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Create cloud, haze, and water masks from satellite imagery
Loading libraries and defining locale environment. This isnt extremely accurate but allows masking in order to avoid overcorrection at a later stage. Note however that you might need another lowpass filtering run to reduce artefacts that originate often from edges in your DEM. ATCOR allows users to prepare their data for analysis, such as GCP collection, segmentation, classification, or extraction of vegetation indices.
Jena Copter Laboratories
Input1: Blue or green image channel 0. The image channel in the input file that contains the blue sensor band. If the blue band is not available, the green band can be used instead. The image channel in the input file that contain the shortwave infrared SWIR sensor band. This parameter specifies, potentially with the value of Source Background Values , which pixels in the source image are to be considered background NoData pixels. In general, if a pixel is considered NoData, the application handles the pixel in a specific manner.
I learned a basic trick when masking that helped me out. It will be a duh to some of you, but for me, I was happy to figure it out. Say you have some close up pine trees and distant very hazy forest behind, and you want to clear the haze. So, you are drawing a mask around the branches of the near pines.