Satellite altimetry data
Trajectory files are composed of a series of points measured along the orbital path of a satellite. This data is similar to a multidimensional dataset in which multiple trajectory files form dimensions or slices, and variables contain the type of scientific measurement acquired by the satellite.
One of the main sources for this type of data is satellite altimetry. Satellite altimeters are used to track changes in sea surface height, sea ice thickness, and glacier topography by sampling points along the sensor trajectory and storing them as a netCDF or HDF file.
A trajectory dataset is a geodatabase that manages a collection of trajectory files. It contains a polygon feature table that stores the spatial extent or footprint of each trajectory file, along with sensor properties, such as start time, end time, and the measurement or variable names. The trajectory data points are referenced on the fly by the trajectory footprints. This allows access to large volumes of point data without the need for data conversion. Supported sensors include Sentinel-3 (SRAL), Sentinel-6, CryoSat and Icesat-2 sensors.
A trajectory layer allows you to visualize trajectory data in a map or scene. It includes a polygon feature layer that represents the trajectory footprints and a point feature layer that displays the measurement points. Each trajectory layer references a dense set of points from the input trajectory files.
A trajectory type defines sensor-specific properties for each dataset. These properties allow you to filter trajectory files using unique keyword pairs. For a list of variable keywords for each sensor, see Trajectory type properties. You can filter trajectory files using the following keywords:
- ProductFilter—Specifies the type of product or product level. Some sensors include multiple product levels, such as Reduced, Standard, and Advanced.
- Frequency—Specifies the frequency band. Trajectory files can contain data collected at different frequencies.
- PredefinedVariables—Specifies a common measurement type. The same type of measurement acquired by different sensors can be stored under different variable names. This allows you to manage and integrate data from multiple sensors.
- Variables—Specifies the type of measurements. Variable names are often unique for each sensor.