Python地理空间坐标格式转换 [英] Python Geo-Spatial Coordinate Format Conversion

问题描述

我有一个包含6列坐标对的数据框:度|分钟|秒(对于纬度和经度).这就是NAD83格式.我想将它们转换为只有2列的十进制格式的新数据框，称为NAD27.

I have a dataframe containing 6 columns of coordinate pairs: Degrees|Minutes|Seconds (for both latitude and longitude). This is known as the NAD83 format. I want to convert these into a new dataframe of only 2 columns in decimal format, known as NAD27.

我通常使用的库geopy实际上支持每种格式，因此实际上没有专用的转换功能.我在这里仔细阅读了文档，以确保: https://geopy.readthedocs.io/en/1.10.0/

The library I typically use, geopy supports virtually every format, so there actually isn't a dedicated conversion function. I went through the documentation here to be sure: https://geopy.readthedocs.io/en/1.10.0/

python还有其他转换为NAD27的方法吗?

Does python have any other means to convert to NAD27?

感谢您阅读

推荐答案

让我们假设您的DataFrame df 包含列 lonD ， lonM ， lonS ， latD ， latM 和 latS .然后，应该在内部使用 geopandas ， shapely 和 pyproj 进行以下操作.

Let's suppose your DataFrame df contains columns lonD, lonM, lonS, latD, latM and latS. Then the following should work, using geopandas, shapely and pyproj internally.

import geopandas as gpd
import numpy as np
from shapely.geometry import Point

def dms_to_dec(d, m, s):
    sign = np.sign(d)
    return d + sign * m / 60 + sign * s / 3600

points = df.apply(lambda row: Point(dms_to_dec(*row[['lonD', 'lonM', 'lonS']]), 
                                    dms_to_dec(*row[['latD', 'latM', 'latS']])),
                  axis=1)
gdf_nad83 = gpd.GeoDataFrame(df, geometry=points, crs={'init': 'EPSG:4269'})
gdf_nad27 = gdf_nad83.to_crs({'init': 'EPSG:4267'})

这篇关于Python地理空间坐标格式转换的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！