Although drone thermography is increasingly applied as an archaeological remote sensing tool in the last few years, the technique and methods are still relatively under investigated. No doubt there are successes in positive identification of buried archaeology, and the prospection technique has clear complementary value. Nevertheless, there are also instances where thermograms did not reveal present shallow buried architectural features which had been clearly identified by, for example, ground-penetrating radar. The other way around, there are cases where the technique was able to pick up a signals of buried archaeology at a time of day that is supposed to be very unfavorable for thermographic recording. The main issue here is that the exact factors determining the potential for tracing thermal signatures of anthropomorphic interventions in the soil are many, and their effect, context, and interaction under investigated. This paper deals with a systematic application of drone thermography on two archaeological sites in different soils and climates, one in The Netherlands, and one in Italy, to investigate important variables that can make the prospection technique effective.

This paper addresses the design of open, reproducible, and transferable workflows for remote sensing data processing in archaeology, the specific case being drone (UAS) remote sensing data. In the context of increased application of remote sensing, stimulated by both recent technological developments, as well as threats to the buried archaeological record by developments such as agricultural intensification and climate change, it is important to allow the archaeological community to really benefit from the multitude of remote sensing applications and their diverging modalities. With the ever-increasing remote sensing datasets spread throughout the field of cultural heritage and archaeology, it has become even more important to be able to clearly communicate the process from data capture to the eventual visualised data model and further archiving and dissemination. This is crucial to scientific transparency required for the assessment of data quality, for example to allow for evaluating interpretations, comparative research, and replication studies. The ultimate goal is to permit data publication adhering to FAIR (Findable, Accessible, Interoperable, Reusable) principles, for which a good metadata documentation is a cornerstone.

Whereas archaeological field survey is relatively fast and effective for the mapping of surface finds in Mediterranean landscapes, two challenges limit its potential for reconstructing ancient settlement patterns. First, field survey usually excludes portions of the landscape that are inaccessible or present low ground visibility due to vegetation or the terrain, and second, including large settlements sites poses logistical problems, as these tend to produce unmanageably high frequencies of finds. In this paper, we explore the potential value of point sampling for integrating these areas in standard transect field survey projects. For this experiment, we sampled a large rural Archaic–Roman period site and its off-site environs in Molise, central-southern Italy. We present a systematic statistical and spatial comparison between data derived from both methods on the same areas. As such, the experiment contributes to the current debate on how to compare and integrate data from survey projects that apply different techniques.

In the practice of archaeological field survey there is a manifest importance for densities, that is, an abundance of artifacts, often relying on simple counts of objects. However, a well‐known issue is variable breakage of pottery that can cause biases in quantitative analysis. Although such issues are generally acknowledged, a direct assessment of breakage and the resulting biases is lacking in research. This paper explores the pros and cons of quantification methods of surface collections in terms of counts or weights, and demonstrates the importance of analysing weight and breakage as part of an integrative approach.