2017-09-20 74 views
1

我已经使用ggplot代码(简化版本的代码)从我在中国的研究地点的栅格对象(来自worldclim的高程数据)创建了一个高程图。相关的栅格对象已从worldclim.org下载并使用栅格包转换为data.frame。这是用于此图的数据的link从ggplot地图上的osmar对象绘制道路

# load library 
library("tidyverse") 
load(file = "gongga.RData") 

ggplot() + 
geom_raster(data = gongga, aes(x=x, y=y, fill = elev)) + 
coord_equal() + 
scale_fill_gradient(name = "Elevation", low = "grey0", high = "grey100") + 
scale_x_continuous(expand = c(0,0)) + 
scale_y_continuous(expand = c(0,0)) + 
theme(aspect.ratio=1/1, text = element_text(size=15)) 

Picture of the map created in ggplot

为清楚起见,我想道路添加到地图中。我遇到了从Openstreetmap中提取道路的osmar包。

使用here中的代码,我提取了正确部分的道路,但我不知道如何将它们绘制到我现有的ggplot中。

# EXTRACT ROADS FROM OPENSTREETMAP AND PLOT THEM WITH RANDOM POINTS 
# Load libraries 
library('osmar') 
library('geosphere') 

# Define the spatial extend of the OSM data we want to retrieve 
moxi.box <- center_bbox(center_lon = 102.025, center_lat = 29.875, 
width = 10000, height = 10000) 

# Download all osm data inside this area 
api <- osmsource_api() 
moxi <- get_osm(moxi.box, source = api) 

# Find highways 
ways <- find(moxi, way(tags(k == "highway"))) 
ways <- find_down(moxi, way(ways)) 
ways <- subset(moxi, ids = ways) 

# SpatialLinesDataFrame object 
hw_lines <- as_sp(ways, "lines") 

# Plot points 
plot(hw_lines, xlab = "Lon", ylab = "Lat") 
box() 

该对象是否需要任何转换将其绘制在ggplot中? 还是有更好的解决方案比奥斯马包为我的目的?

回答

0

可以fortifySpatialLinesDataFrame,然后绘制与ggplot

fortify(hw_lines) %>% 
    ggplot(aes(x = long, y = lat, group = group)) + 
    geom_path() 

group审美从加入所有的道路连成一个长行停止ggplot

+0

谢谢,理查德。完美的工作。 – Aud