CoChat
Sign Up
Cited by 12

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Modeling multivariate landscape affordances and functional ecosystem connectivity in landscape archeology

Kempf, Michael·2020·Archaeological and Anthropological Sciences
DOI 10.1007/s12520-020-01127-w
Open this paper in CoChat — free account

Abstract

Quantitative, digital statistics, and spatial analysis have proven to be useful tools in landscape archeological research. Herein, GIS-based data storage, manipulation, and visualization of environmental attributes and archeological records are among the most intensely applied methods to evaluate human-landscape interaction, movement patterns, and spatial behavior of past societies. Recent land use management and land cover change, however, have largely altered and modified present-day landscapes, which decreases the potential replicability of modern surface conditions to past ecosystem functionalities and the individual human landscape affordances. This article presents a comprehensive multivariate environmental analysis from a regional case study in the Upper Rhine Valley and exemplifies the bias of the archeological record based on modern land use, built-up, and surface change. Two major conclusions can be drawn: modern surfaces are the result of long-term past human landscape development, and the archeological data inherent in the landscape is strongly biased by modern human activity ranges, urban, agricultural and infrastructural development, and the configuration and perception of recent surface management.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s12520-020-01127-w

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Modern data is heavily biased not only by past environmental variability but also by the conceptual framework of our current society.

    “Modern data is heavily biased not only by past environmental variability but also by the conceptual framework of our current society (Kempf 2020).”

    From From landscape affordances to landscape connectivity: contextualizing an archaeology of human ecology (2020) · cites this paper as Kempf 2020

    The Conclusion (page unavailable) says archaeological findings are strongly biased by modern land-use concepts and discusses past climatic and geomorphological changes that affect their interpretation. It does not establish that modern data generally are heavily biased by past environmental variability; its findings concern archaeological records and landscapes. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • The available data is highly biased by the construction activities of modern society.

    “As recently stressed by the author, the available data is highly biased by the construction activities of modern society (Kempf 2020).”

    From From landscape affordances to landscape connectivity: contextualizing an archaeology of human ecology (2020) · cites this paper as Kempf 2020

  • Various environmental parameters and modern surface transformations bias the distribution and the perception of the archaeological record in the Upper Rhine Valley.

    “As pointed out by the author for the Upper Rhine Valley, various environmental parameters and modern surface transformations bias the distribution and the perception of the archaeological record (Kempf 2020).”

    From From landscape affordances to landscape connectivity: contextualizing an archaeology of human ecology (2020) · cites this paper as Kempf 2020

  • The combination of the methodological approach presented in this paper and the multivariate model (Kempf 2020) is one potential step towards a comprehensive interpretation of past human behaviour.

    “The combination of the methodological approach presented in this paper and the multivariate model (Kempf 2020) is one potential step towards a comprehensive interpretation of past human behaviour.”

    From From landscape affordances to landscape connectivity: contextualizing an archaeology of human ecology (2020) · cites this paper as Kempf 2020

  • In a geoarchaeological context, it is possible to interpolate affordances from multivariate landscape analyses.

    “In a geoarchaeological context, this enables the possibility of interpolating affordances from multivariate landscape analyses (Kempf 2019, 2020).”

    From From landscape affordances to landscape connectivity: contextualizing an archaeology of human ecology (2020) · cites this paper as Kempf 2020

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 138

  1. Abate N et al (2020) Multitemporal 2016-2018 Sentinel-2 data enhancement for landscape archaeology: the case study of the Foggia Province, southern Italy. Remote Sens 12(8):1309. https://doi.org/10.3390/rs12081309 · DOI
  2. Adriaenssens V, Baets BD, Goethals PLM, Pauw ND (2004) Fuzzy rule-based models for decision support in ecosystem management. Sci Total Environ 319(1–3):1–12. https://doi.org/10.1016/S0048-9697(03)00433-9 · DOI
  3. Agapiou A, Alexakis D, Sarris A, Hadjimitsis D (2014) Evaluating the potentials of Sentinel-2 for archaeological perspective. Remote Sens 6(3):2176–2194. https://doi.org/10.3390/rs6032176 · DOI
  4. Alexakis D, Sarris A (2010) Environmental and human risk assessment of the prehistoric and historic archaeological sites of Western Crete (Greece) with the use of GIS, remote sensing, fuzzy logic and neural networks. In: Ioannides M et al (eds) Digital heritage: third international conference, EuroMed 2010 Lemessos, Cyprus, November 8–13, 2010 proceedings. Springer, Berlin/Heidelberg, pp 332–342 · DOI
  5. Altieri MA, Nicholls CI (2017) The adaptation and mitigation potential of traditional agriculture in a changing climate. Clim Chang 140(1):33–45. https://doi.org/10.1007/s10584-013-0909-y · DOI · Paper page
  6. Araya S, Lyle G, Lewis M, Ostendorf B (2016) Phenologic metrics derived from MODIS NDVI as indicators for plant available water-holding capacity. Ecol Indic 60:1263–1272. https://doi.org/10.1016/j.ecolind.2015.09.012 · DOI
  7. Asselman NEM, Middelkoop H, van Dijk PM (2003) The impact of changes in climate and land use on soil erosion, transport and deposition of suspended sediment in the river Rhine. Hydrol Process 17(16):3225–3244. https://doi.org/10.1002/hyp.1384 · DOI
  8. Barlindhaug S, Holm-Olsen IM, Tømmervik H (2007) Monitoring archaeological sites in a changing landscape–using multitemporal satellite remote sensing as an ‘early warning’ method for detecting regrowth processes. Archaeol Prospect 14(4):231–244. https://doi.org/10.1002/arp.307 · DOI
  9. Barsi J, Lee K, Kvaran G, Markham B, Pedelty J (2014) The spectral response of the Landsat-8 operational land imager. Remote Sens 6(10):10232–10251. https://doi.org/10.3390/rs61010232 · DOI
  10. Berendse F, van Ruijven J, Jongejans E, Keesstra S (2015) Loss of plant species diversity reduces soil Erosion resistance. Ecosystems 18(5):881–888. https://doi.org/10.1007/s10021-015-9869-6 · DOI
  11. Borga M, Stoffel M, Marchi L, Marra F, Jakob M (2014) Hydrogeomorphic response to extreme rainfall in headwater systems: flash floods and debris flows. J Hydrol 518:194–205. https://doi.org/10.1016/j.jhydrol.2014.05.022 · DOI
  12. Borzenkova I et al. (2015) ‘Climate change during the Holocene (past 12,000 years)’, in The BACC Author (ed.) Second Assessment of Climate Change for the Baltic Sea Basin. (regional climate studies). S.l.: springer, pp. 25–49 · DOI
  13. Brandt R, Groenewoudt BJ, Kvamme KL (1992) An experiment in archaeological site location: modeling in the Netherlands using GIS techniques. World Archaeol 24(2):268–282 (Accessed: 10 May 2019) · DOI · Paper page
  14. Brewer S, Giesecke T, Davis BAS, Finsinger W, Wolters S, Binney H, de Beaulieu JL, Fyfe R, Gil-Romera G, Kühl N, Kuneš P, Leydet M, Bradshaw RH (2017) Late-glacial and Holocene European pollen data. Journal of Maps 13(2):921–928. https://doi.org/10.1080/17445647.2016.1197613 · DOI
  15. Büntgen U, Frank DC, Nievergelt D, Esper J (2006) Summer temperature variations in the European Alps, a.d. 755–2004. J Clim 19(21):5606–5623. https://doi.org/10.1175/JCLI3917.1 · DOI
  16. Büntgen U et al (2011) 2500 years of European climate variability and human susceptibility. Science (New York, NY) 331(6017):578–582. https://doi.org/10.1126/science.1197175 · DOI
  17. Büntgen U, Myglan VS, Ljungqvist FC, McCormick M, di Cosmo N, Sigl M, Jungclaus J, Wagner S, Krusic PJ, Esper J, Kaplan JO, de Vaan MAC, Luterbacher J, Wacker L, Tegel W, Kirdyanov AV (2016) Cooling and societal change during the Late Antique Little Ice Age from 536 to around 660 AD. Nat Geosci 9(3):231–236. https://doi.org/10.1038/ngeo2652 · DOI · Paper page
  18. Buras A, Rammig A, Zang CS (2020) Quantifying impacts of the 2018 drought on European ecosystems in comparison to 2003. Biogeosciences 17(6):1655–1672. https://doi.org/10.5194/bg-17-1655-2020 · DOI
  19. Burt T, Boardman J, Foster I, Howden N (2016) More rain, less soil: long-term changes in rainfall intensity with climate change. Earth Surf Process Landf 41(4):563–566. https://doi.org/10.1002/esp.3868 · DOI
  20. Butzer KW (1982) Archaeology as human ecology. Cambridge University Press, Cambridge · DOI · Paper page
  21. Canning S (2005) Belief' in the past: Dempster-Shafer theory, GIS and archaeological predictive modellIng. Aust Archaeol 60:6–15 (Accessed: 19 June 2019) · DOI
  22. Cao H et al (2019) Operational flood detection using Sentinel-1 SAR data over large areas. Water 11(4):786. https://doi.org/10.3390/w11040786 · DOI
  23. Carbiener R, Schnitzler A (1990) Evolution of major pattern models and processes of alluvial forest of the Rhine in the rift valley (France/Germany). Vegetatio 88:115–129 (Accessed: 21 November 2019) · DOI
  24. Carlson DL (2017) Quantitative methods in archaeology using R. Cambridge University Press, Cambridge · DOI
  25. Carlson TN, Gillies RR, Perry EM (1994) A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover. Remote Sens Rev 9(1–2):161–173. https://doi.org/10.1080/02757259409532220 · DOI
  26. Carrara A (1983) ‘Multivariate models for landslide hazard evaluation’, Math Geol, 15(3) (Accessed: 9 July 2019) · DOI
  27. Cazals C et al (2016) Mapping and characterization of hydrological dynamics in a coastal marsh using high temporal resolution Sentinel-1A images. Remote Sens 8(7):570. https://doi.org/10.3390/rs8070570 · DOI
  28. Chan YK, Koo VC (2008) An introduction to synthetic aperture radar (SAR). Progress Electromagn Res B 2:27–60 (Accessed: 15 May 2019) · DOI
  29. Chen F, Lasaponara R, Masini N (2017) An overview of satellite synthetic aperture radar remote sensing in archaeology: from site detection to monitoring. J Cult Herit 23:5–11. https://doi.org/10.1016/j.culher.2015.05.003 · DOI
  30. Cowley DC (2016) What do the patterns mean? Archaeological distributions and bias in survey data. In: Forte M, Campana S (eds) Digital methods and remote sensing in archaeology. Springer, Cham, pp 147–170 · DOI · Paper page
  31. Dabrowska-Zielinska K et al (2016) Assessment of carbon flux and soil moisture in wetlands applying Sentinel-1 data. Remote Sens 8(9):756. https://doi.org/10.3390/rs8090756 · DOI
  32. Dambeck R, Thiemeyer H (2002) Fluvial history of the northern Upper Rhine River (southwestern Germany) during the Lateglacial and Holocene times. Quat Int 93-94:53–63 · DOI
  33. Dansgaard W et al (1982) A new greenland deep ice core. Science (New York, NY) 218(4579):1273–1277. https://doi.org/10.1126/science.218.4579.1273 · DOI
  34. David B, Thomas J (eds) (2010) Handbook of landscape archaeology. Routledge, Abingdon
  35. Disse M, Engel H (2001) Flood events in the Rhine Basin: genesis, influences and mitigation. Nat Hazards 23:271–290 (Accessed: 28 May 2019) · DOI
  36. Doneus M (2013) Die hinterlassene Landschaft - Prospektion und Interpretation in der Landschaftsarchäologie. (Mitteilungen der Prähistorischen Kommission / Österreichische Akademie der Wissenschaften, Philosophisch-Historische Klasse, 78). Wien: Verl. der Österr. Akad. der Wiss · DOI
  37. Duchne E, Schneider C (2005) Grapevine and climatic changes: a glance at the situation in Alsace. Agron Sustain Dev 25(1):93–99. https://doi.org/10.1051/agro:2004057 · DOI
  38. Ely LL (1997) Response of extreme floods in the southwestern United States to climatic variations in the late Holocene. Geomorphology 19:175–201 (Accessed: 28 May 2019) · DOI
  39. Erfurt M, Glaser R, Blauhut V (2019) Changing impacts and societal responses to drought in southwestern Germany since 1800. Reg Environ Chang 19(8):2311–2323. https://doi.org/10.1007/s10113-019-01522-7 · DOI
  40. Esquivel J, Peña J and Rodríguez-Ariza MO (1999) ‘Multivariate statistic analysis of the relationship between archaeological sites and the geographical data of their surroundings. A quantitative model’, in Dingwall, L. et al. (eds.) Archaeology in the age of internet: CAA 97 ; Computer Applications and Quantitative Methods in Archaeology ; proceedings of the 25th Anniversary Conference, University of Birmingham, April 1997. (BAR international series, 750). Oxford: Archaeopress (Accessed: 19 June 2019)
  41. Fleming A (2006) Post-processual landscape archaeology: a critique. Camb Archaeol J 16(3):267–280 · DOI
  42. Frings RM, Gehres N, Promny M, Middelkoop H, Schüttrumpf H, Vollmer S (2014) Today's sediment budget of the Rhine River channel, focusing on the Upper Rhine Graben and Rhenish Massif. Geomorphology 204:573–587. https://doi.org/10.1016/j.geomorph.2013.08.035 · DOI
  43. Froehlicher L et al (2016) Hedges, colluvium and lynchets along a reference toposequence (Habsheim, Alsace, France): history of erosion in a loess area. Quaternaire 27/2:173–185. https://doi.org/10.4000/quaternaire.7569 · DOI
  44. Fry GLA, Skar B, Jerpåsen G, Bakkestuen V, Erikstad L (2004) Locating archaeological sites in the landscape: a hierarchical approach based on landscape indicators. Landsc Urban Plan 67(1–4):97–107. https://doi.org/10.1016/S0169-2046(03)00031-8 · DOI
  45. Gattiglia G (2015) Think big about data: archaeology and the big data challenge. Archäologische Information 38:1–12 (Accessed: 14 June 2019)
  46. Geudtner, D. et al. (2014) ‘Sentinel-1 System capabilities and applications’, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2014: Held in conjunction with the] 35th Canadian Symposium on Remote Sensing (35th CSRS) ; 13–18 July 2014, Quebec City, Quebec, Canada ; proceedings, IGARSS 2014–2014 IEEE International Geoscience and Remote Sensing Symposium. Institute of Electrical and Electronics Engineers; IEEE Geoscience and Remote Sensing Society; Canadian Remote Sensing Society; IEEE International Geoscience and Remote Sensing Symposium; IGARSS; Canadian Symposium on Remote Sensing; CSRS, Quebec City, QC, 7/13/2014–7/18/2014. Piscataway, NJ: IEEE, pp. 1457–1460. doi: https://doi.org/10.1109/IGARSS.2014.6946711 · DOI
  47. Giacona F et al. (2018) ‘Improving the understanding of flood risk in the Alsatian region by knowledge capitalization: the ORRION participative observatory’, Natl Hazards Earth Syst Sci Discuss 1–49. doi: https://doi.org/10.5194/nhess-2018-210 · DOI
  48. Glaser R, Riemann D, Schönbein J, Barriendos M, Brázdil R, Bertolin C, Camuffo D, Deutsch M, Dobrovolný P, van Engelen A, Enzi S, Halíčková M, Koenig SJ, Kotyza O, Limanówka D, Macková J, Sghedoni M, Martin B, Himmelsbach I (2010) The variability of European floods since AD 1500. Clim Chang 101(1–2):235–256. https://doi.org/10.1007/s10584-010-9816-7 · DOI
  49. Groenhuijzen MR (2019) Palaeogeographic-analysis approaches to transport and settlement in the Dutch part of the Roman limes. In: Verhagen P, Joyce J, Groenhuijzen MR (eds) Finding the limits of the limes. Springer International Publishing, Cham, pp 251–269 (Accessed: 11 May 2019) · DOI
  50. Hagedorn E-M, Boenigk W (2008) The Pliocene and Quaternary sedimentary and fluvial history in the Upper Rhine Graben based on heavy mineral analyses. Neth J Geosci 87(1):21–32 (Accessed: 17 January 2020)
  51. Hargrove WW, Hoffman FM (2004) Potential of multivariate quantitative methods for delineation and visualization of ecoregions. Environ Manag 34(Suppl 1):S39–S60. https://doi.org/10.1007/s00267-003-1084-0 · DOI
  52. Heitz C, Spaeter S, Auzet AV, Glatron S (2009) Local stakeholders’ perception of muddy flood risk and implications for management approaches: a case study in Alsace (France). Land Use Policy 26(2):443–451. https://doi.org/10.1016/j.landusepol.2008.05.008 · DOI
  53. Heitz C, Flinois G, Glatron S (2013) Protection against muddy floods: perception for local actors in Alsace (France) of a protection measure (fascines). International Disaster Risk Conference, Davos, pp 1–4
  54. Hesse R (2010) LiDAR-derived local relief models - a new tool for archaeological prospection. Archaeol Prospect 79(3):n/a. https://doi.org/10.1002/arp.374 · DOI
  55. Himmelsbach I, Glaser R, Schoenbein J, Riemann D, Martin B (2015) Reconstruction of flood events based on documentary data and transnational flood risk analysis of the upper Rhine and its French and German tributaries since AD 1480. Hydrol Earth Syst Sci 19(10):4149–4164. https://doi.org/10.5194/hess-19-4149-2015 · DOI
  56. Jakubauskas ME, Legates DR, Kastens JH (2002) Crop identification using harmonic analysis of time-series AVHRR NDVI data. Comput Electron Agric 37(1–3):127–139. https://doi.org/10.1016/S0168-1699(02)00116-3 · DOI
  57. Johns TC, Gregory JM, Ingram WJ, Johnson CE, Jones A, Lowe JA, Mitchell JFB, Roberts DL, Sexton DMH, Stevenson DS, Tett SFB, Woodage MJ (2003) Anthropogenic climate change for 1860 to 2100 simulated with the HadCM3 model under updated emissions scenarios. Clim Dyn 20(6):583–612. https://doi.org/10.1007/s00382-002-0296-y · DOI
  58. Kamermans H (2000) 'Land evaluation as predictive modelling: a deductive approach', in Lock, G.R. (ed.) Beyond the map: archaeology and spatial technologies
  59. [proceedings of the NATO Advanced Research Workshop on Beyond the Map, Archaeology and Spatial Technologies, Ravello, Italy, 1-2 October, 1999. (NATO science series Series A, Life sciences, 321). Amsterdam: IOS Press, pp. 124-146
  60. Kamermans H and Wansleeben M (1999) 'Predictive Modelling in Dutch Archaeology, Joining Forces', in Barceló, Juan, A., Briz, I. and Vila, A. (eds.) New techniques for old times, CAA 98: Computer applications and quantitative methods in archaeology
  61. proceedings of the 26th Conference, Barcelona, March 1998. (BAR international series, 757). Oxford: Archaeopress, pp. 225-229
  62. Kaplan G (2018) Sentinel-2 Pan sharpening—comparative analysis. Proceedings 2(7):345. https://doi.org/10.3390/ecrs-2-05158 · DOI
  63. Kaplan G, Avdan U (2017) Mapping and monitoring wetlands using Sentinel-2 satellite imagery’, ISPRS Annals of Photogrammetry. Remote Sens Spatial Inform Sci IV-4/W4:271–277. https://doi.org/10.5194/isprs-annals-IV-4-W4-271-2017 · DOI
  64. Kempf M (2018) Migration or landscape fragmentation in Early Medieval eastern France? A case study from Niedernai. J Archaeol Sci Rep 21:593–605. https://doi.org/10.1016/j.jasrep.2018.08.026 · DOI
  65. Kempf M (2019) The application of GIS and satellite imagery in archaeological land-use reconstruction: a predictive model? J Archaeol Sci Rep 25:116–128. https://doi.org/10.1016/j.jasrep.2019.03.035 · DOI · Paper page
  66. Kempf, M. (2020) ‘Fables of the past: landscape (re-)constructions and the bias in the data’, Documenta Praehistorica (in print) · DOI
  67. Knitter D et al (2019) Land use patterns and climate change—a modeled scenario of the Late Bronze Age in Southern Greece. Environ Res Lett 14(12):125003. https://doi.org/10.1088/1748-9326/ab5126 · DOI
  68. Kornhuber K et al (2019) Extreme weather events in early summer 2018 connected by a recurrent hemispheric wave-7 pattern. Environ Res Lett 14(5):54002. https://doi.org/10.1088/1748-9326/ab13bf · DOI
  69. Krolopp E, Sümegi P (1995) Palaeoecological reconstruction of the late pleistocene, based on loess malacofauna in Hungary. GeoJournal 36(2):213–222. https://doi.org/10.1007/BF00813173 · DOI
  70. Kumar P, Prasad R, Gupta DK, Mishra VN, Vishwakarma AK, Yadav VP, Bala R, Choudhary A, Avtar R (2018) Estimation of winter wheat crop growth parameters using time series sentinel-1A SAR data. Geocarto Int 33(9):942–956. https://doi.org/10.1080/10106049.2017.1316781 · DOI
  71. Landuyt L, van Wesemael A, Schumann GJP, Hostache R, Verhoest NEC, van Coillie FMB (2019) Flood mapping based on synthetic aperture radar: an assessment of established approaches. IEEE Trans Geosci Remote Sens 57(2):722–739. https://doi.org/10.1109/TGRS.2018.2860054 · DOI
  72. Lang A, Bork HR, Mäckel R, Preston N, Wunderlich J, Dikau R (2003) Changes in sediment flux and storage within a fluvial system: some examples from the Rhine catchment. Hydrol Process 17(16):3321–3334. https://doi.org/10.1002/hyp.1389 · DOI
  73. Lasaponara R, Masini N (2006) Identification of archaeological buried remains based on the normalized difference vegetation index (NDVI) from Quickbird satellite data. IEEE Geosci Remote Sens Lett 3(3):325–328. https://doi.org/10.1109/LGRS.2006.871747 · DOI
  74. Lasaponara R, Masini N (2007) Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. J Archaeol Sci 34(2):214–221. https://doi.org/10.1016/j.jas.2006.04.014 · DOI
  75. Lasaponara R, Masini N (2011) Satellite remote sensing in archaeology: past, present and future perspectives. J Archaeol Sci 38(9):1995–2002. https://doi.org/10.1016/j.jas.2011.02.002 · DOI
  76. Lasaponara R and Masini N (2012) Satellite remote sensing: a new tool for archaeology. (Remote sensing and digital image processing, 16). s.l.: Springer Netherlands. Available at: https://doi.org/10.1007/978-90-481-8801-7 · DOI
  77. Lasaponara R, Masini N (2013) Satellite synthetic aperture radar in archaeology and cultural landscape: an overview. Archaeol Prospect 20(2):71–78. https://doi.org/10.1002/arp.1452 · DOI
  78. Li J et al (2018) How well can a climate model simulate an extreme precipitation event: a case study using the transpose-AMIP experiment. Am Meteorol Soc 31:6543–6556 (Accessed: 4 July 2019)
  79. Ljungqvist FC (2009) Temperature proxy records covering the last two millennia: a tabular and visual overview. Geografiska Annaler: Series A, Phys Geogr 91(1):11–29. https://doi.org/10.1111/j.1468-0459.2009.00350.x · DOI
  80. Longin R (1971) New method of collagen extraction for radiocarbon dating. Nature 230(5291):241–242. https://doi.org/10.1038/230241a0 · DOI · Paper page
  81. Mäckel R, Schneider R, Seidel J (2003) Anthropogenic impact on the landscape of southern Badenia (Germany) during the Holocene - documented by colluvial and alluvial sediments. Archaeometry 45(3):487–501 (Accessed: 5 June 2019) · DOI
  82. Malenovský Z, Rott H, Cihlar J, Schaepman ME, García-Santos G, Fernandes R, Berger M (2012) Sentinels for science: potential of Sentinel-1, -2, and -3 missions for scientific observations of ocean, cryosphere, and land. Remote Sens Environ 120:91–101. https://doi.org/10.1016/j.rse.2011.09.026 · DOI
  83. Masini N, Soldovieri F (2017) Sensing the past: From artifact to historical site. Springer, Cham (Geotechnologies and the environment, volume 16) · DOI
  84. Masini N, Marzo C, Manzari P, Belmonte A, Sabia C, Lasaponara R (2018) On the characterization of temporal and spatial patterns of archaeological crop-marks. J Cult Herit 32:124–132. https://doi.org/10.1016/j.culher.2017.12.009 · DOI
  85. Mendoza GA, Martins H (2006) Multi-criteria decision analysis in natural resource management: a critical review of methods and new modelling paradigms. For Ecol Manag 230(1–3):1–22. https://doi.org/10.1016/j.foreco.2006.03.023 · DOI
  86. Minářová J, Müller M, Clappier A, Kašpar M (2017a) Characteristics of extreme precipitation in the Vosges Mountains region (north-eastern France). Int J Climatol 37(13):4529–4542. https://doi.org/10.1002/joc.5102 · DOI
  87. Minářová J, Müller M, Clappier A (2017b) Seasonality of mean and heavy precipitation in the area of the Vosges Mountains: dependence on the selection criterion. Int J Climatol 37(5):2654–2666. https://doi.org/10.1002/joc.4871 · DOI
  88. Minářová J, Müller M, Clappier A, Kašpar M (2018) Comparison of extreme precipitation characteristics between the Ore Mountains and the Vosges Mountains (Europe). Theor Appl Climatol 133(3–4):1249–1268. https://doi.org/10.1007/s00704-017-2247-x · DOI
  89. Mleczko M, Mróz M (2018) Wetland mapping using SAR data from the sentinel-1A and TanDEM-X missions: a comparative study in the Biebrza floodplain (Poland). Remote Sens 10(2):78. https://doi.org/10.3390/rs10010078 · DOI
  90. Montandon L, Small E (2008) The impact of soil reflectance on the quantification of the green vegetation fraction from NDVI. Remote Sens Environ 112(4):1835–1845. https://doi.org/10.1016/j.rse.2007.09.007 · DOI
  91. Muthers S, Laschewski G, Matzarakis A (2017) The summers 2003 and 2015 in south-West Germany: heat waves and heat-related mortality in the context of climate change. Atmosphere 8(224):1–13. https://doi.org/10.3390/atmos8110224 · DOI
  92. Nakoinz O, Knitter D (2016) Modelling human behaviour in landscapes. Springer International Publishing, Cham · DOI · Paper page
  93. Omurova GT et al (2018) Reconstruction of extreme paleoclimatic events in northwestern Siberia using ancient wood from Fort Nadym. Archaeol Ethnol Anthropol Eurasia 46(3):32–40. https://doi.org/10.17746/1563-0110.2018.46.3.032-040 · DOI
  94. Overpeck JT, Rind D, Goldberg R (1990) Climate-induced changes in forest disturbance and vegetation. Nature 343:51–53 · DOI
  95. Paloscia S, Pettinato S, Santi E, Notarnicola C, Pasolli L, Reppucci A (2013) Soil moisture mapping using Sentinel-1 images: algorithm and preliminary validation. Remote Sens Environ 134:234–248. https://doi.org/10.1016/j.rse.2013.02.027 · DOI
  96. Parcak SH (2009) Satellite remote sensing for archaeology. Routledge, London Available at: http://​site.ebrary.com​/​lib/​alltitles/​docDetail.action​?​docID=​10288996 · DOI · Paper page
  97. Pettorelli N, Vik JO, Mysterud A, Gaillard JM, Tucker CJ, Stenseth NC (2005) Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends Ecol Evol 20(9):503–510. https://doi.org/10.1016/j.tree.2005.05.011 · DOI
  98. Pfister C, Weingartner R, Luterbacher J (2006) Hydrological winter droughts over the last 450 years in the Upper Rhine basin: a methodological approach. Hydrol Sci J 51(5):966–985. https://doi.org/10.1623/hysj.51.5.966 · DOI
  99. Popa CN, Knitter D (2016) From environment to landscape. Reconstructing environment perception using numerical data. J Archaeol Method Theory 23(4):1285–1306. https://doi.org/10.1007/s10816-015-9264-9 · DOI
  100. Potin P et al. (2016) Sentinel-1 mission status: 11th European Conference on Synthetic Aperture Radar. Frankfurt am Main: VDE (Accessed: 15 January 2019), Sentinel-1 Mission Status
  101. Przyrowski R, Schäfer A (2015) Quaternary fluvial basin of northern Upper Rhine Graben. Z Dtsch Ges Geowiss 166(1):71–98. https://doi.org/10.1127/1860-1804/2014/0080 · DOI
  102. Reeder-Myers LA (2015) Cultural heritage at risk in the twenty-first century: a vulnerability assessment of coastal archaeological sites in the United States. J Island Coastal Archaeol 10(3):436–445. https://doi.org/10.1080/15564894.2015.1008074 · DOI
  103. Rick TC, Sandweiss DH (2020) Archaeology, climate, and global change in the age of humans. Proc Natl Acad Sci U S A 117(15):8250–8253. https://doi.org/10.1073/pnas.2003612117 · DOI · Paper page
  104. Rosenzweig C, Karoly D, Vicarelli M, Neofotis P, Wu Q, Casassa G, Menzel A, Root TL, Estrella N, Seguin B, Tryjanowski P, Liu C, Rawlins S, Imeson A (2008) Attributing physical and biological impacts to anthropogenic climate change. Nature 453(7193):353–357. https://doi.org/10.1038/nature06937 · DOI
  105. Sadeghi M, Babaeian E, Tuller M, Jones SB (2017) The optical trapezoid model: a novel approach to remote sensing of soil moisture applied to Sentinel-2 and Landsat-8 observations. Remote Sens Environ 198:52–68. https://doi.org/10.1016/j.rse.2017.05.041 · DOI
  106. Sarris A, Papadopoulos N, Agapiou A, Salvi MC, Hadjimitsis DG, Parkinson WA, Yerkes RW, Gyucha A, Duffy PR (2013) Integration of geophysical surveys, ground hyperspectral measurements, aerial and satellite imagery for archaeological prospection of prehistoric sites: the case study of Vésztő-Mágor Tell, Hungary. J Archaeol Sci 40(3):1454–1470. https://doi.org/10.1016/j.jas.2012.11.001 · DOI · Paper page
  107. Schmitt L, Maire G, Nobelis P, Humbert J (2007) Quantitative morphodynamic typology of rivers: a methodological study based on the French Upper Rhine basin. Earth Surf Process Landf 32(11):1726–1746. https://doi.org/10.1002/esp.1596 · DOI
  108. Schuppert C, Dix A (2009) Reconstructing former features of the cultural landscape near early Celtic princely seats in southern Germany. Soc Sci Comput Rev 27(3):420–436. https://doi.org/10.1177/0894439308329766 · DOI
  109. Simonneau A, Chapron E, Vannière B, Wirth SB, Gilli A, di Giovanni C, Anselmetti FS, Desmet M, Magny M (2013) Mass-movement and flood-induced deposits in Lake Ledro, southern Alps, Italy: implications for Holocene palaeohydrology and natural hazards. Clim Past 9(2):825–840. https://doi.org/10.5194/cp-9-825-2013 · DOI
  110. Starkel L (2011) Present-day events and the evaluation of Holocene palaeoclimatic proxy data. Quat Int 229:2–7 (Accessed: 28 May 2019) · DOI
  111. Stuiver M, Grootes PM (2000) GISP2 oxygen isotope ratios. Quat Res 53(3):277–284. https://doi.org/10.1006/qres.2000.2127 · DOI
  112. Tapete D, Donoghue D (2014) Satellite remote sensing: a new tool for archaeology by RosaLasaponara and NicolaMasini (eds). Springer-Verlag, Heidelberg, 2012. ISBN 978-90-481-8801-7. Price: £117.00 (hardback). Pages: 364. Archaeol Prospect 21(2):155–156. https://doi.org/10.1002/arp.1479 · DOI
  113. Tapete D, Casagli N, Luzi G, Fanti R, Gigli G, Leva D (2013) Integrating radar and laser-based remote sensing techniques for monitoring structural deformation of archaeological monuments. J Archaeol Sci 40(1):176–189. https://doi.org/10.1016/j.jas.2012.07.024 · DOI
  114. te Linde AH, Bubeck P, Dekkers JEC, de Moel H, Aerts JCJH (2011) Future flood risk estimates along the river Rhine. Nat Hazards Earth Syst Sci 11(2):459–473. https://doi.org/10.5194/nhess-11-459-2011 · DOI
  115. Tegel W, Vanmoerkerke J, Büntgen U (2010) Updating historical tree-ring records for climate reconstruction. Quat Sci Rev 29(17–18):1957–1959. https://doi.org/10.1016/j.quascirev.2010.05.018 · DOI
  116. Tehrany MS, Pradhan B, Jebur MN (2013) Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS. J Hydrol 504:69–79. https://doi.org/10.1016/j.jhydrol.2013.09.034 · DOI
  117. Thiemayer H et al (2005) Soils, sediments and slope processes and their effects on sediment fluxes into the river Rhine. Erdkunde 59:184–198 (Accessed: 17 January 2020) · DOI
  118. Torres R, Snoeij P, Geudtner D, Bibby D, Davidson M, Attema E, Potin P, Rommen BÖ, Floury N, Brown M, Traver IN, Deghaye P, Duesmann B, Rosich B, Miranda N, Bruno C, L'Abbate M, Croci R, Pietropaolo A, Huchler M, Rostan F (2012) GMES Sentinel-1 mission. Remote Sens Environ 120:9–24. https://doi.org/10.1016/j.rse.2011.05.028 · DOI
  119. Tricca A, Stille P, Steinmann M, Kiefel B, Samuel J, Eikenberg J (1999) Rare earth elements and Sr and Nd isotopic compositions of dissolved and suspended loads from small river systems in the Vosges mountains (France), the river Rhine and groundwater. Chem Geol 160:139–158 (Accessed: 4 June 2019) · DOI
  120. Vaiopoulos AD, Karantzalos K (2016) Pansharpening on the narrow VNIR and SWIR spectral bands of Sentinel’, ISPRS - International Archives of the Photogrammetry. Remote Sens Spatial Inform Sci XLI-B7:723–730. https://doi.org/10.5194/isprsarchives-XLI-B7-723-2016 · DOI
  121. van Dinter M (2013) The Roman limes in the Netherlands: how a delta landscape determined the location of the military structures. Neth J Geosci 92(1):11–32 (Accessed: 13 May 2019)
  122. van Leusen PM (1996) Unbiasing the archaeological record. Archeologia e Calcolatori 7:129–136
  123. van Leusen, M. (2002) Pattern to process: methodological investigations into the formation and interpretation of spatial patterns in archaeological landscapes: PhD Thesis. Groningen Institute for Archaeology, University Groningen
  124. van Leusen PM et al (2005) Protohistoric to Roman settlement on the Lepine margins near Ninfa (South Lazio, Italy). In: Attema PAJ et al (eds) Palaeohistoria 45/46: Acta et Communicationes Instituti bio-archaeologici Universitatis Groninganae. Elde, Barkhuis, pp 301–345
  125. van Oldenborgh GJ, Philip S, Kew S, van Weele M, Uhe P, Otto F, Singh R, Pai I, Cullen H, AchutaRao K (2018) Extreme heat in India and anthropogenic climate change. Nat Hazards Earth Syst Sci 18(1):365–381. https://doi.org/10.5194/nhess-18-365-2018 · DOI · Paper page
  126. Verhagen JWHP (2007) Case studies in archaeological predictive modelling. (Archaeological studies Leiden University, 14). Leiden: Leiden Univ. Press · DOI · Paper page
  127. Verhagen P (2018) Predictive modeling. In: López Varela SL (ed) The encyclopedia of archaeological sciences. Wiley-Blackwell, Malden, pp 1–3
  128. Verhagen P et al. (2010) ‘First thoughts on the incorporation of cultural variables into predictive modelling’, in Niccolucci, F. and Hermon, S. (eds.) Beyond the artifact: digital interpretation of the past. Proceedings of CAA2004. Budapest: Archaeolingua, pp. 307–311
  129. Verhulst N, Govaerts B, Sayre KD, Deckers J, François IM, Dendooven L (2009) Using NDVI and soil quality analysis to assess influence of agronomic management on within-plot spatial variability and factors limiting production. Plant Soil 317(1–2):41–59. https://doi.org/10.1007/s11104-008-9787-x · DOI
  130. von Storch H et al. (2015) ‘Introduction and summary’, in The BACC Author (ed.) Second Assessment of climate change for the Baltic Sea Basin. (regional climate studies). S.l.: springer, pp. 1–22 · DOI
  131. Wadge G, Cole P, Stinton A, Komorowski JC, Stewart R, Toombs AC, Legendre Y (2011) Rapid topographic change measured by high-resolution satellite radar at Soufriere Hills Volcano, Montserrat, 2008–2010. J Volcanol Geotherm Res 199(1–2):142–152. https://doi.org/10.1016/j.jvolgeores.2010.10.011 · DOI
  132. Wang X, Piao S, Ciais P, Li J, Friedlingstein P, Koven C, Chen A (2011) Spring temperature change and its implication in the change of vegetation growth in North America from 1982 to 2006. Proc Natl Acad Sci U S A 108(4):1240–1245. https://doi.org/10.1073/pnas.1014425108 · DOI
  133. Weaverdyck EJS (2019) The role of forts in the local market system in the lower Rhine: towards a method of multiple hypothesis testing through comparative Modelling. In: Verhagen P, Joyce J, Groenhuijzen MR (eds) Finding the limits of the limes. Springer International Publishing, Cham, pp 165–190 · DOI · Paper page
  134. Wetter O, Pfister C, Weingartner R, Luterbacher J, Reist T, Trösch J (2011) The largest floods in the High Rhine basin since 1268 assessed from documentary and instrumental evidence. Hydrol Sci J 56(5):733–758. https://doi.org/10.1080/02626667.2011.583613 · DOI
  135. Wulder MA, Loveland TR, Roy DP, Crawford CJ, Masek JG, Woodcock CE, Allen RG, Anderson MC, Belward AS, Cohen WB, Dwyer J, Erb A, Gao F, Griffiths P, Helder D, Hermosilla T, Hipple JD, Hostert P, Hughes MJ, Huntington J, Johnson DM, Kennedy R, Kilic A, Li Z, Lymburner L, McCorkel J, Pahlevan N, Scambos TA, Schaaf C, Schott JR, Sheng Y, Storey J, Vermote E, Vogelmann J, White JC, Wynne RH, Zhu Z (2019) Current status of Landsat program, science, and applications. Remote Sens Environ 225:127–147. https://doi.org/10.1016/j.rse.2019.02.015 · DOI
  136. Xu H (2006) Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int J Remote Sens 27(14):3025–3033. https://doi.org/10.1080/01431160600589179 · DOI
  137. Zheng B, Myint SW, Thenkabail PS, Aggarwal RM (2015) A support vector machine to identify irrigated crop types using time-series Landsat NDVI data. Int J Appl Earth Obs Geoinf 34:103–112. https://doi.org/10.1016/j.jag.2014.07.002 · DOI
  138. Zolitschka B, Behre K-E, Schneider J (2003) Human and climatic impact on the environment as derived from colluvial, fluvial and lacustrine archives—examples from the Bronze Age to the Migration period, Germany. Quat Sci Rev 22:81–100 (Accessed: 5 June 2019) · DOI

Cited by

Sorted by citations

Metadata

Authors
Kempf, M.
ORCID
Kempf, Michael
Venue
Archaeological and Anthropological Sciences
Publisher
Springer Science and Business Media LLC
Published
2020-07-07
Volume
12
Issue
8
ISSN
  • 1866-9557
  • 1866-9565
DOI
10.1007/s12520-020-01127-w
Cited by
12
References
6
Language
en
Licence
Funders
Albert-Ludwigs-Universität Freiburg im Breisgau

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review