R 地图绘制-比例尺与指北针

ggplot绘制map

R语言可以进行数据分析，也可以进行地图绘制，而且非常简洁，快速。
虽然Arcgis基于桌面可视化操作，能够进行空间分析，但是唯一不足的就是操作步骤繁琐而且一不小心，就要从头再来，可重复性较低。

这篇文章主要讲述如何利用R语言中的ggplot与sf绘制带有指北针、图列与标尺的地图

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数据

我们下载非洲地区54个国家的图层Afirca.json保存在本地。然后加载包去读取。然后在ggplot中使用 geom_sf来简单画出非洲地区的轮廓

library(tidyverse)
library(sf)
library(ggspatial)
library(ggthemes)
# https://geojson-maps.ash.ms/
africa <- read_sf("africa.json")

# plot
africa %>% 
  ggplot() + 
  geom_sf()
 
# populations with colors
ggplot(africa) +
  geom_sf(aes(geometry = geometry, fill = pop_est))

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指北针

一张标准的地图需要有比例尺，地图及指北针，所以这次我们加上比例尺与指北针，通过ggspatial包，调用annotation_scale来增加比例尺。location = "bl"是调整比例尺位置， width_hint = 0.3调整比例的长度。
annotation_north_arrow则是用来添加指北针。style =north_arrow_nautical来更改指北针的类型，主要有north_arrow_orienteering；north_arrow_fancy_orienteering；north_arrow_minimal与north_arrow_nautical四种类型，其他参数可help(annotation_north_arrow)查看。

# with scales and north_arrow
ggplot(africa) +
  geom_sf(aes(geometry = geometry, fill = pop_est)) +
  annotation_scale(location = "bl", width_hint = 0.4) +
  annotation_north_arrow(location = "tr", which_north = "true", 
                         pad_x = unit(0.05, "in"), pad_y = unit(0.05, "in"),
                         style = north_arrow_nautical) 

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背景调整

如果不喜欢有grid的背景，可以根据喜好，调节自己喜欢的背景
这里我们采用， theme_light()白色网格背景。更多背景设置，请见ggplot2 主题背景设置

# with blank themes
ggplot(africa) +
  geom_sf(aes(geometry = geometry, fill = pop_est)) +
  annotation_scale(location = "bl", width_hint = 0.4) +
  annotation_north_arrow(location = "tr", which_north = "true", 
                         pad_x = unit(0.05, "in"), pad_y = unit(0.05, "in"),
                         style = north_arrow_nautical) +
  theme_light()

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图例颜色

默认的图例颜色是blue色调，我们可以根据
来更改红色基准的色调。
legend 是默认的分段方式，我们可以根据需要设定成4分类，或者更改图例的距离。

# with colors
ggplot(africa) +
  geom_sf(aes(geometry = geometry, fill = pop_est)) +
  scale_fill_gradientn(colours=brewer.pal(5,"Reds"))+
  annotation_scale(location = "bl", width_hint = 0.4) +
  annotation_north_arrow(location = "tr", which_north = "true", 
                         pad_x = unit(0.05, "in"), pad_y = unit(0.05, "in"),
                         style = north_arrow_nautical) +
  theme_light()

# for 4 categories
africa %>% mutate( new=cut(pop_est,b = 4)) %>% 
ggplot() +
  geom_sf(aes(geometry = geometry, fill = new)) +
  annotation_scale(location = "bl", width_hint = 0.4) +
  annotation_north_arrow(location = "tr", which_north = "true", 
                         pad_x = unit(0.05, "in"), pad_y = unit(0.05, "in"),
                         style = north_arrow_nautical) +
  theme_light()
  
 # set for sacles

my_breaks = c(0,3207562,10401245,18419935,20644434,149229090 )
ggplot(africa) +
  geom_sf(aes(geometry = geometry, fill = pop_est)) +
  scale_fill_gradient(name = "count", 
                        breaks = my_breaks, labels = my_breaks)
                        
#
ggplot(africa) +
  geom_sf(aes(geometry = geometry, fill = pop_est)) +
  scale_fill_gradient(name = "count", 
                        breaks = my_breaks, labels = my_breaks, guide="legend")
  

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关于更多颜色设置ggplot2: Elegant Graphics for Data Analysis
legend分类legend and labels

参考

1. Geospatial Visualization
2. sf 与指北针
3. geocompkg | metapackage for the Gecomputation with R book
4. This repository contains the source for the book Geospatial Visualization.
5. Chapter 8: Making maps with R
6. ggplot2 主题背景设置