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Batch Reprojection

Reprojection is an essential process for aligning, transforming, and reassigning spatial datasets from one coordinate system to another. CATALYST software offers the REPROJ algorithm, which allows users to convert between projections in a supported GDB format and known datums. When working with larger datasets, it may be tedious to reproject the data individually. CATALYST Professional has different tools to enable batch/mass processing and cut back on manual workflows over several files. Although there is no inherent batch reprojection algorithm, users can still mass reproject their data using the CATALYST Python API or Modeler.

Table of Contents

1. Batch Reprojection Using Python

Batch reprojection in Python involves a script that loops through the input folder, applying the REPROJ algorithm to each data file. The code block below shows an example of how to run the REPROJ algorithm iteratively through a folder in Python. This example scales up the reprojection recipe found in our Python Cookbook to a batch application.

from pci.reproj import reproj
import os

indir = os.path.join(os.getcwd(), "Input")          # Input file directory
outdir = os.path.join(os.getcwd(), "Output")        # Output file directory

resolution = [10, 10]
map_units = "UTM 11 D000" # Output will be longitude and latitude with NAD83 Ellipse

for file in os.listdir(indir):
    infile = os.path.join(indir, file)
    outfile = os.path.join(outdir, file)
    reproj(fili=infile, dbic=[1], filo=outfile, repmeth="BR", pxsz=resolution, mapunits=map_units)

2. Batch Reprojection Using Modeler

Modeler is another useful tool for batch processing data. With reprojection, ensure that all the input files have the same number of raster channels

  1. In the CATALYST Professional toolbar, open Modeler
  2. Add the IMPORT module to the canvas - Right-click the canvas > Common Modules > Import > Click anywhere on the canvas.
  3. Open the Import Module Control Panel (MCP) and select Batch to view the batch parameter sets.
  4. In the Batch Parameter Sets table, right-click the File column heading and select Add Files.
  5. With the File Selector window open, navigate to the folder with your input data and select all the files (CTRL + A) and click Open.
  6. In the table, click the box to the left of the File column heading to select all the files. In the Input Params 1 section, check the Raster layers checkbox. This applies this selection to all files.
    Note: All the files should have the same number of channels. Otherwise, in the Batch Parameters set, click through each file to adjust the raster channels.
  7. Load the REPROJ module to the canvas: Algorithm Librarian > REPROJ > Add to Canvas > Click on the canvas.
  8. Double-click on the module to set the output projection
    <INSERT reproj window IMAGE>
  9. Load the EXPORT module to the canvas: Right-click canvas > Common Modules > Export > Click on the canvas.
  10. Open the EXPORT MCP and set the output directory:
    • Click Batch >>
    • Right-click the File column heading and select From Input Module... > keep the default values
      • Input Module = IMPORT:0
      • File Parameter = Filename
    • Select all the files by clicking the box to the left of the File column heading
    • Right-click the File column heading again and select Change Directory.
    • Navigate to the output directory and select OK
    • Select Accept.
  11. Connect the modules:
    • Connect the Raster Port from IMPORT to the Input Layers port for REPROJ
    • Connect the Output Layer port from REPROJ to the Mixed Port for EXPORT
  12. Your model should look like this:
  13. Click the Run Batch button on the toolbar

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