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

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

Quantifying Temporal Decorrelation over Boreal Forest at L- and P-band

Temporal decorrelation is probably the most critical factor towards a successful implementation of Pol-InSAR parameter inversion techniques in terms of repeat-pass InSAR scenarios. In this paper the effect and impact of temporal decorrelation at L- and P-band is quantified. For this, data acquired by DLR’s E-SAR system in the frame of the BioSAR campaign (initiated and sponsored by the European Space Agency (ESA)) over boreal forest with variable temporal baseline in 2007 in Sweden are analyzed. For validation lidar data and ground measurements data are used

Polarimetric SAR Interferometry Evaluation in Mangroves

TanDEM-X (TDX) enables to generate an interferometric coherence without temporal decorrelation effect that is the most critical factor for a successful Pol-InSAR inversion, as have recently been used for forest parameter retrieval. This paper presents mangrove forest height estimation only using single-pass/single-baseline/dual-polarization TDX data by means of new dual-Pol-InSAR inversion technique. To overcome a lack of one polarization in a conventional Pol- InSAR inversion (i.e. an underdetermined problem), the ground phase in the Pol-InSAR model is directly estimated from TDX interferograms assuming flat underlying topography in mangrove forest. The inversion result is validated against lidar measurement data (NASA's G-LiHT data)

Forest Structure Retrieval From EcoSAR P-Band Single-Pass Interferometry

EcoSAR is a single-pass (dual antenna) digital beamforming, P-band radar system that is designed for remote sensing of dense forest structure. Forest structure retrievals require the measurement related to the vertical dimension, for which several techniques have been developed over the years. These techniques use polarimetric and interferometric aspects of the SAR data, which can be collected using EcoSAR. In this paper we describe EcoSAR system in light of its interferometric capabilities and investigate forest structure retrieval techniques

Estimating mangrove aboveground biomass from airborne LiDAR data: a case study from the Zambezi River delta

Mangroves are ecologically and economically important forested wetlands with the highest carbon (C) density of all terrestrial ecosystems. Because of their exceptionally large C stocks and importance as a coastal buffer, their protection and restoration has been proposed as effective mitigation strategy for climate change. The inclusion of mangroves in mitigation strategies requires the quantification of C stocks (both above and belowground) and changes to accurately calculate emissions and sequestration. A growing number of countries are becoming interested in using mitigation initiatives, such as REDD+, in these unique coastal forests. However, it is not yet clear how methods to measure C traditionally used for other ecosystems can be modified to estimate biomass in mangroves with the precision and accuracy needed for these initiatives. Airborne lidar (ALS) data has often been proposed as the most accurate way for larger-scale assessments but, the application of ALS for coastal wetlands is scarce, primarily due to a lack of contemporaneous ALS and field measurements. Here, we evaluated the variability in field and lidar-based estimates of aboveground biomass (AGB) through the combination of different local and regional allometric models and standardized height metrics that are comparable across spatial resolutions and sensor types. The end result being a simplified approach for accurately estimating mangrove AGB at large-scales and determining the uncertainty by combining multiple allometric models. We then quantified wall-to-wall aboveground biomass stocks of a tall mangrove forest in the Zambezi Delta, Mozambique. Our results indicate that the Lidar H100 height metric correlates well with AGB estimates, with R2 between 0.80 and 0.88 and RMSE of 33% or less. When comparing lidar H100 AGB derived from three allometric models, mean AGB values range from 192 Mg. ha-1 up to 252 Mg. ha-1. We suggest the best model to predict AGB was based on the East Africa specific allometry and a power based regression that used Lidar H100 as the height input with a R2 of 0.85 and a RMSE of 122 Mg.ha-1 or 33%. The total AGB of the lidar inventoried mangrove area (6654 ha) was 1,350,902 Mg with a mean AGB 203 Mg. ha-1. Because the allometry suggested here was developed using standardized height metrics, it is recommended that the models can generate AGB estimates using other remote sensing instruments that are more readily accessible over other mangrove ecosystems on a large scale, and as part of future carbon monitoring efforts in mangroves

Estimating mangrove canopy height and above-ground biomass in the Everglades National Park with airborne LiDAR and TanDEM-X data

Mangrove forests are important natural ecosystems due to their ability to capture and store large amounts of carbon. Forest structural parameters, such as canopy height and above-ground biomass (AGB), provide a good measure for monitoring temporal changes in carbon content. The protected coastal mangrove forest of the Everglades National Park (ENP) provides an ideal location for studying these processes, as harmful human activities are minimal. We estimated mangrove canopy height and AGB in the ENP using Airborne LiDAR/Laser (ALS) and TanDEM-X (TDX) datasets acquired between 2011 and 2013. Analysis of both datasets revealed that mangrove canopy height can reach up to ~25 m and AGB can reach up to ~250 Mg·ha-1. In general, mangroves ranging from 9 m to 12 m in stature dominate the forest canopy. The comparison of ALS and TDX canopy height observations yielded an R2 = 0.85 and Root Mean Square Error (RMSE) = 1.96 m. Compared to a previous study based on data acquired during 2000-2004, our analysis shows an increase in mangrove stature and AGB, suggesting that ENP mangrove forests are continuing to accumulate biomass. Our results suggest that ENP mangrove forests have managed to recover from natural disturbances, such as HurricaneWilma

A Simple and Facile Glucose Biosensor Based on Prussian Blue Modified Graphite String

This work describes the string sensor for the simple and sensitive detection of glucose which is based on Prussian blue (PB) modified graphite utilizing dipping. First, PB modified graphite (PB-G) strings are characterized by physical and electrochemical techniques to optimize the PB-G layer thickness. Then, glucose oxidase (GOx) is immobilized on PB-G string electrode with biocompatible chitosan overlayer (Chi/GOx/PB-G). The Chi/GOx/PB-G string electrode exhibits a sensitivity of 641.3 μA·mM−1·cm−2 to glucose with a linear range of 0.03 to 1.0 mM (R2=0.9957) and a rapid response time (<3 s). Moreover, the Chi/GOx/PB-G string electrodes are less sensitive to common interference materials such as ascorbic acid, uric acid, galactose, and acetaminophen than to glucose. The Chi/GOx/PB-G string electrodes also show excellent reproducibility (<5% RSD). Therefore, our Chi/GOx/PB-G string electrodes can be simple, robust, and reliable tools for glucose sensing which can avoid complicated and difficult multistep fabrication processes. In addition, we expect that they have many potential applications in fields ranging from health care to food analysis, in particular where single use is favorable

Clinical Efficacy of Primary Tumor Volume Measurements: Comparison of Different Primary Sites

ObjectivesThe purpose of study was to determine the clinical efficacy of primary tumor volume measurements of different primary sites in the oropharynx compared to the oral cavity.MethodsA retrospective analysis of 85 patients with oral cavity or oropharynx cancer. The tumor area was manually outlined from axial magnetic resonance (MR) series. The software calculated the tumor volumes, automatically. The values of the primary tumor volumes were then subdivided into separate groups (≤3,500 mm3, >3,500 mm3).ResultsThe prognostic indicators were the cT and cN (oral cavity); age, primary site, cT, cN, and primary tumor volume (oropharynx) on the univariate analysis. There was no significant prognostic factor for oral cavity cancer on the multivariate analysis. Primary site, cN, and primary tumor volume were independent prognostic indicators for oropharynx cancer by multivariate analysis.ConclusionPrimary tumor volume measurement is a reliable way to stratify outcome, and make up for the weak points in the American Joint Committee on Cancer staging system with oropharynx cancer

Development of NASA's Next Generation L-Band Digital Beamforming Synthetic Aperture Radar (DBSAR-2)

NASA's Next generation Digital Beamforming SAR (DBSAR-2) is a state-of-the-art airborne L-band radar developed at the NASA Goddard Space Flight Center (GSFC). The instrument builds upon the advanced architectures in NASA's DBSAR-1 and EcoSAR instruments. The new instrument employs a 16-channel radar architecture characterized by multi-mode operation, software defined waveform generation, digital beamforming, and configurable radar parameters. The instrument has been design to support several disciplines in Earth and Planetary sciences. The instrument was recently completed, and tested and calibrated in a anechoic chamber

Development of a Spirometry \u3cem\u3eT\u3c/em\u3e-score in the General Population

Background and objective: Spirometry values may be expressed as T-scores in standard deviation units relative to a reference in a young, normal population as an analogy to the T-score for bone mineral density. This study was performed to develop the spirometry T-score. Methods: T-scores were calculated from lambda-mu-sigma-derived Z-scores using a young, normal age reference. Three outcomes of all-cause death, respiratory death, and COPD death were evaluated in 9,101 US subjects followed for 10 years; an outcome of COPD-related health care utilization (COPD utilization) was evaluated in 1,894 Korean subjects followed for 4 years. Results: The probability of all-cause death appeared to remain nearly zero until -1 of forced expiratory volume in 1 second (FEV1) T-score but increased steeply where FEV1 T-score reached below -2.5. Survival curves for all-cause death, respiratory death, COPD death, and COPD utilization differed significantly among the groups when stratified by FEV1 T-score (P \u3c 0.001). The adjusted hazard ratios of the FEV1 T-score for the four outcomes were 0.54 (95% confidence interval, 0.48–0.60), 0.43 (95% CI: 0.37–0.50), 0.30 (95% CI: 0.24–0.37), and 0.69 (95% CI: 0.59–0.81), respectively, adjusting for covariates (P \u3c 0.001). Conclusion: The spirometry T-score could predict all-cause death, respiratory death, COPD death, and COPD utilization