Archaeological Site Images
Buy and sell archaeological site images data. Excavation photos with artifact locations, stratigraphic layers, and site maps. Archaeological AI identifies patterns in dig site imagery.
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Find Me This Data →Overview
What Is Archaeological Site Images Data?
Archaeological site images data consists of satellite and aerial imagery of excavation and dig locations, captured over time to monitor site conditions and detect changes like looting or damage. These images typically include RGB channels with consistent spatial resolution, organized as time series to track sites across multiple years. The data enables researchers and heritage protection organizations to identify patterns of unauthorized excavation, artifact removal, and site degradation without requiring costly or hazardous ground surveys. Applications center on automated looting detection and site preservation monitoring. Machine learning models trained on satellite image time series can classify sites as looted or preserved, identify subtle signs of damage, and flag sites requiring verification or intervention. This data type is particularly valuable in regions where ground access is restricted due to political or security constraints, making remote monitoring the only viable option for heritage documentation.
Market Data
55,480 images
DAFA-LS Dataset Image Count
Source: arXiv
675 Afghan archaeological sites
Sites Covered
Source: arXiv
135 sites
Looted Sites in Dataset
Source: arXiv
8 years (2016-2023)
Time Series Span
Source: arXiv
266×266 pixels, 3 channels (RGB), 3 meters per pixel GSD
Image Specifications
Source: arXiv
Who Uses This Data
What AI models do with it.do with it.
Heritage Protection Organizations
Monitor archaeological sites for unauthorized excavation and looting, enabling rapid response to threats without requiring expensive or dangerous ground surveys in conflict zones.
Machine Learning Researchers
Train and evaluate deep learning models for satellite image time series classification, change detection, and automated site condition assessment using open-access datasets.
Archaeologists & Cultural Heritage Institutions
Document site conditions over time, track preservation status, and identify looting patterns to inform conservation priorities and legal action against illegal excavation.
Remote Sensing & Computer Vision Teams
Develop and benchmark foundation models and pixel-wise methods for subtle change detection in satellite imagery, advancing techniques for anomaly identification.
What Can You Earn?
What it's worth.worth.
Research Dataset License
Varies
Open-access datasets like DAFA-LS are published under CC BY-NC-SA 4.0 for research use; commercial licensing models differ.
Custom Site Imagery Collections
Varies
Pricing depends on spatial coverage, temporal resolution, number of sites, and licensing rights for satellite imagery sourced from commercial providers.
Annotated/Labeled Data
Varies
Manual annotation of looting status, artifact locations, and stratigraphic features commands premium pricing based on expert archaeological labor.
What Buyers Expect
What makes it valuable.valuable.
Temporal Consistency
Multi-year monthly or regular-interval image sequences to enable time series analysis and reliable detection of changes over time rather than single-frame snapshots.
Spatial Resolution
High-resolution imagery (3 meters per pixel or better) with consistent ground sampling distance to reliably detect looting scars, excavation pits, and artifact disturbance patterns.
Accurate Site Delineation
Binary masks or metadata clearly identifying site boundaries and locations, with reduced ambiguity to focus analysis on archaeologically relevant areas and minimize false positives.
Ground Truth Labels
Verified classification of sites as looted or preserved, ideally with temporal metadata indicating when looting occurred, to enable supervised learning model training.
Geographic Metadata
Coordinate data, sensor information, and acquisition dates for each image to support reproducibility, cross-validation, and integration with external archaeological records.
Companies Active Here
Who's buying.buying.
Archaeological documentation and looting detection through satellite imagery analysis; developed DAFA-LS dataset with archaeologists and French archaeological delegation.
Field archaeology, site preservation monitoring, and identification of looting patterns affecting Afghan heritage sites.
Foundation model development, satellite image time series classification, and machine learning research for archaeological looting detection.
FAQ
Common questions.questions.
What is the DAFA-LS dataset and why does it matter?
DAFA-LS is the first open-access dataset for looting detection, containing 55,480 satellite images of 675 Afghan sites over 8 years. It enables machine learning researchers and archaeologists to develop automated looting detection without access to proprietary or restricted data, addressing a critical gap in public datasets for heritage protection.
How are looted sites identified in satellite images?
Looting appears as subtle but detectable changes in satellite image time series, including excavation scars, soil disturbance, and pit patterns. Machine learning models trained on multi-year sequences can identify these patterns more reliably than single images, with foundation models and time series methods showing significant performance improvements.
What spatial and temporal resolution is typical for this data?
Standard imagery has 3 meters per pixel ground sampling distance with 266×266 pixel frames covering 1 km² areas. Time series are acquired monthly or at regular intervals across multiple years, enabling robust change detection while maintaining computational efficiency.
Who can use archaeological site image datasets and under what terms?
Research datasets like DAFA-LS are published under CC BY-NC-SA 4.0, permitting non-commercial academic use. Commercial licensing, custom collections, and annotated datasets operate under separate terms negotiated with imagery providers and heritage organizations.
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