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Nur Sitzungen am Veranstaltungsort 
Ort: B - Blauer Hörsaal
Datum: Mittwoch, 03.07.2019
13:00 - 14:30B14: GI_Forum Special Session: Food - Local and Global Challenges
Chair der Sitzung: Sabine Hennig
B - Blauer Hörsaal 

Associations of Body Mass Index with Food Environments, Physical Activity and Smoking

Pablo Francisco Cabrera-Barona1, Myriam Paredes2, Donald Cole3

1Instituto de Altos Estudios Nacionales, Universidad San Francisco de Quito; 2Facultad Latinoamericana de Ciencias Sociales; 3University of Toronto

This paper identifies spatial patterns of body mass index (BMI) and obesity in the Metropolitan District of Quito, Ecuador, by applying spatial autocorrelation. We identified BMI hotspots in western rural parishes, and hotspots of obesity in northern urban parishes . We then explored associations between distances to food outlets, physical activity and smoking (independent variables), and BMI and obesity (BMI > 30) (dependent variables) by applying global regressions (GR) and geographical weighted regressions (GWR). Smoking was found to be significantly negatively associated with BMI and obesity. Distance to supermarkets was found to be negatively associated with obesity.

Sustainability objectives of non-profit sharing economy activities: assessing achievement. A case study of the food-sharing project Mundraub

Sabine Hennig

University of Salzburg, Österreich

The rapid advance of Information and Communication Technologies has triggered a boom in online sharing activities. Meanwhile, sharing economy activities cover many sectors including the food sector. Particularly, regarding food sharing the idea of sustainability, participation, social interaction, and change of behavior play a pivotal role. An example therefore is the Mundraub project which aims at enabling the general public to share information on wild and forgotten fruit and nut trees, berry shrubs, and herbaceous plants located in public space (i.e. urban environment in Germany) and, thus, have others harvest them. Even though the literature highlights many benefits related to the Mundraub project, the question is to what degree the existing potential is actually used. To answer this question data (e.g. mapped plants) accessed from the Mundraub database were analyzed. The results reveal several hotspots and clusters across Germany with a high number of mapped plants, but there are also many areas where only few data are available. To leverage the potential of the Mundraub project, measures related to project publicity, founding of local activity groups and attracting the interest of societal groups which have not been reached by the project so far can be seen as promising.

15:00 - 16:30B15: GI_Forum Special Session: Urban Geoinformatics
Chair der Sitzung: Bernd Resch
B - Blauer Hörsaal 

Comparing the Spatial and Temporal Activity Patterns between Snapchat, Twitter and Flickr in Florida

Levente Juhász1, Hartwig Hochmair2

1Florida International University, United States of America; 2University of Florida, United States of America

Social media services generate enormous amounts of spatiotemporal data that can be used to characterize and analyze user activities and social behavior. Although crowd-sourced data have the advantage of comprehensive spatial and temporal coverage compared to data collected in more traditional ways, the various social media platforms target different user groups, which leads to user selection bias. Since data from social media platforms are used for a variety of geospatial applications, understanding such differences and their implications for analysis results is important for geoscientists. Therefore, this research analyzes differences in spatial and temporal contribution patterns to three online platforms, namely Flickr, Twitter and Snapchat, over a six-week period in Florida. For the comparison of spatial contribution patterns, a set of negative binomial regression models are estimated to identify which socio-economic factors and characteristics of the built and natural environments are associated with contribution activities. The contribution differences observed are discussed in light of the targeted user groups and different purposes of the three platforms.

Mapping for Community-Driven Neighborhood Planning: The Case of the South Bronx Land and Community Resource Trust

Monica Flores Castillo, Stephan Petryczka, Joyce Choi-Li, Karlo Ludwig, Yixin Li

Observatorio de Ciudades UC, Pontificia Universidad Católica de Chile, NYU Wagner School of Public Service

The South Bronx neighborhood in New York City has historically been oppressed and left behind by urban planning policies that deliberately created social exclusion in the area. We Stay/Nos Quedamos, a community development organization located in the area, is actively seeking to establish a Community Land Trust (CLT), a mechanism designed to provide homeownership affordability to low-income households.

This study seeks to identify potential sites suitable for acquisition and for establishing a Community Land Trust in the South Bronx area. Analysis is performed using Geographic Information Systems in combination with official New York City data. Moreover, by leveraging NQ’s local knowledge, we propose a critical approach to GIS and official data.

The results of this study will help NQ and local stakeholders in decision-making, support political efforts and negotiations with local authorities in the establishment of a CLT, enhance housing affordability, and consolidate community-managed open spaces in the South Bronx. Furthermore, the methodology presented here will serve as a guide for other local organizations seeking to establish CLTs in their localities, especially in urban settings with a high demand for land acquisition.

Cartoforum – A Map-Based Discussion Forum with Applications in the Planning of Bike Lanes, Community Food Gardens, and Campus Sustainability

Justin Pierre1, Victoria Fast2, Jyothi Kumari3, Claus Rinner1

1Department of Geography and Environmental Studies, Ryerson University; 2Department of Geography, University of Calgary; 3Department of Geology, University of Kerala

Map-based discussion forums are tools for crowdsourcing of people’s ideas and opinions with respect to public planning processes. This information consists of text and other media that are linked to geographic features. Building on the concepts of argumentation mapping, a new tool, Cartoforum, was developed using the Boundless geostack, an open-source geospatial software package. We present the software architecture and functionality along with three pilot studies covering bike lane planning in Toronto, Canada; community garden site selection in the Toronto region; and campus sustainability at the University of Kerala, India. Together, the pilot studies demonstrate the utility of argumentation mapping and illustrate the range of its potential applications in citizen participation.

17:00 - 18:30B16: Citizen Science and PAIS
Chair der Sitzung: Laxmi Ramasubramanian
B - Blauer Hörsaal 

Urban Trees in Sync with Urban Climate – A Monitoring and Geocommunication Setting for Citizen Science

Carola Helletsgruber1, Celina Stanley2, Angela Hof1

1University Salzburg, Austria; 2IOER, Germany

Urban trees are equipped with beacons that connect via Bluetooth to a tailor-made app. The app is used for phenological monitoring, to display microclimate measurements and to broadcast information on the tree's regulating ecosystem services. We demonstrate an exemplary application of environmental monitoring in a young citizen science project. This approach and setting is scalable to other citizen engagement and VGI projects. The study design, and consequently, the results, fosters 1) an understanding how urban trees are in sync with the urban climate, and 2) deepens our understanding of systemic feedbacks which is key for implementing this understanding in urban tree management. Results show inter-species differences in the length of the growing season as a measure of the delivery of regulatory and cultural ecosystem services and as a response to urban heat island intensity.

Beyond 3D Building Modeling: A Citizen Science of 3D Cultural City Mapping.

Szymon Chmielewski1, Cait Bailey2, Adam Gawryluk1

1University of Life Sciences in Lublin (Poland); 2MDI Biological Laboratory (Maine, USA)

The general goal of a smart city is to increase citizens’ well-being through sustainable development. Three-dimensional city modeling plays an increasingly important role in advancing this goal. According to Austrian architect, Christopher Alexander, city models can be considered to be composed of two parts, negative (building) and positive (open outdoor) spaces. Open outdoor spaces can have a significant impact on citizens’ well-being, but current 3D city models leave outdoor spaces almost empty, apart from the shapes of buildings, despite their key importance in cultural mapping. To close this gap, we propose a citizen science mapping project to improve the quality of existing 3D city models by crowdsourcing 3D imagery of public spaces and visual art artefacts.

Citizen Participation via Digital Maps: A Comparison of Current Applications

Sven Schmuderer1,2, Roland Zink2, Werner Gamerith1

1Universität Passau, Deutschland; 2Technische Hochschule Deggendorf, Deutschland

The effects of digitization on social coexistence have been a subject of controversy not only since the increased use of social media for political campaigns. But digital platforms are also being developed which, from the perspective of spatial planning and geography, enhance communication between administrations and citizens at the local, municipal level. These applications are being developed in relation to three areas: (1) the everyday experiences and competences of citizens in dealing with geomedia, especially using smartphones; (2) the individual process design for a particular participatory case; (3) the desired societal or local political benefit. This paper deals with these three aspects and discusses five selected examples of how digital participation platforms can be designed to include the use of geomedia. Based on experiences with the proprietary development of the web application PUBinPLAN in particular and on its comparison with other platforms, insights can be derived with regard to success factors as well as to opportunities and risks.

A Multi-National Human–Computer Interaction Evaluation of the Public Participatory GIS GeoCitizen

Mona Bartling1, Bernd Resch1, Anton Eitzinger2, Leo Zurita-Arthos3

1University of Salzburg, Austria; 2International Center for Tropical Agriculture (CIAT); 3GEOcentro, Universidad San Francisco de Quito (USFQ)

Designing user-friendly Public Participatory Geographic Information Systems (PPGIS) is a challenging task, since a PPGIS is typically used by users of different characteristics and having different requirements and needs. Hence, applying Human–Computer Interaction (HCI) principles is of particular importance in designing PPGIS. This study aims to create an inventory of usability aspects of a PPGIS by focusing on understanding the characteristics of a broad range of users. The usability study included 73 participants from Colombia, Uganda and Austria. We combined a custom qualitative survey (conducted in all three countries) with an eye-tracking based survey (conducted only in Austria). Especially participants with low levels of IT-literacy faced considerable usability problems. This was mostly due to a lack of experience in using functionally complex smartphone applications or interactive maps. In general, we observed a high level of difference in usability between the user groups. The eye-tracking statistics for the Austrian study supported the outcomes of the qualitative survey well.

Datum: Donnerstag, 04.07.2019
9:00 - 10:30B17: The digitally enabled Grid
Chair der Sitzung: Antonia Dückelmann
B - Blauer Hörsaal 

Smallworld Evolution - von der Karte zum digitalen Versorgungsunternehmen

Mark Held1, Marco Bradtke2

1GRINTEC GmbH; 2GE Power Grid Solutions

Vortrag beschäftigt mit den wesentlichen Funktionen und Vorteile eines Netzinformationssystem (NIS) anhand von Ausführungen des Smallword GIS.

Smallworld Evolution - Praxisanwendungen digitaler Versorgungsunternehmen

Mark Held

GRINTEC GmbH, Österreich

Vortrag beschäftigt sich mit Praxisanwendgen bzw. Praxisumsetzungen verschiedener Versorgungsunternehmen welche Smallworld GIS im Einsatz haben.

Spatial Warehouse - ETL Prozess und Historisierung als Grundlage für Analysen und Reports

Marco Bradtke

GE, Deutschland

Der Vortrag beschäftigt sich mit der Aufbereitung von Geodaten für verschiedene Business Prozesse und der Historisierung von Geodaten in einem Warehouse.

15 Jahre Leitungsauskunft in Österreich - ein Blick in Vergangenheit und Zukunft

Daniel Gander

GRINTEC GmbH, Österreich

Vortrag beschäftigt sich mit Thema Leitungsauskunft in Österreich. GRINTEC möchte mit 15 Jahre Erfahrungen vergangene Entwicklung dieses Themas präsentieren und einen Blick in Zukunft werfen.

11:30 - 13:00B18: Joint GI_Forum and EARSeL UAS Summit I
Chair der Sitzung: Alexander Almer
B - Blauer Hörsaal 

UAV-based Tree Height Estimation in Dense Tropical Rainforests Areas in Ecuador and Brazil

Stefan Reder, Lilli Waßermann, Jan-Peter Mund

HNE Eberswalde, Deutschland

The aim of this study was to develop an easy applicable, cost-efficient workflow for tree height estimation in remote, inaccessible rainforest areas in Ecuador and Brazil. Structure from Motion was combined with a digital terrain model (DTM) from the Shuttle Radar Topography Mission (SRTM) to complement relief information to the photogrammetric point clouds (PPC) that represents the upper canopy layers. Based on by ground points extracted form a generated 3D model, a vertical shift of the model was applied to adjust the ellipsoid level of the PPT. Digital surface models (DSM) of 22 research plots (75m x 75m) were normalized to canopy height (CHM) to allow the estimation of relative tree heights in all research plots without using ground control points (GCP). The calculated tree height values indicate the applicability of the proposed workflow even in dense tropical forest canopies. This approach allows the classification of canopy structures for identifying forest succession and for other ecological forest monitoring purposes. Our results emphasize the potential of 3D models for tree height estimation derived from PPTs based on UAVs imagery in rainforests research.

Aerial and Terrestrial Photogrammetric Point Cloud Fusion for Intensive Forest Monitoring

Stuart Krause1,2,3

1Thünen Institute of Forest Ecosystems; 2Faculty of Forest and Environment, Eberswalde University of Sustainable Development; 3Department of Geography, University of Bonn

Remote sensing methods for forest monitoring are rapidly evolving due to recent advancements in UAVs and photogrammetry. Photogrammetric point clouds provide the possibility to achieve the non-destructive derivation of individual tree parameters at a low cost. The fusion of aerial and terrestrial photogrammetry for creating full tree point clouds is of utility for forest research, as tree volume can be assessed more economically and efficiently than traditional methods. This however is a challenge to implement due to difficulties with co-registration and issues of occlusion. This study explores the possibility to use spherical targets typically used for Terrestrial Laser Scanning in order to accomplish the co-registration of UAV-based and terrestrial photogrammetric datasets. Results show a full tree point cloud derived from UAV oblique imagery with terrestrial imagery. Despite issues of noise produced from the sky in terrestrial imagery, the study shows a promising methodology for aerial and terrestrial point cloud fusion.

14:00 - 15:30B19: Spatial Computing
Chair der Sitzung: Jochen Albrecht
B - Blauer Hörsaal 

Replication of the Question-based Spatial Computing Approach – Experiences and Suggestions for Further Developments

Selina Studer, Barbara Hofer

Interfaculty Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria

Geographic Information Systems (GIS) have developed into complex toolboxes and require analysts to formulate spatial questions according to the requirements of the data formats and tools provided by their specific GIS-application. The recently proposed language for spatial computing aims to provide a question-based and thus more comprehensible approach for spatial analyses that especially supports scientists and experts from other disciplines to conduct spatial analyses in their fields. In this contribution, we apply the question-based spatial computing approach to a case study in the humanitarian field and compare the resulting script to one written using a conventional GIS tool. The comparison of the two versions of the script is based on six criteria covering qualitative and quantitative aspects of the analysis. We also discuss the implementation concept behind the new language. Our results show that the new approach requires fewer computational steps than the conventional script. In addition, the declarative approach allows users to focus on the content of the spatial question, and the query-like character of the language makes it easier to understand for non-GIS specialists. In addition, we share observations on challenges of the further development of the language as an outcome of this study.

MovingPandas: Efficient Structures for Movement Data in Python

Anita Graser

AIT Austrian Institute of Technology, Österreich

Movement data analysis is a high-interest topic in many different scientific domains. Even though Python is the scripting language of choice in the GIS world, there is no Python library available so far that would enable researchers and practitioners to interact with and analyze movement data efficiently. To close this gap, we present MovingPandas, a new Python library for dealing with movement data. Its development is based on an analysis of state-of-the-art conceptual frameworks and existing implementations (in PostGIS, Hermes, and the R package trajectories). We describe how MovingPandas avoids limitations of SimpleFeature based movement data models commonly used in the GIS world and demonstrate its use.

Parallel and Distributed Computing for Large-Size Spatial Multicriteria Decision Analysis Problems: A Computational Performance Comparison.

Christoph Erlacher1,2, Angelika Desch1, Karl-Heinrich Anders1, Piotr Jankowski3, Gernot Paulus1

1Carinthia University of Applied Sciences, Department of Geoinformation and Environmental Technologies, Villach 9524, Austria; 2University of Salzburg, Department of Geoinformatics, Salzburg 5020, Austria; 3San Diego State University, Department of Geography

The article focuses on a cluster-based parallel and distributed approach for large raster datasets in the context of Spatial Multicriteria Decision Analysis (S-MCDA). Specifically, the research reported herein addresses a land prioritization model in respect to conservation practices and includes the top-level indicators “Wildlife”, “Water-Quality”, “Soil-Erosion”, “Enduring-Benefits” and “Air-Quality”. The reliability of model results is examined with a variance-based Spatially-Explicit Uncertainty and Sensitivity (SEUSA) framework. The case study employing the model is located in Southwest Michigan, USA and incorporates millions of mapping units (pixels). As part of model sensitivity analysis, several thousand intermediate raster datasets representing suitability surfaces are generated by means of a Monte Carlo Simulation (MCS), which is an integral part of the SEUSA framework. The creation of the suitability surfaces represents the most time-consuming and memory-intensive step within the SEUSA framework. Sequential computational approaches to implementing SEUSA often have to accept a compromise with respect to problem size and the number of simulations, resulting in low quality of model sensitivity measures. This article presents the concept and implementation of a distributed and parallel Python-Dask solution in order to improve the quality of SEUSA results for computationally intensive spatial models.

16:30 - 18:00B20: UNIGIS International Award Winner's Session
Chair der Sitzung: Gudrun Wallentin
B - Blauer Hörsaal 

UNIGIS – studying geoinformatics online

Gudrun Wallentin

University of Salzburg, Österreich

An overview about how UNIGIS offers distance-learning degree programs in geoinformatics around the world.

Trends in the Alaskan Bottom-Trawl Fishery from 1993-2015: A GIS-based Spatiotemporal Analysis

Carrie Elizabeth Steves

University of Southern California, United States of America

Using fishery-dependent observer data from National Marine Fisheries (NMFS) provides insight on the location and the intensity of bottom-trawl fishing effort, which can identify areas most exposed to fishing pressure. In this study, the spatial and temporal extent of Alaskan bottom-trawl fishing effort in the Bering Sea, Aleutian Islands, and Gulf of Alaska between 1993 and 2015 was explored within a space-time cube in ArcGIS Pro v1.4.1. The variables analyzed were number of hauls per area and total catch per area. Statistical techniques were used to examine spatiotemporal clustering in these data. Results indicate that fishing effort was non-randomly clustered over space and time (Moran’s I). A three-dimensional hot spot analysis shows which areas were most intensely fished and illustrates the long-term trends over the study period. The data were then compared with sea ice concentration to determine the effect of changing climate on fishing activity. Sea Ice had a limited effect on fishing effort spatial patterns, but certain areas in the Bering Sea exhibited increased fishing effort in years with less sea ice effect.

Automated Map Projection Selection for GIS

Paul Gosling

UNIGIS, United Kingdom

The selection of an appropriate map projection is a fundamental concern for cartographers and GIS users as the choice impacts the visualisation and analysis of geographic information. It is impossible to transform the curved surface of the Earth onto a two-dimensional plane without introducing distortion, and the number of available projections complicates the decision-making process. Selection of a suitable projection requires simultaneous consideration of several different factors such as the planned map purpose and the size, shape and location of the geographical area of interest, with the goal of assessing the projection distortion characteristics and parameters which best meet those criteria. There are cognitive difficulties in recognising and accounting for projection distortion, even for those with experience of the subject, so map projection selection continues to be a complicated and confusing process for many cartographers and GIS users.

Assessing Shrub and Tree Encroachment in Alpine Pastures from Airborne Laser Scanning Data

Christoph Giger

landplan AG, Schweiz

The forest area in alpine region is increasing. Agricultural land is abandoned – shrub and tree encroachment and reforestation are the consequences with negative impact on agriculture, biodiversity and tourism.

Assessing encroachment on agricultural land from Airborne Laser Scanning (ALS) data was tested in three study areas in Switzerland. The results of the data evaluation were compared with those for manually collected data from the interpretation of orthophotos. The evaluation indicated when a higher point density was available, the detection rate for areas with shrub and tree encroachment was also higher. The workflow using the Vertical Complexity Index (VCI) turned out to be robust for both large areas and large datasets. The accuracy levels achieved in this study for the encroachment index may provide a solid basis for prioritizing certain areas for projects that aim to limit the process of reforestation.

Datum: Freitag, 05.07.2019
9:00 - 10:30B21: GI in Urban Contexts
Chair der Sitzung: Angela Hof
B - Blauer Hörsaal 

Parametric (Geo)Design for Test Planning

Christoph Schaller

Berner Fachhochschule, Schweiz

The revised Swiss Spatial Planning Act pursues inward settlement development to slow down urban sprawl and protect arable land. This requires quality-oriented and sustainable internal densification. The Geodesign Framework by Steinitz can support planning processes with public participation, where models and visualizations help to convey complex interrelationships to stakeholders. This paper presents a Geodesign based process model integrating GIS and Parametric Design, that allows to quantify and communicate effects on internal densification caused by changes to building regulations. An overview of the model and the most important results from its verification are presented. They indicate that the model approximates real interrelations well and is a suitable basis for further work.

A 3D Spatial Data Framework for Urban Land and Property Management

Abbas Rajabifard, Jihye Shin, Behnam Atazadeh, Mohsen Kalantari.

The Centre for Spatial Data Infrastructures and Land Administration, Department of Infrastructure Engineering, The University of Melbourne

Over the last years, the unprecedented urbanization has fostered the rapid development of multi-story buildings and infrastructure facilities, resulting in spatial and functional complexities in cities. Land and property information plays an important role in a wide range of applications in land administration and management in rapidly growing cities. However, the current fragmented practice relied on 2D-based representation does not provide a reliable and accurate legal description of underground and aboveground properties as a foundation of making evidence-based decisions in support of economic prosperity, human activities and the public safety in urban areas. In this paper, the conceptual framework for 3D digital management of urban land and property information is proposed. The suggested framework comprises creating 3D models of urban land and property, validating the integrity of the models, integrating legal and physical information in the various 3D models, and analyzing the federated 3D model with the query. This approach will contribute to integrating silos of urban land and property information which can not only be utilized to manage the complex urban built environment and but also have the potential to reduce costs associated with data duplication.

Automatic Generation of LoD1 City Models and Building Segmentation from Single Aerial Orthographic Images using Conditional Generative Adversarial Networks

Lukas Beer

TU-Berlin, Deutschland

3D city models play an important role in multiple applications, but creating them still requires effort using various possible techniques. This paper proposes a new machine-learning-based framework for generating 3D city models. With the help of conditional Generative Adversarial Networks and single orthographic images, segmentation and height estimations of buildings are achieved. The height information per pixel and the building coordinates were generalized using a histogram for heights and the Douglas-Peucker algorithm. The framework was evaluated by using variations of the same dataset (for the city of Berlin) to show possible differences due to changes of the image size and representation of the heights. The evaluation reveals that it is possible to generate block models with a mean absolute height error of 5.53m per building, a mean absolute height error for the whole raster of 1.32m, and a Jaccard Index of 0.55 for the segmentation. While the proposed framework for generating LoD1 city models does not attain the accuracy of previous techniques, our work represents a step towards successfully using machine learning for the automatic generation of city models and building segmentation.

Creation of Nominal Asset Value-Based Map with GIS: Case Study of Istanbul Beyoğlu and Gaziosmanpaşa Districts

Muhammed Oguzhan Mete, Tahsin Yomralioglu

Istanbul Technical University, Turkey

The approach used in estimating the value of real estate has applications in fields as diverse as taxation, buying and renting properties, expropriation and urban regeneration. Determining the most objective, accurate and acceptable value for real estate by considering spatial criteria is important. One stochastic method used to determine real estate values is “nominal valuation”. In this approach, criteria that may affect land value are subjected to various spatial analyses and pixel-based value maps can be produced using GIS. Land value maps are in raster data format and need to be compared with the actual market values. Pixel-resolution analyses are required that depend on the selected grid dimensions. First of all, nominal value maps were produced using a nominal valuation model, using criteria for proximity, visibility and terrain. These were weighted in order to produce a nominal asset value-based map according to the “Best Worst Method”. Changes in the unit land values were examined for maps at various resolutions; a resolution of 10 meters emerged as the ideal pixel size for valuation maps.

11:00 - 12:30B22: Digital Humanities & Location
Chair der Sitzung: Robert Vogler
B - Blauer Hörsaal 

Simulating Future Urban Expansion in Monastir, Tunisia, as an Input for the Development of Future Flash Flood Risk Scenarios

Mostapha Harb1, Michael Hagenlocher1, Davide Cotti1, Elke Kratzschmar2, Hayet Baccouche2, Karem Ben Khaled2, Felicitas Bellert2, Bouraoui Chebil3, Anis Ben Fredj3, Sonia Ayed3, Matthias Garschagen1,4

1United Nations University Institute for Environment and Human Security (UNU-EHS), Germany; 2Industrieanlagen-Betriebsgesellschaft mbH (IABG mbH); 3Municipality of Monastir; 4Ludwig-Maximilians-Universität München (LMU), Department of Geography

As a result of urbanization coupled with an increasing frequency and intensity of natural hazards, urban disaster risk is on the rise. Simulating future urban expansion can provide relevant information for the development of future exposure scenarios and the identification of targeted risk reduction and adaptation strategies. Here, we present an application of an urban growth simulation for the coastal city of Monastir, Tunisia. The approach integrates local knowledge and a data-driven urban growth model to simulate urban sprawl until 2030. A business-as-usual projection is used to predict the future growth of the city based on the historical trend. Thirteen Landsat images for the period 1975 to 2017 were used to delineate past changes in urban land cover following the European Urban Atlas standard, which served as the main input for the urban growth model. The simulation revealed that the city is likely to grow by additional 127 hectares to an overall size of 1,690 hectares of residential area by 2030, corresponding to 8.1 % growth compared to the urban footprint of 2017. The outcomes of the analysis presented here served as an input for the spatial simulation of future exposure and flash floods risk scenarios in the case study area.

Linguistic Landscaping at School - a Teaching Design

Manuel Huyer

Universität Salzburg, Österreich

Im Rahmen meiner Bachelorarbeit in Geographie bei Dr. Thomas Jekel ist aus einer Idee eine Fächerübergreifende Arbeit aus Geographie und Deutsch entstanden, in der es um Linguistic Landscaping - eine linguistische Methode zur Untersuchung visuell wahrnehmbarer Sprache - und deren Anwendung in der Schule geht. Die Methode soll didaktisiert und für den Schulunterricht verwendbar gemacht werden, um etwas neues auszuprobieren. Die Verknüpfung von Sprache und Raum bietet dabei einen hervorragenden Berührpunkt der beiden Fächer.

Beim Workshop 'Digital Humanities @ Schule 4.0. Co-Creation einer Strategie zur Digitalisierungsinitiative beyond MINDT' im Zuge der 'Digital Humanities Austria 2018' Konferenz wurde die Idee bereits unter FachdidaktikerInnen und VertreterInnen der digital humanities diskutiert, dazu gab es theoretische Inputs, welche in die Arbeit eingeflossen sind.

Für das GI-Forum reiche ich nun eine verknappte Version als short-paper ein.

Uncertain spaces, uncertain places – dealing with geographic information in Digital Humanities on the example of a language legacy data set

Amelie Dorn, Renato Souza, Barbara Piringer, Eveline Wandl-Vogt

Austrian Academy of Sciences, Österreich

Apart from linguistic content, legacy language collections often also contain other aspects of information such as geographical and spatial details, e.g. locations, regions, municipalities, etc. Such information may offer valuable insights into the linguistic landscape, but it may also pose challenges in the case of uncertain aspects. This paper outlines and discusses different known and unknown uncertainties of spatial aspects contained in a non-standard German language legacy dataset (DBÖ), that has undergone several stages of data conversion since the early nineties. The authors introduce and discuss their taxonomy of uncertainties exemplified on a specifically devised taxonomy of spatial information for this one hundred year old project cluster. Finally, it is discussed how the contained uncertainties affect Digital Humanities practice.


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