Julia Sanz

Rapid response for cloud monitoring through Meteosat VIS‐IR and NOAA–A/TOVS image fusion: civil aviation application. A first approach to MSG‐SEVIRI

The aim of this work is to show an automatic method of cloud classification for direct application in civil aviation. We start from the premise of an acceptable trade‐off between calculation speed and accuracy in the output data. For this reason, visible and infrared channels of the Meteosat satellite were used alongside data provided by the A/TOVS (Advanced/Tiros‐N Operational Vertical Sounder) probe onboard NOAA (National Oceanic and Atmospheric Administration) polar satellites. A historical database of mean temperatures at ground level was also used. The analysis of different significant synoptic and mesoscale situations highlighted the efficacy of this method in the representation of the different cloud structures that normally appear in these situations. Considering the results of the study and given its speed and accuracy, it can be concluded that the method is appropriate for monitoring cloud systems in real time.

Synthesis reactivity and molecular structure of 2′-methylspiro[cyclohexane-1,3′-3H-indole]chromium tricarbonyl complex

Abstract Synthesis of 2′-methylspiro[cyclohexane-1,3′-3 H -indole] chromium tricarbonyl and structural analysis by spectroscopy and single-crystal X-ray techniques have been carried out. The reactivity of the CN bond of indolenine with organometallic reagents has also been analysed. The reduction of 2′-methylspiro [cyclohexane-1,3′-3 H -indole] chromium tricarbonyl with AlLiH 4 gave endo- and exo-complexes, which have been isolated and analysed by spectroscopic methods.

Relation between meteorological conditions and the catching of red tuna (Thunnus thynnus) from the measurements of the TOVS and AVHRR sensors of the NOAA satellites

During the second half of the month of June 1997, a massive catch of red tuna (Thunnus thynnus) took place off the coast of Babarte (Spain), in contrast to the first half of that month when there was hardly any presence of this species. The aim of this paper was to examine the relation between the high fishing productivity and the meteorological conditions under which the oceanic events to which the tuna fisheries were attracted took place. This was carried out through the analysis of Advanced Very High Resolution Radiometer (AVHRR) sensor data and the data from the Tiros‐N Operational Vertical Sounder (TOVS) probe of the NOAA‐14 satellite from 10 to 24 June 1997. Results show that the formation of the fishing front was caused by an ocean–atmosphere energetic exchange, which was localized and described through the data transmitted from the NOAA satellites.

An automatic self-learning cloud-filtering algorithm for Meteosat Second Generation–Spinning Enhanced Visible and Infrared Imager

Cloud detection is an important pre-processing step to derive operational products from meteorological satellites. This work presents a new cloud-detection algorithm with Meteosat Second Generation (MSG) images, operative at global scale. The algorithm takes advantage of the spectral and temporal resolution of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor. The algorithm is fully automatic in all its stages, including the thresholds definition by means of a self-learning methodology. These properties remove the need for ancillary data and restrictions in the area of application. This algorithm has been used in order to generate cloud masks during 2009. These cloud masks have been compared to the masks obtained with the National Aeronautics and Space Administration algorithm MOD35 with Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) images and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) algorithm for MSG–SEVIRI in Spain territory. The result shows an 88% agreement with EUMETSAT and a better than 83% agreement with the MOD35 algorithm.

Remote Sensing for Environmental Monitoring: Forest Fire Monitoring in Real Time

The use of remote sensing techniques for the study of forest fires is a subject that started already several years ago and whose possibilities have been increasing as new sensors were incorporated into earth observation international programmes and new goals were reached based on the improved techniques that have been introduced. In this way, three main lines of work can be distinguished in which remote sensing provides results that can be applied directly to the subject of forest fires: risk of fire spreading, detection of hot-spots and establishment of fire parameters.

Detecting Areas Vulnerable to Sand Encroachment Using Remote Sensing and GIS Techniques in Nouakchott, Mauritania

Sand dune advances poses a major threat to inhabitants and local authorities in the area of Nouakchott, Mauritania. Despite efforts to control dune mobility, accurate and adequate local studies are still needed to tackle sand encroachment. We have developed a Sand Dune Encroachment Vulnerability Index (SDEVI) to assess Nouakchott’s vulnerability to sand dune encroachment. Said index is based on the geo-physical characteristics of the area (wind direction and intensity, slope and surface height, land use, vegetation or soil properties) with Geographic Information System (GIS) techniques that can support local authorities and decision-makers in implementing preventive measures or reducing impact on the population and urban infrastructures. In order to validate this new index, we use two remote sensing approaches: optical-Sentinel 2 and Synthetic Aperture Radar (SAR)–Sentinel 1 data. Results show that the greatest vulnerability is located in the north-eastern part of Nouakchott, where local conditions favor the advance of sand in the city, although medium to high values are also found in the eastern part. Optical images enabled us to distinguish desert sand using the ratio between near infrared/blue bands, and SAR Coherence Change Detection (CCD) imagery was used to assess the degree of stability of those sand bodies. The nature of the SDEVI index allows us to currently assess which areas are vulnerable to sand encroachment since we use long data records. Nevertheless, optical and SAR remote sensing allow sand evolution to be monitored on a near real-time basis.