Table of Contents
Last updated: 29 February, 2016
Flags (also called masks) are identifiers of specific issues with the data, such as saturated pixels or a possible spur, that can affect the quality of the final product. Flags are applied by the pipeline and used to identify potentially problematic data, and to make a caution during its processing.
A data flag has a defined name and a value, which specifies the nature of the flag. These flags are divided into two categories depending on whether they apply to an individual channel (pixel), or to a complete Dataframe. They are called channel flags and column rowflags, respectively. There are also Quality Flags which are found in the Quality Product in the ObservationContext and are used to provide you with means to make a quick assessment of the quality of your data. They are described in Section 10.4.