Soil & Water Res., 2009, 4(10):S49-S58 | DOI: 10.17221/480-SWR

Evaluation of functional properties of various types of vegetation cover using remotely sensed data analysis

Jakub BROM1, 2, Jan PROCHÁZKA1, Alžběta REJŠKOVÁ2
1 Department of Landscape Management, Faculty of Agriculture, University of South Bohemia in České Budějovice, České Budějovice, Czech Republic
2 ENKI, Třeboň, Czech Republic

The dissipation of solar energy and consequently the formation of the hydrological cycle are largely dependent on the structural and optical characteristics of the land surface. In our study, we selected seven units with different types of vegetation in the Mlýnský and Horský catchments (South-Eastern part of the Šumava Mountains, Czech Republic) for the assessment of the differences in their functioning expressed through the surface temperature, humidity, and energy dissipation. For our analyses, we used Landsat 5 TM satellite data from June 25th, 2008. The results showed that the microclimatic characteristics and energy fluxes varied in different units according to their vegetation characteristics. A cluster analysis of the mean values was used to divide the vegetation units into groups according to their functional characteristics. The mown meadows were characterised by the highest surface temperature and sensible heat flux and the lowest humidity and latent heat flux. On the contrary, the lowest surface temperature and sensible heat flux and the highest humidity and latent heat flux were found in the forest. Our results showed that the climatic and energetic features of the land surface are related to the type of vegetation. We state that the spatial distribution of different vegetation units and the amount of biomass are crucial variables influencing the functioning of the landscape.

Keywords: vegetation cover; energy fluxes; surface temperature; wetness index; Normalised Difference Vegetation Index (NDVI); albedo; Landsat TM

Published: December 31, 2009  Show citation

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BROM J, PROCHÁZKA J, REJŠKOVÁ A. Evaluation of functional properties of various types of vegetation cover using remotely sensed data analysis. Soil & Water Res. 2009;4(Special Issue 2):S49-58. doi: 10.17221/480-SWR.
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