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Space and airborne sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. Confusion about fire intensity, fire severity, burn severity, and related terms can result in the potential misuse of the inferred information by land managers and remote sensing practitioners who require unambiguous remote sensing products for fire management. The objective of the present paper is to provide a comprehensive review of current and potential remote sensing methods used to assess fire behavior and effects and ecological responses to fire. We clarify the terminology to facilitate development and interpretation of comprehensible and defensible remote sensing products, present the potential and limitations of a variety of approaches for remotely measuring active fires and their post-fire ecological effects, and discuss challenges and future directions of fire-related remote sensing research.

Abstract. Explicit and quantitative models for the spatial prediction of soil and landscape attributes are required for environmental modelling and management. In this study, advances in the spatial representation of hydrological and geomorphological processes using terrain analysis techniques are integrated with the development of a field sampling and soil-landscape model building strategy. Statistical models are developed using relationships between terrain attributes (plan curvature. compound topographic index, upslope mean plan curvature) and soil attributes (A horizon depth, Solum depth, E horizon presencelabsence) in an area with uniform geology and geomorphic history. These techniques seem to provide appropriate methodologies for spatial prediction and understanding soil landscape processes.

The study on the relationship between the soil aggregates stability assessed using water stable aggregate (WSA) index and the selected terrain and soil properties was performed on a morphologically diverse study site in Chernozem soil region of Southern Moravia. Soil analyses and detailed digital elevation model processing were the main methods adopted in the study. The soil structure stability is negatively influenced by the soil material removal from the steep parts of the back-slope and re-deposition of the mineral loess material at the base of the slope. The highest aggregates stability was identified in the upper flat parts of the study plot, undisturbed by erosion processes, and at the concave parts of the back-slope with intensive accumulation of organic matter. Statistical analysis showed a significant dependence of aggregates stability on organic carbon content and plan curvature index.

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