Vertical movement (subsidence and uplift)

Horizontal movement (lateral displacement)

displacement rate, change in rate of movement, and total accumulated deformation

Derived indicators

The reliability of InSAR monitoring in detecting real instability

The combined value of horizontal and vertical displacement analysis for robust forecasting

The importance of clear alert structures to enable proactive action

Color changes reflect the onset of slope instability.

A large slope with potential risks to nearby infrastructure and safety was continuously monitored using InSAR technology starting in March 2022. Between March 25–28, 2025, a visible landslide occurred, causing significant structural impact. However, the historical InSAR data revealed clear signs of instability weeks in advance — meaning the event could have been anticipated and mitigated.

To demonstrate how recurring analysis of vertical and horizontal displacements using InSAR can anticipate real landslide risk several weeks before an event, allowing time for contingency or mitigation actions.

InSAR data provided up to six weeks of early warning before the landslide.

Alert Timeline

Landslide Risk Anticipation with InSAR

Implementing a continuous InSAR monitoring system with periodic analysis:

Promotes a preventive rather than reactive approach to geotechnical safety

A regular (biweekly or monthly) analysis routine could have:

Identified abnormal displacement and acceleration trends early

Triggered timely inspection and mitigation plans

Prevented structural failure and associated damage

Discover how Spotlite’s InSAR monitoring detected slope instability six weeks before a landslide. Learn how early alerts prevent structural failures and improve safety.

Landslide Risk Anticipation with InSAR | Spotlite Geotechnical Monitoring Case Study

The effectiveness of InSAR monitoring in detecting both vertical and horizontal ground deformation

The importance of combining vertical and horizontal displacement analysis for a full structural assessment

The need for continuous geotechnical monitoring to ensure safety, durability, and performance of road infrastructures

A road infrastructure crossing a mixed urban and rural area was continuously monitored using InSAR technology to analyze ground displacement over time. The monitored corridor included several critical components — bridges, valleys, rivers, and extensive embankments.
The InSAR data revealed distinct structural behaviors between bridge decks, which remained stable, and adjacent embankments, which showed significant subsidence. The study aimed to understand deformation trends and assess potential impacts on structural integrity.

Vertical displacement along the road: red = subsidence, blue = uplift.

Bridge deck stable; embankment shows progressive settlement.

Greater movement concentrated in the access embankments.

Opposing lateral movement patterns across the road corridor.

Bridge decks and abutments remained stable, with displacements below 5 mm/year

Adjacent embankments experienced significant settlement, exceeding 150 mm over two years

The instability was associated with geotechnical foundation soil behavior, not the bridge structure

Analysis of points on both sides of the bridge showed vertical displacement patterns aligned with surrounding slopes, suggesting lateral compression effects

Horizontal decomposition revealed tangential ground movements, indicating compression and lateral spreading, which can lead to additional stress on abutments and pavement layers

To demonstrate how continuous InSAR monitoring enables the identification of differential settlement and lateral soil movements in road infrastructures, supporting early detection of instability and ensuring long-term structural safety.

Deformation Summary

Subsidence in Road Infrastructure Embankments Monitored with InSAR

Implementing the Geotechnical Management Module with periodic InSAR analysis:

Enables early detection of differential settlement and lateral deformation

Improves decision-making for maintenance and safety management

Promotes a preventive, data-driven approach to infrastructure monitoring

A regular monitoring and analysis routine (monthly or biweekly) could have:


Detected abnormal vertical and horizontal displacement trends early

Supported the implementation of timely inspection or corrective actions

Prevented stress accumulation on bridge structures and progressive deformation along embankments

Satellite-based vegetation vitality and proximity analysis

Automated risk matrix generation (species, terrain, and growth dynamics)

Workflow integration with corporate GIS and SAP systems

Budget and operational efficiency tracking

The power of satellite-based vegetation monitoring for large-scale network management

The value of automated workflows connecting GIS, SAP, and field operations

The impact of AI-based vegetation classification on safety, compliance, and efficiency

A leading Power Distribution Company managing over 80,000 km of network faced increasing operational and financial challenges in vegetation clearance along transmission lines. Annual vegetation management budgets approached €30 million, with fragmented workflows across GIS, SAP, and mobility platforms, leading to inefficiencies and limited audit capabilities.

High vegetation management costs (~€30M/year) with limited spatial prioritization

Manual workflows between GIS, SAP, and field systems delayed decision-making

Contractor audits covered less than 10% of total network inspections

Lack of centralized visibility hindered proactive vegetation control

To optimize vegetation management operations by integrating a satellite-based monitoring platform, automating risk prioritization, and aligning vegetation clearance activities with available budgets.

Performance Summary

Vegetation Management Optimization for Power Distribution Networks

Implementing the Vegetation Management Module within power distribution networks:

Cuts annual costs by up to 50% through optimized vegetation clearance

Enables automated prioritization based on real risk metrics

Ensures audit-ready transparency with integrated satellite and field data

Supports scalable, data-driven vegetation management across the full network

Prior to implementation, processes were reactive and fragmented. With earlier adoption of satellite-based monitoring and automated data flows:

Work prioritization could have been optimized by risk level and vegetation type

Real-time reporting could have enabled faster intervention cycles

Budget use could have been reduced while expanding maintenance coverage

Alert Type	Trigger Date	Time Before Event
Horizontal Alert	17 Feb 2025	39 days
Horizontal Alarm	1 Mar 2025	27 days
Vertical Alarm	13 Mar 2025	15 days

Solution

Geotechnical Management

Landslide Risk Anticipation with InSAR

Objective

Analysis Focus

Key Findings

Alert Timeline

What Could Have Been Done

Conclusion

Value Proposition

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