Geographic information systems (GIS) have become increasingly important in helping us understand complex social, economic, and natural dynamics where spatial components play a key role. The critical algorithms used in GIS, however, are notoriously difficult to both teach and understand, in part due to the lack of a coherent representation. GIS Algorithms attempts to address this problem by combining rigorous formal language with example case studies and student exercises.
Using Python code throughout, Xiao breaks the subject down into three fundamental areas:
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Ningchuan Xiao is Associate Professor of Geography at the Ohio State University. He has taught a wide ranges of courses in GIS, spatial analysis, and cartography. His research focuses on the development of effective computational methods in spatial and temporal data handling.
The critical algorithms used in GIS are notoriously difficult to both teach and understand. This book address the problem by combining rigorous formal language with example case studies and student exercises.
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