The combined use of probability distribution models and remote sensing data can benefit the study of archaeological landscapes in the perspective of both archaeological risk impact assessment and scientific field surveys planning. A multiscale comparison between two predictive models a Geographical Information System (GIS) based multiparametric spatial analysis (MPSA) and the Maximum Entropy Model (MaxEnt) is presented. Both response (presence only) and independent variables included attributes derived by cartographic sources and satellite data. Best model selection (Akaike’s Information Criterion) and Receiving Operator/Area Under the Curve analysis indicated a better performance of MaxEnt with respect to the GIS-MSPA model. Insights on pitfalls and potentials for the progress of this kind of approach in the archaeology operational context are described.
Investigation of archaelogical sites with species distribution models and satellite data
Barbara Cafarelli;
2020-01-01
Abstract
The combined use of probability distribution models and remote sensing data can benefit the study of archaeological landscapes in the perspective of both archaeological risk impact assessment and scientific field surveys planning. A multiscale comparison between two predictive models a Geographical Information System (GIS) based multiparametric spatial analysis (MPSA) and the Maximum Entropy Model (MaxEnt) is presented. Both response (presence only) and independent variables included attributes derived by cartographic sources and satellite data. Best model selection (Akaike’s Information Criterion) and Receiving Operator/Area Under the Curve analysis indicated a better performance of MaxEnt with respect to the GIS-MSPA model. Insights on pitfalls and potentials for the progress of this kind of approach in the archaeology operational context are described.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
