Sky Maps of Prehistoric Britain

Were the Constellations Originally a Navigational System?

A Long-Term Research Project for 2026/7


Introduction

For thousands of years, humanity has looked upward and seen stories written in the stars.

Ancient cultures named constellations after animals, heroes, gods, monsters, hunters and mythical creatures. Archaeologists and historians generally assume these star patterns were primarily symbolic, religious, or mythological in nature. (Sky Maps of Prehistoric Britain)

But there is a major problem.

Most constellations do not actually resemble the creatures they supposedly represent.

The Great Bear resembles neither a bear nor a wagon.
Orion does not resemble a hunter.
Leo looks nothing like a lion.
Draco barely resembles a dragon.

In many cases, the supposed shapes appear forced, inconsistent, or entirely dependent on later artistic interpretation.

This raises an important question:

What if the original purpose of many stellar patterns was not mythology at all?

What if they were functional?

More specifically:

What if ancient star systems originally formed part of a navigational framework used by an early maritime civilisation operating across the flooded landscapes of post-glacial Europe?

This article outlines a new long-term research project planned for 2026, investigating whether the stars themselves may once have formed part of an integrated navigational system connected to prehistoric waterways, coastlines, monuments, and seasonal movement.

The purpose of this project is not to make unsupported claims, but to establish whether this idea can be scientifically investigated using measurable evidence.

(Sky Maps of Prehistoric Britain)
(Sky Maps of Prehistoric Britain)

The Foundation of the Hypothesis

The idea emerges naturally from the Post-Glacial Flooding Hypothesis (PGFH).

The PGFH proposes that Britain and north-west Europe remained significantly wetter for thousands of years after the end of the last Ice Age.

According to the model:

  • rivers were substantially larger,
  • groundwater tables were higher,
  • floodplains remained saturated,
  • estuaries extended far inland,
  • and water formed the dominant transport infrastructure.

If this model is broadly correct, then prehistoric populations would have depended heavily upon:

  • boats,
  • tidal systems,
  • river navigation,
  • shoreline movement,
  • seasonal travel,
  • and reliable orientation systems.

This immediately creates a practical problem.

How does a civilisation operating across a vast wetland and maritime environment navigate consistently over long distances without maps, compasses, or written instructions?

The answer may already be known.

Historically, maritime cultures throughout the world repeatedly used the stars.


 (Sky Maps of Prehistoric Britain)
(Sky Maps of Prehistoric Britain)

The Stars as Navigation

The use of stars for navigation is not speculative.
It is a historical fact.

Examples include:

  • Polynesian ocean navigation
  • Viking maritime navigation
  • Arab stellar navigation
  • Phoenician trade routes
  • Aboriginal Australian songlines
  • Mediterranean celestial navigation

In many cases, navigation was not based on maps in the modern sense, but on memorised stellar pathways tied to:

  • direction,
  • season,
  • tides,
  • winds,
  • coastlines,
  • and landmark sequences.

This is critical.

Ancient navigation often functioned as a memory system.

The sky became a stable framework onto which travel knowledge could be encoded.

Unlike coastlines or rivers, the stars moved predictably.
They provided consistency across generations.

If prehistoric Britain operated as a water-based civilisation during the early Holocene, then a stellar navigation framework becomes not only plausible, but potentially inevitable.


 (Sky Maps of Prehistoric Britain)
(Sky Maps of Prehistoric Britain)

The Missing Maps Problem

One of the great mysteries of prehistoric maritime movement is the apparent absence of navigational maps.

We know prehistoric populations travelled extraordinary distances.

Examples include:

  • Bluestone transport from Wales to Stonehenge
  • Maritime movement along Atlantic Europe
  • Doggerland migration networks
  • Long-distance exchange systems
  • Coastal monument distributions
  • River corridor settlements

Yet no conventional cartographic systems survive.

This may be because navigation itself was never primarily map-based.

Instead, route knowledge may have been embedded within:

  • oral traditions,
  • landscape markers,
  • astronomical cycles,
  • monument chains,
  • and stellar memory systems.

This possibility becomes especially interesting when viewed alongside the repeated placement of prehistoric monuments near:

  • rivers,
  • estuaries,
  • coastlines,
  • valley entrances,
  • tidal zones,
  • and elevated shoreline positions.

Long barrows, standing stones, beacon hills, avenues, dykes, and henges may not simply represent ritual locations.

Some may have functioned as navigational infrastructure.

 (Sky Maps of Prehistoric Britain)
(Sky Maps of Prehistoric Britain)

Long Barrows and Landscape Markers

One of the most intriguing aspects of prehistoric Britain is the repeated positioning of monuments along visible movement corridors.

Long barrows in particular often occupy:

  • ridge lines,
  • valley edges,
  • coastal approaches,
  • elevated viewpoints,
  • or route intersections.

Traditionally, these sites are interpreted almost exclusively through ritual or funerary frameworks.

But there is another possibility.

In a landscape dominated by wetlands and waterways, elevated monuments would naturally function as:

  • directional markers,
  • navigation points,
  • horizon indicators,
  • territorial signals,
  • or route beacons.

This does not exclude symbolic meaning.

The same structure can serve both practical and cultural purposes simultaneously.

Indeed, this dual-function model is common throughout human history.

Church towers, lighthouses, harbour beacons, hill forts, and even modern skyscrapers operate as both symbols and navigational markers.

The same may have applied in prehistory.


 (Sky Maps of Prehistoric Britain)
(Sky Maps of Prehistoric Britain)

Why the Constellations Matter

The more complex question is whether the constellations themselves formed part of this navigational architecture.

This project proposes a cautious working hypothesis:

The original meanings of some constellation systems may have been practical rather than mythological.

Over time, as the original navigational framework was forgotten, later cultures may have reinterpreted older stellar systems through:

  • mythology,
  • religion,
  • folklore,
  • and storytelling.

This process is not unusual.

Throughout history, practical systems often evolve into symbolic traditions once their original functions are lost.

Examples include:

  • flood myths,
  • agricultural festivals,
  • sacred geometry,
  • pilgrimage routes,
  • and ancient calendrical systems.

The same process may explain why many modern constellation interpretations appear visually unconvincing.

The animals and heroes may represent later narrative overlays applied onto much older orientation frameworks.

 (Sky Maps of Prehistoric Britain)
(Sky Maps of Prehistoric Britain)

Current Evidence Supporting the Idea

At present, there is no direct proof that constellations encoded prehistoric navigation routes.

However, several independent lines of evidence support the broader possibility.

1. Proven Stellar Navigation in Ancient Cultures

The use of stars for navigation is universally documented.

This establishes that:

  • stars can encode movement systems,
  • oral navigation is possible,
  • and complex route memory can operate without maps.

2. Water-Dominated Early Holocene Landscapes

The PGFH and associated geological evidence suggest:

  • extensive wetlands,
  • enlarged river systems,
  • inland tidal environments,
  • and maritime dependency.

Such environments strongly favour navigation-based societies.


3. Monument Distribution Along Water Systems

Many prehistoric sites cluster around:

  • rivers,
  • floodplains,
  • estuaries,
  • coastal corridors,
  • and elevated shoreline terrain.

This pattern is more consistent with movement infrastructure than isolated ritual placement.


4. Horizon Astronomy in Prehistory

Prehistoric societies demonstrably tracked:

  • solar cycles,
  • lunar cycles,
  • solstices,
  • equinoxes,
  • and horizon alignments.

Once astronomical observation is accepted, the application to navigation becomes entirely plausible.


5. Seasonal Movement Systems

Maritime societies depend upon predictable seasonal timing.

Stars naturally provide:

  • seasonal indicators,
  • directional consistency,
  • and long-distance orientation.

6. Ethnographic Parallels

Multiple indigenous cultures linked:

  • landscape movement,
  • memory systems,
  • navigation,
  • and stars.

This provides real-world functional parallels.


What This Project Will Attempt to Test

The 2026 project will focus on measurable and testable questions rather than speculation.

Key research areas include:

GIS Route Analysis

Testing whether:

  • monument chains,
  • river systems,
  • long barrows,
  • beacon hills,
  • and prehistoric movement corridors

show statistically significant astronomical relationships.


Seasonal Navigation Modelling

Investigating whether:

  • key stars,
  • heliacal risings,
  • lunar cycles,
  • or stellar azimuths

correspond to practical travel windows within prehistoric water systems.


Horizon Visibility Studies

Using LiDAR and digital terrain models to reconstruct:

  • prehistoric horizons,
  • sightlines,
  • beacon visibility,
  • and navigational marker ranges.

Maritime Route Reconstruction

Reconstructing:

  • post-glacial coastlines,
  • flooded valleys,
  • inland estuaries,
  • and navigable river systems.

The aim is to determine whether major monuments occupy logical positions within ancient transport networks.


Statistical Testing

This is essential.

Any proposed alignment or pattern must be tested against random distributions.

Without statistical controls, pattern recognition rapidly becomes subjective.

The project, therefore, intends to:

  • establish falsifiable criteria,
  • use control datasets,
  • compare against random models,
  • and avoid arbitrary alignment selection.

What This Project Is NOT Claiming

This research does not claim:

  • that every constellation is a map,
  • that mythology is irrelevant,
  • or that all prehistoric monuments were navigational.

Nor does it claim direct proof already exists.

Instead, the project asks a more careful scientific question:

Could an aquatic civilisation operating across flooded post-glacial landscapes have encoded navigational knowledge into stable stellar frameworks?

At present, the answer appears plausible.

Whether it is correct remains to be tested.


Why This Matters

If even part of this hypothesis proves correct, the implications would be profound.

It would suggest that:

  • prehistoric Britain possessed far more advanced navigational systems than traditionally assumed,
  • monuments may have functioned as infrastructure as well as symbolism,
  • astronomy was practical rather than purely ceremonial,
  • and early maritime societies may have operated sophisticated memory-based route systems long before formal cartography.

Most importantly, it would further support the emerging picture of a civilisation shaped not by isolated ritual sites, but by movement, water, navigation, and environmental adaptation.

In short:

The stars may not simply have inspired prehistoric civilisation.

They may have guided it.


Future Research Updates

This article represents the beginning of a long-term research project planned for 2026.

Future work will include:

  • GIS modelling
  • Hydrological reconstruction
  • Stellar simulation analysis
  • Monument alignment databases
  • Statistical testing
  • Maritime route reconstruction
  • LiDAR visibility studies
  • Ethnographic comparison

Updates will be published through:

Prehistoric Britain

and associated research publications.


Final Thought

Modern civilisation separates:

  • astronomy,
  • geography,
  • navigation,
  • religion,
  • engineering,
  • and landscape.

Prehistoric societies may not have.

For people living in a flooded world of rivers, marshes, estuaries, tides, and coastlines, the sky itself may have functioned as the oldest navigation system humanity ever created.

And perhaps, hidden within the stars, fragments of those ancient water routes still remain.

PODCAST

Author’s Biography

Robert John Langdon, a polymathic luminary, emerges as a writer, historian, and eminent specialist in LiDAR Landscape Archaeology.

His intellectual voyage has been interwoven with stints as an astute scrutineer in government and grand corporate bastions, a tapestry spanning British Telecommunications, Cable and Wireless, British Gas, and the esteemed University of London.

A decade hence, Robert’s transition into retirement unfurled a chapter of insatiable curiosity. This phase saw him immerse himself in Politics, Archaeology, Philosophy, and the enigmatic realm of Quantum Mechanics. His academic odyssey traversed the venerable corridors of knowledge hubs such as the Museum of London, University College London, Birkbeck College, The City Literature Institute, and Chichester University.

In the symphony of his life, Robert is a custodian of three progeny and a pair of cherished grandchildren. His sanctuary lies ensconced in the embrace of West Wales, where he inhabits an isolated cottage, its windows framing a vista of the boundless sea – a retreat from the scrutinising gaze of Her Majesty’s Revenue and Customs, an amiable clandestinity in the lap of nature.

Exploring Prehistoric Britain: A Journey Through Time

My blog delves into the fascinating mysteries of prehistoric Britain, challenging conventional narratives and offering fresh perspectives grounded in cutting-edge research, particularly LiDAR technology. I invite you to explore some key areas of my research. For example, the Wansdyke, often cited as a defensive structure, is re-examined in light of new evidence. I’ve presented my findings in my blog post Wansdyke: A British Frontier Wall – ‘Debunked’, and a Wansdyke LiDAR Flyover video further visualises my conclusions.

My work also often challenges established archaeological dogma. I argue that many sites, such as Hambledon Hill, commonly identified as Iron Age hillforts, are not what they seem. My posts Lidar Investigation Hambledon Hill – NOT an ‘Iron Age Fort’ and Unmasking the “Iron Age Hillfort” Myth explore these ideas in detail and offer an alternative view. Similarly, sites like Cissbury Ring and White Sheet Camp receive re-evaluations based on LiDAR analysis in my posts “Lidar Investigation Cissbury Ring through time” and “Lidar Investigation White Sheet Camp,“ revealing fascinating insights into their true purpose. I have also examined South Cadbury Castle, often linked to the mythical Camelot56.

My research also extends to ancient water management, including the role of canals and other linear earthworks. I have discussed the true origins of Car Dyke in multiple posts, including Car Dyke – ABC News Podcast and Lidar Investigation Car Dyke – North Section, which suggest a Mesolithic origin 2357. I also explore the misidentification of Roman aqueducts, as seen in my posts on the Great Chesters (Roman) Aqueduct. My research has also been greatly informed by my post-glacial flooding hypothesis, which has helped explain landscape transformations over time. I have discussed this hypothesis in several posts, including AI now supports my Post-Glacial Flooding Hypothesis and Exploring Britain’s Flooded Past: A Personal Journey

Finally, my blog also investigates prehistoric burial practices, as seen in Prehistoric Burial Practices of Britain and explores the mystery of Pillow Mounds, often mistaken for medieval rabbit warrens, but with a potential link to Bronze Age cremation in my posts: Pillow Mounds: A Bronze Age Legacy of Cremation? and The Mystery of Pillow Mounds: Are They Really Medieval Rabbit Warrens?. My research also includes astronomical insights into ancient sites, for example, in Rediscovering the Winter Solstice: The Original Winter Festival. I also review new information about the construction of Stonehenge in The Stonehenge Enigma.

Further Reading

For those interested in British Prehistory, visit www.prehistoric-britain.co.uk, a comprehensive resource featuring an extensive collection of archaeology articles, modern LiDAR investigations, and groundbreaking research. The site also includes insights and excerpts from the acclaimed Robert John Langdon Trilogy, a series of books that explore Britain during the Prehistoric period. Titles in the trilogy include The Stonehenge Enigma, Dawn of the Lost Civilisation, and The Post-Glacial Flooding Hypothesis, which offer compelling evidence of ancient landscapes shaped by post-glacial flooding.

To further explore these topics, Robert John Langdon has developed a dedicated YouTube channel featuring over 100 video documentaries and investigations that complement the trilogy. Notable discoveries and studies showcased on the channel include 13 Things that Don’t Make Sense in History and the revelation of Silbury Avenue – The Lost Stone Avenue, a rediscovered prehistoric feature at Avebury, Wiltshire.

In addition to his main works, Langdon has released a series of shorter, accessible publications, ideal for readers delving into specific topics. These include:

For active discussions and updates on the trilogy’s findings and recent LiDAR investigations, join our vibrant community on Facebook. Engage with like-minded enthusiasts by leaving a message or contributing to debates in our Facebook Group.

Whether through the books, the website, or interactive videos, we aim to provide a deeper understanding of Britain’s fascinating prehistoric past. We encourage you to explore these resources and uncover the mysteries of ancient landscapes through the lens of modern archaeology.

For more information, including chapter extracts and related publications, visit the Robert John Langdon Author Page. Dive into works such as The Stonehenge Enigma or Dawn of the Lost Civilisation, and explore cutting-edge theories that challenge traditional historical narratives.

Other Blogs

s

t

Mathematics Meets Archaeology: Discovering the Mesolithic Origins of Car Dyke

Introduction

In archaeology, theories about ancient structures and sites have traditionally been shaped by subjective interpretations, often constrained by the limited evidence.  The lack of precise data, historical bias, and conflicting narratives have left the field somewhat speculative.  However, recent advancements in mathematical modelling have introduced new ways to derive data-driven conclusions.  We can dig deeper into the ancient past by applying Bayesian and Spatial Analysis, extracting valuable insights with greater certainty.  One particularly compelling case study is the re-evaluation of Car Dyke, a linear earthwork historically associated with Roman engineering.  Through these combined mathematical approaches, we have uncovered evidence that suggests Car Dyke may have been constructed much earlier than previously thought, potentially dating back to the Mesolithic period. (Mathematics Meets Archaeology: Discovering the Mesolithic Origins of Car Dyke)

Bayesian Analysis

Bayesian analysis, a statistical method for updating the probability of a hypothesis as new evidence is introduced, has become a powerful tool in archaeology.  Rather than concluding solely on static data, Bayesian analysis allows researchers to adjust their assumptions and probabilities as more evidence becomes available.  For example, when archaeologists find artefacts from a particular period, Bayesian analysis helps calculate the likelihood that the site was occupied or used during that time.  This method is precious for refining timelines and revising outdated interpretations, as it constantly evolves based on the influx of new data.  In archaeology, it has traditionally been applied to analyse when sites were in use rather than when they were constructed.

 (Mathematics Meets Archaeology: Discovering the Mesolithic Origins of Car Dyke)

However, focusing solely on the usage of a site can leave gaps in understanding its origins.  This is where Spatial Analysis comes into play.  Spatial Analysis examines the geographic distribution of artefacts and features, revealing patterns that might indicate when and how the site was built.  By analysing the concentration of artefacts across a landscape, Spatial Analysis can help pinpoint periods of significant activity and uncover the construction date of ancient structures.  When combined with Bayesian analysis, this approach offers a more comprehensive understanding of a site’s construction and use, leading to data-driven and contextually rich conclusions. (Mathematics Meets Archaeology: Discovering the Mesolithic Origins of Car Dyke)

Car Dyke

Car Dyke is an ideal case study for demonstrating the power of this dual approach.  The Dyke stretches across Lincolnshire and Cambridgeshire, and for years, it has been a topic of debate among archaeologists.  Traditionally, scholars have attributed its construction to Roman engineering, primarily due to the presence of Roman artefacts in the broader region.  However, our research applied Bayesian and Spatial Analysis to challenge this assumption.  By focusing on the distribution of artefacts found specifically along the Dyke, we uncovered evidence suggesting that its origins might be much older, potentially tracing back to the Mesolithic or Neolithic periods.

 (Mathematics Meets Archaeology: Discovering the Mesolithic Origins of Car Dyke)

We began our investigation by applying Bayesian analysis to calculate the likelihood of different periods being associated with the construction of Car Dyke.  This required gathering data on all artefacts found across Lincolnshire and using it to calculate the prior probabilities for each period.  Given the abundance of Roman artefacts in the region, our initial Bayesian model favoured a Roman construction date.  However, as we incorporated new evidence from the area surrounding Car Dyke, a different pattern began to emerge.  Spatial Analysis revealed that a significant number of Mesolithic and Neolithic artefacts were clustered in proximity to the Dyke, suggesting that it might have been constructed much earlier than previously believed. (Mathematics Meets Archaeology: Discovering the Mesolithic Origins of Car Dyke)

Spatial Analysis

Spatial Analysis allowed us to go beyond the surface-level examination of artefacts.  By mapping the geographic distribution of Mesolithic and Neolithic finds, we could see that these early artefacts were concentrated in key areas along Car Dyke, particularly where it intersects with ancient landscapes like river valleys and elevated terrain.  This pattern indicated that the Dyke was more than just a Roman infrastructure project—it may have been a significant site for earlier peoples as well.  The concentration of Mesolithic artefacts along the Dyke strongly suggests that the site was either constructed or heavily used during that period.

(Mathematics Meets Archaeology: Discovering the Mesolithic Origins of Car Dyke)

The integration of Bayesian and Spatial Analysis was essential in refining our understanding of Car Dyke’s history.  While Bayesian analysis initially supported the Roman origin theory due to the larger body of Roman artefacts across Lincolnshire, the localised data revealed by Spatial Analysis shifted the probabilities significantly.  This combination of methods allowed us to challenge the traditional narrative and propose a new hypothesis: Car Dyke may have been constructed during the Mesolithic period and later used or modified by the Romans.  This shift in focus—from usage to construction—helped us uncover a deeper history of the site that would not have been apparent through Bayesian analysis alone. (Mathematics Meets Archaeology: Discovering the Mesolithic Origins of Car Dyke)

Data-Driven Methos of Identification

This dual approach also highlights a broader shift in archaeology toward more data-driven methods.  Traditionally, archaeology has relied on subjective interpretations, with researchers filling in the gaps when evidence was sparse.  While this has yielded valuable insights, it has also introduced biases and inconsistencies.  By incorporating mathematical models like Bayesian and Spatial Analysis, we reduce the subjectivity inherent in archaeological interpretation and increase the accuracy of our conclusions.  These methods offer a more transparent and repeatable framework for analysing archaeological data, allowing researchers to refine their hypotheses as new evidence is discovered.

The benefits of this approach extend beyond just Car Dyke.  By applying Spatial Analysis alongside Bayesian calculations, archaeologists can uncover hidden patterns that might go unnoticed.  For example, Spatial Analysis considers the broader context of artefacts within the landscape, revealing relationships between artefact concentrations and natural features such as rivers, hills, and valleys.  This level of analysis helps archaeologists understand not just when a site was used but also why it was built in a specific location.  In the case of Car Dyke, Spatial Analysis allowed us to see that the site’s significance extended far beyond the Roman period, providing a more complete picture of its history and purpose.

Our Revaluation of Car Dyke

The re-evaluation of Car Dyke’s construction date demonstrates the power of combining Bayesian and Spatial Analysis in archaeology.  Bayesian analysis is invaluable for updating our understanding of site usage, but Spatial Analysis provides critical insights into ancient structures’ construction and broader significance.  These methods allow archaeologists to move beyond speculation and embrace a more scientific approach to uncovering the past.  Integrating mathematics into archaeology marks a crucial step forward, helping researchers develop more accurate and evidence-based conclusions.

(Mathematics Meets Archaeology: Discovering the Mesolithic Origins of Car Dyke)
Car Dyke North Section – (Mathematics Meets Archaeology: Discovering the Mesolithic Origins of Car Dyke)

As we refine these techniques and apply them to other sites, the potential for discoveries grows exponentially.  The case of Car Dyke is just one example of how mathematical analysis can reshape our understanding of ancient history.  By embracing data-driven methods like Bayesian and Spatial Analysis, archaeology is evolving into a discipline that is less reliant on conjecture and more focused on scientific rigour.  The future of archaeology lies in this marriage of mathematics and empirical evidence.  As we continue to push the boundaries of what we know, we can expect to uncover even more of history’s mysteries with confidence and clarity.

Conclusion

The combination of Bayesian and Spatial Analysis has revolutionised our understanding of Car Dyke’s construction date, suggesting that it may have been built during the Mesolithic period rather than the Roman era.  This new approach has reduced the subjectivity in archaeological interpretation and allowed us to develop more accurate, data-driven conclusions.  As these mathematical models continue to be refined and applied to other archaeological sites, they will undoubtedly pave the way for even more significant discoveries and a deeper understanding of our ancient past.

The calculations

Bayesian Analysis

To calculate the prior probabilities for each period based on the total number of finds in Lincoln, we first calculate the total number of finds across all periods:

Step 1: Total Number of Finds

Total Finds=13,723(Roman)+8,994(Medieval)+5,619(Post Medieval)+1,680(Early Medieval)+2,451(Iron Age)+2,091(Neolithic)+634(Mesolithic)+980(Bronze Age)=36,172\text{Total Finds} = 13,723 (\text{Roman}) + 8,994 (\text{Medieval}) + 5,619 (\text{Post Medieval}) + 1,680 (\text{Early Medieval}) + 2,451 (\text{Iron Age}) + 2,091 (\text{Neolithic}) + 634 (\text{Mesolithic}) + 980 (\text{Bronze Age}) = 36,172Total Finds=13,723(Roman)+8,994(Medieval)+5,619(Post Medieval)+1,680(Early Medieval)+2,451(Iron Age)+2,091(Neolithic)+634(Mesolithic)+980(Bronze Age)=36,172

Step 2: Calculate Prior Probabilities

Divide the number of finds for each period by the total number of finds:

P(Roman)=13,72336,172≈0.3794P(\text{Roman}) = \frac{13,723}{36,172} \approx 0.3794P(Roman)=36,17213,723​≈0.3794 P(Medieval)=8,99436,172≈0.2487P(\text{Medieval}) = \frac{8,994}{36,172} \approx 0.2487P(Medieval)=36,1728,994​≈0.2487 P(Post Medieval)=5,61936,172≈0.1554P(\text{Post Medieval}) = \frac{5,619}{36,172} \approx 0.1554P(Post Medieval)=36,1725,619​≈0.1554 P(Early Medieval)=1,68036,172≈0.0465P(\text{Early Medieval}) = \frac{1,680}{36,172} \approx 0.0465P(Early Medieval)=36,1721,680​≈0.0465 P(Iron Age)=2,45136,172≈0.0678P(\text{Iron Age}) = \frac{2,451}{36,172} \approx 0.0678P(Iron Age)=36,1722,451​≈0.0678 P(Neolithic)=2,09136,172≈0.0578P(\text{Neolithic}) = \frac{2,091}{36,172} \approx 0.0578P(Neolithic)=36,1722,091​≈0.0578 P(Mesolithic)=63436,172≈0.0175P(\text{Mesolithic}) = \frac{634}{36,172} \approx 0.0175P(Mesolithic)=36,172634​≈0.0175 P(Bronze Age)=98036,172≈0.0271P(\text{Bronze Age}) = \frac{980}{36,172} \approx 0.0271P(Bronze Age)=36,172980​≈0.0271

Summary of Prior Probabilities:

  • Roman: 0.3794
  • Medieval: 0.2487
  • Post Medieval: 0.1554
  • Early Medieval: 0.0465
  • Iron Age: 0.0678
  • Neolithic: 0.0578
  • Mesolithic: 0.0175
  • Bronze Age: 0.0271

Step 1: Define Prior Probabilities

Using the prior probabilities:

  • Roman: P(HRoman)=0.3794P(H_{\text{Roman}}) = 0.3794P(HRoman​)=0.3794
  • Bronze Age: P(HBronze Age)=0.0271P(H_{\text{Bronze Age}}) = 0.0271P(HBronze Age​)=0.0271
  • Neolithic/Mesolithic: P(HNeolithic/Mesolithic)=0.0753P(H_{\text{Neolithic/Mesolithic}}) = 0.0753P(HNeolithic/Mesolithic​)=0.0753

Step 2: Evidence Likelihoods Based on Local Data

Given the distribution of finds:

  • Roman: P(ERoman∣HRoman)=24132≈0.1818P(E_{\text{Roman}}|H_{\text{Roman}}) = \frac{24}{132} \approx 0.1818P(ERoman​∣HRoman​)=13224​≈0.1818
  • Bronze Age: P(EBronze Age∣HBronze Age)=47132≈0.3561P(E_{\text{Bronze Age}}|H_{\text{Bronze Age}}) = \frac{47}{132} \approx 0.3561P(EBronze Age​∣HBronze Age​)=13247​≈0.3561
  • Neolithic/Mesolithic: P(ENeolithic/Mesolithic∣HNeolithic/Mesolithic)=61132≈0.4621P(E_{\text{Neolithic/Mesolithic}}|H_{\text{Neolithic/Mesolithic}}) = \frac{61}{132} \approx 0.4621P(ENeolithic/Mesolithic​∣HNeolithic/Mesolithic​)=13261​≈0.4621

Step 3: Apply Bayes’ Theorem

Posterior Probability for Roman:

P(HRoman∣E)=0.1818×0.3794P(E)=0.0689P(E)P(H_{\text{Roman}}|E) = \frac{0.1818 \times 0.3794}{P(E)} = \frac{0.0689}{P(E)}P(HRoman​∣E)=P(E)0.1818×0.3794​=P(E)0.0689​

Posterior Probability for Bronze Age:

P(HBronze Age∣E)=0.3561×0.0271P(E)=0.0097P(E)P(H_{\text{Bronze Age}}|E) = \frac{0.3561 \times 0.0271}{P(E)} = \frac{0.0097}{P(E)}P(HBronze Age​∣E)=P(E)0.3561×0.0271​=P(E)0.0097​

Posterior Probability for Neolithic/Mesolithic:

P(HNeolithic/Mesolithic∣E)=0.4621×0.0753P(E)=0.0348P(E)P(H_{\text{Neolithic/Mesolithic}}|E) = \frac{0.4621 \times 0.0753}{P(E)} = \frac{0.0348}{P(E)}P(HNeolithic/Mesolithic​∣E)=P(E)0.4621×0.0753​=P(E)0.0348​

Step 4: Normalise the Posterior Probabilities

Sum of the calculated values for normalisation:

P(E)=0.0689+0.0097+0.0348≈0.1134P(E) = 0.0689 + 0.0097 + 0.0348 \approx 0.1134P(E)=0.0689+0.0097+0.0348≈0.1134

Now, calculate the normalised posterior probabilities:

  • Roman:

P(HRoman∣E)=0.06890.1134≈0.6074P(H_{\text{Roman}}|E) = \frac{0.0689}{0.1134} \approx 0.6074P(HRoman​∣E)=0.11340.0689​≈0.6074

  • Bronze Age:

P(HBronze Age∣E)=0.00970.1134≈0.0855P(H_{\text{Bronze Age}}|E) = \frac{0.0097}{0.1134} \approx 0.0855P(HBronze Age​∣E)=0.11340.0097​≈0.0855

  • Neolithic/Mesolithic:

P(HNeolithic/Mesolithic∣E)=0.03480.1134≈0.3069P(H_{\text{Neolithic/Mesolithic}}|E) = \frac{0.0348}{0.1134} \approx 0.3069P(HNeolithic/Mesolithic​∣E)=0.11340.0348​≈0.3069

Analysis and Interpretation:

  • Neolithic/Mesolithic: The higher frequency of finds in this period significantly increases its posterior probability to approximately 30.69%, which is quite substantial.
  • Roman: Despite having fewer finds in this area, the Roman period still has a high posterior probability due to its higher prior, but it is now only about 60.74%.
  • Bronze Age: The probability for the Bronze Age period remains lower at approximately 8.55%.

Conclusion:

The calculated probabilities show a more balanced view, with the Roman period still favoured but with a much stronger case for the Mesolithic/Neolithic period.  This suggests that while Roman use of the Dyke is still likely, the Mesolithic/Neolithic period also holds significant importance, potentially indicating earlier use or occupation before the Romans.

Langdon Mathematics

While Bayesian theory often yields definitive results, its accuracy can be compromised due to its dependence on subjective prior assumptions, which may only sometimes reflect reality.  If these priors are not well-chosen or are based on incomplete or biased information, the resulting analysis might be misleading.

Therefore, relying solely on Bayesian methods without considering the variability and complexity of archaeological data could lead to conclusions that only partially capture the nuances of the actual distribution of artefacts.  My method, which focuses on Spatial Analysis and empirical data, addresses these limitations.

My approach to calculating finds would differ significantly.  First, I would define the area where artefacts could be discovered—using Lincolnshire as a reference due to its comprehensive archaeological data.  By doing so, we can estimate the expected number of artefacts per square meter of Lincolnshire land, offering a more objective and spatially grounded method for understanding artefact distribution.

As IA reports:

To calculate the percentage likelihood of finding an artefact from each period in a single square meter of Lincolnshire, we can follow these steps:

Step 1: Determine the Area of Lincolnshire

  • Area of Lincolnshire: Approximately 6,959 square kilometres (6,959,000,000 square meters).

Step 2: Calculate the Find Density

For each period, calculate the density of finds per square meter by dividing the total number of finds by the area of Lincolnshire.

​

Step 3: Calculate the Likelihood for Each Period

  1. Roman:

Likelihood: 0.000156%

  • Neolithic:

 

Likelihood: 0.000011%

  • Mesolithic:

Likelihood: 0.000004%

  • Bronze Age:

Likelihood: 0.000003%

Summary of Likelihoods in order of expectation:

  • Roman: 0.000156%
  • Medieval: 0.000129%
  • Post Medieval: 0.000081%
  • Early Medieval: 0.000024%
  • Iron Age: 0.000021%
  • Neolithic: 0.000011%
  • Mesolithic: 0.000004%
  • Bronze Age: 0.000003%

These percentages represent the likelihood of finding an artefact from each period in a square meter of Lincolnshire.  Given the extensive activity during that time, the highest is for the Roman period, just marginally ahead of the Medieval period.

We now need to look at the search area (63 miles of the Northern End of Car Dyke) as listing on the LiDAR maps in the previous section of the book.  We must first calculate the total search area in square metres, count the number of finding within this area, and then compare against the expected number.

Summary of Expected Finds:

  • Roman: 15.83 artefacts
  • Medieval: 13.07 artefacts
  • Post Medieval: 8.19 artefacts
  • Early Medieval: 2.44 artefacts
  • Iron Age: 2.17 artefacts
  • Neolithic: 1.07 artefacts
  • Unknown: 0.59 artefacts
  • Modern: 0.50 artefacts
  • Mesolithic: 0.36 artefacts
  • Bronze Age: 0.34 artefacts

Summary of Items Found:

  • Mesolithic/Neolithic: 61 finds
  • Bronze Age: 47 finds
  • Roman: 24 finds

Calculate the Odds of This Kind of Find

For each period, the odds ratio of finding this many artefacts compared to the expected finds:

Step 4: Interpret the Results

  • Mesolithic/Neolithic: A massive 5589.72% increase and an odds ratio of 57.01 suggest significant activity during this period, far beyond what was expected.
  • Bronze Age: An even higher increase of 13723.53% and an odds ratio of 138.24 indicate the area was very important during the Bronze Age.
  • Roman: A modest 51.60% increase with an odds ratio of 1.52 suggests Roman activity, but not as dominant as the earlier periods.

Conclusion

The very high percentage increases and odds ratios for the Mesolithic/Neolithic and Bronze Age periods strongly suggest that the Car Dyke area was occupied and actively used during these times, with significant archaeological activity that exceeds what would be expected based on general Lincolnshire data.  While still represented, the Roman period is less prominent in this area compared to the earlier periods.

This confirms other Dyke surveys such as Offa’s and Wansdyke that also show design (wibbly-wobbly) in construction attributed to the builders seeking natural springs rather than a direct line of route to maintain water levels which were achieved at a later date in history by locks.

Further Reading

For information about British Prehistory, visit www.prehistoric-britain.co.uk for the most extensive archaeology blogs and investigations collection, including modern LiDAR reports.  This site also includes extracts and articles from the Robert John Langdon Trilogy about Britain in the Prehistoric period, including titles such as The Stonehenge Enigma, Dawn of the Lost Civilisation and the ultimate proof of Post Glacial Flooding and the landscape we see today.

Robert John Langdon has also created a YouTube web channel with over 100 investigations and video documentaries to support his classic trilogy (Prehistoric Britain). He has also released a collection of strange coincidences that he calls ‘13 Things that Don’t Make Sense in History’ and his recent discovery of a lost Stone Avenue at Avebury in Wiltshire called ‘Silbury Avenue – the Lost Stone Avenue’.

Langdon has also produced a series of ‘shorts’, which are extracts from his main body of books:

The Ancient Mariners

Stonehenge Built 8300 BCE

Old Sarum

Prehistoric Rivers

Dykes ditches and Earthworks

Echoes of Atlantis

Homo Superior

Other Blogs

s

t