Multi-year monitoring of rice crop phenology through time series analysis of MODIS images

Abstract

Precise phenological calendars, for each cultivated species and variety, are necessary both to highlight anomalous agronomic situations and to feed crop models. This study, conducted in the Italian rice area, focuses on the evaluation of the contribution of remote sensing satellite data to providing phenological information on rice cropping systems. A time series of 5 years (2001–2005) of the Moderate Resolution Imaging Spectrometer (MODIS) Normalized Difference Vegetation Index (NDVI) 16-day composites was analysed with the TIMESAT program in order to automatically retrieve key phenological information such as the start of season (emergence), peak (heading) and end of season (maturity). The procedure involved two steps: (1) interpolation and smoothing of MODIS NDVI temporal profile and (2) the analysis of a temporal signal for the extraction of the phenological metrics. The remote sensing estimates were evaluated using information regarding cultivated variety, sowing dates, management and production directly acquired from rice farmers. A good correlation (R ² = 0.92, n = 24) has been observed between estimates derived from satellites and estimates produced with the traditional Growing Degree Days (GDD) method based on thermal unit accumulation. Improved estimates of the maturity stage were obtained using a procedure that integrates satellite and GDD methods; however its application requires spatially distributed information on the cultivated varieties. Satellite derived maps of the retrieved phenological parameters showed an intra-seasonal pattern related to different cultivated varieties. Inter-seasonal analysis allowed the anomalous behaviour of the year 2003 to be highlighted, characterized by rapid growth at the beginning of the spring and an early senescence. The results confirm the potential of remotely sensed data for the monitoring of crop status and for the forcing of crop models in a spatially distributed way.

Acknowledgments

The authors would like to thank all the colleagues that provided precious help in conducting this field campaign. In particular we want to acknowledge Mr Mauro Musanti for the costly LAI2000 measurements. A particular thanks to Mr Fedeli, who accommodated our experiments on his farms and to Bruno Marabelli (ENR) for providing the official statistics of Italian rice production.