## 1 Introduction  
Healthy ecosystems are a primary source of vital resources for human welfare and survival while regulating the impacts of natural hazards and protecting human settlements against floods, landslides, and drought events, thus playing a key role in mitigating climate change effects [1]. Conserving biodiversity and preventing biodiversity shifts is, therefore, of significant importance and a main target of multiple international conventions. The Sustainable Development Goals (SDGs) [2] and the Paris Agreement by the United Nations Framework Convention on Climate Change (UNFCCC) [3] promote the conservation of ecosystems and their associated biodiversity. The conservation, restoration and sustainable use of ecosystems are specifically mentioned in SDG 6.6 and SDG 15.1. The first, SDG 6.6, aims to _\"protect and restore water-related ecosystems, including mountains, forests, wetlands, rivers, aquifers and lakes\"_, while SDG 15.1 aims at ensuring _\"the conservation, restoration and sustainable use of terrestrial and inland freshwater ecosystems and their services, in particular forests, wetlands, mountains and drylands, in line with obligations under international agreements\"_. Other agreements and commitments include the Aichi Biodiversity Targets by Parties of the United Nations (UN) and the Convention on Biological Diversity (CBD) [4; 5]. Providing information on the health of ecosystems status through monitoring activities is essential for applying suitable conservation and restoration practices. In recent years,Earth Observation (EO) technologies, particularly Satellite Remote Sensing (SRS), have been used to assist national authorities in monitoring programs for the achievement of the SDGs [6]. The main advantages of SRS include the provision of data in a systematic and timely way, the cost-effectiveness of monitoring activities and accessibility to remote areas [7; 8; 9]. SRS can capture biodiversity changes both at global and regional scales [10; 11], thus the joint use of SRS data with in situ data and images obtained from other technologies (Light Detection and Ranging (LiDAR), Unmanned Aerial Vehicle (UAV), etc.) is a key factor to generate actionable knowledge in real-time for improved decision-making [10]. To generate actionable knowledge, SRS data need to be translated into information and specifics metrics, maps, or consumable information products that can then be used to inform decision-makers. Structural and functional indicators are both required to evaluate the ecosystem's health. Structural indicators reflect on the extension and composition of the ecosystems; functional indicators are useful to understand whether the areas are fulfilling their ecosystem role [12]. Structural indicators are often used in monitoring programs whereas ecosystem functions are rarely measured [13; 14; 15; 16], although they are sensitive indicators of ecosystem health [17] and losses of biodiversity [18]. Ecosystem functions are the aggregation of multiple processes that overall define the ecosystem's capacity to bring benefits to a range of species [9; 19]. Among these components, is Primary Productivity (PP). PP can be categorized into Gross Primary Production (GPP), the total amount of carbon or energy captured by plants and Net Primary Production (NPP), the carbon allocated to plant tissue after accounting for the costs of autotrophic respiration. PP is a process that underpins most of the ecosystem functions essential for the understanding of the global carbon cycle [20]. Due to its relevance in the characterization of biodiversity change, PP is considered an Essential Biodiversity Variable (EBV). EBVs are defined as the derived measurements to study and manage biodiversity change, and their estimation is a step forward for integral monitoring programs and holistic health assessments in ecosystems [4; 21]. PP has been widely related to the Vegetation Indexes (VIs), used as a proxy for vegetation productivity and to create long-term and consistent data series.