R 使用SF在光栅中聚合值

使用SF在光栅中聚合值

我需要的是为每个光栅聚合一些度量值。 假设我们有一些数据坐标和值，我想创建一个热图

首先，我使用简单的特征框架创建网格和光栅。 现在我需要获取

df

中的每个坐标，并检查它们是否在一个光栅中。然后为每个光栅计算任何其他聚合函数的平均值

# Packages ----------------------------------------------------------------


library(raster)
library(tidyverse)
library(sf)
library(sp)


# Border Data and Grid ----------------------------------------------------

Regions <- getData("GADM", country= "CZE", level = 1)
Regions %>% 


Regions <-
  Regions %>% st_as_sf()

grid_spacing <- 0.25

polygony <- st_make_grid(Regions, square = T,
                         cellsize = c(grid_spacing, grid_spacing)) %>%
  st_sf()

plot(polygony, col = 'white')
plot(st_geometry(CZ), add = T)

A = st_intersection(polygony, CZ)


# Artifial Values to be use -----------------------------------------------
df <- 
  tibble(long = runif(500, 13.27857, 14),
         lat = runif(500, 49, 50),
         price = rnbinom(500, size = 40, 0.3))

df %>% 
  ggplot(aes(long, lat, color = values)) + 
  geom_point()

A <- 
  A %>% 
  # Here Val shall be calculated as a mean of observations within each rastel grid cell
  mutate(val = rnorm(n = 202))

# Since not every raster cell has observations inside some NAN will be present
A[5, 'val']  = NaN
A[25, 'val']  = NaN

A %>% 
  ggplot(aes(fill = val)) + 
  geom_sf()



# What I need -------------------------------------------------------------

# For each raster in A calculate the mean of price for coordinates within this raster grid.

#包裹----------------------------------------------------------------
图书馆（光栅）
图书馆（tidyverse）
图书馆（sf）
图书馆（sp）
#边界数据与网格----------------------------------------------------
地区%
区域%st_as_sf（）
网格间距%
ggplot（aes（fill=val））+
geom_sf（）
#我需要什么-------------------------------------------------------------
#对于中的每个光栅，计算此光栅栅格内坐标的平均价格。

我基本上需要sf框架中的一些等价物

---

但是，我想打印出来，就像在示例中一样，我确实需要光栅具有给定网格的形状。

因为您仍然使用光栅包

library(raster)
cze <- getData("GADM", country= "CZE", level = 1)
r <- raster(cze, res=0.25)
df <- data.frame(long = runif(500, 13.27857, 14),
         lat = runif(500, 49, 50),
         price = rnbinom(500, size = 40, 0.3))

r <- rasterize(df[,c("long", "lat")], r, df$price, mean, background=0)
p <- as(r, "SpatialPolygonsDataFrame")
p <- crop(p, cze)

library(sf)
s <- st_as_sf(p)
plot(p)

库（光栅）
cze要在网格上聚合点值并保留sf，可以执行以下操作：

library(dplyr)
library(sf)

# get data. using your example, we'll take spatial data from the raster package
Regions <- raster::getData("GADM", country= "CZE", level = 1)

# convert spdf to sf
Regions <- Regions %>% st_as_sf()

# create a grid sf object
grid_spacing <- 0.25

polygony <- st_make_grid(Regions, square = T,
                         cellsize = c(grid_spacing, grid_spacing)) %>%
  st_sf() %>% 
  mutate(ID = row_number()) # add a unique ID to each grid cell

# clip grid to shape of country polygons
A <- st_intersect(polygony, Regions)

# create fake data with coordinates and prices
df <- tibble(long = runif(500, 13.27857, 14),
         lat = runif(500, 49, 50),
         price = rnbinom(500, size = 40, 0.3))

# convert the df to sf point layer
points <- st_as_sf(df, coords = c("long", "lat"), crs = st_crs(A))

# spatially join grid to points, so that each point is assigned the grid ID into which it falls
pointsID <- st_join(points, A)

# group and summarize point values by grid ID
pointsID <- pointsID %>% 
  as.data.frame() %>% 
  group_by(ID) %>% 
  summarize(avg_price = mean(price))

# join aggregated values back to your grid
A<- left_join(A, pointsID, by = "ID")

plot(A["avg_price"])

库（dplyr）
图书馆（sf）
#获取数据。使用您的示例，我们将从光栅包中获取空间数据
你好，谢谢，但不完全是这样。我需要最终的聚合光栅以具有给定网格的形状。