# GPR Data Interpretation Approaches in Archaeological Prospection
## 3 Attribute Analysis  
Attribute analysis was initially performed in seismic data to enhance target detection and improve their interpretability. Although it has not yet fully been incorporated in GPR data processing routines from archaeological prospection, examples found in the literature show a promising lead in improving data imaging. The main concept is to calculate specific attributes aside from the conventional instantaneous amplitude, to highlight archaeological targets that are less sensitive to amplitude changes and might end up being invisible. This analysis is target-directed, meaning that more effort is required to find the most appropriate ones. A few examples found in the related literature are presented in the following paragraphs.  
Several attributes are calculated and studied in Reference [11] aiming to improve interpretation on complex datasets that exhibit archaeological remains of the Roman period buried at different depths. This approach calculates the attributes under investigation in the volumetric GPR data after applying denoising and other processing techniques to improve the signal-to-noise ratio. Namely, the tested attributes are the instantaneous amplitude, the cosine of instantaneous phase, edge detection attributes, the dominant frequency, the similarity and the energy. Their results showed that each attribute highlights specific information. Hence, performing a target-oriented and multi-attribute approach along with the standard process is suggested. In a similar study, RMS amplitude, average peak amplitude, instantaneous phase, and maximum peak time are extracted and compared to characterize an ancient wall, a kiln, and a tomb [12]. Again, the results indicate that attribute selection should be target-oriented.  
In another study, the energy, coherency, and similarity attributes are calculated to interpret data collected with a 3D radar system at two medieval chapels [13]. The results show that coherency and similarity can improve the interpretability of the data and target detection as information invisible to the standard amplitude maps was visualized, revealing more details on detected tombs and burial chambers along with their conservation state. Energy and similarity also helped improve the data interpretability of Roman structural remains found at deeper levels and under complex subsurface layers [13]. Excavations that followed were in agreement with the resulted GPR interpretation. Additionally, small targets of a prehistoric period settlement were also enhanced by an integrated multi-attribute approach of instantaneous amplitude, energy, and similarity, which were visualized using iso-surfaces [14]. Excavations that followed validated the GPR interpretation. In another example, the coherence attribute and the conventional instantaneous amplitude are compared and fused into a single image, enhancing the interpretation of data collected with a 3D GPR system from three Scandinavian Iron age sites exhibiting trenches, pitfalls, and postholes [15]. Some of the sites are multiphased exhibiting archaeological remains that are either Roman or Medieval. The authors used a simple normal blending method and contrast normalization to fuse the images. Finally, an integrated instantaneous attribute approach is performed in Reference [16], highlighting patterns of an ancient road.  
A different set of attributes utilizing image texture analysis is extracted from GPR data collected in three archaeological sites in Italy to characterize targets of different historical periods [17]. These are textural attributes based on the gray-level co-occurrence matrix, namely contrast, homogeneity, energy, and entropy. This approach improved pattern discrimination of the observed targets as well as interpretability of the complex environment when combined displays of the calculated attributes are employed.