GI_Forum 2019, Volume 7, Issue 1

Under scenarios of urbanization coupled with increasing frequency and intensity of natural hazards, urban disaster risk is set to 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 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 up to 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’s residential area is likely to grow by 127 ha to an overall size of 1,690 ha by 2030, corresponding to an increase of 8.1% 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 to flash floods in the case study area.

Schlagworte: urban growth, Urbanization, SLEUTH, future projection, exposure

In this paper, we demonstrate environmental monitoring in a young citizen science project. The dynamics of urban tree phenology and microclimate regulation throughout the growing season is measured in a cross-city approach, along intra- and inter-urban gradients and for a set of the most common urban tree species. We equipped urban trees in five European cities 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 trees' microclimate-regulating ecosystem services. The approach and setting are scalable to other citizen-engagement and VGI projects. It fosters an understanding of how urban trees are in sync with urban climate, and deepens our understanding of systemic feedback, which is key for implementing urban tree management. Results show inter-species differences in the length of the growing season as measures of the delivery of regulatory ecosystem services and as responses to urban heat island intensity.

Schlagworte: microclimate monitoring, app, beacons, regulating ecosystem services, phenology

Designing user-friendly Public Participatory Geographic Information Systems (PPGIS) is a challenging task, since a PPGIS is typically used by users who have different characteristics and 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). Considerable usability problems were faced especially by participants with low levels of IT-literacy. 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.

Schlagworte: mobile PPGIS, usability, multi-national study, eye-tracking

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.

Schlagworte: transdisciplinarity, domain-specific language, question-based analysis, language for spatial computing, core concepts

Movement data analysis is a high-interest topic in many scientific domains. Even though Python is the scripting language of choice in the GIS world, currently there is no Python library that would enable researchers and practitioners to interact with and analyse 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 Simple Feature-based movement data models commonly used to handle trajectories in the GIS world. Finally, we present the current state of the MovingPandas implementation and demonstrate its use in stand-alone Python scripts, as well as within the context of the desktop GIS application QGIS. This work represents the first step towards a general-purpose Python library that enables researchers and practitioners in the GIS field and beyond to handle and analyse movement data more efficiently

Schlagworte: trajectory, spatio-temporal analysis, python, movement data analysis

This article focuses on a cluster-based parallel and distributed approach for large raster datasets in the context of Spatial Multicriteria Decision Analysis (S-MCDA). The research addresses a land-prioritization model with respect to conservation practices. The reliability of the model results is examined using a variance-based Spatially-Explicit Uncertainty and Sensitivity (SEUSA) framework. The original case study area to which we applied the model was located in southwest Michigan, USA, and incorporated millions of mapping units (pixels). As part of the model sensitivity analysis, several thousand intermediate raster datasets representing suitability surfaces are generated by means of a Monte Carlo Simulation (MCS). 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 the low quality of the model sensitivity measures. This article presents the concept and implementation of a distributed and parallel solution based on the Python-Dask framework in order to improve the quality of SEUSA results for computationally-intensive spatial models.

Schlagworte: parallel and distributed computing, Python Dask framework, Monte Carlo Simulation, spatially-explicit uncertainty and sensitivity analysis, spatial multi-criteria decision analysis

Using fishery-dependent observer data from National Marine Fisheries (NMFS) provides insight into the location and intensity of bottom-trawl fishing effort, and allows those areas most exposed to fishing pressure to be identified. 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 is explored within a space-time cube in ArcGIS Pro. The variables analysed were number of hauls per area and total catch per area. Statistical techniques were used to examine spatiotemporal clustering within the data. Results indicate that fishing was significantly clustered over space and time. A three-dimensional hotspot analysis shows which areas were most intensely fished and illustrates the trends over the relatively long 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 the spatial patterns of fishing effort, but certain areas in the Bering Sea exhibited increased fishing effort in years with less sea ice.

Schlagworte: spatiotemporal analysis, marine fisheries, hotspot analysis

The revised Swiss Spatial Planning Act (RPG 2016) pursues the goal of inward settlement development to slow down urban sprawl and better protect arable land. This needs to be addressed in planning processes, as quality-oriented and sustainable internal densification is required. The Geodesign Framework by Steinitz is suitable for supporting such planning processes with public participation, where models and visualizations help to convey the complex systemic interrelationships to stakeholders. This paper presents a process model based on Geodesign that integrates GIS and Parametric Design, so that effects on internal densification caused by changes to building regulations can be quantified and communicated. In addition to an overview of the process model, selected results from its tests and verification are presented. The results suggest that the model approximates real interrelations well and is a suitable basis for further work.

Schlagworte: spatial simulation, test planning, parametric design, geodesign, spatial planning

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 in 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.

Schlagworte: city models, generative adversarial networks, LoD1, segmentation

Social media services generate enormous amounts of spatiotemporal data that can be used to characterize and analyse user activities and social behaviour. 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 analyses 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.

Schlagworte: Social Media, spatiotemporal data, Flickr, Twitter, Snapchat, spatial analysis

The South Bronx neighbourhood 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, 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 the local knowledge of Nos Quedamos, we propose a critical approach to GIS and official data. The results of this study will help Nos Quedamos and local stakeholders in decision-making, support political efforts and negotiations with local authorities in the establishment of a Community Land Trust, enhance housing affordability, and consolidate community-managed open spaces in the South Bronx. Furthermore, the methodology presented here could serve as a guide for other local organizations seeking to establish similar land trusts in their localities, especially in urban settings with a high demand for land acquisition.

Schlagworte: land policy, housing affordability, community land trust, community organizations, critical GIS

Map-based discussion forums can be used for crowdsourcing people’s ideas and opinions with respect to public planning processes. Their volunteered geographic information consists of text and other media that are linked to geographic features. Building on the concept of argumentation mapping, 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 cycle 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.

Schlagworte: argumentation mapping, public participation GIS, campus sustainability, community gardens, cycling infrastructure, volunteered geographic information