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Journal of Archaeological Science 38 (2011) 697e710

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Journal of Archaeological Science

journal homepage: http : / /www.elsevier .com/locate/ jas

UAV and RPV systems for photogrammetric surveys in archaelogical areas:two tests in the Piedmont region (Italy)

F. Chiabrando a,*, F. Nex b, D. Piatti b, F. Rinaudo b

aDipartimento di Scienze e Tecniche per i Processi di Insediamento, Politecnico di Torino, Viale Mattioli 39, 10125 Torino, ItalybDipartimento di Ingegneria del Territorio dell’Ambiente e delle Geotecnologie, Politecnico di Torino, C.so Duca degli Abruzzi 24, 10121 Torino, Italy

a r t i c l e i n f o

Article history:Received 27 January 2010Received in revised form12 October 2010Accepted 24 October 2010

Keywords:UAVPhotogrammetryImage acquisitionDSMMulti-image matchingArchaeological survey

* Corresponding author. Tel þ39 011 5644380; faxE-mail address: filiberto.chiabrando@polito.it (F. C

0305-4403/$ e see front matter � 2010 Elsevier Ltd.doi:10.1016/j.jas.2010.10.022

a b s t r a c t

Aerial photogrammetric surveys are usually expensive and the resolution of the acquired images is oftenlimited. For this reason, different innovative systems have been developed and tested in order to performa photogrammetric survey in an inexpensive way, with high-resolution images. In this context, one of themost promising acquisition techniques is represented by the use of Unmanned Aerial Vehicles (UAVs)equipped with a digital camera.

The paper deals with the acquisition and processing of low-height aerial imagery acquired by UAVsand Remote Piloted Vehicles (RPVs), in order to provide large-scale mapping to support archaeologicalstudies: the pros and cons of these acquisition platforms are presented and discussed. These systemscarry out flights that are usually very different from the manned systems as their dimensions and theirlight weights never allow the set course to be flown; for this reason, the acquired images are oftenaffected by large rotations and small overlaps. Therefore, an ad hoc procedure has been implemented toovercome these limits. In this work, two remote-controlled systems (a mini-helicopter and a mini fixed-wing plane) were tested over two different archaeological sites in order to provide Digital Surface Models(DSMs) and large-scale maps (numeric maps and orthophotos). Finally, an accuracy evaluation of thefinal products is reported.

� 2010 Elsevier Ltd. All rights reserved.

1. Introduction

The survey of archaeological areas is often carried out usingtraditional techniques, such as topographic surveys, close-rangephotogrammetry and terrestrial LiDAR acquisitions. Nevertheless,the main drawback of these methods is the difficulty involved inacquiring reliable radiometric information of the completesurveyed area, which can easily be obtained bymeans of traditionalaerial photogrammetric flights. Furthermore, the costs of aerialphotogrammetry are usually too high in relation to the limitedextension of the surveyed areas. Moreover, the flight altitudes ofaircraft equipped with aerial photogrammetric cameras are notable to supply suitable images for the production of large-scalemaps (higher than 1:500) and the flight of motor aircraft overarchaeological sites is often forbidden. Another problem is that thesites that have to be surveyed are sometimes in remote areas.

For these reasons, the use of low-aerial flying systems couldefficiently be exploited to acquire metric and non-metric data in

þ39 011 5644399.hiabrando).

All rights reserved.

order to document archaeological areas (Verhoeven, 2009). In theGeomatics scientific community, research is focused on the use ofnon-conventional aerial platforms developed for aerial photo-grammetric surveys.

Different tests have been performed using various platforms,(Everaerts, 2008; Eisenbeiss, 2009) such as helium balloons (Altanet al., 2004; Celikoyan et al., 2003; Fotinopoulos, 2004; Gesafidiset al., 1999; Kemper et al., 2003; Mihajlovic et al., 2008), kites(Aber et al., 2002; Bitelli et al., 2003; Bogacki et al., 2008), fixed-wing platforms (Bendea et al., 2007) and mini-helicopters(Colomina et al., 2007; Eisenbeiss et al., 2005; Patias et al., 2007,2009; Remondino et al., 2009; Skarlatos et al., 2004; Spatalaset al., 2006; Theodoridou et al., 2000; Tokmakidis and Skarlatos,2000; Vallet and Skaloud, 2004; Wendel et al., 2006; Zischinskyet al., 2000).

Some fixed-wing platforms and mini-helicopters can beconsidered UAVs (Unmanned Aerial Vehicles), as they are “aircraftwhich are designed or modified, not to carry a human pilot and areoperated through electronic input initiated by the flight controlleror by an onboard autonomous flight management control systemthat does not require flight controller intervention” (AIAA, 2004).These aerial platforms have been developed since the late 1950s for

Table 1UAV classification e Subcategories of tactic UAVs (UAV association).

Subcategories ofTactic UAVs

Acronym Range[Km]

Climbrate [m]

Endurance[hours]

Mass[Kg]

Micro m (Micro) <10 250 1 <5Mini Mini <10 150e300 <2 150Close Range CR 10e30 3000 2e4 150Short Range SR 30e70 3000 3e6 200Medium Range MR 70e200 5000 6e10 1250Medium Range

EnduranceMRE >500 8000 10e18 1250

Low Altitude DeepPenetration

LADP >250 50e9000 0.5e1 350

Low Altitude LongEndurance

LALE >500 3000 >24 < 30

Medium AltitudeLong Endurance

MALE >500 14,000 24e48 1500

F. Chiabrando et al. / Journal of Archaeological Science 38 (2011) 697e710698

military purposes. They are currently employed in military and civilfields for reconnaissance or monitoring operations, atmosphericmeasurements, damage assessment and mapping of natural ormanmade hazards, monitoring in agriculture and forestry and coastguard operations.

UAVs are classified on the basis of different specifications; themost effective classification has been drafted by the UnmannedVehicle Systems International Association (International UnmannedAerial System Community, 2008). According to this classification,UAVs are split into threemain categories under to their possible use:Tactic, Strategic and Special Purpose. Each typology is divided intosubcategories, according to their features and performances: vehicleflight range, maximum climbing rate, endurance weight, etc. Thefirst category of UAVs is usually employed for photogrammetricpurposes: micro andmini-UAVs (Table 1) are employed in particularsince they are cheaper to construct than traditional mannedplatforms.

The work presented in this paper is focused on some tests thatwere performed by the Geomatics research group of the Politecnicodi Torino on UAV and RPV systems to evaluate their suitability forarchaeological surveys. A fixed-wing platform and a mini-helicopterwere used: the first one (Pelican) was employed over the Romanarchaeological site of Augusta Bagiennorum (Bene Vagienna, Pied-mont, Italy), while the second one (Voyager G8 RR mini-helicopter)was used in the Reggia di Venaria Reale (Venaria Reale, Piedmont,Italy).

The first platform can carry out photogrammetric flight coursesin a completely automatic way (excluding take-off and landing),according to the flight plan specifications; instead, the secondsystem cannot perform autonomous flights, and this is why it isnamed RPV. Nevertheless, in both cases the performed flights are

Fig. 1. Aerial views of the Theatre (left) and of the Am

very different from traditional photogrammetric flights: the smalldimensions of these systems and the reduced weight do not allowimages that are close to the normal case to be obtained. For thisreason, the commercial software packages available for imageorientation, DSM extraction and orthophoto production are oftennot sufficient to achieve reliable results. A new ad hoc process isnecessary to achieve maps of test sites in a quick and reliable way.

The basic algorithms set up by the Geomatics group of thePolitecnico di Torino in order to solve this task are describedhereafter. The proposed approach takes advantage of both theComputer Vision and the Photogrammetric application field.Computer Vision algorithms were adapted in the image orientationprocedure and multi-image matching techniques were used for thegeneration of the Digital Surface Model (DSM).

2. Historical framework

The ruins of the Roman city of Augusta Bagiennorum are situateda few kilometers from the actual city of Bene Vagienna in Piedmont(Italy). Due to the strategic position in the middle of the Tanarovalley, Augusta Bagiennorum became an important centre whichwas exploited by the Romans for agricultural purposes and urbanredevelopment. Since the 2nd century BC, Augusta Bagiennorumhas been one of the vertices of a triangle, with nearby cities ofPollentia and Alba Pompeia, which constituted the nodal points ofthe street network required for the expansion of the RomanEmpire. Today, the archaeological remains attest the presence ofsome public buildings, such as the Theatre (Fig. 1 left) and the four-sided portico, which is characterized by a central basement ofa temple devoted to an unknown divinity. These buildings are bothlocated in the south-eastern part of the ancient city. A smallChristian Basilica was built above the temple and its remains canstill be seen; it is currently possible to identify the perimeter wallsand the major apse between two minor ones.

Some structures (houses or workshops), constituted by circularsurrounding walls around a central court (1st to 2nd century BC),are clearly visible in front of the above described archaeologicalarea. Finally, it is also possible to recognize the Amphitheatreoutside the old city (Fig. 1 right).

The other archaeological site examined in this paper is theFontana D’Ercolewhich can be found in the Gardens of the Reggia diVenaria Reale (Fig. 2). The ruins of the Fontana D’Ercole werediscovered during works in the Reggia di Venaria Gardens. Thefountain was built over a period of four years (from 1669 to 1672)on the basis of a project by Amedeo di Castellamonte; the FontanaD’Ercole formed the central architectural and symbolic axis of theprojected seventeenth century garden. Thanks to the two flights of

phitheatre (right) (Augusta Bagiennorum area).

Fig. 2. Fontana D’Ercole: old drawing (left), aerial view (in the centre of the red circle), terrestrial view (right) (for interpretation of the references to colour in this figure legend, thereader is referred to the web version of this article).

F. Chiabrando et al. / Journal of Archaeological Science 38 (2011) 697e710 699

stairs on either side of the large basin, the fountain connected thelower garden to the upper one.

In 1699, Garove suggested a transformation project of thegardens (from an Italian style of garden to a French style of garden)and the first suggestion for the demolition of the Fontana D’Ercolewas made (Bruno and Vinardi, 1990). The fountain, broken up in1726 by Tantarini, was permanently knocked down in order to reusethe bricks for the construction of the new part of the main buildingof the Reggia di Venaria Castle. Today, after the archaeologicaldiggings, the old fountain ruins can clearly be seen in the Gardens.

3. Theoretical background

The use of Photogrammetry and Computer Vision algorithmswere necessary for this work. The photogrammetric workflow(Marenchino, 2009; Lingua et al., 2009a) that is illustrated hereaftershows the different phases of the orthophoto and drawingproduction of the performed tests (Fig. 3).

3.1. Image acquisition

Image acquisition was performed according to the availableaerial platform and it is one of themain phases of theworkflow. Theresults of the automatic DSM and orthophoto generation dependon the quality of the acquired images. Therefore, a good imageacquisition should allow a double stereoscopic coverage (at leastthree images of the same object) to be achieved over the surveyed

Fig. 3. Data acquisition and processing workflow.

area: in this way, a multi-image approach can be performed.Moreover, the acquired images should have a good radiometriccontent and avoid any drag effect. Two different digital cameraswere employed over the test areas (Table 2): a Ricoh-GR cameramounted onto the UAV Pelican for the Augusta Bagiennorum testsite and a Nikon Coolpix 8400 camera onto the mini-helicopter forthe Reggia di Venaria Reale test site.

3.2. Image pre-processing

Image pre-processing techniques allow image quality to beenhanced when the image has been taken in non-ideal conditions(forward motion effects, low radiometric content, etc.). Thesealgorithms are frequently used to enhance image quality, to reducenoise effects and to increase image contrast. A Wallis filter (Wallis,1976) was implemented in the proposed algorithm. The WallisFilter performs a locally-adaptive (spatially-varying) contrastenhancement on a greyscale raster. This filter is designed for imagesinwhich there are significant bright and dark tone areas. TheWallisfilter adjusts brightness values in local areas so that the local meanand standard deviation match the user-specified target values. Thisenhancement produces good local contrast throughout the image,while reducing the overall contrast between bright and dark areas(Fig. 4). This filter algorithm was tested on aerial images and anoptimized set of parameters was determined for the imageenhancement in order to achieve the most stable results(Marenchino, 2009). The goal of using this filter was to providegood radiometric information for point and region detectors.

3.3. Aerial triangulation

Aerial triangulation is a method that is used for the simulta-neous orientation of an unlimited number of spatially distributedimages (Kraus, 2007; McGlone et al., 2004). The input parametersof this process are the photogrammetric observations (measuredhomologous image points) and the Ground Control Point (GCP)coordinates. The mathematical formulation allows single images tobe merged into a global model in which the surface of the objectcan be reconstructed in three dimensions. The connection toa global object coordinate system is provided through the

Table 2Technical specifications of the two cameras employed in the test areas.

RICOH GR Nikon Coolpix 8400

Resolution [Mpixel] 8 8Pixel Dimension [mm] 2.19 2.69Focal length [mm] 5.90 6.10Weight [g] 200 470Dimensions [mm] 107 � 58 � 54 113 � 82 � 75

Fig. 4. Original panchromatic image of the Amphitheatre (left) and the same image obtained applying the Wallis filter (right).

F. Chiabrando et al. / Journal of Archaeological Science 38 (2011) 697e710700

measurement of a set of 3D unknown points, called Tie Points (TPs)and a minimum number of reference points (GCPs).

In the performed tests, the Tie Points were automaticallyextracted using the A2SIFT (Auto-Adaptive Scale Invariant FeatureTransform) operator (Lingua et al., 2009b), which is an extension ofthe well known SIFT operator (Lowe, 1999; Lowe, 2004). The initialimplementation allows features to be extracted that are invariant toimage scaling and rotation and partially invariant to changes inillumination and in 3D camera viewpoints (affine transformation).The A2SIFT operator also allows a large number of points to bematched in bad textured images (i.e. wooded, grassed areas), thusincreasing the performance of the initial implementation. A robustLeast Median Square (LMS) relative orientation should then beperformed to detect any wrong homologous point candidates(Rousseeuw and Leroy, 1987). The extracted points can be used asTie Points in the bundle block adjustment by importing them incommercial software. This final step was carried out using LeicaPhotogrammetric Suite 9.2 (Leica Geosystems). In an over-deter-mined system of equations, a least square adjustment techniqueestimates the 3D object coordinates, the image orientation pa-rameters and any additional model parameters, together with anyrelated statistical information pertaining to accuracy and reliability.Since all the observed (measured) values and all the unknownparameters of a photogrammetric project are taken into account inone simultaneous calculation, the bundle block adjustment is themost powerful and accurate image orientation and point determi-nation method in photogrammetry. Finally, the Tie Points, GroundControl Points and Check Points are used to generate the approxi-mate DSM that is necessary in themulti-imagematching algorithm.

In our tests, the interior orientation parameters of the employedcameras were estimated before the flights using the iWitness soft-ware (Photometrix). This software uses the ten parameter “physical”model commonly employed in digital close-range photogrammetry(Fraser, 1997). The inner parameters are the principal distance (c),the principal point offsets (x0, y0), three radial distortion coefficients(K1, K2 and K3), two decentering distortion coefficients (P1, P2) and

Table 3Estimated interior orientation parameters of the RICOH-GR camera.

Calibration parameters RICOH GR

c (mm) 5.820x0 (mm) 0.053y0 (mm) �0.308K1 (1/mm2) 8.669E-04K2(1/mm2) �3.204E-04K3 (1/mm2) 1.623E-05

the affine deformation (non-orthogonality) parameters (b1 and b2,which are rarely employed in CCD cameras). The estimated interiororientation parameters of the employed cameras are reported inTables 3 and 4. These parameters were used to correct the acquiredimages from lens distortion before point and edge extraction (SeeSection 3.4.1 Point and edge extraction).

3.4. DSM generation

The DSM Generation can be divided into three different steps:the feature extraction, the multi-image matching process and theblunder detection and filtering.

3.4.1. Point and edge extractionIn this first step, one of the stereoscopic distortion-free images

(all the images were previously undistorted) is chosen as thereference image, while the others serve as search images. Pointsand lines are extracted from the reference image. The points areextracted using the Forstner operator (Forstner, 1986), while theedges are extracted by means of the Canny operator (Canny, 1986).The extracted edges are then approximated, by identifying thepixels where each edge changes in direction as knots and linkingthese dominant points by straight edges (Nex and Rinaudo, 2009).

3.4.2. Multi-image matchingThe DSM extraction is performed through the matching of points

and lines in two or more images. A multi-image matching approach,called Multi-Image Geometrically Constraint Cross-Correlation(MIGC3), has been implemented (Marenchino, 2009). This approachis an area-basedmatching algorithm, based on the Cross-Correlationtechnique. The MIGC3 procedure is based on the concept of multi-image matching (Baltsavias, 1991) guided from the object space,therefore any number of images can bematched simultaneously andthe epipolar constraints are implicitly integrated. Together with anadaptive determination of the correlation parameter, it has theability to reduce both problems caused by surface discontinuities,

Table 4Estimated interior orientation parameters of the NikonCoolpix 8400 camera.

Calibration parameters COOLPIX 8400

c (mm) 6.374x0 (mm) �0.044y0 (mm) 0.131K1 (1/mm2) 1.159E-03K2(1/mm2) 3.259E-06K3 (1/mm2) 4.139E-08

Fig. 5. An example of DSM before (left) and after (right) applying the S2MF filter.

Fig. 6. The Solid True OrthoPhoto: generation and structure.

F. Chiabrando et al. / Journal of Archaeological Science 38 (2011) 697e710 701

occlusions and repetitive structures, and to produce dense andreliable point matching results (Zhang, 2005; Eisenbeiss and Zhang,2006).

The image matching procedure is performed for all the extrac-ted points. An image point is projected in the object space and theapproximate DSM allows a first 3D position of the point to bedefined. This height constraint in the object space allows a heightinterval to be defined where the correct homologous point shouldlie. If this height interval is back-projected onto the search images,the bounds of the epipolar segment will be defined (Hartley andZisserman, 2000). After the application of the geometricconstraints, the research of the homologous points along the

Fig. 7. Stereoscopic image acquisition of the Am

epipolar segment is performed using a function called SNCC (Sumof Normalized Cross-Correlation), which represents the mean valueof the Normalized CrosseCorrelation parameters computed foreach stereo pair (Zhang, 2005). Furthermore, auto-adaptive corre-lation window warping and size, and dynamic parallax compen-sation allows the extraction of homologous points on areas withpoor texture, repetitive structures, or geometric discontinuities.

3.4.3. Blunder detection and filteringThe results achieved when using the MIGC3 algorithm still show

some gross errors. The elimination of these blunders is carried outthrough a robust filtering algorithm called the Self-tuning Standard

phitheatre (left) and of the Theatre (right).

Fig. 8. Example of image acquired with the mini-helicopter (left). Image of 3 of the 40 targets positioned on the Fontana D’Ercole and used as GCPs for the photogrammetric process(right).

Table 5Standard deviations on the GCPs and the CPs of the photogrammetric blocks(s0 ¼ 10).

Amphitheatre sx [m] sy [m] sz [m]

GCPs (13) 0.025 �0.019 0.023CPs (8) 0.040 �0.034 0.038

Theatre sx [m] sy [m] sz [m]

GCPs (9) �0.015 0.020 0.018CPs (6) 0.022 0.027 0.031

F. Chiabrando et al. / Journal of Archaeological Science 38 (2011) 697e710702

deviation Median Filter (S2MF), which has been implemented by theauthors. S2MF is a distance-function filter method, which quicklyprocesses 3D point clouds extracted using photogrammetric proce-dures. It produces filtered DSMs with an almost negligible rate ofresidual errors. In the case of DSMs extracted through automaticphotogrammetric procedures, the lack of dense 3D point cloudscauses the traditionalmedianfilter to fail; therefore, thedevelopmentof an auto-adaptive approach is necessary in relation to the density ofthe point cloud. The filterworks as follows: the planimetric DSM areais split into several bins and each point is classified in the respectivebin according to its position. The bin size is a fundamental parameterthat affects the performances of the filter. On one hand, small binsallow a local analysis of the object to be performed and increase thereliability of the method: however, it is likely that some bins do nothave enoughpoints for a statistical analysis. On the otherhand, if binsof largedimensions areused, eachof themhashundredsofpoints, butan ineffective smoothing can be achieved. For this reason, the squarebin size is defined in relation to the density of the points in the objectspace. The median and the standard deviation of the heights arecomputed for each bin. Themedian is a robust estimator of themeanvalue of a random variable; therefore, it is not sensitive to the pres-ence of outliers in the data set. The standard deviation of the data,which is computedwith respect to themedian, is instead sensitive tothe measurements affected by gross errors. Thus, the distance func-tion, which compares the elevations of each point with the altimetrytrend of the surrounding bins, is also sensitive to the gross errors.

A self-tuning approach for the computation of the standarddeviation of each bin has been developed to avoid these problems.Given a bin with several points, the standard deviation s1 of thewhole data set of z-values is computed with respect to the medianvalue. The minimum andmaximum z-values are then removed anda new value in standard deviation s2 is estimated. The process isiterated until the difference of the standard deviations betweentwo adjacent iterations is smaller than a threshold value defined bythe user. The process allows the points that are likely to be affectedby gross errors to be removed from the standard deviationcomputation with an automated robust approach. The outliers,however, are not eliminated from the data set during this step, butthey are ruled out in the self-tuning standard deviation computa-tion. The median and the self-tuning standard deviation of each binare the two parameters necessary for the definition of the distancefunction. The planimetric position of each point, given its coordi-nates, is computed in the bin reference system. Hence, the medianand standard deviation to be applied to this point are computed bymeans of a bilinear interpolation, considering the median andstandard deviation values of the 4 nearest bins, in this way, it is

possible to apply this distance function to each point of the DSM inorder to identify the outliers. Fig. 5 shows an example of DSMbefore (left) and after (right) applying the S2MF filter.

3.5. Orthophoto production

An aerial image is a central projection of a portion of land and itrepresents a permanent archive of qualitative and geometricinformation about the imaged area. In order to acquire a metricvalue that is comparable with the cartographic one, the image hasto be transformed into an orthographic projection.

In the central projection of an aerial image, each detail is ina planimetrically wrong position, with respect to the orthogonalprojection. This is mainly caused by the image inclination withrespect to the horizontal plane and the ground geometry, whichdetermines a scale variation of the image depending on the relativealtitude with respect to the acquisition point.

A digital orthophoto is obtained by correcting each single pixelposition, which is shifted because of the prospective deformationsdue to the altimetric variations obtained from a DSM.

In recent years, Geomatics research has dealt with the integra-tion of digital images and 3D models automatically obtained usingLiDAR or photogrammetric techniques. The Geomatics researchgroup at the Politecnico di Torino has developed and implementedan innovative product, called Solid True OrthoPhoto (STOP) (Biasionet al., 2004), which combines the high radiometric resolution oforthophotos with the 3D information of DSMs. The radiometriccontent and the 3D spatial data allow basic geometric information tobe extracted, and this information can easily be utilized for culturalheritage purposes. STOP records three colour values from the trueorthophoto (RGB) and one height value derived from the DSM foreach pixel (Fig. 6). This is a cheap and efficient product which can beused to represent the correct shape of any 3D object in photographicform. STOP allows the investigated areas to be examined by meansof measurements of 3D points, distances, areas and volumes;

Fig. 10. Final Amphitheatre TIN extracted and filtered with MIGC3 and S2MF algorithms.

Fig. 11. Theatre ruins: results of the MIGC3 and S2MF algorithms (left); 3D visualization of the extracted points (blue) and edges (red) (right) (for interpretation of the references tocolour in this figure legend, the reader is referred to the web version of this article.)

Fig. 9. Amphitheatre ruins: results of the MIGC3 and S2MF algorithms (left); 3D visualization of the extracted points (blue) and edges (red) (right) (for interpretation of thereferences to colour in this figure legend, the reader is referred to the web version of this article.)

F. Chiabrando et al. / Journal of Archaeological Science 38 (2011) 697e710 703

Fig. 12. Final Theatre TIN extracted and filtered with MIGC3 and S2MF algorithms.

F. Chiabrando et al. / Journal of Archaeological Science 38 (2011) 697e710704

therefore, it is the ideal cartographic support for the measurementof archaeological ruins. STOP has been produced by SirIo software,which has been implemented by SIR, a Politecnico di Torino Spin Off.The generation of STOP requires a DSM and a multiple stereoscopiccoverage of the area of interest. If this information is not available, itis possible to generate a Solid Orthophoto (SOP) by integratinga DSM and a set of oriented images.

4. Experimental section

4.1. Data acquisition e Augusta Bagiennorum test site

The UAV Pelican (Bendea et al., 2008) was employed for theAugusta Bagiennorum test area. This UAV is a low-cost platformwhich is capable of performing photogrammetric flights in anautomatic way. The UAV was developed by the Department ofAerospace (DIASP) at the Politecnico di Torino in cooperation withthe ITHACA (Information Technology for Humanitarian AssistanceCooperation and Action) association, in order to carry out photo-grammetric flights in remote areas affected by natural or manmadehazards. Three platforms in wood and carbon fibre and equippedwith digital sensors are currently available. Each platform weights10 kg and can carry a payload of 2 kg onboard. The optimum rangelimit is 30min at a cruise speed of 15m/s. Thewing span of 2 m andthe possibility of assembling the main component of the platformmake the UAV easy to maneuvre and it can be transported onnormal aircraft and used in the field by a couple of operators.

The platforms currently available are equipped with two videocameras (frontal and nadiral views) for navigation operations. They

Table 6Standard deviations on the GCPs and the CPs of the photogrammetric block(s0 ¼ 10).

Fontanad’Ercole sx [m] sy [m] sz [m]

GCPs (22) 0.009 �0.008 0.015CPSs (10) 0.011 0.016 0.018

carrya compactdigital camera, RICOHGR,which is installed inapod inthebellyof the fuselage. ThecameraGSD(GroundSampleDistance)onthe ground is 0.04m at a flight altitude of 100m. The digital camera iscapable of performing automatic shots thanks to a connection witha commercial autopilot system (Micropilot MP2128g). The navigationsystemallowsautonomousflights tobecarriedoutandprovidesareal-time attitude of flight. The MP2128g is composed of an electroniccircuitboardandGroundControl Software (GCS,HORIZONmp).Aradiomodem allows the flight attitude to be transmitted to the GroundControl Station (GCS). The HORIZON software provides flight path andcurrent sensor values in real-time. Therefore, apart from the take-offand landingoperationswhichmust be conductedmanually, due to theinsufficient GPS height accuracy, it is possible to perform autonomousflights. Theflight canbemonitored in real timebyanoperator throughthe GCS. At the end of the flight, the images and the position/attitudedata are downloaded, and then processed in the subsequent steps.

Different photogrammetric flights were planned and realized inthe Augusta Bagiennorum area for both the Theatre and theAmphitheatre areas: a low altitude flight (elevation of 60 m, GSD of2 cm) for theTheatre andahighaltitudeone (elevationof 100m,GSDof 4 cm) for the Amphitheatre. A topographic survey was performedin the two areas, in order to generate a network ofGCPs, adopting theWGS84-ETRS2000 datum (UTMprojection) as the reference system.The GCPs are represented by natural and manmade target points.The target positionwas planned according to the flight specificationand the accessibility of the surrounding areas of the archaeologicalsites. The survey operations were carried out with a GPS LeicaRX1200 receiver in RTK multi reference station mode, while somenatural points were surveyed with the Leica Smart-Station.

The UAV was remotely driven by a pilot from the ground, as theautopilot had someproblems in followinga straight linedue towind.However, the presence of the autopilot allowed the position andattitude data to be logged for post-processing purposes and for real-time monitoring. Unfortunately, the image acquisition of the areasdid not provide the stereoscopic coverage that was designed in theflight plan. This was mainly due to the difficulty the pilot encoun-tered when trying to follow the flight course and keep the flightaltitude. An automatic acquisition of six images with a medium 60%

Fig. 13. High altitude flight over the Fontana D’Ercole: results of the MIGC3 and S2MF algorithms (left) and TIN (right).

F. Chiabrando et al. / Journal of Archaeological Science 38 (2011) 697e710 705

stereoscopic coverage and a relative altitude of 100 m was carriedout for theAmphitheatre (Fig. 7). Only three images fromtheTheatreflights were suitable for a photogrammetric processing. They wereacquired at different flight altitudes (from 60m to 70m) and in non-normal conditions. Unfortunately, the trees next to the ruins lead tosome problems in the maneuverability of the UAV.

4.2. Data acquisition e Reggia di Venaria Reale test site

Themini-helicopter Voyager G8 RR (Chiabrando et al., 2008) wasused in the second test area. Unlike the Pelican UAV, this platform isnot capable of performing photogrammetric flights in an automaticway. In fact, this version is a modified version of the original modelwhich was equipped with custom-made components so that it canbe used for photogrammetric purposes. No GPS or IMU have beeninstalled on it up to now, therefore a human operator pilots it usingremote radio controls, and there is no possibility of performingautonomous flights. The mini-helicopter is equipped with a videocamera for navigation purposes, a pressure altitude transducer anda custom-made remote-controlledmechanical system, positioned inthe lower part of the helicopter to carry a camera for image acqui-sition. This mechanical system is able to rotate around two axes, andit is therefore possible to orient the camera in different directions

Fig. 14. Low altitude flight over the Fontana D’Ercole: results

during the flight, a Nikon Coolpix 8400 camera was used in thiswork for image acquisition and remotely-controlled shots weretaken; moreover during mini-helicopter flight, it is possible to seethe area that is being imaged and to arrange the flight attitude inorder to acquire the area to be surveyed.

Some images of the Fontana D’Ercole were only acquired forphotographic documentation purposes, while several stereoscopicimages were acquired for the photogrammetric process (Fig. 8 left).Five images were taken at a flight altitude of 50 m (high flightaltitude) and twenty images at a flight altitude of 15 m (low flightaltitude); a large number of GCPs was necessary in order to performthe photogrammetric process, for this reason, forty targets werehomogeneously positioned on the area to be surveyed (Fig. 8 right).The position of the targets was determined using a total station andreferring to a local coordinate system fixed to reference points thatalready existed in the area that was surveyed.

4.3. Data processing e Augusta Bagiennorum test site

Two aerial triangulations were performed on the Theatre andthe Amphitheatre using the Leica Photogrammetric Suite 9.2 soft-ware, three images were oriented over the Theatre using 9 groundcontrol points and 6 check points; in the case of the Amphitheatre

of the MIGC3 and S2MF algorithms (left) and TIN (right).

Fig. 15. DSM and derived orthophoto of the Amphitheatre.

Table 7Statistical accuracy check of the Amphitheatre orthophoto.

sCP,E,N[m] 0.0295CP[m] 0.05RMSEOP[m] 0.10CE95OP[m] 0.18CE95EN [m] 0.19TEN 1:500 quick [m] 0.26TEN 1:500 ordinary [m] 0.17

F. Chiabrando et al. / Journal of Archaeological Science 38 (2011) 697e710706

four images were oriented using 13 GCPs and 7 CPs, the achievedstandard deviations of the GCPs and CPs (reported in Table 5) showthe high quality of the bundle block adjustment.

The selected images were processed with the algorithmsimplemented by the authors. First, the images were pre-processedin order to remove the geometrical distortions and to enhance the

Fig. 16. 2D drawing of

radiometric content. Then, the A2SIFT algorithm and the robustrelative orientation were performed with the Least Median Squaremethod on the stereo pairs for the automatic extraction of anapproximate DSM.

More than 1000 points were extracted from the five stereo pairsfor the Amphitheatre. The automatic extraction of the DSM wasthen carried out with the aforementioned procedure. Two imageswere considered as the reference images in the MIGC3 procedure.The automatic point extraction, the edge extraction and the S2MFwere performed for each set of images. Fig. 9 shows the result of theDSM extraction in the Bene Vagienna Amphitheatre area. The rateof points and edgesmatched by theMIGC3 is almost 40%. This resultis due to the low stereoscopic coverage of the area, and the poortexture of the images, especially of the ploughed fields and of thesown land. The high discontinuities of the houses near thearchaeological site and the lack of an accurate DSM also reducethe performance of the image matching technique. Nevertheless,

the Amphitheatre.

Fig. 17. Theatre: DSM (left), orthophotho (centre) and 2D drawing (right).

Fig. 18. High altitude flight over the Fontana d’Ercole: orthophotho (left) and 2D drawing (right).

F. Chiabrando et al. / Journal of Archaeological Science 38 (2011) 697e710 707

the rate of points affected by gross errors is reduced to 20%.Therefore, the number of points and knots correctly matched (morethan 100,000) allows a DSM to be extracted with a mean plani-metric step of 0.5 m. The TIN was regularized using the Krigingalgorithm implemented in the ESRI ArcGis software, the final DSM(Fig. 10) still suffered from some residual errors, especially in themaize field and near the discontinuities due to the buildings, somanual editing was required.

The image processing and the DSM generation of the Theatreareawere carried out in the sameway as for the Amphitheatre case.The extraction of the homologous points with A2SIFT led to theproduction of an approximate DSM of the area, with more than1000 points (Fig. 11), good results were obtained thanks to thetriple stereoscopic coverage of the Theatre ruins and the goodapproximation of the initial DSM. More than 155,000 points/knotswere extracted, which allowed TIN to be obtained with a mean

Table 8Statistical accuracy check of the Theatre orthophoto.

sCP,E,N[m] 0.02CE95CP[m] 0.05RMSEOP[m] 0.09CE95OP[m] 0.14CE95EN [m] 0.15TEN 1:500 quick [m] 0.26TEN 1:500 ordinary [m] 0.17

planimetric step of about 0.15 m. The final TIN (Fig. 12) was regu-larized with the Kriging technique (0.10 m step).

4.4. Data processing e Reggia di Venaria Reale test site

Two approaches were followed for the Fontana D’Ercole case:three images from the high altitude flight were employed toproduce a 1:200 representation (22 ground control points and 10check points), while five images from the lower altitude flight wereused for the generation of a Solid True OrthoPhoto of a portion ofthe Fontana D’Ercole, the results of the aerial triangulation (highflight altitude) are reported in Table 6, the achieved standarddeviations of the GCPs and CPs show the high quality of the bundleblock adjustment.

The DSM generation was carried out as in section 4.3, twodifferent DSMs were realized, one for each of the aforementionedsets of images, Fig. 13 shows the results obtained using the highflight altitude images: a very high number of points/knots wereextracted over the entire surveyed area, with a satisfactory pointdensity per square meter.

The high discontinuities of the object in the low altitude flight(Fig. 14) caused some problems in the automatic 3D point/edgeextraction, especially in the areas near the walls, where there wasa high rate of occlusion. In fact, only 28.3% of the points extracted bythe Forstner/Canny operators werematched and about 50% of themwere gross errors. Nevertheless, a high number of points/knots

Fig. 19. Low altitude flight over the Fontana d’Ercole: orthophotho (left) and 2D drawing (right).

F. Chiabrando et al. / Journal of Archaeological Science 38 (2011) 697e710708

were extracted. The final TIN had a mean planimetric step of0.04 m. The TIN was then regularized and manually edited in orderto produce a suitable DSM for the STOP production.

4.5. Orthophotos and digital plotting e Augusta Bagiennorum testsite

Different testswere performedon the acquired images in order toobtain reliable metric products derived from the photogrammetricprocess that would be useful for archaeological documentation.

In the case of the Amphitheatre, the orthophoto was producedusing the DSM without any editing (Fig. 15 left), in order to checkthe performances of a quick orthophoto production (Fig. 15 right),the pixel size of the orthophoto is 0.05 m in order to obtain a mapscale ranging from 1:200 to 1:500. The accuracy of the final productwas tested according to the CISIS Italian regulations (Brovelli et al.,2009), which are consistent with the ISO TC211 rules (www.isotc211.org), using several check points and performing a statis-tical analysis, as shown in Table 7, the circular error at 95% ofprobability (CE95EN) is lower than the tolerance limit (TEN) of the1:500 map scale for ordinary orthophotos.

A digital plotting of the Amphitheatre area was also realized(using the PRO600 software) in order to produce a traditional 2Ddrawing for documentation purposes (Fig. 16), the same productswere produced for the Theatre (Fig. 17), the accuracy test results are

Table 9Time-consuming comparison for the two tests (two operators for the topographicsurvey, one operator for the other phases).

Processing steps AugustaBagiennorumtest site(Theatre)[hours]

AugustaBagiennorumtest site(Amphitheatre)[hours]

FontanaD’Ercoletest site e

high flight[hours]

FontanaD’Ercoletest site e

low flight[hours]

Topographic survey 7 6 6Image Acquisition 2 2 2 1Image pre-processing 0.5 0.5 0.5 0.5Aerial triangulation 4 4 4 3DSM generation 4 4 4 3DSM editing e 1 e 2Digital Plotting

and editing8 8 8 6

Orthophotoproduction

2 2 2 2

Platform cost 25,000 Euros 8000 Euros

reported in Table 8, and they confirm the suitability of the ortho-photos for a 1:500 map scale.

4.6. Orthophotos, solid true OrthoPhoto and digital plotting e

Reggia di Venaria Reale test site

A different approach was followed in the case of the FontanaD’Ercole. The high altitude flight images were employed to obtainan orthophoto and a digital plotting at a 1:200 scale map, Fig. 18shows the orthophoto and the traditional drawing; moreovera Solid True OrthoPhoto was created using the images from the lowaltitude flight and the manually edited DSM, five images wereresampled and merged using the true orthoprojection approachimplemented in the SirIo software. The final STOP was suitable fora 1:100 map scale representation (Fig. 19).

The accuracy of both orthophotos was evaluated, as in theformer test, considering several control points displaced onthe whole area: the circular error (CE95EN) was compared to thetolerances limits (TEN) and showed the suitability of the higherflight for a 1:200 map scale and the suitability of the higher flightfor a 1:100 map scale.

5. Conclusions and future work

The use of UAV and RPV systems for archaeological documen-tation purposes has been reported in this paper. The tests carriedout with the Pelican UAV and the remote-controlled mini-heli-copter have underlined the suitability of mini-UAV platforms forthe production of orthophotos and digital plottings, which can bevery useful for archaeological documentation purposes for mediumand large-scale maps. The main advantages of these systems, forarchaeological surveys, are the low-cost and the quickness of thedata acquisition at a large scale, even in areas with small exten-sions. Depending on the data acquisition devices and the flightheight, it is possible to obtain metrically correct products with scalemaps ranging from 1:500 to 1:100, a level which could be suitablefor many archaeological surveys. The availability of the rigorousspatial and radiometric information provided by the orthophotosand Solid True Orthophotos allows detailed analysis (3Dmeasurements and photo-interpretations) to be performed ina quick and easy way. The photogrammetric process can be per-formed in a semi-automatic way using the feature extraction andimage matching techniques proposed in this paper. A multi-imageacquisition allows the potential of the MIGC3 and the S2MF to be

F. Chiabrando et al. / Journal of Archaeological Science 38 (2011) 697e710 709

exploited for the automatic extraction of the DSM, which isnecessary for the orthophoto production. The experimental resultsunderline the good performances of the implemented algorithms,especially in DSM extraction and filtering phases. A comparison oftime and costs for the two test sites is reported in Table 9: the timerefers to two operators working on the topographic survey and oneoperator working on all the other phases.

If the two platforms employed in this work are compared, it ispossible to see that the Pelican UAV can automate the photogram-metric process, thanks to the autopilot equipment, while the mini-helicopter needs to be piloted by a human operator. Nevertheless,neither of these systems allows a direct geo-referencing of theimages, as the GNSS/IMU equipment is not sufficiently accurate.

The image quality is therefore influenced by the vehicletypology: in the performed tests, the quality of the images acquiredby themini-helicopter was affected by some drag effects, due to thelack of a camera stabilization system. However, the mini-helicopterpresents more flexibility in the image acquisition than the fixed-wing platform, since it is possible to orient the camera in differentdirections during the flight, thanks to a custom-made remotely-controlled mechanical system positioned in the lower part of thehelicopter. Finally, while the Pelican UAV needs about 20 m to take-off and land, the mini-helicopter needs no more than few meters,and could therefore be the only possible solution in the case oflimited space. Both platforms suffer from environmental condi-tions, such as strong gusts of wind that can yaw them from theircourses. There are some limits in both cases that have to beconsidered during survey planning, depending on the specificapplication.

In the future, the performances of these non-conventionalsystems will surely be increased, thanks to the integration of moreaccurate micro-electromechanical systems (MEMS), such as GNSS/IMU units, for automatic navigation, and this will enlarge theirapplicability for archaeological survey and documentation purposes.

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