Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Map comparison methods that simultaneously address overlap and structure

  • Original Article
  • Published:
Journal of Geographical Systems Aims and scope Submit manuscript

Abstract

Methods for map comparison such as the Kappa and Tau statistics have grown popular in applications of remote sensing accuracy assessment. These methods take pairs of raster maps as sets of paired observations and do not consider spatial structure except for cell-by-cell overlap. In contrast, landscape structure metrics such as mean patch size that are commonly used in landscape ecology do express spatial structure, however without addressing cell-by-cell overlap. This paper introduces a number of comparison methods that consider spatial structure and overlap simultaneously. They achieve this by involving the neighbourhood of a cell in the calculation of similarity at its location. For this, the methods make use of a distance weighted moving window. Two test cases demonstrate that the different comparison methods offer a spatial account of varied aspects of map similarity. It is found that the methods can best be used in conjunction with a visual analysis; they then serve to quantify, reject or confirm hypotheses.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  • Barredo JI, Demicheli L (2003) Urban sustainability in developing countries’ megacities: modelling and predicting future urban growth in Lagos. Cities 20:297–310

    Article  Google Scholar 

  • Binaghi E, Brivio PA, Ghezzi P, Rampini A (1999) A fuzzy set-based accuracy assessment of soft classification. Pattern Recogn Lett 20:935–948

    Article  Google Scholar 

  • Costanza R (1989) Model goodness of fit: a multiple resolution procedure. Ecol Model 47:199–215

    Article  Google Scholar 

  • Csillag F, Boots B (2004) Towards comparing maps as spatial processes. In: Fisher P (ed) Developments in spatial data handling. Proceedings of SDH 2004. Springer, Berlin Heidelberg New York

  • Ehlschlaeger CR (2000) Representing uncertainty of area class maps with a correlated inter-map cell swapping heuristic. Comput Environ Urban Syst 24:451–469

    Article  Google Scholar 

  • Fewster RM, Buckland ST (2001) Similarity indices for spatial ecological data. Biometrics 57:495–501

    Article  PubMed  MathSciNet  Google Scholar 

  • Foody GM (2002) Status of land cover classification accuracy assessment. Remote Sens Environ 80:185–201

    Article  Google Scholar 

  • Hagen A (2002) Multi-method assessment of map similarity. Paper presented at the 5th AGILE conference on geographic information science, Palma, Spain

  • Hagen A (2003) Fuzzy set approach to assessing similarity of categorical maps. Int J Geogr Inf Sci 17:235–249

    Article  Google Scholar 

  • Hagen-Zanker A, Uljee I, Straatman B (2005) Further developments of a fuzzy set map comparison approach. Int J Geogr Inf Sci 19:769–785

    Article  Google Scholar 

  • Lewis HG, Brown M (2001) A generalized confusion matrix for assessing area estimates from remotely sensed data. Int J Remote Sens 22:3223–3235

    Article  Google Scholar 

  • McGarigal K, Cushman SA, Neel MC, Ene E (2002) FRAGSTATS: spatial pattern analysis program for categorical maps. Computer software program produced by the authors at the University of Massachusetts, Amherst. Available at the following web site: http://www.umass.edu/landeco/research/fragstats/fragstats.html

  • Monserud RA, Leemans R (1992) Comparing global vegetation maps with the Kappa statistic. Ecol Model 62:275–293

    Article  Google Scholar 

  • Pontius RG Jr (2000) Quantification error versus location error in comparison of categorical maps. Photogramm Eng Remote Sens 66:1011–1016

    Google Scholar 

  • Pontius RG Jr (2002) Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions. Photogramm Eng Remote Sens 68:1041–1049

    Google Scholar 

  • Power C, Simms A, White R (2001) Hierarchical fuzzy pattern matching for the regional comparison of land use maps. Int J Geogr Inf Sci 15:77–100

    Article  Google Scholar 

  • Remmel TK, Perera AH (2002) Accuracy of discontinuous binary surfaces: a case study using boreal forest fires. Int J Geogr Inf Sci 16:287–298

    Article  Google Scholar 

  • RIKS (2005) Map Comparison Kit: product information [Internet] (http://www.riks.nl/mck; 1 February 2005)

  • Shalan MA, Arora MK, and Elgy J (2003) Cafcam: crisp and fuzzy classification accuracy measurement software. Paper presented at GeoComputation 2003, Southhampton 8–10 September 2003

  • Straatman B, White R, Engelen G (2004) Towards an automatic calibration procedure for constrained cellular automata. Comput Environ Urban Syst 28:149–170

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Research Institute for Knowledge Systems, P.O. Box 463, 6200 AL, Maastricht, The Netherlands

    Alex Hagen-Zanker

Authors
  1. Alex Hagen-Zanker
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alex Hagen-Zanker.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hagen-Zanker, A. Map comparison methods that simultaneously address overlap and structure. J Geograph Syst 8, 165–185 (2006). https://doi.org/10.1007/s10109-006-0024-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10109-006-0024-y

Keywords

Search

Navigation