Spatial Arrangement and Neighborhood of Discrete Variables

This lecture introduces the concept of spatial arrangement and neighborhood in geographic information systems, covering topics such as geometric properties of objects, autocorrelation measurement, interpolation, and interaction between data layers. It explores the description of object sets with unique indicators, organization of objects relative to each other, and the minimum distance to objects. Statistical dispersion indices, like standard deviation and Bachi distance, are discussed. Spatial arrangement indices, such as the nearest neighbor index, are explained along with their comparison to random distributions. The lecture also delves into proximity relationships, Thiessen polygons, and connectivity indices for linear and zonal objects, providing insights into spatial analysis at different levels.