Amazon cover image
Image from Amazon.com
Image from Google Jackets
Image from OpenLibrary
See Baker & Taylor
Image from Baker & Taylor

Mathematical foundation of GIS / by Wolfgang Kainz and Huayi Wu.

By: Contributor(s): Material type: TextTextLanguage: English Series: Topics in advanced geoinformatics ; Volume 2Publication details: Singapore: World Scientific, 2024.Description: xviii, 210p. : ill. ; 25 cmISBN:
  • 9789811292873
Subject(s): Other classification:
  • U:(9S) R4
Summary: "Geographic Information Systems (GIS) originated in the 1960s and have since become the primary tool and science for handling spatial data. This unique compendium introduces essential mathematical knowledge related to GIS, including mathematical logic, geometry, algebra, topology, set theory, graph theory, probability theory and statistics, as well as uncertainty theory. These topics cover GIS data modeling, geometric calculations, topological analysis, spatial inference, and are helpful in understanding how to express spatial feature models, derive logical conclusions from given facts, perform coordinate transformations, and even aspects such as remote sensing image classification and machine learning"-- Provided by publisher.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Home library Call number Status Barcode
Textual Textual Central Science Library Central Science Library U:(9S) R4 (Browse shelf(Opens below)) Available SL1656064

Includes bibliographical references and index.

"Geographic Information Systems (GIS) originated in the 1960s and have since become the primary tool and science for handling spatial data. This unique compendium introduces essential mathematical knowledge related to GIS, including mathematical logic, geometry, algebra, topology, set theory, graph theory, probability theory and statistics, as well as uncertainty theory. These topics cover GIS data modeling, geometric calculations, topological analysis, spatial inference, and are helpful in understanding how to express spatial feature models, derive logical conclusions from given facts, perform coordinate transformations, and even aspects such as remote sensing image classification and machine learning"-- Provided by publisher.

There are no comments on this title.

to post a comment.