Coastal dune ecosystems are highly threatened, and one of the strongest pressures is invasive alien plants (IAPs). Mitigating the negative effects of IAPs requires development of optimal identification and mapping protocols. Remote sensing offers innovative tools that have proven to be very valuable for studying IAPs. In particular, unmanned aerial vehicles (UAVs) can be very promising, especially in the study of herbaceous invasive species, yet research in UAV application is still limited. In this study, we used UAV images to implement an image segmentation approach followed by machine learning classification for mapping a dune clonal invader (Carpobrotus sp. pl.), calibrating a total of 27 models. Our study showed that: (a) the results offered by simultaneous RGB and multispectral data improve the prediction of Carpobrotus; (b) the best results were obtained by mapping the whole plant or its vegetative parts, while mapping flowers was worse; and (c) a training area corresponding to 20% of the total area can be adequate for model building. Overall, our results highlighted the great potential of using UAVs for Carpobrotus mapping, despite some limitations imposed by the particular biology and ecology of these taxa.

Urban settlements can support significant biodiversity and provide a wide range of ecosystem services. Remote sensing (RS) offers valuable tools for monitoring and conserving urban biodiversity. Our research, funded by the Italian Recovery and Resilience Plan (National Biodiversity Future Centre—Urban Biodiversity), undertakes a systematic scientific review to assess the current status and future prospects of urban biodiversity evaluation using RS. An extensive literature search of indexed peer-reviewed papers published between 2008 and 2023 was conducted on the Scopus database, using a selective choice of keywords. After screening the titles, abstracts, and keywords of 500 articles, 117 relevant papers were retained for meta-data analysis. Our analysis incorporated technical (e.g., sensor, platform, algorithm), geographic (e.g., country, city extent, population) and ecological (biodiversity target, organization level, biome) meta-data, examining their frequencies, temporal trends (Generalized Linear Model—GLM), and covariations (Cramer’s V). The rise in publications over time is linked to the increased availability of imagery, enhanced computing power, and growing awareness of the importance of urban biodiversity. Most research focused on the Northern Hemisphere and large metropolitan areas, with smaller cities often overlooked. Consequently, data coverage is predominantly concentrated on Mediterranean and temperate habitats, with limited attention given to boreal, desert, and tropical biomes. A strong association was observed between the source of RS data (e.g., satellite missions), pixel size, and the purpose of its use (e.g., modeling, detection). This research provides a comprehensive summary of RS applications for evaluating urban biodiversity with a focus on the biomes studied, biodiversity targets, and ecological organization levels. This work can provide information on where future studies should focus their efforts on the study of urban biodiversity using remote sensing instruments in the coming years.

The interest of the scientific community about geotourism is abruptly increasing, as well as that on geoparks. According to UNESCO, geoparks should define management policies addressed to increasing the awareness of local people and tourists about Earth’s dynamics to reduce the impact of climate change and natural disasters. With this aim in mind, we tried to provide a solid scientific approach to geotourism that could be useful to the development of a geotourism strategy in the Cilento, Vallo di Diano and Alburni (CVDA) Geopark, in Southern Italy. Starting from the official inventory of the CVDA Geopark, we defined the potential Education Value (EV) and potential Touristic Value (TV) of each of the 160 sites listed by applying the Brilha method. Then we selected 20 geosites and geomorphosites with high values of both the EV and TV, and we included them in two geoitineraries. The two geoitineraries move in the inner sector of the Geopark (i.e., from the Paestum archaeological area to the Vallo di Diano basin) and along a portion of the coastal stretch (i.e., from Punta Telegrafo cape to the Lambro and Mingardo rivers’ mouths). Selected sites are representative of several geoscience disciplines (e.g., geomorphology, structural geology, quaternary geology, hydrogeology), thus suggesting that the CVDA Geopark is an ideal place where dissemination of geoscience concepts may be carried out. The latter point enhances the high geotourism potential of the area. This kind of approach was not tried before in the CVDA Geopark and can be a useful example of how to promote touristic development strategies in the area.

Rapid human population growth accelerates biodiversity loss through urban habitat fragmentation, yet ecologically informed urban planning can mitigate these effects. This study evaluates whether and how vegetation characteristics, as captured by Earth observation data varies across forest habitats in a small Mediterranean city in Italy. The Normalized Difference Vegetation Index (NDVI), the Normalized Difference Moisture Index (NDMI), and Land Surface Temperature (LST) for the Functional Urban Area of Campobasso were derived from multitemporal Landsat 8 imagery (2020–2023) acquired during the growing season and combined with elevation data to account for topographic gradients. Different forest habitats were identified using the regional coeval Carta della Natura (Map of Nature) and were sampled by a random stratified strategy yielding more than 900,000 observations. A linear mixed-effects model was used to model NDVI as a function of NDMI, LST, elevation, and habitat type, while accounting for temporal and spatial dependencies. The model explained a large proportion of NDVI variability (marginal R² = 0.75; conditional R² = 0.85), with NDMI emerging as the strongest predictor, followed by weaker effects of LST and elevation. Habitat differences were also evident: oak-dominated forests (i.e., Quercus frainetto, Q. cerris, and Q. pubescens dominated habitats) exhibited the highest NDVI values, while coniferous plantations (i.e., Pinus nigra dominated habitat) had the lowest; forests dominated by Robinia pseudoacacia and riparian Salix alba showed intermediate vegetation greenness values. These results highlight the ecological importance of oak forests in Mediterranean urban landscapes and demonstrate the value of satellite-based monitoring for capturing habitat variability. The reproducible workflow applied here provides a scalable tool to support habitat conservation and planning in urban environments, also accounting for impending climate change scenarios.

We present PREVALIEN, a dataset created under the project Prevention and Early Detection of the Invasive Alien Plants of European Union Concern in the Italian Protected Areas, an innovative tool supporting prevention and early detection of Invasive Alien Plants. Developed on PostgreSQL, it integrates ecological and spatial data from authoritative European and global sources. This dataset covers 41 vascular plant and algal species, with detailed information on taxonomy, traits, introduction pathways, impacts, and management strategies. Presence and absence records for Italians’ protected areas were obtained from the Italian Institute for Environmental Protection and Research databases and included only if collected within National Park boundaries. Data underwent expert verification, including cross-checking with risk assessments and consultation with park authorities. Structured into 34 relational tables, PREVALIEN supports multi-scale ecological analysis and the development of spatially explicit risk models. As an open-access resource, it fills critical data gaps, enhances national IAS monitoring, and provides a foundation for evidence-based policies and actions against biological invasions, strengthening protection of Europe’s most vulnerable and biodiversity-rich landscapes.