The transiogram as a graphic metric for characterizing the spatial patterns of landscapes

  • Ruiting ZhaiEmail author
  • Weidong Li
  • Chuanrong Zhang
  • Weixing Zhang
  • Wenjie Wang
Research Article



Landscape metrics play an important role in measurement, analysis, and interpretation of spatial patterns of landscapes. There are a variety of different landscape metrics widely used in landscape ecology. However, existing landscape metrics are mostly non-graphic and single-value indices, which may not be sufficient to describe the complex spatial correlation and interclass relationships of various landscapes. As a transition probability diagram over the lag distance, the transiogram, which emerged in recent years, essentially provides a new graphic metric for measuring and visualizing the auto and cross correlations of landscape categories.


To explore the capability of the transiogram for measuring spatial patterns of categorical landscape maps and compare it with existing landscape metrics.


Sixteen commonly-used landscape metrics and transiograms (including auto- and cross-transiograms) were estimated and compared for land cover/use classes in four areas with different landscapes.


Results show that (1) these transiograms can provide visual information about the proportions, aggregation levels, interclass adjacencies, and intra-class/interclass correlation ranges of landscape classes; (2) sills and auto-correlation ranges of transiograms are correlated with the values of some landscape metrics; and (3) the peak height ratios of idealized transiograms can effectively represent the juxtaposition strength of neighboring class pairs.


The transiogram can be an effective graphic metric for characterizing the auto-correlation of single classes (through auto-transiograms) and the complex interclass relationships, such as interdependency and juxtaposition, between different landscape classes (through cross-transiograms).


Transiogram Landscape metrics Transition probability Spatial pattern Graphic metric Visual information 



This research is partially supported by USA NSF grant No. 1414108. Authors have the sole responsibility to all of the viewpoints presented in the paper.

Supplementary material

10980_2018_760_MOESM1_ESM.docx (3.6 mb)
Supplementary material 1 (DOCX 3690 kb)


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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Department of Geography & Center for Environmental Science and EngineeringUniversity of ConnecticutStorrsUSA
  2. 2.Connecticut Transportation Safety Research CenterUniversity of ConnecticutStorrsUSA

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