Given the environmental issues that today’s societies confront, such as climate change, waste management, ecosystem deterioration, etc., environmental education is becoming increasingly important. Adoption of environmental education as an integral part of the educational system is required for the Environmental Education Center (EEC) to be able to provide knowledge, skills, and values so that society can become active and environmentally responsible through awareness-raising. According to the scholarly published research, EECs can positively affect local communities and create an environmentally friendly culture. In addition, given that EECs can even play a significant part in the development of lifelong learning activities at the education and sustainable development nexus, it is considered critical to establishing future potentials and dynamics. Thus, aiming to analyze EECs’ strengths, weaknesses, opportunities, and threats (SWOT analysis) within our complex and ever-evolving world, educators, students, and other fellow citizens in Cyprus and Greece participated in a survey in which they were asked to fill in a questionnaire, specifically developed for each group category. The findings of this study provide a deeper understanding of the implications arising as a result of effective environmental education absence, as well as the importance of a holistic approach through EECs. Moreover, it offers the research community a solid framework for future innovation in citizen engagement and training.

Accurate mapping of forest habitats, especially in NATURA sites, is essential information for forest monitoring and sustainable management but also for habitat characterisation and ecosystem functioning. Remote sensing data and spatial modelling allow accurate mapping of the presence and distribution of tree species and habitats and are valuable tools for the long-term assessment of habitat status required by the European Commission. In order to serve the above, the present study aims to propose a methodology to accurately map the spatial distribution of forest habitats in three NATURA2000 sites of Cyprus by employing Sentinel-1 and Sentinel-2 data as well as topographic features using the Google Earth Engine (GEE). A pivotal aspect of the methodology identified was that the best band combination of the Random Forest (RF) classifier achieves the highest performance for mapping the dominant habitats in the three case studies. Specifically, in the Akamas region, eight habitat types have been mapped, in Paphos nine and six in Troodos. These habitat types are included in three of the nine habitat groups based on the EU’s Habitat Directive: the sclerophyllous scrub, rocky habitats and caves and forests. The results show that using the RF algorithm achieves the highest performance, especially using Dataset 6, which is based on S2 bands, spectral indices and topographical features, and Dataset 13, which includes S2, S1, spectral indices and topographical features. These datasets achieve an overall accuracy (OA) of approximately 91–94%. In contrast, Dataset 7, which includes only S1 bands and Dataset 9, which combines S1 bands and spectral indices, achieve the lowest performance with an OA of approximately 25–43%.

Land degradation, desertification and tree mortality related to global climate change have been in the spotlight of remote sensing research in recent decades since extreme climatic events could affect the composition, structure, and biogeography of forests. However, the complexity of tree mortality processes requires a holistic approach. Herein, we present the first global assessment and a historical perspective of forest tree mortality by reviewing both remote sensing and meteorological ground-based studies. We compiled 254 papers on tree mortality that make use of remotely sensed products, meteorological ground-based monitoring, and climatic drivers, focusing on their spatial and temporal patterns and the methods applied while highlighting research gaps. Our core results indicate that international publications on tree mortality are on the increase, with the main hotspots being North America (39%) and Europe (26%). Wetness indicators appear as the barometer in explaining tree mortality at a local scale, while vegetation indicators derived from multispectral optical sensors are promising for large-scale assessments. We observed that almost all of the studies we reviewed were based on less than 25 years of data and were at the local scale. Longer timeframes and regional scale investigations that will include multiple tree species analysis could have a significant impact on future research.

Land degradation, desertification and tree mortality related to global climate change are in the spotlight of Remote Sensing research in recent decades, since extreme climatic events could affect the composition, structure and biogeography of forests. However, the complexity of tree mortality processes requires a holistic approach. Herein, we present the first global assessment and a historical perspective of tree mortality by reviewing both Remote Sensing and ground-based studies. We compiled 254 papers on tree mortality that make use of remotely sensed products, ground-based monitoring and climatic drivers, focusing on their spatial and temporal patterns, in the methods applied, while highlighting research gaps. Forested ecosystems, especially in the Mediterranean area, appear to have experienced often climatic-induced physiological stress under extreme droughts and warming, raising concern that forests may become increasingly vulnerable to tree mortality. Our core results indicated that international publications on tree mortality are on the increase with the main hotspots being North America (39%) and Europe (26%). Wetness indicators appear as the barometer in explaining tree mortality on a local scale, while vegetation indicators derived from multispectral optical sensors are promising for large scale assessment. We observed that almost all of the studies we have reviewed were based on less than 25 years of data and were of local scale. Longer timeframes and regional scale investigations that will include multiple tree species analysis could have a significant impact on future research.

Widespread tree mortality is increasingly associated with extreme drought, yet its mechanisms remain poorly understood. To address this, we investigated which indicators most accurately delineate the relationship between climatic stressors and satellite-derived metrics related to tree crown/forest canopy conditions and forest decline for conifers and evergreen broadleaves. The study was performed between 1990 and 2020 in woodlands of Cyprus dominated by Juniperus phoenicea , Pinus brutia , and Quercus alnifolia (endemic to Cyprus). Landsat 5, 7, 8 and 9 images were used to assess the condition of tree crowns via 8 remote sensing (RS) indicators (NDMI, EVI, GPP, LAI, NBR, NDVI, NDWI, SAVI) correlated, thereafter, with the SPI, SPEI and PDSI drought indicators. Our findings clearly outline that very severe drought conditions <−2 for the SPI-12 and the SPEI-12, or <−5 for the PDSI-12, exceeded the capacity of all 3 species to sustain healthy stands at habitats representing the xeric limits of their natural distribution range in Europe. Very low precipitation appears as the driving force. However, starting from the year of drought induced mortality and including the years that followed, their annual vegetation’s response via decadal monitoring was related to climate averaged over 4 to 7 past years (including the year of monitoring) depending on species. Observed multi-year associations are consistent with a ‘memory’ effect that may reflect cumulative depletion and slow recharge of deeper, root-accessible moisture pools; however, our remote-sensing indicators do not directly perceive subsurface storage. NBR and NDMI were significantly connected with climatic variability, as described by the SPI or SPEI for the J. phoenicea and by the PDSI for the P. brutia , before and at the first years after mortality has occurred. After some years after the mortality year, the decadal response of vegetation to climate was better described by the NDVI. Before oak mortality the RS indicators applied failed to capture the evergreen vegetation dynamic of Q. alnifolia dense stands. Thereafter, the NDVI provides the highest accuracy, as the oaks likely experienced more severe and faster defoliation than the conifers, reducing their vegetation density at levels detectable by the NDVI. Thus, our study highlights the importance of considering long-term drivers for tree foliage-defoliation status, dependent on species type and habitat-specific water availability. This understanding can explain the types of droughts (seasonal to multiyear) that can trigger tree mortality under climate change.