The inverse-distance weighting interpolation is widely used in 3D geological modeling and directly affects the accuracy of models. With the development of “smart” or “intelligent” geology, classical inverse-distance weighting...
Information on historical flood levels can be communicated verbally, in documents, or in the form of flood marks. The latter are the most useful from the point of view of public awareness building and mathematical modeling of floods. Information abou...
Machine learning models for spatial prediction have been applied in various types of research. However, spatial relation has not been fully considered in modeling, since the Cartesian coordinates of the observed points are directly employed as the lo...
Various externalities caused by highway infrastructures, such as promoting economic development, traffic congestion, and air pollution, are becoming more and more important. Currently, there is no multi-dimensional quantitative evaluation of the exte...
In this study, we investigate sustainable trade between China and Kazakhstan using the gravity model. We find that the distance between the importer and exporter relative to the distance to other trading partners, rather than the absolute distance, s...
Assessing urban resilience under compound shocks requires observable and comparable process evidence that can inform resilient land governance and cross-jurisdiction planning. Using China’s Pilot Free Trade Zones (PFTZs) as a staged institution...
Seed dispersal and environmental heterogeneity, and the effects of their interaction, are perceived to be determinants of the spatial patterns of trees. We applied the spatial point process to analyse Vatica odorata (Griff.) Symington (Dipterocarpace...
One widely used method for analyzing vegetation growth from satellite imagery is the Normalized Difference Vegetation Index (NDVI), a key metric for assessing vegetation dynamics. NDVI varies not only spatially but also temporally, which is essential...
The ultimate goal of PPP-RTK is to achieve rapid ambiguity resolution, which is influenced by the prior precision of the external ionospheric information. This study proposes a method for determining the precision of ionospheric corrections for each...
30 August 2019
By defining the connotation of land use eco-efficiency, land use eco-efficiency from 2003 to 2015 was calculated on the basis of the mixed directional distance function, and its spatial convergence analyzed using a spatial econometric model. Results...
Different from the developmental mode of western developed countries, China’s economy has changed from a stage of high-speed growth to a stage of high-quality development, where the people’s growing needs for better lives can be met, embodying this n...
A key challenge in precision agriculture is acquiring reliable spatial soil information under varying sampling densities, from sparse surveys to intensive monitoring. The individual predictive soil mapping (iPSM) method performs well in data-scarce c...
Drought is a common hydrometeorological phenomenon and a pervasive global hazard. To monitor global drought-wetness conditions comprehensively and promptly, this research proposed a spatial distance drought index (SDDI) which was constructed by four...
Rainfall stations in small and medium-sized river basins in China are sparsely distributed and unevenly spaced, resulting in insufficient spatial representativeness of precipitation data and posing challenges to the accuracy of flood forecasting. Spa...
Fuzzy set theory has shown potential for reducing uncertainty as a result of data sparsity and also provides advantages for quantifying gradational changes like those of pollutant concentrations through fuzzy clustering based approaches. The ability...
This paper estimates China’s water utilization efficiency using the directional distance function to take into account the environmental degradation affecting the economy. We further analyze the spatial correlation and the factors influencing the uti...
In recent years, modeling gully erosion susceptibility has become an increasingly popular approach for assessing the impact of different land degradation factors. However, different forms of human influence have so far not been identified in order to...
Spatial interpolation is a crucial aspect of soil toxic element pollution research, serving as a vital foundation for pollution assessment, treatment, and sustainability efforts. The selection and adjustment of interpolation methods directly influenc...
In a point set in dimension superior to 1, the statistical distribution of the number of pairs of points as a function of distance between the points of the pair is not uniform. This distribution is not considered in a large number of classic methods...
Under the dual constraints of rigid water resource management systems and China’s “dual carbon” national strategy, water resource management authorities face pressing practical demands for the coordinated governance of water conserv...
To more precisely monitor drought, a new remote sensing-based drought index, the Vapor Pressure Deficit–Soil Moisture–Sun-Induced Chlorophyll fluorescence Dryness Index (VMFDI), with a spatial resolution of 1 km based on vapor pressure de...
Spatial capture models are broadly used for population analysis in ecological statistics. Spatial capture models for unidentified individuals rely on data augmentation to create a zero-inflated population. The unknown true population size can be cons...
European roe deer (Capreolus capreolus L.) are important given their economic, recreational and ecological value. However, uncontrolled roe deer numbers can result in negative impacts on forest regeneration and agricultural crops, disease transmissio...
Precipitation data provide a crucial input for examining hydrological issues, including watershed management and mitigation of the effects of floods, drought, and landslides. However, they are collected frequently from the scarce and often insufficie...
This study investigated the spatiotemporal characteristics and influencing factors of PM2.5 concentrations at the provincial scale in China. The findings indicate significant spatial autocorrelation, with notable high–high agglomerations in Eas...
In this paper, we take the position that cities gain to be represented as three-dimensional spaces populated by scores of micro-scale-built spaces (buildings, rooms, passageways, squares, etc.). Effective algorithms that evaluate place-based accessib...
Many experiments on distance perception have revealed that there is a difference between perceptual distance and objective distance. It has been accepted that a route with more memorable features will make its perceived distance longer. This study re...
27 April 2022
Environmental justice advocates that all people are protected from disproportionate impacts of environmental hazards. Despite this ideal aspiration, social and environmental inequalities exist throughout greater Los Angeles. Previous research has ide...
Spatially uneven urbanization shapes various urban-lake spatial patterns; however, the effect of pattern evolution on lake breeze front (LBF) penetration via thermal and aerodynamic mechanisms in inland multi-lake megacities remains unclear. Therefor...
Reducing emissions through the invisible hand of the market has become an important way to promote sustainable environmental development. The shadow price of carbon dioxide (
Geographically neural network weighted regression is an improved model of GWR combined with a neural network. It has a stronger ability to fit nonlinear functions, and complex geographical processes can be modeled more fully. GNNWR uses the distance...
We developed a novel approach in the field of spatiotemporal modeling, based on the spatialisation of time, the Timescape algorithm. It is especially aimed at sparsely distributed datasets in ecological research, whose spatial and temporal variabilit...
2 September 2020
Long-distance caregiving (LDC) is an issue of growing importance in the context of assessing the future of elder care and the maintenance of health and well-being of both the cared-for persons and the long-distance caregivers. Uncertainty in the inte...
The modeling of spatio-temporal processes is crucial in many fields such as environmental science, hydrology, and water storage engineering. A basic concept of the spatio-temporal model is an auto-covariance function. The stream network model based o...
This study utilized a max-stable process (MSP) model with a dependence structure defined via a non-Euclidean distance metric, with the goal of modelling extreme flood data on a river network. The dataset was composed of mean daily discharge observati...
The UN 2030 Agenda sets poverty eradication as the primary goal of sustainable development. An accurate measurement of poverty is a critical input to the quality and efficiency of poverty alleviation in rural areas. However, poverty, as a geographica...
National distance (ND) is the key factor that affects international trade but the traditional trade gravity model only considers spatial distance, which is not enough. This paper therefore constructs a trade gravity model and a Generalized Moment Est...
Spatial relation models are the basis for realising three-dimensional spatial analysis. More researchers are now focusing on models that combine topological relations with distance or directional relations; however, a model that unifies all three rel...
With the development of machine learning technology, research cases for spatial estimation through machine learning approach (MLA) in addition to the traditional geostatistical techniques are increasing. MLA has the advantage that spatial estimation...
17 September 2022
In the past, the research on models related to urban land-use change and prediction was greatly complicated by the high precision of models. When planning some garden cities, we should explore a more applicable, specific, and effective macro approach...
Infection of liver flukes (Opisthorchis viverrini) is partly due to their suitability for habitats in sub-basin areas, which causes the intermediate host to remain in the watershed system in all seasons. The spatial monitoring of fluke at the small b...
Previous studies have demonstrated that non-Euclidean distance metrics can improve model fit in the geographically weighted regression (GWR) model. However, the GWR model often considers spatial nonstationarity and does not address variations in loca...
This paper examines the extent of stock-returns’ co-movements among firms in different countries and explores how various measures of closeness affect those co-movements by estimating a spatial autoregressive (SAR) convex combination model that...
In this paper, we analyse spatial variation in the Japanese dialectal lexicon by assembling a set of methodologies using theories in variationist linguistics and GIScience, and tools used in historical GIS. Based on historical dialect atlas data, we...
The healthy development of the ecosystem and tourism in destinations plays an essential role in sustainable development. Taking Shennongjia as an example, we analyzed the spatial–temporal variation in the ecosystem services value (ESV) and inve...
In hyperspectral image classification (HSIC), each pixel contains information across hundreds of contiguous spectral bands; therefore, the ability to perform long-distance modeling that stably captures and propagates these long-distance dependencies...
Hyperspectral remote sensing images (HSIs) have both spectral and spatial characteristics. The adept exploitation of these attributes is central to enhancing the classification accuracy of HSIs. In order to effectively utilize spatial and spectral fe...
19 March 2012
Production of high quality interpolation maps of heavy metals is important for risk assessment of environmental pollution. In this paper, the spatial correlation characteristics information obtained from Moran’s I analysis was used to supplement the...
In spatial data analysis, outliers or influential observations have a considerable influence on statistical inference. This paper develops Bayesian influence analysis, including the local influence approach and case influence measures in skew-normal...
In the fields of geographic information science and location-based services, the fusion of multisource Point-of-Interest (POI) data is of remarkable importance but faces several challenges. Existing matching methods, including those based on single n...
of 57