Eusébio Reis

Reconstructing pre-erosion topography using spatial interpolation techniques: a validation-based approach

Understanding the topographic context preceding the development of erosive landforms is of major relevance in geomorphic research, as topography is an important factor on both water and mass movement-related erosion, and knowledge of the original surface is a condition for quantifying the volume of eroded material. Although any reconstruction implies assuming that the resulting surface reflects the original topography, past works have been dominated by linear interpolation methods, incapable of generating curved surfaces in areas with no data or values outside the range of variation of inputs. In spite of these limitations, impossibility of validation has led to the assumption of surface representativity never being challenged.In this paper, a validation-based method is applied in order to define the optimal interpolation technique for reconstructing pre-erosion topography in a given study area. In spite of the absence of the original surface, different techniques can be nonetheless evaluated by quantifying their capacity to reproduce known topography in unincised locations within the same geomorphic contexts of existing erosive landforms. A linear method (Triangulated Irregular Network, TIN) and 23 parameterizations of three distinct Spline interpolation techniques were compared using 50 test areas in a context of research on large gully dynamics in the South of Portugal. Results show that almost all Spline methods produced smaller errors than the TIN, and that the latter produced a mean absolute error 61.4% higher than the best Spline method, clearly establishing both the better adjustment of Splines to the geomorphic context considered and the limitations of linear approaches.The proposed method can easily be applied to different interpolation techniques and topographic contexts, enabling better calculations of eroded volumes and denudation rates as well as the investigation of controls by antecedent topographic form over erosive processes.

Remote Sensing Technologies for the Assessment of Marine and Coastal Ecosystems

This chapter reviews the Remote Sensing (RS) technologies that are particularly appropriate for marine and coastal ecosystem research and management. RS techniques are used to perform analysis of water quality in coastal water bodies; to identify, characterize and analyze river plumes; to extract estuarine/coastal sandy bodies; to identify beach features/patterns; and to evaluate the changes and integrity (health) of the coastal lagoon habitats. For effective management of these ecosystems, it is essential to have satellite data available and complementary accurate information about the current state of the coastal regions, in addition to well-informed forecasts about its future state. In recent years, the use of space, air and ground-based RS strategies has allowed for the rapid data collection, Image processing (Pixel-Based and Object-Based Image Analysis (OBIA) classification) and dissemination of such information to reduce vulnerability to natural hazards, anthropic pressures, and to monitoring essential ecological processes, life support systems and biological diversity.

Assessment of the recurrence interval of wildfires in mainland Portugal and the identification of affected LUC patterns

ABSTRACT Wildfires are responsible for major land use and land cover (LUC) changes. These events are frequent and catastrophic in Portugal and are responsible for great damage and loss of human life. In this study, a map to assess the probability of wildfire occurrence (PWO) in mainland Portugal was created for the period 1975-2017 (first half of 2017). The PWO was obtained by the superimposition of all layers by adding all the burned areas for the total period. It was observed that the occurrences and extent of the burned areas are highly variable from year to year. The PWO map was cross-referenced with LUC geoinformation to evaluate the LUC types that were more affected by the wildfires. The results presented and the PWO maps are important for the management and planning of forest areas and for the creation of guidelines to implement preventive and reactive actions in case of wildfires.