Bayesian spatial statistics and modeling represent a robust inferential framework where uncertainty in spatial processes is explicitly quantified through probability distributions. This approach ...

Image analysis and computer vision / Donald Geman and Basilis Gidas -- Oceanographic and atmospheric applications of spatial statistics and digital image analysis / James J. Simpson -- Spatial ...

The rapid advancement of spatial and single-cell omics technologies has revolutionized molecular biosciences by enabling high-resolution profiling of gene ...

Spatial Data Science introduces fundamental aspects of spatial data that every data scientist should know before they start working with spatial data. These aspects include how geometries are ...

Tumors contain many different types of cells organized in complex spatial patterns that can influence how the disease progresses. Because of this, it is hard to predict how a tumor will develop and ...

This course covers specialized methods and models that have been created for performing statistical analysis on spatial data. Students will learn basic statistical concepts and how to apply them to ...

Spatial biology is the study of the spatial organization of biological systems. It has immense clinical applications in disease diagnosis and treatment. By analyzing the spatial arrangement of cells ...