29 results on '"Lavalle, Marco"'
Search Results
2. Global seasonal Sentinel-1 interferometric coherence and backscatter data set
- Author
-
Kellndorfer, Josef, Cartus, Oliver, Lavalle, Marco, Magnard, Christophe, Milillo, Pietro, Oveisgharan, Shadi, Osmanoglu, Batu, Rosen, Paul A., and Wegmüller, Urs
- Published
- 2022
- Full Text
- View/download PDF
3. The NASA AfriSAR campaign: Airborne SAR and lidar measurements of tropical forest structure and biomass in support of current and future space missions
- Author
-
Fatoyinbo, Temilola, Armston, John, Simard, Marc, Saatchi, Sassan, Denbina, Michael, Lavalle, Marco, Hofton, Michelle, Tang, Hao, Marselis, Suzanne, Pinto, Naiara, Hancock, Steven, Hawkins, Brian, Duncanson, Laura, Blair, Bryan, Hansen, Christy, Lou, Yunling, Dubayah, Ralph, Hensley, Scott, Silva, Carlos, Poulsen, John R., Labrière, Nicolas, Barbier, Nicolas, Jeffery, Kathryn, Kenfack, David, Herve, Memiaghe, Bissiengou, Pulchérie, Alonso, Alfonso, Moussavou, Ghislain, White, Lee T.J., Lewis, Simon, and Hibbard, Kathleen
- Published
- 2021
- Full Text
- View/download PDF
4. Tropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning
- Author
-
Pourshamsi, Maryam, Xia, Junshi, Yokoya, Naoto, Garcia, Mariano, Lavalle, Marco, Pottier, Eric, and Balzter, Heiko
- Published
- 2021
- Full Text
- View/download PDF
5. Spaceborne tomography of multi-species Indian tropical forests
- Author
-
Khati, Unmesh, Lavalle, Marco, and Singh, Gulab
- Published
- 2019
- Full Text
- View/download PDF
6. Total ionizing dose effects on 4 Mbit Phase Change Memory arrays
- Author
-
Gasperin, Alberto, Wrachien, Nicola, Paccagnella, Alessandro, Ottogalli, Federica, Corda, Ugo, Fuochi, Piergiorgio, and Lavalle, Marco
- Subjects
Electrons -- Analysis ,Metal oxide semiconductor field effect transistors -- Analysis ,Business ,Electronics ,Electronics and electrical industries - Abstract
We investigate Total Ionizing Dose effects on 4 Mbit Phase Change Memories (PCM) arrays. We demonstrate a high robustness of PCM against ionizing radiation. We irradiated PCM with 8-MeV electrons. Only small variations are measured in the cell distributions after irradiation. The primary cause of these variations is the degradation of the Bit-Line and the Word-Line selector MOSFETs. Finally, radiation does not compromise the functionality of the SET and the RESET operations. Index Terms--Chalcogenide materials, GST, non-volatile memories, phase change memory, radiation effects, total ionizing dose.
- Published
- 2008
7. Pulse radiolysis and theoretical investigation on the initial mechanism of the e-beam polymerization of epoxy resins. The results obtained on (phenoxymethyl)oxirane
- Author
-
Emmi, Salvatore S., Corda, Ugo, Fuochi, Piergiorgio, Lavalle, Marco, Alessi, Sabina, and Spadaro, Giuseppe
- Published
- 2007
- Full Text
- View/download PDF
8. Behaviour of non-conducting plastics under e-beam irradiation
- Author
-
Mehta, Kishor, Fuochi, Piergiorgio, Lavalle, Marco, and Kovács, András
- Published
- 2002
- Full Text
- View/download PDF
9. Digital Terrain, Surface, and Canopy Height Models From InSAR Backscatter-Height Histograms.
- Author
-
Shiroma, Gustavo H. X. and Lavalle, Marco
- Subjects
- *
SYNTHETIC aperture radar , *HISTOGRAMS , *DIGITAL maps , *ALTITUDES - Abstract
This article demonstrates how 3-D vegetation structure can be approximated by interferometric synthetic aperture radar (InSAR) backscatter-height histograms. Single-look backscatter measurements are plotted against the InSAR phase height and are aggregated spatially over a forest patch to form a 3-D histogram, referred to as InSAR backscatter-height histogram or simply InSAR histogram. InSAR histograms resemble LiDAR waveforms, suggesting that existing algorithms used to retrieve canopy height and ground topography from radar tomograms or LiDAR waveforms can be applied to InSAR histograms. Three algorithms are evaluated to generate maps of digital terrain, surface, and canopy height models: Gaussian decomposition, quantile, and backscatter threshold. Full-polarimetric L-band uninhabited aerial vehicle synthetic aperture radar (UAVSAR) data collected over the Gabonese Lopé National Park during the 2016 AfriSAR campaign are used to illustrate and compare the performance of the algorithms for the HH, HV, VV, HH+VV, and HH−VV polarimetric channels. Results show that radar-derived maps using the InSAR histograms differ by 4 m (top-canopy), 5 m (terrain), and 6 m (forest height) in terms of average root-mean-square errors (RMSEs) from standard maps derived from full-waveform laser, vegetation, and ice sensor (LVIS) LiDAR measurements. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
10. Dose distribution in electron-irradiated PMMA: effect of dose and geometry
- Author
-
Mehta, Kishor, Fuochi, Pier-Giorgio, Kovács, András, Lavalle, Marco, and Hargittai, Peter
- Published
- 1999
- Full Text
- View/download PDF
11. A Joint ESA-NASA Multi-mission Algorithm and Analysis Platform (MAAP) for Biomass, NISAR, and GEDI.
- Author
-
Albinet, Clément, Whitehurst, Amanda S., Jewell, Laura Alisic, Bugbee, Kaylin, Laur, Henri, Murphy, Kevin J., Frommknecht, Bjorn, Scipal, Klaus, Costa, Gabriella, Jai, Benhan, Ramachandran, Rahul, Lavalle, Marco, and Duncanson, Laura
- Abstract
In order to help scientists in the above ground biomass community and to support the science behind the upcoming BIOMASS, NISAR, and GEDI satellite missions, ESA and NASA are collaborating on the Multi-Mission Algorithm and Analysis Platform (MAAP). The MAAP is a jointly developed and implemented platform that will include not only data (satellite, airborne, in situ data, and products), but also computing capabilities and sets of tools and algorithms developed to support this specific field of research. To best ensure that users are able to collaborate across the platform and to access needed resources, the MAAP requires all data, algorithms, and software to conform to open access and open source policies. In addition to aiding researchers, the MAAP exercise is establishing a collaboration framework between ESA and NASA that focuses on sharing data, science algorithms, and computable resources in order to foster and accelerate scientific research. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
12. Uncertainties in Forest Canopy Height Estimation From Polarimetric Interferometric SAR Data.
- Author
-
Riel, Bryan, Denbina, Michael, and Lavalle, Marco
- Abstract
The random volume over ground (RVoG) model has been widely applied to estimate forest tree height from polarimetric synthetic aperture radar (SAR) interferometry (PolInSAR) data for the past two decades. Successful application of the RVoG model requires certain assumptions to be valid for the imaged forest and the acquisition scenarios in order to avoid large errors in height estimates. Quantification of errors and uncertainties of RVoG-estimated heights have typically been limited to comparison against external validation data, such as lidar or field measurements. In this paper, we present a straightforward approach to simultaneously estimate height and height uncertainty from PolInSAR data using a Bayesian framework that accounts for errors in the data, as well as errors due to incorrect RVoG modeling assumptions, such as those caused by temporal decorrelation effects and errors in ground phase estimation. We apply our method to synthetic data to study how forest height uncertainty depends on modeling assumptions and PolInSAR acquisition parameters. We also compare our estimated Bayesian uncertainties to PolInSAR-derived and lidar-derived height RMS deviations observed over Gabonese tropical forests during the joint NASA-ESA 2016 AfriSAR campaign. Our results show good correspondence between uncertainties and deviations, as well as a strong correlation between uncertainty and estimated tree height. Furthermore, we demonstrate that we can associate specific areas of high uncertainty to confounding effects, such as temporal decorrelation and noncanopy related scattering. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
13. A Machine-Learning Approach to PolInSAR and LiDAR Data Fusion for Improved Tropical Forest Canopy Height Estimation Using NASA AfriSAR Campaign Data.
- Author
-
Pourshamsi, Maryam, Garcia, Mariano, Lavalle, Marco, and Balzter, Heiko
- Abstract
This paper investigates the benefits of integrating multibaseline polarimetric interferometric SAR (PolInSAR) data with LiDAR measurements using a machine-learning approach in order to obtain improved forest canopy height estimates. Multiple interferometric baselines are required to ensure consistent height retrieval performance across a broad range of tree heights. Previous studies have proposed multibaseline merging strategies using metrics extracted from PolInSAR measurements. Here, we introduce the multibaseline merging using a support vector machine trained by sparse LiDAR samples. The novelty of this method lies in the new way of combining the two datasets. Its advantage is that it does not require a complete LiDAR coverage, but only sparse LiDAR samples distributed over the PolInSAR image. LiDAR samples are not used to obtain the best height among a set of height stacks, but rather to train the retrieval algorithm in selecting the best height using the variables derived through PolInSAR processing. This enables more accurate height estimation for a wider scene covered by the SAR with only partial LiDAR coverage. We test our approach on NASA AfriSAR data acquired over tropical forests by the L-band UAVSAR and the LVIS LiDAR instruments. The estimated height from this approach has a higher accuracy (r2 = 0.81, RMSE = 7.1 m) than previously introduced multibaseline merging approach (r2 = 0.67, RMSE = 9.2 m). This method is beneficial to future spaceborne missions, such as GEDI and BIOMASS, which will provide a wealth of near-contemporaneous LiDAR samples and PolInSAR measurements for mapping forest structure at global scale. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
14. Damage-Mapping Algorithm Based on Coherence Model Using Multitemporal Polarimetric - Interferometric SAR Data.
- Author
-
Jungkyo Jung, Duk-jin Kim, Sang-Ho Yun, and Lavalle, Marco
- Subjects
ALGORITHMS ,COHESION (Linguistics) ,CARTOGRAPHY ,INTERFEROMETRY ,DIFFRACTION patterns ,SYNTHETIC aperture radar - Abstract
This paper presents a new damage-mapping algorithm based on coherence images estimated from multitemporal polarimetric-interferometric synthetic aperture radar (SAR) data. The interferometric coherence has been restricted in the conventional damage-mapping approaches because the decorrelation sources are too complicated to interpret accurately and temporal decorrelation effects caused by slowly occurring natural changes and disaster events are often coupled together. To overcome these limitations, we formulate a coherence model that accounts for temporal decorrelation in two simplified layers, ground and volume layers, for long-temporal repeat-pass scenarios with zero spatial baseline. The model parameters include: 1) ground-to-volume ratio, a factor to determine the relative scattering contribution of ground and volume layers; 2) temporally correlated change, which captures the exponentially decaying behavior of coherence with time; and 3) temporally uncorrelated change, which is associated with random temporal changes. We estimate the model parameters in three steps: coherence optimization, interferometric pair-invariant parameter estimation, and interferometric pair-variant parameter estimation. To isolate the effects of disaster events from background natural changes, we calculate the probability density functions of historical change pixel by pixel and produce a probability map of damage. We tested the algorithm with uninhabited aerial vehicle data acquired from 2009 to 2015 for mapping the area damaged by the 2015 Lake Fire in California. Based on performance evaluation using receiver operating characteristic curves for optimized coherences and averaged probability maps, the proposed method reduced the false alarm from 0.25 to 0.07 when the probability of detection was 0.85 compared to coherence products alone. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
15. UAVSAR PolInSAR and tomographic experiments in Germany.
- Author
-
Hensley, Scott, Lou, Yunling, Michel, Thierry, Muellerschoen, Ron, Hawkins, Brian, Lavalle, Marco, Pinto, Naiara, Reigber, Andreas, and Pardini, Matteo
- Published
- 2016
- Full Text
- View/download PDF
16. Plant: Polarimetric-interferometric Lab and Analysis Tools for ecosystem and land-cover science and applications.
- Author
-
Lavalle, Marco, Shiroma, Gustavo H. X., Agram, Piyush, Gurrola, Eric, Sacco, Gian Franco, and Rosen, Paul
- Published
- 2016
- Full Text
- View/download PDF
17. Coherent change detection using temporal decorrelation model for volcanic ash detection.
- Author
-
Jung, Jungkyo, Kim, Duk-jin, Lavalle, Marco, and Yun, Sang-ho
- Published
- 2016
- Full Text
- View/download PDF
18. Coherent Change Detection Using InSAR Temporal Decorrelation Model: A Case Study for Volcanic Ash Detection.
- Author
-
Jung, Jungkyo, Kim, Duk-jin, Lavalle, Marco, and Yun, Sang-Ho
- Subjects
SYNTHETIC aperture radar ,COHERENCE (Optics) ,VOLCANIC eruptions ,INTERFEROMETRY ,VOLCANIC ash, tuff, etc. ,PIXELS - Abstract
Detection of changes caused by major events—such as earthquakes, volcanic eruptions, and floods—from interferometric synthetic aperture radar (SAR) data is challenging because of the coupled effects with temporal decorrelation caused by natural phenomena, including rain, snow, wind, and seasonal changes. The coupled effect of major events and natural phenomena sometimes leads to misinterpretation of interferometric coherence maps and often degrades the performance of change detection algorithms. To differentiate decorrelation sources caused by natural changes from those caused by an event of interest, we formulated a temporal decorrelation model that accounts for the random motion of canopy elements, temporally correlated dielectric changes, and temporally uncorrelated dielectric changes of canopy and ground. The model parameters are extracted from the interferometric pairs associated with natural changes in canopy and ground using the proposed temporal decorrelation model. In addition, the cumulative distribution functions of the temporally uncorrelated model parameters, which are associated with natural changes in canopy and ground, are estimated from interferometric pairs acquired before the event. Model parameters are also extracted from interferometric SAR data acquired across the event and compared with the cumulative probabilities of natural changes in order to calculate the probability of a major event. Subsequently, pixels with cumulative probabilities greater than 75% are marked as changed due to the event. A case study for detecting volcanic ash during the eruption of the Shinmoedake volcano in January 2011 was carried out using L-band Advanced Land Observation Satellite PALSAR data. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
19. L-band and P-band studies of vegetation at JPL.
- Author
-
Hensley, Scott, Van Zyl, Jakob, Lavalle, Marco, Neumann, Maxim, Michel, Thierry, Muellerschoen, Ron, Pinto, Naiara, Simard, Marc, and Moghaddam, Mahta
- Published
- 2015
- Full Text
- View/download PDF
20. Extraction of Structural and Dynamic Properties of Forests From Polarimetric-Interferometric SAR Data Affected by Temporal Decorrelation.
- Author
-
Lavalle, Marco and Hensley, Scott
- Subjects
- *
POLARIMETRIC remote sensing , *ARTIFICIAL satellites , *REMOTE sensing , *VOLUMETRIC analysis , *SYNTHETIC aperture radar , *RADAR in earth sciences - Abstract
This paper addresses the important yet unresolved problem of estimating forest properties from polarimetric-interferometric radar images affected by temporal decorrelation. We approach the problem by formulating a physical model of the polarimetric-interferometric coherence that incorporates both volumetric and temporal decorrelation effects. The model is termed random-motion-over-ground (RMoG) model, as it combines the random-volume-over-ground (RVoG) model with a Gaussian-statistic motion model of the canopy elements. Key features of the RMoG model are: 1) temporal decorrelation depends on the vertical structure of forests; 2) volumetric and temporal coherences are not separable as simple multiplicative factors; and 3) temporal decorrelation is complex-valued and changes with wave polarization. This third feature is particularly important as it allows compensating for unknown levels of temporal decorrelation using multiple polarimetric channels. To estimate model parameters such as tree height and canopy motion, we propose an algorithm that minimizes the least square distance between model predictions and complex coherence observations. The algorithm was applied to L-band NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar data acquired over the Harvard Forest (Massachussetts, USA). We found that the RMS difference at stand level between estimated RMoG-model tree height and NASA's lidar Laser Vegetation and Ice Sensor tree height was within 12% of the lidar-derived height, which improved significantly the RMS difference of 37% obtained using the RVoG model and ignoring temporal decorrelation. This result contributes to our ability of estimating forest biomass using in-orbit and forthcoming polarimetric-interferometric radar missions. [ABSTRACT FROM PUBLISHER]
- Published
- 2015
- Full Text
- View/download PDF
21. Three-Baseline InSAR Estimation of Forest Height.
- Author
-
Lavalle, Marco and Khun, Kosal
- Abstract
In this letter we propose a three-baseline approach to the extraction of forest tree height from synthetic aperture radar data. Three polarimetric–interferometric pairs are used to constrain a physical model that relates forest parameters to multiple repeat-pass coherence observations. The observations may be performed by a dual, compact or full polarimetric radar, and may be affected by distinct levels of temporal decorrelation. Here, we present the theoretical framework based on the random-motion-over-ground model, and describe an algorithm to extract tree height from the data. The performance of the algorithm is illustrated with L-band airborne data collected by the German Aerospace Center in the frame of the BIOSAR2008 campaign. The proposed method provides height estimates in good agreement with lidar measurements and can be applied to data to be collected by forthcoming polarimetric–interferometric spaceborne missions. [ABSTRACT FROM PUBLISHER]
- Published
- 2014
- Full Text
- View/download PDF
22. Some first polarimetric-interferometric multi-baseline and tomographic results at Harvard forest using UAVSAR.
- Author
-
Hensley, Scott, Michel, Thierry, Nuemann, Maxim, Lavalle, Marco, Muellerschoen, Ron, Chapman, Bruce, Jones, Cathleen, Ahmed, Razi, Lombardini, Fabrizio, and Siqueira, Paul
- Abstract
Quantification of the various components of the carbon cycle budget is key to improved climate modeling and projecting anthropogenic affects on climate in the future. Estimating the levels of above ground biomass contained in the world's forests that comprise 86% of the planet's above ground carbon and monitoring the rate of change to these standing stocks resulting from both natural and anthropogenic disturbances is necessary to solving the carbon cycle sink. Remote sensing is the only viable means of obtaining a global inventory of forest biomass at the hectare scale. The most promising means of obtaining remotely sensed biomass measurements involve using either lidar or radar measurements of vegetation structure coupled with allometric relationships. We have collected repeat-pass L-band fully polarimetric radar data at multiple spatial and temporal baselines to investigate the tree height and structure measurements using polarimetric interferometry techniques. This paper will discuss this experiment and comparison with lidar data. [ABSTRACT FROM PUBLISHER]
- Published
- 2012
- Full Text
- View/download PDF
23. Demonstration of repeat-pass POLINSAR using UAVSAR: The RMOG model.
- Author
-
Lavalle, Marco and Hensley, Scott
- Abstract
In this paper we show our first POLINSAR results using the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) developed by the Jet Propulsion Laboratory (JPL). UAVSAR is a L-band repeat-pass polarimetric and interferometric system designed for measuring vegetation structure and monitoring crustal deformations. In order to extract canopy height from POLINSAR data and account for temporal decorrelation, we formulate a physical model of the temporal-volumetric coherence, random motion over ground (RMOG) model. Canopy height extracted from single-baseline UAVSAR data using the RMOG model is shown to be in agreement with canopy height measured by the Land, Vegetation, and Ice Sensor (LVIS) lidar. [ABSTRACT FROM PUBLISHER]
- Published
- 2012
- Full Text
- View/download PDF
24. Use of airborne instruments for tropical forest monitoring applications.
- Author
-
Lavalle, Marco, Hensley, Scott, and Williams, Mark L.
- Abstract
The world forest systems are dynamic and play an integral role in the Earth's carbon budget. Monitoring of these valuable assets is being mandated by the international community. The requirement of global forest inventories suggests that a global measurement methodology should be adopted and that a verification and validation strategy should be accepted. The wide areas and varied forest types that need monitoring suggest the use of airborne remote sensing assets even for verification or cross validation of the varied global forest measurement methodologies. Airborne SAR systems that operate at appropriate frequencies, e.g., L-band or P-band, can provide useful forest information. The simplest forest product to generate would be a forest/non-forest classification map that can be robustly generated using radar polarimetric or interferometric systems. More elaborated products like forest classification or biomass maps require more sophisticated mapping algorithms and potentially ancillary data sets in order to obtain robust results. In this paper we examine the potential for airborne mapping system to obtain these type of forest mapping products and the limitations and accuracy of such systems. [ABSTRACT FROM PUBLISHER]
- Published
- 2012
- Full Text
- View/download PDF
25. Tomographic Performance of Multi-Static Radar Formations: Theory and Simulations.
- Author
-
Seker, Ilgin, Lavalle, Marco, and Tebaldini, Stefano
- Subjects
- *
RADAR , *THREE-dimensional imaging , *SURFACE of the earth , *VEGETATION mapping , *SURFACE topography , *BISTATIC radar - Abstract
3D imaging of Earth's surface layers (such as canopy, sub-surface, or ice) requires not just the penetration of radar signal into the medium, but also the ability to discriminate multiple scatterers within a slant-range and azimuth resolution cell. The latter requires having multiple radar channels distributed in across-track direction. Here, we describe the theory of multi-static radar tomography with emphasis on resolution, SNR, sidelobes, and nearest ambiguity location vs. platform distribution, observation geometry, and different multi-static modes. Signal-based 1D and 2D simulations are developed and results for various observation geometries, target distributions, acquisition modes, and radar parameters are shown and compared with the theory. Pros and cons of multi-static modes are compared and discussed. Results for various platform formations are shown, revealing that unequal spacing is useful to suppress ambiguities at the cost of increased multiplicative noise. In particular, we demonstrate that the multiple-input multiple-output (MIMO) mode, in combination with nonlinear spacing, outperforms the other modes in terms of ambiguity, sidelobe levels, and noise suppression. These findings are key to guiding the design of tomographic SAR formations for accurate surface topography and vegetation mapping. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
26. Assessment of Forest Biomass Estimation from Dry and Wet SAR Acquisitions Collected during the 2019 UAVSAR AM-PM Campaign in Southeastern United States.
- Author
-
Khati, Unmesh, Lavalle, Marco, Shiroma, Gustavo H. X., Meyer, Victoria, and Chapman, Bruce
- Subjects
- *
SYNTHETIC aperture radar , *POLYWATER , *TEMPERATE forests , *SOIL moisture , *BIOMASS , *BIOMASS estimation - Abstract
Forest above-ground biomass (AGB) estimation from SAR backscatter is affected by varying imaging and environmental conditions. This paper quantifies and compares the performance of forest biomass estimation from L-band SAR backscatter measured selectively under dry and wet conditions during the 2019 AM-PM NASA airborne campaign. Seven Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) images acquired between June and October 2019 over a temperate deciduous forest in Southeastern United States with varying moisture and precipitation conditions are examined in conjunction with LIDAR and field measurements. Biomass is estimated by fitting a 3-parameter modified Water Cloud Model (WCM) to radiometric terrain corrected SAR backscatter. Our experiment is designed to quantify the biomass estimation errors when biomass models are calibrated and validated on varying acquisition conditions (dry or wet). Multi-temporal estimation strategies are also evaluated and compared with single-acquisition estimation approaches. As an outcome, the experiment shows that the WCM model calibrated and validated on single acquisitions adapts to different soil moisture conditions with RMSD up to 18.7 Mg/ha. The AGB estimation performance, however, decreases with RMSD upwards of 30 Mg/ha when the model is cross-validated on moisture and precipitation conditions different than the calibration conditions. Results confirm that calibrating the model over the multi-temporal data using averaged backscatter or weighted combinations of individual AGB estimates, improves the biomass estimation accuracy up to about 20% at L-band. This study helps design biomass cal/val procedures and biomass estimation algorithms for dense time-series to be collected by low-frequency radar missions such as NASA-ISRO SAR (NISAR) and BIOMASS. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
27. Monitoring Tropical Forest Structure Using SAR Tomography at L- and P-Band.
- Author
-
El Moussawi, Ibrahim, Ho Tong Minh, Dinh, Baghdadi, Nicolas, Abdallah, Chadi, Jomaah, Jalal, Strauss, Olivier, Lavalle, Marco, and Ngo, Yen-Nhi
- Subjects
FOREST monitoring ,TROPICAL forests ,STANDARD deviations ,CONTRAST-enhanced ultrasound ,FOREST management ,STRUCTURE-activity relationships ,AIRBORNE-based remote sensing ,TOMOGRAPHY - Abstract
Our study aims to provide a comparison of the P- and L-band TomoSAR profiles, Land Vegetation and Ice Sensor (LVIS), and discrete return LiDAR to assess the ability for TomoSAR to monitor and estimate the tropical forest structure parameters for enhanced forest management and to support biomass missions. The comparison relies on the unique UAVSAR Jet propulsion Laboratory (JPL)/NASA L-band data, P-band data acquired by ONERA airborne system (SETHI), Small Footprint LiDAR (SFL), and NASA Land, Vegetation and Ice Sensor (LVIS) LiDAR datasets acquired in 2015 and 2016 in the frame of the AfriSAR campaign. Prior to multi-baseline data processing, a phase residual correction methodology based on phase calibration via phase center double localization has been implemented to improve the phase measurements and compensate for the phase perturbations, and disturbances originated from uncertainties in allocating flight trajectories. First, the vertical structure was estimated from L- and P-band corrected Tomography SAR data measurements, then compared with the canopy height model from SFL data. After that, the SAR and LiDAR three-dimensional (3D) datasets are compared and discussed at a qualitative basis at the region of interest. The L- and P-band's performance for canopy penetration was assessed to determine the underlying ground locations. Additionally, the 3D records for each configuration were compared with their ability to derive forest vertical structure. Finally, the vertical structure extracted from the 3D radar reflectivity from L- and P-band are compared with SFL data, resulting in a root mean square error of 3.02 m and 3.68 m, where the coefficient of determination shows a value of 0.95 and 0.93 for P- and L-band, respectively. The results demonstrate that TomoSAR holds promise for a scientific basis in forest management activities. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
28. L-Band UAVSAR Tomographic Imaging in Dense Forests: Gabon Forests.
- Author
-
El Moussawi, Ibrahim, Ho Tong Minh, Dinh, Baghdadi, Nicolas, Abdallah, Chadi, Jomaah, Jalal, Strauss, Olivier, and Lavalle, Marco
- Subjects
TOMOGRAPHY ,SYNTHETIC aperture radar ,TROPICAL forests ,THREE-dimensional imaging ,FOREST canopies - Abstract
Developing and enhancing strategies to characterize actual forests structure is a timely challenge, particularly for tropical forests. P-band synthetic aperture radar (SAR) tomography (TomoSAR) has previously been demonstrated as a powerful tool for characterizing the 3-D vertical structure of tropical forests, and its capability and potential to retrieve tropical forest structure has been discussed and assessed. On the other hand, the abilities of L-band TomoSAR are still in the early stages of development. Here, we aim to provide a better understanding of L-band TomoSAR capabilities for retrieving the 3-D structure of tropical forests and estimating the top height in dense forests. We carried out tomographic analysis using L-band UAVSAR data from the AfriSAR campaign conducted over Gabon Lopé Park in February 2016. First, it was found that L-band TomoSAR was able to penetrate into and through the canopy down to the ground, and thus the canopy and ground layers were detected correctly. The resulting TomoSAR vertical profiles were validated with a digital terrain model and canopy height model extracted from small-footprint Lidar (SFL) data. Second, there was a strong correlation between the L-band Capon beam forming profile in HH and HV polarizations with Land Vegetation Ice Sensor (LVIS) Level 1B waveform Lidar over different kinds of forest in Gabon Lopé National Park. Finally, forest top height from the L-band data was estimated and validated with SFL data, resulting in a root mean square error of 3 m and coefficient of determination of 0.92. The results demonstrate that L-band TomoSAR is capable of characterizing 3-D structure of tropical forests. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
29. Depth dose curve and surface dose measurement with a μm thin dosimetric layer.
- Author
-
Schuster, Christiane, Kuntz, Florent, Cloetta, Dominique, Zeller, Marcel, Katzmann, Julia, Strasser, Alain, Härtling, Thomas, and Lavalle, Marco
- Subjects
- *
RADIATION dosimetry , *ELECTRON beams , *MONTE Carlo method , *BATHYMETRY , *POLYMER films , *CURVES , *OPTICAL films - Abstract
In a former work inorganic phosphor particles NaYF 4 :Yb3+, Er3+ were found to exhibit a radiation dose dependency of their luminescence decay time upon near-infrared excitation. This material is now presented in the form of an ultra-thin dosimeter to measure depth dose curves. They were derived by electron beam irradiation of 1.6 μm thin dosimeters through a stepped stack of absorber polymer films followed by optical decay time evaluation. The suitability of the phosphor dosimeters for depth curve measurement is proven by good agreement in normalized dose results with film dosimeter (Risø B3 strips) after medium-energy electron-beam irradiation. But the approach qualifies especially for use at low-energies, where original measurement results from as close as 3–4 μm (water equivalent) from the surface are obtained for 80, 140 and 200 keV e-beam irradiations. They align well with results from Monte Carlo simulations. Thus, an approach is proposed for discussion which may allow the experimental evaluation of the first μm of depth dose curves after low-energy electron beam irradiation. • Dose dependency of phosphor luminescence decay time. • Fabrication of 1.6 μm ultra-thin dosimeter film. • Depth dose profiles through stack of absorbing polymer films for low-energy e-beam. • Unprecedented proximity to surface with first data point at 3.4 μm depth. • Good agreement between measurement and Monte Carlo simulations. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.