gridDE: Grid data for Germany on land use, population density, and...

In markusfritsch/smoothLUR: Functions and data for smooth Land Use Regression Modeling

Grid data for Germany on land use, population density, and road lengths

Description

Data on land use, population density, and road lengths for different types of roads employed in \insertCiteFritsch2021smooth;textualsmoothLUR. The dataset represents Germany on a 1\,x\,1\,km grid and contains 23 variables for 356,793 grid cells, which characterize the area covered by the grid cells. Details on the data sources and how the data were obtained are provided in \insertCiteFritsch2021diB;textualsmoothLUR.

Usage

data(gridDE)

Format

A dataset with 356793 rows and 23 variables containing:

ID

grid cell identifier

Lon.GK3

geocoordinate longitude (Gauss-Kr\"uger) at which the monitoring site is located

Lat.GK3

geocoordinate latitude (Gauss-Kr\"uger) at which the monitoring site is located

Lon.WGS84

geocoordinate longitude (decimal degrees) at which the monitoring site is located

Lat.WGS84

geocoordinate latitude (decimal degrees) at which the monitoring site is located

Alt

altitude (meter above sea level) at which the monitoring site is located

HighDens

proportion of high density residential area within a buffer of radius 1km around the monitoring site

LowDens

proportion of low density residential area within a buffer of radius 1km around the monitoring site

Ind

proportion of industrial area within a buffer of radius 1km around the monitoring site

Transp

proportion of area attributed to transport within a buffer of radius 1km around the monitoring site

Seap

proportion of area attributed to seaport within a buffer of radius 1km around the monitoring site

Airp

proportion of area attributed to airport within a buffer of radius 1km around the monitoring site

Constr

proportion of area attributed to construction within a buffer of radius 1km around the monitoring site

UrbGreen

proportion of area attributed to urban green spaces within a buffer of radius 1km around the monitoring site

Agri

proportion of agricultural area within a buffer of radius 1km around the monitoring site

Forest

proportion of forestry area within a buffer of radius 1km around the monitoring site

PopDens

population density (inhabitants per km^2) at municipality key level

PriRoad

primary roads (length in meter) within buffer of radius 1km around the monitoring site

SecRoad

secondary roads (length in meter) within buffer of radius 1km around the monitoring site

FedAuto

federal autobahn (length in meter) within buffer of radius 1km around the monitoring site

LocRoute

local routes (length in meter) within buffer of radius 1km around the monitoring site

IndRegions

German federal state in which the monitoring site is located

Details

The data given for each grid cell include longitude, latitude, and altitude. Additional information which characterizes the area covered by the grid cells is given via fractions of various land cover classes, population density, and the length of the road traffic network.

Source

European Environmental Agency: CORINE land cover (CLC) 2015 raster data - version 18.5.1 (09/2016)

EuroGeographics: Euroglobalmap (egm), v9.0

Federal Government for Geo-Information and Geodesy, DGM200 GK3 GRID-ASCII, GeoBasis-DE / BKG 2015

Federal Government for Geo-Information and Geodesy, VG250-EW Ebenen GK3 Shape, GeoBasis-DE /BKG 2015

References

\insertAllCited

Examples

## Not run: 
  data(gridDE, package = "smoothLUR")
  pol <- gridDE$FedAuto
  typ <- as.factor(gridDE$IndRegions)
  \donttest{plot(y = pol, x = typ)}

## End(Not run)

markusfritsch/smoothLUR documentation built on Nov. 5, 2022, 3:42 p.m.