Can High-Resolution Imagery Resolve the Ararat Mystery?

Geospatial SolutionsTo the scientific mind, it is easy to see a natural, geological formation when looking at the “Ararat Anomaly” on Turkey’s Mt. Ararat: a lava flow, or perhaps some sort of rock dome. But it is undeniable, at least for the layman, that the shape suggests a ship underneath the ice and snow (albeit one of modern design with tapered bow and stern, not the rectangular barge shape often ascribed to Noah’s Ark).

The myths and legends — or the facts, if you’re a believer in the Qur’an or the Bible’s Old Testament — surrounding Noah’s Ark have persisted for thousands of years. The debate has raged nearly that long about the existence of the Ark, the location and identification of Mt. Ararat, and even whether or not the Ark landed on that particular mountain.

There have been a number of expeditions to Mt. Ararat over the centuries, but many have run afoul of the weather, the geology, and the political and religious intrigues of the region — the area of the Anomaly itself has never been explored on foot. That’s why the Anomaly’s history dates only to 1949, when a U.S. Air Force reconnaissance plane took photos of the area from a mile away and an altitude of 14,000 feet, capturing a large, linear shape protruding from a glacial ice cap at the southwest edge of the western plateau of Mt. Ararat. Defense analysts determined that the object, whatever it was, had been partially exposed by an avalanche.

So perhaps it’s only fitting that GIS science and satellite technology have picked up the quest for Noah’s Ark. Military and spy satellite imagery and aerial photography — both official and declassified, as well as rumored and apocryphal — have fueled the search. But it is modern commercial imagery that is currently leading the way, thanks in large part to the efforts of researcher Porcher Taylor.

Commercial Birds Take Up Where Spy Sats Left Off

Taylor, an associate legal professor in the University of Richmond’s School of Continuing Studies, first documented his efforts for Geospatial Solutions in June 2006. For him, the search for the Ark is a hobby, albeit a serious one; he describes himself as “an armchair satellite archaeologist.”

He was driven at first by rumors of Corona satellite images of Ararat taken in 1974, and later by his work in the ’90s with George A. Carver Jr., a former CIA deputy for national intelligence. Their efforts lead to the declassification of the 1949 aerial photos of the anomaly. Although Taylor’s requests for the 1974 satellite images, among others, are still pending, commercial satellite imagery and GIS technology may make them moot, he said.

As Taylor relayed to Geospatial Solutions two and a half years ago, two commercial satellites — IKONOS and QuickBird — shed some light on the Ararat Anomaly, flying missions on his behalf. The images depicted an elongated, symmetrical structure approximately 1,015 feet in length, but image analyst Rod Franz was unable to detect anything hidden under the ice and snow.

Ararat Anomaly
A panchromatic electro-optical image of the Ararat Anomaly, taken by the QuickBird satellite.

In his latest attempt to find a conclusive answer, Taylor had the images analyzed by Christopher Barnes, an associate professor of digital signal processing at the Georgia Institute of Technology’s School of Electrical and Computer Engineering. Barnes recently finished a project for the U.S. National Geospatial-Intelligence Agency (NGA) on unsupervised image data mining — applications that autonomously detect, classify, and identify features, objects, and scenes in image data flows and archives. The underlying technology involves building a heterogeneous database of indexed, expertly analyzed images; the algorithm at the heart of Barnes’s technique queries that database based on pixel content. It is, in essence, image data mining.

“That’s the most exciting application, and it can be used for autonomous attribution, feature extraction, and Web searching of images,” Barnes explained. At Taylor’s request, Barnes applied the same technique used in his NGA project to create an unsupervised hierarchical segmentation analysis of the electro-optical panchromatic image of the Ararat Anomaly provided by QuickBird.

Subjecting the image to a first pass of analysis using Barnes’s algorithm provided a coarse level of analysis to define segmentation. During subsequent passes, the number of segmentation classes grew with each pass; each pass represented a segmentation level. The idea was to see if there were segmentations unique to the anomaly when compared with the area around it, Barnes explained.

The sigma tree parameters of the segmentation analysis included:

  • 37 x 37 pixel block texture analysis
  • more than 58,000 training blocks
  • 8-level sigma tree
  • 4 nodes at each level.

The end result was a uniqueness map of the anomaly. Barnes’s analysis seemingly reinforces what Franz found in 2006: the anomaly consists of linear structures that are long and smooth. The orientation and linear nature of the structures that persist through the various segmentations is rather uncommon, but they could very easily be geological in nature, he said. “I can say that this part of the image looks similar to the other parts,” he said, comparing the various segmentations. The resulting uniqueness map reveals many unique areas within the anomaly, but they are not completely segmented out.

Ararat Anomaly Segmentation Analysis
Christopher Barnes subjected the image to multiple analyses to define segmentation classes, resulting in a uniqueness map of the anomaly.

Christopher Barnes subjected the image to multiple analyses to define segmentation classes, resulting in a uniqueness map of the anomaly.

As a scientist, Barnes — perhaps understandably so — wasn’t prepared to commit to anything beyond that. “I think it looks like a really good snowboarding site,” he quipped, noting again that the anomaly is smooth, elongated, and curved.

Taylor is encouraged by Barnes’s analysis. What struck Taylor about the QuickBird photo is that the anomaly seemed very distinguishable from the surrounding terrain; now Barnes’s analysis confirms that it is. “It is intriguing to me, from a layperson standpoint, that you can see these patterns,” Taylor said.

Another geography professional that Taylor consults with, Farouk El-Baz, is skeptical that the Ararat Anomaly is anything but a natural formation. El-Baz is a research professor and director of the Center for Remote Sensing at Boston University. Although he has acknowledged that Barnes’s analysis is intriguing, he told Geospatial Solutions that he doesn’t see anything to suggest that it is was made by anything but Mother Nature.

“Usually when you have people talk about something over the course of many millennia, there may be a hint of reality behind that,” El-Baz said, noting that many people, including both religious and scientific experts, have sought to find evidence of Noah’s Ark on Ararat. “There is a lot of folklore behind this notion,” he added.

Nevertheless, from a technical view, everything El-Baz has seen of the Ararat Anomaly up till now can be interpreted as natural features. “I would not at all point to anything there that is man-made or out of the ordinary. Everything I see I interpret as light, slopes, and the effects of shadow.”

El-Baz is no stranger to satellite archeology. He co-authored a book on the subject, Remote Sensing in Archaeology, and has used remote sensing and satellite imagery analysis for two archaeological projects in Egypt, in addition to teaching those skills to others. “They are certainly are very useful techniques,” El-Baz said. “But one must be careful to interpret what one sees; light can play tricks, especially when it comes to shadows,” he cautions.

The More We Look

Taylor is neither troubled nor disappointed by the skepticism of experts; rather, he appreciates their scientific approach. “My goal is simple, to make the anomaly more discernible . . . transparent to the dispassionate, critical eyes of scholars like Dr. Barnes and Dr. El-Baz,” he said. He wants the evidence to decide whether it’s worth making an expedition to the site — a journey that could determine whether the Ararat Anomaly is the Ark, some other man-made structure, or just an unusual formation of rock, ice, and snow. Even if it proves to be the latter, that would be okay by Taylor, he said; he just wants to find out what it is.

As Taylor himself readily acknowledges, the likelihood that such a large wooden structure could retain its shape while buried in glacial ice for millennia is highly unlikely. Nevertheless, the more the site is imaged, the more provocative it becomes. “I’m just intrigued that the more we look . . . the more it looks like a boat,” he said.

“I’m deeply indebted to the likes of Chris Barnes, a world-class scientist and scholar in his field,” Taylor continued. “I’m humbled, quite frankly, that someone of his caliber would take a look at the sat imagery and do a computerized pattern recognition.” He is grateful to El-Baz as well, he said, noting that El-Baz has taken the time to review all of the imagery and analysis that Taylor has garnered on the Ararat Anomaly over the years.

Taylor is also excited about the higher resolution that can be achieved with the latest generation of commercial imaging satellites such as GeoEye-1, the successor to IKONOS that was launched September 6. He has approached GeoEye about flying another imaging mission over Ararat; DigitalGlobe, which launched the successor to QuickBird, Worldview-1, has already accepted his challenge.

Barnes agreed that the better resolution these satellites offer can only serve to better quantify the Ararat Anomaly. His algorithm and approach aren’t constrained by data dimensionality; a finer spectral content and more resolution for a localized analysis would enable him to further segment images, he said. Barnes also would like the opportunity to use Synthetic Aperture Radar (SAR) imagery, as well as color images from the likes of GeoEye-1.

“This is only spatial analysis, as it’s a panchromatic image,” he said of his segmentation analysis of the IKONOS image. “I’d be interested in throwing [the segmentation algorithm] at a color image.”

Editor’s Note: As explained at length elsewhere on this site this is a news story written by me for another publication. This originally appeared on Questex Media’s Geospatial Solutions website; that publication has been folded into sister publication GPS World, where the original story can still be viewed. Questex holds the copyright, of course.

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