The objective of this work is to analyze the behavior of short temporal baseline interferometric coherence in forested areas for L-band spaceborne SAR data. Hence, an exploratory assessment of the impacts of temporal and spatial baselines on coherence, with emphasis on how these effects vary between SAOCOM-1 L-band and Sentinel-1 C-band data is presented. The interferometric coherence is analyzed according to different imaging parameters. In the case of SAOCOM-1, the impacts of the variation of the incidence angle and the ascending and descending orbits over forested areas are also assessed. Finally, short-term 8-day interferometric coherence maps derived from SAOCOM-1 are especially addressed, since this is the first L-band spaceborne mission that allows us to acquire SAR images with such a short temporal span. The analysis is reported over two forest-production areas in Argentina, one of which is part of the most important region in terms of forest plantations at the national level. In the case of SAOCOM, interferometric configurations are characterized by a lack of control on the spatial baseline, so a zero-baseline orbital tube cannot be guaranteed. Nevertheless, this spatial baseline variability is crucial to exploit volume decorrelation for forest monitoring. The results from this exploratory analysis demonstrates that SAOCOM-1 short temporal baseline interferograms, 8 to 16 days, must be considered in order to mitigate temporal decorrelation effects and to be able to experiment with different spatial baseline configurations, in order to allow appropriate forest monitoring.

This work presents the first results of canopy height mapping with L-Band SAOCOM data by means of Polarimetric SAR Interferometry (PolInSAR). SAOCOM stands for Satélite Argentino de Observación con Microondas and it is operated by CONAE, the argentinean space agency. For this study case, a colocated temporal series of SAOCOM fully polarimetric images covering the year 2021 was acquired, with a temporal baseline of 8 to 16 days between each acquisition. The study area corresponds to managed forests in Corrientes, Argentina. which is one of the main forest production regions in the country. Field measurements provided by forest owners were available in order to validate the obtained results, along with canopy height measurements from the Global Ecosystem Dynamics Investigation (GEDI) mission. In this work a multi-baseline PolInSAR approach was adopted, following the methodology proposed by previous works. Field data measurements collected over the study periods were used to select the RVoG-inverted maps that best represented the different forest heights present in the study areas. The results show that this multi-baseline selection approach is more appropriate than a single-baseline one, given the high variability that SAOCOM presents in the spatial baseline between acquisitions, and the lack of orbital control over this parameter. Two forest fields were selected to validate this methodology: one for training and calibrating the model, and another for independent validation. The height maps from the latter yielded an average $R^{2}$ of 0.72 and a mean $RMSE$ of 2.35 m., in agreement with the figures obtained in similar studies. This study presents, for the first time, canopy height maps of 8 and 16-day temporal baselines, L-band, orbital interferograms. The conclusions yielded by this research represent a qualitative and quantitative evaluation of SAOCOM PolInSAR capabilities for forest height mapping. It is also relevant to assess the suitability of the RVoG model to characterize the structure of these forests with L-band data retrieved by the Argentinean constellation.

Polarimetric SAR interferometric (PolInSAR) methods have proven effective for estimating canopy height using airborne data, yet their application with spaceborne sensors remains limited. Addressing this gap is crucial for advancing operational canopy height estimation using spaceborne PolInSAR, particularly given the impact of temporal decorrelation in repeat-pass configurations. However, research on how these effects influence forest height estimation accuracy remains sparse. This study introduces a novel approach that integrates data from the GEDI LiDAR mission and the Argentine SAOCOM satellite constellation to generate canopy height and temporal decorrelation maps. Specifically, GEDI data is used to refine a multi-baseline inversion methodology for improved canopy height retrieval from SAOCOM. The three main contributions of this work are: 1) extending the use of GEDI’s sparse spatial data to enhance a baseline selection approach for PolInSAR inversion, improving canopy height mapping from SAOCOM; 2) introducing a joint exploitation of GEDI and SAOCOM data to produce spatially detailed maps of temporal decorrelation, adapting previous airborne-based approaches to a fully spaceborne context; and 3) demonstrating that incorporating temporal decorrelation into the inversion process leads to more accurate canopy height estimates. Validation against field measurements from forest owners reveals a strong relationship between stand age, height, and temporal decorrelation, with canopy height estimates achieving an RMSE of 2.47 m and an $R^{2}$ of 0.73. These findings highlight the potential for operational canopy height and temporal decorrelation mapping using spaceborne L-band SAR and LiDAR data, contributing to improved forest monitoring capabilities.

This study explores potential irrigation-related land subsidence in an agricultural area of Córdoba, Argentina, using a multi-temporal InSAR analysis on Sentinel-1 imagery (2017-2021) and GRACE-FO gravimetric data. On the basis of the available Sentinel-1 imagery in the study area, Line-Of-Sight (LOS) cumulative displacement maps were generated using both ascending (2017-2018) and descending (2018-2021) acquisitions. To improve data reliability, low-coherence pixels (threshold $<0.5$) were excluded. The resulting maps show LOS displacements ranging from -5 to -10 cm in the first year of analysis $(2017-2018)$, and from -15 to -25 cm over the subsequent three years (2018-2021). The deformation products were compared with GRACE-FO (Gravity Recovery and Climate Experiment Follow- On) gravimetric data to assess possible correlations between land deformation and equivalent water thickness variations. Although the lack of ground-based validation data limits definitive interpretation, the spatial and temporal patterns observed suggest a link between the position of the center-pivot irrigation fields, surface deformation and changes in water storage. These findings underscore the value of integrated satellite-based approaches for preliminary assessment of hydrologically driven ground motion in data-scarce agricultural regions.