Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
 
Session Overview
Session
3B - Spatial Analysis
Time:
Tuesday, 06/July/2021:
8:45am - 10:15am

Session Chair: Inger Fabris-Rotelli
Zoom Host: Tuli Amutenya
Replacement Zoom Host: Rachel Heyard
Location: The Lounge #talk_spatial_analysis
Session Topics:
Spatial analysis


Presentations
8:45am - 9:05am
Talk-Video
ID: 192 / ses-03-B: 1
Regular Talk
Topics: Spatial analysis
Keywords: spatial-analysis, graph-analysis, simple-features, tidygraph, spatial-networks

Tidy Geospatial Networks in R

Lucas van der Meer1, Lorena Abad1, Andrea Gilardi2, Robin Lovelace3

1University of Salzburg, Austria; 2University of Milano - Bicocca, Italy; 3University of Leeds, England

Geospatial networks are graphs embedded in geographical space. That means that both the nodes and edges in the graph can be represented as geographic features: the nodes most commonly as points, and the edges as linestrings. They play an important role in many different domains, ranging from transportation planning and logistics to ecology and epidemiology. The structure and characteristics of geospatial networks go beyond standard graph topology, and therefore it is crucial to explicitly take space into account when analyzing them. The sfnetworks R package is created to facilitate such an integrated workflow. It brings together the sf package for spatial data science and the tidygraph package for standard graph analysis. The core of the package is a data structure that can be provided as input to both the graph analytical functions of tidygraph as well as the spatial analytical functions of sf, without the need for conversion. Additionally, it offers a set of geospatial network specific functions, such as routines for shortest path calculation, network cleaning and topology modification. The package is designed as a general-purpose package suitable for usage across different application domains, and can be seamlessly integrated in "tidy" workflows that use the tidyverse packages for data science.



9:05am - 9:25am
Talk-Live
ID: 290 / ses-03-B: 2
Regular Talk
Topics: Spatial analysis
Keywords: slopes, gradient

slopes: a package for calculated slopes of roads, rivers and other linear (simple) features

Robin Lovelace1, Rosa Félix2

1University of Leeds, United Kingdom; 2University of Lisbon, Portugal

The goal of the slopes is to enable reproducible calculation of slopes for urban, transport, ecological applications and research projects using free and open source software. We have developed the package to be fast, accurate and user friendly, calculating the longitudinal steepness of linear features such as roads and rivers based on open access datasets such as road geometries and digital elevation models (DEMs). The package has a few unique features, including the ability to calculate slopes based on multiple input classes for raster data, and the ability to download and use DEM data on-the-fly in places where users lack DEM data. The package is work in progress but has already attracted attention from road steepness maps of cities in Portugal and Brazil. Integrating with other packages such as sf and sfnetworks, the package should provide a strong foundation for research into the impacts of vertical gradient profiles on phenomena ranging from aquatic migration patterns to flooding and walking and cycling potential. In the talk we will present both the package and some of the research questions we have used it to explore and will ask the audience: how steep a hill would you be willing to walk or cycle up? We will conclude by discussing limitations of the package and future directions of development.

Link to package or code repository.
https://github.com/ITSLeeds/slopes


9:25am - 9:45am
Talk-Live
ID: 142 / ses-03-B: 3
Regular Talk
Topics: Spatial analysis
Keywords: cartography, maps, spatial analysis

mapsf, a New Package for Thematic Mapping

Timothée Giraud

UMS RIATE - CNRS

{mapsf} helps to design various cartographic representations such as proportional symbols, choropleth or typology maps. It also offers several functions to display layout elements that improve the graphic presentation of maps.

The aim of {mapsf} is to obtain thematic maps with the visual quality of those built with a classical mapping or GIS software while being lightweight, versatile and user-friendly. To achieve this goal, the package takes advantage of the features offered by {sf} and provides a limited number of simple mapping functions.

{mapsf} is the successor of {cartography}, it offers the same core features but it is simpler and more robust. Unlike other popular cartographic packages, it does not use grammar of graphics, it depends on a limited number of packages and displays georeferenced plots using base R graphics.

The main function of the package, mf_map(), gives access to 9 map types: base maps, proportional or graduated symbols, choropleth maps, typology maps and various combinations of symbology. Many parameters are available to fine tune the cartographic representations. These parameters are the common ones found in GIS and automatic cartography tools (e.g. classification, color palettes, symbols sizes, legend layout...).

Some additional functions are dedicated to layout design (graphic themes, legends, scale bar, north arrow, title, credits…), map insets or map exports.

The development of {mapsf} follows the current best practices of the R ecosystem (CI/CD, coverage tests) and its documentation is enhanced by a vignette and a website.



9:45am - 10:05am
Talk-Video
ID: 141 / ses-03-B: 4
Regular Talk
Topics: Spatial analysis
Keywords: data management

osmextract: An R package to download, convert, and import large OpenStreetMap datasets

Andrea Gilardi1, Robin Lovelace2

1University of Milano - Bicocca; 2University of Leeds

OpenStreetMap (OSM) is an online database that provides open-access geographic and rich attribute data worldwide, representing a wide range of physical and human features, including roads, rivers, and political boundaries. OSM is the world’s largest open-access source of geographic vector data, comprising nodes (points), ways (lines and polygons) and relations (describing a wide range of entities). Practical applications include disaster response, transport planning, and service location. OSM datasets can be manually downloaded from the project’s servers directly or via the R package osmdata, which uses the Overpass API. Large 'extracts' are also available from external providers (such as geofabrik.de) in a compressed binary format based on protocol buffers. The aim of osmextract is to enable processing and import of such OSM extracts. The package is composed of three main functions that can be used to 1) match an input location with one of the OSM extracts, either via spatial matching or approximate string distance; 2) download the chosen file; 3) convert the compressed data to Geopackage format. The main function, named oe_get(), returns sf objects. This workflow is effective for importing OSM extracts covering large geographical areas. Furthermore, the conversion process is based on GDAL routines, enabling customized spatial filters or SQL-like queries, further boosting import performance.

Link to package or code repository.
Repository: https://github.com/ropensci/osmextract; Website: https://docs.ropensci.org/osmextract/