Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Object-fate analysis - spatial relationships for the assessment of object transition and correspondence

  • Chapter
Object-Based Image Analysis

Part of the book series: Lecture Notes in Geoinformation and Cartography ((LNGC))

  • 7233 Accesses

Abstract

In the near future several new highest resolution, next generation satellites will be launched with panchromatic half-meter resolution imagery, e.g. WorldView 1 and 2. The ever increasing supply of high-resolution imagery seeks for adequate, i.e. more effective, more automated and reliable methods for image processing and interpretation. At the interface of geographic information science and remote sensing, object-based image analysis methodologies provide a solid basis for exploiting imagery more intelligently. Working with image objects enables (1) single feature, specific information extraction, (2) performing complex classifications and multi-scale representations and (3) spatial analysis and modeling. However, deriving image objects from various sources and in different scales implies the problem of generating inconsistent boundaries. To specifically address this challenge, a tool called LIST (landscape interpretation support tool) is used, which, based on a straight-forward principle, analyses the spatial relationships of image objects, i.e. their correspondence and their changes over time. The chapter presents a methodological discussion and preliminary results from an ongoing study on ‘object fate analysis’ (OFA). OFA means the investigation of object transition (change over time) or object correspondence (different delineations or representations). The concept and the application of OFA are illustrated by two case-studies representing both aspects. The first one carried out in medium scale uses Landsat TM and ETM imagery and shows an example of performing change assessment as well as object-based accuracy assessment. The second fine-scale study is based on SPOT 5 scenes and demonstrates how object correspondence can be assessed on two different object representations, machine-based segmentation and manual delineation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  • Baatz M and Schäpe A (2000) Multiresolution Segmentation – an optimization approach for high quality multi-scale image segmentation. In: Angewandte Geographische Informationsverarbeitung XII, Strobl, J., Blaschke, T., Griesebner, G. (eds.), Wichmann: Heidelberg, 2000, pp. 12-23.

    Google Scholar 

  • Blaschke T (2005) A framework for change detection based on image objects. In: Erasmi, S. et al. (eds.), Göttinger Geographische Abhandlungen 113, pp. 1-9.

    Google Scholar 

  • Coppin P R, Jonckheere I G and Lambin E F (2003). Digital change detection in ecosystem monitoring: a review. International Journal of Remote Sensing 25 (9). pp. 1565-1596.

    Article  Google Scholar 

  • Corry R C and Nassauer J I (2005) Limitations of using landscape pattern indices to evaluate the ecological consequences of alternative plans and designs. Landscape and Urban Planning, 72, pp. 256-280.

    Google Scholar 

  • Crews-Meyer K A (2004) Agricultural Landscape Change and Stability: Historical Patch-Level Analysis. Agriculture, Ecosystems and Environment, 101, pp. 155-169.

    Google Scholar 

  • Croissant C (2004) Landscape Patterns and Parcel Boundaries: An Analysis of Composition and Configuration of Land Use and Land Cover in South-Central Indiana. Agriculture, Ecosystems and Environment, 101, pp. 219–232.

    Article  Google Scholar 

  • Csaki C (2000) Agricultural reforms in Central and Eastern Europe and the former Soviet Union - Status and perspectives. Agricultural Economics 22, pp. 37–54.

    Article  Google Scholar 

  • Egenhofer M J (1994) Pre-Processing queries with spatial constraints. Photogrammetric Engineering & Remote Sensing, 60 (6), pp. 783-790.

    Google Scholar 

  • Hornsby K and Egenhofer M J (2000) Identity-based change: a foundation for spatio-temporal knowledge representation. International Journal of Geographical Information Science, 14 (3), pp. 207-224.

    Article  Google Scholar 

  • Hudak A T, Fairbanks D H K and Brockett B H (2004) Trends in fire patterns in a southern African savanna under alternative land use practices. Agriculture, Ecosystems and Environment, 101, pp. 307-325.

    Article  Google Scholar 

  • Kuemmerle T, Radeloff, V C, Perzanowski K and Hostert P (2006) Cross-border comparison of land cover and landscape pattern in Eastern Europe using a hybrid classification technique. Remote Sensing of Environment, 103, pp. 449-464.

    Article  Google Scholar 

  • Lang S, Schöpfer E and Langanke T, in press. Combined object-based classification and manual interpretation – Synergies for a quantitative assessment of parcels and biotopes. Geocarto International.

    Google Scholar 

  • Lang S and Blaschke T (2007) Landschaftsanalyse mit GIS. UTB-Reihe. Stuttgart: Eugen-Ulmer-Verlag, 420 pages.

    Google Scholar 

  • Lang S and Blaschke T (2006) Bridging remote sensing and GIS - what are the most supportive pillars? In: International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. No. XXXVI-4/C42, Salzburg, Austria.

    Google Scholar 

  • Langanke T and Lang S (2004) Strukturelle Indikatoren zur Beurteilung von Habitatqualität im europäischen Naturschutz. In: C. Dormann et al. (Ed.), Habitatmodelle – Methodik, Anwendung, Nutzen. Leipzig: UFZ-Berichte 9/2004, pp. 141-145.

    Google Scholar 

  • Langran G (1992) Time in geographic information system. London: Taylor and Francis.

    Google Scholar 

  • Mark D M (1999) Spatial Representation: A Cognitive View. In: Maguire, D. J. et al. (Ed.), Geographical Information Systems: Principles and Applications. New York: Wiley, pp. 81-89.

    Google Scholar 

  • Narumalani S, Mishra D R and Rothwell R G (2004) Change detection and landscape metrics for inferring anthropogenic processes in the greater EFMO area. Remote Sensing of Environment, 91, pp. 478-489.

    Article  Google Scholar 

  • Petit C C and Lambin E F (2002) Impact of data integration technique on historical land-use/land-cover change: Comparing historical maps with remote sensing data in the Belgian Ardennes. Landscape Ecology, 17, pp. 117-132.

    Article  Google Scholar 

  • Raza A and Kainz W (2001) An Object-Oriented Approach for Modeling Urban Land-Use Changes. URISA Journal, 14 (1), pp. 37-55.

    Google Scholar 

  • Schöpfer E (2005) Change Detection in Multitemporal Images utilizing Object-based Image Analysis unpublished PhD thesis, Universität Salzburg.

    Google Scholar 

  • Schöpfer E and Lang S (2006) Object fate analysis – a virtual overlay method for the categorization of object transition and object-based accuracy assessment. In: International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. No. XXXVI-4/C42, Salzburg, Austria.

    Google Scholar 

  • Schumacher J, Lang S, Tiede D, Hölbling D, Rietze J and Trautner J (2007) Einsatz von GIS und objekt-basierter Analyse von Fernerkundungsdaten in der regionalen Planung: Methoden und erste Erfahrungen aus dem Biotopinformations- und Managementsystem (BIMS) Region Stuttgart. In: Strobl J, Blaschke, T and Griesebner, G (eds.): Angewandte Geoinformatik 2007. Heidelberg: Wichmann, pp. 703-708.

    Google Scholar 

  • Southworth J, Munroe D and Nagendra H (2004) Land cover change and landscape fragmentation – comparing the utility of continuous and discrete analyses for a western Honduras region. Agriculture, Ecosystems and Environment, 101, pp. 185-205.

    Article  Google Scholar 

  • Straub BM, Heipke C (2004) Concepts for internal and external evaluation of automatically delineated tree tops. IntArchPhRS. Vol. No. XXXVI-8/W2, Freiburg, pp. 62-65.

    Google Scholar 

  • Tiede D, Moeller M, Lang S and Hoelbling D (2007) Adapting, splitting and merging cadastral boundaries according to homogenous LULC types derived from SPOT 5 data.- Proc. of the ISPRS Workshop Photogr. Image Analysis, Munich 2007.

    Google Scholar 

  • Turner M G (1990) Spatial and temporal analysis of landscape patterns. Landscape Ecology, 4, pp. 21-30.

    Article  Google Scholar 

  • Turner M G, Gardner R H and O’Neill R V (2001) Landscape Ecology in Theory and Practice: Pattern and Process. New York: Springer-Verlag.

    Google Scholar 

  • Wickam J D, O’Neill R V, Riitters K H, Wade T G and Jones K B (1997) Sensitivity of selected landscape pattern metrics to land-cover misclassification and differences in land-cover composition. Photogrammetric Engineering & Remote Sensing, 63 (4), pp. 397-402.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Schöpfer, E., Lang, S., Albrecht, F. (2008). Object-fate analysis - spatial relationships for the assessment of object transition and correspondence. In: Blaschke, T., Lang, S., Hay, G.J. (eds) Object-Based Image Analysis. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77058-9_43

Download citation

Publish with us

Policies and ethics