Archaeological Materials Science

Activity type

Attività formative affini o integrative

SSD

BIO/07

Year

2nd year

Semester

1st semester

CFU

3

Hours distribution

20 classroom hours, 10 laboratory hours

Lecturers

LUCA MALATESTA

Activity type

Attività formative affini o integrative

SSD

BIO/03

Year

2nd year

Semester

1st semester

CFU

3

Hours distribution

10 classroom hours, 20 laboratory hours

Lecturers

LUCA MALATESTA

At the end of the course the student will have acquired a knowledge on the use of Geographic Information Systems in in archaeological sciences and an understanding of a range of ideas about quantitative approaches to archaeology from how to make better graphs to how we can phrase archaeological questions in a range of quantitative ways.

Module: GIS
- Identify types of variables (quantitative, categorical, continuous and discontinuous)
- Compute descriptive statistics and central measures of a distribution
- Test the normality of distributions and normalize non-normal data
- Carry out bivariate and multivariate correlation and linear regression analyses
- Formulate and test scientific hypotheses based on statistical analyses
- Develop a data collection and processing methodology based on the hypotheses formulated
- Create graphs and summary tables to view analysis results
- Comment on the results of the analyzes based on the knowledge acquired and the existing literature


Module: STATISTICAL TOOLS
- Obtain spatialized data from online repositories
- Loading and dressing raster and vector layers
- Creation of map layouts
- Digitization of points, lines and polygons
- Collection of spatialized data in the field
- Slope and aspect analysis from digital elevation models
- Calculation of multispectral indices
- Creation of geodatabases
- Calculation of distances, perimeters and areas
- Calculation of spatial statistics
- Join of attributes by value and position

Module: GIS
Basic usage of standard Operating Systems (Windows / MacOS / Linux)
Use of spreadsheet software (Excel / OpenOffice Calc / LibreOffice Calc)
Basic concepts of mathematics, algebra and calculus


Module: STATISTICAL TOOLS
Basic usage of standard Operating Systems (Windows / MacOS / Linux)
Use of spreadsheet software (Excel / OpenOffice Calc / LibreOffice Calc)

Module: GIS
- Descriptive Statistics 1: mean, mode and median. Calculation examples and differences between moments. Use of MS Excel spreadsheets for processing.
- Descriptive Statistics 2: Analysis of data variability around the mean and median. Presentation and use of open source software for statistical analysis.
- Descriptive statistics 3: Calculation of variance, standard deviation, standard error, coefficient of variation. Evaluation of the different fluctuations around the mean.
- Introduction to the concept of data normality. Gaussian curve and its use in statistical analysis. Data normalization. Data transformation for normalization purposes.
- One-way analysis of variance ANOVA. Comparison of averages. Introduction to the concepts and use of ANOVA. Examples of ANOVA calculation.
- Introduction to two-way ANOVA and presentation of calculation examples. Neumann-Keuls, Bonferroni, and Tukey tests.
- Correlation analysis. Meaning of r and of r^2. Statistical model concept. Introduction to linear regression. Calculation and meaning of linear regression coefficients.
- Application of linear regression models for predictive purposes. Use of "large databases". Applying linear regression analysis using open source software.
- Multiple linear regression analysis. Evaluation of the statistical significance of coefficients and statistical models. Applications.
- Archaeological approaches to data. Spatial analysis, Seriation, Assemblage diversity.


Module: STATISTICAL TOOLS
General introduction
• Basic concepts about Geographic Information Systems
• GIS software: desktop applications, webGIS, commercial and open source alternatives
• Types of digital maps: vectors, raster and related characteristics
• Georeferencing and projection systems
• Potential GIS use, presentation of case studies

Types of geographic data
• Vector layers and thematic maps
• Digital Elevation Models and Digital Terrain Models
• Multispectral satellite images
• Spectral transformations and indexes: NDVI, NDWI, NDSI, fire detection etc.
• Climate and soil data
• Land Cover and Land Cover Change data
• Online repositories of open GIS data

Basic operations in QGIS
• Browser, data source manager and data loading
• Map canvas and navigation
• Layer styling and labeling
• Layer grouping and themes
• Layout manager and map renders
• Basic vector editing

Advanced operations with GIS data
• Advanced vector editing
• Database editing and field calculator
• Vector analysis and geoprocessing
• Raster calculator
• Vector-raster conversion
• Geospatial Data Abstraction Library (GDAL): main functions and usage
• Spatial statistics and spatial join

Remote Sensing basics
• Satellites and Earth observation
• EM spectrum and RS bands
• Spatial and temporal resolution
• Free and commercial RS data sources
• Earth observation missions and related products
• RS data visualization: RGB and false color
• Segmentation, unsupervised and supervised classification of RS data

webGIS applications
• Basic concepts about webGIS
• Google Earth Engine Explorer and Code Editor
• Introduction to GEE Playground: scripts, assets and basic operation
• Access to global datasets and image processing in GEE Playground
• EarthMap, a GUI frontend to the GEE playground

Geodatabases
• Basic concepts about databases
• Relational Data Base management Systems
• PostgreSQL and PostGIS
• Basic SQL operation: SELECT, UPDATE, CREATE, DROP syntax
• Basic PostGIS operation: “st_” functions
• Creation of a simple geodatabase
• Accessing and managing geodatabases from QGIS

Module: GIS
Reference text: Carlson, D.L. Quantitative methods in Archaeology using R. Cambridge University Press, 2017. 455 pp.

Theory slides used by the teacher and provided to the students
Resources for practical applications provided by the teacher


Module: STATISTICAL TOOLS
Theory slides used by the teacher and provided to the students
Resources for practical applications provided by the teacher

References for practical applications:
QGIS.org, 2023. QGIS 3.28. Geographic Information System User Guide. QGIS Association. Electronic document: https://docs.qgis.org/3.28/en/docs/user_manual/index.html
Cardille J.A., Clinton N., Crowley M.A., Saah D. (eds.) Cloud-Based Remote Sensing with Google Earth Engine: Fundamentals and Applications. Electronic document: https://www.eefabook.org/go-to-the-book.html

Online resources for practical applications:
https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units/countries
https://gadm.org/index.html
https://openlandmap.org/
https://chelsa-climate.org/
https://earthengine.google.com/
https://earthmap.org/

Module: GIS
N/D
Module: STATISTICAL TOOLS
N/D

Module: GIS
Classroom lessons will be complemented by practical activities, consisting of the statistical analysis of example data sets. For data processing the "JASP" software will be used (downloadable for free from the official website, or alternatively provided by the teacher).


Module: STATISTICAL TOOLS
Classroom lessons will be integrated with practical activities, consisting of the visualization and processing of example spatial data. For data processing the "QGIS" software will be used (downloadable for free from the official website, or alternatively provided by the teacher).

Module: GIS
It is necessary to attend the lessons in presence
To carry out the practical activities a laptop running Windows, MacOS or Linux operating system will be required


Module: STATISTICAL TOOLS
It is necessary to attend the lessons in presence
To carry out the practical activities a laptop running Windows, MacOS or Linux operating system will be required

Module: GIS
The oral exam will consist of an assessment of the ability to analyze an example data set. The concepts taught during the course will be applied to a dataset provided by the teacher, and errors of analysis and evaluation will be corrected.
In addition to the analysis of the dataset, some theoretical questions dealing with the concepts taught during the course may be asked.


Module: STATISTICAL TOOLS
The oral exam will consist in the presentation of a simple digital mapping project, realized through the skills acquired and the tools used during the lessons. The presentation should include a general overview of the topic and the study area and a detailed illustration of the methodology adopted and the results obtained. The theme of the presentation can be agreed with the teacher during class or receiving hours.
In addition to the evaluation of the project, some theoretical questions dealing with the methods used for the project itself may be asked.

Module: GIS
- Quantitative and categorical variables: properties and differences
- Normality tests
- Descriptive statistics
- Histograms and density curves
- Tests for comparing means
- Analysis of variance
- Correlation analysis


Module: STATISTICAL TOOLS
- Basic and advanced vector editing
- Creation of contours
- Zonal statistics
- Creation of point vector layers from a table of coordinates
- Spatial reference systems and reprojection of layers
- Rule-based symbology

Module: GIS
N/D
Module: STATISTICAL TOOLS
N/D