scholarly journals An objective approach for feature extraction: distribution analysis and statistical descriptors for scale choice and channel network identification

2011 ◽  
Vol 15 (5) ◽  
pp. 1387-1402 ◽  
Author(s):  
G. Sofia ◽  
P. Tarolli ◽  
F. Cazorzi ◽  
G. Dalla Fontana
Keyword(s):  
Window Size ◽  
Distribution Analysis ◽  
Step Method ◽  
Channel Network ◽  
Standard Score ◽  
Accurate Localization ◽  
Subjective Threshold ◽  
Topographic Attributes ◽  
Score Normalization ◽  
Network Identification

Abstract. A statistical approach to LiDAR derived topographic attributes for the automatic extraction of channel network and for the choice of the scale to apply for parameter evaluation is presented in this paper. The basis of this approach is to use distribution analysis and statistical descriptors to identify channels where terrain geometry denotes significant convergences. Two case study areas with different morphology and degree of organization are used with their 1 m LiDAR Digital Terrain Models (DTMs). Topographic attribute maps (curvature and openness) for various window sizes are derived from the DTMs in order to detect surface convergences. A statistical analysis on value distributions considering each window size is carried out for the choice of the optimum kernel. We propose a three-step method to extract the network based (a) on the normalization and overlapping of openness and minimum curvature to highlight the more likely surface convergences, (b) a weighting of the upslope area according to these normalized maps to identify drainage flow paths and flow accumulation consistent with terrain geometry, (c) the standard score normalization of the weighted upslope area and the use of standard score values as non subjective threshold for channel network identification. As a final step for optimal definition and representation of the whole network, a noise-filtering and connection procedure is applied. The advantage of the proposed methodology, and the efficiency and accurate localization of extracted features are demonstrated using LiDAR data of two different areas and comparing both extractions with field surveyed networks.

scholarly journals Channel network identification from high-resolution DTM: a statistical approach

2010 ◽  
Vol 7 (6) ◽  
pp. 9327-9365
Author(s):  
G. Sofia ◽  
P. Tarolli ◽  
F. Cazorzi ◽  
G. Dalla Fontana
Keyword(s):  
Statistical Approach ◽  
Z Score ◽  
Step Method ◽  
Channel Network ◽  
Accurate Localization ◽  
Digital Terrain ◽  
Subjective Threshold ◽  
Topographic Attributes ◽  
Score Normalization ◽  
Network Identification

Abstract. A statistical approach to LiDAR derived topographic attributes for the automatic extraction of channel network is presented in this paper. The basis of this approach is to use statistical descriptors to identify channel where terrain geometry denotes significant convergences. Two case study areas of different morphology and degree of organization are used with their 1 m LiDAR Digital Terrain Models (DTMs). Topographic attribute maps (curvature and openness) for different window sizes are derived from the DTMs in order to detect surface convergences. For the choice of the optimum kernel size, a statistical analysis on values distributions of these maps is carried out. For the network extraction, we propose a three-step method based (a) on the normalization and overlapping of openness and minimum curvature in order to highlight the more likely surface convergences, (b) a weighting of the upslope area according to such normalized maps in order to identify drainage flow paths and flow accumulation consistent with terrain geometry, (c) the z-score normalization of the weighted upslope area and the use of z-score values as non-subjective threshold for channel network identification. As a final step for optimal definition and representation of the whole network, a noise-filtering and connection procedure is applied. The advantage of the proposed methodology, and the efficiency and accurate localization of extracted features are demonstrated using LiDAR data of two different areas and comparing both extractions with field surveyed networks.

scholarly journals Delineating incised stream sediment sources within a San Francisco Bay tributary basin

2016 ◽  
Author(s):  
Paul Bigelow ◽  
Lee Benda ◽  
Sarah Pearce
Keyword(s):  
Land Use ◽  
San Francisco ◽  
San Francisco Bay ◽  
Sediment Supply ◽  
Spatially Explicit ◽  
Sediment Sources ◽  
Channel Network ◽  
Bay Area ◽  
Reduction Strategies ◽  
Topographic Attributes

Abstract. Erosion and sedimentation pose ubiquitous problems for land and watershed managers, requiring delineation of sediment sources and sinks across landscapes. However, the technical complexity of many spatially explicit erosion models precludes their use by practitioners. To address this critical gap, we demonstrate a contemporary use of applied geomorphometry through a straightforward GIS analysis of sediment sources in the San Francisco Bay Area in California, USA, designed to support erosion reduction strategies. Using 2 m LiDAR DEMs, we delineated the entire river network in the Arroyo Mocho watershed (573 km2) at the scale of ~30 m segments and identified incised landforms using a combination of hillslope gradient and planform curvature. Chronic erosion to the channel network was estimated based on these topographic attributes and the density and size of vegetation, and calibrated to sediment gage data, providing a spatially explicit estimate of sediment yield from incised channels across the basin. Rates of erosion were summarized downstream through the channel network, revealing patterns of sediment supply at the reach scale. Erosion and sediment supply were also aggregated to subbasins, allowing comparative analyses at the scale of tributaries. The erosion patterns delineated using this approach provide land use planners with a robust framework to design erosion reduction strategies. More broadly, the study demonstrates a modern analysis of important geomorphic processes affected by land use that is easily applied by agencies to solve common problems in watersheds, improving the integration between science and environmental management.

scholarly journals Delineating incised stream sediment sources within a San Francisco Bay tributary basin

2016 ◽  
Vol 4 (3) ◽  
pp. 531-547 ◽  
Author(s):  
Paul Bigelow ◽  
Lee Benda ◽  
Sarah Pearce
Keyword(s):  
Land Use ◽  
San Francisco ◽  
San Francisco Bay ◽  
Sediment Supply ◽  
Spatially Explicit ◽  
Sediment Sources ◽  
Channel Network ◽  
Bay Area ◽  
Reduction Strategies ◽  
Topographic Attributes

Abstract. Erosion and sedimentation pose ubiquitous problems for land and watershed managers, requiring delineation of sediment sources and sinks across landscapes. However, the technical complexity of many spatially explicit erosion models precludes their use by practitioners. To address this critical gap, we demonstrate a contemporary use of applied geomorphometry through a straightforward GIS analysis of sediment sources in the San Francisco Bay Area in California, USA, designed to support erosion reduction strategies. Using 2 m lidar digital elevation models, we delineated the entire river network in the Arroyo Mocho watershed (573 km2) at the scale of  ∼  30 m segments and identified incised landforms using a combination of hillslope gradient and planform curvature. Chronic erosion to the channel network was estimated based on these topographic attributes and the size of vegetation, and calibrated to sediment gage data, providing a spatially explicit estimate of sediment yield from incised channels across the basin. Rates of erosion were summarized downstream through the channel network, revealing patterns of sediment supply at the reach scale. Erosion and sediment supply were also aggregated to subbasins, allowing comparative analyses at the scale of tributaries. The erosion patterns delineated using this approach provide land use planners with a robust framework to design erosion reduction strategies. More broadly, the study demonstrates a modern analysis of important geomorphic processes affected by land use that is easily applied by agencies to solve common problems in watersheds, improving the integration between science and environmental management.

Novel Design, Preparation, Characterization and Antimicrobial Activity of Silver Nanoparticles during Oak Acorns Bark Retrograde

2018 ◽  
Vol 232 (2) ◽  
pp. 209-221 ◽  
Author(s):  
Iraj Mesgarzadeh ◽  
Ali Reza Akbarzadeh ◽  
Rahmatollah Rahimi ◽  
Ali Maleki
Keyword(s):  
Silver Nanoparticles ◽  
Silver Nanoparticle ◽  
Metal Ion ◽  
Colloidal Stability ◽  
Single Step ◽  
Bark Extract ◽  
Distribution Analysis ◽  
Step Method ◽  
External Energy ◽  
Reducing Ability

AbstractIn search for a probable local solution for Qarasu River problems and based on our prescience about metal ion chelating/reducing ability of tannins which are found in large amount in oak acorns bark, Quercus brantii (Persian oak) acorns bark extract was exploited as reducing/capping agent in silver nanoparticles synthesis. Synthesis was carried out as a single-step method at room temperature, and without consuming any external energy by using these renewable barks. The crystallinity, size and shape of the nanoparticles were characterized by X-ray diffraction and scanning electron microscopy (SEM) respectively. The involvement of phenolic compounds in metal ion reduction was supported by UV-Visible and infrared spectroscopies and by acidity and conductivity measurements. The SEM-based particle size distribution analysis and antimicrobial susceptibility test of oak acorns bark-extract-mediated silver nanoparticles against bacterial effluent were pointed out to the critical proportion of silver salt to the capping/reducing agent. It seems that the bactericidal action depends on the extent to which accumulation of silver nanoparticle (Ag-Np) in bacterial cell surface alters the silver nanoparticle colloidal stability in broth medium.

scholarly journals Spatial variation of channel head curvature in small mountainous watersheds

2019 ◽  
Vol 50 (5) ◽  
pp. 1251-1266
Author(s):  
Jian Wu ◽  
Lei Ye ◽  
Chenchen Wu ◽  
Qingrui Chang ◽  
Zhuohang Xin ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Spatial Distributions ◽  
Nonparametric Method ◽  
Channel Network ◽  
Contour Lines ◽  
Digital Elevation ◽  
Topographic Attributes ◽  
Mountainous Watersheds ◽  
Realistic Topography ◽  
Contour Curvature

Abstract High-resolution digital elevation models (DEMs) offer opportunities for channel network extraction due to its representation of realistic topography. Channels are generally surrounded by well-defined banks that have a distinct signature in the contour lines. Contour curvature is one of the important topographic attributes usually used for channel head identification; however, the curvature at channel heads may vary considerably between and even within watersheds. Therefore, uncertainty exists in the extracted channel heads due to the specified curvature threshold. In this paper, the locations of channel heads in 14 small mountainous watersheds are obtained using a nonparametric method based on the shape of contour lines generated from DEMs with a spatial resolution of 1 m, and the channel head curvature is computed from the extracted channel heads. The spatial distributions of the channel head curvature in these 14 watersheds have been analyzed, and another two watersheds with field-mapped channel heads are selected for validation. The results indicate that: (1) the channel head curvature is sensitive to the local terrain and varies within and between watersheds; (2) the Gamma distribution effectively fits the spatial distribution of the channel head curvature in all the selected watersheds; and (3) constant threshold-based methods for channel head identification gain significant location errors even within a single watershed.

A New System For Optomanual Semiautomatic Quantitative Image Analysis

1977 ◽  
Vol 35 ◽  
pp. 210-211
Author(s):  
H.P. Rohr
Keyword(s):  
Image Analysis ◽  
Volume Density ◽  
List Type ◽  
Distribution Analysis ◽  
Type Number ◽  
Point Counting ◽  
Human Eye ◽  
Quantitative Image ◽  
Point Density ◽  
Electronic Counting

Today, in image analysis the broadest possible rationalization and economization have become desirable. Basically, there are two approaches for image analysis: The image analysis through the so-called scanning methods which are usually performed without the human eye and the systems of optical semiautomatic analysis completely relying on the human eye.The new MOP AM 01 opto-manual system (fig.) represents one of the very promising approaches in this field. The instrument consists of an electronic counting and storing unit, which incorporates a microprocessor and a keyboard for choice of measuring parameters, well designed for easy use.Using the MOP AM 01 there are three possibilities of image analysis:the manual point counting,the opto-manual point counting andthe measurement of absolute areas and/or length (size distribution analysis included).To determine a point density for the calculation of the corresponding volume density the intercepts lying within the structure are scanned with the light pen.

Immunocytochemical detection of hepatic carbohydrate metabolic enzymes: Improved resolution with polyethylene glycol embedding and visio-bond semithin sections

1992 ◽  
Vol 50 (1) ◽  
pp. 792-793
Author(s):  
Kuixiong Gao ◽  
Randal E. Morris ◽  
Bruce F. Giffin ◽  
Robert R. Cardell
Keyword(s):  
Polyethylene Glycol ◽  
Glycogen Phosphorylase ◽  
Phosphoenolpyruvate Carboxykinase ◽  
Glycogen Synthase ◽  
Metabolic Enzymes ◽  
Silver Stain ◽  
Accurate Localization ◽  
Immunocytochemical Detection ◽  
Semithin Sections ◽  
Parenchymal Cells

Several enzymes are involved in the regulation of anabolic and catabolic pathways of carbohydrate metabolism in liver parenchymal cells. The lobular distribution of glycogen synthase (GS), phosphoenolpyruvate carboxykinase (PEPCK) and glycogen phosphorylase (GP) was studied by immunocytochemistry using cryosections of normal fed and fasted rat liver. Since sections of tissue embedded in polyethylene glycol (PEG) show good morphological preservation and increased detectability for immunocytochemical localization of antigenic sites, and semithin sections of Visio-Bond (VB) embedded tissue provide higher resolution of cellular structure, we applied these techniques and immunogold-silver stain (IGSS) for a more accurate localization of hepatic carbohydrate metabolic enzymes.

Local atomic structure of relaxor ferroelectric solids studied by pulsed neutron scattering

1994 ◽  
Vol 52 ◽  
pp. 554-555
Author(s):  
T. Egami ◽  
H. D. Rosenfeld ◽  
S. Teslic
Keyword(s):  
Neutron Scattering ◽  
Atomic Structure ◽  
Argonne National Laboratory ◽  
Relaxor Ferroelectrics ◽  
Relaxor Ferroelectric ◽  
Crystallographic Structure ◽  
Chemical Inhomogeneity ◽  
Distribution Analysis ◽  
Ferroelectric Transition ◽  
Pulsed Neutron

Relaxor ferroelectrics, such as Pb(Mg1/3Nb2/3)O3 (PMN) or (Pb·88La ·12)(Zr·65Ti·35)O3 (PLZT), show diffuse ferroelectric transition which depends upon frequency of the a.c. field. In spite of their wide use in various applications details of their atomic structure and the mechanism of relaxor ferroelectric transition are not sufficiently understood. While their crystallographic structure is cubic perovskite, ABO3, their thermal factors (apparent amplitude of thermal vibration) is quite large, suggesting local displacive disorder due to heterovalent ion mixing. Electron microscopy suggests nano-scale structural as well as chemical inhomogeneity.We have studied the atomic structure of these solids by pulsed neutron scattering using the atomic pair-distribution analysis. The measurements were made at the Intense Pulsed Neutron Source (IPNS) of Argonne National Laboratory. Pulsed neutrons are produced by a pulsed proton beam accelerated to 750 MeV hitting a uranium target at a rate of 30 Hz. Even after moderation by a liquid methane moderator high flux of epithermal neutrons with energies ranging up to few eV’s remain.

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