Free Downloads Object-Based Image Analysis: Spatial Concepts For Knowledge-Driven Remote Sensing Applications (Lecture Notes In Geoinformation And Cartography)
This book brings together a collection of invited interdisciplinary persp- tives on the recent topic of Object-based Image Analysis (OBIA). Its c- st tent is based on select papers from the 1 OBIA International Conference held in Salzburg in July 2006, and is enriched by several invited chapters. All submissions have passed through a blind peer-review process resulting in what we believe is a timely volume of the highest scientific, theoretical and technical standards. The concept of OBIA first gained widespread interest within the GIScience (Geographic Information Science) community circa 2000, with the advent of the first commercial software for what was then termed ‘obje- oriented image analysis’. However, it is widely agreed that OBIA builds on older segmentation, edge-detection and classification concepts that have been used in remote sensing image analysis for several decades. Nevert- less, its emergence has provided a new critical bridge to spatial concepts applied in multiscale landscape analysis, Geographic Information Systems (GIS) and the synergy between image-objects and their radiometric char- teristics and analyses in Earth Observation data (EO).
Series: Lecture Notes in Geoinformation and Cartography
Hardcover: 817 pages
Publisher: Springer; 2008 edition (August 27, 2008)
Language: English
ISBN-10: 3540770577
ISBN-13: 978-3540770572
Product Dimensions: 9.4 x 6.2 x 1.8 inches
Shipping Weight: 3.5 pounds (View shipping rates and policies)
Average Customer Review: 5.0 out of 5 stars See all reviews (1 customer review)
Best Sellers Rank: #2,084,965 in Books (See Top 100 in Books) #187 in Books > Computers & Technology > Programming > Graphics & Multimedia > GIS #456 in Books > Computers & Technology > Graphics & Design > Computer Modelling > Remote Sensing & GIS #469 in Books > Science & Math > Earth Sciences > Geophysics
Most OBIA articles are relative neophytes. Blaschke et al. succeed in assembling some of the very best in the field.
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