Landscape analysis with landscape metrics

The aim of this tutorial is to familiarize the user with the concept of landscape metrics (LM) and their capacity as landscape descriptors in an archaeological context. The tutorial provides a detailed method for applying LM to remote sensing data in archaeological studies using QGIS and Fragstats. It begins with instructions on installing these essential tools and proceeds to guide users through visualizing both classification and original images in QGIS. The tutorial then moves to image filtering in QGIS. This refined data is then imported into Fragstats for in-depth analysis using nine metrics at class and landscape levels. The tutorial exemplifies how the results can be interpreted, helping users understand each metric's significance in an archaeological context. Metrics like the Landscape Patch Index and Edge Density are explained in terms of their utility for understanding distribution density of archaeological sites, settlement patterns, and interactions between land uses in historical settings. Additionally, the tutorial offers a background on the importance of LM in landscape ecology, stressing their role in assessing biodiversity, habitat fragmentation, and human activity impacts. It also touches on the innovative application of these metrics in archaeology, highlighting the potential to significantly enhance understanding of anthropological and historical landscapes. Overall, this tutorial aims to be a resource for archaeologists and researchers, combining practical analytical steps with theoretical insights. It ensures users not only execute the analysis correctly but also comprehend the implications of their findings in archaeological research.

This tutorial is part of a group of tutorials focused on landscape analysis, integrating digital methods to study and interpret archaeological landscapes. All tutorials can be found on the DARKLab website and are created within the Swedish National Infrastructure for Digital Archaeology (Swedigarch). Explore more at the Swedigarch website.