646 research outputs found

    Extrapolation of Airborne Polarimetric and Interferometric SAR Data for Validation of Bio-Geo-Retrieval Algorithms for Future Spaceborne SAR Missions

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    Spaceborne SAR system concepts and mission design is often based on algorithms developed and the experience gathered from airborne SAR experiments and associated dedicated campaigns. However, airborne SAR systems have better performance parameters than their future space-borne counterparts as their design is not impacted by mass, power, and storage constraints. This paper describes a methodology to extrapolate spaceborne quality SAR image products from long wavelength airborne polarimetric SAR data which were acquired especially for the development and validation of bio/geo-retrieval algorithms in forested regions. For this purpose not only system (sensor) related parameters are altered, but also those relating to the propagation path (ionosphere) and to temporal decorrelation

    Utilization of bistatic TanDEM-X data to derive land cover information

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    Forests have significance as carbon sink in climate change. Therefore, it is of high importance to track land use changes as well as to estimate the state as carbon sink. This is useful for sustainable forest management, land use planning, carbon modelling, and support to implement international initiatives like REDD+ (Reducing Emissions from Deforestation and Degradation). A combination of field measurements and remote sensing seems most suitable to monitor forests. Radar sensors are considered as high potential due to the weather and daytime independence. TanDEM-X is a interferometric SAR (synthetic aperture radar) mission in space and can be used for land use monitoring as well as estimation of biophysical parameters. TanDEM-X is a X-band system resulting in low penetration depth into the forest canopy. Interferometric information can be useful, whereas the low penetration can be considered as an advantage. The interferometric height is assumable as canopy height, which is correlated with forest biomass. Furthermore, the interferometric coherence is mainly governed by volume decorrelation, whereas temporal decorrelation is minimized. This information can be valuable for quantitative estimations and land use monitoring. The interferometric coherence improved results in comparison to land use classifications without coherence of about 10% (75% vs. 85%). Especially the differentiation between forest classes profited from coherence. The coherence correlated with aboveground biomass in a R² of about 0.5 and resulted in a root mean square error (RSME) of 14%. The interferometric height achieved an even higher correlation with the biomass (R²=0.68) resulting in cross-validated RMSE of 7.5%. These results indicated that TanDEM-X can be considered as valuable and consistent data source for forest monitoring. Especially interferometric information seemed suitable for biomass estimation

    A Tower-Based Radar Study of Temporal Coherence of a Boreal Forest at P-, L-, and C-Bands and Linear Cross Polarization

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    Cross-polarized temporal coherence observations of a boreal forest, acquired using a tower-based radar, are presented in this article. Temporal coherence is analyzed with respect to frequency, temporal baseline, time of day of observation, season, meteorological variables, and biophysical variables. During the summer, P- and L-band temporal coherence exhibited diurnal cycles, which appeared to be due to high rates of transpiration and convective winds during the day. During the winter, freeze-thaw cycles and precipitation resulted in decorrelation. At temporal baselines of seconds to hours, a high temporal coherence was observed even at C-band. The best observation times of the day were midnight and dawn. Temporal coherence is the main limitation of accuracy in interferometric and tomographic forest applications. The observations from this experiment will allow for better spaceborne SAR mission designs for forest applications, better temporal decorrelation modeling, and more accurate forest parameter estimation algorithms using interferometric and tomographic SAR data

    Temporal Characteristics of Boreal Forest Radar Measurements

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    Radar observations of forests are sensitive to seasonal changes, meteorological variables and variations in soil and tree water content. These phenomena cause temporal variations in radar measurements, limiting the accuracy of tree height and biomass estimates using radar data. The temporal characteristics of radar measurements of forests, especially boreal forests, are not well understood. To fill this knowledge gap, a tower-based radar experiment was established for studying temporal variations in radar measurements of a boreal forest site in southern Sweden. The work in this thesis involves the design and implementation of the experiment and the analysis of data acquired. The instrument allowed radar signatures from the forest to be monitored over timescales ranging from less than a second to years. A purpose-built, 50 m high tower was equipped with 30 antennas for tomographic imaging at microwave frequencies of P-band (420-450 MHz), L-band (1240-1375 MHz) and C-band (5250-5570 MHz) for multiple polarisation combinations. Parallel measurements using a 20-port vector network analyser resulted in significantly shorter measurement times and better tomographic image quality than previous tower-based radars. A new method was developed for suppressing mutual antenna coupling without affecting the range resolution. Algorithms were developed for compensating for phase errors using an array radar and for correcting for pixel-variant impulse responses in tomographic images. Time series results showed large freeze/thaw backscatter variations due to freezing moisture in trees. P-band canopy backscatter variations of up to 10 dB occurred near instantaneously as the air temperature crossed 0⁰C, with ground backscatter responding over longer timescales. During nonfrozen conditions, the canopy backscatter was very stable with time. Evidence of backscatter variations due to tree water content were observed during hot summer periods only. A high vapour pressure deficit and strong winds increased the rate of transpiration fast enough to reduce the tree water content, which was visible as 0.5-2 dB backscatter drops during the day. Ground backscatter for cross-polarised observations increased during strong winds due to bending tree stems. Significant temporal decorrelation was only seen at P-band during freezing, thawing and strong winds. Suitable conditions for repeat-pass L-band interferometry were only seen during the summer. C-band temporal coherence was high over timescales of seconds and occasionally for several hours for night-time observations during the summer. Decorrelation coinciding with high transpiration rates was observed at L- and C-band, suggesting sensitivity to tree water dynamics.The observations from this experiment are important for understanding, modelling and mitigating temporal variations in radar observables in forest parameter estimation algorithms. The results also are also useful in the design of spaceborne synthetic aperture radar missions with interferometric and tomographic capabilities. The results motivate the implementation of single-pass interferometric synthetic aperture radars for forest applications at P-, L- and C-band

    Temporal Decorrelation Effect in Carbon Stocks Estimation Using Polarimetric Interferometry Synthetic Aperture Radar (PolInSAR) (Case Study: Southeast Sulawesi Tropical Forest)

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    This paper was aimed to analyse the effect of temporal decorrelation in carbon stocks estimation. Estimation of carbon stocks plays important roles particularly to understand the global carbon cycle in the atmosphere regarding with climate change mitigation effort. PolInSAR technique combines the advantages of Polarimetric Synthetic Aperture Radar (PolSAR) and Interferometry Synthetic Aperture Radar (InSAR) technique, which is evidenced to have significant contribution in radar mapping technology in the last few years. In carbon stocks estimation, PolInSAR provides information about vertical vegetation structure to estimate carbon stocks in the forest layers. Two coherence Synthetic Aperture Radar (SAR) images of ALOS PALSAR full-polarimetric with 46 days temporal baseline were used in this research. The study was carried out in Southeast Sulawesi tropical forest. The research method was by comparing three interferometric phase coherence images affected by temporal decorrelation and their impacts on Random Volume over Ground (RvoG) model. This research showed that 46 days temporal baseline has a significant impact to estimate tree heights of the forest cover where the accuracy decrease from R2=0.7525 (standard deviation of tree heights is 2.75 meters) to R2=0.4435 (standard deviation 4.68 meters) and R2=0.3772 (standard deviation 3.15 meters) respectively. However, coherence optimisation can provide the best coherence image to produce a good accuracy of carbon stocks.

    The NASA AfriSAR campaign: Airborne SAR and lidar measurements of tropical forest structure and biomass in support of current and future space missions

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    International audienceIn 2015 and 2016, the AfriSAR campaign was carried out as a collaborative effort among international space and National Park agencies (ESA, NASA, ONERA, DLR, ANPN and AGEOS) in support of the upcoming ESA BIOMASS, NASA-ISRO Synthetic Aperture Radar (NISAR) and NASA Global Ecosystem Dynamics Initiative (GEDI) missions. The NASA contribution to the campaign was conducted in 2016 with the NASA LVIS (Land Vegetation and Ice Sensor) Lidar, the NASA L-band UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar). A central motivation for the AfriSAR deployment was the common AGBD estimation requirement for the three future spaceborne missions, the lack of sufficient airborne and ground calibration data covering the full range of ABGD in tropical forest systems, and the intercomparison and fusion of the technologies. During the campaign, over 7000 km2 of waveform Lidar data from LVIS and 30,000 km2 of UAVSAR data were collected over 10 key sites and transects. In addition, field measurements of forest structure and biomass were collected in sixteen 1-hectare sized plots. The campaign produced gridded Lidar canopy structure products, gridded aboveground biomass and associated uncertainties, Lidar based vegetation canopy cover profile products, Polarimetric Interferometric SAR and Tomographic SAR products and field measurements. Our results showcase the types of data products and scientific results expected from the spaceborne Lidar and SAR missions; we also expect that the AfriSAR campaign data will facilitate further analysis and use of waveform lidar and multiple baseline polarimetric SAR datasets for carbon cycle, biodiversity, water resources and more applications by the greater scientific community

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

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    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 L-Band SAOCOM InSAR coherence and its comparison with C-Band: A case study over managed forests in Argentina

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    The objective of this work is to analyze the behavior of short temporal baseline interferomet ric 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 research was funded by the project INTERACT PID2020-114623RB-C32 funded by the Spanish MCIN /AEI /10.13039 /501100011033.Peer ReviewedPostprint (published version

    4D Characterization of Short- and Long-term Height-varying Decorrelated Forest SAR Backscattering

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    Pol-InSAR and 3D multibaseline SAR Tomography (Tomo-SAR) can extract rich information on complex scenarios with multiple scatterers mapped in the SAR cell, in particular for forest remote sensing. However, forest scenarios are characterized by a temporal decorrelating volume canopy scatterer, and a set of related open problems exists, in particular for Tomo-SAR techniques to be applied to spaceborne monitoring of biomass. Multipass 4D Differential Tomography (Diff-Tomo) is a promising advancement, furnishing space (height)-time signatures of multiple scatterer dynamics in the SAR cell, originally with urban applications. In this paper, to better characterize forest decorrelation phenomena impacting Tomo-SAR/Pol-InSAR, experimental results are presented of the extension of Diff-Tomo methods for analyzing vegetated scenes, to extract jointly geometric and dynamic information of forest layers, at both the long and short time scale. The Diff-Tomo enabled functionality of separation in the height dimension of different temporal coherence levels (“coherence profilingâ€) that are mixed (undiscriminated) in classical total coherence analyses is extensively applied to airborne P-band multipolarimetric data, and results of this investigation are shown. Also, first ground-based radar results are presented of an innovative profiling along the height dimension of the short-term coherence, in particular aiming to characterize the magnitudes of short-term coherence times. Their expected variability along the tree structures is confirmed for the first time
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