Usefulness of ERS coherence time series for monitoring the vegetation cycle of a mixed deciduous forest

The usefulness of ERS Tandem coherence time series for monitoring the seasonal dynamics of a mixed temperate forest is analyzed. Firstly, we present the experimental approach conducted on the Fontainebleau forest. Thanks to a theoretical work, a first explanation of the temporal variations of the interferometric coherence over deciduous trees is then given. INTRODUCTION Recent studies, based on measurements of atmospheric CO 2 oncentrations and on the use of atmospheric transport model, have suggested that temperate ecosystems, particularly forests, might presently act as major carbon sinks. This would mainly result from a human-induced effect of CO 2 fertilization on forest growth [1]. However, large uncertainties still exist for determining whether carbon sink or source occurs in temperate deciduous forests [2]. In this context, the potentialities of space-borne Synthetic Aperture Radars (SARs) for monitoring forest ecosystems must be investigated. Today, few studies are concerned with temperate deciduous forests. In addition, they all suffer from a lack of experimental data both in radar time series and in the associated relevant ground data [3]. In the present study, we have conducted experiments to complete the assessment of the potentialities of ERS C-band system for the analysis of temperate forest dynamics. As we have shown before [4], the usefulness of ERS C-band backscattering coefficients was not demonstrated for this purpose. However, using interferometric coherence information, some studies have recently shown interesting results for retrieving structural parameters of boreal forests [5]-[7], but they have also pointed out the need for a better understanding of interferometric signatures of forests [8]. The present paper aims to evaluate the relevance of ERS-1/2 SAR instruments for monitoring temporal and structural changes in a mixed temperate forest ecosystem. Emphasis is put on the capability of InSar time series for detecting the leafy cycle of a deciduous forest. Firstly, we present our experimental approach consisting of the processing of 9 interferograms and the analysis of coherence images versus forest parameters. Secondly, after describing the coherent model we have used in this work, a first explanation of the seasonal coherence signatures is proposed.