将纬度和经度点转换为 UTM

Question

我找到了一个相当简单的示例来说明如何执行此操作，但我无法让它为我工作。我对 R 很陌生

library(rgdal) 
xy <- cbind(c(118, 119), c(10, 50)) 
project(xy, "+proj=utm +zone=51 ellps=WGS84") 
          [,1]    [,2] 
[1,] -48636.65 1109577 
[2,] 213372.05 5546301

但这是示例数字。我有数千个坐标需要转换，但我不知道如何将它们从我的表中获取到这个脚本中

我的数据集有 3 列，ID、X 和 Y。如何使用这个等式转换它们？我已经坚持了好几个星期了

Answer 1

在您的问题中，您不清楚您是否已经将数据集读入 data.frame 或矩阵。所以我假设在下面你有你的数据集在一个文本文件中：

# read in data
dataset = read.table("dataset.txt", header=T)

# ... or use example data
dataset = read.table(text="ID X Y
1 118 10
2 119 50
3 100 12
4 101 12", header=T, sep=" ")

# create a matrix from columns X & Y and use project as in the question
project(as.matrix(dataset[,c("X","Y")]), "+proj=utm +zone=51 ellps=WGS84")
#             [,1]    [,2]
# [1,]   -48636.65 1109577
# [2,]   213372.05 5546301
# ...

更新：

cmets 表明问题来自于将project() 应用于data.frame。 project() 不适用于 data.frames，因为它会检查 is.numeric()。因此，您需要将数据转换为矩阵，如我上面的示例所示。如果您想坚持使用 cbind() 的代码，您必须执行以下操作：

 X <- dd[,"X"]
 Y <- dd[,"Y"]
 xy <- cbind(X,Y) 

dd["X"] 和 dd[,"X"] 之间的区别在于后者不会返回 data.frame，因此cbind() 将产生一个矩阵而不是一个 data.frame。

Answer 2

为确保在与坐标相关的每个步骤中都有适当的投影元数据，我建议尽快将这些点转换为 SpatialPointsDataFrame 对象。

有关如何将简单的 data.frames 或矩阵转换为 SpatialPointsDataFrame 对象的更多信息，请参阅 ?"SpatialPointsDataFrame-class"。

library(sp)
library(rgdal)

xy <- data.frame(ID = 1:2, X = c(118, 119), Y = c(10, 50))
coordinates(xy) <- c("X", "Y")
proj4string(xy) <- CRS("+proj=longlat +datum=WGS84")  ## for example

res <- spTransform(xy, CRS("+proj=utm +zone=51 ellps=WGS84"))
res
#            coordinates ID
# 1 (-48636.65, 1109577)  1
# 2    (213372, 5546301)  2

## For a SpatialPoints object rather than a SpatialPointsDataFrame, just do: 
as(res, "SpatialPoints")
# SpatialPoints:
#              x       y
# [1,] -48636.65 1109577
# [2,] 213372.05 5546301
# Coordinate Reference System (CRS) arguments: +proj=utm +zone=51
# +ellps=WGS84 

Answer 3

将经纬度点转换为 UTM

library(sp)
library(rgdal)

#Function
LongLatToUTM<-function(x,y,zone){
 xy <- data.frame(ID = 1:length(x), X = x, Y = y)
 coordinates(xy) <- c("X", "Y")
 proj4string(xy) <- CRS("+proj=longlat +datum=WGS84")  ## for example
 res <- spTransform(xy, CRS(paste("+proj=utm +zone=",zone," ellps=WGS84",sep='')))
 return(as.data.frame(res))
}

# Example
x<-c( -94.99729,-94.99726,-94.99457,-94.99458,-94.99729)
y<-c( 29.17112, 29.17107, 29.17273, 29.17278, 29.17112)
LongLatToUTM(x,y,15)

Answer 4

基于上面的代码，我还添加了一个版本的区域和半球检测（解决转换问题，如某些 cmets 中所述）+ CRS 字符串的简写并转换回 WSG86：

library(dplyr)
library(sp)
library(rgdal)
library(tibble)

find_UTM_zone <- function(longitude, latitude) {

 # Special zones for Svalbard and Norway
    if (latitude >= 72.0 && latitude < 84.0 ) 
        if (longitude >= 0.0  && longitude <  9.0) 
              return(31);
    if (longitude >= 9.0  && longitude < 21.0)
          return(33)
    if (longitude >= 21.0 && longitude < 33.0)
          return(35)
    if (longitude >= 33.0 && longitude < 42.0) 
          return(37)

    (floor((longitude + 180) / 6) %% 60) + 1
}


find_UTM_hemisphere <- function(latitude) {

    ifelse(latitude > 0, "north", "south")
}

# returns a DF containing the UTM values, the zone and the hemisphere
longlat_to_UTM <- function(long, lat, units = 'm') {

    df <- data.frame(
        id = seq_along(long), 
        x = long, 
        y = lat
    )
    sp::coordinates(df) <- c("x", "y")

    hemisphere <- find_UTM_hemisphere(lat)
    zone <- find_UTM_zone(long, lat)

    sp::proj4string(df) <- sp::CRS("+init=epsg:4326") 
    CRSstring <- paste0(
        "+proj=utm +zone=", zone,
        " +ellps=WGS84",
        " +", hemisphere,
        " +units=", units)
    if (dplyr::n_distinct(CRSstring) > 1L) 
        stop("multiple zone/hemisphere detected")

    res <- sp::spTransform(df, sp::CRS(CRSstring[1L])) %>%
        tibble::as_data_frame() %>%
        dplyr::mutate(
            zone = zone,
            hemisphere = hemisphere
        )

    res
}

UTM_to_longlat <- function(utm_df, zone, hemisphere) {

    CRSstring <- paste0("+proj=utm +zone=", zone, " +", hemisphere)
    utmcoor <- sp::SpatialPoints(utm_df, proj4string = sp::CRS(CRSstring))
    longlatcoor <- sp::spTransform(utmcoor, sp::CRS("+init=epsg:4326"))
    tibble::as_data_frame(longlatcoor)
}

其中CRS("+init=epsg:4326") 是CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs +towgs84=0,0,0") 的简写。

查找 UTM 区域引用：http://www.igorexchange.com/node/927

Answer 5

关于示例，给定坐标的默认 UTM 区域为 50。不建议将坐标投影到较远的区域。您可以使用来自 NOAA 的 NCAT tool 检查转换。

下面的代码使用sf 包进行转换。

library(sf)
library(tidyverse)

# Coordinate examples with expected UTM values
coord_sample <- data.frame(
  "Northing" = c(1105578.589, 5540547.370),
  "Easting" = c(609600.773, 643329.124),
  "Latitude" = c(10, 50),
  "Longitude" = c(118, 119))

#' Find UTM EPSG code from Latitude and Longitude coordinates (EPSG 4326 WGS84)
#' (vectorised)
#' Source: https://geocompr.robinlovelace.net/reproj-geo-data.html
#' Source: https://gis.stackexchange.com/questions/13291/computing-utm-zone-from-lat-long-point
LatLonToUTMEPSGCode <- function(lat, lon) {

  zone_number <- (floor((lon + 180) / 6) %% 60) + 1

  # Special zones for Norway
  cond_32 <- lat >= 56.0 & lat < 64.0 & lon >= 3.0 & lon < 12.0
  zone_number[cond_32] <- 32

  # Special zones for Svalbard
  cond_lat <- lat >= 72.0 & lat < 84.0

  cond_31 <- cond_lat & lon >= 0.0 & lon <  9.0
  zone_number[cond_31] <- 31

  cond_33 <- cond_lat & lon >= 9.0 & lon < 21.0
  zone_number[cond_33] <- 33

  cond_35 <- cond_lat & lon >= 21.0 & lon < 33.0
  zone_number[cond_35] <- 35

  cond_37 <- cond_lat & lon >= 33.0 & lon < 42.0
  zone_number[cond_37] <- 37

  # EPSG code
  utm <- zone_number
  utm[lat > 0] <- utm[lat > 0] + 32600
  utm[lat <= 0] <- utm[lat <= 0] + 32700

  return(utm)
}

sf_sample <- sf::st_as_sf(coord_sample, coords = c("Longitude", "Latitude"),
                          crs = 4326)

sf_sample %>%
  do(cbind(., st_coordinates(.))) %>%
  mutate(EPSG = LatLonToUTMEPSGCode(lat = Y, lon = X)) %>%
  group_by(EPSG) %>%
  do(cbind(as.data.frame(.) %>% select(Northing, Easting),
           st_coordinates(st_transform(., crs = head(.$EPSG, 1))))) %>%
  ungroup()

您可以通过与预期值比较来检查转换：

# A tibble: 2 x 5
   EPSG Northing Easting      X       Y
  <dbl>    <dbl>   <dbl>  <dbl>   <dbl>
1 32650  1105579  609601 609601 1105579
2 32650  5540547  643329 643329 5540547