3 resultados para sequential exploitation

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Throughout the world, pressures on water resources are increasing, mainly as a result of human activity. Because of their accessibility, groundwater and surface water are the most used reservoirs. The evaluation of the water quality requires the identification of the interconnections among the water reservoirs, natural landscape features, human activities and aquatic health. This study focuses on the estimation of the water pollution linked to two different environmental issues: salt water intrusion and acid mine drainage related to the exploitation of natural resources. Effects of salt water intrusion occurring in the shallow aquifer north of Ravenna (Italy) was analysed through the study of ion- exchange occurring in the area and its variance throughout the year, applying a depth-specific sampling method. In the study area were identified ion exchange, calcite and dolomite precipitation, and gypsum dissolution and sulphate reduction as the main processes controlling the groundwater composition. High concentrations of arsenic detected only at specific depth indicate its connexion with the organic matter. Acid mine drainage effects related to the tin extraction in the Bolivian Altiplano was studied, on water and sediment matrix. Water contamination results strictly dependent on the seasonal variation, on pH and redox conditions. During the dry season the strong evaporation and scarce water flow lead to low pH values, high concentrations of heavy metals in surface waters and precipitation of secondary minerals along the river, which could be released in oxidizing conditions as demonstrated through the sequential extraction analysis. The increase of the water flow during the wet season lead to an increase of pH values and a decrease in heavy metal concentrations, due to dilution effect and, as e.g. for the iron, to precipitation.

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A single picture provides a largely incomplete representation of the scene one is looking at. Usually it reproduces only a limited spatial portion of the scene according to the standpoint and the viewing angle, besides it contains only instantaneous information. Thus very little can be understood on the geometrical structure of the scene, the position and orientation of the observer with respect to it remaining also hard to guess. When multiple views, taken from different positions in space and time, observe the same scene, then a much deeper knowledge is potentially achievable. Understanding inter-views relations enables construction of a collective representation by fusing the information contained in every single image. Visual reconstruction methods confront with the formidable, and still unanswered, challenge of delivering a comprehensive representation of structure, motion and appearance of a scene from visual information. Multi-view visual reconstruction deals with the inference of relations among multiple views and the exploitation of revealed connections to attain the best possible representation. This thesis investigates novel methods and applications in the field of visual reconstruction from multiple views. Three main threads of research have been pursued: dense geometric reconstruction, camera pose reconstruction, sparse geometric reconstruction of deformable surfaces. Dense geometric reconstruction aims at delivering the appearance of a scene at every single point. The construction of a large panoramic image from a set of traditional pictures has been extensively studied in the context of image mosaicing techniques. An original algorithm for sequential registration suitable for real-time applications has been conceived. The integration of the algorithm into a visual surveillance system has lead to robust and efficient motion detection with Pan-Tilt-Zoom cameras. Moreover, an evaluation methodology for quantitatively assessing and comparing image mosaicing algorithms has been devised and made available to the community. Camera pose reconstruction deals with the recovery of the camera trajectory across an image sequence. A novel mosaic-based pose reconstruction algorithm has been conceived that exploit image-mosaics and traditional pose estimation algorithms to deliver more accurate estimates. An innovative markerless vision-based human-machine interface has also been proposed, so as to allow a user to interact with a gaming applications by moving a hand held consumer grade camera in unstructured environments. Finally, sparse geometric reconstruction refers to the computation of the coarse geometry of an object at few preset points. In this thesis, an innovative shape reconstruction algorithm for deformable objects has been designed. A cooperation with the Solar Impulse project allowed to deploy the algorithm in a very challenging real-world scenario, i.e. the accurate measurements of airplane wings deformations.