Relevant bibliographies by topics / Local Getis-Ord statistics

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Academic literature on the topic 'Local Getis-Ord statistics'

Author: Grafiati
Published: 3 June 2025
Last updated: 13 July 2025

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Journal articles on the topic "Local Getis-Ord statistics"

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Leung, Yee, Chang-Lin Mei, and Wen-Xiu Zhang. "Statistical Test for Local Patterns of Spatial Association." Environment and Planning A: Economy and Space 35, no. 4 (2003): 725–44. http://dx.doi.org/10.1068/a3550.

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In recent years, there has been a growing interest in the use of local measures such as Anselin's LISAs and Ord and Getis G statistics to identify local patterns of spatial association. The statistical significance test based on local statistics is one of the most important aspects in performing this kind of analysis, and a randomized permutation approach and normal approximation are commonly used to derive the p-values of the statistics. To circumvent some of the shortcomings of these existing methods and to offer a more formal approach in line with classical statistical framework, we develop in this paper an exact method for computing the p-values of the local Moran's Ii, local Geary's ci, and the modified Ord and Getis G statistics based on the distributional theory of quadratic forms in normal variables. Furthermore, an approximate method, called three-moment χ2 approximation, with explicit calculation formulae is also proposed to achieve a computational cost lower than the exact method. Numerical evaluation on the accuracy of the approximate null distributions of the local statistics demonstrates that the proposed three-moment χ2 method is useful in some situations although it is inappropriate for approximating the null distribution of Ii. The study not only provides an exact test for local patterns of spatial association, but also put the tests of several local statistics within a unified statistical framework.
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Dobryakova, V. A., N. N. Moskvina, and L. F. Zhegalina. "Getis-Ord Gi* statistics at adaptation of perennial hydrocarbon content data in Bolshoy Balyk river basin." Geodesy and Cartography 959, no. 5 (2020): 54–64. http://dx.doi.org/10.22389/0016-7126-2020-959-5-54-64.

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Balyk river basin for the period 2006–2017 using ArcGIS Pro statistical analysis tools are presented in this article. The information basis of the research is the local environment monitoring data of license areas of Ugra, Khanty-Mansiysk Autonomous Okrug, RF. The research was implemented in two stages. At the first stage, pollution hot spots were revealed basing on the calculation of local Getis-Ord Gi* index for each year. The calculation was made taking into account the mutual location of sampling points and value of the neighborhood. At the second stage hot spots genesis for 12 years was analyzed via modelling space-and-time cube. Clustering time series of hydrocarbons average annual concentration according to the Getis-Ord Gi* indicator made it possible to determine the places of one-off pollution, most likely associated with oil spills, and to track pollutants transportation along the current. The location of the increasing river ecosystem pollution was also determined. The obtained results enable bringing out basic zones of permanent high hydrocarbon concentrations and places of periodic discharges into the river basin.
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Dobryakova, Valentina, Natalya Moskvina, Andrey Dobryakov, Lilia Zhegalina, and Ildar Idrisov. "Getis-Ord Gi* statistics for hydrocarbons content analysis in the Tromjegan river basin." InterCarto. InterGIS 26, no. 2 (2020): 151–60. http://dx.doi.org/10.35595/2414-9179-2020-2-26-151-160.

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The information content and effectiveness of ecological research of the territory can be improved using the methods of multivariate analysis and mapping of the results. The article presents the analysis and mapping results of spatial and temporal trends of hydrocarbon pollution in the Tromjegan river basin for the period 2006–2018 using the tools of ArcGIS Pro. The informational and basic research is the data of local environmental monitoring of licensed blocks of the Khanty-Mansiysk Autonomous Okrug — Ugra. Pollution analysis was carried out on the basis of a detailed study of the geography of the source data using statistical calculations (minimum, average, maximum distances between sampling points, Getis-Ord Gi* index). Thematic maps were constructed using data averaged over the year. The spatial and temporal dynamics of hydrocarbons concentration in surface waters for 2006–2018 is analyzed using the “Hot Spot Analysis” tool. A temporary cluster section of hydrocarbons average annual concentration according to the Getis-Ord Gi* indicator allowed us to identify trends in the dynamics of indicators. Maps of hydrocarbons average annual concentration were compiled and the results of a spatial-temporal analysis of hydrocarbons average annual concentration in surface waters were presented. The identification of patterns in large arrays of long-term data and the consideration of the spatial component are necessary elements of modern environmental research. Analysis of the time series of average annual concentrations in the Tromjegan river basin showed a clear trend in the dynamics of hydrocarbon pollution. The findings can be the basis for making managerial decisions in the environmental monitoring of licensed blocks of the Khanty-Mansiysk Autonomous Okrug — Ugra.
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Wang, Zheye, and Nina S. N. Lam. "Extending Getis–Ord Statistics to Account for Local Space–Time Autocorrelation in Spatial Panel Data." Professional Geographer 72, no. 3 (2020): 411–20. http://dx.doi.org/10.1080/00330124.2019.1709215.

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Pasaribu, Ayodhia Pitaloka, Tsheten Tsheten, Muhammad Yamin, et al. "Spatio-Temporal Patterns of Dengue Incidence in Medan City, North Sumatera, Indonesia." Tropical Medicine and Infectious Disease 6, no. 1 (2021): 30. http://dx.doi.org/10.3390/tropicalmed6010030.

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Dengue has been a perennial public health problem in Medan city, North Sumatera, despite the widespread implementation of dengue control. Understanding the spatial and temporal pattern of dengue is critical for effective implementation of dengue control strategies. This study aimed to characterize the epidemiology and spatio-temporal patterns of dengue in Medan City, Indonesia. Data on dengue incidence were obtained from January 2016 to December 2019. Kulldorff’s space-time scan statistic was used to identify dengue clusters. The Getis-Ord Gi* and Anselin Local Moran’s I statistics were used for further characterisation of dengue hotspots and cold spots. Results: A total of 5556 cases were reported from 151 villages across 21 districts in Medan City. Annual incidence in villages varied from zero to 439.32 per 100,000 inhabitants. According to Kulldorf’s space-time scan statistic, the most likely cluster was located in 27 villages in the south-west of Medan between January 2016 and February 2017, with a relative risk (RR) of 2.47. Getis-Ord Gi* and LISA statistics also identified these villages as hotpot areas. Significant space-time dengue clusters were identified during the study period. These clusters could be prioritized for resource allocation for more efficient prevention and control of dengue.
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Kurek, Sławomir, Mirosław Wójtowicz, and Jadwiga Gałka. "Using Spatial Autocorrelation for identification of demographic patterns of Functional Urban Areas in Poland." Bulletin of Geography. Socio-economic Series 52, no. 52 (2021): 123–44. http://dx.doi.org/10.2478/bog-2021-0018.

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Abstract Functional Urban Areas (FUAs) leads to a better knowledge of urban spatial organisation, which may play a significant role in regional policy making and may be helpful in understanding the connection between urbanisation and demographic development. An explanation of population change in urban regions can be associated the second demographic transition comprising fertility decline below replacement level and postponement of births. The aim of this paper is to focus on establishing similarity patterns and anomalous values of selected demographic variables in the cores and peripheral areas of Functional Urban Areas. At the background of this study lies an assumption that population development of FUA's is shaped by different factors connected with second demographic transition and migrations. To achieve the aims the following demographic characteristics were used: population growth rate, dependency ratio, rate of natural increase, the net migration rate, and the dynamic economic ageing index, Spatial methods play an increasingly important role in contemporary socio-demographic research. In order to identify spatial systems Global Moran Statistics and the Local Indicators of Spatial Association (LISA) including Local Moran statistics as well as Getis-Ord Gi* statistics were used. The research showed global and local autocorrelation of demographic processes in Functional Urban Areas in Poland, namely population growth, natural increase, net migration and population ageing. The use of local Moran's I statistic and the Getis-Ord Gi* method has led to identification of spatial clusters and dispersions representing different demographic variables. Spatial autocorrelation methods can be useful in an analysis of demographic variables including changes in time. The main contribution of this study to the research on demographic processes in urban areas was an application of spatial groupings techniques not only to find out similarity and dissimilarity patterns of demographic indicators but also to apply this findings for the needs of spatial planning.
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Hazaymeh, Khaled, Ali Almagbile, and Ahmad H. Alomari. "Spatiotemporal Analysis of Traffic Accidents Hotspots Based on Geospatial Techniques." ISPRS International Journal of Geo-Information 11, no. 4 (2022): 260. http://dx.doi.org/10.3390/ijgi11040260.

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This paper aims to explore the spatiotemporal pattern of traffic accidents using five years of data between 2015 and 2019 for the Irbid Governorate, Jordan. The spatial pattern of traffic-accident hotspots and their temporal evolution were identified along the internal and arterial roads network in the study area using spatial autocorrelation (Global Moran I index) and local hotspot analysis (Getis–Ord Gi*) techniques within the GIS environment. The study showed a gradual increase in the reported traffic accidents of approximately 38% at the year level. The analysis of traffic accidents at the severity level showed a distinguished spatial distribution of hotspot locations. The less severe traffic accidents (~95%) occurred on the internal road network in the Irbid Governorate’s towns where the highest traffic volume exist. The spatial autocorrelation analysis and the Getis–Ord Gi* statistics with 99% of significance level showed clustering patterns of traffic accidents along the internal and the arterial road network segments. Between 2015 and 2019, a notable evolution of the traffic-accident hotspots clusters was pronounced. The results can be used to guide traffic managers and decision makers to take appropriate actions for enhancing the hotspot locations and improving their traffic safety status.
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Coca, Oswaldo, and Constanza Ricaurte-Villota. "Regional Patterns of Coastal Erosion and Sedimentation Derived from Spatial Autocorrelation Analysis: Pacific and Colombian Caribbean." Coasts 2, no. 3 (2022): 125–51. http://dx.doi.org/10.3390/coasts2030008.

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Coastal erosion is a common phenomenon along the world’s coasts. Studying it is complex because such studies must cover large portions of land, and it is necessary to understand the multiple processes that interact in each area, so it is important to recognize regional patterns that allow for defining representativeness in relation to the surrounding dynamics. Spatial statistics can be used in coastal geomorphology to identify and quantify trends in coastal morphodynamics. This study analyzes and interprets the spatio-temporal patterns present in the changes in a shoreline, that is, the processes of erosion and coastal sedimentation in the Pacific and the Colombian Caribbean. The results are derived from the detection of significant changes in the coastline via satellite images. For this study, the shoreline of Colombia was digitized for the years 1986 and 2016, thus obtaining changes in the shoreline at a medium temporal scale. The Global Moran’s Index, Local Moran’s Index and Getis–Ord Index were used to explain the spatial statistics. The Global I Moran values for the Pacific were I = 0.190, z = 31.063 and p = 0.01, and for the Caribbean I = 0.624, z = 74.545 and p = 0.01, which suggests good grouping in the Caribbean and very low grouping for the Pacific. The local indices (Moran’s and Getis–Ord) allowed us to visualize and spatialize the significant points of coastal erosion and sedimentation. According to the results, three conceptual models are herein proposed that relate the indices with the geomorphological characteristics: (a) the greater the geomorphological heterogeneity, the greater the grouping; (b) the greater the geomorphological homogeneity, the lower the degree of clustering; (c) the greater the geomorphological complexity, the lower the degree of clustering. Finally, it is confirmed that coastal erosion and sedimentation processes predominate along low coasts.
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SHAMSUTDINOVA, Nailya K., Elmira I. ISIANGULOVA, Irina A. LAKMAN, Vadim B. PRUDNIKOV, and Liana F. SADIKOVA. "Spatial Distribution of Human Development Index in the Regions of Russia." Journal of Advanced Research in Law and Economics 8, no. 8 (2018): 2594. http://dx.doi.org/10.14505//jarle.v8.8(30).31.

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Spatial effects in human development levels among different regions of a territory are important to study in the context of the core-periphery model. We use different methods to study human development index (HDI) for 85 Russian regions. The authors studied the human development index (HDI) for 85 Russian regions. Methods of spatial statistics (econometrics) are used to estimate the ‘spatial gradient’ in economic geography (Moran’s global and local I, Geary’s C, Getis-Ord global G indices). As a weighting matrix we used a contiguity matrix, taking into account the HDI levels only in neighboring regions. Analysis of the global indices of Moran’s I, Geary’s C and Getis-Ord G and Morans scatter plots showed the presence of time-inconsistent spatial autoregressive dependence of the level of HDI in regions of Russia. The ‘spatial gradient’ of the level of human development in Russia is influenced by historically existing imbalances (due to strong oil and gas export-oriented nature of the economy) and insufficient use of human capital. To our view the regional differentiation in human development among the regions is caused primarily by the ‘catching up’ style of Russian economy: human capital is concentrated in regions with already high level of development, although in terms of growth rates Moscow and St. Petersburg are not the leaders. The territorial and geopolitical policies of Russian Federation also influence HDI distribution. For example, huge public investments in the regions of Russian Far East are often ineffective.
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Seman, Busiai Bin, and Tarmiji Masron. "HOTSPOT ANALYSIS OF HAND FOOT AND MOUTH DISEASE (HFMD) USING GIS IN KUCHING, SARAWAK, MALAYSIA." Humanities & Social Sciences Reviews 7, no. 2 (2019): 36–44. http://dx.doi.org/10.18510/hssr.2019.725.

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Purpose of the study: The main objective of this study was to identify the hotspot area of HFMD reported cases within two local councils, namely, Kuching North City Council and Kuching South City Council, by using Geographic Information System (GIS) technique.
 Methodology: Two methods, namely, Getis-Ord GI* and Thiessen polygon, were used in this study. Getis-Ord GI* statistics was used to identify the hotspot areas and Thiessen polygon method was used to create an influencing boundary for each village. The analysis was conducted from 2014 to 2018 on the basis of the cases reported and registered with Sarawak Health Department by using ArcGIS Software.
 Main Findings: The hotspot areas were confined to the Western area of Kuching North City Council, which is located at Rampangi Fasa II and Semariang Pinggir villages. Subsequently, in Kuching South City Council, there were two villages were identified as hotspot areas at Kampung Stampin and Kampung Stutong Baru.
 Applications of this study: The findings from this study will help local authorities, public health officers, epidemiologists, and the public to identify the hotspot areas of HFMD occurrences and therefore, the information obtained in this study will be of a great help to them in coming up with the necessary mitigation plan to control this disease before it spreads to other locations.
 Novelty/Originality of this study: Previous studies conducted in Sarawak on HFMD were based on divisional boundaries, which were too broad to be used as a guide for mitigation planning. Therefore, the outcome from this study, which was based on the village boundary, provides more information on the hotspot areas of HFMD at a micro level.
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Book chapters on the topic "Local Getis-Ord statistics"

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Mauro, Giovanni, Maria Ronza, and Claudio Sossio De Simone. "Agricultural Crops and Spatial Distribution of Migrants: Case Studies in Campania Region (Southern Italy)." In Computational Science and Its Applications – ICCSA 2023 Workshops. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37114-1_28.

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AbstractIn the current context of increasing stabilization of migrants permanently residing in the Campania region (southern Italy), this paper aims to investigate the relationship between the spatial distribution of migrants and the work opportunities in the agricultural sector. We analyse data in the agriculture and population censuses currently available at the municipality level (referring to 2011) and we apply spatial autocorrelation techniques, using the Local Indicator of Spatial Association (LISA) and Getis-Ord Gi* statistic. The maps clusters of migrants (classified by continent) and agricultural crops or breeding (horticulture, orchards and citrus, buffalo and poultry farms), highlight a positive spatial correspondence between resulting hot spots. Finally, we overlay the resulting cluster maps to understand the significance of any external factors, such as the employment opportunities in the areas where migrants have settled.
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Conference papers on the topic "Local Getis-Ord statistics"

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Wang, Xinming, Xin Chen, and Maolin Li. "Classification of high spatial resolution remote sensing image using SVM and local spatial statistics Getis-Ord Gi." In Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), edited by Jianguo Liu, Jinwen Tian, Hongshi Sang, and Jie Ma. SPIE, 2011. http://dx.doi.org/10.1117/12.901810.

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Bekti, Rokhana Dwi, Gideon Eka Dirgantara, and Edhy Sutanta. "Distance and AMOEBA Weights Matrices in Local Getis Ord-G Statistics to Identify Spatial Cluster of Gini Ratio." In 2021 3rd International Conference on Electronics Representation and Algorithm (ICERA). IEEE, 2021. http://dx.doi.org/10.1109/icera53111.2021.9538666.

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