When characterizing the processes that shape ecosystems, ecologists increasingly use the unique perspective offered by repeat observations of remotely sensed imagery. However, the concept of change embodied in much of the traditional remote‐sensing literature was primarily limited to capturing large or extreme changes occurring in natural systems, omitting many more subtle processes of interest to ecologists. Recent technical advances have led to a fundamental shift toward an ecological view of change. Although this conceptual shift began with coarser‐scale global imagery, it has now reached users of Landsat imagery, since these datasets have temporal and spatial characteristics appropriate to many ecological questions. We argue that this ecologically relevant perspective of change allows the novel characterization of important dynamic processes, including disturbances, long‐term trends, cyclical functions, and feedbacks, and that these improvements are already facilitating our understanding of critical driving forces, such as climate change, ecological interactions, and economic pressures.

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In the 1990s, a bark beetle (Ips typographus [L.]) infection caused the decay of spruce forest (Picea abies [L.] Karst.) in the central part of the Š umava Mountains, the Czech Republic, bordering the Bavarian Forest National Park, Germany, where the bark beetle infection started in the late 1980s. Some areas were left without human intervention and, consequently, the trees around these areas were removed to stop further bark beetle outbreak. The objective of our study was the assessment of surface temperature (ST) change in spruce forest decayed under bark beetle and following clear-cutting. The change detection of ST is based on the comparison of modelled values and thermal satellite data. For this purpose, Landsat scenes from July 11th, 1987 and July 28th, 2002 were used.The models describe the dependence of ST of living spruce forest on topography. The topography effect is based on the Altitude and Hillshade index, which expresses the influence of Aspect and Slope on the relief illumination. Then the modelled ST values were extrapolated for decayed spruce forest and clear-cut areas. In order to increase model accuracy, the forest edge zones (90 m wide) were removed because of their different energy balance; then explained variability value (R 2 ) increased from 0.37 to 0.55. The results of comparing modelled values with satellite ST in the decayed spruce forest and clear-cut areas show an average increase of ST by 5.2 and 3.5°C, respectively. The thermal satellite data from 1987 were used for model validation. This showed that the accuracy of ST modelling using topography was sufficient, because the difference between the modelled ST with and without decayed spruce forest and clear-cut areas was at most only 0.4°C.

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