R 绘制交互式地图 Mapview

leaflet可以实现交互式地图，这里直接一中国为例，展示不同省份的population以及mapview上的实现。
leaflet基础篇可以去官网；

该文章内容的地图图层文件，均是sf形式。leaflet可以直接加载sf，省去转换Polygons的麻烦。

1.leaflet

1.1 加载China地图

library(ggplot2)
library(dplyr)
library(tibble)
library(sf)
library(leaflet)
library(leaflet.extras)
rm(list = ls())
China=read_sf("https://geo.datav.aliyun.com/areas_v2/bound/100000_full.json")
Anhui=read_sf("https://geo.datav.aliyun.com/areas_v2/bound/340000_full.json")
franconia
breweries


CHNmap=leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons( data=China,   stroke = TRUE,
               color = "#444444",
               weight = 1,
               smoothFactor = 0.5,
               opacity = 1.0,
               fillOpacity = 0.1,
                  label = ~ name,
               highlightOptions = highlightOptions(color = "white",
                                                   weight = 2,
                                                   bringToFront = TRUE),
               labelOptions = labelOptions(
                 style = list("font-weight" = "normal", padding = "3px 8px"),
                 textsize = "15px",
                 direction = "auto"))
CHNmap

image.png

这里直接加载到leaflet图层上，可以看到China的轮廓及各个省份的位置

1.2 添加安徽地图

在上述的图层中，再添加安徽内部的市及区的地图。

CHNmap %>% 
  addPolygons( data=Anhui,   stroke = T,
               color = "blue",
               weight = 1,
               opacity = 1,
               fillOpacity = 0.1)

image.png

1.3.根据各个省含有的市及区多少，添加颜色

有时候，需要根据不同省份的人口或者经济，进行不同颜色渲染，突出地区间的比较。现在以各个省份内部所包含的市及县数量，来进行一个等级划分。其中重点是将连续性变量转成分类变量，还要匹配上对应颜。

# set categories and color bins bins = c(0, 5, 10, 15, 20, 30, Inf) pal = colorBin("Reds", domain = China$childrenNum, bins = bins)

##  set categories and color bins
bins = c(0, 5, 10, 15, 20, 30, Inf)
pal = colorBin("Reds", domain = China$childrenNum, bins = bins)

## leaflet
map=leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons( data=China,   stroke = TRUE,
               fillColor = ~pal(childrenNum),
               color = "black",
               weight = 1,
               smoothFactor = 0.5,
               opacity = 0.5,
               fillOpacity = 0.5,
               label = ~ name,
               highlightOptions = highlightOptions(color = "green",
                                                   weight = 2,
                                                   bringToFront = TRUE),
               labelOptions = labelOptions(
                 style = list("font-weight" = "normal", padding = "3px 8px"),
                 textsize = "15px",
                 direction = "auto")) %>% 
  addLegend(data=China, pal = pal,
            values = ~childrenNum,
            opacity = 0.7,
            title = "Number",
            position = "bottomright") 
            
# plot
map

image.png

1.4.添加点的信息

China_point = st_centroid(China) %>% 
  st_coordinates() %>% 
  as_data_frame() %>% 
  slice(-35)

map %>% 
  addCircles(data = China_point,
                  lng = ~X, lat = ~Y,
                  fillOpacity =2)

image.png

2.Mapview 绘图

其实谈到交互地图，mapview包已经做到了精简，详细教程见官网，
这里只需要一行code即可；
但是缺点是，不容易个性化设置，譬如legend名称，legend设置等。
主要是简单，快速。
但是官方文档，里面有更详细的操作步骤。

## 
mapview::mapview(China)
mapview::mapview(China,zcol = "childrenNum")
mapview(China,  col.regions = "white", lwd = 0.5,legend = F)

image.png

后续还会更新，包括怎样将leaflet与mapview结合到shiny中。
及legend细化。

参考

Drawing interactive maps with Leaflet
Buffer areas for nearest neighbours or national marine areas delineation
Interactive Choropleths with Shiny and Leaflet
Lesson 2 Interactive Maps

R 绘制交互式地图 Mapview