Geostatistical data—spatially referenced observations related to some continuous spatial
phenomenon—are ubiquitous in ecology and can reveal ecological processes and inform …

Gaussian processes and random fields have a long history, covering multiple approaches to
representing spatial and spatio-temporal dependence structures, such as covariance …

Spatial data is crucial to improve decision-making in a wide range of fields including
environment, health, ecology, urban planning, economy, and society. Spatial Statistics for …

Generating accurate spatial information on soil organic matter (SOM) is increasingly
important in the context of global environmental change. Both prediction models and …

In recent years, the growing frequency and severity of wildfires, influenced by both human
activities and climate change, have posed significant challenges worldwide. Among the …

Hemorrhagic fever with renal syndrome (HFRS) is a category B infectious disease caused
by Hantavirus infection, which can cause acute kidney injury and has a high mortality rate. At …

Accurate estimation of grassland leaf area index (LAI), fractional vegetation cover (FVC),
and aboveground biomass (AGB) is fundamental in grassland studies. The newly launched …

Background Geostatistical analysis of health data is increasingly used to model spatial
variation in malaria prevalence, burden, and other metrics. Traditional inference methods for …

Understanding the spatial variability of soil organic matter (SOM), soil total nitrogen (STN),
soil total phosphorus (STP), and soil total potassium (STK) is important to support site …

Background The latest national survey on the distribution of human parasites in China
demonstrated that Guangdong was among the endemic provinces with the highest …