Comparing Amplitude and Coherence Time Series With ICEYE US GTR Data and ENVI SARscape

Large commercial SAR satellite constellations have opened a new era for persistent Earth monitoring, giving analysts the ability to move beyond simple two-image comparisons into robust time series analysis. By acquiring SAR data with near-identical geometry every 24 hours, Ground Track Repeat (GTR) missions minimize geometric decorrelation, making it possible to reliably stack images and detect even the most subtle changes.

This post explores the complementary ENVI® SARscape workflows, (Intensity Timeline and Coherence Timeline) to reveal distinct insights when applied to a Daily Repeat GTR dataset. One example uses a 14-day temporal stack of spotlight mode SAR data from ICEYE US, collected daily between July 31, 2025, and August 13, 2025. The area includes center-pivot irrigation examples near the U.S.-Mexican border, making it ideal for studying dynamic agricultural environments. With daily revisit rates and consistent geometry, the dataset captures rapid changes while maintaining coherence needed for high-fidelity Coherence Time Series analysis.

SARscape Intensity Time Series (Amplitude)

The Intensity Time Series (generated in SARscape via Basic > Intensity Time Series) tracks how the radar brightness (amplitude) of a target changes over multiple acquisitions. Brightness primarily reflects the physical and geometry properties of ground targets.

What It Measures & Why It's Useful

Gross Structural Change: Excellent for detecting obvious changes such as new construction, demolition, or the flooding/draining water bodies.
Volumetric or Biomass Changes: Effective for tracking vegetation cycles such as crop growth, harvest, or tilling, where radar return changes significantly over time.

Use in the Example: In our pivot irrigation fields, the Intensity Time Series highlights irrigation activity (if operational) over the 14 days or shows sharp drops where a field was harvested or plowed.

Output Visualization: The workflow produces a series of calibrated, geocoded amplitude images and statistical maps (e.g., mean, standard deviation) that visually reveal where the scene has brightened or darkened consistently over the period.

SARscape Coherence Time Series

The Coherence Time Series (generated in SARscape via Interferometry > Coherence Workflows > Coherence CCD Timeline) tracks how a target’s coherence evolves over time. Coherence measures the stability of the radar signal's phase, making it highly sensitive to motion or surface changes, even at the sub-centimeter level.

What It Measures & Why It's Useful

Subtle Surface Changes (Decorrelation): Detects minute movements or changes in surface material and structure that don't necessarily change the overall brightness.
Moisture and Roughness: Coherence is extremely sensitive to changes in surface moisture (e.g., dry soil vs. wet soil) and small-scale surface roughness (e.g., footprints, vehicle tracks).
Use in the Example: In our pivot fields, the Coherence Time Series captures the daily effects of the irrigation (low-coherence traces caused by wet soil and canopy motion) or subtle vegetation changes from growth or wind, even when the amplitude remains steady.

Output Visualization: The workflow generates a chronological series of coherence images, allowing analysts to plot small changes at specific location across the 14 days, revealing when and how rapidly a site decorrelates.

Analyzing Amplitude and Coherence

Historically, analysts compared amplitude change using a product called Two-Color Multiview or 2CMV, a composite where the “before” image is assigned the red channel, and the “after” image to both green and blue channels. This visualization highlights change through color contrast: stable areas appear gray, while new or disappearing features show as brighter tones.

Beyond two-image analysis, a third acquisition adds temporal depth. With three SAR scenes, analysts can create a Three-Color Multiview (3CMV) composite by assigning each date to its own RGB channel. The result is a powerful visualization of both timing and directional change where persistent features appear neutral, and activity unique to each date shows as distinct colors. For instance, irrigation cycles, equipment movement, or short-term vegetation shifts appear as dynamic color transitions that clearly reveal day-to-day behavior.

With this 3-date RGB composite, the day-to-day activity of each field’s irrigator is clearly visible. When your dataset grows beyond three dates, you can move beyond RGB composites into statistical analysis of the entire temporal stack, which provides richer quantitative insight.

One powerful SARscape output for this purpose is the CovMinGrad image, short for Covariance-Minimum-Gradient. Generated from the Intensity Time Series processing in SARscape. Generated from the Intensity Time Series, CovMinGrad is a multi-temporal RGB composite that highlights rapid, consistent, or directional amplitude changes across the observational period.

Color Channel	Statistical Feature	What it Represents
Red (R)	Covariance (Cov)	Variability in brightness across time. Bright Red areas indicate highly dynamic surfaces such as active irrigation or seasonal changes.
Green (G)	Minimum Intensity (Min)	The dark amplitude observed is useful for highlighting temporary dark zones (e.g., flooded areas, harvested fields).
Blue (B)	Gradient (Grad) or Rate of Change	The rate of direction of change in brightness. Bright Blue areas indicate steady trends like continuous construction or consistent crop growth or decline).

In this visualization, green areas remain stable across the temporal stack. Field 5 shows irrigation in roughly one-third of the area, while magenta tones highlight regions where the water activity or irrigator motion occurred consistently across the 14 days.

Extending the Analysis: Coherence and 3CMV

Not every change appears in amplitude. Fine-grained surface changes are captured through coherence products, and the 3CMV (Three-Color Multiview) technique remains valuable, though the interpretation differs slightly.

Day-to-day coherence fluctuations appear as varying colors in the 3CMV, while consistently high coherence appears as white and consistently low coherence appears black. In our example, daily small-scale variations are visible across fields 2-7 for the selected date range. In field 1, a brief coherence drop between August 8-9 indicate equipment tracks, verified visually as surface patterns in this recently developed field.

Conclusion

Amplitude confirms where activity is present, while coherence reveals the sub-wavelength changes in detail. For persistent monitoring of dynamic environments—whether agricultural, industrial, or infrastructure-related—combining both amplitude and coherence in SARscape time-series analyses provides a complete, multi-dimensional understanding of the scene.

By leveraging ICEYE US GTR’s daily repeat capability and SARscape’s temporal analytics, analysts can move beyond snapshots toward continuous situational awareness, detecting not just that change happened, but how, when, and why.

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