Le chemin de traverse

UANL

Le secteur de la Traverse de Lévis, entrer par la grande porte.

Affiche de projet terminal, baccalauréat en Urbanisme. Institut d'urbanisme, Université de Montréal.

Using airborne laser altimetry to improve river flood extents delineated from SAR data

Flood extent maps derived from SAR images are a useful source of data for validating hydraulic models of river flood flow. The accuracy of such maps is reduced by a number of factors, including changes in returns from the water surface caused by different meteorological conditions and the presence of emergent vegetation. The paper describes how improved accuracy can be achieved by modifying an existing flood extent delineation algorithm to use airborne laser altimetry (LiDAR) as well as SAR data. The LiDAR data provide an additional constraint that waterline (land-water boundary) heights should vary smoothly along the flooded reach. The method was tested on a SAR image of a flood for which contemporaneous aerial photography existed, together with LiDAR data of the un-flooded reach. Waterline heights of the SAR flood extent conditioned on both SAR and LiDAR data matched the corresponding heights from the aerial photo waterline significantly more closely than those from the SAR flood extent conditioned only on SAR data.

Contemporary (2001) and ‘Little Ice Age’ glacier extents in the Buordakh Massif, Cherskiy Range, north east Siberia

The Buordakh Massif of the Cherskiy Range of sub-arctic north east Siberia, Russia has a cold continental climate and supports over 80 glaciers. Despite previous research in the region, a georeferenced map of the glaciers has only recently been completed and an enhanced version of it is reproduced in colour here. The mountains of this region reach heights in excess of 3,000 m and the glaciers on their slopes range in size from 0.1 to 10.4 km2. The mapping has been compiled through the interpretation of Landsat 7 ETM+ satellite imagery from August 2001 which has been augmented by data from a field campaign undertaken at the same time. The glaciers of the region are of the cold, ‘firn-less’ continental type and their mass balance relies heavily on the formation of superimposed ice. Moraines which lie in front of the glaciers by up to a few kilometres are believed to date from the Little Ice Age (ca. 1550-1850 AD). Over half of the glaciers mapped have shown marked retreat from these moraines.

Calibrating flood inundation models: identifying and addressing uncertainty in satellite observed flood extents

Improvements in the resolution of satellite imagery have enabled extraction of water surface elevations at the margins of the flood. Comparison between modelled and observed water surface elevations provides a new means for calibrating and validating flood inundation models, however the uncertainty in this observed data has yet to be addressed. Here a flood inundation model is calibrated using a probabilistic treatment of the observed data. A LiDAR guided snake algorithm is used to determine an outline of a flood event in 2006 on the River Dee, North Wales, UK, using a 12.5m ERS-1 image. Points at approximately 100m intervals along this outline are selected, and the water surface elevation recorded as the LiDAR DEM elevation at each point. With a planar water surface from the gauged upstream to downstream water elevations as an approximation, the water surface elevations at points along this flooded extent are compared to their ‘expected’ value. The pattern of errors between the two show a roughly normal distribution, however when plotted against coordinates there is obvious spatial autocorrelation. The source of this spatial dependency is investigated by comparing errors to the slope gradient and aspect of the LiDAR DEM. A LISFLOOD-FP model of the flood event is set-up to investigate the effect of observed data uncertainty on the calibration of flood inundation models. Multiple simulations are run using different combinations of friction parameters, from which the optimum parameter set will be selected. For each simulation a T-test is used to quantify the fit between modelled and observed water surface elevations. The points chosen for use in this T-test are selected based on their error. The criteria for selection enables evaluation of the sensitivity of the choice of optimum parameter set to uncertainty in the observed data. This work explores the observed data in detail and highlights possible causes of error. The identification of significant error (RMSE = 0.8m) between approximate expected and actual observed elevations from the remotely sensed data emphasises the limitations of using this data in a deterministic manner within the calibration process. These limitations are addressed by developing a new probabilistic approach to using the observed data.

The potential of flood forecasting using a variable-resolution global Digital Terrain Model and flood extents from Synthetic Aperture Radar images

A basic data requirement of a river flood inundation model is a Digital Terrain Model (DTM) of the reach being studied. The scale at which modeling is required determines the accuracy required of the DTM. For modeling floods in urban areas, a high resolution DTM such as that produced by airborne LiDAR (Light Detection And Ranging) is most useful, and large parts of many developed countries have now been mapped using LiDAR. In remoter areas, it is possible to model flooding on a larger scale using a lower resolution DTM, and in the near future the DTM of choice is likely to be that derived from the TanDEM-X Digital Elevation Model (DEM). A variable-resolution global DTM obtained by combining existing high and low resolution data sets would be useful for modeling flood water dynamics globally, at high resolution wherever possible and at lower resolution over larger rivers in remote areas. A further important data resource used in flood modeling is the flood extent, commonly derived from Synthetic Aperture Radar (SAR) images. Flood extents become more useful if they are intersected with the DTM, when water level observations (WLOs) at the flood boundary can be estimated at various points along the river reach. To illustrate the utility of such a global DTM, two examples of recent research involving WLOs at opposite ends of the spatial scale are discussed. The first requires high resolution spatial data, and involves the assimilation of WLOs from a real sequence of high resolution SAR images into a flood model to update the model state with observations over time, and to estimate river discharge and model parameters, including river bathymetry and friction. The results indicate the feasibility of such an Earth Observation-based flood forecasting system. The second example is at a larger scale, and uses SAR-derived WLOs to improve the lower-resolution TanDEM-X DEM in the area covered by the flood extents. The resulting reduction in random height error is significant.

Improving the TanDEM-X Digital Elevation Model for flood modelling using flood extents from Synthetic Aperture Radar images

The topography of many floodplains in the developed world has now been surveyed with high resolution sensors such as airborne LiDAR (Light Detection and Ranging), giving accurate Digital Elevation Models (DEMs) that facilitate accurate flood inundation modelling. This is not always the case for remote rivers in developing countries. However, the accuracy of DEMs produced for modelling studies on such rivers should be enhanced in the near future by the high resolution TanDEM-X WorldDEM. In a parallel development, increasing use is now being made of flood extents derived from high resolution Synthetic Aperture Radar (SAR) images for calibrating, validating and assimilating observations into flood inundation models in order to improve these. This paper discusses an additional use of SAR flood extents, namely to improve the accuracy of the TanDEM-X DEM in the floodplain covered by the flood extents, thereby permanently improving this DEM for future flood modelling and other studies. The method is based on the fact that for larger rivers the water elevation generally changes only slowly along a reach, so that the boundary of the flood extent (the waterline) can be regarded locally as a quasi-contour. As a result, heights of adjacent pixels along a small section of waterline can be regarded as samples with a common population mean. The height of the central pixel in the section can be replaced with the average of these heights, leading to a more accurate estimate. While this will result in a reduction in the height errors along a waterline, the waterline is a linear feature in a two-dimensional space. However, improvements to the DEM heights between adjacent pairs of waterlines can also be made, because DEM heights enclosed by the higher waterline of a pair must be at least no higher than the corrected heights along the higher waterline, whereas DEM heights not enclosed by the lower waterline must in general be no lower than the corrected heights along the lower waterline. In addition, DEM heights between the higher and lower waterlines can also be assigned smaller errors because of the reduced errors on the corrected waterline heights. The method was tested on a section of the TanDEM-X Intermediate DEM (IDEM) covering an 11km reach of the Warwickshire Avon, England. Flood extents from four COSMO-SKyMed images were available at various stages of a flood in November 2012, and a LiDAR DEM was available for validation. In the area covered by the flood extents, the original IDEM heights had a mean difference from the corresponding LiDAR heights of 0.5 m with a standard deviation of 2.0 m, while the corrected heights had a mean difference of 0.3 m with standard deviation 1.2 m. These figures show that significant reductions in IDEM height bias and error can be made using the method, with the corrected error being only 60% of the original. Even if only a single SAR image obtained near the peak of the flood was used, the corrected error was only 66% of the original. The method should also be capable of improving the final TanDEM-X DEM and other DEMs, and may also be of use with data from the SWOT (Surface Water and Ocean Topography) satellite.

L’infidélité dans le couple : Charles et Emma Bovary dans Madame Bovary de Flaubert et Dinah et Loulou dans Traversée de la Mangrove de Maryse Condé

Ce travail sur l’infidélité dans le couple traite les différentes sources de l’ennui ainsi que leurs conséquences dans la vie du couple. Les différentes opinions de différents auteurs sur la cause de l’infidélité dans le couple sont vues en long et en large. L’éducation féminine du XIXème siècle éclaire sur le handicap qui a entrainé certaines filles dans le malheur car l’éducation de l’époque ne les avait pas bien préparées pour devenir de bonnes épouses. Ce mémoire montre l’image de la religion dans ces deux oeuvres : Madame Bovary et Traversée de la mangrove. La question est de voir comment ces auteurs peignent la religion dans ces oeuvres et pourquoi ils adoptent l’infidélité pour sauver la femme de son ennui. Enfin, la comparaison de ces ennuis est faite afin de voir que dans ces couples, malgré le fait qu’ils appartiennent à des époques différentes, l’ennui dans le couple est le même. Ces auteurs ont procédé aux mêmes stratégies pour sauver le couple de son ennui. La morale critique et religieuse a été utilisée pour aborder ce thème, lorsque nous avons fait une lecture biblique de ces deux oeuvres.

A framework for mapping vegetation over broad spatial extents : a technique to aid land management across jurisdictional boundaries

Mismatches in boundaries between natural ecosystems and land governance units often complicate an ecosystem approach to management and conservation. For example, information used to guide management, such as vegetation maps, may not be available or consistent across entire ecosystems. This study was undertaken within a single biogeographic region (the Murray Mallee) spanning three Australian states. Existing vegetation maps could not be used as vegetation classifications differed between states. Our aim was to describe and map ‘tree mallee’ vegetation consistently across a 104 000km2 area of this region. Hierarchical cluster analyses, incorporating floristic data from 713 sites, were employed to identify distinct vegetation types. Neural network classification models were used to map these vegetation types across the region, with additional data from 634 validation sites providing a measure of map accuracy. Four distinct vegetation types were recognised: Triodia Mallee, Heathy Mallee, Chenopod Mallee and Shrubby Mallee. Neural network models predicted the occurrence of three of them with 79% accuracy. Validation results identified that map accuracy was 67% (kappa = 0.42) when using independent data. The framework employed provides a simple approach to describing and mapping vegetation consistently across broad spatial extents. Specific outcomes include: (1) a system of vegetation classification suitable for use across this biogeographic region; (2) a consistent vegetationmapto inform land-use planning and biodiversity management at local and regional scales; and (3) a quantification of map accuracy using independent data. This approach is applicable to other regions facing similar challenges associated with integrating vegetation data across jurisdictional boundaries.

Traverse: Energie. Erzeugung, Verbreitung und Nutzung im 19. und 20. Jahrhundert

Energie ist eine der wichtigsten Ressourcen der Gegenwart. Wir nutzen sie täglich zum Heizen, Kochen, Beleuchten, Fortbewegen, Arbeiten. Neben der Endlichkeit der fossilen Energieträger rückten in den letzten Jahren auch die mit den Energieregimen verbundenen Risiken (wieder) vermehrt ins Bewusstsein. Gerade deshalb erlebte besonders die Energiegeschichte zum 20. Jahrhundert jüngst einen Aufschwung. Die einzelnen Beiträge zeichnen dabei nicht nur den ungestillten Energiehunger während des Wirtschaftsbooms nach dem Zweiten Weltkrieg nach, sondern gehen auch den Wurzeln des heutigen Energieregimes im 19. Jahrhundert nach. Thematisiert werden die wichtigsten Triebkräfte der Innovationen in der Wasserkraft, die Entwicklungslinien der Energieverwendung und des Energieverbrauchs im Verkehr und in der Landwirtschaft sowie die Auswirkungen eines mehrtägigen Stromausfalls auf die Gesellschaft.