1,121 Results Found

The journal retracts the article titled “Statistical Modeling for Spatial Groundwater Potential Map Based on GIS Technique” [...]

Spatial variability and source apportionment of river pollution flowing into the Bohai Sea are of great significance to the pollution liability and development of control strategies to reduce the terrestrial discharge of pollution in the ocean. In th...

In recent years, the most advanced pioneering techniques in the computing field have found application in assorted areas. Deep learning approaches, including artificial neural networks (ANNs), have become popular thanks to their ability to draw infer...

ALS-derived raster visualization techniques have become common in recent years, opening up new possibilities for subtle landform detection in earth sciences and archaeology, but they have also introduced confusion for users. As a consequence, the cho...

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...

In arid and semi-arid lands like Iran water is scarce, and not all the wastewater can be treated. Hence, groundwater remains the primary and the principal source of water supply for human consumption. Therefore, this study attempted to spatially asse...

Groundwater quality deterioration has become an environmental problem of widespread concern. In this study, we used a water quality index (WQI) and multivariate statistical techniques to assess groundwater quality and to trace pollution sources in th...

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...

The severe water quality pollution of the Bohai Sea impacts both the ecosystem and the economy of the region. This study assesses the water quality of the Bohai Sea using a two-year (2020–2021) dataset to investigate the spatial distribution an...

This study investigates the seasonal and spatial trends in Kuwait’s coastal water’s physical, chemical, and biological parameters by applying multivariate statistical techniques, including cluster analysis (CA), principal component/factor...

The water quality of Rudrasagar Lake, the second-largest natural reservoir of Tripura is of great ecological and economic importance as it serves a diverse range of purposes, including fishing, irrigation, aquaculture, domestic use, and recreation ac...

The magnitude of pollution in Lake Hawassa has been exacerbated by population growth and economic development in the city of Hawassa, which is hydrologically closed and retains pollutants entering it. This study was therefore aimed at examining seaso...

Groundwater (GW) is a critical freshwater resource for billions of individuals worldwide. Rapid anthropogenic exploitation has increasingly deteriorated GW quality and quantity. Reliable estimation of complex hydrochemical properties of GW is crucial...

Cities are human ecosystems. Understanding human ecology is important for designing and planning the built environment. The ability to respond to changes and adapt actions in a positive way helps determine the health of cities. Recently, many studies...

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...

In the Duliujian River, 12 water environmental parameters corresponding to 45 sampling sites were analyzed over four seasons. With a statistics test (Spearman correlation coefficient) and multivariate statistical methods, including cluster analysis (...

The outbreak of SARS-CoV-2 in Wuhan, China in late December 2019 became the harbinger of the COVID-19 pandemic. During the pandemic, geospatial techniques, such as modeling and mapping, have helped in disease pattern detection. Here we provide a synt...

Spatial modeling is an integral component of most geographic information systems (GISs). However, conventional GIS modeling techniques can require substantial processing time and storage space and have limited statistical and machine learning functio...

Sampling and estimation of geographical attributes that vary across space (e.g., area temperature, urban pollution level, provincial cultivated land, regional population mortality and state agricultural production) are common yet important constituen...

PM₁₀ prediction has attracted special legislative and scientific attention due to its harmful effects on human health. Statistical techniques have the potential for high-accuracy PM₁₀ prediction and accordingly, previous studies on statistical method...

Remote sensing technologies continue to expand their role in environmental monitoring, providing invaluable advances in soil assessing and mapping. This study aimed to prove the need to apply spatial statistical models for processing data in remote s...

The spatial flows of school-age children and educational resources have been driven by such factors as regional differences in population migration and the uneven development of the education quality and living standards of residents in urban and rur...

Forests store approximately as much carbon as is in the atmosphere, with potential to take in or release carbon rapidly based on growth, climate change and human disturbance. Above-ground biomass (AGB) is the largest carbon pool in most forest system...

This article presents an overview of methodologies for spatial prediction of functional data, focusing on both stationary and non-stationary conditions. A significant aspect of the functional random fields analysis is evaluating stationarity to chara...

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...

Rapid urbanization in developing megacities has exacerbated hydrological imbalances, positioning urban flooding as a major environmental and socio-economic challenge of the twenty-first century. This study investigates the spatial relationship betwee...

Land subsidence induced by excessive groundwater withdrawal has become one of the most significant geohazards affecting the Konya Closed Basin, Turkey. Although previous studies have successfully monitored ground deformation using geodetic and remote...

Aboveground biomass (AGB) estimates derived from Landsat’s spectral bands are limited by spectral saturation when AGB densities exceed 150–300 Mg ${\mathrm{ha}}^{-1}$. Statistical features that characterize image texture have been proposed as a mea...

In general, weather forecasting has been significantly developed at a large scale and, joined with statistical techniques, is used to predict at a local scale. However, there is no way to propagate winds between two nearby locations; this is a spatia...

The multi-exposure fusion (MEF) technique provides humans a new opportunity for natural scene representation, and the related quality assessment issues are urgent to be considered for validating the effectiveness of these techniques. In this paper, a...

The importance of the distribution of accommodation businesses over a certain area has grown remarkably, especially if such distribution is mapped using tools and techniques that utilize the territory as a variable in the analysis. The purpose of thi...

In this paper, we present the concept of the Radio Environment Map (REM) designed to ensure electromagnetic situational awareness of cognitive radio networks. The map construction techniques based on spatial statistics are presented. The results of f...

Coffee production in Peru plays a crucial socio-economic role, supporting over 200,000 families and contributing significantly to export income. However, the spatial variation in coffee farming across ecological and socio-economic regions remains poo...

Oil extraction and agricultural production are central to North Dakota’s economy, yet their spatial interactions remain poorly understood. This study conducts a statewide geospatial analysis integrating OpenStreetMap data, GIS processing, DBSCA...

This paper develops a new approach for the detection of spatial clusters in the presence of random environmental effects and covariates when the observed data consist of counts over a regular grid. Such data are frequently overdispersed and spatially...

The scope of this work is to compare Sentinel-2 and unmanned aerial vehicles (UAV) imagery from northern Greece for use in precision agriculture by implementing statistical analysis and 2D visualization. Surveys took place on five dates with a differ...

Risk analysis of water resources systems can use statistical weather generators coupled with hydrologic models to examine scenarios of extreme events caused by climate change. These require multivariate, multi-site models that mimic the spatial, temp...

Road Traffic Accidents (RTAs) represent a significant public safety issue in rapidly urbanising nations, resulting in considerable fatalities, injuries, and economic losses. This research investigates the spatio-temporal distribution and hotspot dyna...

A variation of the reduction-based approach to spatiotemporal interpolation (STI), in which time is treated independently from the spatial dimensions, is proposed in this paper. We reviewed and compared three widely-used spatial interpolation techniq...

While there exists extensive assessment of urban heat, we observe myriad methods for describing thermal distribution, factors that mediate temperatures, and potential impacts on urban populations. In addition, the limited spatial and temporal resolut...

Extension of usable frequency spectrum from microwave to millimeter-wave (mmWave) is one of the key research directions in addressing the capacity demands of emerging 5th-generation communication networks. This paper presents a thorough analysis on t...

Identifying patterns and drivers of regional land use changes is crucial for supporting land management and planning. Doing so for mountain ecosystems in East Asia, such as the So-yang River Basin in South Korea, has until now been a challenge becaus...

Quality education is necessary as it provides the basis for equality in society. It is also significantly important that educational institutes be focused on tracking and improving the academic performance of each student. Thus, it is important to id...

Pedestrians are vulnerable road users that are directly exposed to road traffic crashes with high odds of resulting in serious injuries and fatalities. Therefore, there is a critical need to identify the risk factors associated with injury severity i...

The present study focuses on identifying and describing the possible proximate and underlying causes of deforestation and its factors using the combination of two techniques: (1) specialized consultation and (2) spatial logistic regression modeling....

Numerous environmental conditions may influence when a female Loggerhead sea turtle (Caretta caretta) selects a nesting site. Limited research has used Geographic Information Systems (GIS) and statistical analysis to study sea turtle spatial patterns...

The objective of this paper is to investigate different methods to generate future potential climatic scenarios at monthly scale considering meteorological droughts. We assume that more reliable scenarios would be generated by using regional climatic...

This retrospective population-based study was conducted to analyze spatial patterns of tuberculosis (TB) incidence in Si Sa Ket province, Thailand. TB notification data from 2004 to 2008 collected from TB clinics throughout the province was used alon...

The objective of the presented article is the identification of spatial relations between the inhabitants’ standards of living and the districts’ financial capacity basing on data for 2017. The investigation comprised all of the 380 Polis...

This study set out to identify and analyze the factors that influence the formation of rental prices for residential apartments in the city of Belém. The approach adopted was based on the hedonic price theory, which considers that the rental p...