City of Gold: The lost city of Paititi may be the Most Lucrative Historical Find
Many explorers have died searching for Paititi: the Lost City of Gold and many became convinced that the city was hidden in the last undiscovered regions of the Amazon. The infamous journeys to discover Paititi was also what inspired Sir Arthur Conan Doyle to write “The Lost World.”
Much has been documented about the divine sense of quest to discover this magical kingdom. From treasure hunters to archaeologists and explorers, Paititi has until now remained the subject of lore and tribal legend spread through generations. But now, a remote location in the Peruvian Amazon thought to be the legendary Lost City has been discovered and is the target for a professional expedition taking place this summer.
Inca traditions mention a city, deep in the jungle and east of the Andes area of Cusco which could be the last Incan refuge following the Spanish Conquest. The Spanish conquistadors pillaged Cusco for its gold and silver, they only discovered a small amount of bounty in the capital, and the bulk of the mass treasure has never been found. Just recently a Spanish Galleon that sunk over 300 years ago, was discovered off the coast of Columbia and possibly holding billions of dollars worth of treasure looted from Peru.
In 2001, Italian archaeologist Mario Polia discovered the report of a missionary named Andres Lopez in the Vatican archives. In the document, which dates from 1600, Lopez describes in great detail, a large city rich in gold, silver, and jewels, located in the middle of the tropical jungle called Paititi by the natives. Lopez informed the Pope about his discovery and the Vatican has kept Paititi’s location secret for decades.
Paititi: Last City Of The Incas
To understand the research, we must first know what Paititi is. Paititi is most commonly believed to be the last refuge of the Incas. After substantial research, scientists believe Paititi may have been home to the Chachapoyas, warriors and skilled builders ruled by the Incas in the north Cusco region.
Until the arrival of the Spaniards in South America in 1532, there was the Inca Empire , Tavantisuyu (“Four Corners” in Quechua), which was the most potent political structure on the continent. Governed from its capital, Cusco, it controlled vast areas covering parts of Peru, Ecuador, Colombia, Bolivia, Chile, and Argentina. The Inca civilization , although very developed in political, administrative, and urban respects, lacked the use of horses, armor, and firearms for war. Armed with just bows and arrows, the Inca warriors were no match for Francisco Pizarro , the brutal Spanish conquistador. With only two hundred followers, Pizzaro was able to capture the Inca emperor, Atahualpa, and force his warriors to retreat. The remnants of Inca royalty escaped to Vilcabamba, situated in the jungle-covered lowlands northwest of Cusco.
But after a few decades, their small state fell, and the last Inca ruler, Tupac Amaru, was captured and executed. Thus, the final chapter of the Inca story came to an end. In the following centuries, the ruins of Vilcabamba and its whereabouts slipped into oblivion with the forest gaining the upper hand.
Meanwhile, various legends and testimonies began to appear, pointing to the existence of another significant undiscovered center of Incan civilization — Paititi. According to some of the legends, it should be located in the wild, uncharted region northeast of Cusco. Over hundreds of years, many explorers have tried to find Paititi by exploring the region with old maps and accounts. However, the harsh environment, wildlife, and terrain have so far prevented any relevant discoveries regarding where Paititi actually is.
This is where Paititi Research is changing the game. Instead of blindly venturing into uncharted territory, we have first completed extensive research. This scientific approach to exploration is already yielding many positive results.
The Science Used To Narrow Down Where Paititi May Be Hidden
The difficult part about searching for Paititi is that the region is mostly uncharted, many parts of the terrain are impassible, and the vegetation is thick and obstructive. Due to these conditions, Paititi Research used remote sensing and geo-information systems (GIS) for their research. The first provides up-to-date information about the most inaccessible areas from artificial earth satellites. The second provides tools for the organization of data and a thorough geospatial analysis .
Based on specialized software, such as PostGIS, Earth Engine, and QGIS, Paititi Research created a multi-user GIS and a dedicated database that melted together all sorts of data concerning Paititi. It includes satellite and aerial images (e.g., GeoEye-1, RapidEye, and UAVSAR), old and modern maps, written and verbal testimonies, results of other expeditions, authentic documents, and legends. This conglomerate of information resulted in unprecedented outcomes and allowed Paititi Research to perform sophisticated geographic analyses. For example, the team assessed the morphometric characteristics of the terrain, modeled water flows, calculated incoming solar radiation, explored landscapes in 3D, etc. The analysis of all this data was essential in order to narrow down the area that could contain Paititi.
A map of the river network in the target region was crucial to finding Paititi. The literary sources, old maps, and verbal accounts mentioned rivers as landmarks. Therefore, to study and apply the information in these sources, a map with river names was needed. By using a digital elevation model (DEM), Paititi Research built a river network and labeled the river names. The screenshot above shows the process of georeferencing old maps with the distinct meanders of known rivers.
Another important feature needed in the maps was the morphometric relief characteristics of potential areas. Mountainous environments constrain movement, so settlements cannot be made on terrain with certain slopes. Several studies in the Alpine Region already confirmed this idea. Therefore, the surface steepness of ancient and modern settlements in the area of interest, such as the ruins of Vilcabamba and settlements in the valley of the Yavero River, were studied. It was found that all places that were settled had a slope grade of less than twenty degrees. This significantly reduced the areas that could contain Paititi.
In addition, a solar radiation map was also created. Areas with too little solar radiation are unfavorable for life. Therefore, Paititi Research created a solar radiation distribution map. The team used the radiation levels of modern settlements and existing ruins to narrow down the possible areas containing Paititi even further. To be able to interpret all of these maps better, Paititi Research used three-dimensional modeling.
Finally, from the maps discussed above, thematic maps were created. These maps include the Passability Map and the Settlement Suitability Map. The Passability Map was created using surface slope and tree density. This map shows areas where people can and cannot walk on foot and was used for planning the Paititi Research team’s expedition routes. Dark green areas in the map correspond to highly passable areas, while red means “impassable.”
Furthermore, Paititi Research created the Settlement Suitability Map using the slope steepness, and solar radiation maps explained earlier. This map shows flat and well-lit areas that are suitable for human activities which could contain Incan archaeological sites. The picture below demonstrates a Fragment of the Settlement Suitability Map in the area around Machu Picchu.
As you can see, the famous Incan site is situated in a “green” zone, which means that the area is suitable. Red corresponds to highly unsuitable regions. The initial area of our research was approximately 1300 km 2 (502 square miles). After mapping settlement suitability, we reduced the research area dramatically. Focusing on highly suitable zones, the team studied high-resolution imagery in different spectral ranges: visible, near-infrared, and microwave. This revealed patterns and structures that were interpreted as potential archaeological sites. Some of them are indicated below. These three pictures cover the same area but highlight different aspects: multi-spectral optical image, settlement suitability map, and a radar image.
Another exciting result of the Paititi Research team’s work was the Potential Inca Road Network map. Using terrain parameters, satellite imagery, and already known ruins and Inca trails, the team managed to reconstruct the ancient Inca road system for the region of their study. This map can also be explored and investigated for archaeological sites. The GIS screenshot below shows a fragment of the map with discovered Inca trails (continuous orange lines) and reconstructed paths (dashed lines), overlaid on a high-resolution satellite image.
Paititi Research’s Expedition to Find The Lost Incan City
Since the beginning of 2017, Paititi Research has collected, analyzed, and evaluated a considerable amount of materials originating from their research. The team found some potential sites and considered six of them as Paititi Candidates. In June 2019, they organized a land expedition to obtain new information, refine the digital research model of Paititi, and examine their possibilities and equipment. The expedition started in Cusco, Peru. From Cusco the expedition team traveled to Choquecancha and finally, Rio Yavero. Throughout the journey, the team was faced with injuries, wildlife, and the harsh environment of the Andes. In Choquecancha, uncharted Incan terraces were found, shown earlier in this report, thus demonstrating that there are many Incan sites yet to be found.
As a result of this expedition, Paititi Research selected one of the six Paititi Candidates, on which they are now focusing all their efforts. To consolidate the outcomes of their research, the Paititi Research team is working on a paper for a peer-reviewed journal. At the same time, they are establishing relationships with Peruvian universities to get support for the final expedition, which will confirm or disprove their findings.