useR! 2024: Full Schedule

In Person
8 - 11 July, 2024
Learn more and Register to Attend

The Sched app allows you to build your schedule but is not a substitute for your event registration. You must be registered for useR! 2024 to participate in the sessions. If you have not registered but would like to join us, please go to the event registration page to purchase a registration.

Please note: This schedule is automatically displayed in Central European Summer Time (UTC+02:00). To see the schedule in your preferred timezone, please select from the drop-down located at the bottom of the menu to the right.

IMPORTANT NOTE: Timing of sessions and room locations are subject to change.

The virtual program will take place on 2 July. Please see the virtual schedule page for more information.

14:10 CEST

Analyzing Real-World Geospatial Networks in R for Sustainable Transport Planning - Lucas van der Meer & Lorena Abad, University of Salzburg

Tuesday July 9, 2024 14:10 - 14:30 CEST

Salzburg I

Geospatial networks are graphs embedded in geographical space. They can be used to represent, analyze and model a variety of real-world complex systems. A motivating example is urban transport systems with their ongoing transition towards a sustainable design and increased focus on active travel. Streets, their surroundings, and their interconnections form the geospatial network. The analysis often involves an assessment of transport accessibility: how well does the network connect people to the places they want to go to? This talk will cover three main stages of such an analysis, and its implementation in R. First, we show how to import street geometries and amenity datasets from OpenStreetMap, using the packages {osmdata} and {osmextract}. Second, we show how to build a clean and routable street network from these data, using the package {sfnetworks}. Finally, we give an example of how to compute bicycle accessibility to different amenities, taking into account the suitability of the network for cycling. Although we focus on the application domain of transport planning, the content is meant to be useful for anyone interested in analyzing real-world geospatial networks in R.

Speakers

Lorena Abad

MSc., University of Salzburg

Doctoral researcher at the Department of Geoinformatics - Z_GIS of the University of Salzburg. Part of the research groups Risk, Hazard and Climate and EO Analytics. I focus on the analysis of big Earth observation data to map and monitor landscape dynamics and I am researching the... Read More →

Lucas van der Meer

Msc, University of Salzburg

Lucas van der Meer is a doctoral researcher in Geoinformatics at the University of Salzburg. He holds a bachelor in Environmental & Infrastructure Planning, and a master in Geospatial Technologies. He is particularly interested in the application of geospatial data science to address... Read More →

Tuesday July 9, 2024 14:10 - 14:30 CEST
Salzburg I

Spatial data and maps

14:30 CEST

Interfacing QGIS Spatial Processing Algorithms from R - Floris Vanderhaeghe, Research Institute for Nature and Forest (INBO) (Brussels, Belgium)

Tuesday July 9, 2024 14:30 - 14:50 CEST

Salzburg I

R is a powerful language for processing, analyzing and visualizing spatial data, with packages such as sf, terra, and stars. However, dedicated geographic information system (GIS) software tools offer thousands of specific algorithms that are either not available in R, or may be faster than equivalent R functions. This presentation describes how it is now possible to combine the strengths of R and QGIS, the most popular open source GIS platform, through R packages that interface QGIS processing algorithms: qgisprocess and qgis. These packages allow users to create data processing pipelines that combine R and QGIS algorithms seamlessly. We discuss the current state of these R packages and demonstrate the usage of their most important functions by example. We show the usage of qgis_search_algorithms(), qgis_run_algorithm(), qgis_extract_output(), coercion methods and more. We highlight recent updates in QGIS that improve functionality in R. Finally, we seek feedback from the community and invite contributions.

Speakers

Floris Vanderhaeghe

Dr. Floris Vanderhaeghe, open science methodologist at INBO, Research Institute for Nature and Forest (INBO) (Brussels, Belgium)

Floris Vanderhaeghe is a biologist specialized in scientific methodology, with a focus on spatial survey design. Together with his team mates, he promotes the implementation of open science practices at INBO. He has a special interest in geospatial computation in R and likes to collaborate... Read More →

Tuesday July 9, 2024 14:30 - 14:50 CEST
Salzburg I

Spatial data and maps

14:50 CEST

Sfislands: An R Package for Accommodating Islands and Disjoint Zones in Areal Spatial Modelling - Kevin Horan, Maynooth University

Tuesday July 9, 2024 14:50 - 15:10 CEST

Salzburg I

Fitting areal spatial models can be a cumbersome task, particularly when the geographical units are not well-behaved. The presence of islands, for example, gives rise to particular issues when creating neighbourhood structures based on contiguity. Further complications can arise from the presence of other natural barriers such as rivers and mountains, or man-made connectivities such as bridges, tunnels and ferry crossings. In order to create what a researcher considers to be an appropriate neighbourhood structure, incorporating all of the domain knowledge that they might have about the system, it should be simple and intuitive to add and remove connections between spatial units. Using examples from Indonesian earthquakes to London's river Thames, this session demonstrates a package which streamlines the human workflow involved in both the setting up of neighbourhood structures for spatial models, and the extraction of predictions from subsequent models. The package has a heavy emphasis on visualisation of both neighbourhood structures and model predictions and this will be reflected in the examples.

Speakers

Kevin Horan

PhD researcher, Maynooth University

Kevin Horan is a third-year PhD researcher in the Science Foundation Ireland Centre for Research Training in Foundations of Data Science at Maynooth University.

Tuesday July 9, 2024 14:50 - 15:10 CEST
Salzburg I

Spatial data and maps

15:10 CEST

Wavelet Secure Maps: Enhancing Privacy Protected Maps - Edwin de Jonge, Statistics Netherlands

Tuesday July 9, 2024 15:10 - 15:30 CEST

Salzburg I

We present a novel privacy protection method for spatial density maps based on wavelet MRA analysis. sdcSpatial is an R package designed to create spatial density maps, while protecting the privacy of the obervations involved. It contains several protection methods, which work well, but may create a suboptimal density map: the spatial resolutions of urban and rural areas often are very different. Wavelet Secure Maps are a novel method that use multi-resolution analysis to derive a spatial density map that adapts to the local spatial resolution. The presentation will introduce the method and its application using the upcoming update for sdcSpatial.

Speakers

Edwin de Jonge

Statistics Netherlands

Edwin de Jonge is a research and statistical consultant working at Statistics Netherlands for more than 25 years. He has a background in theoretical and computational physics. He has a long experience in methodological research, including data cleaning, visualization and network analysis... Read More →

Tuesday July 9, 2024 15:10 - 15:30 CEST
Salzburg I

Spatial data and maps

15:30 CEST

Boost Spatial Data Science Workflows with GRASS GIS and R - Veronica Andreo, Center for Geospatial Analytics. North Carolina State University.

Tuesday July 9, 2024 15:30 - 15:50 CEST

Salzburg I

GRASS GIS is a powerful geoprocessing engine that offers a robust and mature toolset for diverse applications. The core distribution brings together more than 500 tools for spatial and temporal analysis of vector, raster, 3D raster and imagery data. GRASS was developed for speed and efficiency, which allows it to scale workflows with massive datasets rather simply. At the same time, R excels at statistical analysis, modeling and data visualization. The spatial community within R has indeed grown significantly in the last decade, with the rise of packages like sf, stars, gdalcubes, terra, mapview, tmap, among many others. The beauty of open source software is that we do not need to reinvent the wheel each time. Instead, we can join forces to build bridges that connect our individual strengths. In this talk, I’ll stand over the shoulders of giants, to demonstrate how the combination of GRASS GIS and R through the rgrass package can help us integrate and streamline our spatial data engineering and data science workflows for scientific and operational applications.

Speakers

Veronica Andreo

Dr., Center for Geospatial Analytics. North Carolina State University.

Veronica Andreo holds a PhD in Biology and an MSc in Remote Sensing and GIS Applications. She is part of the GRASS Dev Team, and serves as PSC chair since 2021. She is currently working at the Center for Geospatial Analytics, in North Carolina State University (USA) within an NSF... Read More →

Tuesday July 9, 2024 15:30 - 15:50 CEST
Salzburg I

Spatial data and maps

13:30 CEST

R for Spatio-Temporal Handling of Moving Polygons - Lorena Abad, University of Salzburg

Wednesday July 10, 2024 13:30 - 15:00 CEST

TBD

Data cubes are structures to store and analyse spatio-temporal data in raster and vector format. Typical examples of spatio-temporal vector data are weather stations collecting data over time, or administrative polygons where historical data is aggregated per zone. A less explored use case for data cubes are moving polygons. Example of moving polygons would be spatial representations of glacier retreat, emergence of volcanic lava flows or the changes of a city boundary over time. In this contribution, I introduce the handling of polygons that evolve and move over time using vector data cubes. The implementation in R makes use of the packages {stars} and {cubble} as ways to represent data in array and tabular formats. The advantage of vector data cubes in both formats is the ability to apply common array operations, but also tidy data wrangling techniques to explore and analyse data. Temporal analyses can be performed using packages like {tsibble}, while spatial analyses can be performed using {sf} methods. Further, more complex spatio-temporal analyses like change detection can be performed using {stampr}. Visualization techniques using {ggplot2} and {tmap} are also explored.

Speakers

Lorena Abad

MSc., University of Salzburg

Wednesday July 10, 2024 13:30 - 15:00 CEST
TBD

Spatial data and maps, Poster Session