A new disease mapping method for improving data completeness of syndromic surveillance with high missing rates.

Understanding and extending the geographical detector model under a linear regression framework.

sandwichr: Spatial prediction in R based on spatial stratified heterogeneity.

Assessing work resumption in hospitals during the COVID-19 epidemic in China using multiscale geographically weighted regression.

Spatial rough set-based geographical detectors for nominal target variables.

A two-point machine learning method for the spatial prediction of soil pollution.

Encoder-Decoder Full Residual Deep Networks for Robust Regression and Spatiotemporal Estimation.

Space-time disease mapping by combining Bayesian maximum entropy and Kalman filter: the BME-Kalman approach.

Theoretical and empirical comparative evaluations on measures of map association.

Spatial interpolation of marine environment data using P-MSN.

Incorporating spatial association into statistical classifiers: local pattern-based prior tuning.

The spatial statistic trinity: A generic framework for spatial sampling and inference.

Spatiotemporally Varying Coefficients (STVC) model: a Bayesian local regression to detect spatial and temporal nonstationarity in variables relationships.

A spatial heterogeneity-based rough set extension for spatial data.

A Bayesian Space-Time Hierarchical Model for Remotely Sensed Lattice Data Based on Multiscale Homogeneous Statistical Units.

Using Spatial Analysis to Understand the Spatial Heterogeneity of Disability Employment in China.

Geographically weighted regression-based determinants of malaria incidences in northern China.

Towards Identifying and Reducing the Bias of Disease Information Extracted from Search Engine Data.

Detecting nominal variables' spatial associations using conditional probabilities of neighboring surface objects' categories.

Driving forces and their interactions of built-up land expansion based on the geographical detector - a case study of Beijing, China.

Evaluation of Sampling Methods for Validation of Remotely Sensed Fractional Vegetation Cover.

Sampling design optimization of a wireless sensor network for monitoring ecohydrological processes in the Babao River basin, China.

A stratified optimization method for a multivariate marine environmental monitoring network in the Yangtze River estuary and its adjacent sea.

Sandwich mapping of diseases with a small sample in a stratified heterogeneous domain.

Hybrid Optimal Design of the Eco-Hydrological Wireless Sensor Network in the Middle Reach of the Heihe River Basin, China.

A method for extracting rules from spatial data based on rough fuzzy sets.

Spatial data discretization methods for geocomputation.

Design-based spatial sampling: Theory and implementation.

A B-SHADE based best linear unbiased estimation tool for biased samples.

Environmental health risk detection with GeogDetector.

A spatial sampling optimization package using MSN theory.

Geographical Detectors-Based Health Risk Assessment and its Application in the Neural Tube Defects Study of the Heshun Region, China.

Sample surveying to estimate the mean of a heterogeneous surface: reducing the error variance through zoning.

Integration of GP and GA for mapping population distribution.

Using spatial analysis and Bayesian network to model the vulnerability and make insurance pricing of catastrophic risk.

Using rough set theory to identify villages affected by birth defects: the example of Heshun, Shanxi, China.

Modeling Spatial Means of Surfaces With Stratified Nonhomogeneity.

Sampling and Kriging Spatial Means: Efficiency and Conditions.

Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis.

A traffic cellular automata model based on road network grids and its spatial and temporal resolution's influences on simulation.

Typhoon insurance pricing with spatial decision support tools.