• 11:10 On Combining BIOMASS with Contemporary Sensors

  Williams, Mark L. Horizon Geoscience Consulting, Australia

  Show abstract

  Whilst, with good reason, the ESA Earth Explorer BIOMASS mission may have been conceived as a stand-alone system, there should exist benefits for forest cover and biomass retrieval through augmenting BIOMASS with data from other contemporary remote sensing systems. For example, knowledge of land cover and forest composition is a requirement for accurate biomass retrieval [1]: high biomass mangrove can appear darker than rain forest of a similar biomass [2]. The BIOMASS mission may yield altitude data useful for distinguishing forest types, but low resolution P-band SAR imagery may not, on its own, provide fine land cover class separation. A combination of SAR and optical data from various sensors could be used to improve land cover separations and biomass retrieval accuracies. Although P-band backscatter sensitivity (arguably) extends to high forest biomass, low-biomass forest yields P-band backscatter levels which are generally lower than at L-band [3]. Although L-band backscatter cannot accurately distinguish biomass variation at high forest biomass, L-band brightness at lower biomass indicates that L-band SAR and PolInSAR, perhaps from a future Tandem-L mission, might be used to complement BIOMASS P-band data. BIOMASS is designed to exploit P-band PolInSAR to recover forest height information. The difficulties associated with doing this from space have been addressed in the BIOMASS system design, but the proof will be in the implementation. Multi-frequency InSAR has been used successfully to recover forest biophysical information [4-9], and corrected X-band InSAR from Tandem-X could be used with BIOMASS ground height estimates to provide adjunct forest height estimates. Stereo-Optical data may also be useful for this purpose and has been combined with X-band InSAR for forest change detection [10]. X-band or C-band InSAR may also provide useful estimates of ground height close to forested areas, where the ground height from P-band is uncertain due to low backscatter levels, whilst the ground-height under the canopy may be overestimated due to volume backscatter [11]. In addition LiDAR derived canopy heights, although relatively costly and of limited coverage, are correlated with those derived from multi-frequency InSAR [12] and will no doubt prove valuable in assessing the accuracy of BIOMASS forest height estimates. They may also provide information regarding canopy depth profiles [13] that perturb wave propagation in the canopy away from the simple RVOG model, and influence the accuracy of biomass retrieval algorithms. Finally an important issue for many countries is the ability not simply to receive estimates of biomass but to derive their own estimates of forest cover and biomass using BIOMASS data that benefit from their expert knowledge of the nature and composition of their forests. Many (perhaps even most) tropical countries have significant experience only of processing optical data and this may prove a barrier to BIOMASS data uptake unless provision is made for tropical forest countries to combine their traditional data sources with P-band SAR in an accessible way [14]. Potential synergies of the BIOMASS system with other sensors will be illustrated in the presentation using studies in Peru and Papua New Guinea involving P-band and X-band InSAR, stereo-optical data and LiDAR. References [1] J Fox, M L Williams, T Milne, R Keenan, Protocols for Field Sampling of Forest Carbon Pools for Monitoring, Reporting and Verification of REDD, Proceedings of the International Geoscience and Remote Sensing Symposium, July, Hawaii, 2010 [2] M L Williams, A K Milne, I J Tapley, A Mitchell, J Fox and C Yosi, The Kokoda Track and Owen Stanley Ranges Remote Sensing Pilot Project, for the Department of Environment and Conservation, Papua New Guinea, 18th April, 2013 (avail. on request from Mr James Sabi, DEC PNG) [3] I Hajnsek and D Hoekman, Final Report: Indrex-II Campaign over Tropical Forest in L-band and P-band, ESA (http://earth.esa.int/campaigns/DOC/indrexII_finalreport_v6.pdf), 2006 [4] A Ulbricht, A Reigber, R Horn, A Potsis and A Moreira, Multi-Frequency SAR Interferometry: DEM-generation in L- and P-band and Vegetation Height Estimation in Combination with X-band, Proceedings EUSAR 2000, 51, Munich, 23-25 May, 2000 [5] M L Williams, M Silman, S Saatchi, S Hensley, M Sanford, A Yohannan, B Kofman, J Reis, B Kampes, Analysis of GeoSAR, Dual-Band InSAR Data for Peruvian Forest, Proc. IGARSS, July, Hawaii, 2010 [6] M L Williams, T Milne, I Tapley, J Reis, M Sanford, B Kofman, S Hensley, Tropical Forest Biomass Recovery using GeoSAR Observations, Proc. IGARSS, July, Cape Town, 2009 [7] S Saatchi, M L Williams, M Silman, S Hensely, Estimation of Tropical Forest Height and Aboveground Biomass from Dual-Band InSAR Measurements in Peruvian Amazon, Proc. IGARSS, July, Hawaii, 2010 [8] M Lavalle, S Hensley and M L Williams, Use of Airborne Instruments for Tropical Forest Monitoring Applications, 2012, Proc. IEEE International Symposium on Geoscience and Remote Sensing, Munich, July, 2012 [9] A Mitchell, M L Williams, I Tapley and A K Milne, Interoperability of Multi-Frequency SAR Data for Forest Information Extraction in Support of National MRV Systems, 2012, Proc. IEEE IGARSS, Munich, July, 2012 [10] T Tadono, M L Williams and S Hensley, Comparison of Stereo-Optical and Dual-Band InSAR DEMs in Papua New Guinea, 2012, Proc. IEEE IGARSS, Munich, July, 2012 [11] M Lavalle, M L Williams, S Hensley, D Solimini, and E Pottier, Dependence of P-band Interferometric Height on Forest Parameters from Simulation and Observation, Proc. IGARSS, July, Cape Town, 2009 [12] J O Sextona, T Baxa, P Siqueira, J J Swensona and S Hensley, A comparison of lidar, radar, and field measurements of canopy height in pine and hardwood forests of southeastern North America, Forest Ecology and Management, 257, 3, 1136-1147, 10th February, 2009 [13] R M Lucas, J Armston, P Bunting, D Clewley, P Scarth, M Schmidt, A Accad, P Siqueira Yang Lei, Forest Biomass Estimation, Australia, Presentation to JAXA K&C Mtg, 9-12th April, 2013 [14] GFOI. 2013. Review of Priority Research & Development Topics: R&D related to the use of Remote Sensing in National Forest Monitoring. Pub. GEO, Switzerland, 2013 ISBN 978-92-990047-5-3.

  
   

• 12:10 Impact of temporal decorrelation on tree height and biomass estimation at P-band: PolInSAR experiments with the P-band RMoG model

  Lavalle, Marco; Pinto, Naiara; Amhed, Razi; Neumann, Maxim; Hensley, Scott JPL/Caltech, United States of America

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  The future European Space Agency’s BIOMASS mission will use 3-day repeat-pass PolInSAR observations to map forest tree height globally with about 20%-30% error [1]. Temporal decorrelation is a major limitation for repeat-pass PolInSAR as it alters randomly the coherence phase and magnitude by an amount comparable to the volumetric decorrelation. Experiments have shown that significant temporal decorrelation can occur in both L-band and P-band observations and with temporal scales on the order of a few days. If temporal decorrelation is not properly accounted for during parameter estimation, tree height is typically overestimated with error depending on the relative level of temporal decorrelation [3-6]. Much of our research effort in the past five years has been focused on the modeling and compensation of temporal decorrelation at L-band. We have developed the random-motion-over-ground (RMoG) model, which combines the volumetric coherence inherited from the random-volume-over-ground (RVOG) model with the temporal coherence based on Gaussian-statistic motion of scattering elements. The most important feature of the RMoG model is the complex-valued, polarization-dependent temporal decorrelation, which allows formulating the inverse problem with compensation for temporal decorrelation. In previous works we have validated the RMoG model and successful extracted the model parameters from L-band JPL/UAVSAR and DLR/E-SAR data [7-9]. In this contribution we step forward and apply for the first time the RMoG model to P-band data. Our goal is to provide the BIOMASS scientific community with an algorithm for the robust estimation of tree height from repeat-pass PolInSAR BIOMASS data. The specific objectives of this work are to: (1) provide an assessment of the impact of temporal decorrelation in tree height estimation from non-zero baseline P-band data; (2) reprocess the TROPISAR campaign data with our RMoG model-based inversion procedure; (3) show first results of PolInSAR inversion using new data collected by NASA’s airborne P-band sensor UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar). To meet objective (1) above we will use the RMoG model in conjunction with discrete scattering simulations of idealized forests at P-band. The output of several simulations with various scattering and dynamic characteristics will be inverted through the RMoG model-based algorithm to produce plots of estimated tree height error versus input model parameters. At the workshop we will describe briefly the simulator and show how temporal decorrelation (induced by both scatterer motion and dielectric changes) impacts the estimation of tree height at P-band. Next, we will show results of the RMoG model-based parameter estimation applied to real P-band data. We have already acquired the data from the ESA/TROPISAR campaign and carried out a preliminary analysis of the data. At the workshop we will discuss maps of estimated tree height and complex-valued temporal decorrelation for the Paracou site. We are also in the process of generating P-band UAVSAR interferograms collected in the frame of the AirMoss campaign over the United States, which will offer an additional opportunity to validate our PolInSAR estimation approach. [1] K. Scipal, M. Arcioni, F. Fois, C. Lin, “ESA's Biomass mission candidate: system and payload overview ESA's Biomass mission candidate: system and payload overview”, presented at the PolInSAR workshop 2013, Frascati, Italy, January 2013. [2] T. Le Toan, S. Quegan, M. Davidson, H. Balzter, P. Paillou, K. Pap- athanassiou, S. Plummer, F. Rocca, S. Saatchi, H. Shugart, and L. Ulan- der, “The BIOMASS mission: Mapping global forest biomass to better understand the terrestrial carbon cycle,” Remote Sensing of Environment, vol. 115, no. 11, pp. 2850–2860, Nov. 2011. [3] H. A. Zebker and J. Villasenor, “Decorrelation in interferometric radar echoes,” IEEE Transactions on Geoscience and Remote Sensing, vol. 30, no. 5, pp. 950–959, Sep. 1992. [4] R. Ahmed, P. Siqueira, S. Hensley, B. Chapman, and K. Bergen, “A survey of temporal decorrelation from spaceborne L-band repeat-pass InSAR,” Remote Sensing of Environment, vol. 115, no. 11, pp. 2887– 2896, Nov. 2011. [5] M. Simard, S. Hensley, M. Lavalle, R. Dubayah, N. Pinto, and M. Hofton, “An empirical assessment of temporal decorrelation using the Uninhabited Aerial Vehicle Synthetic Aperture Radar over forested landscapes,” Remote Sensing, vol. 4, no. 4, pp. 975–986, April 2012. [6] S.-K. Lee, F. Kugler, K. Papathanassiou, and I. Hajnsek, “Quantification of Temporal Decorrelation Effects at L-Band for Polarimetric SAR Inter- ferometry Applications,” Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, vol. 6, no. 3, pp. 1351–1367, June 2013. [7] M. Lavalle, M. Simard, and S. Hensley,“A temporal decorrelation model for polarimetric radar interferometers,” IEEE Trans. Geosci. Remote Sens., vol. 50, no. 7, pp. 2880–2888, July 2012. [8] M. Lavalle and K. Khun, “Three-baseline insar estimation of forest height,” Geoscience and Remote Sensing Letters, IEEE, vol. 11, no. 10, pp. 1737–1741, Oct. 2014. [9] M. Lavalle and S. Hensley, “Extraction of Structural and Dynamic Properties of Forests from Polarimetric-Interferometric SAR Data Affected by Temporal Decorrelation”, accepted in IEEE Trans. Geosci. Remote Sens.

  
   

• 12:50 A Comparison of P- and L-Band 3-D PolInSAR Forest Structure Estimates: A Study Case in Traunstein (Germany)

  Pardini, Matteo (1); Tello Alonso, Maria (1); Torano-Caicoya, Astor (2); Papathanassiou, Kostas (1) 1: German Aerospace Center (DLR), Germany; 2:Technische Universität München (TUM), Germany

• Show abstract

  Forest vertical structure is a key variable for assessing biodiversity, structural degradation and/or regeneration, and for the development of accurate biomass estimators. Moreover, the knowledge of forest structure changes is important to determine the type and the intensity of forest disturbance as well as the seasonal and annual forest cycle variation. In this framework, the next generation of low-frequency spaceborne SAR configurations will play a crucial role in forest structure monitoring as they will provide the unique ability to image large areas at high spatial and temporal resolution. Among the different SAR techniques that have been developed in the last decades, SAR Tomography (TomoSAR) allows the estimation of the 3-D distribution of the backscattered power from multiple SAR images, thus providing a proxy to forest vertical structure. Although TomoSAR is an established technique with several algorithmic implementations a still underdeveloped element is the physical interpretation of tomograms. The link between the obtained tomograms (that depend in general on frequency, polarisation and acquisition geometry) and physical forest structure parameters is essential for establishing potential applications and is not well understood yet. The enhanced observation scenario provided by SAR sensors on one side and the need for 3-D structure products for ecosystem modeling on the other, motivate the exploration of the information content of multi-baseline polarimetric interferometric measurements for the retrieval of physical forest structure parameters by means of TomoSAR techniques. As different carrier frequencies are in general sensitive to different structure elements, the comparison of the related tomograms represents an additional way to assess scattering model assumptions and to advance in their physical interpretation. With this in mind, the objective of this work is to compare TomoSAR vertical profiles of the backscattered power obtained at L- and P-band over the forest site of Traunstein. The forest of Traunstein is a temperate mixed mountain forest and is located in south-eastern Germany. Dominant tree species are European spruce and Silver fir accompanied with small fractions of European beech. It is a managed forest composed of even-aged stands which cover forest heights from 10m to 40m. Mean biomass level is on the order of 210t/ha, while some old forest stands can reach biomass levels up to 600t/ha. Compared to other managed forests in this ecological zone the biomass values of Traunstein forest are significantly higher. This very high ecological variety, together with the availability of detailed ground measurements, make the Traunstein forest an interesting study case. Multibaseline fully polarimetric SAR data were acquired by the DLR’S E-SAR platform during the TempoSAR 2009 campaign. The tomographic focusing will be carried out by means of (model-based) high resolution techniques in order to increase the vertical resolution as much as possible, as well as to overcome the imaging limitations intrinsic to a low number of baselines. By extensively using ground and airborne LiDAR measurements, the key processes and structure elements will be identified in each band, and their influence on the scattering will be discussed. To this purpose, different polarimetric channels will be combined. The capability of separating between ground and volume scatterers by using multibaseline PolInSAR models will be evaluated for the two frequencies. In addition, the structure information content of a full-pol configuration will be compared with a dual-pol one. It is expected that these experiments will allow to asses (1) the physical information content of L-band and P-band, and, therefore, (2) their synergies and complementarities towards the derivation of structure-related products. At the same, implications on SAR system design and acquisition strategies will be outlined for the derivation of forest products at a global scale.

  
   

• 11:30 A POLARIMETRIC MODEL OF TOPOGRAPHIC EFFECTS ON P-BAND FOREST BACKSCATTER

  Blomberg, Erik; Soja, Maciej J.; Ulander, Lars M. H.

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  A POLARIMETRIC MODEL OF TOPOGRAPHIC EFFECTS ON P-BAND FOREST BACKSCATTER Erik Blomberg, Maciej Jerzy Soja, and Lars M. H. Ulander Chalmers University of Technology, Gothenburg, Sweden BIOMASS, recently selected for ESAs seventh Earth Explorer mission, will for the first time provide space based P-band SAR imagery and thereby enable global mapping of forest parameters such as biomass and tree height. Several data collection campaigns were conducted to support the proposal, such as BioSAR, concentrating on boreal forest at two test sites in Sweden, and TropiSAR, focusing on tropical forest in French Guiana. These have provided forest and airborne P-band SAR data which have been used to demonstrate how this novel resource can be used to estimate relevant forest parameters [1-4]. It has been observed in P-Band polarimetric SAR images that the backscatter is significantly affected by the local topography, likely due to the strong stem ground double bounce contribution. This can interfere with the retrieval of biomass from P-band SAR – for example, good accuracy biomass estimation has been achieved using a polarimetric regression model which requires information about the ground slope angle [3,5]. It is therefore desirable to further examine the impact of topography on the forest backscatter, especially for the different polarization components. Previous work using a polarimetric electromagnetic model has produced significant variations in P-band backscatter when modeling boreal forest if a local topography is included [6]. It concluded with a comparison with SETHI SAR data from BioSAR2010 plots at the Remningstorp test site in the south of Sweden. The general features of the HH, HV, and VV components were replicated for an acquisition looking west, but the agreement was poor for images and simulations looking south. This paper will verify and expand on these results by evaluating the basic performance of the model and include modeling of the two Pauli decompositions with the aim of providing further information on the topographic effect as well as new possibilities for mitigation. We will also apply the model to BioSAR2008 data from Krycklan, a more topographically varied test site located in the north of Sweden, and results will be shown at the conference. [1] D. H. T. Minh, T. L. Toan, F. Rocca, S. Tebaldini, M. M. d'Alessandro, and L. Villard, "Relating P-Band Synthetic Aperture Radar Tomography to Tropical Forest Biomass," IEEE Transactions on Geoscience and Remote Sensing, vol. 52, pp. 967-979, Feb 2014. [2] G. Sandberg, L. M. H. Ulander, J. Wallerman, and J. E. S. Fransson, "Measurements of Forest Biomass Change Using P-Band Synthetic Aperture Radar Backscatter," IEEE Transactions on Geoscience and Remote Sensing, vol. 52, pp. 6047-6061, 2014. [3] M. J. Soja, G. Sandberg, and L. M. H. Ulander, "Regression-Based Retrieval of Boreal Forest Biomass in Sloping Terrain using P-band SAR Backscatter Intensity Data," IEEE Transactions on Geoscience and Remote Sensing, vol. 51, pp. 2646-2665, May 2013. [4] I. Hajnsek, R. Scheiber, L. M. H. Ulander, A. Gustavsson, G. Sandberg, S. Tebaldini, et al., "BioSAR 2007 technical assistance for the development of airborne SAR and geophysical measurements during the BioSAR 2007 experiment: Final report without synthesis," ESA contract no. 20755/07/NL/CB2008. [5] M. J. Soja and L. M. H. Ulander, "Polarimetric-Interferometric Boreal Forest Scattering Model for BIOMASS End-to-End Simulator," in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Quebec City, QC, Canada, 2014, pp. 1061-1064. [6] E. Blomberg, M. J. Soja and L. M. H. Ulander, "P-bans Polarimetric Model of Vertical Tree Stems on Sloping Ground," in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Quebec City, QC, Canada, 2014, pp. 80-83.

  
   

• 12:30 PolInSAR Height Retrieval Method based on Electromagnetic Forward Meta-Model initiated with TomoSAR Estimates : Applications on TropiSAR Data and Prospects for Biomass mission

  Villard, Ludovic; Le Toan, Thuy; Ho Tong, Dinh CESBIO, France

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  I. Context & Methodology In the frame of Biomass mission, recent works based on P-band (~400MHz) Synthetic Aperture Radar (SAR) airborne campaigns have shown the potential of using polarimetric, interferometric and tomographic data to retrieve forest height and biomass. However most retrieval algorithms require local training samples in order to calibrate or refine the inversion model according to bio/geo-physical perturbations. This dependence on in-situ samples could be a strong limiting factor in the context of global spaceborne missions such as Biomass. Among prospects of improvements, a more thorough use of SAR measurements (a complex observation vector) combined to predictions resulting from electromagnetic (EM) microwave scattering models could help solving inversion ambiguities, since most minimization problems based on cost functions between predictions and observations are often ill-posed. However, such approaches rely on the twofold ability of an EM model, first to reproduce the main physical scattering mechanisms contributing to the various components of the SAR observation vector (intensity, polarimetric and interferometric phase) and second to be simple and fast enough to be implemented in a feedback inversion scheme. Most state-of-the-art models being heavy to implement, especially since extensive set of input parameters (describing the medium) are often required, this paper demonstrates the interest of Forward Meta-Models (FMM), simpler invertible models that aim at reproducing as faithfully as possible the main characteristics of the observation vector. For that purpose, a key point lies in the determination of a reduced set of input parameters which govern the main trends of the model surface response. The method presented in this study is based on a model-based parameterization of the complete EM model (refer to as MIPERS – Multisatic Interferometric Polarimetric Electromagnetic model for Remote Sensing), using a Forest Growth Descriptive Model (FGDM) which enables to derive most of the geometrical input parameters as a function of forest Above Ground Biomass (AGB). To assess the impact of the remaining parameters -- i.o which can not be modelled as outputs of FGDM -- a sensitivity analysis is performed based on simulations using MIPERS, which shows the importance of forest structure, especially through the ratio between crown layer total forest height. To cope with that additional required parameterization, estimates from Tomographic SAR acquisitions (TomoSAR) could be used, based on the vertical profiles resulting from the backscattering levels associated to TomoSAR voxels. Such method would particularly take advantage of Biomass mission acquisition plans, given the scheduled preliminary phase of TomoSAR data during one year and with global coverage. Based on such parameterization, EM simulations are performed following specific designs of experiments in order to build a mesh for the response surface of the complete model. These samples are then used to estimate an interpolated continuous response surface for the FMM, described as a functional of the inputs, the interpolation being conducted through scalar Kriging technique extended to the vectorial case. Such continuous response surface, describing the FMM as a functional of the inputs, is fundamental to solve the inverse problem, for which standard non-linear optimization techniques or iterative approaches couldn't be adapted to non real-time models. II. Applications to P-band PolInSAR height Retrieval on TropiSAR data As far as P-band PolInSAR height retrieval is concerned, the FMM presented above is developed as a functional relating an output vector made of PolInSAR complex coherences and an input vector made by forest height, vegetation and soil water content. The functional is also parameterized according to TomoSAR estimates of the mean crown to total forest height ratio, resulting from vertical profiles of the backscatter. To assess the ability of the FMM to reproduce experimental observations, these simulated PolInSAR coherences have been confronted to those obtained from the TropiSAR airborne campaign and analysed as a function of forest AGB at Paracou test site, where more than 80 ha forest plots have been inventoried and are available for validation. Our analysis shows the importance of forest structure, which causes in this case significant differences between extinction coefficients in vertical and horizontal polarizations and which results in higher VV phase center than expected by the standard inverse PolInSAR model (and the so-called RVOG model). In order to demonstrate the feasibility of the FMM based PolInSAR inversion algorithm, forest height have been estimated and compared to airborne LiDAR heights over most forest plots at Paracou test site, tough restricted in this study to forest plots over moderate terrain topography (typically with mean terrain slopes lower than 10%). Considering terrain topography as another time-invariant feature of a forest plot, next developments will be therefore dedicated to include TomoSAR estimates of terrain slopes in the parameterization of the Forward Meta-Model.

  
   

• 11:50 FIRST RESULTS FROM THE ECOSAR P-BAND DIGITAL BEAMFORMING SINGLE PASS INSAR

  Fatoyinbo, Lola; Rincon, Rafael; Osmanoglu, Batuhan; Sun, Guoqing; Lee, Seung Kuk; Ranson, Jon NASA Goddard Space Flight Center, United States of America

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  Climate change constitutes the greatest environmental problem of this century and is destined to significantly impact all societies. Quantifying the carbon cycle is the most important element in understanding climate change and its consequences, yet is still poorly understood. Forests store 85% of terrestrial carbon, but the amount of carbon contained in the earth’s forests is not known to even one significant figure, ranging from 385 to 650 10^15g carbon. Better monitoring techniques are needed to supply objective information on forest biomass and biomass change, locating and quantifying the terrestrial carbon sinks, and improving understanding of their dynamics. In this presentation, we will introduce the EcoSAR instrument, an airborne Polarimetric and Interferometric P-band Synthetic Aperture Radar (SAR) instrument that provides two- and three-dimensional fine scale measurements of terrestrial ecosystem structure and biomass. Many tropical and some temperate forests’ biomasses can reach up to 600 Mg/ha or more, which cannot be measured with current SAR capabilities. Interferometric SAR (InSAR) and Polarimetric InSAR (PolInSAR) are able to measure vegetation structure and biomass, without any saturation at longer wavelengths. SAR measurements are needed for frequently mapping global vegetation cover and changes due to natural and human-induced disturbances. P-Band polarimetric backscatter provides the unique capability of mapping the forest cover, disturbance from deforestation and degradation, forest recovery, wetland inundation, and aboveground biomass. The longer P band wavelength of is also desirable for other critically important science measurements such as permafrost and ice dynamics, in addition to archaeological applications. The EcoSAR system employs a digital beamforming architecture, a digital waveform generator and receiver system, and advanced dual-polarization array antennas. It is a highly reconfigurable polarimetric and interferometric P-band SAR instrument designed specifically for accurately characterizing ecosystems structure and quantifying very high biomasses. The design leverages the L-band Digital beamforming SAR (DBSAR) architecture developed at NASA Goddard Space Flight Center which has demonstrated advanced digital beamforming SAR techniques for surface imaging and biomass applications. The system architecture allows for considerable measurement flexibility such as post processing synthesis of multiple beams, simultaneous measurement over both sides of the flight track, and variable incidence angles. EcoSAR operates at a center frequency of 435 MHz (69 cm wavelength) and features a fully programmable bandwidth. An operational mode with medium resolution was designed as a nominal mode for use in frequency-restricted areas, and a science mode with high resolution (up to 200 MHz) was used in non-restricted areas, specifically in remote areas of Costa Rica. In this presentation we will give an overview of the EcoSAR system and its applications, followed by a description of the data acquired during the first flight campaign to the Bahamas and Costa Rica in 2014 and finally we will show the first polarimetric and interferometric images and science retrievals generated using the EcoSAR sensor.

  
   

Highlights

In May 2013, the Biomass mission concept was selected to become the next in the series of satellites developed to further our understanding of Earth.

Released: 21/06/2013

REPLAY EARTH EXPLORER 7 USER CONSULTATION MEETING (PART 1)

Released: 11/03/2013

POLinSAR 2013 Workshop

Released: 22/02/2013