Marine phanerogams are considered biological sentinels or indicators since any modification in seagrass meadow distribution and coverage signals negative changes in the marine environment. In recent decades, seagrass meadows have undergone global losses at accelerating rates, and almost one-third of their coverage has disappeared globally. This study focused on the dynamics of seagrass meadows in the northern Adriatic Sea, which is one of the most anthropogenically affected areas in the Mediterranean Sea. Seagrass distribution data and remote sensing products were utilized to identify the stable and dynamic parts of the seagrass ecosystem. Different seagrass species could not be distinguished with the Sentinel-2 (BOA) satellite image. However, results revealed a generally stable seagrass meadow (283.5 Ha) but, on the other hand, a stochastic behavior in seagrass meadow retraction (90.8 Ha) linked to local environmental processes associated with anthropogenic activities or climate change. If systemized, this proposed approach to monitoring seagrass meadow dynamics could be developed as a spatial decision support system for the entire Mediterranean basin. Such a tool could serve as a key element for decision makers in marine protected areas and would potentially support more effective conservation and management actions in these highly productive and important environments.

The urban heat island (UHI) phenomenon has been gaining intensity because of population growth, continuous urbanization and inappropriate urban planning and design. Geospatial models can importantly contribute to solving the negative impacts left behind by these developments in the urban environment. Here, the influence of different weather patterns (anticyclonic, cyclonic and advective), occurring as a consequence of regional synoptic conditions, on UHI intensity and morphology was studied. The previously published geographically weighted regression UHI model was used in order to predict the behaviour of the urban–rural temperature anomaly in different weather patterns in a small city named Ljutomer (8 km² of built‐up area occupied by 3,500 inhabitants) located in the northeast part of Slovenia. As expected, UHI intensity was significantly higher in the anticyclonic weather pattern compared to cyclonic and advective conditions. The urban–rural temperature contrast was at least recognizable under a turbulent windy atmosphere. Surprisingly, Ljutomer's UHI can be most accurately modelled in the cyclonic weather pattern, followed by advective and anticyclonic conditions, and statistically significant cold‐spots can be better predicted, with selected predictor variables, than hot‐spots.