Estimating the “memory of landscape” to predict changes in archaeological settlement patterns

Estimating the “memory of landscape” to predict

changes in archaeological settlement patterns

Philip VerhagenLaure Nuninger

Frédérique BertoncelloAngelo Castrorao Barba

CAA2015 SienaSession 5D – 2 April 2015

VU University Amsterdam

THE ROLE OF SOCIO-ENVIRONMENTAL DYNAMICS

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• settlement patterns are dynamic with creations, abandonments, reoccupations …

• where did communities settle during the past ?

• what drives their choices? – the environmental conditions? – the landscape’s potential for movement or control

of territories?– socio-economic considerations? – all of them?

analysing the settling conditions of archaeological sites can help to assess the factors that play a role in the transformations of ancient settlement systems


socio-environmental

visibility, accessibility

environmentalslope, aspect, solar radiation

socio-culturalheritage, hierarchy,

networks

PREDICTIVEVARIABLES

subsistence production

access and control

durability, path dependence

THEORETICALCONCEPTS

contextual analysisstatistical comparisonpredictive modelling

cross-regional

diachronic

ANALYSISTECHNIQUES

MODEL BUILDING BLOCKS

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THE “MEMORY OF LANDSCAPE”

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• where people settle, they manage the landscape– clearing– parcellation– soil improvement

• managed landscapes can be attractive to new settlement– even when they have been abandoned for some time

• the “memory of landscape” may therefore be a predictive variable


CALCULATING HERITAGE

AB

CD

E

300 400 5002001001-100-200-300-400-500

• settlement A is surrounded by other settlements with different life spans

• at the moment that A starts its occupation, there already is “memory of landscape” at its location– the “heritage” of A is the weight of duration of

occupation in its surroundings, prior to the period under study

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TEMPORAL WEIGHT

B = 100 x 1 + 100 x 0.8 + 100 x 0.6

= 240

C = 100 x 0.8

= 80

D = 0

E = 50 x 1 + 100 x 0.8 + 100 x 0.6 + 100 x 0.4 + 100 x 0.2 + 100 x 0

= 250

• temporal weight: linear decay, 0.2 per century– after 5 centuries, there will be no more influence of previous

occupation

-500 -400 -300 -200 -100 0 100 200 300 400 5000

50100150200250300350

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SPATIAL WEIGHT

• spatial weight: distance decay based on Epanechnikov kernel density function

• neighbourhood for kernel density is set to 1000 m– 500 m is supposed to be the average size of the exploitation

zone for Roman rural settlement– assumption: the surroundings of this exploitation zone have been

attractive for new settlement as well• heritage is then calculated for each grid cell in

study area, and for each century

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0.00.20.40.60.81.0

distance from site

weig

ht


STUDY AREA

• study area: Argens-Maures region (Var, Provence)- extensively studied for Archaeomedes and

Archaedyn programmes

- rugged terrain, approx. 35 x 45 km- archaeological inventory 800 BC – 800 AD- centuries studied:- 2nd BC, 1st BC, 1st AD and 5th AD

- potential problems- chronological resolution- reliability of survey

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HERITAGE MAPS

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HERITAGE MAPS

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HERITAGE MAPS

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HERITAGE MAPS

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SITE LOCATION ANALYSIS

• location of new settlements per century

- no-heritage areas (HER0)underrepresented-> effect of survey reliability?

- areas with strongheritage (HER3-4) become more important with time- -> path dependency?

% heritage class in the

landscape

% heritage class new

settlements

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ENVIRONMENT OR HERITAGE?

• MaxEnt modelling using environmental context (slope, aspect, solar radiation) and heritage

quality of prediction

contribution of variablesperiod heritage (%)

environment (%)

IIBC 73.6 26.4IBC 62.3 37.7IAD 56.4 43.6VAD 91.7 8.3

period AUC nIIBC 0.719 36IBC 0.672 67IAD 0.694 146VAD 0.793 45

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RELIABILITY OF SURVEY

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• use of bias filter changes contribution of variables

• effects on model quality are less marked- predictions were only moderately strong anyway

EFFECTS ON MODEL RESULTS

environment (%)

environment (%)

26.4 37.037.7 45.543.6 67.78.3 11.8

period heritage (%)

heritage (%)

IIBC 73.6 63.0IBC 62.3 54.5IAD 56.4 32.3VAD 91.7 88.2

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period AUC AUCIIBC 0.719 0.688IBC 0.672 0.667IAD 0.694 0.695VAD 0.793 0.797


CONCLUSIONS

• “memory of landscape” seems to influence the location of new settlements- predictive power is only moderately strong - though

stronger thanenvironmental context

- path dependency can be hypothesized- survey intensity should be taken into account

• heritage variable needs closer scrutiny- potentially conflates two variables1. heritage of abandoned settlements and their

surroundings2. heritage in surroundings of existing settlements -> these settlements are not available for reoccupation

• testing in other areas necessary17

Estimating the “memory of landscape” to predict changes in archaeological settlement patterns

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