mapping to evaluate earthquake risks, combining data on regional risk areas, demographic and economic profiles, and resilience capacities. This approach provides a detailed understanding of each municipality’s strengths and areas in need of improvement, encouraging a collaborative framework for sharing and implementing best practices. The results reveal significant variations in earthquake resilience across different regions, highlighting the need for tailored resilience strategies. Conclusively, the RIACT method not only enhances the resilience of individual municipalities but also contributes to a broader national strategy for urban resilience, offering valuable insights for effective disaster risk management and recovery planning.

Use of GIS and BIM for the integration of tunnel design and construction process in conventional tunneling

This paper presents the development of a framework for the parametric design of tunnels using geographic information system (GIS) mapping and building information modelling (BIM). According to the framework, a parametric representation of each system component (e.g., layers of rock mass, size of excavation, topography, fault geometry, primary lining, secondary lining, rock bolts, etc.) can be incorporated in the GIS model with high levels of detail and used for the automatic generation of numerical models for the design of tunnel construction. This parametric evaluation allows the designer to consider several levels of detail for each component, for the efficient design and process optimization in conventional tunneling. Information between parametric analysis and numerical simulations can be freely exchanged with significantly reduced computational effort while results can be exported into BIM. It is anticipated that the proposed framework could lead to a comprehensive, yet efficient analysis of complex conventional tunneling project using parametric evaluations at the early design stages.

COVID-19 vaccine coverage effectiveness among elderly with geographical information system mapping: what about Indonesia?

The elderly are the next priority after health workers and public service workers get the COVID-19 vaccine to control morbidity and even mortality in the elderly who have a risk factor that is up to 60 times more severe than children. This study aimed to spatially analyze the effectiveness of COVID-19 vaccine coverage among the elderly in Indonesia with geographic information system (GIS) mapping and to analyze the relationship between COVID-19 vaccine coverage in the elderly with the COVID-19 cure rate. This quantitative study used secondary data on COVID-19 vaccination coverage in the elderly group of Central Java Province, Indonesia in 2021. Data were analyzed using a simple linear correlation test to test the relationship between variables with a 1,774,396 elderly sample size, then distributed using mapping of COVID-19 vaccination coverage using a GIS. The relationship between COVID-19 vaccine dose-2 elderly coverage cure rate showed a strong relationship (r = 0.677) and a positive pattern. The coefficient value with a determination of 0.459 means that the regression line equation obtained can explain 45.90% of the variation in the COVID-19 cure rate. There was a significant relationship between COVID-19 vaccine elderly coverage and the COVID-19 cure rate (p-value = 0.005). Clinicians and public health workers should continue to encourage elderly vaccination at all recommended doses for eligible individuals.

Geographic information system-aided evaluation of epidemiological trends of dengue serotypes in West Bengal, India.

West Bengal is a dengue-endemic State in India, with all four dengue serotypes in co-circulation. The present study was conceived to determine the changing trends of circulating dengue virus (DENV) serotypes in five consecutive years (2015-2019) using a geographic information system (GIS) during the dengue season in West Bengal, India. Molecular serotyping of dengue NS1 sero-reactive serum samples from individuals with ≤5 days of fever was performed using conventional nested reverse transcriptase-PCR. GIS techniques such as Getis-Ord Gi* hotspot analysis and heatmap were used to elucidate dengue transmission based on the received NS1-positive cases and vector data analysis was used to point out risk-prone areas. A total of 3915 dengue NS1 sero-positive samples were processed from most parts of West Bengal and among these, 3249 showed RNA positivity. The major circulating serotypes were DENV 3 (63.54%) in 2015, DENV 1 (52.79%) in 2016 and DENV 2 (73.47, 76.04 and 47.15%) in 2017, 2018 and 2019, respectively. Based on the NS1 positivity, dengue infections were higher in males than females and young adults of 21-30 yr were mostly infected. Getis-Ord Gi* hotspot cluster analysis and heatmap indicate that Kolkata has become a hotspot for dengue outbreaks and serotype plotting on maps confirms a changing trend of predominant serotypes during 2015-2019 in West Bengal. Co-circulation of all the four dengue serotypes was observed in this study, but only one serotype became prevalent during an outbreak. Representation of NS1-positive cases and serotype distribution in GIS mapping clearly showed serotypic shift in co-circulation. The findings of this study suggest the need for stringent surveillance in dengue-endemic areas to limit the impact of dengue and implement better vector-control strategies.

Classification of Water Bodies Using Ensemble of U-Net and Random Forest Algorithm

Water bodies classification using remote sensing and deep learning techniques plays a pivotal role in the effective management of water resources. This study aims to address the challenge of accurate water body detection and classification, which is essential for understanding their distribution and characteristics, ultimately informing water usage and conservation efforts. Current methodologies predominantly rely on Support Vector Machines (SVM) and pixel-based approaches, resulting in suboptimal accuracy. In response, this paper proposes an ensemble model that combines the U-Net neural network and the Random Forest algorithm for enhanced water body detection and classification. The research commences by obtaining high-resolution satellite images with a resolution of 0.5 m. The U-Net model is employed to segment water bodies, and contour analysis is subsequently applied to extract shape features. The Random Forest Classifier is then utilized to classify the segmented water bodies into distinct categories, including rivers, ponds, lakes, canals, and other water bodies. Following the U-Net segmentation, the rasterized segments are converted into vector format. These vector data are leveraged to update Geographic Information System (GIS) maps, contributing to more accurate cartographic representations. The proposed approach is rigorously evaluated using a dataset from urban areas in Kolkata, West Bengal, India. The achieved accuracy rate stands at 67.01%.

Using participatory geographic information systems (PGIS) mapping to describe household food access in Buffalo, New York

ABSTRACT Despite existing only blocks apart, neighborhoods in Buffalo, NY can have very different levels of food availability and access due to their local food environment. This study uses participatory geographic information systems (PGIS) mapping and qualitative interviewing to describe these food environments based on the lived experiences of Buffalo residents. PGIS mapping interviews were conducted with residents of the city who regularly used food pantries and focused on access to and availability of both free food resources (such as soup kitchens and food pantries) and purchased food resources (such as grocery stores). Participants were also asked about food access in their own neighborhood, their perceptions of food access in the city, and what develops they thought would contribute to greater food security for their neighborhoods. Results show cost of living and transportation were important barriers to food access for many participants. Findings suggest that residents of historically marginalized neighborhoods in Buffalo continue to have lower access to affordable healthy foods.

EXAMINING THE ASSOCIATION OF HISTORICAL REDLINING WITH NURSING HOME QUALITY

Abstract Aim Redlining systemically relegated people of color to lower-resourced areas which are known to have had long-term effects on access to healthcare; however, it is not currently known if access to nursing home (NH) quality was impacted. Methods In this cross-sectional descriptive study, we created a Geographical Information Systems map of the distribution of Massachusetts NH in the year 2021, layered over a 1934 redlining map with neighborhood categories: Best, Still Desirable, Declining, and Hazardous. Our dataset included redlining categories, 2021 NH characteristics (e.g., bed size, 5-star quality rating), and change in median household income from 1930 – 2021 (proxy for resources, in 2021 dollars). Descriptive statistics estimated the association of each variable with NHs’ 5-star quality rating. Results The majority of NHs were in historically Declining (n=45,71%) or Hazardous (n=10,16%) neighborhoods. While 3% (n=2) were in Best neighborhoods. Both NHs in Best neighborhoods were 5-star, while 1 NH was 5-star in Hazardous neighborhoods. There were 63 NH included with a mean change in median household income of $47,684.06 (SD $37,844.01). The greatest increases in mean income were observed in hazardous neighborhoods containing 1-4-star NHs. The highest increase in mean income was $140,000 (n=1), occurring in a neighborhood with a 4-star NH. Conclusion Despite the growth of resources in hazardous neighborhoods, most NHs in these areas were less than 4-stars. Increasing resources may not benefit NH quality in historically redlined/hazardous areas. Future research should examine this phenomenon at a national level.

Hepatitis A Chronic Immunity in Iran: A Geographic Information System-Based Study

Background: Chronic immunity to hepatitis A (HA) is largely influenced by environmental factors, such as socioeconomic indicators, public health conditions, and access to safe water. In the past two decades, Iran has witnessed improvements in socioeconomic status, increased urbanization, enhanced health education, improved access to safe drinking water sources, and better public health conditions. However, these changes have not been uniform across all regions of Iran, and varying epidemiological situations are expected. Objectives: This study aimed to delineate the pattern of HA chronic immunity across different regions of Iran using geographical information system (GIS) mapping. Methods: The study included a total of 3255 individuals who tested positive for anti-hepatitis A virus (anti-HAV) immunoglobulin G (IgG). This study analyzed factors such as place of residence, marital status, age, and gender to explore possible relationships. Univariate and multivariable analyses were conducted to identify independently associated factors for HA. A locally weighted scatterplot smoothing (LOWESS) multivariate model was developed using a backward stepwise approach. Geographical variations in the prevalence of HA chronic immunity in the general population of Iran were assessed to understand spatial effects and risk factors. A Bayesian spatial model was employed to identify the spatial pattern of HA chronic immunity prevalence, using OpenBUGS version 3.2.3. Results: The prevalence of HAV immunity was higher in regions with mild semi-dry climates (aPR = 2.37, 95% confidence interval [CI] = 2.30 - 3.33, P< 0.001), medium semi-dry climates (aPR = 1.37, 95% CI = 1.14 - 1.63, P< 0.001), dry climates (aPR = 1.13, 95% CI = 0.9 - 1.4), and ultra-dry climates (aPR = 1.79, 95% CI = 1.05 - 2.98, P = 0.033), compared to semi-humid climates. Other variables did not exhibit a significant relationship with HA chronic immunity. The GIS analysis map revealed that immunity to HA was generally lower in the capital cities of Iran’s provinces. However, most central regions of Iran exhibit medium endemicity; nevertheless, higher immunity to HA was observed in border areas and coastal regions, particularly in the northern part of the country. Conclusions: Different regions of Iran display distinct patterns of HAV endemicity, influenced by the country’s climatic diversity.

The Geography of Dispossession: Race, Bankruptcy, and Foreclosure in a Deep South US County

ABSTRACT Scant attention has been paid to the racial impacts of bankruptcy and foreclosure in the United States. This article examines the links between bankruptcy, housing loss, and “risk responsibilization,” a neoliberal process in which consumers rather than lending institutions are held responsible for debt management. We used data sequencing, and Geographic Information Systems Mapping (GIS) to analyse 1,057 cases of home foreclosure and related bankruptcies from 2016 to 2019 in a Deep South US County. We found housing vulnerability to be a racialized process, with Black homeowners more likely to face foreclosure and less likely to receive a fresh start through bankruptcy. In foreclosure, Black-owned homes were more likely to convert to rental property. The study provides sequential and spatial evidence of connections between risk responsibilization, systemic racism, and housing loss in the geography of dispossession.

Investigating Strategies and Practices to Enhance the Resilience of Agricultural Supply Chains in the Face of Disruptions and Uncertainties

Amidst disruptions and uncertainties, this research examines strategies to increase the resilience of agricultural supply chains. Factors such as diversification, adoption of technology, and climate-resilient agricultural practices emerge to fortify the robustness of supply chains. These events look set to become more common, and survey results point emphatically in the direction of diversifying sources and markets. Case studies offer a model for successful strategies against an uncertain future. Recognized as a resilience enabler, technology is challenged by limited access and concerns about data security and interoperability. Precision farming and geographic information system mapping are among the climate-resilient practices that help stabilize crop production. Financial limitations, which disproportionately affect small and medium-sized enterprises, prevent the implementation of resilience measures. Differences in regulatory standards across the regions create bottlenecks, and all policies have to be standardized while still being locally sensitive. The research argues for strategic interventions, such as financial support mechanisms and skills development programs to remove obstacles limiting resilience. These results have far-reaching potential to inform policymakers, industry participants, and researchers about how to build an integrated regulatory environment for innovation in technology.. KEYWORDS :Agricultural supply chains, Climate-resilient practices, Diversification, Financial constraints, Resilience, Technology adoption

An open-source workflow for scaling burn severity metrics from drone to satellite to support post-fire watershed management

Wildfires are increasing in size and severity across much of the western United States, exposing vulnerable wildland-urban interfaces to post-fire hazards. The Mediterranean chaparral region of Northern California contains many high sloping watersheds prone to hazardous post-fire flood events and identifying watersheds at high risk of soil loss and debris flows is a priority for post-fire response and management. Uncrewed Aerial Systems (UAS; aka drones) offer post-fire management teams the ability to quickly mobilize and survey burned areas with very high-resolution imagery (∼1 cm), facilitating emergency management and post-fire hazard assessment. However, adoption of this technology by hazard response teams may be hindered by complicated workflows for UAS data acquisition, image processing and analysis. We present an open-source workflow using mature Geographic Information Systems (GIS) software and Python packages in a Jupyter Notebook environment that guides users through classification of true-color UAS imagery to generate high resolution burn severity maps which can then be scaled across larger watersheds using Sentinel-2 normalized burn ratio (NBR) images. Soil burn severity classifications using a weighted brightness (WB) image and Char Index (CI) generated from UAS imagery were validated with in-situ data and random stratified points, resulting in the CI having the highest overall accuracy of 87.5%. CI also displayed a marginally stronger relationship over the WB with the post-fire Sentinel-2 NBR, R2 = 0.79 and R2 = 0.78 respectively. Our methods offer the unique opportunity to standardize GIS workflows, promoting replication through transparency, while improving the user's understanding of scientific GIS functionality.

Climate and Gender: Association Between Droughts and Intimate Partner Violence in India.

Extreme climate events are related to women's exposure to different forms of violence. We examined the relationship between droughts and physical, sexual, and emotional intimate partner violence (IPV) in India by using 2 different definitions of drought: precipitation-based drought and socioeconomic drought. We analyzed data from 2 rounds of a nationally representative survey, the National Family Health Survey, where married women were asked about their experiences of IPV in the previous year (2015-2016 and 2019-2021; n=122,696). Precipitation-based drought was estimated using remote sensing data and geographic information system (GIS) mapping, while socioeconomic drought status was collected from government records. Logistic regression models showed precipitation-based drought to increase the risk of experiencing physical IPV and emotional IPV. Similar findings were observed for socioeconomic drought; women residing in areas classified as drought-impacted by the government were more likely to report physical IPV, sexual IPV, and emotional IPV. These findings support the growing body of evidence regarding the relationship between climate change and women's vulnerability, and highlight the need for gender responsive strategies for disaster management and preparedness.

Mitigation Strategy of Disaster Based on Information Technology in Semarang City

Semarang is a city located on the northern coast of the Java Sea which makes it becomes one of the cities threatened by tidal flooding. Besides tidal flood inundation, several other disasters occuring in Semarang include fires, fallen trees, floods, landslides, hurricanes, and collapsed houses. This study identified the disasters occurred in Semarang City from 2012 through 2021, as well as the strategies to cope with them in general, and specifically using information technology, namely Geographic Information System (GIS) maps. The data in this study were obtained from Regional Development Planning Board, Public Works Office, Central Bureau of Statistics (BPS), Semarang City Social Service, and several related stakeholders. Those data were, then, visualized on a GIS map. The findings indicated that one method of mitigation is the use of GIS maps of floods and landslides, as well as disaster mitigation through Semarang economy and government policies Keywords: Semarang, GIS, tidal, flooding, disaster, mitigation

Mapping of Manado State Polytechnic campus area with web-based Geographic Information System (GIS): A Small Unmanned Aerial Vehicle (SUAV) application

Technology is continuously developing, especially in mapping and information technology. Geographic Information System (GIS) is a system used to collect, store, analyze, and display geographic data. Geographic data is information about location or geography, such as maps, satellite imagery, digital elevation models, or data associated with a particular location. This study aims to produce a web-based GIS map by visualizing spatial data containing each room's location, parking area, and landscape in the Manado State Polytechnic campus area. The method used in this study was to collect location data using a Small Unmanned Aerial Vehicle (SUAV) to take aerial photos, Ground Control Point (GCP), and tagging photos. Data processing uses Agisoft Metashape Software to combine all aerial photographs to become an exclusive photo and ArcGIS for programming. The result is creating a digital map that makes it easy for users to get the position of buildings with a visual display along with the information contained therein.

Web-Based Geographical Information System Mapping High School and Vocational School In The City Of Ternate

The government of the Education Office of North Maluku Province is trying to overcome the problem of student distribution for schools in the city of Ternate, especially SMA/SMK/equivalent which aims to make all schools quality and there are no more superior schools. However, new problems arise related to the zoning system itself, sometimes some parents of prospective students and prospective students themselves do not know the schools in their domicile zone. The problem formulation is how to create and compile a Geographic Information System Mapping SMA and SMK in Ternate City. Designing a geographic information system that can provide information about web-based SMA and SMK Mapping in Ternate City and become a reference for the community in choosing their or their children's schools according to the zoning system. For testing the system is in accordance with the stages tested where for testing the system is used black box testing, namely testing to see the suitability of data accessed. The high school and vocational recession geographic information system was built using the PHP programming language, Mysql as a database, while for making locations of high school and vocational high school vulnerable places using google maps, maps API. All high school and vocational tracking information system uploads use black boxes, run as expected on the system upload carried out. From the results of this design, it will make it easier for parents to find information on SMA and SMK schools, such as the domicile zone of the school where they live.

Strengthening City Branding Through Investment in Ambarawa Urban Area, Semarang Regency

City branding can shape an area’s positioning and marketing differentiation so that a city can build a clear identity and strong associations and instil positive attributes to compete with other cities, especially for tourism. The primary purpose of city branding is to increase tourists and foster a good perception of the area. Ambarawa Urban Area is part of strategic National Kedungsepur (province) for social and cultural focus. The development of this area aims to create a historical city area that becomes the centre of tourism development. Tourism development also requires support from investors. Investment is important because it can also provide social benefits to the community. Therefore, this article aims to determine investment locations to strengthen the city branding of the Ambarawa Urban Area. The data used in this research are secondary and primary. Secondary data includes land value, road network, land use, and hazard map. The validation of land use data and road networks is carried out using the ground check. The variables used in the analysis are land value, ease of accessibility, and availability of land that can be developed for construction. The analysis techniques used are kernel density and overlay mapping such a conservation area, limited development land and tourism location. The processing map using Geographic Information System (GIS) mapping software. This research resulted in investment locations in several villages, such as Baran, Kupang, Lodoyong, Ngampin, Panjang and Tambakboyo with a total area of 19.14 hectares. The largest investment location can be allocated in Panjang Village which has an area of 9.79 hectares and is spread across two locations.

Experimental Studies on Water Quality Analysis Integrating GIS Mapping at Aarang

Abstract: Groundwater is a primary source of drinking water in our country but day by day increment of groundwater contamination due to various anthropogenic activities and anthropogenic activities makes the life difficult especially for the rural people. Groundwater is getting contamination rapidly due to various anthropogenic activities as well as some natural sources. In the direction, assessment of water quality analysis is the basic requirement for nurturing human being and its evolution. Water Quality Index (WQI) parameter has been widely used in determining water quality globally. Conventional method used for computing WQI is tedious and takes longer time because it involved processing for larger datasets. The present investigation aims to provide the suitability of groundwater in the specified region using GIS (Geographic Information System) of physiochemical parameters, that are used in drinking purpose, domestic works and household chores. Locations are marked using GPS and the parameters are also used to find out about the WQI (Water Quality Index). The parameters are compared with the BIS (Bureau of India Standards) for checking the suitability of groundwater. The present approach output can be beneficial to the administrators in making decisions on groundwater quality but also gaining inside into the trade of between system benefit and environment requirement.

An assessment of spatial pattern of urban sprawl in JOS metropolis of plateau state, Nigeria: Using remote sensing and GIS techniques

In Jos metropolis, urban sprawl debate has closely paralleled on urban growth trends over the past few decades. These studies indicate that it is the pattern, types, density and rate of new urban growth that creates the appearance of sprawl. Population dynamics are often cited as a driving force behind urban sprawl. This paper uses Geographic Information Systems (GIS) mapping and land cover change analysis, neighbourhood statistics, cross change detection techniques, field work on Urban sprawl areas in Jos metropolis. The paper also highlights the characteristics, types, rates, pattern and density of sprawl to examine the spatial pattern of sprawl in Jos North and Jos South. Linear sprawl pattern can only be visually seen by the road, the roads in Jos play important role in linear pattern of urban sprawl formation through road data, it helped to visualize clearly the areas of linear sprawl in Jos metropolis. An example can be visually seen in Naraguta area, part of a large high residential development of Jos north. Cluster types of urban sprawl settlement development in Jos metropolis. From the map, it shows that cluster types of sprawls in study area are found in the core city of Jos metropolis like Jos city and Bukuru in the study area. Cluster type of urban sprawl also appeared to grow out of what was once a leapfrog pattern of development in some area in the study area. Leapfrog patterns of urban sprawl appeared to be somewhat disconnected from other areas of existing developed settlement land. Leapfrog types of urban sprawl in Jos metropolis can be seen in Kuru North, Dan Miangu, Barakin Kuru and Kuru Hills.After the map of the densities urban sprawl for new growth areas has been created. The study reveals that settlement area has increase from 125.45 to 208.16 sq.km between 2002-2022 in twenty years period. It also revealed that water bodies have also drastically reduced by 3.33 sq.km and open space land use contributed about 127.57 km2 land converted to settlement within the time under study. Further analysis reveals that the urban settlement land of the area increased approximately 82.71 km2 in the twenty years’ time period of the study (2002 to 2022). Next, the patterns of urban expansions were analyzed by using mapping capabilities within the GIS and neighborhood statistics in order to show the density and connectivity of patches of new growth. Based on the density and connectivity of new growth areas, the patterns of growth were classified as: linear along highways, cluster, and leapfrog. The threshold densities are; 0 to 2000 as 30-meter pixels per km2 for low density, 2000 to 25000 for medium density, and 25000 to 130000 for high density. The results indicate that Jos metropolis did experience an increase in urban growth from 2002 to 2022 and that urban growth in the study area can be classified as urban sprawl. The density of new development is more in Jos North, but the pattern and character with which development has occurred in Jos North is synonymous with sprawl in Jos South. the type, rate and patterns of urban expansions were analyzed by using mapping capabilities within the GIS and neighborhood statistics in order to show the density and connectivity of patches of new growth in the study area.