scholarly journals Novel classification of aggregation structure of monolayers on the water surface.

MEMBRANE ◽  
1992 ◽  
Vol 17 (5) ◽  
pp. 333-343 ◽  
Author(s):  
Tisato Kajiyama ◽  
Yushi Oishi
Keyword(s):  
Water Surface ◽  
Aggregation Structure

scholarly journals Experimental analysis on the optimal excitation wavelength for fine-grained identification of refined oil pollutants on water surface based on laser-induced fluorescence

2021 ◽  
Author(s):  
Ming Xie ◽  
Yunpeng Jia ◽  
Ying Li ◽  
Xiaohua Cai ◽  
Kai Cao
Keyword(s):  
Oil Spill ◽  
Theoretical Basis ◽  
Water Surface ◽  
Laser Induced Fluorescence ◽  
Excitation Wavelength ◽  
Refined Oil ◽  
Fine Grained ◽  
Optimal Excitation ◽  
Oil Spill Identification

Abstract Laser-induced fluorescence (LIF) is an effective, all-weather oil spill identification method that has been widely applied for oil spill monitoring. However, the distinguishability on oil types is seldom considered while selecting excitation wavelength. This study is intended to find the optimal excitation wavelength for fine-grained classification of refined oil pollutants using LIF by comparing the distinguishability of fluorometric spectra under various excitation wavelengths on some typical types of refined-oil samples. The results show that the fluorometric spectra of oil samples significantly vary under different excitation wavelengths, and the four types of oil applied in this study are most likely to be distinguished under the excitation wavelengths of 395 nm and 420 nm. This study is expected to improve the ability of oil types identification using LIF method without increasing time or other cost, and also provides theoretical basis for the development of portable LIF devices for oil spill identification.

On-site visualized classification of transparent hazards and noxious substances on a water surface by multispectral techniques

2019 ◽  
Vol 58 (16) ◽  
pp. 4458 ◽  
Author(s):  
Haocai Huang ◽  
Shuchang Liu ◽  
Chao Wang ◽  
Kaibo Xia ◽  
Dejun Zhang ◽  
...  
Keyword(s):  
Water Surface ◽  
Noxious Substances

scholarly journals Theoretical classification of two-layered stratified flow discharged at water surface.

1985 ◽  
pp. 107-113
Author(s):  
Akira MUROTA ◽  
Keiji NAKATSUJI ◽  
Keijiroh NAKAMURA
Keyword(s):  
Water Surface ◽  
Stratified Flow

scholarly journals Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment

2017 ◽  
Vol 21 (1) ◽  
pp. 43-63 ◽  
Author(s):  
Mikkel Skovgaard Andersen ◽  
Áron Gergely ◽  
Zyad Al-Hamdani ◽  
Frank Steinbacher ◽  
Laurids Rolighed Larsen ◽  
...  
Keyword(s):  
Transition Zone ◽  
Water Surface ◽  
High Energy ◽  
Green Laser ◽  
Morphological Features ◽  
Tidal Range ◽  
Surface Model ◽  
Lidar Data ◽  
Surface Detection

Abstract. The transition zone between land and water is difficult to map with conventional geophysical systems due to shallow water depth and often challenging environmental conditions. The emerging technology of airborne topobathymetric light detection and ranging (lidar) is capable of providing both topographic and bathymetric elevation information, using only a single green laser, resulting in a seamless coverage of the land–water transition zone. However, there is no transparent and reproducible method for processing green topobathymetric lidar data into a digital elevation model (DEM). The general processing steps involve data filtering, water surface detection and refraction correction. Specifically, the procedure of water surface detection and modelling, solely using green laser lidar data, has not previously been described in detail for tidal environments. The aim of this study was to fill this gap of knowledge by developing a step-by-step procedure for making a digital water surface model (DWSM) using the green laser lidar data. The detailed description of the processing procedure augments its reliability, makes it user-friendly and repeatable. A DEM was obtained from the processed topobathymetric lidar data collected in spring 2014 from the Knudedyb tidal inlet system in the Danish Wadden Sea. The vertical accuracy of the lidar data is determined to ±8 cm at a 95 % confidence level, and the horizontal accuracy is determined as the mean error to ±10 cm. The lidar technique is found capable of detecting features with a size of less than 1 m2. The derived high-resolution DEM was applied for detection and classification of geomorphometric and morphological features within the natural environment of the study area. Initially, the bathymetric position index (BPI) and the slope of the DEM were used to make a continuous classification of the geomorphometry. Subsequently, stage (or elevation in relation to tidal range) and a combination of statistical neighbourhood analyses (moving average and standard deviation) with varying window sizes, combined with the DEM slope, were used to classify the study area into six specific types of morphological features (i.e. subtidal channel, intertidal flat, intertidal creek, linear bar, swash bar and beach dune). The developed classification method is adapted and applied to a specific case, but it can also be implemented in other cases and environments.

Classification for molecular aggregation structure of monolayers on the water surface

1995 ◽  
Vol 2 (2) ◽  
pp. 107-116 ◽  
Author(s):  
Tisato Kajiyama ◽  
Hiroyuki Kozuru ◽  
Yoshinari Takashima ◽  
Yushi Oishi ◽  
Kazuaki Suehiro
Keyword(s):  
Water Surface ◽  
Molecular Aggregation ◽  
Aggregation Structure

scholarly journals Recognition and classification of water surface targets based on deep learning

2021 ◽  
Vol 1820 (1) ◽  
pp. 012166
Author(s):  
Yanhua Peng ◽  
Yipu Yan ◽  
Biao Feng ◽  
Xingyu Gao
Keyword(s):  
Deep Learning ◽  
Water Surface

scholarly journals Experimental analysis on the optimal excitation wavelength for fine-grained identification of refined oil pollutants on water surface based on laser-induced fluorescence

2021 ◽  
Author(s):  
Ming Xie ◽  
Yunpeng Jia ◽  
Ying Li ◽  
Xiaohua Cai ◽  
Kai Cao
Keyword(s):  
Oil Spill ◽  
Theoretical Basis ◽  
Water Surface ◽  
Laser Induced Fluorescence ◽  
Excitation Wavelength ◽  
Refined Oil ◽  
Fine Grained ◽  
Optimal Excitation ◽  
Oil Spill Identification

Abstract Laser-induced fluorescence (LIF) is an effective, all-weather oil spill identification method that has been widely applied for oil spill monitoring. However, the distinguishability on oil types is seldom considered while selecting excitation wavelength. This study is intended to find the optimal excitation wavelength for fine-grained classification of refined oil pollutants using LIF by comparing the distinguishability of fluorometric spectra under various excitation wavelengths on some typical types of refined-oil samples. The results show that the fluorometric spectra of oil samples significantly vary under different excitation wavelengths, and the four types of oil applied in this study are most likely to be distinguished under the excitation wavelengths of 395 nm and 420 nm. This study is expected to improve the ability of oil types identification using LIF method without increasing time or other cost, and also provides theoretical basis for the development of portable LIF devices for oil spill identification.

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