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This lecture introduces the analysis of geographic information focusing on discrete variables, including geometric properties, spatial arrangement, and neighbourhood. It covers topics such as autocorrelation, digital elevation models, derived variables, and integrating data layers. Students will learn about position, dispersion, and proximity indices, as well as point objects position and dispersion metrics. The lecture also explores spatial arrangement indices for point and linear objects, as well as different levels of analysis for zonal objects. It concludes with landscape-level indices evaluating central tendency and variability, such as the Index of Majority and Shannon's Diversity Index.