# Autonomous Service Drones for Multimodal Detection and Monitoring of Archaeological Sites
## 1 Introduction  
Experts in digital cultural heritage endeavor to use detection techniques to document the physical dimensions of sites and cultural objects. They seek to use and keep digital material documented so that they remain usable for wider research and documentation [1]. Digital detection of heritage and historical places in reference-scaled models has become crucial, as many heritage sites are threatened by different human and natural factors. Since the 1970s, archaeologists have known about the potential of infrared thermal images for identifying structures not visible on the surface, including concentrations of materials, or landscape elements, including ancient roads, boundaries of cultivated fields, paleoriver beds, etc. [2].  
Thermal photography has evolved into a powerful nondestructive tool for cultural heritage conservation study [3, 4, 5]. Despite this long period, the excessive cost of thetechnologies used has greatly limited the possibilities of research. Now, a new phase of development is emerging throughout the expanding application of service drones in research. In particular, the recent advancements in drone technology and the development of commercial drones with thermal cameras are permitting, on the one hand, less expensive use costs and, on the other, accelerated reconnaissance [6; 7; 8; 9]. Infrared thermography offers a method of visualization that is nondestructive and capable of revealing various types of archaeological anomaly. The advantages of remote and nondestructive examination of cultural heritage are two-fold: data may be obtained without damage to the historic site, and information may be collected that no other technique is capable of extracting.  
The physical principle behind the analysis of thermal images is quite simple: the materials that are above and below the soil surface absorb, emit or reflect infrared rays in different ways, based on their composition, density and moisture content. Therefore, a large number of archaeological elements can theoretically be identified in thermal images as depicted in Figure 1[10].  
There are three essential factors for archaeological features to stand out in a thermal image, which can be summarized as follows:  
1. There must be a sufficient contrast between the thermal properties of the material of interest and those of the soil.
2. The archaeological material below the surface must be close enough to the surface to be affected by heat flux.
3. The thermal image must be acquired when the thermal differences are more pronounced as shown in Figure 2.  
Figure 1: Thermal image identification of archaeological elements, introduced by the authors in [10].  
Figure 2: Diurnal thermal variation in different soil, introduced by the authors in [9].  
These three factors are the basis of our proposed archaeological sites detection and monitoring framework. In the following sections, we will begin with a brief literature review and proceed to discussing our methodology. We will then discuss our testing and validation results and present a general conclusion from the benefits of the methodology.  
The main contribution of our work is an end-to-end framework for the detection and monitoring of archaeological sites. To achieve this goal, we also propose: (1) a two-stage multimodal depth-to-RGB and thermal-to-RGB mosaicking algorithm to align and aggregate collected images; (2) an AI-based detection algorithm to identify change regions in archaeological sites; (3) and a user interface for temporal tracking.