Package 'spDataLarge'

Title: Large datasets for spatial analysis
Description: Large datasets for spatial analysis. The data from this package could be retrived using the spData package.
Authors: Jakub Nowosad [aut, cre], Robin Lovelace [aut], Jannes Muenchow [ctb]
Maintainer: Jakub Nowosad <[email protected]>
License: CC0
Version: 2.2.0
Built: 2026-05-27 07:38:15 UTC
Source: https://github.com/Nowosad/spDataLarge

Help Index

Datasets providing a snapshot of Bristol's transport system

Description

Data used in the transport chapter in Geocomputation with R. See https://r.geocompx.org/transport.html for details.

Usage

bristol_ways

Format

sf data frame objects

Source

https://wicid.ukdataservice.ac.uk/ and other open access sources

Examples

## Not run: 
library(sf)
bristol_ways
bristol_od
bristol_region
bristol_ttwa
bristol_zones
bristol_stations

## End(Not run)

Datasets providing building blocks for a location analysis

Description

Data used in the geomarketing chapter in Geocomputation with R. See https://r.geocompx.org/location.html for details.

Usage

census_de

metro_names

shops

Format

census_de

A data.frame with census variables

metro_names

A data.frame with metropolitan area information

shops

An sf data.frame with POINT geometry

An object of class data.frame with 10 rows and 3 columns.

An object of class sf (inherits from data.frame) with 180035 rows and 3 columns.

Details

census_de

A data.frame with German census data at 1km resolution. Contains columns: x, y (EPSG:3035 coordinates), pop (population count, 2022), women (percentage of women, 2011), mean_age (mean age in years, 2022), hh_size (average household size, 2022). Missing values are coded as -1.

metro_names

A data.frame with metropolitan area names derived from Census 2022 population data. Contains columns: city, town, state. Generated by aggregating 1km population grid to 20km resolution, filtering cells with >500,000 inhabitants, and reverse geocoding centroids.

shops

An sf data.frame of shop locations from OpenStreetMap for the identified metropolitan areas. Contains columns: osm_id, shop, geometry.

Examples

data("census_de", package = "spDataLarge")
head(census_de)

data("metro_names", package = "spDataLarge")
metro_names

data("shops", package = "spDataLarge")
head(shops)

Community matrix of the Mt. Mongón

Description

A community matrix with species as columns and sites as rows. The rownames correspond to the id which can be also found in [random_points]. Please note that in fact 100 sites have been visited but in 16 of them no species could be found (see again [random_points]). The data is used in the "Ecology" chapter in Geocomputation with R. See https://r.geocompx.org/eco.html for details.

Format

A dataframe with 100 sites (rows) and 69 species (columns). Species presence is given in percentage points (between 0-100 site). Due to overlapping cover between individual plants, the total cover per site can be >100%.

References

Muenchow, J., Bräuning, A., Rodríguez, E.F. & von Wehrden, H. (2013): Predictive mapping of species richness and plant species' distributions of a Peruvian fog oasis along an altitudinal gradient. Biotropica 45, 5, 557-566, doi: 10.1111/btp.12049.

Examples

data("comm", package = "spDataLarge")

Digital elevation model (DEM) of the Mongón study area.

Description

A raster geotiff (EPSG:32717) representing altitude (ASTER GDEM, LP DAAC 2012) with 117 rows and 117 columns:

dem

Altitude in m asl.

. For more details, please refer to Muenchow et al. (2013).. The data is used in the "Ecology" chapter in Geocomputation with R. See https://r.geocompx.org/eco.html for details.

Format

A geotiff file

References

Muenchow, J., Bräuning, A., Rodríguez, E.F. & von Wehrden, H. (2013): Predictive mapping of species richness and plant species' distributions of a Peruvian fog oasis along an altitudinal gradient. Biotropica 45, 5, 557-566, doi: 10.1111/btp.12049.

LP DAAC (2012): Land Processes Distributed Active Archive Center, located at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. Available at: https://lpdaac.usgs.gov/ (last accessed 25 January 2012).

Examples

system.file("raster/ndvi.tif", package = "spDataLarge")

Environmental predictors

Description

A geotiff file (CRS: UTM zone 17S; EPSG:32717) with 117 rows and 117 columns:

  1. dem Digital elevation model (ASTER GDEM, LP DAAC 2012), see also [spDataLarge::dem].

  2. ndvi Normalized Differenced Vegetation index.

  3. carea Catchment area.

  4. cslope Catchment slope

The data is used in the "Ecology" chapter in Geocomputation with R. See https://r.geocompx.org/eco.html for details.

Format

A geotiff file

References

LP DAAC (2012): Land Processes Distributed Active Archive Center, located at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. Available at: https://lpdaac.usgs.gov/ (last accessed 25 January 2012).

Muenchow, J., Brauning, A., Rodriguez, E.F. & von Wehrden, H. (2013): Predictive mapping of species richness and plant species' distributions of a Peruvian fog oasis along an altitudinal gradient. Biotropica 45, 5, 557-566, doi: 10.1111/btp.12049.

Muenchow, J., Schratz, P., and A. Brenning. 2017. RQGIS: Integrating R with QGIS for Statistical Geocomputing. The R Journal 9, 2, 409-428. https://rjournal.github.io/archive/2017/RJ-2017-067/RJ-2017-067.pdf.

Examples

system.file("raster/ep.tif", package = "spDataLarge")

Dataset landsat

Description

This is a dataset containing the four bands (2, 3, 4, 5) of the Landsat 8 image for the area of Zion National Park. A scale factor should be applied before using the data: https://www.usgs.gov/faqs/how-do-i-use-a-scale-factor-landsat-level-2-science-products

Format

A multilayer geotiff file

Source

http://landsat-pds.s3.amazonaws.com/L8/038/034/LC80380342015230LGN00/

Examples

system.file("raster/landsat.tif", package = "spDataLarge")

Streets of london downloaded from OSM

Description

Data used in the "Bridges to GIS" chapter in Geocomputation with R. See https://r.geocompx.org/gis.html for details.

Usage

london_streets

Format

An sf-object with one attribute (osm_id) and one geometry column.

Source

OpenStreetMap (see https://www.openstreetmap.org/).

Examples

## Not run: 
library(sf)
library(osmdata)
library(spData)
library(dplyr)
data(cycle_hire)
points = cycle_hire[1:25, ]
b_box = sf::st_bbox(points)
london_streets = opq(b_box) %>%
        add_osm_feature(key = "highway") %>%
        osmdata_sf() %>%
        `[[`("osm_lines")
london_streets = dplyr::select(london_streets, 1)

## End(Not run)

Landslide dataset from Southern Ecuador

Description

Data used in the "Statistical learning for geographic data" chapter in Geocomputation with R. See https://r.geocompx.org/spatial-cv.html for details.

Usage

lsl

Format

The landslide dataset consists of two objects (CRS: UTM zone 17S; EPSG:32717):

  1. lsl A data.frame object representing the coordinates of landslide initiation points with 350 rows and 8 columns.

  2. study_mask An sf-object delineating the natural part of the study area.

Source

Landslide dataset of the RSAGA package: data("landslides", package = "RSAGA").

Landslide Data:

Muenchow, J., Brenning, A., Richter, R. (2012): Geomorphic process rates of landslides along a humidity gradient in the tropical Andes, Geomorphology 139-140, 271-284. DOI: 10.1016/j.geomorph.2011.10.029.

Stoyan, R. (2000): Aktivitaet, Ursachen und Klassifikation der Rutschungen in San Francisco/Suedecuador. Unpublished diploma thesis, University of Erlangen-Nuremberg, Germany.

See Also

?ta.tif

Examples

data("lsl", "study_mask", package = "spDataLarge")

Normalized difference vegetation index for the Mongón study area.

Description

NDVI raster geotiff (EPSG:32717) computed from a Landsat scene (path 9, row 67, acquisition date: 09/22/2000; USGS 2013) with 117 rows and 117 columns:

ndvi

Normalized difference vegetation index.

. For more details, please refer to Muenchow et al. (2013).. The data is used in the "Ecology" chapter in Geocomputation with R. See https://r.geocompx.org/eco.html for details.

Format

A geotiff file

References

Muenchow, J., Bräuning, A., Rodríguez, E.F. & von Wehrden, H. (2013): Predictive mapping of species richness and plant species' distributions of a Peruvian fog oasis along an altitudinal gradient. Biotropica 45, 5, 557-566, doi: 10.1111/btp.12049.

USGS (2013): U.S. Geological Survey. Earth Explorer. Available at: http://earthexplorer.usgs.gov/ (last accessed 1 March 2013).

Examples

system.file("raster/ndvi.tif", package = "spDataLarge")

Dataset nlcd

Description

This is a dataset containing a simplified version of the National Land Cover Database 2011 product for the Zion National Park area

Format

A geotiff file

Source

https://www.mrlc.gov/nlcd2011.php

Examples

system.file("raster/nlcd.tif", package = "spDataLarge")

Dataset nlcd2011

Description

This is a dataset containing the National Land Cover Database 2011 product for the Zion National Park area

Format

A geotiff file

Source

https://www.mrlc.gov/nlcd2011.php

Examples

system.file("raster/nlcd2011.tif", package = "spDataLarge")

New Zeleand elevation raster data

Description

Elevation raster data of the New Zealand area from the Mapzen Terrain Service. For teaching purposes only

Format

A geotiff file

Source

https://registry.opendata.aws/terrain-tiles/

See Also

See the elevatr package: https://cran.r-project.org/web/packages/elevatr

Examples

system.file("raster/nz_elev.tif", package = "spDataLarge")

Polish election data 2015

Description

Polish Presidential election 2015 data by gminy and Warsaw borough areal units

Usage

pol_pres15

Format

sf data frame object with 2495 areal units and 65 variables

  • TERYT, TERYT0, gm0TERYT areal unit IDs

  • name0original areal unit names

  • namecleaned areal unit names

  • typesfactor with levels “Rural”, “Urban”, “Urban/rural” and “Warsaw borough”

  • I_turnoutFirst round turnout proportion

  • II_turnoutRunoff round turnout proportion

  • I_Duda_shareWinner first round share

  • II_Duda_shareWinner runoff round share

  • I_Komorowski_shareIncumbent first round share

  • II_Komorowski_shareIncumbent runoff round share

  • I_*First round aggregated counts of all polling station data

  • II_*Runoff round aggregated counts of all polling station data

Note

“PVE” in variable names means “postal voting envelopes”; voters requesting a postal voting package are expected to return a postal voting envelope with a declaration, and a sealed voting envelope to be placed in the ballot box.

Author(s)

Roger Bivand

Source

http://prezydent2015.pkw.gov.pl/319_Pierwsze_glosowanie/, http://prezydent2015.pkw.gov.pl/325_Ponowne_glosowanie/, https://www.gov.pl/web/gugik

Examples

## Not run: 
data("pol_pres15", package = "spDataLarge")
wd = aggregate(pol_pres15$I_entitled_to_vote, list(pol_pres15$types), sum)$x
boxplot(I_turnout ~ types, data = pol_pres15, width = wd)

## End(Not run)

Random points.

Description

An [sf] (EPSG:32717) object with 100 randomly sampled points (stratified by altitude) on the Mt. Mongón (Peru). For more details, please refer to Muenchow et al. (2013). The data is used in the "Ecology" chapter in Geocomputation with R. See https://r.geocompx.org/eco.html for details.

Format

An [sf] object with 100 rows and 3 variables:

id

Plot ID.

spri

Number of vascular plant species per plot (species richness).

geometry

Simple feature point geometry.

References

Muenchow, J., Bräuning, A., Rodríguez, E.F. & von Wehrden, H. (2013): Predictive mapping of species richness and plant species' distributions of a Peruvian fog oasis along an altitudinal gradient. Biotropica 45, 5, 557-566, doi: 10.1111/btp.12049.

Examples

data("random_points", package = "spDataLarge")

Dataset srtm

Description

This is a dataset containing the elevation raster data from SRTM of the Zion National Park area

Format

A geotiff file

Source

https://srtm.csi.cgiar.org/SRT-ZIP/SRTM_V41/SRTM_Data_GeoTiff/srtm_14_05.zip

Examples

system.file("raster/srtm.tif", package = "spDataLarge")

Mask of the study area on the Mount Mongón

Description

An [sf] (EPSG:32717) object of geometry class polygon.

Format

An [sf] object with 1 row and 2 variables:

name

Name.

geometry

Simple feature polygon geometry.

References

Muenchow, J., Bräuning, A., Rodríguez, E.F. & von Wehrden, H. (2013): Predictive mapping of species richness and plant species' distributions of a Peruvian fog oasis along an altitudinal gradient. Biotropica 45, 5, 557-566, doi: 10.1111/btp.12049.

Examples

data("study_area", package = "spDataLarge")

Terrain attributes of the landslide dataset from Southern Ecuador

Description

Data used in the "Statistical learning for geographic data" chapter in Geocomputation with R. See https://r.geocompx.org/spatial-cv.html for details.

Format

A geotiff file with the five terrain attribute layers: slope, plan curvature, profile curvature, elevation and catchment area.

Source

DEM dataset of the RSAGA package: data("landslides", package = "RSAGA").

DEM:

Ungerechts, L. (2010): DEM 10m (triangulated from aerial photo - b/w). Available online:

'http://www.tropicalmountainforest.org/data_pre.do?citid=901'

Jordan, E., Ungerechts, L., Caceres, B. Penafiel, A. and Francou, B. (2005): Estimation by photogrammetry of the glacier recession on the Cotopaxi Volcano (Ecuador) between 1956 and 1997. *Hydrological Sciences* 50, 949-961.

See Also

?lsl

Examples

system.file("raster/ta.tif", package = "spDataLarge")

Point vector data

Description

Dataset containing 30 randomly located points in the Zion National Park

Usage

zion_points

Format

A sf object

Point vector data

Description

Dataset containing 30 randomly located points in the Zion National Park

Format

A geopackage file

Source

https://irma.nps.gov/DataStore/DownloadFile/580617

Examples

system.file("vector/zion_points.gpkg", package = "spDataLarge")

Dataset zion

Description

This is a dataset containing the borders of Zion National Park

Format

A geopackage file

Source

https://irma.nps.gov/DataStore/DownloadFile/580617

Examples

system.file("vector/zion.gpkg", package = "spDataLarge")