In this study, the interferometric coherence calculated from 12-day Sentinel-1 image pairs was analysed in relation to mowing events on agricultural grasslands. Results showed that after a mowing event, median VH (vertical transmit, horizontal receive) and VV (vertical transmit, vertical receive) polarisation coherence values were statistically significantly higher than those from before the event. The shorter the time interval after the mowing event and the first interferometric acquisition, the higher the coherence. The coherence tended to stay higher, even 24 to 36 days after a mowing event. Precipitation caused the coherence to decrease, impeding the detection of a mowing event. Given the three analysed acquisition geometries, it was concluded that afternoon acquisitions and steeper incidence angles were more useful in the context of this study. In the case of morning acquisitions, dew might have caused a decrease of coherence for mowed and unmowed grasslands. Additionally, an increase of coherence after a mowing event was not evident during the rapid growth phase, due to the 12-day separation between the interferometric acquisitions. In future studies, six-day pairs utilising Sentinel-1A and 1B acquisitions should be considered.

In this study, four models describing the interferometric coherence of the forest vegetation layer are proposed and compared with the TanDEM-X data. Our focus is on developing tools for hemiboreal forest height estimation from single-pol interferometric SAR measurements, suitable for wide area forest mapping with limited a priori information. The multi-temporal set of 19 TanDEM-X interferometric pairs and the 90th percentile forest height maps are derived from Airborne LiDAR Scanning (ALS), covering an area of 2211 ha of forests over Estonia. Three semi-empirical models along with the Random Volume over Ground (RVoG) model are examined for applicable parameter ranges and model performance under various conditions for over 3000 forest stands. This study shows that all four models performed well in describing the relationship between forest height and interferometric coherence. Use of an advanced model with multiple parameters is not always justified when modeling the volume decorrelation in the boreal and hemiboreal forests. The proposed set of semi-empirical models, show higher robustness compared to a more advanced RVoG model under a range of seasonal and environmental conditions during data acquisition. We also examine the dynamic range of parameters that different models can take and propose optimal conditions for forest stand height inversion for operationally-feasible scenarios.

In this study, an extensive flood in Estonia during spring 2010 was mapped with TerraSAR-X data acquired over both open and forested areas. This was the first time when a large scale flooding area was mapped in Estonia by means of spaceborne remote sensing. This was also the first time when X-band SAR images were successfully used for flood mapping under the forest canopy in the temperate forest zone. The tree height in the study region was 15-25 meters on average, and main tree species were birch (leaf-off condition), pine and spruce. The results were compared with ALOS PALSAR and Envisat ASAR images of the same flooding event. In the study area, TerraSAR-X provided on average 3.2 dB higher backscatter over mixed forest flooded areas compared to non-flooded areas. In deciduous and coniferous forests the difference in average backscatter between flooded and non-flooded forests was even greater, 6.2 dB and 4.0 dB, respectively. A supervised classification algorithm was developed to produce high resolution maps of the flooded area from the TerraSAR-X images to demonstrate the flood mapping capability at X-band. Our results show, that spaceborne X-band SAR data, which currently has the highest resolution among the SAR instruments in space, can be used to map floods under forest canopy in temperate zone despite its short wavelength and high attenuation.

In this study, TerraSAR-X dual-polarimetric HH/VV and RADARSAT-2 fully polarimetric synthetic aperture radar (SAR) parameters are compared to results from field surveys of grasslands in order to establish a methodology for the detection of grass cutting events. The experiment over grasslands in Estonia during the vegetative season of 2013 was carried out with an extensive survey measuring grass height, wet and dry biomass, and soil moisture. An entropy/alpha decomposition was applied to the data. Additionally, the polarimetric coherences between the different channels, backscatter levels, and intensity ratios were analyzed. From the numerous polarimetric parameters studied, HH/VV polarimetric coherence and the scattering entropy seemed to provide the most reliable indication about a cutting event based on the polarimetric SAR (PolSAR) time series. The behavior was more pronounced in TerraSAR-X data than in RADARSAT-2 data, possibly due to the finer temporal sampling (11 days vs. 24 days for exactly the same imaging geometry) and shorter wavelength. After the grass was cut, TerraSAR-X HH/VV polarimetric coherence magnitude decreased by 0.27 (by 0.12 on average) and scattering entropy increased by 0.21 (by 0.07 on average). The observed behavior can be well explained by field observations and modeling of the vegetation backscattering. According to a vegetation particle model, growing grass (mainly vertically oriented dipoles) corresponds to lower entropy and higher HH/VV polarimetric coherence magnitude than cut grass (more horizontally and more randomly oriented dipoles). This indicates the potential to use HH/VV polarimetric coherence magnitude and scattering entropy for the monitoring of grassland cutting practices.

In this article, we report on the in-orbit experience - an overview of ESTCube-1 operations from the launch until the experiment, as well as on lessons learned from five years of development and almost two years of operations. Lessons are identified from the point of view of system engineering, electrical engineering, mechanical engineering, software engineering, testing and measurements, payload, and management. Detailed flight results of ESTCube-1 will be provided in dedicated articles. We hope that other teams can benefit from our experience.

This study evaluates the potential of X-band interferometry for monitoring of agricultural grasslands. Time series of HH-polarization COSMO-SkyMed 1-day repeat-pass interferometric SAR (InSAR) pairs is analyzed in regard to detecting mowing events, and assessing vegetation height and biomass on grasslands. The time series of four InSAR pairs was analyzed in regard to the ground reference data collected during an extensive campaign covering 11 agricultural grasslands. The calculated temporal interferometric coherence was found to be inversely correlated to the vegetation height and wet above-ground biomass. It was found that grass removal increases the coherence magnitude indicating a potential use of this parameter for the detection of mowing. However, precipitation and farming activity between the acquisitions interfere with this effect. Temporal coherence was expressed as a function of the vegetation height through the random motion of scatterers in the vegetation layer. For vegetation height limited to the range between 0 and 1 m, a very strong correlation between the grass height and the linearised temporal coherence was found, with a coefficient r = 0.81. No significant correlation was found between the backscattering coefficient and the wet above-ground biomass as well as the height of grass. However, a strong negative correlation was found between the backscattering coefficient and the measured soil moisture.