Methods
Summary
Project Methods: A Non-Invasive Geophysical Survey Around the Turkana Boy Site
Overview
This project aims to investigate the 30-hectare area surrounding the site where the famous Turkana Boy fossil (Homo erectus) was discovered using state-of-the-art non-invasive subsurface imaging technologies. Our goal is to determine whether additional fossilized hominin remains, related features, or paleoenvironmental structures remain undiscovered in the vicinity. This will be accomplished through a combination of Ground-Penetrating Radar (GPR) and Electrical Resistivity Imaging (ERI), supported by precise GIS-based mapping, expert field interpretation, and rigorous data analysis workflows.
Why Non-Invasive Methods?
Traditional archaeological excavation is slow, destructive, and highly localized. By contrast, geophysical techniques such as GPR and ERI allow for rapid, repeatable, and environmentally friendly scanning of large areas without disturbing the ground. These technologies are especially suited to paleoanthropological landscapes like Turkana—where fossils are often buried under layers of sediment, and preservation is crucial.
1. Site Description and Target Area
The project site is a 30-hectare area surrounding the Nariokotome region near Lake Turkana. This site has rich geological and paleoanthropological significance, situated within a sedimentary basin characterized by alternating layers of volcanic ash, silts, and clays. These sediments are known for excellent fossil preservation but present challenges for traditional excavation due to fluctuating soil moisture and compaction.
2. Team Composition and Roles
Geophysical Survey Lead – Plans grid layout, calibrates equipment, and oversees scanning operations.
Archaeological Liaison – Provides insight on fossil context, cultural layers, and potential features of interest.
GIS & Remote Sensing Specialist – Integrates topographic data and survey outputs into spatial models.
GPR Technician – Operates the GSSI SIR 4000 system and handles real-time radargram interpretation.
Resistivity Technician – Manages the Geoscan RM85 system, electrode placement, and data capture.
Local Field Assistants – Handle logistics, security, and assist with equipment transport and ground prep.
Data Analyst – Leads data processing, filtering, interpretation, and modeling using specialized software.
3. Equipment and Technology
A. Ground Penetrating Radar (GPR)
Device: GSSI SIR 4000 with 350 MHz and 900 MHz antennas
Function: Sends high-frequency electromagnetic pulses into the ground; reflected signals are recorded to detect subsurface features based on dielectric contrast.
Expected Results from GPR:
Identification of bone structures or fossilized cavities
Mapping sedimentary layering or ancient soil horizons
Differentiation between compacted sediment and anomalies
B. Electrical Resistivity Imaging (ERI)
Device: Geoscan RM85 with Wenner array configuration
Function: Measures soil resistance to electrical current; anomalies in resistivity indicate changes in moisture, density, or buried objects.
Expected Results from ERI:
Cross-sectional views (2D resistivity slices) of buried structures
Locating fossil deposits where moisture-retaining soil contrasts with dry bone
Detecting buried riverbeds or erosion channels
4. Grid Layout and Survey Design
The 30-hectare site will be subdivided into 100x100 meter grid squares, each surveyed individually for full coverage. Grid corners will be georeferenced using high-accuracy GPS (sub-meter accuracy). GPR transects will be spaced at 1-meter intervals, while ERI lines will be spaced at 10-meter intervals, adjusted for terrain and equipment limits.
This systematic grid design ensures:
Redundancy of data
High-resolution GPR coverage
Broad-scale resistivity mapping
Easy integration into GIS for post-survey visualization
5. Data Collection Protocols
GPR Scanning Workflow
1. Set up base station and conduct electromagnetic interference check.
2. Calibrate GPR unit based on soil dielectric properties.
3. Run test lines and adjust gain/time window settings.
4. Conduct parallel transects using wheeled or sled-mounted antennas.
5. Mark obstacles or disturbances for contextual analysis.
6. Store radargrams with synchronized GPS data.
ERI Survey Workflow
1. Insert stainless steel electrodes at pre-defined intervals (typically 1 meter).
2. Configure Geoscan RM85 in Wenner or Dipole-Dipole array depending on depth target.
3. Inject low-voltage current and measure potential difference.
4. Log resistivity values and transfer to interpretation software.
5. Rotate array or repeat survey lines at different orientations for 3D modeling.
6. Data Processing and Interpretation
Software Tools Used:
GPR-SLICE / RADAN (GSSI) – for GPR data filtering, migration, and depth calibration
Res2Dinv / Res3Dinv – for 2D and 3D resistivity inversion modeling
ArcGIS Pro / QGIS – for integrating spatial data and generating final maps
CloudCompare – for 3D point cloud analysis and visualization
Processing Steps:
Noise filtering and baseline correction
Gain adjustments and depth migration (GPR)
Inverse modeling (ERI)
Anomaly detection using comparative stratigraphy
Overlay of GPR and ERI data in GIS
Validation with known fossil depth and geological layers
7. Data Quality Control
Repeat Scans: 10% of grids will be re-scanned to confirm repeatability
Cross-validation: GPR anomalies will be checked against resistivity data
GPS Accuracy: All features will be recorded with sub-meter spatial accuracy
Manual Logs: Field teams will record vegetation, slope, surface disturbance, and weather data
8. Anticipated Challenges and Mitigation
Challenge Mitigation Strategy
Variable soil moisture Daily dielectric calibration; use resistivity as backup
Equipment overheating Early morning/evening surveys; portable shade units
GPS signal loss Use differential GPS with offline correction logs
Interpretation uncertainty Anomaly validation via multi-sensor comparison
9. Deliverables to Backers and Community
High-resolution GPR radargrams & ERI resistivity profiles
Interactive 2D and 3D maps of potential fossil zones
Mid-survey report with visuals and interpreted findings
Final technical report with full results and raw data archive
Public-friendly summary for schools, museums, and outreach
If discoveries are made: recommendations for excavation by authorized paleoanthropologists
10. Reproducibility and Open Science
To ensure reproducibility and contribute to the broader scientific community, we will:
Publish detailed survey protocols and grid coordinates
Make anonymized datasets and GIS layers publicly available
Share all software settings used in data processing
Upload a project video showing step-by-step equipment use and analysis pipeline
Submit results to an open-access journal in geophysics or paleoanthropology
11. Sustainability and Ethical Considerations
The project will follow UNESCO and national archaeological ethics guidelines.
No excavation will occur without formal paleontological permissions.
Local communities will be involved in every step and credited accordingly.
Equipment will be reused for future educational projects in the region.
Conclusion
This project combines cutting-edge geophysical technology with a robust, reproducible methodology to scan one of the world’s most iconic paleoanthropological landscapes. With careful planning, ethical research practices, and a multidisciplinary team, we aim to uncover new insights into early human history—while preserving the integrity of the landscape and contributing openly to scientific knowledge.
Challenges
Challenges and Risk Management
While the planned geophysical scanning project around the Turkana Boy discovery site is designed with precision and non-invasive technologies in mind, several challenges—both logistical and technical—are anticipated. This section outlines the primary project risks, their potential impact on outcomes, and proposed strategies for overcoming them to ensure project success.
1. Environmental and Soil Conditions
One of the most significant challenges is the high variability of soil composition in the Turkana Basin region. The alternating layers of volcanic ash, clay, sand, and alluvial sediments can cause signal attenuation or distortion, especially for Ground-Penetrating Radar (GPR). Additionally, moisture levels may vary greatly depending on season and local microclimates, which could affect both GPR and Electrical Resistivity Imaging (ERI) accuracy.
Impact:
Reduced penetration depth for GPR
False positives or signal scattering
Increased noise in resistivity data
Mitigation Strategy:
Conduct soil conductivity and dielectric tests prior to each day's scan
Use multi-frequency GPR antennas (350 MHz for depth, 900 MHz for resolution)
Rely on complementary resistivity imaging when GPR returns are weak
Schedule fieldwork during dry seasons when soils are more stable and predictable
2. Equipment Malfunction or Downtime
The sensitive nature of high-frequency GPR antennas and electrical resistivity meters makes them vulnerable to environmental damage, especially under the extreme heat, dust, and rugged terrain of the Turkana region. In remote areas, repair or replacement delays could stall the project timeline significantly.
Impact:
Lost scanning days
Data loss or incomplete coverage
Budget overruns due to emergency equipment rental or transport
Mitigation Strategy:
Secure two units of each device where possible (one backup GPR or antenna)
Establish a preventive maintenance checklist for daily care
Store equipment in waterproof/hard-shell containers when not in use
Arrange for standby support from equipment vendors or field tech partners
3. GPS and Geolocation Accuracy
Accurate spatial referencing is critical for mapping anomalies, merging GPR and ERI results, and supporting future excavation. The open landscape may offer good satellite visibility, but interference from volcanic rocks, sudden cloud cover, or signal drift can affect GPS readings.
Impact:
Inaccurate anomaly locations
Misaligned data layers
Difficulty in revisiting anomaly zones
Mitigation Strategy:
Use differential GPS (DGPS) with sub-meter precision
Apply post-processing correction using offline base stations
Maintain manual logs of physical markers and survey flags as a backup
4. Interpretation Ambiguity
One of the inherent risks of non-invasive scanning is the difficulty in conclusively identifying fossil material without excavation. Bones, rocks, tree roots, and buried sediment layers can appear similar on GPR or resistivity scans, and false positives are a known challenge.
Impact:
Misidentification of anomalies
Unnecessary attention to unremarkable zones
Skepticism from stakeholders or peer reviewers
Mitigation Strategy:
Use both GPR and ERI simultaneously to cross-validate anomalies
Involve multiple interpreters during data analysis to reduce bias
Prioritize anomalies with consistent returns across multiple layers and transects
Only recommend excavation after robust, repeatable anomaly evidence
5. Logistical Challenges and Accessibility
The remote nature of the Turkana region poses challenges in transporting personnel, equipment, and supplies, especially during the rainy season or in areas with rugged terrain. Moreover, accommodation, electricity, and internet connectivity in the field may be limited.
Impact:
Survey delays due to difficult terrain
Limited field operation hours
Reduced real-time data transmission or cloud backup
Mitigation Strategy:
Conduct terrain assessment and drone reconnaissance prior to fieldwork
Use all-terrain vehicles and portable solar-powered units for field bases
Designate a local base camp with basic storage, charging, and working space
Employ offline data logging tools and back up results daily
6. Cultural and Community Considerations
Paleoanthropological sites in the region are often in or near lands inhabited by indigenous communities. Unclear communication or lack of local engagement could lead to misunderstandings or distrust, especially if equipment use or research goals are not clearly explained.
Impact:
Community resistance or withdrawal of access permission
Cultural conflict or reputational risk
Delays due to conflict resolution or loss of goodwill
Mitigation Strategy:
Engage community leaders well before project commencement
Translate project goals into local languages and visual formats
Employ local guides and assistants as part of the team
Ensure local stakeholders receive recognition and project updates
Follow national and UNESCO guidelines for ethical research in heritage zones
7. Budget Constraints and Unexpected Costs
Despite careful planning, unexpected issues such as fuel cost surges, equipment damage, or extended fieldwork can lead to budget strain. Additionally, costs for data processing software or specialist consultation can rise.
Impact:
Reduction in survey coverage area
Delay in data analysis or reporting
Increased pressure on project funding
Mitigation Strategy:
Allocate a 10–15% contingency reserve in the budget
Negotiate discounts or partnerships with equipment providers
Seek co-funding or cost-sharing from universities or partner institutions
Prioritize essential outputs in case of scaled-back resources
8. Post-Fieldwork Data Overload
Large-scale geophysical surveys generate vast amounts of data—especially when scanning 30 hectares at high resolution. Without proper data management, valuable insights may be delayed, misfiled, or lost.
Impact:
Backlogs in data cleaning and modeling
Loss of important metadata (e.g., scan location or operator notes)
Delayed reporting to backers and peer reviewers
Mitigation Strategy:
Establish daily data logging and backup protocols
Use standardized file naming and tagging conventions
Assign a dedicated data manager for the duration of the project
Begin preliminary processing in parallel with ongoing scanning
9. Legal and Permitting Delays
Though the project is non-invasive, scanning in a protected fossil area may require specific permits from heritage authorities or conservation boards. Delays in issuing these permits can affect the timeline.
Impact:
Missed survey season
Lost team availability
Delayed engagement with backers
Mitigation Strategy:
Submit applications months in advance
Maintain communication with issuing agencies
Keep an alternate schedule ready in case of delay
Ensure all documentation and ethical review approvals are in place
Conclusion
Despite these challenges, this project has been carefully designed with foresight, risk-mitigation protocols, and field-tested strategies. With a professional team, advanced tools, local collaboration, and built-in redundancy, the project is well-positioned to overcome obstacles. Every challenge is also an opportunity for learning and innovation—and we are fully committed to adapting as needed to deliver high-quality results to both the scientific community and our supporters.
Pre Analysis Plan
Pre-Analysis Plan
This pre-analysis plan outlines the framework that will be used to study, interpret, and draw conclusions from the geophysical data collected during a non-invasive field survey of the 30-hectare area surrounding the original Turkana Boy discovery site. The goal is to detect subsurface anomalies that could represent fossilized human or animal remains, buried geological features, or ancient human activity zones. To ensure transparency, reproducibility, and scientific rigor, we describe below our research hypotheses, analytical procedures, expected outputs, and how we will address issues like multiple outcomes, variance, and interpretation ambiguity.
1. Research Objectives and Hypothesis
The primary research hypothesis is as follows:
> H1: There are additional fossilized remains or fossil-bearing features within the 30-hectare zone surrounding the original Turkana Boy discovery site that can be detected using non-invasive geophysical methods—specifically Ground Penetrating Radar (GPR) and Electrical Resistivity Imaging (ERI).
Secondary hypotheses include:
H2: Subsurface anomalies identified through GPR and ERI correspond to natural fossil-preserving sedimentary environments (e.g., paleo-riverbeds, erosional basins, ash deposits).
H3: High-density anomaly clusters may indicate previously undetected zones of paleoanthropological or faunal significance.
H4: Variance in anomaly depth and resistivity values reflects different depositional episodes or preservation contexts within the basin.
2. Data Collection Summary
The data will come from two main geophysical instruments:
GPR (GSSI SIR 4000 with 350 MHz and 900 MHz antennas): Produces 2D radargrams and 3D subsurface reflection maps showing dielectric contrast (e.g., bone vs. sediment).
ERI (Geoscan RM85): Provides 2D and 3D resistivity profiles showing variations in soil resistance related to density, porosity, and material composition.
Additional supporting data will include:
High-accuracy GPS location data for georeferencing scans
Field logs on vegetation cover, soil type, and surface disturbances
Manual flags and notes on anomalies detected during live scans
Daily environmental readings (soil moisture, temperature, humidity)
3. Data Preprocessing and Cleaning
Before formal analysis begins, all raw data will undergo systematic preprocessing using the following steps:
GPR Data
Time-zero correction
Bandpass filtering to remove noise
Gain adjustment (automatic and manual)
Background subtraction to eliminate repetitive layers
Migration to correct dipping reflectors
Conversion from time to depth based on local dielectric constant
ERI Data
Removal of incomplete or noisy measurements
Electrode contact resistance checks
Error masking and smoothing
Inversion of resistivity pseudosections using Res2DInv
Rescaling resistivity values to standard ohm-meter ranges
Processed data will be saved in multiple formats (.csv, .grd, .tif, .kmz) and backed up daily.
4. Analytical Approach
A. Identification of Subsurface Anomalies
Anomalies will be defined as any localized, significant deviation from the surrounding subsurface reflectivity (in GPR) or resistivity (in ERI) that:
Appears in 3 or more adjacent scan lines
Persists across multiple depth slices
Presents with clear boundary contrasts
GPR anomalies will be detected visually and algorithmically using software like GPR-SLICE and RADAN. ERI anomalies will be flagged using contour thresholds and inversion maps from Res2DInv.
B. Cross-Validation of Anomalies
All flagged anomalies will be cross-validated:
GPR anomalies will be checked against resistivity highs or lows in ERI
Overlapping anomalies in both datasets will be marked as “High Confidence”
Unique anomalies (only GPR or only ERI) will be analyzed further for artifact signals, depth, and geologic context
C. Spatial Analysis
Use GIS (ArcGIS Pro or QGIS) to map all anomalies, overlay them on topography, and analyze:
Anomaly density per hectare
Proximity to known fossil discovery locations
Depth clustering patterns
Correlation with historical riverbeds or depositional environments
D. Statistical Modeling
Generalized Linear Models (GLMs) will be used to assess whether anomaly occurrence is statistically associated with known fossil-rich stratigraphy.
Variance in dielectric and resistivity values will be plotted to determine:
How distinct each anomaly is from background readings
Whether there are groupings suggestive of different material types (e.g., bone vs. rock)
5. Handling Multiple Outcomes
Given the possibility of detecting more than one type of anomaly (e.g., fossil, geologic feature, void, root), the analysis will follow this multi-tiered interpretation framework:
Tier 1: High-confidence anomalies supported by both GPR and ERI, consistent with known fossil dimensions and buried structures
Tier 2: Medium-confidence anomalies with strong signal in one modality, but inconclusive or noisy in the other
Tier 3: Low-confidence anomalies that are either shallow, isolated, or show no clear boundary
Each tier will be analyzed separately and scored for:
Size
Depth
Shape
Layering context
Consistency across multiple transects
6. Dealing with Variability
Natural variation in soil properties, compaction, and moisture can impact signal quality and consistency. To account for this:
Field moisture readings will be factored into interpretation (e.g., high moisture can reduce GPR penetration but improve ERI contrast)
A stratified analysis approach will group data by similar terrain, soil, or vegetation conditions
Control scans will be taken in known fossil-free zones to establish “normal” background levels for both radar and resistivity
Outliers or irregular signal returns will not be discarded outright but flagged for further review during team interpretation sessions.
7. Hypothesis Testing and Outcomes
Each hypothesis will be tested as follows:
H1: Confirmed if at least 5 high-confidence anomaly zones are discovered that are consistent with bone or cavity signatures and supported by ERI contrast.
H2: Confirmed if clustering of anomalies aligns with known fossil-bearing stratigraphy or paleo-riverbeds.
H3: Confirmed if anomaly density significantly exceeds background frequency or is statistically non-random.
H4: Confirmed through observed variance in resistivity/dielectric values, interpreted as evidence of multiple burial or erosion phases.
All confirmed results will be supported by figures, maps, and visual evidence.
8. Peer Review and Validation
To ensure transparency and avoid confirmation bias:
Raw and processed datasets will be reviewed by at least two external experts
Anomaly interpretation sessions will be held with the team (and optionally streamed or recorded)
We will submit our methods and early findings to open-access preprint platforms or conference sessions for early feedback
9. Open Access and Reproducibility
In alignment with open science principles:
Data and code used for analysis (Python, R, GIS) will be shared via GitHub and Zenodo
GPR and ERI processing parameters will be published in our final report
An anomaly detection guide will be produced for replication by other researchers
Conclusion
This pre-analysis plan provides a robust framework for collecting, analyzing, and interpreting geophysical survey data in a structured and reproducible manner. By combining multi-instrument data collection, rigorous
statistical methods, cross-validation, and open data practices, the project aims to uncover new insights into early human presence without invasive excavation—while also setting a standard for non-invasive fossil research methodology.
Protocols
This project has not yet shared any protocols.