Abstract
In this contribution, we apply different methods of spatial and geomorphometric analysis in order to present a general approach of data exploration in areas where detailed local information is absent. Our data are based on locations of megalithic graves from Funnel Beaker societies (3700–2800 BCE) in the area of Schleswig-Holstein, Germany. Using these locations, we apply methods of point pattern analysis in order to reconstruct the spatial processes that created the sample: We use density-based measures to show the influence of first-order effects on the dataset. While first-order effects are related to the underlying areal characteristics of the point locations and hence are determinant of their intensity, second-order effects are the result of interactions between points. We conduct distance-related approaches, e.g. focusing on nearest-neighbour characteristics, in order to investigate the interaction between the points. The point pattern analyses are complemented by integrating geomorphometric measures that are indirectly indicative for some general environmental conditions, even in prehistoric times. This helps (a) to relate first-order effects to societal or environmental features and (b) to understand the specific pattern of interactions between the points. The necessary raw data in the form of digital elevation models are freely available for large parts of the globe. All analyses are conducted using free and open-source software in order to provide their limitless application.
Notes
- 1.
Note that the term event is used here in the technical sense of spatial point pattern analysis: In a spatial point pattern, locations are referred to as events in order to distinguish them from other points of the region in question (Diggle 2013, 1).
References
Ahnert F (1981) Über die Beziehung zwischen quantitativen, semiquantitativen und qualitativen Methoden in der Geomorphologie. Z Geomorphol Supplement Band 39:1–28
Ahnert F (2003) Einführung in die Geomorphologie. Eugen Ulmer, Stuttgart
Baddeley A, Turner R (2005) Spatstat: an R package for analyzing spatial point patterns. J Stat Softw 12(6):1–42
Baddeley A, Turner R (2015) Spatstat manual. CRAN. http://www.spatstat.org
Baddeley AJ, Møller J, Waagepetersen R (2000) Non- and semi-parametric estimation of interaction in inhomogeneous point patterns. Stat Neerl 54(3):329–350. https://doi.org/10.1111/1467-9574.00144
Böhner J, McCloy KR, Strobl J (eds) (2006) SAGA – analysis and modelling applications. Göttinger Geographische Abhandlungen 115
Bivand RS, Pebesma EJ, Gómez-Rubio V (2008) Applied spatial data analysis with R. Springer, New York
Bivand R, Keitt T, Rowlingson B (2015) Rgdal: bindings for the geospatial data abstraction library. r package version 0.9-2, http://CRAN.R-project.org/package=rgdal
Borcard D, Gillet F, Legendre P (2011) Numerical ecology with R. Springer, New York. http://link.springer.com/10.1007/978-1-4419-7976-6
Chisholm M (2007) Rural settlement and land use. Hutchinson, London
De Reu J, Bourgeois J, Bats M, Zwertvaegher A, Gelorini V, De Smedt P, Chu W, Antrop M, De Maeyer P, Finke P, Van Meirvenne M, Verniers J, Crombé P (2013) Application of the topographic position index to heterogeneous landscapes. Geomorphology 186:39–49. https://doi.org/10.1016/j.Geomorph.2012.12.015
Diggle PJ (2013) Statistical analysis of spatial and spatio-temporal point patterns, 3rd edn. Chapman and Hall/CRC, Boca Raton
Fritsch B, Furholt M, Hinz M, Lorenz L, Nelson H, Schafferer G, Schiesberg S, Sjögren KG (2010) Dichtezentren und lokale Gruppierungen – Eine Karte zu den Großsteingräbern Mittel- und Nordeuropas. J Neolithic Archaeol. 10.12766/jna.2010.56. http://www.jna.uni-kiel.de/index.php/jna/article/view/56
Furholt M (2012) Monuments and durable landscapes in the Neolithic of southern Scandinavia and northern Central Europe. In: Furholt M, Hinz M, Miscka D (eds) “As time goes by?” Monumentality, landscapes and the temporal perspective. Proceedings of the international workshop “socio-environmental dynamics over the last 12,000 years: the creation of landscapes II (14th–18th March 2011)” in Kiel, no. 206 in Universitätsforschungen zur prähistorischen Archäologie. Habelt, Bonn, pp 115–132
Gallant JC, Read AM, Dowling TI (2012) Removal of tree offsets from SRTM and other digital surface models. ISPRS Int Arch Photogramm Remote Sens Spat Inf Sci XXXIX-B4:275–280. https://doi.org/10.5194/isprsarchives-XXXIX-B4-275-2012
Guisan A, Weiss SB, Weiss AD (1999) GLM versus CCA spatial modeling of plant species distribution. Plant Ecol 143(1):107–122. http://link.springer.com/article/10.1023/A:1009841519580
Hijmans RJ (2015) Raster: geographic data analysis and modeling. R package version 2.3-40. http://CRAN.R-project.org/package=raster
Hill T (2002) Von Wegen: auf den Spuren des Ochsenweges (Heerweg) zwischen dänischer Grenze und Eider. No. 12 in Flensburger regionale Studien, Inst. für Geographie und ihre Didaktik, Landeskunde und Regionalforschung, Flensburg
Illian J, Penttinen A, Stoyan H, Stoyan D (2008) Statistical analysis and modelling of spatial point patterns. Wiley, Chichester, WS
Jarvis A, Reuter HI, Nelson A, Guevara E (2008) Hole-filled seamless SRTM data V4. International Centre for Tropical Agriculture (CIAT). http://srtm.csi.cgiar.org
Jasiewicz J, Stepinski TF (2013) Geomorphons—a pattern recognition approach to classification and mapping of landforms. Geomorphology 182:147–156. https://doi.org/10.1016/j.geomorph.2012.11.005
Knitter D, Nakoinz O, Del Fabbro R, Kohlmeyer K, Meyer M, Schütt B (2014) The centrality of Aleppo and its environs. eTopoi J Anc Stud 3:107–127
Koethe R, Lehmeier F (1996) SARA – System zur Automatischen Relief-Analyse. User manual. Department of Geography, University of Goettingen (unpublished)
Kvamme KL (2006) There and back again: revisiting archaeological location modeling. In: Mehrer MW, Wescott KL (eds) GIS and archaeological site location modeling. Taylor & Francis, Boca Raton, pp 2–34
Legendre P, Legendre L (2012) Numerical ecology. In: Developments in environmental modelling, 3rd english edn, vol 24. Elsevier, Amsterdam
Liedtke H, Marcinek J (eds) (2002) Physische Geographie Deutschlands, 3rd edn. Perthes Geographie-Kolleg, Klett-Perthes, Gotha
Litt T, Behre KE, Meyer KD, Stephan HJ, Wansa S (2007) Stratigraphische Begriffe für das Quartär des norddeutschen Vereisungsgebietes. Eiszeitalter und Gegenwart 56(1-2):7–65. https://doi.org/10.3285/eg.56.1-2.02
Lloyd CD (2011) Local models for spatial analysis. CRC Press, Boca Raton
Lüth P (2011) Die neolithische Besiedlung des nördlichen Schleswig-Holsteins am Übergang vom Früh- zum Mittelneolithikum. Offa Berichte und Mitteilungen zur Urgeschichte, Frühgeschichte und Mittelalterarchäologie 65/66 (2008/2009):93–133
Meynen E, Schmithüsen J (eds) (1962) Handbuch der naturräumlichen Gliederung Deutschlands, vol Band II. Bundesanstalt für Landeskunde und Raumforschung, Bad Godesberg
Müller J (2011) Megaliths and funnel beakers: societies in change 4100–2700 BC. Drieendertigste Kroon-Voordracht, Amsterdam
Müller J (2014) 4100–2700 B.C. monuments and ideologies in the neolithic landscape. In: Osborne JF (ed) Approaching monumentality in archaeology, The Institute for European and Mediterranean Archaeology distinguished monograph series. State University of New York Press, Albany, pp 181–214
Neteler M, Bowman M, Landa M, Metz M (2012) GRASS GIS: a multi-purpose Open Source GIS. Environ Model Softw 31:124–130. https://doi.org/10.1016/j.envsoft. 2011.11.014
Olaya V, Conrad O (2009) Chapter 12 Geomorphometry in SAGA. In: Hengl T, Reuter HI (eds) Geomorphometry – concepts, software, applications. Developments in soil science, vol 33. Elsevier, Amsterdam, pp 293–308
Openshaw S (1984) The modifiable areal unit problem. Geo Abstracts Univ. of East Anglia, Norwich
O’Sullivan D, Perry GLW (2013) Spatial simulation: exploring pattern and process. Wiley, Chichester, WS
O’Sullivan D, Unwin D (2010) Geographic information analysis. Wiley, Hoboken
Pebesma E, Bivand RS (2005) S classes and methods for spatial data: the sp package. R News 5(2):9–13. ftp://200.236.31.2/CRAN/web/packages/sp/vignettes/intro_sp.pdf
Pike R, Evans I, Hengl T (2009) Chapter 1 Geomorphometry: a brief guide. In: Hengl T, Reuter HI (eds) Geomorphometry – concepts, software, applications. Developments in soil science, vol 33. Elsevier, Amsterdam, pp 3–30
R Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org/
Ripley BD (2004) Spatial statistics. Wiley series in probability and statistics. Wiley, Hoboken
Schmidtke KD (1995) Die Entstehung Schleswig-Holsteins: von der Eiszeit zur Kulturlandschaft, 3rd edn. Wachholtz, Neumünster
Schütt B, Löhr H, Baumhauer R (2002) Mensch-Umwelt-Beziehungen in Raum und Zeit–Konzeption eines Fundstellenkatasters für die Region Trier. Petermanns Geographische Mitteilungen 146(6):74–83
Shortridge A, Messina J (2011) Spatial structure and landscape associations of SRTM error. Remote Sens Environ 115(6):1576–1587. https://doi.org/10.1016/j.rse.2011.02.017. http://www.sciencedirect.com/science/article/pii/S0034425711000678
Ssymank A (1994) Neue Anforderungen im europäischen Naturschutz. Das Schutzgebietssystem Natura 2000 und die FFH -Richtlinie der EU. Natur und Landschaft 69(9):395–406
Stepinski TF, Jasiewicz J (2011) Geomorphons – a new approach to classification of landforms. In: Geomorphometry 2011, Redlands
Stewig R (1982) Landeskunde von Schleswig-Holstein. In: Geocolleg, 2nd edn, vol 5. Borntraeger, Stuttgart (1. Aufl. im Hirt-Verl., Kiel)
Tagil S, Jenness J (2008) GIS-based automated landform classification and topographic, landcover and geologic attributes of landforms around the Yazoren Polje, Turkey. J Appl Sci 8:910–921
Thomas M (1949) A generalization of Poisson’s binomial limit for use in ecology. Biometrika 36(1–2):18–25. https://doi.org/10.1093/biomet/36.1-2.18. http://biomet.oxfordjournals.org/content/36/1-2/18
Tobler WR (1970) A computer movie simulating urban growth in the detroit region. Econ Geogr 46:234–240. https://doi.org/10.2307/143141. http://www.jstor.org/stable/143141
Verhagen P (2007) Case studies in archaeological predictive modelling. Leiden University Press, Leiden
Weiss A (2001) Topographic position and landforms analysis. In: Poster presentation, ESRI User Conference, San Diego, CA, pp 200–200
Wickham H (2009) ggplot2: Elegant graphics for data analysis. Springer, New York
Wiegand T, Moloney KA (2004) Rings, circles, and null-models for point pattern analysis in ecology. Oikos 104(2):209–229. http://www.jstor.org/stable/3547954
Wiegand T, Moloney KA (2013) Handbook of spatial point-pattern analysis in ecology. CRC Press, Boca Raton
Witt W (1962) Schleswiger geest. In: Meynen E, Schmithüsen J (eds) Handbuch der naturräumlichen Gliederung Deutschlands, vol Band II. Bundesanstalt für Landeskunde und Raumforschung, Bad Godesberg, pp 1018–1021
Acknowledgements
Daniel Knitter is grateful to the Excellence Cluster Topoi—The Formation and Transformation of Space and Knowledge in Ancient Civilizations—for supporting this study.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Knitter, D., Nakoinz, O. (2018). Point Pattern Analysis as Tool for Digital Geoarchaeology: A Case Study of Megalithic Graves in Schleswig-Holstein, Germany. In: Siart, C., Forbriger, M., Bubenzer, O. (eds) Digital Geoarchaeology. Natural Science in Archaeology. Springer, Cham. https://doi.org/10.1007/978-3-319-25316-9_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-25316-9_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25314-5
Online ISBN: 978-3-319-25316-9
eBook Packages: Social SciencesSocial Sciences (R0)