Surface Displacement Measurement from Remote Sensing Images. Olivier Cavalie

deformations. Finally, Chapter 6 focuses on the methods that have been developed to unwrap the phase and to take the phase closure principle into account, improving the results or discovering hidden phenomena.

      The second part, Applications for Surface Displacements, exhaustively covers the use of SAR interferometry and image correlation to retrieve the Earth’s surface displacements. Indeed, the first application of InSAR that made the cover of Nature, in April 1993, was for the measurement of earthquake movements. Chapter 7 is thus dedicated to measuring tectonic displacements and showing how InSAR and image correlation have been used over time to monitor more subtle tectonic motions of the Earth. Next, Chapter 8 describes how measuring surface displacement is crucial to understanding the dynamics of volcanoes. In addition to natural phenomena, some of the Earth’s surface deformations are induced by human activities. Chapter 9 reviews all kinds of human-induced signals and how InSAR is beneficial to monitoring them. Chapters 10 and 11 focus on surface motions due to gravity, namely landslide and glacier dynamics. Finally, the last chapter opens up the field of image correlation by cleverly taking advantage of the small spatial baseline and the time lag between the instruments imaging the Earth in different spectral bands onboard the very same satellite.

This book offers for the first time a complete overview of the methodological approaches deployed for the deformation measurement of the Earth’s surface using RSI and their applications to the monitoring of major geophysical phenomena. Over the last few years, a virtuous circle between space agencies and scientists has developed. Indeed, in the last 20 years, the cost of satellite images has decreased drastically, the quantity of data has increased and the performance of data processing algorithms has greatly improved. As a result, the maturity of the remote sensing community now allows near real-time observation of the Earth’s surface deformation, enhancing our capability to detect and mitigate natural hazards substantially.

      Olivier CAVALIÉ

      Coordinator of the book

      Emmanuel TROUVÉ

      Coordinator of the book and head of the “Remote Sensing Imagery” subject

      Avik BHATTACHARYA

      Head of the “Remote Sensing Imagery” subject

      February 2022

PART 1 Theory, Principles and Methodology

      1

      Relevant Past, On-going and Future Space Missions

       Philippe DURAND and Stephane MAY

       CNES, Toulouse, France

      Earth observation satellites have provided images all around the world for more than half a century. Passive optical imaging systems and synthetic aperture radar (SAR) active sensors are nowadays the main sources of information used to derive surface displacement fields. To provide an overview of the images available through space agencies and their main characteristics, this first chapter describes different space missions with data relevant for ground motion displacement measurements. For radar, it is important to observe the field under the same incidence angle, meaning that this may depend upon the satellite orbit housekeeping and general design. SAR missions where orbit is not maintained are not mentioned (except the Iceye mission): their data seem useless at first sight for SAR interferometry (InSAR, see Chapter 4) and probably for SAR correlation algorithms (offset tracking, see Chapter 3). Data access, particularly when free of charge, is also described for the missions.

1.1. Some key parameters for space missions

      1.1.1. Parameters for both SAR and optical missions

Remote sensing missions to date have had low-altitude orbits of a few hundred kilometers around the Earth. While optical missions mainly work, except for infrared instruments, along half of the orbit under sun lighting, SAR images can be acquired across the whole orbit, day and night, and also through cloud cover for the frequencies examined later in this chapter.

      Sun-synchronous missions: Most remote sensing missions are placed on sun-synchronous orbits. This is important for optical imagery to assure the same looking angle with regard to the sunlight (although it slightly changes anyway with the seasons). These orbits are also used for SAR imagery, sometimes because they are on the same platform as optical sensors (e.g. JERS-1, Envisat or ALOS), and also because of power constraints. Radar instruments have high power consumption and thus recent missions are often on a 6:00 and 18:00 (or dawn–dusk) orbit that maximizes the energy received by a solar panel (which can be fixed and always orientated towards the sun). ERS-1 and ERS-2 inherited a platform heritage from the first French optical satellite (SPOT-1), keeping the local hour at 22:30 (10:30 descending): the panel had a fixed direction towards the sun but had to make one rotation per orbit on the spacecraft.

      These orbits are also near polar orbits, which assure a large coverage of the Earth, except some areas near the poles, depending on the look angle and swath, and with differences between the south and north poles depending on whether the radar is left- or right-looking. When crossing the equator, these orbits have a fixed local hour, which must be maintained throughout the mission duration (inclination maneuvers): this is a key parameter, and all satellite passes occur at the same hour if observed under the same incidence angle. Note that the reference value of the local hour is when the orbit crosses the equator from south to north (ascending part).

      Revisit: This corresponds to the time taken for a satellite to revisit a given geographical location on the Earth. It depends on the satellite orbit (altitude, inclination, etc.) and agility.

      Repeat cycle: This key parameter expresses the number of days separating two data takes under the same orbital point of view, which can be equal to or higher than the revisit. At the beginning of the mission, in relation to the sensor field of view or swath, we must establish a total number of orbits Ntot and also choose the number of days in the cycle Dcycle. Then, we have the following relationship:

      [1.1]

      where [14(or 15) + p/Dcycle] is the number of orbit revolutions in one day. The orbit duration is about 100 min as the orbit altitudes are in the range of 400–900 km: when under 96 min, there will be at least 15 orbits/day. p is an integer chosen with a close relationship to Dcycle.

It is possible to change the repeat cycle during a mission, which means a change of altitude for the satellite. For example, ERS-1, with a change of altitude of less than 6 km, had a Dcycle that changed from 35 to 3 days. With a constellation where all satellites have the same orbit (but are phased differently), for example, with SPOT, ERS, CSK, Sentinel and TerraSAR-X/TanDEM-X/PAZ constellations, it is possible to combine images from the different satellites and hence reduce the time interval between data takes while keeping the same orbital point of view, called the “repeat time”.

Table 1.1. Main orbital parameters for some sun-synchronous SAR missions

Satellite

Local hour

Entire rev.

p

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