GEOBIA

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GEOBIA: GEO-Object-Based Image Analysis (pronounced ge-o-be-uh) is a recent sub-discipline of Geographic Information Science devoted to developing automated methods to partition remote sensing (RS) imagery into meaningful geographically based image-objects, and assessing their characteristics through spatial, spectral and temporal scales. Its applications range from agriculture and natural resource management, to national defense and global climate change. Its economic impact spans from data collection, hardware and software vendors, developers and users, to recipients of sound sustainable environmental policy.


At its most fundamental level, GEOBIA requires image segmentation, attribution, classification and the ability to query and link individual objects (a.k.a. segments) in space and time. In order to achieve this, GEOBIA incorporates knowledge from a vast array of disciplines involved in the generation and use of geographic information (GI). It is this unique focus on RS and GI that distinguishes GEOBIA from related disciplines such as Computer Vision and Biomedical Imaging, where outstanding research exists that may significantly contribute to GEOBIA.


A key objective of GEOBIA is to develop and apply appropriate theory, methods and tools sufficient to replicate (and or exceed experienced) human interpretation of RS images in automated/semi-automated ways, that will result in increased repeatability and production, while reducing subjectivity, labor and time costs.

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About this page

This wiki page is an initiative complementing the upcoming 2nd International Conference on Geo-Object-based Image Analysis ([1], Calgary, 5-7 August 2008). It's goal is to ensure that a common understanding of GEOBIA as a discipline is agreed and integrated within the research and commercial software that is being developed for object-based image analysis. This integrative effort can draw upon the strong theoretical and application based components that already exist in the established fields of remote sensing, computer vision, and landscape ecology among others. A way to achieve this is by developing a living document – an GEOBIA guide book – to which practitioners can turn to for understanding and direction. Wikis may be the ideal vehicle to develop such a device. As such, we cordially invite interested parties to contribute to this page so that GEOBIA may be developed from a user community and scientific perspective, rather than solely from commercial drivers. We intend to move this page to Wikipedia once it reaches enough content and quality.


This page is open to anyone interested to contribute. To edit this page, click on the 'edit' tab at the top of this page (you need to create an user account beforehand). If you only want to modify a particular section or subsection, click on the '[edit]' hyperlink to the right of the relevant header. When you are done, click the 'show preview' button at the bottom of this page to see the new appearance the page would have, and if it is OK click the 'save page' button. Further information can be found at Wikipedia:How to edit a page. If you don't agree with the content of some item within the page, you may change or delete it, but please explain your reasons in the discussion page, which can be reached by clicking the 'discussion tab' on top of this page. Further guidance on modifying wiki pages can be found in Wiki Etiquette.

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Brief history

The first RS spaceborne sensors were multispectral to compensate for the reduced spatial resolution of the data, with the implicit assumption that different landcover types would behave like distinct surface materials susceptible of being analyzed with a spectrometric approach. Hence it was natural to treat each pixel as a sample introduced in a desktop spectrometer, and therefore the individual pixel has been considered the basic unit of analysis in RS since the beginning. Several digital classification methods were developed based on this approach and soon (even before the launch of Landsat-1 in 1972) they were established as the trusted common practice, becoming the accepted paradigm in the analysis of RS images. The fact that pixels are not isolated but knitted into an image full of spatial patterns was left out of the paradigm since it could only be exploited by human interpreters.

GEOBIA has emerged as an alternative to this paradigm, and is based on the assumption that semi-automated object-based methods can emulate (or exceed) visual interpretation, making better use of spatial information implicit within RS images and providing greater integration with vector based GIS.


The ECHO classifier developed by David Langrebe's team at Purdue University in the 70s included a segmentation algorithm that can be viewed as the first GEOBIA precedent. The image was divided into 'cells' of 2x2 pixels that were subject to a simple test of statistical homogeneity. Cells failing the test were assumed to overlap a boundary and were later classified on a per-pixel basis.Adjacent cells passing the test were selected and subsequently subject to hypothesis testing for statistical similarity. Cells found similar were merged or annexed into regions. 'In this way an object can grow to its natural boundaries, whereupon either the cell selection or annexation test will fail'.

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Theory

Here are a number of theoretical issues that need to be addressed:


  • There is a lack of consensus and research on the conceptual foundations of this new paradigm i.e., on the relationship between image-objects (segments) and landscape objects (patches). For example:
(i) what is the basis to believe that segmentation-derived objects are fine representations of landscape structural-functional units?
(ii) How do you know when your segmentation is good?


  • In addition, there exists a poor understanding of scale and hierarchical relations among objects derived at different resolutions:
(iii) Do segments at coarse resolutions really ‘emerge’ or ‘evolve’ from the ones at finer resolutions?
(iv) Should boundaries perfectly overlap (coincide) through scale? Operationally it’s very appealing, but what is the ecological basis for this?
(vi) how should we deal with transition zones in the landscape?

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Methods

This section gives an overview of known methods of segmentation and classification that are been used within OBIA

Segmentation

Classification

Software tools

This subsection gives an overview of software suites or modules, either commercially available or available as demo, that implement some GEOBIA method(s). Add a paragraph of length proportional to the interest of the tool to GEOBIA practitioners, provide external hyperlinks to further information, and please use no marketing speech, as this page is not an infomercial. Insert your paragraph in alphabetical order.

Definiens Developer,which resulted from the continuous advancement of eCognition is an object based image analysis software which features various segmentation algorithms that enable users to generate a networked object hierarchy. These objects can then be classified either rule-based or sample based. Definiens Developer is part of the Definiens Enterprise Image Intelligence Suite which consists of client and server software products which meet the needs of any image-based business process. The client products are role-based and support the needs of the different users. The server products provide a batch processing environment that enables the analysis of tens, hundreds or millions of images. A free trial version can be downloaded here For exchange with fellow users, visit the Definiens User Forum

The Feature Analyst and LIDAR Analyst software systems from Overwatch Geospatial (formerly Visual Learning Systems) are available as a plugin to six different software platforms: ArcGIS, RemoteView, ELT, ERDAS IMAGINE, SOCET SET and GeoMedia. Feature Analyst has been available for 8 years and is a complete end-to-end system for Automated/Assisted Feature Extraction (AFE) and LIDAR Analyst is its counterpart for LIDAR feature extraction. Both systems create vector products with a simple and intuitive workflow for feature classification and image segmentation. The products provides utilities for 2D and 3D feature extraction, image segmentation, cleanup tools, automated attribution tools, handles all types of imagery, stereo capabilities, hyperspectral workflows, database updating utilities, and many other capabilities. A free software evaluation is available at the Overwatch VLS Ops website.

The ENVI Feature Extraction Module is available as a plugin to the ENVI remote sensing software package available from ITT Visual Information Solutions (formerly Research Systems, Inc.). This add-on module uses object-based image analysis technology to extract features from imagery and automatically vectorize into Shapefile format. The ENVI Feature Extraction Module uses the combined process of segmenting an image into regions of pixels, computing attributes for each region to create objects, and classifying the objects (with rule-based or supervised classification) based on attributes in order to extract features. To request a free software evaluation simply contact your ITT-VIS Representative.

Applications

This section is intended to give an overview of problems where OBIA has been successfully applied, with emphasis on improvements achieved compared to other approaches. For particular examples or success stories, insert the references in the 'Further reading'

section

Landcover mapping and monitoring
Forestry
Urban studies
Disaster prevention, assessment and relief
[ propose another field of application... ]

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Key Terms

No discipline can be considered such without a consistent ontology. An ontology is an specification of a conceptualization of a knowledge domain, that is, an ontology is a (typically hierarchical) taxonomy that describes the objects relevant to a given field and their mutual relations in a formal way. The aim of this section is to help develop a GEOBIA ontology with contribution from peers. We believe that wikis may allow to reach consensus much faster than through formal publications. Please add your proposals of key terms (include the ';' wiki markup before the term)and/or new definitions (include the ':' wiki markup before it). In order to avoid 'authority bias', please do not include authorship of definitions. Insert new terms so that the list remains alphabetically ordered.

Feature
  • A term to be avoided within this discipline, as it is ambiguous (it can refer both to a ground object and to a dimension of the hyperspace where the classification operates, i.e an attribute used to discriminate between different classes of objects.


Image-objects
  • Delimited regions of the image that are internally coherent and different from their surroundings
  • Delimited regions of the image that are internally coherent


Scale


Segmentation


Spatial Resolution of a Classification
  • The minimum size of the circle, expressed by its diameter, over which the surroundings of a particular point on the earth have to be observed in order to determine the class (e.g. landcover type) from a list (legend) that should be assigned to that point.


Structural signature
  • Recurrent spatial patterns observable at certain scales that can be readily associated to specific thematic classes.

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Key Issues

Here are a number of strategic issues that need to be addressed:


Other resources

GEOBIA research groups (in alphabetic order)

  • Foothills Facility for Remote Sensing and GIScience - University of Calgary, Alberta, Canada - Contact: Dr Geoffrey J. Hay ([2])
  • Z_GIS – Centre of Geoinformatics at Salzburg University. ([3])

Conferences

  • Object-Based Landscape Analysis. Two-day meeting of RSPSoc Land Cover/ Land Use SIG 7-8 April 2009, University of Nottingham, United Kingdom([4]). Call for abstracts - deadline 9 February 2008. Earth Observation imagery is a major source of information for characterizing the Earth's surface, but is conventionally analyzed using pixel- based approaches that do not incorporate the concept of landscape features or real world objects. Approaches and technology that exploit landscape features to increase the accuracy and usability of EO-derived products are now becoming mainstream. These object-based methods employ spatial frameworks often aligned to the needs of scientists, policy makers and end users, but straightforward application of off-the-shelf packages is not always well- conceived. The aim of this meeting is to bring together practitioners in remote sensing, GIS and environmental science to identify best-practice in the development and application of object-based landscape analysis techniques. Contact Paul Aplin / Geoff Smith c/o rspsoc@rspsoc.org if interested.
  • GEOBIA, 2008 - Pixels, Objects, Intelligence: Geo-Object Based Image Analysis for the 21St Century.([5]). GEOBIA 2008 will be held at the University of Calgary (UofC), Alberta, Canada August, 6-7, 2008, with an icebreaker on the evening of August 5, and workshops scheduled for Aug 4-5, and 8-9. We are expecting 250 participants including four internationally recognized keynote speakers from academia and industry. The conference will be based on two or three concurrent oral sessions - and at least one poster session per day - covering a range of topics from theory, methods, applications and social implications. Opportunities for industry booths and displays will be promoted. Conference proceedings will be linked with ISPRS working groups to provide literary/scientific standards and online access. A GEOBIA special issue of Photogrammetric Engineering and Remote Sensing (PE&RS) will be published in 2009.
  • 14th Australasian Remote Sensing and Photogrammetry Conference.([6]). 14ARSPC will be held at the Darwin Convention Centre, Darwin, Northern Territory, Australia, September 29 - October 3 2008. There are several object-based specific sessions and other OB papers in other sessions (program is online @ http://www.14arspc.com). Three object-based workshops are also part of the program. Those wishing to attend will need to register very soon as accommodation options are becoming limited. Any queries to info@14arspc.com.
  • Remote Sensing and Photogrammetry Society - Annual Conference 2007 ([7], Newcastle upon Tyne, United Kingdom, 11 - 14 September). If sufficient GEOBIA-related abstracts are accepted there may be an opportunity for a special session within the conference. Please submit a 500 word abstract using the on-line submission form at the conference website by the deadline of 17:00 (GMT) 26th March 2007. Also, please contact Geoff Smith (gesm@ceh.ac.uk) if you are interested.
  • 1st International Conference on Object-based Image Analysis ([8], Salzburg, 4-5 July 2006), Flyer (PDF): [9]

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GEOBIA Literature