分析空间连接（指向网格）的数据，并在R中生成新的数据集

我有一个包含经度/纬度点的数据集，以及每组坐标的结果值。我想创建一个空间网格，然后取同一网格中坐标的平均结果，并生成一个新的数据帧，为每个坐标分配一个网格编号，并具有平均结果。例如，从以下代码开始：

require(sp)
require(raster)

frame <- data.frame(x = c(7.5, 8.2, 8.3), y = c(1,4,4.5), z = c(10,15,30))

coordinates(frame) <- c("x", "y")
proj4string(frame) <- CRS("+proj=longlat")

grid <- GridTopology(cellcentre.offset= c(0,0), cellsize = c(2,2), cells.dim = c(5,5))
sg <- SpatialGrid(grid)
poly <- as.SpatialPolygons.GridTopology(grid)
proj4string(poly) <-  CRS("+proj=longlat")

plot(poly)
text(coordinates(poly), labels = row.names(poly), col = "gray", cex. =.6)
points(frame$x, frame$y, col = "blue", cex = .8)

谢谢你的帮助

您可以使用包

sp

中的

over（…）

函数来完成此操作。据我所知，您根本不需要包

光栅

require(sp)

frame  <- data.frame(x = c(7.5, 8.2, 8.3), y = c(1,4,4.5), z = c(10,15,30))
points <- SpatialPoints(frame)
proj4string(points) <-  CRS("+proj=longlat")

grid  <- GridTopology(cellcentre.offset= c(0,0), cellsize = c(2,2), cells.dim = c(5,5))
sg    <- SpatialGrid(grid)
poly  <- as.SpatialPolygons.GridTopology(grid)
proj4string(poly) <-  CRS("+proj=longlat")

# identify grids...
result <- data.frame(frame,grid=over(points,poly))
# calculate means...
result <- merge(result,aggregate(z~grid,result,mean),by="grid")
# rename and reorder columns to make it look like your result
colnames(result) <- c("grid","x","y","z","grid_mean")
result <- result[,c(2,3,4,1,5)]
result
#     x   y  z grid grid_mean
# 1 8.2 4.0 15   15      22.5
# 2 8.3 4.5 30   15      22.5
# 3 7.5 1.0 10   25      10.0

require（sp）
框架您提供的代码将第一个点放在g20和g25之间的边界上，而不是g10中。你确定网格是你想要的吗？另外，您希望如何处理边界上的点？？谢谢您的关注。我把它列在g20；对于边界点，随机分配将是我的首选。太好了，谢谢-这正是我想要的。
require(sp)

frame  <- data.frame(x = c(7.5, 8.2, 8.3), y = c(1,4,4.5), z = c(10,15,30))
points <- SpatialPoints(frame)
proj4string(points) <-  CRS("+proj=longlat")

grid  <- GridTopology(cellcentre.offset= c(0,0), cellsize = c(2,2), cells.dim = c(5,5))
sg    <- SpatialGrid(grid)
poly  <- as.SpatialPolygons.GridTopology(grid)
proj4string(poly) <-  CRS("+proj=longlat")

# identify grids...
result <- data.frame(frame,grid=over(points,poly))
# calculate means...
result <- merge(result,aggregate(z~grid,result,mean),by="grid")
# rename and reorder columns to make it look like your result
colnames(result) <- c("grid","x","y","z","grid_mean")
result <- result[,c(2,3,4,1,5)]
result
#     x   y  z grid grid_mean
# 1 8.2 4.0 15   15      22.5
# 2 8.3 4.5 30   15      22.5
# 3 7.5 1.0 10   25      10.0