## 1 Introduction  
Various hazards, both anthropogenic and natural, can affect cultural heritage landscapes, sites, and monuments. These hazards include fires, landslides, soil erosion, agricultural pressure, and urban expansion [1; 2; 3; 4; 5]. In the recent past, several publications have demonstrated the benefits of Earth Observation sensors, providing wide and systematic coverage over archaeological sites providing systematic observations at medium and high-resolution images [6; 7; 8; 9; 10]. In addition, access to archival images is a unique advantage of Earth Observation repositories, allowing for the analysis of the temporal evolution of a hazard [11; 12; 13]. Nowadays, open and freely distributed satellite images, both radar and optical, have become available due to the European Copernicus Programme [14]. The Sentinel sensors, with increased revisit time and medium-resolution satellite images, can be downloaded through specialized big data cloud platforms such as the Sentinel Hub [15]. These kinds of services provide radiometric and geometric corrected Bottom of Atmosphere (BOA) reflectance bands of the Sentinel-2A,B sensors, as well as orthorectified gamma 0 VV and VH radar images of the Sentinel-1 Synthetic Aperture Radar (SAR) sensor (ascending and descending). Beyond these calibrated images, other ready products are available for further re-use, like optical and radar vegetation indices (e.g., the Normalized Difference Vegetation Index--NDVI and the Radar Vegetation Index--RVI). Pseudo-colour composites can be readily displayed in the Sentinel Hub service, thus enhancing urban and agricultural areas, while classification products are also provided. Monitoring vegetation dynamics and long-term temporal changes of vegetation cover is of great importance for assessing the risk level of a hazard [16; 17]. For instance, the decrease of vegetation cover, as a change to either the NDVI or RVI, can be a signal for land-use change and a result of the urbanization sprawl phenomenon [18; 19; 20; 21]. In contrast, an increase in the vegetation cover, beyond the phenological cycle of the crops, can be a warning of agricultural pressure [22; 23; 24]. Similarly, vegetation indices are input parameters for studying other hazards such as soil erosion and fires [25; 26]. For soil erosion, vegetation cover is linked with the land cover factor, which indicates the proportion of water that runs on the ground surface. A decrease of vegetation in a concise period can be an indicator of a fire event. For instance, [PERSON] et al. [27] used the NDVI to estimate the soil erosion by water, based on the Revised Universal Soil Loss Equation. In [PERSON] et al. 's study [28], multi-temporal vegetation indices analysis was used to map fire events and help to understand and interpret archaeological problems related to past settlement patterns or environmental scenarios. However, in many cases, optical and radar vegetation indices are applied separately with no synergistic use, thus minimizing the full potentials of existing Earth Observation systems. In this study, we aim to investigate the use of optical and radar images, from freely available and open-access datasets, like the Sentinel-1 and Sentinel-2 sensors for estimating the proportion of vegetation cover. The investigation was supported by other open access services, namely the crowdsourced OpenStreetMap initiative. OpenStreetMap is an editable geo-service with more than 6 million users all around the world. These ground-truthed datasets can be used to train the medium-resolution Sentinel images, for detecting fully vegetated and non-vegetated areas. Additionally, Google Earth, a free platform that provides systematic snapshots of high-resolution optical satellite data, can be used as an evaluation of the OpenStreetMap datasets.