## 1 Introduction
In particular, only the definition of LC is fundamental, because in many existing classifications and legends it is confused with land use. LC is defined as the observed (bio)physical cover on the Earth's surface. According to this definition, land covers include forests, agricultural areas, human settlements, glaciers, water and wetlands per the Directive 2007/02 of the European Commission [24; 25]. When considering LC in a very pure and strict sense, it should be confined to describe vegetation and man-made features. Consequently, the areas where the surface consists of bare rock or bare soil are describing land itself rather than LC. Additionally, it is disputable whether water surfaces are considered land cover. However, in practice, the scientific community usually describes those aspects under the term LC as well as some agricultural types of cover such as orchards, vineyards and pastures. The application of Sentinel-2, Sentinel-1 and PlanetScope in land cover mapping have rapidly spread since 2020 [26]. Earth Observation data applications from multi-platform sensors, in particular from Sentinel-2, Sentinel-1 and PlanetScope, are mainly focused on plain areas [27]. There is still a lack of local application mountainous area. Most of classification approaches are based on single one-shot classifications or combined approaches with two supervised classifications from optical and SAR data [28]. Others are focused on multimodal remote sensing data fusion from open-access and commercial EO data in cloud platform, such as the Google Earth Engine, and in deep learning classification (mainly focused on classifying a single geometrical land cover component such as urban areas) [29]. Nevertheless, a mixed hierarchical approach adopting different sensors and several classifications to improve the land cover quality on mountainous areas still continues to be minutely explored and exploited. Under this scenario, the development of a local LC EO continuous service according to the new EAGLE guidelines is becoming of great interest to the public administration at the alpine level and beyond. In fact, at the national level in Italy, the Istituto Superiore Per la Protezione e Ricerca Ambiente (ISPRA) produced and updated the national land consumption map, as well as several national land use and LC maps [21; 22], but they do not necessary fit with alpine needs. Conversely, other regional products are frequently produced with CLC and are not up to date [30; 31] or, in the case of high resolution global updated products such as Dynamic World, they do not answer to the local needs in terms of the accuracies, methodologies followed and legends. Therefore, in order to fill the gap of a lack of a LC at high resolution and answering to the EAGLE requests, the Aosta Valleyautonomous region charged the Regional Cartographic Office to develop a new map with a 10 m GSD. This body commissioned the regional public company INVA spa, in particular the GIS unit, to carry out this work. The intent was to create a static product and service capable of dynamically mapping the Aosta Valley territory according to the required needs. Therefore, the principal aim of this work is to present the new Aosta Valley LC and create a scalable and economically sustainable local EO service capable of mapping LC according to the EAGLE guidelines. The EO service developed adopted SAR Sentinel-1; Sentinel-2; PlanetScope and updated GIS local datasets to overcome the common troubles that remote sensing (RS) has in mountainous areas due to the topography, weather condition and shadows, as well as uniform LC class distributions.