At The Fault Lines

On

February 6, 2023 at 04:17AM


a devastating M7.8 earthquake struck southeastern Turkey.

FEBRUARY 6, 2023 • 04:17AM

M7.8 EARTHQUAKE
STRIKES SOUTHEAST TURKEY

60,000

LIVES LOST

The combined death toll from these earthquakes is estimated at nearly 60,000 people, with more than 15 million people affected across 11 provinces.

230,000

BUILDINGS COLLAPSED

More than 230,000 buildings, housing 520,000 apartments, collapsed. Even newly built, luxury residences marketed to the public as “earthquake-proof” were reduced to rubble.

58%

OF THE HISTORICAL CITY OF ANTAKYA
WAS COMPLETELY FLATTENED

The cities of Hatay and Kahramanmaraş were among the most severely damaged by the February 6th earthquakes. Historic towns and city-centers, such as the millennia-old city of Antakya, were completely leveled, rendering the city unrecognizable to its residents.

30,000

SMALLER QUAKES AND AFTERSHOCKS FOLLOWED
ALL WITHIN 24 HOURS

Following the initial 7.8 magnitude earthquake, the region experienced relentless aftershocks—more than 30,000 in total. Some aftershocks reached magnitudes of 6.4, plunging survivors into a state of constant fear and uncertainty.

M7.8 EARTHQUAKE
STRIKES SOUTHEAST TURKEY

FEBRUARY 6, 2023 • 04:17AM

FEBRUARY 6, 2023 • 01:24PM

SECOND M7.7 QUAKE
OCCURS JUST HOURS LATER

9 Hours

TIME BETWEEN THE FIRST
AND THE SECOND EARTHQUAKE

The second major earthquake, considered a powerful aftershock, struck about nine hours later at 1:24 PM local time (10:24 UTC). This was a magnitude 7.7 earthquake centered northwest of Kahramanmaraş.

110,000 km2

TOTAL LAND AREA OF
THE EARTHQUAKE REGION

The disaster area covered a staggering mass of land, about 110,000 square kilometers (42,000 square miles). If the same earthquake struck the United States, the path of destruction would stretch from Washington D.C. to Boston.

$163.3 Billion

ESTIMATED COST OF DAMAGE

The cost of the disaster was estimated at over $163.6 billion, with the greatest damage across southern and central Turkey, as well as northern and western Syria.

CHAPTER 01

February 6

On February 6, 2023, two consecutive earthquakes with magnitudes of 7.8 and 7.7 struck southern Turkey and northern Syria, resulting in the deaths of more than 60,000 people. Now named as the Kahramanmaraş Earthquakes, largest since the 1939 Erzincan Earthquake of the same magnitude, is the second most powerful ever recorded in the region. Affecting 14 million people and leaving 1.5 million homeless across 11 provinces, it is now recognized as the deadliest natural disaster in the history of Turkey.

A Drone Shot Through the Streets of Antakya by NYTimes
A drone shot through the historic center of Antakya after the earthquake, showing the extent of destruction.
Visual investigation by the New York Times.

The earthquake region, encompassing the 11 southeastern provinces of Kahramanmaraş, Hatay, Osmaniye, Adıyaman, Gaziantep, Şanlıurfa, Diyarbakır, Malatya, Kilis, Adana, and Elazığ, totals up to over 110,000 square kilometers (42,000 square miles) - nearly the same size as the neighboring Bulgaria. This is equivalent to stretching from Washington, D.C. to Boston, MA, encompassing the entire northeastern metropolitan region of the United States.

US Northeast compared to Turkey earthquake region of the Southeast
The earthquake region is roughly as big as the Northeast United States
From Washington, D.C. to Boston, MA.

In Hatay province, the historic center of Antakya is now nearly uninhabitable. The city, which has stood for millennia, has been flattened, leaving it almost unrecognizable. The extent of the destruction has driven nearly all residents away, transforming familiar streets and landmarks into a stark, altered landscape. In Kahramanmaraş, the historic district has been decimated, leaving once-vibrant neighborhoods in ruins. Similarly, Gaziantep, known for its rich history and architectural heritage, has seen extensive damage to its old city center, including the Gaziantep Castle—originally built by the Hittite Empire and later expanded by the Romans—and its traditional markets. Despite more than a year of reconstruction efforts, most of these cities remain unrecognizable to more than 500,000 people who once called them home.

  • ANTAKYA, HATAY
  • ANTAKYA, HATAY
  • 12 SUBAT STADIUM, KAHRAMANMARAS
  • ISKENDERUN
  • OSMANIYE
  • ANTAKYA, HATAY

Yet, Turkey is no stranger to such catastrophic earthquakes, as the country geographically sits on top two major fault zones - the North Anatolian fault zone being one of the most seismically active in the World. 20 years ago when a similarly destructive earthquake struck near Istanbul, the country’s economic and population center, it was a wake up call for the country: The government changed shortly after being deemed “incompetent,” much stricter building codes and regulations were put in place, nation-wide first response organizations were founded, and a new “earthquake tax” was introduced to help fund urban renewal and recovery efforts. The recent earthquakes exposed that many of these efforts have been immensely inadequate, mostly due to large-scale corrupt political, regulatory, and construction practices throughout the 20-year AKP rule. Moreover, the country’s most prominent scientists have been incessantly alarming against a long-awaited “Istanbul Earthquake” to strike in the next decade, with consequences exponentially graver.

“The devastation we witnessed in Antakya could easily happen in Istanbul. We are sitting on a ticking time bomb.”

-Prof. Naci Görür, Geologist, Istanbul Technical University

This study aims to dissect these corrupt practices, identify their traces in the architectural level across an urban scale, and develop an alternative risk assessment mapping method that may offer critical insight for local authorities, municipalities, as well as individuals. Recent developments in interctive mapping techniques, artificial intelligence and machine learning have allowed large urban-scale risk assessment models to be implemented in order to detect possible structural defects before any failure or collapse. In this article, we will explain the structural malpractices that led to such destruction in the area, and will propose an automated, faster, and more scalable alternative “risk assessment method” that could be used to create an earthquake risk map of the bustling metropolis of Istanbul that is home to 16 million people.

In order to better understand this, we first need to zoom out and understand the country’s geological, social, and political relationship with the earthquakes — starting with the East Anatolian Fault, which is where the Feb 6 earthquakes happened.

The East
Anatolian Fault

Powerful earthquakes such as the ones that occurred on Feb 6 along the EAF may induce tectonic events along the neighboring faults.
The East Anatolian Fault is neighboring to East the North Anatolian Fault, which is considered one of the most active in the World.
The NAF has a track record of being triggered by neighboring tectonic events, which is why the recent quakes are concerning for many.

A Long History of
Devastating Earthquakes

Despite its relatively modest land area, Turkey has experienced numerous M7.0+ earthquakes since antiquity. Positioned at the intersection of the Eurasian, African, and Arabian tectonic plates and crisscrossed by several major fault lines, it is one of the most seismically active regions in the world.

CHAPTER 02

The North Anatolian Fault

A soft story structure diagram

The North Anatolian Fault (NAF) is a major strike-slip fault zone stretching approximately 1,500 kilometers (900 miles) across northern Turkey, from the junction with the East Anatolian Fault in eastern Turkey to the northern Aegean Sea.

Since the mid-20th century, seismologists have understood that earthquakes along the NAF move in a westward progression, with each quake triggering the next. This phenomenon became evident following the 1939 Erzincan earthquake, which resulted in over 32,000 fatalities and more than 100,000 injuries.

Research indicates that nine out of ten major earthquakes along the NAF between 1939 and 1992 were brought closer to failure by the preceding shocks due to the transfer of stress along the fault line. This progressive failure mechanism suggests that each large earthquake can set up the next one by altering the stress distribution along the fault.

By studying the sequence of past earthquakes, seismologists can identify patterns and potential stress points, enabling them to predict future earthquakes. The most recent major earthquake along the NAF, the 1999 Izmit earthquake, which killed over 17,000 people, has led the scientific community to anticipate the next major earthquake hitting Istanbul.

Due to Istanbul’s proximity to the NAF, the warning time for a major earthquake could be as short as 2-6 seconds, making a rapid response challenging. Combined with its dense population of 20 million and inconsistent infrastructure quality, the city could face an unprecedented level of destruction.

A Century of Earthquakes

Over the past century, eight +M7 earthquakes occurred along the North Anatolian Fault Line. Each happening further west of the one preceding it.
The most recent of which is the 1999 Izmit-Gölcük Earthquake, which struck 50 miles outside of Istanbul, igniting widespread political, social, and economic change across Turkey.
Experts are concerned that the February 6 earthquakes could potentially trigger a future earthquake along the North Anatolian Fault (NAF) near or beneath Istanbul.

1999 Gölcük-Izmit Earthquake:
A Disaster Powerful Enough to Change Governments

The most recent major tectonic event along the North Anatolian Fault, the 1999 Izmit-Gölcük Earthquake has served as a catalyst for the country, causing widespread changes in the government, and brough new approaches to disaster management, urban planning, construction regulations, and raised the public's awareness about seismic risks.

CHAPTER 03

1999 Golcuk Earthquake

The most recent major tectonic event along the North Anatolian Fault, the 1999 Izmit-Gölcük Earthquake, struck on August 17 at 3:01 AM local time. With a magnitude of 7.6 and an epicenter just 90 kilometers east of Istanbul, this 37-second tremor claimed over 17,000 lives and displaced 500,000 people. As Turkey’s most destructive earthquake until February 6, it exposed critical vulnerabilities in the country’s disaster preparedness, many of which were due to rampant corruption in the construction industry.

The incumbent government’s organizational failure and inability to respond and provide help to the area, combined with a long-standing financial crisis, has left the public with a bitter sentiment that “the state has left them on their own.” As a result, the government received less than 10% of the vote in the 2002 elections.

A comparison of before 2002, after 2002, and the current state of disaster preparedness efforts in Turkey.
The states of disaster preparedness in Turkey,
informed and taxonomized by major tectonic events.

The Justice and Development Party (AKP), which still is the ruling party in the country, rose to power in the elections with Mr. Recep Tayyip Erdogan, back then the very popular and highly-acclaimed Mayor of Istanbul, promising drastic changes. The newly appointed government codified what was initially planned to be a short-term recovery act, the infamous “Earthquake Tax,” making it permanent. It also launched the country’s first nationwide disaster response organization, AFAD, fore-fronted much stricter construction regulations and building codes, and introduced massive-scale urban renewal programs.

Since 2002, the AKP has been able to consolidate its base largely due to initiatives that many believed had transformed Turkey from a run-down, old country to modern standards, with new highways, residences, and other infrastructure improvements. However, the February 6 earthquakes have led to widespread disillusionment. The devastation revealed that many of the government’s commitments were not fulfilled, exposing significant inadequacies and corruption in regulatory enforcement, infrastructural reconstruction and disaster preparedness efforts.

This, along with the westward pattern of the seismic activity along the North Anatolian Fault suggesting an increased possibility of a tectonic event taking place around Istanbul, directly to the west of the most-recent quake zone Izmit, has left a city of 20 million worried about the safety of their homes and workplaces.

The 1999
Izmit-Gölcük Earthquake

The M7.6 earthquake lasted 37 seconds and took lives of more than 17,000 people, and displaced 500,000 others. It was the biggest that the country has ever seen until the Feb 6 earthquakes.
The devastating event has caused significant changes, such as the Ecevit government to lose in the following elections to AKP, which still holds the office today.
The AKP campaign promised significant changes to the country's natural disaster response strategies, including a new Earthquake Tax, and stricter construction codes.

The Impending Istanbul Earthquake

Decades of corrupt practices that led to the February 6 aftermath and warnings about an impending tectonic event, informed by historical patterns, now cause widespread concern about the safety of current buildings in a city of 20 million people.

Population Density

Home to a quarter of the country, Istanbul is operating way above its capacity as a result of failed migration policies.

State of Structural Testing

Only less than 15% of the buildings are tested. Many don't opt in due to potential legal implications.

Low Damage

The February 6 earthquakes has once again reminded the residents of 20 million city that the impending earthquake may happen anytime.

Medium Damage

The February 6 earthquakes has once again reminded the residents of 20 million city that the impending earthquake may happen anytime.

Heavy Damage

The February 6 earthquakes has once again reminded the residents of 20 million city that the impending earthquake may happen anytime.

Extremely Heavy Damage

The February 6 earthquakes has once again reminded the residents of 20 million city that the impending earthquake may happen anytime.

Estimated Loss of Life

Proejcted figures show that the densest neighborhoods are at the highest risk of loss of life.

CHAPTER 04

The Big Istanbul Earthquake

The devastating earthquake in February of 2023 has heightened anxiety among Istanbul’s residents about the inevitable "Büyük Istanbul Depremi" (The Next Great Istanbul Earthquake).

Given the Istanbul’s proximity to the North Anatolian Fault, the warning time for such an event could be as short as 2-6 seconds, making rapid emergency response extremely challenging. Combined with its dense population of 20 million and widespread structural vulnerabilities, the city is at risk of unprecedented destruction.

POPULATION

20
Million

1/4 of the Country Lives in Istanbul

BUILDINGS

1.2
Million

Only a fraction of them tested

EXPECTED TO COLLAPSE

+52%
Under Risk

625.000 Buildings Built Before 1999

With 3,049 people per square kilometer, Istanbul is one of the densest urban areas in the world, and the most densely packed neighborhoods also tend to be the most prone to earthquake damage. According to Mehmet Özhaseki, the Minister of Environment and Urbanization, approximately 600,000 residential units in Istanbul would likely collapse in earthquake with a magnitude above 7.0.

IMM Risk Simulation, Mapped


Hover over a neighborhood for more

The February 6 earthquakes laid bare the extent of corruption and lax enforcement in Istanbul’s construction industry, rendering past records unreliable. Coupled with an increasing number of scientific warnings about an imminent major earthquake near the city, these revelations have triggered a race against time to conduct structural tests on nearly every building in Istanbul—a task of unprecedented scale and speed.

In response, the municipality has initiated several studies to simulate the potential damage to buildings, people, and infrastructure. The data, now publicly available on the city's Open Data portal, includes interactive maps that display damage estimates, injury and death tolls, and shelter availability by neighborhood. While informative, these simulations lack the granularity needed at the building level, which is crucial given the varying degrees of structural integrity across the city.

To address this gap, the city has rolled out a Rapid Scan program, allowing residents to opt for a faster, albeit less comprehensive, structural evaluation. However, this initiative faces substantial hurdles. Soaring property prices have trapped many residents in potentially unsafe buildings, with many tenants unwilling or unable to relocate even if their homes fail the assessment. According to Mayor İmamoğlu, "Even with the fast scan program, many residents hesitate to participate simply because they cannot afford to move." Despite these challenges, the city has launched several ambitious housing projects, totaling around 300,000 new units. However, this number falls far short of meeting the skyrocketing demand for affordable housing, exacerbated by recent seismic activity and an ongoing economic crisis.

It may take up to 21 years to get
a structural test for your building.

The situation is even more dire when considering the sheer backlog of structural tests. At the current pace of 120 buildings per day, it could take the average Istanbul resident up to 21 years to see if their building is safe. With the North Anatolian Fault signaling an imminent quake, grassroots initiatives led by local architects, engineers, and students have emerged as a stopgap. These groups have taken to social media, circulating makeshift checklists for residents to identify visible structural deficiencies. These grassroots efforts have gained widespread popularity, sparking public conversations and helping residents make critical safety decisions. However, these movements also highlight the need for a more agile, granular, and scalable approach to Istanbul’s urgent structural testing crisis.

The Upcoming
Istanbul Earthquake

Researchers predict that the likelihood of a M7.0 quake to hit Istanbul in the next 5 years is 70%.
That is nearly 20 Million people, living in more than 1.2 million buildings.
625.000 of them are to be heavily damaged - that's more than 52%.

Despite numerous studies pinpointing the most vulnerable structures and communities throughout Istanbul, few have yielded actionable solutions that can be easily communicated to the public. The Municipality's risk simulation study, while available as a spreadsheet on the city's Open Data portal, falls short in terms of interactivity and accessibility, making it difficult for the average resident to engage with and understand the data.

Risk Simulation data, retrieved from Istanbul Open Data portal.
Risk simulation studies and datasets are open to public, although mostly in unfriendly formats.

However, some high-risk areas are well-known: The southern districts of the European side and the Princes’ Islands face the greatest danger due to their proximity to the North Marmara fault lines. Similarly, low-income neighborhoods, originally developed as “gecekondus” (makeshift buildings hastily constructed by factory workers in the 1960s), are poorly documented, with many erected before modern construction regulations were enforced. The disparity between these under-resourced areas and the well-established, affluent neighborhoods is stark, with the absence of planning and open spaces clearly visible even in satellite imagery.

Satellite imagery, average rent, and green space analysis chart

$1,587

$442

Levent Mahallesi

Çeliktepe Mahallesi

Satellite images retrieved by using Google Maps API.
Real estate data is retrieved from Zingat.com

Many well-planned high-income neighborhoods and the adjacent “gecekondu” areas often lie side by side, separated only by highways, hills, or the high-rise buildings of urban renewal programs. Most of these renewal projects have focused on middle- to high-income neighborhoods, where profit margins are higher, frequently neglecting the low-income areas where residents are more vulnerable and at greater risk.

Before
Atakoy Sirinevler

This is why we selected Hurriyet and Şirinevler neighborhoods as the pilot site for our project. Separated by only a highway strip from one of the city’s most meticulously planned developments, Ataköy, this area consistently ranks high in risk assessments and simulation studies. Many of its buildings were constructed before modern regulations took effect, sharing a common set of structural flaws and malpractices known to contribute to failures during earthquakes.

//Anatomy of A Collapse

CHAPTER 05

Anatomy of A Collapse

The 1999 Earthquake was different in the way that it was widely studied and well documented. A detailed field investigation conducted by the Earthquake Engineering Field Investigation Team (EEFIT) offers particularly useful insights here, highlighting that many structures collapse in a similar way, commonly referred as “pancake collapse”, that occurs in buildings with poor structural configurations, specifically those with soft stories. Nearly 24 years after regulatory amendments were introduced to eliminate these outdated construction practices, numerous photos and videos from the February 6 Earthquakes reveal that even newly constructed buildings collapsed due to the same malpractices these regulations were meant to address.

Below is a frame-by-frame excerpt from a social media post depicting a building in Şanlıurfa collapsing due to soft-floor failure to better illustrate this concept.

MOMENTS OF A PANCAKE COLLAPSE CAPTURED DURING FEBRUARY EARTHQUAKES IN SANLIURFA, TURKEY.
VIDEO BY VOX MEDIA. SOURCE

This type of building, ubiquitous across the nation, is a mid-rise residential structure with street-level retail and auxiliary spaces. The upper floors extend beyond the building's footprint to increase residential square footage—a maneuver that takes advantage of a tax loophole, allowing developers to maximize profits.

In the first few seconds of the quake, the building seems stable, with only subtle indicators of stress, such as the increasingly intense shaking of the glass storefronts. However, it isn’t long before the ground floor begins to buckle under the weight of the upper floors. The collapse initiates at this level, causing the ground floor to crumble and lose its structural integrity—this is when the soft-floor failure becomes apparent.

As the ground floor gives way, the unsupported upper floors begin to collapse in a domino effect, with each floor pancaking onto the one below. Within seconds, the entire structure is reduced to a pile of debris and dust.

//Common reasons behind structural failures

Common Reasons Behind
Structural Failures in the Region



1. Soft Story Buildings

A soft story structure diagram

Soft story buildings are multiple story buildings that has a ground floor that has large windows, wide openings, and large open commercial shopfronts where a shear wall or vertical support element would typically be needed to ensure that the structural stability. Especially in earthquake-prone areas such as Turkey, at least 30% of the ground floor area must be dedicated to structural elements to ensure that the structural system could withstand the stress of the above floors. Soft story buildings are highly common in the region, with many multi-story apartment buildings accommodate commercial floor space on the ground floor, which is allowed by mixed-used zoning practices. The 1999 quake has led to an updated building code that prohibited such structures, many developers did not feel pressed to follow the regulations due to the lack of a strictly enforced control mechanism.


2. Heavy Overhangs

A building with heavy overhangs/protruding parts

Another common practice is excessive cantilevering above the ground floor, as this allows developers to go beyond the site land usage limitations to maximize profits over extra square footage. Although cantilevering structures are a common practice in architectural design, combined with other malpractices such as soft story building designs, or using lower-quality building materials significantly increases the structural stress on the ground-level structural system. This may lead to a structural failure in the moment of an earthquake, even when the building may be able to withstand this load under normal conditions.


3. Pounding Effect

A building with heavy overhangs/protruding parts

Pounding effect is a common cause of collisions between adjacent structures during seismic events due to insufficient gaps between buildings that share one or more walls. In fact, pounding effect accounted for over 40 percent of all structural failures, with at least 15 percent collapsing mainly due to this phenomenon. Similarly, 200 out of 500 surveyed structures after the 1989 Loma Prieta earthquake were damaged due to the pounding forces of adjacent buildings.

Although Turkish construction codes have clear guidelines for proper seismic gaps, this remains a widespread issue in many metropolitan areas worldwide due to financial and architectural constraints. In metropolitan cities, the gap is often narrow or nonexistent. For instance, statistics from Eskisehir, Turkey, show that only 36 percent of adjacent buildings are adequately separated.

In addition to seismic gaps, studies show that the distance between floor levels, floor slab misalignments, and mass differences between adjacent buildings contribute to the extent of damage.

4. Short Columns, Misaligned Sturctural Elements and Other Post-Construction Alterations

A building with heavy overhangs/protruding parts

Structural alterations such as removing vertical supporting elements on the ground floor to open up space for commercial activities is another common practice many building owners employ to maximize profitability. Although there are multiple laws and regulations strictly prohibiting this, many buildings that has such alterations go unnoticed as it’s mostly done in the inside of the buildings.


5. Usage of Prohibited Materials and Techniques

Sea sand mixed cement

The 1999 Earthquake has shown that the usage of certain construction materials, such as “sea-sand mixed cement” or rebars with no ribs, can be a significant risk factor during a earthquake. Although most of these materials cannot be identified without a structural test, some easy-to-spot visual hints can offer useful information. Many locals are advised to look for sea shells on the surface of the concrete to identify whether the cement is mixed with sea-sand.

"I come from the kitchen" in this business, as we say, meaning all my family, under my father, were also a part of this sector, the construction sector. I grew up working with him, witnessing all of the development at that time.

...

70 percent of all the settlements in Istanbul, I would say, are vulnerable to a major earthquake. Without the proper diagnosis treating a patient is not possible. The construction materials used for various settlements in different parts of Istanbul used to be of poor quality - I personally know this myself, as I was one of those who extracted, sold, and used this type of cement.



-Ali Agaoglu, Turkish Real Estate Mogul

//AI + Computer Vision

CHAPTER 06

AI + Computer Vision

The original idea for FaultLines came from a deceptively simple hypothesis: if architects and civil engineers could recognize common structural defects just from looking at a building, could we teach a computer to do the same based off images of buildings?

Before
An early study of the FaultLines algorithm, May 2023.

Stress testing using a physical sample has long been considered the gold standard for assessing a building’s structural integrity. However, many citizens are discouraged from pursuing this option due to years-long wait times, potential legal implications, and municipal or bureaucratic backlogs.

Traditional risk assessment studies, on the other hand, primarily rely on human-generated datasets, which are highly accurate but time-consuming and resource-intensive to produce. These studies often take place within rather static GIS environments. Moreover, the findings are rarely presented in an accessible, easy-to-understand format that can effectively inform the broader public.

CADASTRAL

GEOLOGICAL

LEGAL

IMAGERY

HISTORICAL

Visual indicators that architects or engineers use to make informed assessments can now be identified by multi-modal image processing algorithms. With the ever-growing amount of data available about our cities—such as live bus schedules, real-time traffic maps, or panoramic images of virtually every street—these tools are becoming increasingly powerful. The data we all utilize today, through platforms like Google Street View or IMM's own Panorama 360 City Street Viewer, combined with recent advancements in AI and computer vision algorithms, allows us to analyze the built environment in new ways, at exponentially larger scales, with greater speed, and using far fewer resources.

STREET LEVEL IMAGERY

StreetView images that our workflow intelligently collects and pre-processes for semantic image segmentation.

To test our hypothesis, we first needed to identify points where two buildings were either close together or explicitly touching at one or more surfaces. To automate this process, we developed a custom Python script in QGIS that enabled us to query street imagery showing only the buildings that are sharing a wall. Once obtained, we rectified these images to correct any image segmentation or calculation issues that might have arisen due to varying perspectives.

Windows from both sides of the adjacency line are (mostly) segmented for processing.
Windows of each building of both sides of the adjacency line are segmented for processing.

These rectified street images then needed to be intelligently segmented to distinguish between the left and right buildings, as well as the windows within each facade. To address this, we developed a custom Geospatial AI workflow that leverages the Grounding DINO and Segment Anything models, both of which are publicly available on HuggingFace and Meta AI. By combining these two models, we can semantically process various objects—such as buildings, sidewalks, cars, windows, doors, and walls—across Istanbul’s street imagery. For this study, we further refined this workflow to detect and calculate misalignments in adjacent buildings, which is one of the five key visual cues that may indicate critical structural deficiencies.

Windows from both sides of the adjacency line are (mostly) segmented for processing.
Facade segmentation enable us to make calculations - such as measuring the distance between windows,
which allowed us then to measure difference between floor levels.

Semantic image segmentation enabled us to generate grouped masks for each window on both facades, using red and blue color maps for easier identification. We then created subgroups for vertical and horizontal arrays of windows, allowing us to index facade elements. This approach enabled us to perform calculations based on specific groups of windows by floors or bays. By measuring distances from either side of the adjacency line and comparing them with the opposite side, we were able to generate an adjacency score—an integer value representing the length difference between corresponding floor slabs of the left and right buildings.

Indexin and naming convention.
INDEXING AND NAMING CONVENTION THAT ALLOWED FOR
TRANSFERRING, TRACKING AND MATCHING ATTRIBUTES BETWEEN GIS AND ML ENVIRONMENTS.

The processed images were then saved with a naming convention that included latitude, longitude, index numbers for buildings on both sides of the adjacency line, and the adjacency score. This method facilitated the seamless transfer of information between GIS and image segmentation environments, allowing us to match these numbers with their geospatial counterparts in QGIS, where we could visualize and analyze the results, as shown below.

Merging adjacency calculations back in QGIS for visualization.
MERGING ADJACENCY CALCULATIONS BACK WITH CORRESPONDING BUILDING IN QGIS FOR VISUALIZATION

In summary, our workflow encompassed four main steps:

1. Finding street-facing points at which two buildings share one or more surfaces.
Query a street-level image of this adjacency line for further processing.
2. Semantically segmenting the image to find out floor slabs and distances based on street facing elevations.
3. Calculating the distance between floor slabs of buildings from both left and right side of the adjacency line.
4. Assigning this calculated score back onto the GIS object.

Evaluation


We evaluated the accuracy of zero-shot prompt-based image segmentation for estimating floor misalignment-related pounding effects in adjacent buildings. This evaluation was based on a series of metrics applied during score generation and was conducted on a randomly selected test group of buildings within our pilot ZIP code, 34188. To achieve this, we compared machine-generated image segmentation results and floor misalignment scores with human-evaluated results across the same images using three distinct methods:

1. Annotators rated floor misalignment levels from A (perfectly aligned) to F (completely misaligned).
2. Annotators compared AI-generated results with corresponding human evaluations.
3. If an issue was found in the post-processed image or score, annotators specified the error based on a comprehensive list of points of failure, ranging from object obstruction to facade misindexing.

POST-PROCESSING
SUCCESS RATE

65.38%

SEGMENTATION AND POST-PROCESSING (E.G. FACADE INDEXING)

AI ESTIMATION
SUCCESS RATE

84.61%

EXCLUDING MISINDEXING & POST-SEGMENTATION PROCESSING FAILURES

POTENTIAL
SUCCESS RATE

97.11%

IN THE CASE OF SEGMENTATION SUCCESS RATE BEING 100%

Our results showed an 84.61% success rate in the semantic segmentation of facade elements. The remaining samples could not be successfully segmented due to extreme facade irregularities, vehicle and object obstructions, misaligned perspectives, angles, or headings prior to capturing street imagery, and low raster quality after image processing.

Despite these challenges, the results underscore the potential of zero-shot models for practical applications in raster and geospatial use cases, such as our experiment. Future improvements could leverage the newly released SAM 2.0 model by Meta AI, which offers significantly higher accuracy rates. Additionally, incorporating more accurate geospatial datasets and up-to-date raster imagery could further enhance segmentation precision.

Merging adjacency calculations back in QGIS for visualization.
Merging adjacency calculations back in QGIS for visualization.

INTERACTIVE MAP

By intelligently detecting adjacent buildings and accurately calculating critical measurements across neighboring structural frames within a GIS environment, we were able to share these findings on an interactive map interface. The information was not only represented through static geometries but was also enriched with calculation results, explanations, and machine-generated process images. This approach ensured that our workflow accurately reflected real-world scenarios and allowed viewers to critically assess the results for transparency.

CHAPTER 07

Interactive Map

The fundamental aim of this project has always been to create an interactive platform where people can access critical information about their buildings in a clear, engaging, and easy-to-use way.

By leveraging recent advancements in computer vision, AI, and computing power, we've trained computers to examine the built environment much like an architect or engineer would, parsing visual information into meaningful insights. The resulting datasets are then funneled into an immersive interactive map where anyone can look up their address and access machine-generated structural insights.

When dealing with AI-generated data, transparency is essential, especially because much of this data comes from "blackbox" processes that aren't always easy to control or interpret. To address this, we made sure that every step of our computations on the initial images was clear, explainable, and easy to share. We were upfront about our objectives with each calculation and used straightforward language to encourage users to critically evaluate the AI-generated results. This approach ensures that these "risk insights" are seen as part of an ongoing process rather than definitive answers, while also equipping people with the knowledge to identify important structural indicators in their surroundings.


Ethical Concerns &
Future Research Discussions


While this study maintains an optimistic perspective on AI-driven initiatives for the public good, there remains numerous complex challenges to be addressed moving forward. Below are some highlights from this year-long discussion:

1. How can we develop better validation methods for AI assessments beyond current practices? What testing procedures ensure AI models are validated against benchmarks or ground truth data? How will structural engineers review AI-generated assessments, and how will their expertise refine the models?

2. Structural issues often stem from internal defects not visible externally. How does the project address undetectable flaws? How can we combine AI-generated surface-level data with existing datasets like municipal inventories, geological surveys, and seismic history to gain deeper insights into the built environment?

3. How can we clearly differentiate AI-generated assessments as insights rather than factual data? Could this distinction help develop solutions that protect the most vulnerable, instead of being used as grounds for forced evacuations or other punitive measures?

4. How can we communicate the limitations of AI assessments to build trust in the data without causing undue fear or stress? How can the project share information that encourages proactive safety measures?

5. Obligation to inform vs. risk of harm: Is there a moral imperative to inform residents about the structural safety of their buildings, even if the information may cause panic or distress among those unable to relocate or retrofit?

6. How should access to this data be managed to balance open availability with privacy concerns? How can the project ensure that any citizen who wishes to access the information can do so, while respecting the privacy and rights of those who choose not to participate?

7. To what extent are the AI algorithms and decision-making processes transparent to stakeholders? How does this transparency build trust in the assessments?

8. How can educational resources alongside risk assessments help residents make informed decisions? How can the project involve community members to ensure actions align with their needs and capabilities?

9. Who is responsible if an inaccurate AI assessment leads to harm or consequences for property owners?

10. What protocols should be established to prevent the misuse of AI-generated data by public or private organizations, such as governments or insurance companies, ensuring that vulnerable populations are not disproportionately targeted or disadvantaged?


Using the Map


Below is the first publicly accessible interactive map, the culmination of a year-long research effort at the Center for Spatial Research. As of now, you can explore risk insights related to "misaligned floor calculations" in Hürriyet Mahallesi, a pilot neighborhood densely populated with buildings constructed before the 1999 Earthquake, where open spaces and greenery are scarce. This area is particularly noteworthy in the IMM Earthquake Risk Simulation dataset due to its high projected levels of damage and casualty rates.

Use the search bar to find building names, door numbers, addresses, and more (currently limited to available ZIP codes), or simply hover over a building to view a detailed risk report and a visual summary of the tests conducted. The interactive map will gradually expand to cover all boroughs and ZIP codes across Istanbul, with more tests and data contributing to the overall risk score for each building.

FaultLines

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