This study assesses, adapting the weather types method, the suitability of the climate in Jardines del Rey (Cuba) for the practice of sun and beach tourism over the period 1991–2014, and the potential future impacts of climate change on this form of tourism on the basis of outputs from the PRECIS-Caribbean Regional Climate Model for the period 2021–2050. The methodology applied makes a classification of daily situations according to the most frequent combinations of climatological variables in tropical areas while focusing on a very specific segment of the tourism market (sun and beach tourism) and taking into account the behaviour of beach users and bioclimatic criteria. The results indicate that the distribution of weather types at the destination during the period 1991–2014 was highly consistent with the monthly distribution of tourists in Cuba, highlighting the existence of a low season from May to October and a high season between November and April. The future scenarios project an improvement in climate conditions for the practice of sun and beach tourism. This improvement is not based on a spectacular increase in favourable weather types compared to unfavourable ones, but rather on a better distribution of both.

Invasive plants are a serious problem in island ecosystems and are the main cause of the extinction of endemic species. Cuba is located within one of the hotspots of global biodiversity, which, coupled with high endemism and the impacts caused by various disturbances, makes it a region particularly sensitive to potential damage by invasive plants like Dichrostachys cinerea (L.) Wight & Arn. (marabú). However, there is a lack of timely information for monitoring this species, as well as about the land use and land cover (LULC) classes most significantly impacted by this invasion in the last few decades and their spatial distribution. The main objective of this study, carried out in Central Cuba, was to detect and monitor the spread of marabú over a 28-year period. The land covers for the years 1994 and 2022 were classified using Landsat 5 TM and 8 OLI images with three different classification algorithms: maximum likelihood (ML), support vector machine (SVM), and random forest (RF). The results obtained showed that RF outperformed the other classifiers, achieving AUC values of 0.92 for 1994 and 0.97 for 2022. It was confirmed that the area covered by marabú increased by 29,555 ha, from 61,977.59 ha in 1994 to 91,533.47 ha in 2022 (by around 48%), affecting key land covers like woodlands, mangroves, and rainfed croplands. These changes in the area covered by marabú were associated, principally, with changes in land uses and tenure and not with other factors, such as rainfall or relief in the province. The use of other free multispectral imagery, such as Sentinel 2 data, with higher temporal and spatial resolution, could further refine the model’s accuracy.

Irma was a major hurricane that developed during the 2017 season. It was a category 5 on the Saffir–Simpson Hurricane wind scale. This hurricane caused severe damage in the Caribbean area and the Florida Keys. The social, economic, and environmental impacts, mainly related to coastal flooding, were also significant in Cuba. The maximum limits of coastal flooding caused by this hurricane were determined in this research. Field trips and the use of the GPS supported our work, which focused on both the northern and southern coasts of the Ciego de Ávila province. This work has been critical for improving coastal flooding scenarios related to a strong hurricane, as it has been the first experience according to hurricane data since 1851. Results showed that the Punta Alegre and Júcaro towns were the most affected coastal towns. The locals had never seen similar flooding in these places before. The differences between flood areas associated with Hurricane Irma and previous modeled hazard scenarios were evident (the flooded areas associated with Hurricane Irma were smaller than those modeled for categories 1, 3, and 5 hurricanes). The effects of this hurricane on the most vulnerable coastal settlements, including the impacts on the archeological site “Los Buchillones”, were also assessed.

The main objective of this work was to develop a viewer with web output, through which the changes experienced by the mangroves of the Gran Humedal del Norte de Ciego de Avila (GHNCA) can be evaluated from remote sensors, contributing to the understanding of the spatiotemporal variability of their vegetative dynamics. The achievement of this objective is supported by the use of open-source technologies such as MapStore, GeoServer and Django, as well as Google Earth Engine, which combine to offer a robust and technologically independent solution to the problem. In this context, it was decided to adopt an action model aimed at automating the workflow steps related to data preprocessing, downloading, and publishing. A visualizer with web output (Geospatial System for Monitoring Mangrove Ecosystems or SIGMEM) is developed for the first time, evaluating changes in an area of central Cuba from different vegetation indices. The evaluation of the machine learning classifiers Random Forest and Naive Bayes for the automated mapping of mangroves highlighted the ability of Random Forest to discriminate between areas occupied by mangroves and other coverages with an Overall Accuracy (OA) of 94.11%, surpassing the 89.85% of Naive Bayes. The estimated net change based on the year 2020 of the areas determined during the classification process showed a decrease of 5138.17 ha in the year 2023 and 2831.76 ha in the year 2022. This tool will be fundamental for researchers, decision makers, and students, contributing to new research proposals and sustainable management of mangroves in Cuba and the Caribbean.

This study focuses on the relationship between hotel sites (current and planned) and exposure to hurricanes in Cuba. The hypothesis focused on demonstrating that Cuban tourist areas have differing degrees of exposure to tropical cyclones according to the month. The results indicate that although the whole Cuban archipelago is exposed to hurricanes, the tourist regions in Cuba’s western provinces have a greater chance of being affected than those located in the center, east, and south. The tourism development that will take place by 2030 in Cuba includes significant hotel expansion in coastal areas that are highly exposed to hurricanes. Information on the risk of hurricanes in tourist regions provides information that could enable the creation of the organizational conditions needed to tackle these phenomena in the short to medium term and to refine spatial and tourism planning approaches in the long term.

Mediante el método de los tipos de tiempo, se analiza la potencialidad climática para la práctica del turismo de sol y playa en la región turística Jardines del Rey (Cuba) durante el periodo 1991-2014, y los potenciales impactos del cambio climático sobre la misma a partir de salidas del Modelo Climático Regional PRECIS-Caribe (2021-2050). El análisis presta especial atención a los cambios en el confort climático. Los resultados señalan que la distribución de los tipos de tiempo en el destino durante el período base muestra una gran coherencia con la distribución de turistas, evidenciando la existencia de una temporada baja comprendida entre mayo y octubre y una temporada alta entre noviembre y abril. Los escenarios de futuro proyectan una mejora de las condiciones climáticas para el desarrollo del turismo de sol y playa en el ámbito considerado. Los resultados permiten explorar posibles repercusiones sobre la gestión de los destinos turísticos.