R 在地图上绘制填充的经纬度网格单元 [英] R Plot Filled Longitude-Latitude Grid Cells on Map

问题描述

我有一个包含多个 (x,y,z) 数据点的数据框，(x,y) 是经度的右下坐标- 大小为 w 的纬度单元(例如 1 度网格).z 值已在此单元格上取平均值.

I have a data frame containing a number of (x,y,z) data points, (x,y) is the lower-right coordinate of a longitude-latitude cell of size w (e.g. a 1-degree grid). The z value has been averaged over this cell.

我想在 R 中绘制这些点，以便整个网格单元都填充一些源自 z 的颜色.

I'd like to plot these points in R so that the entire grid cell is filled with some colour derived from z.

结果将类似于以下图像之一:

The result would look something like one of these images:

投影本身(例如 Lambert 等角圆锥曲线、等距柱状投影)并不重要，重要的是网格单元绘制.

The projection itself (e.g. Lambert conformal conic, equirectangular) isn't important, just the grid cell plotting.

我的数据很稀疏:并非每个经纬度单元格都会有与之关联的数据.

My data is sparse: not every longitude-latitude cell will have data associated with it.

我希望是一个类似于

library(maps)
map("state")
grid_points(my_data,c("x","y","z"),0.5)

其中 0.5 是上面的网格分辨率，表示 0.5 度的单元格.

where 0.5 is the grid resolution above, indicating a 0.5-degree cell.

有什么想法吗?

谢谢！

推荐答案

使用 spplot 或 image 的替代方案是使用 ggplot2.相关的几何图形是 geom_raster 和 geom_tile.第一个应该表现更好并产生更小的文件，第二个更标准.以下示例调用:

An alternative to using either spplot or image is to use ggplot2. The relevant geometries are geom_raster and geom_tile. The first is supposed to perform better and yield smaller files, and the second is more standard. The following example call:

ggplot(aes(x = x, y = y, fill = value), data = dat_grid) + geom_tile() + 
  geom_path(data = ant_ggplot)

源自这篇博文 我的.此外，ggplot2 通过 mapproj 包，见coord_map 了解更多详情.

orginates from this blogpost of mine. In addition, ggplot2 supports a range of projections through the mapproj package, see coord_map for more details.

以下是一个工作示例(假设您已将 YOUR_DATA 定义为具有 x,y,z 列):

The following is a working example (provided you've defined YOUR_DATA to have x,y,z columns):

library(ggplot2)
library(maps)
us_states <- map_data("state")
(ggplot(aes(x=x,y=y,fill=z),data=YOUR_DATA) + geom_tile())+geom_polygon(data=us_states,aes(x=long, y=lat, group=group), colour="black", fill="white", alpha=0)

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