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technology & engineering > remote sensing & geographic information systems
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Mathematical Morphology in Geomorphology and GISci presents a multitude of mathematical morphological approaches for processing and analyzing digital images in quantitative geomorphology and geographic information science (GISci). Covering many interdisciplinary applications, the book explains how to use mathematical morphology not only to perform quantitative morphologic and scaling analyses of terrestrial phenomena and processes, but also to deal with challenges encountered in quantitative spatial reasoning studies.
For understanding the spatiotemporal characteristics of terrestrial phenomena and processes, the author provides morphological approaches and algorithms to:
Incorporating peer-reviewed content, this book offers simple explanations that enable readers--even those with no background in mathematical morphology--to understand the material. It also includes easy-to-follow equations and many helpful illustrations that encourage readers to implement the ideas.
B.S. Daya Sagar is an associate professor at the Indian Statistical Institute, Bangalore, where he is also the founding head of the Systems Science and Informatics Unit. He has written more than 80 papers and is the editor of Discrete Dynamics in Nature and Society: Multidisciplinary Research and Review Journal. Dr. Sagar is a senior member of the IEEE Geoscience and Remote Sensing Society; a member of the New York Academy of Sciences, American Geophysical Union, International Association for Mathematical Geosciences, and Association for Computing Machinery; and a fellow of the Royal Geographical Society and Indian Geophysical Union. He has been a recipient of several honors, including the Georges Matheron Award from the International Association for Mathematical Geosciences. His research interests include mathematical morphology and fractal geometry and their applications to terrestrial surface and associated features as well as geomorphologic information retrieval, quantitative geomorphometry, allometry, granulometry, scaling analysis, quantitative spatial reasoning, and spatiotemporal modeling.
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