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OLS Field Name OLS Field Data
Main Title Object-Based Image Analysis Spatial Concepts for Knowledge-Driven Remote Sensing Applications / [electronic resource] :
Author Blaschke, Thomas.
Other Authors
Author Title of a Work
Lang, Stefan.
Hay, Geoffrey J.
Publisher Springer Berlin Heidelberg,
Year Published 2008
Call Number GA1-1776
ISBN 9783540770589
Subjects Geography. ; Physical geography. ; Remote sensing. ; Information systems. ; Computer vision. ; Geographical information systems. ; Regional planning.
Internet Access
Description Access URL
Collation XVII, 817 p. online resource.
Due to license restrictions, this resource is available to EPA employees and authorized contractors only
Contents Notes
Why object-based image analysis -- Object-based image analysis for remote sensing applications: modeling reality - dealing with complexity -- Progressing from object-based to object-oriented image analysis -- An object-based cellular automata model to mitigate scale dependency -- Geographic Object-Based Image Analysis (GEOBIA): A new name for a new discipline -- Image objects and geographic objects -- Multiscale representation and object-based classification -- Using texture to tackle the problem of scale in land-cover classification -- Domain-specific class modelling for one-level representation of single trees -- Object recognition and image segmentation: the Feature Analyst® approach -- A procedure for automatic object-based classification -- Change detection using object features -- Identifying benefits of pre-processing large area QuickBird imagery for object-based image analysis -- A hybrid texture-based and region-based multi-scale image segmentation algorithm -- Semi-automated forest stand delineation using wavelet based segmentation of very high resolution optical imagery -- Quality assessment of segmentation results devoted to object-based classification -- Automated classification, mapping and updating: forest -- Object-based classification of QuickBird data using ancillary information for the detection of forest types and NATURA 2000 habitats -- Estimation of optimal image object size for the segmentation of forest stands with multispectral IKONOS imagery -- An object based approach for the implementation of forest legislation in Greece using very high resolution satellite data -- Object based classification of SAR data for the delineation of forest cover maps and the detection of deforestation - A viable procedure and its application in GSE Forest Monitoring -- Pixels to objects to information: Spatial context to aid in forest characterization with remote sensing -- Automated classification, mapping and updating: environmental resource management and agriculture -- Object oriented oil spill contamination mapping in West Siberia with Quickbird data -- An object-oriented image analysis approach for the identification of geologic lineaments in a sedimentary geotectonic environment -- Classification of linear environmental impacts and habitat fragmentation by object oriented analysis of aerial photographs in Corrubedo National Park (NW Iberian Peninsula) -- Multi-scale functional mapping of tidal marsh vegetation using object-based image analysis -- A Local Fourier Transform approach for vine plot extraction from aerial images -- Automated classification, mapping and updating: land use / land cover -- Object-based classification of IKONOS data for vegetation mapping in Central Japan -- Structural biodiversity monitoring in savanna ecosystems: Integrating LiDAR and high resolution imagery through object-based image analysis -- Fusion of multispectral optical and SAR images towards operational land cover mapping in Central Europe -- The development of integrated object-based analysis of EO data within UK national land cover products -- Automated classification, mapping and updating: urban applications -- Detecting informal settlements from QuickBird data in Rio de Janeiro using an object based approach -- Opportunities and limitations of object based image analysis for detecting urban impervious and vegetated surfaces using true-colour aerial photography -- Object-based Image Analysis using QuickBird satellite images and GIS data, case study Belo Horizonte (Brazil) -- An object-based approach to detect road features for informal settlements near Sao Paulo, Brazil -- Development of new methodologies -- Object-oriented analysis of image and LiDAR data and its potential for a dasymetric mapping application -- Characterising mountain forest structure using landscape metrics on LiDAR-based canopy surface models -- Object detection in airborne laser scanning data - an integrative approach on object-based image and point cloud analysis -- Support Vector Machine Classification for Object-Based Image Analysis -- Genetic adaptation of segmentation parameters -- Principles of full autonomy in image interpretation. The basic architectural design for a sequential process with image objects -- Strategies for semi-automated habitat delineation and spatial change assessment in an Alpine environment -- Burning research questions, research needs and outlook -- On segment based image fusion -- Modelling uncertainty in high resolution remotely sensed scenes using a fuzzy logic approach -- Assessing image segmentation quality - concepts, methods and application -- Object-fate analysis - spatial relationships for the assessment of object transition and correspondence. Advances in earth observations sensors and GIScience have led to the emerging fields of Object-based Image Analysis (OBIA). The need for timely and accurate geo-spatial information is steadily increasing. This book discusses means, technologies and approaches related to the processing and analysis of multi-sensor, multi-resolution data with a focus on the generation, modelling and classification of objects. In high resolution images these objects are typically derived through regionalisation principles. The advancement of feature recognition and advanced image analysis techniques facilitate the extraction of thematic information for policy making support and informed decisions. The applications also address the integration of Geographic Information and the concurrent developments of GIScience and vanquish limitations of pixelwise image processing by exploiting image information context-driven and "intelligently".