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Sensors, Volume 8, Issue 8 (August 2008) , Pages 4487-5228

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Open AccessReview
Mesoporous Silicate Materials in Sensing
Sensors 2008, 8(8), 5202-5228; https://doi.org/10.3390/s8085202
Received: 6 August 2008 / Revised: 21 August 2008 / Accepted: 28 August 2008 / Published: 29 August 2008
Cited by 182 | Viewed by 11115 | PDF Full-text (311 KB) | HTML Full-text | XML Full-text
Abstract
Mesoporous silicas, especially those exhibiting ordered pore systems and uniform pore diameters, have shown great potential for sensing applications in recent years. Morphological control grants them versatility in the method of deployment whether as bulk powders, monoliths, thin films, or embedded in coatings. [...] Read more.
Mesoporous silicas, especially those exhibiting ordered pore systems and uniform pore diameters, have shown great potential for sensing applications in recent years. Morphological control grants them versatility in the method of deployment whether as bulk powders, monoliths, thin films, or embedded in coatings. High surface areas and pore sizes greater than 2 nm make them effective as adsorbent coatings for humidity sensors. The pore networks also provide the potential for immobilization of enzymes within the materials. Functionalization of materials by silane grafting or through cocondensation of silicate precursors can be used to provide mesoporous materials with a variety of fluorescent probes as well as surface properties that aid in selective detection of specific analytes. This review will illustrate how mesoporous silicas have been applied to sensing changes in relative humidity, changes in pH, metal cations, toxic industrial compounds, volatile organic compounds, small molecules and ions, nitroenergetic compounds, and biologically relevant molecules. Full article
(This article belongs to the Special Issue Molecular Recognition and Sensors, Including Molecular Imprinting)
Open AccessArticle
Surface Energy Balance Based Evapotranspiration Mapping in the Texas High Plains
Sensors 2008, 8(8), 5186-5201; https://doi.org/10.3390/s8085186
Received: 27 July 2008 / Revised: 12 August 2008 / Accepted: 27 August 2008 / Published: 28 August 2008
Cited by 23 | Viewed by 9672 | PDF Full-text (235 KB) | HTML Full-text | XML Full-text
Abstract
Agriculture on the Texas High Plains (THP) uses approximately 89% of groundwater withdrawals from the Ogallala Aquifer. Consequently, groundwater levels are declining faster than the recharge rate. Therefore, efficient agricultural water use is essential for economic viability and sustainability of the THP. Accurate [...] Read more.
Agriculture on the Texas High Plains (THP) uses approximately 89% of groundwater withdrawals from the Ogallala Aquifer. Consequently, groundwater levels are declining faster than the recharge rate. Therefore, efficient agricultural water use is essential for economic viability and sustainability of the THP. Accurate regional evapotranspiration (ET) maps would provide valuable information on actual crop water use. In this study, METRIC (Mapping Evapotranspiration at High Resolution using Internalized Calibration), a remote sensing based ET algorithm, was evaluated for mapping ET in the THP. Two Landsat 5 Thematic Mapper images acquired on 27 June (DOY 178) and 29 July (DOY 210) 2005 were used for this purpose. The performance of the ET model was evaluated by comparing the predicted daily ET with values derived from soil moisture budget at four commercial agricultural fields. Daily ET estimates resulted with a prediction error of 12.7±8.1% (mean bias error ± root mean square error) on DOY 178 and -4.7±9.4% on DOY 210 when compared with ET derived from measured soil moisture through the soil water balance. These results are good considering the prevailing advective conditions in the THP. METRIC have the potential to be used for mapping regional ET in the THP region. However, more evaluation is needed under different agroclimatological conditions. Full article
Open AccessArticle
Critical Evaluation of Acetylcholine Determination in Rat Brain Microdialysates using Ion-Pair Liquid Chromatography with Amperometric Detection
Sensors 2008, 8(8), 5171-5185; https://doi.org/10.3390/s8085171
Received: 1 July 2008 / Revised: 24 August 2008 / Accepted: 25 August 2008 / Published: 28 August 2008
Cited by 18 | Viewed by 8227 | PDF Full-text (170 KB) | HTML Full-text | XML Full-text
Abstract
Liquid chromatography with amperometric detection remains the most widely used method for acetylcholine quantification in microdialysis samples. Separation of acetylcholine from choline and other matrix components on a microbore chromatographic column (1 mm internal diameter), conversion of acetylcholine in an immobilized enzyme reactor [...] Read more.
Liquid chromatography with amperometric detection remains the most widely used method for acetylcholine quantification in microdialysis samples. Separation of acetylcholine from choline and other matrix components on a microbore chromatographic column (1 mm internal diameter), conversion of acetylcholine in an immobilized enzyme reactor and detection of the produced hydrogen peroxide on a horseradish peroxidase redox polymer coated glassy carbon electrode, achieves sufficient sensitivity for acetylcholine quantification in rat brain microdialysates. However, a thourough validation within the concentration range required for this application has not been carried out before. Furthermore, a rapid degradation of the chromatographic columns and enzyme systems have been reported. In the present study an ion-pair liquid chromatography assay with amperometric detection was validated and its long-term stability evaluated. Working at pH 6.5 dramatically increased chromatographic stability without a loss in sensitivity compared to higher pH values. The lower limit of quantification of the method was 0.3 nM. At this concentration the repeatability was 15.7%, the inter-day precision 8.7% and the accuracy 103.6%. The chromatographic column was stable over 4 months, the immobilized enzyme reactor up to 2-3 months and the enzyme coating of the amperometric detector up to 1-2 months. The concentration of acetylcholine in 30 μl microdialysates obtained under basal conditions from the hippocampus of freely moving rats was 0.40 ± 0.12 nM (mean ± SD, n = 30). The present method is therefore suitable for acetylcholine determination in rat brain microdialysates. Full article
(This article belongs to the Special Issue Amperometric Sensors and Techniques for Neurochemical Monitoring)
Open AccessReview
Biotests and Biosensors for Ecotoxicology of Metal Oxide Nanoparticles: A Minireview
Sensors 2008, 8(8), 5153-5170; https://doi.org/10.3390/s8085153
Received: 10 July 2008 / Revised: 25 August 2008 / Accepted: 26 August 2008 / Published: 28 August 2008
Cited by 152 | Viewed by 12875 | PDF Full-text (782 KB) | HTML Full-text | XML Full-text
Abstract
Nanotechnologies have become a significant priority worldwide. Several manufactured nanoparticles - particles with one dimension less than 100 nm - are increasingly used in consumer products. At nanosize range, the properties of materials differ substantially from bulk materials of the same composition, mostly [...] Read more.
Nanotechnologies have become a significant priority worldwide. Several manufactured nanoparticles - particles with one dimension less than 100 nm - are increasingly used in consumer products. At nanosize range, the properties of materials differ substantially from bulk materials of the same composition, mostly due to the increased specific surface area and reactivity, which may lead to increased bioavailability and toxicity. Thus, for the assessment of sustainability of nanotechnologies, hazards of manufactured nanoparticles have to be studied. Despite all the above mentioned, the data on the potential environmental effects of nanoparticles are rare. This mini-review is summarizing the emerging information on different aspects of ecotoxicological hazard of metal oxide nanoparticles, focusing on TiO2, ZnO and CuO. Various biotests that have been successfully used for evaluation of ecotoxic properties of pollutants to invertebrates, algae and bacteria and now increasingly applied for evaluation of hazard of nanoparticles at different levels of the aquatic food-web are discussed. Knowing the benefits and potential drawbacks of these systems, a suite of tests for evaluation of environmental hazard of nanoparticles is proposed. Special attention is paid to the influence of particle solubility and to recombinant metal-sensing bacteria as powerful tools for quantification of metal bioavailability. Using recombinant metal-specific bacterial biosensors and multitrophic ecotoxicity assays in tandem will create new scientific knowledge on the respective role of ionic species and of particles in toxicity of metal oxide nanoparticles. Full article
Open AccessArticle
A Novel Nonenzymatic Hydrogen Peroxide Sensor Based on a Polypyrrole Nanowire-Copper Nanocomposite Modified Gold Electrode
Sensors 2008, 8(8), 5141-5152; https://doi.org/10.3390/s8085141
Received: 10 July 2008 / Revised: 19 August 2008 / Accepted: 20 August 2008 / Published: 28 August 2008
Cited by 45 | Viewed by 7371 | PDF Full-text (2835 KB) | HTML Full-text | XML Full-text
Abstract
A novel nonenzymatic hydrogen peroxide (H2O2) sensor has been fabricated by dispersing copper nanoparticles onto polypyrrole (PPy) nanowires by cyclic voltammetry (CV) to form PPy-copper nanocomposites on gold electrodes. Scanning electron microscopy (SEM) was used to characterize the morphologies of the PPy nanowires [...] Read more.
A novel nonenzymatic hydrogen peroxide (H2O2) sensor has been fabricated by dispersing copper nanoparticles onto polypyrrole (PPy) nanowires by cyclic voltammetry (CV) to form PPy-copper nanocomposites on gold electrodes. Scanning electron microscopy (SEM) was used to characterize the morphologies of the PPy nanowires and the PPy-copper nanocomposite. The reactivity of the PPy-copper nanocomposite towards H2O2 was characterized by cyclic voltammetry and chronoamperometry. Effects of applied potential, the concentrations of detection solution upon the response currents of the sensor were investigated for an optimum analytical performance. It was proved that the PPy-copper nanocomposite showed excellent catalytic activity for the reduction of hydrogen peroxide (H2O2). The sensor showed a linear response to hydrogen peroxide in the concentration range between 7.0×10-6 and 4.3×10-3 mol L-1 with a high sensitivity, and a detection limit of 2.3×10-6 mol L-1. Experiment results also showed that the sensor had good stability. Full article
Open AccessArticle
The Improved Dual-view Field Goniometer System FIGOS
Sensors 2008, 8(8), 5120-5140; https://doi.org/10.3390/s8085120
Received: 3 July 2008 / Revised: 22 August 2008 / Accepted: 24 August 2008 / Published: 28 August 2008
Cited by 22 | Viewed by 7849 | PDF Full-text (880 KB) | HTML Full-text | XML Full-text
Abstract
In spectrodirectional Remote Sensing (RS) the Earth’s surface reflectance characteristics are studied by means of their angular dimensions. Almost all natural surfaces exhibit an individual anisotropic reflectance behaviour due to the contrast between the optical properties of surface elements and background and the [...] Read more.
In spectrodirectional Remote Sensing (RS) the Earth’s surface reflectance characteristics are studied by means of their angular dimensions. Almost all natural surfaces exhibit an individual anisotropic reflectance behaviour due to the contrast between the optical properties of surface elements and background and the geometric surface properties of the observed scene. The underlying concept, which describes the reflectance characteristic of a specific surface area, is called the bidirectional reflectance distribution function (BRDF). BRDF knowledge is essential for both correction of directional effects in RS data and quantitative retrieval of surface parameters. Ground-based spectrodirectional measurements are usually performed with goniometer systems. An accurate retrieval of the bidirectional reflectance factors (BRF) from field goniometer measurements requires hyperspectral knowledge of the angular distribution of the reflected and the incident radiation. However, prior to the study at hand, no operational goniometer system was able to fulfill this requirement. This study presents the first dual-view field goniometer system, which is able to simultaneously collect both the reflected and the incident radiation at high angular and spectral resolution and, thus, providing the necessary spectrodirectional datasets to accurately retrieve the surface specific BRF. Furthermore, the angular distribution of the incoming diffuse radiation is characterized for various atmospheric conditions and the BRF retrieval is performed for an artificial target and compared to laboratory spectrodirectional measurement results obtained with the same goniometer system. Suggestions for further improving goniometer systems are given and the need for intercalibration of various goniometers as well as for standardizing spectrodirectional measurements is expressed. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Switzerland)
Open AccessArticle
The Statistical Meaning of Kurtosis and Its New Application to Identification of Persons Based on Seismic Signals
Sensors 2008, 8(8), 5106-5119; https://doi.org/10.3390/s8085106
Received: 14 July 2008 / Revised: 14 August 2008 / Accepted: 20 August 2008 / Published: 27 August 2008
Cited by 16 | Viewed by 8035 | PDF Full-text (122 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a new algorithm making use of kurtosis, which is a statistical parameter, to distinguish the seismic signal generated by a person's footsteps from other signals. It is adaptive to any environment and needs no machine study or training. As persons [...] Read more.
This paper presents a new algorithm making use of kurtosis, which is a statistical parameter, to distinguish the seismic signal generated by a person's footsteps from other signals. It is adaptive to any environment and needs no machine study or training. As persons or other targets moving on the ground generate continuous signals in the form of seismic waves, we can separate different targets based on the seismic waves they generate. The parameter of kurtosis is sensitive to impulsive signals, so it’s much more sensitive to the signal generated by person footsteps than other signals generated by vehicles, winds, noise, etc. The parameter of kurtosis is usually employed in the financial analysis, but rarely used in other fields. In this paper, we make use of kurtosis to distinguish person from other targets based on its different sensitivity to different signals. Simulation and application results show that this algorithm is very effective in distinguishing person from other targets. Full article
Open AccessArticle
Electrocatalytic Detection of Amitrole on the Multi-Walled Carbon Nanotube – Iron (II) tetra-aminophthalocyanine Platform
Sensors 2008, 8(8), 5096-5105; https://doi.org/10.3390/s8085096
Received: 21 May 2008 / Revised: 9 June 2008 / Accepted: 11 June 2008 / Published: 27 August 2008
Cited by 72 | Viewed by 5984 | PDF Full-text (125 KB) | HTML Full-text | XML Full-text
Abstract
It is shown that iron(II) tetra-aminophthalocyanine complex electropolymerized onto a multi-walled carbon nanotube-modified basal plane pyrolytic graphite electrode greatly enhanced the electrocatalytic detetion of amitrole (a toxic herbicide), resulting in a very low detection limit (0.5 nM) and excellent sensitivity of 8.80±0.44 μA/nM, [...] Read more.
It is shown that iron(II) tetra-aminophthalocyanine complex electropolymerized onto a multi-walled carbon nanotube-modified basal plane pyrolytic graphite electrode greatly enhanced the electrocatalytic detetion of amitrole (a toxic herbicide), resulting in a very low detection limit (0.5 nM) and excellent sensitivity of 8.80±0.44 μA/nM, compared to any known work reported so far. The electrocatalytic detection of amitrole at this electrode occurred at less positive potential (~0.3 V vs Ag|ACl) and also revealed a typical coupled chemical reaction. The mechanism for this response is proposed. The electrode gave satisfactory selectivity to amitrole in the presence of other potential interfering pesticides in aqueous solutions. Full article
Open AccessArticle
A Polypyrrole-based Strain Sensor Dedicated to Measure Bladder Volume in Patients with Urinary Dysfunction
Sensors 2008, 8(8), 5081-5095; https://doi.org/10.3390/s8085081
Received: 1 July 2008 / Revised: 22 August 2008 / Accepted: 26 August 2008 / Published: 27 August 2008
Cited by 25 | Viewed by 6298 | PDF Full-text (227 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes a new technique to measure urine volume in patients with urinary bladder dysfunction. Polypyrrole – an electronically conducting polymer - is chemically deposited on a highly elastic fabric. This fabric, when placed around a phantom bladder, produced a reproducible change [...] Read more.
This paper describes a new technique to measure urine volume in patients with urinary bladder dysfunction. Polypyrrole – an electronically conducting polymer - is chemically deposited on a highly elastic fabric. This fabric, when placed around a phantom bladder, produced a reproducible change in electrical resistance on stretching. The resistance response to stretching is linear in 20%-40% strain variation. This change in resistance is influenced by chemical fabrication conditions. We also demonstrate the dynamic mechanical testing of the patterned polypyrrole on fabric in order to show the feasibility of passive interrogation of the strain sensor for biomedical sensing applications. Full article
Open AccessArticle
Empirical Evidence for Impacts of Internal Migration on Vegetation Dynamics in China from 1982 to 2000
Sensors 2008, 8(8), 5069-5080; https://doi.org/10.3390/s8085069
Received: 28 July 2008 / Revised: 20 August 2008 / Accepted: 22 August 2008 / Published: 27 August 2008
Cited by 7 | Viewed by 7525 | PDF Full-text (214 KB) | HTML Full-text | XML Full-text
Abstract
Migration is one of the major socio-economic characteristics of China since the country adopted the policy of economic reform in late 1970s. Many studies have been dedicated to understand why and how people move, and the consequences of their welfare. The purpose of [...] Read more.
Migration is one of the major socio-economic characteristics of China since the country adopted the policy of economic reform in late 1970s. Many studies have been dedicated to understand why and how people move, and the consequences of their welfare. The purpose of this study is to investigate the environmental impacts of the large scale movement of population in China. We analyzed the trend in the Normalized Difference Vegetation Index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) along with China migration data from the 1 percent national survey during 1982-1987, the 4th national census during 1985-1990 and the 5th national census during1995~2000. We found that the internal migration in China has a statistically significant negative impact on vegetation growth at the provincial scale from 1982 to 2000 even though the overall vegetation abundance increased in China. The impact from migration (R2=0.47, P=0.0001) on vegetation dynamics is the second strongest as among the factors considered, including changes in annual mean air temperature (R2=0.50, P=0.0001) and annual total precipitation (R2=0.30, P=0.0049) and gross domestic production (R2= 0.25, P=0.0102). The negative statistical relationship between the rate of increase in total migration and the change in vegetation abundance is stronger (R2=0.56, P=0.0000) after controlling for the effects of changes in temperature and precipitation. In-migration dominates the impacts of migration on vegetation dynamics. Therefore, it is important for policy makers in China to take the impacts of migration on vegetation growth into account while making policies aiming at sustainable humanenvironment relations. Full article
(This article belongs to the Special Issue Remote Sensing of Natural Resources and the Environment)
Open AccessArticle
Silicon Wafer-Based Platinum Microelectrode Array Biosensor for Near Real-Time Measurement of Glutamate in Vivo
Sensors 2008, 8(8), 5023-5036; https://doi.org/10.3390/s8085023
Received: 29 July 2008 / Revised: 22 August 2008 / Accepted: 22 August 2008 / Published: 27 August 2008
Cited by 90 | Viewed by 8574 | PDF Full-text (373 KB) | HTML Full-text | XML Full-text
Abstract
Using Micro-Electro-Mechanical-Systems (MEMS) technologies, we have developed silicon wafer-based platinum microelectrode arrays (MEAs) modified with glutamate oxidase (GluOx) for electroenzymatic detection of glutamate in vivo. These MEAs were designed to have optimal spatial resolution for in vivo recordings. Selective detection of glutamate [...] Read more.
Using Micro-Electro-Mechanical-Systems (MEMS) technologies, we have developed silicon wafer-based platinum microelectrode arrays (MEAs) modified with glutamate oxidase (GluOx) for electroenzymatic detection of glutamate in vivo. These MEAs were designed to have optimal spatial resolution for in vivo recordings. Selective detection of glutamate in the presence of the electroactive interferents, dopamine and ascorbic acid, was attained by deposition of polypyrrole and Nafion. The sensors responded to glutamate with a limit of detection under 1μM and a sub-1-second response time in solution. In addition to extensive in vitro characterization, the utility of these MEA glutamate biosensors was also established in vivo. In the anesthetized rat, these MEA glutamate biosensors were used for detection of cortically-evoked glutamate release in the ventral striatum. The MEA biosensors also were applied to the detection of stress-induced glutamate release in the dorsal striatum of the freely-moving rat. Full article
(This article belongs to the Special Issue Amperometric Sensors and Techniques for Neurochemical Monitoring)
Open AccessArticle
Wireless and Powerless Sensing Node System Developed for Monitoring Motors
Sensors 2008, 8(8), 5005-5022; https://doi.org/10.3390/s8085005
Received: 25 July 2008 / Revised: 22 August 2008 / Accepted: 26 August 2008 / Published: 27 August 2008
Cited by 28 | Viewed by 6873 | PDF Full-text (1796 KB) | HTML Full-text | XML Full-text
Abstract
Reliability and maintainability of tooling systems can be improved through condition monitoring of motors. However, it is difficult to deploy sensor nodes due to the harsh environment of industrial plants. Sensor cables are easily damaged, which renders the monitoring system deployed to assure [...] Read more.
Reliability and maintainability of tooling systems can be improved through condition monitoring of motors. However, it is difficult to deploy sensor nodes due to the harsh environment of industrial plants. Sensor cables are easily damaged, which renders the monitoring system deployed to assure the machine’s reliability itself unreliable. A wireless and powerless sensing node integrated with a MEMS (Micro Electro-Mechanical System) sensor, a signal processor, a communication module, and a self-powered generator was developed in this study for implementation of an easily mounted network sensor for monitoring motors. A specially designed communication module transmits a sequence of electromagnetic (EM) pulses in response to the sensor signals. The EM pulses can penetrate through the machine’s metal case and delivers signals from the sensor inside the motor to the external data acquisition center. By using induction power, which is generated by the motor’s shaft rotation, the sensor node is self-sustaining; therefore, no power line is required. A monitoring system, equipped with novel sensing nodes, was constructed to test its performance. The test results illustrate that, the novel sensing node developed in this study can effectively enhance the reliability of the motor monitoring system and it is expected to be a valuable technology, which will be available to the plant for implementation in a reliable motor management program. Full article
Open AccessArticle
Surface Temperature Mapping of the University of Northern Iowa Campus Using High Resolution Thermal Infrared Aerial Imageries
Sensors 2008, 8(8), 5055-5068; https://doi.org/10.3390/s8085055
Received: 25 July 2008 / Revised: 22 August 2008 / Accepted: 22 August 2008 / Published: 25 August 2008
Cited by 11 | Viewed by 10078 | PDF Full-text (757 KB) | HTML Full-text | XML Full-text
Abstract
The goal of this project was to map the surface temperature of the University of Northern Iowa campus using high-resolution thermal infrared aerial imageries. A thermal camera with a spectral bandwidth of 3.0-5.0 μm was flown at the average altitude of 600 m, [...] Read more.
The goal of this project was to map the surface temperature of the University of Northern Iowa campus using high-resolution thermal infrared aerial imageries. A thermal camera with a spectral bandwidth of 3.0-5.0 μm was flown at the average altitude of 600 m, achieving ground resolution of 29 cm. Ground control data was used to construct the pixelto-temperature conversion model, which was later used to produce temperature maps of the entire campus and also for validation of the model. The temperature map then was used to assess the building rooftop conditions and steam line faults in the study area. Assessment of the temperature map revealed a number of building structures that may be subject to insulation improvement due to their high surface temperatures leaks. Several hot spots were also identified on the campus for steam pipelines faults. High-resolution thermal infrared imagery proved highly effective tool for precise heat anomaly detection on the campus, and it can be used by university facility services for effective future maintenance of buildings and grounds. Full article
(This article belongs to the Special Issue Remote Sensing of Land Surface Properties, Patterns and Processes)
Open AccessArticle
Detection of Aspens Using High Resolution Aerial Laser Scanning Data and Digital Aerial Images
Sensors 2008, 8(8), 5037-5054; https://doi.org/10.3390/s8085037
Received: 5 August 2008 / Revised: 21 August 2008 / Accepted: 22 August 2008 / Published: 25 August 2008
Cited by 13 | Viewed by 8571 | PDF Full-text (145 KB) | HTML Full-text | XML Full-text
Abstract
The aim was to use high resolution Aerial Laser Scanning (ALS) data and aerial images to detect European aspen (Populus tremula L.) from among other deciduous trees. The field data consisted of 14 sample plots of 30 m × 30 m [...] Read more.
The aim was to use high resolution Aerial Laser Scanning (ALS) data and aerial images to detect European aspen (Populus tremula L.) from among other deciduous trees. The field data consisted of 14 sample plots of 30 m × 30 m size located in the Koli National Park in the North Karelia, Eastern Finland. A Canopy Height Model (CHM) was interpolated from the ALS data with a pulse density of 3.86/m2, low-pass filtered using Height-Based Filtering (HBF) and binarized to create the mask needed to separate the ground pixels from the canopy pixels within individual areas. Watershed segmentation was applied to the low-pass filtered CHM in order to create preliminary canopy segments, from which the non-canopy elements were extracted to obtain the final canopy segmentation, i.e. the ground mask was analysed against the canopy mask. A manual classification of aerial images was employed to separate the canopy segments of deciduous trees from those of coniferous trees. Finally, linear discriminant analysis was applied to the correctly classified canopy segments of deciduous trees to classify them into segments belonging to aspen and those belonging to other deciduous trees. The independent variables used in the classification were obtained from the first pulse ALS point data. The accuracy of discrimination between aspen and other deciduous trees was 78.6%. The independent variables in the classification function were the proportion of vegetation hits, the standard deviation of in pulse heights, accumulated intensity at the 90th percentile and the proportion of laser points reflected at the 60th height percentile. The accuracy of classification corresponded to the validation results of earlier ALS-based studies on the classification of individual deciduous trees to tree species. Full article
(This article belongs to the Special Issue Remote Sensing of Land Surface Properties, Patterns and Processes)
Open AccessArticle
Free Base Porphyrins as Ionophores for Heavy Metal Sensors
Sensors 2008, 8(8), 4995-5004; https://doi.org/10.3390/s8084995
Received: 25 July 2008 / Revised: 13 August 2008 / Accepted: 21 August 2008 / Published: 25 August 2008
Cited by 26 | Viewed by 8451 | PDF Full-text (125 KB) | HTML Full-text | XML Full-text
Abstract
Two functionalized porphyrins: 5,10,15,20-tetrakis(3,4-dimethoxyphenyl) porphyrin (A) and 5,10,15,20-tetrakis(3-hydroxyphenyl)porphyrin (B) obtained and characterized by us were used as ionophores (I) for preparing PVC-based membrane sensors selective to Ag+, Pb2+ and Cu2+. The membranes were prepared using three different plasticizers: [...] Read more.
Two functionalized porphyrins: 5,10,15,20-tetrakis(3,4-dimethoxyphenyl) porphyrin (A) and 5,10,15,20-tetrakis(3-hydroxyphenyl)porphyrin (B) obtained and characterized by us were used as ionophores (I) for preparing PVC-based membrane sensors selective to Ag+, Pb2+ and Cu2+. The membranes were prepared using three different plasticizers: (bis(2-ethylhexyl)sebacate (DOS), dioctylphtalate (DOP), o-nitrophenyl octyl ether (NPOE) and potassium tetrakis(4-chlorophenyl)borate (KTClPB) as additive. The functional parameters (linear concentration range, slope and selectivity) of the sensors with membrane composition: (I:PVC:KTClPB:Plasticizer) in different ratios were investigated. The best results were obtained for the membranes in the ratio I:PVC:KTClPB:Plasticizer 10:165:5:330. The influence of pH on the sensors response was studied. The sensors were used for a period of four months and their utility has been tested on synthetic and real samples. Full article
Open AccessArticle
Mapping Regional Distribution of a Single Tree Species: Whitebark Pine in the Greater Yellowstone Ecosystem
Sensors 2008, 8(8), 4983-4994; https://doi.org/10.3390/s8084983
Received: 25 July 2008 / Revised: 15 August 2008 / Accepted: 21 August 2008 / Published: 25 August 2008
Cited by 16 | Viewed by 7107 | PDF Full-text (611 KB) | HTML Full-text | XML Full-text
Abstract
Moderate resolution satellite imagery traditionally has been thought to be inadequate for mapping vegetation at the species level. This has made comprehensive mapping of regional distributions of sensitive species, such as whitebark pine, either impractical or extremely time consuming. We sought to determine [...] Read more.
Moderate resolution satellite imagery traditionally has been thought to be inadequate for mapping vegetation at the species level. This has made comprehensive mapping of regional distributions of sensitive species, such as whitebark pine, either impractical or extremely time consuming. We sought to determine whether using a combination of moderate resolution satellite imagery (Landsat Enhanced Thematic Mapper Plus), extensive stand data collected by land management agencies for other purposes, and modern statistical classification techniques (boosted classification trees) could result in successful mapping of whitebark pine. Overall classification accuracies exceeded 90%, with similar individual class accuracies. Accuracies on a localized basis varied based on elevation. Accuracies also varied among administrative units, although we were not able to determine whether these differences related to inherent spatial variations or differences in the quality of available reference data. Full article
Open AccessReview
Chemical Sensors Based on Cyclodextrin Derivatives
Sensors 2008, 8(8), 4961-4982; https://doi.org/10.3390/s8084961
Received: 28 July 2008 / Revised: 20 August 2008 / Accepted: 20 August 2008 / Published: 25 August 2008
Cited by 180 | Viewed by 10361 | PDF Full-text (1815 KB) | HTML Full-text | XML Full-text
Abstract
This review focuses on chemical sensors based on cyclodextrin (CD) derivatives. This has been a field of classical interest, and is now of current interest for numerous scientists. First, typical chemical sensors using chromophore appended CDs are mentioned. Various “turn-off” and “turn-on” fluorescent [...] Read more.
This review focuses on chemical sensors based on cyclodextrin (CD) derivatives. This has been a field of classical interest, and is now of current interest for numerous scientists. First, typical chemical sensors using chromophore appended CDs are mentioned. Various “turn-off” and “turn-on” fluorescent chemical sensors, in which fluorescence intensity was decreased or increased by complexation with guest molecules, respectively, were synthesized. Dye modified CDs and photoactive metal ion-ligand complex appended CDs, metallocyclodextrins, were also applied for chemical sensors. Furthermore, recent novel approaches to chemical sensing systems using supramolecular structures such as CD dimers, trimers and cooperative binding systems of CDs with the other macrocycle [2]rotaxane and supramolecular polymers consisting of CD units are mentioned. New chemical sensors using hybrids of CDs with p-conjugated polymers, peptides, DNA, nanocarbons and nanoparticles are also described in this review. Full article
(This article belongs to the Special Issue Molecular Recognition and Sensors, Including Molecular Imprinting)
Open AccessArticle
Ship Detection in SAR Image Based on the Alpha-stable Distribution
Sensors 2008, 8(8), 4948-4960; https://doi.org/10.3390/s8084948
Received: 19 June 2008 / Revised: 18 July 2008 / Accepted: 19 July 2008 / Published: 22 August 2008
Cited by 55 | Viewed by 8239 | PDF Full-text (1534 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alphastable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background [...] Read more.
This paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alphastable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle
Empirical Retrieval of Surface Melt Magnitude from Coupled MODIS Optical and Thermal Measurements over the Greenland Ice Sheet during the 2001 Ablation Season
Sensors 2008, 8(8), 4915-4947; https://doi.org/10.3390/s8084915
Received: 3 July 2008 / Revised: 22 July 2008 / Accepted: 25 August 2008 / Published: 22 August 2008
Cited by 4 | Viewed by 7643 | PDF Full-text (3372 KB) | HTML Full-text | XML Full-text
Abstract
Accelerated ice flow near the equilibrium line of west-central Greenland Ice Sheet (GIS) has been attributed to an increase in infiltrated surface melt water as a response to climate warming. The assessment of surface melting events must be more than the detection of [...] Read more.
Accelerated ice flow near the equilibrium line of west-central Greenland Ice Sheet (GIS) has been attributed to an increase in infiltrated surface melt water as a response to climate warming. The assessment of surface melting events must be more than the detection of melt onset or extent. Retrieval of surface melt magnitude is necessary to improve understanding of ice sheet flow and surface melt coupling. In this paper, we report on a new technique to quantify the magnitude of surface melt. Cloud-free dates of June 10, July 5, 7, 9, and 11, 2001 Moderate Resolution Imaging Spectroradiometer (MODIS) daily reflectance Band 5 (1.230-1.250μm) and surface temperature images rescaled to 1km over western Greenland were used in the retrieval algorithm. An optical-thermal feature space partitioned as a function of melt magnitude was derived using a one-dimensional thermal snowmelt model (SNTHERM89). SNTHERM89 was forced by hourly meteorological data from the Greenland Climate Network (GC-Net) at reference sites spanning dry snow, percolation, and wet snow zones in the Jakobshavn drainage basin in western GIS. Melt magnitude or effective melt (E-melt) was derived for satellite composite periods covering May, June, and July displaying low fractions (0-1%) at elevations greater than 2500m and fractions at or greater than 15% at elevations lower than 1000m assessed for only the upper 5 cm of the snow surface. Validation of E-melt involved comparison of intensity to dry and wet zones determined from QSCAT backscatter. Higher intensities (> 8%) were distributed in wet snow zones, while lower intensities were grouped in dry zones at a first order accuracy of ~ ±2%. Full article
(This article belongs to the Special Issue Remote Sensing of Land Surface Properties, Patterns and Processes)
Open AccessArticle
SAR Observation and Modeling of Gap Winds in the Prince William Sound of Alaska
Sensors 2008, 8(8), 4894-4914; https://doi.org/10.3390/s8084894
Received: 12 July 2008 / Revised: 19 August 2008 / Accepted: 20 August 2008 / Published: 22 August 2008
Cited by 12 | Viewed by 6863 | PDF Full-text (6595 KB) | HTML Full-text | XML Full-text
Abstract
Alaska’s Prince William Sound (PWS) is a unique locale tending to have strong gap winds, especially in the winter season. To characterize and understand these strong surface winds, which have great impacts on the local marine and aviation activities, the surface wind retrieval [...] Read more.
Alaska’s Prince William Sound (PWS) is a unique locale tending to have strong gap winds, especially in the winter season. To characterize and understand these strong surface winds, which have great impacts on the local marine and aviation activities, the surface wind retrieval from the Synthetic Aperture Radar data (SAR-wind) is combined with a numerical mesoscale model. Helped with the SAR-wind observations, the mesoscale model is used to study cases of strong winds and relatively weak winds to depict the nature of these winds, including the area of extent and possible causes of the wind regimes. The gap winds from the Wells Passage and the Valdez Arm are the most dominant gap winds in PWS. Though the Valdez Arm is north-south trending and Wells Passage is east-west oriented, gap winds often develop simultaneously in these two places when a low pressure system is present in the Northern Gulf of Alaska. These two gap winds often converge at the center of PWS and extend further out of the Sound through the Hinchinbrook Entrance. The pressure gradients imposed over these areas are the main driving forces for these gap winds. Additionally, the drainage from the upper stream glaciers and the blocking effect of the banks of the Valdez Arm probably play an important role in enhancing the gap wind. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle
Estimation of Phytoplankton Responses to Hurricane Gonu over the Arabian Sea Based on Ocean Color Data
Sensors 2008, 8(8), 4878-4893; https://doi.org/10.3390/s8084878
Received: 11 June 2008 / Revised: 14 August 2008 / Accepted: 15 August 2008 / Published: 21 August 2008
Cited by 23 | Viewed by 8323 | PDF Full-text (1079 KB) | HTML Full-text | XML Full-text
Abstract
In this study the authors investigated phytoplankton variations in the Arabian Sea associated with Hurricane Gonu using remote-sensing data of chlorophyll-a (Chl-a), sea surface temperature (SST) and winds. Additional data sets used for the study included the hurricane and Conductivity-Temperature-Depth [...] Read more.
In this study the authors investigated phytoplankton variations in the Arabian Sea associated with Hurricane Gonu using remote-sensing data of chlorophyll-a (Chl-a), sea surface temperature (SST) and winds. Additional data sets used for the study included the hurricane and Conductivity-Temperature-Depth data. Hurricane Gonu, presenting extremely powerful wind intensity, originated over the central Arabian Sea (near 67.7ºE, 15.1ºN) on June 2, 2007; it traveled along a northwestward direction and made landfall in Iran around June 7. Before Hurricane Gonu, Chl-a data indicated relatively low phytoplankton biomass (0.05-0.2 mg m-3), along with generally high SST (>28.5 ºC) and weak wind (<10 m s-1) in the Arabian Sea. Shortly after Gonu’s passage, two phytoplankton blooms were observed northeast of Oman (Chl-a of 3.5 mg m-3) and in the eastern central Arabian Sea (Chl-a of 0.4 mg m-3), with up to 10-fold increase in surface Chl-a concentrations, respectively. The Chl-a in the two post-hurricane blooms were 46% and 42% larger than those in June of other years, respectively. The two blooms may be attributed to the storm-induced nutrient uptake, since hurricane can influence intensively both dynamical and biological processes through vertical mixing and Ekman Pumping. Full article
(This article belongs to the Special Issue Ocean Remote Sensing)
Open AccessArticle
A Fast Inspection of Tool Electrode and Drilling Depth in EDM Drilling by Detection Line Algorithm
Sensors 2008, 8(8), 4866-4877; https://doi.org/10.3390/s8084866
Received: 1 July 2008 / Revised: 12 August 2008 / Accepted: 15 August 2008 / Published: 21 August 2008
Cited by 3 | Viewed by 6840 | PDF Full-text (662 KB) | HTML Full-text | XML Full-text
Abstract
The purpose of this study was to develop a novel measurement method using a machine vision system. Besides using image processing techniques, the proposed system employs a detection line algorithm that detects the tool electrode length and drilling depth of a workpiece accurately [...] Read more.
The purpose of this study was to develop a novel measurement method using a machine vision system. Besides using image processing techniques, the proposed system employs a detection line algorithm that detects the tool electrode length and drilling depth of a workpiece accurately and effectively. Different boundaries of areas on the tool electrode are defined: a baseline between base and normal areas, a ND-line between normal and drilling areas (accumulating carbon area), and a DD-line between drilling area and dielectric fluid droplet on the electrode tip. Accordingly, image processing techniques are employed to extract a tool electrode image, and the centroid, eigenvector, and principle axis of the tool electrode are determined. The developed detection line algorithm (DLA) is then used to detect the baseline, ND-line, and DD-line along the direction of the principle axis. Finally, the tool electrode length and drilling depth of the workpiece are estimated via detected baseline, ND-line, and DD-line. Experimental results show good accuracy and efficiency in estimation of the tool electrode length and drilling depth under different conditions. Hence, this research may provide a reference for industrial application in EDM drilling measurement. Full article
Open AccessArticle
Using the Remote Sensing and GIS Technology for Erosion Risk Mapping of Kartalkaya Dam Watershed in Kahramanmaras, Turkey
Sensors 2008, 8(8), 4851-4865; https://doi.org/10.3390/s8084851
Received: 11 June 2008 / Revised: 20 July 2008 / Accepted: 24 July 2008 / Published: 21 August 2008
Cited by 32 | Viewed by 7834 | PDF Full-text (361 KB) | HTML Full-text | XML Full-text
Abstract
The soil erosion is the most serious environmental problem in watershed areas in Turkey. The main factors affecting the amount of soil erosion include vegetation cover, topography, soil, and climate. In order to describe the areas with high soil erosion risks and to [...] Read more.
The soil erosion is the most serious environmental problem in watershed areas in Turkey. The main factors affecting the amount of soil erosion include vegetation cover, topography, soil, and climate. In order to describe the areas with high soil erosion risks and to develop adequate erosion prevention measures in the watersheds of dams, erosion risk maps should be generated considering these factors. Remote Sensing (RS) and Geographic Information System (GIS) technologies were used for erosion risk mapping in Kartalkaya Dam Watershed of Kahramanmaras, Turkey, based on the methodology implemented in COoRdination of INformation on the Environment (CORINE) model. ASTER imagery was used to generate a land use/cover classification in ERDAS Imagine. The digital maps of the other factors (topography, soil types, and climate) were generated in ArcGIS v9.2, and were then integrated as CORINE input files to produce erosion risk maps. The results indicate that 33.82%, 35.44%, and 30.74% of the study area were under low, moderate, and high actual erosion risks, respectively. The CORINE model integrated with RS and GIS technologies has great potential for producing accurate and inexpensive erosion risk maps in Turkey. Full article
Open AccessArticle
Modelling Amperometric Biosensors Based on Chemically Modified Electrodes
Sensors 2008, 8(8), 4800-4820; https://doi.org/10.3390/s8084800
Received: 18 April 2008 / Accepted: 28 July 2008 / Published: 19 August 2008
Cited by 18 | Viewed by 7097 | PDF Full-text (300 KB) | HTML Full-text | XML Full-text
Abstract
The response of an amperometric biosensor based on a chemically modified electrode was modelled numerically. A mathematical model of the biosensor is based on a system of non-linear reaction-diffusion equations. The modelling biosensor comprises two compartments: an enzyme layer and an outer diffusion [...] Read more.
The response of an amperometric biosensor based on a chemically modified electrode was modelled numerically. A mathematical model of the biosensor is based on a system of non-linear reaction-diffusion equations. The modelling biosensor comprises two compartments: an enzyme layer and an outer diffusion layer. In order to define the main governing parameters the corresponding dimensionless mathematical model was derived. The digital simulation was carried out using the finite difference technique. The adequacy of the model was evaluated using analytical solutions known for very specific cases of the model parameters. By changing model parameters the output results were numerically analyzed at transition and steady state conditions. The influence of the substrate and mediator concentrations as well as of the thicknesses of the enzyme and diffusion layers on the biosensor response was investigated. Calculations showed complex kinetics of the biosensor response, especially when the biosensor acts under a mixed limitation of the diffusion and the enzyme interaction with the substrate. Full article
Open AccessArticle
An Interactive Technique for Cartographic Feature Extraction from Aerial and Satellite Image Sensors
Sensors 2008, 8(8), 4786-4799; https://doi.org/10.3390/s8084786
Received: 2 July 2008 / Revised: 24 July 2008 / Accepted: 11 August 2008 / Published: 19 August 2008
Cited by 2 | Viewed by 6654 | PDF Full-text (173 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, an interactive technique for extracting cartographic features from aerial and spatial images is presented. The method is essentially an interactive method of image region segmentation based on pixel grey level and texture information. The underlying segmentation method is seeded region [...] Read more.
In this paper, an interactive technique for extracting cartographic features from aerial and spatial images is presented. The method is essentially an interactive method of image region segmentation based on pixel grey level and texture information. The underlying segmentation method is seeded region growing. The criterion for growing regions is based on both texture and grey level, where texture is quantified using cooccurrence matrices. The Kullback distance is utilised with co-occurrence matrices in order to describe the image texture, then the Theory of Evidence is applied to merge the information coming from texture and grey level image from the RGB bands. Several results from aerial and spatial images that support the technique are presented Full article
Open AccessArticle
CO2 Selective Potentiometric Sensor in Thick-film Technology
Sensors 2008, 8(8), 4774-4785; https://doi.org/10.3390/s8084774
Received: 2 July 2008 / Revised: 8 August 2008 / Accepted: 8 August 2008 / Published: 19 August 2008
Cited by 18 | Viewed by 7730 | PDF Full-text (288 KB) | HTML Full-text | XML Full-text
Abstract
A potentiometric sensor device based on screen-printed Nasicon films was investigated. In order to transfer the promising sensor concept of an open sodium titanate reference to thick film technology, “sodium-rich” and “sodium-poor” formulations were compared. While the “sodium-rich” composition was found to react [...] Read more.
A potentiometric sensor device based on screen-printed Nasicon films was investigated. In order to transfer the promising sensor concept of an open sodium titanate reference to thick film technology, “sodium-rich” and “sodium-poor” formulations were compared. While the “sodium-rich” composition was found to react with the ion conducting Nasicon during thermal treatment, the “sodium-poor” reference mixture was identified as an appropriate reference composition. Screen-printed sensor devices were prepared and tested with respect to CO2 response, reproducibility, and cross-interference of oxygen. Excellent agreement with the theory was observed. With the integration of a screen-printed heater, sensor elements were operated actively heated in a cold gas stream. Full article
Open AccessArticle
Feature Reduction in Graph Analysis
Sensors 2008, 8(8), 4758-4773; https://doi.org/10.3390/s8084758
Received: 10 July 2008 / Revised: 7 August 2008 / Accepted: 7 August 2008 / Published: 19 August 2008
Cited by 2 | Viewed by 5159 | PDF Full-text (172 KB) | HTML Full-text | XML Full-text
Abstract
A common approach to improve medical image classification is to add more features to the classifiers; however, this increases the time required for preprocessing raw data and training the classifiers, and the increase in features is not always beneficial. The number of commonly [...] Read more.
A common approach to improve medical image classification is to add more features to the classifiers; however, this increases the time required for preprocessing raw data and training the classifiers, and the increase in features is not always beneficial. The number of commonly used features in the literature for training of image feature classifiers is over 50. Existing algorithms for selecting a subset of available features for image analysis fail to adequately eliminate redundant features. This paper presents a new selection algorithm based on graph analysis of interactions among features and between features to classifier decision. A modification of path analysis is done by applying regression analysis, multiple logistic and posterior Bayesian inference in order to eliminate features that provide the same contributions. A database of 113 mammograms from the Mammographic Image Analysis Society was used in the experiments. Tested on two classifiers – ANN and logistic regression – cancer detection accuracy (true positive and false-positive rates) using a 13-feature set selected by our algorithm yielded substantially similar accuracy as using a 26-feature set selected by SFS and results using all 50-features. However, the 13-feature greatly reduced the amount of computation needed. Full article
Open AccessArticle
Geodetic Network Design and Optimization on the Active Tuzla Fault (Izmir, Turkey) for Disaster Management
Sensors 2008, 8(8), 4742-4757; https://doi.org/10.3390/s8084742
Received: 31 March 2008 / Revised: 29 July 2008 / Accepted: 30 July 2008 / Published: 19 August 2008
Cited by 7 | Viewed by 8347 | PDF Full-text (412 KB) | HTML Full-text | XML Full-text
Abstract
Both seismological and geodynamic research emphasize that the Aegean Region, which comprises the Hellenic Arc, the Greek mainland and Western Turkey is the most seismically active region in Western Eurasia. The convergence of the Eurasian and African lithospheric plates forces a westward motion [...] Read more.
Both seismological and geodynamic research emphasize that the Aegean Region, which comprises the Hellenic Arc, the Greek mainland and Western Turkey is the most seismically active region in Western Eurasia. The convergence of the Eurasian and African lithospheric plates forces a westward motion on the Anatolian plate relative to the Eurasian one. Western Anatolia is a valuable laboratory for Earth Science research because of its complex geological structure. Izmir is a large city in Turkey with a population of about 2.5 million that is at great risk from big earthquakes. Unfortunately, previous geodynamics studies performed in this region are insufficient or cover large areas instead of specific faults. The Tuzla Fault, which is aligned trending NE–SW between the town of Menderes and Cape Doganbey, is an important fault in terms of seismic activity and its proximity to the city of Izmir. This study aims to perform a large scale investigation focusing on the Tuzla Fault and its vicinity for better understanding of the region's tectonics. In order to investigate the crustal deformation along the Tuzla Fault and Izmir Bay, a geodetic network has been designed and optimizations were performed. This paper suggests a schedule for a crustal deformation monitoring study which includes research on the tectonics of the region, network design and optimization strategies, theory and practice of processing. The study is also open for extension in terms of monitoring different types of fault characteristics. A one-dimensional fault model with two parameters – standard strike-slip model of dislocation theory in an elastic half-space – is formulated in order to determine which sites are suitable for the campaign based geodetic GPS measurements. Geodetic results can be used as a background data for disaster management systems. Full article
(This article belongs to the Special Issue Sensors for Disaster and Emergency Management Decision Making)
Open AccessArticle
Detecting Land Subsidence in Shanghai by PS-Networking SAR Interferometry
Sensors 2008, 8(8), 4725-4741; https://doi.org/10.3390/s8084725
Received: 14 July 2008 / Revised: 5 August 2008 / Accepted: 13 August 2008 / Published: 19 August 2008
Cited by 35 | Viewed by 8436 | PDF Full-text (4460 KB) | HTML Full-text | XML Full-text
Abstract
Existing studies have shown that satellite synthetic aperture radar (SAR) interferometry has two apparent drawbacks, i.e., temporal decorrelation and atmospheric contamination, in the application of deformation mapping. It is however possible to improve deformation analysis by tracking some natural or man-made objects with [...] Read more.
Existing studies have shown that satellite synthetic aperture radar (SAR) interferometry has two apparent drawbacks, i.e., temporal decorrelation and atmospheric contamination, in the application of deformation mapping. It is however possible to improve deformation analysis by tracking some natural or man-made objects with steady radar reflectivity, i.e., permanent scatterers (PS), in the frame of time series of SAR images acquired over the same area. For detecting land subsidence in Shanghai, China, this paper presents an attempt to explore an approach of PS-neighborhood networking SAR interferometry. With use of 26 ERS-1/2 SAR images acquired 1992 through 2002 over Shanghai, the analysis of subsiding process in time and space is performed on the basis of a strong network which is formed by connecting neighboring PSs according to a distance threshold. The linear and nonlinear subsidence, atmospheric effects as well as topographic errors can be separated effectively in this way. The subsidence velocity field in 10 years over Shanghai is also derived. It was found that the annual subsidence rates in the study area range from -2.1 to -0.6 cm/yr, and the averaged subsidence rate reaches -1.1 cm/yr. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle
Distributed Principal Component Analysis for Wireless Sensor Networks
Sensors 2008, 8(8), 4821-4850; https://doi.org/10.3390/s8084821
Received: 27 May 2008 / Revised: 29 July 2008 / Accepted: 4 July 2008 / Published: 11 August 2008
Cited by 39 | Viewed by 7806 | PDF Full-text (1046 KB) | HTML Full-text | XML Full-text
Abstract
The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like compression, event detection, and event recognition. This technique is based on a linear transform where the sensor measurements [...] Read more.
The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like compression, event detection, and event recognition. This technique is based on a linear transform where the sensor measurements are projected on a set of principal components. When sensor measurements are correlated, a small set of principal components can explain most of the measurements variability. This allows to significantly decrease the amount of radio communication and of energy consumption. In this paper, we show that the power iteration method can be distributed in a sensor network in order to compute an approximation of the principal components. The proposed implementation relies on an aggregation service, which has recently been shown to provide a suitable framework for distributing the computation of a linear transform within a sensor network. We also extend this previous work by providing a detailed analysis of the computational, memory, and communication costs involved. A compression experiment involving real data validates the algorithm and illustrates the tradeoffs between accuracy and communication costs. Full article
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