Independent Field Measurements Research Articles

Producing annual Australia-wide vegetation height images from GEDI and Landsat data

ABSTRACT Vegetation height, and its spatial and temporal changes, is an important environmental parameter required for understanding natural habitats, estimating carbon stores and monitoring forestry activities. Recent satellite LiDAR altimetry sensors have discontinuous spatial coverage but can be combined with spatially complete remote sensing data to extrapolate to large regions. Earlier studies have focused on producing a single spatially continuous vegetation height product. This research builds on past studies, using Landsat (annual surface reflectance and fractional cover products) and the Global Ecosystem Dynamics Investigation (GEDI) data to generate annual vegetation height layers from 1988 to 2022. GEDI data for 2019 were used to train and validate the model, resulting in a root mean square error (RMSE) of 5.45 m, mean absolute error (MAE) of 3.82 m, and coefficient of determination (R2) of 0.63. This accuracy reduces when the modelled height for 2020, 2021, and 2022 is compared to GEDI data for the same years (RMSE = 6.08–6.29 m, MAE = 4.36–4.73 m, and R2 = 0.48–0.54). Validation with independent field measurements across Australia from 2011 to 2021 shows an RMSE, MAE, and R2 of 8.2 m, 5.2 m, and 0.48, respectively. One source of error is the saturation of the Landsat signal in tall, closed canopy vegetation. While model accuracy is correlated with plot-based vegetation height measurements, results indicate that accuracy reduces for the years outside of the model calibration year (i.e. 2019). When compared to other vegetation height products (also produced using GEDI and spatial remote sensing data) from three independent published studies (one for 2009, one for 2019, and one for 2020), the model developed here tends to estimate 2–4 m taller than the first two studies and around 5 m shorter when compared to the third study. This investigation demonstrates the potential to produce multiyear vegetation height at a continental scale but also highlights the large uncertainty in modelled estimates especially when extrapolating to years other than the model calibration year.

Effect of water table level on metro-induced vibrations received by adjacent historical buildings

One of the main concerns in development of metros in historical cities is adverse effects of train-induced vibrations on Cultural and Historical Structures (CHS). In this regard, several approaches have been developed in the literature to predict the level of railway-induced vibration received by CHSs. One of the main limitations of the proposed prediction approaches is a lack of consideration of the effect of variation of water table level on the railway-induced vibrations. To fill this gap, a comprehensive field measurement was carried out in this research in the historical city of Isfahan. Based on the data obtained from the field measurement, significant effects of variation of water table level on the Peak Particle Velocity (PPV) and Soil Transfer Function (STF) were shown. Using the result obtained from the measurement, an adjustment factor was derived to consider the effect of variation of water table level in the conventional train-induced vibration prediction approach. The accuracy and validity of the water table level adjustment factor derived in this study were evaluated through an independent comprehensive field measurement performed in a different historical city.

Rapid MR Scanner Independent B1 Field Measurement System for Phased Arrays.

This paper demonstrates a rapid B1 field benchtop measurement system that is independent of an MR scanner and network analyzer. This system can be used to obtain radiofrequency (B1 field) strength distribution plots of multiple 2D slices (with an extension to 3D) of a liquid cylindrical phantom for multi-element phased arrays used in MRI. The system can be used in three modes- element, phased array, and multiple fixed point pattern measurement. These modes are demonstrated for a 7T 1H eight-channel dipole array and a corn-syrup based phantom. The system can measure complex phase and amplitude measurements from up to 8 elements in the first mode one or 8 different phase settings in the second mode at a rate of approximately 37 positions per minute, allowing a full 2D B1 mapping for 1303 points in 33.05 minutes. The scan patterns obtained using this setup are compared to the ones obtained using an HP network analyzer and simulations. This work can be extended to measure the E field, SAR and upon increasing the speed of measurement, could be used for applications such as Transmit SENSE. Clinical Relevance- This work benefits a faster and more widely accessible measurement system for phased array antennas for MRI. As phased arrays are becoming very important in MRI, the ability to assess individual element performance more rapidly and B1 shimming performance is important to aid in their further development.

Variability in Oceanic Particle Size Distributions and Estimation of Size Class Contributions Using a Non-parametric Approach.

A dataset of nearly 400 measurements of the particle size distribution (PSD) compiled from the Pacific, Atlantic, and Arctic Oceans is used to examine variability in the magnitude and shape of the PSD, and to characterize the partitioning of particle number, cross‐sectional area, and volume concentration among defined size intervals. The results indicate that the relative contributions of three size classes based upon the pico‐, nano‐, and microplankton size range exhibit substantial changes among measures of particle size and between oceanic environments. The single‐slope power law model commonly employed to characterize the PSD in aquatic studies is demonstrated to have significant limitations in capturing the complexity of PSD shapes observed for natural particle assemblages, and in consequence poorly predicts the relative contributions of these different size intervals. We show that specific percentile diameters derived from the cumulative distributions of particle size are strongly correlated with the contributions of these three size classes, and that these non‐parametric descriptors of the cumulative distribution provide superior performance for estimating their contributions while requiring no assumption of underlying PSD shape. A comparison of these predictive relationships with independent field measurements suggests that this approach is generally robust for particle assemblages representing a wide diversity of marine environments.

Understanding spatial variability of forage production in California grasslands: delineating climate, topography and soil controls

Rangelands are a key global resource, providing a broad range of ecological services and economic benefits. California’s predominantly annual rangelands cover ∼12% of the state’s land area, and the forage production is highly heterogeneous, making balancing economic (grazing), conservation (habitat) and environmental (erosion/water quality) objectives a big challenge. Herein, we examined how climate and environmental factors regulate annual grassland forage production spatially across the state and among four ecoregions using machine learning models. We estimated annual forage production at 30 m resolution over a 14 year period (2004–2017) using satellite images and data fusion techniques. Our satellite-based estimation agreed well with independent field measurements, with a R 2 of 0.83 and RMSE of 682 kg ha−1. Forage production (14 year average) showed large spatial variability (2940 ± 934 kg ha-1 yr-1; CV = 35%) across the study area. The gradient boosted regression tree with 11 feature variables explained 67% of the variability in forage production across the state. Precipitation amount, especially in November (germination) and April (rapid growth), was found as the dominant driver for spatial variation in forage production, especially in drier ecoregions and during drier years. Seasonal distribution of precipitation and minimum air temperature showed a relatively stronger control on forage production in wetter regions and during wet years. Additionally, solar energy became more important in wetter ecoregions. Drought reduced forage production from the long-term mean, i.e. a 33% ± 19% decrease in production (2397 ± 926 kg ha-1yr-1; CV = 38%) resulting from a 29% ± 5% decrease in precipitation. The machine learning based spatial analysis using ‘big data’ provided insights on impacts of climate and environmental factors on forage production variation at various scales. This study demonstrates a cost-effective approach for rapid mapping and assessment of annual forage production with the potential for near real-time application.

Comment on “Overland runoff erosion dynamics on steep slopes with forages under field simulated rainfall and inflow by C. Li and C. Pan”

AbstractManaging sloping landscapes to control soil erosion processes due to rainfall and runoff is a relevant problem, especially when the vegetation is absent or sparse. The aim of this paper was to investigate the applicability of a theoretically resistance law for overland flow under simulated rainfall, based on a power‐velocity profile, using field measurements carried out by Li and Pan for three plots with planted forage species (Astragalus adsurgens, Medicago sativa and Cosmos bipinnatus).The relationship between the velocity profile parameter Γ, the flow Froude number and the rain Reynolds number was calibrated using the data by Li and Pan. The obtained overland flow resistance law was also verified by independent field measurements carried out by Li and Pan in the same plots with the same forage species subjected to three different treatments (intact grass control IG, no litter or leaves NLL (only the grass stems and roots were reserved) and only roots remaining OR).The theoretical approach and the measurements carried out in the investigated conditions allowed to state that a) the Darcy‐Weisbach friction factor can be accurately estimated using the proposed theoretical approach, b) the Darcy‐Weisbach friction factor varies with rainfall intensity and c) for the investigated forage species, the vegetation treatment (IG, NLL, OR) does not significantly affect the flow resistance in laminar regime.

Estimation of the distribution of the total net radiative flux from satellite and automatic weather station data in the Upper Blue Nile basin, Ethiopia

Net radiation is an important factor in studies of land–atmosphere processes, water resource management, and global climate change. This is particularly true for the Upper Blue Nile (UBN) basin, where significant parts of the basin are dry and evapotranspiration (ET) is a major mechanism for water loss. However, net radiation has not yet been appropriately parameterized in the basin. In this study, we estimated the instantaneous distribution of the net radiation flux in the basin using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite and Automatic Weather Station (AWS) data. Downward shortwave radiation and air temperature usually vary with topography, so we applied residual kriging spatial interpolation techniques to convert AWS data for point locations into gridded surface data. Simulated net radiation outputs were validated through comparison with independent field measurements. Validation results show that our method successfully reproduced the downward shortwave, upward shortwave, and net radiation fluxes. Using AWS data and residual kriging spatial interpolation techniques makes our results robust and comparable to previous works that used satellite data at a finer spatial resolution than MODIS. The estimated net shortwave, longwave, and total radiation fluxes were in close agreement with ground truth measurements, with mean bias (MB) values of − 14.84, 5.7, and 20.53 W m−2 and root mean square error (RMSE) values 83.43, 32.54, and 78.07 W m−2, respectively. The method presented here has potential applications in research focused on energy balance, ET estimation, and weather prediction for regions with similar physiographic features to those of the Nile basin.

Constructing a Finer-Resolution Forest Height in China Using ICESat/GLAS, Landsat and ALOS PALSAR Data and Height Patterns of Natural Forests and Plantations

Monitoring forest height is crucial to determine the structure and biodiversity of forest ecosystems. However, detailed spatial patterns of forest height from 30 m resolution remotely sensed data are currently unavailable. In this study, we present a new method for mapping forest height by combining spaceborne Light Detection and Ranging (LiDAR) with imagery from multiple remote sensing sources, including the Landsat 5 Thematic Mapper (TM), the Phased Array L-band Synthetic Aperture Radars (PALSAR), and topographic data. The nationwide forest heights agree well with results obtained from 525 independent forest height field measurements, yielding correlation coefficient, root mean square error (RMSE), and mean absolute error (MAE) values of 0.92, 4.31 m, and 3.87 m, respectively. Forest heights derived from remotely sensed data range from 1.41 m to 38.94 m, with an average forest height of 16.08 ± 3.34 m. Mean forest heights differ only slightly among different forest types. In natural forests, conifer forests have the greatest mean forest heights, whereas in plantations, bamboo forests have the greatest mean forest heights. Important predictors for modeling forest height using the random forest regression tree method include slope, surface reflectance of red bands and HV backscatter. The uncertainty caused by the uneven distribution of Geoscience Laser Altimeter System (GLAS) footprints is estimated to be 0.64 m. After integrating PALSAR data into the model, the uncertainty associated with forest height estimation was reduced by 4.58%. Our finer-resolution forest height could serve as a benchmark to estimate forest carbon storage and would greatly contribute to better understanding the roles of ecological engineering projects in China.

Precise Model-Free Spline-Based Approach for Magnetic Field Mapping

Untethered magnetic manipulation has found applications in a rapidly increasing number of fields, ranging from minimally invasive surgery to assembly of industrial micro electromechanical systems. Despite this relevance, present-day literature on precise magnetic mapping is sparse, especially for magnetic fields affected by external disturbances. In this work, we address this deficiency by introducing a model-free mapping technique. Remarkably, the presented spline-based approach is capable of addressing the presence of inhomogeneous static disturbances and the mapping of non-azimuthally symmetric electromagnets. The work is validated with the mapping of nine metal-core electromagnets in the presence of inhomogeneous static disturbances. A grid of 5120 measurements is collected, by a custom-programed robotic arm, and used for mapping. Further, the values predicted by the approach are compared against 3430 independent field measurements, obtaining an R 2 value of 0.9884 and maximum relative errors of 7%. Overall, this spline-based approach provides a flexible technique for the precise mapping of electromagnetic fields and gradients even when, for reasons regarding coil shape or disturbances, the electromagnetic field does not present any axial symmetry.

Multi-Annual Kinematics of an Active Rock Glacier Quantified from Very High-Resolution DEMs: An Application-Case in the French Alps

Rock glaciers result from the long-term creeping of ice-rich permafrost along mountain slopes. Under warming conditions, deformation is expected to increase, and potential destabilization of those landforms may lead to hazardous phenomena. Monitoring the kinematics of rock glaciers at fine spatial resolution is required to better understand at which rate, where and how they deform. We present here the results of several years of in situ surveys carried out between 2005 and 2015 on the Laurichard rock glacier, an active rock glacier located in the French Alps. Repeated terrestrial laser-scanning (TLS) together with aerial laser-scanning (ALS) and structure-from-motion-multi-view-stereophotogrammetry (SFM-MVS) were used to accurately quantify surface displacement of the Laurichard rock glacier at interannual and pluri-annual scales. Six very high-resolution digital elevation models (DEMs, pixel size <50 cm) of the rock glacier surface were generated, and their respective quality was assessed. The relative horizontal position accuracy (XY) of the individual DEMs is in general less than 2 cm with a co-registration error on stable areas ranging from 20–50 cm. The vertical accuracy is around 20 cm. The direction and amplitude of surface displacements computed between DEMs are very consistent with independent geodetic field measurements (e.g., DGPS). Using these datasets, local patterns of the Laurichard rock glacier kinematics were quantified, pointing out specific internal (rheological) and external (bed topography) controls. The evolution of the surface velocity shows few changes on the rock glacier’s snout for the first years of the observed period, followed by a major acceleration between 2012 and 2015 affecting the upper part of the tongue and the snout.

Field measurement and investigation of spatial coherence for near-surface strong winds in Southeast China

With aid of structural health monitoring systems, the field measurements have been proceeded in a ready manner in recent years. This treatment, however, raises a question on the influence of complex terrain associated with engineering structures upon coherence analysis. An independent field measurement is thus still necessary for the analysis of spatial coherence. In the present paper, the field measurement of near-surface strong winds in Southeast China is carried out. For implementing the purpose, an observation array was built up in a typhoon-prone area. The wind characteristics of local site, the spatial coherence of wind field and statistics of decay parameters in exponential formats are investigated. It is revealed that decay parameters of the Davenport and Krenk models have a different relationship to vertical and lateral separations, which are positively and weakly correlated to vertical separation, respectively; while both negatively correlated to lateral separation. The statistics of decay parameters relies significantly upon the time period of velocity readings. Besides, there is a logical relationship between decay parameters and wind velocity, maintaining a consistency with the pioneering measured data in 1960s–1970s.

Inventory Policies for Public Pharmaceutical Distribution in Zambia: Improving Availability and Geographic Access Equity for Essential Medicines

Problem de finition: The inventory control problem associated with the distribution of essential medicines in Zambia involves seasonality and uncertainty in both demand and lead-times, heterogeneous delivery locations, and lost sales. Beyond the traditional performance metrics of system service level and inventory level, the equity of distribution across delivery locations must be considered. Academic/practical relevance: Stockouts of life-saving medicines are currently widespread in sub- Saharan Africa including Zambia. The companion study Leung et al. (2017) suggests that inventory management is an important opportunity, but ignores the challenge of distributing limited inventory to multiple locations. The existing literature on inventory management does not consider all aspects of this problem. Methodology: A simulation model generating inventory dynamics of anti-malaria products in 212 (17%) of Zambia's health facilities is used to compare the current and various proposed inventory policies. It leverages extensive data including digital photographs of facility stock reports and its stockout prediction accuracy is validated against independent field measurements. Results: Inventory control constitutes an important opportunity to improve patient access to medicines in Zambia. The policies proposed in USAID DELIVER (2011b) and Watson et al. (2014) perform well for only two of the three metrics of system service level, facility inventory and distribution equity, and are sensitive to their base stock parameter. Our proposed optimization-based policy outperforms these policies, and seems robust to policy parameters and demand forecasts accuracy. Managerial implications: The proposed optimization-based policy seems a desirable alternative to current inventory management practices and other proposed enhancements for Zambia's public pharmaceutical distribution system, and may outperform the so-called min/max rule in other settings. In distribution systems with heterogeneous delivery locations, widespread proportional inventory rationing rules may lead to substantial service level discrepancies between facilities. The performance metrics of average service level and distribution equity may be frequently at odds, prompting non-trivial design trade-o s and considerations.

Thermal comfort evaluation in cruise terminals

The variations of building typologies contribute to the difficulty of performing a correct analysis of the comfort conditions in buildings that do not fit the more common geometries and occupation patterns. The main objective of the article is to evaluate the comfort conditions of cruise terminal buildings, an example of this type of problem. A twofold strategy, comprising in-situ measurements and user surveys was implemented. A total of 20 independent field measurements of thermal comfort parameters underwent in 2 facilities located in Portugal. The in-situ measurements supported the comfort assessment by the PMV analytical index and by the ASHRAE 55 and EN15251 adaptive approaches. The responses to 572 questionnaires to judge sensations and preferences of the passengers were obtained. Other aspects were also inquired, such as the time spent in the facilities and the health status. The comparison of the comfort assessment with the results of the survey showed that the adaptive models provided a broader acceptance of the measured environmental conditions, in line with the broader acceptance demonstrated by the users. The significant restriction of the PMV model application in this building typology was emphasized. The contrast of sensations by passengers of different national origin, with tropical originals feeling neutral at higher operative temperatures than temperate climate originals, was detected as an influencing factor. Waiting time was another relevant factor found, as the time spent inside the buildings pointed to a greater demand by passengers.

Unmanned aircraft system advances health mapping of fragile polar vegetation

Abstract Plants like mosses can be sensitive stress markers of subtle shifts in Arctic and Antarctic environmental conditions, including climate change. Traditional ground‐based monitoring of fragile polar vegetation is, however, invasive, labour intensive and physically demanding. High‐resolution multispectral satellite observations are an alternative, but even their recent highest achievable spatial resolution is still inadequate, resulting in a significant underestimation of plant health due to spectral mixing and associated reflectance impurities. To resolve these obstacles, we have developed a new method that uses low‐altitude unmanned aircraft system (UAS) hyperspectral images of sub‐decimeter spatial resolution. Machine‐learning support vector regressions (SVR) were employed to infer Antarctic moss vigour from quantitative remote sensing maps of plant canopy chlorophyll content and leaf density. The same maps were derived for comparison purposes from the WorldView‐2 high spatial resolution (2.2 m) multispectral satellite data. We found SVR algorithms to be highly efficient in estimating plant health indicators with acceptable root mean square errors (RMSE). The systematic RMSEs for chlorophyll content and leaf density were 3.5–6.0 and 1.3–2.0 times smaller, respectively, than the unsystematic errors. However, application of correctly trained SVR machines on space‐borne multispectral images considerably underestimated moss chlorophyll content, while stress indicators retrieved from UAS data were found to be comparable with independent field measurements, providing statistically significant regression coefficients of determination (median r2 = .50, pt test = .0072). This study demonstrates the superior performance of a cost‐efficient UAS mapping platform, which can be deployed even under the continuous cloud cover that often obscures optical high‐altitude airborne and satellite observations. Antarctic moss vigour maps of appropriate resolution could provide timely and spatially explicit warnings of environmental stress events, including those triggered by climate change. Since our polar vegetation health assessment method is based on physical principles of quantitative spectroscopy, it could be adapted to other short‐stature and fragmented plant communities (e.g. tundra grasslands), including alpine and desert regions. It therefore shows potential to become an operational component of any ecological monitoring sensor network.

Modelling nearshore hydrodynamics and circulation under the impact of high waves at the coast of Varkiza in Saronic-Athens Gulf

Summary A plethora of physical parameters, such as hydro-, litho- and morpho-dynamic characteristics, are essential for understanding the response of coastal systems to intense sea states in terms of sediment transport and shoreline evolution. Nowadays, numerical models are extensively applied to meet the above needs and support coastal planning and management. In the present work, a 2DH dynamic modelling system is used for simulating the hydrodynamic and meteorological/oceanographic characteristics of the Saronic Gulf, in order to examine circulation patterns and predict sediment transport phenomena under high wave conditions at the coast of Varkiza, a sandy beach in the southern Attica, Greece. Time series of wind and wave data were used as input at the open boundaries of the model domain while the model was calibrated and validated through (linear and directional) statistical measures with respect to in situ wave measurements, since there was lack of hydrodynamic data at the site of interest. The simulation period of the model was between January 3 and February 19, 2013, with consecutive high waves in-between. The good agreement of the numerical results from the wave and hydrodynamic model with in situ measurements confirmed the suitability of the model for the support of sediment transport rates at Varkiza coastal segment. Model results reveal that there is a counter-clockwise water circulation during high waves that contribute to the erosion of the examined beach, which is also confirmed by independent field measurements.

Ground‐level observation of a terrestrial gamma ray flash initiated by a triggered lightning

AbstractWe report on a terrestrial gamma ray flash (TGF) that occurred on 15 August 2014 coincident with an altitude‐triggered lightning at the International Center for Lightning Research and Testing (ICLRT) in North Central Florida. The TGF was observed by a ground‐level network of gamma ray, close electric field, distant magnetic field, Lightning Mapping Array (LMA), optical, and radar measurements. Simultaneous gamma ray and LMA data indicate that the upward positive leader of the triggered lightning flash induced relativistic runaway electron avalanches when the leader tip was at about 3.5 km altitude, resulting in the observed TGF. Channel luminosity and electric field data show that there was an initial continuous current (ICC) pulse in the lightning channel to ground during the time of the TGF. Modeling of the observed ICC pulse electric fields measured at close range (100–200 m) indicates that the ICC pulse current had both a slow and fast component (full widths at half maximum of 235 μs and 59 μs) and that the fast component was more or less coincident with the TGF, suggesting a physical association between the relativistic runaway electron avalanches and the ICC pulse observed at ground. Our ICC pulse model reproduces moderately well the measured close electric fields at the ICLRT as well as three independent magnetic field measurements made about 250 km away. Radar and LMA data suggest that there was negative charge near the region in which the TGF was initiated.

Comparison and Evaluation of Methods to Apportion Ambient PM2.5 to Residential Wood Heating in Fairbanks, AK

Biomass burning for residential heating significantly contributes to ambient PM_(2.5) burdens in many areas, making source apportionment to wood heater emissions an important issue. This study compares and evaluates Chemical Mass Balance (CMB), levoglucosan analysis, and ^(14)C analysis methods for apportionment. Results suggest that the CMB method appears to overestimate the contribution of residential wood heating in Fairbanks, perhaps due to non-representativeness of emissions source profiles. Carbon-14 analysis allows for apportionment to biomass sources, but must be corrected for noncarbon PM_(2.5) content. Levoglucosan analysis has the advantage of being relatively inexpensive, but there is considerable uncertainty in determining conversion factors to calculate wood smoke levels from measured levoglucosan concentrations. Conversion factors in the range of 9.1 to 13.3 are calculated from previously published and experimental mass fractions of levoglucosan in wood smoke PM_(2.5). Conversion factors in the range of 10.7 to 12.9 are determined from analysis of independent field measurements of ^(14)C and levoglucosan in Fairbanks. The calculated and measured conversion factors are consistent and are similar to previously-reported values. The three apportionment methods (focused on residential wood smoke contributions) are complementary and collectively provide a means to evaluate or confirm apportionment results.

Comparison of Laser and Stereo Optical, SAR and InSAR Point Clouds from Air- and Space-Borne Sources in the Retrieval of Forest Inventory Attributes

It is anticipated that many of the future forest mapping applications will be based on three-dimensional (3D) point clouds. A comparison study was conducted to verify the explanatory power and information contents of several 3D remote sensing data sources on the retrieval of above ground biomass (AGB), stem volume (VOL), basal area (G), basal-area weighted mean diameter (Dg) and Lorey’s mean height (Hg) at the plot level, utilizing the following data: synthetic aperture radar (SAR) Interferometry, SAR radargrammetry, satellite-imagery having stereo viewing capability, airborne laser scanning (ALS) with various densities (0.8–6 pulses/m2) and aerial stereo imagery. Laser scanning is generally known as the primary source providing a 3D point cloud. However, photogrammetric, radargrammetric and interferometric techniques can be used to produce 3D point clouds from space- and air-borne stereo images. Such an image-based point cloud could be utilized in a similar manner as ALS providing that accurate digital terrain model is available. In this study, the performance of these data sources for providing point cloud data was evaluated with 91 sample plots that were established in Evo, southern Finland within a boreal forest zone and surveyed in 2014 for this comparison. The prediction models were built using random forests technique with features derived from each data sources as independent variables and field measurements of forest attributes as response variable. The relative root mean square errors (RMSEs) varied in the ranges of 4.6% (0.97 m)–13.4% (2.83 m) for Hg, 11.7% (3.0 cm)–20.6% (5.3 cm) for Dg, 14.8% (4.0 m2/ha)–25.8% (6.9 m2/ha) for G, 15.9% (43.0 m3/ha)–31.2% (84.2 m3/ha) for VOL and 14.3% (19.2 Mg/ha)–27.5% (37.0 Mg/ha) for AGB, respectively, depending on the data used. Results indicate that ALS data achieved the most accurate estimates for all forest inventory attributes. For image-based 3D data, high-altitude aerial images and WorldView-2 satellite optical image gave similar results for Hg and Dg, which were only slightly worse than those of ALS data. As expected, spaceborne SAR data produced the worst estimates. WorldView-2 satellite data performed well, achieving accuracy comparable to the one with ALS data for G, VOL and AGB estimation. SAR interferometry data seems to contain more information for forest inventory than SAR radargrammetry and reach a better accuracy (relative RMSE decreased from 13.4% to 9.5% for Hg, 20.6% to 19.2% for Dg, 25.8% to 20.9% for G, 31.2% to 22.0% for VOL and 27.5% to 20.7% for AGB, respectively). However, the availability of interferometry data is limited. The results confirmed the high potential of all 3D remote sensing data sources for forest inventory purposes. However, the assumption of using other than ALS data is that there exist a high quality digital terrain model, in our case it was derived from ALS.

Modeling bioaccumulation and biomagnification of nonylphenol and its ethoxylates in estuarine–marine food chains

There are several studies on bioaccumulation and biomagnification of nonylphenol (NP) and its ethoxylates (NPEOs), but their toxico-kinetic mechanisms remain unclear. In the present investigation, we explored the accumulation of NP and NPEOs in estuarine–marine food chains with a bioaccumulation model comprising five trophic levels. Using this model, we estimated uptake and elimination rate constants for NPEOs based on the organisms’ weight and lipid content and the chemicals’ Kow. Further, we calculated accumulation factors for NP and NPEOs, including biota-sediment accumulation factors (BSAF) and biomagnification factors (BMF), and compared these to independent field measurements collected in the Western Scheldt estuary in The Netherlands and field data reported in the literature. The estimated BSAF values for NP and total NPEOs were below 1 for all trophic levels. The estimated BMF values were around 1 for all trophic levels except for the highest level (carnivorous mammals and birds). For this trophic level, the estimated BMF value varied between 0.1 and 2.4, depending on the biotransformation capacity. For all trophic levels, except primary producers, the accumulation estimates that accounted for biotransformation of NPEOs into NP were closer to the field data than model estimates that did not include biotransformation, indicating that NP formation by biotransformation of NPEOs might occur in organisms.

Performance Assessment of High Resolution Airborne Full Waveform LiDAR for Shallow River Bathymetry

We evaluate the performance of full waveform LiDAR decomposition algorithms with a high-resolution single band airborne LiDAR bathymetry system in shallow rivers. A continuous wavelet transformation (CWT) is proposed and applied in two fluvial environments, and the results are compared to existing echo retrieval methods. LiDAR water depths are also compared to independent field measurements. In both clear and turbid water, the CWT algorithm outperforms the other methods if only green LiDAR observations are available. However, both the definition of the water surface, and the turbidity of the water significantly influence the performance of the LiDAR bathymetry observations. The results suggest that there is no single best full waveform processing algorithm for all bathymetric situations. Overall, the optimal processing strategies resulted in a determination of water depths with a 6 cm mean at 14 cm standard deviation for clear water, and a 16 cm mean and 27 cm standard deviation in more turbid water.