Predicting Disaster Before It Strikes: How Geospace Solutions Used ENVI® and ENVI SARscape® to Analyze and Anticipate the Llallagua Landslide in Bolivia

Challenge

In many countries, water management infrastructure is aging, and threats induced by climate change are putting them at further risk. Today, stability and risk mapping through continuous monitoring is becoming an increasingly important requirement to mitigate damage, risk of collapse, and life-threatening accidents.

Any anomalous movement of water management infrastructure must be identified and analyzed in near real-time and at a millimeter-scale. While traditional monitoring methods are highly accurate, they are unfortunately challenging to conduct, time-consuming, expensive, and often cannot provide continuous data on the stability of a structure. Further, ﬂood and water management structures are often located in relatively remote locations, such as on riverbanks or in deep valleys, making onsite surveying difficult. Overgrown vegetation also limits how well water management structures can be accessed and surveyed.

Benefits of InSAR Based Earth Observation Monitoring

In March 2025, the collapse of the Kenko artificial lagoon unleashed a devastating landslide in Llallagua, Potosí, Bolivia. Toxic mud and mining waste swept through the Andavilque community, affecting more than 50% of the population, contaminating local rivers, and destroying infrastructure and livestock. With mining waste dating back to the 19th century, the resulting environmental and human toll was catastrophic. Responders urgently needed a way to assess the damage as well as identify signs that might have predicted the event – to try and avoid a future catastrophe. 

Figure 1: Study area map of Llallagua, Potosi, Bolivia, where the Kenko artificial lagoon collapsed, triggering a deadly landslide the devastated the Andavilque community.

Solution

Geospace Solutions, a remote sensing and geospatial analytics company based in Ecuador, turned to ENVI® and ENVI SARscape®, NV5’s industry-standard geospatial analysis tools, to evaluate the landslide's impact and uncover precursors hidden in historical satellite data. 

By applying multitemporal analysis, SAR interferometry, and change detection workflows to Sentinel-1 and Sentinel-2 data, the team was able to detect significant land deformation, quantify damage, and demonstrate how early warning systems could be built using ENVI SARscape’s automated tools.

Figure 2: DInSAR-derived ground deformation map showing millimeter displacements before and after the landslide. Red indicated upward (positive) deformation; purple indicates downward (negative) deformation along the satellite line-of-sight.

Approach

Monitoring Ground Instability (Before the Landslide)

Using ENVI SARscape’s automated SBAS (Small Baseline Subset) interferometry workflow, analysts identified subtle surface deformations as early as September 2024, with ground velocity exceeding 20 mm/year in areas surrounding the lagoon. This pre-collapse activity provided clear warning signs of structural instability. 

Quantifying Impact (After the Landslide)

Following the event, Geospace Solutions used ENVI’s Change Detection tools with multispectral Sentinel-2 imagery to measure the extent of the damage, spanning over 100 hectares. Differential Interferometric SAR (DInSAR)workflows in ENVI SARscape revealed millimetric surface displacement, highlighting the force and direction of material flow.

Visualizing and Sharing Results

Color-coded deformation maps, time-series graphs, and spectral change maps provided a clear picture of the event’s timeline and severity. Outputs were georeferenced for integration with decision support platforms and emergency management systems. 

Early Warning Potential:

If the ground motion trends identified by ENVI SARscape’s SBAS analysis had been monitored in real time, local officials may have had weeks, or even months, of advance warning to mitigate risk. 

Rapid Damage Assessment:

Multitemporal SAR and multispectral imagery enabled near-instant understanding of impacted zones, infrastructure loss, and environmental contamination. 

Figure 3: Visual Interpretation of ground movement in the affected area. The upper slope near the Kenko lagoon showed pre-event bulging (red), while material displaced downslope toward the river is visible in purple.

Figure 4: SBAS interferometry results derived from Sentinel-1 time series show progressive ground velocity rates near the lagoon exceeding 20 mm/year and accelerating months before the collapse.

Informed Future Planning:

With ENVI and ENVI SARscape, Geospace Solutions demonstrated how historical satellite archives and automated time-series analysis can support the design of early warning systems, especially in geohazard-prone regions. 

With ENVI SARscape’s automated SBAS workflows, Geospace Solutions analysts identified ground velocity rates exceeding 20 mm/year, which was well before the catastrophic collapse (Figure 3, 4). If incorporated into early warning systems, this type of monitoring could alert decision-makers to intervene sooner, potentially preventing loss of life and infrastructure.

“ENVI and ENVI SARscape allowed us to not only document the destruction—but to show how we might prevent the next one.” 
— Rafeal Castro, CEO, Geospace Solutions 

Tools & Technologies

ENVI® – Multispectral Change Detection, Image Classification, and Visualization 
ENVI SARscape® – SBAS and DInSAR Interferometry, Time-Series Analysis
Data Sources: Sentinel-1 (SAR) & Sentinel-2 (Multispectral)

Why NV5 Geospatial

ENVI and ENVI SARscape are designed to turn Earth observation data into decisions, automatically, at scale, and with scientifically validated methods. These tools are trusted by governments, NGOs, and commercial organizations around the world for environmental monitoring, disaster response, and predictive modeling. 

Conclusion

The Llallagua landslide was tragic, but it was also predictable. Geospace Solutions’ work proves that with the right tools and access to satellite archives, disasters don’t have to take us by surprise. Remote sensing and time-series analysis are transforming how we understand, respond to, and prepare for geohazards. 

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