Archaeology Field Practices

Archaeology from above - using drones, GPR, and magnetometers. In the Mimbres region of New Mexico, Measur and Altomaxx supported archaeologists in a non-invasive survey of ancestral sites. A drone equipped with Radar Systems, Inc. Zond Aero 500 NG GPR and SENSYS - Magnetometers & Survey Solutions MagDrone R3 magnetometer helped identify buried walls, fire pits, and room blocks, without the need to dig. The setup included a DJI M300 drone, SPH Engineering SkyHub, and UgCS for flight planning, turning a rugged landscape into a 3D map of the past. A great example of how UAV-based geophysics is reshaping fieldwork and cultural preservation. What used to take days on foot can now be done in hours, with better resolution and access to hard-to-reach areas.

Have you ever wondered how scientists can discover buried treasures and ancient ruins without digging a single hole? That’s the magic of Geophysics! By using non-invasive techniques like Ground Penetrating Radar (GPR) and Magnetometry, geophysicists can "see" beneath the surface and detect anomalies that hint at archaeological remains — walls, tombs, even whole cities. This approach: Saves time and cost, Preserves the site, And helps direct excavations more precisely. In Egypt — the land of ancient wonders — geophysics is becoming a powerful ally to archaeologists. Imagine using science to uncover the secrets of Pharaohs without disturbing the soil! Geophysics isn’t just about oil and earthquakes. It’s also about unveiling human history hidden deep beneath our feet. --- Geophysicist AbdelFattah Sabry ⚡ Sources: Conyers, L. B. (2013). Ground-Penetrating Radar for Archaeology. Clark, A. (1996). Seeing Beneath the Soil: Prospecting Methods in Archaeology. #Geophysics #Archaeology #GPR #Geoscience #ScienceCommunication #LinkedInScience

Forensic Paleoradiology—a discipline that bridges forensic science, radiology, and archaeology to study ancient human remains without damaging them. Forensic paleoradiology applies modern imaging techniques such as Computed Tomography (CT), X-rays, and 3D digital reconstruction to analyze mummies, skeletal remains, and artifacts from archaeological contexts. These techniques help researchers determine age, sex, stature, disease patterns, and even trauma associated with death, all while preserving fragile remains that are thousands of years old. Unlike conventional forensic radiology, which focuses on modern medico-legal investigations, forensic paleoradiology helps us understand health, lifestyle, and causes of death in ancient populations. Case Study: The Mummy of Pharaoh Seqenenre Tao II One remarkable example is the study of the mummy of the Egyptian Pharaoh Seqenenre Tao II, who ruled during the 17th Dynasty. For many years, researchers debated whether his death was due to a ritual killing, an assassination, or battlefield trauma. Using CT scanning, scientists were able to visualize internal injuries hidden beneath the mummy wrappings. The scans revealed multiple severe craniofacial injuries caused by different types of weapons, suggesting that the pharaoh likely died in close combat during battle against the Hyksos rulers. The imaging also showed that embalmers had attempted to conceal these wounds with filling materials during mummification. This study demonstrated how modern imaging can reconstruct historical events, reveal ancient warfare practices, and clarify centuries-old mysteries—without unwrapping or damaging the mummy. Forensic paleoradiology highlights how technology allows us to respectfully study the past while preserving invaluable archaeological heritage. As someone working in forensic science, it is fascinating to see how investigative techniques used in modern medico-legal practice can also help solve mysteries from thousands of years ago. Reference: https://lnkd.in/gnWrfpGP https://lnkd.in/gs4DGRPS #ForensicScience #Paleoradiology #ForensicRadiology #Archaeology #AncientMysteries #MedicalImaging #InterdisciplinaryResearch

🧠 What if AI had the power to ‘see’ beneath the Earth's surface? 🤯  This question has driven me for years now. What if we could apply the power of SciML to tackle this challenge? Today, I’m beyond excited to share that we at S2 Labs, alongside my incredible partners at EmPact Artificial Intelligence, Texas Department of Transportation, Drone Geoscience, LLC, Kraken Robotics, Amazon Web Services (AWS) and Shadeform (YC S23), have successfully demonstrated a groundbreaking (pun intended!) non-invasive technology—one that could transform the way we explore the unseen world below us.  Subsurface imaging is essential for construction, energy, and environmental monitoring, yet traditional methods have limitations in resolution, depth, and cost. Our latest research demonstrates the power of deep-learning-based 3D inversion of magnetic data to enhance subsurface imaging—both onshore and offshore. 🔍 Key Highlights:  ✅ Used AI-driven inversion to map buried utilities before construction at Texas A&M’s Rellis Campus  ✅ Located oil well conductors buried under 35-45m of sediment in the Gulf of Mexico/America, post-Hurricane Ivan  ✅ Achieved unprecedented accuracy (17 cm precision) compared to excavation data 🌍 Why does this matter? AI-based geophysical techniques are scalable, cost-effective, and adaptable across diverse environments. I’m truly excited to see how this can reduce carbon footprint by slashing construction costs and delays, preventing oil and gas leaks, and minimizing environmental disruption through smarter, data-driven decision-making.    A heartfelt congratulations to my fellow authors: Souvik Mukherjee, Jacques Guigne, Gary Young, Harshit Shukla, Kevin Kennelley, Dillon Hoffman, Ron Bell, Bill Barkhouse! I would also like to thank my cloud partners Vidyasagar Ananthan, Ph.D., Xuele (Ryan) Qi, Srinivas Tadepalli, Ph.D., MBA, Ed Goode and Ronald Ding. 🚀 Read the full study here:  https://lnkd.in/ejUN6Hvj 📌 #Geophysics #ArtificialIntelligence #MachineLearning #DeepLearning #Energy #Infrastructure #AIinGeoscience   

🏛️ AI is Literally Unearthing History - And You Probably Haven't Heard About It Your next major archaeological discovery isn't waiting in a dusty archive. It's hidden in satellite data. A few months ago, researchers used AI + Cold War-era satellite photos to discover 4 previously unknown ancient Mesopotamian cities that archaeologists had searched for decades to find. Here's what's changed: ✅ 90% accuracy in detecting buried civilizations from space ✅ DeepMind's AI restores ancient texts so damaged that only 25% could be read before - now historians read 72% correctly with AI ✅ Stone tool classification: An AI model outperformed human archaeologists at distinguishing real artifacts from natural rocks ✅ 3 hours to map what used to take 3 years (LiDAR + machine learning) The wild part? This isn't replacing archaeologists. It's supercharging them. When historians used DeepMind's Ithaca system to restore ancient Greek inscriptions, their accuracy jumped from 25% → 72%. The AI did the heavy lifting; humans made the final calls. - Google DeepMind is literally teaching AI to read ancient languages - Open-source tools (like PyPotteryLens) are democratizing access to AI archaeology - not just for Harvard, but for any university - Al-Azhar University is opening a dedicated AI + Islamic Archaeology faculty in 2025 - Satellite AI is racing against time as looting and climate change destroy sites faster than we can excavate This isn't the future of archaeology. It's happening right now. 🔥 Will we use AI to preserve our heritage - or will we let it concentrate power over human history in the hands of a few tech companies? #AI #Archaeology #History #DeepLearning #Innovation #QuantumHistory #ArchaeologyTech #HistoricalAI #DeepMind #MachineLearning #AlAzharUniversity #MIT #Cambridge #Oxford #Archaeology

When Dutch explorers reached Rapa Nui in 1722, they saw giant moai statues, no trees, and a small population. They assumed ecological collapse—deforestation, overpopulation, warfare, even cannibalism. It became a cautionary tale repeated in textbooks worldwide. Now, archaeologists Carl Lipo (Binghamton University) and Terry Hunt (University of Arizona) are rewriting that narrative using drone imagery and GIS technology. What they're discovering challenges everything we thought we knew. The evidence tells a different story: one of ingenuity, not catastrophe. The islanders engineered sophisticated rock mulch gardens in nutrient-poor soil. They built well-like traps to capture freshwater from coastal springs. They moved multi-ton moai statues by rocking them into place with rope—the trees were never needed. This research has gained prominent attention from the science press, including featured coverage in The New York Times Science section, as new data replaces old assumptions. Esri's Lain Graham, Ph.D., RPA, who leads the National Government Sciences Solution Engineer team, explores how GIS technology made this breakthrough possible. Using drones, the researchers captured 20,000 high-resolution images and created a digital twin of the entire island—allowing them to study archaeological sites without excavation, engage the Rapa Nui community with their findings, and track landscape changes over time. You can explore the 3D island yourself through Esri's 3D Scene Viewer, zooming into the Rano Raraku quarry where hundreds of moai remain embedded in volcanic rock, frozen mid-creation when the work stopped centuries ago. You can read more about the Rapa Nui people's real history and explore their world in 3D: https://lnkd.in/g4_3fWba #GIS #Archaeology #RemoteSensing #DigitalTwin #Innovation #Science

𝐀𝐫𝐜𝐡𝐚𝐞𝐨𝐥𝐨𝐠𝐲 𝐢𝐬 𝐧𝐨 𝐥𝐨𝐧𝐠𝐞𝐫 𝐥𝐢𝐦𝐢𝐭𝐞𝐝 𝐭𝐨 𝐞𝐱𝐜𝐚𝐯𝐚𝐭𝐢𝐨𝐧 𝐚𝐥𝐨𝐧𝐞 — 𝐢𝐭 𝐢𝐬 𝐫𝐚𝐩𝐢𝐝𝐥𝐲 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐭𝐡𝐞 𝐩𝐨𝐰𝐞𝐫 𝐨𝐟 𝐆𝐈𝐒 𝐚𝐧𝐝 𝐑𝐞𝐦𝐨𝐭𝐞 𝐒𝐞𝐧𝐬𝐢𝐧𝐠. Today, technologies like satellite imagery, LiDAR, and geospatial analysis are helping archaeologists uncover hidden landscapes without disturbing the ground. From identifying buried structures to mapping ancient settlements and tracking landscape evolution, GIS and RS are redefining how we explore the past. 🔍 Key Applications: • Detection of buried archaeological sites using multispectral and SAR data • Mapping ancient river courses and lost civilizations • Predictive modeling for site identification using spatial analysis • Monitoring and preservation of heritage sites • 3D reconstruction of archaeological landscapes With platforms like Google Earth Engine and advanced machine learning techniques, large-scale archaeological analysis has become faster, more accurate, and highly scalable. As a GIS professional, it's exciting to see how geospatial technologies are bridging the gap between history and innovation — helping us protect cultural heritage while discovering stories buried for centuries. #Archaeology #GIS #RemoteSensing #Geospatial #CulturalHeritage #SatelliteData #LiDAR #EarthObservation #DigitalArchaeology

AI Uncovers 5,000-Year-Old Ancient Civilizations Hidden Beneath The World’s Largest Deserts -- https://lnkd.in/gsNauxPt <-- shared technical article -- https://lnkd.in/gYs3PAKD <-- shared paper -- [older paper, but still fascinating…] “Exploring vast desert landscapes has long been a formidable challenge for archaeologists. Shifting sands and immense scales often obscure historical treasures, leaving much of humanity’s ancient past hidden beneath the surface. However, a revolutionary breakthrough in artificial intelligence (AI) is transforming this age-old endeavor, enabling researchers to uncover ancient sites previously concealed beneath desert sands. Desert terrains such as the Rub Al-Khali, also known as the Empty Quarter, span hundreds of thousands of square kilometers. Traditional archaeological methods, including ground surveys, are labor-intensive, costly, and time-consuming. These limitations have left vast swathes of potential historical sites unexplored. The integration of cutting-edge technologies like Synthetic Aperture Radar (SAR) and machine learning algorithms is changing the game. By combining these tools, researchers are dramatically improving the efficiency and precision of archaeological discovery. Synthetic Aperture Radar (SAR) is a remote sensing technology that uses radar signals to create high-resolution images of the Earth’s surface. Unlike optical imaging, SAR can penetrate obstacles such as vegetation, ice, or sand, making it particularly useful for detecting features buried beneath desert landscapes. By capturing subtle variations in surface and subsurface structures, SAR data provides a foundation for identifying archaeological sites. Machine learning algorithms, particularly those in deep learning, process SAR data to identify patterns and anomalies. By training these algorithms on known archaeological sites, researchers can teach them to recognize features that suggest buried settlements, pathways, or other human-made structures. This combination significantly reduces the manual labor required and increases the likelihood of discovering previously unknown sites…” #GIS #spatial #mapping #desert #archaeology #MiddleEast #ancienthistory #AI #RubAlKhali #EmptyQuarter #SyntheticApertureRadar #SAR #remotesensing #machinelearning #artificalintelligence #deeplearning #settlements #pathways #humanmade #spatialanalysis #PALSAR2 #Worldview3 #SaruqAlHadid #Dubai #UEA #UnitedArabEmirates