pyproj conversion UTM to lat/long out by 3 deg

Question

I am reading UTM point data from a shape file. The geopandas CRS string associated with the shape file is:

PROJCS["WGS 84 / Falk",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-60],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH]]

I convert the point data to lat/long using pyproj:

projn = pyproj.Proj('+proj=utm +zone=21 +south +ellps=WGS84 +datum=WGS84 +units=m +no_defs +lon_0=-60')
ylon, ylat = projn(utm_e, utm_n, inverse=True)

This gives me the correct latitude but the longitude is exactly 3 degrees out. I changed the UTM zone to utm=+20 but now am 3 degress out in the other direction. I also tried setting the false easting with x_0=500000 and the central longitude with lon_0=-60 but that made no difference. Finally, I tried setting a projection system using one of the EPSG settings in the CRS string eg

projn = pyproj.CRS.from_epsg(6326)

but that gave the error message CRSError: Invalid projection: epsg:6326: (Internal Proj Error: proj_create: crs not found). Would appreciate any suggestions as I am new to GIS and finding it difficult to understand projections. An illustration of the problem is shown below:

import pyproj

# Define points to process

well_dict = {}
well_dict['14/09-1']  = [-59.384869, -49.319319, 544706.1998681703, 4536872.299629836]
well_dict['14/09-2']  = [-59.349633, -49.247411, 547331.1995800878, 4544831.399531693]
well_dict['14/10-1']  = [-59.176736, -49.275033, 559882.9998544991, 4541663.299837932]
well_dict['14/13-1']  = [-59.496483, -49.417692, 536519.4998223917, 4525987.899903225]
well_dict['14/05-1A'] = [-59.177950, -49.162275, 559930.8995227005, 4554179.299983081]
well_dict['14/24-1']  = [-59.297611, -49.812692, 550533.2498328319, 4481958.129964017]

# Define projections

projns = {}
projns['base'] = pyproj.Proj('+proj=utm +zone=21 +south +ellps=WGS84 +datum=WGS84 +units=m +no_defs +lon_0=-60')
projns['6326'] = pyproj.CRS.from_epsg(6326) #FIXME: gives CRSerror
# projns['6326'] = pyproj.Proj('epsg:6326')
# projns['7030'] = pyproj.Proj('epsg:7030')
# projns['9001'] = pyproj.Proj('epsg:9001')

# Convert UTMs for each well to lat/long using each projection

for well in well_dict:
    xlon, xlat, utm_e, utm_n = well_dict[well]
    print("%-9s  %10.2f %10.2f  %7.3f %7.3f" % (well, utm_e, utm_n, xlat, xlon), end='')    
    
    for pname in projns:
        projn = projns[pname]
        ylon, ylat = projn(utm_e, utm_n, inverse=True)
        print("  %7.3f %7.3f" % (ylat, ylon), end='')
        
    print("")

EDIT: After further investigation I found that I should have been using the Transverse Mercator projection, not Universal Transverse Mercator. If I use:

projns['tmerc'] = pyproj.Proj('+proj=tmerc +lat_0=0 +lon_0=-60 +k=0.9996 +x_0=500000 +y_0=10000000 +datum=WGS84 +units=m +no_defs')

then the points plot in the correct position.

Answer 1

Recommendations:

• Use Transformer (https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1)
• The WKT can be used as input directly

import pyproj


wkt = 'PROJCS["WGS 84 / Falk",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",-60],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",10000000],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH]]'
transformer = pyproj.Transformer.from_crs(wkt, "EPSG:4326", always_xy=True)
# Define points to process

well_dict = {}
well_dict['14/09-1']  = [-59.384869, -49.319319, 544706.1998681703, 4536872.299629836]
well_dict['14/09-2']  = [-59.349633, -49.247411, 547331.1995800878, 4544831.399531693]
well_dict['14/10-1']  = [-59.176736, -49.275033, 559882.9998544991, 4541663.299837932]
well_dict['14/13-1']  = [-59.496483, -49.417692, 536519.4998223917, 4525987.899903225]
well_dict['14/05-1A'] = [-59.177950, -49.162275, 559930.8995227005, 4554179.299983081]
well_dict['14/24-1']  = [-59.297611, -49.812692, 550533.2498328319, 4481958.129964017]

# Define projections

# Convert UTMs for each well to lat/long using each projection

for well in well_dict:
    xlon, xlat, utm_e, utm_n = well_dict[well]
    print("%-9s  %10.2f %10.2f  %7.3f %7.3f" % (well, utm_e, utm_n, xlat, xlon), end='')    
    ylon, ylat = transformer.transform(utm_e, utm_n)
    print("  %7.3f %7.3f" % (ylat, ylon))

Output:

14/09-1     544706.20 4536872.30  -49.319 -59.385  -49.319 -59.385
14/09-2     547331.20 4544831.40  -49.247 -59.350  -49.247 -59.350
14/10-1     559883.00 4541663.30  -49.275 -59.177  -49.275 -59.177
14/13-1     536519.50 4525987.90  -49.418 -59.496  -49.418 -59.496
14/05-1A    559930.90 4554179.30  -49.162 -59.178  -49.162 -59.178
14/24-1     550533.25 4481958.13  -49.813 -59.298  -49.813 -59.298