https://github.com/stscl/geocn
Loads Spatial Data Sets of China
https://github.com/stscl/geocn
china china-region geospatial-visualization maps r
Last synced: 6 months ago
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Loads Spatial Data Sets of China
- Host: GitHub
- URL: https://github.com/stscl/geocn
- Owner: stscl
- Created: 2024-08-02T02:37:11.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-09-09T08:14:07.000Z (8 months ago)
- Last Synced: 2024-09-09T09:53:39.489Z (8 months ago)
- Topics: china, china-region, geospatial-visualization, maps, r
- Language: R
- Homepage: https://stscl.github.io/geocn/
- Size: 48.1 MB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "##",
fig.path = "man/figures/README-",
out.width = "100%",
warning = FALSE,
message = FALSE
)
```
# geocn 
[](https://CRAN.R-project.org/package=geocn)
[](https://stscl.r-universe.dev/geocn)
The goal of **geocn** is to provide various commonly used spatial data related to Chinese regions in the R programming environment.
## Installation
- Install development binary version from [R-universe](https://stscl.r-universe.dev/geocn) with:
``` r
install.packages("geocn",
repos = c("https://stscl.r-universe.dev",
"https://cloud.r-project.org"),
dep = TRUE)
```
- Install development source version from [GitHub](https://github.com/stscl/geocn) with:
``` r
# install.packages("devtools")
devtools::install_github("stscl/geocn",
build_vignettes = TRUE,
dep = TRUE)
```
## Example
### Drawing a Map of China Using `ggplot2`
```{r map1,fig.width=9.5,fig.height=7.5,fig.dpi=120}
library(sf)
library(ggplot2)
library(cowplot)
library(geocn)
albers = load_cn_alberproj()
province = load_cn_province()
tenline = load_cn_tenline()
ocean = load_world_ocean()
lakes = load_world_lake()
coastline = load_world_coastline()
ggplot() +
geom_sf(data = ocean,fill="#BEE8FF",color="white",size=.1) +
geom_sf(data = coastline,color="#252525",size=.5) +
geom_sf(data = province,fill="white",size=.1,color="grey") +
geom_sf(data = lakes,fill="#BEE8FF",color="white",size=.1) +
geom_sf(data = tenline,size=.2,color="#9d98b7") +
ggfx::with_shadow(geom_sf(data = tenline,size=.2,color="#9d98b7") ,
sigma = 3,x_offset = -5,y_offset = -2) -> fig1
fig1 +
coord_sf(crs = albers,
ylim = c(1500000,6000000),
xlim = c(-3100000,2000000),
expand = FALSE) +
theme_bw() +
theme(plot.background = element_rect("grey97", fill = NA),
axis.text = element_blank(),
axis.ticks = element_blank(),
axis.title = element_blank()) -> china.main
fig1 +
coord_sf(crs = albers,
ylim = c(273000,2800000),
xlim = c(-350000,1350000)) +
theme_minimal() +
theme(
axis.text = element_blank(),
axis.ticks = element_blank(),
axis.title = element_blank(),
panel.grid = element_blank(),
panel.background = element_rect("#BEE8FF", color = NA),
panel.border = element_rect(fill=NA,
linetype = 1,
linewidth = 0.5),
plot.margin=unit(c(0,0,0,0),"cm")) -> china.ocean
ggdraw() +
draw_plot(china.main) +
draw_plot(china.ocean,x = .815, y = .015,
width = .13, height = .20) -> cnmap1
cnmap1
```
### Drawing a Map of China Using `tmap`
```{r ,fig.show='hide',fig.dpi=120}
library(sf)
library(tmap)
library(cowplot)
library(geocn)
albers = load_cn_alberproj()
cn_border = load_cn_border()
main_border = load_cn_landcoast()
tenline = load_cn_tenline()
province = load_cn_province()
tm_shape(main_border,
projection = albers) +
tm_lines(col = NA,lwd = 0.01) +
tm_shape(province) +
tm_fill(col = 'white',alpha = .5) +
tm_borders(col = 'grey40', lwd = 1.25) +
tm_shape(cn_border) +
tm_lines(col='#9d98b7',lwd = 2.5) +
tm_scale_bar(position = c(0.05,0.01),
width = 0.15,text.size = 1.05,
lwd = 2) +
tm_compass(position = c(0.05,0.9),
just = 'center',size = 1.5,
text.size = .65,show.labels = 1) +
tm_layout(legend.width = 0.75,
legend.text.size = 1,
legend.height = 1.75,
legend.position = c(0.045,0.075),
compass.type = "arrow",
fontfamily = "serif") -> cn_mainplot
tm_shape(tenline,
projection = albers) +
tm_lines(col=NA,lwd=0.01) +
tm_shape(province) +
tm_fill(col = 'white',alpha = .5) +
tm_borders(col = 'grey40', lwd = 1.25) +
tm_shape(cn_border) +
tm_lines(col='#9d98b7',lwd = 2.5) -> cn_miniplot
ggdraw() +
draw_plot(tmap_grob(cn_mainplot)) +
draw_plot(tmap_grob(cn_miniplot),
halign = 0.5,valign = 0.5,
height = 0.2,
x = 0.427,
y = 0.019) -> cnmap2
```
```{r map2,fig.width=7.25,fig.height=6,fig.dpi=120}
cnmap2
```