Total Backscattering Research Articles

Changes in the Optical Corneal Densitometry, Visual Acuity, and Refractive Error after the Annular Intracorneal Inlay Implantation.

Purpose:To investigate the changes in the optical corneal densitometry as an objective method in assessing the corneal light back-scattering before and 1 year after the annular intracorneal inlay (AICI) implantation into the keratoconic corneas.Methods:Changes in the optical corneal densitometry, visual acuity, refractive, and tomographical status were assessed before and 1 year after the AICI implantation into the corneas with different stages of keratoconus. Optical corneal densitometry was evaluated using the Pentacam-HR in 0–2, 2–6, 6–10, and 10–12 mm rings in the anterior 120 μ, central layers, posterior 60 μ and also the total value were measured for cornea in the Grey Scale Unit criterion.Results:Totally, 34 patients with keratoconus were studied; the uncorrected and best corrected visual acuity were increased after the surgery (0.98 ± 0.25 to 0.53 ± 0.30 logMAR, P < 0.001 and 0.26 ± 0.18 to 0.19 ± 0.14, P = 0.007 logMAR, respectively); the spherical equivalent was decreased from −4.45 ± 2.25 to − 2.06 ± 2.01 D (P = 0.004). AICI implantation led to an increase in the amount of optical corneal densitometry in 0–2 mm central, 2–6 mm central, 6–10 mm central, total central, 2–6 mm posterior, and 2–6 mm total rings (all, P < 0.05); however, a decrease was observed in 0–2 mm anterior ring (P = 0.049). Results of statistical analysis showed that the total optical corneal densitometry, anterior total, and posterior total back-scattering did not change after the AICI implantation (all, P > 0.05).Conclusions:Our results revealed a significant improvement in the visual function, including refractive error and visual acuity following the AICI implantation. Changes in the optical corneal densitometry were different in distinct regions and layers however, the total amount did not change after the AICI implantation.

The Role of Micro Breaking of Small-Scale Wind Waves in Radar Backscattering from Sea Surface

The study of the microwave scattering mechanisms of the sea surface is extremely important for the development of radar sensing methods. Some time ago, Bragg (resonance) scattering of electromagnetic waves from the sea surface was proposed as the main mechanism of radar backscattering at moderate incidence angles of microwaves. However, it has been recently confirmed that Bragg scattering is often unable to correctly explain observational data and that some other physical mechanisms should be taken into consideration. The newly introduced additional scattering mechanism was characterized as non-polarized, or non-Bragg scattering, from quasi-specular facets appearing due to breaking wave crests, the latter usually occurring in moderate and strong winds. In this paper, it was determined experimentally that such non-polarized radar backscattering appeared not only for rough sea conditions in which wave crests strongly break and “white caps” occur, but also at very low wind velocities close to their threshold values for the wave generation process. The experiments were performed using two polarized Doppler radars. The experiments demonstrated that a polarization ratio, which characterizes relative contributions of non-polarized and Bragg components to the total backscatter, changed slightly with wind velocity and wind direction. Detailed analysis of radar Doppler shifts revealed two types of scatterers responsible for the non-polarized component. One type of scatterer, moving with the velocities of decimeter-scale wind waves, determined radar backscattering at low winds. We identified these scatterers as “microbreakers” and related them to nonlinear features in the profile of decimeter-scale waves, like bulges, toes and parasitic capillary ripples. The scatterers of the second type were associated with strong breaking, moved with the phase velocities of meter-scale breaking waves and appeared at moderate winds additionally to the “microbreakers”. Along with strong breakers, the impact of microbreaking in non-polarized backscattering at moderate winds remained significant; specifically the microbreakers were found to be responsible for about half of the non-polarized component of the radar return. The presence of surfactant films on the sea surface led to a significant suppression of the small-scale non-Bragg scattering and practically did not change the non-Bragg scatterer speed. This effect was explained by the fact that the nonlinear structures associated with dm-scale waves were strongly reduced in the presence of a film due to the cascade mechanism, even if the reduction of the amplitude of dm waves was weak. At the same time, the velocities of non-Bragg scatterers remained practically the same as in non-slick areas since the phase velocity of dm waves was not affected by the film.

PolInSAR decorrelation-based decomposition modelling of spaceborne multifrequency SAR data

ABSTRACT The characterization of ground targets from a remotely sensed Synthetic Aperture Radar (SAR) image is addressed by polarimetric decomposition. The polarimetric SAR (PolSAR) decomposition measures the contribution of total backscatter from different scattering mechanisms using SAR images. The ambiguities present in the retrieval of scattering are the major problems associated with the model-based decomposition which could be reduced with a combination of interferometric coherence and PolSAR backscatter. The objective of this study is to improve the polarimetric decomposition model for identifying the scattering mechanisms based on the Polarimetric SAR Interferometry (PolInSAR) coherence for natural and manmade features. In this paper, we have proposed a model-based polarimetric decomposition using PolInSAR decorrelation. The PolInSAR decorrelation is exploited here to distinguish the time-varying and invariant scatterers present in the ground. The volume scattering power was calculated using the proposed decorrelation parameter which is the combination of PolInSAR coherence and decorrelation. The proposed algorithm has been tested on spaceborne multifrequency SAR datasets consisting of X-band TerraSAR-X and TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X), C-band Radarsat-2, and phased array L-band synthetic aperture radar-2 (PALSAR-2) data of advanced land observing satellite-2 (ALOS-2) PolInSAR data for the Dehradun region, India. The results show that there is a remarkable reduction in the ambiguities present in the identification of the scattering mechanism from the SAR image by using the proposed decorrelation-based decomposition model. Moreover, the algorithm is tested on X-band TerraSAR-X and TanDEM-X data of the Haridwar area and Rudrapur area, Uttarakhand, India to analyse the potential of the proposed decomposition technique in representing different manmade and natural features.

Dynamic Monitoring of Haze Pollution Using Satellite Remote Sensing

The severe haze pollution episode from December 1 to 10, 2013 occurred in Shanghai area, and seriously threatened human health and transportation safety. As regional air pollution, it is practical significance to the rapid monitoring and comprehensive analysis for haze treatment. Based on the moderate resolution imaging spectro- radiometer (MODIS) and cloud-aerosol LiDAR with orthogonal polarization (CALIOP) data, via combing with meteorological features during the haze pollution period, the current study analyzed and explored the spatial distribution, aerosol vertical structure, source and migration path of haze pollution. The results showed that: (1) There are obvious aerosol layers over Shanghai area, aerosol optical depth (AOD) fluctuates frequently and has distinctive features such as complexity, regionality and seasonality. (2) The aerosol layer is mainly at the heights ranging from 0 to 2 km and composed mostly of spherical aerosol but there is also non-spherical aerosol. (3) The total backscattering intensity of aerosol is centralized at the heights ranging from 0 to 1 km, especially at the heights ranging from 0 to 0.5 km. (4) The haze pollution episode was affected by both specific meteorological factors and migration of the non-local particles in the surrounding areas and northern China.

Controls on Ocean Color Spectra Observed During the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES)

Satellite ocean color remote sensing is the primary method to retrieve synoptic measurements of the optical properties of the ocean on large spatial and regular time scales.Through bio-optical modelling, changes in ocean color spectra can be linked to changes in marine 2 ecosystem and biogeochemical properties. Bio-optical algorithms rely on assumptions about the covariance of marine constituents as well as the relationships among their inherent and apparent optical properties. Validation with in situ measurements of in-water constituents and their optical properties is required to extrapolate local knowledge about ocean color variations to global scales.Here, we evaluate seasonal and spatial relationships between optical constituents and their inherent and apparent optical properties throughout the annual cycle of the North Atlantic plankton bloom using bio-optical data from four cruises conducted as part of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). Our results show ocean color variability, quantified using field observations of the remote sensing reflectance spectrum at each NAAMES station, is driven by colored dissolved organic matter (CDOM) absorption in the ultraviolet wavelengths, phytoplankton absorption in the blue wavelengths, and total particulate backscattering in the green wavelengths. Results from a recently storm-mixed station at the height of the spring bloom demonstrate that significant changes in bio-optical properties can occur on daily scales. By testing the effects of variations in lighting conditions and solar geometries, we also demonstrate that, for this data set, remote sensing reflectance should be considered a quasi-inherent optical property.We find that the temporal and spatial chlorophyll concentrations and the magnitudes of inherent optical properties can be accurately assessed using previously published ocean color algorithms.However, changes in the spectral slopes of the inherent optical properties are often poorly retrieved, indicating the need for improvements in the retrieval of optical constituent composition.The characterization of such a dynamic environment provides beneficial insights for future biooptical algorithms.

Optical Properties Using Adaptive Selection of NIR/SWIR Reflectance Correction and Quasi-Analytic Algorithms for the MODIS-Aqua in Estuarine-Ocean Continuum: Application to the Northern Gulf of Mexico

An adaptive selection of the near/shortwave infrared (NIR/SWIR) reflectance correction and the quasi-analytic algorithms (QAAs) is proposed for the Moderate Resolution Imaging Spectroradiometer (MODIS-Aqua) to utilize the strengths of different correction algorithms and QAAs in a single satellite scene with water types ranging from turbid coastal to clear open ocean waters. A blended satellite product is generated by merging three atmospheric-correction algorithms(AD-ATCOR): 1) iterative NIR correction; 2) management unit of the north sea mathematical models (MUMM); and 3) SWIR, using a spectral threshold-based selection for different water types. The validation analysis of a blended remote sensing reflectance product showed overall good agreement with AERONET-OC observations followed by NASA bio-optical marine algorithm data set (NOMAD) at the blue wavelengths and the estuarine data set at the green and red wavelengths. The results suggest that the adaptive method is a better alternative to address the challenging problem of selecting different correction algorithms for different water types in a single satellite scene. Likewise, an adaptive selection of a QAA (AD-QAA) used the QAA-v5 and the QAA-V to obtain merged inherent optical property (IOP) products in a single MODIS-Aqua scene with varying water types. As a case study, the two adaptive selection procedures were sequentially applied to the MODIS-Aqua imagery representing four environmental conditions in the northern Gulf of Mexico. Improved retrievals of the total absorption and backscattering coefficients along an estuarine to ocean continuum demonstrated the effectiveness of this method in an optically complex and dynamic river-dominated system.

Transport Patterns, Size Distributions, and Depolarization Characteristics of Dust Particles in East Asia in Spring 2018

AbstractThe long‐range transport of Asian dust and its complex interaction with anthropogenic pollutants have a significant yet poorly quantified effect on the global climate. In this study, dust events were observed based on an optical particle counter with a polarization detection module at an urban site in North China. The temporal variations in the size distribution and morphological changes of dust particles were analyzed. The results demonstrate that the dust events were induced by a deep Siberian low‐pressure anomaly and/or Mongolian cyclone in the low troposphere. The morphology of dust particles, as indicated by the depolarization ratio (δ = s/(s + p), the ratio of the parallel signal to the total backscattering signal), varied significantly at different transport heights. A decreasing tendency was found when dust was trapped within the boundary layer over polluted areas, particularly when the atmospheric loading of pollutants and the relative humidity were high. During a typical polluted dust case, the δ value of mineral dust (Dp = 5 μm) decreased by 39%, as the conditions were stagnant in East China, consistent with the Cloud‐Aerosol LIDAR with Orthogonal Polarization results. The morphological variation was evaluated according to the aspect ratio, presuming that the dust particles were ellipsoidal. The interaction between dust particles and water vapor could lead to an increase of at least 6% in volume when the relative humidity increased up to 90%. An aerosol classification based on δ values and size information could be performed to estimate the contributions of different aerosol types to pollution days. The results should be helpful for evaluating satellite‐borne and ground‐based light detection and ranging data analyses.

Parameterization of the modified water cloud model (MWCM) using normalized difference vegetation index (NDVI) for winter wheat crop: a case study from Punjab, India

Soil moisture is essential for water resources management, yet accurate information of soil moisture has been a challenge. The major goal was to parametrize the Modified Water Cloud Model (MWCM). The Sentinel-1A data of winter wheat crop was collected for two weeks. Concurrently, in-situ soil moisture data was collected using Time Domain Reflectometer (TDR). A parametric scheme was used for the retrieval of the VV polarization of Sentinel-1A. The effect of NDVI as a vegetation descriptors (V1 and V2) on total VV backscatter (σ 0) was analyzed. The calibration showed NDVI has the potential to influence Water Cloud Model (WCM) and vegetation descriptors; hence it is recommended to calibrate the MWCM. The coefficient of determination (R2 = 0.83) showed a good agreement between observed and estimated soil moisture. Therefore, this approach help improve soil moisture prediction, and can be applied to determine soil moisture more accurately for winter crops, grasses, and pasture lands.

Observations of SAR polarimetric parameters of lake and fast sea ice during the early growth phase

This study examines links between two sets of parameters obtained from Radarsat-2 Quad-pol data and geophysical information of lake ice and landfast sea ice in the Resolute Bay area, Nunavut, Canada. The first set includes the three orthogonal backscatter coefficients (σhh0, σvv0, σvh0) in addition to the total backscatter power (SPAN). The second set includes polarimetric decomposition parameters obtained using Cloude-Pottier and Yamaguchi decomposition methods. Data were collected during the early freezing period from 20 September until 28 December 2017. Meteorological and ice climatological data from the weather station of Resolute Bay were used to facilitate this task. Ice thickness and salinity were obtained from established empirical models. Results show that single-bounce and multiple-bounce scattering mechanisms are active in lake ice during the entire freezing period while multiple-bounce scattering is active in sea ice only during the initial freezing. Backscatter parameters can be used to determine the thickness of lake ice up to any depth, while both backscatter and the tested decomposition parameters are related to the thickness of young sea ice (<30 cm thick). Physical explanations are offered in each case. Spatial maps of ice thickness are produced. Polarimetric decomposition parameters demonstrate erratic behavior throughout the development of lake ice. High entropy (>0.6) is found to be associated with comparable single- and multiple-bounce scattering mechanisms, hence can be used to identify new ice. Orthogonal backscatter coefficients and polarimetric decomposition parameters provide different information, yet their combination offers clues to better identify ice conditions and investigate questions about scattering mechanisms.

Towards more robust hydroacoustic estimates of fish abundance in the presence of pelagic macroinvertebrates

The inclusion of unwanted targets in hydroacoustic surveys biases estimates of fish abundance. Thus, knowledge of frequency-dependent responses of unwanted targets (e.g., pelagic macroinvertebrates) can help ensure that transducer frequencies are used that minimize this bias. We determined how fish density estimates varied across multiple frequencies when the larval stage of a midge, Chaoborus, was present in the water column. We hypothesized that fish density estimates would increase with increasing transducer frequency, owing to greater backscattering by Chaoborus at higher frequencies than lower ones, which allows it to be included with the backscattering caused by fish. We found that fish density estimates were always greater at higher frequencies (e.g., 120 and 200 kHz) compared to a lower one (70 kHz) in several productive north-temperate reservoirs. Furthermore, pairwise comparisons of total (i.e., fish plus Chaoborus) backscattering showed that significantly more backscattering occurred at higher rather than lower frequencies. We also found that fish density estimates varied between spring and summer, partially owing to inter-seasonal size variation in Chaoborus that influenced its backscattering. Beyond demonstrating why the presence of pelagic macroinvertebrates needs to be considered when estimating fish abundance with hydroacoustics, we provide methods to identify and reduce this bias.

Estimation of Surface Soil Moisture during Corn Growth Stage from SAR and Optical Data Using a Combined Scattering Model

As an indispensable ecological parameter, surface soil moisture (SSM) is of great significance for understanding the growth status of vegetation. The cooperative use of synthetic aperture radar (SAR) and optical data has the advantage of considering both vegetation and underlying soil scattering information, which is suitable for SSM monitoring of vegetation areas. The main purpose of this paper is to establish an inversion approach using Terra-SAR and Landsat-7 data to estimate SSM at three different stages of corn growth in the irrigated area. A combined scattering model that can adequately represent the scattering characteristics of the vegetation coverage area is proposed by modifying the water cloud model (WCM) to reduce the effect of vegetation on the total SAR backscattering. The backscattering from the underlying soil is expressed by an empirical model with good performance in X-band. The modified water cloud model (MWCM) as a function of normalized differential vegetation index (NDVI) considers the contribution of vegetation to the backscattering signal. An inversion technique based on artificial neural network (ANN) is used to invert the combined scattering model for SSM estimation. The inversion method is established and verified using datasets of three different growth stages of corn. Using the proposed method, we estimate the SSM with a correlation coefficient R ≥ 0.72 and root-mean-square error R M S E ≤ 0.043 cm 3 /cm 3 at the emergence stage, with R ≥ 0.87 and R M S E ≤ 0.046 cm 3 /cm 3 at the trefoil stage and with R ≥ 0.70 and R M S E ≤ 0.064 cm 3 /cm 3 at the jointing stage. The results suggest that the method proposed in this paper has operational potential in estimating SSM from Terra-SAR and Landsat-7 data at different stages of early corn growth.

A global compilation of in situ aquatic high spectral resolution inherent and apparent optical property data for remote sensing applications.

Light emerging from natural water bodies and measured by radiometers contains information about the local type and concentrations of phytoplankton, non-algal particles and colored dissolved organic matter in the underlying waters. An increase in spectral resolution in forthcoming satellite and airborne remote sensing missions is expected to lead to new or improved capabilities for characterizing aquatic ecosystems. Such upcoming missions include NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission; the NASA Surface Biology and Geology designated observable mission; and NASA Airborne Visible/Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) airborne missions. In anticipation of these missions, we present an organized dataset of geographically diverse, quality-controlled, high spectral resolution inherent and apparent optical property (IOP-AOP) aquatic data. The data are intended to be of use to increase our understanding of aquatic optical properties, to develop aquatic remote sensing data product algorithms, and to perform calibration and validation activities for forthcoming aquatic-focused imaging spectrometry missions. The dataset is comprised of contributions from several investigators and investigating teams collected over a range of geographic areas and water types, including inland waters, estuaries, and oceans. Specific in situ measurements include remote-sensing reflectance, irradiance reflectance, and coefficients describing particulate absorption, particulate attenuation, non-algal particulate absorption, colored dissolved organic matter absorption, phytoplankton absorption, total absorption, total attenuation, particulate backscattering, and total backscattering. The dataset can be downloaded from https://doi.org/10.1594/PANGAEA.902230 (Casey et al., 2019).

Optical interference coatings measurement problem 2019 [Invited

The 2019 Optical Interference Coatings measurement problem comprised the determination of the total backscattering, forward scattering, reflectance, and transmittance spectra of a multilayer system.

Experimental Estimates of Optical Backscattering Associated With Submicron Particles in Clear Oceanic Waters

AbstractThe volume scattering functions for bulk and two submicron size fractions (passing through 0.7 μm GF/F and 0.2 μm membrane filters) were measured in the North Pacific Ocean using a LISST‐VSF to assess the contributions by submicron particles to the overall particle scattering. The contribution by submicron particles increased generally with scattering angle and peaked around 110°. The total backscattering by both submicron fractions did not vary, but that by larger particles increased, with the trophic level. Consequently, the fractional backscattering contribution by submicron particles decreased from approximately 50% to 30% as the chlorophyll‐a concentration increased from &lt;0.1 to 0.3 mg m−3. Despite the experiment covering a limited range of trophic levels, our results confirm that backscattering by submicron particles in clear ocean waters is significant and seems to form a background independent of the backscattering by larger particles.

An OLCI-based algorithm for semi-empirically partitioning absorption coefficient and estimating chlorophyll a concentration in various turbid case-2 waters

Accurate remote assessment of phytoplankton chlorophyll-a (Chla) concentration in turbid case-2 waters is a challenge, owing largely to terrestrial substances (such as minerals and humus) that are optically significant but do not co-vary with phytoplankton. Here, we propose an improved Quasi-Analytical Algorithm (QAA) (denoted as TC2) for retrieving Chla concentrations from remote sensing reflectance (Rrs(λ)) which can be applied to Sentinel-3 Ocean and Land Colour Instrument (OLCI) images in turbid case-2 waters. TC2 has two main extensions when compared with QAA. First, TC2 makes an additional assumption to separate the total non-water absorption at 665 nm (anw(665)) into phytoplankton absorption (aph(665)) and yellow matter (aym(665)), which is the sum of colored dissolved matter (CDOM) and detritus. Second, for selecting the position of the near-infrared (NIR) band which is used to estimate the signal of total backscattering coefficient (bb(λ0)) at QAA reference band (λ0), we take into account the assumption that the absorption of pure water should be dominant at this band, as well as the impact of the signal-to-noise ratio (SNR) in the NIR band on the Chla concentration estimating model. When applied to in situ Rrs(λ) and OLCI match-up Rrs(λ) data in this study, TC2 provided more accurate Chla estimation than previous Cha concentration retrieval algorithms for turbid case-2 waters. TC2 has the potential for use as a simple and effective algorithm for monitoring Chla concentrations in the turbid case-2 waters at a global scale from space.

Cloud Aerosol Transport System (CATS) 1064 nm Calibration and Validation.

The Cloud-Aerosol Transport System (CATS) lidar on board the International Space Station (ISS) operated from 10 February 2015 to 30 October 2017 providing range-resolved vertical backscatter profiles of Earth's atmosphere at 1064 and 532 nm. The CATS instrument design and ISS orbit lead to a higher 1064 nm signal-to-noise ratio than previous space-based lidars, allowing for direct atmospheric calibration of the 1064 nm signals. Nighttime CATS Version 3-00 data were calibrated by scaling the measured data to a model of the expected atmospheric backscatter between 22 and 26 km above mean sea level (AMSL). The CATS atmospheric model is constructed using molecular backscatter profiles derived from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) re-analysis data and aerosol scattering ratios measured by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The nighttime normalization altitude region was chosen to simultaneously minimize aerosol loading and variability within the CATS data frame, which extends from 28 km to -2 km AMSL. Daytime CATS Version 3-00 data were calibrated through comparisons with nighttime measurements of the layer integrated attenuated total backscatter (iATB) from strongly scattering, rapidly attenuating opaque cirrus clouds. The CATS nighttime 1064 nm attenuated total backscatter (ATB) uncertainties for clouds and aerosols are primarily related to the uncertainties in the CATS nighttime calibration technique, which are estimated to be ~9%. Median CATS V3-00 1064 nm ATB relative uncertainty at night within cloud and aerosol layers is 7%, slightly lower than these calibration uncertainty estimates. CATS median daytime 1064 nm ATB relative uncertainty is 21% in cloud and aerosol layers, similar to the estimated 16-18% uncertainty in the CATS daytime cirrus cloud calibration transfer technique. Coincident daytime comparisons between CATS and the Cloud Physics Lidar (CPL) during the CATS-CALIPSO Airborne Validation Experiment (CCAVE) project show good agreement in mean ATB profiles for clear-air regions. Eight nighttime comparisons between CATS and the PollyXT ground based lidars also show good agreement in clear-air regions between 3-12 km, with CATS having a mean ATB of 19.7 % lower than PollyXT. Agreement between the two instruments (~7%) is even better within an aerosol layer. Six-month comparisons of nighttime ATB values between CATS and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) also show that iATB comparisons of opaque cirrus clouds agree to within 19%. Overall, CATS has demonstrated that direct calibration of the 1064 nm channel is possible from a space based lidar using the atmospheric normalization technique.

An integrated approach to estimate surface soil moisture in agricultural lands

Sentinel-1 and Landsat-8 data were used to retrieve soil moisture from top soil surface (0–5 cm depth) at agricultural land (area under wheat crop). After pre-processing of satellite data and removal of vegetation influence (σ°veg) using Water Cloud Model (WCM), total backscattering coefficient (σ°total) and Normalized Difference Vegetation Index (NDVI) were used to simulate backscattering from soil (σ°soil). Modified Dubois Model (MDM) and Topp's Model were used to retrieve soil moisture using ε. Further, modelled soil moisture was evaluated using in situ soil moisture measurements and a Time Domain Reflectometer during Sentinel-1 overpass (24 January, 25 February and 13 March 2018). Statistical tests showed that an integrated approach has potential to improve soil moisture estimates over the vegetated/cropped area for agricultural and hydrological studies.

Acoustic Assessment of the Micronekton Community on the Chatham Rise, New Zealand, Using a Semi-Automated Approach

Micronekton are a key component of the pelagic food web of the Chatham Rise east of New Zealand. The Chatham Rise is an important fishing area for hoki (Macruronus novaezelandiae), New Zealand’s largest finfish fishery, and a predator on mesopelagic fish. Four fisheries oceanographic voyages provided multi-frequency acoustic data (18, 38, 70 120 and 200 kHz) and midwater trawls, which were used to define a classification tree to separate micronektonic organisms. We carried out validation and sensitivity analyses that showed that we were able to classify pearlside (Maurolicus australis) and euphausiids. Other mesopelagic targets (mainly myctophids) were classified together based on their acoustic frequency response. Using scripting in the open-source software ESP3, we applied our classification tree to an independent time series of acoustic data from trawl surveys on the Chatham Rise between 2009 and 2018, that was not used for model development or validation. Our methodology allowed us to study temporal and spatial patterns of M. australis, euphausiids, and total backscatter in the water column. Total backscatter associated with micronekton has varied over the last ten years, with no clear trend. The abundance of euphausiids showed a significant decreasing trend over the last ten years. Abundance of M. australis also decreased since 2012, though this was not significant. This work contributes to on-going efforts to monitor and detect changes in the pelagic ecosystems.

Retrieving Surface Soil Moisture over Wheat and Soybean Fields during Growing Season Using Modified Water Cloud Model from Radarsat-2 SAR Data

Surface soil moisture (SSM) retrieval over agricultural fields using synthetic aperture radar (SAR) data is often obstructed by the vegetation effects on the backscattering during the growing season. This paper reports the retrieval of SSM from RADARSAT-2 SAR data that were acquired over wheat and soybean fields throughout the 2015 (April to October) growing season. The developed SSM retrieval algorithm includes a vegetation-effect correction. A method that can adequately represent the scattering behavior of vegetation-covered area was developed by defining the backscattering from vegetation and the underlying soil individually to remove the effect of vegetation on the total SAR backscattering. The Dubois model was employed to describe the backscattering from the underlying soil. A modified Water Cloud Model (MWCM) was used to remove the effect of backscattering that is caused by vegetation canopy. SSM was derived from an inversion scheme while using the dual co-polarizations (HH and VV) from the quad polarization RADARSAT-2 SAR data. Validation against ground measurements showed a high correlation between the measured and estimated SSM (R2 = 0.71, RMSE = 4.43 vol.%, p &lt; 0.01), which suggested an operational potential of RADARSAT-2 SAR data on SSM estimation over wheat and soybean fields during the growing season.

Analyzing the atmospheric boundary layer using high-order moments obtained from multiwavelength lidar data: impact of wavelength choice

Abstract. The lowest region of the troposphere is a turbulent layer known as the atmospheric boundary layer (ABL) and characterized by high daily variability due to the influence of surface forcings. This is the reason why detecting systems with high spatial and temporal resolution, such as lidar, have been widely applied for researching this region. In this paper, we present a comparative analysis on the use of lidar-backscattered signals at three wavelengths (355, 532 and 1064 nm) to study the ABL by investigating the high-order moments, which give us information about the ABL height (derived by the variance method), aerosol layer movement (skewness) and mixing conditions (kurtosis) at several heights. Previous studies have shown that the 1064 nm wavelength, due to the predominance of particle signature in the total backscattered atmospheric signal and practically null presence of molecular signal (which can represent noise in high-order moments), provides an appropriate description of the turbulence field, and thus in this study it was considered a reference. We analyze two case studies that show us that the backscattered signal at 355 nm, even after applying some corrections, has a limited applicability for turbulence studies using the proposed methodology due to the strong contribution of the molecular signature to the total backscatter signal. This increases the noise associated with the high-order profiles and, consequently, generates misinformation. On the other hand, the information on the turbulence field derived from the backscattered signal at 532 nm is similar to that obtained at 1064 nm due to the appropriate attenuation of the noise, generated by molecular component of backscattered signal by the application of the corrections proposed.