Monitoring coastal marine wildlife is crucial for biodiversity conservation, environmental management, and sustainable utilization of tourism-related natural assets. Conducting in situ censuses and population studies in extensive and remote marine habitats often faces logistical constraints, necessitating the adoption of advanced technologies to enhance the efficiency and accuracy of monitoring efforts. This study investigates the utilization of aerial imagery and deep learning methodologies for the automated detection, classification, and enumeration of marine-coastal species. A comprehensive dataset of high-resolution images, captured by drones and aircrafts over southern elephant seal (Mirounga leonina) and South American sea lion (Otaria flavescens) colonies in the Valdés Peninsula, Patagonia, Argentina, was curated and annotated. Using this annotated dataset, a deep learning framework was developed and trained to identify and classify individual animals. The resulting model may help produce automated, accurate population metrics that support the analysis of ecological dynamics. The resulting model achieved F1 scores of between 0.7 and 0.9, depending on the type of individual. Among its contributions, this methodology provided essential insights into the impacts of emergent threats, such as the outbreak of the highly pathogenic avian influenza virus H5N1 during the 2023 austral spring season, which caused significant mortality in these species.

The movement in favor of the use of bicycles as an alternative to mobility has been booming in the last two decades. This has been inserted within the policy of revaluation of the urban environment and improvement of the quality of life in the city. In this work we expose: an analytical model of cyclist transit, the design of a cycling simulator and a path analysis and visualization tool. The objective of this simulator is to determine the appropriate streets to install bikeways in the city of Puerto Madryn. The results of this work can be extrapolated to other intermediate cities, which present low density and high population growth, with a size of less than 150,000 inhabitants.