Experimental study on the variation of optical remote sensing imaging characteristics of internal solitary waves with wind speed

Optical remote sensing has been widely used to study internal solitary waves(ISWs).Wind speed has an important effect on ISW imaging of optical remote sensing.The light and dark bands of ISWs cannot be observed by optical remote sensing when the wind is too strong.The relationship between the characteristics of ISWs bands in optical remote sensing images and the wind speed is still unclear.The influence of wind speeds on the characteristics of the ISWs bands is investigated based on the physical simulation experiments with the wind speeds of 1.6,3.1,3.5,3.8,and 3.9 m/s.The experimental results show that when the wind speed is 3.9 m/s,the ISWs bands cannot be observed in optical remote sensing images with the stratification of h_(1)∶h_(2)=7∶58,ρ_(1)∶ρ_(2)=1∶1.04.When the wind speeds are 3.1,3.5,and 3.8 m/s,which is lower than 3.9 m/s,the ISWs bands can be obtained in the simulated optical remote sensing image.The location of the band’s dark and light extremum and the band’s peak-to-peak spacing are almost not affected by wind speed.More-significant wind speeds can cause a greater gray difference of the light-dark bands.This provided a scientific basis for further understanding of ISW optical remote sensing imaging.

Optical remote sensing image characteristics of large amplitude convex mode-2 internal solitary waves:an experimental study

A series of experiments are designed to propose a new method to study the characteristics of convex mode-2internal solitary waves(ISWs)in optical remote sensing images using a laboratory-based optical remote sensing simulation platform.The corresponding wave parameters of large-amplitude convex mode-2 ISWs under smooth surfaces are investigated along with the optical remote sensing characteristic parameters.The mode-2 ISWs in the experimentally obtained optical remote sensing image are produced by their overall modulation effect on the water surface,and the extreme points of the gray value of the profile curve of bright-dark stripes appear at the same location as the real optical remote sensing image.The present data extend to a larger range than previous studies,and for the characteristics of large amplitude convex mode-2 ISWs,the experimental results show a second-order dependence of wavelength on amplitude.There is a close relationship between optical remote sensing characteristic parameters and wave parameters of mode-2 ISWs,in which there is a positive linear relationship between the bright-dark spacing and wavelength and a nonlinear relationship with the amplitude,especially when the amplitude is very large,there is a significant increase in bright-dark spacing.

Analysis of Morphometric Parameters and Radioactive Characteristics Using Remote Sensing Data and GIS Techniques in the Wadi Wizr Basin Area, Central Eastern Desert, Egypt

The purpose of this study is to demonstrate how modern technologies such as geographic information systems (GIS) and digital elevation models can help in the creation of a geographic database for the Wadi Wizr basin in Egypt’s Central Eastern Desert, in addition to examining and analysing the radioactive properties of various rocks. This was accomplished with the help of a digital elevation model (DEM) with a 30 metre accuracy and GIS software in 10.8 Arc Map. The RS-230 was also used to measure uranium and thorium concentrations. GIS softwares and digital elevation models have been shown to be more effective than the traditional method. This was demonstrated by the flexible and quick working method, the accuracy of the parameters used, and the results of the morphometric analysis of the basin river network. In addition to, the main drainage pattern from subtype to tree type, where the branching ratio was (1.59). This basin could also cause flooding. Similar studies, according to the results of this study, should make greater use of geographic information system technology and modern data sources. Wadi Wizr also has a radioactive anomaly, with uranium equivalent concentrations reaching 70 ppm in some fault parts.

Remote Sensing Monitoring of Tobacco Field Based on Phenological Characteristics and Time Series Image―A Case Study of Chengjiang County, Yunnan Province, China

Using three-phase remote sensing images of China-Brazil Earth Resources Satellite 02B (CBERS02B) and Landsat-5 TM, tobacco field was extracted by the analysis of time series image based on the different phenological characteristics between tobacco and other crops. The spectral characteristics of tobacco and corn in luxuriant growth stage are very similar, which makes them difficult to be distinguished using a single-phase remote sensing image. Field film after tobacco seedlings transplanting can be used as significant sign to identify tobacco. Remote sensing interpre- tation map based on the fusion image of TM and CBERS02B's High-Resolution (HR) camera image was used as stan- dard reference material to evaluate the classification accuracy of Spectral Angle Mapper (SAM) and Maximum Like- lihood Classifier (MLC) for time series image based on full samples test method. SAM has higher classification accu- racy and stability than MLC in dealing with time series image. The accuracy and Kappa of tobacco coverage extracted by SAM are 83.4% and 0.692 respectively, which can achieve the accuracy required by tobacco coverage measurement in a large area.

THE CHARACTERISTICS OF REMOTE SENSING TECTONICS IN QIANGTANG-CHANGDU MASSIF, QINGHAI-TIBET PLATEAU

The northern Tibet plateau is the core of generalized Qinghai—Tibet plateau. The main part of Qiangtang—Changdu massif, which is 45×10 4km 2 and more than 5000m in altitude, conforms to the northern Tibet plateau in area.1 The shape features and boundary conditions of Qiangtang—Changdu massif\;(1) Qiangtang—Changdu massif shows huge flat\|lying “S” area In MSS7 mosaic image, Qiangtang—Changdu massif extends in west and east, and appears a long\|elliptic huge block composed of feathered and dendritic textures.. Noticeably, there are two similar texture “tails" in the west and east ends of the massif. The western tail turns and constringes to the north, and eastern tail to the south. Thereby, the massif shows huge “S" area. According to the regional analysis, the eastern tail locates between Shaluli Mt.\|Taniantaweng Mt. and Mujiang River, and western part through Bangong\|Co connects with Pamirs along Karakoram Mt. In regional tectonics, the massif locates between Lazhulong\|Xijinwulan\|Co\|Jinshajiang River and Bangong\|Co\|Dongqiao\|Nujiang River fault belts.

DYNAMIC CHARACTERISTICS OF A CANTILEVER BEAM WITH PARTIAL SELF-SENSING ACTIVE CONSTRAINED LAYER DAMPING TREATMENT

The equations of motion governing the vibration of a cantilever beam with partiallytreated self-sensing active constrained layer damping treatment(SACLD)are derived by application ofthe extended Hamilton principle.The assumed-modes method and cloud loop velocity feedback controllaw are used to analyze and control the flexural vibration of the beam.The influences of the bondinglayer and piezoelectric layer thickness,material properties,placements of the piezoelectric patch andfeedback control parameters on the actuation ability of the vibration suppression are investigated.Somedesign considerations for pure passive,pure active control,and self-sensing active constrained layerdamping are discussed.

Field Sensing Characteristic Research of Carbon Fiber Smart Material

In order to research the field sensing characteristic of the carbon fiber smart material, the Tikhonov regularization principle and the modified Newton-Raphson(MNR) algorithm were adopted to solve the inverse problem of the electrical resistance tomography(ERT). An ERT system of carbon fiber smart material was developed. Field sensing characteristic was researched with the experiment. The experimental results show that the specific resistance distribution of carbon fiber smart material is highly consistent with the distribution of structural strain. High resistance zone responds to high strain area, and the specific resistance distribution of carbon fiber smart material reflects the distribution of sample strain in covering area. Monitoring by carbon fiber smart material on complicated strain status in sample field domain is realized through theoretical and experimental study.

Winter wheat identification by integrating spectral and temporal information derived from multi-resolution remote sensing data

Timely crop acreage and distribution information are the basic data which drive many agriculture related applications.For identifying crop types based on remote sensing,methods using only a single image type have significant limitations.Current research that integrates fine and coarser spatial resolution images,using techniques such as unmixing methods,regression models,and others,usually results in coarse resolution abundance without sufficient detail within pixels,and limited attention has been paid to the spatial relationship between the pixels from these two kinds of images.Here we propose a new solution to identify winter wheat by integrating spectral and temporal information derived from multi-resolution remote sensing data and determine the spatial distribution of sub-pixels within the coarse resolution pixels.Firstly,the membership of pixels which belong to winter wheat is calculated using a 25-m resolution resampled Landsat Thematic Mapper(TM)image based on the Bayesian equation.Then,the winter wheat abundance(acreage fraction in a pixel)is assessed by using a multiple regression model based on the unique temporal change features from moderate resolution imaging spectroradiometer(MODIS)time series data.Finally,winter wheat is identified by the proposed Abundance-Membership(AM)model based on the spatial relationship between the two types of pixels.Specifically,winter wheat is identified by comparing the spatially corresponding 10×10 membership pixels of each abundance pixel.In other words,this method takes advantage of the relative size of membership in a local space,rather than the absolute size in the entire study area.This method is tested in the major agricultural area of Yiluo Basin,China,and the results show that acreage accuracy(Aa)is 93.01%and sampling accuracy(As)is 91.40%.Confusion matrix shows that overall accuracy(OA)is 91.4%and the kappa coefficient(Kappa)is 0.755.These values are significantly improved compared to the traditional Maximum Likelihood classification(MLC)and Random Forest classification(RFC)which rely on spectral features.The results demonstrate that the identification accuracy can be improved by integrating spectral and temporal information.Since the identification of winter wheat is performed in the space corresponding to each MODIS pixel,the influence of differences of environmental conditions is greatly reduced.This advantage allows the proposed method to be effectively applied in other places.

Relationship between Environmental Pollution of Coal Mine and Spectral Characteristics of Nearby Plants

Remote sensing technology, as the most advanced method for collecting data, along with the common ways often used in the past on research of environmenal science, was integrated to study the relationship between environmental pollution of coal mine and spectral characteristics of nearby plants. With compositive index and mean refiectivity at near infrared, a regression equation was established, and a conclusion was made that spectral reflectivity can be used to distinguish regions with different pollution degree. Through testing with real status of the research region, it is verified that this kind of integration and conclusion not only are helpful for human being in controlling the movement law of pollutants and the corresponding change of coal mine environmental quality, but also bring a new way for the research of environment problems of coal mine.

Characteristics of Large-Scale Harmful Algal Blooms (HABs) in the Yangtze River Estuary and the Adjacent East China Sea (ECS) from 2000 to 2010

Harmful algal blooms (HABs) are a serious worldwide issue which has posed great risks on marine ecosystems and public health by directly releasing toxins or indirectly leading to anoxia in marine environment. In recent years HABs have caused huge economic losses in China, particularly in the Yangtze Estuary and the adjacent East China Sea (ECS). The present study investigated the spatial-temporal and species characteristics of large-scale HABs in this area using geographic information system (GIS) Kernel Density Estimation (KDE) spatial analysis, statistical methods and satellite image interpretation. Results revealed that the Yangtze Estuary, Zhoushan island, Xiangshan bay and Jiushan island are the regions with highest frequency of large-scale HABs. HABs in the ECS reached a peak in terms of total number and area in 2003 to 2005 and occupied a high percentage (around 70% in area and 60% in occurrence) in the four Chinese coastal waters. The number of large-scale HABs (> 1000 km2) in the Yangtze Estuary and the adjacent ECS declined after 2005 while that of HABs (> 100 km2) declined after 2008. Large-scale HABs occurrences concentrated in summer (May to July), and the averaged duration increased continually from the shortest time (1.3 days) in 2001 to the longest (10.9 days) in 2010 for each HAB. 17 causative species were found with Prorocentrum dentutam as the most frequent dominant species, followed by Skeletonema costatum, Karenia mikimotoi, and Chaetoceros curvisetus. Water discoloration observed in MODIS satellite true color images was well consistent with the corresponding HABs reported by State Oceanic Administration of China (SOA). Multiple factors involving eutrophication, physical dynamics, topography and deposition conditions contributed to the formation of frequent HABs in the ECS. Three strategies including establishing a synthesized system, improving the previous database and investigating multiple contributors were proposed for future HABs monitoring and management.

Remote Sensing Study of Gold Biogeochemical Effects in the Western Guangdong-Hainan Region——A Case Study of the Hetai Gold Deposit

The vegetation has been poisoned by gold in the western Guangdong-Hainan region. The gold content ofthe leaves there is as high as 10-1961 times the abundance, the chlorophyll content is 10%-30% lower thanthat of the vegetation in metamorphic terrains and 10%-20% higher than that in granite terrains, and thecarotenoid content is 10%-44% lower than the background value. The water content of leaves is 10% to 20%lower than the background value. The cells of leaves are deformed and broken. The leaf surface shows colourspots and becomes yellow or dark green. The spectral reflectance of the leaf surface is 5%-30% higher than thebackground value: the spectral shape has shifted 5-15 nm to the short wavelength. The gray scales of eanopyon images of Landsat TM and airborne imaging scanner (AIS) are 10%-100% higher than the backgroundvalues. On Landsat TM and AIS false colour images, plants poisoned by gold display a yellow color, whichdisinguishes them from background plants. According to the spectral and image features of goldbiogeochemical effects, the author has constructed a gold information system and expert prediction system,and thus two gold target areas and two gold prospect areas have been identified rapidly, economically andaccurately in the western Guangdong-Hainan region which is extensively covered by vegetation.

A Predictive 6G Network with Environment Sensing Enhancement:From Radio Wave Propagation Perspective

In order to support the future digital society,sixth generation(6G)network faces the challenge to work efficiently and flexibly in a wider range of scenarios.The traditional way of system design is to sequentially get the electromagnetic wave propagation model of typical scenarios firstly and then do the network design by simulation offline,which obviously leads to a 6G network lacking of adaptation to dynamic environments.Recently,with the aid of sensing enhancement,more environment information can be obtained.Based on this,from radio wave propagation perspective,we propose a predictive 6G network with environment sensing enhancement,the electromagnetic wave propagation characteristics prediction enabled network(EWave Net),to further release the potential of 6G.To this end,a prediction plane is created to sense,predict and utilize the physical environment information in EWave Net to realize the electromagnetic wave propagation characteristics prediction timely.A two-level closed feedback workflow is also designed to enhance the sensing and prediction ability for EWave Net.Several promising application cases of EWave Net are analyzed and the open issues to achieve this goal are addressed finally.

Spatio-temporal Characteristics of Area Coverage and Observation Geometry of the MISR Land-surface BRF Product: A Case Study of the Central Part of Northeast Asia

The Multi-angle imaging spectroradiometer(MISR) land-surface(LS) bidirectional reflectance factor(BRF) product(MILS_BRF) has unique semi-simultaneous multi-angle sampling and global coverage. However, unlike on-satellite observations, the spatio-temporal characteristics of MILS_BRF data have rarely been explicitly and comprehensively analysed. Results from 5-yr(2011–2015) of MILS_BRF dataset from a typical region in central Northeast Asia as the study area showed that the monthly area coverage as well as MILS_BRF data quantity varies significantly, from the highest in October(99.05%) through median in June/July(78.09%/75.21%) to lowest in January(18.97%), and a large data-vacant area exists in the study area during four consecutive winter months(December through March). The data-vacant area is mainly composed of crop lands and cropland/natural vegetation mosaic. The amount of data within the principal plane(PP)±30°(nPP) or cross PP ±30°(nCP), varies intra-annually with significant differences from different view zeniths or forward/backward scattering directions. For example, multiple off-nadir cameras have nPP but no nCP data for up to six months(September through February), with the opposite occurring in June and July. This study provides explicit and comprehensive information about the spatio-temporal characteristics of product coverage and observation geometry of MILS_BRF in the study area. Results provide required user reference information for MILS_BRF to evaluate performance of BRDF models or to compare with other satellite-derived BRF or albedo products. Comparing this final product to on-satellite observations, what was found here reveals a new perspective on product spatial coverage and observation geometry for multi-angle remote sensing.

Comparison of algorithms for monitoring wheat powdery mildew using multi-angular remote sensing data

Powdery mildew is a disease that threatens wheat production and causes severe economic losses worldwide. Its timely diagnosis is imperative for preventing and controlling its spread. In this study, the multiangle canopy spectra and disease severity of wheat were investigated at several developmental stages and degrees of disease severity. Four wavelength variable-selected algorithms: successive projection(SPA), competitive adaptive reweighted sampling(CARS), feature selection learning(Relief-F), and genetic algorithm(GA), were used to identify bands sensitive to powdery mildew. The wavelength variables selected were used as input variables for partial least squares(PLS), extreme learning machine(ELM), random forest(RF), and support vector machine(SVM) algorithms, to construct a suitable prediction model for powdery mildew. Spectral reflectance and conventional vegetation indices(VIs) displayed angle effects under several disease severity indices(DIs). The CARS method selected relatively few wavelength variables and showed a relatively homogeneous distribution across the 13 viewing zenith angles.Overall accuracies of the four modeling algorithms were ranked as follows: ELM(0.70–0.82) > PLS(0.63–0.79) > SVM(0.49–0.69) > RF(0.43–0.69). Combinations of features and algorithms generated varied accuracies, with coefficients of determination(R^(2)) single-peaked at different observation angles. The constructed CARS-ELM model extracted a predictable bivariate relationship between the multi-angle canopy spectrum and disease severity, yielding an R^(2)> 0.8 at each measured angle. Especially for larger angles,monitoring accuracies were increased relative to the optimal VI model(40% at-60°, 33% at +60°), indicating that the CARS-ELM model is suitable for extreme angles of-60° and +60°. The results are proposed to provide a technical basis for rapid and large-scale monitoring of wheat powdery mildew.

Quantitative description of infrared radiation characteristics of preflawed sandstone during fracturing process

Previous studies show that infrared radiation temperature(IRT)abnormalities are always accompanied by the crack development in rocks under external loads.In this context,experiments were conducted on preflawed sandstone to investigate the infrared radiation characteristics during failure process.Two indicators were defined herein,i.e.coefficient of variation of IRT(CVIRT)and skewness of IRT(SIRT).The regression analysis shows that the IRT probability distributions during loading process fit the Gaussian model.The variations in the CVIRT are characterized by four stages:primary stage,steady stage,accelerating stage and post-peak stage.Besides,the variations in the SIRT are divided into three stages:primary stage,steady stage and failure and post-peak stage.The precursor point for preflawed rock failure is identified based on the CVIRTetime curve,with average precursor point of 83%of the peak stress.Compared with other IRT indicators,the proposed two IRT indicators have higher sensitivity to IRT abnormalities during failure process.Furthermore,the connection between the IRT indicators and the rock fracturing was investigated to interpret the IRT indicator abnormalities.Based on the Verhulst inverse function,a new quantitative model was presented to describe the primary stage,steady stage and accelerating stage of the CVIRTetime curve.The results obtained in this study can provide early-warning information for rock failure prediction.

EXPERIMENTAL STUDY OF LOAD SENSING SYSTEM WITH LONG PIPES

A test platform is established as per the practical working condition of elevating platform fire truck. The influences of pipes and load on dynamic characteristics of load-sensing system are studied by series of step response experiments. Experimental results show that the feedback pipe makes the most important influence on the dynamic response speed of load-sensing system. Its internal diameter should be optimized for given length of pipe. On the other hand, the stability of load-sensing pump is improved as the length of input pipe increases in a certain range. The influence of input pipe on the dynamic response speed is caused mainly by the pressure-wave travel time in the input pipe.

An Approach to Extracting Fractal in Remote Sensing Image

In order to apply the spatial structure information to remote sensing interpretation through fractal theory, an algorithm is introduced to compute the single pixel fractal dimension in remote sensing images. After a computer program was written according to the algorithm, the ETM+ images were calculated to obtain their fractal data through the program. The algorithm has following characteristics: The obtained fractal values indicate the complexity of image, and have positive correlation with the complexity of images and ground objects. Moreover, the algorithm is simple and reliable, and easy to be implemented.

REBUILDING THE SEA WAVE HEIGHT SPECTRUM BY USING MICROWAVE SCATTERING CHARACTERISTICS

The microwave back-scattering characteristics are numerically analysed by the elec-tromagnetic scattering theory,and the sea wave height spectrum that reflects the wind field isrebuilt by comparing the calculated data with experimental data which were measured by airbornescatter.According to the wave height spectrum,the relationship between the back-scattering co-efficients and wind speeds can be obtained.Once the back-scattering coefficients of the sea surfaceare measured,then the wind speeds over the sea surface can approximately be determined.It isuseful for the microwave remote sensing in ocean.

The characteristics of welding currents in a rotating arc leadtandem GMAW process and the weld-seam tracking

Tandem gas metal arc welding( T-GMAW) process shows a high deposition rate that up to three times of the single electrode GMAW,so the welding speed could be significantly increased in this process. However,the majority of this process applications are based on the pre-programmed robotic welding,which does not allow them to track the seam real-time during welding. Rotating arc sensor,sensing the seam position by detecting the changing of welding currents,has been widely adopted in the automatic robot welding process. It is proposed in this paper to integrate the rotating arc sensor with a trailing torch to develop a new approach of rotating arc lead tandem gas metal arc welding( RLT-GMAW) process. The characteristics of the welding currents in the proposed new welding process were firstly studied,and then a self-turning fuzzy control seam tracking strategy was developed for the mobile robot automatic welding. The experimental results showed that the proposed RLT-GMAW process had an excellent seam tracking performance and high welding deposition rate. Even if there were some electromagnetic interactions between the two arcs,the deviation of the welding seam could also be reflected by the fluctuation of the welding currents on the leading arc once the correct welding parameters were selected. Based on the detected deviation,the welding tracking experiments showed that the proposed self-turning fuzzy controller had a good performance for the RLT-GMAW process seam tracking.

Optical and NH₃Gas Sensing Properties of Hole-Transport Layers Based on PEDOT: PSS Incorporated with Nano-TiO₂

Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) incorporated with nanocrystalline TiO2 powder (PEDOT:PSS+nc-TiO2) films were prepared by spin-coating technique. SEM surface morphology, UV-Vis spectra and NH3 gas sensing of were studied. Results showed that the PEDOT:PSS+nc-TiO2 film with a content of 9.0 wt% of TiO2 is most suitable for both the hole transport layer and the NH3 sensing. The responding time of the sensor made from this composite film reached a value as fast as 20 s. The rapid responsiveness to NH3 gas was attributed to the efficient movement of holes as the major charge carriers in PEDOT:PSS+nc-TiO2 composite films. Useful applications in organic electronic devices like light emitting diodes and gas thin film sensors can be envisaged.