Throwing light on archaeological landscapes: The application of airborne laser scanning and relief visualisation techniques for archaeological prospection

Ralf Hesse, State Office for Cultural Heritage Baden-Württemberg, Germany

STATE OFFICE FOR CULTURAL HERITAGE

Throwing light on archaeological landscapesThe application of airborne laser scanning and reli ef visualisation techniques

for archaeological prospection

Lidar prospection project in Baden-W ürttemberg

• total area: 35,752 km2

• 24,400 km2 (~70%) mapped

• 36,000 known sites checked

• 720,000 features mapped

2012201320142015

Throwing light on archaeological landscapes

• Lidar remote sensing – how does it work?

• From elevation data to images – DTM visualisation techniques

• Traces of past activities – examples from Baden-Württemberg

• From sites to features and landscapes – implications

T

Lidar remote sensing - how does it work?

• Light Detection And Ranging (LiDAR) / Airborne Laser Scanning (ALS)

• time-of-flight of laser pulses (105/s)

• position (GPS), orientation (IMU), beam direction

� millions of 3D point coordinatesreflection vs. backscatter

T

T

Digital Surface Model (DSM)





� millions of 3D point coordinates

T

Digital Terrain Model (DTM)

Filtering

?





� millions of 3D point coordinates


• parameters

• footprint size

• pulse rate, flight altitude and velocity � ground point density

• single/dual/multiple return, full waveform

• survey season (central Europe)

• autumn-spring (trees without leaves)

• ideally: early spring after snowmelt

• laser colour

• infrared: absorption by water, ice and snow

• green: suitable for shallow water

• problems:

• very dense vegetation (spuce regrowth etc.)

• low vegetation (blackberry bushes etc.)

• steep slopes

Lidar DTM Shaded Relief Lidar intensity


• lidar intesity

• strength (brightness) of backscattered signal

• similar to NIR air photo

• active system � independent of natural illlumination, no shadows

DTM visualisation techniques - why?

• What is a DTM?

DTM visualisation techniques - why?

• What is a DTM?

a (gridded) data set containing elevation values

needs to be transformed into human-readable images

Greyscale / colour-coding

• range of elevation values � range of pixel brightness/colour values

slope range: 0…45°

Slope

• range of slope values � range of pixel brightness/colour values


Slope



Slope


Shaded Relief

• simulation of a directional illumination from a point light source

• specified azimuth and elevation (Imhof, 2007)

Shaded Relief



Shaded Relief



Shaded Relief



• vertical exaggeration possible

Shaded Relief

• poor visibility of linear features aligned parallel with illumination azimuth

• bright/dark areas on slopes facing towards/away from illumination

• multiple illumination directions required

• optical illusions for illumination azimuths 90-270°

Shaded Relief

• poor visibility of linear features aligned parallel with illumination azimuth

• bright/dark areas on slopes facing towards/away from illumination

• multiple illumination directions required

• optical illusions for illumination azimuths 90-270°

Trend Removal

• subtraction of a smoothed (low-pass-filtered) version from the original DTM

• highlights small topographic differences

Local Relief Model (LRM)

• advanced trend removal method





Sky-View Factor (SVF)

• diffuse illumination from a homogeneously bright hemisphere (Zakšek et al., 2011)

• single illumination

(Zakšek et al. 2011, Fig. 6)

Sky-View Factor (SVF)

• diffuse illumination from a homogeneously bright hemisphere (Zakšek et al., 2011)

• single illumination

• negative relief features and features on slopes very well visbile

Openness

• diffuse illumination from a homogeneously bright sphere centered on each pixel(Yokoyama et al., 2002; Doneus, 2013)

(Yokoyama et al., 2002, Fig. 5)

Openness


positive openness:

Openness


negative openness:

Local Dominance

• How dominant is an observer with regards to the local surroundings?

Local Dominance

• How dominant is an observer with regards to the local surroundings?

Multi-Scale Integral Invariants (MSII)

• for n spheres with different diameters, centered on each DTM pixel, the percentageof each sphere above and below the DTM surface is computed

• the resulting sets of n values for each pixel are interpreted as n-dimensional vectors,and the distance to a reference vector is computed (Mara et al., 2010)

Multi-Scale Integral Invariants (MSII)

• for n spheres with different diameters, centered on each DTM pixel, the percentageof each sphere above and below the DTM surface is computed

• the resulting sets of n values for each pixel are interpreted as n-dimensional vectors,and the distance to a reference vector is computed (Mara et al., 2010)

Laplacian-of-Gaussian

• Laplacian filter: edge detection filter (Mlsna & Rodríguez, 2005)

• LoG: second derivative of elevation (convexity)

Traces of past activities

• archaeology: material traces of past human activities

• for lidar: traces in surface topography

• mapping traces = stamp collection?

• research question?

• traces record activities

• different activities � different traces?

• economy, social life, ritual

• extraction / deposition / scraping


extraction

deposition

ritual• burial mounds• ritual construction

conflict• rubble mounds

production• mine spoil mounds• slag heaps• middens

mineral resource extraction• flint/chert mines• salt mines• ore mines• clay and sand pits• rock quarries• fertiliser pits

production• charcoal burning pits• charcoal burning platforms• tar pits• fish ponds• mill ponds

agriculture• ridge and furrow• terraces, lynchets• field boundaries• celtic fields• irrigation and drainage

movement & transport• hollow ways• raised roadways• canals

conflict• bomb and mine craters• moats, ditches, trenches• castle mounds• ramparts

ritual• geoglyphs• ritual ponds

habitation• house platforms• pit houses

scraping


extraction

deposition

mineral resource extraction• flint/chert mines• salt mines• ore mines• clay and sand pits• rock quarries• fertiliser pits

ritual• burial mounds• ritual construction

agriculture• ridge and furrow• terracces, lynchets• field boundaries• celtic fields• irrigation and drainage

movement & transport• hollow ways• canals

conflict• rubble mounds

production• mine spoil mounds• slag heaps• middens

conflict• bomb and mine craters• moats, ditches, trenches• castle mounds• ramparts

movement & transport• raised roadways

production• charcoal burning pits• charcoal burning platforms• tar pits• fish ponds• mill ponds

ritual• geoglyphs• ritual ponds

habitation• house platforms• pit houses

scraping

�� palimpsest� “messy landscape” (Mlekuž, 2012)


resource exploitation //

agriculture //

former field boundaries

(n=349,147)

Shaded Relief ccLRM over Shaded Relief Local Dominance



agriculture //

former field boundaries

(n=349,147)



agriculture //

ridge and furrow

(n=4669)

(AiD 2/1995)



agriculture //

Roman field systems(?)

Laplacian-of-Gaussian & Local Dominance

LoG & LD



mineral resource extraction //

ore mining (medieval)

Shaded Relief LoG & SVF

LoG & LD




ore mining (medieval)


LoG & LD




ore mining





extraction pits



charcoal production //

charcoal burning platforms

(n=22,997)

yellow: ≥ 50/km2

http://commons.wikimedia.org/wiki/File:Charcoal_pile_06.jpg



mill and fishery dams

(n=3024)


transport and communication //

hollow ways

LoG & LDShaded Relief Sky-View Factor


settlement //

rectangular enclosures (Iron Age) red: ground-based (n=105)blue: aerial photo (n=198)yellow: lidar (n=202)


conflict //

Roman limes


conflict //

early modern fortification (War of Polish Succession, 1733-1738)

Shaded ReliefccLRM & Shaded ReliefLocal Dominance


conflict // WW-II bunkers and trenches

Orthophoto Shaded Relief Local Dominance LD & SR


conflict //

WW-II bomb craters

Sky-View Factor


conflict //

modern artillery craters

LoG & LDShaded Relief LoG & SVF


• “messy landscapes” (Mlekuž, D., 2012)

Implications for archaeological research

• expand knowledge

• huge amount of data

• full area coverage

• reconsider notions of

• land use

• resource exploitation

• spatial distribution patterns

• “sites” vs. “features” vs. “landscapes”

Implications for heritage management

• scale: sites vs. features vs. landscapes

• “site” – convenient scale for delineation, management and protection

• “features” – individually don’t merit protection status

• “landscape” – large, challenges for delineation, management and protection

Implications for heritage management

• heritage vs. economy

• How can use of landscapes and economic development coexist withlandscape-scale notions of heritage?

• rapidly expanding mechanisation of forestry

• How can priorities for protection be developed (and justified on scientificas well as economic grounds)?

• values worth protecting?

• focus on “iconic” rather than “average” sites?

• strength in numbers? - validity of heritage management arguments

• Does the sheer number of sites devaluate the individual one?

Conclusions

• variety of visualisation techniques � get the most out of the data

• wide range of (overlapping) archaeological relief features � “messy landscapes”

• not sites, but landscapes full of features � implications for research and protection

ReferencesDevereux, B.J., Amable, G.S., Crow, P., 2008. Visualisation of LiDAR terrain models for archaeological featuredetection. Antiquity 82, 470–479.

Doneus, M., 2013. Openness as visualization technique for interpretative mapping of airborne LiDAR derived digitalterrain models. Remote Sensing 5, 6427-6442.

Hesse, R. 2010. LiDAR-derived Local Relief Models – a new tool for archaeological prospection. ArchaeologicalProspection 17, 67–72.

Imhof, E., 2007. Cartographic relief representation. English language edition edited by H.J. Steward. Redlands: ESRIPress.

Jolliffe, I.T., 2002. Principal component analysis. Second edition. Spinger, New York.

Mara, H., Krömker, S., Jakob, S., Breuckmann, B., 2010. GigaMesh and Gilgamesh – 3D Multiscale Integral InvariantCuneiform Character Extraction, In: Artusi, A., Joly-Parvex, M., Lucet, G., Ribes, A., Pitzalis, D. (eds.), The 11thInternational Symposium on Virtual Reality, Archaeology and Cultural Heritage VAST (Paris, France, 2010), pp.131–138.

Miller, G., 1994. Efficient algorithm for local and global accessibility shading. Computer Graphics Proceedings, AnnualConference Series SIGGRAPH, 319–325.Mlekuž, D., 2012. Messy landscapes: lidar and the p ractices of landscaping. In: Cowley, D.C., Opitz, R .S.,(eds.), Interpreting archaeological topography: las ers, 3D data, observation, visualisation and applic ations.Oxbow, Oxford, pp. 90-101.Mlsna, P.A., Rodríguez, J.J., 2005. Gradient and Laplacian edge detection. In: Bovik, A.C. (ed.), Handbook of imageand video processing. 2nd. edition. Elsevier, Amsterdam. pp. 535–553.

Rusinkiewicz, S., Burns, M., DeCarlo, D., 2006. Exaggerated Shading for depicting shape and detail. ACMTransactions on Graphics (Proceedings SIGGRAPH) 25(3), 1199–1205.

Yokoyama, R., Shirasawa, M., Pike, R.J., 2002. Visualizing topography by openness: a new application of imageprocessing to digital elevation models. Photogrammetric Engineering & Remote Sensing 68(3), 257–265.

Zakšek, K., Oštir, K., Kokalj, Z., 2011. Sky-View Factor as a relief visualisation technique. Remote Sensing 3, 398–415.

LIDAR data: LGL/LAD Baden-Württemberg

LiVT – an Open Source toolbox for DEM visualisation

• stand-alone software that computes various visualisations

• spatial filters (incl. Laplacian of Gaussian)

• Shaded Relief

• Sky-View Factor

• Trend Removal

• Local Relief Model

• Exaggerated Relief

• Local Dominance

• Accessibility

• Openness

• MSII

• Visibility

Documents

Throwing light on archaeological landscapes: The application of airborne laser scanning and relief visualisation techniques for archaeological prospection