Earth observation (EO) techniques have significantly evolved over time, covering a wide range of applications in different domains. The scope of this study is to review the research conducted on EO in the Eastern Mediterranean, Middle East, and North Africa (EMMENA) region and to identify the main knowledge gaps. We searched through the Web of Science database for papers published between 2018 and 2022 for EO studies in the EMMENA. We categorized the papers in the following thematic areas: atmosphere, water, agriculture, land, disaster risk reduction (DRR), cultural heritage, energy, marine safety and security (MSS), and big Earth data (BED); 6647 papers were found with the highest number of publications in the thematic areas of BED (27%) and land (22%). Most of the EMMENA countries are surrounded by sea, yet there was a very small number of studies on MSS (0.9% of total number of papers). This study detected a gap in fundamental research in the BED thematic area. Other future needs identified by this study are the limited availability of very high-resolution and near-real-time remote sensing data, the lack of harmonized methodologies and the need for further development of models, algorithms, early warning systems, and services.

Water-scarce areas are threatened by climate crisis and, thus, there is an urgent need for optimizing water resources management. Remote sensing has been widely used for calculating the evapotranspiration over large areas, which is an essential variable for calculating the actual irrigation needs of crops. The main objective of this work is to design an approach to optimize the irrigation needs for specific crops. The island of Cyprus is used as a case study providing first insights for water management in the country. The proposed approach is crucial to the agricultural industry of Cyprus since it is located in the Mediterranean region which is affected by warm climate and drought events. Specifically, the proposed approach calculates daily the crop evapotranspiration over the island for three of the most important crops (i.e., citrus, olives, and potatoes) cultivated in Cyprus. The results of this study are showing that the three crop types are withdrawing much more water than the total annual inflow of reservoirs in 2023. Therefore, better irrigation management needs to be adopted by farmers while optimized water resources management practices have to be embraced by local authorities and stakeholders.

Long-term monitoring studies on the transition of different land cover units to barren areas are crucial to gain a better understanding of the potential challenges and threats that land surface ecosystems face. This study utilized the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover products (MCD12C1) to conduct geospatial analysis based on the maximum extent (MaxE) concept, to assess the spatiotemporal changes in barren areas from 2001 to 2022, at global and continental scales. The MaxE area includes all the pixels across the entire period of observations where the barren land cover class was at least once present. The relative expansion or reduction of the barren areas can be directly assessed with MaxE, as any annual change observed in the barren distribution is comparable over the entire dataset. The global barren areas without any land change (UA) during this period were equivalent to 12.8% (18,875,284 km²) of the global land surface area. Interannual land cover changes to barren areas occurred in an additional area of 3,438,959 km² (2.3% of the global area). Globally, barren areas show a gradual reduction from 2001 (91.1% of MaxE) to 2012 (86.8%), followed by annual fluctuations until 2022 (88.1%). These areas were mainly interchanging between open shrublands and grasslands. A relatively high transition between barren areas and permanent snow and ice is found in Europe and North America. The results show a 3.7% decrease in global barren areas from 2001 to 2022. Areas that are predominantly not barren account for 30.6% of the transitional areas (TAs), meaning that these areas experienced short-term or very recent transitions from other land cover classes to barren. Emerging barren areas hotspots were mainly found in the Mangystau region (Kazakhstan), Tibetan plateau, northern Greenland, and the Atlas Mountains (Morocco, Tunisia).

Earth Observation (EO) techniques have significantly evolved over time, covering a wide range of applications in different domains. The scope of this study is to review the research conducted on EO in the Eastern Mediterranean, Middle East, and North Africa (EMMENA) region and to identify the main knowledge gaps. We searched through the Web of Science database for papers published between 2018 and 2022 for EO studies in the EMMENA. We categorized the papers in the following thematic areas: Atmosphere, Water, Agriculture, Land, Disaster Risk Reduction (DRR), Cultural Heritage, Energy, Marine Safety and Security (MSS) and Big Earth Data (BED); 6647 papers were found with the highest number of publications in the thematic areas of BED (27%) and Land (22%). Most of the EMMENA countries are surrounded by sea, yet there was a very small number of studies on MSS (0.9% of total number of papers). This study detected a gap in fundamental research in the BED thematic area. Other future needs identified by this study are the limited availability of very high resolution and near real time remote sensing data, the lack of harmonized methodologies and the need for further development of models, algorithms, early warning systems and services.

The concept of sustainable intensification in agriculture necessitates the implementation of management practices that prioritize sustainability without compromising productivity. However, the effects of such practices are known to depend on environmental conditions, and are therefore expected to change as a result of a changing climate. We study the impact of crop diversification on productivity in the context of climate change. We leverage heterogeneous Earth Observation data and contribute a data-driven approach based on causal machine learning for understanding how crop diversification impacts may change in the future. We apply this method to the country of Cyprus throughout a 4-year period. We find that, on average, crop diversification significantly benefited the net primary productivity of crops, increasing it by 2.8%. The effect generally synergized well with higher maximum temperatures and lower soil moistures. In a warmer and more drought-prone climate, we conclude that crop diversification exhibits promising adaptation potential and is thus a sensible policy choice with regards to agricultural productivity for present and future.