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espanolExiste una relacion entre la produccion primaria neta del trigo y los indices de vegetacion obtenidos de imagenes de satelite. Con frecuencia se utiliza el NDVI (Normalized Difference Vegetation Index) para la estimacion de produccion y rendimiento de trigo y otros cultivos. Sin embargo, hay pocas investigaciones que utilicen el indice MTCI (MERIS Terrestrial Chlorophyll Index) para conocer el rendimiento y la produccion de los cultivos a una escala regional posiblemente debido a la falta de continuidad del sensor MERIS. No obstante, la posibilidad del calculo de MTCI a partir de Sentinel 2 abre nuevas oportunidades para su aplicacion e investigacion. En esta investigacion se han generado dos modelos empiricos de estimacion de produccion y rendimiento de trigo en Andalucia. Para ello, se ha empleado la serie temporal completa (imagenes semanales de 2006 a 2011) del indice de vegetacion MTCI del sensor satelital MERIS (Medium Resolution Imaging Spectrometer) asociada a los datos de produccion y rendimiento del Anuario de estadisticas agrarias y pesqueras de Andalucia (AEAP). Para la creacion de estos modelos ha sido necesaria la identificacion del periodo optimo del desarrollo de la planta, la agregacion temporal de los valores MTCI usando ese momento optimo como referencia, relacionar ese indice con observaciones directas de produccion y rendimiento a traves de agregaciones espaciales mediante la utilizacion de coberturas SIGPAC y las solicitudes de ayudas PAC, caracterizar la variacion del indice en funcion del ano de cultivo y relacionarlo con los datos estadisticos. Los resultados obtenidos indican una correlacion estadisticamente significativa (p-valor EnglishThere is a relationship between net primary production of wheat and vegetation indices obtained from satellite imaging. Most wheat production studies use the Normalised Difference Vegetation Index (NDVI) to estimate the production and yield of wheat and other crops. On the one hand, few studies use the MERIS Terrestrial Chlorophyll Index (MTCI) to determine crop yield and production on a regional level. This is possibly due to a lack of continuity of MERIS. On the other hand, the emergence of Sentinel 2 open new possibilities for the research and application of MTCI. This study has built two empirical models to estimate wheat production and yield in Andalusia. To this end, the study used the complete times series (weekly images from 2006–2011) of the MTCI vegetation index from the Medium Resolution Imaging Spectrometer (MERIS) sensor associated with the Andalusian yearbook for agricultural and fishing statistics (AEAP—Anuario de estadisticas agrarias y pesqueras de Andalucia). In order to build these models, the optimal development period for the plant needed to be identified, as did the time-based aggregation of MTCI values using said optimal period as a reference, and relation with the index, with direct observations of production and yield through spatial aggregation using coverage from the Geographic Information System for Agricultural Parcels (SIGPAC—Sistema de informacion geografica de parcelas agricolas) and requests for common agricultural policy (CAP) assistance. The obtained results indicate a significant association between the MTCI index and the production and yield data collected by AEAP at the 95% confidence level (R2 =0.81 and R2 =0.57, respectively).

Estimación de la cosecha de trigo en Andalucía usando series temporales de MERIS Terrestrial Chlorophyll Index (MTCI)