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Golfgootproeven en ook andere laboratoriumproeven zijn van groot belang gebleken voor het kwantificeren van golfbelastingen en bijbehorende erosie van dijken en duinen, maar hebben ook een aantal beperkingen die relevant zijn voor de belastingen die in het laboratorium opgewekt kunnen worden, en de doorwerking daarvan op dijkbekledingen en dijkerosie. In een onderzoekstrategie voor de ontwikkeling, kalibratie en validatie van modellen voor de belasting van dijkbekledingen moeten zulke beperkingen worden meegewogen. Dit was aanleiding een quick scan uit te voeren, gericht op potentieel relevante verschillen tussen golfgootmetingen en in-situ veldmetingen, zowel voor extreme als vaker voorkomende condities. Een belangrijk doel van de quick scan is het op een rij zetten van onderzoeksvragen gerelateerd aan de verschillen tussen golfgoot- en veldmetingen, en meer generiek tussen laboratorium- en veldmetingen.

In het kader van de Waterwet1 (aanpassing van 2014) is de nieuwe normering ingevoerd per 1/1/2017. Het Wettelijke Beoordelingsinstrumentarium (WBI2017) en Ontwerpinstrumentarium (OI) hebben daarbij respectievelijk in 2017 en 2014 het instrumentarium geleverd voor de beoordeling en het ontwerp. Dit rapport gaat over een update binnen het WBI2017 en het OI voor het watersysteem Vecht- en IJsseldelta. Dit rapport beschrijft hoe de Hydraulische Belastingen voor de Vecht- en IJsseldelta in 2020 zijn bepaald. De volgende onderwerpen worden behandeld: de reden voor de verandering; hoe het systeem is veranderd; de fysische modellen; de statistiek en modelonzekerheden; de probabilistische modellen Hydra-NL en Riskeer; verschillen met WBI2017 en OI; een impactanalyse; gevoeligheidsberekeningen.

Afgelopen jaren hebben KNMI en Deltares in samenwerking met RWS WVL ten behoeve van het beoordelingsinstrumentarium voor de primaire waterkeringen veel werk verzet voor het verbeteren van de extreme-wind-statistiek en ruimtelijke windmodellering. Bij gebrek aan voldoende metingen waren in eerste instantie onvoldoende verbeteringen haalbaar. Daarom heeft KNMI een nieuwe aanpak ontwikkeld, op basis van zeer lange KNMI-modelreeksen. In de jaren 2019 en 2020 zijn een proef-of-concept ontwikkeld, en een plan van aanpak voor de uitrol ervan. Het huidige Meerwaardedocument is geschreven ter ondersteuning van die uitrol. Daarnaast gaat dit rapport in op aanvullende toepassingen van de methode, en hun meerwaarde. Het huidige rapport is primair bedoeld als businesscase-beschrijving, voor verdere achtergronden wordt verwezen naar de in dit rapport genoemde literatuurreferenties.

Korte notitie over het risico van een tsunami en een meteotsunami langs de Nederlandse kust.

Op 28 februari 2010, rond 2 uur in de ochtend, bereikte de storm Xynthia de westkust van Frankrijk. Op meerdere locaties bezweken de waterkeringen, met kustoverstromingen tot gevolg. Meer dan 50.000 hectare aan land overstroomde. In totaal vielen in Frankrijk 47 doden, de meesten door het water en een enkeling door de gevolgen van de storm. Vooral de regio’s Vendée en CharenteMaritime kregen het zwaar te verduren. De schade en de slachtoffers van de overstroming zijn niet alleen veroorzaakt door het natuurverschijnsel zelf, maar zijn ook door het menselijk handelen of het uitblijven daarvan. Nederland kan uit deze Franse kustoverstromingen lessen trekken. De omstandigheden in Nederland en Frankrijk zijn voor een groot deel vergelijkbaar. Zo is ook in Frankrijk sprake van laaggelegen kustgebieden die gevoelig zijn voor overstroming. Weliswaar is het beschermingsniveau in Nederland veel hoger, maar ook in Nederland is een overstroming denkbaar. Net als in Frankrijk wordt een overstroming langs de Nederlandse kust veroorzaakt door een combinatie van getijde, stormopzet en golfaanval. Ook weten regelgeving vertonen overeenkomsten; de basis hiervan is gelegd in de tijd van Napoleon. Dit boek beschrijft de overstroming door de storm Xynthia en de gevolgen daarvan. We trekken hier lessen uit en doen aanbevelingen voor Nederland. We zoeken aansluiting bij de drie onderdelen van meerlaagsveiligheid: preventie, ruimtelijke inrichting en rampenbeheersing.

On the 28th of February 2010 at 2 a.m. the storm Xynthia hit the French Atlantic coast. The storm surge combined with the high tide and large waves caused flood defences to fail along the coastline from the Gironde (Bordeaux) to the Loire Estuary. A significant amount of land, (>50 000 ha) was consequently flooded and 47 people died as a result of the storm. Most people died due to the flooding (they drowned, were exhausted or died from hypothermia). A number of people died as a result of the storm itself (storm debris). The French departments of Vendée and Charente Maritime suffered the most. Some parts of the departments Gironde and Loire Atlantique were also flooded. Since 1953 the Netherlands has not had any experience with major floods. Large parts of the Netherlands are also prone to coastal flooding, even though we have very high safety standards. The Netherlands can learn from this flood in a neighbouring country with a common history and legal system. The foundation of the legal system in the Netherlands and France was laid down in the Napoleonic period with the introduction of the book on common law. Jurisprudence plays a minor role in Napoleonic law. The flood was not caused by natural phenomena alone, organisational failure plays a large role in understanding the flood. This book describes the Xynthia storm and its consequences. Using multiple viewpoints of the “multy-layer safety”: flood warning, flood prevention, special planning and disaster management, this book gives lessons from the storm for the Netherlands. Please note: We have used all available public sources up to the beginning of August 2010. The official facts about the storm have been assembled in three French public enquiries, by each house of parliament and by the French ministry of Ecology, Energy Transport and Development MEEDEM. Our purpose is to give lessons for the Netherlands and not to give a perfect list of facts about the storm. The Dutch, French and English versions differ sligh

Le 28 février 2010, vers 2 heures du matin, la tempête Xynthia atteint la côte occidentale de la France. A plusieurs endroits, les digues, dunes et d’autres ouvrages cédèrent, donnant lieu à des inondations du littoral. Plus de 50.000 hectares de terres furent inondées. Au total, la France compta 47 morts suite à la tempête, la plupart d’entre eux suite à la crue. Essentiellement les régions de la Vendée et de la Charente-Maritime endurèrent de terribles privations. Les dégâts et les victimes ne sont pas uniquement la conséquence du phénomène naturel, mais également des interventions de l’homme ou le manque de celles-ci. Les Pays-Bas pourraient tirer des leçons de ces inondations côtières françaises. Les circonstances aux Pays-Bas et en France sont, dans une grande mesure, comparables. La France, elle aussi, connaît des zones côtières à basse altitude sensibles aux inondations. Certes, le niveau de protection aux Pays-Bas est plus élevé, mais une inondation aux Pays-Bas est aussi bien concevable. Tout comme en France, une inondation du littoral néerlandais est causée par une combinaison de la marée, d’une tempête et d’une surcote. Les législations et les réglementations présentent des concordances ; leurs bases datent de l’époque de Napoléon. Ce livre décrit l’inondation par la tempête Xynthia et ses conséquences. Nous en tirons des leçons et nous formulons des avis pour les Pays-Bas. Nous cherchons à nous associer à une protection contre l’inondation à trois volets: la prévention, l’aménagement du territoire et la maîtrise des catastrophes.

This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach.

Soft biometrics are characteristics that can be used to describe, but not uniquely identify an individual. These include traits such as height, weight, gender, hair, skin and clothing colour. Unlike traditional biometrics (i.e. face, voice) which require cooperation from the subject, soft biometrics can be acquired by surveillance cameras at range without any user cooperation. Whilst these traits cannot provide robust authentication, they can be used to provide coarse authentication or identification at long range, locate a subject who has been previously seen or who matches a description, as well as aid in object tracking. In this paper we propose three part (head, torso, legs) height and colour soft biometric models, and demonstrate their verification performance on a subset of the PETS 2006 database. We show that these models, whilst not as accurate as traditional biometrics, can still achieve acceptable rates of accuracy in situations where traditional biometrics cannot be applied.

Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.

In public venues, crowd size is a key indicator of crowd safety and stability. Crowding levels can be detected using holistic image features, however this requires a large amount of training data to capture the wide variations in crowd distribution. If a crowd counting algorithm is to be deployed across a large number of cameras, such a large and burdensome training requirement is far from ideal. In this paper we propose an approach that uses local features to count the number of people in each foreground blob segment, so that the total crowd estimate is the sum of the group sizes. This results in an approach that is scalable to crowd volumes not seen in the training data, and can be trained on a very small data set. As a local approach is used, the proposed algorithm can easily be used to estimate crowd density throughout different regions of the scene and be used in a multi-camera environment. A unique localised approach to ground truth annotation reduces the required training data is also presented, as a localised approach to crowd counting has different training requirements to a holistic one. Testing on a large pedestrian database compares the proposed technique to existing holistic techniques and demonstrates improved accuracy, and superior performance when test conditions are unseen in the training set, or a minimal training set is used.

The relationship between multiple cameras viewing the same scene may be discovered automatically by finding corresponding points in the two views and then solving for the camera geometry. In camera networks with sparsely placed cameras, low resolution cameras or in scenes with few distinguishable features it may be difficult to find a sufficient number of reliable correspondences from which to compute geometry. This paper presents a method for extracting a larger number of correspondences from an initial set of putative correspondences without any knowledge of the scene or camera geometry. The method may be used to increase the number of correspondences and make geometry computations possible in cases where existing methods have produced insufficient correspondences.

A novel shape recognition algorithm was developed to autonomously classify the Northern Pacific Sea Star (Asterias amurenis) from benthic images that were collected by the Starbug AUV during 6km of transects in the Derwent estuary. Despite the effects of scattering, attenuation, soft focus and motion blur within the underwater images, an optimal joint classification rate of 77.5% and misclassification rate of 13.5% was achieved. The performance of algorithm was largely attributed to its ability to recognise locally deformed sea star shapes that were created during the segmentation of the distorted images.

Texture segmentation is the process of partitioning an image into regions with different textures containing similar group of pixels. This paper presents a comparative study of four texture segmentation methods based on the following features: descriptors, heuristic function, fuzzy logic and Mask based features. Many types of textures are considered for analysis. The comparative results show that descriptor based approach is the most suitable for segmenting both natural and mosaic textures whereas heuristic function based approach is most suitable for random textures. Fuzzy features based approach is found to yield better segments for regular patterns while Mask feature based approach is the best for segmenting Natural images, but fails miserably on Mosaic textures. Fuzzy C-means classification is used for achieving texture segmentation.

This paper presents the recognition of handwritten Hindi Characters based on the modified exponential membership function fitted to the fuzzy sets derived from features consisting of normalized distances obtained using the Box approach. The exponential membership function is modified by two structural parameters that are estimated by optimizing an objective function that includes the entropy and error function. A Reuse Policy that provides guidance from the past policies is utilized to improve the reinforcement learning. This relies on the past errors exploiting the past policies. The Reuse Policy improves the speed of convergence of the learning process over the strategies that learn without reuse and combined with the use of the reinforcement learning, there is a 25-fold improvement in training. Experimentation is carried out on a database of 4750 samples. The overall recognition rate is found to be 90.65%.

This paper presents an appearance--based method to automatically determine places from vision data for topological mapping. The approach exploits the continuity of the visual appearance of consecutive images when a robot traverses the environment. Places are determined by clustering colour histograms, and a probabilistic filtering strategy eliminates spurious places with weak evidence. Further, we discuss steps towards the induction of the topology of an environment from a sequence of visited places. Particularly, our system faces the problem of physically different places which appear identical in perception space. We present results from experiments on two data sets, one consist of panoramic images and another one includes images from a standard camera.

Cultural objects are increasingly stored and generated in digital form, yet effective methods for their indexing and retrieval still remain an open area of research. The main problem arises from the disconnection between the content-based indexing approach used by computer scientists and the description-based approach used by information scientists. There is also a lack of representational schemes that allow the alignment of the semantics and context with keywords and low-level features that can be automatically extracted from the content of these cultural objects. This paper presents an integrated approach to address these problems, taking advantage of both computer science and information science approaches. The focus is on the rationale and conceptual design of the system and its various components. In particular, we discuss techniques for augmenting commonly used metadata with visual features and domain knowledge to generate high-level abstract metadata which in turn can be used for semantic and context-based indexing and retrieval. We use a sample collection of Vietnamese traditional woodcuts to demonstrate the usefulness of this approach.

Current research on shape based classification has been generally aimed at utilising various visual features. Previous research has shown that the existing knowledge in a specific domain can assist in understanding the image content. Ontologies are currently being used for explicit representation of the domain knowledge. In this paper, two contributions are presented: 1) a shape ontology framework which constitutes both domain and shape ontologies and in which domain and shape ontologies are mapped to each other. 2) A new approach for automatic construction of shape ontology. The experimental results are promising. Future work will focus on validating the framework and automatic method of the shape ontology construction for a much larger dataset.

This paper presents a new approach for efficient 3D rendering on mobile devices, where selective rendering can be achieved with the help of 3D scene annotation. By taking advantage of first person environments in most 3D applications, we are able to annotate the flooring details of the 3D space. This allows 3D environments to be interfaced using a higher level view of objects. With the higher level of scene understanding, it is possible to determine which 3D objects are not required for loading or rendering based on the viewer’s location and its surrounding constraints.

We develop a method for estimating the flight critical parameters of pitch angle, roll angle and the three body rates using horizon detection and optical flow. We achieve this through the use of an image processing front-end to detect candidate horizon lines through the use of morphological image processing and the Hough transform. The optical flow of the image for each candidate line is calculated, and using these measurements, we are able to estimate the body rates of the aircraft. Using an Extended Kalman Filter (EFK), the candidate horizon lines are propagated and tracked through successive image frames, with statistically unlikely horizon candidates eliminated. Results qualitativly describing the performance of the image processing front-end on real datasets are presented, followed by an analysis of the improvement when utilising the motion model of the vehicle.

Low-cost aerial vision systems need to face the challenges of using low quality products to perform aerial photography. Such systems are widely used in remote controlled aircrafts and unmanned aerial vehicles (UAVs) to collect aerial imagery and are used for image acquisition, terrain mapping or remote sensing. A one-pixel shift in a 0.8 mega pixel resolution image captured from a UAV operating at 1000ft will correspond to about 2.5m measurement error on the ground. In our case, a vibrating fisheye lens moving relative to the camera added new uncertainties in the collected images and required compensation. This paper presents a vibration compensation approach using a modified Hough Transform utilizing the circle shaped image provided by a fisheye lens. We define the fisheye circle boundary by using a Canny edge detector. Our vibration compensation was tested using our collected aerial images with enhanced performance in more than 80% of the cases.

Cheap digital cameras are readily available. They can be mounted on robots and used to build maps of the surrounding environment. However, these cameras suffer from several drawbacks such as a narrow field of view, low resolution and limited range due to perspective. These limitations can cause traditional approaches to Simultaneous Localization and Mapping to fail due to insufficient information content in the visual sensor data. This paper discusses these issues and presents a solution for indoor environments.

Existing asymmetric encryption algorithms require the storage of the secret private key. Stored keys are often protected by poorly selected user passwords that can either be guessed or obtained through brute force attacks. This is a weak link in the overall encryption system and can potentially compromise the integrity of sensitive data. Combining biometrics with cryptography is seen as a possible solution but any biometric cryptosystem must be able to overcome small variations present between different acquisitions of the same biometric in order to produce consistent keys. This paper discusses a new method which uses an entropy based feature extraction process coupled with Reed-Solomon error correcting codes that can generate deterministic bit-sequences from the output of an iterative one-way transform. The technique is evaluated using 3D face data and is shown to reliably produce keys of suitable length for 128-bit Advanced Encryption Standard (AES).

In the period 1997-2007, an extensive wind and wave measuring campaign has been carried out on Lake IJssel and Lake Sloten in The Netherlands. The aim of this campaign was to gather and analyse welldocumented wind and wave measurements of high quality, for a range of fetch, depth and (strong) wind conditions. The data should serve a number of purposes, and dike design in particular. The campaign has resulted in a good indication of wind and wave climatology of both lakes, while enhancing the knowledge on various aspects of wind and waves. However, the gap between measured conditions (up to 9 Beaufort inclusive) and dike design conditions (with 12 Beaufort winds) has only slightly decreased due to an exceptionally long storm-free period from 1990 to at least mid 2007. Hence, it is recommended to continue (part of) the present measurements until at least one event with 10 Beaufort winds is suitably measured. In the following, a brief overview of the contents of this report is given. Chapters 1 and 2 give some introductory details like relevance and aim of the present project, the measuring locations, instrumentation, data processing and data validation. Detailed overviews of experimental techniques and measuring errors are given in Appendix A-B. Appendix C shows that step gauge, capa probe and log-a-level instruments all (can) agree excellently, but that the latter is sensitive to wind from 6 Beaufort (12 m/s) winds on. In Chapter 3, the availability and range of the data is discussed. In the last 5 years, data availability during gales was excellent (Table 3.1). Some gales yielded wave periods that nearly equalled the (12 Beaufort) dike design values. However, water levels, wave heights and wave-run-up levels all remained well below the design values (section 3.3). Chapter 4 is about wind and temperatures. A key result is the fact that during gales, wind speed differences between land and water largely disappear; a feature that can not yet be explained by any of the