Integrating Archaeological Data in Multidisciplinary Environmental Studies—Methodological Notes from High-Resolution Mapping of Ancient Features in Southern Israel

Abstract

The article presents two aspects of a project of high-resolution mapping of archaeological features in the southern region of Israel, which was conducted intermittently between 2003 and 2016. One aspect is archaeological, with emphasis on the dense features underlying the area on the periphery of ancient settlements; the second aspect is the objective of integrating the data in multidisciplinary environmental studies. The main conclusion derived from the mapping project is that the existing data in the databases and publications, despite their richness, will not suffice and that there is a need to return to the field and supplement the features in accordance with the aims of the study. Sorting the collected features is a no less complex challenge, as is the relationship with the settlements in question. This challenge calls for expertise gained from cumulative experience gained in fieldwork, for the simple reason that the features date from different periods, and the potential correlation of certain features with a specific settlement is the test. This kind of upgrading with regard to the archaeological aspect in multidisciplinary environmental studies is critical because, in our view, the archaeological data lag behind the technological development of accompanying research, including research that has employed remote sensing as well as a variety of laboratory tests. It has been found that quite a few of these advanced studies use terms such as “site”, which in many cases is no more than a point indicating the general location of feature distribution. The same applies to the use of dating as a preferred goal before investing the necessary effort in sorting the features. If this effort is not invested first, there is no way of conclusively determining what is being dated and how dating a specific object contributes to understanding the settlement distribution in a region.