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

Topographic Correction for Biomass Retrieval from P-band SAR Data in Boreal Forests

The influence of the ground slope on radar backscatter has been proven to be greater for lower radar frequencies due to deeper canopy penetration. In this study, multiple heading, Pband SAR data of boreal forest in Sweden was used to find a model for topographic correction for improved biomass retrieval. Eleven models were tested and the best model was selected. The selected model was then used for biomass retrieval. Even by means of the most simplified approach, forest biomass could be established with a root-mean-square error of approximately 50 t/ha for HV and 66 t/ha for HH

Estimation of Forest Biomass and Faraday Rotation using Ultra High Frequency Synthetic Aperture Radar

Synthetic Aperture Radar (SAR) data in the Ultra High Frequency (UHF; 300 MHz – 3 GHz)) band have been shown to be strongly dependent of forest biomass, which is a poorly estimated variable in the global carbon cycle. In this thesis UHF-band SAR data from the fairly flat hemiboreal test site Remningstorp in southern Sweden were analysed. The data were collected on several occasions with different moisture conditions during the spring of 2007. Regression models for biomass estimation on stand level (0.5-9 ha) were developed for each date on which SAR data were acquired. For L-band (centre frequency 1.3 GHz) the best estimation model was based on HV-polarized backscatter, giving a root mean squared error (rmse) between 31% and 46% of the mean biomass. For P-band (centre frequency 340 MHz), regression models including HH, HV or HH and HV backscatter gave an rmse between 18% and 27%. Little or no saturation effects were observed up to 290 t/ha for P-band. A model based on physical-optics has been developed and was used to predict HH-polarized SAR data with frequencies from 20 MHz to 500 MHz from a set of vertical trunks standing on an undulating ground surface. The model shows that ground topography is a critical issue in SAR imaging for these frequencies. A regression model for biomass estimation which includes a correction for ground slope was developed using multi-polarized P-band SAR data from Remningstorp as well as from the boreal test site Krycklan in northern Sweden. The latter test site has pronounced topographic variability. It was shown that the model was able to partly compensate for moisture variability, and that the model gave an rmse of 22-33% when trained using data from Krycklan and evaluated using data from Remningstorp. Regression modelling based on P-band backscatter was also used to estimate biomass change using data acquired in Remningstorp during the spring 2007 and during the fall 2010. The results show that biomass change can be measured with an rmse of about 15% or 20 tons/ha. This suggests that not only deforestation, but also forest growth and degradation (e.g. thinning) can be measured using P-band SAR data. The thesis also includes result on Faraday rotation, which is an ionospheric effect which can have a significant impact on spaceborne UHF-band SAR images. Faraday rotation angles are estimated in spaceborne L-band SAR data. Estimates based on distributed targets and calibration targets with high signal to clutter ratios are found to be in very good agreement. Moreover, a strong correlation with independent measurements of Total Electron Content is found, further validating the estimates

Simultaneous Estimation of Sub-canopy Topography and Forest Height with Single-baseline Single-polarization TanDEM-X Interferometric Data Combined with ICESat-2 Data

To address the challenge of retrieving sub-canopy topography using single-baseline single-polarization TanDEM-X InSAR data, we propose a novel InSAR processing framework. Our methodology begins by employing the SINC model to estimate the penetration depth (PD). Subsequently, we establish a linear relationship between PD and phase center height (PCH) to generate a wall-to-wall PCH product. To achieve this, space-borne LiDAR data are employed to capture the elevation bias between actual ground elevation and InSAR-derived elevation. Finally, the sub-canopy topography is derived by subtracting the PCH from the conventional InSAR-based DEM. Moreover, this approach enables the simultaneous estimation of forest height from single-baseline TanDEM-X data by combining the estimated PD and PCH components. The approach has been validated against Airborne Lidar Scanning data over four diverse sites encompassing different forest types, terrain conditions, and climates. The derived sub-canopy topography in the boreal and hemi-boreal forest sites (Krycklan and Remningstorp) demonstrated notable improvement in accuracy. Additionally, the winter acquisitions outperformed the summer ones in terms of inversion accuracy. The achieved RMSEs for the winter scenarios were 2.45 m and 3.83 m, respectively, representing a 50% improvement over the InSAR-based DEMs. And the forest heights are also close to the ALS measurements, with RMSEs of 2.70 m and 3.33 m, respectively. For the Yanguas site in Spain, characterized by rugged terrain, sub-canopy topography in forest areas was estimated with an accuracy of 4.27m, a 35% improvement over the original DEM. For the denser tropical forest site, only an average elevation bias could be corrected.This work is funded by the National Key R&D Program of China (No. 2022YFB3902605), the National Natural Science Foundation of China (Nos. 42227801, 42030112, 42204024, 42104016, 42330717), the Spanish Ministry of Science and Innovation (State Agency of Research, AEI) and the European Funds for Regional Development under Project PID2020-117303GB-C22/AEI/10.13039/501100011033, the Natural Science Foundation for Excellent Young Scholars of Hunan Province (No. 2023JJ20061), and in part by the China Scholarship Council Foundation to the Joint Ph.D. Studies at University of Alicante (No. 202106370125)

Summaries of the Sixth Annual JPL Airborne Earth Science Workshop

The Sixth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on March 4-8, 1996, was divided into two smaller workshops:(1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, and The Airborne Synthetic Aperture Radar (AIRSAR) workshop. This current paper, Volume 2 of the Summaries of the Sixth Annual JPL Airborne Earth Science Workshop, presents the summaries for The Airborne Synthetic Aperture Radar (AIRSAR) workshop

Estimation of RVoG Scene Parameters by Means of PolInSAR With TanDEM-X Data: Effect of the Double-Bounce Contribution

This article evaluates the effect of the double-bounce (DB) decorrelation term that appears in single-pass bistatic acquisitions, as in the TanDEM-X system, on the inversion of scene parameters by means of polarimetric SAR interferometry (PolInSAR). The retrieval of all scene parameters involved in the Random Volume over Ground (RVoG) model (i.e., ground topography, vegetation height, extinction, and ground-to-volume ratios) is affected by this term when the radar response from the ground is dominated by the DB. The estimation error in all these parameters is analyzed by means of simulations over a wide range of system configurations and scene variables for both agricultural crops and forest scenarios. Simulations demonstrate that the inclusion of the DB term, which complicates the inversion algorithm, is necessary for the angles of incidence shallower than 30° to achieve an estimation error below 10% in vegetation height and to avoid a significant underestimation in the ground-to-volume ratios. At steep incidences, this decorrelation term does not affect the estimation of vegetation height and ground-to-volume ratios. Regarding the extinction, this parameter is intrinsically not well estimated, since most retrieved values are close to the initial guesses employed for the optimization algorithm, regardless of the use or not of the DB decorrelation term. Finally, these findings are compared with the experimental results from the TanDEM-X data acquired over the rice fields in Spain for the available system parameters (baseline and incidence angle) of the acquired data set.This work was supported in part by the Spanish Ministry of Science, Innovation and Universities, the State Agency of Research (AEI), and in part by the European Funds for Regional Development (EFRD) 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 (ESF) under Grant ACIF/2018/204

Retrieval of vegetation height in rice fields using polarimetric SAR interferometry with TanDEM-X data

This work presents for the first time a demonstration with satellite data of polarimetric SAR interferometry (PolInSAR) applied to the retrieval of vegetation height in rice fields. Three series of dual-pol interferometric SAR data acquired with large baselines (2–3 km) by the TanDEM-X system during its science phase (April–September 2015) are exploited. A novel inversion algorithm especially suited for rice fields cultivated in flooded soil is proposed and evaluated. The validation is carried out over three test sites located in geographically different areas: Sevilla (SW Spain), Valencia (E Spain), and Ipsala (W Turkey), in which different rice types are present. Results are obtained during the whole growth cycle and demonstrate that PolInSAR is useful to produce accurate height estimates (RMSE 10–20 cm) when plants are tall enough (taller than 25–40 cm), without relying on external reference information.This work has been supported by the Spanish Ministry of Economy and Competitiveness (MINECO) and EU FEDER under project TIN2014-55413-C2-2-P. The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement 606983, and the Land-SAF (the EUMETSAT Network of Satellite Application Facilities) project. The in-situ measurements in the Ipsala site were conducted with the funding of The Scientific and Technological Research Council of Turkey (TUBITAK, Project No.: 113Y446)

The BIOMASS level 2 prototype processor : design and experimental results of above-ground biomass estimation

BIOMASS is ESA’s seventh Earth Explorer mission, scheduled for launch in 2022. The satellite will be the first P-band SAR sensor in space and will be operated in fully polarimetric interferometric and tomographic modes. The mission aim is to map forest above-ground biomass (AGB), forest height (FH) and severe forest disturbance (FD) globally with a particular focus on tropical forests. This paper presents the algorithms developed to estimate these biophysical parameters from the BIOMASS level 1 SAR measurements and their implementation in the BIOMASS level 2 prototype processor with a focus on the AGB product. The AGB product retrieval uses a physically-based inversion model, using ground-canceled level 1 data as input. The FH product retrieval applies a classical PolInSAR inversion, based on the Random Volume over Ground Model (RVOG). The FD product will provide an indication of where significant changes occurred within the forest, based on the statistical properties of SAR data. We test the AGB retrieval using modified airborne P-Band data from the AfriSAR and TropiSAR campaigns together with reference data from LiDAR-based AGB maps and plot-based ground measurements. For AGB estimation based on data from a single heading, comparison with reference data yields relative Root Mean Square Difference (RMSD) values mostly between 20% and 30%. Combining different headings in the estimation process significantly improves the AGB retrieval to slightly less than 20%. The experimental results indicate that the implemented retrieval scheme provides robust results that are within mission requirements

Estimation of change in forest variables using synthetic aperture radar

Large scale mapping of changes in forest variables is needed for both environmental monitoring, planning of climate actions and sustainable forest management. Remote sensing can be used in conjunction with field data to produce wall-to-wall estimates that are practically impossible to produce using traditional field surveys. Synthetic aperture radar (SAR) can observe the forest independent of sunlight, clouds, snow, or rain, providing reliable high frequency coverage. Its wavelength determines the interaction with the forest, where longer wavelengths interact with larger structures of the trees, and shorter wavelengths interact mainly with the top part of the canopy, meaning that it can be chosen to fit specific applications. This thesis contains five studies conducted on the Remningstorp test site in southern Sweden. Studies I – III predicted above ground biomass (AGB) change using long wavelength polarimetric P- (in I) and L-band (in I – III) SAR data. The differences between the bands were small in terms of prediction quality, and the HV polarization, just as for AGB state prediction, was the polarization channel most correlated with AGB change. A moisture correction for L-band data was proposed and evaluated, and it was found that certain polarimetric measures were better for predicting AGB change than all of the polarization channels together. Study IV assessed the detectability of silvicultural treatments in short wavelength TanDEM-X interferometric phase heights. In line with earlier studies, only clear cuts were unambiguously distinguishable. Study V predicted site index and stand age by fitting height development curves to time series of TanDEM-X data. Site index and age were unbiasedly predicted for untreated plots, and the RMSE would likely decrease with longer time series. When stand age was known, SI was predicted with an RMSE comparable to that of the field based measurements. In conclusion, this thesis underscores SAR data's potential for generalizable methods for estimation of forest variable changes

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