transform_coord: Transform coordinates from/to WGS-84, GCJ-02 and BD-09...

In madlogos/asesgeo: ASES Analytic Toolkit on Geographics

Description

There are three commonly seen coordinate systems:

• WGS-84 is the gloabal coordinate system, typcially collected by GPS.
  

• GCJ-02 is the coordinate system mandated by Chinese Gov't.
  

• BD-09 is the coordinates system developed by Baidu Inc. that encrypts GCJ-02 further more.

The functions in this family encrypts coordinates from 'WGS-84' to 'GCJ-02' and 'BD-09', and decrypts them back vice versa. The built-in algorithm called by these functions is open source and comes with absolutely no ganrantee.

Usage

wgs_to_gcj(y, ..., force = FALSE, accurate_cn_bou = TRUE)

gcj_to_wgs(y, ..., force = FALSE, accurate_cn_bou = TRUE)

gcj_to_bd(y, ..., force = FALSE, accurate_cn_bou = TRUE)

bd_to_gcj(y, ..., force = FALSE, accurate_cn_bou = TRUE)

wgs_to_bd(y, ..., force = FALSE, accurate_cn_bou = TRUE)

bd_to_wgs(y, ..., force = FALSE, accurate_cn_bou = TRUE)

Arguments

y	one of coordinate pair: a list of coordinate vectors list(lat1, lon1), in which case you can provide other coordiante vectors in ... latitude vector: latitude number(s), in which case you need to provice longitute number(s) in ... coordinate matrix: a matrix (row 1-2 or col 1-2). The function will choose how to read the data coordinate data.frame: a data.frame (col 1-2)
...	one of coordinate pairs: when y is a list containing a coordinate pair (e.g., list(lat1, lon1)), you can pass other coordinate pairs here (e.g., list(lat2, lon2), list(lat3, lon3), ...). longitude vector: when y is only latitude vector, you can pass x (longitude) here. when y is a coordinate matrix or data.frame, ... is omitted.
force	logical, whether convert the coordinates regardless if they locate inside China. Default FALSE, indicating that only coordinates inside China will be converted.
accurate_cn_bou	logical, whether to convert the coordinates based on accurate China boundary. Only effective when api is NULL (local mode). Default TRUE. The WGS-84 ==> GCJ-02 conversion will only be conducted in coordinates inside China. When using the accurate China boundary, the function will check if the coordinates are actually inside China's territory. When set FALSE, the function will use a very vague rectangle to reprensent China boundary.

Value

A 2-col data.frame ([lng, lat]) of transformed coordinates. Note that points out of China will not have the coordinates converted.

Note

Latitude is the horizontal line serving as y-axis metric, longitude is the vertical line serving as x-axis metric.

Author(s)

Yiying Wang, [e-mail]

References

https://on4wp7.codeplex.com/SourceControl/changeset/view/21483#353936

See Also

• conv_coord() is a wrapper of these functions (local mode transforming functions) and conv_coord_api (api mode transforming function).
  

• asesgeo:::get_cn_bou(): a list of the 'accurate China boundary' in 'WGS-84', 'GCJ-02' and 'BD-09', which are all sp::SpatialPolygons objects.
  

• is_out_of_china(): how points are distinguished as in or out of China.

Examples

## Not run: 

## ========== wgs_to_gcj ==========

# Tiananmen square's WGS-84 coordinate is c(39.90734, 116.39089)
# http://www.google.cn/maps/place/Tiananmen,+Dongcheng,+Beijing/
# @39.90874,116.39713,16z?hl=en

## Single point
wgs_to_gcj(list(39.90734, 116.39089))  # or
wgs_to_gcj(39.90734, 116.39089)  # get
#           lat      lng
# [1,] 39.90874 116.3971

## Multiple points
### Coordinate pairs or Lat / Lon vectors
wgs_to_gcj(list(39.90734, 116.39089), list(39.90734, 116.39089))  # or
wgs_to_gcj(c(39.90734, 39.90734), c(116.39089, 116.39089))  # get
#           lat      lng
# [1,] 39.90874 116.3971
# [2,] 39.90874 116.3971

### Matrix
m <- matrix(c(39.90734, 116.39089, 39.90734, 116.39089, 39.90734, 
              116.39089), nrow=2)
m
#           [,1]      [,2]      [,3]
# [1,]  39.90734  39.90734  39.90734
# [2,] 116.39089 116.39089 116.39089

wgs_to_gcj(m)  # get
#           lat      lng
# [1,] 39.90874 116.3971
# [2,] 39.90874 116.3971
# [3,] 39.90874 116.3971

### data.frame
df <- data.frame(lat=c(39.90734, 39.90734, 39.90734, NA),
                 lon=c(116.39089, 116.39089, 116.39089, 116.39089))
wgs_to_gcj(df)  # get
#           lat      lng
# [1,] 39.90874 116.3971
# [2,] 39.90874 116.3971
# [3,] 39.90874 116.3971
# [4,]       NA       NA

## End(Not run)

## Not run: 

## ========== gcj_to_wgs ==========

# Tiananmen square's GCJ-02 coordinate is c(39.908746, 116.397131)
# http://www.openstreetmap.org/#map=19/39.90734/116.39089

## Single point
gcj_to_wgs(list(39.908746, 116.397131))  # or
gcj_to_wgs(39.908746, 116.397131)  # get
#           lat       lng
# [1,] 39.90734  116.3909

## Multiple points
### Coordinate pairs or lat / lon vectors
gcj_to_wgs(list(39.908746, 116.397131), list(39.908746, 116.397131))  # or
gcj_to_wgs(c(39.908746, 39.908746), c(116.397131, 116.397131))  # get
#           lat       lng
# [1,] 39.90734  116.3909
# [2,] 39.90734  116.3909

### Matrix
m <- matrix(c(39.908746, 116.397131, 39.908746, 116.397131, 39.908746, 
              116.397131), nrow=2)
m
#           [,1]       [,2]       [,3]
# [1,]  39.90875   39.90875   39.90875
# [2,] 116.39713  116.39713  116.39713
gcj_to_wgs(m)  # get
#           lat       lng
# [1,] 39.90734  116.3909
# [2,] 39.90734  116.3909
# [3,] 39.90734  116.3909

### data.frame
df <- data.frame(lat=c(39.908746, 39.908746, 39.908746, NA),
                 lon=c(116.397131, 116.397131, 116.397131, 116.397131))
gcj_to_wgs(df)  # get
#           lat       lng
# [1,] 39.90734  116.3909
# [2,] 39.90734  116.3909
# [3,] 39.90734  116.3909
# [4,]       NA        NA

## End(Not run)

## Not run: 

## ========== gcj_to_bd ==========

# Tiananmen square's GCJ-02 coordinate is c(39.908746, 116.397131)
#http://api.map.baidu.com/marker?location=39.91509,116.40350&title=Tiananmen&
 content=Tiananmen%20square&output=html

## Single point
gcj_to_bd(list(39.908746, 116.397131))  # or
gcj_to_bd(39.908746, 116.397131)  # get
#           lat       lng
# [1,] 39.91509  116.4035

## Multiple points
### Coordiante pairs or lat / lon vectors
gcj_to_bd(list(39.908746, 116.397131), list(39.908746, 116.397131))  # or
gcj_to_bd(c(39.908746, 39.908746), c(116.397131, 116.397131))  # get
#           lat       lng
# [1,] 39.91509  116.4035
# [2,] 39.91509  116.4035

### Matrix
m <- matrix(c(39.908746, 116.397131, 39.908746, 116.397131, 39.908746, 
              116.397131), nrow=2)
m
#           [,1]       [,2]       [,3]
# [1,]  39.90875   39.90875   39.90875
# [2,] 116.39713  116.39713  116.39713
gcj_to_bd(m)  # get
#           lat       lng
# [1,] 39.91509  116.4035
# [2,] 39.91509  116.4035
# [3,] 39.91509  116.4035

### data.frame
df <- data.frame(lat=c(39.908746, 39.908746, 39.908746, NA),
                 lon=c(116.397131, 116.397131, 116.397131, 116.397131))
gcj_to_bd(df)  # get
#           lat       lng
# [1,] 39.91509  116.4035
# [2,] 39.91509  116.4035
# [3,] 39.91509  116.4035
# [4,]       NA        NA

## End(Not run)

## Not run: 

## ========== bd_to_gcj ==========

# Tiananmen square's BD-06 coordinate is c(39.91509, 116.40350)
# http://www.google.cn/maps/place/Tiananmen,+Dongcheng,+Beijing/
# @39.90875,116.39713,16z?hl=en

## Single point
bd_to_gcj(list(39.91509, 116.40350))  # or
bd_to_gcj(39.91509, 116.40350)  # get
#           lat       lng
# [1,] 39.90875  116.3971

## Multiple points
### coordinate pairs or lat / lon vectors
bd_to_gcj(list(39.91509, 116.40350), list(39.91509, 116.40350))  # or
bd_to_gcj(c(39.91509, 39.91509), c(116.40350, 116.40350))  # get
#           lat       lng
# [1,] 39.90875  116.3971
# [2,] 39.90875  116.3971

### Matrix
m <- matrix(c(39.91509, 116.40350, 39.91509, 116.40350, 39.91509, 
              116.40350), nrow=2)
m
#           [,1]       [,2]       [,3]
# [1,]  39.91509   39.91509   39.91509
# [2,] 116.40350  116.40350  116.40350
bd_to_gcj(m)  # get
#           lat       lng
# [1,] 39.90875  116.3971
# [2,] 39.90875  116.3971
# [3,] 39.90875  116.3971

### data.frame
df <- data.frame(lat=c(39.91509, 39.91509, 39.91509, NA),
                 lon=c(116.40350, 116.40350, 116.40350, 116.40350))
bd_to_gcj(df)  # get
#           lat       lng
# [1,] 39.90875  116.3971
# [2,] 39.90875  116.3971
# [3,] 39.90875  116.3971
# [4,]       NA        NA

## End(Not run)

## Not run: 

## ========== wgs_to_bd ==========

# Tiananmen square's WGS-84 coordinate is c(39.90734, 116.39089)
# http://api.map.baidu.com/marker?location=39.91509,116.40350&title=
# Tiananmen&content=Tiananmen%20square&output=html

## Single point
wgs_to_bd(list(39.90734, 116.39089))  # or
wgs_to_bd(39.90734, 116.39089)  # get
#           lat       lng
# [1,] 39.91508  116.4035

## Multiple points
### Coordinate pairs or lat / lon vectors
wgs_to_bd(list(c(39.90734, 116.39089), c(39.90734, 116.39089)))  # or
wgs_to_bd(c(39.90734, 39.90734), c(116.39089, 116.39089))  # get
#           lat       lng
# [1,] 39.91508  116.4035
# [2,] 39.91508  116.4035

### Matrix
m <- matrix(c(39.90734, 116.39089, 39.90734, 116.39089, 39.90734, 
              116.39089), nrow=2)
m
#           [,1]       [,2]       [,3]
# [1,]  39.90734   39.90734   39.90734
# [2,] 116.39089  116.39089  116.39089
wgs_to_bd(m)  # get
#           lat       lng
# [1,] 39.91508  116.4035
# [2,] 39.91508  116.4035
# [3,] 39.91508  116.4035

### data.frame
df <- data.frame(lat=c(39.90734, 39.90734, 39.90734, NA),
                 lon=c(116.39089, 116.39089, 116.39089, 116.39089))
wgs_to_bd(df)  # get
#           lat       lng
# [1,] 39.91508  116.4035
# [2,] 39.91508  116.4035
# [3,] 39.91508  116.4035
# [4,]       NA        NA

## End(Not run)

## Not run: 

## ========== bd_to_wgs ==========

# Tiananmen square's BD-06 coordinate is c(39.91509, 116.40350)
# http://www.openstreetmap.org/#map=19/39.90734/116.39089

## Single point
bd_to_wgs(list(39.91509, 116.40350))  # or
bd_to_wgs(39.91509, 116.40350)  # get
#           lat       lng
# [1,] 39.90734  116.3909

## Multiple points
### Coordinate pairs or lat / lon vectors
bd_to_wgs(list(39.91509, 116.40350), list(39.91509, 116.40350))  # or
bd_to_wgs(c(39.91509, 39.91509), c(116.40350, 116.40350))  # get
#           lat       lng
# [1,] 39.90734  116.3909
# [2,] 39.90734  116.3909

### Matrix
m <- matrix(c(39.91509, 116.40350, 39.91509, 116.40350, 39.91509, 
              116.40350), nrow=2)
m
#           [,1]       [,2]       [,3]
# [1,]  39.90734   39.90734   39.90734
# [2,] 116.39089  116.39089  116.39089
bd_to_wgs(m)  # get
#           lat       lng
# [1,] 39.90734  116.3909
# [2,] 39.90734  116.3909
# [3,] 39.90734  116.3909

### data.frame
df <- data.frame(lat=c(39.91509, 39.91509, 39.91509, NA),
                 lon=c(116.40350, 116.40350, 116.40350, 116.40350))
bd_to_wgs(df)  # get
#           lat       lng
# [1,] 39.90734  116.3909
# [2,] 39.90734  116.3909
# [3,] 39.90734  116.3909
# [4,]       NA        NA

## End(Not run)

madlogos/asesgeo documentation built on Aug. 9, 2019, 9:53 a.m.