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A mixed methods approach using GIS was applied to identify places relevant for regional branding and to support co-creation in a transdisciplinary process in Northern Germany. For this purpose, local stakeholders mapped characteristic landscape features, places of leisure activities and places where they feel happy. In addition, public authoritiesâ geodata were processed to identify landscape classes and elements, which are characteristic from a quantitative point of view. The results indicate a cross-thematic, cross-methodological and cross-regional significance of water landscapes. However, their relationship to other landscape elements and further topics differs significantly in the two study regions presented here, leading to different starting points for place branding. The use of maps as a basis for discussion helps bringing together stakeholders with different experiences and involving them in brand building. In this way, the chosen approach supports inter- and transdisciplinary changes towards a sustainable regional development and acts as a bridge between brand building and its implementation on site.
Transdisciplinarity is a principle of integrative research, in which scientific and practical partners jointly generate new knowledge. This approach is supported by the German Federal Ministry of Education and Research (BMBF) within the funding priority "Innovation groups for a sustainable land use" (Förderschwerpunkt "Innovationsgruppen fĂŒr eine nachhaltige Landnutzung"). One project that has been implemented within this regard is Regiobranding. The project aims at investigating the characteristics of landscapes in different Northern German regions in order to use their uniqueness for sustainable regional branding and development. The combination and integration of heterogeneous knowledge of the different project partners from eight institutions in three federal states was a central challenge for the transdisciplinary work. In the absence of a common technical language, "space" served as a common ground for bridging differences and actively involving local partners. Against this backdrop, the local public participated in the branding process via various mapping workshops. The results of the mapping exercises were later combined with GIS-based quantitative landscape analyses derived form scientific investigation by partners from the fields of surveying, archeology and environmental planning. The paper presents results of our approach and highlights the benefits of combining qualitative analyses based on user-generated spatial content with quantitative landscape analyses based on various sources of official agencies' geodata.
3D and spectral digital recording of cultural heritage monuments is a common activity for their documentation, preservation, conservation management, and reconstruction. Recent developments in 3D and spectral technologies have provided enough flexibility in selecting one technology over another, depending on the data content and quality demands of the data application. Each technology has its own pros/cons, suited perfectly to some situations and not to others. They are mostly unknown to humanities experts, besides having a limited understanding of the data requirements demanded by the research question. These are often left to technical experts who again have a limited understanding of cultural heritage requirements. A common point of view has to be achieved through interdisciplinary discussions. Such agreements need to be documented for their future references and re-uses. We present a method based on semantic concepts that not only documents the semantic essence of such discussions, but also uses it to infer a guidance mechanism that recommends technologies/technical process to generate the required data based on individual needs. Experts' knowledge is represented explicitly through a knowledge representation that allows machines to manage and infer recommendations. First, descriptive semantics guide end users to select the optimal technology/technologies for recording data. Second, structured knowledge controls the processing chain extracting and classifying objects contained in the acquired data. Circumstantial situations during object recording and the behaviour of the technologies in that situation are taken into account. We will explain the approach as such and give results from tests at a CH object.
Disaster management requires both individual and collaborative preparedness among the various stakeholders.
Collaborative exercises aim to train stakeholders to apply the plans prepared and to identify potential problems and areas for improvement. As these exercises are costly, computer simulation is an interesting tool to evaluate preparation through a wider variety of contexts.
However, research on simulation and disaster management focuses on a particular problem rather than on the overall assessment of the plans prepared. This limitation is explained by the challenge of creating a simulation model that can represent and adapt to a wide variety of plans from various disciplines.
The work presented in this paper addresses this challenge by adapting the simulation model based on disaster management information and plans integrated into a knowledge base. The simulation model created is then automatically programmed to perform simulation experiments to improve action plans.
The results of the experiments are analyzed in order to generate new knowledge and know-how to enrich disaster management plans in a virtuous cycle.
This paper presents a proof of concept on the French national Novi plan, for which simulation experiments have made it possible to know the impact of the distribution of doctors on the application of the plan as well as to identify their distribution.
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