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DETECTION AND ASSESSMENT OF ABIOTIC STRESS OF CONIFEROUS LANDSCAPES CAUSED BY URANIUM MINING (USING MULTITEMPORAL HIGH RESOLUTION LANDSAT DATA)

https://doi.org/10.24057/2071-9388-2012-5-1-52-66

Abstract

Remote sensing have become one of decisive technologies for detection and assessment of abiotic stress situations, such as snowstorms, forest fires, drought, frost, technogenic pollution etc. Present work is aiming at detection and assessment of abiotic stress of coniferous landscapes caused by uranium mining using high resolution satellite data from Landsat. To achieve the aim, ground-based geochemical data and were coupled with the satellite data for two periods, i.e. prior and after uranium mining decommissioning, into a file geodatabase in ArcGIS/ArcInfo 9.2, where spatial analyses were carried out. As a result, weak and very weak relationships were found between the factor of technogenic pollution—Zc and vegetation indices NDVI, NDWI, MSAVI, TVI, and VCI. The TVI performs better compared to other indices in terms of separability among classes, whereas the NDVI and VCI correlate well than other indices with Zc.

About the Authors

Lachezar Filchev

Bulgaria
Chief assistant, Remote Sensing and GIS Department, Space Research and Technology Institute, Bulgarian Academy of Sciences (SRTI-BAS), Acad. Georgi Bonchev St., bl. 1, 1113, Sofia, Bulgaria


Eugenia Roumenina

Bulgaria
Associate professor, Remote Sensing and GIS Department, Space Research and Technology Institute, Bulgarian Academy of Sciences (SRTI-BAS), Acad. Georgi Bonchev St., bl. 1, 1113, Sofia, Bulgaria


References

1. Aronoff, S., Dunn, C.E., Reilly, G. (1985) Biogeochemical anomallies and Landsat imagery:

2. a comparison on the Wollaston Lake area, Saskatchewan. Miscellaneous Report, Saskatchewan

3. Geology Survey, Saskatchewan Energy and Miners, 85–4, pp. 116–124.

4. Broge, N.H., Leblanc, E. (2001) Deriving green crop area index and canopy chlorophyll

5. density of winter wheat from spectral reflectance data. Remote Sensing of Environment,

6. Vol. 81, N 1, pp. 45–57.

7. Chuvieco, E., (Ed.) Earth Observation of Global Change – The Role of Satellite Remote Sensing

8. in Monitoring the Global Environment, Springer Science + Business Media B.V., 2008,

9. р.

10. Gao, B. (1996) NDWI – A normalized difference water index for remote sensing of vegetation

11. liquid water from space. Remote Sensing of Environment, Vol. 58, N 3, pp. 257–266.

12. Garbuk, S.V., Gershenzon, V.E. (1997) Space Remote Sensing. Moscow: A and B.

13. (in Russian).

14. Mardirossian, G.H. (1999) Natural Ecocatastrophes and Aerospace Techniques and Instrumentation

15. for their Study. Sofia: Prof. Marin Drinov Academic Publishing house, 368 p.

16. (in Bulg.).

17. Naydenov, M., Misheva, L. Yordanova, I. Stanev, D., Dureva, L. (2001) Collection of Procedures

18. for Determinations on Alpha, Beta, and Gamma Radioactive Isotopes in Radioactive

19. Objects from Natural Environment, Sofia: NTSAN. (in Bulg.).

20. Staykova, P. Naydenova, C. (2008) Contamination of the environment and food with heavy

21. metals in the region of Kardjali. Scientific Conference of Ecology, Plovdiv, pp. 551–559.

22. (in Bulg.).

23. Stoyanov, S. (1999) Heavy metals in the environment and food - toxic damage to the

24. human, clinical picture, treatment, and prevention. Sofia: Pensoft – PublishSaiSet-Agri.

25. (in Bulg.)

26. Filchev, L. (2009) Design of digital landscape model of the Teyna river watershed for the

27. purposes of landscape-ecological planning. Proceedings of Fifth Scientific Conference

28. with International Participation “Space, Ecology, Nanotechnology, Safety” SENS 2009,

29. pp. 168–173.

30. Filchev, L., Yordanova, I. (2011) Landscape-geochemical studies of the effects of uranium

31. mining in Teyna river basin. Ecological Engineering and Environmental Protection (EEEP).

32. (in Bulg.) (under print).

33. Franklin, S.E. (2001) Remote Sensing for Sustainable Forest Management, LEWIS PUBLISHERS

34. – CRC Press LLC.

35. Omasa, K., Nouchi, I., De Kok, J. (Eds.) (2005) Plant Responses to Air Pollution and Global

36. Change. Tokyo, Springer–Verlag, 300 p.

37. Kogan, F.N. (1987) Vegetation index for areal analysis of crop condition. Proceedings of the

38. th Conference on Agricultural and Forest Meteorology (1987), pp. 103–106, American

39. Meteorological Society, West Lafayette, IN.

40. Kottek, M., Grieser, J., Beck, C., Rudolf, B., Rubel, F. (2006) World Map of the Koppen-

41. Geiger Climate Classification Updated, Meteorologische Zeitschrift, Vol. 15, N 3,

42. pp. 259–263.

43. McCoy, R. (2005) Field Methods in Remote Sensing, New York-London: The Guilford

44. Press, 159 p.

45. Mücher, C.A., Klijn, J.A., Wascher, D.M., Schaminée, J.H.J. (2010). A new European Landscape

46. Classification (LANMAP): A transparent, flexible and user-oriented methodology to distinguish

47. landscapes. Ecological Indicators, Vol. 10, pp. 87–103.

48. Pennin, R. (1997) Handbook of Geochemistry of the landscape, Sofia: Publishing House “St.

49. Kliment Ohridski”. (in Bulg.).

50. Qi, J., Chehbouni, A., Huete, A.R., Kerr, Y.H., Sorooshian, S. (1994) A modified soil adjusted

51. vegetation index (MSAVI). Remote Sensing of Environment, Vol. 48, N 2, pp. 119–126.

52. Rouse, J.W., Haas, R.H. et al. (1973) Monitoring vegetation systems in the Great Plains with

53. ERTS. In: Proceedings of Third ERTS Symposium, 10–14 December, Washington DC, USA,

54. NASA, 1974.

55. Saet, Yu.E., Revich, B.A., Yanin, E.P. (1990) Geochemistry of the Environment. Moscow, Nedra,

56. p. (In Russian).

57. Seiler, R.A., Kogan, F.N., Sullivan, J. (1998) AVHRR-Based Vegetation аnd Temperature Condition

58. Indices for Drought Detection in Argentina. Advances in Space Research, Vol. 21, N 3,

59. pp. 481–484.

60. Unganai, L.S., Kogan, F.N. (1998) Drought Monitoring and Corn Yield Estimation in Southern

61. Africa from AVHRR Data. Remote Sensing of Environment, Vol. 63, N 3, pp. 219–232.

62. Vodyanitskii, Yu.N. (2010) Equations for assessing the total contamination of soils with

63. heavy metals and metalloids. Eurasian Soil Science, Degradation, Rehabilitation, and Conservation

64. of Soils, Vol. 43, N 10, pp. 1184–1188.

65. About COST. (2011) Brussels, COST Office.

66. ArcGIS Desktop Help. (2008). Redlands, CA, ESRI Inc.

67. ENVI Atmospheric Correction Module – User's Guide. (2010), ITT VIS Inc.


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For citations:


Filchev L., Roumenina E. DETECTION AND ASSESSMENT OF ABIOTIC STRESS OF CONIFEROUS LANDSCAPES CAUSED BY URANIUM MINING (USING MULTITEMPORAL HIGH RESOLUTION LANDSAT DATA). GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2012;5(1):52-66. https://doi.org/10.24057/2071-9388-2012-5-1-52-66

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