Cartography and subjectiveness

A kartográfiai döntéseket, munkafolyamatokat és termékeket a szubjektivitás nagymértékben befolyásolja. Ez ellentétben van a modern tudomány sok területével ahol a tudományos munkák minden szakaszában megkövetelik a maximális objektivitást. A tanulmány elsőként Platón barlangi allegóriáját mutatja be, amely a szubjektivitás dilemmáját már a korai időkben felvetette. Ez rámutat olyan esetekre, ahol az ábrázolás szubjektivitása még inkább szándékos, és szemlélteti a térképészet nehéz helyzetét a két szélső helyzet, az objektivitás és a szubjektivitás között. A térképészet úgy kerekedik felül ezen a kihíváson, hogy szabályokat alkot, amelyek leírják a földrajzi adatok kezelését s azok ábrázolásának módját. De a térképi ábrázolásnak vannak helyi, kulturális, sőt személyes vonatkozásai is. A térképek absztrakt természete akár új (virtuális) valóságokat is létrehozhat, amely a való világ értelmezését is befolyásolhatja. A tanulmány az új médiatechnológiákon alapuló jelenlegi és jövőbeli térképek absztrakcióinak áttekintésével záródik

Visualization of uncertainty in natural hazards assessments using an interactive cartographic information system

Natural hazard assessments are always subject to uncertainties due to missing knowledge about the complexity of hazardous processes as well as their natural variability. Decision-makers in the field of natural hazard management need to understand the concept, components, sources, and implications of existing uncertainties in order to reach informed and transparent decisions. Until now, however, only few hazard maps include uncertainty visualizations which would be much needed for an enhanced communication among experts and decision-makers in order to make informed decisions possible. In this paper, an analysis of how uncertainty is currently treated and communicated by Swiss natural hazards experts is presented. The conducted expert survey confirmed that the communication of uncertainty has to be enhanced, possibly with the help of uncertainty visualizations. However, in order to visualize the spatial characteristics of uncertainty, existing uncertainties need to be quantified. This challenge is addressed by the exemplary simulation of a snow avalanche event using a deterministic model and quantified uncertainties with a sensitivity analysis. Suitable visualization methods for the resulting spatial variability of the uncertainties are suggested, and the advantages and disadvantages of their implementation in an interactive cartographic information system are discusse

Cross-attention Spatio-temporal Context Transformer for Semantic Segmentation of Historical Maps

Historical maps provide useful spatio-temporal information on the Earth's surface before modern earth observation techniques came into being. To extract information from maps, neural networks, which gain wide popularity in recent years, have replaced hand-crafted map processing methods and tedious manual labor. However, aleatoric uncertainty, known as data-dependent uncertainty, inherent in the drawing/scanning/fading defects of the original map sheets and inadequate contexts when cropping maps into small tiles considering the memory limits of the training process, challenges the model to make correct predictions. As aleatoric uncertainty cannot be reduced even with more training data collected, we argue that complementary spatio-temporal contexts can be helpful. To achieve this, we propose a U-Net-based network that fuses spatio-temporal features with cross-attention transformers (U-SpaTem), aggregating information at a larger spatial range as well as through a temporal sequence of images. Our model achieves a better performance than other state-or-art models that use either temporal or spatial contexts. Compared with pure vision transformers, our model is more lightweight and effective. To the best of our knowledge, leveraging both spatial and temporal contexts have been rarely explored before in the segmentation task. Even though our application is on segmenting historical maps, we believe that the method can be transferred into other fields with similar problems like temporal sequences of satellite images. Our code is freely accessible at https://github.com/chenyizi086/wu.2023.sigspatial.git

Inferring Implicit 3D Representations from Human Figures on Pictorial Maps

In this work, we present an automated workflow to bring human figures, one of the most frequently appearing entities on pictorial maps, to the third dimension. Our workflow is based on training data and neural networks for single-view 3D reconstruction of real humans from photos. We first let a network consisting of fully connected layers estimate the depth coordinate of 2D pose points. The gained 3D pose points are inputted together with 2D masks of body parts into a deep implicit surface network to infer 3D signed distance fields (SDFs). By assembling all body parts, we derive 2D depth images and body part masks of the whole figure for different views, which are fed into a fully convolutional network to predict UV images. These UV images and the texture for the given perspective are inserted into a generative network to inpaint the textures for the other views. The textures are enhanced by a cartoonization network and facial details are resynthesized by an autoencoder. Finally, the generated textures are assigned to the inferred body parts in a ray marcher. We test our workflow with 12 pictorial human figures after having validated several network configurations. The created 3D models look generally promising, especially when considering the challenges of silhouette-based 3D recovery and real-time rendering of the implicit SDFs. Further improvement is needed to reduce gaps between the body parts and to add pictorial details to the textures. Overall, the constructed figures may be used for animation and storytelling in digital 3D maps.Comment: to be published in 'Cartography and Geographic Information Science

Das Verfahren vor dem Berner Kindes- und Erwachsenenschutzgericht

In the canton of Bern, the Child and Adult Protection Court performs the tasks of the judicial complaints authority in child and adult protection matters. It forms part of the civil department of the higher court and is made up of senior judges as well as specialist judges. The proceedings before this specialized court are characterized by a pluralism of legal sources: a federal rump order in the Swiss Civil Code is given concrete form by a cantonal special procedural code, which in turn refers to the general administrative process of the canton of Bern. The present work systematically presents the proceedings before the child and adult protection court and is intended to serve as an orientation for those seeking justice, lawyers and members of the court on procedural issues

A decade of geoinformation sharing at ETH Zurich

Paper presented at the 27th International Cartographic Conference: Spatial data infrastructures, standards, open source and open data for geospatial (SDI-Open 2015) 20-21 August 2015, Brazilian Institute of Geography and Statistics (IBGE), Rio de Janeiro, Brazil.http://sdistandards.icaci.org/2015/09/sdi-open-2015-proceedingsam201

Geosciences Roadmap for Research Infrastructures 2025 - 2028 by the Swiss Geosciences Community

This roadmap is the product of a grassroots effort by the Swiss Geosciences community. It is the first of its kind, outlining an integrated approach to research facilities for the Swiss Geosciences. It spans the planning period 2025-2028. Swiss Geoscience is by its nature leading or highly in-volved in research on many of the major national and global challenges facing society such as climate change and meteorological extreme events, environmental pol-lution, mass movements (land- and rock-slides), earth-quakes and seismic hazards, global volcanic hazards, and energy and other natural resources. It is essential to under- stand the fundamentals of the whole Earth system to pro-vide scientific guidelines to politicians, stakeholders and society for these pressing issues. Here, we strive to gain efficiency and synergies through an integrative approach to the Earth sciences. The research activities of indivi- dual branches in geosciences were merged under the roof of the 'Integrated Swiss Geosciences'. The goal is to facilitate multidisciplinary synergies and to bundle efforts for large research infrastructural (RI) requirements, which will re-sult in better use of resources by merging sectorial acti- vities under four pillars. These pillars represent the four key RIs to be developed in a synergistic way to improve our understanding of whole-system processes and me- chanisms governing the geospheres and the interactions among their components. At the same time, the roadmap provides for the required transition to an infrastructure adhering to FAIR (findable, accessible, interoperable, and reusable) data principles by 2028.The geosciences as a whole do not primarily profit from a single large-scale research infrastructure investment, but they see their highest scientific potential for ground-break-ing new findings in joining forces in establishing state-of-the-art RI by bringing together diverse expertise for the benefit of the entire geosciences community. Hence, the recommendation of the geoscientific community to policy makers is to establish an integrative RI to support the ne- cessary breadth of geosciences in their endeavor to ad-dress the Earth system across the breadth of both temporal and spatial scales. It is also imperative to include suffi-cient and adequately qualified personnel in all large RIs. This is best achieved by fostering centers of excellence in atmospheric, environmental, surface processes, and deep Earth projects, under the roof of the 'Integrated Swiss Geosciences'. This will provide support to Swiss geo-sciences to maintain their long standing and internatio- nally well-recognized tradition of observation, monitor-ing, modelling and understanding of geosciences process-es in mountainous environments such as the Alps and beyond