Aplicativo web para el análisis de series de tiempo de imágenes satelitales para variables meteorológicas e índices

Abstract

Climate predictions support risk management and the prevention of natural disasters. They also provide the necessary support elements to make decisions about the management and planning of climate-sensitive activities to cope with possible natural disasters. In turn, the monitoring and predictions of the vegetative state of crops, pastures, forests and others support the Food security taking into account that farmers can adapt their dates of planting, plant the best combination of crops and choose those resistant to diseases and adapted to the conditions they have in certain months of the year. Through the application developed it is possible to make predictions or estimated values ​​of meteorological variables (Evapotranspiration, accumulation of precipitation, soil moisture, temperature and speed of time) and indexes (NDVI, EVI, NBRT, NDWI), for a given day, without being limited by the temporal resolution of the remote sensors or by the availability of climatic stations on land, since through the time series of images, it is possible to define a behavior pattern and thus be able to make predictions through a estimated regression model of said behavior, in this case, of the meteorological variables and vegetation and water indices, in order to predict the behavior of the series in future dates or in days in which data are not available, allowing the climate risk analysis, action planning and decision making.