scholarly journals Assessment of the Impact of a Motorway on Content andSpatial Distribution of Mercury in Adjacent Agricultural Soils

Minerals ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1221
Author(s):  
Hanna Jaworska ◽  
Joanna Klimek
Keyword(s):  
Crop Protection ◽  
Spatial Relationship ◽  
Mercury Content ◽  
Test Point ◽  
Moran’S I ◽  
Arable Soils ◽  
Weighted Interpolation ◽  
Moran's I ◽  
Noise Barrier ◽  
The Impact

The distribution of Hg in the vicinity of roads is probably not exclusively dependent on car emissions, but also on the presence of other point or diffuse sources of Hg emissions located from metres to several km away. The source of mercury in urbanised areas is pollution derived from the burning of fuels and industrial and transport waste, while in agricultural areas, it is constituent in mineral fertilisers and crop protection products. The research objective was to evaluate the content and spatial distribution of mercury in arable soils adjacent to the A1 motorway in Poland. The research material consisted of 40 soil samples taken from 20 test points on four transects at distances of 5, 10, 25 and 50 m from a noise barrier and in the direction of an arable field, and 10 m from the noise barrier in the direction of the motorway. Total mercury content was determined by atomic absorption spectrometry using an AMA 254 analyser. The spatial relationship between adjacent observations of variables was assessed using Moran’s I overall autocorrelation coefficient. Probability maps of mercury distribution in the field and pollution indicators were elaborated in ArcGIS 10.4.1. using Inverse Distance Weighted interpolation. Analysis of the spatial correlation of Moran’s I showed a lack of spatial dependence between tested points, which may evidence that the motorway does not affect mercury contents in the soil. The elevated mercury content at a single test point may indicate a random event unrelated to the motorway’s operation.

scholarly journals Can health service equity alleviate the health expenditure poverty of Chinese patients? Evidence from the CFPS and China health statistics yearbook

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shaoliang Tang ◽  
Ling Yao ◽  
Chaoyu Ye ◽  
Zhengjun Li ◽  
Jing Yuan ◽  
...  
Keyword(s):  
Health Service ◽  
Health Expenditure ◽  
Negative Impact ◽  
Medical Insurance ◽  
Moran’S I ◽  
Chinese Patients ◽  
Index Formula ◽  
Moran's I ◽  
Per Capita ◽  
The Impact

Abstract Objectives To comprehend the relationship between various indicators of health service equity and patients’ health expenditure poverty in different regions of China, identify areas where equity in health service is lacking and provide ideas for improving patients’ health expenditure poverty. Method Data from China Family Panel Studies (CFPS) in 2018 and the HFGT index formula were used to calculate the health expenditure poverty index of each province. Moreover, Global Moran’s I and Local Moran’s I test are applied to measure whether there is spatial aggregation of health expenditure poverty. Finally, an elastic net regression model is established to analyze the impact of health service equity on health expenditure poverty, with the breadth of health expenditure poverty as the dependent variable and health service equity as the independent variable. Results In the developed eastern provinces of China, the breadth of health expenditure poverty is relatively low. There is a significant positive spatial agglomeration. “Primary medical and health institutions per 1,000 population”, “rural doctors and health workers per 1,000 population”, “beds in primary medical institutions per 1,000 population”, “proportion of government health expenditure” and “number of times to participate in medical insurance (be aided) per 1,000 population” have a positive impact on health expenditure poverty. “Number of health examinations per capita” and “total health expenditure per capita” have a negative impact on health expenditure poverty. Both effects passed the significance test. Conclusion To enhance the fairness of health resource allocation in China and to alleviate health expenditure poverty, China should rationally plan the allocation of health resources at the grassroots level, strengthen the implementation of hierarchical diagnosis and treatment and encourage the investment in business medical insurance industry. Meanwhile, it is necessary to increase the intensity of medical assistance and enrich financing methods. All medical expenses of the poorest should be covered by the government.

scholarly journals Research on Spatial Correlations and Influencing Factors of Logistics Industry Development Level

2019 ◽  
Vol 11 (5) ◽  
pp. 1356 ◽  
Author(s):  
Xinbao Tian ◽  
Meirong Zhang
Keyword(s):  
Spatial Relationship ◽  
Moran’S I ◽  
Spatial Error ◽  
Moran's I ◽  
Spatial Agglomeration ◽  
Logistics Industry ◽  
Industry Development ◽  
Agglomeration Effect ◽  
Development Level ◽  
Relationship Of

The logistics industry plays a greater role in the sustainable development of regional economies. The development of the logistics industry between regions is not independent, and there is a spatial correlation due to the existence of spatial spillover effect or spatial expansion among regions. This paper uses the method of entropy weight to evaluate the development level of the logistics industry in 31 provinces in China. On this basis, Moran’s index (Moran’s I), Moran’s I scatter plot, and local indicators of spatial association (LISA) agglomeration plot are used to analyze the overall and local spatial agglomeration characteristics of the logistics industry. Four main factors affecting the spatial relationship of the logistics industry are analyzed by choosing the fixed effect of the spatial error model. We find that: (i) There is spatial agglomeration effect in the development level of the logistics industry from the overall perspective; (ii) regional differentiation of the spatial agglomeration effect of logistics industry development level is obvious from the local perspective; and (iii) the influence of human resource factors on the spatial relationship of logistics development level is declining.

scholarly journals Measuring The Impact of Spatial Perturbations on The Relationship Between Data Privacy and Validity of Descriptive Statistics

2020 ◽  
Author(s):  
Kelly Broen ◽  
Rob Trangucci ◽  
Jon Zelner
Keyword(s):  
Spatial Statistics ◽  
Spatial Patterns ◽  
Spatial Data ◽  
Data Privacy ◽  
Perturbation Methods ◽  
Descriptive Statistics ◽  
Moran’S I ◽  
Mortality Data ◽  
Moran's I ◽  
The Impact

Abstract Background: Like many scientific fields, epidemiology is addressing issues of research reproducibility. Spatial epidemiology, which often uses the inherently identifiable variable of participant address, must balance reproducibility with participant privacy. In this study, we assess the impact of several different data perturbation methods on key spatial statistics and patient privacy. Methods: We analyzed the impact of perturbation on spatial patterns in the full set of address- level mortality data from Lawrence, MA during the period from 1911-1913. The original death locations were perturbed using seven different published approaches to stochastic and deterministic spatial data anonymization. Key spatial descriptive statistics were calculated for each perturbation, including changes in spatial pattern center, Global Moran’s I, Local Moran’s I, distance to the k-th nearest neighbors, and the L-function (a normalized form of Ripley’s K). A spatially adapted form of k-anonymity was used to measure the privacy protection conferred by each method, and the its compliance with HIPAA privacy standards. Results: Random perturbation at 50 meters, donut masking between 5 and 50 meters, and Voronoi masking maintain the validity of descriptive spatial statistics better than other perturbations. Grid center masking with both 100x100 and 250x250 meter cells led to large changes in descriptive spatial statistics. None of the perturbation methods adhered to the HIPAA standard that all points have a k-anonymity > 10. All other perturbation methods employed had at least 265 points, or over 6%, not adhering to the HIPAA standard. Conclusions: Using the set of published perturbation methods applied in this analysis, HIPAA- compliant de-identification was not compatible with maintaining key spatial patterns as measured by our chosen summary statistics. Further research should investigate alternate methods to balancing tradeoffs between spatial data privacy and preservation of key patterns in public health data that are of scientific and medical importance.

scholarly journals Evaluation of the Operation Process of Medical Equipment to Enhance Ergonomic Reliability Based on FRAM–Moran’s I and CREAM

2021 ◽  
Vol 12 (1) ◽  
pp. 200
Author(s):  
Xin Liu ◽  
Zheng Liu ◽  
Kang-Chao Lin ◽  
Zhi-Lin Huang ◽  
Ming-Yu Ling ◽  
...  
Keyword(s):  
Individual Differences ◽  
Medical Equipment ◽  
Evaluation Method ◽  
Moran’S I ◽  
Analysis Method ◽  
Moran's I ◽  
Operation Process ◽  
Order Preference ◽  
The Individual ◽  
The Impact

To improve the ergonomic reliability of medical equipment design during the operation process, a method for evaluating the operating procedure of a medical equipment interface according to functional resonance analysis method (FRAM)-Moran’s I and cognitive reliability and error analysis method (CREAM) is proposed in this study. The novelty of this research is to analyze the ergonomic reliability of medical equipment in a more systematic manner and to minimize the impact of human subjectivity and individual differences on the evaluation results of the operation process. To solve the calculation problem of functional resonance in FRAM and to make the evaluation results more objective, Moran’s I was introduced to quantify the deviation degree caused by the individual differences of the subjects. By giving weights based on Moran’s I, the influence of individual differences and subjectivity on the evaluation results can be minimized, to a certain extent. Considering the importance of a special environment, which is not fully considered by the conventional CREAM, the weighting values based on Moran’s I, Delphi survey, and technique for order preference by similarity to an ideal solution (TOPSIS) were adopted to assign weights to common performance conditions (CPCs) in CREAM. The optimal design scheme was selected more objectively than in the conventional method. The validity and practicability of this operation process evaluation method was verified by a statistical method based on ergonomic reliability experiments.

scholarly journals Measuring the impact of spatial perturbations on the relationship between data privacy and validity of descriptive statistics

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Kelly Broen ◽  
Rob Trangucci ◽  
Jon Zelner
Keyword(s):  
Spatial Statistics ◽  
Spatial Patterns ◽  
Spatial Data ◽  
Data Privacy ◽  
Perturbation Methods ◽  
Descriptive Statistics ◽  
Moran’S I ◽  
Mortality Data ◽  
Moran's I ◽  
The Impact

Abstract Background Like many scientific fields, epidemiology is addressing issues of research reproducibility. Spatial epidemiology, which often uses the inherently identifiable variable of participant address, must balance reproducibility with participant privacy. In this study, we assess the impact of several different data perturbation methods on key spatial statistics and patient privacy. Methods We analyzed the impact of perturbation on spatial patterns in the full set of address-level mortality data from Lawrence, MA during the period from 1911 to 1913. The original death locations were perturbed using seven different published approaches to stochastic and deterministic spatial data anonymization. Key spatial descriptive statistics were calculated for each perturbation, including changes in spatial pattern center, Global Moran’s I, Local Moran’s I, distance to the k-th nearest neighbors, and the L-function (a normalized form of Ripley’s K). A spatially adapted form of k-anonymity was used to measure the privacy protection conferred by each method, and its compliance with HIPAA and GDPR privacy standards. Results Random perturbation at 50 m, donut masking between 5 and 50 m, and Voronoi masking maintain the validity of descriptive spatial statistics better than other perturbations. Grid center masking with both 100 × 100 and 250 × 250 m cells led to large changes in descriptive spatial statistics. None of the perturbation methods adhered to the HIPAA standard that all points have a k-anonymity > 10. All other perturbation methods employed had at least 265 points, or over 6%, not adhering to the HIPAA standard. Conclusions Using the set of published perturbation methods applied in this analysis, HIPAA and GDPR compliant de-identification was not compatible with maintaining key spatial patterns as measured by our chosen summary statistics. Further research should investigate alternate methods to balancing tradeoffs between spatial data privacy and preservation of key patterns in public health data that are of scientific and medical importance.

scholarly journals The Impact of Inter-City Traffic Restriction on COVID-19 Transmission from Spatial Econometric Perspective

2021 ◽  
Vol 33 (5) ◽  
pp. 705-716
Author(s):  
Xijin Lu ◽  
Changxi Ma
Keyword(s):  
Spatial Correlation ◽  
Goodness Of Fit ◽  
Ordinary Least Squares ◽  
Hubei Province ◽  
Error Model ◽  
Moran’S I ◽  
Spatial Error ◽  
Moran's I ◽  
Spatial Lag ◽  
The Impact

The aim of this paper is to conduct a spatial correlation study of virus transmission in the Hubei province, China. The number of confirmed COVID-19 cases released by the National Health and Construction Commission, the traffic flow data provided by Baidu migration, and the current situation of Wuhan intercity traffic were collected. The Moran’s I test shows that there is a positive spatial correlation between the 17 cities in the Hubei province. The result of Moran’s I test also shows that four different policies to restrict inter-city traffic can be issued for the four types of cities. The ordinary least squares regression, spatial lag model, spatial error model, and spatial lag error model were built. Based on the analysis of the spatial lag error model, whose goodness of fit is the highest among the four models, it can be concluded that the speed of COVID-19 spread within a certain region is not only related to the current infection itself but also associated with the scale of the infection in the surrounding area. Thus, the spill-over effect of the COVID-19 is also presented. This paper bridges inter-city traffic and spatial economics, provides a theoretical contribution, and verifies the necessity of a lockdown from an empirical point of view.

scholarly journals Autocorrelation of Spatial Based Dengue Hemorrhagic Fever Cases in Air Putih Area, Samarinda City

2020 ◽  
Vol 12 (2) ◽  
pp. 78
Author(s):  
Syamsir Syamsir ◽  
Dwi Murdaningsih Pangestuty
Keyword(s):  
Spatial Autocorrelation ◽  
Health Center ◽  
Dengue Hemorrhagic Fever ◽  
Control Program ◽  
Hemorrhagic Fever ◽  
Moran’S I ◽  
Autocorrelation Analysis ◽  
Index Method ◽  
Moran's I ◽  
The Impact

Introduction: Dengue Hemorrhagic Fever (DHF) is the disease that spread quickly in tropical and subtropical regions. DHF can spread quickly because the dengue virus is transmitted through the Aedes aegypti and Aedes albopictus into the human body. One of the provinces that felt the impact of the dengue outbreak was East Kalimantan, especially Samarinda City. Efforts to prevent dengue have been attempted by health center officials in Samarinda City. The cause has not yet been effective in controlling DHF programs in Samarinda City because there is no mapping of DHF vulnerable areas. This study aims to map the pattern of DHF distribution in the working area of the health center to maximize the implementation of the DHF control program. Methods: The population in this study were all DHF sufferers registered at the Air Putih Health Center in 2018. Withdrawal samples using total sampling techniques. The analysis used in this study is spatial autocorrelation analysis by Moran’s I. The Moran Index method is used to determine the autocorrelation of the distribution of DHF cases. Result and Discussion: The results of the autocorrelation analysis showed a Z score <-Z α/2, meaning Ho was rejected. This shows that there is spatial autocorrelation in the distribution of DHF in the Health Center. Based on the Moran’s I value (Moran’s I = -0.045850) which has a negative value indicates that the distribution of DHF in the working area of the Health Center tends to spread or dispersed. Conclusion: This study concludes that the more cases of DHF in a densely populated area, the greater the chance of spatial autocorrelation. The closeness between DHF cases can form spatial autocorrelation with the dispersed category.

Spatial Pattern of Cholera Incidence in Ibadan City

2014 ◽  
Vol 1 (1) ◽  
pp. 112-120
Author(s):  
E. A. Salubi
Keyword(s):  
Spatial Pattern ◽  
Moran’S I ◽  
Moran's I ◽  
Environmental Sanitation ◽  
The Core ◽  
Statistiquement Significatives ◽  
Eau Potable ◽  
Core Areas ◽  
The Impact ◽  
The City

The recurrence of the cholera outbreak in Ibadan is alarming and very little has been documented on its spatial pattern. Hence, this study investigated the spatial pattern of cholera in Ibadan using GIS techniques and spatial statistics. Cholera is a disease that has been known to be associated with poor environmental sanitation. However, the impact of other contributory factors is also becoming evident. The study investigated the pattern of cholera incidence within the city for a period of three years. The process of geocoding was used to match addresses of cholera patients to the districts within Ibadan city. Anselin's Local Moran's I was used to assess statistically significant clusters within the city. The results depict clusters of cholera incidences located more within the core areas of the city characterized by high population density and poor sanitation. This study suggests improved environmental sanitation and provision of potable water supply to the core areas of the city. La récurrence de l'épidémie de choléra à Ibadan est alarmante et très peu a été documentée sur sa configuration spatiale. Par conséquent, cette étude a examiné le schéma spatial du choléra à Ibadan en utilisant des techniques SIG et des statistiques spatiales. Le choléra est une maladie connue pour être associée à un mauvais assainissement de l'environnement. Cependant, l'impact d'autres facteurs contributifs devient également évident. L'étude a examiné le schéma de l'incidence du choléra dans la ville pendant une période de trois ans. Le processus de géocodage a été utilisé pour faire correspondre les adresses des patients atteints de choléra aux districts de la ville d'Ibadan. Le Local Moran's I d'Anselin a été utilisé pour évaluer les grappes statistiquement significatives au sein de la ville. Les résultats décrivent des grappes d'incidences de choléra situées davantage dans les zones centrales de la ville caractérisées par une forte densité de population et un assainissement médiocre. Cette étude suggère une amélioration de l'assainissement de l'environnement et de l'approvisionnement en eau potable dans les zones centrales de la ville.

Analisis Perubahan Tata Guna Lahan di Kabupaten Bantul Menggunakan Metode Global Moran’s I

2017 ◽  
Vol 8 (4) ◽  
Author(s):  
Matheus Supriyanto Rumetna ◽  
Eko Sediyono ◽  
Kristoko Dwi Hartomo
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Spatial Autocorrelation ◽  
Land Use Changes ◽  
Geographical Information ◽  
Moran’S I ◽  
Complete Spatial Randomness ◽  
Moran's I ◽  
Global Moran’S I ◽  
Spatial Randomness

Abstract. Bantul Regency is a part of Yogyakarta Special Province Province which experienced land use changes. This research aims to assess the changes of shape and level of land use, to analyze the pattern of land use changes, and to find the appropriateness of RTRW land use in Bantul District in 2011-2015. Analytical methods are employed including Geoprocessing techniques and analysis of patterns of distribution of land use changes with Spatial Autocorrelation (Global Moran's I). The results of this study of land use in 2011, there are thirty one classifications, while in 2015 there are thirty four classifications. The pattern of distribution of land use change shows that land use change in 2011-2015 has a Complete Spatial Randomness pattern. Land use suitability with the direction of area function at RTRW is 24030,406 Ha (46,995406%) and incompatibility of 27103,115 Ha or equal to 53,004593% of the total area of Bantul Regency.Keywords: Geographical Information System, Land Use, Geoprocessing, Global Moran's I, Bantul Regency. Abstrak. Analisis Perubahan Tata Guna Lahan di Kabupaten Bantul Menggunakan Metode Global Moran’s I. Kabupaten Bantul merupakan bagian dari Provinsi Daerah Istimewa Yogyakarta yang mengalami perubahan tata guna lahan. Penelitian ini bertujuan untuk mengkaji perubahan bentuk dan luas penggunaan lahan, menganalisis pola sebaran perubahan tata guna lahan, serta kesesuaian tata guna lahan terhadap RTRW yang terjadi di Kabupaten Bantul pada tahun 2011-2015. Metode analisis yang digunakan antara lain teknik Geoprocessing serta analisis pola sebaran perubahan tata guna lahan dengan Spatial Autocorrelation (Global Moran’s I). Hasil dari penelitian ini adalah penggunaan tanah pada tahun 2011, terdapat tiga puluh satu klasifikasi, sedangkan pada tahun 2015 terdapat tiga puluh empat klasifikasi. Pola sebaran perubahan tata guna lahan menunjukkan bahwa perubahan tata guna lahan tahun 2011-2015 memiliki pola Complete Spatial Randomness. Kesesuaian tata guna lahan dengan arahan fungsi kawasan pada RTRW adalah seluas 24030,406 Ha atau mencapai 46,995406 % dan ketidaksesuaian seluas 27103,115 Ha atau sebesar 53,004593 % dari total luas wilayah Kabupaten Bantul. Kata Kunci: Sistem Informasi Georafis, tata guna lahan, Geoprocessing, Global Moran’s I, Kabupaten Bantul.

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