SF&；dplyr：按相同坐标分组不起作用 [英] sf & dplyr: Grouped mean by same coordinates doesn't work
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问题描述
我有一个从S2卫星栅格(10x10米)提取的数据集，其中有12个值(ras.df.ll)，但6个在一个块(T21JYG)中，第二个在另一个(T21JYG)中。
我想计算瓷砖之间相同(x，y坐标)的平均值，但没有成功。我找不到任何方法来识别第一个块中的第一行与第二个块中的第一行的坐标相同，只是我的数据集的末尾。在我的示例中：
library(sf)
library(sfheaders)
library(dplyr)
# Raster (10x10 meters) info in data frame 1 - crs +proj=utm +zone=21 +south +datum=WGS84 +units=m +no_defs
x <-c(789385,789395,789405,789415,789425,789435)
y <-c(6626865,6626865,6626865,6626865,6626865,6626865)
tile <- rep("T21JYG",6)
values <-c(321,249,234,238,224,244)
ras.ds1<-data.frame(x,y,tile,values)
ras.ds1.sf <- st_as_sf(ras.ds1, coords = c("x", "y"), crs = 32721, agr = "constant")
ras.ds1.sf.ll <- st_transform(ras.ds1.sf, crs=4326)
ras.ds1.sf.ll
#Simple feature collection with 6 features and 2 fields
#Attribute-geometry relationship: 2 constant, 0 aggregate, 0 identity
#Geometry type: POINT
#Dimension: XY
#Bounding box: xmin: -53.98638 ymin: -30.45564 xmax: -53.98586 ymax: -30.45562
#Geodetic CRS: WGS 84
# tile values geometry
# 1 T21JYG 321 POINT (-53.98638 -30.45564)
# 2 T21JYG 249 POINT (-53.98628 -30.45563)
# 3 T21JYG 234 POINT (-53.98617 -30.45563)
# 4 T21JYG 238 POINT (-53.98607 -30.45563)
# 5 T21JYG 224 POINT (-53.98596 -30.45563)
# 6 T21JYG 244 POINT (-53.98586 -30.45562)
# Raster (10x10 meters) info in data frame - crs +proj=utm +zone=22 +south +datum=WGS84 +units=m +no_defs
x <-c(213285,213295,213305,213315,213325,213335)
y <-c(6626955,6626955,6626955,6626955,6626955,6626955)
tile <- rep("T22JBM",6)
values <-c(336,355,363,426,341,308)
ras.ds2 <-data.frame(x,y,tile,values)
ras.ds2.sf <- st_as_sf(ras.ds2, coords = c("x", "y"), crs = 32722, agr = "constant")
ras.ds2.sf.ll <- st_transform(ras.ds2.sf, crs=4326)
ras.ds2.sf.ll
# Simple feature collection with 6 features and 2 fields
# Attribute-geometry relationship: 2 constant, 0 aggregate, 0 identity
# Geometry type: POINT
# Dimension: XY
# Bounding box: xmin: -53.98638 ymin: -30.45564 xmax: -53.98586 ymax: -30.45562
# Geodetic CRS: WGS 84
# tile values geometry
# 1 T21JYG 321 POINT (-53.98638 -30.45564)
# 2 T21JYG 249 POINT (-53.98628 -30.45563)
# 3 T21JYG 234 POINT (-53.98617 -30.45563)
# 4 T21JYG 238 POINT (-53.98607 -30.45563)
# 5 T21JYG 224 POINT (-53.98596 -30.45563)
# 6 T21JYG 244 POINT (-53.98586 -30.45562)
# Join information
ras.ds.sf.ll <- rbind(ras.ds1.sf.ll, ras.ds2.sf.ll)
ras.df.ll <- sf_to_df(ras.ds.sf.ll, fill = TRUE, unlist = NULL)
# Mean values by tile
ras.df.ll %>%
group_by(x,y) %>% dplyr::summarise(values=mean(values))
# `summarise()` has grouped output by 'x'. You can override using the `.groups` argument.
# # A tibble: 12 x 3
# # Groups: x [12]
# x y values
# <dbl> <dbl> <dbl>
# 1 -54.0 -30.5 321
# 2 -54.0 -30.5 249
# 3 -54.0 -30.5 234
# 4 -54.0 -30.5 238
# 5 -54.0 -30.5 224
# 6 -54.0 -30.5 244
# 7 -54.0 -30.5 336
# 8 -54.0 -30.5 355
# 9 -54.0 -30.5 363
# 10 -54.0 -30.5 426
# 11 -54.0 -30.5 341
# 12 -54.0 -30.5 308
# Nothing happened!!
# But if I try to change x and y values using accuracy
round_any = function(x, accuracy, f=round){f(x/ accuracy) * accuracy}
ras.df.ll2 <- ras.df.ll %>%
mutate(x = round_any(x, accuracy = 0.001),
y = round_any(y, accuracy = 0.001))
ras.df.ll2 %>%
group_by(x,y) %>% dplyr::summarise(values=mean(values))
`summarise()` has grouped output by 'x'. You can override using the `.groups` argument.
# # A tibble: 3 x 3
# # Groups: x [2]
# x y values
# <dbl> <dbl> <dbl>
# 1 -54.0 -30.5 252.
# 2 -54.0 -30.5 370
# 3 -54.0 -30.5 324.
# Hapens something but is wrong!!
请问，有什么方法可以使这个修正后的平均值提取？ 提前谢谢你 亚历山大
推荐答案
让我们首先注意到您编写的内容过于复杂。 我建议你这样做。
fst = function(data)
st_as_sf(data, coords = c("x", "y"),
crs = data$crs, agr = "constant") %>%
st_transform(crs=4326) %>%
sf_to_df(fill = TRUE, unlist = NULL)
df = tibble(
tile = rep(c("T21JYG", "T22JBM"), each = 6) %>% fct_inorder(),
values = c(321,249,234,238,224,244,336,355,363,426,341,308),
x = c(789385,789395,789405,789415,789425,789435,
213285,213295,213305,213315,213325,213335),
y = c(6626865,6626865,6626865,6626865,6626865,6626865,
6626955,6626955,6626955,6626955,6626955,6626955),
crs = rep(c(32721, 32722), each = 6)
) %>% group_by(tile) %>%
nest(data=x:crs) %>%
mutate(st = map(data, ~ fst(.x))) %>%
unnest(st) %>%
mutate(
x = x %>% plyr::round_any(accuracy = 0.001) %>% paste(),
y = y %>% plyr::round_any(accuracy = 0.001) %>% paste(),
) %>% group_by(x,y)
输出
# A tibble: 12 x 8
# Groups: x, y [3]
tile values data crs sfg_id point_id x y
<fct> <dbl> <list> <dbl> <int> <int> <chr> <chr>
1 T21JYG 321 <tibble [1 x 3]> 32721 1 1 -53.986 -30.456
2 T21JYG 249 <tibble [1 x 3]> 32721 1 1 -53.986 -30.456
3 T21JYG 234 <tibble [1 x 3]> 32721 1 1 -53.986 -30.456
4 T21JYG 238 <tibble [1 x 3]> 32721 1 1 -53.986 -30.456
5 T21JYG 224 <tibble [1 x 3]> 32721 1 1 -53.986 -30.456
6 T21JYG 244 <tibble [1 x 3]> 32721 1 1 -53.986 -30.456
7 T22JBM 336 <tibble [1 x 3]> 32722 1 1 -53.986 -30.455
8 T22JBM 355 <tibble [1 x 3]> 32722 1 1 -53.986 -30.455
9 T22JBM 363 <tibble [1 x 3]> 32722 1 1 -53.986 -30.455
10 T22JBM 426 <tibble [1 x 3]> 32722 1 1 -53.986 -30.455
11 T22JBM 341 <tibble [1 x 3]> 32722 1 1 -53.985 -30.455
12 T22JBM 308 <tibble [1 x 3]> 32722 1 1 -53.985 -30.455
但是，我完全不明白您在其中看到的不正确之处
df %>% dplyr::summarise(values=mean(values))
输出
# A tibble: 3 x 3
# Groups: x [2]
x y values
<chr> <chr> <dbl>
1 -53.985 -30.455 324.
2 -53.986 -30.455 370
3 -53.986 -30.456 252.
x、y组中values的mean。
明确你想要实现的目标。不要把它写在评论里，而是写在帖子的正文里！
嗯。我对函数st_as_sf、st_transform、sf_to_df一无所知。我不知道他们做了什么，也不知道如何解读他们的结果。然而，请注意，它们被放置在一个管道中(在我的fst函数中)，因此它们执行必要的计算，然后将结果相互传递。因此，这些结果必须是正确的。
可能问题在于您最初在st_as_sf函数中指定了两个不同的crs参数。为此，我将此变量放入tibble。但是，您只将crs = 4326的一个值传递给st_transform函数。也许这里还应该传达两个不同的值？
最后，当我将round_any函数中的accuracy设置为0.00025时，得到六个结果。
看看这些答案。
# A tibble: 6 x 3
# Groups: x [6]
x y values
<chr> <chr> <dbl>
1 -53.98525 -30.4555 308
2 -53.9855 -30.4555 377.
3 -53.98575 -30.4555 312.
4 -53.986 -30.45575 231
5 -53.98625 -30.45575 242.
6 -53.9865 -30.45575 321
总之，我向您展示了正确的编程方法。
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