Search
Search Results
-
Exploring the Spatial Pattern of Urban Forest Ecosystem Services based on i-Tree Eco and Spatial Interpolation: A Case Study of Kyoto City, Japan
Urban forest, as an essential urban green infrastructure, is critical in providing ecosystem services to cities. To enhance the mainstreaming of...
-
Optimization of spatial prediction and sampling strategy of site contamination based on Thiessen polygon coupling interpolation
Contaminated sites pose a serious threat to the ecological environment and human health. Because of the presence of multiple peaks in the pollution...
-
Imputation of missing monthly rainfall data using machine learning and spatial interpolation approaches in Thale Sap Songkhla River Basin, Thailand
Missing rainfall data has been a prevalent issue and primarily interested in hydrology and meteorology. This research aimed to examine the capability...
-
Exploratory factor analysis-based co-kriging method for spatial interpolation of multi-layered soil particle-size fractions and texture
PurposePrecision map** of soil texture is critical for hydrological, ecological, environmental, and agricultural modeling and field management....
-
Prediction of MODIS land surface temperature using new hybrid models based on spatial interpolation techniques and deep learning models
Land surface temperature (LST) prediction is of great importance for climate change, ecology, environmental and industrial studies. These studies...
-
Accuracy assessment of inverse distance weighting interpolation of groundwater nitrate concentrations in Bavaria (Germany)
For the designation of nitrate vulnerable zones under the EU Nitrate Directive, some German federal states use inverse distance weighting (IDW) as...
-
A parsimonious, computationally efficient machine learning method for spatial regression
We introduce the modified planar rotator method (MPRS), a physically inspired machine learning method for spatial/temporal regression. MPRS is a...
-
Analysis of changes in air pollution quality and impact of COVID-19 on environmental health in Iran: application of interpolation models and spatial autocorrelation
In the global COVID-19 epidemic, humans are faced with a new challenge. The concept of quarantine as a preventive measure has changed human...
-
Interpolation, Satellite-Based Machine Learning, or Meteorological Simulation? A Comparison Analysis for Spatio-temporal Map** of Mesoscale Urban Air Temperature
Fine-resolution spatio-temporal maps of near-surface urban air temperature ( T a ) provide crucial data inputs for sustainable urban decision-making,...
-
Effects of long-term cultivation on spatial-temporal variation of soil nitrogen and phosphorus: a case study in Shaanxi Province, China
Investigating the spatial-temporal variation of soil nitrogen (N) and phosphorus (P) is essential to determine the balance between increased food...
-
Cumulative Ordinary Kriging interpolation model to forecast radioactive fallout, and its application to Chernobyl and Fukushima assessment: a new method and mini review
The Cumulative Ordinary Kriging (COK) interpolation method has been proposed for the spatial prediction of atmospheric radioactive fallout in any...
-
Effectiveness of predicting spatial contaminant distributions at industrial sites using partitioned interpolation method
Soil pollution at industrial sites is an important issue in China and in most other regions of the world. The accurate prediction of the spatial...
-
Assessing the Topsoil Contamination of Cesium-137 Environmental Fallout in Konya, Turkey: Spatial Distribution and Analysis
Although more than 30 years have passed since the Chernobyl accident, artificial radionuclides are still present in the soil. Especially, 137 Cs is...
-
Understanding Soil Contamination in Nitrogen Fertilizer Manufacturing: Spatial Distribution, Factors, and Implications for Environmental Management
Soil contamination caused by the nitrogen fertilizer manufacturing industry is a growing global concern. This study focused on soil contamination in...
-
Spatial Variation in Soils
Soil variation can be modeled either by dividing the space into discrete units, or by quantifying autocorrelationAutocorrelation in space from known...
-
Does digital economy agglomeration promote green economy efficiency? A spatial spillover and spatial heterogeneity perspective
The digital economy has been booming in China in recent years and is characterized by spatial agglomeration. However, there is little literature...
-
Spatial extreme model for rainfall depth: application to the estimation of IDF curves in the Basque country
Intensity-duration-frequency (IDF) curves are commonly used in engineering practice for the hydraulic design of flood protection infrastructures and...
-
Spatial modelling and quantification of soil potentially toxic elements based on variability in sample size and land use along a toposequence at a district scale
This study applied ordinary kriging (OK), geographically weighted regression (GWR), and positive matrix factorization to model soil Cu and Mn in the...
-
The vulnerability analysis of groundwater contamination and Bayesian-based spatial modelling
The groundwater vulnerability assessment is an effective measure to analyse potential quality of available water in increasingly populated and...
-
Implementation of an integrated health risk assessment coupled with spatial interpolation and source contribution: a case study of soil heavy metals from an abandoned industrial area in Suzhou, China
Soil heavy metal contaminated sites with multiple sources of pollution have caused worldwide public concern. However, the lack of correlation of risk...
