Advances in Anthropology
2012. Vol.2, No.2, 39-48
Published Online May 2012 in SciRes (http://www.SciRP.org/journal/aa) http://dx.doi.org/10.4236/aa.2012.22005
Copyright © 2012 SciRes.
39
Mapping Three-Dimensional Density Patterns for Analyzing
Artefact (Re)distribution Trends in Palaeolithic Sites
Rosalia Gallotti1, Giuseppe Lembo2, Carlo Peretto2
1Université Bordeaux, UMR 5199 PACEA PPP, Talence, France
2Sezione Paleobiologia, Preistoria ed Antropologia, Dipartimento di Biologia ed Evoluzione,
Università degli Studi di Ferrara, Ferrara, Italy
Email: rosalia.gallotti@u-bordeaux1.fr
Received February 5th, 2012; revised March 20th, 2012; accepted March 30th, 2012
The artefact density in an archaeological deposit provides a direct record of the concentrating and dis-
persing effects of various formation processes. 2D density analyses have frequently been processed, espe-
cially through the topological properties of the Geographical Information System. Nevertheless, the re-
sulting 2D visualisation by density maps does not consider or analyze the vertical interpolation of ar-
chaeological finds. This is limiting in the case of very thick archaeostratigraphic units, where the 3D
visualisation of the density phenomena provides a basic tool for a better understanding of the real spatial
distribution trends of archaeological remains. In this paper, we propose a new method for processing 3D
density analyses, and we present its first application to the Middle Pleistocene site of Isernia La Pineta as
a further step towards distinguishing the impact of natural and anthropogenic processes on site formation
and stratogenesis.
Keywords: Intra-Site Spatial Analyses; 3D Density Patterns; Site Formation Processes; Geographical
Information System; Middle Pleistocene; Isernia La Pineta
Introduction
The spatial distribution of archaeological remains in Palaeo-
lithic sites rarely reflects an undisturbed state of abandon by
humans. Frequently, complex post-depositional phenomena,
which can be anthropogenic or natural, alter the initial human-
induced site patterning and produce multi-genesis palimpsests
(Bailey, 2007; D’Andrea & Gallotti, 2004; D’Andrea et al.,
2002; Malinsky-Buller et al., 2011; Schiffer, 1983; Texier,
2000).
Especially in the case of very rich archaeostratigraphic units
resulting from long-lasting human occupation and/or corre-
sponding to palimpsests, the increase and/or overlapping of
activity areas along with natural disturbance mechanisms
strongly limit our ability to recognize clear-cut distribution
trends and interpret their socio-economic and behavioural
meaning (Yellen, 1977; Djindjian, 1999).
By considering the numerous potential disturbance factors,
intra-site spatial analyses, integrated in a multidisciplinary ap-
proach for determining the mechanisms that have contributed to
sedimentation, nowadays appear to be among most advanced
techniques of spatial investigation for estimating the role of
burial processes. The identification of these processes should
precede behavioural inference that uses evidence from the ar-
chaeological record (Blankholm, 1991; D’Andrea & Gallotti,
2004; D’Andrea et al., 2002; Djindjian, 1988, 1999; Hodder &
Orton, 1976; Johnson, 1976; Kintigh & Ammermann, 1982;
Simek, 1984; Whallon, 1984; Wheatley & Gillings, 2002).
In the last two decades these techniques have been frequently
processed through the topological properties of the Geographi-
cal Information System (GIS). This has been employed for a
long time in archaeological landscape studies (Petrie et al.,
1995) and has recently been applied to interpretations of intra-
site spatial distribution trends of artefacts (Benito-Calvo & de
la Torre, 2011; Cooper & Qiu, 2006; Craig et al., 2006;
D’Andrea et al., 2000, 2002; Gallotti & Piperno, 2004; Gallotti
et al., 2004, 2011; Lembo & Gallotti, 2006; Nigro et al., 2001,
2003; Peretto et al., 2010; Thomas et al., 1996; Vullo et al.,
1999).
Among the most useful spatial techniques is density analysis
of artefacts (Jerardino, 1995; Johnson, 1976; Schagen, 1986),
which is able to recognize concentration and dispersing trends
in artefacts (re)distribution (Schiffer, 1983). The density func-
tion calculates the quantity of points in a level on a continuous
surface. Thus, the occurrence and, in particular, the closeness of
points is highlighted through the generation of a new two-di-
mensional map of density values beginning from a given point.
Values are expressed through density curves quantified on the
basis of a k-nearest neighbour distance calculated from the
centroid of the objects. Proximity function in the GIS performs
this analysis by creating a buffer zone around each artefact
point (Mitchell, 1999).
However, the resulting two-dimensional map does not con-
sider and analyze the vertical dispersal of finds. Unfortunately,
the two-dimensional model is not always appropriate for con-
ducting spatial analyses in thick archaeostratigraphic units,
where the vertical interpolation influences the two-dimensional
representation of spatial patterns. Until recently this has re-
ceived relatively little attention in the specialist literature, likely
due to certain limitations of conventional GIS software (Moyes,
2002; Spikins et al., 2002).
Previously, the tree-dimensional representation of density
analyses has been approached in only two instances (Barceló,
2002; Baxter et al, 1997; Beardah, 1999; Beardah & Baxter,
39
R. GALLOTTI ET AL.
1999; Nigro et al., 2003). In an attempt to bypass this obstacle,
we have created a user-friendly software (DA3D) that calcu-
lates a three-dimensional density function. Resulting calcula-
tions were performed by Voxler©, a three-dimensional visuali-
sation software. Finally, we present the first results from the
application of this new technique, as carried out at the Early
Middle Pleistocene site of Isernia La Pineta (Molise, Italy).
Isernia La Pineta Archaeological Context
The site of Isernia La Pineta is located at an elevation of ca.
400 m a.s.l. in the Upper Volturno Basin at the periphery of the
town of Isernia in Central Italy (Figure 1(a)). It represents the
oldest and morphostratigraphically highest Pleistocene sedi-
mentological unit described in the basin (Coltorti, 1983; Van
Otterloo & Sevink, 1983).
Isernia La Pineta is one of the earliest Italian archaeological
sites (Coltorti et al., 2005; Shao et al., 2011) and is one of the
key sites for our understanding of human behavior at the begin-
ning of the Middle Pleistocene. Numerous faunal remains and a
core and flake industry have been found within a thick strati-
graphy composed of fluvial, lacustrine and volcanic sediments
(Anconetani et al., 1992; Coltorti et al., 1982; Cremaschi, 1983;
Cremaschi & Peretto, 1988; Peretto et al., 2004). The deposit
has been excavated in two different sectors: Sector I of about
250 m2 (the present area of excavation is covered by a pavilion),
and Sector II of 90 m2, investigated at the beginning of 1980s
(Peretto, 1999).
The stratigraphy of the site (Figures 1(b), (c)) has been de-
scribed mainly by Coltorti & Cremaschi (1982) and by Cre-
maschi (1983), who recognized the following units (listed from
the base of the section, upwards): Unit 5, lacustrine clays with
thin layers of gravels and debris; Unit 4, travertines; Unit 3,
palustrine deposits with sands and fine gravels; Unit 2, sands
and gravels; Unit 1, gravels and sands with intercalated tuffs.
Unit 3 contains the archaeological deposits and it is composed
of the following sub-units in Sector I (again listed from the base
Figure 1.
Stratigraphic setting and location of the site. (a) 1, limestone bedrock; 2, main filling of
the basin; 3, travertines; 4, recent fluvial deposits; (b) Stratigraphic sequence of Isernia La
Pineta and Villa Belfiore with the indication of the lithological units utilised by Cremaschi
(1993); 1C, detailed stratigraphy of Unit 3 in Sector I (after Coltorti et al., 2005).
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R. GALLOTTI ET AL.
of the unit):
3F: this sub-unit is subdivided into three layers:
t.3c—archaeological and paleontological remains lying on
phytoclastic travertine of the Unit 4;
t.3b—alluvial muddy-clayey covering t.3c, archaeologically
sterile;
t.3a—the main occupation level lying on top of the clay layer
and travertines, composed of a high concentration of flint and
limestone artefacts, faunal remains that mostly consist of large
bones, and reworked natural elements of travertine;
3E (or 3coll): pyroclastic layer (debris-flow) composed of up
to 30 - 100 cm thick unit of reworked and well sorted elements
including large crystals of sanidine (with a 40Ar/39Ar age of 610
± 10 and 606 ± 2 ka; Coltorti et al., 2005), and pyroxene. This
sub-unit is usually rich in archaeological materials;
3D: gravels, coarse sands and finer sediments of ca. 150 cm
thick, divided in two artificial splits: 3s1-5 and 3s6-9. Lithic
and faunal remains are scattered throughout the entire thickness
of this subunit. The number of finds recorded to present is
summarized in Table 1.
The faunal remains are predominantly bison, elephant and
rhinoceros. Less common are megaceros, red deer, fallow deer,
thar and hippopotamus. Amongst the carnivores, bear is fre-
quent, and lion is known from a single ferine tooth (Peretto,
1996; Peretto et al., 2004). Impact areas caused by intentional
fracturing are evident on a great number of bones from the
entire stratigraphic sequence; striations related to butchery with
lithic tools are sometimes visible (Thun Hohenstein et al.,
2002).
The main goals of lithic production are the flaking activities,
on both flint and limestone. The flint has often been worked
using the bipolar technique on anvil (Peretto et al., 2004).
Background on Previous Spatial Analyses at
Isernia La Pineta
The t.3a excavation in Sector I has yielded the greatest quan-
tity of paleontological remains. It is located directly above the
travertine of the Unit 4 in the SW part; northward, it lies on
mudstone (t.3b). This discontinuity gradually becomes less
marked towards the NE, and the materials are contained within
muddy-clayey layers (Cremaschi, 1983). Cross-bedded fine
gravelly sands 3E (3coll) containing reworked archaeological
elements cover the deposits and are interlayered with tuffs very
rich in pyroxene and sanidine.
In previous studies, t.3a of Sector I has been interpreted as a
single depositional and anthropogenic event (“living floor”), it
has been labeled as an “archaeosurface” and behavioral inter-
pretation has been deduced from the analysis of the spatial dis-
tribution of finds (Peretto, 1999; Peretto et al., 2004). This is
Table 1.
Isernia La Pineta. Number of finds recorded per stratigraphic unit.
t.3c
(52 m2)
t.3a
(167 m2)3E
(82 m2)
3s6-9
(81 m2)3s1-5
(65 m2)
Lithic artefacts 451 4056 6051 2554 653
Faunal remains 388 7432 5235 2791 1045
Natural materials 230 7871 693 314 0
Total 1069 19,35911,979 5659 1698
likely due to the existence of a general consensus (possibly
unfounded) broadly shared in previous years over the primary
position of this Lower Paleolithic deposit. Given the fine-
grained contexts in which assemblages are located and the
mainly fresh condition of artefacts and bones, it is widely
agreed that t.3a experienced no major postdepositional distur-
bance. Furthermore, the idea of a “living floor” has been effec-
tively induced during the first years of excavation based on two
main factors: 1) the presence of numerous large anatomical
elements together with lithic industry lying on a sub-horizontal
surface creating a sort of anthropic “pavage”; 2) the partial
destruction of the upper part of the stratigraphic sequence by
the beginning of works for construction of the Naples-Vasto
highway. This event did not permit a detailed analysis of the
stratigraphic relationship between t.3a and 3E in the western
part of the excavated area.
In order to investigate the patterns of the spatial distribution
of finds in the archaeostratigraphic units, a specific GIS for the
mapping and analysis of fossil deposits at Isernia La Pineta has
been developed. Due both to the extent of the investigated area
and the number of finds, the adoption of a GIS was indispensa-
ble for data management and for performing spatial statistical
techniques.
This GIS application, developed since 2001 (Gallotti, 2004;
allotti et al., 2004), permitted the following operations: G
- conversion of paper archives of previous excavations (1978-
1999) into digital format;
- three-dimensional location of all finds from the new exca-
vations (2000-present) collected using a total station;
- processing of archaeological entities as spatial variables;
- spatial interrogations for creating thematic maps (Figure
2(a)) and cross-sections (Figure 2(e)). A vector model, rep-
resenting features as points or polygons for plans, and as
points for cross-sections, was used. Cross-sections corre-
spond effectively to a two-dimensional representation: by
ranging the values of x or y, respectively, on the abscissa,
and those of z on the ordinate, it was possible to plot the
projection of all finds for mapping transversal and longitu-
dinal sections. Thus, this operation does not correspond to a
true three-dimensional space management;
- statistical inference of two-dimensional spatial data (fre-
quency matrixes, density analyses) to highlight distribution
patterns (Figures 2(b), (c), (d)).
These GIS-based analyses highlight that spatial patterns at
t.3a, considered globally, appear to be random. Although ana-
lyzed for single categories, the spatial distribution trends in the
central and eastern part of this archaeosurface do not differ
significantly from a uniform model. This datum is expected
from archaeological and/or paleontological concentrations dis-
turbed by natural agents and it is uncharacteristic of in situ
assemblages.
Nevertheless, when analyzing the spatial trends of the vari-
ous categories of finds, it appears to be possible that some
zones in the SW part of Sector I directly above the travertine of
the Unit 4 may harbor some associations due to anthropogenic
action, as a flint knapping area, where products and by-products
of the same chaînes opératoire aimed at different output are
concentrated (Figure 2(b)).
Method
The method of the three-dimensional density analysis was
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R. GALLOTTI ET AL.
Figure 2.
Isernia La Pineta, Sector I. (a) t.3a—distribution of all remains (red: limestone; blue: flint; black: faunal elements; green: travertine); (b) t.3a—two-
dimensional density map of flint; (c) t.3a—frequencies per square meter of all remains; (d) t.3a—chart map with the relationship between flint (blue)
and limestone (red); (e) 3E: longitudinal projection of all remains.
processed in 2009 following the development of the GIS. The
complexity of the depositional phenomena and the thickness of
the stratigraphic sequence required the mapping and spatial
analysis of a true three-dimensional distribution of finds. For
this goal we created a software package (DA3D) with the abil-
ity to count the number of finds (points) within a sphere at a
variable radius, whose center is a given point corresponding to
the centroid (geometric center) of each find. This counting re-
sults from the Euclidean distance calculation for measuring the
space from the center of the sphere to the center of all other
points in the dataset. If this distance is equal to or less than the
radius of the sphere, the point is counted.
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R. GALLOTTI ET AL.
Thus,
Set of archaeological objects: A(xA, yA, zA), B(xB, yB, zB), C(xC,
yC, zC) N(xN, yN, zN)
for each (PA in Points)
for each (PB in Points)
if (k d(PA, PB))
count (PA)++
where:
P = dataset for density calculation. Example: PA is the set of
points considered for counting and the centre of the sphere is
the point A
k = radius of the sphere
d(Euclidean distance) =

ABAB AB
22
PPPP PP
xxyy zz
2
The complexity of the algorithm is O(n2).
A schematic example is given in Figure 3.
The database obtained from the data processing in DA3D
was imported to Voxler©, a three-dimensional scientific visu-
alization program, primarily oriented toward volumetric ren-
dering and three-dimensional data display. While the emphasis
is on three-dimensional volumes, Voxler© can also utilize two-
dimensional grids including DEM files, images, and scattered
point data. Voxler© can display streamlines, vector plots, con-
tour maps, isosurfaces, image slices, three-dimensional scatter
plots, and direct volume rendering, among others. Computa-
tional modules include three-dimensional gridding (performed
using inverse distance and local polynomial gridding method),
resampling, numerous lattice operations, and image processing.
Using the three-dimensional lattice properties, a sphere at a
variable radius was visualized around each point. A three-di-
mensional thematic map for ranges of values can be created
starting from the density values contained in the database asso-
ciated to the point set (Figure 4).
It is also possible to explore the density patterns using the
functions of clipPlane and orthoimage: one or more orthogonal
or oblique planes can be visualized and moved across the three-
dimensional density map. Thus, the map can be cut in any posi-
tion and in any angle. Additionally, several two- and/or three-
dimensional maps can be viewed simultaneously or separately.
Preliminary Results
As described above, random spatial distribution of finds has
PB
PA
Figure 3.
Schematic representation of the density calculating method.
B
A
A
B C
C D D E E
Z Z
DD
B B
A A
CC
E E
X X
Y Y
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R. GALLOTTI ET AL.
Figure 4.
An example of data elaboration in Voxler©.
been identified in the central and eastern part of the t.3a in Sec-
tor I, where it lies on mudstone (t.3b). Spatial investigation and
the revised Sector I stratigraphy advanced the hypothesis that
3E, the debris-flow, could have partially reworked the underly-
ing t.3a (Coltorti et al., 2005). In order to add further spatial
analytical components to test this hypothesis, as well as better
understand formation mechanisms for this part of the deposit,
we explored the spatial distribution of finds in t.3a and 3E and
their relationship to each other. In particular, the density analy-
sis allows us to identify whether the concentrating and dispers-
ing areas in these entities are superimposed.
In this paper we present the preliminary results of the 3D
density analysis of these archaeostratigraphic (sub)units as the
first step towards a general revaluation of the formation mecha-
nisms of t.3a deposit using new data from spatial archaeology,
geology, sedimentology, stratigraphy and geoarchaeology.
We selected a test area of 24 m2 where both units were com-
pletely excavated. We processed two-dimensional density maps
for t.3a because it is impossible to reconstruct the z values of
archaeological finds as they have been left in situ for museal
purposes. In this case, we considered a two-dimensional analy-
sis representative of the effective spatial density patterns be-
cause, as mentioned previously, the finds of t.3a lie on a sub-
horizontal surface without vertical dislocation. However, the
thickness of 3E required the application of three-dimensional
density analysis to explore the vertical location of the density
areas in order to evaluate the effective correspondence with the
underlying density phenomena identified in t.3a.
The density patterns were calculated using a sphere at a ra-
dius of 25 cm. Considering the excavated surface of the study-
area and the thickness of its deposit, the choice of such a radius
allowed us the optimal visualization to highlight phenomena of
spatial concentration and dispersion of finds.
In order to visualize both units simultaneously, a standard z
value was assigned to the finds recorded in t.3a. The resulting
maps show the top view of both units (Figures 5(a) and (b)),
the front and lateral views of the superimposed units and the
relative axonometric view (Figures 5(c)-(e)). Also, we ex-
plored the density phenomena by slicing the maps along or-
thogonal (Figure 6(a)) and oblique planes (Figure 6(b)).
These maps allowed us to recognize that the maximum den-
sity in 3E is located in the lower SE part of the sampled area
(Figures 5(b)-(d), 6); this is clearly due to the slope of the de-
bris-flow. This area does not correspond to an equivalent den-
sity trend in t.3a, where the maximum concentration of finds is
in the NW zone of the same excavated area (Figure 5(a)).
Therefore, the spatial patterns obtained in our analysis suggest
that action of a geological agent such as the debris-flow has not
moved fossils and stone tools of t.3a. If supported by further
archaeological and geological data, as well as enlarging the
study area, this datum could confirm that the debris-flow 3E
has not reworked or not strongly reworked the underlying unit
t.3a and that the formation processes of these two units are
completely or nearly independent. In this case, 3E would not be
directly responsible of the random distribution patterns in the
central and eastern area of the excavated surface. Likely, the
formation processes of the western part and of the central and
astern area of t.3a could be due to two or more distinct (post) e
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R. GALLOTTI ET AL.
Figure 5.
Isernia La Pineta, Sector I. (a) Density map of t.3a; (b) Density map of 3E; (c) Front view of the density patterns of t.3a and 3E; (d) Lateral view of
the density patterns of t.3a and 3E; (e) Axonometric view of the density patterns of t.3a and 3E.
depositional phenomena and not correspond to a single event,
as has been assumed previously.
Conclusion
Density analyses, associated with other archaeological and/or
geological criteria, are a useful tool to investigate site formation
processes. Because most applications are limited to two dimen-
sions, most archaeological studies allow for only a partial as-
sessment of three-dimensional spatial density patterns, particu-
larly in the case of very thick archaeostratigraphic units.
This project set out to develop a method to process three-
dimensional density analyses and to visualize the resulting spa-
ial trends. After developing a specific GIS for mapping and t
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R. GALLOTTI ET AL.
Figure 6.
Isernia La Pineta, Sector I. (a) Orthogonal planes cutting the axonometric view of the density patterns of t.3a and 3E; (b) Oblique plane cutting the
axonometric view of the density patterns of t.3a and 3E.
analyzing fossil deposits, we attempt to assess the potential of
this method in the reconstruction of depositional and post-de-
positional mechanisms of the Middle Pleistocene site of Isernia
La Pineta. The results show that this model has clear potentials
and can be broadly applied to other similar sites.
Acknowledgements
We thank the Ministero per i Beni e le Attività culturali for
giving permission to Carlo Peretto from the Università degli
Studi di Ferrara to conduct research at Isernia La Pineta. We
would like to express deep thanks to all institution that finan-
cially supported field and laboratory activities (Ministero per i
Beni e le Attività culturali, Provincia di Isernia, CERP, Istituto
Banco di Napoli-Fondazione, Università degli studi di Ferrara,
CNR, PRIN). We thank Université Bordeaux 1, UMR 5199
PACEA-PPP who allowed Rosalia Gallotti to pursue her work
at Isernia La Pineta in the frame of a Post-PhD grant of Région
Aquitaine.
We thank also Jean-Paul Raynal for his suggestions, Leah
Morgan for the English revision, and reviewer for its useful
comments.
Finally, we are thankful to those who have given us their
constant and continuous collaboration.
REFERENCES
Anconetani, P., Crovetto, C., Ferrari, M., Giusberti, G., Longo, L.,
Peretto, C., & Vianello, F. (1992). Nuove ricerche nel giacimento di
Isernia La Pineta (Molise). Rivista di Scienze Preistoriche, XLIV,
3-41.
Bailey, G. (2007). Time perspectives, palimpsests and the archaeology
Copyright © 2012 SciRes.
46
R. GALLOTTI ET AL.
of time. Journal of Anthropological A rc h a eo l og y , 26, 198-223.
doi:10.1016/j.jaa.2006.08.002
Barceló, J. A. (2002). Archaeological thinking: between space and time.
Archeologia e Calcolatori, 13, 237-257.
Baxter, M., Beardah, C. C., & Wright, R. V. S. (1997). Some archaeo-
logical applications of Kernel Density Estimates. Journal of Ar-
chaeological Science, 24, 347-354. doi:10.1006/jasc.1996.0119
Beardah, C. C. (1999). Uses of multivariate kernel density estimates in
archaeology. In L. Dingwall, S. Exon, V. Gaffney, & S. Laflin (Eds.),
Archaeology in the Age of the Internet. Oxford: BAR International
Series 750.
Beardah, C. C., & Baxter, M. (1999). Three-dimensional data display
using kernel density estimates. In J. Barceló, I. Briz, & A. Vila (Eds.),
New Techniques for Old Times. Proceedings of CAA98 (pp. 163-169).
Oxford: Archaeopress.
Benito-Calvo, A., & De la Torre, I. (2011). Analysis of orientation
patterns in Olduvai Bed I assemblages using GIS techniques: Impli-
cations for site formation processes. Journal of Human Evolution, 61,
50-60. doi:10.1016/j.jhevol.2011.02.011
Blankholm, H. P. (1991). Intrasite spatial analysis in theory and prac-
tice. Aarhus: Aarhus University Press.
Coltorti, M. (1983). Le fasi principali dell’evoluzione del paesaggio nel
bacino di Isernia (Molise). In M. Coltorti (Ed.), Isernia La Pineta, un
accampamento più antico di 700.000 anni (pp. 41-47). Bologna:
Calderini.
Coltorti, M., & Cremaschi, M. (1982). Depositi quaternari e movimenti
neotettonici nella conca di Isernia. Contributi Conclusivi per la carta
Neotettonica d’Italia, Consiglio Nazionale Richerche. Progreso
Financiero, 506, 173-198.
Coltorti, M., Feraud, G., Marzoli, A., Peretto, C., Ton-That, T.,
Voinchet, P., Bahain, J.-J., Minelli, A., & Thun Hohenstein, U.
(2005). New 40Ar/39Ar, stratigraphic and palaeoclimatic data on the
Isernia La Pineta Lower Palaeolithic site, Molise, Italy. Quaternary
International, 131, 11-22. doi:10.1016/j.quaint.2004.07.004
Cooper, J. R., & Qiu, F. (2006). Expediting and standardizing stone
artifact refitting using a computerized suitability model. Journal of
Archaeological Science, 33, 987-998.
doi:10.1016/j.jas.2005.11.005
Craig, N., Aldenderfer, M., & Moyes, H. (2006). Multivariate vis-
ualization and analysis of photomapped artifact scatters. Journal of
Archaeological Science, 33, 1617-1627.
doi:10.1016/j.jas.2006.02.018
Cremaschi, M. (1983). La serie pleistocenica di Isernia La Pineta
(Molise) e la posizione stratigrafica dei suoli di abitato paleolitici in
essa inclusi. In M. Coltorti (Ed.), Isernia La Pineta. Un accam-
pamento più antico di 700.000 anni (pp. 49-62). Bologna: Calderini.
Cremaschi, M., & Peretto, C. (1988). Les sols d’habitat du site paleo-
lithique d’Isernia La Pineta (Molise, Italie). LAnthropologie, 92,
643-682.
D’Andrea, A., & Gallotti, R. (2004). GIS and intra-site spatial analysis.
In J. Chavaillon, & M. Piperno, (Eds.), Studies on the Early Paleo-
lithic Si te of Me lk a Ku n tu r e, E t hi o pia (pp. 589-597). Firenze: Origines.
D’Andrea, A., Gallotti, R., & Piperno, M. (2000). Applicazione di un
GIS intra-site al giacimento paleolitico di Garba IV (Melka Kunture,
Etiopia). Archeologia e Calcolatori, 11, 319-338.
D’Andrea, A., Gallotti, R., & Piperno, M. (2002). Taphonomic inter-
pretation of the developed Oldowan site of Garba IV (Melka Kunture,
Ethiopia) through a GIS application. Antiquity, 7 6 , 991-1001.
Djindjian, F. (1988). Improvements in intrasite spatial analysis tech-
niques. In S. P. Q. Rahtz (Ed.), Computer and Quntitative Methods in
Archaeology (pp. 95-106). Oxford: British Archaeological Reports
(International Series).
Djindjian, F. (1999). L’analyse spatiale de l’habitat: Etat de l’art. Arch-
eologia e Calcolatori, 10 , 17-32.
Gallotti, R. (2004). Analisi spaziali e metodologie computazionali per
un approccio cognitivo ai modelli di frequentazione antropica del
giacimento di Isernia La Pineta (Molise, Italia). Ph.D. Thesis,
Ferrara: Ferrara University.
Gallotti, R., Arzarello, M., Lembo, G., Minelli, A., Thun Hohenstein,
U., & Peretto, C. (2004). Informatic management of the excavation
data of Isernia La Pineta (Molise, Italy). Proceedings of the XIV
UISPP Congress, Liege, 2-8 September 2002.
Gallotti, R., Mohib, A., El Graoui, M., Sbihi-Alaoui, F.-Z., & Raynal,
J.-P. (2011). GIS and intra-site spatial analyses: An Integrated ap-
proach for recording and analyzing the fossil deposits at Casablanca
Prehistoric sites (Morocco). Journal of Geographic Information Sys-
tem, 3, 373-381. doi:10.4236/jgis.2011.34036
Gallotti, R., & Piperno, M. (2004). Prehistoric archaeology. The site of
Garba IV. Spatial analysis of the lithic material from Level D. In J.
Chavaillon, & M. Piperno, (Eds.), Studies on the Early Paleolithic
site of Melka Kunture, Ethiopia (pp. 599-635). Firenze: Origines.
Hodder, I., & Orton, C. (1976). Spatial Analysis in Archaeology. Cam-
bridge: CUP.
Jerardino, A. (1995). The problem with density values in archaeological
analysis. A case study from Tortoise Cave, Western Cape, South Af-
rica. South African Archaeological Bullettin, 50, 21-27.
doi:10.2307/3889271
Johnson, T. (1976). Contribution méthodologique à l’étude de la
répartition des vestiges dans les niveaux archéologiques. Diplôme
d’Etudes Supérieures, Bordeaux: University of Bordeaux.
Kintigh, K. W., & Ammermann, A. J. (1982). Heuristic approaches to
spatial analysis in archaeology. American Antiquity, 47, 31-63.
doi:10.2307/280052
Lembo, G., & Gallotti, R. (2006). L’analisi spaziale intra-site. Trend
distributivi dei reperti litici e paleontologici delle archeosuperfici 3c
e 3a del I Settore di scavo. In C. Peretto, & A. Minelli (Eds.), La
Preistoria del Molise. Gli insediamenti nel territorio di Isernia (pp.
96-119). Collana Ricerche del Centro Europeo Ricerche Preistoriche
(CERP), 3. Isernia: ARACNE.
Malinsky-Buller, A., Hovers E., & Marder O. (2011). Making time:
‘Living floors’, ‘palimpsests’ and site formation processes—A per-
spective from the open-air lower paleolithic site of Revadim Quarry,
Israel. Journal of Anthropological Arc ha eo lo gy , 30, 89-101.
doi:10.1016/j.jaa.2010.11.002
Mitchell, A. (1999). Mapping density. The ESRI Guide to GIS Analysis
Volume 1: Geographic Patterns & Relationships (pp. 69-85). Cali-
fornia, ESRI Press.
Moyes, H. (2002). The use of GIS in the Spatial analysis of an ar-
chaeological cave site. Journal of Cave a nd Ka rs t St ud ies, 64, 9-16.
Nigro, D., De Ruiter, D. J., Berger, L. R., & Ungar, P. S. (2001). A
tridimensional geographic information system for Swartkrans. Meet-
ing of the Paleoanthropology Society, Kansas City.
Nigro, D., Ungar, P. S., De Ruiter, D. J., & Berger, L. R. (2003). De-
veloping a geographical information system (GIS) for mapping and
analysing fossil deposits at Swartkrans, Gauteng Province, South Af-
rica. Journal of Archaeological Science, 30, 317-324.
doi:10.1006/jasc.2002.0839
Peretto, C. (1996). I reperti paleontologici del giacimento paleolitico di
Isernia La Pineta. Isernia: Cosmo Iannone Editore.
Peretto, C. (1999). I suoli d’abitato del giacimento paleolitico di
Isernia La Pineta, natura e distribuzione dei reperti. Isernia: Cosmo
Iannone Editore.
Peretto, C., Arzarello, M., Gallotti, R., Lembo, G., Minelli, A., & Thun
Hohenstein, U. (2004). Middle Pleistocene behavioural strategies:
the contribution of Isernia La Pineta site. In E. Baquedano, & S.
Rubio Jara (Eds.), Miscelanea en Homenaje a Emiliano Aguirre,
Volumen IV, Arqueologia (pp. 369-381). Alcalá de Henares: Museo
Arqueologico Regional.
Peretto C., Arzarello M., Gallotti R., Lembo G., Minelli A., & Thun
Hohenstein, U. (2010). The intra-site analysis of the palaeolithic site
of Isernia La Pineta (Molise, Italia). In F. Niccolucci, & S. Hermon
(Eds.), Beyond the Artifact. Digital Interpretation of the Past (pp.
201-206). Budapest: Archaeolingua.
Peretto, C., Biagi, P., Boschian, G., Broglio, A., De Stefani, M., Fasani,
L., Fontana, F., Grifoni, R., Guerreschi, A., Iacopini, A., Minelli, A.,
Pala, R., Peresani, M., Radi, G., Ronchitelli, A., Sarti, L., Thun
Hohenstein, U., & Tozzi, C. (2004). Living-floors and structures
from the lower paleolithic to the bronze age in Italy. Collegium an-
tropologicum, 28, 63-88.
Petrie, L., Johnson, I., Cullen, B., & Kvamme, K. (1995). GIS in ar-
Copyright © 2012 SciRes. 47
R. GALLOTTI ET AL.
Copyright © 2012 SciRes.
48
chaeology: An annotated bibliography. Archaeological Methods Se-
ries 1. Sydney: Sydney University.
Schagen, I.P. (1986). Construction of continuous density functions
from spatially distributed categorical data. Applied Mathematical
Modelling, 10, 53-56. doi:10.1016/0307-904X(86)90009-0
Shao, Q., Bahain, J.-J., Falguères C., Peretto, C., Arzarello, M., Minelli,
A., Thun Hohenstein, U., Dolo, J.-M., Garcia, T., Frank, N., & Dou-
ville, E. (2011). New ESR/U-series data for the early Middle Pleis-
tocene site of Isernia la Pineta, Italy. Radiation Measurements, 46,
847-852. doi:10.1016/j.radmeas.2011.03.026
Shiffer, M. B. (1983). Toward the identification of formation processes.
American Antiquity, 48, 675-706. doi:10.2307/279771
Simek, J. F. (1984). A K-means approach to the analysis of spatial
structures in Upper Palaeolithic habitation sites: Le Flageolet I and
Pincevent Section 36. Oxford: British Archaeological Reports (In-
ternational Series), 205.
Spikins, P., Conneller, C., Ayestaran, H., & Scaife, B. (2002). GIS
Based interpolation applied to distinguishing occupation phases of
early prehistoric sites. Journal of Archaeological Science, 29, 1235-
1245. doi:10.1006/jasc.2001.0752
Texier, J.-P. (2000). A propos des processus de formation des sites
préhistoriques. Paléo, 12, 379-386.
Thomas, J., Potts, R., & Cole, D. (1996). The role of GIS in the inter-
disciplinary investigation at Olorgesailie, Kenya, a Pleistocene Ar-
chaeological Locality. In M. Aldenderfer, & H. D. G. Maschner
(Eds.), Anthropology, Space and Geographical Information System
(pp. 202-213). New York: Oxford University Press.
Thun Hohenstein, U., Malerba, G., Ghirelli, E., Giacobini, G., & Per-
etto, C. (2002). Attività di sussistenza nel paleolitico inferiore di
Isernia La Pineta: Archeozoologia delle US 3S10 e 3coll. Rivista di
Scienze preistoriche, LII, 1-18.
Van Otterloo, R., & Sevink, J. (1983). The Quaternary evolution of the
Upper Volturno basin. In M. Coltorti (Ed.), Isernia La Pineta. Un
accampamento più antico di 700.000 anni (pp. 35-39). Bologna:
Calderini.
Vullo, N., Fontana, F., & Guerreschi, A. (1999). The application of GIS
to intra-site spatial analysis: preliminary results from Alpe Veglia
(VB) and Mondeval de Sora (BL), two mesolithic sites, in Italian
Alpes. In J. Barcelò, I. Briz, & A. Vila (Eds.), New Techniques for
Old Times (pp. 111-115). Oxford: BAR International Series, 757.
Whallon, R. (1984). Unconstrained clustering for the analysis of spatial
distributions in archaeology. In H. J. Hietala (Ed.), Intrasite Spatial
Analysis in Archaeology (pp. 242-277). Cambridge: Cambridge
University Press.
Wheatley, D., & Gillings, M. (2002). Spatial technology and archae-
ology. The archaeological applications of GIS. London: Taylor and
Francis. doi:10.4324/9780203302392
Yellen, J. (1977). Archaeological approaches to the present. New York:
Academic Press.