Open Source GIS : A GRASS GIS Approach

Helena Mitasova, Markus Neteler

ISBN 10: 038735767X / ISBN 13: 9780387357676

Published by Springer US, 2007

About this Item

Zustand: Sehr gut - Gepflegter, sauberer Zustand. 3. Auflage. Außen: vergilbt. Aus der Auflösung einer renommierten Bibliothek. Kann Stempel beinhalten. | Seiten: 428 | Sprache: Englisch | Produktart: Sonstiges. Seller Inventory # 3276437/202

Bibliographic Details

Title: Open Source GIS : A GRASS GIS Approach

Publisher: Springer US

Publication Date: 2007

Binding: Hardcover

Condition: Sehr gut

Edition: 3rd Edition

About this title

Synopsis:

Thoroughly updated with material related to the GRASS6, the third edition includes new sections on attribute database management and SQL support, vector networks analysis, lidar data processing and new graphical user interfaces. All chapters were updated with numerous practical examples using the first release of a comprehensive, state-of-the-art geospatial data set.

From the Back Cover:

With this third edition of Open Source GIS: A GRASS GIS Approach, we enter the new era of GRASS6, the first release that includes substantial new code developed by the International GRASS Development Team.  The dramatic growth in open source software libraries has made GRASS6 development more efficient, and has enhanced GRASS interoperability with a wide range of open source and proprietary geospatial tools.

Thoroughly updated with material related to GRASS6, the third edition includes new sections on attribute database management and SQL support, vector networks analysis, lidar data processing and new graphical user interfaces. All chapters are updated with numerous practical examples using the first release of a comprehensive, state-of-the-art geospatial data set.

Open Source GIS: A GRASS GIS Approach, Third Edition preserves the continuity of previous editions by maintaining the book's proven structure.  This volume is structured for a professional audience composed of researchers and practitioners in government and industry, as well as graduate students interested in geospatial analysis and modeling.