archaeological predictive models-libre

8/12/2019 Archaeological Predictive Models-libre

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ARCHAEOLOGICAL PREDICTIVE MODELS AND THE HUNGARIAN

CULTURAL HERITAGE PROTECTION

GBOR MESTERHZY MT STIBRNYI1

The first and foremost task of archaeological heritage protection is the spatial identification of archaeological

sites. Our study proposes the introduction of predictive archaeological models in Hungary based on studies

involving the known Hungarian site register. These could mean extensive tools, already available at the initial

planning phase of the construction works, by which the preliminary protection of national sites can be secured.

Keywords: site, GIS, predictive modelling

The approach , where these decisions are taken

on the basis of (expert) knowledge of the known archaeological site sample,

is in our view an irresponsible approach to archaeological heritage management.

VERHAGEN2010, 438

When asking archaeologists to show us the location of their research, we are bound to

be shown a wealth of thrilling sites. Yet they will be in trouble when we ask them to show us

each and every one of them. This is due to the fact that no one knows the actual number of

archaeological sites in Hungary. This is not a theoretical problem,2 since the chance of

protecting sites we do not know the location of is next to none.3 Although almost all

archaeological research deals with sites, there is disproportionately little discourse on the

possibilities of identifying a register of sites. Nevertheless, without doubt such a huge amountis in question that it simply cannot be managed without a geographic information system

(GIS). Any archaeological data within the archaeological register of sites which lacks more

1 Hungarian National Museum Centre for National Cultural Heritage, Department of Topography;[email protected], [email protected] LXIV 11 and 7 (20) of 2001.3It is not possible to discuss the definition of archaeological sites here; we interpret the archaeological site asthe distinctive spatial location of the special collective of finds, archaeological features and ecological remains(RACZKY 2006), augmented by the fact that its expanse is defined by the surrounding area lacking of finds.

However, this does not answer a number of questions: e.g., when finds from several periods are unearthedtogether should they be regarded as one or more sites; or how many sites comprise, for example, the Romanperiod city town of Aquincum? We have already discussed the question briefly (REMNYI STIBRNYI2010).


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precise geographical data cannot be studied; it simply cannot be identified as a site. In the

following essay we will summarize the state of the Hungarian archaeological register of sites,

connecting GIS-based analyses, as well as those options which serve as a more protective

solution for the sites from such a viewpoint.

The known archaeological site register in Hungary

At first sight, the situation is promising. A unified and centralized data archive exists

where information about archaeological sites is collected. This is quite an outstanding feat

knowing the divided state of Hungarian archaeology. The official site register of the National

Office of Cultural Heritage (KH) can be regarded as a reliable base for the study of the siteregisters state as it contains the topographical data collected by the Archaeological

Topography of Hungary (MRT),4the archival databases of the majority of museums, as well

as archaeological excavational data conducted since 2001. Currently it contains more than

70 000 records, while the number of sites in Hungary is estimated to be about 100 000

(WOLLK2009). According to this, we already know 70% of the sites.

However, this is not true. First of all: we certainly do not know 70 000 sites. Sites can

only be considered known when they possess spatial data, that is, simply their geographical

location is known. The database of the KH was not contrived as a geographic information

system at the time of its compilation; thus, it contains a lot of site descriptions that do not

have, and indeed cannot have any geographical data. Only about two thirds of the given

information, 50 000 sites have some kind of geographical data added (whether they have an

extension or are only dot-like). Furthermore, only ca. 10% among these can be found within

city borders (this means 5.42% of the area of Hungary), which sheds light on its

disproportionate state caused by the fact that due to divisions usually the same site receives

different registry numbers according to the assigned plots of land. Fairly often a single site is

registered under several numbers. In all, we estimate the actually known number of sites to be

between 25 00030 000.5 As we can identify several periods and characteristics at the

majority of sites this number cannot be given unequivocally. Nevertheless, for the time being

let us be content with the current practice based on spatially defined units: site means a

location where archaeology is found surrounded by an area free from artefacts.

4

See below for further details.5In 2004 this number was 10 00012 000 (WOLLK2004, 76); however, this did not yet contain the geographicdata resulting from the Transdanubian research of the MRT (cf. WOLLK2004, 77, fig. 5).


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Many scholars have already extrapolated the number of sites on regions systematically

researched up till now to the whole area of the country (JANKOVICH-BSN AND NAGY2004;

WOLLK2004), which resulted in an estimate of 100.000150.000 sites within Hungary. This

implies ca. 11.5 sites to each square kilometre. This is feasible judging by the study of the

sites observable on the surface, which number is more or less supported by current research as

well. The staff of the KH and the Directorate of Somogy County Museums conducted

topographical research at 17 settlements of Inner Somogy between 20002004, where 517

sites were located in an area of 426 square kilometres (1.21 sites/km) (FEKETEet al. 2005).

Our field survey conducted in spring 2011 at Perkta and environs with an area of almost 160

km surveyed resulted in 220 sites (1.375 sites/km). These surveys, just as those conducted

by the MRT, certainly have not found all the sites of a given area, but we can state that they

have given significant results.

The 11.5 sites/km ratio is reasonable in comparison to European site registers as

well, although we meet rather different figures according to each region. In Poland 435 000

sites were located on a 270 000 km area (1.6 sites/km) (PRINKE 2009, 72); in Sweden

570 000 sites were identified on a 450 000 km area in 2009 (1.2 sites/km) (NORMAN -

SOHLENIUS2009, 83); the 20 000 km area of Slovenia yielded 26 000 sites (1.3 sites /km)

(DJURIet al. 2009, 90). Due to the variation in the data (e.g. site definitions) we must not

draw far-reaching conclusions from these figures, but the ratios are observable. Thus the 100

000150 000 sites estimated for the area of Hungary seems reasonable.

We should not omit from our calculations the fact that there are also archaeological

sites which are unidentifiable by mere field surveys. However, for the moment we do not

know of such an extensive survey which could significantly elucidate the question of the ratio

of these types of sites within the site register.

All in all, we think it is not the numbers which are important, but what results from

them; and based on these we know 2030% of the archaeological sites in Hungary, while ca.25% of the country has been systematically researched.6We feel this is a significant problem

from several aspects.

From an archaeological perspective, apart from academic relevance, this low figure

means that practically 70% of the site register is unprotected, as current legislation only

protects registered sites. In line with Act LXIV of 2001, protection primarily refers to

6

The MRT examined 11.7% of Hungary, researching ca. 10 000 sites, while there are a further two volumes andalmost 2 000 sites still in manuscript form (WOLLK2004, and for data from manuscripts Istvn Torma,personal communication).


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preventing the disturbance of the site and not its excavation. Archaeology is thus concerned

with constructions avoiding the sites, although due to its underfinanced state in the past few

years we seem to forget that our primary ethical and professional duty is not the excavation of

sites, but protecting them for the future.

From the viewpoint of constructions, this state is also problematic as the high

percentage of unknown sites does not allow for planning to avoid them. If such a large percent

of the sites is unknown, it is practically futile to ask for archaeological data during the course

of planning as there is only a little chance that it will be of any use. An average 70% of the

sites ideally only emerge during the compulsory field survey conducted because of the

authorization. During the planning phase of the Nabucco gas pipelines running along 384 km

through seven counties of Hungary 77 sites were already registered. After a single field

survey in 2010, this was modified to 339, but including the percentage of areas where the

survey could not be conducted we can estimate at least 400 sites altogether. This of course

means an unforeseen risk with regard to schedules and monetary matters for the construction

works, which can only be more precisely revealed ideally during authorization, less ideally

during construction itself.

Solution possibilities

1.

As we have already mentioned in the previous chapter, we regard current legislation,

which tries to carry out the protection of sites based solely on the rather small list of sites

known, very dangerous.

One possibility was outlined ahead of its time by the Archaeological Topography of

Hungary (MRT): to conduct intensive field surveys throughout the country. Under the

circumstances prevalent in Hungary, due to the extremely high number of cultivated land,

field surveys are the cheapest and easiest methods for identifying sites. By this procedure we

can gain reliable information in ploughed fields regarding how much they were affected by

archaeology. However, its drawbacks are that although the surface-collected finds are deeply

connected to the features hidden under the surface, their relationship does not always mean

they can be more precisely associated. The fact that a site exists at the spot can usually be

determined with certainty, but its precise extent cannot, grounded simply on surface features.

Furthermore, in certain areas and with certain types of sites this method cannot be employed.


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The early undertaking of the MRT started with a positivist approach in the 1960s,

growing into a progressive topographical workshop, but was eventually broken off by the end

of the 1990s; it had surveyed 11.7% of the area (WOLLK2004). We may regard this as the

basis. What we know from the site register was compiled for the most part by these studies. It

is enough to think of the fact that almost 12 000 sites from the total number of 25 00030 000

known sites were identified by the MRT (WOLLK 2004, and for data from manuscripts

Istvn Torma, pers. comm.).

Even though the numbers suggest so, the task is not impossible, yet it requires

significant resources. In Poland the National Archaeological Survey (Archeologiczne Zdjcia

Polski, AZP) organized the field survey of almost the whole of the country with a huge

amount of human and material resources involved. The end of the first phase (field survey) of

the project started in 1978 is to be expected in a few years time. By 2009 with the

involvement of 500 archaeologists more than 435 000 sites were identified in Poland (P RINKE

2009). In Sweden archaeologists have conducted field surveys twice so far in areas not

covered by forests, resulting in 600 000 sites; currently the archaeological survey of forested

areas is underway (NORMAN- SOHLENIUS2009).

For the moment, we do not see reality in any form for systematic topographical surveys,

similar to the abovementioned, to start in Hungary in the near future. This is partially due to

financial reasons; for archaeology in such an underfinanced state, it can only be conceived

with increased state engagement. A greater, more complex problem is the disinterest of the

archaeological profession on this matter. The reasons for this would deserve an essay of their

own, but we think its roots lead back to the fact that the archaeological revolution spreading

throughout Europe following the Malta Convention in 1992 has only partially reached

Hungary (BNFFY 2004). The profession regards the necessity of preliminary rescue

excavations as self-evident, but not that this would also entail the establishment of a Cultural

Resources Management (CRM) independent from academic research.7CRM, however, doesnot only cover archaeological companies and motorway excavations, but also implies a

change in approach that results from the complex task of protecting every archaeological

feature. Nevertheless, this raises different, not too scholarly questions in the academic sense

of the word.

2.

7For the definition of the phrase cf. K ING2004, 4.


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We can approach the solution to this problem from another angle as well: let us turn

the question around and try to anticipate where archaeological sites and features can be

expected. The method is based on model experiments that are employed by several sciences

from medicine to zoology, collectively called predictive models (ARC-WOFE 1998).

Fig. 1.: DEM of the Srrt-region at Fejr County. (SRTM 2006)

Archaeological predictive models try to predict the location of archaeological sites

or materials in a region, based either on a sample of that region or on fundamental notions

concerning human behaviour (VERHAGEN 2007,13). The majority of these are based on two

assumptions: on the one hand, the choice of the location of a human settlement was largely

influenced by certain characteristics of the natural environment. On the other hand, these

natural factors influencing settlement location appear at least indirectly on modern maps

(WARREN ASCH 2000, 6-7). Thus, human settlement is not random in the region and the

dispersion of sites found so far can be modelled along natural and cultural resultants. In such a

way the locations where sites may occur with more possibility or where this is less likely can

be filtered by geographic information and geostatistical analyses. This is quite a pragmatic

attitude and obviously comes from a CRM stance: if time and money are not sufficient for a


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Fig. 2.: Archaeological predictive model of Srrt-region in Fejr County (MESTERHZY 201175.)


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full-scale examination, but we definitely need to give an answer and fast, then we must be

aware of the possible solutions. In the past 3040 years that these models have been in use,

however, the methodology has outgrown the status of a simple aid. Today we use these data

to better understand and study connections between human activity and the natural

environment. Likewise, the spatial analyses prepared during the modelling are not only to be

interpreted as elements of the model, but as an additional benefit, so to speak, they can be

useful data on their own.

The effect of natural geography, thus, primarily watercourses, relief features and soil,

on human settlement has already been studied both ethnographically and geographically in the

first half of the 20th century; Zsigmond Btky and Istvn Gyrffy from an ethnographical

perspective (BTKY-GYRFFY-VISKI1941), and the geographer Tibor Mendl also researched

the topic (MENDL 1932). In terms of archaeological settlement structure, Istvn Mri was

among the first to emphasize the significance of proximity to water and the features of the

terrain (MRI1952), but this realization also led the directors of the field surveys conducted

by the MRT. The relationship of waters and settlements is an obvious fact for archaeologists

today. Hungarian archaeological research in the past 20 years has been primarily influenced

by environmental archaeology, a science closely connected to and parallelly developing with

predictive modelling. We can regard these results as the basis for predictive models.

Thus, in the following we will briefly summarize those Hungarian studies which we

find progressive from such a perspective and which can be useful for predictive modelling.

Archaeological GIS in Hungary

Among GIS systems used for archaeological purposes in Hungary we must first

mention those that categorize and systematize data collected during archaeological

excavations and display these spatially. The primary aim of these database-like systems based

on features and/or stratigraphical units is to store the wealth of data collected from

excavations with large surfaces, otherwise rather difficult to manage, according to unified

system requirements (WOLF 2002; EKE et al. 2007; TOLNAI 2009; HOLL PUSZTAI 2011).

Nonetheless, we will not go into detail regarding these processing methods and applications

within the scope of this essay even if they were one of the first steps taken in Hungarian GIS

research. Most of all for the reason that from the perspective of predictive models those

Hungarian works are more important that not only structurally organize and store data, but

have also prepared spatial studies and reconstructions, and among them those that have been


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spatially displayed, that is, they can be presented on a map. It has to be stressed, that

predictive archaeological modelling makes use of archaeological data on the level of and

above the site surface, thus we concentrated on these during the study.

From the viewpoint of a study relying on the predictive archaeological model that is

mostly based on environmental factors, it is of great importance to determine environmental

changes. A significant difference between predictive models and environmental

reconstructions is that the latter deal with a single level or coverage of the environment. As

will be seen later, they do contain predictions regarding favourable and non-favourable zones

of prospective archaeological site locations; however, this only refers to the given coverage.

On the other hand, the predictive archaeological model is a complex prediction based on

several environmental factors implemented by geographical information and geostatistical

analyses regarding the probable location of archaeological sites. Consequently, environmental

reconstructions can specify the model itself as the input data of the predictive model. It is

important to emphasize that this is only possible, if these input data meant for improvement

form databases with well-defined precision and spatial characteristics that can be managed by

geographical information systems and are not just textual statements. The following research

historical sketch serves to point out, amongst others, that: the knowledge necessary for the

predictive archaeological models (or geographical information coverages, if you will) is used

more and more in Hungarian archaeology; although collective and unified processing through

geographical information systems is still rarely to be seen (FEKETE2008; PADNYI-GULYS

2010; PADNYI-GULYS2011; MESTERHZY 2011).

It is easy to see that during the reconstruction of any archaeological period, all the

changes in the region and the environment that happened after the period under examination,

or after 17118at the latest, are mostly negligible from an archaeological point of view. Thus,

one of the important sources and starting points for environmental reconstructions is the

information to be found on modern maps. One of the most significant roles of thesecontemporary representations is to unravel the land formation effects of the river regulation

and swamp reclamation works that had commenced in the 19 th century; but it also offers

valuable data on topography and vegetation. The changes that came about in the natural

landscape, and thus in the environment of the archaeological sites as well, can be sufficiently

demonstrated by the three military surveys (ARCANUM 2004, ARCANUM 2006a, ARCANUM

8Act LXIV 19 of 2001.


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2007) and other, county (ARCANUM 2009) or various local (ARCANUM 2006b, ARCANUM

2006c) maps referring to the area of research.

Most examples apply to the adjustment of hydrographic data and the refinement of

contemporary circumstances. This already goes to show that water, whether still or flowing, is

one of the most important factors in human settlement, either from a positive or negative

aspect. Since it not only attracts settlements, but it also repels them if we think of swampy

regions and floods. The opportunity presents itself to reconstruct the configurations of the

terrain prior to river regulations directly next to the site and to trace back the waterlogged

areas on them (RACZKY et al. 1997, 170; SZAB et al.1997a, 81; SZAB et al. 1997b, 87;

FISCHL 2006, 12). In the case of larger, microregional studies, however, it is necessary to

employ geological data as well (RACZKYet al. 2002; GYUCHA DUFFY2008; FZESI2009).

Logic in such cases is the opposite contrary to old maps, as the direction of approaching

prehistoric circumstances is not from the top but from below, through the changes

occurring in the Pleistocene and Holocene epochs determined by geological methods. For the

moment only along shorter lengths, but it is proven that the location of archaeological sites is

also suitable for the delineation of old river-beds and flood plains (GYUCHA DUFFY2008,

20; FZESI 2009, 382) at areas where the beds are known to change frequently; this is

characteristic of wide glacial valleys such as those at the lower section of the Saj and Hernd

rivers. These data also result in the refinement of geological data.

Usage of old maps, however, is often not sufficient anymore. Despite the given

sources varying according to each area, they provide reliable information only until the

17th18th centuries. Thus, the other significant sources of environmental reconstructions are

the results of various scientific analyses that are less defined by periods.

Environmental archaeological research based on general samples spreading across

large expanses are also known in Hungary (GL et al. 2005; ZATYK et al. 2007); the

complex geomorphological, sedimentological, radiocarbon, palaeo- and macrobotanical, andmalacological analyses serve the better understanding of the related settlement history

overviews.

The studies of Pl Smegi cannot be left out from our survey, who is an authoritative

figure within the field of Hungarian environmental archaeological research (an incomplete list

of examples: KERTSZ SMEGI 1999; RACZKY et al. 2002, 840-842; SMEGI et al. 2003;

SMEGI MOLNR 2004; SMEGI 2009). For our survey the spatially displayed, more

accurate periodic hydrographic models are the most relevant (SMEGI2007, 379-382; SMEGIet al. 2007, 250-251).


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A significant result of soil boring conducted directly in the vicinity of archaeological

sites is precisely the more accurate delineation of the contemporary relief of an area. The

results of the drills conducted usually along a 10x10 square grid can be utilized when

deducted from the height values of the current relief model (VARGA 2000, 75; SALISBURY

2008, 53). However, the problem with this method is that on a vast territory this also

culminates in significant expenses in the budget.

During the research conducted at Kelemr-Mohosvr, the access of the castle and the

direction the finds were washed down could be determined by calculating the gradient

categories (PUSZTAI2007b, 56-57). Likewise, visibility could be studied by the reconstruction

of a digital elevation model and the height of the tower (PUSZTAI2005, 419), which made it

possible to define the microenvironment of the castle and the exact locations of the nearby

settlements connected to the castle.

Two studies have to be mentioned at the end of our overview. It can be considered a

great progress that a hydrographic reconstruction supported by remote sensing data was made

in the flat terrain of the Great Hungarian Plain (TMR2004). At areas where the half metre

sea level differences on even the best contemporary Unified National Mapping System

(EOTR) maps practically appear as flat surfaces on a relief model, much more advantageous

possibilities arise with the processing of remote sensing images, which means the redrawing

of river-beds that appear on them in the case of a hydrographic reconstruction. Its drawback,

however, is that in exchange for the exact spatial data one must conduct chronological

examinations at the given area.

One of the most important elements of the research conducted at Ecsegfalva besides

the hydrographic reconstruction was the mapping of vegetation data resulting from the

environmental reconstruction. Thus, visibility studies conducted on plain and vegetation-

covered surfaces present varying prospects (GILLINGS 2007, 39-42). Likewise, a visibility

study conducted from a single given location, which already considers lengths withindistances still seen by the unaided eye (GILLINGS2007, 44-46), can be very useful in studies

regarding relationships between the individual settlements.

The creation of predictive archaeological models in Hungary is still in the making.

Until now two essays have been published: one of research conducted in Somogy County

(FEKETE2008, 147-156) and one in the area of the Zsmbk Basin (PADNYI-GULYS2010,

1-6); while a further data collection is known from Borsod-Abaj-Zempln County (F ISCHL

2008). So far, two predictive models have been prepared at the professional workshop of theCentre for National Cultural Heritage of the Hungarian National Museum. These are shortly


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to be published in detail, where one deals with the results of modelling conducted at Srrt

(MESTERHZY 2011) and the other at the Srvz Basin (PADNYI-GULYS 2011). We must

also mention the predictive model made in connection with Kelemr-Mohosvr, which

defined the location of the medieval village of Fancsal based on visibility and exposure;

unfortunately, a field survey has not been carried out thus far to verify the hypothesis

(PUSZTAI2007, 63).

Predictive models: history of research

P. Verhagen attributes the research historical basis of modelling to the settlement

network analyses of New Archaeology (Verhagen 2007, 14). Its background is built up of thearchaeological interpretation of the geographical location theory and the site catchment

analysis developed from the latter (CHISHOLM 1962). At the end of the 1960s these

theoretical approaches received a quantitative background for employment in the period of

processual archaeology; while by the end of the 1970s two volumes discussing

archaeological spatial analysis were born (HODDER ORTON1976; CLARKE1977). After this,

the theoretical background of the predictive model in archaeology was practically ready.

The first predictive models were prepared in the USA. According to the NationalHistoric Preservation Act, approved by the Federal Government in 1966, archaeological sites

were not renewable resources and were thus values to be protected. Since, however, this

referred to the heritage protection of such vast expanses where field surveys could not be

conducted, there was a lot of pressure on the departments involved to find a solution. This

resulted in the establishment of the first data-driven predictive models (MEHRER WESCOTT

2004, 6-9). These were prepared in large numbers after the second half of the 1970s. The

basis of preparing the American-type predictive model was widely published (KOHLER

PARKER 1986; JUDGE SEBASTIAN 1988); later on easy-to-use tools were also compiled for

the modelling (WESCOTT BRANDON 2000).

Predictive models actually received their working base with the creation of GIS, which

was necessary for their applicability. It was equally difficult to explain the theory of statistical

employment and to introduce the results; the possibility of spatial representation was a huge

leap either way. In the 1990s, the rapid development of GIS occurred parallel to the

spreading of the postprocessual approach within archaeology. Most scientific criticism aimed

at predictive models, according to P. Verhagen, actually stems from the processual


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postprocessual contrast, where the quantitative approach overly simplifies the requirements of

habitation (VERHAGEN 2007, 16).

From this time on the opinions on predictive models became somewhat divided. Its

professional reception was quite low, with continuous criticism as the basis of the analyses

was not sufficiently supported by scientific evidence. At the same time, it was a readily

usable, practical tool for CRM in order to draw the attention of decision makers to the actual

number of archaeological risks at hand. The archaeological agencies of the USA and Canada

use it as an everyday tool in administrative and planning tasks even today.

In Europe we can reckon with the large demand of heritage protection tasks previously

unaccounted for starting from the Malta Convention in 1992, which resulted in the creation of

CRM. The first predictive models were prepared in connection with this, which had the most

impact on the archaeology of the Netherlands. The Netherlands uses the only nationwide

model that was created in 1997 (Indicatieve Kaart van Archeologische Waarden IKAW)

that is continuously developed through a wide scientific cooperation (VERHAGEN2007): they

are now using a third generation model for public administration today.

The structure and methodological background of predictive

models

The comprehensive collection and handling of data at motorway excavations

involving vast areas could only be managed with the help of geographic information systems,

which meant a significant and partially constrained shift of paradigm compared to the

previous small surface excavations. Precisely such a leap in scale can be observed in field

survey site locations, as the surface data of large areas can only be handled and employed by

geographic information databases. Just as in the case of the geographic informational

background of excavations, the most exact spatial location of surface finds and sites also

obtains a significant role. As we have already mentioned above, we have located about 20

30% of Hungarian archaeological sites in the past 50 years. The accuracy of these data is to be

questioned, moreover, simply because the surveys were by necessity usually conducted on a

rough estimate without the help of geodesic tools (GPS).

With field surveys only even if the systematic studies discontinued since the past 15

years would advance more rapidly a long time would elapse until the majority of


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archaeological sites could be identified and protected. Predictive modelling in contrast offers

an alternative that can draw an exact, reliable and approximate picture of the archaeologically

concerned areas of Hungary.

During predictive modelling, the spatial location probability of new, thus far unknown

sites can be determined in a given region by considering the environmental characteristics of

the archaeological sites (human settlement) already known. Today this process is usually

defined by statistical methods. However, we need to briefly review the techniques employed

during modelling before outlining the environmental factors, as various new methods have

appeared following almost 30 years of development.

A significant difference in the case of predictive models is whether the known

archaeological data are to be used or not. This helps in separating the inductive models

employing archaeological data and the deductive models that do not. Due to lack of space we

cannot compare the positive and negative aspects of the two model types, but we can state that

here in Hungary the inductive models have more possibilities, thus we will be dealing with

these in the following.

The most important characteristic of the initial model types with dichotomous

variables (Boolean overlay, weighted binary addition) was that the modelling specialist could

determine which environmental conditions, in which zone would predict the location of

unknown archaeological sites (EJSTRUD2003, 128-129). Nowadays, the base of modelling is

placed on modern methods of mathematics, such as the Bayesian probability theory, the

Dempster-Shafer theory based on the latter, the Weights of Evidence, and fuzzy logics (for an

overview of their archaeological use cf. EJSTRUD 2003; NYKNEN SALMIRINNE 2007).

During their use, when choosing the environmental factors a mathematical (function) relation

is determined between the location of the known archaeological sites and the environmental

factors; thus the indicators not showing significant relations can be filtered out before the

modelling itself. On the other hand, accurate probability rates and reliability values can bedetermined by these methods, which are important for measuring the stages of models.

The most variation between models appears in the choice of environmental factors.

There is no prescription for these choices; the variations in natural geography regarding each

studied area call for different processing methods and data. As it was seen earlier, these

environmental factors are not unknown in Hungarian research either. Therefore, in the

following we will summarize the characteristic environmental factors employed and the

geographical information to be derived from these.


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One of the basic requirements for human settlement is the proximity of water, whether

still or flowing. As we have already stated above, an archaeologically accurate hydrographic

map can be obtained if we do not consider hydrographic changes following the archaeological

periods; and furthermore, incorporate dry watercourses into our database. There are three

methods to outline it. Firstly, each change can be defined with the help of old maps; however,

this is lengthy and costly work with large areas involved. Secondly, the opportunity arises to

generate outflow models based on the (improved) relief model (TELBISZ 2007). Thirdly,

experience (MESTERHZY2011; PADNYI-GULYS2011) shows that the layers of geographic

maps related to flowing and still waters can also give a good point of departure. The distance

from water or flooded areas can be employed as coverage for geographic information, which

can be defined generating zones; in our experience the depth of ground water levels can also

be an important factor.

Geographical and pedological data can be employed as well; and not just in predicting

the flooded areas already mentioned. It is absolutely necessary to simplify these data, and to

merge their categories, for example according to characteristic rock-forming minerals, to

enable them to be authoritative information resources that can be managed by statistical

analyses. The special role of geographical data is the identification of temporary, former

watercourses, as we have already discussed in detail.

Digital elevation models (DEM) are available either free (SRTM, ASTER GDEM), or

can be bought (the products of The Institute of Geodesy, Cartography and Remote Sensing

and the MoD Mapping Non-Profit Ltd in Hungary). They fundamentally influence the

achievement of predictive models. This is caused by the fact that on the one hand, the freely

available elevation models (DEM) are actually digital surface models (DSM). That is, the

DSMs produced by remote sensing methods contain not only the relief features of the terrain,

but also incorporate all the features, buildings, vegetation and their height values are also

added to the heights of the relief map. Nevertheless, whichever elevation model will be usedits precision measurements and resolution must be well considered, as it gives the lower end

of the scale of the modelling as well. Usually three coverages from the relief data can be built

into the predictive archaeological model: exposure, gradient categories and individual surface

forms; but several other modes of application are also possible.

The choice of environmental factors and their categorization requires varying values

whether in flat, hilly or mountainous areas. Thus, such near homogenous units need to be

found in an area where the coverages do not have extreme values. The Cadastre of theMicroregions of Hungary (MKK 2010) offers precisely such delimitations for the whole of


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Hungary, and provides the scale of modelling too for microregions usually 100500 km2that

have a sufficient number of sites for the building of a substantial model (STIBRNYI 2010,

352).

The end-product of modelling is a raster image file where fixed probability and

reliability values are determined for its basic construction units: the pixels. These values can

be categorized and result in a clear, colour-coded map, where three or four zones can be

identified to indicate the very low, low, middle, and high archaeologically significant areas.

Yet, it is important to emphasize that the actual site expansion cannot be read from such

maps, only the probability values showing the probability of the location of archaeological

sites.

Concerns about predictive models

Archaeological predictive modelling has divided the international archaeological

community since its beginnings, stirring up heated debate within scientific circles. The main

objections have been summarized by P. Verhagen in the following four points (V ERHAGEN

2007, 17):

1) use of incomplete archaeological datasets;2) the biased selection of environmental parameters, often governed by the

availability of cheap datasets such as DEM;

3) as a consequence, a neglect for the influence of cultural factors, both in thechoice of environmental parameters, as well as in the archaeological dataset;

4) and lastly, a neglect of the changing nature of the landscape

The archaeological database currently available and the archaeological site register in

it, as we have already mentioned, is far from complete. Nonetheless, this idea would hold true

for the comprehensive processing of any archaeological object or feature type; while the goal

of modelling is non other than to serve data for these unplumbed areas of archaeology.

The accuracy of inductive models is defined by the accuracy of the worst resolution

coverage. One of the primary viewpoints of selecting environmental factors besides the

quality of data is that the piece of information should be available in digital format or able tobe digitalized. The incentives behind it are naturally to cut expenditures, on the one hand; and


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as we have mentioned with regard to environmental archaeology above, on the other hand, the

textually formatted environmental reconstructions are difficult to form into geographic

informational data and thus incorporate a significant amount of uncertainty.

One method of defining cultural effects, and culturally specific characteristics of a

given period or culture is precisely predictive modelling, inasmuch as we can consider the

differences between the models building on periods when creating a complex model.

There are a growing number of methods to define natural changes in the landscape.

The elimination of the effects of erosion (CENTERI2001, 12-14), the definitions of the change

in vegetation (BR2006; BRet al. 2010) and vertical surface movements (PAPPet al. 2005)

are all steps towards achieving this. Yet we must realize that however much these researches

help in making the image of the natural environment more accurate in a given period, they

will not be complete or we cannot be sure about their completeness, just as we cannot know

all the archaeological sites in Hungary. Of course, this does not mean we should not strive to

achieve it.

Applying predictive archaeological models in Hungarian

CRM

Archaeological studies also regularly make use of models specific to periods or

predicting features (e.g. GRAVES 2011). Academic research, however, is rarely interested in

every feature, much rather the individual feature types or cultures are focused on.

Nevertheless, the models are primarily connected to CRM, already in connection with their

creation, usage and development. They are suitable for producing reliable predictions on

relatively large, archaeologically less known areas. This should not be confused with site

predictions because, as we have mentioned, the models do not tell us where the sites are, butwhere they are highly likely to be located.

During the planning phase of investments it is equally important for both the

archaeologist and the investor to avoid archaeological sites. Naturally, from the investors

point of view this is only a single phase of the whole planning but archaeology can only be of

use in this respect if the construction is planned on a known archaeological site. Due to the

low level of known sites, the risks of heritage protection are like time-bombs to all

construction works, which after detonation causes damage to the investor, the site, and thesocial status of archaeology as well. A good predictive model can minimize this risk by


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offering an overlay that indicates this to the investor or planner. This can be regarded as just

another overlay among the overlays of risks to be considered, but as the most important

characteristic: it can be anticipated and can give quantifiable predictions.

The employment of models can thus be pivotal, on one hand during the planning phase

of investments as, if other terms permit it, the constructions can simply be re-planned to an

area of lower risk in the knowledge of the predictable risks. This has a further advantage in

real estate developments: predictions can be made without the investors disclosing

information about the location of the planning, which is often handled as an anxiously

protected trade secret in the initial phase. Currently, if an investor was to call on an

archaeologist to ask for advice on such matters, he or she would not be able to help without

the knowledge of the exact location. In the case, however, when a predictive model would be

available for the area chosen (microregion), then the basic heritage risks can be clarified

without knowing the actual (lot number of the) location.

The model may help prior to construction as well, calling attention to the areas where

for various reasons no sites have been identified but these can be expected (e.g. at

motorways). Calculating with such areas, the amount of time and expenses needed for the

archaeological excavation can be estimated more precisely. The model can also be of

immense use for the archaeological tasks during construction, pointing out those regions

where archaeological monitoring should be more active and earthworks more careful as we

can expect to find unforeseeable archaeological features.

The model offers further assistance during everyday heritage protection. Whilst the

field surveys compulsory for the heritage protection of large-scale investments signify a

considerable amount of security in the case of unknown sites, this is not mandatory with other

investments; thus, unknown sites are practically not protected at all under these

circumstances. When the archaeological inspector does not have sufficient data to specify any

type of preliminary measures, the regional museum authorized to conduct excavations canonly acquire information about unexpectedly appearing sites by chance. However, should

there be a predictive model available of the area in question, then the archaeological inspector

can use this data for constructions planned in zones of high predictability to at least prescribe

monitoring, which can already assure archaeological presence and protection. Incidentally,

this is also granted by law to enable the protection of areas archaeologically affected. Models

are such an important part of administrative procedures in heritage protection in the

Netherlands that excavations have to be conducted at locations of high probability prior toconstructions even when no actual site is known there.


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Interestingly enough, Hungarian legislative regulation is familiar with the category of

highly probable areas defined in predictive models, which was added to Act LXIV in 2001 as

an influence of the Dutch example: this is the category of area of archaeological concern

(Katalin Wollk, pers. comm.). According to this all areas at which archaeological sites

can be predicted are to be regarded as areas of archaeological concern.9The employment of

the model could fill this phrase with meaning, defining exactly which areas count as

archaeologically concerned and on what grounds.

Although the models can and should be continuously developed it would be nave to expect

the model to be infallible. Nevertheless, even the worst model offers more protection for

unknown sites than the present practise. Moreover, its values can even be set to be less precise

but more accurate (WHITLEY 2004, 238). That means that the high probability zone will

appear on a larger scale at the surveyed area, but the majority of the sites will be included

within it. Hidden sites pose as major problems for heritage protection. These are features

that cannot be observed through surface surveys either because they cannot be found by field

surveying methods (e.g. row cemeteries), or because they are covered (by forests, pastures,

architecture, etc.). Prior to earthworks, the identification of site remains on such areas is

usually very expensive, but the model draws attention to the risks affecting these locations as

well.

Possible considerations of modelling

The Hungarian microregional system could be a good base for the implementation of

models. As mentioned above, these microregions form an excellent possibility for

delimitation in connection with creating models for the description of homogeneity. We

estimate that the 230 microregions would fit into more or less 20-30 separate models. Each

model is exact inasmuch as the data entered are, but our experience shows that archaeological

data is the least accurate of these (MESTERHZY 2011;PADNYI-GULYS 2011). Thus, each

modelling period should be preceded by a field survey during which 20-30% of the area is

thoroughly surveyed, where each feature observable on the surface is identified by GPS. This

base, including the archaeological excavations conducted earlier on the site, can be

extrapolated later on. As referred to above, we have prepared the experimental models of two

microregions so far. Based on our experience, one microregional model can be prepared in

9Act LXIV 7 of 2001 (17) about the protection of cultural heritage.


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about a month involving 8 people (including field surveys and monitoring). Models can (and

should) be continuously improved with the development of both the input data and the know-

how, and will be increasingly more accurate by channelling the results of development in

remote sensing (LiDAR, hyperspectral images). This, however, requires a base that can be

developed.

The tools of archaeology are developing at an increasing speed providing more and

more possibilities; while putting more responsibility on archaeologists shoulders to protect

archaeological heritage with all methods available. Predictive models form a cost-effective

and highly accurate, continuously developing part of these tools.

The application of predictive archaeological models and the field surveys are not two

opposite methods, both can be organically integrated into each other. In any systematic field

survey we are to conduct, we must always consider those areas where perception is not

possible. Models can predict the heritage risks concerning these areas, moreover, any further

archaeological examination will strengthen the precision of the model. We are convinced that

in the current situation of Hungarian archaeology predictive models offer such a possibility

for heritage protection, which enables responsible safeguarding that can be continuously

developed.

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