Contact © European Union, 2012 Use of low-resolution satellites for permanent pasture yield estimation at regional scale. Lorenzo Seguini European Commission Joint Research Centre IES/MARS Tel Seguini L. (1), Lopez-Lozano R. (1), Garcia Condado S. (1), Duveiller G. (1) & Baruth B. (1) (1) European Commission Joint Research Centre IES/MARS Introduction Permanent pastures are an important agricultural land use in Europe representing about 13 % of total EU land surface and constituting one of the main sources for livestock feed. An operational assessment of permanent pastures productivity along the season is important: the share of livestock energy needs that are not satisfied by permanent pastures creates a demand for other agricultural products, which may have a considerable impact on agricultural markets. Due to the complexity of the European pasture systems a system based on modelling pasture growth results difficult to implement. Remote sensing biophysical indicators analysis could represent a spatial and temporal homogeneous proxy for pasture productivity estimation at large scale. Abstract Remote sensing observations have proved to be a useful tool for agricultural monitoring over large regions and for quantitative crops forecasting. The main objective of this study is to evaluate the correspondence between the inter-annual variability of officials permanent pasture yields statistics and temporal anomalies of biophysical indicators at regional scale. Pasture yields statistics in Europe were collected and France was identified as test country. Remote sensed data (JRC-fAPAR for SPOT VEGETATION) available in the MARS Crop Yield Forecasting System (MCYFS) were used to extract regional (NUTS3 scale) time-series over permanent pastures as defined by specific land cover maps. Cumulated fAPAR over specific time-windows were correlated to official regional yields. The results allowed to assess the degree of relationship between biophysical products time-series and official permanent pasture yields. Moreover, the variability of that correlation along the growing season was analyzed to identify the time window –region-specific– over fAPAR becomes more reliable for yield forecasting. Materials Official statistics: statistics of areas and yields were collected for all France regions and for temporary and permanent pasture. Time series available: 1989 – Remote sensing data: 1km fAPAR time series computed with JRC-fAPAR methodology from SPOT-VEGETATION data. Time series available: 1999 – Pasture mask definition and spatialization: two different sources were used. The class Pasture (231) of CORINE 2000 land cover product and the class GRASS as defined from the CAPRI project. Masks, at 1km of resolution, explains the percentage of pasture surface. Results Minor influence related to pixel purity or masks: different mask and threshold of pixel pasture density were used above The results comparison underlined minor changes in the r 2 values. Geographical pattern of windows width: northern regions spring and summer and northern regions with no water limitations; southern regions: summer or only late part of the summer when water limitation could be strong. Outliers analysis: 2011 results to be an outlier in the main producing regions: relatively high yields VS low fAPAR in the window. Main explanation lays in the after summer growth that gave improvement to the overall yields but was not catch by the windows’ width. Positive results: in the main producing regions the regressions display positive correlation with yields encouraging further analysis. LEGEND: to be inserted Methodology t Statis tics fAPAR – SPOT VEG. PERIOD of ANALYSIS ONE LINE DESCRPITON