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HK80(Hong Kong 1980 Grid System)是香港的一种坐标系(EPSG:2326),一般用于地图绘制、工程勘测、树木调查等。不过,生态学研究中最常用的坐标系为WGS84(EPSG:4326),例如GPS一般就是直接给出WGS84的经纬度,Google Earth等也用WGS84坐标系。那么HK80坐标如何转换为WGS84坐标呢?
香港地政署测绘处给出了测量基准说明(https://www.geodetic.gov.hk/common/data/pdf/explanatorynotes_c.pdf), 其中有非常详细的转换公式。根据这些公式,本人曾于2014年编写了HK80 R程序包(https://cran.r-project.org/web/packages/HK80/index.html)。
近几年来,也有不少新工具诞生:例如,香港地政署测绘处的HK80坐标在线转换工具(https://www.geodetic.gov.hk/en/services/tform/tform.aspx )公开了API,该API可以根据用户在网址中传入的参数返回json数据。sf程序包也在proj程序包的基础上开发了st_transform函数,让不同坐标系之间的转换变得非常方便。也有人基于pyproj(https://pyproj4.github.io/pyproj/stable/#,https://proj.org/)开发了hk80 python程序包(https://pypi.org/project/hk80/)等。
本文给出在R中进行WGS84和HK80坐标相互转换的三种方法,其中首选为香港地政署的在线转换工具,但是由于服务器可能会有一定的限制,如果有大量数据需要准换,访问会较为频繁,用户IP可能受限。下载到本地的sf和HK80程序包就没有这些限制。sf和HK80的程序包的结果都是可靠的。相比之下,在sf中建立坐标点并进行转换批量转换更为方便。HK80程序包的结果可以作为参考。
地理坐标转换常涉及度、分、秒和十进制的转换,本文也给出两种方法,作为附录,以方便读者。
library(HK80) HK1980GRID_TO_WGS84GEO(N = 820359.389, E = 832591.320)
## latitude longitude ## 1 22.32225 114.1412
the Geodetic Survey Section, Lands Department, Hong Kong SAR Gov.
API example: http://www.geodetic.gov.hk/transform/v2/?inSys=hkgrid&e=832591.320&n=820359.389
library(jsonlite)data1 <- fromJSON(" names(data1)
## [1] "wgsLat" "wgsLong" "hkLat" "hkLong" "utmGridZone" ## [6] "utmGridE" "utmGridN" "utmRefZone" "utmRefE" "utmRefN"
data1$wgsLat
## [1] 22.32224
data1$wgsLong
## [1] 114.1412
library(sf)
## Linking to GEOS 3.8.1, GDAL 3.1.1, PROJ 6.3.1
p1 = st_point(c(832591.320, 820359.389)) sfc = st_sfc(p1, crs = 2326) (st_transform(sfc, 4326))
## Geometry set for 1 feature ## geometry type: POINT ## dimension: XY ## bbox: xmin: 114.1412 ymin: 22.32224 xmax: 114.1412 ymax: 22.32224 ## geographic CRS: WGS 84
## POINT (114.1412 22.32224)
library(HK80) WGS84GEO_TO_HK1980GRID(latitude = 22.32224, longitude = 114.14118)
## N E ## 1 820358.7 832591.4
from the Geodetic Survey Section, Lands Department, Hong Kong SAR Gov.
# Copy the following URL to browser # # {"hkN": 820358.910,"hkE": 832590.508,"hkpd": 26.009} library(jsonlite) data1 <- fromJSON(" names(data1)
## [1] "hkN" "hkE" "hkpd"
data1$hkN
## [1] 820358.9
data1$hkE
## [1] 832590.5
library(sf) p1 = st_point(c(114.14118, 22.32224)) sfc = st_sfc(p1, crs = 4326) (ccc <- st_transform(sfc, 2326))
## Geometry set for 1 feature ## geometry type: POINT ## dimension: XY ## bbox: xmin: 832590.5 ymin: 820358.9 xmax: 832590.5 ymax: 820358.9 ## projected CRS: Hong Kong 1980 Grid System
## POINT (832590.5 820358.9)
library(sp) dd2dms(114.14118) # decimal to Degree, Minute, Second format
## [1] 114d8'28.248"E
as.numeric(dd2dms(114.14118)) #
## [1] 114.1412
char2dms("47d15'6.12\"E")
## [1] 47d15'6.12"E
as.numeric(char2dms("47d15'6.12\"E"))
## [1] 47.2517
library(biogeo) res <- dms2dd(47,15,6.12,"E") # ns letters (N,S,E,W) print(res)
## [1] 47.2517
dd2dmslong(114.14118)
## xdeg xmin xsec EW ## 1 114 8 28.2 E
dd2dmslat(22.32224)
## ydeg ymin ysec NS ## 1 22 19 20.1 N
Ooms J. (2014). The jsonlite Package: A Practical and Consistent Mapping Between JSON Data and R Objects. arXiv:1403.2805 [stat.CO] URL https://arxiv.org/abs/1403.2805.
Zhang J. (2016). HK80: Conversion Tools for HK80 Geographical Coordinate System. R package version 0.0.2. https://CRAN.R-project.org/package=HK80
Robertson M. (2016). biogeo: Point Data Quality Assessment and Coordinate Conversion. R package version 1.0. https://CRAN.R-project.org/package=biogeo
Pebesma, E., (2018). Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10 (1), 439-446, https://doi.org/10.32614/RJ-2018-009
Roger S. Bivand, Edzer Pebesma, Virgilio Gomez-Rubio,(
2013) Applied spatial data analysis with R, Second edition. Springer, NY. https://asdar-book.org/
https://pypi.org/project/hk80/
https://spatialreference.org/ref/?search=Hong+Kong
https://www.geodetic.gov.hk/en/download.htm
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