Tuna Kalaycı & Apostolos Sarris Institute for Mediterranean Studies

Laboratory of Geophysical-Satellite Remote Sensing and Archaeo-environment

Sensor Data Integration:

Concepts and Methods

According to Luo and Kay (1992) multi-sensor fusion “refers to any stage in an integration

process where there is an actual combination (or fusion) of different sources of sensory

information into one representational format.”

Starr and Desforges (1998) suggests “[d]ata fusion is a process that combines data and

knowledge from different sources with the aim of maximising the useful information

content, for improved reliability or discriminant capability, while minimising the quantity of

data ultimately retained.”

Wald (1998) defines it as “a formal framework in which are expressed means and tools for

the alliance of data of the same scene originating from different sources. It aims at obtaining

information of greater quality; the exact definition of greater quality will depend upon the

application.”

According to McGirr (2001) data fusion is “the process of bringing large amounts of

dissimilar information together into a more comprehensive and easily manageable form”

A PLETHORA of DEFINITIONS and WORKFLOWS

R. C. Luo and M. G Kay (1992) Data fusion and sensor integration: State-of-the-art 1990s.

Data Fusion in Robotics and Machine Intelligence, Academic Press Limited, San Diego

Starr and M. Desforges (1998) Strategies in data fusion - sorting through the tool box. Proceedings of European Conference on Data

Fusion

L. Wald (1998) A European proposal for terms of reference in data fusion, In: International Archives of Photogrammetry and Remote

Sensing, Vol. XXXII, Part 7, pp. 651-654

S. C. McGirr (2001) “Resources for the design of data fusion systems”, In: Proc. International Conference on Information Fusion

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DATA INTEGRATION/FUSION STUDIES in ARCHAEOLOGY

Brizzolari, E., F. Ermolli, L. Orlando, S. Piro, and L. Versino. 1992. “Integrated Geophysical

Methods in Archaeological Surveys.” Journal of Applied Geophysics 29 (1): 47–55.

Cammarano, F., P. Mauriello, and S. Piro. 1997. “High-Resolution Geophysical Prospecting

with Integrated Methods. The Ancient Acropolis of Veio (Rome, Italy).” Archaeological

Prospection 4: 157–64.

Doneus, M., and W. Neubauer. 1998. “2D Combination of Prospection Data.”

Archaeological Prospection 5: 29–56.

Gaffney, V., H. Patterson, S. Piro, D. Goodman, and Y. Nishimura. 2004.

“Multimethodological Approach to Study and Characterize Forum Novum (Vescovio,

Central Italy).” Archaeological Prospection 11 (4): 201–12.

Johnson, Jay K., and B.S. Haley. 2004. “Data Fusion as a Means of Sensor Evaluation in

Archaeological Applications.” In SPIE Proceedings, 5234:688–97. International Society for

Optics and Photonics.

Drahor, M.G. 2006. “Integrated Geophysical Studies in the Upper Part of Sardis

Archaeological Site, Turkey.” Journal of Applied Geophysics 59 (3): 205–23.

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Kvamme, K.L. 2006. “Integrating Multidimensional Geophysical Data” Archaeological

Prospection 13 (1): 57–72.

Piro, S., D. Peloso, and R. Gabrielli. 2007. “Integrated Geophysical and Topographical

Investigation in the Territory of Ancient Tarquinia (viterbo, Central Italy).” Archaeological

Prospection 14 (3): 191–201.

Masini, N., E. Rizzo, R. Lasaponara, and G. Orefici. 2008. “Integrated Remote Sensing

Techniques for the Detection of Buried Archaeological Adobe Structures: Preliminary

Results in Cahuachi (Peru).” Advances in Geosciences 19: 75.

Keay, S., G. Earl, S. Hay, S. Kay, J. Ogden, and K.D. Strutt. 2009. “The Role of Integrated

Geophysical Survey Methods in the Assessment of Archaeological Landscapes: The Case of

Portus.” Archaeological Prospection 16 (3): 154–66.

Cardarelli, E., and G. Di Filippo. 2009. “Integrated Geophysical Methods for the

Characterisation of an Archaeological Site (Massenzio Basilica — Roman Forum, Rome,

Italy).” Journal of Applied Geophysics 68 (4): 508–21.

DATA INTEGRATION/FUSION STUDIES in ARCHAEOLOGY

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(Brizzolari et al. 1992)

Some Examples

(Doneus and Neubauer 1998)

(Gaffney et al. 2004)

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Kvamme, 2006, Integrating Multidimensional Geophysical Data

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DATA INTEGRATION LEVELS

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METHODS of INTEGRATION: Two Case Studies

Almyros 2

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METHODS of INTEGRATION: Two Case Studies

Mantinea

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METHODS of INTEGRATION: A Comprehensive List

Graphical Integration

•RGB Composites

•Alpha Compositing

•HIS Transformation

Binary Operations

•Boolean Union

•Boolean Intersection

•Boolean Sum

Continuous Data Operations

•Numeric Combinations

•Data Product and Data Sum

Statistical Operations

•Cluster Analysis

•Principle Component Analysis

•Mahalanobis Classification

•Logistic Regression

•Cokriging

•Wavelet Transformation

•Curvelet Transformation

•Multi-scale Decompositions

…and many others

•Neural Networks

•Dempster-Shafer Evidence Theory

•Joint Inversion Geo

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GEOPHYSICAL PROSPECTION

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RGB Composites

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RGB Composites

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HIS Transformation

• Intensity is the total brightness/lightness of a color

• Hue is the color itself as we perceive it

• Saturation is the purity of that color

< transform RGB space to HIS space >

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HIS Transformation

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Data Product and Data Sum

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Data Product and Data Sum

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Wavelet Transformation

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Wavelet Transformation

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Multi-Scale Decomposition

Subsampling results in size differences in sub-band images, creating a

pyramid.

A rule based cascading of pyramids of different data sources while keeping

the most significant details provides integration

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Multi-Scale Decomposition

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Conclusion and Future Prospects

1 + 1 = 1.5 1 + 1 = 3

• the need for more empirical studies,

representing diverse datasets

• systematic testing for different methods

• a method for performance evaluation

• a specialized software for data integration in

archaeological prospection

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