scholarly journals Spatio-Temporal Analysis of Urban Crime Pattern and its Implication for Abuja Municipal Area Council, Nigeria

2017 ◽  
Vol 49 (2) ◽  
pp. 145
Author(s):  
Taiye Oluwafemi Adewuyi ◽  
Patrick Ali Eneji ◽  
Anthonia Silas Baduku ◽  
Emmanuel Ajayi Olofin
Keyword(s):  
Information System ◽  
Spatial Data ◽  
Temporal Analysis ◽  
Urban Crime ◽  
High Rate ◽  
Geographical Information ◽  
Positioning Systems ◽  
Spatio Temporal ◽  
Gis Environment ◽  
Crime Pattern

This study examined the spatio-temporal analysis of urban crime pattern and its implication for Abuja Municipal Area Council of the Federal Capital Territory of Nigeria; it has the aim of using Geographical Information System to improve criminal justice system. The aim was achieved by establishing crime incident spots, types of crime committed, the time it occurred and factors responsible for prevailing crime. The methods for data collection involved Geoinformatics through the use of remote sensing and Global Positioning Systems (GPS) for spatial data. Questionnaires were administered for other attribute information required. The analysis carried out in a Geographic Information System (GIS) environment especially for mapping and the establishment of spatial patterns.  The results indicated that the main types of crime committed were theft and house breaking (42.9%), followed by assault (12.4%), mischief (11.3%), forgery (10.5%), car snatching (9.05%), armed robbery (8.5%), trespass (5.2%) and culpable homicide (0.2%). In terms of hot spots the districts recorded the following: Garki (27.62%), Maitama (25.7%), Utako (24.3%), Wuse (20.9%) and Asokoro district (1.4%) respectively with most of the crime committed during the day time. Many attributed the crimes to mainly high rate of unemployment and poverty (79.1%). Consequently to reduce the crime rate, the socio-economic situation of the city must be improved through properly constructed interventions scheme in areas known to quickly generate employment such as agriculture, small and medium scale enterprises, mining and tourism. 

scholarly journals Spatio-temporal epidemiology of the tuberculosis incidence rate in Iran 2008 to 2018

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Behzad Kiani ◽  
Amene Raouf Rahmati ◽  
Robert Bergquist ◽  
Soheil Hashtarkhani ◽  
Neda Firouraghi ◽  
...  
Keyword(s):  
High Risk ◽  
Incidence Rate ◽  
Policy Development ◽  
Temporal Pattern ◽  
Temporal Analysis ◽  
High Rate ◽  
Spatial Scan Statistic ◽  
Cross Sectional ◽  
Risk Areas ◽  
Spatio Temporal

Abstract Background Effective reduction of tuberculosis (TB) requires information on the distribution of TB incidence rate across time and location. This study aims to identify the spatio-temporal pattern of TB incidence rate in Iran between 2008 and 2018. Methods This cross-sectional study was conducted on aggregated TB data (50,500 patients) at the provincial level provided by the Ministry of Health in Iran between 2008 and 2018. The Anselin Local Moran’s I and Getis-Ord Gi* were performed to identify the spatial variations of the disease. Furthermore, spatial scan statistic was employed for purely temporal and spatio-temporal analyses. In all instances, the null hypothesis of no clusters was rejected at p ≤ 0.05. Results The overall incidence rate of TB decreased from 13.46 per 100,000 (95% CI: 13.19–13.73) in 2008 to 10.88 per 100,000 (95% CI: 10.65–11.11) in 2018. The highest incidence rate of TB was observed in southeast and northeast of Iran for the whole study period. Additionally, spatial cluster analysis discovered Khuzestan Province, in the West of the country, having significantly higher rates than neighbouring provinces in terms of both total TB and smear-positive pulmonary TB (SPPTB). Purely temporal analysis showed that high-rate and low-rate clusters were predominantly distributed in the time periods 2010–2014 and 2017–2018. Spatio-temporal results showed that the statistically significant clusters were mainly distributed from centre to the east during the study period. Some high-trend TB and SPPTB statistically significant clusters were found. Conclusion The results provided an overview of the latest TB spatio-temporal status In Iran and identified decreasing trends of TB in the 2008–2018 period. Despite the decreasing incidence rate, there is still need for screening, and targeting of preventive interventions, especially in high-risk areas. Knowledge of the spatio-temporal pattern of TB can be useful for policy development as the information regarding the high-risk areas would contribute to the selection of areas needed to be targeted for the expansion of health facilities.

scholarly journals Application of Geographical Information System Techniques to Determine High Crash-Prone Areas in the Fort Peck Indian Reservation

2020 ◽  
Vol 14 (1) ◽  
pp. 174-185
Author(s):  
Sahima Nazneen ◽  
Mahdi Rezapour ◽  
Khaled Ksaibati
Keyword(s):  
Information System ◽  
High Risk ◽  
Injury Severity ◽  
Statistical Significance ◽  
Temporal Analysis ◽  
The United States ◽  
Geographical Information ◽  
Improvement Program ◽  
Indian Reservation ◽  
Road Segments

Background: Historically, Indian reservations have been struggling with higher crash rates than the rest of the United States. In an effort to improve roadway safety in these areas, different agencies are working to address this disparity. For any safety improvement program, identifying high risk crash locations is the first step to determine contributing factors of crashes and select corresponding countermeasures. Methods: This study proposes an approach to determine crash-prone areas using Geographic Information System (GIS) techniques through creating crash severity maps and Network Kernel Density Estimation (NetKDE). These two maps were assessed to determine the high-risk road segments having a high crash rate, and high injury severity. However, since the statistical significance of the hotspots cannot be evaluated in NetKDE, this study employed Getis-Ord Gi* (d) statistics to ascertain statistically significant crash hotspots. Finally, maps generated through these two methods were assessed to determine statistically significant high-risk road segments. Moreover, temporal analysis of the crash pattern was performed using spider graphs to explore the variance throughout the day. Results: Within the Fort Peck Indian Reservation, some parts of the US highway 13, BIA Route 1, and US highway 2 are among the many segments being identified as high-risk road segments in this analysis. Also, although some residential roads have PDO crashes, they have been detected as high priority areas due to high crash occurrence. The temporal analysis revealed that crash patterns were almost similar on the weekdays reaching the peak at traffic peak hours, but during the weekend, crashes mostly occurred at midnight. Conclusion: The study would provide tribes with the tool to identify locations demanding immediate safety concerns. This study can be used as a template for other tribes to perform spatial and temporal analysis of the crash patterns to identify high risk crash locations on their roadways.

scholarly journals Spatio-temporal Analysis of Maximum and Minimum Temperature in Bangladesh

2015 ◽  
Vol 7 (2) ◽  
pp. 73-77 ◽  
Author(s):  
MN Uddin ◽  
MSA Mondal ◽  
NMR Nasher
Keyword(s):  
Spatial Distribution ◽  
Minimum Temperature ◽  
Statistical Significance ◽  
Temporal Analysis ◽  
Temperature Data ◽  
Spatially Distributed ◽  
Spatio Temporal ◽  
Gis Environment ◽  
Maximum Temperatures ◽  
Kendall Method

The analysis of annual mean maximum and annual mean minimum temperature data are studied in GIS environment, obtained from 34 meteorological stations scattered throughout the Bangladesh from 1948 to 2013. IDW method was used for the spatial distribution of temperature over the study area, using ArcGIS 10.2 software. Possible trends in the spatially distributed temperature data were examined, using the non-parametric Mann-Kendall method with statistical significance, and the magnitudes of available trends were determined using Sen’s method in ArcMap depiction. The findings of the study show positive trends in annual mean maximum temperatures with 90%, 95%, 99% and 99.9% significance levels.DOI: http://dx.doi.org/10.3329/jesnr.v7i2.22210 J. Environ. Sci. & Natural Resources, 7(2): 73-77 2014

scholarly journals Spatial and spatio-temporal statistical analyses of retinal images: a review of methods and applications

2020 ◽  
Vol 5 (1) ◽  
pp. e000479
Author(s):  
Wenyue Zhu ◽  
Ruwanthi Kolamunnage-Dona ◽  
Yalin Zheng ◽  
Simon Harding ◽  
Gabriela Czanner
Keyword(s):  
Statistical Methods ◽  
Spatial Data ◽  
Temporal Analysis ◽  
Statistical Analyses ◽  
Retinal Images ◽  
Imaging Data ◽  
Spatial Correlations ◽  
Clinical Variables ◽  
Text Information ◽  
Spatio Temporal

BackgroundClinical research and management of retinal diseases greatly depend on the interpretation of retinal images and often longitudinally collected images. Retinal images provide context for spatial data, namely the location of specific pathologies within the retina. Longitudinally collected images can show how clinical events at one point can affect the retina over time. In this review, we aimed to assess statistical approaches to spatial and spatio-temporal data in retinal images. We also review the spatio-temporal modelling approaches used in other medical image types.MethodsWe conducted a comprehensive literature review of both spatial or spatio-temporal approaches and non-spatial approaches to the statistical analysis of retinal images. The key methodological and clinical characteristics of published papers were extracted. We also investigated whether clinical variables and spatial correlation were accounted for in the analysis.ResultsThirty-four papers that included retinal imaging data were identified for full-text information extraction. Only 11 (32.4%) papers used spatial or spatio-temporal statistical methods to analyse images, others (23 papers, 67.6%) used non-spatial methods. Twenty-eight (82.4%) papers reported images collected cross-sectionally, while 6 (17.6%) papers reported analyses on images collected longitudinally. In imaging areas outside of ophthalmology, 19 papers were identified with spatio-temporal analysis, and multiple statistical methods were recorded.ConclusionsIn future statistical analyses of retinal images, it will be beneficial to clearly define and report the spatial distributions studied, report the spatial correlations, combine imaging data with clinical variables into analysis if available, and clearly state the software or packages used.

Applications of Geographical Information System in E-Government

2011 ◽  
pp. 80-86
Author(s):  
Y. Yongling
Keyword(s):  
Information System ◽  
Spatial Analysis ◽  
Geographical Information System ◽  
Real World ◽  
Spatial Data ◽  
Geographical Information ◽  
The Real ◽  
Definition Of ◽  
At Will

Geographical information system (GIS) is one kind of information system that handles spatial data. It is difficult to give one definitive definition about GIS (Heywood, Cornelius, & Carver, 2002; Maguire, Goodchild, & Rhind, 2001). This variety of definitions can be explained by the fact that any definition of GIS will depend on who is giving it, and their background and viewpoint (Pinkles, 2002). The complete definition of GIS is selected here as: “a set of tools for collecting, storing, retrieving at will, transforming, and displaying spatial data from the real world for a particular set of purposes”(Burrough, 1986, p. 6). As an important part of e-government, is that it has functions of cartography, manages spatial data and spatial analysis.

scholarly journals Sustainable Development: Evaluating Optimal Technique for Spatial Data Forecast

Proceedings ◽  
2018 ◽  
Vol 2 (22) ◽  
pp. 1371
Author(s):  
Gaurav Kumar ◽  
Rajiv Gupta
Keyword(s):  
Information System ◽  
Spatial Data ◽  
Satellite Images ◽  
Moving Average ◽  
Vegetation Indices ◽  
Geographical Information ◽  
One Dimensional ◽  
Regression Methods ◽  
Gis Tools ◽  
Normalized Difference Vegetation Indices

This paper is an approach to forecast the spatial data in time series domain. Normally in GIS (Geographical Information System), we need raster forecasting. Moving average, exponential smoothing, and linear regression methods of forecasting are used over one-dimensional data. Present work concentrates on using these methods on satellite images applying them from pixel to pixel of historical temporal satellite data. An example set of satellite images from years 2011 to 2015 has been used to forecast the image in the year 2016. GIS tools have been developed in ArcGIS 10.1 using python to implement the methods of forecasting. Forecasted and actual images of the year 2016 have been compared by calculating the Normalized Difference Vegetation Indices (NDVI) and change detection to identify the best method.

Research on Visualization of Spatial Data and Symbols Based on ArcGIS

2012 ◽  
Vol 241-244 ◽  
pp. 3107-3111
Author(s):  
Xu Dan Sun
Keyword(s):  
Information System ◽  
Geographical Information System ◽  
Spatial Data ◽  
Geographical Information ◽  
Space Environment ◽  
Point Line

To the problem of visualization expression, under the ArcGIS space environment, I use the ArcObjects components to do the symbols allocation and visualization expression for spatial data and point, line and polygon target. Result shows that it has finished the visualization effect of spatial data and symbols in the geographical information system.

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