README

General

This program applies an affine spatial transformation to project unprojected point data. This program will also simulate the locational uncertainty introduced through imprecise GPS point data through creating nsims realizations of the control points used for affine transformation.

Two files must be passed to the program:

1. Data file containing unique identifier for each point, an x coordinate, and a y coordinate. Other fields may be kept in the input file, but will not appear in the output file from this program. You can, of course, later join the projected coordinate to your other data associated with each point by joining on the unique identifier.

2. Control points file (see below for formatting requirements).

Output

This program returns two files:

1. A file with unprojected points projected to utm coordinates using affine transformation.

2. A file with nsims realizations of utm coordinates for each input point.

The simulated locations are based on the precision estimates for your projected points. Such data may be available for GPS coordinates collected using differential GPS. Normal distributions in the north and east directions are parameterized using the mean and se for mean. Draws from both normals then give a simulated location for the corner. An affine spatial transformation is then parameterized with the simulated corners. The parameterized affine transformation model is then used to project the unprojected data.

Dependencies

sklearn, numpy

Control Points File

A file containing projected and unprojected coordinates. Optionally, also contains measurements of precision in the projected coordinate space for the easting and northing.

Control Points CSV Input file header:

proj_e	proj_n	unproj_x	unproj_y

see test-control-points.csv for example.

OR

proj_e	proj_n	unproj_x	unproj_y	proj_e_se	proj_n_se

see test-control-points-with-precision.csv for example.

Variable name	Description
proj_e	projected easting (e) coordinate
proj_n	projected northing (y) coordinate
unproj_e	unprojected easting (e) coordinate
unproj_n	unprojected northing (y) coordinate
proj_e_se	projected easting (e) standard error
proj_n_se	projected northing (y) standard error

The example control points are in the projection WGS 1984 UTM Zone 17N (EPSG 32617) and an unprojected coordinate system.

Data File

Enter column names next to adjacent flags

For help on command line flags type

./afproj.py -h

The example data file is data.csv

Example call

Make sure the program permissions are set to executable chmod u+x afproj.py

Then run the program with the example data file and without simulation.

./afproj.py -c test-control-points.csv -u data.csv -x gx -y gy -i uid -o projected-data

Here is an example that will both project the unprojected data using the mean for each control point and also produce simulated locations for each data point using simulated control points.

./afproj.py -c test-control-points-with-precision.csv -u data.csv -x gx -y gy -i uid -n 1000 -o projected-data