Results

For each raw scene found in the specified scene folder, the Data Ingest and GCP Collection module creates a PCIDSK file with a system-generated file name in the specified output folder. Each file name contains a scene ID, a state (includes a _RAW tag in the file name), and a type, such as _PAN, _MS, or _PSH.

In addition to the output files, the module also creates a text file for each image that contains collected GCPs stored in a GCP segment. The file name of each of these text files is system-generated. The residuals reported in the text file are generated automatically after GCP collection.

The number of GCP segments created depends on various factors, such as GCP refinement, the number of GCPs collected, and the distribution of the GCPs, among others. In most cases, each image contains at least two model segments (either a rational function model or a satellite model). The first comes from the raw data itself, and the second is created after collecting the GCPs. A new model can then be computed based on the GCPs.

For each scene type in which GCPs were collected automatically, the Data Ingest and GCP Collection module creates an OrthoEngine project file. For example, when multispectral and panchromatic data is ingested, two project files, gcp-collection_RAW_MS.prj and gcp-collection_RAW_PAN.prj are created in the specified output folder.

In addition to the OrthoEngine project files, two other files are created for each scene type in the specified output folder. For example, with panchromatic data:

gcp-collection_RAW_PAN.summary.pix
gcp-collection_RAW_PAN.summary.txt

Known as "summary files", these files are created from all of the data in the output folder each time you run the Data Ingest and GCP Collection module (regardless of whether the Overwrite Results check box is clear).

Note: The summary files retain data from any previous GCP-collection task. That is, if you delete one or more of your input scenes, but not the corresponding output data, the summary files will still contain information on the deleted scenes when you run the Data Ingest and GCP Collection module. To avoid having data from a previous GCP-collection task in your summary files, first remove them from your output folder.

You can open the ingested scenes in CATALYST Professional Focus or OrthoEngine to perform QA tasks, or proceed to the next module in your workflow.

After successfully running this module, you will generally proceed to run:

Tie-Point Collection and Refinement module: for tie-point collection to improve relative accuracy between overlapping scenes
DEM Extraction module: uses the improved math model of stereo images to extract a digital surface model (DSM), digital terrain model (DTM), or both
Orthorectification module: uses the updated math model to orthorectify a set of images