Integrated GIS for the studies of prehistoric archaeological assemblages: Insights from Olorgesailie an early Acheulean open-air site in Kenya

Olorgesailie Prehistoric Site

Acheulean Tools (Oval shaped, and longest used technology in human prehistory)

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Zelalem Assefa

Geog 797 Final Project – Spring 2011

Project Motivation

• Despite increasing importance of Geographic Information System (GIS) in different fields of the archaeological investigations, its application in Paleolithic collections of the distant past is still very limited. Main objective of this project is to explore and introduce different approaches of GIS based analyses that can be applied for studying spatial distributions of the Paleolithic collections.

• As a case study this analysis targets the excavated collections from the very well known Acheuleansite, the Olorgesailie Basin in southern Kenya

Overall Project Objectives

• Develop Archival Procedures

-For applying spatial analysis on tens of thousands of stone tools and

fauna collected from the site over the years.

• Undertake Intra-site spatial investigations-Tracing differences and similarities in patterns of the spatial distributions of different archaeological samples (bones, tools) at site level; reconstruct some aspects of site formation processes

• Undertake Inter-site spatial investigations-With a focus on certain attributes of the stone tools, such as the raw material and specific types of stone tools, investigation their patterns of clustering and spatial distribution across the site.

Research Question

Intra-site1. (A.) With a focus on few selected sites within the Olorgesailie basin, explore if there is

a difference in the spatial distribution of bones versus stone tools.-Faunal remains and stone tools will be evaluated for Complete Spatial Randomness (CSR). The null hypothesis will be:

H0 – the distribution of bones and stone tools at each of the sites included in the analysis is not different from a random pattern.

(B.) Explore clustering characteristics of bones and tool at local and higher scales:-Depending on composition and density of the stone tools and fauna at particular sites the distribution of either bones or fauna should show a more localized or extended distribution.

(C.) Evaluate possible impacts of hydraulic forces on redistribution and accumulation of the findings from a few selected sites:

-Prior researches indicate possible impact on formation of the archaeological assemblages due to impacts by moving water

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Intra-site2. (A.): Investigate relations between distance from source of raw material and stone tool distribution across the site

-According to the theory of optimal resource exploitation strategy, stone tools made out

of raw materials from sources closer to the location of the site tend to be more common than stone tools made out of exotic raw materials from distant sources. Do the stone tools from Olorgesailie reflect this patter?

(B): Is there a specific clustering pattern that the distribution of certain artifact types exhibit across the site.

-With a focus on flaked pieces and flake fragments, evaluate the spatial autocorrelation

that these groups of stone tools show at few selected sites.

(C): Bivariate Analysis to evaluate if the spatial distribution of flake pieces can be explained by the flake fragments.

-Such relations between the two types of tools is assumed because the flake pieces are

end-products of tool manufacturing activity which often results in accumulation of high concentration of flake fragments as residues or debris.

Research Question

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Study Area

Localities and site distributions within the Olorgesailie Basin

Data Description

Paleolandscape Approach: A procedure of sampling archaeological sites over broad lateral exposures, targeting continuous and narrow natural layers.

85

18

16

85

0.900

Composite Natural Layers

Excavated sites

(following lateral extension of single layer)

UM1p = Upper Member 1 paleosolM6/7s = Member 6 and Lower Member 7 sandsLM7ds = Lower Member 7 diatomaceous silts

Du

Duration

≤ 1000 yrs

≤ 1000 yrs~ 500 yrs

Interval Layers

Age

992ka

990ka

974ka900ka780ka

746ka

t

Total excavated materials 12, 781(stone tools 6,781, bone 6,000)

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SitesSample

size Interval Layer RemarkSite 1 120 UM1p 4L Relative high artifact density Site 2 374 UM1p 4L Dense concentration of associated fauna and artifacts

Site 15 706 UM1p 4LDense concentration of elephant skeleton associated with artifacts

Site 102 362 UM1p 4L Hyena accumulated fauna with few associated artifactsSite 126 39 UM1p 4L less dense but widely scatter red fauna and artifacts

Hyena hill 560 UM1p 4LSeries of excavations sampling a complex burrow system of hyena dens

C7-1 Trench 1 188 LM7dp

LM7 ds Dense concentration of associated fauna and artifacts

C7-1 Trench 3 86 LM7dp

LM7 ds Dense concentration of associated fauna and artifacts

Sites within the Olorgesailie Basin, selected for more detailed investigations

Data Description

= behavioral and ecological

= site formation process

CodeD = Dip (plunge)O = Orientation (bearing)ArtType = Artifact TypeWGT = Weightrawmat = Raw material

Data Gathering and Compilation -Conversion of paper archives to digital format(georeferencing, rectifying, digitizing)

-With the excavated materials, extrapolation of the Total Station readings (XYZ ) to trueGeographic coordinates

-Joining and linking the excavation data and the stone tool attribute data

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Excavated Stone Tools AnalysisField Number Site

X - coordinate Ext

Y - coordinate Field Number

Z - depth Square

subfield Layer

Site name Artifact Type

Dip Weight

Orientation Raw Material

Long Axis Primary form

Layer Cortex

Object Condition

Square Fresh break

Remarks length

Breadth

Thickness

Comments

Methods

(X + d*sin(o), Y + d*cos(o)) Trigonometric function =

Distance = given (changed to 10cm)0rientation angle = converted to radian

To find the XY at one tip of the bone:

Back Azimuth- If O is ≤ 1800 add 180- If O is > 1800 subtract 180

Given (X,Y)

distanceGiven dip

Excavated object

Methods-Replicating orientation of excavated materials in polylines

Excel worksheet for calculating necesary data for replicating the polylines

Method

A reference for interpretation of the orientations of excavated materials

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Random = undisturbed

Aligned = disturbed by hydraulic force (single event)

Criss-cross = disturbed by hydraulic force (multiple event)

Modified from McPherron (2005).

Raw material sources

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Sources of raw materials used for making stone tools

Location of the archaeological sites

-Distance from raw material (created usingthe ArcGIS’s proximity tool – ‘Near’)

Methods-Building data for distance from sources of raw material

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1. Intra-Site •SDA4PP – GIS plugin•ArcGIS – Average Neighbor

Analysis•ArcGIS – Spatial autocorrelation

•GEOrient – Rose Diagram•Xtools Pro – ArcGIS addin

•Point Pattern Analysis

•Circular Variance

•Average Nearest NeighborAnalysis

•Weighted Standard deviational ellipses

•Moran’s I ?

•K - function

•Ordinary Least Square• Geographically Weighted

Regression (GWR)

Statistical Test Applicability Application/tool

2. Inter-Site

1A. Overall faunal andstone tool distribution

1B. Extent of distribution:Local or higher

1C. Site Formation:Hydraulic forces

2A. Raw material distribution

2B. Spatial autocorrelation:Flaked pieces and flake fragments

2C. Bivariate Analysis

•Nearest Neighbor hierarchical clustering

•Rose Diagram

•Anselin Local Moran’s I•Getis-Ord Gi*

•ArcGIS tool box•Measuring geographic distribution•Analyzing patterns•Mapping Clusters•Analysis tools (proximity)

Methods-Statistical tests employed in different areas of the spatial analyses

Excavated sites showing on Quickbird Sat. (60cm resolution) imagery

Geocoding of the excavated samples

Results - Archiving

Geocoded excavated samplesoverlaid on the Quickbird sat. image

Site 102: Two-dimensional and three-dimensional Views of excavated materials

Faunal samples and stone tools from site 102 and site 2

bones

tools

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Site 2: Two-dimensional and three- dimensional Views of excavated materials

Results - Archiving

Average Nearest Neighbor

Site Object Sample Area in meters Average Intensity

P-value Z-score

Site 126 Lithics 366 21.61 16.90 0 -12.00

Fauna 87 15.05 5.78 0.0013 -3.21

Combined 453 22.19 20.40 0 -13.46

Site 1 Lithics 176 9.06 19.40 0 -3.36

Fauna 150 12.05 12.40 0 -7.08

Combined 326 12.19 26.75 0 -8.83

Site 2 Lithics 675 71.19 9.48 0 -16.18

Fauna 706 74.78 9.44 0 -21.08

Combined 1381 77.54 17.80 0 -29.88

Site 15 Without EXT2

Lithics 883 139.70 6.32 0 -24.23

Fauna 806 147.35 5.47 0 -22.26

Combined 1689 147.35 11.50 0 -32.88

Site 15 - EXT2 Lithics 477 34.34 13.90 0 -13.18

Fauna 261 67.22 3.88 0 -25.15

Combined 738 67.54 10.93 0 -23.20

Site102 Lithics 143 40.91 3.49 0 -7.73

Fauna 1098 43.88 25.01 0 -34.31

Combined 1241 47.95 25.88 0 -33.24

C7-1 Trench 1 Lithics 427 21.03 20.30 0 -16.40

Fauna 116 13.49 8.59 0 -8.19

Combined 543 22.11 24.56 0 -20.69

C7-1 Trench 3 Lithics 106 19.39 5.46 0 -7.58

Fauna 22 20.75 1.06 0.0776 -1.76*

Combined 129 25.37 5.08 0 -8.52

Summary Statistics of faunal and lithics collections from a few selected sites

Z-Score results for the most part reject the CSR null hypothesisfor randomness

Results – Intra-site (1A)

Results – Intra-site (1B)

-Strong local and well extended clustering(Site 102, Site 15 Main, C7-Trench 1 and 3)-More localized clustering(Site 2, Site 15 Ext. 2)

-Marked difference between the patternsFaunal and stone tool clustering at Site 102

Close-ups

Results – Intra-site (1C)

Orientations of excavated materials from a few selected sites

A more random pattern of orientations

Results – Intra-site (1C)

Rose diagrams plotting orientations of the same material shown in the earlier slide

Randomly scattered orientations

1 = The mean for compass angle (clockwise from due north)(only for one angle, the reverse (360 – 94.29 = 265.71) is also true for orientation)

2= Directional mean counterclockwise from due east3 = Circular variance – indicates how much line directions/orientations deviate

from the directional mean

-If all input vectors have exact or very similar direction CirVar is near 0-If the input vectors span the entire compass, the CirVar is near 1

ArcGIS GEOrient

SiteCompass

AngleDirectional

MeanCircular Variance

Max Frequency

(100)Circular Variance

Site 1 87.24 2.76 0.37 9.20% 0.65Site 2 93.06 356.95 0.37 7.00% 0.51Site 15 –EXTs only 82.16 7.84 0.36 7.10% 0.48Site 102 88.68 1.32 0.34 8.80% 0.52Site 126 100.25 349.75 0.33 12.80% 0.48Hyena hill 90.83 359.17 0.36 7.90% 0.59C7-1 Trench 1 77.04 12.96 0.37 9.60% 0.38C7-1 Trench 3 81.65 8.35 0.33 9.50% 0.47

Results – Intra-site (1C)

Circular ValuesSuggest a more Random pattern of orientation

Quantitative results from the ‘directional mean’ computations in ArcGIS and the rose-diagram in GEOrient

Results – Intra-site (2A)

Elliptical Polygons showing directional distribution of stone tools sorted by types of raw material

At least two differentpatterns of distributionswere observed

Results – Intra-site (2A)

K – function plots showing differences in patterns of stone tool distribution (sorted by types of raw material) with distance

All, but the stone tools madefrom Otp raw material, showa similar clustered distribution across the basin

Results – Intra-site (2B)Hot spot analysis (Getis-Ord Gi*) on flaked pieces Cluster/Outlier analysis on flaked pieces using local Moran’s I statistic

Hot spot analysis (Getis-Ord Gi*) on flaked pieces Cluster/Outlier analysis on flaked pieces using local Moran’s I statistic

Results – Intra-site (2B)

-Overall a patchy distribution of flaked pieces-More clustered distribution and better concentrations

of high-high values at Site 1, Site 2, and Site 15 Main-Mixed clustering of high and low values at Site 102-A cold spot (low values) at Site 15 Ext. 2-At Site 126, strong clustering (hot spot) with high-high and low-high values

Results – Intra-site (2B)Hot spot analysis (Getis-Ord Gi*) on flake fragments Cluster/Outlier analysis on flake fragments using local Moran’s I statistic

Results – Intra-site (2B)

Hot spot analysis (Getis-Ord Gi*) on flake fragments (Site 126)

Cluster/Outlier analysis on flake fragments using local Moran’s I statistic(Site 126)

-Strong clustering of flake fragments and high concentrationsof high-high values at Site 1, Site 2, and Site 15 Main

-Hot spots of flake fragments extended to hyena hill areas -Significant clustering of low values at Site 104 and Site 15 Ext. 2. -At Site 126 still strong clustering (hot spot) marked byhigh concentration of high-high values in southern portion of the site

Ordinary Least Square (OLS) Geographically Weighted Regression (GWR)

Element Value Element Value

R-Squared 0.036 Bandwidth 1

Adjusted R-Squared 0.036 Residual Squares 359.877

Coefficient 0.05 Effective Number 555.345

t-stat 11.93 Sigma 0.335

Probability 0 AICc****** 2771.83

AIC* 2838.02 R-Squared 0.25

Robust probability 0 R-Squared adjusted 0.13

Robust _t 7.044

F-stat** 142.53

F-Stat prob 0

Wald*** 49.625

Wald-Prob 0

K(Bp)**** 54.658

K(Bp)-Prob 0

JB***** 28562.55

JB-Prob 0

Sigma2 0.124

*Akaike's Information Criterion

** Joint F-statistics

***Wald Statistics

****Koenker's studentized Breusch-Pagan Statististic

*****Jarque-Bera Statistic

******corrected Akaike Information Criterion

Dependent Field Flaked Pieces

Results – Intra-site (2C)

Unreliable OLS result-Problem of nonstationarity

-Misspecification

GWR Result-More effective with multiple

exploratory variable

-Indicate only 13% of the flake piecesVariance can be related with the flake fragments

Bavariate Analysis – Flake pieces and flake fragments

Conclusion

• Different analytical approaches employed in this project can be used as a model to apply GIS as effective research tool in the study of Paleolithic collections of the distant past.

• Specific to Olorgesailie, this project has managed to:

– Develop efficient archival system for studying spatial distribution of all excavated findings.

– Look at variations in the spatial distributions of stone tools and fauna at several sites in the basin. The average nearest neighbor result rejects the CSR based null hypothesis.

– Develop a new approach of investigating possible impact of hydraulic forces in site formation process. The result from the analysis show lack of any major impact from hydraulic forces on distribution and accumulation of the archaeological remains

– Investigate the relation between distance from source of material and patterns of spatial distributions with a focus on particular group of stone tools.

– Analyze spatial autocorrelations of particular types of stone tools (flake pieces and flake fragments) across the basin. For the most part, the observed clustering noted at many of the sites found to be consistent with predicted patterns. Observations at a few sites, such as Site 126 reveal some important features shared by other major sites in the basin.

– Conduct bivariate analyses, which in spite of some limitations in applicability, provided important highlights that the spatial distribution of the flake pieces has no strong relations with distribution of the flake fragments

Future Improvements

• Integrate observations from multiple paleosols or intervals for better understanding changes in land-use patterns through time

• In the analysis of spatial data, integrate three-dimensional analyses for better control of spatial variations both horizontally and vertically.

• Incorporate multiple explanatory variables in future bivariate analyses.