A Fast Dense Feature Tracking Routine with its Application in Cryosphere Remote Sensing Using Sentinel-1 and Landsat-8 Data
- Creators
- Lei, Yang
- Gardner, Alex
- Agram, Piyush
Abstract
In this paper, we present a fast and intelligent routine for dense feature tracking with almost two orders of magnitude runtime improvement over conventional dense cross-correlation techniques. This routine consists of two novel modules: 1) "autoRIFT", an efficient and intelligent dense cross-correlater with nested grid design, sparse/dense combinative searching strategy and disparity filtering technique; 2) "Geogrid", the precise geocoding component that supports pointwise mapping between imaging coordinates (pixel location and displacement) and geographic Cartesian coordinates (geolocation and displacement velocity). autoRIFT can run on a grid in the native imaging coordinates (such as radar or map) and, when used in conjunction with the Geogrid module, on a user-defined grid in a geographic Cartesian coordinate system such as Universal Transverse Mercator or Polar Stereographic. Here we demonstrated its application in tracking ice displacement and validated with ESA's Sentinel-1A/B radar and NASA's Landsat-8 optical data.
Additional Information
© 2020 IEEE. This effort was funded by the NASA MEaSUREs program in contribution to the Inter-mission Time Series of Land Ice Velocity and Elevation (ITS LIVE) project (https://its-live.jpl.nasa.gov/) and through Alex Gardner's participation in the NASA NISAR Science TeamAdditional details
- Eprint ID
- 108194
- DOI
- 10.1109/igarss39084.2020.9323412
- Resolver ID
- CaltechAUTHORS:20210225-102221469
- NASA
- Created
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2021-02-25Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field