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March 28th, 2022
Synspective works with the World Bank and NDRRMA to assess slope instability-related geohazards in Melamchi, Nepal

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Tokyo, Japan – Synspective Inc., under the supervision of the World Bank and National Disaster Risk Reduction and Management Authority (NDRRMA), Government of Nepal, investigated the land displacement hazards in the upstream part of the Melamchi River, Nepal in response to the destructive flood disaster that occurred there on June 15, 2021. The results demonstrated that Synthetic Aperture Radar (SAR) data and time-series interferometric SAR (InSAR) analysis-based Earth observation techniques have the capabilities to offer a more cost-saving alternative to periodically monitor slopes with susceptibility and identify the potential precursors of slow-evolving failure conditions.

Landslide Outburst Flood in Melamchi Basin and Planning for Resilience where Synspective’s work was presented in front of a large audience and stakeholders

Using data gathered by the European Space Agency’s SAR satellite, Synspective’s Land Displacement Monitoring (LDM) service monitored over 400 km2 of slope area in the upstream proximity of the Melamchi River. The analysis results were used to support the authorities’ work in managing slope susceptibility risk in the region. In addition to residential communities, critical facilities and lifeline infrastructure are also present in the region including the Headworks of the Kathmandu Valley Water Supply Improvement Project financed by the ADB.

“In the aftermath of a natural disaster,” Synspective CEO Motoyuki Arai said, “it is vital that local authorities have sufficient information to understand what happened and why, and they need this quickly. Conventional surveying techniques such as leveling, GNSS (Global Navigation Satellite System) sensor placement, drones, and helicopters, have been used for detecting and measuring land displacement and deformation. However, these survey methods are restricted to in-situ monitoring capabilities. Using InSAR technique and LDM technology, we were able to overcome the geographical accessibility challenges in Melamchi and provide insightful information that highlighted slope instability risks. On top of that, five months after the disaster, a helicopter survey confirmed our findings, which highlights the quality of information we can achieve using this monitoring technology. This project provides strong evidence of how the remote, wide and rapid data acquisition and the right analysis techniques can provide a great amount of support in disaster risk management, especially in difficult-to-access areas and under the recent COVID-19 mobility restrictions. And we believe this positive result can be a great boost to our company’s activities.”

Synspective’s analysis provides complementary insight in explaining ground failure mechanisms in the high-altitude area in the Himalayan region. In addition to the slope areas in the north-western Melamchi watershed, Synspective’s analysis highlights other catchment areas in the neighboring watershed and in other parts of Melamchi watershed as having susceptibility based on land displacement and spatio-temporal behavior and characteristics. It is also being discussed that it can be applied to risk monitoring of glacial lake outburst floods in the Himalayas, where the risk is increasing due to climate change.

The project benefited from technical discussions and reviews with the broader team including international and local experts and partners, and from various data shared from the field. We hope our output will be useful for government, relevant partners, and communities to plan resilient communities and infrastructure in Nepal.

About Synspective
Synspective provides one-stop solutions using satellite observation data to steadily move the world forward. Applying the results of the ImPACT program (led by the Government of Japan, Cabinet Office), Synspective is building a constellation of 30 high-frequency, high-resolution SAR satellites to provide data and solutions to government and commercial outfits.

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