A. Romo

Early prediction of crop production using drought indices at different time‐scales and remote sensing data: application in the Ebro Valley (north‐east Spain)

This Letter shows the results of early crop prediction from combined use of AVHRR‐NDVI data and drought indices at different time‐scales. The study was carried out in an agricultural municipality located in the Middle Ebro valley, one of the most arid regions in Europe. The methodology proposed here has allowed the prediction of wheat and barley production in February, four months before harvest. Moreover, the predictive models created have explained 88% and 82% of the temporal variability of wheat and barley production, respectively. This procedure could be very useful for managing crop production at a municipal level. Moreover, insurance companies could take advantage of the early prediction of crop losses, which are very frequent in this drought‐affected area.

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.

Latest algorithms and scientific developments for forest fire detection and monitoring using MSG/SEVIRI and MODIS sensors

The detection of fires in an operative way is not a finished task in remote sensing. This work present approaches for fire detection and fire monitoring. The described rare detection algorithm exploits a physical radiative transfer model based on a sub-pixel description of the remote sensing data. This model allows refining the detection capabilities in order to perform early detection by exploiting geostationary sensors which have a low spatial resolution but high temporal resolution. Polar sensors are used to supply updated parameters to the physical model. The described fire monitoring approaches allows estimating fire parameters and defining the evolution of the fire, using different spatial resolutions, in order to complete and refine the analysis performed by the detection algorithm.

IFEMS: a new approach for monitoring wildfire evolution with NOAA-AVHRR imagery

A new approach for monitoring wildfire evolution was developed. It was achieved by integrating both the burned area mapping system and the fire detection system. Multi-spectral multi-temporal images of the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) were employed. The new system has an excellent performance in monitoring fire growth due to its ability of capturing areas that were burned completely between two consecutive images, as well as those which were burned before the monitoring time. In addition, the system has the ability to differentiate among burned areas, active fire (fire front) and the area beneath flames. The algorithm of the system is described. The false alarm due to the saturation problem of channel 3 was avoided. The integration of the system with fire simulation programs for fire monitoring is discussed.

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.

Operational cloud classification for the Iberian Peninsula using Meteosat Second Generation and AQUA-AIRS image fusion

The aim of this work was the adaptation and improvement of a previous cloud detection and classification algorithm that was developed for the Meteosat-7 satellite. The functions of this satellite have now been taken on by the new series of Meteosat Second Generation (MSG) satellites, which are not just replicas but new, much improved versions of their predecessor. The formerly used Advanced/Tiros-N Operational Vertical Sounder (A/TOVS) probe has also been superseded technologically by new sensors with better spatial resolution, capable of carrying out more accurate measurements at a greater number of wavelengths. This is the case of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the TERRA and AQUA satellites and of the Atmospheric Infrared Sounder (AIRS) probe. In this context, new potential improvements are analysed for this algorithm by using these new platforms and sensors and the results are compared to those obtained in the first classification.

Spatial differences in the evolution of NDVI in the high river basin of the Aragón : effects of the changes of land uses

(*) fm@ipe.csic.es . RESUMEN: Se estudia la evolucion del Indice de Vegetacion Normalizado (NDVI) en el periodo 1993 –2000 en la cuenca Alta del Aragon (Pirineo occidental de Aragon) mediante imagenes de satelite NOAAAVHRR. Se comprueba que una parte importante del territorio muestra una tendencia positiva en los valores de NDVI, si bien se establecen algunos contrastes espaciales. Los valores mas altos corresponden a los antiguos campos agricolas, abandonados a lo largo del siglo XX, seguidos por las areas de matorral y los pinares (cubiertas derivadas de un proceso de sucesion vegetal tras la extensificacion productiva), mientras que el espacio cultivado y los pastos supraforestales (usos que mantienen una utilizacion mas intensiva) poseen los valores mas bajos. Estos resultados ponen de relieve el destacado papel de los cambios de uso del suelo en la evolucion de la biomasa vegetal. ABSTRACT: The vegetation cover evolution in the central Spanish Pyrenees is analysed from 1993 to 2000. The analysis has been achieved using one NDVI (Normalized Vegetation Index) temporal series obtained from NOAA-AVHRR images. A positive trend in NDVI data has been detected. However, the spatial differences in the magnitude and sign of NDVI trends are significant. An important increment of vegetation biomass is detected in most areas, particularly in those affected by field abandonment and extensive land use (shrublands and pine forests). Cultivated fields and pastures above timberline show a smaller increase in vegetation cover. The results indicate the important role of socio-economic transformations and land-use extensification in the vegetal biomass evolution.

Integrated Fire Evolution Monitoring System (IFEMS) for monitoring spatial-temporal behaviour of multiple fire phenomena

This study focuses on multiple fire phenomena in Valencia, Spain. The monitoring of fire recurrence was conducted by means of smoke visualization, mapping the burned area and fire detection, and took place for the whole of the fire period from 21 May to 13 July 1994. The temporal and spatial evolution of the fire was addressed on a daily basis, by means of approaches for mapping burned areas, fire detection, and integrated fire evolution monitoring system.