This lecture introduces spatial autocorrelation and dependence in geographic information systems, covering topics such as global spatial autocorrelation measurement, basic elements of digital elevation models, and interactions between different data layers. It explains the concept of spatial dependence, presents the paradox related to classical statistics in a geographical context, and discusses biases caused by using classical statistics in geography. The lecture also explores the limitations of classical statistical tools in spatial analysis and provides examples of biases in linear regression due to spatial dependence.