This study predicts the presence or absence of terrorism in Europe on a previously unexplored spatial scale. Dependent variables consist of satellite imagery and socio-environmental data. Five machine learning models were evaluated over the following...
8 June 2011
This study explored the spatial pattern of heavy metals in Beijing agricultural soils using Moran’s I statistic of spatial autocorrelation. The global Moran’s I result showed that the spatial dependence of Cr, Ni, Zn, and Hg changed with different sp...
Traffic accidents, which continue to increase from year to year in Turkey and in the world, have become a huge problem that can result in serious traumas, injuries, and deaths, as well as their material and moral consequences. Many studies have been...
Induced seismicity is one of the negative phenomena caused by anthropogenic activities that include mining of minerals. This phenomenon manifests itself as sudden and unpredictable shocks of rock mass, which can cause surface deformation and damage t...
Unlike previous regionalized studies on a worldwide crisis, this study aims to analyze spatial distribution patterns and evolution characteristics of the COVID-19 pandemic, using space-time aggregation and spatial statistics from a global perspective...
Estimating the aboveground biomass (AGB) at the plot level plays a major role in connecting accurate single-tree AGB measurements to relatively difficult regional AGB estimates. However, AGB estimates at the plot level suffer from many uncertainties....
Every biological image contains quantitative data that can be used to test hypotheses about how patterns were formed, what entities are associated with one another, and whether standard mathematical methods inform our understanding of biological phen...
This study proposes a method to quantitatively assess evacuation demographics during regional floods using Mobile Spatial Statistics (MSSs). It focuses on Koriyama City, affected by Typhoon Hagibis in 2019, as well as Yamagata City, which experienced...
The deployment of deep learning models in Internet of Things (IoT) systems is increasingly threatened by adversarial attacks. To address the challenge of effectively detecting adversarial examples generated by Generative Adversarial Networks (AdvGANs...
Both historically and in terms of practiced academic organization, the anticipation should be that a flourishing synergistic interface exists between statistics and operations research in general, and between spatial statistics/econometrics and spati...
Studying the temporal and spatial evolution trends in earthquakes in an area is beneficial for determining the earthquake risk of the area so that local governments can make the correct decisions for disaster prevention and reduction. In this paper,...
Negative spatial autocorrelation is one of the most neglected concepts in quantitative geography, regional science, and spatial statistics/econometrics in general. This paper focuses on and contributes to the literature in terms of the following thre...
Spatial documentation is exponentially increasing given the availability of Big Data in the Internet of Things, enabled by device miniaturization and data storage capacity. Bayesian spatial statistics is a useful statistical tool to determine the dep...
The objective of this study is the classification of urban climate zones (UCZs) based on spatial statistical approaches to provide key information for the establishment of thermal environments to improve urban planning. To achieve this, using data fr...
In this paper, we propose a novel statistical beamforming (SBF) method called the partial-nulling-based SBF (PN-SBF) to serve a number of users that are undergoing distinct degrees of spatial channel correlations in massive multiple-input multiple-ou...
To formulate and monitor the progress of development policies, acquiring data with sufficient spatiotemporal details is inevitable. With the increasing availability of open remote-sensing data and open-source software packages, this research suggeste...
Statistical depth is widely used as a powerful tool to measure the center-outward rank of multivariate and functional data. Recent studies have introduced the notion of depth to the temporal point process, which exhibits randomness in the cardinality...
In recent decades, the field of statistical linguistics has made significant strides, which have been fueled by the availability of data. Leveraging Twitter data, this paper explores the English and Spanish languages, investigating their rank diversi...
The objectives of this study were to evaluate spatial sampling and statistical aspects of landscape-level wildfire rate of spread (ROS) estimates derived from airborne thermal infrared imagery (ATIR). Wildfire progression maps and ROS estimates were...
Evidence shows that multiple factors, such as socio-economic status and access to health care facilities, affect tuberculosis (TB) incidence. However, there is limited literature available with respect to the correlation between socio-economic/health...
EU Directive 49/2002 and Spanish law 37/2006 urge cities to develop strategic noise maps and action plans to evaluate noise exposure and to establish noise abatement procedures in critical areas. However, noise mapping involves costly and cumbersome...
Land use profoundly changes the terrestrial ecosystem and landscape patterns, and these changes reveal the extent and scope of the ecological influence of land use on the terrestrial ecosystem. The study area selected for this research was the middle...
Statistical optimization methods serve as fundamental tools for studying sea-ice-related phenomena in the polar regions. To comprehensively analyze the spatial distributions of ice ridge keels, including the draft and spacing distributions, a statist...
As a type of earth observation technology, interferometric synthetic aperture radar (InSAR) is increasingly widely used in the field of geological disaster detection. However, the application of InSAR in low-coherence areas, such as alpine canyon are...
The changes of spatial pattern in energy consumption have an impact on global climate change. Based on the spatial autocorrelation analysis and the auto-regression model of spatial statistics, this study has explored the spatial disparities and drivi...
The spatiotemporal distribution pattern of the surface temperatures of urban forest canopies (STUFC) is influenced by many environmental factors, and the identification of interactions between these factors can improve simulations and predictions of...
Rainfall, one of the most important climate variables, is commonly studied due to its great heterogeneity, which occasionally causes negative economic, social, and environmental consequences. Modeling the spatial distributions of rainfall patterns ov...
Gene differential expression consists of the study of the possible association between the gene expression, evaluated using different types of data as DNA microarray or RNA-Seq technologies, and the phenotype. This can be performed marginally for eac...
This study presents an analysis of data from patients with ascending thoracic aortic aneurysms (ATAAs). Two databases of 87 patients were available: one containing clinical variables and the other consisting of measurements of the maximum diameter ta...
This article discusses public transport fare evasion from the point of view of the relations between inspection actions and detected evasion, with the aim of improving the efficacy of the former. By applying spatial statistics methods to a large data...
Karst aquifers are indispensable, yet vulnerable, resources; therefore, they require a comprehensive protection strategy. Since springs are the terminal points of the karst flow systems, knowledge of their distribution is a key element for the better...
Understanding the spatial variability of soil organic matter (SOM) is crucial for implementing precise land degradation control and fertilization to improve crop productivity. Studying spatial variability provides a scientific basis for precision fer...
With the development of machine learning and GIS (geographic information systems) technology, it is possible to combine them to mine the knowledge rules behind massive spatial data. GIS, also known as geographic information systems, is a comprehensiv...
Built-up areas (BAs) information acquisition is essential to urban planning and sustainable development in the Greater Bay Area in China. In this paper, a pseudo-Siamese dense convolutional network, namely PSDNet, is proposed to automatically extract...
In this paper, grid cell based spatial statistics were used to quantify the drivers of land-cover and land-use change (LCLUC) and habitat degradation in a tropical rainforest in Madagascar. First, a spectral database of various land-cover and land-us...
Improving the accuracy of edge pixel classification is an important aspect of using convolutional neural networks (CNNs) to extract winter wheat spatial distribution information from remote sensing imagery. In this study, we established a method usin...
The evaluation of anthropogenic impacts on the landscape is an issue that has traditionally been carried out from a descriptive or at least somewhat qualitative perspective. However, in recent years, the technological improvements provided by geograp...
22 June 2018
Existing measures of health equity bear limitations due to the shortcomings of traditional economic methods (i.e., the spatial location information is overlooked). To fill the void, this study investigates the equity in health workforce distribution...
Image de-noising is an important scheme that makes an image visually prominent and obtains enough useful information to produce a clear image. Many applications have been developed for effective noise suppression that produce good image quality. This...
Urban heat islands (UHIs) present a growing environmental issue in swiftly urbanizing regions, where impermeable surfaces and a lack of vegetation increase local temperatures. This research analyzes the spatial distribution of urban heat islands in Z...
What are the effects of Corona Virus Disease 19 (COVID-19) on inflation, unemployment, and GDP in Africa? Using geo-coded cross-sectional data taken from the World Health Organization and International Monetary Fund, we investigate the spatial distri...
This paper explores map users' cognitive processes in learning, acquiring and remembering information presented via screen maps. In this context, we conducted a mixed-methods user experiment employing digital sketch maps and eye tracking. On the one...
23 August 2018
Gastric cancer (GC) is the fourth most common type of cancer and the second leading cause of cancer-related deaths worldwide. To detect the spatial trends of GC risk based on hospital-diagnosed patients, this study presented a selection probability m...
Using local spatial statistics to explore local spatial association of geo-referenced data has attracted much attention. As is known, a local statistic is formulated at a particular sampling unit based on a prespecific proximity relationship and the...
The Geumho River in South Korea passes through a metropolitan area with a high population density and multiple industrial complexes; therefore, the water quality of this river is of significance for human health and economic activities. This study as...
One of the main pillars of sustainable urban development at the local scale is to control the social aspect of urban equality of socio-economic systems. A number of studies confirm that poverty in urban space is accompanied by negative phenomena, suc...
By analyzing atomic force microscopy images, we studied the spatial distribution of nanoholes etched by InAl droplets in In0.52Al0.48As surfaces, employing molecular beam epitaxy. We identified two temperature regimes, which exhibit significantly dif...
The purpose of this paper was to study the spatial characteristics and possible influencing factors of farmland soil texture and salt content in the Syr Darya River Basin. Data on the soil grain size and salt content were collected at 56 sampling sit...
Spatiotemporal evaluation of human mobility is crucial to deepen and broaden the understanding of drivers and mechanisms behind urbanization. In this study, daytime human mobility was quantified based on the inflow and outflow of population in 500 &t...
To provide safe drinking water in contaminated hydrogeological environments, it is essential to have precise geochemical information on contamination hotspots. In this study, Geographic Information System (GIS) and multivariate statistics were utiliz...
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