Landscape Archaeology Research Group

Data collection

Archaeological and topographic surveys. We have developed many different types of surveys during the last years. While we conduct GIS-aided traditional pedestrian survey, we have also strongly contributed to defining specific survey types, such as archaeomorphological and high mountain surveys. We are now pioneering the first applications of automated drone-based survey, which combines drone-based photogrammetry and artificial intelligence to detect, map and extract remains of material culture dispersed on the soil surface. We also develop high resolution topographic surveys (using a combination of drones and differential GPS) and are able to analyse their results using cutting edge technology and algorithms developed in house.

Archaeomorphological analysis is one of our key areas of expertise. Archaeomorphological analysis is the study of landscape macrostructures (such as roads, field systems, irrigation networks, and so on) using mostly photographic and cartographic sources. This type of analysis has a long tradition but has been somewhat left outside of most current landscape studies as its results are very difficult to check and can lead to erroneous interpretations. During the last 12 years we have been developing complementary techniques that can improve and test archaeomorphological studies while integrating them within GIS environments. As a result we have long experience in georeferencing and rectification of cartographic and photographic sources, and automated extraction and digitalisation of features of interest. Our archaeomorphological studies are complex, detailed and accurate as they are based on multidisciplinary approaches that can verify and enrich archaeomorphological interpretations.

Remote Sensing and geosciences. GIAP is one of the few research groups in archaeology with capacity to develop multitemporal and multisource remote sensing applications at very large scales. Our research on remote sensing is designed to address specific archaeological questions and this is why we develop our own purposedly design algorithms for the archaeological projects we are working on. Remote sensing research at GIAP is never applied in isolation but combined with legacy archaeological data, geostatistics, GIS and filedwork, which are essential for the validation of the results and the achievement of more thorough understandings of their archaeological importance.

We use all kinds of platforms and sensors in our remote sensing approaches: from satellite multispectral and synthetic aperture radar to submilimetric-scanners, passing through aerial and drone applications. Our studies cover both palaeolandscape reconstruction and the location and analysis of elements of archaeological interest, using a wide selection of techniques, such as machine learning.

Data analysis and interpretation

GIS-based, geostatistical and geospatial analyses are some of the approaches we use to make sense of the data we collect using remote sensing, archaeomorphology and survey. These techniques allow us to use space as an interpretative tool that can be applied in many ways in different types of environments and analytical frameworks. From predictive route modelling to the analysis of the distribution of archaeological sites GIAP has developed a large toolbox to deal with all aspects of the archaeological analysis of past landscapes.

Artificial Intelligence (machine learning and deep learning) is playing an increasingly important role in our research. It allows us to automatise procedures that can be extremely taxing and/or repetitive if done manually. It can also be applied to many situations for which the information available is only partial as it can develop models using known examples that can be applied to the classification of datasets for which we do not have information. For example, we can use the spectral signature of known sites to develop a machine learning classifier that will be able to detect sites with similar signatures in satellite multispectral imagery. Artificial intelligence can be applied in many situations and our team is currently leading its application to landscape archaeology while expanding to other related fields, such as bioarchaeology and material culture.