Main content

Home

Menu

Loading wiki pages...

View
Wiki Version:
# Evidence Density Estimation The Evidence Density Estimation (EDE) function can be applied on radiocarbon-dated as well as typo-chronologically dated archaeological evidence to produce spatio-temporal distribution maps or summed distributions representing intensity of settlement activities within the examined area. ---------- The mechanisms of settlement and land use in prehistory can be examined by testing the hypothesis that variations in spatio-temporal distribution of archaeological evidence of settlements mirror changes of the actual settlement patterns. To test this, we need a mathematical model describing the relation between the quantity of evidence and intensity of settlement activities which produced it. This model has to take into account all of the following uncertainties inherent to archaeological data: (1) The actual time and place of past events is not known and lies within the boundaries given by dating and localization of the evidence. (2) The events took place in areas which had a certain extent in time and space. (3) The observed distribution of evidence is affected by variations in feature visibility, sampling intensity and accuracy. We can test the null hypothesis that changes in spatio-temporal distribution of archaeological evidence can be explained by fluctuations stemming from these uncertainties. If we assume that an archaeologically detected site of settlement activity (as defined by the settlement area theory) represents a spatio-temporal volume, rather than a single point in time and space, we need a probabilistic method, which considers spatial and temporal dimensions equally. We propose the Evidence Density Estimation (EDE) function, which can be applied on radiocarbon-dated evidence as well as typo-chronologically dated evidence to produce spatio-temporal distribution maps or summed distributions representing intensity of settlement activities within the examined area. **Paper on EDE:** Demján, P., & Dreslerová, D. (2016). Modelling distribution of archaeological settlement evidence based on heterogeneous spatial and temporal data. Journal of Archaeological Science, 69, 100–109. [DOI:10.1016/j.jas.2016.04.003](https://doi.org/10.1016/j.jas.2016.04.003) [Presentation on EDE in English](https://mfr.de-1.osf.io/render?url=https://osf.io/t78vh/?action=download%26mode=render) [Presentation on EDE in Slovak](https://mfr.de-1.osf.io/render?url=https://osf.io/h95v4/?action=download%26mode=render) ### EDE Interpolation plugin A QGIS 3 plugin for spatio-temporal interpolation of archaeological settlement evidence. Produces spatio-temporal distribution maps or summed distributions representing intensity of settlement activities within the examined area in different time periods. Uses radiocarbon-dated as well as typo-chronologically dated evidence as input. ### Installation **Install in QGIS**: Plugins -> Manage and Install Plugins -> search for "EDE Interpolation" The option "Show also experimental plugins" **must be enabled** in Plugins -> Manage and Install Plugins -> Settings ![enter image description here][2] ![enter image description here][3] ![enter image description here][4] ![enter image description here][1] [Download](https://plugins.qgis.org/plugins/ede_interpolation/) [Source code](https://github.com/demjanp/ede_interpolation) ### Data [Sample Data](https://osf.io/y6ak3/) [Data for Bohemia from the Archaeological Map of the Czech Republic and Slovak Archaeochronometric Database](https://osf.io/buvra/) ### Usage #### Input: * Shapefile with point data representing evidence of settlement activities (e.g. archaeologically dated components of excavation sites) in a projected coordinate system. #### Required fields for every feature in the source shapefile: * `Spatial Accuracy (m)` - radius around registered point, where the actual location of the evidence is expected. * `Dating Mean (years BP)` - mean value of dating of the archaeological component, representing either a Uniform Probability Distribution (UPD) of calendar years, or a Normal Probability Distribution (NPD) of radiocarbon years. * `Dating Uncertainty (years)` - half length of the UPD interval or 1 standard deviation of the radiocarbon age in case of an NPD interval. * `Dating Type ('UPD' or 'NPD')` - UPD is a range of calendar years BP (Before Present), assigned to an archaeological period (e.g. a culture), represented here as a mean value and half length of the interval. NPD is a radiocarbon age, represented here as a mean and standard deviation in radiocarbon years BP. #### Model parameters: * `Expected Settlement Duration (years)` - standard length of time that a settlement in the observed time and space is expected to exist, before it moves or in case of typological dating its cultural expression changes. * `Expected Settlement Diameter (m)` - standard size of a settlement core. A diameter of 200 m means a settlement of cca 1 ha area. #### Output parameters: * `Time Step (years)` - distribution maps representing probability of presence of evidence of settlement activities at different spatial coordinates will be created at regular intervals in time, specified by this value. Evidence is summed along the time axis for each time step. * `Time From (years BP)` - optional parameter specifying the begin of the observed time period. * `Time To (years BP)` - optional parameter specifying the end of the observed time period. * `Raster Cell Size (m)` - specifies length of the interpolation step along the spatial axes. * `Approximate Spatial Probability (yes/no)` - set to use a faster, but slightly less precise calculation of the spatial component of the EDE function. * `Save Output Layers to Directory` - specify directory where the spatial distribution maps in GeoTIFF format will be saved. * `Save Summed Probability to File` - specify location of a CSV file, where values of probability summed along the spatial axis for every time step from the Intcal13 calibration curve (the highest possible temporal resolution) will be saved. [1]: https://files.osf.io/v1/resources/v7ahe/providers/osfstorage/5e428f597610e10058ca44f3?mode=render [2]: https://files.osf.io/v1/resources/v7ahe/providers/osfstorage/5e428f147610e10053ca65fb?mode=render [3]: https://files.osf.io/v1/resources/v7ahe/providers/osfstorage/5e428f367610e1005cca4494?mode=render [4]: https://files.osf.io/v1/resources/v7ahe/providers/osfstorage/5e428f4ca057ec0050b08881?mode=render
OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.
Accept
This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.
Accept
×

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.