GIS-based variability of building materials towards the Ile-de-France

cuesta (Paris Basin, France): inventory, distribution, uses and

relationship with the environment

A. TURMEL1*, G. FRONTEAU1, L. CHALUMEAU1, J. -P. DEROIN1, S. EYSSAUTIER-

CHUINE1, C. THOMACHOT-SCHNEIDER1, T. DE KOCK2, V. CNUDDE2 & V. BARBIN1

1Groupe d’Etude des Geomateriaux et Environnement Naturels, Anthropiques et

Archeologiques (GEGENAA), EA3795,University of Reims Champagne-Ardenne,

CREA, 2 Esplanade Roland Garros, F-51100 Reims, France2Department of Geology and Soil Science (UGCT), Ghent University,

Krijgslaan 281/S8, B-9000, Ghent, Belgium

*Corresponding author (e-mail: aurelie.turmel@univ-reims.fr)

Abstract: The Pays remois in the eastern Paris Basin is an administrative area of 1394 km2; in thesurroundings of Reims (France). Two main geological substrata are separated by the Ile-de-Francecuesta: the Tertiary substratum in the western part is composed of various types of geomaterials(clay, sandstone, limestone, burrstone), whereas the substratum in the eastern part is composedonly of Cretaceous Chalk. A field survey in each commune of the Pays remois identified 26 buildingmaterials documented in a Geographic Information System database (GIS-database) that includesinformation about them (lithology, petrographical and petrophysical data, weathering) and the cor-responding buildings (e.g. town, georeferenced data, building type, position on the facade). Thespatial analysis of the building materials’ distribution (Standard Deviational Ellipse) with GISidentifies their uses and the criteria established for the selection of the materials: availability, effi-ciency, workability and durability. Some lithologies were preferred for particular buildings orselected for their efficiency in specific positions. The study also defines the relation between thestones’ origin (local and non-local stones) and their application. This database is useful to establishstone replacement strategies in the Pays remois.

The study of building materials links culturalheritage to the environment and socio-economichistory, which reveals the territorial cohesion. Thisconnection may be observed through buildingmaterials’ distribution and uses, and thanks tothe conservation of local traditional buildings.Understanding these relationships constitutes aninterdisciplinary approach combining geology/engineering, geomorphology (Pope et al. 2002),economy, history and art conservation. Each disci-pline has its own methodology and combining allthese disciplines is a challenge. In geology/engin-eering, the petrography of building materials isstudied and tests are applied to building materialssuch as petrophysical experiments or salt crystalli-zation (Moropoulou et al. 2007; Hyslop & Albornoz-Parra 2009; Prikryl & Torok 2010). In geomorphol-ogy, landforms and human structures are studiedand the spatial distribution of weathering processesare assessed (Pope et al. 2002; Andre et al. 2014).According to Pope et al. (2002), art conservationworks on the aesthetic appreciation and chemical

analysis of the materials. The built heritage in a giventerritory is also studied with reference to economyand history through bibliographies and old archives(Frangipane 2010). In the past decade, GeographicInformation System databases (GIS-databases) andstone databases were recognized to be useful forinterdisciplinary approaches to establish territorialcohesion models (Cassar 2004; Kampfova &Prikryl 2010; Maio et al. 2013; Oikonomopoulouet al. 2013). Such GIS-databases are used to studyspatial distributions of materials or weatheringforms (Inkpen et al. 2001; El-Gohary 2010). In thisstudy, the research goal was to identify and charac-terize building materials, their uses and their distri-bution throughout the Pays remois. The establishedGIS-database was elaborated and includes petro-graphic descriptions and percentages of obser-vations for each building material in the differentbuildings in every commune. Distribution tools wereused from sociology, econometrics or biology tocharacterize the spatial patterns of the building mate-rials in the Pays remois (Chen 2014; Cidell 2014;

From: Prikryl, R., Torok, A., Gomez-Heras, M., Miskovsky K. & Theodoridou, M. (eds) Sustainable Use ofTraditional Geomaterials in Construction Practice. Geological Society, London, Special Publications, 416,http://dx.doi.org/10.1144/SP416.16# 2015 The Author(s). Published by The Geological Society of London. All rights reserved.For permissions: http://www.geolsoc.org.uk/permissions. Publishing disclaimer: www.geolsoc.org.uk/pub_ethics

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Villagra et al. 2014). The GIS-database is used tounderstand the relationship between building mate-rials and the environment and to propose a view ofthe local area that can guide restoration workaccording to aesthetic or petrophysical properties.

State of the art: spatial analysis in building

conservation

The different disciplines to study building materialsthat were reviewed by Pope et al. (2002) are essen-tial to the preservation and conservation of thesematerials and cultural heritage. For decades, thisinformation was gathered in databases. In 2000,De’Gennaro et al. described stones used in theancient city of Naples. This first approach combinedprevious art history data with petrographical orengineering viewpoints. As a result, they describedthe usage patterns throughout an area and in time.Very early, Inkpen et al. (2001) noted the utilityof GIS to produce decay maps that integrate weath-ering scales. Later, Dreesen & Dusar (2004) helpedwith a stone database that described the petrographyand highlighted micro-regions of natural buildingstones in the province of Limburg (Belgium).Another study was established by Cassar (2004) torelate the properties of Malta’s building stoneswith their original quarry. These publications werethe beginning of the common use of GIS and data-bases to link these different disciplines.

Since then, studies on this issue have multiplied.GIS was applied at different scales, such as acountry (Accardo et al. 2003; Hyslop et al. 2010;Kampfova & Prikryl 2010), a region (Martinez-Torres 2007; Revenu 2008; Frangipane 2010;Buttner 2011), a city (Hyslop & Albornoz-Parra2009; Gomez-Heras et al. 2010) or a few facades(El-Gohary 2010; Delegou et al. 2013; Oikonomo-poulou et al. 2013).

This approach took into account a large amountof data types: lithology, weathering, petrophysicalproperties, quarries, buildings, etc. Considering tra-ditional buildings or major cultural heritage, GIS-databases were used to quantify weathering gradesor connect stone alteration morphologies to envi-ronmental or geographical parameters (Inkpenet al. 2001; Accardo et al. 2003; Andre et al.2008, 2014). Other applications were related tothese GIS-databases. For most of these databases,the provenance and spatial distributions of usagewere investigated throughout a country or region(De’Gennaro et al. 2000; Dreesen & Dusar 2004;Martinez-Torres 2007; Hyslop et al. 2010; Kamp-fova & Prikryl 2010; Siegesmund et al. 2010) oron facades (Revenu 2008; El-Gohary 2010; Delegouet al. 2013). However, materials in traditionalbuildings vary according to technical properties

(Prikryl & Torok 2010), availability of localresources, chronological influences, and economicor aesthetic choices. The ‘historical environment’(Gomez-Heras et al. 2010) and the local story ofeach town, house cluster and facade led to modi-fications in the stone compositions in a specificwall (De’Gennaro et al. 2000; Frangipane 2010;Delegou et al. 2013). The spatial analysis of vari-ous parameters provides a quantified evaluationof the territory, which helps to plan documentsand define protected areas (Accardo et al. 2003;Frangipane 2010; Hyslop et al. 2010; Kampfova& Prikryl 2010).

Despite the increasing numbers of GIS-data-bases, very few presented quantified data (Accardoet al. 2003; El-Gohary 2010) and spatial pattern ana-lyses. Cultural heritage or environmental buildingstudies could learn from others. Neves et al. (2012)developed maps predicting seismic vulnerability.Maio et al. (2013) produced landscape reconstruc-tion models with topography, ancient cartogra-phies, and temporal and spatial features. Blachowski(2014) conducted spatial analysis with miningresources and transport density maps in Poland.The most interesting was a publication from Villa-gra et al. (2014) that used easy spatial indexes (Stan-dard Deviational Ellipse) to study the adaptivecapacity of cities in the aftermath of an earthquake.

The study area: Pays remois

The Pays remois is located in the northeastern partof the Paris Basin, centred on the city of Reims. Itcontains 137 French communes (including cities,towns and villages) with a total surface area of1394 km2;. This administrative area was created in2007 by the Syndical committee SIEPRUR (localauthority and joint board of studies and programmesin the urban region of Reims) to provide an econ-omic, cultural and patrimonial cooperation structurefor all the communes.

Historical events

The Pays remois experienced various historicalchanges. During the Gallo-Roman period, Reimswas named Durocortorum and became Belgium’scapital. During medieval times, Reims becamethe Episcopal city where the French kings werecrowned. The Champagne area remains a rich pro-vince with numerous trade fairs due to its leadershipin sheet-making and its position at the intersec-tion of Flemish and Italian influences. Most ofthe Reims countryside was overturned by the FirstWorld War, which completely destroyed 60% ofReims’ buildings (Cochet 1989) and some villagesin the surroundings.

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Geographical setting

The face of the Ile-de-France cuesta is located in themiddle of the Pays remois (Fig. 1). To the west, theplateaus in the cuesta (Massif de Saint-Thierry,Montagne de Reims and Ardre Valley) are occupiedmainly by forest but are also cultivated with cerealcrops and vines. To the east, the chalky plain ismainly cultivated. The reliefs in this plain indicatemonadnocks sharing the same geological for-mations as the cuesta (Mont de Brimont, Mont deBerru and Mont de Champagne). The cuesta isabraded by the Vesle and Ardre Rivers and theplain by the Suippe River to the east of the Paysremois. The Tardenois corresponds to a micro-region in the east that encompasses the ArdreValley and surrounding plateaus.

Geological setting

The Pays remois is located along the western bound-ary of the chalky Champagne, which belongs to theUpper Cretaceous in the Paris Basin. The areasclosely surrounding the city of Reims and towardsthe NE and east lie on chalk, which does not haveflint, and its weathered products. To the west andSW, the geological succession is largely more diver-sified and consists of a stacking of Tertiary hori-zontal or slightly monoclinal formations (Fig. 2):sands and sandstones (Thanetian Stage), sandyclays with lignite (Lower Ypresian Stage), glauconi-tic sands (Upper Ypresian Stage), and limestonesand marls (Lutetian Stage). The Montagne deReims is crowned to the south not by marine Lute-tian limestones, which are generally missing dueto the palaeogeographical context, but by continen-tal limestones and clays (Bartonian Stages) and theArgiles a Meulieres Formation (Rupelian Stage),which contains clays and a large irregular mass ofburrstones (Guerin 1990). To the east and north, asuccession of small residual hills (Mont de Berru)and outliers (Mont de Brimont, Mont de Cham-pagne) provide some outcrops of siliceous Tertiaryformations, which sit on top of the CretaceousChalk. The Reims area is characterized by two mainfeatures: the lack of strong building materials andthe partition between the chalky countryside to theeast and the Tertiary hills, plateaus and valleys tothe west.

Before the nineteenth century, the buildingstones and geomaterials used in construction in theReims area mainly came from surrounding Frenchdepartments to a maximum distance of 50 km (Fron-teau et al. 2014). After 1850, building stones fromAisne (Colligis, Vendresse), Oise (Saint-Maximin)and Meuse (Savonnieres, Euville) became promi-nent because of the synchronous opening of acanal and railway line.

Thus, the Pays remois is a region that integratesmany historical events and various geographical orgeological contexts that may have induced differentusage of building materials within the area (Devoset al. 2010; Fronteau et al. 2010a).

The GIS-database

The GIS-database was established with obser-vations of each building material employed on abuilding facade. The fieldwork consisted of asurvey of at least three facades per commune withvisual determination of the materials by macro-scopic observations using magnifying glass orfurther sampling for laboratory determination. Thenumber of observations increased with the size ofthe commune (e.g. 30 observations in Reims).Where possible, the church was the first buildingobserved and traditional houses or farm buildingswere favoured instead of contemporary construc-tions. This information was gathered in a georefer-enced database named ‘survey information’. Besidesthis, a second database was created, collecting thepetrographical information and physical propertiesof the observed building materials: e.g. total poros-ity, water uptake, mercury porosimetry and X-raymicro-computed tomography (Cnudde & Boone2013; Turmel et al. 2014). This way, two types ofdatabases were created (Fig. 3). Every materialwas identified by a code, allowing connection ofthe two databases (Fig. 3). Only the results fromthe first database are presented in this article.

The survey database used georeferenced datafrom BD TOPOw and GEOFLAw IGN#, a publicFrench database produced by the National Instituteof Geographic and Forest Information (IGN) thatcollects all information and boundaries data of com-munes. The percentage of each building stone wascalculated for each position on the facade, buildingtype and commune. As mentioned above, the mainbuilding types recognized were churches, housesand farm buildings. Categories referring to the pos-ition in the building included basements, elevation,windows and door frames, quoins and buttresses.

Spatial statistical analysis was established withthe GIS-database to understand where each stonewas employed the most frequently for an accuratepurpose on facades (Martinez-Torres 2007). Thespatial analysis was performed with the ArcGISw

software (ESRI#). The spatial distribution of a geo-material defined its distribution throughout the Paysremois.

Choropleth maps

Choropleth maps represented the percentage of geo-material in every commune and showed its spatial

GIS-BASED VARIABILITY OF BUILDING STONES

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Fig. 1. Location of the study area with the two main regions: the chalky plain and the Ile-de-France cuesta.

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distribution. Geographic distribution tools (meancentre, median centre and Standard DeviationalEllipse) were used to obtain a comparable value ofthe spatial distribution of every geomaterial (Fig. 4).

Standard Deviational Ellipse

The Standard Deviational Ellipse (SDE) representsthe standard deviation of the x and y coordinates ofa percentage of a specific building material (Mitch-ell 2005; Villagra et al. 2014):

SDEx =

�����������������∑ni=1 (xi − X)

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SDEy =

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where xi and yi are the coordinates for feature i,(X, Y) representing the mean centre for a featureand n is the total number of features. The calculatedstandard distance has two directions that define the xand y axes (long and short axes, respectively) of theSDE. The orientation represents the rotation of thelong axis of the ellipse. The distribution trend isshown by an elongated shape and a specific orien-tation. In this study, the standard deviation encom-passed 68% of the input feature centroids.

The SDEs for every stone were overlaid, andintersection tools distinguished the main areas ofvarious building materials that were studied.

Durability map

A durability value from 1 to 5 was attributed to eachmaterial according to observations of alterations on

the field survey. A value of 1 represents weak dura-bility from weathering and a value of 5 indicateshigh durability.

A weighted average was calculated for everycommune from the durability value multiplied bythe percentage of each material. Thus, a mean dura-bility (unitless value) was obtained and mapped as achoropleth map of the durability. The unitless valuewas classified into three categories: high, moderateand low.

Results

The building-stone database

The GIS-database indexed three main groups ofthe 26 identified building materials: local stone,stone of regional or extraregional origin, and mate-rials other than stone (Fig. 5). A total of 2082 obser-vations of building materials on 136 churches and5046 observations on 483 houses were performedin the Pays remois.

Group 1: local stone. The recognized local stoneswere as follows (in stratigraphical order):

(1) Chalk (CRA) is a white and soft wackestoneto mudstone made of micrite nanograins,coccoliths and foraminifera. The chalk fromthe Reims area, dated to the Upper Cretac-eous (Fig. 2), is a very pure carbonate rockwithout flint.

(2) Trepail conglomerate (TRP) is a coarse andheterogeneous sandy or calcareous conglom-erate. It contains chalk gravels or pebbles.The TRP is not seen in outcrop but seemsto be linked to Microcodium calcareoussandstone.

(3) Microcodium calcareous sandstone (CRO)is a homogeneous, fine stratified and porous,medium calcareous sandstone to sandy bio-calcarenite dated to the basal Ypresian Stage(Fig. 2). It contains chalk gravels or pebblesand prismatic calcitic fragments (dismantledMicrocodium aggregates).

(4) Sandstones (GRE) include three mainfacies: quartzitic sandstones without fossils;calcareous sandstones with shell fossils, for-aminifera and plant residues; and ferruginoussandstones that are often coarse and porous.They were dated to the Thanetian/Ypresian(Fig. 2).

(5) Ditrupa limestones (DIT1) comprise threemain facies: a fine-grained facies; a bioclas-tic facies; and a partly detrital and sandyfacies. These packstones contain Ditrupastrangulata (a cylindrical serpula from anne-lids) that varies considerably (Turmel et al.

Fig. 3. Scheme of the GIS-databases and themethodology used.

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2014). They were dated to the Middle Lute-tian Stage (Fig. 2).

(6) Miliolid limestones (MIL) are mainlyrepresented by yellow-red to grey-brownpackstone with coarse white shells and fora-minifera (milliolids, Orbitolites complanatusand Alveolinidae). These limestones weredated to the upper part of Middle Lutetianstrata (Fig. 2) (Gely 1996; Huyghe et al.2012).

(7) Silicified limestones (CHA) are smallpatches of brown or grey to black silicifica-tion. They were dated to the upper part ofthe Middle Lutetian Stage (Fig. 2). Theysometimes form pseudo-banks by mouldingthe bioturbation network or grow in porous,coarse and shelly limestone banks.

(8) Cerithium limestones (CER1) are beige towhite grainstones (Turmel et al. 2014) withmilliolids, gastropoda imprints (withoutshell preservation) and Cerithium (Cerithiumdenticulatum), which is exclusive to thisrock. They were local marine Lutetian banksand interstratified in a laguno-lacustral for-mation containing soft lacustral limestones,marls and clays (Fig. 2) (Gely 1996).

(9) Potamide limestones (GAS) are pack-stones that vary from yellowish to white incolour and are massive or vacuolar due topotamide imprints. They are related to theCER1 and belonged to a laguno-lacustralformation.

(10) Sublithographical limestones (SUB) arebeige micritic limestones interbedded in asuccession of marls and clays dating to theUpper Lutetian (Fig. 2). Similar facies existin Bartonian marl and limestone successions,mainly in the Montagne de Reims area.

(11) ‘Flints’ and Tertiary lacustral cherts (SIL)are siliceous stones and are very specific stra-tified silicifications that developed in softlacustral charophyta limestones from theBartonian Stage (Fig. 2) in the Tardenois area.

(12) Lacustral Limnaea limestones (LIM1)are yellow-beige to white packstones withcharophyta (oogonia and occasionally stems)and numerous Limnaea associated with Pla-norbis in a few banks. They were found inlacustral banks from the Upper Thanetian,Upper Lutetian and Bartonian Stages (Fig.2). These lithofacies horizontally vary to aSUB.

Fig. 4. Choropleth map and geographic distribution tools for the Ditrupa limestone (DIT1).

GIS-BASED VARIABILITY OF BUILDING STONES

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(13) Siliceous stones and burrstones (MEU) arecherts that offer very polymorphic facies,colours and aspects (from the RupelianStage). They are called burrstones (or burr-stones), which refers to their use as mill-stones, as does the word meuliere in French.In the study area, these siliceous limestonesare mainly located to the south (Montagnede Reims area) or to the east, including relicsand dismantled formations on top of a fewhills (Mont de Berru, Mont de Champagne).

Group 2: regional or extraregional stone. Non-localbuilding stones were grouped together according totheir provenance area (and sorted by stratigraphicalorder), namely, limestones from Aisne, Oise andMeuse in the Lorraine region. They are all famousFrench limestones and largely used in the northernregions of the country and abroad, including in theUK, Belgium, Germany and the Netherlands.

The limestones from Aisne and Oise came fromthe Lutetian Stage:

(1) Nummulitic sandy limestones (NUM) arebeige grainstones with numerous Nummuliteslaevigatus and recrystallized microspariticcement. They were dated to the Lower Lute-tian Stage and developed in the Soissonnaisarea (Fig. 2).

(2) Ditrupa limestones (DIT2) are beige grain-stones that were mainly extracted in the Aisnearea and present more porous and thicker bedsthan in the study area.

(3) Saint-Maximin limestones (SMA) comprisea large range of grey to white micro-granularmiliolid packstones from very massive toporous facies. The Saint-Maximin area isone of the main building-stone quarry districtsin the centre of the Paris Basin. These lime-stones are the lateral equivalent to the localLutetian limestones in the Pays remois.

(4) Saint-Pierre-Aigle limestones (SPA) includevarious qualities (and perhaps origins) of theCER1 that are still quarried in the Soissonsarea. They are more homogeneous and thickerthan the equivalent facies located in thestudy area.

(5) Lacustral Limnea limestones (LIM2) aregrey to greenish with Limnaea white shellpackstones. They are mainly observed inreused architectural elements (most likelyfrom Gallo-Roman buildings) (Fronteauet al. 2010a). It was difficult to give a geo-graphical and stratigraphical provenance forthis specific stone without exact correspon-dence in quarries and outcrops. However, itmost likely came from the Upper Lutetianbanks of the plateaus in the northern AisneValley (Fronteau et al. 2010a). All of thelacustral limestones with Limnaea in the data-base were regrouped into the same lithologicalfacies (called LIM).

(6) Orange granular Cerithium limestones(CER2) are the last marine Lutetian banks(from the Upper Lutetian, Fig. 2). These

Code Usual name Geological noitpircseDegatsMEU Siliceous stones and burrstones Rupelian chertsLIM1 Lacustral Limnea limestones Upper Lute�an/Bartonian packstone with charophyta and LimneaSIL “Flints” and ter�ary lacustral suoecilisstrehc stonesSUB Sublithographical enotsdumsenotsemilGAS Potamides enotskcapsenotsemil with Potamides imprintsCER1 Cerithium limestones grainstone with milliolids, gastropoda imprints and CerithiumCHA Silicified limestones packstone with patches of brown or grey to black silicifica�onMIL Miliolid enotskcapsenotsemil with coarse white shells and foraminiferaDIT1 Ditrupa limestones packstone with Ditrupa strangulataGRE Sandstones Thane�an/Ypresian quartzi�c, calcareous, ferruginous sandstonesCRO Microcodium calcareous muidemenotsdnas calcareous sandstone to sandy biocalcareniteTRP Trépail ydnasetaremolgnoc or calcareous conglomerate with chalk gravelsCRA Chalk Upper Cretaceous wackestone to mudstone with coccolithes and foraminiferaCER2 Cerithium limestones grainstone with ooïdes, milliolids and cerithium imprintsLIM2 Lacustral Limnea enotskcapsenotsemil Limnea white shellsSPA Saint-Pierre-Aigle limestones Cerithium limestonesDIT2 Ditrupa limestones Middle Lute�an grainstone with Ditrupa strangulataSMA Saint-Maximin limestones Lute�an milliolid packstonesNUM Nummuli�c sandy limestones Lower Lute�an grainstone with numerous NummulitesOOV Savonnières limestone Lower Tithonian ooli�c grainstone with layers of bivalvesENT Euville limestone Middle Oxfordian crinoidal grainstoneBRQ1 Fired clay ytlisskcirb or loamy claysBRQ2 Cormicy’s sand grey yalCskcirb with Thane�an sandsCDT Chalky htraeseboda bricks (mix of mud or clay)BET ConcreteBOI doowdooW beam and �mber frameMET norislateM and steel bars and plates

Localstone

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Upper Lute�an

middle Lute�an

Basal Ypresian

Upper Lute�an

Fig. 5. Summary of stones and geomaterials identified in the Pays remois: name, code, geological stages andpetrographical description.

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grainstones have many ooıdes or milliolidsand some Cerithium (Cerithium denticulatum)imprints cemented by microspar. It was diffi-cult to distinguish the geographical prove-nance because this facies was not observedin the local outcrops.

The limestones from Meuse in the Lorraine regioncame from the Jurassic Period:

(1) Savonnieres limestone (OOV) is a yellowishto grey oolitic grainstone with layers ofbivalve shells (Roels et al. 2001). This stonewere quarried from the Meuse area in theLorraine region.

(2) Euville limestone (ENT) is a white-grey cri-noidal grainstone with a spar syntaxialcalcite (Fronteau et al. 2010b).

Group 3: non-stone materials. The last groupincluded all the materials that were not stones:

(1) Metals (MET) are iron and steel bars andplates.

(2) Wood (BOI) is wood beams and timberframes.

(3) Concrete (BET) is blocks.(4) Chalky adobes (CDT) or earth bricks are

made of a mix of mud or clay (from thesurface or soil) and aggregates coming frombricks, sands, limestones, chalk and alluvialgravels.

(5) Brick (BRQ1) is fired-clay bricks made ofsilty or loamy clays with the addition of fewsand grains or small siliceous stone fragments.

(6) Cormicy’s sand grey bricks (BRQ2) aremainly made of Thanetian sands mixed witha little bit of clay. They were only producedfor reconstruction after the First World Warnear the village of Cormicy to the north ofPays remois.

The survey GIS-database

The proportion of each building material was calcu-lated for every commune and mapped on the Paysremois to determine the spatial distribution. Theresults showed that the main building materialsused were local stones (Figs 5 & 6), in particularfrom the Middle Lutetian (with MIL 21% and DIT19%). The regional and extraregional stones onlyrepresented 6% and the other materials 15%. Theresults from LIM2, SMA, SPA and DIT1 are notdescribed in this paper because their proportionswere too low (1%).

The building material usage was discriminatedaccording to its position on a facade (base, ele-vation, door or window frame and quoin) and thiswas investigated with spatial statistics. This wasassessed from the proportion of each materialinside and outside each SDE. Three trends werenoticed. The first suggested that building materialswere employed for one or two specific positions;hence CRA, CDT, GRE and GAS were used forelevated areas, while GRE was also used for base-ments. The second trend highlighted a specificzone with no specific uses in its centre (SDE) anda spreading zone with one or two specific uses for

Fig. 6. Proportions of the building materials.

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the material; for instance, SUB, MEU, DIT2 andCER2 were used for elevated areas in the spreadingzone, while SUB was also used in quoins and DIT2in frames. The third trend indicated that a buildingmaterial had been used in all areas in every positionalthough there were one or two dominant positions;for instance, DIT1, BRQ1 and OOV were dominantin elevated areas, while BRQ1 and OOV were alsoused in window frames and OOV in door frames.MIL was only dominant in door or windowframes. CHA, SIL, NUM and ENT had no specificusage trends.

The choropleth maps illustrate the percentageper commune of building stones in churches andhouses. Only maps of CRA, SUB and DIT1 are pre-sented in Figures 4 and 7. The closer spatial meanand median centres display a good representationof the SDEs regarding the distribution of buildingmaterials. The gradient of CRA percentage indi-cates two usage poles for both building types (Fig.7a, b). The first pole occurs around the SuippeValley and spreads in the direction of Reims. Thesecond pole appears in Reims and the Montagnede Reims area. The SDE includes these two poles

but presents the direction of the main usage on thechalky plain. The SUB choropleth maps exhibit itsusage through the Ile-de-France cuesta and thechalky plain to the west of Reims (Fig. 7c, d). Thehighest percentages are observed along the ArdreValley. SUB is also less used in the Massif de Saint-Thierry. The distribution of DIT1 on its cloroplethmap is concentrated in the northwestern part of thePays remois (Fig. 4).

Thus, three SDE sizes were inferred (Fig. 8). Thefirst corresponds to a strongly concentrated SDEthat measures c. 12 km (major axis) by 5–8 km(minor axis). The types of materials used inhouses were twice as numerous as in churches. Allthe materials were local except for the NUM,which were present for both building types. CROand TRP were only observed in churches, andBRQ2, CHA and SIL were only observed inhouses. These materials had minor proportions inthese buildings. The second SDE, measuring c.15 km (major axis) by 8–12 km (minor axis), corre-sponds to a concentrated SDE. These buildingmaterials were generally confined to one specificsection. CDT was a specific material for houses.

Fig. 7. (a) and (b) Choropleth map of chalk CRA and (c) and (d) sublithographical limestone SUB observed in churches(a) and (b) and houses (b) and (d).

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Most materials with a concentrated ellipse werelocal, except for extraregional stones from Aisne(DIT2, CER2) and Meuse (OOV) in houses. Thenumber of materials used in houses (8) was twicethat in churches (4). The third SDE, measuring c.19 km (major axis) by 8–12 km, corresponds to anextended SDE. Unlike in the other SDEs, thenumber of materials employed in churches (9) wasaround twice that used in houses (4). The regionaland extraregional stones employed in the churchescame from Aisne (DIT2, CER2) and Meuse (ENT,OOV). Those employed in houses mainly came

from Meuse (ENT). Furthermore, the materialshave different SDE sizes due to the building types.For instance, MIL has an extended SDE in churchesbut a concentrated SDE in houses. Finally, thespatial distributions of BOI, BET and MET werenot shown in this study due to the lack of a relation-ship between the building materials and theirgeographical use.

The SDE size results displayed the territo-rial cohesion of the building materials. Territorialcohesion was defined as a cluster of communesthat mostly employed the same building materials.

Fig. 8. Distribution of local (without frame) and regional materials (with frame) in churches and houses in the threegroups of SDEs.

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Intersecting SDEs distinguished five micro-regionsof building materials used in the Pays remois(Fig. 9):

(1) Micro-region 1 is to the NE of the Massif deSaint-Thierry and partly on the Vesle Valley.It mainly contains local materials (GRE,DIT1 and MIL) and some regional to extrare-gional stones (NUM and DIT2).

(2) Micro-region 2 is located to the east on theTardenois plateaus, Ardre Valley and part ofthe Vesle Valley. It contains Upper Lutetianand Bartonian building stones (CER1,CER2, SUB, GAS, LIM, CHA and SIL).DIT1 and MIL were less used in this micro-region compared to previous building stones.

(3) Micro-region 3, located on the Montagne deReims, is associated with CRO, TRP, MEU,BRQ1, CRA and CER2.

(4) Micro-region 4 is located on the chalky plainand is composed of CRA, CDT, BRQ1, OOVand ENT.

(5) Micro-region 5 is in metropolitan Reims. It isthe crossroads of all micro-regions, and everybuilding material is observed. Nonetheless,this region contains fewer building materialsfrom the second micro-region.

The durability was estimated by the weightedaverage of the materials’ durability for each com-mune (Fig. 10). The materials prone to greater dam-age are CDT, BRQ2, CRO, CRA, MIL and NUM. Inthe eastern part of the Pays remois, along the Vesleand Ardre Valleys, the low durability was due to thehigh proportion of MIL and lesser proportion ofNUM. In the southern and western areas of the Paysremois, the low durability was due to CDT, CRO,CRA and MIL. In the field, the materials that wereobserved to be resistant to weathering were CER1,CHA, GAS, LIM, SIL, SUB and MEU for localstones and CER2, ENT and OOV for regional orextraregional stones. In the Tardenois plateaus (tothe SE), the usage of MEU, GAS, SUB, CER1,CHA, GAS and SUB explain the high durabilityobserved in these communes. To the west, this highdurability was due to the usage of BRQ1, MEU,OOV and ENT.

Discussion

The present GIS-database identified the main build-ing materials in the Pays remois and their origin. Italso quantified and analysed the spatial distributionsof these 26 building materials used in churches andhouses. The SDE and choropleth maps also showedthe origin, distribution, usage and durability of thesematerials, which displayed the territorial cohesionof building materials.

Territorial cohesion depends on several criteriawhen choosing and using building materials in con-struction. One of the most important criteria is trans-portation (Martinez-Torres 2007), but other criteriaare also defined (Gomez-Heras et al. 2010; Fronteauet al. 2014):

(1) availability – ability of a building material tobe provided, extracted and diffused;

(2) efficiency – ability of a building material tomeet the specifications (colour and sizerequirements, low cost for customer, profit-ability and low cost for transport);

(3) workability – ability of a building material tobe carved and sculpted;

(4) durability – ability of a building material to beresistant to weathering.

Comparing the micro-regions to the geologyrevealed spatial distributions of each building mate-rial close to their geological origin (Figs 2 & 9).These distributions enabled the assessment of theavailability of each material. For instance, CRA isstrictly used on the Cretaceous substratum. Simi-larly, many local building materials (local stonesin Fig. 5) extracted from the Tertiary substratum(Thanetian/Ypresian, Lutetian and BartonianStages) are mainly used in the same area. For exam-ple, local stones from the Upper Lutetian, Bartonianand Rupelian Stages were extracted and employedin the Montagne de Reims area and along theArdre Valley. GRE is mostly observed to the northand NE of the study area, where the communes areclose to the Thanetian/Ypresian Stages (e.g. Montde Brimont; Fig. 2). MIL and DIT1 are alsomainly used close to their extraction area in theMassif de Saint-Thierry (Fronteau et al. 2010a).These two limestones were specifically extractedin the Middle Ages for Reims Cathedral (Turmelet al. 2014). Furthermore, these two materials arealso employed throughout the Pays remois, whichmeans that they had high availability and efficiency.Consequently, the geology has been a major par-ameter in the territorial cohesion of building mate-rial usage. Outcrop areas from Fronteau (2000)were compared with this research (Fig. 11). District(1) in the Ardre and Vesle Valleys includes theextraction zone of MIL; here, it actually encom-passes a larger zone to the south and the extractionzone of other limestones from the Upper Lutetianand Bartonian Stages. District (2) in the Massif deSaint-Thierry corresponds to the extraction zone ofMIL and DIT1 (Fronteau 2000) and includes theextraction zone of GRE and the DIT2 and NUMusage areas. District (a), located in the Montagnede Reims area, was the extraction zone for MEU(Guerin 1990), CRO and TRP (Fronteau 2000). Inour study, the main usage of the buildings in the dis-trict was assessed. Indeed, the comparisons with the

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Fig. 9. Landscape units of geomaterial usage.

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Fig. 10. Durability map of the materials for each commune.

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origin (geology) and SDE sizes for every materialcharacterize their availability and efficiency.

BRQ1, only used in houses, and DIT1 and MIL,used for both types of buildings, were the mainmaterials used throughout the studied area. MILwas dominantly used for door and window framesand DIT1 for elevated areas. Thus, those specificpositions required workability in ashlars. The utiliz-ation trends of these building materials were corre-lated with the SDE sizes. Indeed, most buildingmaterials from the first or second trend belongedto the first or second SDE size. Moreover, onlybuilding materials with extended spatial distri-butions had a dominant utilization trend. This

trend revealed that these materials were the mostavailable (the most extracted) and efficient for thisposition on the facade. Few building materialswere only employed in houses, such as CDT andBRQ2, or churches, such as TRP and CRO. Thus,they were specific to building types, indicatingtheir poor efficiency.

Other than for DIT1, MEU and ENT, the SDEsizes were dissimilar for each material employedin churches and houses, indicating that their build-ing management was different. To build churches,many materials were used and exported throughthe Pays remois. In contrast, the houses weremade of local materials, and fewer were chosen as

Fig. 11. Superimposition of landscape units (Fig. 8) and district quarry identified by Fronteau (2000).

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specific markers for the study area. Thus, the maincriterion to build churches was efficiency becausethe constructors requested specific materials (fortheir colours, durability, etc.) despite their avail-ability. Availability was the most important cri-terion for houses, meaning that the cost due toextraction and/or transport was the most important.

Furthermore, these results indicate that thechurches outside of Reims were not submitted to aspecific geomaterial choice, as suggested byPrache (1979), who estimated that all the churchesbuilt in approximately the twelfth and thirteenthcenturies were based on major religious monuments(Reims Cathedral and Basilica).

Comparing the durability maps and distributionindicators (choropleth maps, SDE sizes) indicatesthat the two are not correlated. Despite the low dura-bility of MIL due to weathering such as spalling,flaking, peeling, crusting (Fronteau 2000; Verges-Belmin 2008) and salt susceptibility (Turmel et al.2014), this stone is one of the most common geoma-terials used in the Pays remois in specific positions.In contrast, some materials such as CER1, SUB,MEU or GAS have high durability but stronglyconcentrated to concentrated SDE sizes. Theseresults highlight that some micro-regions, such as2 or 3, tend to be built with resistant materials com-pared to micro-regions 1 and 5, which are mainlybuilt with MIL, DIT1 and DIT2. In micro-region4, the opening of the canal and railway line after1850 could have influenced the decrease in thelocal usage of low durability materials because ofthe introduction of extraregional Saint-Maximin(SMA) and Saint-Pierre-Aigle stones (SPA) fromthe Aisne and Oise regions or Savonnieres (OOV)stones and Euville (ENT) from Meuse. Indeed,MIL compete with these stones, which had betteravailability (thicker layers) and efficiency (lowercosts). Thus, the SDE sizes and utilization help toidentify the criteria.

This study accurately describes building mate-rials (petrographical characterization) and theirutilization. Combining the petrography and GIS-database creates a framework for the selection ofsuitable stones for repairs or new construction.This method has been proven already by Hyslop &Albornoz-Parra (2009) and Hyslop et al. (2010) inGlasgow, and Delegou et al. (2013) in Rhodes.The SDEs quantify the spatial distributions of thebuilding materials, which provide a better under-standing of territorial cohesion and help to differen-tiate building management between churches andhouses. This specific tool highlights a spatial pat-tern that shows the criteria for choosing materialsfor the construction of buildings, which is in con-strast to other authors’ observations (i.e. El-Gohary2010; Frangipane 2010; Kampfova & Prikryl 2010;Siegesmund et al. 2010). As already observed, the

distance between the origin and usage of materialscharacterized the historical availability of thesources (Dreesen & Dusar 2004; Gomez-Heraset al. 2010). The greater the distance from thesources, the higher the availability/efficiency orworkability (Martinez-Torres 2007). In addition,this study has highlighted the utilization of mate-rials and the differences in building managementbetween houses and churches; additions to the archi-tectural style information in the GIS-database wouldprovide more results. In fact, many authors haveshown that stones are specific to architectural styles(e.g. Martinez-Torres 2007). Among other factors,these are related to specific time-lapses, whichcould help distinguish the temporal uses of eachmaterial (e.g. De’Gennaro et al. 2000; Revenu2008). Compared to Dreesen & Dusar (2004) orButtner (2011), the present study has determinedspecific uses of regions of stones using a statisticalapproach, which provides a quantified and betterdefinition of the area of each micro-region. Thedurability for each commune could be related to arisk map, similar to earthquake vulnerability (Villa-gra et al. 2014) or the Risk Map of Italian CulturalHeritage (Accardo et al. 2003). These provide arecord of the cultural heritage and a predictionmap of preferential sensitive zones. The GIS-database would be enriched by redefining the dura-bility for each stone with weathering assessmentsfor specific buildings. This approach could be com-pleted with photography and descriptions of facades(Inkpen et al. 2001; Delegou et al. 2013) or withexperimental data, such as petrophysical data, i.e.mercury porosimetry, tomography, salt suscepti-bility or freeze/thaw cycles (Cnudde & Boone2013; Dewanckele et al. 2013; Turmel et al. 2014).In turn, this would allow the calculation of the per-centage of deteriorated surfaces and the weatheringrate for each building material (Andre et al. 2014).This would also help identify the preferential weath-ering zones on facades (i.e. El-Gohary 2010).

Conclusion

A GIS-database including the petrographical dataand spatial locations of 26 building materials usedin the Pays remois has allowed statistical and spa-tial analysis. Milliolid limestones (MIL), Ditrupalimestones (DIT1), millstones (MEU) and bricks(BRQ1) are the main local and building materials.Three utilization trends are identified (using SDE):the first suggests building materials were employedfor one or two specific positions; the second definesspecific zone with no utilization trends in its centreand outside of this specific zone with one or twotrends; and the third indicates that building materialswere used in every position in the entire area with

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just one or two dominant positions. Thus, each spe-cific use of building materials shows utilizationtrends throughout the study area. The spatial distri-butions studied with the quantitative method inducethree SDE sizes: a strongly concentrated SDE, aconcentrated SDE and an extended SDE. The over-laid SDEs of 26 building materials identified fivemicro-regions, which revealed the territorial man-agement. The spatial distributions of building mate-rial usage reflect the geology of the Pays remoisfor each building type. The territorial cohesioncould be described based on different criteria (avail-ability, efficiency, workability and durability).This GIS-database is useful in the work of historicmonument restoration; it also provides guidanceon building in terms of local trends, micro-regionsand built heritage.

The distribution tools used here quantify thespatial distributions and they enable us to proposea geomaterial spatial model. With the integrationof temporal extraction and usage data, the modelwill provide information on the evolution of usage.Furthermore, with the integration of quarry localiz-ations, the model will provide information on spatialdiffusion. These two models will highlight the his-torical and economic management of local buildingmaterial diffusion at multiple scales. In the future, itwill be interesting to include data from archae-ological sites and dated vernacular and monumentalbuildings. The relationship with petrophysical prop-erties and weathering patterns will provide guidancedata to find replacement stones.

We gratefully acknowledge the city of Reims for fundingthe PhD scholarship of Aurelie Turmel.

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