Monitoring Multi-Depth Suspended Sediment Loads in Lake Erie's Maumee River Using Landsat 8 and Unmanned Aerial Vehicle (UAV) Imagery PDF Download
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Author: Matthew David Larson
Publisher:
ISBN:
Category : Remote sensing
Languages : en
Pages : 292
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Book Description
Suspended sediment in water bodies is a considerable environmental concern. Traditional sampling methods for suspended sediment are time-consuming as they involve vertical and spatial point-sampling. Remote sensing (RS) is an alternative to in-situ measurements and it is capable of monitoring suspended sediments in shallow waters spatially at large scales. Use of RS technology to map suspended sediment concentrations (SSC) depends on sensor type and its capability `to see through' the water column at given surface and water column conditions. This study examined the capabilities of RS technology to spatially quantify SSC at multi-depth intervals within the Maumee River, Ohio. Water samples were collected and analyzed for SSC in May, June, and October at depths of 0.5 ft., 2 ft., 3 ft., and 6 ft. Landsat 8, surface hyperspectral measurements (aggregated to simulate sensors), and MicaSense Sequoia camera onboard an unmanned aerial vehicle (UAV) were used. Single spectral bands, ratios, and multiple bands/ratios were examined in developing algorithms relating RS and field measurements. Linear regression models provided the best relationship for surface, Landsat 8, and UAV data throughout all depths. A 6 ft. depth had the highest correlation for surface (R2adj=0.93) and Landsat 8 (R2adj=0.79) data. For UAV a 3 ft. depth provided the best relationship (R2adj=0.52). Band ratios using nonlinear fitting provided good relationships (surface R2adj=0.72 and Landsat 8 R2adj=0.54) at 6 ft. as well. Results showed Landsat 8 more accurately measured suspended solids at 6 ft. than shallower depths. Regression equations and band ratios showed increasing relationships with SSC with increasing depth for Landsat 8 with an exception for 3 ft., which can occur due to stratification. UAV measurements produced best results for 3 ft. Algorithms with best results included ultra blue, blue, and green bands which are not typically used for quantifying SSC. Shorter wavelength bands (400 nm-550 nm) should be considered in waters with small suspended sediments as those found in the Maumee River. Equations were not transferable from one day to another. It is surmised that concentration thresholds of 40-60 mg/L play a role in equation derivation, as well as meteorological factors.
Author: Matthew David Larson
Publisher:
ISBN:
Category : Remote sensing
Languages : en
Pages : 292
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Book Description
Suspended sediment in water bodies is a considerable environmental concern. Traditional sampling methods for suspended sediment are time-consuming as they involve vertical and spatial point-sampling. Remote sensing (RS) is an alternative to in-situ measurements and it is capable of monitoring suspended sediments in shallow waters spatially at large scales. Use of RS technology to map suspended sediment concentrations (SSC) depends on sensor type and its capability `to see through' the water column at given surface and water column conditions. This study examined the capabilities of RS technology to spatially quantify SSC at multi-depth intervals within the Maumee River, Ohio. Water samples were collected and analyzed for SSC in May, June, and October at depths of 0.5 ft., 2 ft., 3 ft., and 6 ft. Landsat 8, surface hyperspectral measurements (aggregated to simulate sensors), and MicaSense Sequoia camera onboard an unmanned aerial vehicle (UAV) were used. Single spectral bands, ratios, and multiple bands/ratios were examined in developing algorithms relating RS and field measurements. Linear regression models provided the best relationship for surface, Landsat 8, and UAV data throughout all depths. A 6 ft. depth had the highest correlation for surface (R2adj=0.93) and Landsat 8 (R2adj=0.79) data. For UAV a 3 ft. depth provided the best relationship (R2adj=0.52). Band ratios using nonlinear fitting provided good relationships (surface R2adj=0.72 and Landsat 8 R2adj=0.54) at 6 ft. as well. Results showed Landsat 8 more accurately measured suspended solids at 6 ft. than shallower depths. Regression equations and band ratios showed increasing relationships with SSC with increasing depth for Landsat 8 with an exception for 3 ft., which can occur due to stratification. UAV measurements produced best results for 3 ft. Algorithms with best results included ultra blue, blue, and green bands which are not typically used for quantifying SSC. Shorter wavelength bands (400 nm-550 nm) should be considered in waters with small suspended sediments as those found in the Maumee River. Equations were not transferable from one day to another. It is surmised that concentration thresholds of 40-60 mg/L play a role in equation derivation, as well as meteorological factors.
Author: Donna N. Myers
Publisher:
ISBN:
Category : Conservation tillage
Languages : en
Pages : 52
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Book Description
Author: Mark Emil Seidelmann
Publisher:
ISBN:
Category :
Languages : en
Pages : 144
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Book Description
Author: Steven Sobieszczyk
Publisher:
ISBN:
Category : Landslides
Languages : en
Pages : 262
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Book Description
The Little North Santiam River Basin is a 111-square mile watershed located in the Cascade Range of western Oregon. The Little North Santiam River is a major tributary to the North Santiam River, which is the primary source of drinking water for Salem, Oregon and surrounding communities. Consequently, water quality conditions in the Little North Santiam River, such as high turbidity, affect treatment and delivery of the drinking water. Between 2001 and 2008, suspended-sediment loads from the Little North Santiam River accounted for 69% of the total suspended-sediment load that passed the treatment plant. Recent studies suggest that much of this sediment originates from landslide activity in the basin. Using airborne Light Detection and Ranging (LiDAR)-derived imagery, 401 landslides were mapped in the Little North Santiam River Basin. Landslide types vary by location, with deep-seated earth flows and earth slumps common in the lower half of the basin and channelized debris flows prominent in the upper basin. Over 37% of the lower basin shows evidence of landslide activity compared to just 4% of the upper basin. Instream turbidity monitoring and suspended-sediment load estimates during the winter of 2009-2010 demonstrate a similar distribution of sediment transport in the basin. During a 3-month study period, from December 2009 through February 2010, the lower basin supplied 2,990 tons, or 91% of the suspended-sediment load to the Little North Santiam River, whereas the upper basin supplied only 310 tons of sediment. One small 23-acre earth flow in the lower basin, the Evans Creek Landslide, supplied 28% of the total suspended-sediment load, even though it only comprises 0.0004% of the basin. The Evans Creek Landslide is an active earth flow that has been moving episodically since at least 1945, with surges occurring between 1945 and 1955, 1970 and 1977, in February 1996, and in January 2004. Recent erosion of the landslide toe by Evans Creek continues to destabilize the slope, supplying much of the sediment measured in the Little North Santiam River. Over the last 64 years, the average landslide movement rate has been between 5 and 12 feet per year.
Author: Scott D. Hamshaw
Publisher:
ISBN:
Category : Photogrammetry
Languages : en
Pages : 582
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Book Description
Excessive erosion and fine sediment delivery to river corridors and receiving waters degrade aquatic habitat, add to nutrient loading, and impact infrastructure. Understanding the sources and movement of sediment within watersheds is critical for assessing ecosystem health and developing management plans to protect natural and human systems. As our changing climate continues to cause shifts in hydrological regimes (e.g., increased precipitation and streamflow in the northeast U.S.), the development of tools to better understand sediment dynamics takes on even greater importance. In this research, advanced geomatics and machine learning are applied to improve the (1) monitoring of streambank erosion, (2) understanding of event sediment dynamics, and (3) prediction of sediment loading using meteorological data as inputs. Streambank movement is an integral part of geomorphic changes along river corridors and also a significant source of fine sediment to receiving waters. Advances in unmanned aircraft systems (UAS) and photogrammetry provide opportunities for rapid and economical quantification of streambank erosion and deposition at variable scales. We assess the performance of UAS-based photogrammetry to capture streambank topography and quantify bank movement. UAS data were compared to terrestrial laser scanner (TLS) and GPS surveying from Vermont streambank sites that featured a variety of bank conditions and vegetation. Cross-sectional analysis of UAS and TLS data revealed that the UAS reliably captured the bank surface and was able to quantify the net change in bank area where movement occurred. Although it was necessary to consider overhanging bank profiles and vegetation, UAS-based photogrammetry showed significant promise for capturing bank topography and movement at fine resolutions in a flexible and efficient manner. This study also used a new machine-learning tool to improve the analysis of sediment dynamics using three years of high-resolution suspended sediment data collected in the Mad River watershed. A restricted Boltzmann machine (RBM), a type of artificial neural network (ANN), was used to classify individual storm events based on the visual hysteresis patterns present in the suspended sediment-discharge data. The work expanded the classification scheme typically used for hysteresis analysis. The results provided insights into the connectivity and sources of sediment within the Mad River watershed and its tributaries. A recurrent counterpropagation network (rCPN) was also developed to predict suspended sediment discharge at ungauged locations using only local meteorological data as inputs. The rCPN captured the nonlinear relationships between meteorological data and suspended sediment discharge, and outperformed the traditional sediment rating curve approach. The combination of machine-learning tools for analyzing storm-event dynamics and estimating loading at ungauged locations in a river network provides a robust method for estimating sediment production from catchments that informs watershed management.
Author: Marshall L. Strong
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: David C. Roman
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Author: Pierre Y. Julien
Publisher: Cambridge University Press
ISBN: 1107462770
Category : Science
Languages : en
Pages : 527
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Book Description
Completely updated and with three new chapters, this analysis of river dynamics is invaluable for advanced students, researchers and practitioners.
Author: C. Nellemann
Publisher: UNEP/Earthprint
ISBN: 9788277010601
Category : Law
Languages : en
Pages : 80
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Book Description
This report explores the potential for mitigating the impacts of climate change by improved management and protection of marine ecosystems and especially the vegetated coastal habitat, or blue carbon sinks. The objective of this report is to highlight the critical role of the oceans and ocean ecosystems in maintaining our climate and in assisting policy makers to mainstream an oceans agenda into national and international climate change initiatives. While emissions' reductions are currently at the centre of the climate change discussions, the critical role of the oceans and ocean ecosystems has been vastly overlooked.
Author: G. E. Gorman
Publisher: Facet Publishing
ISBN: 1856044726
Category : Business & Economics
Languages : en
Pages : 305
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Book Description
This established text is the only introduction to qualitative research methodologies in the field of library and information management. Its extensive coverage encompasses all aspects of qualitative research work from conception to completion, and all types of study in a variety of settings from multi-site projects to data organization. The book features many case studies and examples, and offers a comprehensive manual of practice designed for LIS professionals. This new edition has been thoroughly revised and includes three new chapters. It has been updated to take account of the substantial growth in the amount and quality of web-based information relevant to qualitative research methods and practice, and the many developments in software applications and resources. The authors have identified a clear need for a new chapter on the evaluation of existing research, as a gateway into new research for information professionals. The final chapter, 'Human Resources In Knowledge Management', takes the form of a model case study, and is an 'ideal' qualitative investigation in an information setting. It exemplifies many of the approaches to qualitative research discussed in earlier chapters. Readership: Directed primarily at the beginner researcher, this book also offers a practical refresher in this important area for the more experienced researcher. It is a useful tool for all practitioners and researchers in information organizations, whether libraries, archives, knowledge management centres, record management centres, or any other type of information service provider.
