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By Aditya Chaturvedi - 02/21/2022


Itay Bar-Lev, Managing Director, The Intel Lab


More than a century ago, ‘muckraker’ — coined by Theodore Roosevelt — became a widely popular and defining term for investigative journalism. Today, when the internet is an animated town hall, public square and caucus rolled into one, the veritable eye-from-the-sky (satellite imagery + precise analytics) plays a crucial role in breaking stories and providing exclusive on-ground footage of far-flung isolated regions, illicit activities, and clandestine developments.

Satellite imagery and analytics are behind most of the events that unfold today. The role and scope of GeoInt in investigations, fact-finding, and intelligence missions have increased rapidly over the years.

The Intel Lab, a collaborative network of global geospatial intelligence professionals, unearths a lot of these events across the world. It is an Intelligence-as-a-service company that provides reliable and actionable data to decision-makers.

The Intel Lab outlook for the coming years is strengthening its current assets by developing computer vision algorithms and leveraging its knowledge and experience to fulfill subject-matter expert roles in civilian and military AI-driven solutions.

“Mostly we operate from behind the curtains, but we have publicly shared our findings with the media on the latest India-China tensions and Iran’s nuclear ambitions,” says Itay Bar-Lev, Managing Director, The Intel Lab, in an exclusive interview with Geospatial World.


What’s your take on the way geospatial intelligence has transformed journalism, which in turn has empowered citizen activism, public participation, and democratized information access over the years, and how do you foresee its future?


It is indeed a giant stride in journalism, and the benefits are tremendous for democracies, activists, and common citizens. Technologies once accessible to just governments and militaries are available to everyone today. This has helped to make the world a safer place as compared to earlier.

However, these technologies such as Very High Resolution (VHR) images, Synthetic Aperture Radar (SAR) images need a certain level of knowledge, training, expertise, and experience. We see that media and social media misinterpretations often lead to erroneous conclusions. Purchasing a satellite image is indeed easier and cheaper today but the analysis should only be performed by professionals through a peer-review process to avoid potentially dangerous glitches.


From what I understand, The Intel Lab is a collaboration of intelligence analysts and geospatial professionals from across the globe. Tell us more about it, and what was the motivation behind it?


First, let me state the obvious. We are not a governmental agency, and we are not funded by any government-linked outfit. So, we don’t have the same capability that a government-funded agency would exploit and deploy. A robust network of geospatial professionals allows us to be swift, agile, creative, and mission-oriented. This is the sweet spot, which is of interest to bigger companies and agencies, as we operate outside the administrative and regulatory complexities.


What do you think are some of the major technology trends and forces that will play a key role in geospatial intelligence in the coming years, and do you think ongoing developments in 5G and Artificial Intelligence (AI) will influence it?


Satellite miniaturization and cheaper ride-share launching is the gateway to a fascinating future where remote sensing data will be part of our daily routine. In a year or two, we will be able to easily monitor all areas on the globe, multiple times a day, with a plethora of sensors. This would be a radical shift.

We can cope with the already exponential rate of data collection with more satellite on-board, AI-assisted analytics, laser satellite uplink, downlink, 5G networks on the ground, easier to deploy, less energy consuming cloud computing pipelines, and more efficient algorithms. We are at the cusp of a new technological era.


Even before the advent of GIS and geospatial intelligence, geography has been at the kernel in figuring out choices, alternatives, possibilities, strategic leverages, and the way to escape logjams in international politics. ‘The Revenge of Geography’ — to borrow a phrase — has wielded a powerful influence in framing optionalities. Do you think geospatial intelligence and GIS have added an altogether new, more evolved dimension to both better understanding conflict patterns and prepare better for their resolution?


‘The Revenge of the Nerds’ I would say with a pinch of humor and sarcasm. Geography brought to us 2D access to our spatial understanding of the world, while GIS and GEOINT brought us the additional 3D and 4D layers, thus allowing us to fathom complex models, events, and their implications.

Today’s GIS and GEOINT data are served to decision-makers as a multi-layered package with easy-to-understand visuals and sets of recommendations in a scenario-specific way. The ease of access and understanding makes GEOINT and GIS a preferred tool of choice inside governments for more objective knowledgeable decisions.


At a time of aggravated uncertainties and turbulence, what role do you think can geospatial intelligence play in making the world more sustainable and resilient?


GEOINT plays a crucial role to create transformative pathways to resilience and sustainability in a broad array of industries, from supply chains, national infrastructures, city planning, climate change to renewable energies, homeland security, civil engineering to name a few. GEOINT is a significant contributor in preparing our world for the best — and the worst.


How does The Intel Lab ensure that the geo-intelligence analytics is precise, actionable, and without any margin of errors?


Unfortunately, the world is not error-free, neither are humans. However, we aspire to reduce the margin of errors to the bare minimum based on the information we gather, analyze, and disseminate. We have instituted a rigorous peer-review process.

We always ask ourselves “What if?” and play the devil’s advocate to test the strength of our arguments and then put forward the hypothesis. It is an essential and healthy process for every intelligence-related activity to minimize professional shortcomings.


How do you use SAR satellites, and what are some of your main offerings in perception modeling and intelligence?


SAR technologies, whether spaceborne, airborne, or ground-based, have a special place in our business model. We use SAR satellites for various tasks related to installation monitoring, oil spill monitoring, mining-related deformations, tunneling-related deformations, or ground subsidence. Today’s SAR satellites give us an extra edge to fully assess physical change on the ground.


We consider perception modeling as a high-quality tool to assist intelligence analysts though not all analysts are interested in algorithms detecting cars, trucks, building footprints, or commercial aircraft at 98% accuracy. If your task is to detect a specific warship class in the middle of the ocean, would you need an algorithm trained to detect just a ‘small ship’, ‘medium ship’, or ‘large warship’? This is where the analyst can truly make a difference.





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Power outages, gas pipe bursting, rails deformed, sinkholes, buildings tilting, roads cracking...

Tehran plains ground subsidence has been covered and studied in recent decades however this man-induced phenomenon is now catching Tehran city itself for the last years thus endangering a growing population of 13 million inhabitants and its critical infrastructures.

Excessive groundwater extraction has caused land subsidence at a rate of up to 25 centimeters per year in some areas.


In this brief study, Differential InSAR processing was used to identify and estimate land displacement by using Sentinel-1A SAR SLC imageries. Our dataset includes 14 pairs of images from January 2020 to May 2021 with a small temporal-perpendicular baseline and using the SBAS approach, processing was performed by the GAMMA Software via ASF DAAC .


The results were further converted to an estimated vertical ground displacement map with a maximum average subsidence rate of 40mm/year.

It is known that subsidence phenomenons are non-linear, this estimated average rate takes into account events that occurred with higher subsidence during the period of images acquisition as well as events with ground uplift.






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