Mass blooms and stranding of pelagic Sargassum spp. in the Atlantic, termed Sargassum events are becoming more frequent in response to several factors: nutrient enrichment, increased temperature, changes in climatological patterns, but some causes remain unknown. The magnitude of Sargassum events in the Caribbean Sea since 2011 make us aware of the necessity to tackle these events, and macroalgal blooms generally, not only locally but on a regional scale. At least three pelagic species of Sargassum have been dominant in the blooms that have occurred along Caribbean coastlines in great quantities. Due to the regional scale of these events and its complexity, its management should be based on basic and applied information generated by different collaborative actors (national and international) through interdisciplinary and transdisciplinary work. To address this, we propose different phases (exploratory, valorization, and management) and the approach for their study should include detection, collection, stabilization and experimentation. This information will help identify the potential applications and/or ecological services to develop for the exploitation and mitigation strategies in the region. Relevant challenges and opportunities are discussed, remarking on the necessity to evaluate the spatiotemporal variation in the abundance and chemical composition of floating and stranded biomass. The above-mentioned will provide management strategies and economic opportunities as possible solutions to their extensive impact in the Caribbean.

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Several built-up indices have been proposed in the literature in order to extract the urban sprawl from satellite data. Given their relative simplicity and easy implementation, such methods have been widely adopted for urban growth monitoring. Previous research has shown that built-up indices are sensitive to different factors related to image resolution, seasonality, and study area location. Also, most of them confuse urban surfaces with bare soil and barren land covers. By gathering the existing built-up indices, the aim of this paper is to discuss some of their advantages, difficulties, and limitations. In order to illustrate our study, we provide some application examples using Sentinel 2A data.

This paper addresses the problem of tracking a planar region of the scene using an uncalibrated omnidirectional camera. Omnidirectional cameras are a popular choice of visual sensors in robotics because the large field of view is well adapted to motion estimation and obstacle avoidance. The novelty of this work resides in simplifying the calibration phase by providing a direct approach to tracking without any prior knowledge of the camera, lens or mirror parameters. We deal with a nonlinear optimization problem that can be solved for small displacements between two images like those acquired at video rate by a camera mounted on a robot. In order to assess the performance of the proposed method, we perform experiments with synthetic and real data.