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Published November 2014 | public
Journal Article

Motion detection using near-simultaneous satellite acquisitions

Abstract

A number of acquisition constellations for airborne or spaceborne optical images involve small time-lags and produce near-simultaneous images, a type of data which has thus far been little exploited to detect or quantify target motion at the Earth's surface. These time-lag constellations were for the most part not even meant to exhibit motion tracking capabilities, or these capabilities were considered a drawback. In this contribution, we give the first systematic overview of the methods and issues involved in exploiting near-simultaneous airborne and satellite acquisitions. We first cover the category of the near-simultaneous acquisitions produced by individual stereo sensors, typically designed for topographic mapping, with a time-lag on the order of a minute. Over this time period, we demonstrate that the movement of river ice debris, sea ice floes or suspended sediments can be tracked, and we estimate the corresponding water surface velocity fields. Similarly, we assess cloud motion vector fields and vehicle trajectories. A second category of near-simultaneous acquisitions, with much smaller time-lags of at most a few seconds, is associated with along-track offsets of detector lines in the focal plane of pushbroom systems. These constellations are demonstrated here to be suitable to detect motion of fast vehicles, such as cars and airplanes, or, for instance, ocean waves. Acquisition delays are, third, also produced by other constellations such as 'trains' of satellites following each other and leading to time-lags of minutes to tens of minutes, which are in this contribution used to track icebergs and features of floating ice crystals on the sea, and an algae bloom. For all acquisition categories, the higher the spatial resolution of the data and the longer the time-lag, the smaller the minimum speed that can be detected.

Additional Information

© 2014 Elsevier Inc. Received 24 April 2014; Received in revised form 8 August 2014; Accepted 10 August 2014; Available online 16 September 2014. Special thanks are due to two anonymous referees for their careful comments. The providers of the data used in this study are much acknowledged. ASTER data were obtained from NASA through Reverb/ ECHO under the GLIMS project (www.glims.org); ALOS PRISM data from ESA under AOALO.3579; WorldView-2 and Ikonos data from DigitalGlobe; USGS airphoto, Landsat and EO-1 ALI data from the USGS (earthexplorer.usgs.gov), RapidEye sample data from Blackbridge (www.blackbridge.com/rapideye), and the airphotos over Yukon River from Matt Nolan (www.drmattnolan.org). A. Kääb was supported by the Research Council of Norway (contracts 185906/V30 and SFF-ICG 146035/420) and the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC grant agreement no. 320816. S. Leprince was supported by the Gordon and Betty Moore Foundation through Grant GBM 2808 to the Advanced Earth Observation Project at Caltech.

Additional details

Created:
August 22, 2023
Modified:
October 18, 2023