Electromagnetic Scattering Models for InSAR Correlation Measurements of Vegetation and Snow

Interferometric Synthetic Aperture Radar (InSAR) has proved successful and efficient in measuring the vertical structure of the distributed targets such as vegetation and snow, which are dominated by volume scattering. In particular, the InSAR correlation measurement has been utilized to retrieve the target vertical structural information. One existing and well-known electromagnetic scattering model of the InSAR correlation was first brought forward focusing on the single-pass InSAR observation of a sparse random medium like vegetation. However, the lack of the adaption of this InSAR scattering model for repeat-pass InSAR observation of vegetation as well as for single-pass InSAR observation of snow by considering its dense medium characteristics, essentially constrain fully exploiting InSAR\u27s capability of measuring sparse and dense medium characteristics. In this work, the well-known InSAR scattering model will be adapted to accommodate the two scenarios: 1) repeat-pass InSAR observation of vegetation and 2) single-pass InSAR observation of snow and considering its dense medium characteristics. Theoretical model derivations as well as parameter retrieval approaches are demonstrated for both of the applications, respectively. Both of the simulated and ground validation results are also presented. The InSAR scattering models along with the parameter retrieval analysis described in this work will expand InSAR\u27s capability as well as the range of vegetation and snow characteristics that can be retrieved by single-pass and/or repeat-pass InSAR systems

The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space

The primary objective of the European Space Agency's 7th Earth Explorer mission, BIOMASS, is to determine the worldwide distribution of forest above-ground biomass (AGB) in order to reduce the major uncertainties in calculations of carbon stocks and fluxes associated with the terrestrial biosphere, including carbon fluxes associated with Land Use Change, forest degradation and forest regrowth. To meet this objective it will carry, for the first time in space, a fully polarimetric P-band synthetic aperture radar (SAR). Three main products will be provided: global maps of both AGB and forest height, with a spatial resolution of 200 m, and maps of severe forest disturbance at 50 m resolution (where “global” is to be understood as subject to Space Object tracking radar restrictions). After launch in 2022, there will be a 3-month commissioning phase, followed by a 14-month phase during which there will be global coverage by SAR tomography. In the succeeding interferometric phase, global polarimetric interferometry Pol-InSAR coverage will be achieved every 7 months up to the end of the 5-year mission. Both Pol-InSAR and TomoSAR will be used to eliminate scattering from the ground (both direct and double bounce backscatter) in forests. In dense tropical forests AGB can then be estimated from the remaining volume scattering using non-linear inversion of a backscattering model. Airborne campaigns in the tropics also indicate that AGB is highly correlated with the backscatter from around 30 m above the ground, as measured by tomography. In contrast, double bounce scattering appears to carry important information about the AGB of boreal forests, so ground cancellation may not be appropriate and the best approach for such forests remains to be finalized. Several methods to exploit these new data in carbon cycle calculations have already been demonstrated. In addition, major mutual gains will be made by combining BIOMASS data with data from other missions that will measure forest biomass, structure, height and change, including the NASA Global Ecosystem Dynamics Investigation lidar deployed on the International Space Station after its launch in December 2018, and the NASA-ISRO NISAR L- and S-band SAR, due for launch in 2022. More generally, space-based measurements of biomass are a core component of a carbon cycle observation and modelling strategy developed by the Group on Earth Observations. Secondary objectives of the mission include imaging of sub-surface geological structures in arid environments, generation of a true Digital Terrain Model without biases caused by forest cover, and measurement of glacier and icesheet velocities. In addition, the operations needed for ionospheric correction of the data will allow very sensitive estimates of ionospheric Total Electron Content and its changes along the dawn-dusk orbit of the mission

A Review of Crop Height Retrieval Using InSAR Strategies: Techniques and Challenges

This article compares the performance of four different interferometric synthetic aperture radar (SAR) techniques for the estimation of rice crop height by means of bistatic TanDEM-X data. Methods based on the interferometric phase alone, on the coherence amplitude alone, on the complex coherence value, and on polarimetric SAR interferometry (PolInSAR) are analyzed. Validation is conducted with reference data acquired over rice fields in Spain during the Science Phase of the TanDEM-X mission. Single- and dual-polarized data are exploited to also provide further insights into the polarization influence on these approaches. Vegetation height estimates from methodologies based on the interferometric phase show a general underestimation for the HH channel (with a bias that reaches around 25 cm in mid-July for some fields), whereas the VV channel is strongly influenced by noisy phases, especially at large incidences [root-mean-square error (RMSE) = 31 cm]. Results show that these approaches perform better at shallower incidences than the methodologies based on coherence amplitude and on PolInSAR, which obtain the most suitable results at steep incidences, with RMSE values of 17 and 23 cm. On the contrary, at shallower incidences, they are highly affected by very low input coherence levels. Hence, they tend to overestimate vegetation height.This work was supported by the Spanish Ministry of Science and Innovation, in part by the State Agency of Research, and in part by the European Funds for Regional Development under Project TEC2017-85244-C2-1-P. The work of Noelia Romero-Puig was supported in part by the Generalitat Valenciana and in part by the European Social Fund under Grant ACIF/2018/204

On the Sensitivity of TanDEM-X-Observations to Boreal Forest Structure

The structure of forests is important to observe for understanding coupling to global dynamics of ecosystems, biodiversity, and management aspects. In this paper, the sensitivity of X-band to boreal forest stem volume and to vertical and horizontal structure in the form of forest height and horizontal vegetation density is studied using TanDEM-X satellite observations from two study sites in Sweden: Remningstorp and Krycklan. The forest was analyzed with the Interferometric Water Cloud Model (IWCM), without the use of local data for model training, and compared with measurements by Airborne Lidar Scanning (ALS). On one hand, a large number of stands were studied, and in addition, plots with different types of changes between 2010 and 2014 were also studied. It is shown that the TanDEM-X phase height is, under certain conditions, equal to the product of the ALS quantities for height and density. Therefore, the sensitivity of phase height to relative changes in height and density is the same. For stands with a phase height >5 m we obtained an root-mean-square error, RMSE, of 8% and 10% for tree height in Remningstorp and Krycklan, respectively, and for vegetation density an RMSE of 13% for both. Furthermore, we obtained an RMSE of 17% for estimation of above ground biomass at stand level in Remningstorp and in Krycklan. The forest changes estimated with TanDEM-X/IWCM and ALS are small for all plots except clear cuts but show similar trends. Plots without forest management changes show a mean estimated height growth of 2.7% with TanDEM-X/IWCM versus 2.1% with ALS and a biomass growth of 4.3% versus 4.2% per year. The agreement between the estimates from TanDEM-X/IWCM and ALS is in general good, except for stands with low phase height

Boreal Forest Properties from TanDEM-X Data Using Interferometric Water Cloud Model and Implications for a Bistatic C-Band Mission

Data from TanDEM-X in single-pass and bistatic interferometric mode together with the interferometric water cloud model (IWCM) can provide estimates of forest height and stem volume (or the related above-ground biomass) of boreal forests with high accuracy. We summarize results from two boreal test sites using two approaches, i.e., 1) based on model calibration using reference insitu stands, and 2) based on minimization of a cost function. Both approaches are based on inversion of IWCM, which models the complex coherence and backscattering coefficient of a homogeneous forest layer, which includes gaps where free-space wave propagation is assumed. A digital terrain model of the ground is also needed. IWCM is used to estimate forest height or stem volume, since the two variables are assumed to be related through an allometric equation. A relationship between the fractional area of gaps, the area-fill, and stem volume is also required to enable model inversion. The accuracy of the stem volume estimate in the two sites varies between 16% and 21% for height of ambiguity <100 m. The results clearly show the importance of using summer-time acquisitions. Based on the TanDEM-X results at X-band, C-band data from the ERS-1/ERS-2 tandem mission are revisited to investigate the potential of a future bistatic C-band interferometric mission. Out of nine ERS-1/ERS-2 pairs, only one pair was found to be acquired at summer temperatures, without precipitation and with high coherence. A simulated bistatic phase height is shown to give approximately the same sensitivity to stem volume as TanDEM-X

Assessment of Paddy Rice Height: Sequential Inversion of Coherent and Incoherent Model

This paper investigates the evolution of canopy height of rice fields for a complete growth cycle. For this purpose, copolar interferometric Synthetic Aperture Radar (Pol-InSAR) time series data were acquired during the large across-track baseline (>1 km) science phase of the TanDEM-X mission. The height of rice canopies is estimated by three different model-based approaches. The first approach evaluates the inversion of the Random Volume over Ground (RVoG) model. The second approach evaluates the inversion of a metamodel-driven electromagnetic backscattering model by including a priori morphological information. The third approach combines the previous two processes. The validation analysis was carried out using the Pol-InSAR and ground measurement data acquired between May and September in 2015 over rice fields located in Ipsala district of Edirne, Turkey. The results of presented height estimation algorithms demonstrated the advantage of Pol-InSAR data. The combined RvoG model and EM metamodel height estimation approach provided rice canopy heights with errors less than 20 cm for the complete growth cycle

Parameters affecting interferometric coherence and implications for long-term operational monitoring of mining-induced surface deformation

Includes abstract.Includes bibliographical references.Surface deformation due to underground mining poses risks to health and safety as well as infrastructure and the environment. Consequently, the need for long-term operational monitoring systems exists. Traditional field-based measurements are point-based meaning that the full extent of deforming areas is poorly understood. Field-based techniques are also labour intensive if large areas are to be monitored on a regular basis. To overcome these limitations, this investigation considered traditional and advanced differential radar interferometry techniques for their ability to monitor large areas over time, remotely. An area known to be experiencing mining induced surface deformation was used as test case. The agricultural nature of the area implied that signal decorrelation effects were expected. Consequently, four sources of data, captured at three wavelengths by earth-orbiting satellites were obtained. This provided the opportunity to investigate different phase decorrelation effects on data from standard imaging platforms using real-world deformation phenomenon as test-case. The data were processed using standard dInSAR and polInSAR techniques. The deformation measurement results together with an analysis of parameters most detrimental to long-term monitoring were presented. The results revealed that, contrary to the hypothesis, polInSAR techniques did not provide an enhanced ability to monitor surface deformation compared to dInSAR techniques. Although significant improvements in coherence values were obtained, the spatial heterogeneity of phase measurements could not be improved. Consequently, polInSAR could not overcome ecorrelation associated with vegetation cover and evolving land surfaces. However, polarimetric information could be used to assess the scattering behaviour of the surface, thereby guiding the definition of optimal sensor configuration for long-term monitoring. Despite temporal and geometric decorrelation, the results presented demonstrated that mining-induced deformation could be measured and monitored using dInSAR techniques. Large areas could be monitored remotely and the areal extent of deforming areas could be assessed, effectively overcoming the limitations of field-based techniques. Consequently, guidelines for the optimal sensor configuration and image acquisition strategy for long-term operational monitoring of mining-induced surface deformation were provided

ALOS-2/PALSAR-2 Calibration, Validation, Science and Applications

Twelve edited original papers on the latest and state-of-art results of topics ranging from calibration, validation, and science to a wide range of applications using ALOS-2/PALSAR-2. We hope you will find them useful for your future research