RPC Orthorectification Using Reference Image

This tool performs a refined orthorectification by automatically generating ground control points (GCPs) from a reference image. This is a fully automated end-to-end solution if you have a reference image. Use the RPC Orthorectification workflow instead if you want to edit GCPs and review error statistics in an interactive environment.

You can also write a script to perform RPC Orthorectification using the RPCOrthorectificationUsingReferenceImage task.

Follow these steps:

1. From the Toolbox, select Geometric Correction > Orthorectification > RPC Orthorectification Using Reference Image.
2. Select any supportedInput Raster that contains a community sensor model (CSM) or rational polynomial coefficient (RPC) sensor model.
3. Select an Input Reference Raster. This is typically an orthorectified reference image with the same or slightly higher spatial resolution than the input raster. Here are some examples:
   • For the United States: U.S. Department of Agriculture National Agriculture Imagery Program (NAIP), Digital Orthophoto Quadrangles (DOQs), or High-resolution Orthoimagery. Download data from the U.S. Geological Survey National Map and Download Platform or EarthExplorer, then use the Seamless Mosaic tool to create a mosaic of individual tiles.
   • Controlled image base (CIB)

Try to choose a reference image that is close to the year and season of the input image. Automatic GCP generation is based on image matching between the reference and source images, so the scene contents should not be vastly different. Automatic GCP generation is more robust if the reference image and input image have similar resolution. If the reference image has a much higher resolution than the input image (i.e., the ratio is greater than 2.5), consider down-sampling the reference image first.

• To change it, click the Browse button and select a different coordinate system.
• Click the From Dataset button to use the coordinate system of en existing raster dataset.
• Click the Current View button to use the coordinate system established in the current view.
• Click the Reset button to clear the Output Coordinate System field.

• Nearest Neighbor: Uses the nearest pixel without any interpolation.
• Bilinear: (default) Performs a linear interpolation using four pixels to resample.
• Cubic Convolution: Uses 16 pixels to approximate the sinc function using cubic polynomials to resample the image.

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