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This paper discusses potential of obtaining answers to key issues related to the use of landscape metrics by applying approaches of mathematical landscape morphology. Mathematical landscape morphology that has emerged in Russia’s geography in recent years serves as the basis of the new scientific direction in landscape science. Mathematical landscape morphology deals with quantitative regularities of the development of landscape patterns and methods of mathematical analysis. The results of the research conducted have demonstrated that landscape metrics are subjected to stochastic laws specific to genetic types of territories; furthermore, these laws may be derived through mathematical analysis. It has been also shown that the informational value of different landscape metrics differs and can be predicted. Finally, some landscape metrics, based on the values derived from single observations, nevertheless allow one to provide assessment of dynamic parameters of existing processes; thus, the volume of repeated monitoring observations could be reduced. Other metrics do not posses this characteristic. All results have been obtained by applying mathematical landscape modeling.

About the Author

Alexey Victorov

Russian Federation
Deputy Director on Research, Ye. M. Sergeev Institute of Geoecology of RAS P.O. Box 145 Ulanskyi Ln, 13-2, 101000 Moscow, Russia


1. Ivashutin, L.I. and V.A. Nikolaev. (1969) On analysis of the landscape structure of physiographic

2. regions, Vestnik MGU, Ser. Geogr., № 4, pp. 49–59. (in Russian).

3. Kapralova, V.N. (2007) Application of remote sensing and mathematical morphology of

4. landscape for studying thermo-karst processes. Landform Analysis, 5, pp. 35–37.

5. Kapralova, V.N. (2008) The use of remote sensing data and methods of mathematical

6. landscape morphology to explore thermokarst processes // The International Year of the

7. Planet Earth: implications for geoecology, geology, and hydrogeology. Sergeev’s Readings.

8. Moscow: GEOS. 10, pp. 430–434 (in Russian).

9. Leitao, A.B., J. Miller, and K. McGarigal. (2006) Measuring landscapes: a planner’s handbook.

10. Island press, Washington, 245 p.

11. McGarigal, K., S.A. Cushman, M.C. Neel, and E. Ene. (2002) FRAGSTATS: Spatial Pattern Analysis

12. Program for Categorical Maps. Computer software program produced by the authors

13. at the University of Massachusetts, Amherst, MA University of Massachusetts. Available

14. from http:/

15. Moser, B., J.A.G. Jaeger, U. Tappeiner, E. Tasser, and B. Eiselt. (2007) Modification of the effective

16. mesh size for measuring landscape fragmentation to solve the boundary problem.

17. Landscape Ecol 22(3), pp. 447–459.

18. Nikolaev, V.A. (1975). On analyzing the structure of the steppe and semi-steppe landscapes

19. from aerial photographs. Bulletin of Moscow State University. Ser. Geogr., № 3, pp. 15–21

20. (in Russian).

21. Nikolaev, V.A. (1978) Classification and small-scale mapping of landscapes. Moscow:

22. Moscow State University Press, 63 p. (in Russian).

23. Pshenichnikov, A.E. (2004) Automated morphometric analysis of geographic features

24. on images and maps for thematic mapping. Candidate Dissertation Abstract. Moscow:

25. Moscow State University Press, 24 p. (in Russian).

26. Riitters, K.H., R.V. O’Neill, C.T. Hunsaker, J.D. Wickham, D.H. Yankee, S.P. Timmins, K.B. Jones,

27. and B.L. Jackson. (1995) A vector analysis of landscape pattern and structure metrics.

28. Landscape Ecol. 10 (1), pp. 23–39.

29. Victorov, A.S. (1995) A mathematical model of thermokarst lake plains as one of the

30. foundations of interpretation of satellite imagery. Study of the Earth from the Space, № 5,

31. pp. 42–51. (in Russian).

32. Victorov, A.S. (1998) Mathematical landscape morphology. Moscow: Tratek. 180 p.

33. (in Russian).

34. Victorov A.S. (2005a) Mathematical Models of Thermokarst and Fluvial Erosion Plains GIS

35. and Spatial Analysis. Proceedings of IAMG 2005, Toronto, Canada, 1, pp. 62–67.

36. Victorov, A.S. (2005b) Quantitative assessment of natural hazards using methods of

37. mathematical landscape morphology. Geoecology, № 4, pp. 291–297 (in Russian).

38. Victorov, A.S. (2006) Basic problems of mathematical landscape morphology. Moscow:

39. Nauka. 252 p. (in Russian).

40. Victorov, A.S. (2007a) The model of the age differentiation of alluvial plains. Geoecology.

41. № 4, pp. 34–46 (in Russian).

42. Victorov, A.S. (2007b) Risk Assessment Based on the Mathematical Model of Diffuse

43. Exogenous Geological Processes. Mathematical Geology, vol. 39 №8, 2007. pp. 735–748.

44. Victorov, A.S. and O.N. Trapeznikova. (2000) The erosion plain mathematical model as

45. a base for space images interpretation methods in geoenvironmental research. In:

46. Proceedings of the 4th international symposium on environmental geotechnology and

47. global sustainable development. Lowell, Boston, 1, pp. 603–612.

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