Petr Rapant

An initial formal model for spatial data infrastructures

The Commission on Spatial Data Standards of the International Cartographic Association is working to define formal models and technical characteristics of Spatial Data Infrastructures (SDI). To date, this work has been restricted to the Enterprise and Information Viewpoints from the ISO Reference Model for Open Distributed Processing standard. The Commission has developed models for these two viewpoints. These models describe how the different parts of an SDI fit together in the viewpoints in question. These models should be seen as a contribution towards the overall model of the SDI and its technical characteristics. During the model development process, the roles of the different Actors in an SDI in the Enterprise and Information Viewpoints have also been identified in Use Case diagrams of an SDI. All the models have been developed using the Unified Modeling Language. ✠ This author passed away in September 2007.

A spatial data infrastructure model from the computational viewpoint

The Commission on Geoinformation Infrastructures and Standards of the International Cartographic Association (ICA) is working on defining models of spatial data infrastructures (SDIs). SDI models from the enterprise and information viewpoints of the Reference Model for Open Distributed Processing (RM-ODP) have already been presented. Our model from the computational viewpoint identifies the main computational objects of an SDI and their interfaces, which are modelled using Unified Modelling Language (UML) component diagrams. Presented here is the first comprehensive SDI model from the computational viewpoint, which enhances the understanding of the computational objects and their interactions in an SDI. This viewpoint complements the previous two and together, the three viewpoints contribute towards a more holistic interpretation of an SDI, which is independent of specific SDI legislation, technology and implementations. For the computational viewpoint, we identified six computational objects, SDI Registry, SDI Data, SDI Processing, SDI Application, SDI Portrayal and SDI Management, and their provided and required interfaces. We describe the interactions of the computational objects in stakeholder activities and the roles they play in the different processes of SDI development and use, which we identified as Initiation, Creation, Management, Manipulation, Access, Processing, Evaluation and Liaison. Two tables summarise the SDI services that are provided by computational objects for stakeholder activities and SDI processes.

Exploring the Impact of a Spatial Data Infrastructure on Value-Added Resellers and Vice Versa

A spatial data infrastructure (SDI) is an evolving concept for facilitating, coordinating and monitoring the exchange and sharing of geospatial data and services. In earlier work, we developed a formal model for an SDI from the Enterprise, Information and Computational Viewpoints of the Reference Model for Open Distributed Processing. Within the Enterprise Viewpoint, we identified six stakeholders, including a Value-added Reseller (VAR), a stakeholder who adds value to an existing product or group of products, and then makes it available as a new product. A VAR is particularly important because they extend the usefulness of SDI products: high quality and useful VAR products help ensure continued funding by governments of publicly provided data. We engaged with various types of VAR around the world, to understand what encourages or inhibits VARs in an SDI, and the contributions VARs can make to an SDI. The results are described here.

The Academic SDI—Towards Understanding Spatial Data Infrastructures for Research and Education

The demand for geospatial data across different disciplines and organisations has led to the development and implementation of spatial data infrastructures (SDI) and the theory and concepts behind them. An SDI is an evolving concept about facilitating and coordinating the exchange of geospatial data and services between stakeholders from different levels in the spatial data community. Universities and other research organisations typically have well-established libraries and digital catalogues for scientific literature, but catalogues for geospatial data are rare. Geospatial data is widely used in research, but geospatial data produced by researchers is seldom available, accessible and usable, e.g., for purposes of teaching or further research after completion of the project. This chapter describes the experiences of a number of SDI implementations at universities and research institutes. Based on this, the Academic SDI, an SDI for research and education, is defined and its stakeholders are described. The purpose, scope and stakeholders of the Academic SDI are described based on the formal model of an SDI developed by the International Cartographic Association (ICA) Commission on SDIs and Standards (formerly the Commission on Geoinformation Infrastructures and Standards). The results contribute to understanding the state-of-the-art in SDI implementations at universities and research institutes; how the Academic SDI differs from a ‘regular’ SDI; and which role players need to be involved in a successful SDI implementation for research and education.

Hodnocení rizikovosti území obce pro případ přívalové povodně

Předpověď výskytu přivalových povodni se potýka předevsim s mimořadnou nepravidelnosti vzniku přicinných sražek. Ty teprve ve spojitosti s nasycenim uzemi předchozimi sražkami přivedou k realizaci dalsi mistni faktory, ktere mohou důsledky extremnich kratkodobých sražek buď zhorsit, anebo naopak zmirnit. Dalsi vlastnosti uzemi obce tak představuji trvalý potencial pro adekvatni reakci tohoto uzemi po vydatných sražkach. Podle dosavadnich znalosti je možne rizikovost konkretniho uzemi pro připad přivalove povodně po extremnich sražkach předem vyhodnotit. Nastanou-li takove sražky, nebo pokud se k nim teprve schyluje, mistni povodňový stab ma k dispozici alespoň casový předstih k výklaseni poplachu a vydat varovani před povodni. V idealnim připadě je možne takove hodnoceni zakomponovat jak do konceptu rozhodovani krizoveho stabu, tak vůpžit do uzemně planovaci dokumentace.

Dynamical Flash Flood Risk Forecast

Flash floods represent very dynamical natural phenomenon. Mostly, they are the result of torrential rains which can rise suddenly in any part of a country and are tough to predict. Of course, there are many weather forecasting systems, but their spatial and temporal resolution is usually insufficient for these purposes. There are also monitoring systems which can either register precipitation over the ground (a network of rain gauge stations) or runoff in riverbeds (a network of hydrometric stations). Again, spatial (and possibly temporal) resolution is not sufficient, and in the case of runoff monitoring, there is a substantial delay between actual rainfall and registration of runoff in riverbeds. And, of course, when the hydrometric station registers higher runoff than the flash floods is running or even over. From the point of early warning, all these systems reveal disadvantages. Aside from these systems, there is one which provides us with timely information about the spatial and temporal distribution of precipitation intensity over the ground. That is weather radar. We will demonstrate possible usage of these data for dynamic prediction of flash flood risk distribution in space and time over the monitored area. Proper processing of these data in combination with soil saturation indicator established using Flash flood guidance methodology developed by the US Hydrologic Research Center can generate timely information usable for early warning with a substantially reduced level of false warnings.

Regionální a blesková povodeň jako limitující faktor rozvoje

Lokalizacni a rozvojove faktory jsou zpravidla dobře zname, zkoumane a zohledňovane při přijimani řeseni v rozhodovaci sfeře. Naopak limitujici faktory rozvoje obvykle stoji v pozadi. Soucasne datove zdroje, znalosti a modelacni technologie umožňuji do znacne miry předvidat rozsah nastale povodňove situace. Hodnoceni miry rizika regionalni nebo bleskove povodně nema být informaci odrazujici investory, ale naopak usměrňujici jejich aktivity do bezpecneho prostoru. Znalost rizikových lokalit v CR z hlediska uvaděných typů povodni přispiva rovněž bezpecnosti navstěvniků a mistniho obyvatelstva. Poznatky vhodně zakomponovane do rozvojových planů vsech dimenzi naopak podporuji iniciativy mistnich i externich investorů. Přispěvek doklada nekonvencni využiti veřejně dostupných geodat v podobě nabidky zasadni informace pro plany regionalniho rozvoje.

Nonparametric Prediction of the Onset of Regional Floods: Floods in North-western Bohemia, Czech Republic, 2010

Currently, ongoing global climate change brings, among other things, an increasing frequency of extreme weather events such as heavy rains, which can cause flash floods. Responsible authorities have tried to develop systems for early warning of such events. Such systems already exist in the US and in some European countries. They often rely on the prediction of extreme rainfall, possibly with the use of weather radar data, as well as rainfall-runoff models. The weakness in these systems, which limits their global usage, is based on the precise use of rainfall-runoff models and the attempt to quantify the impacts of extreme rainfall in the affected area. Therefore, we have developed a methodology based on the simplified data inputs (data from weather radar) that release a warning for potentially vulnerable areas in the longest time possible before extreme rainfall effects are due to occur. Our ambition is not to quantify these effects. Due to the short time interval between downpours and flash floods caused by them, we do not consider this information to be significant. We decided to test our methodology inter alia on a case of regional flooding, which was the result of regional precipitations combined with extreme local rains. The results presented in this paper show that, even in this situation, the proposed methodology allows us to provide an early warning for the population to take refuge in a safe site.

Visual System for Metric 3D Data Gathering and Processing in Real Time

Emergency events can create situations, which exclude presence of people in hazardous places or at least create conditions hostile or dangerous for people. Using special equipment for assessment of a situation can help to do some operations without direct presence of people in place. There are some stationary or mobile means, mostly remotely controlled, which can be directed or navigated to risky place to do some visual investigation. These tools are usually equipped by simple camera system, which permits to do some visual investigations but they provide no metric information about observed scene. Presented paper describes modular system which permits 3D metric measurements in dangerous or inaccessible places.