Discernibility of Burial Mounds in High-Resolution X-Band SAR Images for Archaeological Prospections in the Altai Mountains

remote sensing

Letter Discernibility of Burial Mounds in High-Resolution X-Band SAR Images for Archaeological Prospections in the Altai Mountains

Timo Balz 1,2,*, Gino Caspari 3, Bihong Fu 4 and Mingsheng Liao 1,2

1 State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China; [email protected] 2 Collaborative Innovation Center for Geospatial Technology, Wuhan University, Wuhan 430072, China 3 Institute of Archaeology, University of Hamburg, Hamburg 20146, Germany; [email protected] 4 Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; [email protected] * Correspondence: [email protected]; Tel.: +86-27-6877-9986

Academic Editors: Kenneth L. Kvamme, Zhong Lu, Richard Gloaguen and Prasad S. Thenkabail Received: 30 June 2016; Accepted: 24 September 2016; Published: 30 September 2016

Abstract: The Altai Mountains are a heritage-rich archaeological landscape with monuments in almost every valley. Modern nation state borders dissect the region and limit archaeological landscape analysis to intra-national areas of interest. Remote sensing can help to overcome these limitations. Due to its high precision, Synthetic Aperture Radar (SAR) data can be a very useful tool for supporting archaeological prospections, but compared to optical imagery, the detectability of sites of archaeological interest is limited. We analyzed the limitations of SAR using TerraSAR-X images in different modes. Based on ground truth, the discernibility of burial mounds was analyzed in different SAR acquisition modes. We show that very-high-resolution TerraSAR-X staring spotlight images are very well suited for the task, with >75% of the larger mounds being discernible, while in images with a lower spatial resolution only a few large sites can be detected, at rates below 50%.

Keywords: SAR; archaeology; object detection; Altai; spatial resolution

1. Introduction The Altai Mountains have been an important transitional zone in Central Asia for thousands of years. Today, the region is transected by the borders of China, Kazakhstan, Russia, and Mongolia, as shown in Figure1. It is also situated at the center of Eurasia’s four major steppe zones with the Mongolian steppe to its east, the pastures of Kazakhstan and Russia to its west, the forested taiga of Siberia in the north, and the dry arid landscapes of Xinjiang to the south [1]. The region is one of Central Asia’s richest archaeological areas, with some of the oldest archaeological sites in Siberia dating back to 430,000 BP (before present) [2] and an abundant Bronze and Iron Age heritage. In this vast, rugged terrain, most valleys contain a large number of cultural heritage sites [1,3]. Ideally, the region should be studied as a whole in order to understand this highly complex heritage and its significance in the larger context of Central Asia. However, militarized border zones, language barriers, and differing research cultures make transnational cooperation on field projects extremely difficult. Under these circumstances, remote sensing can be an invaluable tool for the analysis of the archaeological landscape, because it (1) can cover large areas; (2) is not limited by national borders; and (3) can provide a basis for joint analysis of the larger region.

Remote Sens. 2016, 8, 817; doi:10.3390/rs8100817 www.mdpi.com/journal/remotesensing Remote Sens. 2016, 8, 817 2 of 10

Remote sensing takes the role of a supportive tool in archaeological surveys and excavations. Both optical [4] and Synthetic Aperture Radar (SAR) [5] data were used for our fieldwork in summer 2015. Due to its weather independence and high geo-location accuracy, we found high-resolution SAR data to be a useful tool for planning archaeological prospections, for example when identifying Remoteareas Sens. 2016of interest, 8, 817 and planning the logistics of surveys. In recent years, thanks to its wider availability2 of 10 and higher spatial resolution, SAR is becoming more commonly used in archaeology (see, e.g., [6–9]).

FigureFigure 1. 1.The The area area of of interestinterest in the the Altai Altai Mountains. Mountains.

A high spatial resolution is necessary in order to detect archaeological features. However, how Remotehigh is the sensing spatial resolution takes the we role need of afor supportive archaeological tool prospections in archaeological in the Altai surveys area? Since and we excavations. need Bothto optical cover [a4 large] and area Synthetic of interest Aperture at a high Radar resolution, (SAR) the [5 ]tradeoff data were between used spatial for our coverage fieldwork and spatial in summer 2015.resolution Due to its in weather SAR acquisition independence becomes and an important high geo-location question.accuracy, we found high-resolution SAR data to beIn a usefulthis paper, tool forwe planninganalyze the archaeological spatial and prospections,radiometric resolutions for example necessary when identifyingfor effective areas of interestidentification and planning of clusters the of logistics larger (e.g., of surveys. >10 m diameter) In recent burial years, mounds thanks in tothe its Altai wider Mountains. availability We and higherused spatial various resolution, TerraSAR-X SAR (TSX) is becoming images in more different commonly acquisition used modes in archaeology and spatial (see, resolutions e.g., [6– 9to]). Adetermine high spatial the spatial resolution resolution is necessary required to in clea orderrly identify to detect burial archaeological mounds of different features. sizes. However, how In Section 2, we describe the different types of burial mounds and other structures of high is the spatial resolution we need for archaeological prospections in the Altai area? Since we need archaeological interest relevant for our study, which are archaeological structures with a minimum to cover a large area of interest at a high resolution, the tradeoff between spatial coverage and spatial dimension of at least one square meter, since we cannot identify single stone steles from remote resolutionsensing in data. SAR In acquisition Section 3, the becomes test data an and important our methodology question. are introduced. In Section 4, we present Inand this discuss paper, the results we analyze of our analysis the spatial and finally and we radiometric state our conclusions. resolutions necessary for effective identification of clusters of larger (e.g., >10 m diameter) burial mounds in the Altai Mountains. We used2. Burial various Mounds TerraSAR-X in the Altai (TSX) Region images in different acquisition modes and spatial resolutions to determineIn the thespatial context resolutionof remote sensing–supported required to clearly landsc identifyape archaeology, burial mounds we focused of different on larger sizes. objects Inand Section their spatial2, we distribution. describe theWe differentare especially types interested of burial in Scythian mounds kurgans and, otherSaka kurgans structures, and of archaeologicalogradkas (see interest Figure 2). relevant for our study, which are archaeological structures with a minimum dimensionWe of define at least a Scythian one square kurgan meter, as a burial since wemound, cannot dating identify to the single Iron Age, stone built steles of stones from with remote a light sensing data.central In Section depression3, the testif it has data not and been our robbed, methodology often lining are up introduced. in an approximate In Section north-south4, we presentdirection and discusswith the others results of its of ourkind. analysis Scythian andkurgans finally are wetypically state between our conclusions. 5–15 m in diameter, but smaller and larger monuments can also be found. We define a Saka kurgan as a large earthen mound with a circular 2. Burialditch, Moundsalso dating in to the the Altai Iron RegionAge. The Saka kurgans are typically between 10–60 m in diameter, but again there are monuments outside this range. An ogradka is a mound-like accumulation of stones Inwith the a contextrectangular of remoteenclosure sensing–supported of big stone slabs inside landscape and often archaeology, (but not necessa we focusedrily) a single on larger stele or objects and their spatial distribution. We are especially interested in Scythian kurgans, Saka kurgans, and ogradkas (see Figure2). We define a Scythian kurgan as a burial mound, dating to the Iron Age, built of stones with a light central depression if it has not been robbed, often lining up in an approximate north-south direction with others of its kind. Scythian kurgans are typically between 5–15 m in diameter, but smaller and larger monuments can also be found. We define a Saka kurgan as a large earthen mound with a circular ditch, also dating to the Iron Age. The Saka kurgans are typically between 10–60 m in diameter, but again there are monuments outside this range. An ogradka is a mound-like accumulation of stones with a rectangular enclosure of big stone slabs inside and often (but not necessarily) a single stele or array Remote Sens. 2016, 8, 817 3 of 10

Remote Sens. 2016, 8, 817 3 of 10 of standing stones, dating to the Turkic period. Ogradkas are smaller, with a width and height of only a fewarray meters of and,standing as we stones, will showdating below, to the Turkic are too period. small toOgradkas be clearly are smaller, identified with from a width contemporary and height SAR remotelyof only sensed a few data. meters and, as we will show below, are too small to be clearly identified from contemporaryAs other archaeological SAR remotely features, sensed data. such as stone circles, standing stones, stone concentrations, etc., As other archaeological features, such as stone circles, standing stones, stone concentrations, etc., are often in close proximity to these larger structures, the detection of these three types can provide are often in close proximity to these larger structures, the detection of these three types can provide sufficient information for a preliminary landscape archaeological analysis and for survey planning. sufficient information for a preliminary landscape archaeological analysis and for survey planning. Furthermore,Furthermore, these these structures structures are are also also oftenoften spatiallyspatially clustered clustered so so the the detection detection of large of large clusters clusters may may be sufficientbe sufficient for for wide-area wide-area overview overview analysis analysis regarding, regarding, e.g.,e.g., thethe spatialspatial patte patternsrns of of these these structures structures in Centralin Central Asia. Asia.

(a) (b)(c)

Figure 2. (a) Example of a Scythian kurgan lining up with others of its kind; (b) Example of a Saka Figure 2. (a) Example of a Scythian kurgan lining up with others of its kind; (b) Example of a Saka kurgan kurgan (left side) with a clearly visible ditch; (c) Example of a Turkic ogradka. The scale bar seen in (left side) with a clearly visible ditch; (c) Example of a Turkic ogradka. The scale bar seen in photos photos (a) and (c) is 50 cm long. (a) and (c) is 50 cm long. 3. Data Processing and Methodology 3. Data Processing and Methodology 3.1. Data Used in Our Analysis 3.1. Data Used in Our Analysis For the experiments described in this paper we used six TSX images. In Table 1, we listed the detailsFor the of experimentsthe images. TSX described offers different in this paperacquisition we used modes. six TSXFor our images. experiments, In Table we1, weused listed TSX the detailsstripmap of the (SM) images. data, TSX TSX spotlight offers different (SL) data, acquisition and TSX staring modes. spotlight For ourdata experiments,(ST). The stripmap we usedmode TSX stripmap(SM) is (SM) the standard data, TSX acquisition spotlight mode (SL) of data, a SAR and sensor TSX staringand in the spotlight case of TSX data offers (ST). an The approximately stripmap mode (SM)3 ism theresolution. standard In acquisitionthe spotlight mode modes of (e.g., a SAR SL sensorand ST), and the inacquisition the case oftime TSX is offersincreased an approximatelyby shifting 3 mthe resolution. squint angle In the of spotlightthe sensor modes from slightly (e.g., SL forward-looking and ST), the acquisition to slightly timebackward-looking is increased byduring shifting theacquisition. squint angle This of increases the sensor the from acquisition slightly time forward-looking and is used to enhance to slightly the spatial backward-looking resolution in the during azimuth direction of the sensor, allowing for an increased resolution of approximately 1.5 m in the acquisition. This increases the acquisition time and is used to enhance the spatial resolution in the standard spotlight mode (SL). In the staring spotlight mode, this acquisition time is further increased, azimuth direction of the sensor, allowing for an increased resolution of approximately 1.5 m in the leading to an approximately 0.25 m resolution in azimuth, and due to the larger bandwidth in the standardrange spotlightof 300 MHz, mode compared (SL). In to thethe staring150 MHZ spotlight in SL and mode, SM, a thisrange acquisition resolution timeof approximately is further increased, 1 m leadingcan be to achieved. an approximately We therefore 0.25 assumed m resolution that we in azimuth,can get the and highest due todiscernibility the larger bandwidthin the staring in the rangespotlight of 300 mode MHz, images, compared followed to the by 150 the MHZspotlight in SLmode and images. SM, a We range expected resolution the results of approximately from the 1 mstripmap can be achieved. mode images We thereforeto be the least assumed satisfac thattory weduecan to their get thelower highest spatialdiscernibility resolution. in the staring spotlight mode images, followed by the spotlight mode images. We expected the results from the stripmapTable mode 1. TSX images images to beused the in leastthe experiment, satisfactory with due reso tolution their given lower as spatialground-range resolution. resolution by azimuth resolution and incidence angle (Inc. angle) at the scene center (ST = staring spotlight mode, TableSL 1.= spotlightTSX images mode, used SM = in stripmap the experiment, mode). with resolution given as ground-range resolution by azimuthSatellite resolution Mode and incidence Acquisition angle (Inc. Date angle) at theOrbit scene center Resolution (ST = staring (m) spotlight Inc. Angle mode, SLTSX-1 = spotlight mode, ST SM = stripmap 16 September mode). 2015 descending 0.91 × 0.23 39.8° TSX-1 SL 15 July 2015 ascending 3.03 × 1.60 22.7° TSX-1Satellite SL Mode 14Acquisition July 2015 Date ascending Orbit Resolution 1.57 × 1.60 (m) Inc. 48.4° Angle TSX-1TSX-1 SL ST 1612 SeptemberJuly 2015 2015 descending descending 1.83 0.91 ×× 1.600.23 39.9° 39.8◦ ◦ TSX-1TSX-1 SL SL 9 July 15 July 2015 2015 ascending ascending 1.94 3.03 ×× 1.601.60 37.3° 22.7 TSX-1 SL 14 July 2015 ascending 1.57 × 1.60 48.4◦ TSX-1TSX-1 SM SL 5 June 12 July 2014 2015 descending descending 2.64 1.83 ×× 3.301.60 26.4° 39.9◦ TSX-1 SL 9 July 2015 ascending 1.94 × 1.60 37.3◦ TSX-1 SM 5 June 2014 descending 2.64 × 3.30 26.4◦

Remote Sens. 2016, 8, 817 4 of 10

From our ground survey in summer 2015, we collected survey information from 842 monuments that have a spatial extension of more than one meter. As we can see from Table2, most of the structures have a diameter below 10 m and are therefore difﬁcult to identify clearly in SAR images. However, the remaining 152 objects with more than a 10 m diameter should be identiﬁable.

Table 2. Distribution of the diameters of the archaeological structure in the test area.

Number of Objects Diameter ≥ 40 m 8 Diameter ≥ 30 m and <40 m 14 Diameter ≥ 20 m and <30 m 38 Diameter ≥ 10 m and <20 m 92 Diameter ≥ 1 m and <10 m 690

3.2. Geo-Coding Considerations and Pre-Processing TSX offers a very precise geo-referencing capability, as the orbit is well-known [10]. The accuracy in azimuth depends mainly on the orbit accuracy and timing error and can reach below one decimeter of absolute precision. In range, the accuracy depends on the atmospheric path delay of the signal as well as on various other error sources (see, e.g., [10,11]). Including corrections for these errors, an absolute position accuracy of below one decimeter in range and azimuth can be achieved for TSX images acquired in a stereo configuration [12]. Using only the path delay information included in the TerraSAR-X header files, we can achieve a precision of <0.5 m, based on our experiments with TSX data in Wuhan [13]. To be able to geo-correct the data accordingly, we use single-look complex (SLC) data for the geo-referencing and in the following experiments. Using a corner reflector, we set up in the test area during our ground survey, we corrected for systematical errors in the GPS measurements. As it turns out, although just a handheld GPS was used, the measurements were quite accurate, and after correction for the geoid, the difference between the TerraSAR-X estimated coordinates and the GPS coordinates was <1 m, which was acceptable for our experiments.

3.3. Transforming the Survey Results into the SAR Image Coordinate System In our experiment we were interested in the discernibility of archaeological features in SAR images. As such, we wanted the SAR images to be undisturbed to allow a better analysis of the detectability without introducing additional disturbances from resampling the data. Therefore, we transformed the survey results into the SAR coordinate system instead of resampling the SAR images to a geographic or local coordinate system. As discussed previously, the coordinates from our ground survey were quite good, but there are still shifts and errors; we will analyze these sources of uncertainty in detail in Section4. After transforming the coordinates in the radar coordinate system based on the Range-Doppler model using the height information from the GPS measurements, and including the dry-atmosphere path delay information from the TerraSAR-X headers (see [13]), we marked Saka kurgans with a red rectangle, Scythian kurgans with a green rectangle, ogradkas in purple, undatable mounds in yellow and all other objects in cyan.

4. Analyzing the Detectability of Archaeological Structures

4.1. Very High Resolution TSX Staring Spotlight Images (ST) Using the TerraSAR-X staring spotlight mode, we used four-time multi-looking in azimuth to reduce the speckle effect before analyzing the data. This resulted in almost square pixels with a pixel size of approximately 0.9 m by 0.9 m. As we can see in Figure3, we can clearly identify large Saka kurgans in the TSX ST images, especially when they are clustered. Remote Sens. 2016, 8, 817 5 of 10

However, not all Saka kurgans are clearly visible and there is also an increased likelihood of confusing archaeological structures with recent soil markings from husbandry, as can be seen in Figure 4. Furthermore, large Scythian kurgans can be identified in TSX ST images, but generally Remoteogradkas Sens. 2016 (in, 8 ,purple) 817 are too small to be clearly identified even in TSX ST images, as we can see in5 of 10 Figure 5. Remote Sens. 2016, 8, 817 5 of 10

Remote Sens. 2016, 8, 817 5 of 10 However, not all Saka kurgans are clearly visible and there is also an increased likelihood of confusingHowever, archaeological not all Saka structures kurgans arewith clearly recent visible soil markings and there from is also husbandry, an increased as can likelihood be seen inof Figureconfusing 4. Furthermore,archaeological large structures Scythian with kurgans recent can soil be markings identified from in TSXhusbandry, ST images, as can but be generally seen in ogradkasFigure 4. (in Furthermore, purple) are toolarge small Scythian to be kurgans clearly canident beified identified even in inTSX TSX ST STimages, images, as webut cangenerally see in Figureogradkas 5. (in purple) are too small to be clearly identified even in TSX ST images, as we can see in Figure 5.

Figure 3. Cluster of Saka kurgans in the TSX ST image from 16 September 2015 (SAR image © DLR, Saka kurgans Figure2015). 3. Cluster (Saka kurgans of = red, Scythianin the kurgans TSX = ST green, image ogradkas from = 16 purple, September undatable 2015 mounds (SAR image = yellow,© DLR, 2015).and (Saka all other kurgans objects= red, = cyan).Scythian kurgans = green, ogradkas = purple, undatable mounds = yellow, and all other objects = cyan).

However, not all Saka kurgans are clearly visible and there is also an increased likelihood of confusing archaeological structures with recent soil markings from husbandry, as can be seen in Figure 3. Cluster of Saka kurgans in the TSX ST image from 16 September 2015 (SAR image © DLR, Figure4. Furthermore, large Scythian kurgans can be identiﬁed in TSX ST images, but generally ogradkas 2015). (Saka kurgans = red, Scythian kurgans = green, ogradkas = purple, undatable mounds = yellow, (in purple)Figure are too3. Cluster small of to Saka be kurgans clearly in identiﬁed the TSX ST even image in from TSX 16 ST September images, 2015 as we(SAR can image see © in DLR, Figure 5. and2015). all ( Sakaother kurgans objects = cyan).red, Scythian kurgans = green, ogradkas = purple, undatable mounds = yellow, and all other objects = cyan).

Figure 4. Saka kurgans and a non-archaeological structure (marked with the yellow arrow) in the TSX ST image from 16 September 2015 (SAR image © DLR, 2015). (Saka kurgans = red, Scythian kurgans = green, ogradkas = purple, undatable mounds = yellow, and all other objects = cyan).

Figure 4. Saka kurgans and a non-archaeological structure (marked with the yellow arrow) in the TSX Figure 4. Saka kurgans and a non-archaeological structure (marked with the yellow arrow) in the TSX STFigure image 4. Sakafrom kurgans 16 September and a non-archaeological 2015 (SAR image ©structure DLR, 2015). (mar ked(Saka with kurgans the yellow= red, Scythianarrow) in kurgans the TSX = ST image from 16 September 2015 (SAR image © DLR, 2015). (Saka kurgans = red, Scythian kurgans = green,ST image ogradkas from =16 purple, September undatable 2015 (SARmounds image = yellow, © DLR, and 2015). all other (Saka objects kurgans = =cyan). red, Scythian kurgans = green, ogradkas = purple, undatable mounds = yellow, and all other objects = cyan). green, ogradkas = purple, undatable mounds = yellow, and all other objects = cyan).

Figure 5. Cluster of Saka kurgans, Scythian kurgans and ogradkas in the TSX ST image from 16 September 2015 (SAR image © DLR, 2015). (Saka kurgans = red, Scythian kurgans = green, ogradkas = purple, undatable mounds = yellow, and all other objects = cyan).

Figure 5. Cluster of Saka kurgans, Scythian kurgans and ogradkas in the TSX ST image from 16 September 2015Figure (SAR 5. Cluster image of © Saka DLR, kurgans 2015)., Scythian (Saka kurgans kurgans =and red, ogradkas Scythian in thekurgans TSX ST= green,image fromogradkas 16 September = purple, Figure 5. Cluster of Saka kurgans, Scythian kurgans and ogradkas in the TSX ST image from 16 September undatable2015 (SAR mounds image © = yellow,DLR, 2015). and all(Saka other kurgans objects = = red, cyan). Scythian kurgans = green, ogradkas = purple, 2015 undatable (SAR image mounds© DLR, = yellow, 2015). and (allSaka other kurgans objects= = red,cyan).Scythian kurgans = green, ogradkas = purple, undatable mounds = yellow, and all other objects = cyan).

Remote Sens. 2016, 8, 817 6 of 10

Remote Sens. 2016, 8, 817 6 of 10 Remote Sens. 2016, 8, 817 6 of 10 4.2. TSX Spotlight Images (SL) 4.2. TSX4.2. TSXSpotlight Spotlight Images Images (SL) (SL) In the TSX spotlight mode (SL) images, the spatial resolution in azimuth is reduced to 1.6 m. In In the TSX spotlight mode (SL) images, the spatial resolution in azimuth is reduced to 1.6 m. In this instance,In wethe didTSX notspotlight use anymode multi-looking (SL) images, the to spatial keep resolution the full spatial in azimuth resolution. is reduced As to we 1.6 canm. In see from this instance,this instance, we wedid did not not use use any any multi-looking multi-looking toto keep thethe full full spatial spatial resolution. resolution. As weAs canwe seecan from see from the images shown in Figure6, the cluster of Saka kurgans shown in Figure3 can also be discerned in the imagesthe images shown shown in Figurein Figure 6, 6,the the cluster cluster of of SakaSaka kurgans shown shown in in Figure Figure 3 can 3 can also also be discerned be discerned in in thethe SL SL images,the images, SL images, but but appears but appears appears much much much less less less clear. clear. clear.

(a) (b)

Figure 6. Cluster of Saka kurgans in TSX SL images acquired on 9 July 2015 (a) and 15 July 2015 (b); Figure 6. Cluster of Saka(a)kurgans in TSX SL images acquired on 9 July 2015(b) (a) and 15 July 2015 (b); (SAR images © DLR, 2015). (Saka kurgans = red, Scythian kurgans = green, ogradkas = purple, undatable (SARFigure imagesmounds 6. Cluster© =DLR, yellow, of 2015). Saka and kurgansall (Saka other kurgans objectsin TSX = =SL cyan). red, images Scythian acquired kurgans on 9= July green, 2015ogradkas (a) and= 15 purple, July 2015 undatable (b); mounds(SAR images = yellow, © DLR, and all2015). other (Saka objects kurgans = cyan). = red, Scythian kurgans = green, ogradkas = purple, undatable moundsThe =discernibility yellow, and allalso other seems objects to depend = cyan). on the orbit and the incidence angle. The Saka kurgans in Thethe discernibility image acquired also on seems9 July 2015, to depend as shown on in the Figure orbit 6a, and from the an incidence ascending angle.orbit with The a Saka37.3° kurgans incidence angle at the scene center, are harder to detect than in the image from 15 July 2015, acquired in the imageThe discernibility acquired on also 9 Julyseems 2015, to depend as shown on the in orbit Figure and6a, the from incidence an ascending angle. The orbit Saka withkurgans a 37.3 in ◦ the imagefrom an acquired ascending on orbit 9 July with 2015, a 22.7° as incidence shown angle,in Figure as shown 6a, from in Figure an ascending6b, although orbit this imagewith ain 37.3° incidence6a has angle a much at the smaller scene ground-range center, are harderresolution. to detect than in the image from 15 July 2015, acquired incidence angle at the scene center, are harder to detect than in the image from 15 July 2015, acquired from an ascendingHowever, orbit even withthe large a 22.7 kurgan◦ incidence, shown in angle,Figure 5, as is shown hard to insee Figure in the SL6b, images, although as shown this imagein in from an ascending orbit with a 22.7° incidence angle, as shown in Figure 6b, although this image in Figure6Figurea has a7a. much The visibility smaller is ground-range much better in resolution. Figure 6b, the image acquired on 14 July 2015 from an 6a has a much smaller ground-range resolution. However,ascending even orbit thewith large a 48.4°kurgan incidence, shown angle, incompar Figureed to5, the is hardimage to from see a indescending the SL images, orbit with as a shown 39.9°However, incidence even angle, the largeshown kurgan in Figure, shown 7a. in Figure 5, is hard to see in the SL images, as shown in in FigureFigure 77a.a. TheThe visibilityvisibility is much better better in in Figure Figure 6b,6b, the the image image acquired acquired on on 14 14 July July 2015 2015 from from an an ◦ ascendingascending orbit orbit with with a a 48.4 48.4°incidence incidence angle,angle, comparedcompared to to the the image image from from a adescending descending orbit orbit with with a a ◦ 39.939.9°incidence incidence angle, angle, shown shown in in Figure Figure7 a.7a.

(a) (b)

Figure 7. Cluster of Scythian kurgans, Saka kurgans, and ogradkas in the TSX SL images from 12 July 2015 (a) and 14 July 2015 (b)—flipped vertically and horizontally for better comparability (SAR image © DLR, 2015). (Saka kurgans = red, Scythian kurgans = green rectangle, ogradkas = purple, undatable

mounds = yellow, and all (othera) objects = cyan). (b)

Figure 7. Cluster of Scythian kurgans, Saka kurgans, and ogradkas in the TSX SL images from 12 July Figure 7. Cluster of Scythian kurgans, Saka kurgans, and ogradkas in the TSX SL images from 12 July 2015 (a) and 14 July 2015 (b)—flipped vertically and horizontally for better comparability (SAR image 2015 (a) and 14 July 2015 (b)—ﬂipped vertically and horizontally for better comparability (SAR image © DLR, 2015). (Saka kurgans = red, Scythian kurgans = green rectangle, ogradkas = purple, undatable © DLR, 2015). (Saka kurgans = red, Scythian kurgans = green rectangle, ogradkas = purple, undatable mounds = yellow, and all other objects = cyan). mounds = yellow, and all other objects = cyan).

Remote Sens. 2016, 8, 817 7 of 10

Remote Sens. 2016, 8, 817 7 of 10 Even though the cluster of Saka kurgans seen in Figures3 and6 is visible in the ST and the SL Even though the cluster of Saka kurgans seen in Figure 3 and Figure 6 is visible in the ST and the modeRemote images, Sens. 2016 this, 8 is, 817 not true for all of these monuments, as shown in Figure8, where no Saka7 of kurgans 10 SL mode images, this is not true for all of these monuments, as shown in Figure 8, where no Saka are detectable. This is also the case in the other SL images taken from different orbits and different kurgans are detectable. This is also the case in the other SL images taken from different orbits and angles. ThisEven cluster though of thekurgans clusteris of not Saka detectable kurgans seen in anyin Figure of the 3 and SL images. Figure 6 is visible in the ST and the SLdifferent mode images,angles. Thisthis clusteris not trueof kurgans for all is of not th esedetectable monuments, in any asof theshown SL images. in Figure 8, where no Saka kurgans are detectable. This is also the case in the other SL images taken from different orbits and different angles. This cluster of kurgans is not detectable in any of the SL images.

Figure 8. Several clusters of Saka kurgans in TSX SL image acquired on 14 July 2015 (SAR images © Figure 8. Several clusters of Saka kurgans in TSX SL image acquired on 14 July 2015 (SAR images © DLR, DLR, 2015). (Saka kurgans = red, Scythian kurgans = green rectangle, ogradkas = purple, undatable 2015).mounds (Saka kurgans = yellow,= red,and allScythian other objects kurgans = cyan).= green rectangle, ogradkas = purple, undatable mounds = yellow,Figure and 8. all Several other objectsclusters =of cyan). Saka kurgans in TSX SL image acquired on 14 July 2015 (SAR images © DLR,From 2015). these ( resultsSaka kurgans we can = red,see theScythian detection kurgans of larger = green burial rectangle, structures ogradkas is still = purple, possible undatable in SL mode mounds = yellow, and all other objects = cyan). Fromimages; these nevertheless, results we detection can see depends the detection strongly of on larger the burialtype of structures object and is the still acquisition possible in SL parameters. Generally, very flat and very steep acquisition angles are preferable, as they enhance the mode images; nevertheless, detection depends strongly on the type of object and the acquisition visibilityFrom ofthese three-dimensional results we can seestructures the detection by increa of largersing the burial layover structures or the shadow is still possible area, respectively. in SL mode parameters.images;Nevertheless, Generally,nevertheless, from veryan operationaldetection ﬂat and depends verypoint steepof viewstrongly acquisition the detectability on the angles type of arelargerof preferable,object structures and asinthe theySL acquisition images enhance is the visibilityparameters.already of three-dimensional very Generally, limited and very cannot flat structures and be guaranteed. very by steep increasing acqu isition the angles layover are preferable, or the shadow as they area, enhance respectively. the Nevertheless,visibility of from three-dimensional an operational structures point of by view increa thesing detectability the layover ofor the larger shadow structures area, respectively. in SL images is alreadyNevertheless,4.3. very TSX limited Stripmap from and Images an cannotoperational (SM) be guaranteed. point of view the detectability of larger structures in SL images is already very limited and cannot be guaranteed. As we can see from Figure 9, when marked we can detect some of the Saka kurgans in the cluster, 4.3. TSXbut Stripmapit would generally Images (SM) be very difficult or even impossible to recognize grave mounds without any 4.3. TSX Stripmap Images (SM) Asprevious we can knowledge. see from FigureTherefore,9, when TSX stripmap marked data we canis not detect suitable some for ofthe the detectionSaka kurgansof these intypes the of cluster, As we can see from Figure 9, when marked we can detect some of the Saka kurgans in the cluster, but it wouldarchaeological generally structures. be very difﬁcult or even impossible to recognize grave mounds without any but it would generally be very difficult or even impossible to recognize grave mounds without any previous knowledge. Therefore, TSX stripmap data is not suitable for the detection of these types of previous knowledge. Therefore, TSX stripmap data is not suitable for the detection of these types of archaeologicalarchaeological structures. structures.

Figure 9. Cluster of Saka kurgans in the TSX SM image from 5 June 2014 (SAR image © DLR, 2015). (Saka kurgans = red, Scythian kurgans = green rectangle, ogradkas = purple, undatable mounds = yellow, and all other objects = cyan). Figure 9. Cluster of Saka kurgans in the TSX SM image from 5 June 2014 (SAR image © DLR, 2015). Figure 9. Cluster of Saka kurgans in the TSX SM image from 5 June 2014 (SAR image © DLR, 2015). (Saka kurgans = red, Scythian kurgans = green rectangle, ogradkas = purple, undatable mounds = yellow, Saka kurgans Scythian kurgans ogradkas ( and all other= red, objects = cyan). = green rectangle, = purple, undatable mounds = yellow, and all other objects = cyan).

Remote Sens. 2016, 8, 817 8 of 10

4.4. Quantifying the Analysis In the sections above, we demonstrated the discernibility of several archaeological structures in TSX images of different spatial resolutions, modes, orbits, and incident angles. However, for quantifying the results, we generated a random sample of image subsets showing Saka kurgans and Scythian kurgans of different sizes from different images. As we want to analyze the discernibility of the structures in the data and not the advantages and disadvantages of automatic detection methods, we instead tested the visual detectability by showing the images to a test group and asking them to detect the structures in the images. Our test group consisted of 11 members, all graduate students with experience in SAR image analysis. Only one of the group members has knowledge of archaeology and only two had knowledge of the region. For each set of different object sizes, two examples were randomly selected and 200 × 200 pixel image subsets from different images were created. To keep the number of images limited for the test group, we selected three sample images: a TSX stripmap mode image from 5 June 2014, a TSX spotlight image from 14 July 2015, and a TSX staring spotlight image from 16 September 2015 (see Table1). We presented the images in slant-range and in the original resolution. However, for the staring spotlight image, we multi-looked four times in azimuth. As the interpretability of SAR images may also depend on the stretching of the amplitude data to the eight-bit grey-scale display, we used two different stretching methods. For the first method we calibrated the data to beta-nought in dB and stretched that from −15 dB to 10 dB for visualization. In the second√ method, we used a square root of the digital number and stretched the images between 0 and 2048. However, that did not make a significant difference in the results and we therefore aggregated these results together in the analysis. Furthermore, we presented the test group with three response options to the question “Can they can identify a burial mound in the center of the test image?”: yes, maybe, and no. As we can see from the results shown in Table3, the majority could not discern the archaeological features in the stripmap image. Even the large Saka kurgans were only identified by around 22% of the test group. In the spotlight image, the ‘maybe’ responses dominated and none of the objects are identified clearly. Only in the ST images did a majority respond that a clear identification of the objects was possible. Interestingly, the identification of the Saka kurgans was generally less certain than the Scythian kurgans.

Table 3. Aggregated voting results from the test group with 11 members. The majority votes are marked in bold.

TerraSAR-X Stripmap— TerraSAR-X Spotlight— TSX Staring Spotlight— 5 June 2014 14 July 2015 16 September 2015 No Maybe Yes No Maybe Yes No Maybe Yes Scythian kurgan (10 m–20 m) 40.9% 29.5% 29.5% 22.7% 68.2% 9.1% 22.7% 20.5% 56.8% Scythian kurgan (20 m–30 m) 63.6% 22.7% 13.6% 21.8% 60.0% 18.2% 18.2% 4.5% 77.3% Saka kurgan (>30 m) 30.3% 47.0% 22.7% 40.0% 43.6% 16.4% 23.4% 18.2% 58.4%

For analyzing the discernibility, we used two methods for considering a burial mound to be detected. In the first method, an object needs to have >50% of the test persons clearly identify the object as a burial mound and >75% percent of the test persons identify it as a mound or maybe identifiable as a mound. Under these rather strict conditions, all of the grave mounds with a >10 m diameter were identified in the staring spotlight image and 50% of the kurgans with a <10 m diameter were identified in the staring spotlight image. However, none of the examples were identified in the spotlight or the stripmap image. In our second method, we defined every object that had more than 75% of the test persons voting with yes or maybe. Under these conditions, all the objects with a diameter of 10 m and above were Remote Sens. 2016, 8, 817 9 of 10 identified in the staring spotlight images. Of the Saka kurgans larger than 30 m, 50% were identified in the stripmap and the spotlight images. From the Scythian kurgans of a more than 10 m diameter, 66% were identified in the spotlight image, but none were identified in the stripmap image. For the kurgans with a diameter of 10 m, only half were identified in the spotlight image and none in the stripmap image.

5. Discussion As shown by our results, using the staring spotlight mode, most larger mounds (>10 m diameter) were clearly distinguished and clusters of smaller mounds were also identifiable. However, the high spatial resolution of the staring spotlight mode comes with a reduced coverage, making it very difficult and expensive to obtain data from large areas, whereas in spotlight and especially in the stripmap mode, large areas can be covered. The problem is that in these modes even the largest mounds (>30 m diameter) were only seldom identified clearly, making these modes unsuitable for mound detection. Due to the speckling effect, the discernibility of large archaeological and natural structures in SAR images is, especially in comparison with more recent man-made structures, quite limited. Compared to optical imagery, we estimate it would require approximately a two- to three-times-higher spatial resolution for the clear identification of burial mounds. In our experience, we were able to identify larger burial mounds in optical images with a resolution of about one meter; however, for SAR imagery we need at least the spatial and radiometrical resolution of the TSX staring spotlight mode data to discern the burial mounds in our test site. Although we tested many different modes and acquisition parameters, there might be approaches that provide better results and that would certainly be valuable for further research. Future inquiries might focus on polarimetric analyses as well as time-series and multi-baseline interferometry.

6. Conclusions In this paper, we demonstrated the discernibility of burial mounds in TSX images of different acquisition modes. We showed that in the staring spotlight mode, more than 50% of the larger mounds (>10 m diameter) can clearly be identified with more than 75% positive votes. Furthermore, clusters of smaller mounds are also identifiable. However, in the spotlight and stripmap mode, even the largest mounds (>30 m diameter) were only clearly identified in about 16% and 22% of the cases, respectively, making these modes unsuitable for mound detection. Based on our experiments, we conclude that the TerraSAR-X staring spotlight mode is useful for archaeological applications, because that mode approaches the spatial resolution of many archaeological features. This was also recently demonstrated by Tapete et al. [14] using TSX staring spotlight data to measure the rates of looting activities in Syria. As such, the staring spotlight mode might pave the way towards an increased use of SAR in archaeology. However, for landscape analysis and wide-area mapping, the staring spotlight mode data is less advantageous due to the limited acquisition size. Nevertheless, with the approval at the World Radio Conference in November 2015, future SAR systems will be able to use the 1200 MHz spectrum range in X-band, allowing for much higher spatial resolution in stripmap mode, thus opening possibilities for SAR data usage in wide-area mapping of archaeological features. With the next-generation systems, e.g., TerraSAR-X NG (next generation), very-high-resolution stripmap mode data will become available and will catalyze SAR data applications suitable for landscape archaeology.

Acknowledgments: This work was supported in part by the National Natural Science Foundation of China under Grants 61331016 and 41174120, the CAS-CSIRO Cooperative Research Program (Grant No. GJHZ1407), the Archaeocare Foundation, as well as the Swiss National Science Foundation (Grant P2SKP1_168315). The TerraSAR-X data was provided by DLR via MTH2240. The authors would also like to especially thank the Xinjiang branch of the Chinese Academy of Sciences for their support during our ﬁeld work. Remote Sens. 2016, 8, 817 10 of 10

Author Contributions: T. Balz designed and performed the experiments. G. Caspari was responsible for the archaeological analysis; B. Fu organized the field work; M. Liao contributed in editorial and technical support. T. Balz and G. Caspari wrote the paper. Conflicts of Interest: The authors declare no conflict of interest.

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