scholarly journals Examining the Links between Multi-Frequency Multibeam Backscatter Data and Sediment Grain Size

2021 ◽  
Vol 13 (8) ◽  
pp. 1539
Author(s):  
Robert Mzungu Runya ◽  
Chris McGonigle ◽  
Rory Quinn ◽  
John Howe ◽  
Jenny Collier ◽  
...  
Keyword(s):  
Grain Size ◽  
Mean Squared Error ◽  
Explanatory Power ◽  
Low Frequency ◽  
Ground Truth ◽  
Single Frequency ◽  
Sediment Grain Size ◽  
Ground Truth Data ◽  
Marine Habitats ◽  
The Mean

Acoustic methods are routinely used to provide broad scale information on the geographical distribution of benthic marine habitats and sedimentary environments. Although single-frequency multibeam echosounder surveys have dominated seabed characterisation for decades, multifrequency approaches are now gaining favour in order to capture different frequency responses from the same seabed type. The aim of this study is to develop a robust modelling framework for testing the potential application and value of multifrequency (30, 95, and 300 kHz) multibeam backscatter responses to characterize sediments’ grain size in an area with strong geomorphological gradients and benthic ecological variability. We fit a generalized linear model on a multibeam backscatter and its derivatives to examine the explanatory power of single-frequency and multifrequency models with respect to the mean sediment grain size obtained from the grab samples. A strong and statistically significant (p < 0.05) correlation between the mean backscatter and the absolute values of the mean sediment grain size for the data was noted. The root mean squared error (RMSE) values identified the 30 kHz model as the best performing model responsible for explaining the most variation (84.3%) of the mean grain size at a statistically significant output (p < 0.05) with an adjusted r2 = 0.82. Overall, the single low-frequency sources showed a marginal gain on the multifrequency model, with the 30 kHz model driving the significance of this multifrequency model, and the inclusion of the higher frequencies diminished the level of agreement. We recommend further detailed and sufficient ground-truth data to better predict sediment properties and to discriminate benthic habitats to enhance the reliability of multifrequency backscatter data for the monitoring and management of marine protected areas.

scholarly journals Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction Index

2021 ◽  
Vol 13 (9) ◽  
pp. 5274
Author(s):  
Xinyang Yu ◽  
Younggu Her ◽  
Xicun Zhu ◽  
Changhe Lu ◽  
Xuefei Li
Keyword(s):  
Arable Land ◽  
Ground Truth ◽  
Northwest China ◽  
Hexi Corridor ◽  
Ground Truth Data ◽  
Land Protection ◽  
Promising Tool ◽  
Study Results ◽  
Multi Temporal ◽  
The Mean

Development of a high-accuracy method to extract arable land using effective data sources is crucial to detect and monitor arable land dynamics, servicing land protection and sustainable development. In this study, a new arable land extraction index (ALEI) based on spectral analysis was proposed, examined by ground truth data, and then applied to the Hexi Corridor in northwest China. The arable land and its change patterns during 1990–2020 were extracted and identified using 40 Landsat TM/OLI images acquired in 1990, 2000, 2010, and 2020. The results demonstrated that the proposed method can distinguish arable land areas accurately, with the User’s (Producer’s) accuracy and overall accuracy (kappa coefficient) exceeding 0.90 (0.88) and 0.89 (0.87), respectively. The mean relative error calculated using field survey data obtained in 2012 and 2020 was 0.169 and 0.191, respectively, indicating the feasibility of the ALEI method in arable land extracting. The study found that arable land area in the Hexi Corridor was 13217.58 km2 in 2020, significantly increased by 25.33% compared to that in 1990. At 10-year intervals, the arable land experienced different change patterns. The study results indicate that ALEI index is a promising tool used to effectively extract arable land in the arid area.

A Theoretical Framework for Estimating Swarm Success Probability Using Scouts

2010 ◽  
Vol 1 (4) ◽  
pp. 17-45
Author(s):  
Antons Rebguns ◽  
Diana F. Spears ◽  
Richard Anderson-Sprecher ◽  
Aleksey Kletsov
Keyword(s):  
Mean Squared Error ◽  
Success Probability ◽  
Ground Truth ◽  
Theoretical Framework ◽  
Bernoulli Trials ◽  
Lennard Jones ◽  
Squared Error ◽  
The Mean ◽  
The Bayesian Approach ◽  
Bayesian Formula

This paper presents a novel theoretical framework for swarms of agents. Before deploying a swarm for a task, it is advantageous to predict whether a desired percentage of the swarm will succeed. The authors present a framework that uses a small group of expendable “scout” agents to predict the success probability of the entire swarm, thereby preventing many agent losses. The scouts apply one of two formulas to predict – the standard Bernoulli trials formula or the new Bayesian formula. For experimental evaluation, the framework is applied to simulated agents navigating around obstacles to reach a goal location. Extensive experimental results compare the mean-squared error of the predictions of both formulas with ground truth, under varying circumstances. Results indicate the accuracy and robustness of the Bayesian approach. The framework also yields an intriguing result, namely, that both formulas usually predict better in the presence of (Lennard-Jones) inter-agent forces than when their independence assumptions hold.

scholarly journals A Multispectral Bayesian Classification Method for Increased Acoustic Discrimination of Seabed Sediments Using Multi-Frequency Multibeam Backscatter Data

Geosciences ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. 455 ◽  
Author(s):  
Timo Gaida ◽  
Tengku Tengku Ali ◽  
Mirjam Snellen ◽  
Alireza Amiri-Simkooei ◽  
Thaiënne van Dijk ◽  
...  
Keyword(s):  
Ground Truth ◽  
Single Frequency ◽  
Qualitative Comparison ◽  
Ground Truth Data ◽  
Geological Interpretation ◽  
Additional Information ◽  
Triple Frequency ◽  
Acoustic Discrimination ◽  
Multiple Frequencies ◽  
Seabed Sediments

Multi-frequency backscatter data collected from multibeam echosounders (MBESs) is increasingly becoming available. The ability to collect data at multiple frequencies at the same time is expected to allow for better discrimination between seabed sediments. We propose an extension of the Bayesian method for seabed classification to multi-frequency backscatter. By combining the information retrieved at single frequencies we produce a multispectral acoustic classification map, which allows us to distinguish more seabed environments. In this study we use three triple-frequency (100, 200, and 400 kHz) backscatter datasets acquired with an R2Sonic 2026 in the Bedford Basin, Canada in 2016 and 2017 and in the Patricia Bay, Canada in 2016. The results are threefold: (1) combining 100 and 400 kHz, in general, reveals the most additional information about the seabed; (2) the use of multiple frequencies allows for a better acoustic discrimination of seabed sediments than single-frequency data; and (3) the optimal frequency selection for acoustic sediment classification depends on the local seabed. However, a quantification of the benefit using multiple frequencies cannot clearly be determined based on the existing ground-truth data. Still, a qualitative comparison and a geological interpretation indicate an improved discrimination between different seabed environments using multi-frequency backscatter.

Local scour of cohesive beds downstream of a rigid apron

2017 ◽  
Vol 44 (11) ◽  
pp. 935-944 ◽  
Author(s):  
Hossein Hamidifar ◽  
Mohammad Hossein Omid
Keyword(s):  
Grain Size ◽  
Empirical Equation ◽  
Scour Depth ◽  
Removal Mechanism ◽  
Sediment Grain Size ◽  
Scour Hole ◽  
Hole Profile ◽  
The Mean ◽  
New Equation ◽  
Individual Particles

In this paper, the physics of scour hole in a mixed sand–clay bed downstream of an apron is studied experimentally. Seven combinations of sand–clay mixtures including clay contents, Cc, ranging from 0 to 0.4 were used. The results show that Cc = 0.4 can reduce the maximum scour depth, εm, up to about 80% for all the densimetric Froude numbers in the range of the present study. An empirical equation has been proposed for calculation of εm in sand–clay mixtures with the mean error of 0.12. The removal mechanism of sediments from the bed was different based on the Cc. For low clay contents, i.e., Cc ≤ 15%, individual particles were detached from the bed. At higher Cc, clusters of particles were separated and moved downstream with the flow. A new equation has been proposed to predict the dimensionless scour hole profile in mixed sand–clay sediments. Dimensionless graphs have been presented for incorporating the effect of tailwater depth and sediment grain size on the main characteristics lengths in sand–clay mixtures.

scholarly journals Methods for Earth-Observing Satellite Surface Reflectance Validation

2019 ◽  
Vol 11 (13) ◽  
pp. 1543
Author(s):  
Badawi ◽  
Helder ◽  
Leigh ◽  
Jing
Keyword(s):  
Solar Spectrum ◽  
Ground Truth ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Radiometric Calibration ◽  
Ground Truth Data ◽  
Initial Validation ◽  
Reliable Performance ◽  
The Mean ◽  
The U.S

In this study an initial validation of the Landsat 8 (L8) Operational Land Imager (OLI) Surface Reflectance (SR) product was performed. The OLI SR product is derived from the L8 Top-of-Atmosphere product via the Landsat Surface Reflectance Code (LaSRC) software and generated by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The goal of this study is to develop and evaluate proper validation methodology for the OLI L2 SR product. Validation was performed using near-simultaneous ground truth SR measurements during Landsat 8 overpasses at 13 sites located in the U.S., Brazil, Chile and France. The ground truth measurements consisted of field spectrometer measurements, automated hyperspectral ground measurements operated by the Radiometric Calibration Network (RadCalNet) and derived SR measurements from Airborne Observation Platforms (AOP) operated by the National Ecological Observatory Network (NEON). The 13 sites cover a broad range of 0–0.5 surface reflectance units across the reflective solar spectrum. Results show that the mean reflectance difference between OLI L2 SR products and ground truth measurements for the 13 validation sites and all bands was under 2.5%. The largest uncertainties of 11% and 8% were found in the CA and Blue bands, respectively; whereas, the longer wavelength bands were within 4% or less. Results consistently indicated similarity between the OLI L2 SR product and ground truth data, especially in longer wavelengths over dark and bright targets, while less reliable performance was observed in shorter wavelengths and sparsely vegetated targets.

scholarly journals Sentinel 1A SAR Backscattering Signature of Maize and Cotton Crops

2017 ◽  
Vol 104 (.1-.4) ◽  
Author(s):  
Kumaraperumal R ◽  
◽  
Shama M ◽  
Balaji Kannan ◽  
Ragunath K P ◽  
...  
Keyword(s):  
Tamil Nadu ◽  
Ground Truth ◽  
Backscattering Coefficient ◽  
Ground Truth Data ◽  
Crop Monitoring ◽  
Multi Temporal ◽  
The Mean ◽  
Sar Data ◽  
Remote Sensing Techniques ◽  
Crop Discrimination

Crop discrimination is a key issue for agricultural monitoring using remote sensing techniques. Synthetic Aperture Radar (SAR) data are advantageous for crop monitoring and classification because of their all-weather imaging capabilities. The multi-temporal Sentinel 1A SAR data was acquired from 08th August, 2015 to 23rd January, 2016 at 12 days interval covering the extent of Perambalur district of Tamil Nadu. Both the Vertical - Vertical (VV) and Vertical-Horizontal (VH) polarized data are compared. The ground truth data collection was performed for cotton and maize during the vegetative, flowering and harvesting stages. The temporal backscattering coefficient (σ0 ) for cotton and maize are extracted using the training datasets. The mean backscattering values for cotton during the entire cropping period ranges from -10.58 dB to -6.28 dB and -20.59 dB to -14.53 dB for VV and VH polarized data respectively, and for maize it ranges from -11.08 dB to -7.07 dB and -19.85 dB to -14.14 dB for VV and VH polarized data respectively.

A Theoretical Framework for Estimating Swarm Success Probability Using Scouts

2012 ◽  
pp. 277-307
Author(s):  
Antons Rebguns ◽  
Diana F. Spears ◽  
Richard Anderson-Sprecher ◽  
Aleksey Kletsov
Keyword(s):  
Bayesian Approach ◽  
Mean Squared Error ◽  
Success Probability ◽  
Ground Truth ◽  
Theoretical Framework ◽  
Experimental Results ◽  
Squared Error ◽  
The Mean ◽  
The Bayesian Approach ◽  
Bayesian Formula

This paper presents a novel theoretical framework for swarms of agents. Before deploying a swarm for a task, it is advantageous to predict whether a desired percentage of the swarm will succeed. The authors present a framework that uses a small group of expendable “scout” agents to predict the success probability of the entire swarm, thereby preventing many agent losses. The scouts apply one of two formulas to predict – the standard Bernoulli trials formula or the new Bayesian formula. For experimental evaluation, the framework is applied to simulated agents navigating around obstacles to reach a goal location. Extensive experimental results compare the mean-squared error of the predictions of both formulas with ground truth, under varying circumstances. Results indicate the accuracy and robustness of the Bayesian approach. The framework also yields an intriguing result, namely, that both formulas usually predict better in the presence of (Lennard-Jones) inter-agent forces than when their independence assumptions hold.

PHYSICAL AND CHEMICAL RECOVERY OF INTERTIDAL AND SHALLOW SUBTIDAL SEDIMENTS IMPACTED BY THE ARCO ANCHORAGE OIL SPILL, EDIZ HOOK, WASHINGTON

1989 ◽  
Vol 1989 (1) ◽  
pp. 487-491 ◽  
Author(s):  
James A. Miller
Keyword(s):  
Grain Size ◽  
Crude Oil ◽  
Oil Spill ◽  
Oil Content ◽  
Sediment Chemistry ◽  
Intertidal Sediments ◽  
Sediment Grain Size ◽  
Oil Concentration ◽  
Shallow Subtidal ◽  
The Mean

ABSTRACT The December 21, 1985 Arco Anchorage crude oil spill affected approximately 7,000 feet of the sheltered, south-facing shore of Ediz Hook, Washington. Some of the stranded crude oil penetrated sand and gravel sediments in the intertidal zone. An aggressive beach agitation program was implemented between February and April 1986 to remove most of the oil trapped within the intertidal sediments. Post-cleanup monitoring activities between August 1986 and January 1988 determined the crude oil content of intertidal and shallow subtidal sediments at five elevations along thirteen sampling transects. Sediment samples were also obtained for laboratory grain-size testing at five of these transects. Post-cleanup monitoring of sediment chemistry indicated a consistent trend of decreasing crude oil content of the intertidal sediments between March/April 1986 (mean oil concentration 670 ppm) and July 1987 (mean oil concentration 110 ppm). A similar pattern was observed for the shallow subtidal sediments, where the mean crude oil concentration decreased from 460 ppm in August 1986 to 110 ppm in July 1987. The mean oil content of these sediments increased somewhat after July 1987, indicating probable hydrocarbon inputs from other sources. Chromatograms of the hydrocarbons in the sediments after July 1987 were dissimilar to chromatograms for the unweathered oil from the Arco Anchorage. The grain-size distribution of the sediments changed relatively little during the post-cleanup monitoring period, reflecting the relatively sheltered nature of the study area. However, the minor changes observed in sediment grain size suggest that gradual redistribution of intertidal and subtidal sediment occurred along the south shore of Ediz Hook during the monitoring program.

scholarly journals Measurement and Analysis of Acoustic Backscatter Value for Bottom Classification of waters Tidung Island

2021 ◽  
Vol 5 (2) ◽  
pp. 544-550
Author(s):  
M Hasbi Sidqi Alajuri ◽  
Henry M Manik ◽  
Sri Pujiyati
Keyword(s):  
Grain Size ◽  
Single Frequency ◽  
Acoustic Backscatter ◽  
Sediment Grain Size ◽  
Single Beam ◽  
Measurement And Analysis ◽  
Sediment Sampling ◽  
Backscattering Strength ◽  
Bottom Classification

Sediment in a water has an important role for organisms, namely as a habitat, a place for foraging for food, and a place for spawning. These sediment can affect the composition of organisms in the water. The purpose of this study is to calculate the value of acoustic backscatter for the classification of the bottom of the water and to see the effect of sediment grain size on the backscatter value obtained from a single beam acoustic instrument. Data collection was carried out from 10 to 12 June 2021 in the water of Tidung Island, Seribu Islands, using the SIMRAD EK-15 single beam, single frequency 200 kHz instrument. Sediment sampling was carried out at 13 stations. The results showed that the waters of Tidung Island were dominated by muddy substrate which was classified based on the Surface Backscattering Strength (SS) value. Meanwhile, the grain size of the sediment affects the SVb value, where the large the grain size of the bottom sediment, the SVb value will be higher. The higher SVb value the SS value will be higher. Keywords: Bottom Classification, Acoustic Backscatter, Tidung Island

Automatic Estimation of Soil Biochar Quantity via Hyperspectral Imaging

2019 ◽  
pp. 1608-1635
Author(s):  
Lei Tong ◽  
Jun Zhou ◽  
Shahla Hosseini Bai ◽  
Chengyuan Xu ◽  
Yuntao Qian ◽  
...  
Keyword(s):  
Polynomial Regression ◽  
Estimation Method ◽  
Ground Truth ◽  
Infrared Light ◽  
Ground Truth Data ◽  
Hyperspectral Unmixing ◽  
Term Functions ◽  
The Mean ◽  
Mean Square Errors

Biochar soil amendment is globally recognized as an emerging approach to mitigate CO2 emissions and increase crop yield. Because the durability and changes of biochar may affect its long term functions, it is important to quantify biochar in soil after application. In this chapter, an automatic soil biochar estimation method is proposed by analysis of hyperspectral images captured by cameras that cover both visible and infrared light wavelengths. The soil image is considered as a mixture of soil and biochar signals, and then hyperspectral unmixing methods are applied to estimate the biochar proportion at each pixel. The final percentage of biochar can be calculated by taking the mean of the proportion of hyperspectral pixels. Three different models of unmixing are described in this chapter. Their experimental results are evaluated by polynomial regression and root mean square errors against the ground truth data collected in the environmental labs. The results show that hyperspectral unmixing is a promising method to measure the percentage of biochar in the soil.

Sign in / Sign up

Export Citation Format

Share Document