## 1 Introduction  
Synthetic Aperture Radar interferometry (InSAR) has been widely used for topographic and surface mapping [1]. The technique has evolved significantly since its beginnings, leading to the possibility of generating global DEMs, such as SRTM [2] or TanDEM-X DEMs [3]. In the case of forestry, the generation of digital surface models is a key input for the estimation of forest canopy height, as it may represent the initial step to the calculation of forest biomass or forest productivity [4, 5]. Additionally, Polarimetric SAR Interferometry (PolInSAR) is an InSAR-based technique that exploits the phase and amplitude observations at different polarization states to estimate forest parameters by using a radar scattering model [6, 7]. PolInSAR has been applied with special emphasis on forest canopy height estimation [8, 9, 10, 11, 12, 13, 14]. Under both approaches--InSAR and PolInSAR--the main observable is the interferometric coherence, a complex magnitude that measures the correlation between two SAR images. For volumetric scatters, such as forests, canopy height information can be estimated from the volume decorrelation term, providing a suitable physical separation between the SAR acquisitions [15, 16, 17]. Nevertheless, when considering repeat-pass InSAR configurations, another decorrelation source that arises is the temporal one. In general, as more time passes between two SAR acquisitions, more changes may occur in the target's properties, or even in its location, which in turn degrades the accuracy of forest canopy height measurements [18; 19]. Besides, temporal decorrelation increases generally with frequency in forests, as electromagnetic waves increase sensitivity with frequency to smaller components, such as branches or leaves, which are more affected by weather effects, such as wind, for instance. Thus, proper InSAR and PolInSAR forest mapping faces a compromise among (i) the InSAR geometric configuration in terms of the physical separation between the SAR acquisitions or spatial baseline, (ii) the temporal separation of the SAR acquisitions or temporal baseline and (iii) the imaging frequency, as it determines the penetration capabilities into the forest volume. Temporal decorrelation studies for repeat-pass interferometry have been widely addressed in airborne SAR missions as these systems offer the flexibility of experimenting with different temporal baselines and there is full control on the spatial baseline [20; 21; 22; 23; 24]. In spaceborne systems, the conditions are quite different. First, satellite platforms have a pre-defined revisit cycle which can be too long in terms of temporal decorrelation. Second, because not all spaceborne systems have a stable orbital tube over the platform's position. This implies that there might be high variability in the spatial baseline, which may not always be the most appropriate for an InSAR configuration [25] focused on forest monitoring. As for the first constraint, satellite missions in X-band such as TerraSAR-X/TanDEM-X/PAZ and COSMO-SkyMed have offered the possibility of developing InSAR case studies with very short temporal separation [26; 27], limiting temporal decorrelation, but where forest canopy penetration capabilities are reduced, compared to L- or C-bands. With the launch of C-band ESA's constellation Sentinel-1 research has been focused on the study of temporal series of the interferometric coherence for different application fields, taking advantage of the mission's short revisit time of 6 to 12 days [28; 29; 30; 31]. For lower frequencies, there has been a number of studies on the InSAR capabilities of JAXA's ALOS-PALSAR mission to map vegetation or forest canopy height considering the temporal decorrelation with a revisit time from 23 to 46 days [25; 32; 33], but no studies have considered coherence at shorter revisit times for L-band orbital data. The Argentinian L-band SAOCOM system fills this gap, thanks to the capability to generate 8-day interferograms.