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Conceptual Modeling in a Meta-model of Sustainability Indicators

During last 30 years, due to the interest in sustainable development and ecology, different systems of sustainability indicators have been developed. These systems are increasingly complex, varying their scope both for territorial and thematic areas. A key point developing sustainable policies is the accessibility of good indicators. Developing a knowledge model about them can facilitate their management and interpretation. Due to the complexity of diverse set of indicators developed for 29 areas in 9 countries, we were taken to develop a conceptual model of these indicators, which associate to the different indicators their validity scope, specific interpretation and use. We have integrated the different indicators using conceptual maps (using CMap-Tool) and associating to them semantic labels. The web developed to manage the different projects includes these labels (it is a semantic web) and all the referenced texts have been labeled using them.

Exploitation of the digital elevation models in arid and semi-arid areas.selective detection of the topological shapes using different approaches

Into the framework of the Almanzora*GIS project, which objective was building a GIS tool to develop two counties north the province of Almeria, it was required to build an topologic model of the territory to evaluate proposals to stop the erosion of the area and manage hydrological risks. In our case, we decided to use the TopoShape utility included into Idrisi, which offered the required functionality (generating an adequate topologic classification of the territory). After applying the option to the work digital elevation model of the territory, we obtained a dismaying result; the image was a confusing mix of minimal topologic structures. From the bibliography, we got the idea of a) changing input configuration parameters and b) preprocessing the image using the FFT; obtaining a better result from the second option. However, we decided to analyze the reason of the observed behavior, and look for a possible use of this feature. Based in the origin of the observed behavior, the great detail of the used DEM, we built a set of treatment alternatives in order to exploit the detailed data. From this set of treatments we could establish a qualitative correlation between the changing of topologic structures and the erosion of the territory. We propose a set of alternative topologic treatments, which results are compared.

Integration of a model of insolation into Almanzora*GIS in order to take anti-erosion decisions. Analysis of alternative models

Into the framework of the Almanzora*GIS project, which has the objective of building a GIS tool to develop two counties in the northern part of the province of Almeria, it was required to build an insolation model to evaluate proposals to stop the erosion of the area. Due to the lack of detailed field data and the complex topography of the area, we decided to compute the insolation theoretically using the SolarFlux macro with ARC/Info. Computing insolation limits through the year was relatively easy using solstitial values, but evaluating the received insolation through the year, taking account of the relief required a long computation time. In this work, we present how we evaluated the impact, in quality of data and computing time, by taking account of the relief in the study area and its environment, as well as the distribution of the influence of the relief. This study presents a methodology and an example of the analysis of the conditions to compute the insolation maps taking account of the relief conditions.

Detection of main structures in digital images by expansion of border-containing windows

There is a wide set of digital images, where the problem of detecting specific structures is filtering between multiple and complex lines and secondary elements. The real problem is extracting relevant information from images, discarding uninteresting information previously, during and after the segmentation process. In this work, we resume the advantages and disadvantages of each approach, concluding a basic preference of filtering as soon as possible. In this sense, we present a method of filtering during segmentation, which mixes the mobile windows and the seeded regions approaches. Main steps are: 1) The whole image is divided in windows with a size related with the searched structures; 2) Previous knowledge about the location of the searched elements is applied to reduce the number of windows; 3) The number of windows is reduced using distribution and compacity conditions; 4) The population of each work windows is analyzed to fix one threshold; 5) Filtered work pairs are segmented using simple two populations criteria; 6) Analyzing the detected segments, the list of work window-threshold pairs is extended to include new windows. Most relevant result is the definition of a new border based segmentation approach, which gives good results searching specific objects in complex images.