Spatial and temporal remote sensing data fusion for vegetation monitoring

USDA-ARS?s Scientific Manuscript database

The suite of available remote sensing instruments varies widely in terms of sensor characteristics, spatial resolution and acquisition frequency. For example, the Moderate-resolution Imaging Spectroradiometer (MODIS) provides daily global observations at 250m to 1km spatial resolution. While imagery...

High spatial resolution burn severity mapping of the New Jersey Pine Barrens with WorldView-3 near-infrared and shortwave infrared imagery

Treesearch

Timothy A. Warner; Nicholas S. Skowronski; Michael R. Gallagher

2017-01-01

The WorldView-3 (WV-3) sensor, launched in 2014, is the first highspatial resolution scanner to acquire imagery in the shortwave infrared (SWIR). A spectral ratio of the SWIR combined with the nearinfrared (NIR) can potentially provide an effective differentiation of wildfire burn severity. Previous high spatial resolution sensors were limited to data fromthe visible...

Fiber optic sensors for sub-centimeter spatially resolved measurements: Review and biomedical applications

NASA Astrophysics Data System (ADS)

Tosi, Daniele; Schena, Emiliano; Molardi, Carlo; Korganbayev, Sanzhar

2018-07-01

One of the current frontier of optical fiber sensors, and a unique asset of this sensing technology is the possibility to use a whole optical fiber, or optical fiber device, as a sensor. This solution allows shifting the whole sensing paradigm, from the measurement of a single physical parameter (such as temperature, strain, vibrations, pressure) to the measurement of a spatial distribution, or profiling, of a physical parameter along the fiber length. In the recent years, several technologies are achieving this task with unprecedentedly narrow spatial resolution, ranging from the sub-millimeter to the centimeter-level. In this work, we review the main fiber optic sensing technologies that achieve a narrow spatial resolution: Fiber Bragg Grating (FBG) dense arrays, chirped FBG (CFBG) sensors, optical frequency domain reflectometry (OFDR) based on either Rayleigh scattering or reflective elements, and microwave photonics (MWP). In the second part of the work, we present the impact of spatially dense fiber optic sensors in biomedical applications, where they find the main impact, presenting the key results obtained in thermo-therapies monitoring, high-resolution diagnostic, catheters monitoring, smart textiles, and other emerging applicative fields.

Urban-scale mapping of PM2.5 distribution via data fusion between high-density sensor network and MODIS Aerosol Optical Depth

NASA Astrophysics Data System (ADS)

Ba, Yu Tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Tang, Yu jia; Zhang, Da wei

2017-04-01

High-resolution mapping of PM2.5 is the prerequisite for precise analytics and subsequent anti-pollution interventions. Considering the large variances of particulate distribution, urban-scale mapping is challenging either with ground-based fixed stations, with satellites or via models. In this study, a dynamic fusion method between high-density sensor network and MODIS Aerosol Optical Depth (AOD) was introduced. The sensor network was deployed in Beijing ( > 1000 fixed monitors across 16000 km2 area) to provide raw observations with high temporal resolution (sampling interval < 1 hour), high spatial resolution in flat areas ( < 1 km), and low spatial resolution in mountainous areas ( > 5 km). The MODIS AOD was calibrated to provide distribution map with low temporal resolution (daily) and moderate spatial resolution ( = 3 km). By encoding the data quality and defects (e.g. could, reflectance, abnormal), a hybrid interpolation procedure with cross-validation generated PM2.5 distribution with both high temporal and spatial resolution. Several no-pollutant and high-pollution periods were tested to validate the proposed fusion method for capturing the instantaneous patterns of PM2.5 emission.

Effect of spatial resolution on remote sensing estimation of total evaporation in the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Shoko, Cletah; Clark, David; Mengistu, Michael; Dube, Timothy; Bulcock, Hartley

2015-01-01

This study evaluated the effect of two readily available multispectral sensors: the newly launched 30 m spatial resolution Landsat 8 and the long-serving 1000 m moderate resolution imaging spectroradiometer (MODIS) datasets in the spatial representation of total evaporation in the heterogeneous uMngeni catchment, South Africa, using the surface energy balance system model. The results showed that sensor spatial resolution plays a critical role in the accurate estimation of energy fluxes and total evaporation across a heterogeneous catchment. Landsat 8 estimates showed better spatial representation of the biophysical parameters and total evaporation for different land cover types, due to the relatively higher spatial resolution compared to the coarse spatial resolution MODIS sensor. Moreover, MODIS failed to capture the spatial variations of total evaporation estimates across the catchment. Analysis of variance (ANOVA) results showed that MODIS-based total evaporation estimates did not show any significant differences across different land cover types (one-way ANOVA; F1.924=1.412, p=0.186). However, Landsat 8 images yielded significantly different estimates between different land cover types (one-way ANOVA; F1.993=5.185, p<0.001). The validation results showed that Landsat 8 estimates were more comparable to eddy covariance (EC) measurements than the MODIS-based total evaporation estimates. EC measurement on May 23, 2013, was 3.8 mm/day, whereas the Landsat 8 estimate on the same day was 3.6 mm/day, with MODIS showing significantly lower estimates of 2.3 mm/day. The findings of this study underscore the importance of spatial resolution in estimating spatial variations of total evaporation at the catchment scale, thus, they provide critical information on the relevance of the readily available remote sensing products in water resources management in data-scarce environments.

High-resolution room-temperature sample scanning superconducting quantum interference device microscope configurable for geological and biomagnetic applications

NASA Astrophysics Data System (ADS)

Fong, L. E.; Holzer, J. R.; McBride, K. K.; Lima, E. A.; Baudenbacher, F.; Radparvar, M.

2005-05-01

We have developed a scanning superconducting quantum interference device (SQUID) microscope system with interchangeable sensor configurations for imaging magnetic fields of room-temperature (RT) samples with submillimeter resolution. The low-critical-temperature (Tc) niobium-based monolithic SQUID sensors are mounted on the tip of a sapphire and thermally anchored to the helium reservoir. A 25μm sapphire window separates the vacuum space from the RT sample. A positioning mechanism allows us to adjust the sample-to-sensor spacing from the top of the Dewar. We achieved a sensor-to-sample spacing of 100μm, which could be maintained for periods of up to four weeks. Different SQUID sensor designs are necessary to achieve the best combination of spatial resolution and field sensitivity for a given source configuration. For imaging thin sections of geological samples, we used a custom-designed monolithic low-Tc niobium bare SQUID sensor, with an effective diameter of 80μm, and achieved a field sensitivity of 1.5pT/Hz1/2 and a magnetic moment sensitivity of 5.4×10-18Am2/Hz1/2 at a sensor-to-sample spacing of 100μm in the white noise region for frequencies above 100Hz. Imaging action currents in cardiac tissue requires a higher field sensitivity, which can only be achieved by compromising spatial resolution. We developed a monolithic low-Tc niobium multiloop SQUID sensor, with sensor sizes ranging from 250μm to 1mm, and achieved sensitivities of 480-180fT /Hz1/2 in the white noise region for frequencies above 100Hz, respectively. For all sensor configurations, the spatial resolution was comparable to the effective diameter and limited by the sensor-to-sample spacing. Spatial registration allowed us to compare high-resolution images of magnetic fields associated with action currents and optical recordings of transmembrane potentials to study the bidomain nature of cardiac tissue or to match petrography to magnetic field maps in thin sections of geological samples.

Characterizing the Diurnal Cycle of Land Surface Temperature and Evapotranspiration at High Spatial Resolution Using Thermal Observations from sUAS.

NASA Astrophysics Data System (ADS)

Dutta, D.; Drewry, D.; Johnson, W. R.

2017-12-01

The surface temperature of plant canopies is an important indicator of the stomatal regulation of plant water use and the associated water flux from plants to atmosphere (evapotranspiration (ET)). Remotely sensed thermal observations using compact, low-cost, lightweight sensors from small unmanned aerial systems (sUAS) have the potential to provide surface temperature (ST) and ET estimates at unprecedented spatial and temporal resolutions, allowing us to characterize the intra-field diurnal variations in canopy ST and ET for a variety of vegetation systems. However, major challenges exist for obtaining accurate surface temperature estimates from low-cost uncooled microbolometer-type sensors. Here we describe the development of calibration methods using thermal chamber experiments, taking into account the ambient optics and sensor temperatures, and applying simple models of spatial non-uniformity correction to the sensor focal-plane-array. We present a framework that can be used to derive accurate surface temperatures using radiometric observations from low-cost sensors, and demonstrate this framework using a sUAS-mounted sensor across a diverse set of calibration and vegetation targets. Further, we demonstrate the use of the Surface Temperature Initiated Closure (STIC) model for computing spatially explicit, high spatial resolution ET estimates across several well-monitored agricultural systems, as driven by sUAS acquired surface temperatures. STIC provides a physically-based surface energy balance framework for the simultaneous retrieval of the surface and atmospheric vapor conductances and surface energy fluxes, by physically integrating radiometric surface temperature information into the Penman-Monteith equation. Results of our analysis over agricultural systems in Ames, IA and Davis, CA demonstrate the power of this approach for quantifying the intra-field spatial variability in the diurnal cycle of plant water use at sub-meter resolutions.

Demonstration of Airborne Wide Area Assessment Technologies at Pueblo Precision Bombing Ranges, Colorado. Hyperspectral Imaging, Version 2.0

DTIC Science & Technology

2007-09-27

the spatial and spectral resolution ...variety of geological and vegetation mapping efforts, the Hymap sensor offered the best available combination of spectral and spatial resolution , signal... The limitations of the technology currently relate to spatial and spectral resolution and geo- correction accuracy. Secondly, HSI datasets

Ultra-high resolution coded wavefront sensor.

PubMed

Wang, Congli; Dun, Xiong; Fu, Qiang; Heidrich, Wolfgang

2017-06-12

Wavefront sensors and more general phase retrieval methods have recently attracted a lot of attention in a host of application domains, ranging from astronomy to scientific imaging and microscopy. In this paper, we introduce a new class of sensor, the Coded Wavefront Sensor, which provides high spatio-temporal resolution using a simple masked sensor under white light illumination. Specifically, we demonstrate megapixel spatial resolution and phase accuracy better than 0.1 wavelengths at reconstruction rates of 50 Hz or more, thus opening up many new applications from high-resolution adaptive optics to real-time phase retrieval in microscopy.

Benefits of GMR sensors for high spatial resolution NDT applications

NASA Astrophysics Data System (ADS)

Pelkner, M.; Stegemann, R.; Sonntag, N.; Pohl, R.; Kreutzbruck, M.

2018-04-01

Magneto resistance sensors like GMR (giant magneto resistance) or TMR (tunnel magneto resistance) are widely used in industrial applications; examples are position measurement and read heads of hard disk drives. However, in case of non-destructive testing (NDT) applications these sensors, although their properties are outstanding like high spatial resolution, high field sensitivity, low cost and low energy consumption, never reached a technical transfer to an application beyond scientific scope. This paper deals with benefits of GMR/TMR sensors in terms of high spatial resolution testing for different NDT applications. The first example demonstrates the preeminent advantages of MR-elements compared with conventional coils used in eddy current testing (ET). The probe comprises one-wire excitation with an array of MR elements. This led to a better spatial resolution in terms of neighboring defects. The second section concentrates on MFL-testing (magnetic flux leakage) with active field excitation during and before testing. The latter illustrated the capability of highly resolved crack detection of a crossed notch. This example is best suited to show the ability of tiny magnetic field sensors for magnetic material characterization of a sample surface. Another example is based on characterization of samples after tensile test. Here, no external field is applied. The magnetization is only changed due to external load and magnetostriction leading to a field signature which GMR sensors can resolve. This gives access to internal changes of the magnetization state of the sample under test.

Multi-sensor fusion of Landsat 8 thermal infrared (TIR) and panchromatic (PAN) images.

PubMed

Jung, Hyung-Sup; Park, Sung-Whan

2014-12-18

Data fusion is defined as the combination of data from multiple sensors such that the resulting information is better than would be possible when the sensors are used individually. The multi-sensor fusion of panchromatic (PAN) and thermal infrared (TIR) images is a good example of this data fusion. While a PAN image has higher spatial resolution, a TIR one has lower spatial resolution. In this study, we have proposed an efficient method to fuse Landsat 8 PAN and TIR images using an optimal scaling factor in order to control the trade-off between the spatial details and the thermal information. We have compared the fused images created from different scaling factors and then tested the performance of the proposed method at urban and rural test areas. The test results show that the proposed method merges the spatial resolution of PAN image and the temperature information of TIR image efficiently. The proposed method may be applied to detect lava flows of volcanic activity, radioactive exposure of nuclear power plants, and surface temperature change with respect to land-use change.

Toroidal sensor arrays for real-time photoacoustic imaging

NASA Astrophysics Data System (ADS)

Bychkov, Anton S.; Cherepetskaya, Elena B.; Karabutov, Alexander A.; Makarov, Vladimir A.

2017-07-01

This article addresses theoretical and numerical investigation of image formation in photoacoustic (PA) imaging with complex-shaped concave sensor arrays. The spatial resolution and the size of sensitivity region of PA and laser ultrasonic (LU) imaging systems are assessed using sensitivity maps and spatial resolution maps in the image plane. This paper also discusses the relationship between the size of high-sensitivity regions and the spatial resolution of real-time imaging systems utilizing toroidal arrays. It is shown that the use of arrays with toroidal geometry significantly improves the diagnostic capabilities of PA and LU imaging to investigate biological objects, rocks, and composite materials.

Light-Addressable Potentiometric Sensors for Quantitative Spatial Imaging of Chemical Species.

PubMed

Yoshinobu, Tatsuo; Miyamoto, Ko-Ichiro; Werner, Carl Frederik; Poghossian, Arshak; Wagner, Torsten; Schöning, Michael J

2017-06-12

A light-addressable potentiometric sensor (LAPS) is a semiconductor-based chemical sensor, in which a measurement site on the sensing surface is defined by illumination. This light addressability can be applied to visualize the spatial distribution of pH or the concentration of a specific chemical species, with potential applications in the fields of chemistry, materials science, biology, and medicine. In this review, the features of this chemical imaging sensor technology are compared with those of other technologies. Instrumentation, principles of operation, and various measurement modes of chemical imaging sensor systems are described. The review discusses and summarizes state-of-the-art technologies, especially with regard to the spatial resolution and measurement speed; for example, a high spatial resolution in a submicron range and a readout speed in the range of several tens of thousands of pixels per second have been achieved with the LAPS. The possibility of combining this technology with microfluidic devices and other potential future developments are discussed.

Radiometric Calibration Assessment of Commercial High Spatial Resolution Multispectral Image Products

NASA Technical Reports Server (NTRS)

Holekamp, Kara; Aaron, David; Thome, Kurtis

2006-01-01

Radiometric calibration of commercial imaging satellite products is required to ensure that science and application communities can better understand their properties. Inaccurate radiometric calibrations can lead to erroneous decisions and invalid conclusions and can limit intercomparisons with other systems. To address this calibration need, satellite at-sensor radiance values were compared to those estimated by each independent team member to determine the sensor's radiometric accuracy. The combined results of this evaluation provide the user community with an independent assessment of these commercially available high spatial resolution sensors' absolute calibration values.

Sensitivity encoded silicon photomultiplier--a new sensor for high-resolution PET-MRI.

PubMed

Schulz, Volkmar; Berker, Yannick; Berneking, Arne; Omidvari, Negar; Kiessling, Fabian; Gola, Alberto; Piemonte, Claudio

2013-07-21

Detectors for simultaneous positron emission tomography and magnetic resonance imaging in particular with sub-mm spatial resolution are commonly composed of scintillator crystal arrays, readout via arrays of solid state sensors, such as avalanche photo diodes (APDs) or silicon photomultipliers (SiPMs). Usually a light guide between the crystals and the sensor is used to enable the identification of crystals which are smaller than the sensor elements. However, this complicates crystal identification at the gaps and edges of the sensor arrays. A solution is to use as many sensors as crystals with a direct coupling, which unfortunately increases the complexity and power consumption of the readout electronics. Since 1997, position-sensitive APDs have been successfully used to identify sub-mm crystals. Unfortunately, these devices show a limitation in their time resolution and a degradation of spatial resolution when placed in higher magnetic fields. To overcome these limitations, this paper presents a new sensor concept that extends conventional SiPMs by adding position information via the spatial encoding of the channel sensitivity. The concept allows a direct coupling of high-resolution crystal arrays to the sensor with a reduced amount of readout channels. The theory of sensitivity encoding is detailed and linked to compressed sensing to compute unique sparse solutions. Two devices have been designed using one- and two-dimensional linear sensitivity encoding with eight and four readout channels, respectively. Flood histograms of both devices show the capability to precisely identify all 4 × 4 LYSO crystals with dimensions of 0.93 × 0.93 × 10 mm(3). For these crystals, the energy and time resolution (MV ± SD) of the devices with one (two)-dimensional encoding have been measured to be 12.3 · (1 ± 0.047)% (13.7 · (1 ± 0.047)%) around 511 keV with a paired coincidence time resolution (full width at half maximum) of 462 · (1 ± 0.054) ps (452 · (1 ± 0.078) ps).

Sensitivity encoded silicon photomultiplier—a new sensor for high-resolution PET-MRI

NASA Astrophysics Data System (ADS)

Schulz, Volkmar; Berker, Yannick; Berneking, Arne; Omidvari, Negar; Kiessling, Fabian; Gola, Alberto; Piemonte, Claudio

2013-07-01

Detectors for simultaneous positron emission tomography and magnetic resonance imaging in particular with sub-mm spatial resolution are commonly composed of scintillator crystal arrays, readout via arrays of solid state sensors, such as avalanche photo diodes (APDs) or silicon photomultipliers (SiPMs). Usually a light guide between the crystals and the sensor is used to enable the identification of crystals which are smaller than the sensor elements. However, this complicates crystal identification at the gaps and edges of the sensor arrays. A solution is to use as many sensors as crystals with a direct coupling, which unfortunately increases the complexity and power consumption of the readout electronics. Since 1997, position-sensitive APDs have been successfully used to identify sub-mm crystals. Unfortunately, these devices show a limitation in their time resolution and a degradation of spatial resolution when placed in higher magnetic fields. To overcome these limitations, this paper presents a new sensor concept that extends conventional SiPMs by adding position information via the spatial encoding of the channel sensitivity. The concept allows a direct coupling of high-resolution crystal arrays to the sensor with a reduced amount of readout channels. The theory of sensitivity encoding is detailed and linked to compressed sensing to compute unique sparse solutions. Two devices have been designed using one- and two-dimensional linear sensitivity encoding with eight and four readout channels, respectively. Flood histograms of both devices show the capability to precisely identify all 4 × 4 LYSO crystals with dimensions of 0.93 × 0.93 × 10 mm3. For these crystals, the energy and time resolution (MV ± SD) of the devices with one (two)-dimensional encoding have been measured to be 12.3 · (1 ± 0.047)% (13.7 · (1 ± 0.047)%) around 511 keV with a paired coincidence time resolution (full width at half maximum) of 462 · (1 ± 0.054) ps (452 · (1 ± 0.078) ps).

Atomic-Scale Nuclear Spin Imaging Using Quantum-Assisted Sensors in Diamond

NASA Astrophysics Data System (ADS)

Ajoy, A.; Bissbort, U.; Lukin, M. D.; Walsworth, R. L.; Cappellaro, P.

2015-01-01

Nuclear spin imaging at the atomic level is essential for the understanding of fundamental biological phenomena and for applications such as drug discovery. The advent of novel nanoscale sensors promises to achieve the long-standing goal of single-protein, high spatial-resolution structure determination under ambient conditions. In particular, quantum sensors based on the spin-dependent photoluminescence of nitrogen-vacancy (NV) centers in diamond have recently been used to detect nanoscale ensembles of external nuclear spins. While NV sensitivity is approaching single-spin levels, extracting relevant information from a very complex structure is a further challenge since it requires not only the ability to sense the magnetic field of an isolated nuclear spin but also to achieve atomic-scale spatial resolution. Here, we propose a method that, by exploiting the coupling of the NV center to an intrinsic quantum memory associated with the nitrogen nuclear spin, can reach a tenfold improvement in spatial resolution, down to atomic scales. The spatial resolution enhancement is achieved through coherent control of the sensor spin, which creates a dynamic frequency filter selecting only a few nuclear spins at a time. We propose and analyze a protocol that would allow not only sensing individual spins in a complex biomolecule, but also unraveling couplings among them, thus elucidating local characteristics of the molecule structure.

Novel eye-safe line scanning 3D laser-radar

NASA Astrophysics Data System (ADS)

Eberle, B.; Kern, Tobias; Hammer, Marcus; Schwanke, Ullrich; Nowak, Heinrich

2014-10-01

Today, the civil market provides quite a number of different 3D-Sensors covering ranges up to 1 km. Typically these sensors are based on single element detectors which suffer from the drawback of spatial resolution at larger distances. Tasks demanding reliable object classification at long ranges can be fulfilled only by sensors consisting of detector arrays. They ensure sufficient frame rates and high spatial resolution. Worldwide there are many efforts in developing 3D-detectors, based on two-dimensional arrays. This paper presents first results on the performance of a recently developed 3D imaging laser radar sensor, working in the short wave infrared (SWIR) at 1.5 μm. It consists of a novel Cadmium Mercury Telluride (CMT) linear array APD detector with 384x1 elements at a pitch of 25 μm, developed by AIM Infrarot Module GmbH. The APD elements are designed to work in the linear (non-Geiger) mode. Each pixel will provide the time of flight measurement, and, due to the linear detection mode, allowing the detection of three successive echoes. The resolution in depth is 15 cm, the maximum repetition rate is 4 kHz. We discuss various sensor concepts regarding possible applications and their dependence on system parameters like field of view, frame rate, spatial resolution and range of operation.

Lensfree on-chip microscopy over a wide field-of-view using pixel super-resolution

PubMed Central

Bishara, Waheb; Su, Ting-Wei; Coskun, Ahmet F.; Ozcan, Aydogan

2010-01-01

We demonstrate lensfree holographic microscopy on a chip to achieve ~0.6 µm spatial resolution corresponding to a numerical aperture of ~0.5 over a large field-of-view of ~24 mm2. By using partially coherent illumination from a large aperture (~50 µm), we acquire lower resolution lensfree in-line holograms of the objects with unit fringe magnification. For each lensfree hologram, the pixel size at the sensor chip limits the spatial resolution of the reconstructed image. To circumvent this limitation, we implement a sub-pixel shifting based super-resolution algorithm to effectively recover much higher resolution digital holograms of the objects, permitting sub-micron spatial resolution to be achieved across the entire sensor chip active area, which is also equivalent to the imaging field-of-view (24 mm2) due to unit magnification. We demonstrate the success of this pixel super-resolution approach by imaging patterned transparent substrates, blood smear samples, as well as Caenoharbditis Elegans. PMID:20588977

Fusion of spectral and panchromatic images using false color mapping and wavelet integrated approach

NASA Astrophysics Data System (ADS)

Zhao, Yongqiang; Pan, Quan; Zhang, Hongcai

2006-01-01

With the development of sensory technology, new image sensors have been introduced that provide a greater range of information to users. But as the power limitation of radiation, there will always be some trade-off between spatial and spectral resolution in the image captured by specific sensors. Images with high spatial resolution can locate objects with high accuracy, whereas images with high spectral resolution can be used to identify the materials. Many applications in remote sensing require fusing low-resolution imaging spectral images with panchromatic images to identify materials at high resolution in clutter. A pixel-based false color mapping and wavelet transform integrated fusion algorithm is presented in this paper, the resulting images have a higher information content than each of the original images and retain sensor-specific image information. The simulation results show that this algorithm can enhance the visibility of certain details and preserve the difference of different materials.

Higher resolution satellite remote sensing and the impact on image mapping

USGS Publications Warehouse

Watkins, Allen H.; Thormodsgard, June M.

1987-01-01

Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges.The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

HPT: A High Spatial Resolution Multispectral Sensor for Microsatellite Remote Sensing

PubMed Central

Takahashi, Yukihiro; Sakamoto, Yuji; Kuwahara, Toshinori

2018-01-01

Although nano/microsatellites have great potential as remote sensing platforms, the spatial and spectral resolutions of an optical payload instrument are limited. In this study, a high spatial resolution multispectral sensor, the High-Precision Telescope (HPT), was developed for the RISING-2 microsatellite. The HPT has four image sensors: three in the visible region of the spectrum used for the composition of true color images, and a fourth in the near-infrared region, which employs liquid crystal tunable filter (LCTF) technology for wavelength scanning. Band-to-band image registration methods have also been developed for the HPT and implemented in the image processing procedure. The processed images were compared with other satellite images, and proven to be useful in various remote sensing applications. Thus, LCTF technology can be considered an innovative tool that is suitable for future multi/hyperspectral remote sensing by nano/microsatellites. PMID:29463022

Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study

USGS Publications Warehouse

Chander, G.; Helder, D.L.; Aaron, David; Mishra, N.; Shrestha, A.K.

2013-01-01

Cross-calibration of satellite sensors permits the quantitative comparison of measurements obtained from different Earth Observing (EO) systems. Cross-calibration studies usually use simultaneous or near-simultaneous observations from several spaceborne sensors to develop band-by-band relationships through regression analysis. The investigation described in this paper focuses on evaluation of the uncertainties inherent in the cross-calibration process, including contributions due to different spectral responses, spectral resolution, spectral filter shift, geometric misregistrations, and spatial resolutions. The hyperspectral data from the Environmental Satellite SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY and the EO-1 Hyperion, along with the relative spectral responses (RSRs) from the Landsat 7 Enhanced Thematic Mapper (TM) Plus and the Terra Moderate Resolution Imaging Spectroradiometer sensors, were used for the spectral uncertainty study. The data from Landsat 5 TM over five representative land cover types (desert, rangeland, grassland, deciduous forest, and coniferous forest) were used for the geometric misregistrations and spatial-resolution study. The spectral resolution uncertainty was found to be within 0.25%, spectral filter shift within 2.5%, geometric misregistrations within 0.35%, and spatial-resolution effects within 0.1% for the Libya 4 site. The one-sigma uncertainties presented in this paper are uncorrelated, and therefore, the uncertainties can be summed orthogonally. Furthermore, an overall total uncertainty was developed. In general, the results suggested that the spectral uncertainty is more dominant compared to other uncertainties presented in this paper. Therefore, the effect of the sensor RSR differences needs to be quantified and compensated to avoid large uncertainties in cross-calibration results.

Enhancing hyperspectral spatial resolution using multispectral image fusion: A wavelet approach

NASA Astrophysics Data System (ADS)

Jazaeri, Amin

High spectral and spatial resolution images have a significant impact in remote sensing applications. Because both spatial and spectral resolutions of spaceborne sensors are fixed by design and it is not possible to further increase the spatial or spectral resolution, techniques such as image fusion must be applied to achieve such goals. This dissertation introduces the concept of wavelet fusion between hyperspectral and multispectral sensors in order to enhance the spectral and spatial resolution of a hyperspectral image. To test the robustness of this concept, images from Hyperion (hyperspectral sensor) and Advanced Land Imager (multispectral sensor) were first co-registered and then fused using different wavelet algorithms. A regression-based fusion algorithm was also implemented for comparison purposes. The results show that the fused images using a combined bi-linear wavelet-regression algorithm have less error than other methods when compared to the ground truth. In addition, a combined regression-wavelet algorithm shows more immunity to misalignment of the pixels due to the lack of proper registration. The quantitative measures of average mean square error show that the performance of wavelet-based methods degrades when the spatial resolution of hyperspectral images becomes eight times less than its corresponding multispectral image. Regardless of what method of fusion is utilized, the main challenge in image fusion is image registration, which is also a very time intensive process. Because the combined regression wavelet technique is computationally expensive, a hybrid technique based on regression and wavelet methods was also implemented to decrease computational overhead. However, the gain in faster computation was offset by the introduction of more error in the outcome. The secondary objective of this dissertation is to examine the feasibility and sensor requirements for image fusion for future NASA missions in order to be able to perform onboard image fusion. In this process, the main challenge of image registration was resolved by registering the input images using transformation matrices of previously acquired data. The composite image resulted from the fusion process remarkably matched the ground truth, indicating the possibility of real time onboard fusion processing.

Multi-image acquisition-based distance sensor using agile laser spot beam.

PubMed

Riza, Nabeel A; Amin, M Junaid

2014-09-01

We present a novel laser-based distance measurement technique that uses multiple-image-based spatial processing to enable distance measurements. Compared with the first-generation distance sensor using spatial processing, the modified sensor is no longer hindered by the classic Rayleigh axial resolution limit for the propagating laser beam at its minimum beam waist location. The proposed high-resolution distance sensor design uses an electronically controlled variable focus lens (ECVFL) in combination with an optical imaging device, such as a charged-coupled device (CCD), to produce and capture different laser spot size images on a target with these beam spot sizes different from the minimal spot size possible at this target distance. By exploiting the unique relationship of the target located spot sizes with the varying ECVFL focal length for each target distance, the proposed distance sensor can compute the target distance with a distance measurement resolution better than the axial resolution via the Rayleigh resolution criterion. Using a 30 mW 633 nm He-Ne laser coupled with an electromagnetically actuated liquid ECVFL, along with a 20 cm focal length bias lens, and using five spot images captured per target position by a CCD-based Nikon camera, a proof-of-concept proposed distance sensor is successfully implemented in the laboratory over target ranges from 10 to 100 cm with a demonstrated sub-cm axial resolution, which is better than the axial Rayleigh resolution limit at these target distances. Applications for the proposed potentially cost-effective distance sensor are diverse and include industrial inspection and measurement and 3D object shape mapping and imaging.

A technique for enhancing and matching the resolution of microwave measurements from the SSM/I instrument

NASA Technical Reports Server (NTRS)

Robinson, Wayne D.; Kummerrow, Christian; Olson, William S.

1992-01-01

A correction technique is presented for matching the resolution of all the frequencies of the satelliteborne Special Sensor Microwave/Imager (SSM/I) to the about-25-km spatial resolution of the 37-GHz channel. This entails, on the one hand, the enhancement of the spatial resolution of the 19- and 22-GHz channels, and on the other, the degrading of that of the 85-GHz channel. The Backus and Gilbert (1970) approach is found to yield sufficient spatial resolution to render such a correction worthwhile.

Distributed optical fiber vibration sensor based on spectrum analysis of Polarization-OTDR system.

PubMed

Zhang, Ziyi; Bao, Xiaoyi

2008-07-07

A fully distributed optical fiber vibration sensor is demonstrated based on spectrum analysis of Polarization-OTDR system. Without performing any data averaging, vibration disturbances up to 5 kHz is successfully demonstrated in a 1km fiber link with 10m spatial resolution. The FFT is performed at each spatial resolution; the relation of the disturbance at each frequency component versus location allows detection of multiple events simultaneously with different and the same frequency components.

Effects of satellite image spatial aggregation and resolution on estimates of forest land area

Treesearch

M.D. Nelson; R.E. McRoberts; G.R. Holden; M.E. Bauer

2009-01-01

Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We...

Image-receptor performance: a comparison of Trophy RVG UI sensor and Kodak Ektaspeed Plus film.

PubMed

Ludlow, J; Mol, A

2001-01-01

Objective. This study compares the physical characteristics of the RVG UI sensor (RVG) with Ektaspeed Plus film. Dose-response curves were generated for film and for each of 6 available RVG modes. An aluminum step-wedge was used to evaluate exposure latitude. Spatial resolution was assessed by using a line-pair test tool. Latitude and resolution were assessed by observers for both modalities. The RVG was further characterized by its modulation transfer function. Exposure latitude was equal for film and RVG in the periodontal mode. Other gray scale modes demonstrated much lower latitude. The average maximum resolution was 15.3 line-pairs per millimeter (lp/mm) for RVG in high-resolution mode, 10.5 lp/mm for RVG in low-resolution mode, and 20 lp/mm for film (P <.0001). Modulation transfer function measurements supported the subjective assessments. In periodontal mode, the RVG UI sensor demonstrates exposure latitude similar to that of Ektaspeed Plus film. Film images exhibit significantly higher spatial resolution than the RVG images acquired in high-resolution mode.

High spatial resolution fiber optical sensors for simultaneous temperature and chemical sensing for energy industries

NASA Astrophysics Data System (ADS)

Yan, Aidong; Huang, Sheng; Li, Shuo; Zaghloul, Mohamed; Ohodnicki, Paul; Buric, Michael; Chen, Kevin P.

2017-05-01

This paper demonstrates optical fibers as high-temperature sensor platforms. Through engineering and onfiber integration of functional metal oxide sensory materials, we report the development of an integrated sensor solution to perform temperature and chemical measurements for high-temperature energy applications. Using the Rayleigh optical frequency domain reflectometry (OFDR) distributed sensing scheme, the temperature and hydrogen concentration were measured along the fiber. To overcome the weak Rayleighbackscattering intensity exhibited by conventional optical fibers, an ultrafast laser was used to enhance the Rayleigh scattering by a direct laser writing method. Using the Rayleigh-enhanced fiber as sensor platform, both temperature and hydrogen reaction were monitored at high temperature up to 750°C with 4-mm spatial resolution.

What is the spatial sampling of MISR?

Atmospheric Science Data Center

2014-12-08

... spatial resolution of the sensors without exceeding the data transfer quotas, MISR can be operated in two different data acquisition modes: ... data at the full resolution, but only for limited periods of time and therefore for limited regions, typically about 300 km in length (along ...

Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

NASA Astrophysics Data System (ADS)

Song, Huihui

Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat-MODIS image pairs, we build the corresponding relationship between the difference images of MODIS and ETM+ by training a low- and high-resolution dictionary pair from the given prior image pairs. In the second scenario, i.e., only one Landsat- MODIS image pair being available, we directly correlate MODIS and ETM+ data through an image degradation model. Then, the fusion stage is achieved by super-resolving the MODIS image combining the high-pass modulation in a two-layer fusion framework. Remarkably, the proposed spatial-temporal fusion methods form a unified framework for blending remote sensing images with phenology change or land-cover-type change. Based on the proposed spatial-temporal fusion models, we propose to monitor the land use/land cover changes in Shenzhen, China. As a fast-growing city, Shenzhen faces the problem of detecting the rapid changes for both rational city planning and sustainable development. However, the cloudy and rainy weather in region Shenzhen located makes the capturing circle of high-quality satellite images longer than their normal revisit periods. Spatial-temporal fusion methods are capable to tackle this problem by improving the spatial resolution of images with coarse spatial resolution but frequent temporal coverage, thereby making the detection of rapid changes possible. On two Landsat-MODIS datasets with annual and monthly changes, respectively, we apply the proposed spatial-temporal fusion methods to the task of multiple change detection. Afterward, we propose a novel spatial and spectral fusion method for satellite multispectral and hyperspectral (or high-spectral) images based on dictionary-pair learning and sparse non-negative matrix factorization. By combining the spectral information from hyperspectral image, which is characterized by low spatial resolution but high spectral resolution and abbreviated as LSHS, and the spatial information from multispectral image, which is featured by high spatial resolution but low spectral resolution and abbreviated as HSLS, this method aims to generate the fused data with both high spatial and high spectral resolutions. Motivated by the observation that each hyperspectral pixel can be represented by a linear combination of a few endmembers, this method first extracts the spectral bases of LSHS and HSLS images by making full use of the rich spectral information in LSHS data. The spectral bases of these two categories data then formulate a dictionary-pair due to their correspondence in representing each pixel spectra of LSHS data and HSLS data, respectively. Subsequently, the LSHS image is spatially unmixed by representing the HSLS image with respect to the corresponding learned dictionary to derive its representation coefficients. Combining the spectral bases of LSHS data and the representation coefficients of HSLS data, we finally derive the fused data characterized by the spectral resolution of LSHS data and the spatial resolution of HSLS data.

Performance of Orbital Neutron Instruments for Spatially Resolved Hydrogen Measurements of Airless Planetary Bodies

PubMed Central

Elphic, Richard C.; Feldman, William C.; Funsten, Herbert O.; Prettyman, Thomas H.

2010-01-01

Abstract Orbital neutron spectroscopy has become a standard technique for measuring planetary surface compositions from orbit. While this technique has led to important discoveries, such as the deposits of hydrogen at the Moon and Mars, a limitation is its poor spatial resolution. For omni-directional neutron sensors, spatial resolutions are 1–1.5 times the spacecraft's altitude above the planetary surface (or 40–600 km for typical orbital altitudes). Neutron sensors with enhanced spatial resolution have been proposed, and one with a collimated field of view is scheduled to fly on a mission to measure lunar polar hydrogen. No quantitative studies or analyses have been published that evaluate in detail the detection and sensitivity limits of spatially resolved neutron measurements. Here, we describe two complementary techniques for evaluating the hydrogen sensitivity of spatially resolved neutron sensors: an analytic, closed-form expression that has been validated with Lunar Prospector neutron data, and a three-dimensional modeling technique. The analytic technique, called the Spatially resolved Neutron Analytic Sensitivity Approximation (SNASA), provides a straightforward method to evaluate spatially resolved neutron data from existing instruments as well as to plan for future mission scenarios. We conclude that the existing detector—the Lunar Exploration Neutron Detector (LEND)—scheduled to launch on the Lunar Reconnaissance Orbiter will have hydrogen sensitivities that are over an order of magnitude poorer than previously estimated. We further conclude that a sensor with a geometric factor of ∼ 100 cm2 Sr (compared to the LEND geometric factor of ∼ 10.9 cm2 Sr) could make substantially improved measurements of the lunar polar hydrogen spatial distribution. Key Words: Planetary instrumentation—Planetary science—Moon—Spacecraft experiments—Hydrogen. Astrobiology 10, 183–200. PMID:20298147

Generating High-Temporal and Spatial Resolution TIR Image Data

NASA Astrophysics Data System (ADS)

Herrero-Huerta, M.; Lagüela, S.; Alfieri, S. M.; Menenti, M.

2017-09-01

Remote sensing imagery to monitor global biophysical dynamics requires the availability of thermal infrared data at high temporal and spatial resolution because of the rapid development of crops during the growing season and the fragmentation of most agricultural landscapes. Conversely, no single sensor meets these combined requirements. Data fusion approaches offer an alternative to exploit observations from multiple sensors, providing data sets with better properties. A novel spatio-temporal data fusion model based on constrained algorithms denoted as multisensor multiresolution technique (MMT) was developed and applied to generate TIR synthetic image data at both temporal and spatial high resolution. Firstly, an adaptive radiance model is applied based on spectral unmixing analysis of . TIR radiance data at TOA (top of atmosphere) collected by MODIS daily 1-km and Landsat - TIRS 16-day sampled at 30-m resolution are used to generate synthetic daily radiance images at TOA at 30-m spatial resolution. The next step consists of unmixing the 30 m (now lower resolution) images using the information about their pixel land-cover composition from co-registered images at higher spatial resolution. In our case study, TIR synthesized data were unmixed to the Sentinel 2 MSI with 10 m resolution. The constrained unmixing preserves all the available radiometric information of the 30 m images and involves the optimization of the number of land-cover classes and the size of the moving window for spatial unmixing. Results are still being evaluated, with particular attention for the quality of the data streams required to apply our approach.

Improved spatial resolution of luminescence images acquired with a silicon line scanning camera

NASA Astrophysics Data System (ADS)

Teal, Anthony; Mitchell, Bernhard; Juhl, Mattias K.

2018-04-01

Luminescence imaging is currently being used to provide spatially resolved defect in high volume silicon solar cell production. One option to obtain the high throughput required for on the fly detection is the use a silicon line scan cameras. However, when using a silicon based camera, the spatial resolution is reduced as a result of the weakly absorbed light scattering within the camera's chip. This paper address this issue by applying deconvolution from a measured point spread function. This paper extends the methods for determining the point spread function of a silicon area camera to a line scan camera with charge transfer. The improvement in resolution is quantified in the Fourier domain and in spatial domain on an image of a multicrystalline silicon brick. It is found that light spreading beyond the active sensor area is significant in line scan sensors, but can be corrected for through normalization of the point spread function. The application of this method improves the raw data, allowing effective detection of the spatial resolution of defects in manufacturing.

High Resolution Mapping of Wetland Ecosystems SPOT-5 Take 5 for Evaluation of Sentinel-2

NASA Astrophysics Data System (ADS)

Ade, Christiana; Hestir, Erin L.; Khanna, Shruti; Ustin, Susan L.

2016-08-01

Around the world wetlands are critical to human societies and ecosystems, providing services such as habitat, water, food and fiber, flood and nutrient control, and cultural, recreational and religious value. However, the dynamic nature of tidal wetlands makes measuring ecosystem responses to climate change, seasonal inundation regimes, and anthropogenic disturbance from current and previous Earth observing sensors challenging due to limited spatial and temporal resolutions. Sentinel- 2 will directly address this challenge by providing high spatial resolution data with frequent revisit time. This pilot study aims to develop methodology for future Sentinel-2 products and highlight the variability of tidal wetland ecosystems, thereby demonstrating the necessity of improved spatial particularly temporal resolution. Here the simulated Sentinel-2 dataset from the SPOT-5 Take 5 experiment reveals the capacity of the new sensor to simultaneously assess tidal wetland ecosystem phenology and water quality in inland waters.

Downscaling Land Surface Temperature in an Urban Area: A Case Study for Hamburg, Germany

NASA Astrophysics Data System (ADS)

Bechtel, Benjamin; Zakšek, Klemen

2013-04-01

Land surface temperature (LST) is an important parameter for the urban radiation and heat balance and a boundary condition for the atmospheric urban heat island (UHI). The increase in urban surface temperatures compared to the surrounding area (surface urban heat island, SUHI) has been described and analysed with satellite-based measurements for several decades. Besides continuous progress in the development of new sensors, an operational monitoring is still severely limited by physical constraints regarding the spatial and temporal resolution of the satellite data. Essentially, two measurement concepts must be distinguished: Sensors on geostationary platforms have high temporal (several times per hour) and poor spatial resolution (~ 5 km) while those on low earth orbiters have high spatial (~ 100-1000 m) resolution and a long return period (one day to several weeks). To enable an observation with high temporal and spatial resolution, a downscaling scheme for LST from the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) sensor onboard the geostationary meteorological Meteosat 9 to spatial resolutions between 100 and 1000 m was developed and tested for Hamburg in this case study. Therefore, various predictor sets (including parameters derived from multi-temporal thermal data, NDVI, and morphological parameters) were tested. The relationship between predictors and LST was empirically calibrated in the low resolution domain and then transferred to the high resolution domain. The downscaling was validated with LST data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) for the same time. Aggregated parameters from multi-temporal thermal data (in particular annual cycle parameters and principal components) proved particularly suitable. The results for the highest resolution of 100 m showed a high explained variance (R² = 0.71) and relatively low root mean square errors (RMSE = 2.2 K). Larger predictor sets resulted in higher errors, because they tended to overfit. As expected the results were better for coarser spatial resolutions (R² = 0.80, RMSE = 1.8 K for 500 m). These results are similar or slightly better than in previous studies, although we are not aware of any study with a comparably large downscaling factor. A considerable percentage of the error is systematic due to the different viewing geometry of the sensors (the high resolution LST was overestimated about 1.3 K). The study shows that downscaling of SEVIRI LST is possible up to a resolution of 100 m for urban areas and that multi-temporal thermal data are particularly suitable as predictors.

Evaluation of glued-diaphragm fibre optic pressure sensors in a shock tube

NASA Astrophysics Data System (ADS)

Sharifian, S. Ahmad; Buttsworth, David R.

2007-02-01

Glued-diaphragm fibre optic pressure sensors that utilize standard telecommunications components which are based on Fabry-Perot interferometry are appealing in a number of respects. Principally, they have high spatial and temporal resolution and are low in cost. These features potentially make them well suited to operation in extreme environments produced in short-duration high-enthalpy wind tunnel facilities where spatial and temporal resolution are essential, but attrition rates for sensors are typically very high. The sensors we consider utilize a zirconia ferrule substrate and a thin copper foil which are bonded together using an adhesive. The sensors show a fast response and can measure fluctuations with a frequency up to 250 kHz. The sensors also have a high spatial resolution on the order of 0.1 mm. However, with the interrogation and calibration processes adopted in this work, apparent errors of up to 30% of the maximum pressure have been observed. Such errors are primarily caused by mechanical hysteresis and adhesive viscoelasticity. If a dynamic calibration is adopted, the maximum measurement error can be limited to about 10% of the maximum pressure. However, a better approach is to eliminate the adhesive from the construction process or design the diaphragm and substrate in a way that does not require the adhesive to carry a significant fraction of the mechanical loading.

Comparison of Envisat ASAR GM, AMSR-E Passive Microwave, and MODIS Optical Remote Sensing for Flood Monitoring in Australia

NASA Astrophysics Data System (ADS)

Ticehurst, C. J.; Bartsch, A.; Doubkova, M.; van Dijk, A. I. J. M.

2009-11-01

Continuous flood monitoring can support emergency response, water management and environmental monitoring. Optical sensors such as MODIS allow inundation mapping with high spatial and temporal resolution (250-1000 m, twice daily) but are affected by cloud cover. Passive microwave sensors also acquire observations at high temporal resolution, but coarser spatial resolution (e.g. ca. 5-70 km for AMSR-E) and smaller footprints are also affected by cloud and/or rain. ScanSAR systems allow all-weather monitoring but require spatial resolution to be traded off against coverage and/or temporal resolution; e.g. the ENVISAT ASAR Global Mode observes at ca. 1 km over large regions about twice a week. The complementary role of the AMSR-E and ASAR GM data to that of MODIS is here introduced for three flood events and locations across Australia. Additional improvements can be made by integrating digital elevation models and stream flow gauging data.

Some effects of finite spatial resolution on skin friction measurements in turbulent boundary layers

NASA Technical Reports Server (NTRS)

Westphal, Russell V.

1988-01-01

The effects of finite spatial resolution often cause serious errors in measurements in turbulent boundary layers, with particularly large effects for measurements of fluctuating skin friction and velocities within the sublayer. However, classical analyses of finite spatial resolution effects have generally not accounted for the substantial inhomogeneity and anisotropy of near-wall turbulence. The present study has made use of results from recent computational simulations of wall-bounded turbulent flows to examine spatial resolution effects for measurements made at a wall using both single-sensor probes and those employing two sensing volumes in a V shape. Results are presented to show the effects of finite spatial resolution on a variety of quantitites deduced from the skin friction field.

A novel vibration sensor based on phase grating interferometry

NASA Astrophysics Data System (ADS)

Li, Qian; Liu, Xiaojun; Zhao, Li; Lei, Zili; Lu, Zhen; Guo, Lei

2017-05-01

Vibration sensors with high accuracy and reliability are needed urgently for vibration measurement. In this paper a vibration sensor with nanometer resolution is developed. This sensor is based on the principle of phase grating interference for displacement measurement and spatial polarization phase-shift interference technology, and photoelectric counting and A/D signal subdivision are adopted for vibration data output. A vibration measurement system consisting of vibration actuator and displacement adjusting device has been designed to test the vibration sensor. The high resolution and high reliability of the sensor are verified through a series of comparison experiments with Doppler interferometer.

Radiometric and Spatial Characterization of High-Spatial Resolution Sensors

NASA Technical Reports Server (NTRS)

Thome, Kurtis; Zanoni, Vicki (Technical Monitor)

2002-01-01

The development and improvement of commercial hyperspatial sensors in recent years has increased the breadth of information that can be retrieved from spaceborne and airborne imagery. NASA, through it's Scientific Data Purchases, has successfully provided such data sets to its user community. A key element to the usefulness of these data are an understanding of the radiometric and spatial response quality of the imagery. This proposal seeks funding to examine the absolute radiometric calibration of the Ikonos sensor operated by Space Imaging and the recently-launched Quickbird sensor from DigitalGlobe. In addition, we propose to evaluate the spatial response of the two sensors. The proposed methods rely on well-understood, ground-based targets that have been used by the University of Arizona for more than a decade.

Comparing the Potential of Multispectral and Hyperspectral Data for Monitoring Oil Spill Impact.

PubMed

Khanna, Shruti; Santos, Maria J; Ustin, Susan L; Shapiro, Kristen; Haverkamp, Paul J; Lay, Mui

2018-02-12

Oil spills from offshore drilling and coastal refineries often cause significant degradation of coastal environments. Early oil detection may prevent losses and speed up recovery if monitoring of the initial oil extent, oil impact, and recovery are in place. Satellite imagery data can provide a cost-effective alternative to expensive airborne imagery or labor intensive field campaigns for monitoring effects of oil spills on wetlands. However, these satellite data may be restricted in their ability to detect and map ecosystem recovery post-spill given their spectral measurement properties and temporal frequency. In this study, we assessed whether spatial and spectral resolution, and other sensor characteristics influence the ability to detect and map vegetation stress and mortality due to oil. We compared how well three satellite multispectral sensors: WorldView2, RapidEye and Landsat EMT+, match the ability of the airborne hyperspectral AVIRIS sensor to map oil-induced vegetation stress, recovery, and mortality after the DeepWater Horizon oil spill in the Gulf of Mexico in 2010. We found that finer spatial resolution (3.5 m) provided better delineation of the oil-impacted wetlands and better detection of vegetation stress along oiled shorelines in saltmarsh wetland ecosystems. As spatial resolution become coarser (3.5 m to 30 m) the ability to accurately detect and map stressed vegetation decreased. Spectral resolution did improve the detection and mapping of oil-impacted wetlands but less strongly than spatial resolution, suggesting that broad-band data may be sufficient to detect and map oil-impacted wetlands. AVIRIS narrow-band data performs better detecting vegetation stress, followed by WorldView2, RapidEye and then Landsat 15 m (pan sharpened) data. Higher quality sensor optics and higher signal-to-noise ratio (SNR) may also improve detection and mapping of oil-impacted wetlands; we found that resampled coarser resolution AVIRIS data with higher SNR performed better than either of the three satellite sensors. The ability to acquire imagery during certain times (midday, low tide, etc.) or a certain date (cloud-free, etc.) is also important in these tidal wetlands; WorldView2 imagery captured at high-tide detected a narrower band of shoreline affected by oil likely because some of the impacted wetland was below the tideline. These results suggest that while multispectral data may be sufficient for detecting the extent of oil-impacted wetlands, high spectral and spatial resolution, high-quality sensor characteristics, and the ability to control time of image acquisition may improve assessment and monitoring of vegetation stress and recovery post oil spills.

Comparing the Potential of Multispectral and Hyperspectral Data for Monitoring Oil Spill Impact

PubMed Central

Santos, Maria J.; Ustin, Susan L.; Haverkamp, Paul J.; Lay, Mui

2018-01-01

Oil spills from offshore drilling and coastal refineries often cause significant degradation of coastal environments. Early oil detection may prevent losses and speed up recovery if monitoring of the initial oil extent, oil impact, and recovery are in place. Satellite imagery data can provide a cost-effective alternative to expensive airborne imagery or labor intensive field campaigns for monitoring effects of oil spills on wetlands. However, these satellite data may be restricted in their ability to detect and map ecosystem recovery post-spill given their spectral measurement properties and temporal frequency. In this study, we assessed whether spatial and spectral resolution, and other sensor characteristics influence the ability to detect and map vegetation stress and mortality due to oil. We compared how well three satellite multispectral sensors: WorldView2, RapidEye and Landsat EMT+, match the ability of the airborne hyperspectral AVIRIS sensor to map oil-induced vegetation stress, recovery, and mortality after the DeepWater Horizon oil spill in the Gulf of Mexico in 2010. We found that finer spatial resolution (3.5 m) provided better delineation of the oil-impacted wetlands and better detection of vegetation stress along oiled shorelines in saltmarsh wetland ecosystems. As spatial resolution become coarser (3.5 m to 30 m) the ability to accurately detect and map stressed vegetation decreased. Spectral resolution did improve the detection and mapping of oil-impacted wetlands but less strongly than spatial resolution, suggesting that broad-band data may be sufficient to detect and map oil-impacted wetlands. AVIRIS narrow-band data performs better detecting vegetation stress, followed by WorldView2, RapidEye and then Landsat 15 m (pan sharpened) data. Higher quality sensor optics and higher signal-to-noise ratio (SNR) may also improve detection and mapping of oil-impacted wetlands; we found that resampled coarser resolution AVIRIS data with higher SNR performed better than either of the three satellite sensors. The ability to acquire imagery during certain times (midday, low tide, etc.) or a certain date (cloud-free, etc.) is also important in these tidal wetlands; WorldView2 imagery captured at high-tide detected a narrower band of shoreline affected by oil likely because some of the impacted wetland was below the tideline. These results suggest that while multispectral data may be sufficient for detecting the extent of oil-impacted wetlands, high spectral and spatial resolution, high-quality sensor characteristics, and the ability to control time of image acquisition may improve assessment and monitoring of vegetation stress and recovery post oil spills. PMID:29439504

Comparison of NDVI fields obtained from different remote sensors

NASA Astrophysics Data System (ADS)

Escribano Rodriguez, Juan; Alonso, Carmelo; Tarquis, Ana Maria; Benito, Rosa Maria; Hernandez Díaz-Ambrona, Carlos

2013-04-01

Satellite image data have become an important source of information for monitoring vegetation and mapping land cover at several scales. Beside this, the distribution and phenology of vegetation is largely associated with climate, terrain characteristics and human activity. Various vegetation indices have been developed for qualitative and quantitative assessment of vegetation using remote spectral measurements. In particular, sensors with spectral bands in the red (RED) and near-infrared (NIR) lend themselves well to vegetation monitoring and based on them [(NIR - RED) / (NIR + RED)] Normalized Difference Vegetation Index (NDVI) has been widespread used. Given that the characteristics of spectral bands in RED and NIR vary distinctly from sensor to sensor, NDVI values based on data from different instruments will not be directly comparable. The spatial resolution also varies significantly between sensors, as well as within a given scene in the case of wide-angle and oblique sensors. As a result, NDVI values will vary according to combinations of the heterogeneity and scale of terrestrial surfaces and pixel footprint sizes. Therefore, the question arises as to the impact of differences in spectral and spatial resolutions on vegetation indices like the NDVI and their interpretation as a drought index. During 2012 three locations (at Salamanca, Granada and Córdoba) were selected and a periodic pasture monitoring and botanic composition were achieved. Daily precipitation, temperature and monthly soil water content were measurement as well as fresh and dry pasture weight. At the same time, remote sensing images were capture by DEIMOS-1 and MODIS of the chosen places. DEIMOS-1 is based on the concept Microsat-100 from Surrey. It is conceived for obtaining Earth images with a good enough resolution to study the terrestrial vegetation cover (20x20 m), although with a great range of visual field (600 km) in order to obtain those images with high temporal resolution and at a reduced cost. By contranst, MODIS images present a much lower spatial resolution (500x500 m). The aim of this study is to establish a comparison between two different sensors in their NDVI values at different spatial resolutions. Acknowledgements. This work was partially supported by ENESA under project P10 0220C-823. Funding provided by Spanish Ministerio de Ciencia e Innovación (MICINN) through project no. MTM2009-14621 and i-MATH No. CSD2006-00032 is greatly appreciated.

Soil water sensor response to bulk electrical conductivity

USDA-ARS?s Scientific Manuscript database

Soil water monitoring using electromagnetic (EM) sensors can facilitate observations of water content at high temporal and spatial resolutions. These sensors measure soil dielectric permittivity (Ka) which is largely a function of volumetric water content. However, bulk electrical conductivity BEC c...

Distributed fiber optic vibration sensor with enhanced response bandwidth and high signal-to-noise ratio

NASA Astrophysics Data System (ADS)

Chen, Dian; Liu, Qingwen; Fan, Xinyu; He, Zuyuan

2017-04-01

A novel distributed fiber-optic vibration sensor (DVS) is proposed based on multi-pulse time-gated digital optical frequency domain reflectometry (TGD-OFDR), which can solve both the trade-off between the maximum measurable distance and the spatial resolution, and the one between the measurement distance and the vibration response bandwidth. A 21-kHz vibration is detected experimentally over 10-kilometer-long fiber, with a signal-to-noise ratio approaching 25 dB and a spatial resolution of 10 m.

On the Challenge of Observing Pelagic Sargassum in Coastal Oceans: A Multi-sensor Assessment

NASA Astrophysics Data System (ADS)

Hu, C.; Feng, L.; Hardy, R.; Hochberg, E. J.

2016-02-01

Remote detection of pelagic Sargassum is often hindered by its spectral similarity to other floating materials and by the inadequate spatial resolution. Using measurements from multi-spectral satellite sensors (Moderate Resolution Imaging Spectroradiometer or MODIS), Landsat, WorldView-2 (or WV-2) as well as hyperspectral sensors (Hyperspectral Imager for the Coastal Ocean or HICO, Airborne Visible-InfraRed Imaging Spectrometer or AVIRIS) and airborne digital photos, we analyze and compare their ability (in terms of spectral and spatial resolutions) to detect Sargassum and to differentiate from other floating materials such as Trichodesmium, Syringodium, Ulva, garbage, and emulsified oil. Field measurements suggest that Sargassum has a distinctive reflectance curvature around 630 nm due to its chlorophyll c pigments, which provides a unique spectral signature when combined with the reflectance ratio between brown ( 650 nm) and green ( 555 nm) wavelengths. For a 10-nm resolution sensor on the hyperspectral HyspIRI mission currently being planned by NASA, a stepwise rule to examine several indexes established from 6 bands (centered at 555, 605, 625, 645, 685, 755 nm) is shown to be effective to unambiguously differentiate Sargassum from all other floating materials Numerical simulations using spectral endmembers and noise in the satellite-derived reflectance suggest that spectral discrimination is degraded when a pixel is mixed between Sargassum and water. A minimum of 20-30% Sargassum coverage within a pixel is required to retain such ability, while the partial coverage can be as low as 1-2% when detecting floating materials without spectral discrimination. With its expected signal-to-noise ratios (SNRs 200:1), the hyperspectral HyspIRI mission may provide a compromise between spatial resolution and spatial coverage to improve our capacity to detect, discriminate, and quantify Sargassum.

Research relative to angular distribution of snow reflectance/snow cover characterization and microwave emission

NASA Technical Reports Server (NTRS)

Dozier, Jeff; Davis, Robert E.

1987-01-01

Remote sensing has been applied in recent years to monitoring snow cover properties for applications in hydrologic and energy balance modeling. In addition, snow cover has been recently shown to exert a considerable local influence on weather variables. Of particular importance is the potential of sensors to provide data on the physical properties of snow with high spatial and temporal resolution. Visible and near-infrared measurements of upwelling radiance can be used to infer near-surface properties through the calculation of albedo. Microwave signals usually come from deeper within the snow pack and thus provide depth-integrated information, which can be measured through clouds and does not relay on solar illumination.Fundamental studies examining the influence of snow properties on signals from various parts of the electromagnetic spectrum continue in part because of the promise of new remote sensors with higher spectral and spatial accuracy. Information in the visible and near-infrared parts of the spectrum comprise nearly all available data with high spatial resolution. Current passive microwave sensors have poor spatial resolution and the data are problematic where the scenes consist of mixed landscape features, but they offer timely observations that are independent of cloud cover and solar illumination.

Time Series Analysis for Spatial Node Selection in Environment Monitoring Sensor Networks

PubMed Central

Bhandari, Siddhartha; Jurdak, Raja; Kusy, Branislav

2017-01-01

Wireless sensor networks are widely used in environmental monitoring. The number of sensor nodes to be deployed will vary depending on the desired spatio-temporal resolution. Selecting an optimal number, position and sampling rate for an array of sensor nodes in environmental monitoring is a challenging question. Most of the current solutions are either theoretical or simulation-based where the problems are tackled using random field theory, computational geometry or computer simulations, limiting their specificity to a given sensor deployment. Using an empirical dataset from a mine rehabilitation monitoring sensor network, this work proposes a data-driven approach where co-integrated time series analysis is used to select the number of sensors from a short-term deployment of a larger set of potential node positions. Analyses conducted on temperature time series show 75% of sensors are co-integrated. Using only 25% of the original nodes can generate a complete dataset within a 0.5 °C average error bound. Our data-driven approach to sensor position selection is applicable for spatiotemporal monitoring of spatially correlated environmental parameters to minimize deployment cost without compromising data resolution. PMID:29271880

Landsat multispectral sharpening using a sensor system model and panchromatic image

USGS Publications Warehouse

Lemeshewsky, G.P.; ,

2003-01-01

The thematic mapper (TM) sensor aboard Landsats 4, 5 and enhanced TM plus (ETM+) on Landsat 7 collect imagery at 30-m sample distance in six spectral bands. New with ETM+ is a 15-m panchromatic (P) band. With image sharpening techniques, this higher resolution P data, or as an alternative, the 10-m (or 5-m) P data of the SPOT satellite, can increase the spatial resolution of the multispectral (MS) data. Sharpening requires that the lower resolution MS image be coregistered and resampled to the P data before high spatial frequency information is transferred to the MS data. For visual interpretation and machine classification tasks, it is important that the sharpened data preserve the spectral characteristics of the original low resolution data. A technique was developed for sharpening (in this case, 3:1 spatial resolution enhancement) visible spectral band data, based on a model of the sensor system point spread function (PSF) in order to maintain spectral fidelity. It combines high-pass (HP) filter sharpening methods with iterative image restoration to reduce degradations caused by sensor-system-induced blurring and resembling. Also there is a spectral fidelity requirement: sharpened MS when filtered by the modeled degradations should reproduce the low resolution source MS. Quantitative evaluation of sharpening performance was made by using simulated low resolution data generated from digital color-IR aerial photography. In comparison to the HP-filter-based sharpening method, results for the technique in this paper with simulated data show improved spectral fidelity. Preliminary results with TM 30-m visible band data sharpened with simulated 10-m panchromatic data are promising but require further study.

Investigation of spatial resolution and temporal performance of SAPHIRE (scintillator avalanche photoconductor with high resolution emitter readout) with integrated electrostatic focusing

NASA Astrophysics Data System (ADS)

Scaduto, David A.; Lubinsky, Anthony R.; Rowlands, John A.; Kenmotsu, Hidenori; Nishimoto, Norihito; Nishino, Takeshi; Tanioka, Kenkichi; Zhao, Wei

2014-03-01

We have previously proposed SAPHIRE (scintillator avalanche photoconductor with high resolution emitter readout), a novel detector concept with potentially superior spatial resolution and low-dose performance compared with existing flat-panel imagers. The detector comprises a scintillator that is optically coupled to an amorphous selenium photoconductor operated with avalanche gain, known as high-gain avalanche rushing photoconductor (HARP). High resolution electron beam readout is achieved using a field emitter array (FEA). This combination of avalanche gain, allowing for very low-dose imaging, and electron emitter readout, providing high spatial resolution, offers potentially superior image quality compared with existing flat-panel imagers, with specific applications to fluoroscopy and breast imaging. Through the present collaboration, a prototype HARP sensor with integrated electrostatic focusing and nano- Spindt FEA readout technology has been fabricated. The integrated electron-optic focusing approach is more suitable for fabricating large-area detectors. We investigate the dependence of spatial resolution on sensor structure and operating conditions, and compare the performance of electrostatic focusing with previous technologies. Our results show a clear dependence of spatial resolution on electrostatic focusing potential, with performance approaching that of the previous design with external mesh-electrode. Further, temporal performance (lag) of the detector is evaluated and the results show that the integrated electrostatic focusing design exhibits comparable or better performance compared with the mesh-electrode design. This study represents the first technical evaluation and characterization of the SAPHIRE concept with integrated electrostatic focusing.

Systems, methods, and software for determining spatially variable distributions of the dielectric properties of a heterogeneous material

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrington, Stephen P.

Systems, methods, and software for measuring the spatially variable relative dielectric permittivity of materials along a linear or otherwise configured sensor element, and more specifically the spatial variability of soil moisture in one dimension as inferred from the dielectric profile of the soil matrix surrounding a linear sensor element. Various methods provided herein combine advances in the processing of time domain reflectometry data with innovations in physical sensing apparatuses. These advancements enable high temporal (and thus spatial) resolution of electrical reflectance continuously along an insulated waveguide that is permanently emplaced in contact with adjacent soils. The spatially resolved reflectance ismore » directly related to impedance changes along the waveguide that are dominated by electrical permittivity contrast due to variations in soil moisture. Various methods described herein are thus able to monitor soil moisture in profile with high spatial resolution.« less

A flexible spatiotemporal method for fusing satellite images with different resolutions

Treesearch

Xiaolin Zhu; Eileen H. Helmer; Feng Gao; Desheng Liu; Jin Chen; Michael A. Lefsky

2016-01-01

Studies of land surface dynamics in heterogeneous landscapes often require remote sensing datawith high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta Fusion (FSDAF) method, to generate synthesized frequent high spatial...

Source-space ICA for MEG source imaging.

PubMed

Jonmohamadi, Yaqub; Jones, Richard D

2016-02-01

One of the most widely used approaches in electroencephalography/magnetoencephalography (MEG) source imaging is application of an inverse technique (such as dipole modelling or sLORETA) on the component extracted by independent component analysis (ICA) (sensor-space ICA + inverse technique). The advantage of this approach over an inverse technique alone is that it can identify and localize multiple concurrent sources. Among inverse techniques, the minimum-variance beamformers offer a high spatial resolution. However, in order to have both high spatial resolution of beamformer and be able to take on multiple concurrent sources, sensor-space ICA + beamformer is not an ideal combination. We propose source-space ICA for MEG as a powerful alternative approach which can provide the high spatial resolution of the beamformer and handle multiple concurrent sources. The concept of source-space ICA for MEG is to apply the beamformer first and then singular value decomposition + ICA. In this paper we have compared source-space ICA with sensor-space ICA both in simulation and real MEG. The simulations included two challenging scenarios of correlated/concurrent cluster sources. Source-space ICA provided superior performance in spatial reconstruction of source maps, even though both techniques performed equally from a temporal perspective. Real MEG from two healthy subjects with visual stimuli were also used to compare performance of sensor-space ICA and source-space ICA. We have also proposed a new variant of minimum-variance beamformer called weight-normalized linearly-constrained minimum-variance with orthonormal lead-field. As sensor-space ICA-based source reconstruction is popular in EEG and MEG imaging, and given that source-space ICA has superior spatial performance, it is expected that source-space ICA will supersede its predecessor in many applications.

Using a high spatial resolution tactile sensor for intention detection.

PubMed

Castellini, Claudio; Koiva, Risto

2013-06-01

Intention detection is the interpretation of biological signals with the aim of automatically, reliably and naturally understanding what a human subject desires to do. Although intention detection is not restricted to disabled people, such methods can be crucial in improving a patient's life, e.g., aiding control of a robotic wheelchair or of a self-powered prosthesis. Traditionally, intention detection is done using, e.g., gaze tracking, surface electromyography and electroencephalography. In this paper we present exciting initial results of an experiment aimed at intention detection using a high-spatial-resolution, high-dynamic-range tactile sensor. The tactile image of the ventral side of the forearm of 9 able-bodied participants was recorded during a variable-force task stimulated at the fingertip. Both the forces at the fingertip and at the forearm were synchronously recorded. We show that a standard dimensionality reduction technique (Principal Component Analysis) plus a Support Vector Machine attain almost perfect detection accuracy of the direction and the intensity of the intended force. This paves the way for high spatial resolution tactile sensors to be used as a means for intention detection.

Vector sensor for scanning SQUID microscopy

NASA Astrophysics Data System (ADS)

Dang, Vu The; Toji, Masaki; Thanh Huy, Ho; Miyajima, Shigeyuki; Shishido, Hiroaki; Hidaka, Mutsuo; Hayashi, Masahiko; Ishida, Takekazu

2017-07-01

We plan to build a novel 3-dimensional (3D) scanning SQUID microscope with high sensitivity and high spatial resolution. In the system, a vector sensor consists of three SQUID sensors and three pick-up coils realized on a single chip. Three pick-up coils are configured in orthogonal with each other to measure the magnetic field vector of X, Y, Z components. We fabricated some SQUID chips with one uniaxial pick-up coil or three vector pick-up coils and carried out fundamental measurements to reveal the basic characteristics. Josephson junctions (JJs) of sensors are designed to have the critical current density J c of 320 A/cm2, and the critical current I c becomes 12.5 μA for the 2.2μm × 2.2μm JJ. We carefully positioned the three pickup coils so as to keep them at the same height at the centers of all three X, Y and Z coils. This can be done by arranging them along single line parallel to a sample surface. With the aid of multilayer technology of Nb-based fabrication, we attempted to reduce an inner diameter of the pickup coils to enhance both sensitivity and spatial resolution. The method for improving a spatial resolution of a local magnetic field image is to employ an XYZ piezo-driven scanner for controlling the positions of the pick-up coils. The fundamental characteristics of our SQUID sensors confirmed the proper operation of our SQUID sensors and found a good agreement with our design parameters.

Design trade-off between spatial resolution and power consumption in CMOS biosensor circuit based on millimeter-wave LC oscillator array

NASA Astrophysics Data System (ADS)

Matsunaga, Maya; Kobayashi, Atsuki; Nakazato, Kazuo; Niitsu, Kiichi

2018-03-01

In this paper, we describe a trade-off between spatial resolution and power consumption in an LC oscillator-based CMOS biosensor, which can detect biomolecules by observing the resonance frequency shift due to changes in the complex permittivity of the biomolecules. The optimal operating frequency and improvement in the image resolution of the sensor output require a reduction in the size of the inductor. However, it is necessary to increase the transconductance of the cross-coupling transistor to achieve the oscillation condition, although the power consumption increases. We confirmed the trade-off between the spatial resolution and the power consumption of this sensor using SPICE simulation. A test chip was fabricated using a 65 nm CMOS process, and the transition in the peak frequency and the power consumption were measured. When the outer diameter of the inductor was 46 µm, the power consumption was 31.2 mW, which matched well with the simulation results.

Fiber Optic Based Thermometry System for Superconducting RF Cavities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kochergin, Vladimir

2013-05-06

Thermometry is recognized as the best technique to identify and characterize losses in SRF cavities. The most widely used and reliable apparatus for temperature mapping at cryogenic temperatures is based on carbon resistors (RTDs). The use of this technology on multi-cell cavities is inconvenient due to the very large number of sensors required to obtain sufficient spatial resolution. Recent developments make feasible the use of multiplexible fiber optic sensors for highly distributed temperature measurements. However, sensitivity of multiplexible cryogenic temperature sensors was found extending only to 12K at best and thus was not sufficient for SRF cavity thermometry. During themore » course of the project the team of MicroXact, JLab and Virginia Tech developed and demonstrated the multiplexible fiber optic sensor with adequate response below 20K. The demonstrated temperature resolution is by at least a factor of 60 better than that of the best multiplexible fiber optic temperature sensors reported to date. The clear path toward at least 10times better temperature resolution is shown. The first to date temperature distribution measurements with ~2.5mm spatial resolution was done with fiber optic sensors at 2K to4K temperatures. The repeatability and accuracy of the sensors were verified only at 183K, but at this temperature both parameters significantly exceeded the state of the art. The results of this work are expected to find a wide range of applications, since the results are enabling the whole new testing capabilities, not accessible before.« less

The EO-1 hyperion and advanced land imager sensors for use in tundra classification studies within the Upper Kuparuk River Basin, Alaska

NASA Astrophysics Data System (ADS)

Hall-Brown, Mary

The heterogeneity of Arctic vegetation can make land cover classification vey difficult when using medium to small resolution imagery (Schneider et al., 2009; Muller et al., 1999). Using high radiometric and spatial resolution imagery, such as the SPOT 5 and IKONOS satellites, have helped arctic land cover classification accuracies rise into the 80 and 90 percentiles (Allard, 2003; Stine et al., 2010; Muller et al., 1999). However, those increases usually come at a high price. High resolution imagery is very expensive and can often add tens of thousands of dollars onto the cost of the research. The EO-1 satellite launched in 2002 carries two sensors that have high specral and/or high spatial resolutions and can be an acceptable compromise between the resolution versus cost issues. The Hyperion is a hyperspectral sensor with the capability of collecting 242 spectral bands of information. The Advanced Land Imager (ALI) is an advanced multispectral sensor whose spatial resolution can be sharpened to 10 meters. This dissertation compares the accuracies of arctic land cover classifications produced by the Hyperion and ALI sensors to the classification accuracies produced by the Systeme Pour l' Observation de le Terre (SPOT), the Landsat Thematic Mapper (TM) and the Landsat Enhanced Thematic Mapper Plus (ETM+) sensors. Hyperion and ALI images from August 2004 were collected over the Upper Kuparuk River Basin, Alaska. Image processing included the stepwise discriminant analysis of pixels that were positively classified from coinciding ground control points, geometric and radiometric correction, and principle component analysis. Finally, stratified random sampling was used to perform accuracy assessments on satellite derived land cover classifications. Accuracy was estimated from an error matrix (confusion matrix) that provided the overall, producer's and user's accuracies. This research found that while the Hyperion sensor produced classfication accuracies that were equivalent to the TM and ETM+ sensor (approximately 78%), the Hyperion could not obtain the accuracy of the SPOT 5 HRV sensor. However, the land cover classifications derived from the ALI sensor exceeded most classification accuracies derived from the TM and ETM+ senors and were even comparable to most SPOT 5 HRV classifications (87%). With the deactivation of the Landsat series satellites, the monitoring of remote locations such as in the Arctic on an uninterupted basis thoughout the world is in jeopardy. The utilization of the Hyperion and ALI sensors are a way to keep that endeavor operational. By keeping the ALI sensor active at all times, uninterupted observation of the entire Earth can be accomplished. Keeping the Hyperion sensor as a "tasked" sensor can provide scientists with additional imagery and options for their studies without overburdening storage issues.

Single-photon semiconductor photodiodes for distributed optical fiber sensors: state of the art and perspectives

NASA Astrophysics Data System (ADS)

Ripamonti, Giancarlo; Lacaita, Andrea L.

1993-03-01

The extreme sensitivity and time resolution of Geiger-mode avalanche photodiodes (GM- APDs) have already been exploited for optical time domain reflectometry (OTDR). Better than 1 cm spatial resolution in Rayleigh scattering detection was demonstrated. Distributed and quasi-distributed optical fiber sensors can take advantage of the capabilities of GM-APDs. Extensive studies have recently disclosed the main characteristics and limitations of silicon devices, both commercially available and developmental. In this paper we report an analysis of the performance of these detectors. The main characteristics of GM-APDs of interest for distributed optical fiber sensors are briefly reviewed. Command electronics (active quenching) is then introduced. The detector timing performance sets the maximum spatial resolution in experiments employing OTDR techniques. We highlight that the achievable time resolution depends on the physics of the avalanche spreading over the device area. On the basis of these results, trade-off between the important parameters (quantum efficiency, time resolution, background noise, and afterpulsing effects) is considered. Finally, we show first results on Germanium devices, capable of single photon sensitivity at 1.3 and 1.5 micrometers with sub- nanosecond time resolution.

Land use change detection based on multi-date imagery from different satellite sensor systems

NASA Technical Reports Server (NTRS)

Stow, Douglas A.; Collins, Doretta; Mckinsey, David

1990-01-01

An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

Sharpening advanced land imager multispectral data using a sensor model

USGS Publications Warehouse

Lemeshewsky, G.P.; ,

2005-01-01

The Advanced Land Imager (ALI) instrument on NASA's Earth Observing One (EO-1) satellite provides for nine spectral bands at 30m ground sample distance (GSD) and a 10m GSD panchromatic band. This report describes an image sharpening technique where the higher spatial resolution information of the panchromatic band is used to increase the spatial resolution of ALI multispectral (MS) data. To preserve the spectral characteristics, this technique combines reported deconvolution deblurring methods for the MS data with highpass filter-based fusion methods for the Pan data. The deblurring process uses the point spread function (PSF) model of the ALI sensor. Information includes calculation of the PSF from pre-launch calibration data. Performance was evaluated using simulated ALI MS data generated by degrading the spatial resolution of high resolution IKONOS satellite MS data. A quantitative measure of performance was the error between sharpened MS data and high resolution reference. This report also compares performance with that of a reported method that includes PSF information. Preliminary results indicate improved sharpening with the method reported here.

Oil slick morphology derived from AVIRIS measurements of the Deepwater Horizon oil spill: Implications for spatial resolution requirements of remote sensors

USGS Publications Warehouse

Sun, Shaojie; Hu, Chuanmin; Feng, Lian; Swayze, Gregg A.; Holmes, Jamie; Graettinger, George; MacDonald, Ian R.; Garcia, Oscar; Leifer, Ira

2016-01-01

Using fine spatial resolution (~ 7.6 m) hyperspectral AVIRIS data collected over the Deepwater Horizon oil spill in the Gulf of Mexico, we statistically estimated slick lengths, widths and length/width ratios to characterize oil slick morphology for different thickness classes. For all AVIRIS-detected oil slicks (N = 52,100 continuous features) binned into four thickness classes (≤ 50 μm but thicker than sheen, 50–200 μm, 200–1000 μm, and > 1000 μm), the median lengths, widths, and length/width ratios of these classes ranged between 22 and 38 m, 7–11 m, and 2.5–3.3, respectively. The AVIRIS data were further aggregated to 30-m (Landsat resolution) and 300-m (MERIS resolution) spatial bins to determine the fractional oil coverage in each bin. Overall, if 50% fractional pixel coverage were to be required to detect oil with thickness greater than sheen for most oil containing pixels, a 30-m resolution sensor would be needed.

Hyperspectral and multispectral satellite sensors for mapping chlorophyll content in a Mediterranean Pinus sylvestris L. plantation

NASA Astrophysics Data System (ADS)

Navarro-Cerrillo, Rafael Mª; Trujillo, Jesus; de la Orden, Manuel Sánchez; Hernández-Clemente, Rocío

2014-02-01

A new generation of narrow-band hyperspectral remote sensing data offers an alternative to broad-band multispectral data for the estimation of vegetation chlorophyll content. This paper examines the potential of some of these sensors comparing red-edge and simple ratio indices to develop a rapid and cost-effective system for monitoring Mediterranean pine plantations in Spain. Chlorophyll content retrieval was analyzed with the red-edge R750/R710 index and the simple ratio R800/R560 index using the PROSPECT-5 leaf model and the Discrete Anisotropic Radiative Transfer (DART) and experimental approach. Five sensors were used: AHS, CHRIS/Proba, Hyperion, Landsat and QuickBird. The model simulation results obtained with synthetic spectra demonstrated the feasibility of estimating Ca + b content in conifers using the simple ratio R800/R560 index formulated with different full widths at half maximum (FWHM) at the leaf level. This index yielded a r2 = 0.69 for a FWHM of 30 nm and r2 = 0.55 for a FWHM of 70 nm. Experimental results compared the regression coefficients obtained with various multispectral and hyperspectral images with different spatial resolutions at the stand level. The strongest relationships where obtained using high-resolution hyperspectral images acquired with the AHS sensor (r2 = 0.65) while coarser spatial and spectral resolution images yielded a lower root mean square error (QuickBird r2 = 0.42; Landsat r2 = 0.48; Hyperion r2 = 0.56; CHRIS/Proba r2 = 0.57). This study shows the need to estimate chlorophyll content in forest plantations at the stand level with high spatial and spectral resolution sensors. Nevertheless, these results also show the accuracy obtained with medium-resolution sensors when monitoring physiological processes. Generating biochemical maps at the stand level could play a critical rule in the early detection of forest decline processes enabling their use in precision forestry.

Optical fiber sensors-based temperature distribution measurement in ex vivo radiofrequency ablation with submillimeter resolution.

PubMed

Macchi, Edoardo Gino; Tosi, Daniele; Braschi, Giovanni; Gallati, Mario; Cigada, Alfredo; Busca, Giorgio; Lewis, Elfed

2014-01-01

Radiofrequency thermal ablation (RFTA) induces a high-temperature field in a biological tissue having steep spatial (up to 6°C∕mm) and temporal (up to 1°C∕s) gradients. Applied in cancer care, RFTA produces a localized heating, cytotoxic for tumor cells, and is able to treat tumors with sizes up to 3 to 5 cm in diameter. The online measurement of temperature distribution at the RFTA point of care has been previously carried out with miniature thermocouples and optical fiber sensors, which exhibit problems of size, alteration of RFTA pattern, hysteresis, and sensor density worse than 1 sensor∕cm. In this work, we apply a distributed temperature sensor (DTS) with a submillimeter spatial resolution for the monitoring of RFTA in porcine liver tissue. The DTS demodulates the chaotic Rayleigh backscattering pattern with an interferometric setup to obtain the real-time temperature distribution. A measurement chamber has been set up with the fiber crossing the tissue along different diameters. Several experiments have been carried out measuring the space-time evolution of temperature during RFTA. The present work showcases the temperature monitoring in RFTA with an unprecedented spatial resolution and is exportable to in vivo measurement; the acquired data can be particularly useful for the validation of RFTA computational models.

The absolute calibration of KOMPSAT-3 and 3A high spatial resolution satellites using radiometric tarps and MFRSR measurments

NASA Astrophysics Data System (ADS)

Yeom, J. M.

2017-12-01

Recently developed Korea Multi-Purpose Satellite-3A (KOMPSAT-3A), which is a continuation of the KOMPSAT-1, 2 and 3 earth observation satellite (EOS) programs from the Korea Aerospace Research Institute (KARI) was launched on March, 25 2015 on a Dnepr-1 launch vehicle from the Jasny Dombarovsky site in Russia. After launched, KARI performed in-orbit-test (IOT) including radiometric calibration for 6 months from 14 Apr. to 4 Sep. 2015. KOMPSAT-3A is equipped with two distinctive sensors; one is a high resolution multispectral optical sensor, namely the Advances Earth Image Sensor System-A (AEISS-A) and the other is the Scanner Infrared Imaging System (SIIS). In this study, we focused on the radiometric calibration of AEISS-A. The multispectral wavelengths of AEISS-A are covering three visible regions: blue (450 - 520 nm), green (520 - 600 nm), red (630 - 690 nm), one near infrared (760 - 900 nm) with a 2.0 m spatial resolution at nadir, whereas the panchromatic imagery (450 - 900 nm) has a 0.5 m resolution. Those are the same spectral response functions were same with KOMPSAT-3 multispectral and panchromatic bands but the spatial resolutions are improved. The main mission of KOMPSAT-3A is to develop for Geographical Information System (GIS) applications in environmental, agriculture, and oceanographic sciences, as well as natural hazard monitoring.

Evaluation of multi-resolution satellite sensors for assessing water quality and bottom depth of Lake Garda.

PubMed

Giardino, Claudia; Bresciani, Mariano; Cazzaniga, Ilaria; Schenk, Karin; Rieger, Patrizia; Braga, Federica; Matta, Erica; Brando, Vittorio E

2014-12-15

In this study we evaluate the capabilities of three satellite sensors for assessing water composition and bottom depth in Lake Garda, Italy. A consistent physics-based processing chain was applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat-8 Operational Land Imager (OLI) and RapidEye. Images gathered on 10 June 2014 were corrected for the atmospheric effects with the 6SV code. The computed remote sensing reflectance (Rrs) from MODIS and OLI were converted into water quality parameters by adopting a spectral inversion procedure based on a bio-optical model calibrated with optical properties of the lake. The same spectral inversion procedure was applied to RapidEye and to OLI data to map bottom depth. In situ measurements of Rrs and of concentrations of water quality parameters collected in five locations were used to evaluate the models. The bottom depth maps from OLI and RapidEye showed similar gradients up to 7 m (r = 0.72). The results indicate that: (1) the spatial and radiometric resolutions of OLI enabled mapping water constituents and bottom properties; (2) MODIS was appropriate for assessing water quality in the pelagic areas at a coarser spatial resolution; and (3) RapidEye had the capability to retrieve bottom depth at high spatial resolution. Future work should evaluate the performance of the three sensors in different bio-optical conditions.

Tactile Recognition and Localization Using Object Models: The Case of Polyhedra on a Plane.

DTIC Science & Technology

1983-03-01

poor force resolution, but high spatial resolution. We feel that the viability of this recognition approach has important implications on the design of...of the touched object: 1. Surface point - On the basis of sensor readings, some points on the sensor can be identified as being in contact with...the sensor’s shape and location in space are known, one can determine the position of some point on the touched object, to within some uncertainty

Generic Sensor Modeling Using Pulse Method

NASA Technical Reports Server (NTRS)

Helder, Dennis L.; Choi, Taeyoung

2005-01-01

Recent development of high spatial resolution satellites such as IKONOS, Quickbird and Orbview enable observation of the Earth's surface with sub-meter resolution. Compared to the 30 meter resolution of Landsat 5 TM, the amount of information in the output image was dramatically increased. In this era of high spatial resolution, the estimation of spatial quality of images is gaining attention. Historically, the Modulation Transfer Function (MTF) concept has been used to estimate an imaging system's spatial quality. Sometimes classified by target shapes, various methods were developed in laboratory environment utilizing sinusoidal inputs, periodic bar patterns and narrow slits. On-orbit sensor MTF estimation was performed on 30-meter GSD Landsat4 Thematic Mapper (TM) data from the bridge pulse target as a pulse input . Because of a high resolution sensor s small Ground Sampling Distance (GSD), reasonably sized man-made edge, pulse, and impulse targets can be deployed on a uniform grassy area with accurate control of ground targets using tarps and convex mirrors. All the previous work cited calculated MTF without testing the MTF estimator's performance. In previous report, a numerical generic sensor model had been developed to simulate and improve the performance of on-orbit MTF estimating techniques. Results from the previous sensor modeling report that have been incorporated into standard MTF estimation work include Fermi edge detection and the newly developed 4th order modified Savitzky-Golay (MSG) interpolation technique. Noise sensitivity had been studied by performing simulations on known noise sources and a sensor model. Extensive investigation was done to characterize multi-resolution ground noise. Finally, angle simulation was tested by using synthetic pulse targets with angles from 2 to 15 degrees, several brightness levels, and different noise levels from both ground targets and imaging system. As a continuing research activity using the developed sensor model, this report was dedicated to MTF estimation via pulse input method characterization using the Fermi edge detection and 4th order MSG interpolation method. The relationship between pulse width and MTF value at Nyquist was studied including error detection and correction schemes. Pulse target angle sensitivity was studied by using synthetic targets angled from 2 to 12 degrees. In this report, from the ground and system noise simulation, a minimum SNR value was suggested for a stable MTF value at Nyquist for the pulse method. Target width error detection and adjustment technique based on a smooth transition of MTF profile is presented, which is specifically applicable only to the pulse method with 3 pixel wide targets.

High Resolution Eddy-Current Wire Testing Based on a Gmr Sensor-Array

NASA Astrophysics Data System (ADS)

Kreutzbruck, Marc; Allweins, Kai; Strackbein, Chris; Bernau, Hendrick

2009-03-01

Increasing demands in materials quality and cost effectiveness have led to advanced standards in manufacturing technology. Especially when dealing with high quality standards in conjunction with high throughput quantitative NDE techniques are vital to provide reliable and fast quality control systems. In this work we illuminate a modern electromagnetic NDE approach using a small GMR sensor array for testing superconducting wires. Four GMR sensors are positioned around the wire. Each GMR sensor provides a field sensitivity of 200 pT/√Hz and a spatial resolution of about 100 μm. This enables us to detect under surface defects of 100 μm in size in a depth of 200 μm with a signal-to-noise ratio of better than 400. Surface defects could be detected with a SNR of up to 10,000. Besides this remarkably SNR the small extent of GMR sensors results in a spatial resolution which offers new visualisation techniques for defect localisation, defect characterization and tomography-like mapping techniques. We also report on inverse algorithms based on either a Finite Element Method or an analytical approach. These allow for accurate defect localization on the urn scale and an estimation of the defect size.

On the soil moisture estimate at basin scale in Mediterranean basins with the ASAR sensor: the Mulargia basin case study

NASA Astrophysics Data System (ADS)

Fois, Laura; Montaldo, Nicola

2017-04-01

Soil moisture plays a key role in water and energy exchanges between soil, vegetation and atmosphere. For water resources planning and managementthesoil moistureneeds to be accurately and spatially monitored, specially where the risk of desertification is high, such as Mediterranean basins. In this sense active remote sensors are very attractive for soil moisture monitoring. But Mediterranean basinsaretypicallycharacterized by strong topography and high spatial variability of physiographic properties, and only high spatial resolution sensorsare potentially able to monitor the strong soil moisture spatial variability.In this regard the Envisat ASAR (Advanced Synthetic Aperture Radar) sensor offers the attractive opportunity ofsoil moisture mapping at fine spatial and temporal resolutions(up to 30 m, every 30 days). We test the ASAR sensor for soil moisture estimate in an interesting Sardinian case study, the Mulargia basin withan area of about 70 sq.km. The position of the Sardinia island in the center of the western Mediterranean Sea basin, its low urbanization and human activity make Sardinia a perfect reference laboratory for Mediterranean hydrologic studies. The Mulargia basin is a typical Mediterranean basinin water-limited conditions, and is an experimental basin from 2003. For soil moisture mapping23 satellite ASAR imagery at single and dual polarization were acquired for the 2003-2004period.Satellite observationsmay bevalidated through spatially distributed soil moisture ground-truth data, collected over the whole basin using the TDR technique and the gravimetric method, in days with available radar images. The results show that ASAR sensor observations can be successfully used for soil moisture mapping at different seasons, both wet and dry, but an accurate calibration with field data is necessary. We detect a strong relationship between the soil moisture spatial variability and the physiographic properties of the basin, such as soil water storage capacity, deep and texture of soils, type and density of vegetation, and topographic parameters. Finally we demonstrate that the high resolution ASAR imagery are an attractive tool for estimating surface soil moisture at basin scale, offering a unique opportunity for monitoring the soil moisture spatial variability in typical Mediterranean basins.

Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping.

PubMed

Borra-Serrano, Irene; Peña, José Manuel; Torres-Sánchez, Jorge; Mesas-Carrascosa, Francisco Javier; López-Granados, Francisca

2015-08-12

Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights.

Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping

PubMed Central

Borra-Serrano, Irene; Peña, José Manuel; Torres-Sánchez, Jorge; Mesas-Carrascosa, Francisco Javier; López-Granados, Francisca

2015-01-01

Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights. PMID:26274960

Air Pollution Measurements by Citizen Scientists and NASA Satellites: Data Integration and Analysis

NASA Astrophysics Data System (ADS)

Gupta, P.; Maibach, J.; Levy, R. C.; Doraiswamy, P.; Pikelnaya, O.; Feenstra, B.; Polidori, A.

2017-12-01

PM2.5, or fine particulate matter, is a category of air pollutant consisting of solid particles with effective aerodynamic diameter of less than 2.5 microns. These particles are hazardous to human health, as their small size allows them to penetrate deep into the lungs. Since the late 1990's, the US Environmental Protection Agency has been monitoring PM2.5 using a network of ground-level sensors. Due to cost and space restrictions, the EPA monitoring network remains spatially sparse. That is, while the network spans the extent of the US, the distance between sensors is large enough that significant spatial variation in PM concentration can go undetected. To increase the spatial resolution of monitoring, previous studies have used satellite data to estimate ground-level PM concentrations. From imagery, one can create a measure of haziness due to aerosols, called aerosol optical depth (AOD), which then can be used to estimate PM concentrations using statistical and physical modeling. Additionally, previous research has identified a number of meteorological variables, such as relative humidity and mixing height, which aide in estimating PM concentrations from AOD. Although the high spatial resolution of satellite data is valuable alone for forecasting air quality, higher resolution ground-level data is needed to effectively study the relationship between PM2.5 concentrations and AOD. To this end, we discuss a citizen-science PM monitoring network deployed in California. Using low-cost PM sensors, this network achieves higher spatial resolution. We additionally discuss a software pipeline for integrating resulting PM measurements with satellite data, as well as initial data analysis.

Spatial Downscaling of TRMM Precipitation using MODIS product in the Korean Peninsula

NASA Astrophysics Data System (ADS)

Cho, H.; Choi, M.

2013-12-01

Precipitation is a major driving force in the water cycle. But, it is difficult to provide spatially distributed precipitation data from isolated individual in situ. The Tropical Rainfall Monitoring Mission (TRMM) satellite can provide precipitation data with relatively coarse spatial resolution (0.25° scale) at daily basis. In order to overcome the coarse spatial resolution of TRMM precipitation products, we conducted a downscaling technique using a scaling parameter from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor. In this study, statistical relations between precipitation estimates derived from the TRMM satellite and the normalized difference vegetation index (NDVI) which is obtained from the MODIS sensor in TERRA satellite are found for different spatial scales on the Korean peninsula in northeast Asia. We obtain the downscaled precipitation mapping by regression equation between yearly TRMM precipitations values and annual average NDVI aggregating 1km to 25 degree. The downscaled precipitation is validated using time series of the ground measurements precipitation dataset provided by Korea Meteorological Organization (KMO) from 2002 to 2005. To improve the spatial downscaling of precipitation, we will conduct a study about correlation between precipitation and land surface temperature, perceptible water and other hydrological parameters.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Gul, M. Shahzeb Khan; Gunturk, Bahadir K.

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks.

PubMed

Gul, M Shahzeb Khan; Gunturk, Bahadir K

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Estimating Morning Change in Land Surface Temperature from MODIS Day/Night Observations: Applications for Surface Energy Balance Modeling.

PubMed

Hain, Christopher R; Anderson, Martha C

2017-10-16

Observations of land surface temperature (LST) are crucial for the monitoring of surface energy fluxes from satellite. Methods that require high temporal resolution LST observations (e.g., from geostationary orbit) can be difficult to apply globally because several geostationary sensors are required to attain near-global coverage (60°N to 60°S). While these LST observations are available from polar-orbiting sensors, providing global coverage at higher spatial resolutions, the temporal sampling (twice daily observations) can pose significant limitations. For example, the Atmosphere Land Exchange Inverse (ALEXI) surface energy balance model, used for monitoring evapotranspiration and drought, requires an observation of the morning change in LST - a quantity not directly observable from polar-orbiting sensors. Therefore, we have developed and evaluated a data-mining approach to estimate the mid-morning rise in LST from a single sensor (2 observations per day) of LST from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the Aqua platform. In general, the data-mining approach produced estimates with low relative error (5 to 10%) and statistically significant correlations when compared against geostationary observations. This approach will facilitate global, near real-time applications of ALEXI at higher spatial and temporal coverage from a single sensor than currently achievable with current geostationary datasets.

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 1; Theory

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Schull, Mitchell A.; Samanta, Arindam; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramakrishna R.; Knyazikhin, Yuri; Myneni, Ranga B.

2008-01-01

The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher information content). Implementation of this approach indicates good consistency in LAI values retrieved from NDVI (AVHRRmode) and spectral BRF (MODIS-mode). Specific details of the implementation and evaluation of the derived products are detailed in the second part of this two-paper series.

Environmental monitoring of Galway Bay: fusing data from remote and in-situ sources

NASA Astrophysics Data System (ADS)

O'Connor, Edel; Hayes, Jer; Smeaton, Alan F.; O'Connor, Noel E.; Diamond, Dermot

2009-09-01

Changes in sea surface temperature can be used as an indicator of water quality. In-situ sensors are being used for continuous autonomous monitoring. However these sensors have limited spatial resolution as they are in effect single point sensors. Satellite remote sensing can be used to provide better spatial coverage at good temporal scales. However in-situ sensors have a richer temporal scale for a particular point of interest. Work carried out in Galway Bay has combined data from multiple satellite sources and in-situ sensors and investigated the benefits and drawbacks of using multiple sensing modalities for monitoring a marine location.

Validation and Temporal Analysis of Lai and Fapar Products Derived from Medium Resolution Sensor

NASA Astrophysics Data System (ADS)

Claverie, M.; Vermote, E. F.; Baret, F.; Weiss, M.; Hagolle, O.; Demarez, V.

2012-12-01

Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) have been defined as Essential Climate Variables. Many Earth surface monitoring applications are based on global estimation combined with a relatively high frequency. The medium spatial resolution sensors (MRS), such as SPOT-VGT, MODIS or MERIS, have been widely used to provide land surface products (mainly LAI and FAPAR) to the scientific community. These products require quality assessment and consistency. However, due to consistency of the ground measurements spatial sampling, the medium resolution is not appropriate for direct validation with in situ measurements sampling. It is thus more adequate to use high spatial resolution sensors which can integrate the spatial variability. The recent availability of combined high spatial (8 m) and temporal resolutions (daily) Formosat-2 data allows to evaluate the accuracy and the temporal consistency of medium resolution sensors products. In this study, we proposed to validate MRS products over a cropland area and to analyze their spatial and temporal consistency. As a matter of fact, this study belongs to the Stage 2 of the validation, as defined by the Land Product Validation sub-group of the Earth Observation Satellites. Reference maps, derived from the aggregation of Formosat-2 data (acquired during the 2006-2010 period over croplands in southwest of France), were compared with (i) two existing global biophysical variables products (GEOV1/VGT and MODIS-15 coll. 5), and (ii) a new product (MODdaily) derived from the inversion of PROSAIL radiative transfer model (EMMAH, INRA Avignon) applied on MODIS BRDF-corrected daily reflectance. Their uncertainty was calculated with 105 LAI and FAPAR reference maps, which uncertainties (22 % for LAI and 12% for FAPAR) were evaluated with in situ measurements performed over maize, sunflower and soybean. Inter-comparison of coarse resolution (0.05°) products showed that LAI and FAPAR have consistent phenology (Figure). The GEOLAND-2 showed the smoothest time series due to a 30-day composite, while MODdaily noise was satisfactory (<12%). The RMSE of LAI calculated for the period 2006-2010 were 0.46 for GEOV1/VGT, 0.19 for MODIS-15 and 0.16 for MODdaily. A significant overestimation (bias=0.43) of the LAI peak were observed for GEOV1/VGT products, while MOD-15 showed a small underestimation (bias=-0.14) of highest LAI. Finally, over a larger area (a quarter of France) covered by cropland, grassland and forest, the products displayed a good spatial consistency.; LAI 2006-2010 time-series of a coarse resolution pixel of cropland (extent in upper-left corner). Products are compared to Formosat-2 reference maps.

An optical sensor for detecting the contact location of a gas-liquid interface on a body.

PubMed

Belden, Jesse; Jandron, Michael

2014-08-01

An optical sensor for detecting the dynamic contact location of a gas-liquid interface along the length of a body is described. The sensor is developed in the context of applications to supercavitating bodies requiring measurement of the dynamic cavity contact location; however, the sensing method is extendable to other applications as well. The optical principle of total internal reflection is exploited to detect changes in refractive index of the medium contacting the body at discrete locations along its length. The derived theoretical operation of the sensor predicts a signal attenuation of 18 dB when a sensed location changes from air-contacting to water-contacting. Theory also shows that spatial resolution (d) scales linearly with sensor length (L(s)) and a resolution of 0.01L(s) can be achieved. A prototype sensor is constructed from simple components and response characteristics are quantified for different ambient light conditions as well as partial wetting states. Three methods of sensor calibration are described and a signal processing framework is developed that allows for robust detection of the gas-liquid contact location. In a tank draining experiment, the prototype sensor resolves the water level with accuracy limited only by the spatial resolution, which is constrained by the experimental setup. A more representative experiment is performed in which the prototype sensor accurately measures the dynamic contact location of a gas cavity on a water tunnel wall.

A non-parametric, supervised classification of vegetation types on the Kaibab National Forest using decision trees

Treesearch

Suzanne M. Joy; R. M. Reich; Richard T. Reynolds

2003-01-01

Traditional land classification techniques for large areas that use Landsat Thematic Mapper (TM) imagery are typically limited to the fixed spatial resolution of the sensors (30m). However, the study of some ecological processes requires land cover classifications at finer spatial resolutions. We model forest vegetation types on the Kaibab National Forest (KNF) in...

Multisensor data fusion across time and space

NASA Astrophysics Data System (ADS)

Villeneuve, Pierre V.; Beaven, Scott G.; Reed, Robert A.

2014-06-01

Field measurement campaigns typically deploy numerous sensors having different sampling characteristics for spatial, temporal, and spectral domains. Data analysis and exploitation is made more difficult and time consuming as the sample data grids between sensors do not align. This report summarizes our recent effort to demonstrate feasibility of a processing chain capable of "fusing" image data from multiple independent and asynchronous sensors into a form amenable to analysis and exploitation using commercially-available tools. Two important technical issues were addressed in this work: 1) Image spatial registration onto a common pixel grid, 2) Image temporal interpolation onto a common time base. The first step leverages existing image matching and registration algorithms. The second step relies upon a new and innovative use of optical flow algorithms to perform accurate temporal upsampling of slower frame rate imagery. Optical flow field vectors were first derived from high-frame rate, high-resolution imagery, and then finally used as a basis for temporal upsampling of the slower frame rate sensor's imagery. Optical flow field values are computed using a multi-scale image pyramid, thus allowing for more extreme object motion. This involves preprocessing imagery to varying resolution scales and initializing new vector flow estimates using that from the previous coarser-resolution image. Overall performance of this processing chain is demonstrated using sample data involving complex too motion observed by multiple sensors mounted to the same base. Multiple sensors were included, including a high-speed visible camera, up to a coarser resolution LWIR camera.

On the feasibility of measuring urban air pollution by wireless distributed sensor networks.

PubMed

Moltchanov, Sharon; Levy, Ilan; Etzion, Yael; Lerner, Uri; Broday, David M; Fishbain, Barak

2015-01-01

Accurate evaluation of air pollution on human-wellbeing requires high-resolution measurements. Standard air quality monitoring stations provide accurate pollution levels but due to their sparse distribution they cannot capture the highly resolved spatial variations within cities. Similarly, dedicated field campaigns can use tens of measurement devices and obtain highly dense spatial coverage but normally deployment has been limited to short periods of no more than few weeks. Nowadays, advances in communication and sensory technologies enable the deployment of dense grids of wireless distributed air monitoring nodes, yet their sensor ability to capture the spatiotemporal pollutant variability at the sub-neighborhood scale has never been thoroughly tested. This study reports ambient measurements of gaseous air pollutants by a network of six wireless multi-sensor miniature nodes that have been deployed in three urban sites, about 150 m apart. We demonstrate the network's capability to capture spatiotemporal concentration variations at an exceptional fine resolution but highlight the need for a frequent in-situ calibration to maintain the consistency of some sensors. Accordingly, a procedure for a field calibration is proposed and shown to improve the system's performance. Overall, our results support the compatibility of wireless distributed sensor networks for measuring urban air pollution at a sub-neighborhood spatial resolution, which suits the requirement for highly spatiotemporal resolved measurements at the breathing-height when assessing exposure to urban air pollution. Copyright © 2014 Elsevier B.V. All rights reserved.

Soil moisture downscaling using a simple thermal based proxy

NASA Astrophysics Data System (ADS)

Peng, Jian; Loew, Alexander; Niesel, Jonathan

2016-04-01

Microwave remote sensing has been largely applied to retrieve soil moisture (SM) from active and passive sensors. The obvious advantage of microwave sensor is that SM can be obtained regardless of atmospheric conditions. However, existing global SM products only provide observations at coarse spatial resolutions, which often hamper their applications in regional hydrological studies. Therefore, various downscaling methods have been proposed to enhance the spatial resolution of satellite soil moisture products. The aim of this study is to investigate the validity and robustness of a simple Vegetation Temperature Condition Index (VTCI) downscaling scheme over different climates and regions. Both polar orbiting (MODIS) and geostationary (MSG SEVIRI) satellite data are used to improve the spatial resolution of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative (ESA CCI) soil moisture, which is a merged product based on both active and passive microwave observations. The results from direct validation against soil moisture in-situ measurements, spatial pattern comparison, as well as seasonal and land use analyses show that the downscaling method can significantly improve the spatial details of CCI soil moisture while maintain the accuracy of CCI soil moisture. The application of the scheme with different satellite platforms and over different regions further demonstrate the robustness and effectiveness of the proposed method. Therefore, the VTCI downscaling method has the potential to facilitate relevant hydrological applications that require high spatial and temporal resolution soil moisture.

High spatiotemporal resolution monitoring of hydrological function across degraded peatlands in the south west UK.

NASA Astrophysics Data System (ADS)

Ashe, Josie; Luscombe, David; Grand-Clement, Emilie; Gatis, Naomi; Anderson, Karen; Brazier, Richard

2014-05-01

The Exmoor/Dartmoor Mires Project is a peatland restoration programme focused on the geoclimatically marginal blanket bogs of South West England. In order to better understand the hydrological functioning of degraded/restored peatlands and support land management decisions across these uplands, this study is providing robust spatially distributed, hydrological monitoring at a high temporal resolution and in near real time. This paper presents the conceptual framework and experimental design for three hydrological monitoring arrays situated in headwater catchments dominated by eroding and drained blanket peatland. Over 250 individual measurements are collected at a high temporal resolution (15 minute time-step) via sensors integrated within a remote telemetry system. These are sent directly to a dedicated server over VHF and GPRS mobile networks. Sensors arrays are distributed at varying spatial scales throughout the studied catchments and record multiple parameters including: water table depth, channel flow, temperature, conductivity and pH measurements. A full suite of meteorological sensors and ten spatially distributed automatic flow based water samplers are also connected to the telemetry system and controlled remotely. This paper will highlight the challenges and solutions to obtaining these data in exceptionally remote and harsh field conditions over long (multi annual) temporal scales.

Multi-Decadal Pathfinder Data Sets of Global Land Biophysical Variables from AVHRR and MODIS and their Use in GCM Studies of Biogeophysics and Biogeochemistry

NASA Technical Reports Server (NTRS)

Myneni, Ranga

2003-01-01

The problem of how the scale, or spatial resolution, of reflectance data impacts retrievals of vegetation leaf area index (LAI) and fraction absorbed photosynthetically active radiation (PAR) has been investigated. We define the goal of scaling as the process by which it is established that LAI and FPAR values derived from coarse resolution sensor data equal the arithmetic average of values derived independently from fine resolution sensor data. The increasing probability of land cover mixtures with decreasing resolution is defined as heterogeneity, which is a key concept in scaling studies. The effect of pixel heterogeneity on spectral reflectances and LAI/FPAR retrievals is investigated with 1 km Advanced Very High Resolution Radiometer (AVHRR) data aggregated to different coarse spatial resolutions. It is shown that LAI retrieval errors at coarse resolution are inversely related to the proportion of the dominant land cover in such pixel. Further, large errors in LAI retrievals are incurred when forests are minority biomes in non-forest pixels compared to when forest biomes are mixed with one another, and vice-versa. A physically based technique for scaling with explicit spatial resolution dependent radiative transfer formulation is developed. The successful application of this theory to scaling LAI retrievals from AVHRR data of different resolutions is demonstrated

Assessment and Prediction of Natural Hazards from Satellite Imagery

PubMed Central

Gillespie, Thomas W.; Chu, Jasmine; Frankenberg, Elizabeth; Thomas, Duncan

2013-01-01

Since 2000, there have been a number of spaceborne satellites that have changed the way we assess and predict natural hazards. These satellites are able to quantify physical geographic phenomena associated with the movements of the earth’s surface (earthquakes, mass movements), water (floods, tsunamis, storms), and fire (wildfires). Most of these satellites contain active or passive sensors that can be utilized by the scientific community for the remote sensing of natural hazards over a number of spatial and temporal scales. The most useful satellite imagery for the assessment of earthquake damage comes from high-resolution (0.6 m to 1 m pixel size) passive sensors and moderate resolution active sensors that can quantify the vertical and horizontal movement of the earth’s surface. High-resolution passive sensors have been used to successfully assess flood damage while predictive maps of flood vulnerability areas are possible based on physical variables collected from passive and active sensors. Recent moderate resolution sensors are able to provide near real time data on fires and provide quantitative data used in fire behavior models. Limitations currently exist due to atmospheric interference, pixel resolution, and revisit times. However, a number of new microsatellites and constellations of satellites will be launched in the next five years that contain increased resolution (0.5 m to 1 m pixel resolution for active sensors) and revisit times (daily ≤ 2.5 m resolution images from passive sensors) that will significantly improve our ability to assess and predict natural hazards from space. PMID:25170186

Attribution of soil information associated with modeling background clutter

NASA Astrophysics Data System (ADS)

Mason, George; Melloh, Rae

2006-05-01

This paper examines the attribution of data fields required to generate high resolution soil profiles for support of Computational Test Bed (CTB) used for countermine research. The countermine computational test bed is designed to realistically simulate the geo-environment to support the evaluation of sensors used to locate unexploded ordnance. The goal of the CTB is to derive expected moisture, chemical compounds, and measure heat migration over time, from which we expect to optimize sensor performance. Several tests areas were considered for the collection of soils data to populate the CTB. Collection of bulk soil properties has inherent spatial resolution limits. Novel techniques are therefore required to populate a high resolution model. This paper presents correlations between spatial variability in texture as related to hydraulic permeability and heat transfer properties of the soil. The extracted physical properties are used to exercise models providing a signature of subsurface media and support the simulation of detection by various sensors of buried and surface ordnance.

Spatial resolution enhancement of terrestrial features using deconvolved SSM/I microwave brightness temperatures

NASA Technical Reports Server (NTRS)

Farrar, Michael R.; Smith, Eric A.

1992-01-01

A method for enhancing the 19, 22, and 37 GHz measurements of the SSM/I (Special Sensor Microwave/Imager) to the spatial resolution and sampling density of the high resolution 85-GHz channel is presented. An objective technique for specifying the tuning parameter, which balances the tradeoff between resolution and noise, is developed in terms of maximizing cross-channel correlations. Various validation procedures are performed to demonstrate the effectiveness of the method, which hopefully will provide researchers with a valuable tool in multispectral applications of satellite radiometer data.

Estimation of Orbital Neutron Detector Spatial Resolution by Systematic Shifting of Differential Topographic Masks

NASA Technical Reports Server (NTRS)

McClanahan, T. P.; Mitrofanov, I. G.; Boynton, W. V.; Chin, G.; Livengood, T.; Starr, R. D.; Evans, L. G.; Mazarico, E.; Smith, D. E.

2012-01-01

We present a method and preliminary results related to determining the spatial resolution of orbital neutron detectors using epithermal maps and differential topographic masks. Our technique is similar to coded aperture imaging methods for optimizing photonic signals in telescopes [I]. In that approach photon masks with known spatial patterns in a telescope aperature are used to systematically restrict incoming photons which minimizes interference and enhances photon signal to noise. Three orbital neutron detector systems with different stated spatial resolutions are evaluated. The differing spatial resolutions arise due different orbital altitudes and the use of neutron collimation techniques. 1) The uncollimated Lunar Prospector Neutron Spectrometer (LPNS) system has spatial resolution of 45km FWHM from approx. 30km altitude mission phase [2]. The Lunar Rennaissance Orbiter (LRO) Lunar Exploration Neutron Detector (LEND) with two detectors at 50km altitude evaluated here: 2) the collimated 10km FWHM spatial resolution detector CSETN and 3) LEND's collimated Sensor for Epithermal Neutrons (SETN). Thus providing two orbital altitudes to study factors of: uncollimated vs collimated and two average altitudes for their effect on fields-of-view.

Distributed Optical Fiber Sensors Based on Optical Frequency Domain Reflectometry: A review

PubMed Central

Wang, Chenhuan; Liu, Kun; Jiang, Junfeng; Yang, Di; Pan, Guanyi; Pu, Zelin; Liu, Tiegen

2018-01-01

Distributed optical fiber sensors (DOFS) offer unprecedented features, the most unique one of which is the ability of monitoring variations of the physical and chemical parameters with spatial continuity along the fiber. Among all these distributed sensing techniques, optical frequency domain reflectometry (OFDR) has been given tremendous attention because of its high spatial resolution and large dynamic range. In addition, DOFS based on OFDR have been used to sense many parameters. In this review, we will survey the key technologies for improving sensing range, spatial resolution and sensing performance in DOFS based on OFDR. We also introduce the sensing mechanisms and the applications of DOFS based on OFDR including strain, stress, vibration, temperature, 3D shape, flow, refractive index, magnetic field, radiation, gas and so on. PMID:29614024

Distributed Optical Fiber Sensors Based on Optical Frequency Domain Reflectometry: A review.

PubMed

Ding, Zhenyang; Wang, Chenhuan; Liu, Kun; Jiang, Junfeng; Yang, Di; Pan, Guanyi; Pu, Zelin; Liu, Tiegen

2018-04-03

Distributed optical fiber sensors (DOFS) offer unprecedented features, the most unique one of which is the ability of monitoring variations of the physical and chemical parameters with spatial continuity along the fiber. Among all these distributed sensing techniques, optical frequency domain reflectometry (OFDR) has been given tremendous attention because of its high spatial resolution and large dynamic range. In addition, DOFS based on OFDR have been used to sense many parameters. In this review, we will survey the key technologies for improving sensing range, spatial resolution and sensing performance in DOFS based on OFDR. We also introduce the sensing mechanisms and the applications of DOFS based on OFDR including strain, stress, vibration, temperature, 3D shape, flow, refractive index, magnetic field, radiation, gas and so on.

Proof of principle study of the use of a CMOS active pixel sensor for proton radiography.

PubMed

Seco, Joao; Depauw, Nicolas

2011-02-01

Proof of principle study of the use of a CMOS active pixel sensor (APS) in producing proton radiographic images using the proton beam at the Massachusetts General Hospital (MGH). A CMOS APS, previously tested for use in s-ray radiation therapy applications, was used for proton beam radiographic imaging at the MGH. Two different setups were used as a proof of principle that CMOS can be used as proton imaging device: (i) a pen with two metal screws to assess spatial resolution of the CMOS and (ii) a phantom with lung tissue, bone tissue, and water to assess tissue contrast of the CMOS. The sensor was then traversed by a double scattered monoenergetic proton beam at 117 MeV, and the energy deposition inside the detector was recorded to assess its energy response. Conventional x-ray images with similar setup at voltages of 70 kVp and proton images using commercial Gafchromic EBT 2 and Kodak X-Omat V films were also taken for comparison purposes. Images were successfully acquired and compared to x-ray kVp and proton EBT2/X-Omat film images. The spatial resolution of the CMOS detector image is subjectively comparable to the EBT2 and Kodak X-Omat V film images obtained at the same object-detector distance. X-rays have apparent higher spatial resolution than the CMOS. However, further studies with different commercial films using proton beam irradiation demonstrate that the distance of the detector to the object is important to the amount of proton scatter contributing to the proton image. Proton images obtained with films at different distances from the source indicate that proton scatter significantly affects the CMOS image quality. Proton radiographic images were successfully acquired at MGH using a CMOS active pixel sensor detector. The CMOS demonstrated spatial resolution subjectively comparable to films at the same object-detector distance. Further work will be done in order to establish the spatial and energy resolution of the CMOS detector for protons. The development and use of CMOS in proton radiography could allow in vivo proton range checks, patient setup QA, and real-time tumor tracking.

Evolution of miniature detectors and focal plane arrays for infrared sensors

NASA Astrophysics Data System (ADS)

Watts, Louis A.

1993-06-01

Sensors that are sensitive in the infrared spectral region have been under continuous development since the WW2 era. A quest for the military advantage of 'seeing in the dark' has pushed thermal imaging technology toward high spatial and temporal resolution for night vision equipment, fire control, search track, and seeker 'homing' guidance sensing devices. Similarly, scientific applications have pushed spectral resolution for chemical analysis, remote sensing of earth resources, and astronomical exploration applications. As a result of these developments, focal plane arrays (FPA) are now available with sufficient sensitivity for both high spatial and narrow bandwidth spectral resolution imaging over large fields of view. Such devices combined with emerging opto-electronic developments in integrated FPA data processing techniques can yield miniature sensors capable of imaging reflected sunlight in the near IR and emitted thermal energy in the Mid-wave (MWIR) and longwave (LWIR) IR spectral regions. Robotic space sensors equipped with advanced versions of these FPA's will provide high resolution 'pictures' of their surroundings, perform remote analysis of solid, liquid, and gas matter, or selectively look for 'signatures' of specific objects. Evolutionary trends and projections of future low power micro detector FPA developments for day/night operation or use in adverse viewing conditions are presented in the following test.

Evolution of miniature detectors and focal plane arrays for infrared sensors

NASA Technical Reports Server (NTRS)

Watts, Louis A.

1993-01-01

Sensors that are sensitive in the infrared spectral region have been under continuous development since the WW2 era. A quest for the military advantage of 'seeing in the dark' has pushed thermal imaging technology toward high spatial and temporal resolution for night vision equipment, fire control, search track, and seeker 'homing' guidance sensing devices. Similarly, scientific applications have pushed spectral resolution for chemical analysis, remote sensing of earth resources, and astronomical exploration applications. As a result of these developments, focal plane arrays (FPA) are now available with sufficient sensitivity for both high spatial and narrow bandwidth spectral resolution imaging over large fields of view. Such devices combined with emerging opto-electronic developments in integrated FPA data processing techniques can yield miniature sensors capable of imaging reflected sunlight in the near IR and emitted thermal energy in the Mid-wave (MWIR) and longwave (LWIR) IR spectral regions. Robotic space sensors equipped with advanced versions of these FPA's will provide high resolution 'pictures' of their surroundings, perform remote analysis of solid, liquid, and gas matter, or selectively look for 'signatures' of specific objects. Evolutionary trends and projections of future low power micro detector FPA developments for day/night operation or use in adverse viewing conditions are presented in the following test.

Combining environment and health information systems for the assessment of atmospheric pollution on human health.

PubMed

Skouloudis, Andreas N; Kassomenos, Pavlos

2014-08-01

The use of emerging technologies for environmental monitoring with satellite and in-situ sensors have become essential instruments for assessing the impact of environmental pollution on human health, especially in areas that require high spatial and temporal resolution. This was until recently a rather difficult problem. Regrettably, with classical approaches the spatial resolution is frequently inadequate in reporting environmental causes and health effects in the same time scale. This work examines with new tools different levels of air-quality with sensor monitoring with the aim to associate those with severe health effects. The process established here facilitates the precise representation of human exposure with the population attributed in a fine spatial grid and taking into account environmental stressors of human exposure. These stressors can be monitored with innovative sensor units with a temporal resolution that accurately describes chronic and acute environmental burdens. The current understanding of the situation in densely populated areas can be properly analyzed, before commitments are made for reductions in total emissions as well as for assessing the effects of reduced trans-boundary fluxes. In addition, the data processed here with in-situ sensors can assist in establishing more effective regulatory policies for the protection of vulnerable population groups and the satellite monitoring instruments permit abatement strategies that are close to real-time over large geographical areas. Copyright © 2014 Elsevier B.V. All rights reserved.

Influence of resolution in irrigated area mapping and area estimation

USGS Publications Warehouse

Velpuri, N.M.; Thenkabail, P.S.; Gumma, M.K.; Biradar, C.; Dheeravath, V.; Noojipady, P.; Yuanjie, L.

2009-01-01

The overarching goal of this paper was to determine how irrigated areas change with resolution (or scale) of imagery. Specific objectives investigated were to (a) map irrigated areas using four distinct spatial resolutions (or scales), (b) determine how irrigated areas change with resolutions, and (c) establish the causes of differences in resolution-based irrigated areas. The study was conducted in the very large Krishna River basin (India), which has a high degree of formal contiguous, and informal fragmented irrigated areas. The irrigated areas were mapped using satellite sensor data at four distinct resolutions: (a) NOAA AVHRR Pathfinder 10,000 m, (b) Terra MODIS 500 m, (c) Terra MODIS 250 m, and (d) Landsat ETM+ 30 m. The proportion of irrigated areas relative to Landsat 30 m derived irrigated areas (9.36 million hectares for the Krishna basin) were (a) 95 percent using MODIS 250 m, (b) 93 percent using MODIS 500 m, and (c) 86 percent using AVHRR 10,000 m. In this study, it was found that the precise location of the irrigated areas were better established using finer spatial resolution data. A strong relationship (R2 = 0.74 to 0.95) was observed between irrigated areas determined using various resolutions. This study proved the hypotheses that "the finer the spatial resolution of the sensor used, greater was the irrigated area derived," since at finer spatial resolutions, fragmented areas are detected better. Accuracies and errors were established consistently for three classes (surface water irrigated, ground water/conjunctive use irrigated, and nonirrigated) across the four resolutions mentioned above. The results showed that the Landsat data provided significantly higher overall accuracies (84 percent) when compared to MODIS 500 m (77 percent), MODIS 250 m (79 percent), and AVHRR 10,000 m (63 percent). ?? 2009 American Society for Photogrammetry and Remote Sensing.

Merging thermal and microwave satellite observations for a high-resolution soil moisture data product

USDA-ARS?s Scientific Manuscript database

Many societal applications of soil moisture data products require high spatial resolution and numerical accuracy. Current thermal geostationary satellite sensors (GOES Imager and GOES-R ABI) could produce 2-16km resolution soil moisture proxy data. Passive microwave satellite radiometers (e.g. AMSR...

Expanding the functionality and applications of nanopore sensors

NASA Astrophysics Data System (ADS)

Venta, Kimberly E.

Nanopore sensors have developed into powerful tools for single-molecule studies since their inception two decades ago. Nanopore sensors function as nanoscale Coulter counters, by monitoring ionic current modulations as particles pass through a nanopore. While nanopore sensors can be used to study any nanoscale particle, their most notable application is as a low cost, fast alternative to current DNA sequencing technologies. In recent years, signifcant progress has been made toward the goal of nanopore-based DNA sequencing, which requires an ambitious combination of a low-noise and high-bandwidth nanopore measurement system and spatial resolution. In this dissertation, nanopore sensors in thin membranes are developed to improve dimensional resolution, and these membranes are used in parallel with a high-bandwidth amplfier. Using this nanopore sensor system, the signals of three DNA homopolymers are differentiated for the first time in solid-state nanopores. The nanopore noise is also reduced through the addition of a layer of SU8, a spin-on polymer, to the supporting chip structure. By increasing the temporal and spatial resolution of nanopore sensors, studies of shorter molecules are now possible. Nanopore sensors are beginning to be used for the study and characterization of nanoparticles. Nanoparticles have found many uses from biomedical imaging to next-generation solar cells. However, further insights into the formation and characterization of nanoparticles would aid in developing improved synthesis methods leading to more effective and customizable nanoparticles. This dissertation presents two methods of employing nanopore sensors to benet nanoparticle characterization and fabrication. Nanopores were used to study the formation of individual nanoparticles and serve as nanoparticle growth templates that could be exploited to create custom nanoparticle arrays. Additionally, nanopore sensors were used to characterize the surface charge density of anisotropic nanopores, which previously could not be reliably measured. Current nanopore sensor resolution levels have facilitated innovative research on nanoscale systems, including studies of DNA and nanoparticle characterization. Further nanopore system improvements will enable vastly improved DNA sequencing capabilities and open the door to additional nanopore sensing applications.

Surface acoustic impediography: a new technology for fingerprint mapping and biometric identification: a numerical study

NASA Astrophysics Data System (ADS)

Schmitt, Rainer M.; Scott, W. Guy; Irving, Richard D.; Arnold, Joe; Bardons, Charles; Halpert, Daniel; Parker, Lawrence

2004-09-01

A new type of fingerprint sensor is presented. The sensor maps the acoustic impedance of the fingerprint pattern by estimating the electrical impedance of its sensor elements. The sensor substrate, made of 1-3 piezo-ceramic, which is fabricated inexpensively at large scales, can provide a resolution up to 50 μm over an area of 20 x 25 mm2. Using FE modeling the paper presents the numerical validation of the basic principle. It evaluates an optimized pillar aspect ratio, estimates spatial resolution and the point spread function for a 100 μm and 50 μm pitch model. In addition, first fingerprints obtained with the prototype sensor are presented.

Wavefront sensor based on the Talbot effect with the precorrected holographic grating.

PubMed

Podanchuk, Dmytro; Kurashov, Vitalij; Goloborodko, Andrey; Dan'ko, Volodymyr; Kotov, Myhaylo; Goloborodko, Natalya

2012-04-01

A holographic wavefront sensor based on the Talbot effect is proposed. Optical wavefronts are measured by sampling the light amplitude distribution with a two-dimensional (2D) precorrected holographic grating. The factors that allow changing an angular measurement range and a spatial resolution of the sensor are discussed. A comparative analysis with the Shack-Hartmann sensor is illustrated with some experimental results.

Improved laser-based triangulation sensor with enhanced range and resolution through adaptive optics-based active beam control.

PubMed

Reza, Syed Azer; Khwaja, Tariq Shamim; Mazhar, Mohsin Ali; Niazi, Haris Khan; Nawab, Rahma

2017-07-20

Various existing target ranging techniques are limited in terms of the dynamic range of operation and measurement resolution. These limitations arise as a result of a particular measurement methodology, the finite processing capability of the hardware components deployed within the sensor module, and the medium through which the target is viewed. Generally, improving the sensor range adversely affects its resolution and vice versa. Often, a distance sensor is designed for an optimal range/resolution setting depending on its intended application. Optical triangulation is broadly classified as a spatial-signal-processing-based ranging technique and measures target distance from the location of the reflected spot on a position sensitive detector (PSD). In most triangulation sensors that use lasers as a light source, beam divergence-which severely affects sensor measurement range-is often ignored in calculations. In this paper, we first discuss in detail the limitations to ranging imposed by beam divergence, which, in effect, sets the sensor dynamic range. Next, we show how the resolution of laser-based triangulation sensors is limited by the interpixel pitch of a finite-sized PSD. In this paper, through the use of tunable focus lenses (TFLs), we propose a novel design of a triangulation-based optical rangefinder that improves both the sensor resolution and its dynamic range through adaptive electronic control of beam propagation parameters. We present the theory and operation of the proposed sensor and clearly demonstrate a range and resolution improvement with the use of TFLs. Experimental results in support of our claims are shown to be in strong agreement with theory.

Computational multispectral video imaging [Invited].

PubMed

Wang, Peng; Menon, Rajesh

2018-01-01

Multispectral imagers reveal information unperceivable to humans and conventional cameras. Here, we demonstrate a compact single-shot multispectral video-imaging camera by placing a micro-structured diffractive filter in close proximity to the image sensor. The diffractive filter converts spectral information to a spatial code on the sensor pixels. Following a calibration step, this code can be inverted via regularization-based linear algebra to compute the multispectral image. We experimentally demonstrated spectral resolution of 9.6 nm within the visible band (430-718 nm). We further show that the spatial resolution is enhanced by over 30% compared with the case without the diffractive filter. We also demonstrate Vis-IR imaging with the same sensor. Because no absorptive color filters are utilized, sensitivity is preserved as well. Finally, the diffractive filters can be easily manufactured using optical lithography and replication techniques.

Sensor Webs: Autonomous Rapid Response to Monitor Transient Science Events

NASA Technical Reports Server (NTRS)

Mandl, Dan; Grosvenor, Sandra; Frye, Stu; Sherwood, Robert; Chien, Steve; Davies, Ashley; Cichy, Ben; Ingram, Mary Ann; Langley, John; Miranda, Felix

2005-01-01

To better understand how physical phenomena, such as volcanic eruptions, evolve over time, multiple sensor observations over the duration of the event are required. Using sensor web approaches that integrate original detections by in-situ sensors and global-coverage, lower-resolution, on-orbit assets with automated rapid response observations from high resolution sensors, more observations of significant events can be made with increased temporal, spatial, and spectral resolution. This paper describes experiments using Earth Observing 1 (EO-1) along with other space and ground assets to implement progressive mission autonomy to identify, locate and image with high resolution instruments phenomena such as wildfires, volcanoes, floods and ice breakup. The software that plans, schedules and controls the various satellite assets are used to form ad hoc constellations which enable collaborative autonomous image collections triggered by transient phenomena. This software is both flight and ground based and works in concert to run all of the required assets cohesively and includes software that is model-based, artificial intelligence software.

Downscaling of Remotely Sensed Land Surface Temperature with multi-sensor based products

NASA Astrophysics Data System (ADS)

Jeong, J.; Baik, J.; Choi, M.

2016-12-01

Remotely sensed satellite data provides a bird's eye view, which allows us to understand spatiotemporal behavior of hydrologic variables at global scale. Especially, geostationary satellite continuously observing specific regions is useful to monitor the fluctuations of hydrologic variables as well as meteorological factors. However, there are still problems regarding spatial resolution whether the fine scale land cover can be represented with the spatial resolution of the satellite sensor, especially in the area of complex topography. To solve these problems, many researchers have been trying to establish the relationship among various hydrological factors and combine images from multi-sensor to downscale land surface products. One of geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS), has Meteorological Imager (MI) and Geostationary Ocean Color Imager (GOCI). MI performing the meteorological mission produce Rainfall Intensity (RI), Land Surface Temperature (LST), and many others every 15 minutes. Even though it has high temporal resolution, low spatial resolution of MI data is treated as major research problem in many studies. This study suggests a methodology to downscale 4 km LST datasets derived from MI in finer resolution (500m) by using GOCI datasets in Northeast Asia. Normalized Difference Vegetation Index (NDVI) recognized as variable which has significant relationship with LST are chosen to estimate LST in finer resolution. Each pixels of NDVI and LST are separated according to land cover provided from MODerate resolution Imaging Spectroradiometer (MODIS) to achieve more accurate relationship. Downscaled LST are compared with LST observed from Automated Synoptic Observing System (ASOS) for assessing its accuracy. The downscaled LST results of this study, coupled with advantage of geostationary satellite, can be applied to observe hydrologic process efficiently.

CMOS foveal image sensor chip

NASA Technical Reports Server (NTRS)

Scott, Peter (Inventor); Sridhar, Ramalingam (Inventor); Bandera, Cesar (Inventor); Xia, Shu (Inventor)

2002-01-01

A foveal image sensor integrated circuit comprising a plurality of CMOS active pixel sensors arranged both within and about a central fovea region of the chip. The pixels in the central fovea region have a smaller size than the pixels arranged in peripheral rings about the central region. A new photocharge normalization scheme and associated circuitry normalizes the output signals from the different size pixels in the array. The pixels are assembled into a multi-resolution rectilinear foveal image sensor chip using a novel access scheme to reduce the number of analog RAM cells needed. Localized spatial resolution declines monotonically with offset from the imager's optical axis, analogous to biological foveal vision.

Thinking Outside of the Blue Marble: Novel Ocean Applications Using the VIIRS Sensor

NASA Technical Reports Server (NTRS)

Vandermeulen, Ryan A.; Arnone, Robert

2016-01-01

While planning for future space-borne sensors will increase the quality, quantity, and duration of ocean observations in the years to come, efforts to extend the limits of sensors currently in orbit can help shed light on future scientific gains as well as associated uncertainties. Here, we present several applications that are unique to the polar orbiting Visual Infrared Imaging Radiometer Suite (VIIRS), each of which challenge the threshold capabilities of the sensor and provide lessons for future missions. For instance, while moderate resolution polar orbiters typically have a one day revisit time, we are able to obtain multiple looks of the same area by focusing on the extreme zenith angles where orbital views overlap, and pair these observations with those from other sensors to create pseudo-geostationary data sets. Or, by exploiting high spatial resolution (imaging) channels and analyzing patterns of synoptic covariance across the visible spectrum, we can obtain higher spatial resolution bio-optical products. Alternatively, non-traditional products can illuminate important biological interactions in the ocean, such as the use of the Day-Night-Band to provide some quantification of phototactic behavior of marine life along light polluted beaches, as well as track the location of marine fishing vessel fleets along ocean fronts. In this talk, we explore ways to take full advantage of the capabilities of existing sensors in order to maximize insights for future missions.

Evaluation of Sun Glint Correction Algorithms for High-Spatial Resolution Hyperspectral Imagery

DTIC Science & Technology

2012-09-01

ACRONYMS AND ABBREVIATIONS AISA Airborne Imaging Spectrometer for Applications AVIRIS Airborne Visible/Infrared Imaging Spectrometer BIL Band...sensor bracket mount combining Airborne Imaging Spectrometer for Applications ( AISA ) Eagle and Hawk sensors into a single imaging system (SpecTIR 2011...The AISA Eagle is a VNIR sensor with a wavelength range of approximately 400–970 nm and the AISA Hawk sensor is a SWIR sensor with a wavelength

Comparison of the performance of intraoral X-ray sensors using objective image quality assessment.

PubMed

Hellén-Halme, Kristina; Johansson, Curt; Nilsson, Mats

2016-05-01

The main aim of this study was to evaluate the performance of 10 individual sensors of the same make, using objective measures of key image quality parameters. A further aim was to compare 8 brands of sensors. Ten new sensors of 8 different models from 6 manufacturers (i.e., 80 sensors) were included in the study. All sensors were exposed in a standardized way using an X-ray tube voltage of 60 kVp and different exposure times. Sensor response, noise, low-contrast resolution, spatial resolution and uniformity were measured. Individual differences between sensors of the same brand were surprisingly large in some cases. There were clear differences in the characteristics of the different brands of sensors. The largest variations were found for individual sensor response for some of the brands studied. Also, noise level and low contrast resolution showed large variations between brands. Sensors, even of the same brand, vary significantly in their quality. It is thus valuable to establish action levels for the acceptance of newly delivered sensors and to use objective image quality control for commissioning purposes and periodic checks to ensure high performance of individual digital sensors. Copyright © 2016 Elsevier Inc. All rights reserved.

Review of recent advances in analytical techniques for the determination of neurotransmitters

PubMed Central

Perry, Maura; Li, Qiang; Kennedy, Robert T.

2009-01-01

Methods and advances for monitoring neurotransmitters in vivo or for tissue analysis of neurotransmitters over the last five years are reviewed. The review is organized primarily by neurotransmitter type. Transmitter and related compounds may be monitored by either in vivo sampling coupled to analytical methods or implanted sensors. Sampling is primarily performed using microdialysis, but low-flow push-pull perfusion may offer advantages of spatial resolution while minimizing the tissue disruption associated with higher flow rates. Analytical techniques coupled to these sampling methods include liquid chromatography, capillary electrophoresis, enzyme assays, sensors, and mass spectrometry. Methods for the detection of amino acid, monoamine, neuropeptide, acetylcholine, nucleoside, and soluable gas neurotransmitters have been developed and improved upon. Advances in the speed and sensitivity of these methods have enabled improvements in temporal resolution and increased the number of compounds detectable. Similar advances have enabled improved detection at tissue samples, with a substantial emphasis on single cell and other small samples. Sensors provide excellent temporal and spatial resolution for in vivo monitoring. Advances in application to catecholamines, indoleamines, and amino acids have been prominent. Improvements in stability, sensitivity, and selectivity of the sensors have been of paramount interest. PMID:19800472

Photonics and microarray technology

NASA Astrophysics Data System (ADS)

Skovsen, E.; Duroux, M.; Neves-Petersen, M. T.; Duroux, L.; Petersen, S. B.

2007-05-01

Photonic induced immobilization of biosensor molecules is a novel technology that results in spatially oriented and spatially localized covalent coupling of a large variety of biomolecules onto thiol reactive surfaces, e.g. thiolated glass, quartz, gold or silicon. The reaction mechanism behind the reported new technology involves light-induced breakage of disulphide bridges in proteins upon UV illumination of nearby aromatic amino acids resulting in the formation of reactive molecules that will form covalent bonds with thiol reactive surfaces. This new technology has the potential of replacing present micro dispensing arraying technologies, where the size of the individual sensor spots are limited by the size of the dispensed droplets. Using light-induced immobilization the spatial resolution is defined by the area of the sensor surface that is illuminated by UV light and not by the physical size of the dispensed droplets of sensor molecules. This new technology allows for dense packing of different biomolecules on a surface, allowing the creation of multi-potent functionalized materials, such as biosensors with micrometer sized individual sensor spots. Thus, we have developed the necessary technology for preparing large protein arrays of enzymes and fragments of antibodies, with micrometer resolution, without the need for liquid micro dispensing.

Hyperspectral Sensor Data Capability for Retrieving Complex Urban Land Cover in Comparison with Multispectral Data: Venice City Case Study (Italy)

PubMed Central

Cavalli, Rosa Maria; Fusilli, Lorenzo; Pascucci, Simone; Pignatti, Stefano; Santini, Federico

2008-01-01

This study aims at comparing the capability of different sensors to detect land cover materials within an historical urban center. The main objective is to evaluate the added value of hyperspectral sensors in mapping a complex urban context. In this study we used: (a) the ALI and Hyperion satellite data, (b) the LANDSAT ETM+ satellite data, (c) MIVIS airborne data and (d) the high spatial resolution IKONOS imagery as reference. The Venice city center shows a complex urban land cover and therefore was chosen for testing the spectral and spatial characteristics of different sensors in mapping the urban tissue. For this purpose, an object-oriented approach and different common classification methods were used. Moreover, spectra of the main anthropogenic surfaces (i.e. roofing and paving materials) were collected during the field campaigns conducted on the study area. They were exploited for applying band-depth and sub-pixel analyses to subsets of Hyperion and MIVIS hyperspectral imagery. The results show that satellite data with a 30m spatial resolution (ALI, LANDSAT ETM+ and HYPERION) are able to identify only the main urban land cover materials. PMID:27879879

An optical wavefront sensor based on a double layer microlens array.

PubMed

Lin, Vinna; Wei, Hsiang-Chun; Hsieh, Hsin-Ta; Su, Guo-Dung John

2011-01-01

In order to determine light aberrations, Shack-Hartmann optical wavefront sensors make use of microlens arrays (MLA) to divide the incident light into small parts and focus them onto image planes. In this paper, we present the design and fabrication of long focal length MLA with various shapes and arrangements based on a double layer structure for optical wavefront sensing applications. A longer focal length MLA could provide high sensitivity in determining the average slope across each microlens under a given wavefront, and spatial resolution of a wavefront sensor is increased by numbers of microlenses across a detector. In order to extend focal length, we used polydimethysiloxane (PDMS) above MLA on a glass substrate. Because of small refractive index difference between PDMS and MLA interface (UV-resin), the incident light is less refracted and focused in further distance. Other specific focal lengths could also be realized by modifying the refractive index difference without changing the MLA size. Thus, the wavefront sensor could be improved with better sensitivity and higher spatial resolution.

Image Stability Requirements For a Geostationary Imaging Fourier Transform Spectrometer (GIFTS)

NASA Technical Reports Server (NTRS)

Bingham, G. E.; Cantwell, G.; Robinson, R. C.; Revercomb, H. E.; Smith, W. L.

2001-01-01

A Geostationary Imaging Fourier Transform Spectrometer (GIFTS) has been selected for the NASA New Millennium Program (NMP) Earth Observing-3 (EO-3) mission. Our paper will discuss one of the key GIFTS measurement requirements, Field of View (FOV) stability, and its impact on required system performance. The GIFTS NMP mission is designed to demonstrate new and emerging sensor and data processing technologies with the goal of making revolutionary improvements in meteorological observational capability and forecasting accuracy. The GIFTS payload is a versatile imaging FTS with programmable spectral resolution and spatial scene selection that allows radiometric accuracy and atmospheric sounding precision to be traded in near real time for area coverage. The GIFTS sensor combines high sensitivity with a massively parallel spatial data collection scheme to allow high spatial resolution measurement of the Earth's atmosphere and rapid broad area coverage. An objective of the GIFTS mission is to demonstrate the advantages of high spatial resolution (4 km ground sample distance - gsd) on temperature and water vapor retrieval by allowing sampling in broken cloud regions. This small gsd, combined with the relatively long scan time required (approximately 10 s) to collect high resolution spectra from geostationary (GEO) orbit, may require extremely good pointing control. This paper discusses the analysis of this requirement.

Efficient space-time sampling with pixel-wise coded exposure for high-speed imaging.

PubMed

Liu, Dengyu; Gu, Jinwei; Hitomi, Yasunobu; Gupta, Mohit; Mitsunaga, Tomoo; Nayar, Shree K

2014-02-01

Cameras face a fundamental trade-off between spatial and temporal resolution. Digital still cameras can capture images with high spatial resolution, but most high-speed video cameras have relatively low spatial resolution. It is hard to overcome this trade-off without incurring a significant increase in hardware costs. In this paper, we propose techniques for sampling, representing, and reconstructing the space-time volume to overcome this trade-off. Our approach has two important distinctions compared to previous works: 1) We achieve sparse representation of videos by learning an overcomplete dictionary on video patches, and 2) we adhere to practical hardware constraints on sampling schemes imposed by architectures of current image sensors, which means that our sampling function can be implemented on CMOS image sensors with modified control units in the future. We evaluate components of our approach, sampling function and sparse representation, by comparing them to several existing approaches. We also implement a prototype imaging system with pixel-wise coded exposure control using a liquid crystal on silicon device. System characteristics such as field of view and modulation transfer function are evaluated for our imaging system. Both simulations and experiments on a wide range of scenes show that our method can effectively reconstruct a video from a single coded image while maintaining high spatial resolution.

Investigation of CMOS pixel sensor with 0.18 μm CMOS technology for high-precision tracking detector

NASA Astrophysics Data System (ADS)

Zhang, L.; Fu, M.; Zhang, Y.; Yan, W.; Wang, M.

2017-01-01

The Circular Electron Positron Collider (CEPC) proposed by the Chinese high energy physics community is aiming to measure Higgs particles and their interactions precisely. The tracking detector including Silicon Inner Tracker (SIT) and Forward Tracking Disks (FTD) has driven stringent requirements on sensor technologies in term of spatial resolution, power consumption and readout speed. CMOS Pixel Sensor (CPS) is a promising candidate to approach these requirements. This paper presents the preliminary studies on the sensor optimization for tracking detector to achieve high collection efficiency while keeping necessary spatial resolution. Detailed studies have been performed on the charge collection using a 0.18 μm CMOS image sensor process. This process allows high resistivity epitaxial layer, leading to a significant improvement on the charge collection and therefore improving the radiation tolerance. Together with the simulation results, the first exploratory prototype has bee designed and fabricated. The prototype includes 9 different pixel arrays, which vary in terms of pixel pitch, diode size and geometry. The total area of the prototype amounts to 2 × 7.88 mm2.

Stochastic Downscaling of Digital Elevation Models

NASA Astrophysics Data System (ADS)

Rasera, Luiz Gustavo; Mariethoz, Gregoire; Lane, Stuart N.

2016-04-01

High-resolution digital elevation models (HR-DEMs) are extremely important for the understanding of small-scale geomorphic processes in Alpine environments. In the last decade, remote sensing techniques have experienced a major technological evolution, enabling fast and precise acquisition of HR-DEMs. However, sensors designed to measure elevation data still feature different spatial resolution and coverage capabilities. Terrestrial altimetry allows the acquisition of HR-DEMs with centimeter to millimeter-level precision, but only within small spatial extents and often with dead ground problems. Conversely, satellite radiometric sensors are able to gather elevation measurements over large areas but with limited spatial resolution. In the present study, we propose an algorithm to downscale low-resolution satellite-based DEMs using topographic patterns extracted from HR-DEMs derived for example from ground-based and airborne altimetry. The method consists of a multiple-point geostatistical simulation technique able to generate high-resolution elevation data from low-resolution digital elevation models (LR-DEMs). Initially, two collocated DEMs with different spatial resolutions serve as an input to construct a database of topographic patterns, which is also used to infer the statistical relationships between the two scales. High-resolution elevation patterns are then retrieved from the database to downscale a LR-DEM through a stochastic simulation process. The output of the simulations are multiple equally probable DEMs with higher spatial resolution that also depict the large-scale geomorphic structures present in the original LR-DEM. As these multiple models reflect the uncertainty related to the downscaling, they can be employed to quantify the uncertainty of phenomena that are dependent on fine topography, such as catchment hydrological processes. The proposed methodology is illustrated for a case study in the Swiss Alps. A swissALTI3D HR-DEM (with 5 m resolution) and a SRTM-derived LR-DEM from the Western Alps are used to downscale a SRTM-based LR-DEM from the eastern part of the Alps. The results show that the method is capable of generating multiple high-resolution synthetic DEMs that reproduce the spatial structure and statistics of the original DEM.

Scaling of surface energy fluxes using remotely sensed data

NASA Astrophysics Data System (ADS)

French, Andrew Nichols

Accurate estimates of evapotranspiration (ET) across multiple terrains would greatly ease challenges faced by hydrologists, climate modelers, and agronomists as they attempt to apply theoretical models to real-world situations. One ET estimation approach uses an energy balance model to interpret a combination of meteorological observations taken at the surface and data captured by remote sensors. However, results of this approach have not been accurate because of poor understanding of the relationship between surface energy flux and land cover heterogeneity, combined with limits in available resolution of remote sensors. The purpose of this study was to determine how land cover and image resolution affect ET estimates. Using remotely sensed data collected over El Reno, Oklahoma, during four days in June and July 1997, scale effects on the estimation of spatially distributed ET were investigated. Instantaneous estimates of latent and sensible heat flux were calculated using a two-source surface energy balance model driven by thermal infrared, visible-near infrared, and meteorological data. The heat flux estimates were verified by comparison to independent eddy-covariance observations. Outcomes of observations taken at coarser resolutions were simulated by aggregating remote sensor data and estimated surface energy balance components from the finest sensor resolution (12 meter) to hypothetical resolutions as coarse as one kilometer. Estimated surface energy flux components were found to be significantly dependent on observation scale. For example, average evaporative fraction varied from 0.79, using 12-m resolution data, to 0.93, using 1-km resolution data. Resolution effects upon flux estimates were related to a measure of landscape heterogeneity known as operational scale, reflecting the size of dominant landscape features. Energy flux estimates based on data at resolutions less than 100 m and much greater than 400 m showed a scale-dependent bias. But estimates derived from data taken at about 400-m resolution (the operational scale at El Reno) were susceptible to large error due to mixing of surface types. The El Reno experiments show that accurate instantaneous estimates of ET require precise image alignment and image resolutions finer than landscape operational scale. These findings are valuable for the design of sensors and experiments to quantify spatially-varying hydrologic processes.

Climate Change Mitigation: Can the U.S. Intelligence Community Help?

DTIC Science & Technology

2013-06-01

satellite sensors to establish the concentration of atmospheric CO2 parts per million (ppm mole fraction) in samples collected at multiple...measurements. Spatial sampling density, the number of sensors or—in the case of satellite imagery the number and resolution of the images—likewise influences...Somewhat paradoxically, sensor accuracy from either remote ( satellites ) or in situ sensors is an important consideration, but it must also be evaluated

Comparison of Different EO Sensors for Mapping Tree Species- A Case Study in Southwest Germany

NASA Astrophysics Data System (ADS)

Enßle, Fabian; Kattenborn, Teja; Koch, Barbara

2014-11-01

The variety of different remote sensing sensors and thus the types of data specifications which are available is increasing continuously. Especially the differences in geometric, radiometric and temporal resolutions of different platforms affect their ability for the mapping of forests. These differences hinder the comparability and application of uniform methods of different remotely sensed data across the same region of interest. The quality and quantity of retrieved forest parameters is directly dependent on the data source, and therefore the objective of this project is to analyse the relationship between the data source and its derived parameters. A comparison of different optical EO-data (e.g. spatial resolution and spectral resolution of specific bands) will help to define the optimum data sets to produce a reproducible method to provide additional inputs to the Dragon cooperative project, specifically to method development for woody biomass estimation and biodiversity assessment services. This poster presents the first results on tree species mapping in a mixed temperate forest by satellite imagery taken from four different sensors. Tree species addressed in this pilot study are Scots pine (Pinus sylvestris), sessile oak (Quercus petraea) and red oak (Quercus rubra). The spatial resolution varies from 2m to 30m and the spectral resolutions range from 8bands up to 155bands.

Comparison of Different EO Sensors for Mapping Tree Species- A Case Study in Southwest Germany

NASA Astrophysics Data System (ADS)

Enβle, Fabian; Kattenborn, Teja; Koch, Barbara

2014-11-01

The variety of different remote sensing sensors and thus the types of data specifications which are available is increasing continuously. Especially the differences in geometric, radiometric and temporal resolutions of different platforms affect their ability for the mapping of forests. These differences hinder the comparability and application of uniform methods of different remotely sensed data across the same region of interest. The quality and quantity of retrieved forest parameters is directly dependent on the data source, and therefore the objective of this project is to analyse the relationship between the data source and its derived parameters. A comparison of different optical EO-data (e.g. spatial resolution and spectral resolution of specific bands) will help to define the optimum data sets to produce a reproducible method to provide additional inputs to the Dragon cooperative project, specifically to method development for woody biomass estimation and biodiversity assessment services. This poster presents the first results on tree species mapping in a mixed temperate forest by satellite imagery taken from four different sensors. Tree species addressed in this pilot study are: Scots pine (Pinus sylvestris), sessile oak (Quercus petraea) and red oak (Quercus rubra). The spatial resolution varies from 2m to 30m and the spectral resolutions range from 8bands up to 155bands.

Single image super-resolution via regularized extreme learning regression for imagery from microgrid polarimeters

NASA Astrophysics Data System (ADS)

Sargent, Garrett C.; Ratliff, Bradley M.; Asari, Vijayan K.

2017-08-01

The advantage of division of focal plane imaging polarimeters is their ability to obtain temporally synchronized intensity measurements across a scene; however, they sacrifice spatial resolution in doing so due to their spatially modulated arrangement of the pixel-to-pixel polarizers and often result in aliased imagery. Here, we propose a super-resolution method based upon two previously trained extreme learning machines (ELM) that attempt to recover missing high frequency and low frequency content beyond the spatial resolution of the sensor. This method yields a computationally fast and simple way of recovering lost high and low frequency content from demosaicing raw microgrid polarimetric imagery. The proposed method outperforms other state-of-the-art single-image super-resolution algorithms in terms of structural similarity and peak signal-to-noise ratio.

Single-shot and single-sensor high/super-resolution microwave imaging based on metasurface.

PubMed

Wang, Libo; Li, Lianlin; Li, Yunbo; Zhang, Hao Chi; Cui, Tie Jun

2016-06-01

Real-time high-resolution (including super-resolution) imaging with low-cost hardware is a long sought-after goal in various imaging applications. Here, we propose broadband single-shot and single-sensor high-/super-resolution imaging by using a spatio-temporal dispersive metasurface and an imaging reconstruction algorithm. The metasurface with spatio-temporal dispersive property ensures the feasibility of the single-shot and single-sensor imager for super- and high-resolution imaging, since it can convert efficiently the detailed spatial information of the probed object into one-dimensional time- or frequency-dependent signal acquired by a single sensor fixed in the far-field region. The imaging quality can be improved by applying a feature-enhanced reconstruction algorithm in post-processing, and the desired imaging resolution is related to the distance between the object and metasurface. When the object is placed in the vicinity of the metasurface, the super-resolution imaging can be realized. The proposed imaging methodology provides a unique means to perform real-time data acquisition, high-/super-resolution images without employing expensive hardware (e.g. mechanical scanner, antenna array, etc.). We expect that this methodology could make potential breakthroughs in the areas of microwave, terahertz, optical, and even ultrasound imaging.

Scaling field data to calibrate and validate moderate spatial resolution remote sensing models

USGS Publications Warehouse

Baccini, A.; Friedl, M.A.; Woodcock, C.E.; Zhu, Z.

2007-01-01

Validation and calibration are essential components of nearly all remote sensing-based studies. In both cases, ground measurements are collected and then related to the remote sensing observations or model results. In many situations, and particularly in studies that use moderate resolution remote sensing, a mismatch exists between the sensor's field of view and the scale at which in situ measurements are collected. The use of in situ measurements for model calibration and validation, therefore, requires a robust and defensible method to spatially aggregate ground measurements to the scale at which the remotely sensed data are acquired. This paper examines this challenge and specifically considers two different approaches for aggregating field measurements to match the spatial resolution of moderate spatial resolution remote sensing data: (a) landscape stratification; and (b) averaging of fine spatial resolution maps. The results show that an empirically estimated stratification based on a regression tree method provides a statistically defensible and operational basis for performing this type of procedure. 

Linear mixing model applied to coarse spatial resolution data from multispectral satellite sensors

NASA Technical Reports Server (NTRS)

Holben, Brent N.; Shimabukuro, Yosio E.

1993-01-01

A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55-3.95 micron channel was used with the two reflective channels 0.58-0.68 micron and 0.725-1.1 micron to run a constrained least squares model to generate fraction images for an area in the west central region of Brazil. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse spatial resolution data for global studies.

Low-Cost Sensor Units for Measuring Urban Air Quality

NASA Astrophysics Data System (ADS)

Popoola, O. A.; Mead, M.; Stewart, G.; Hodgson, T.; McLoed, M.; Baldovi, J.; Landshoff, P.; Hayes, M.; Calleja, M.; Jones, R.

2010-12-01

Measurements of selected key air quality gases (CO, NO & NO2) have been made with a range of miniature low-cost sensors based on electrochemical gas sensing technology incorporating GPS and GPRS for position and communication respectively. Two types of simple to operate sensors units have been designed to be deployed in relatively large numbers. Mobile handheld sensor units designed for operation by members of the public have been deployed on numerous occasions including in Cambridge, London and Valencia. Static sensor units have also been designed for long-term autonomous deployment on existing street furniture. A study was recently completed in which 45 sensor units were deployed in the Cambridge area for a period of 3 months. Results from these studies indicate that air quality varies widely both spatially and temporally. The widely varying concentrations found suggest that the urban environment cannot be fully understood using limited static site (AURN) networks and that a higher resolution, more dispersed network is required to better define air quality in the urban environment. The results also suggest that higher spatial and temporal resolution measurements could improve knowledge of the levels of individual exposure in the urban environment.

Integrated sensor with frame memory and programmable resolution for light adaptive imaging

NASA Technical Reports Server (NTRS)

Zhou, Zhimin (Inventor); Fossum, Eric R. (Inventor); Pain, Bedabrata (Inventor)

2004-01-01

An image sensor operable to vary the output spatial resolution according to a received light level while maintaining a desired signal-to-noise ratio. Signals from neighboring pixels in a pixel patch with an adjustable size are added to increase both the image brightness and signal-to-noise ratio. One embodiment comprises a sensor array for receiving input signals, a frame memory array for temporarily storing a full frame, and an array of self-calibration column integrators for uniform column-parallel signal summation. The column integrators are capable of substantially canceling fixed pattern noise.

Distributed optical fiber dynamic magnetic field sensor based on magnetostriction.

PubMed

Masoudi, Ali; Newson, Trevor P

2014-05-01

A distributed optical fiber sensor is introduced which is capable of quantifying multiple magnetic fields along a 1 km sensing fiber with a spatial resolution of 1 m. The operation of the proposed sensor is based on measuring the magnetorestrictive induced strain of a nickel wire attached to an optical fiber. The strain coupled to the optical fiber was detected by measuring the strain-induced phase variation between the backscattered Rayleigh light from two segments of the sensing fiber. A magnetic field intensity resolution of 0.3 G over a bandwidth of 50-5000 Hz was demonstrated.

Regional forest land cover characterisation using medium spatial resolution satellite data

USGS Publications Warehouse

Huang, Chengquan; Homer, Collin G.; Yang, Limin; Wulder, Michael A.; Franklin, Steven E.

2003-01-01

Increasing demands on forest resources require comprehensive, consistent and up-to-date information on those resources at spatial scales appropriate for management decision-making and for scientific analysis. While such information can be derived using coarse spatial resolution satellite data (e.g. Tucker et al. 1984; Zhu and Evans 1994; Cihlar et al. 1996; Cihlar et al., Chapter 12), many regional applications require more spatial and thematic details than can be derived by using coarse resolution imagery. High spatial resolution satellite data such as IKONOS and Quick Bird images (Aplin et al. 1997), though usable for deriving detailed forest information (Culvenor, Chapter 9), are currently not feasible for wall-to-wall regional applications because of extremely high data cost, huge data volume, and lack of contiguous coverage over large areas. Forest studies over large areas have often been accomplished using data acquired by intermediate spatial resolution sensor systems, including the Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and the Enhanced Thematic Mapper Plus (ETM+) of Landsat, the High Resolution Visible (HRV) of the Systeme Pour l'Observation de la Terre (SPOT), and the Linear Image Self-Scanner (LISS) of the Indian Remote Sensing satellite. These sensor systems are more appropriate for regional applications because they can routinely produce spatially contiguous data over large areas at relatively low cost, and can be used to derive a host of forest attributes (e.g. Cohen et al. 1995; Kimes et al. 1999; Cohen et al. 2001; Huang et al. 2001; Sugumaran 2001). Of the above intermediate spatial resolution satellites, Landsat is perhaps the most widely used in various types of land remote sensing applications, in part because it has provided more extensive spatial and temporal coverage of the globe than any other intermediate resolution satellite. Spatially contiguous Landsat data have been developed for many regions of the globe (e.g. Lunetta and Sturdevant 1993; Fuller et al. 1994b; Skole et al. 1997), and a circa 1990 Landsat image data set covering the entire land area of the globe has also been developed recently (Jones and Smith 2001). An acquisition strategy aimed at acquiring at least one cloud free image per year for the entire land area of the globe has been initiated for Landsat-7 (Arvidson et al. 2001). This will probably ensure the continued dominance of Landsat in the near future.

Cross-Calibration of Earth Observing System Terra Satellite Sensors MODIS and ASTER

NASA Technical Reports Server (NTRS)

McCorkel, J.

2014-01-01

The Advanced Spaceborne Thermal Emissive and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectrometer (MODIS) are two of the five sensors onboard the Earth Observing System's Terra satellite. These sensors share many similar spectral channels while having much different spatial and operational parameters. ASTER is a tasked sensor and sometimes referred to a zoom camera of the MODIS that collects a full-earth image every one to two days. It is important that these sensors have a consistent characterization and calibration for continued development and use of their data products. This work uses a variety of test sites to retrieve and validate intercalibration results. The refined calibration of Collection 6 of the Terra MODIS data set is leveraged to provide the up-to-date reference for trending and validation of ASTER. Special attention is given to spatially matching radiance measurements using prelaunch spatial response characterization of MODIS. Despite differences in spectral band properties and spatial scales, ASTER-MODIS is an ideal case for intercomparison since the sensors have nearly identical views and acquisitions times and therefore can be used as a baseline of intercalibration performance of other satellite sensor pairs.

Microscopic resolution broadband dielectric spectroscopy

NASA Astrophysics Data System (ADS)

Mukherjee, S.; Watson, P.; Prance, R. J.

2011-08-01

Results are presented for a non-contact measurement system capable of micron level spatial resolution. It utilises the novel electric potential sensor (EPS) technology, invented at Sussex, to image the electric field above a simple composite dielectric material. EP sensors may be regarded as analogous to a magnetometer and require no adjustments or offsets during either setup or use. The sample consists of a standard glass/epoxy FR4 circuit board, with linear defects machined into the surface by a PCB milling machine. The sample is excited with an a.c. signal over a range of frequencies from 10 kHz to 10 MHz, from the reverse side, by placing it on a conducting sheet connected to the source. The single sensor is raster scanned over the surface at a constant working distance, consistent with the spatial resolution, in order to build up an image of the electric field, with respect to the reference potential. The results demonstrate that both the surface defects and the internal dielectric variations within the composite may be imaged in this way, with good contrast being observed between the glass mat and the epoxy resin.

Multi-scales and multi-satellites estimates of evapotranspiration with a residual energy balance model in the Muzza agricultural district in Northern Italy

NASA Astrophysics Data System (ADS)

Corbari, C.; Bissolati, M.; Mancini, M.

2015-05-01

Evapotranspiration estimates were performed with a residual energy balance model (REB) over an agricultural area using remote sensing data. REB uses land surface temperature (LST) as main input parameter so that energy fluxes were computed instantaneously at the time of data acquisition. Data from MODIS and SEVIRI sensors were used and downscaling techniques were implemented to improve their spatial resolutions. Energy fluxes at the original spatial resolutions (1000 m for MODIS and 5000 m for SEVIRI) as well as at the downscaled resolutions (250 m for MODIS and 1000 m for SEVIRI) were calculated with the REB model. Ground eddy covariance data and remote sensing information from the Muzza agricultural irrigation district in Italy from 2010 to 2012 gave the opportunity to validate and compare spatially distributed energy fluxes. The model outputs matched quite well ground observations when ground LST data were used, while differences increased when MODIS and SEVIRI LST were used. The spatial analysis revealed significant differences between the two sensors both in term of LST (around 2.8 °C) and of latent heat fluxes with values (around 100 W m-2).

A PIXEL COMPOSITION-BASED REFERENCE DATA SET FOR THEMATIC ACCURACY ASSESSMENT

EPA Science Inventory

Developing reference data sets for accuracy assessment of land-cover classifications derived from coarse spatial resolution sensors such as MODIS can be difficult due to the large resolution differences between the image data and available reference data sources. Ideally, the spa...

A Flexible Spatiotemporal Method for Fusing Satellite Images with Different Resolutions

USDA-ARS?s Scientific Manuscript database

Studies of land surface dynamics in heterogeneous landscapes often require remote sensing data with high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta ...

Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data

NASA Astrophysics Data System (ADS)

Moradizadeh, Mina; Saradjian, Mohammad R.

2018-03-01

Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.

Spatial variability of summer Florida precipitation and its impact on microwave radiometer rainfall-measurement systems

NASA Technical Reports Server (NTRS)

Turner, B. J.; Austin, G. L.

1993-01-01

Three-dimensional radar data for three summer Florida storms are used as input to a microwave radiative transfer model. The model simulates microwave brightness observations by a 19-GHz, nadir-pointing, satellite-borne microwave radiometer. The statistical distribution of rainfall rates for the storms studied, and therefore the optimal conversion between microwave brightness temperatures and rainfall rates, was found to be highly sensitive to the spatial resolution at which observations were made. The optimum relation between the two quantities was less sensitive to the details of the vertical profile of precipitation. Rainfall retrievals were made for a range of microwave sensor footprint sizes. From these simulations, spatial sampling-error estimates were made for microwave radiometers over a range of field-of-view sizes. The necessity of matching the spatial resolution of ground truth to radiometer footprint size is emphasized. A strategy for the combined use of raingages, ground-based radar, microwave, and visible-infrared (VIS-IR) satellite sensors is discussed.

Remote Sensing, GIS, and Vector-Borne Disease

NASA Technical Reports Server (NTRS)

Beck, Louisa R.

2001-01-01

The concept of global climate change encompasses more than merely an alteration in temperature; it also includes spatial and temporal covariations in precipitation and humidity, and more frequent occurrence of extreme weather events. The impact of these variations, which can occur at a variety of temporal and spatial scales, could have a direct impact on disease transmission through their environmental consequences for pathogen, vector, and host survival, as well as indirectly through human demographic and behavioral responses. New and future sensor systems will allow scientists to investigate the relationships between climate change and environmental risk factors at multiple spatial, temporal and spectral scales. Higher spatial resolution will provide better opportunities for mapping urban features previously only possible with high resolution aerial photography. These opportunities include housing quality (e.g., Chagas'disease, leishmaniasis) and urban mosquito habitats (e.g., dengue fever, filariasis, LaCrosse encephalitis). There are or will be many new sensors that have higher spectral resolution, enabling scientists to acquire more information about parameters such as soil moisture, soil type, better vegetation discrimination, and ocean color, to name a few. Although soil moisture content is now detectable using Landsat, the new thermal, shortwave infrared, and radar sensors will be able to provide this information at a variety of scales not achievable using Landsat. Soil moisture could become a key component in transmission risk models for Lyme disease (tick survival), helminthiases (worm habitat), malaria (vector-breeding habitat), and schistosomiasis (snail habitat).

Initial Validation of NDVI time seriesfrom AVHRR, VEGETATION, and MODIS

NASA Technical Reports Server (NTRS)

Morisette, Jeffrey T.; Pinzon, Jorge E.; Brown, Molly E.; Tucker, Jim; Justice, Christopher O.

2004-01-01

The paper will address Theme 7: Multi-sensor opportunities for VEGETATION. We present analysis of a long-term vegetation record derived from three moderate resolution sensors: AVHRR, VEGETATION, and MODIS. While empirically based manipulation can ensure agreement between the three data sets, there is a need to validate the series. This paper uses atmospherically corrected ETM+ data available over the EOS Land Validation Core Sites as an independent data set with which to compare the time series. We use ETM+ data from 15 globally distributed sites, 7 of which contain repeat coverage in time. These high-resolution data are compared to the values of each sensor by spatially aggregating the ETM+ to each specific sensors' spatial coverage. The aggregated ETM+ value provides a point estimate for a specific site on a specific date. The standard deviation of that point estimate is used to construct a confidence interval for that point estimate. The values from each moderate resolution sensor are then evaluated with respect to that confident interval. Result show that AVHRR, VEGETATION, and MODIS data can be combined to assess temporal uncertainties and address data continuity issues and that the atmospherically corrected ETM+ data provide an independent source with which to compare that record. The final product is a consistent time series climate record that links historical observations to current and future measurements.

Single Photon Counting Large Format Imaging Sensors with High Spatial and Temporal Resolution

NASA Astrophysics Data System (ADS)

Siegmund, O. H. W.; Ertley, C.; Vallerga, J. V.; Cremer, T.; Craven, C. A.; Lyashenko, A.; Minot, M. J.

High time resolution astronomical and remote sensing applications have been addressed with microchannel plate based imaging, photon time tagging detector sealed tube schemes. These are being realized with the advent of cross strip readout techniques with high performance encoding electronics and atomic layer deposited (ALD) microchannel plate technologies. Sealed tube devices up to 20 cm square have now been successfully implemented with sub nanosecond timing and imaging. The objective is to provide sensors with large areas (25 cm2 to 400 cm2) with spatial resolutions of <20 μm FWHM and timing resolutions of <100 ps for dynamic imaging. New high efficiency photocathodes for the visible regime are discussed, which also allow response down below 150nm for UV sensing. Borosilicate MCPs are providing high performance, and when processed with ALD techniques are providing order of magnitude lifetime improvements and enhanced photocathode stability. New developments include UV/visible photocathodes, ALD MCPs, and high resolution cross strip anodes for 100 mm detectors. Tests with 50 mm format cross strip readouts suitable for Planacon devices show spatial resolutions better than 20 μm FWHM, with good image linearity while using low gain ( 106). Current cross strip encoding electronics can accommodate event rates of >5 MHz and event timing accuracy of 100 ps. High-performance ASIC versions of these electronics are in development with better event rate, power and mass suitable for spaceflight instruments.

Applying narrowband remote-sensing reflectance models to wideband data.

PubMed

Lee, Zhongping

2009-06-10

Remote sensing of coastal and inland waters requires sensors to have a high spatial resolution to cover the spatial variation of biogeochemical properties in fine scales. High spatial-resolution sensors, however, are usually equipped with spectral bands that are wide in bandwidth (50 nm or wider). In this study, based on numerical simulations of hyperspectral remote-sensing reflectance of optically-deep waters, and using Landsat band specifics as an example, the impact of a wide spectral channel on remote sensing is analyzed. It is found that simple adoption of a narrowband model may result in >20% underestimation in calculated remote-sensing reflectance, and inversely may result in >20% overestimation in inverted absorption coefficients even under perfect conditions, although smaller (approximately 5%) uncertainties are found for higher absorbing waters. These results provide a cautious note, but also a justification for turbid coastal waters, on applying narrowband models to wideband data.

Proof of principle study of the use of a CMOS active pixel sensor for proton radiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seco, Joao; Depauw, Nicolas

2011-02-15

Purpose: Proof of principle study of the use of a CMOS active pixel sensor (APS) in producing proton radiographic images using the proton beam at the Massachusetts General Hospital (MGH). Methods: A CMOS APS, previously tested for use in s-ray radiation therapy applications, was used for proton beam radiographic imaging at the MGH. Two different setups were used as a proof of principle that CMOS can be used as proton imaging device: (i) a pen with two metal screws to assess spatial resolution of the CMOS and (ii) a phantom with lung tissue, bone tissue, and water to assess tissuemore » contrast of the CMOS. The sensor was then traversed by a double scattered monoenergetic proton beam at 117 MeV, and the energy deposition inside the detector was recorded to assess its energy response. Conventional x-ray images with similar setup at voltages of 70 kVp and proton images using commercial Gafchromic EBT 2 and Kodak X-Omat V films were also taken for comparison purposes. Results: Images were successfully acquired and compared to x-ray kVp and proton EBT2/X-Omat film images. The spatial resolution of the CMOS detector image is subjectively comparable to the EBT2 and Kodak X-Omat V film images obtained at the same object-detector distance. X-rays have apparent higher spatial resolution than the CMOS. However, further studies with different commercial films using proton beam irradiation demonstrate that the distance of the detector to the object is important to the amount of proton scatter contributing to the proton image. Proton images obtained with films at different distances from the source indicate that proton scatter significantly affects the CMOS image quality. Conclusion: Proton radiographic images were successfully acquired at MGH using a CMOS active pixel sensor detector. The CMOS demonstrated spatial resolution subjectively comparable to films at the same object-detector distance. Further work will be done in order to establish the spatial and energy resolution of the CMOS detector for protons. The development and use of CMOS in proton radiography could allow in vivo proton range checks, patient setup QA, and real-time tumor tracking.« less

Impact of microwave derived soil moisture on hydrologic simulations using a spatially distributed water balance model

NASA Technical Reports Server (NTRS)

Lin, D. S.; Wood, E. F.; Famiglietti, J. S.; Mancini, M.

1994-01-01

Spatial distributions of soil moisture over an agricultural watershed with a drainage area of 60 ha were derived from two NASA microwave remote sensors, and then used as a feedback to determine the initial condition for a distributed water balance model. Simulated hydrologic fluxes over a period of twelve days were compared with field observations and with model predictions based on a streamflow derived initial condition. The results indicated that even the low resolution remotely sensed data can improve the hydrologic model's performance in simulating the dynamics of unsaturated zone soil moisture. For the particular watershed under study, the simulated water budget was not sensitive to the resolutions of the microwave sensors.

Distributed optical fiber temperature sensor (DOFTS) system applied to automatic temperature alarm of coal mine and tunnel

NASA Astrophysics Data System (ADS)

Zhang, Zaixuan; Wang, Kequan; Kim, Insoo S.; Wang, Jianfeng; Feng, Haiqi; Guo, Ning; Yu, Xiangdong; Zhou, Bangquan; Wu, Xiaobiao; Kim, Yohee

2000-05-01

The DOFTS system that has applied to temperature automatically alarm system of coal mine and tunnel has been researched. It is a real-time, on line and multi-point measurement system. The wavelength of LD is 1550 nm, on the 6 km optical fiber, 3000 points temperature signal is sampled and the spatial position is certain. Temperature measured region: -50 degree(s)C--100 degree(s)C; measured uncertain value: +/- 3 degree(s)C; temperature resolution: 0.1 degree(s)C; spatial resolution: <5 cm (optical fiber sensor probe); <8 m (spread optical fiber); measured time: <70 s. In the paper, the operated principles, underground test, test content and practical test results have been discussed.

New results on diamond pixel sensors using ATLAS frontend electronics

NASA Astrophysics Data System (ADS)

Keil, M.; Adam, W.; Berdermann, E.; Bergonzo, P.; de Boer, W.; Bogani, F.; Borchi, E.; Brambilla, A.; Bruzzi, M.; Colledani, C.; Conway, J.; D'Angelo, P.; Dabrowski, W.; Delpierre, P.; Dulinski, W.; Doroshenko, J.; Doucet, M.; van Eijk, B.; Fallou, A.; Fischer, P.; Fizzotti, F.; Kania, D.; Gan, K. K.; Grigoriev, E.; Hallewell, G.; Han, S.; Hartjes, F.; Hrubec, J.; Husson, D.; Kagan, H.; Kaplon, J.; Kass, R.; Knöpfle, K. T.; Koeth, T.; Krammer, M.; Logiudice, A.; mac Lynne, L.; Manfredotti, C.; Meier, D.; Menichelli, D.; Meuser, S.; Mishina, M.; Moroni, L.; Noomen, J.; Oh, A.; Pan, L. S.; Pernicka, M.; Perera, L.; Riester, J. L.; Roe, S.; Rudge, A.; Russ, J.; Sala, S.; Sampietro, M.; Schnetzer, S.; Sciortino, S.; Stelzer, H.; Stone, R.; Suter, B.; Trischuk, W.; Tromson, D.; Vittone, E.; Weilhammer, P.; Wermes, N.; Wetstein, M.; Zeuner, W.; Zoeller, M.

2003-03-01

Diamond is a promising sensor material for future collider experiments due to its radiation hardness. Diamond pixel sensors have been bump bonded to an ATLAS pixel readout chip using PbSn solder bumps. Single chip devices have been characterised by lab measurements and in a high-energy pion beam at CERN. Results on charge collection, spatial resolution, efficiency and the charge carrier lifetime are presented.

Holographic imaging with a Shack-Hartmann wavefront sensor.

PubMed

Gong, Hai; Soloviev, Oleg; Wilding, Dean; Pozzi, Paolo; Verhaegen, Michel; Vdovin, Gleb

2016-06-27

A high-resolution Shack-Hartmann wavefront sensor has been used for coherent holographic imaging, by computer reconstruction and propagation of the complex field in a lensless imaging setup. The resolution of the images obtained with the experimental data is in a good agreement with the diffraction theory. Although a proper calibration with a reference beam improves the image quality, the method has a potential for reference-less holographic imaging with spatially coherent monochromatic and narrowband polychromatic sources in microscopy and imaging through turbulence.

Radiometric calibration of the Earth observing system's imaging sensors

NASA Technical Reports Server (NTRS)

Slater, P. N.

1987-01-01

Philosophy, requirements, and methods of calibration of multispectral space sensor systems as applicable to the Earth Observing System (EOS) are discussed. Vicarious methods for calibration of low spatial resolution systems, with respect to the Advanced Very High Resolution Radiometer (AVHRR), are then summarized. Finally, a theoretical introduction is given to a new vicarious method of calibration using the ratio of diffuse-to-global irradiance at the Earth's surfaces as the key input. This may provide an additional independent method for in-flight calibration.

High-Density, High-Resolution, Low-Cost Air Quality Sensor Networks for Urban Air Monitoring

NASA Astrophysics Data System (ADS)

Mead, M. I.; Popoola, O. A.; Stewart, G.; Bright, V.; Kaye, P.; Saffell, J.

2012-12-01

Monitoring air quality in highly granular environments such as urban areas which are spatially heterogeneous with variable emission sources, measurements need to be made at appropriate spatial and temporal scales. Current routine air quality monitoring networks generally are either composed of sparse expensive installations (incorporating e.g. chemiluminescence instruments) or higher density low time resolution systems (e.g. NO2 diffusion tubes). Either approach may not accurately capture important effects such as pollutant "hot spots" or adequately capture spatial (or temporal) variability. As a result, analysis based on data from traditional low spatial resolution networks, such as personal exposure, may be inaccurate. In this paper we present details of a sophisticated, low-cost, multi species (gas phase, speciated PM, meteorology) air quality measurement network methodology incorporating GPS and GPRS which has been developed for high resolution air quality measurements in urban areas. Sensor networks developed in the Centre for Atmospheric Science (University of Cambridge) incorporated electrochemical gas sensors configured for use in urban air quality studies operating at parts-per-billion (ppb) levels. It has been demonstrated that these sensors can be used to measure key air quality gases such as CO, NO and NO2 at the low ppb mixing ratios present in the urban environment (estimated detection limits <4ppb for CO and NO and <1ppb for NO2. Mead et al (submitted Aug., 2012)). Based on this work, a state of the art multi species instrument package for deployment in scalable sensor networks has been developed which has general applicability. This is currently being employed as part of a major 3 year UK program at London Heathrow airport (the Sensor Networks for Air Quality (SNAQ) Heathrow project). The main project outcome is the creation of a calibrated, high spatial and temporal resolution data set for O3, NO, NO2, SO2, CO, CO2, VOCstotal, size-speciated PM, temperature, relative humidity, wind speed and direction. The network incorporates existing GPRS infrastructures for real time sending of data with low overheads in terms of cost, effort and installation. In this paper we present data from the SNAQ Heathrow project as well as previous deployments showing measurement capability at the ppb level for NO, NO2 and CO. We show that variability can be observed and measured quantitatively using these sensor networks over widely differing time scales from individual emission events, diurnal variability associated with traffic and meteorological conditions, through to longer term synoptic weather conditions and seasonal behaviour. This work demonstrates a widely applicable generic capability to urban areas, airports as well as other complex emissions environments making this sensor system methodology valuable for scientific, policy and regulatory issues. We conclude that the low-cost high-density network philosophy has the potential to provide a more complete assessment of the high-granularity air quality structure generally observed in the environment. Further, when appropriately deployed, has the potential to offer a new paradigm in air quality quantification and monitoring.

Prototyping and Testing a Wireless Sensor Network to Retrieve SWE at High Spatial Resolution

NASA Astrophysics Data System (ADS)

Kang, D.; Barros, A. P.

2007-12-01

A critical challenge in snow research from space is the ability to obtain measurements at the spatial and temporal resolution to characterize the statistical structure of the space-time variability of the physical properties of the snowpack within an area consistent with the pixel resolution in snow hydrology models or that expected from a future NASA mission dedicated to cold region processes. That is, observations of relevant snow dielectric properties are necessary at high spatial and temporal resolution during the accumulation and melt seasons. We present a new wireless sensor network prototype consisting of multiple antennas and buried low-power, multi- channel transmitters operating in L-band that communicate to a central pod equipped with a Vector Signal Analyzer (VSA) that receives, processes and manages the data. Only commercial off-the-shelf hard-ware parts were used to build the sensors. Because the sensors are very low cost and run autonomously, one envisions that self-organizing networks of large numbers of such sensors might be distributed over very large areas, therefore proving much needed data sets for scaling studies. The measurement strategy consists of placing the transmitters the land surface in the beginning of the snow season which are then run autonomously till the end of the spring and waken at pre-determined time-intervals to emit radio frequency signals and thus sample the snowpack. Along with the sensors, an important component of this work entails the development of an estimation algorithm to estimate snow dielectric properties, snow density, and volume fraction of snow (VF) from the time-of-travel, amplitude and phase modification of the multi-channel RF signals as they propagate through the snow-pack. Here, we present results from full system testing and evaluation of the sensors that were conducted at Duke University using ¢®¡Æsynthetic¢®¡¾ limited-area snowpacks (0.5 by 0.5 m2 and 1 by 2 m2) constructed of various combinations of foam layers of different porosities to simulate heterogeneous distributions of water. The existing sensors are currently being primed for field deployment. Discussion is also presented regarding further technology development including power usage, networking, and distribution and operations in remote regions.

Comparison of fractal dimensions based on segmented NDVI fields obtained from different remote sensors.

NASA Astrophysics Data System (ADS)

Alonso, C.; Benito, R. M.; Tarquis, A. M.

2012-04-01

Satellite image data have become an important source of information for monitoring vegetation and mapping land cover at several scales. Beside this, the distribution and phenology of vegetation is largely associated with climate, terrain characteristics and human activity. Various vegetation indices have been developed for qualitative and quantitative assessment of vegetation using remote spectral measurements. In particular, sensors with spectral bands in the red (RED) and near-infrared (NIR) lend themselves well to vegetation monitoring and based on them [(NIR - RED) / (NIR + RED)] Normalized Difference Vegetation Index (NDVI) has been widespread used. Given that the characteristics of spectral bands in RED and NIR vary distinctly from sensor to sensor, NDVI values based on data from different instruments will not be directly comparable. The spatial resolution also varies significantly between sensors, as well as within a given scene in the case of wide-angle and oblique sensors. As a result, NDVI values will vary according to combinations of the heterogeneity and scale of terrestrial surfaces and pixel footprint sizes. Therefore, the question arises as to the impact of differences in spectral and spatial resolutions on vegetation indices like the NDVI. The aim of this study is to establish a comparison between two different sensors in their NDVI values at different spatial resolutions. Scaling analysis and modeling techniques are increasingly understood to be the result of nonlinear dynamic mechanisms repeating scale after scale from large to small scales leading to non-classical resolution dependencies. In the remote sensing framework the main characteristic of sensors images is the high local variability in their values. This variability is a consequence of the increase in spatial and radiometric resolution that implies an increase in complexity that it is necessary to characterize. Fractal and multifractal techniques has been proven to be useful to extract such complexities from remote sensing images and will applied in this study to see the scaling behavior for each sensor in generalized fractal dimensions. The studied area is located in the provinces of Caceres and Salamanca (east of Iberia Peninsula) with an extension of 32 x 32 km2. The altitude in the area varies from 1,560 to 320 m, comprising natural vegetation in the mountain area (forest and bushes) and agricultural crops in the valleys. Scaling analysis were applied to Landsat-5 and MODIS TERRA to the normalized derived vegetation index (NDVI) on the same region with one day of difference, 13 and 12 of July 2003 respectively. From these images the area of interest was selected obtaining 1024 x 1024 pixels for Landsat image and 128 x 128 pixels for MODIS image. This implies that the resolution for MODIS is 250x250 m. and for Landsat is 30x30 m. From the reflectance data obtained from NIR and RED bands, NDVI was calculated for each image focusing this study on 0.2 to 0.5 ranges of values. Once that both NDVI fields were obtained several fractal dimensions were estimated in each one segmenting the values in 0.20-0.25, 0.25-0.30 and so on to rich 0.45-0.50. In all the scaling analysis the scale size length was expressed in meters, and not in pixels, to make the comparison between both sensors possible. Results are discussed. Acknowledgements This work has been supported by the Spanish MEC under Projects No. AGL2010-21501/AGR, MTM2009-14621 and i-MATH No. CSD2006-00032

Real-time and quantitative isotropic spatial resolution susceptibility imaging for magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Pi, Shiqiang; Liu, Wenzhong; Jiang, Tao

2018-03-01

The magnetic transparency of biological tissue allows the magnetic nanoparticle (MNP) to be a promising functional sensor and contrast agent. The complex susceptibility of MNPs, strongly influenced by particle concentration, excitation magnetic field and their surrounding microenvironment, provides significant implications for biomedical applications. Therefore, magnetic susceptibility imaging of high spatial resolution will give more detailed information during the process of MNP-aided diagnosis and therapy. In this study, we present a novel spatial magnetic susceptibility extraction method for MNPs under a gradient magnetic field, a low-frequency drive magnetic field, and a weak strength high-frequency magnetic field. Based on this novel method, a magnetic particle susceptibility imaging (MPSI) of millimeter-level spatial resolution (<3 mm) was achieved using our homemade imaging system. Corroborated by the experimental results, the MPSI shows real-time (1 s per frame acquisition) and quantitative abilities, and isotropic high resolution.

Fiber-connected position localization sensor networks

NASA Astrophysics Data System (ADS)

Pan, Shilong; Zhu, Dan; Fu, Jianbin; Yao, Tingfeng

2014-11-01

Position localization has drawn great attention due to its wide applications in radars, sonars, electronic warfare, wireless communications and so on. Photonic approaches to realize position localization can achieve high-resolution, which also provides the possibility to move the signal processing from each sensor node to the central station, thanks to the low loss, immunity to electromagnetic interference (EMI) and broad bandwidth brought by the photonic technologies. In this paper, we present a review on the recent works of position localization based on photonic technologies. A fiber-connected ultra-wideband (UWB) sensor network using optical time-division multiplexing (OTDM) is proposed to realize high-resolution localization and moving the signal processing to the central station. A 3.9-cm high spatial resolution is achieved. A wavelength-division multiplexed (WDM) fiber-connected sensor network is also demonstrated to realize location which is independent of the received signal format.

Gyrocopter-Based Remote Sensing Platform

NASA Astrophysics Data System (ADS)

Weber, I.; Jenal, A.; Kneer, C.; Bongartz, J.

2015-04-01

In this paper the development of a lightweight and highly modularized airborne sensor platform for remote sensing applications utilizing a gyrocopter as a carrier platform is described. The current sensor configuration consists of a high resolution DSLR camera for VIS-RGB recordings. As a second sensor modality, a snapshot hyperspectral camera was integrated in the aircraft. Moreover a custom-developed thermal imaging system composed of a VIS-PAN camera and a LWIR-camera is used for aerial recordings in the thermal infrared range. Furthermore another custom-developed highly flexible imaging system for high resolution multispectral image acquisition with up to six spectral bands in the VIS-NIR range is presented. The performance of the overall system was tested during several flights with all sensor modalities and the precalculated demands with respect to spatial resolution and reliability were validated. The collected data sets were georeferenced, georectified, orthorectified and then stitched to mosaics.

Detection and mapping the spatial distribution of bracken fern weeds using the Landsat 8 OLI new generation sensor

NASA Astrophysics Data System (ADS)

Matongera, Trylee Nyasha; Mutanga, Onisimo; Dube, Timothy; Sibanda, Mbulisi

2017-05-01

Bracken fern is an invasive plant that presents serious environmental, ecological and economic problems around the world. An understanding of the spatial distribution of bracken fern weeds is therefore essential for providing appropriate management strategies at both local and regional scales. The aim of this study was to assess the utility of the freely available medium resolution Landsat 8 OLI sensor in the detection and mapping of bracken fern at the Cathedral Peak, South Africa. To achieve this objective, the results obtained from Landsat 8 OLI were compared with those derived using the costly, high spatial resolution WorldView-2 imagery. Since previous studies have already successfully mapped bracken fern using high spatial resolution WorldView-2 image, the comparison was done to investigate the magnitude of difference in accuracy between the two sensors in relation to their acquisition costs. To evaluate the performance of Landsat 8 OLI in discriminating bracken fern compared to that of Worldview-2, we tested the utility of (i) spectral bands; (ii) derived vegetation indices as well as (iii) the combination of spectral bands and vegetation indices based on discriminant analysis classification algorithm. After resampling the training and testing data and reclassifying several times (n = 100) based on the combined data sets, the overall accuracies for both Landsat 8 and WorldView-2 were tested for significant differences based on Mann-Whitney U test. The results showed that the integration of the spectral bands and derived vegetation indices yielded the best overall classification accuracy (80.08% and 87.80% for Landsat 8 OLI and WorldView-2 respectively). Additionally, the use of derived vegetation indices as a standalone data set produced the weakest overall accuracy results of 62.14% and 82.11% for both the Landsat 8 OLI and WorldView-2 images. There were significant differences {U (100) = 569.5, z = -10.8242, p < 0.01} between the classification accuracies derived based on Landsat OLI 8 and those derived using WorldView-2 sensor. Although there were significant differences between Landsat and WorldView-2 accuracies, the magnitude of variation (9%) between the two sensors was within an acceptable range. Therefore, the findings of this study demonstrated that the recently launched Landsat 8 OLI multispectral sensor provides valuable information that could aid in the long term continuous monitoring and formulation of effective bracken fern management with acceptable accuracies that are comparable to those obtained from the high resolution WorldView-2 commercial sensor.

Satellite image fusion based on principal component analysis and high-pass filtering.

PubMed

Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E

2010-06-01

This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.

Single-shot and single-sensor high/super-resolution microwave imaging based on metasurface

PubMed Central

Wang, Libo; Li, Lianlin; Li, Yunbo; Zhang, Hao Chi; Cui, Tie Jun

2016-01-01

Real-time high-resolution (including super-resolution) imaging with low-cost hardware is a long sought-after goal in various imaging applications. Here, we propose broadband single-shot and single-sensor high-/super-resolution imaging by using a spatio-temporal dispersive metasurface and an imaging reconstruction algorithm. The metasurface with spatio-temporal dispersive property ensures the feasibility of the single-shot and single-sensor imager for super- and high-resolution imaging, since it can convert efficiently the detailed spatial information of the probed object into one-dimensional time- or frequency-dependent signal acquired by a single sensor fixed in the far-field region. The imaging quality can be improved by applying a feature-enhanced reconstruction algorithm in post-processing, and the desired imaging resolution is related to the distance between the object and metasurface. When the object is placed in the vicinity of the metasurface, the super-resolution imaging can be realized. The proposed imaging methodology provides a unique means to perform real-time data acquisition, high-/super-resolution images without employing expensive hardware (e.g. mechanical scanner, antenna array, etc.). We expect that this methodology could make potential breakthroughs in the areas of microwave, terahertz, optical, and even ultrasound imaging. PMID:27246668

Ground-based radiometric calibration of the Landsat 8 Operational Land Imager (OLI) using in situ techniques

NASA Astrophysics Data System (ADS)

Czapla-Myers, J.

2013-12-01

Landsat 8 was successfully launched from Vandenberg Air Force Base in California on 11 February 2013, and was placed into the orbit previously occupied by Landsat 5. Landsat 8 is the latest platform in the 40-year history of the Landsat series of satellites, and it contains two instruments that operate in the solar-reflective and the thermal infrared regimes. The Operational Land Imager (OLI) is a pushbroom sensor that contains eight multispectral bands ranging from 400-2300 nm, and one panchromatic band. The spatial resolution of the multispectral bands is 30 m, which is similar to previous Landsat sensors, and the panchromatic band has a 15-m spatial resolution, which is also similar to previous Landsat sensors. The 12-bit radiometric resolution of OLI improves upon the 8-bit resolution of the Enhanced Thematic Mapper Plus (ETM+) onboard Landsat 7. An important requirement for the Landsat program is the long-term radiometric continuity of its sensors. Ground-based vicarious techniques have been used for over 20 years to determine the absolute radiometric calibration of sensors that encompass a wide variety of spectral and spatial characteristics. This work presents the early radiometric calibration results of Landsat 8 OLI that were obtained using the traditional reflectance-based approach. University of Arizona personnel used five sites in Arizona, California, and Nevada to collect ground-based data. In addition, a unique set of in situ data were collected in March 2013, when Landsat 7 and Landsat 8 were observing the same site within minutes of each other. The tandem overfly schedule occurred while Landsat 8 was shifting to the WRS-2 orbital grid, and lasted only a few days. The ground-based data also include results obtained using the University of Arizona's Radiometric Calibration Test Site (RadCaTS), which is an automated suite of instruments located at Railroad Valley, Nevada. The results presented in this work include a comparison to the L1T at-sensor spectral radiance and the top-of-atmosphere reflectance, both of which are standard products available from the US Geological Survey.

A Framework for Mapping Global Evapotranspiration using 375-m VIIRS LST

NASA Astrophysics Data System (ADS)

Hain, C.; Anderson, M. C.; Schull, M. A.; Neale, C. M. U.

2017-12-01

As the world's water resources come under increasing tension due to dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. Remote sensing methods for monitoring consumptive water use are becoming increasingly important, especially in areas of food insecurity. One method to estimate ET from satellite-based methods, the Atmosphere Land Exchange Inverse (ALEXI) model uses the change in morning land surface temperature to estimate the partitioning of sensible/latent heat fluxes which are then used to estimate daily ET. This presentation will outline several recent enhancements to the ALEXI modeling system, with a focus on global ET and drought monitoring. Until recently, ALEXI has been limited to areas with high resolution temporal sampling of geostationary sensors. The use of geostationary sensors makes global mapping a complicated process, especially for real-time applications, as data from as many as five different sensors are required to be ingested and harmonized to create a global mosaic. However, our research team has developed a new and novel method of using twice-daily observations from polar-orbiting sensors such as MODIS and VIIRS to estimate the mid-morning rise in LST that is used to drive the energy balance estimations within ALEXI. This allows the method to be applied globally using a single sensor rather than a global compositing of all available geostationary data. Other advantages of this new method include the higher spatial resolution provided by MODIS and VIIRS and the increased sampling at high latitudes where oblique view angles limit the utility of geostationary sensors. Improvements to the spatial resolution of the thermal infrared wavelengths on the VIIRS instrument, as compared to MODIS (375-m VIIRS vs. 1-km MODIS), allows for a much higher resolution ALEXI product than has been previously available. Therefore, recent developments have been to generate 375-m ALEXI ET products over several pilot regions (e.g. western US and the MENA region). The monitoring of consumptive water use over regions where significant groundwater pumping for irrigation is employed is important to accurately quantify the efficiency of water use in the region.

Multi-Image Registration for an Enhanced Vision System

NASA Technical Reports Server (NTRS)

Hines, Glenn; Rahman, Zia-Ur; Jobson, Daniel; Woodell, Glenn

2002-01-01

An Enhanced Vision System (EVS) utilizing multi-sensor image fusion is currently under development at the NASA Langley Research Center. The EVS will provide enhanced images of the flight environment to assist pilots in poor visibility conditions. Multi-spectral images obtained from a short wave infrared (SWIR), a long wave infrared (LWIR), and a color visible band CCD camera, are enhanced and fused using the Retinex algorithm. The images from the different sensors do not have a uniform data structure: the three sensors not only operate at different wavelengths, but they also have different spatial resolutions, optical fields of view (FOV), and bore-sighting inaccuracies. Thus, in order to perform image fusion, the images must first be co-registered. Image registration is the task of aligning images taken at different times, from different sensors, or from different viewpoints, so that all corresponding points in the images match. In this paper, we present two methods for registering multiple multi-spectral images. The first method performs registration using sensor specifications to match the FOVs and resolutions directly through image resampling. In the second method, registration is obtained through geometric correction based on a spatial transformation defined by user selected control points and regression analysis.

Using object-oriented classification and high-resolution imagery to map fuel types in a Mediterranean region.

Treesearch

L. Arroyo; S.P. Healey; W.B. Cohen; D. Cocero; J.A. Manzanera

2006-01-01

Knowledge of fuel load and composition is critical in fighting, preventing, and understanding wildfires. Commonly, the generation of fuel maps from remotely sensed imagery has made use of medium-resolution sensors such as Landsat. This paper presents a methodology to generate fuel type maps from high spatial resolution satellite data through object-oriented...

Automated Verification of Spatial Resolution in Remotely Sensed Imagery

NASA Technical Reports Server (NTRS)

Davis, Bruce; Ryan, Robert; Holekamp, Kara; Vaughn, Ronald

2011-01-01

Image spatial resolution characteristics can vary widely among sources. In the case of aerial-based imaging systems, the image spatial resolution characteristics can even vary between acquisitions. In these systems, aircraft altitude, speed, and sensor look angle all affect image spatial resolution. Image spatial resolution needs to be verified with estimators that include the ground sample distance (GSD), the modulation transfer function (MTF), and the relative edge response (RER), all of which are key components of image quality, along with signal-to-noise ratio (SNR) and dynamic range. Knowledge of spatial resolution parameters is important to determine if features of interest are distinguishable in imagery or associated products, and to develop image restoration algorithms. An automated Spatial Resolution Verification Tool (SRVT) was developed to rapidly determine the spatial resolution characteristics of remotely sensed aerial and satellite imagery. Most current methods for assessing spatial resolution characteristics of imagery rely on pre-deployed engineered targets and are performed only at selected times within preselected scenes. The SRVT addresses these insufficiencies by finding uniform, high-contrast edges from urban scenes and then using these edges to determine standard estimators of spatial resolution, such as the MTF and the RER. The SRVT was developed using the MATLAB programming language and environment. This automated software algorithm assesses every image in an acquired data set, using edges found within each image, and in many cases eliminating the need for dedicated edge targets. The SRVT automatically identifies high-contrast, uniform edges and calculates the MTF and RER of each image, and when possible, within sections of an image, so that the variation of spatial resolution characteristics across the image can be analyzed. The automated algorithm is capable of quickly verifying the spatial resolution quality of all images within a data set, enabling the appropriate use of those images in a number of applications.

The spatial resolving power of earth resources satellites: A review

NASA Technical Reports Server (NTRS)

Townshend, J. R. G.

1980-01-01

The significance of spatial resolving power on the utility of current and future Earth resources satellites is critically discussed and the relative merits of different approaches in defining and estimating spatial resolution are outlined. It is shown that choice of a particular measure of spatial resolution depends strongly on the particular needs of the user. Several experiments have simulated the capabilities of future satellite systems by degradation of aircraft images. Surprisingly, many of these indicated that improvements in resolution may lead to a reduction in the classification accuracy of land cover types using computer assisted methods. However, where the frequency of boundary pixels is high, the converse relationship is found. Use of imagery dependent upon visual interpretation is likely to benefit more consistently from higher resolutions. Extraction of information from images will depend upon several other factors apart from spatial resolving power: these include characteristics of the terrain being sensed, the image processing methods that are applied as well as certain sensor characteristics.

Combined Landsat-8 and Sentinel-2 Burned Area Mapping

NASA Astrophysics Data System (ADS)

Huang, H.; Roy, D. P.; Zhang, H.; Boschetti, L.; Yan, L.; Li, Z.

2017-12-01

Fire products derived from coarse spatial resolution satellite data have become an important source of information for the multiple user communities involved in fire science and applications. The advent of the MODIS on NASA's Terra and Aqua satellites enabled systematic production of 500m global burned area maps. There is, however, an unequivocal demand for systematically generated higher spatial resolution burned area products, in particular to examine the role of small-fires for various applications. Moderate spatial resolution contemporaneous satellite data from Landsat-8 and the Sentinel-2A and -2B sensors provide the opportunity for detailed spatial mapping of burned areas. Combined, these polar-orbiting systems provide 10m to 30m multi-spectral global coverage more than once every three days. This NASA funded research presents results to prototype a combined Landsat-8 Sentinel-2 burned area product. The Landsat-8 and Sentinel-2 pre-processing, the time-series burned area mapping algorithm, and preliminary results and validation using high spatial resolution commercial satellite data over Africa are presented.

An Optical Wavefront Sensor Based on a Double Layer Microlens Array

PubMed Central

Lin, Vinna; Wei, Hsiang-Chun; Hsieh, Hsin-Ta; Su, Guo-Dung John

2011-01-01

In order to determine light aberrations, Shack-Hartmann optical wavefront sensors make use of microlens arrays (MLA) to divide the incident light into small parts and focus them onto image planes. In this paper, we present the design and fabrication of long focal length MLA with various shapes and arrangements based on a double layer structure for optical wavefront sensing applications. A longer focal length MLA could provide high sensitivity in determining the average slope across each microlens under a given wavefront, and spatial resolution of a wavefront sensor is increased by numbers of microlenses across a detector. In order to extend focal length, we used polydimethysiloxane (PDMS) above MLA on a glass substrate. Because of small refractive index difference between PDMS and MLA interface (UV-resin), the incident light is less refracted and focused in further distance. Other specific focal lengths could also be realized by modifying the refractive index difference without changing the MLA size. Thus, the wavefront sensor could be improved with better sensitivity and higher spatial resolution. PMID:22346643

Active and Passive Sensing from Geosynchronous and Libration Orbits

NASA Technical Reports Server (NTRS)

Schoeberl, Mark; Raymond, Carol; Hildebrand, Peter

2003-01-01

The development of the LEO (EOS) missions has led the way to new technologies and new science discoveries. However, LEO measurements alone cannot cost effectively produce high time resolution measurements needed to move the science to the next level. Both GEO and the Lagrange points, L1 and L2, provide vantage points that will allow higher time resolution measurements. GEO is currently being exploited by weather satellites, but the sensors currently operating at GEO do not provide the spatial or spectral resolution needed for atmospheric trace gas, ocean or land surface measurements. It is also may be possible to place active sensors in geostationary orbit. It seems clear, that the next era in earth observation and discovery will be opened by sensor systems operating beyond near earth orbit.

A forestry GIS-based study on evaluating the potential of imaging spectroscopy in mapping forest land fertility

NASA Astrophysics Data System (ADS)

Mõttus, Matti; Takala, Tuure

2014-12-01

Fertility, or the availability of nutrients and water, controls forest productivity. It affects its carbon sequestration, and thus the forest's effect on climate, as well as its commercial value. Although the availability of nutrients cannot be measured directly using remote sensing methods, fertility alters several vegetation traits detectable from the reflectance spectra of the forest stand, including its pigment content and water stress. However, forest reflectance is also influenced by other factors, such as species composition and stand age. Here, we present a case study demonstrating how data obtained using imaging spectroscopy is correlated with site fertility. The study was carried out in Hyytiälä, Finland, in the southern boreal forest zone. We used a database of state-owned forest stands including basic forestry variables and a site fertility index. To test the suitability of imaging spectroscopy with different spatial and spectral resolutions for site fertility mapping, we performed two airborne acquisitions using different sensor configurations. First, the sensor was flown at a high altitude with high spectral resolution resulting in a pixel size in the order of a tree crown. Next, the same area was flown to provide reflectance data with sub-meter spatial resolution. However, to maintain usable signal-to-noise ratios, several spectral channels inside the sensor were combined, thus reducing spectral resolution. We correlated a number of narrowband vegetation indices (describing canopy biochemical composition, structure, and photosynthetic activity) on site fertility. Overall, site fertility had a significant influence on the vegetation indices but the strength of the correlation depended on dominant species. We found that high spatial resolution data calculated from the spectra of sunlit parts of tree crowns had the strongest correlation with site fertility.

Characterizing Intra-Urban Air Quality Gradients with a Spatially-Distributed Network

NASA Astrophysics Data System (ADS)

Zimmerman, N.; Ellis, A.; Schurman, M. I.; Gu, P.; Li, H.; Snell, L.; Gu, J.; Subramanian, R.; Robinson, A. L.; Apte, J.; Presto, A. A.

2016-12-01

City-wide air pollution measurements have typically relied on regulatory or research monitoring sites with low spatial density to assess population-scale exposure. However, air pollutant concentrations exhibit significant spatial variability depending on local sources and features of the built environment, which may not be well captured by the existing monitoring regime. To better understand urban spatial and temporal pollution gradients at 1 km resolution, a network of 12 real-time air quality monitoring stations was deployed beginning July 2016 in Pittsburgh, PA. The stations were deployed at sites along an urban-rural transect and in urban locations with a range of traffic, restaurant, and tall building densities to examine the impact of various modifiable factors. Measurements from the stationary monitoring stations were further supported by mobile monitoring, which provided higher spatial resolution pollutant measurements on nearby roadways and enabled routine calibration checks. The stationary monitoring measurements comprise ultrafine particle number (Aerosol Dynamics "MAGIC" CPC), PM2.5 (Met One Neighborhood PM Monitor), black carbon (Met One BC 1050), and a new low-cost air quality monitor, the Real-time Affordable Multi-Pollutant (RAMP) sensor package for measuring CO, NO2, SO2, O3, CO2, temperature and relative humidity. High time-resolution (sub-minute) measurements across the distributed monitoring network enable insight into dynamic pollutant behaviour. Our preliminary findings show that our instruments are sensitive to PM2.5 gradients exceeding 2 micro-grams per cubic meter and ultrafine particle gradients exceeding 1000 particles per cubic centimeter. Additionally, we have developed rigorous calibration protocols to characterize the RAMP sensor response and drift, as well as multiple linear regression models to convert sensor response into pollutant concentrations that are comparable to reference instrumentation.

Pairwise graphical models for structural health monitoring with dense sensor arrays

NASA Astrophysics Data System (ADS)

Mohammadi Ghazi, Reza; Chen, Justin G.; Büyüköztürk, Oral

2017-09-01

Through advances in sensor technology and development of camera-based measurement techniques, it has become affordable to obtain high spatial resolution data from structures. Although measured datasets become more informative by increasing the number of sensors, the spatial dependencies between sensor data are increased at the same time. Therefore, appropriate data analysis techniques are needed to handle the inference problem in presence of these dependencies. In this paper, we propose a novel approach that uses graphical models (GM) for considering the spatial dependencies between sensor measurements in dense sensor networks or arrays to improve damage localization accuracy in structural health monitoring (SHM) application. Because there are always unobserved damaged states in this application, the available information is insufficient for learning the GMs. To overcome this challenge, we propose an approximated model that uses the mutual information between sensor measurements to learn the GMs. The study is backed by experimental validation of the method on two test structures. The first is a three-story two-bay steel model structure that is instrumented by MEMS accelerometers. The second experimental setup consists of a plate structure and a video camera to measure the displacement field of the plate. Our results show that considering the spatial dependencies by the proposed algorithm can significantly improve damage localization accuracy.

Downscaling of land surface temperatures from SEVIRI

NASA Astrophysics Data System (ADS)

Bechtel, B.; Zaksek, K.

2013-12-01

Land surface temperature (LST) determines the radiance emitted by the surface and hence is an important boundary condition of the energy balance. In urban areas, detailed knowledge about the diurnal cycle in LST can contribute to understand the urban heat island (UHI). Although the increased surface temperatures compared to the surrounding rural areas (surface urban heat island, SUHI) have been measured by satellites and analysed for several decades, an operational SUHI monitoring is still not available due to the lack of sensors with appropriate spatiotemporal resolution. While sensors on polar orbiting satellites are still restricted to approx. 100 m spatial resolution and coarse temporal coverage (about 1-2 weeks), sensors on geostationary platforms have high temporal (several times per hour) and poor spatial resolution (>3 km). Further, all polar orbiting satellites have a similar equator crossing time and hence the SUHI can at best be observed at two times a day. A downscaling DS scheme for LST from the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) sensor onboard the geostationary meteorological Meteosat 8 to spatial resolutions between 100 and 1000 m was developed and tested for Hamburg. Various data were tested as predictors, including multispectral data and derived indices, morphological parameters from interferometric SAR and multitemporal thermal data. All predictors were upscaled to the coarse resolution approximating the point spread function of SEVIRI. Then empirical relationships between the predictors and LST were derived which are then transferred to the high resolution domain, assuming they are scale invariant. For validation LST data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Enhanced Thematic Mapper Plus (ETM+) for two dates were used. Aggregated parameters from multi-temporal thermal data (in particular annual cycle parameters and principal components) proved particularly suitable. The results for the highest resolution of 100 m showed a high explained variance (R^2 = 0.71) and relatively low root mean square errors (RMSE = 2.2 K) for the ASTER scene and slightly higher errors (R^2 = 0.73, RMSE = 2.53) for the ETM+ scene. A considerable percentage of the error was systematic due to the different viewing geometry of the sensors (the high resolution LST was overestimated about 1.3 K for ASTER and 0.66 K for ETM+). This shows that DS of SEVIRI LST is possible up to a resolution of 100 m for urban areas and that multitemporal thermal data are particularly suitable as predictors. Further, the scheme was used to produce an entire diurnal cycle in high resolution. While essential characteristics of the diurnal cycle were well reproduced, certain artefacts resulting from the multitemporal predictors from different seasons (like phenology and different water surface temperatures) were generated. Eventually, the bias and its dependence on the viewing geometry and topography are currently investigated.

Low-cost Photoacoustic-based Measurement System for Carbon Dioxide Fluxes with the Potential for large-scale Monitoring

NASA Astrophysics Data System (ADS)

Scholz, L. T.; Bierer, B.; Ortiz Perez, A.; Woellenstein, J.; Sachs, T.; Palzer, S.

2016-12-01

The determination of carbon dioxide (CO2) fluxes between ecosystems and the atmosphere is crucial for understanding ecological processes on regional and global scales. High quality data sets with full uncertainty estimates are needed to evaluate model simulations. However, current flux monitoring techniques are unsuitable to provide reliable data of a large area at both a detailed level and an appropriate resolution, at best in combination with a high sampling rate. Currently used sensing technologies, such as non-dispersive infrared (NDIR) gas analyzers, cannot be deployed in large numbers to provide high spatial resolution due to their costs and complex maintenance requirements. Here, we propose a novel CO2 measurement system, whose gas sensing unit is made up of low-cost, low-power consuming components only, such as an IR-LED and a photoacoustic detector. The sensor offers a resolution of < 50 ppm in the interesting concentration range up to 5000 ppm and an almost linear and fast sensor response of just a few seconds. Since the sensor can be applied in-situ without special precautions, it allows for environmental monitoring in a non-invasive way. Its low energy consumption enables long-term measurements. The low overall costs favor the manufacturing in large quantities. This allows the operation of multiple sensors at a reasonable price and thus provides concentration measurements at any desired spatial coverage and at high temporal resolution. With appropriate 3D configuration of the units, vertical and horizontal fluxes can be determined. By applying a closely meshed wireless sensor network, inhomogeneities as well as CO2 sources and sinks in the lower atmosphere can be monitored. In combination with sensors for temperature, pressure and humidity, our sensor paves the way towards the reliable and extensive monitoring of ecosystem-atmosphere exchange rates. The technique can also be easily adapted to other relevant greenhouse gases.

Derivation of high spatial resolution albedo from UAV digital imagery: application over the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Ryan, Jonathan C.; Hubbard, Alun; Box, Jason E.; Brough, Stephen; Cameron, Karen; Cook, Joseph M.; Cooper, Matthew; Doyle, Samuel H.; Edwards, Arwyn; Holt, Tom; Irvine-Fynn, Tristram; Jones, Christine; Pitcher, Lincoln H.; Rennermalm, Asa K.; Smith, Laurence C.; Stibal, Marek; Snooke, Neal

2017-05-01

Measurements of albedo are a prerequisite for modelling surface melt across the Earth's cryosphere, yet available satellite products are limited in spatial and/or temporal resolution. Here, we present a practical methodology to obtain centimetre resolution albedo products with accuracies of 5% using consumer-grade digital camera and unmanned aerial vehicle (UAV) technologies. Our method comprises a workflow for processing, correcting and calibrating raw digital images using a white reference target, and upward and downward shortwave radiation measurements from broadband silicon pyranometers. We demonstrate the method with a set of UAV sorties over the western, K-sector of the Greenland Ice Sheet. The resulting albedo product, UAV10A1, covers 280 km2, at a resolution of 20 cm per pixel and has a root-mean-square difference of 3.7% compared to MOD10A1 and 4.9% compared to ground-based broadband pyranometer measurements. By continuously measuring downward solar irradiance, the technique overcomes previous limitations due to variable illumination conditions during and between surveys over glaciated terrain. The current miniaturization of multispectral sensors and incorporation of upward facing radiation sensors on UAV packages means that this technique will likely become increasingly attractive in field studies and used in a wide range of applications for high temporal and spatial resolution surface mapping of debris, dust, cryoconite and bioalbedo and for directly constraining surface energy balance models.

LANDSAT-4 Scientific Characterization: Early Results Symposium

NASA Technical Reports Server (NTRS)

1983-01-01

Radiometric calibration, geometric accuracy, spatial and spectral resolution, and image quality are examined for the thematic mapper and the multispectral band scanner on LANDSAT 4. Sensor performance is evaluated.

Performance of irradiated CVD diamond micro-strip sensors

NASA Astrophysics Data System (ADS)

Adam, W.; Berdermann, E.; Bergonzo, P.; Bertuccio, G.; Bogani, F.; Borchi, E.; Brambilla, A.; Bruzzi, M.; Colledani, C.; Conway, J.; D'Angelo, P.; Dabrowski, W.; Delpierre, P.; Deneuville, A.; Dulinski, W.; van Eijk, B.; Fallou, A.; Fizzotti, F.; Foulon, F.; Friedl, M.; Gan, K. K.; Gheeraert, E.; Hallewell, G.; Han, S.; Hartjes, F.; Hrubec, J.; Husson, D.; Kagan, H.; Kania, D.; Kaplon, J.; Kass, R.; Koeth, T.; Krammer, M.; Logiudice, A.; Lu, R.; mac Lynne, L.; Manfredotti, C.; Meier, D.; Mishina, M.; Moroni, L.; Noomen, J.; Oh, A.; Pan, L. S.; Pernicka, M.; Peitz, A.; Perera, L.; Pirollo, S.; Procario, M.; Riester, J. L.; Roe, S.; Rousseau, L.; Rudge, A.; Russ, J.; Sala, S.; Sampietro, M.; Schnetzer, S.; Sciortino, S.; Stelzer, H.; Stone, R.; Suter, B.; Tapper, R. J.; Tesarek, R.; Trischuk, W.; Tromson, D.; Vittone, E.; Walsh, A. M.; Wedenig, R.; Weilhammer, P.; Wetstein, M.; White, C.; Zeuner, W.; Zoeller, M.; Plano, R.; Somalwar, S. V.; Thomson, G. B.

2002-01-01

CVD diamond detectors are of interest for charged particle detection and tracking due to their high radiation tolerance. In this article, we present, for the first time, beam test results from recently manufactured CVD diamond strip detectors and their behavior under low doses of electrons from a β-source and the performance before and after intense (>10 15/cm 2) proton- and pion-irradiations. We find that low dose irradiation increase the signal-to-noise ratio (pumping of the signal) and slightly deteriorate the spatial resolution. Intense irradiation with protons 2.2×10 15 p/ cm2 lowers the signal-to-noise ratio slightly. Intense irradiation with pions 2.9×10 15 π/ cm2 lowers the signal-to-noise ratio more. The spatial resolution of the diamond sensors improves after irradiations.

Mid-infrared Shack-Hartmann wavefront sensor fully cryogenic using extended source for endoatmospheric applications.

PubMed

Robert, Clélia; Michau, Vincent; Fleury, Bruno; Magli, Serge; Vial, Laurent

2012-07-02

Adaptive optics provide real-time compensation for atmospheric turbulence. The correction quality relies on a key element: the wavefront sensor. We have designed an adaptive optics system in the mid-infrared range providing high spatial resolution for ground-to-air applications, integrating a Shack-Hartmann infrared wavefront sensor operating on an extended source. This paper describes and justifies the design of the infrared wavefront sensor, while defining and characterizing the Shack-Hartmann wavefront sensor camera. Performance and illustration of field tests are also reported.

Long-Term Quantitative Precipitation Estimates (QPE) at High Spatial and Temporal Resolution over CONUS: Bias-Adjustment of the Radar-Only National Mosaic and Multi-sensor QPE (NMQ/Q2) Precipitation Reanalysis (2001-2012)

NASA Astrophysics Data System (ADS)

Prat, Olivier; Nelson, Brian; Stevens, Scott; Seo, Dong-Jun; Kim, Beomgeun

2015-04-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is completed for the period covering from 2001 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Several in-situ datasets are available to assess the biases of the radar-only product and to adjust for those biases to provide a multi-sensor QPE. The rain gauge networks that are used such as the Global Historical Climatology Network-Daily (GHCN-D), the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), and the Climate Reference Network (CRN), have different spatial density and temporal resolution. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. The objective of this work is threefold. First, we investigate how the different in-situ networks can impact the precipitation estimates as a function of the spatial density, sensor type, and temporal resolution. Second, we assess conditional and un-conditional biases of the radar-only QPE for various time scales (daily, hourly, 5-min) using in-situ precipitation observations. Finally, after assessing the bias and applying reduction or elimination techniques, we are using a unique in-situ dataset merging the different RG networks (CRN, ASOS, HADS, GHCN-D) to adjust the radar-only QPE product via an Inverse Distance Weighting (IDW) approach. In addition, we also investigate alternate adjustment techniques such as the kriging method and its variants (Simple Kriging: SK; Ordinary Kriging: OK; Conditional Bias-Penalized Kriging: CBPK). From this approach, we also hope to generate estimates of uncertainty for the gridded bias-adjusted QPE. Further comparison with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) and satellite products (TMPA, CMORPH, PERSIANN) is also provided in order to give a detailed picture of the improvements and remaining challenges.

High Data Rate Satellite Communications for Environmental Remote Sensing

NASA Astrophysics Data System (ADS)

Jackson, J. M.; Munger, J.; Emch, P. G.; Sen, B.; Gu, D.

2014-12-01

Satellite to ground communication bandwidth limitations place constraints on current earth remote sensing instruments which limit the spatial and spectral resolution of data transmitted to the ground for processing. Instruments such as VIIRS, CrIS and OMPS on the Soumi-NPP spacecraft must aggregate data both spatially and spectrally in order to fit inside current data rate constraints limiting the optimal use of the as-built sensors. Future planned missions such as HyspIRI, SLI, PACE, and NISAR will have to trade spatial and spectral resolution if increased communication band width is not made available. A number of high-impact, environmental remote sensing disciplines such as hurricane observation, mega-city air quality, wild fire detection and monitoring, and monitoring of coastal oceans would benefit dramatically from enabling the downlinking of sensor data at higher spatial and spectral resolutions. The enabling technologies of multi-Gbps Ka-Band communication, flexible high speed on-board processing, and multi-Terabit SSRs are currently available with high technological maturity enabling high data volume mission requirements to be met with minimal mission constraints while utilizing a limited set of ground sites from NASA's Near Earth Network (NEN) or TDRSS. These enabling technologies will be described in detail with emphasis on benefits to future remote sensing missions currently under consideration by government agencies.

Evaluation of ERTS-1 image sensor spatial resolution in photographic form

NASA Technical Reports Server (NTRS)

Slater, P. N. (Principal Investigator); Schowengerdt, R. A.

1973-01-01

The author has identified the following significant results. A coherent optical system was used to display the spatial frequency content of the amplitude image of one area of the ground as obtained in the four wavelength bands of the multispectral scanner. This enabled a rapid comparison to be made between the four bands, from which it was clear that bands 5 and 7 were preferred to the others in terms of image definition, and thus mapping and acreage estimation, for the particular agricultural area imaged. With suitable scaling it was also possible to compare the modulation, as a function of spatial frequency, of MSS bands 4 and 5 with the green (BB) and red (DD) bands of the same area from the Apollo 9, SO65 experiment. A significant result is that the modulation in the MSS amplitude imagery is 65%-90% of that in the Apollo 9 amplitude imagery. In addition, the ratio of spatial frequencies for the ERTS-1 and Apollo imagery, at which the same modulation occurs, lies between 0.55 and 0.75 for the red band. This ratio is closely related to the ratio of resolutions for the two sensors. These values corroborate statements that the resolution of the MSS imagery is better than anticipated by pre-flight predictions.

Towards breaking the spatial resolution barriers: An optical flow and super-resolution approach for sea ice motion estimation

NASA Astrophysics Data System (ADS)

Petrou, Zisis I.; Xian, Yang; Tian, YingLi

2018-04-01

Estimation of sea ice motion at fine scales is important for a number of regional and local level applications, including modeling of sea ice distribution, ocean-atmosphere and climate dynamics, as well as safe navigation and sea operations. In this study, we propose an optical flow and super-resolution approach to accurately estimate motion from remote sensing images at a higher spatial resolution than the original data. First, an external example learning-based super-resolution method is applied on the original images to generate higher resolution versions. Then, an optical flow approach is applied on the higher resolution images, identifying sparse correspondences and interpolating them to extract a dense motion vector field with continuous values and subpixel accuracies. Our proposed approach is successfully evaluated on passive microwave, optical, and Synthetic Aperture Radar data, proving appropriate for multi-sensor applications and different spatial resolutions. The approach estimates motion with similar or higher accuracy than the original data, while increasing the spatial resolution of up to eight times. In addition, the adopted optical flow component outperforms a state-of-the-art pattern matching method. Overall, the proposed approach results in accurate motion vectors with unprecedented spatial resolutions of up to 1.5 km for passive microwave data covering the entire Arctic and 20 m for radar data, and proves promising for numerous scientific and operational applications.

On the exploitation of optical and thermal band for river discharge estimation: synergy with radar altimetry

NASA Astrophysics Data System (ADS)

Tarpanelli, Angelica; Filippucci, Paolo; Brocca, Luca

2017-04-01

River discharge is recognized as a fundamental physical variable and it is included among the Essential Climate Variables by GCOS (Global Climate Observing System). Notwithstanding river discharge is one of the most measured components of the hydrological cycle, its monitoring is still an open issue. Collection, archiving and distribution of river discharge data globally is limited, and the currently operating network is inadequate in many parts of the Earth and is still declining. Remote sensing, especially satellite sensors, have great potential in offering new ways to monitor river discharge. Remote sensing guarantees regular, uniform and global measurements for long period thanks to the large number of satellites launched during the last twenty years. Because of its nature, river discharge cannot be measured directly and both satellite and traditional monitoring are referred to measurements of other hydraulic variables, e.g. water level, flow velocity, water extent and slope. In this study, we illustrate the potential of different satellite sensors for river discharge estimation. The recent advances in radar altimetry technology offered important information for water levels monitoring of rivers even if the spatio-temporal sampling is still a limitation. The multi-mission approach, i.e. interpolating different altimetry tracks, has potential to cope with the spatial and temporal resolution, but so far few studies were dedicated to deal with this issue. Alternatively, optical sensors, thanks to their frequent revisit time and large spatial coverage, could give a better support for the evaluation of river discharge variations. In this study, we focus on the optical (Near InfraRed) and thermal bands of different satellite sensors (MODIS, MERIS, AATSR, Landsat, Sentinel-2) and particularly, on the derived products such as reflectance, emissivity and land surface temperature. The performances are compared with respect to the well-known altimetry (Envisat/Ra-2, Jason-2/Poseidon-3 and Saral/Altika) for estimating the river discharge variation in Nigeria and Italy. For optical and thermal bands, results are more affected by the temporal resolution than the spatial resolution. Indeed, even if affected by cloud cover that limits the number of available images, thermal bands from MODIS (spatial resolution of 1 km) can be conveniently used for the estimation of the variation in the river discharge, whereas optical sensors as Landsat or Sentinel-2, characterized by 10 - 30 m of spatial resolution, fail in the estimation of extreme events, missing most of the peak values, because of the long revisit time ( 14-16 days). The best performances are obtained with the Near InfraRed bands from MODIS and MERIS that give similar results in river discharge estimation, even though with some underestimation of the flood peak values. Moreover, the multi-mission approach applied to radar altimetry data is found to be the most reliable tool to estimate river discharge in large rivers but its success is constrained both spatially (number of satellite tracks) and temporally (revisit time of the satellites). Therefore, it is expected that the multi-mission approach, merging also sensors of different characteristics (radar altimetry, and optical/thermal sensors), could improve the performances, if a consistent and comparable methodology is used for reducing the inter-satellite biases.

High temperature superconductor dc SQUID micro-susceptometer for room temperature objects

NASA Astrophysics Data System (ADS)

Faley, M. I.; Pratt, K.; Reineman, R.; Schurig, D.; Gott, S.; Atwood, C. G.; Sarwinski, R. E.; Paulson, D. N.; Starr, T. N.; Fagaly, R. L.

2004-05-01

We have developed a scanning magnetic microscope (SMM) with 25 µm resolution in spatial position for the magnetic features of room temperature objects. The microscope consists of a high-temperature superconductor (HTS) dc SQUID sensor, suspended in vacuum with a self-adjusting standoff, close spaced liquid nitrogen Dewar, X-Y scanning stage and a computer control system. The HTS SQUIDs were optimized for better spatial and field resolutions for operation at liquid nitrogen temperature. Measured inside a magnetic shield, the 10 pT Hz-1/2 typical noise of the SQUIDs is white down to frequencies of about 10 Hz, increasing up to about 20 pT Hz-1/2 at 1 Hz. The microscope is mounted on actively damped platforms, which negate vibrations from the environment as well as damping internal stepper motor noises. A high-resolution video telescope and a 1 µm precision z-axis positioning system allow a close positioning of the sample under the sensor. The ability of the sensors to operate in unshielded environmental conditions with magnetic fields up to about 15 G allowed us to perform 2D mapping of the local ac and dc susceptibility of the objects.

Micro Cantilever Movement Detection with an Amorphous Silicon Array of Position Sensitive Detectors

PubMed Central

Contreras, Javier; Costa, Daniel; Pereira, Sonia; Fortunato, Elvira; Martins, Rodrigo; Wierzbicki, Rafal; Heerlein, Holger; Ferreira, Isabel

2010-01-01

The movement of a micro cantilever was detected via a self constructed portable data acquisition prototype system which integrates a linear array of 32 1D amorphous silicon position sensitive detectors (PSD). The system was mounted on a microscope using a metal structure platform and the movement of the 30 μm wide by 400 μm long cantilever was tracked by analyzing the signals acquired by the 32 sensor array electronic readout system and the relevant data algorithm. The obtained results show a linear behavior of the photocurrent relating X and Y movement, with a non-linearity of about 3%, a spatial resolution of less than 2 μm along the lateral dimension of the sensor as well as of less than 3 μm along the perpendicular dimension of the sensor, when detecting just the micro-cantilever, and a spatial resolution of less than 1 μm when detecting the holding structure. PMID:22163648

Design of an integrated aerial image sensor

NASA Astrophysics Data System (ADS)

Xue, Jing; Spanos, Costas J.

2005-05-01

The subject of this paper is a novel integrated aerial image sensor (IAIS) system suitable for integration within the surface of an autonomous test wafer. The IAIS could be used as a lithography processing monitor, affording a "wafer's eye view" of the process, and therefore facilitating advanced process control and diagnostics without integrating (and dedicating) the sensor to the processing equipment. The IAIS is composed of an aperture mask and an array of photo-detectors. In order to retrieve nanometer scale resolution of the aerial image with a practical photo-detector pixel size, we propose a design of an aperture mask involving a series of spatial phase "moving" aperture groups. We demonstrate a design example aimed at the 65nm technology node through TEMPEST simulation. The optimized, key design parameters include an aperture width in the range of 30nm, aperture thickness in the range of 70nm, and offer a spatial resolution of about 5nm, all with comfortable fabrication tolerances. Our preliminary simulation work indicates the possibility of the IAIS being applied to the immersion lithography. A bench-top far-field experiment verifies that our approach of the spatial frequency down-shift through forming large Moire patterns is feasible.

Bridging the Past with Today's Microwave Remote Sensing: A Case Study of Long Term Inundation Patterns in Two River Deltas

NASA Astrophysics Data System (ADS)

McDonald, K. C.; Jensen, K.; Schroeder, R.; Tessler, Z. D.

2016-12-01

Surface inundation extent and its predictability vary tremendously across the globe. This dynamic is being and has been captured by three general categories of satellite imagery: a) low-spatial-resolution microwave sensors with global coverage and a long record of observations (e.g., SSM/I), b) optical sensors with high spatial and temporal resolution and global coverage as well, but with cloud contamination (e.g. MODIS), and also c) less frequently in ``snapshot'' form by high-resolution synthetic aperture radar (SAR) sensors. We explore the ability to bridge techniques that can exploit the higher spatial resolution of more recent data products back in time with the help of the temporal evolution of lower resolution products. We present a study of long term (20+ yrs) inundation patterns in two river deltas: (1) the Mekong, and (2) the Ganges-Brahmaputra. This research utilizes baseline observations from the Surface Water Microwave Product Series (SWAMPS), an inundation area fraction product derived at 25km scale from active and passive microwave instruments (ERS, QuikSCAT, ASCAT, and SSM/I) that spans from Jan 1992 to the present. Every hydrological basin has unique characteristics - such as its topography, land cover / land use, and spatio-temporal variability - thus, a downscaling algorithm needs to take into account these idiosyncrasies. We merge SWAMPS with topographical information derived from 30m SRTM DEM, river networks from USGS HydroSHEDS, and train a downscaling algorithm to learn from two sets of classified SAR data: (1) L-band imaging radar from ALOS PALSAR, 2007-2010, and (2) more recent C-band imagery from the Sentinel-1 mission (2014 to present). We present an accuracy assessment of retrospective downscaled flood extent with Landsat imagery and address potential sources of biases. With a higher spatial resolution of past flooding extent, we can improve our understanding of how delta surface hydrology has responded to climate events and human activities. This is important both in the short-term for accurate flood prediction, as well as on longer-term planning horizons.

Suomi NPP VIIRS Prelaunch and On-orbit Geometric Calibration and Characterization

NASA Technical Reports Server (NTRS)

Wolfe, Robert E.; Lin, Guoqing; Nishihama, Masahiro; Tewari, Krishna P.; Tilton, James C.; Isaacman, Alice R.

2013-01-01

The Visible Infrared Imager Radiometer Suite (VIIRS) sensor was launched 28 October 2011 on the Suomi National Polarorbiting Partnership (SNPP) satellite. VIIRS has 22 spectral bands covering the spectrum between 0.412 m and 12.01 m, including 16 moderate resolution bands (M-bands) with a spatial resolution of 750 m at nadir, 5 imaging resolution bands (I-bands) with a spatial resolution of 375 m at nadir, and 1 day-night band (DNB) with a near-constant 750 m spatial resolution throughout the scan. These bands are located in a visible and near infrared (VisNIR) focal plane assembly (FPA), a short- and mid-wave infrared (SWMWIR) FPA and a long-wave infrared (LWIR) FPA. All bands, except the DNB, are co-registered for proper environmental data records (EDRs) retrievals. Observations from VIIRS instrument provide long-term measurements of biogeophysical variables for climate research and polar satellite data stream for the operational communitys use in weather forecasting and disaster relief and other applications. Well Earth-located (geolocated) instrument data is important to retrieving accurate biogeophysical variables. This paper describes prelaunch pointing and alignment measurements, and the two sets of on-orbit correction of geolocation errors, the first of which corrected error from 1,300 m to within 75 m (20 I-band pixel size), and the second of which fine tuned scan angle dependent errors, bringing VIIRS geolocation products to high maturity in one and a half years of the SNPP VIIRS on-orbit operations. Prelaunch calibration and the on-orbit characterization of sensor spatial impulse responses and band-to-band co-registration (BBR) are also described.

Effects of instrument characteristics on cloud properties retrieved from satellite imagery data

NASA Technical Reports Server (NTRS)

Baldwin, D. G.; Coakley, J. A., Jr.; Zhang, M. S.

1986-01-01

The relationships between sensor resolution and derived cloud properties in satellite remote sensing were studied by comparisons of cloud characteristics determined by spatial coherence analysis of AVHRR and GOES data. The latter data were simulated from 11 microns AVHRR data and were assigned a resolution (8 sq km) half that of the AVHRR. Day and nighttime passes were considered for single-layer maritime cloud systems. Sample radiance vs local standard deviation plots of 1024 points are provided for the same area from AVHRR and GOES-East sensors, demonstrating a qualitative agreement.

Snapshot hyperspectral fovea vision system (HyperVideo)

NASA Astrophysics Data System (ADS)

Kriesel, Jason; Scriven, Gordon; Gat, Nahum; Nagaraj, Sheela; Willson, Paul; Swaminathan, V.

2012-06-01

The development and demonstration of a new snapshot hyperspectral sensor is described. The system is a significant extension of the four dimensional imaging spectrometer (4DIS) concept, which resolves all four dimensions of hyperspectral imaging data (2D spatial, spectral, and temporal) in real-time. The new sensor, dubbed "4×4DIS" uses a single fiber optic reformatter that feeds into four separate, miniature visible to near-infrared (VNIR) imaging spectrometers, providing significantly better spatial resolution than previous systems. Full data cubes are captured in each frame period without scanning, i.e., "HyperVideo". The current system operates up to 30 Hz (i.e., 30 cubes/s), has 300 spectral bands from 400 to 1100 nm (~2.4 nm resolution), and a spatial resolution of 44×40 pixels. An additional 1.4 Megapixel video camera provides scene context and effectively sharpens the spatial resolution of the hyperspectral data. Essentially, the 4×4DIS provides a 2D spatially resolved grid of 44×40 = 1760 separate spectral measurements every 33 ms, which is overlaid on the detailed spatial information provided by the context camera. The system can use a wide range of off-the-shelf lenses and can either be operated so that the fields of view match, or in a "spectral fovea" mode, in which the 4×4DIS system uses narrow field of view optics, and is cued by a wider field of view context camera. Unlike other hyperspectral snapshot schemes, which require intensive computations to deconvolve the data (e.g., Computed Tomographic Imaging Spectrometer), the 4×4DIS requires only a linear remapping, enabling real-time display and analysis. The system concept has a range of applications including biomedical imaging, missile defense, infrared counter measure (IRCM) threat characterization, and ground based remote sensing.

Nondestructive testing of advanced materials using sensors with metamaterials

NASA Astrophysics Data System (ADS)

Rozina, Steigmann; Narcis Andrei, Danila; Nicoleta, Iftimie; Catalin-Andrei, Tugui; Frantisek, Novy; Stanislava, Fintova; Petrica, Vizureanu; Adriana, Savin

2016-11-01

This work presents a method for nondestructive evaluation (NDE) of advanced materials that makes use of the images in near field and the concentration of flux using the phenomenon of spatial resolution. The method allows the detection of flaws as crack, nonadhesion of coating, degradation or presence delamination stresses correlated with the response of electromagnetic sensor.

Evaluation of MODIS NPP and GPP products across multiple biomes.

Treesearch

David P. Turner; William D. Ritts; Warren B. Cohen; Stith T. Gower; Steve W. Running; Maosheng Zhao; Marcos H. Costa; Al A. Kirschbaum; Jay M. Ham; Scott R. Saleska; Douglas E. Ahl

2006-01-01

Estimates of daily gross primary production (GPP) and annual net primary production (NPP) at the 1 km spatial resolution are now produced operationally for the global terrestrial surface using imagery from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. Ecosystem-level measurements of GPP at eddy covariance flux towers and plot-level measurements of...

High spatial resolution LWIR hyperspectral sensor

NASA Astrophysics Data System (ADS)

Roberts, Carson B.; Bodkin, Andrew; Daly, James T.; Meola, Joseph

2015-06-01

Presented is a new hyperspectral imager design based on multiple slit scanning. This represents an innovation in the classic trade-off between speed and resolution. This LWIR design has been able to produce data-cubes at 3 times the rate of conventional single slit scan devices. The instrument has a built-in radiometric and spectral calibrator.

The Need for High Spatial Resolution Multispectral Thermal Remote Sensing Data In Urban Heat Island Research

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.

2006-01-01

Although the study of the Urban Heat Island (UHI) effect dates back to the early 1800's when Luke Howard discovered London s heat island, it has only been with the advent of thermal remote sensing systems that the extent, characteristics, and impacts of the UHI have become to be understood. Analysis of the UHI effect is important because above all, this phenomenon can directly influence the health and welfare of urban residents. For example, in 1995, over 700 people died in Chicago due to heat-related causes. UHI s are characterized by increased temperature in comparison to rural areas and mortality rates during a heat wave increase exponentially with the maximum temperature, an effect that is exacerbated by the UHI. Aside from the direct impacts of the UHI on temperature, UHI s can produce secondary effects on local meteorology, including altering local wind patterns, increased development of clouds and fog, and increasing rates of precipitation either over, or downwind, of cities. Because of the extreme heterogeneity of the urban surface, in combination with the sprawl associated with urban growth, thermal infrared (TIR) remote sensing data have become of significant importance in understanding how land cover and land use characteristics affect the development and intensification of the UHI. TIR satellite data have been used extensively to analyze the surface temperature regimes of cities to help observe and measure the impacts of surface temperatures across the urban landscape. However, the spatial scales at which satellite TIR data are collected are for the most part, coarse, with the finest readily available TIR data collected by the Landsat ETM+ sensor at 60m spatial resolution. For many years, we have collected high spatial resolution (10m) data using an airborne multispectral TIR sensor over a number of cities across the United States. These high resolution data have been used to develop an understanding of how discrete surfaces across the urban environment (e.g., rooftops, pavements) interact from a surface-lower atmosphere energy flux perspective, to force the development of the UHI. Moreover, the airborne TIR sensor we used in our UHI studies was a multispectral sensor that had six channels in the 8-12pm range. The advantages of collecting multispectral TIR data became readily evident as a valuable tool for better calculation of unique surface thermal energy responses for urban materials over the 8-12 micrometer region, and also for getting a better handle on surface emissivity characteristics for these discrete surfaces. In this presentation, we will provide evidence on the virtues of how high spatial resolution multispectral TIR data can provide for better analysis of the UHI that cannot now be attained via TIR data obtained from satellites. Furthermore, we wish to provide compelling evidence on why future TIR satellite sensors should collect data at fine spatial resolutions (e.g. less than or equal to 30m) to better allow for measurement of surface thermal energy fluxes from discrete urban surfaces, and to better understand how surface fluxes from different urban materials in cities around the world in different climatic regimes, affect development of the UHI characteristics.

Building Change Detection in Very High Resolution Satellite Stereo Image Time Series

NASA Astrophysics Data System (ADS)

Tian, J.; Qin, R.; Cerra, D.; Reinartz, P.

2016-06-01

There is an increasing demand for robust methods on urban sprawl monitoring. The steadily increasing number of high resolution and multi-view sensors allows producing datasets with high temporal and spatial resolution; however, less effort has been dedicated to employ very high resolution (VHR) satellite image time series (SITS) to monitor the changes in buildings with higher accuracy. In addition, these VHR data are often acquired from different sensors. The objective of this research is to propose a robust time-series data analysis method for VHR stereo imagery. Firstly, the spatial-temporal information of the stereo imagery and the Digital Surface Models (DSMs) generated from them are combined, and building probability maps (BPM) are calculated for all acquisition dates. In the second step, an object-based change analysis is performed based on the derivative features of the BPM sets. The change consistence between object-level and pixel-level are checked to remove any outlier pixels. Results are assessed on six pairs of VHR satellite images acquired within a time span of 7 years. The evaluation results have proved the efficiency of the proposed method.

GelSight: High-Resolution Robot Tactile Sensors for Estimating Geometry and Force

PubMed Central

Yuan, Wenzhen; Dong, Siyuan; Adelson, Edward H.

2017-01-01

Tactile sensing is an important perception mode for robots, but the existing tactile technologies have multiple limitations. What kind of tactile information robots need, and how to use the information, remain open questions. We believe a soft sensor surface and high-resolution sensing of geometry should be important components of a competent tactile sensor. In this paper, we discuss the development of a vision-based optical tactile sensor, GelSight. Unlike the traditional tactile sensors which measure contact force, GelSight basically measures geometry, with very high spatial resolution. The sensor has a contact surface of soft elastomer, and it directly measures its deformation, both vertical and lateral, which corresponds to the exact object shape and the tension on the contact surface. The contact force, and slip can be inferred from the sensor’s deformation as well. Particularly, we focus on the hardware and software that support GelSight’s application on robot hands. This paper reviews the development of GelSight, with the emphasis in the sensing principle and sensor design. We introduce the design of the sensor’s optical system, the algorithm for shape, force and slip measurement, and the hardware designs and fabrication of different sensor versions. We also show the experimental evaluation on the GelSight’s performance on geometry and force measurement. With the high-resolution measurement of shape and contact force, the sensor has successfully assisted multiple robotic tasks, including material perception or recognition and in-hand localization for robot manipulation. PMID:29186053

Spatial Metadata for Global Change Investigations Using Remote Sensing

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Quattrochi, Dale A.; Lam, Nina Siu-Ngan; Arnold, James E. (Technical Monitor)

2002-01-01

Satellite and aircraft-borne remote sensors have gathered petabytes of data over the past 30+ years. These images are an important resource for establishing cause and effect relationships between human-induced land cover changes and alterations in climate and other biophysical patterns at local to global scales. However, the spatial, temporal, and spectral characteristics of these datasets vary, thus complicating long-term studies involving several types of imagery. As the geographical and temporal coverage, the spectral and spatial resolution, and the number of individual sensors increase, the sheer volume and complexity of available data sets will complicate management and use of the rapidly growing archive of earth imagery. Mining this vast data resource for images that provide the necessary information for climate change studies becomes more difficult as more sensors are launched and more imagery is obtained.

A model-based approach for detection of runways and other objects in image sequences acquired using an on-board camera

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Devadiga, Sadashiva; Tang, Yuan-Liang

1994-01-01

This research was initiated as a part of the Advanced Sensor and Imaging System Technology (ASSIST) program at NASA Langley Research Center. The primary goal of this research is the development of image analysis algorithms for the detection of runways and other objects using an on-board camera. Initial effort was concentrated on images acquired using a passive millimeter wave (PMMW) sensor. The images obtained using PMMW sensors under poor visibility conditions due to atmospheric fog are characterized by very low spatial resolution but good image contrast compared to those images obtained using sensors operating in the visible spectrum. Algorithms developed for analyzing these images using a model of the runway and other objects are described in Part 1 of this report. Experimental verification of these algorithms was limited to a sequence of images simulated from a single frame of PMMW image. Subsequent development and evaluation of algorithms was done using video image sequences. These images have better spatial and temporal resolution compared to PMMW images. Algorithms for reliable recognition of runways and accurate estimation of spatial position of stationary objects on the ground have been developed and evaluated using several image sequences. These algorithms are described in Part 2 of this report. A list of all publications resulting from this work is also included.

A novel capacitive absolute positioning sensor based on time grating with nanometer resolution

NASA Astrophysics Data System (ADS)

Pu, Hongji; Liu, Hongzhong; Liu, Xiaokang; Peng, Kai; Yu, Zhicheng

2018-05-01

The present work proposes a novel capacitive absolute positioning sensor based on time grating. The sensor includes a fine incremental-displacement measurement component combined with a coarse absolute-position measurement component to obtain high-resolution absolute positioning measurements. A single row type sensor was proposed to achieve fine displacement measurement, which combines the two electrode rows of a previously proposed double-row type capacitive displacement sensor based on time grating into a single row. To achieve absolute positioning measurement, the coarse measurement component is designed as a single-row type displacement sensor employing a single spatial period over the entire measurement range. In addition, this component employs a rectangular induction electrode and four groups of orthogonal discrete excitation electrodes with half-sinusoidal envelope shapes, which were formed by alternately extending the rectangular electrodes of the fine measurement component. The fine and coarse measurement components are tightly integrated to form a compact absolute positioning sensor. A prototype sensor was manufactured using printed circuit board technology for testing and optimization of the design in conjunction with simulations. Experimental results show that the prototype sensor achieves a ±300 nm measurement accuracy with a 1 nm resolution over a displacement range of 200 mm when employing error compensation. The proposed sensor is an excellent alternative to presently available long-range absolute nanometrology sensors owing to its low cost, simple structure, and ease of manufacturing.

NDVI, scale invariance and the modifiable areal unit problem: An assessment of vegetation in the Adelaide Parklands

USGS Publications Warehouse

Nouri, Hamideh; Anderson, Sharolyn; Sutton, Paul; Beecham, Simon; Nagler, Pamela L.; Jarchow, Christopher J.; Roberts, Dar A.

2017-01-01

This research addresses the question as to whether or not the Normalised Difference Vegetation Index (NDVI) is scale invariant (i.e. constant over spatial aggregation) for pure pixels of urban vegetation. It has been long recognized that there are issues related to the modifiable areal unit problem (MAUP) pertaining to indices such as NDVI and images at varying spatial resolutions. These issues are relevant to using NDVI values in spatial analyses. We compare two different methods of calculation of a mean NDVI: 1) using pixel values of NDVI within feature/object boundaries and 2) first calculating the mean red and mean near-infrared across all feature pixels and then calculating NDVI. We explore the nature and magnitude of these differences for images taken from two sensors, a 1.24 m resolution WorldView-3 and a 0.1 m resolution digital aerial image. We apply these methods over an urban park located in the Adelaide Parklands of South Australia. We demonstrate that the MAUP is not an issue for calculation of NDVI within a sensor for pure urban vegetation pixels. This may prove useful for future rule-based monitoring of the ecosystem functioning of green infrastructure.

Quadrant anode image sensor

NASA Technical Reports Server (NTRS)

Lampton, M.; Malina, R. F.

1976-01-01

A position-sensitive event-counting electronic readout system for microchannel plates (MCPs) is described that offers the advantages of high spatial resolution and fast time resolution. The technique relies upon a four-quadrant electron-collecting anode located behind the output face of the microchannel plate, so that the electron cloud from each detected event is partly intercepted by each of the four quadrants. The relative amounts of charge collected by each quadrant depend on event position, permitting each event to be localized with two ratio circuits. A prototype quadrant anode system for ion, electron, and extreme ultraviolet imaging is described. The spatial resolution achieved, about 10 microns, allows individual MCP channels to be distinguished.

EEG-MEG Integration Enhances the Characterization of Functional and Effective Connectivity in the Resting State Network

PubMed Central

Mideksa, Kidist Gebremariam; Anwar, Abdul Rauf; Stephani, Ulrich; Deuschl, Günther; Freitag, Christine M.; Siniatchkin, Michael

2015-01-01

At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general conclusion multi-center studies would be helpful. PMID:26509448

High spatial resolution measurements of ram accelerator gas dynamic phenomena

NASA Technical Reports Server (NTRS)

Hinkey, J. B.; Burnham, E. A.; Bruckner, A. P.

1992-01-01

High spatial resolution experimental tube wall pressure measurements of ram accelerator gas dynamic phenomena are presented. The projectile resembles the centerbody of a ramjet and travels supersonically through a tube filled with a combustible gaseous mixture, with the tube acting as the outer cowling. Pressure data are recorded as the projectile passes by sensors mounted in the tube wall at various locations along the tube. Data obtained by using a special highly instrumented section of tube has allowed the recording of gas dynamic phenomena with a spatial resolution on the order of one tenth the projectile length. High spatial resolution tube wall pressure data from the three regimes of propulsion studied to date (subdetonative, transdetonative, and superdetonative) are presented and reveal the 3D character of the flowfield induced by projectile fins and the canting of the projectile body relative to the tube wall. Also presented for comparison to the experimental data are calculations made with an inviscid, 3D CFD code.

Roi-Orientated Sensor Correction Based on Virtual Steady Reimaging Model for Wide Swath High Resolution Optical Satellite Imagery

NASA Astrophysics Data System (ADS)

Zhu, Y.; Jin, S.; Tian, Y.; Wang, M.

2017-09-01

To meet the requirement of high accuracy and high speed processing for wide swath high resolution optical satellite imagery under emergency situation in both ground processing system and on-board processing system. This paper proposed a ROI-orientated sensor correction algorithm based on virtual steady reimaging model for wide swath high resolution optical satellite imagery. Firstly, the imaging time and spatial window of the ROI is determined by a dynamic search method. Then, the dynamic ROI sensor correction model based on virtual steady reimaging model is constructed. Finally, the corrected image corresponding to the ROI is generated based on the coordinates mapping relationship which is established by the dynamic sensor correction model for corrected image and rigours imaging model for original image. Two experimental results show that the image registration between panchromatic and multispectral images can be well achieved and the image distortion caused by satellite jitter can be also corrected efficiently.

Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping.

PubMed

Lomperski, Stephen; Gerardi, Craig; Lisowski, Darius

2016-11-07

The reliability of computational fluid dynamics (CFD) codes is checked by comparing simulations with experimental data. A typical data set consists chiefly of velocity and temperature readings, both ideally having high spatial and temporal resolution to facilitate rigorous code validation. While high resolution velocity data is readily obtained through optical measurement techniques such as particle image velocimetry, it has proven difficult to obtain temperature data with similar resolution. Traditional sensors such as thermocouples cannot fill this role, but the recent development of distributed sensing based on Rayleigh scattering and swept-wave interferometry offers resolution suitable for CFD code validation work. Thousands of temperature measurements can be generated along a single thin optical fiber at hundreds of Hertz. Sensors function over large temperature ranges and within opaque fluids where optical techniques are unsuitable. But this type of sensor is sensitive to strain and humidity as well as temperature and so accuracy is affected by handling, vibration, and shifts in relative humidity. Such behavior is quite unlike traditional sensors and so unconventional installation and operating procedures are necessary to ensure accurate measurements. This paper demonstrates implementation of a Rayleigh scattering-type distributed temperature sensor in a thermal mixing experiment involving two air jets at 25 and 45 °C. We present criteria to guide selection of optical fiber for the sensor and describe installation setup for a jet mixing experiment. We illustrate sensor baselining, which links readings to an absolute temperature standard, and discuss practical issues such as errors due to flow-induced vibration. This material can aid those interested in temperature measurements having high data density and bandwidth for fluid dynamics experiments and similar applications. We highlight pitfalls specific to these sensors for consideration in experiment design and operation.

High Resolution Flash Flood Forecasting Using a Wireless Sensor Network in the Dallas-Fort Worth Metroplex

NASA Astrophysics Data System (ADS)

Bartos, M. D.; Kerkez, B.; Noh, S.; Seo, D. J.

2017-12-01

In this study, we develop and evaluate a high resolution urban flash flood monitoring system using a wireless sensor network (WSN), a real-time rainfall-runoff model, and spatially-explicit radar rainfall predictions. Flooding is the leading cause of natural disaster fatalities in the US, with flash flooding in particular responsible for a majority of flooding deaths. While many riverine flood models have been operationalized into early warning systems, there is currently no model that is capable of reliably predicting flash floods in urban areas. Urban flash floods are particularly difficult to model due to a lack of rainfall and runoff data at appropriate scales. To address this problem, we develop a wide-area flood-monitoring wireless sensor network for the Dallas-Fort Worth metroplex, and use this network to characterize rainfall-runoff response over multiple heterogeneous catchments. First, we deploy a network of 22 wireless sensor nodes to collect real-time stream stage measurements over catchments ranging from 2-80 km2 in size. Next, we characterize the rainfall-runoff response of each catchment by combining stream stage data with gage and radar-based precipitation measurements. Finally, we demonstrate the potential for real-time flash flood prediction by joining the derived rainfall-runoff models with real-time radar rainfall predictions. We find that runoff response is highly heterogeneous among catchments, with large variabilities in runoff response detected even among nearby gages. However, when spatially-explicit rainfall fields are included, spatial variability in runoff response is largely captured. This result highlights the importance of increased spatial coverage for flash flood prediction.

Measurement of the Extracellular pH of Adherently Growing Mammalian Cells with High Spatial Resolution Using a Voltammetric pH Microsensor.

PubMed

Munteanu, Raluca-Elena; Stǎnicǎ, Luciana; Gheorghiu, Mihaela; Gáspár, Szilveszter

2018-05-15

There are only a few tools suitable for measuring the extracellular pH of adherently growing mammalian cells with high spatial resolution, and none of them is widely used in laboratories around the world. Cell biologists very often limit themselves to measuring the intracellular pH with commercially available fluorescent probes. Therefore, we built a voltammetric pH microsensor and investigated its suitability for monitoring the extracellular pH of adherently growing mammalian cells. The voltammetric pH microsensor consisted of a 37 μm diameter carbon fiber microelectrode modified with reduced graphene oxide and syringaldazine. While graphene oxide was used to increase the electrochemically active surface area of our sensor, syringaldazine facilitated pH sensing through its pH-dependent electrochemical oxidation and reduction. The good sensitivity (60 ± 2.5 mV/pH unit), reproducibility (coefficient of variation ≤3% for the same pH measured with 5 different microsensors), and stability (pH drift around 0.05 units in 3 h) of the built voltammetric pH sensors were successfully used to investigate the acidification of the extracellular space of both cancer cells and normal cells. The results indicate that the developed pH microsensor and the perfected experimental protocol based on scanning electrochemical microscopy can reveal details of the pH regulation of cells not attainable with pH sensors lacking spatial resolution or which cannot be reproducibly positioned in the extracellular space.

Preliminary investigations of active pixel sensors in Nuclear Medicine imaging

NASA Astrophysics Data System (ADS)

Ott, Robert; Evans, Noel; Evans, Phil; Osmond, J.; Clark, A.; Turchetta, R.

2009-06-01

Three CMOS active pixel sensors have been investigated for their application to Nuclear Medicine imaging. Startracker with 525×525 25 μm square pixels has been coupled via a fibre optic stud to a 2 mm thick segmented CsI(Tl) crystal. Imaging tests were performed using 99mTc sources, which emit 140 keV gamma rays. The system was interfaced to a PC via FPGA-based DAQ and optical link enabling imaging rates of 10 f/s. System noise was measured to be >100e and it was shown that the majority of this noise was fixed pattern in nature. The intrinsic spatial resolution was measured to be ˜80 μm and the system spatial resolution measured with a slit was ˜450 μm. The second sensor, On Pixel Intelligent CMOS (OPIC), had 64×72 40 μm pixels and was used to evaluate noise characteristics and to develop a method of differentiation between fixed pattern and statistical noise. The third sensor, Vanilla, had 520×520 25 μm pixels and a measured system noise of ˜25e. This sensor was coupled directly to the segmented phosphor. Imaging results show that even at this lower level of noise the signal from 140 keV gamma rays is small as the light from the phosphor is spread over a large number of pixels. Suggestions for the 'ideal' sensor are made.

Adjusting Spectral Indices for Spectral Response Function Differences of Very High Spatial Resolution Sensors Simulated from Field Spectra

PubMed Central

Cundill, Sharon L.; van der Werff, Harald M. A.; van der Meijde, Mark

2015-01-01

The use of data from multiple sensors is often required to ensure data coverage and continuity, but differences in the spectral characteristics of sensors result in spectral index values being different. This study investigates spectral response function effects on 48 spectral indices for cultivated grasslands using simulated data of 10 very high spatial resolution sensors, convolved from field reflectance spectra of a grass covered dike (with varying vegetation condition). Index values for 48 indices were calculated for original narrow-band spectra and convolved data sets, and then compared. The indices Difference Vegetation Index (DVI), Global Environmental Monitoring Index (GEMI), Enhanced Vegetation Index (EVI), Modified Soil-Adjusted Vegetation Index (MSAVI2) and Soil-Adjusted Vegetation Index (SAVI), which include the difference between the near-infrared and red bands, have values most similar to those of the original spectra across all 10 sensors (1:1 line mean 1:1R2 > 0.960 and linear trend mean ccR2 > 0.997). Additionally, relationships between the indices’ values and two quality indicators for grass covered dikes were compared to those of the original spectra. For the soil moisture indicator, indices that ratio bands performed better across sensors than those that difference bands, while for the dike cover quality indicator, both the choice of bands and their formulation are important. PMID:25781511

Vibration-based monitoring and diagnostics using compressive sensing

NASA Astrophysics Data System (ADS)

Ganesan, Vaahini; Das, Tuhin; Rahnavard, Nazanin; Kauffman, Jeffrey L.

2017-04-01

Vibration data from mechanical systems carry important information that is useful for characterization and diagnosis. Standard approaches rely on continually streaming data at a fixed sampling frequency. For applications involving continuous monitoring, such as Structural Health Monitoring (SHM), such approaches result in high volume data and rely on sensors being powered for prolonged durations. Furthermore, for spatial resolution, structures are instrumented with a large array of sensors. This paper shows that both volume of data and number of sensors can be reduced significantly by applying Compressive Sensing (CS) in vibration monitoring applications. The reduction is achieved by using random sampling and capitalizing on the sparsity of vibration signals in the frequency domain. Preliminary experimental results validating CS-based frequency recovery are also provided. By exploiting the sparsity of mode shapes, CS can also enable efficient spatial reconstruction using fewer spatially distributed sensors. CS can thereby reduce the cost and power requirement of sensing as well as streamline data storage and processing in monitoring applications. In well-instrumented structures, CS can enable continued monitoring in case of sensor or computational failures.

Resolution-enhanced Mapping Spectrometer

NASA Technical Reports Server (NTRS)

Kumer, J. B.; Aubrun, J. N.; Rosenberg, W. J.; Roche, A. E.

1993-01-01

A familiar mapping spectrometer implementation utilizes two dimensional detector arrays with spectral dispersion along one direction and spatial along the other. Spectral images are formed by spatially scanning across the scene (i.e., push-broom scanning). For imaging grating and prism spectrometers, the slit is perpendicular to the spatial scan direction. For spectrometers utilizing linearly variable focal-plane-mounted filters the spatial scan direction is perpendicular to the direction of spectral variation. These spectrometers share the common limitation that the number of spectral resolution elements is given by the number of pixels along the spectral (or dispersive) direction. Resolution enhancement by first passing the light input to the spectrometer through a scanned etalon or Michelson is discussed. Thus, while a detector element is scanned through a spatial resolution element of the scene, it is also temporally sampled. The analysis for all the pixels in the dispersive direction is addressed. Several specific examples are discussed. The alternate use of a Michelson for the same enhancement purpose is also discussed. Suitable for weight constrained deep space missions, hardware systems were developed including actuators, sensor, and electronics such that low-resolution etalons with performance required for implementation would weigh less than one pound.

Neutron imaging with lithium indium diselenide: Surface properties, spatial resolution, and computed tomography

NASA Astrophysics Data System (ADS)

Lukosi, Eric D.; Herrera, Elan H.; Hamm, Daniel S.; Burger, Arnold; Stowe, Ashley C.

2017-11-01

An array of lithium indium diselenide (LISe) scintillators were investigated for application in neutron imaging. The sensors, varying in thickness and surface roughness, were tested using both reflective and anti-reflective mounting to an aluminum window. The spatial resolution of each LISe scintillator was calculated using the knife-edge test and a modulation transfer function analysis. It was found that the anti-reflective backing case yielded higher spatial resolutions by up to a factor of two over the reflective backing case despite a reduction in measured light yield by an average of 1.97. In most cases, the use of an anti-reflective backing resulted in a higher spatial resolution than the 50 μm-thick ZnS(Cu):6 LiF comparison scintillation screen. The effect of surface roughness was not directly correlated to measured light yield or observed spatial resolution, but weighting the reflective backing case by the random surface roughness revealed that a linear relationship exists between the fractional change (RB/ARB) of the two. Finally, the LISe scintillator array was used in neutron computed tomography to investigate the features of halyomorpha halys with the reflective and anti-reflective backing.

Evaluating the ASTER sensor for mapping and characterizing forest fire fuels in northern Idaho

Treesearch

Michael J. Falkowski; Paul Gessler; Penelope Morgan; Alistair M. S. Smith; Andrew T. Hudak

2004-01-01

Land managers need cost-effective methods for mapping and characterizing fire fuels quickly and accurately. The advent of sensors with increased spatial resolution may improve the accuracy and reduce the cost of fuels mapping. The objective of this research is to evaluate the accuracy and utility of imagery from the Advanced Spaceborne Thermal Emission and Reflection...

Recent progress in distributed fiber optic sensors.

PubMed

Bao, Xiaoyi; Chen, Liang

2012-01-01

Rayleigh, Brillouin and Raman scatterings in fibers result from the interaction of photons with local material characteristic features like density, temperature and strain. For example an acoustic/mechanical wave generates a dynamic density variation; such a variation may be affected by local temperature, strain, vibration and birefringence. By detecting changes in the amplitude, frequency and phase of light scattered along a fiber, one can realize a distributed fiber sensor for measuring localized temperature, strain, vibration and birefringence over lengths ranging from meters to one hundred kilometers. Such a measurement can be made in the time domain or frequency domain to resolve location information. With coherent detection of the scattered light one can observe changes in birefringence and beat length for fibers and devices. The progress on state of the art technology for sensing performance, in terms of spatial resolution and limitations on sensing length is reviewed. These distributed sensors can be used for disaster prevention in the civil structural monitoring of pipelines, bridges, dams and railroads. A sensor with centimeter spatial resolution and high precision measurement of temperature, strain, vibration and birefringence can find applications in aerospace smart structures, material processing, and the characterization of optical materials and devices.

System Characterization Results for the QuickBird Sensor

NASA Technical Reports Server (NTRS)

Holekamp, Kara; Ross, Kenton; Blonski, Slawomir

2007-01-01

An overall system characterization was performed on several DigitalGlobe' QuickBird image products by the NASA Applied Research & Technology Project Office (formerly the Applied Sciences Directorate) at the John C. Stennis Space Center. This system characterization incorporated geopositional accuracy assessments, a spatial resolution assessment, and a radiometric calibration assessment. Geopositional assessments of standard georeferenced multispectral products were obtained using an array of accurately surveyed geodetic targets evenly spaced throughout a scene. Geopositional accuracy was calculated in terms of circular error. Spatial resolution of QuickBird panchromatic imagery was characterized based on edge response measurements using edge targets and the tilted-edge technique. Relative edge response was estimated as a geometric mean of normalized edge response differences measured in two directions of image pixels at points distanced from the edge by -0.5 and 0.5 of ground sample distance. A reflectance-based vicarious calibration approach, based on ground-based measurements and radiative transfer calculations, was used to estimate at-sensor radiance. These values were compared to those measured by the sensor to determine the sensor's radiometric accuracy. All imagery analyzed was acquired between fall 2005 and spring 2006. These characterization results were compared to previous years' results to identify any temporal drifts or trends.

Recent Progress in Distributed Fiber Optic Sensors

PubMed Central

Bao, Xiaoyi; Chen, Liang

2012-01-01

Rayleigh, Brillouin and Raman scatterings in fibers result from the interaction of photons with local material characteristic features like density, temperature and strain. For example an acoustic/mechanical wave generates a dynamic density variation; such a variation may be affected by local temperature, strain, vibration and birefringence. By detecting changes in the amplitude, frequency and phase of light scattered along a fiber, one can realize a distributed fiber sensor for measuring localized temperature, strain, vibration and birefringence over lengths ranging from meters to one hundred kilometers. Such a measurement can be made in the time domain or frequency domain to resolve location information. With coherent detection of the scattered light one can observe changes in birefringence and beat length for fibers and devices. The progress on state of the art technology for sensing performance, in terms of spatial resolution and limitations on sensing length is reviewed. These distributed sensors can be used for disaster prevention in the civil structural monitoring of pipelines, bridges, dams and railroads. A sensor with centimeter spatial resolution and high precision measurement of temperature, strain, vibration and birefringence can find applications in aerospace smart structures, material processing, and the characterization of optical materials and devices. PMID:23012508

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

NASA Technical Reports Server (NTRS)

Mcgwire, K.; Friedl, M.; Estes, J. E.

1993-01-01

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Measuring high spatiotemporal variability in saltation intensity using a low-cost Saltation Detection System: Wind tunnel and field experiments

NASA Astrophysics Data System (ADS)

de Winter, W.; van Dam, D. B.; Delbecque, N.; Verdoodt, A.; Ruessink, B. G.; Sterk, G.

2018-04-01

The commonly observed over prediction of aeolian saltation transport on sandy beaches is, at least in part, caused by saltation intermittency. To study small-scale saltation processes, high frequency saltation sensors are required on a high spatial resolution. Therefore, we developed a low-cost Saltation Detection System (SalDecS) with the aim to measure saltation intensity at a frequency of 10 Hz and with a spatial resolution of 0.10 m in wind-normal direction. Linearity and equal sensitivity of the saltation sensors were investigated during wind tunnel and field experiments. Wind tunnel experiments with a set of 7 SalDec sensors revealed that the variability of sensor sensitivity is at maximum 9% during relatively low saltation intensities. During more intense saltation the variability of sensor sensitivity decreases. A sigmoidal fit describes the relation between mass flux and sensor output measured during 5 different wind conditions. This indicates an increasing importance of sensor saturation with increasing mass flux. We developed a theoretical model to simulate and describe the effect of grain size, grain velocity and saltation intensity on sensor saturation. Time-averaged field measurements revealed sensitivity equality for 85 out of a set of 89 horizontally deployed SalDec sensors. On these larger timescales (hours) saltation variability imposed by morphological features, such as sand strips, can be recognized. We conclude that the SalDecS can be used to measure small-scale spatiotemporal variabilities of saltation intensity to investigate saltation characteristics related to wind turbulence.

Feasibility of approaches combining sensor and source features in brain-computer interface.

PubMed

Ahn, Minkyu; Hong, Jun Hee; Jun, Sung Chan

2012-02-15

Brain-computer interface (BCI) provides a new channel for communication between brain and computers through brain signals. Cost-effective EEG provides good temporal resolution, but its spatial resolution is poor and sensor information is blurred by inherent noise. To overcome these issues, spatial filtering and feature extraction techniques have been developed. Source imaging, transformation of sensor signals into the source space through source localizer, has gained attention as a new approach for BCI. It has been reported that the source imaging yields some improvement of BCI performance. However, there exists no thorough investigation on how source imaging information overlaps with, and is complementary to, sensor information. Information (visible information) from the source space may overlap as well as be exclusive to information from the sensor space is hypothesized. Therefore, we can extract more information from the sensor and source spaces if our hypothesis is true, thereby contributing to more accurate BCI systems. In this work, features from each space (sensor or source), and two strategies combining sensor and source features are assessed. The information distribution among the sensor, source, and combined spaces is discussed through a Venn diagram for 18 motor imagery datasets. Additional 5 motor imagery datasets from the BCI Competition III site were examined. The results showed that the addition of source information yielded about 3.8% classification improvement for 18 motor imagery datasets and showed an average accuracy of 75.56% for BCI Competition data. Our proposed approach is promising, and improved performance may be possible with better head model. Copyright © 2011 Elsevier B.V. All rights reserved.

Radiometric Characterization of the IKONOS, QuickBird, and OrbView-3 Sensors

NASA Technical Reports Server (NTRS)

Holekamp, Kara

2006-01-01

Radiometric calibration of commercial imaging satellite products is required to ensure that science and application communities can better understand their properties. Inaccurate radiometric calibrations can lead to erroneous decisions and invalid conclusions and can limit intercomparisons with other systems. To address this calibration need, satellite at-sensor radiance values were compared to those estimated by each independent team member to determine the sensor's radiometric accuracy. The combined results of this evaluation provide the user community with an independent assessment of these commercially available high spatial resolution sensors' absolute calibration values.

OPTICAL FIBRES AND FIBREOPTIC SENSORS: Fibreoptic distributed temperature sensor with spectral filtration by directional fibre couplers

NASA Astrophysics Data System (ADS)

Kuznetsov, A. G.; Babin, Sergei A.; Shelemba, Ivan S.

2009-11-01

We demonstrate a Raman-based all-fibre temperature sensor utilising a pulsed erbium fibre laser. The sensor is made of a standard single-mode telecom fibre, SMF-28, and includes a number of directional couplers as band-pass filters. The temperature profile along a 7-km fibreoptic line is measured with an accuracy of 2oC and a spatial resolution of 10 m. In data processing, we take into account the difference in attenuation between the spectral components of the backscatter signal.

Evaluation of realistic layouts for next generation on-scalp MEG: spatial information density maps.

PubMed

Riaz, Bushra; Pfeiffer, Christoph; Schneiderman, Justin F

2017-08-01

While commercial magnetoencephalography (MEG) systems are the functional neuroimaging state-of-the-art in terms of spatio-temporal resolution, MEG sensors have not changed significantly since the 1990s. Interest in newer sensors that operate at less extreme temperatures, e.g., high critical temperature (high-T c ) SQUIDs, optically-pumped magnetometers, etc., is growing because they enable significant reductions in head-to-sensor standoff (on-scalp MEG). Various metrics quantify the advantages of on-scalp MEG, but a single straightforward one is lacking. Previous works have furthermore been limited to arbitrary and/or unrealistic sensor layouts. We introduce spatial information density (SID) maps for quantitative and qualitative evaluations of sensor arrays. SID-maps present the spatial distribution of information a sensor array extracts from a source space while accounting for relevant source and sensor parameters. We use it in a systematic comparison of three practical on-scalp MEG sensor array layouts (based on high-T c SQUIDs) and the standard Elekta Neuromag TRIUX magnetometer array. Results strengthen the case for on-scalp and specifically high-T c SQUID-based MEG while providing a path for the practical design of future MEG systems. SID-maps are furthermore general to arbitrary magnetic sensor technologies and source spaces and can thus be used for design and evaluation of sensor arrays for magnetocardiography, magnetic particle imaging, etc.

Comparison of Huanjing and Landsat satellite remote sensing of the spatial heterogeneity of Qinghai-Tibet alpine grassland

NASA Astrophysics Data System (ADS)

Wang, Junbang; Sun, Wenyi

2014-11-01

Remote sensing is widely applied in the study of terrestrial primary production and the global carbon cycle. The researches on the spatial heterogeneity in images with different sensors and resolutions would improve the application of remote sensing. In this study two sites on alpine meadow grassland in Qinghai, China, which have distinct fractal vegetation cover, were used to test and analyze differences between Normalized Difference Vegetation Index (NDVI) and enhanced vegetation index (EVI) derived from the Huanjing (HJ) and Landsat Thematic Mapper (TM) sensors. The results showed that: 1) NDVI estimated from HJ were smaller than the corresponding values from TM at the two sites whereas EVI were almost the same for the two sensors. 2) The overall variance represented by HJ data was consistently about half of that of Landsat TM although their nominal pixel size is approximately 30m for both sensors. The overall variance from EVI is greater than that from NDVI. The difference of the range between the two sensors is about 6 pixels at 30m resolution. The difference of the range in which there is not more corrective between two vegetation indices is about 1 pixel. 3) The sill decreased when pixel size increased from 30m to 1km, and then decreased very quickly when pixel size is changed to 250m from 30m or 90m but slowly when changed from 250m to 500m. HJ can capture this spatial heterogeneity to some extent and this study provides foundations for the use of the sensor for validation of net primary productivity estimates obtained from ecosystem process models.

Fiber Optic Temperature Sensors in TPS: Arc Jet Model Design & Testing

NASA Technical Reports Server (NTRS)

Black, Richard; Feldman, Jay; Ellerby, Donald; Monk, Joshua; Moslehi, Behzad; Oblea, Levy; Switzer, Matthew

2017-01-01

Techniques for using fiber optics with Fiber Bragg Gratings (FBGs) have been developed by IFOS Corp. for use in thermal protection systems (TPS) on spacecraft heat shield materials through NASA Phase 1 and 2 SBIR efforts and have been further improved in a recent collaboration between IFOS and NASA that will be described here. Fiber optic temperature sensors offer several potential advantages over traditional thermocouple sensors including a) multiplexing many sensors in a single fiber to increase sensor density in a given array or to provide spatial resolution, b) improved thermal property match between sensor and TPS to reduce heat flow disruption, c) lack of electrical conductivity.

Tuning Selectivity of Fluorescent Carbon Nanotube-Based Neurotransmitter Sensors.

PubMed

Mann, Florian A; Herrmann, Niklas; Meyer, Daniel; Kruss, Sebastian

2017-06-28

Detection of neurotransmitters is an analytical challenge and essential to understand neuronal networks in the brain and associated diseases. However, most methods do not provide sufficient spatial, temporal, or chemical resolution. Near-infrared (NIR) fluorescent single-walled carbon nanotubes (SWCNTs) have been used as building blocks for sensors/probes that detect catecholamine neurotransmitters, including dopamine. This approach provides a high spatial and temporal resolution, but it is not understood if these sensors are able to distinguish dopamine from similar catecholamine neurotransmitters, such as epinephrine or norepinephrine. In this work, the organic phase (DNA sequence) around SWCNTs was varied to create sensors with different selectivity and sensitivity for catecholamine neurotransmitters. Most DNA-functionalized SWCNTs responded to catecholamine neurotransmitters, but both dissociation constants ( K d ) and limits of detection were highly dependent on functionalization (sequence). K d values span a range of 2.3 nM (SWCNT-(GC) 15 + norepinephrine) to 9.4 μM (SWCNT-(AT) 15 + dopamine) and limits of detection are mostly in the single-digit nM regime. Additionally, sensors of different SWCNT chirality show different fluorescence increases. Moreover, certain sensors (e.g., SWCNT-(GT) 10 ) distinguish between different catecholamines, such as dopamine and norepinephrine at low concentrations (50 nM). These results show that SWCNTs functionalized with certain DNA sequences are able to discriminate between catecholamine neurotransmitters or to detect them in the presence of interfering substances of similar structure. Such sensors will be useful to measure and study neurotransmitter signaling in complex biological settings.

A study of aerosol absorption and height retrievals with a hyperspectral (UV to NIR) passive sensor

NASA Astrophysics Data System (ADS)

Gasso, S.

2017-12-01

With the deployment of the first sensor (TOMS, in 1978) with capabilities to detect aerosol absorption (AA) from space, there has been a continuous evolution in hardware and algorithms used to measured this property. Although with TOMS and its more advanced successors (such as OMI) made significant progress in globally characterizing AA , there is room for improvement especially by taking advantage of sensors with extended spectral coverage (UV to NIR) and high spatial resolution (<1 km). While such unique sensor does not exist yet, the collocation of observations from different platforms that jointly fulfill those characteristics (e.g. A-Train, S-NPP) confirm that it is possible to fully retrieve all AA parameters that modulate absorption in the upwelling radiance (AOD, SSA and aerosol layer height). However, such combined approaches still have some drawbacks such as the difficulty to account for cloud contamination. The upcoming deployment of satellite detectors with the desired features all in one sensor (PACE, TropOMI, GEMS) prompt a revision of the AA retrieval technique used in past approaches. In particular,the TropOMI mission, a hyperspectral UV-to-NIR sensor with moderate ( 5km nadir pixel) spatial resolution to be launched in Fall 2017. In addition , the sensor will include sensing capabilities for the wavelength range of the Oxygen bands A and B at very high wavelength resolution. This study will be centered on the aerosol detection capabilities of TropOMI. Because the spectral range covered, it is theoretically possible to simultaneously retrieve the aerosol optical depth, the single scattering albedo and aerosol mean height without assuming any of them as it was the case with previous retrieval approaches. Specifically, we intend to present a theoretical study based on simulated radiances at selected UV, VIS and near-IR bands (including the Oxygen bands) and evaluate the sensitivity of this sensor to different levels of aerosol concentration, height and absorption properties (imaginary index) along with particle size distribution.

Simulated Performances of a Very High Energy Tomograph for Non-Destructive Characterization of large objects

NASA Astrophysics Data System (ADS)

Kistler, Marc; Estre, Nicolas; Merle, Elsa

2018-01-01

As part of its R&D activities on high-energy X-ray imaging for non-destructive characterization, the Nuclear Measurement Laboratory has started an upgrade of its imaging system currently implemented at the CEA-Cadarache center. The goals are to achieve a sub-millimeter spatial resolution and the ability to perform tomographies on very large objects (more than 100-cm standard concrete or 40-cm steel). This paper presentsresults on the detection part of the imaging system. The upgrade of the detection part needs a thorough study of the performance of two detectors: a series of CdTe semiconductor sensors and two arrays of segmented CdWO4 scintillators with different pixel sizes. This study consists in a Quantum Accounting Diagram (QAD) analysis coupled with Monte-Carlo simulations. The scintillator arrays are able to detect millimeter details through 140 cm of concrete, but are limited to 120 cm for smaller ones. CdTe sensors have lower but more stable performance, with a 0.5 mm resolution for 90 cm of concrete. The choice of the detector then depends on the preferred characteristic: the spatial resolution or the use on large volumes. The combination of the features of the source and the studies on the detectors gives the expected performance of the whole equipment, in terms of signal-over-noise ratio (SNR), spatial resolution and acquisition time.

Downscaling of Aircraft-, Landsat-, and MODIS-based Land Surface Temperature Images with Support Vector Machines

NASA Astrophysics Data System (ADS)

Ha, W.; Gowda, P. H.; Oommen, T.; Howell, T. A.; Hernandez, J. E.

2010-12-01

High spatial resolution Land Surface Temperature (LST) images are required to estimate evapotranspiration (ET) at a field scale for irrigation scheduling purposes. Satellite sensors such as Landsat 5 Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) can offer images at several spectral bandwidths including visible, near-infrared (NIR), shortwave-infrared, and thermal-infrared (TIR). The TIR images usually have coarser spatial resolutions than those from non-thermal infrared bands. Due to this technical constraint of the satellite sensors on these platforms, image downscaling has been proposed in the field of ET remote sensing. This paper explores the potential of the Support Vector Machines (SVM) to perform downscaling of LST images derived from aircraft (4 m spatial resolution), TM (120 m), and MODIS (1000 m) using normalized difference vegetation index images derived from simultaneously acquired high resolution visible and NIR data (1 m for aircraft, 30 m for TM, and 250 m for MODIS). The SVM is a new generation machine learning algorithm that has found a wide application in the field of pattern recognition and time series analysis. The SVM would be ideally suited for downscaling problems due to its generalization ability in capturing non-linear regression relationship between the predictand and the multiple predictors. Remote sensing data acquired over the Texas High Plains during the 2008 summer growing season will be used in this study. Accuracy assessment of the downscaled 1, 30, and 250 m LST images will be made by comparing them with LST data measured with infrared thermometers at a small spatial scale, upscaled 30 m aircraft-based LST images, and upscaled 250 m TM-based LST images, respectively.

AN ACTIVE-PASSIVE COMBINED ALGORITHM FOR HIGH SPATIAL RESOLUTION RETRIEVAL OF SOIL MOISTURE FROM SATELLITE SENSORS (Invited)

NASA Astrophysics Data System (ADS)

Lakshmi, V.; Mladenova, I. E.; Narayan, U.

2009-12-01

Soil moisture is known to be an essential factor in controlling the partitioning of rainfall into surface runoff and infiltration and solar energy into latent and sensible heat fluxes. Remote sensing has long proven its capability to obtain soil moisture in near real-time. However, at the present time we have the Advanced Scanning Microwave Radiometer (AMSR-E) on board NASA’s AQUA platform is the only satellite sensor that supplies a soil moisture product. AMSR-E coarse spatial resolution (~ 50 km at 6.9 GHz) strongly limits its applicability for small scale studies. A very promising technique for spatial disaggregation by combining radar and radiometer observations has been demonstrated by the authors using a methodology is based on the assumption that any change in measured brightness temperature and backscatter from one to the next time step is due primarily to change in soil wetness. The approach uses radiometric estimates of soil moisture at a lower resolution to compute the sensitivity of radar to soil moisture at the lower resolution. This estimate of sensitivity is then disaggregated using vegetation water content, vegetation type and soil texture information, which are the variables on which determine the radar sensitivity to soil moisture and are generally available at a scale of radar observation. This change detection algorithm is applied to several locations. We have used aircraft observed active and passive data over Walnut Creek watershed in Central Iowa in 2002; the Little Washita Watershed in Oklahoma in 2003 and the Murrumbidgee Catchment in southeastern Australia for 2006. All of these locations have different soils and land cover conditions which leads to a rigorous test of the disaggregation algorithm. Furthermore, we compare the derived high spatial resolution soil moisture to in-situ sampling and ground observation networks

Optical scanner system for high resolution measurement of lubricant distributions on metal strips based on laser induced fluorescence

NASA Astrophysics Data System (ADS)

Holz, Philipp; Lutz, Christian; Brandenburg, Albrecht

2017-06-01

We present a new optical setup, which uses scanning mirrors in combination with laser induced fluorescence to monitor the spatial distribution of lubricant on metal sheets. Current trends in metal processing industry require forming procedures with increasing deformations. Thus a welldefined amount of lubricant is necessary to prevent the material from rupture, to reduce the wearing of the manufacturing tool as well as to prevent problems in post-deforming procedures. Therefore spatial resolved analysis of the thickness of lubricant layers is required. Current systems capture the lubricant distribution by moving sensor heads over the object along a linear axis. However the spatial resolution of these systems is insufficient at high strip speeds, e.g. at press plants. The presented technology uses fast rotating scanner mirrors to deflect a laser beam on the surface. This 405 nm laser light excites the autofluorescence of the investigated lubricants. A coaxial optic collects the fluorescence signal which is then spectrally filtered and recorded using a photomultiplier. From the acquired signal a two dimensional image is reconstructed in real time. This paper presents the sensor setup as well as its characterization. For the calibration of the system reference targets were prepared using an ink jet printer. The presented technology for the first time allows a spatial resolution in the millimetre range at production speed. The presented test system analyses an area of 300 x 300 mm² at a spatial resolution of 1.1 mm in less than 20 seconds. Despite this high speed of the measurement the limit of detection of the system described in this paper is better than 0.05 g/m² for the certified lubricant BAM K-009.

A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska

USGS Publications Warehouse

Selkowitz, D.J.

2010-01-01

Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (> 0.5 m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30 m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250 m and 500 m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275 m spatial resolution for a 1067 km2 study area in Arctic Alaska. The study area is centered at 69 ??N, ranges in elevation from 130 to 770 m, is composed primarily of rolling topography with gentle slopes less than 10??, and is free of glaciers and perennial snow cover. Shrubs > 0.5 m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from in situ shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250 m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets, an expected result for a study area where most shrub cover is concentrated in narrow patches associated with rivers, drainages, and slopes. Including the middle infrared bands available from Landsat and MODIS in the regression tree models (in addition to the four standard visible and near-infrared spectral bands) typically results in a slight boost in accuracy. Including the multi-angular red band data available from MISR in the regression tree models, however, typically boosts accuracy more substantially, resulting in moderate resolution fractional shrub canopy estimates approaching the accuracy of estimates derived from the much higher spatial resolution Landsat sensor. Given the poor availability of snow and cloud-free Landsat scenes in many areas of the Arctic and the promising results demonstrated here by the MISR sensor, MISR may be the best choice for large area fractional shrub canopy mapping in the Alaskan Arctic for the period 2000-2009.

Optical path difference microscopy with a Shack-Hartmann wavefront sensor.

PubMed

Gong, Hai; Agbana, Temitope E; Pozzi, Paolo; Soloviev, Oleg; Verhaegen, Michel; Vdovin, Gleb

2017-06-01

In this Letter, we show that a Shack-Hartmann wavefront sensor can be used for the quantitative measurement of the specimen optical path difference (OPD) in an ordinary incoherent optical microscope, if the spatial coherence of the illumination light in the plane of the specimen is larger than the microscope resolution. To satisfy this condition, the illumination numerical aperture should be smaller than the numerical aperture of the imaging lens. This principle has been successfully applied to build a high-resolution reference-free instrument for the characterization of the OPD of micro-optical components and microscopic biological samples.

Challenges and trends in magnetic sensor integration with microfluidics for biomedical applications

NASA Astrophysics Data System (ADS)

Cardoso, S.; Leitao, D. C.; Dias, T. M.; Valadeiro, J.; Silva, M. D.; Chicharo, A.; Silverio, V.; Gaspar, J.; Freitas, P. P.

2017-06-01

Magnetoresistive (MR) sensors have been successfully applied in many technologies, in particular readout electronics and smart systems for multiple signal addressing and readout. When single sensors are used, the requirements relate to spatial resolution and localized field sources. The integration of MR sensors in adaptable media (e.g. flexible, stretchable substrates) offers the possibility to merge the magnetic detection with mechanical functionalities. In addition, the precision of a micrometric needle can benefit greatly from the integration of MR sensors with submicrometric resolution. In this paper, we demonstrate through several detailed examples how advanced MR sensors can be integrated with the systems described above, and also with microfluidic technologies. Here, the challenges of handling liquids over a chip combine with those for miniaturization of microelectronics for MR readout. However, when these are overcome, the result is an integrated system with added functionalities, capable of answering the demand in biomedicine and biochemistry for lab-on-a-chip devices.

High-resolution distributed temperature sensing with the multiphoton-timing technique

NASA Astrophysics Data System (ADS)

Höbel, M.; Ricka, J.; Wüthrich, M.; Binkert, Th.

1995-06-01

We report on a multiphoton-timing distributed temperature sensor (DTS) based on the concept of distributed anti-Stokes Raman thermometry. The sensor combines the advantage of very high spatial resolution (40 cm) with moderate measurement times. In 5 min it is possible to determine the temperature of as many as 4000 points along an optical fiber with an accuracy Delta T less than 2 deg C. The new feature of the DTS system is the combination of a fast single-photon avalanche diode with specially designed real-time signal-processing electronics. We discuss various parameters that affect the operation of analog and photon-timing DTS systems. Particular emphasis is put on the consequences of the nonideal behavior of sensor components and the corresponding correction procedures.

Multi-Sensor Methods for Mobile Radar Motion Capture and Compensation

NASA Astrophysics Data System (ADS)

Nakata, Robert

Remote sensing has many applications, including surveying and mapping, geophysics exploration, military surveillance, search and rescue and counter-terrorism operations. Remote sensor systems typically use visible image, infrared or radar sensors. Camera based image sensors can provide high spatial resolution but are limited to line-of-sight capture during daylight. Infrared sensors have lower resolution but can operate during darkness. Radar sensors can provide high resolution motion measurements, even when obscured by weather, clouds and smoke and can penetrate walls and collapsed structures constructed with non-metallic materials up to 1 m to 2 m in depth depending on the wavelength and transmitter power level. However, any platform motion will degrade the target signal of interest. In this dissertation, we investigate alternative methodologies to capture platform motion, including a Body Area Network (BAN) that doesn't require external fixed location sensors, allowing full mobility of the user. We also investigated platform stabilization and motion compensation techniques to reduce and remove the signal distortion introduced by the platform motion. We evaluated secondary ultrasonic and radar sensors to stabilize the platform resulting in an average 5 dB of Signal to Interference Ratio (SIR) improvement. We also implemented a Digital Signal Processing (DSP) motion compensation algorithm that improved the SIR by 18 dB on average. These techniques could be deployed on a quadcopter platform and enable the detection of respiratory motion using an onboard radar sensor.

Coding Strategies and Implementations of Compressive Sensing

NASA Astrophysics Data System (ADS)

Tsai, Tsung-Han

This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others. This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system. Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity. Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.

Direction-of-arrival estimation for a uniform circular acoustic vector-sensor array mounted around a cylindrical baffle

NASA Astrophysics Data System (ADS)

Yang, DeSen; Zhu, ZhongRui

2012-12-01

This work investigates the direction-of-arrival (DOA) estimation for a uniform circular acoustic Vector-Sensor Array (UCAVSA) mounted around a cylindrical baffle. The total pressure field and the total particle velocity field near the surface of the cylindrical baffle are analyzed theoretically by applying the method of spatial Fourier transform. Then the so-called modal vector-sensor array signal processing algorithm, which is based on the decomposed wavefield representations, for the UCAVSA mounted around the cylindrical baffle is proposed. Simulation and experimental results show that the UCAVSA mounted around the cylindrical baffle has distinct advantages over the same manifold of traditional uniform circular pressure-sensor array (UCPSA). It is pointed out that the acoustic Vector-Sensor (AVS) could be used under the condition of the cylindrical baffle and that the UCAVSA mounted around the cylindrical baffle could also combine the anti-noise performance of the AVS with spatial resolution performance of array system by means of modal vector-sensor array signal processing algorithms.

Optimum Image Formation for Spaceborne Microwave Radiometer Products.

PubMed

Long, David G; Brodzik, Mary J

2016-05-01

This paper considers some of the issues of radiometer brightness image formation and reconstruction for use in the NASA-sponsored Calibrated Passive Microwave Daily Equal-Area Scalable Earth Grid 2.0 Brightness Temperature Earth System Data Record project, which generates a multisensor multidecadal time series of high-resolution radiometer products designed to support climate studies. Two primary reconstruction algorithms are considered: the Backus-Gilbert approach and the radiometer form of the scatterometer image reconstruction (SIR) algorithm. These are compared with the conventional drop-in-the-bucket (DIB) gridded image formation approach. Tradeoff study results for the various algorithm options are presented to select optimum values for the grid resolution, the number of SIR iterations, and the BG gamma parameter. We find that although both approaches are effective in improving the spatial resolution of the surface brightness temperature estimates compared to DIB, SIR requires significantly less computation. The sensitivity of the reconstruction to the accuracy of the measurement spatial response function (MRF) is explored. The partial reconstruction of the methods can tolerate errors in the description of the sensor measurement response function, which simplifies the processing of historic sensor data for which the MRF is not known as well as modern sensors. Simulation tradeoff results are confirmed using actual data.

Synergistic Use of SMOS Measurements with SMAP Derived and In-situ Data over Valencia Anchor Station by Using Downscaling Technique

NASA Astrophysics Data System (ADS)

Ansari Amoli, Abdolreza; Lopez-Baeza, Ernesto; Mahmoudi, Ali; Mahmoodi, Ali

2016-07-01

Synergistic Use of SMOS Measurements with SMAP Derived and In-situ Data over the Valencia Anchor Station by Using a Downscaling Technique Ansari Amoli, A.(1),Mahmoodi, A.(2) and Lopez-Baeza, E.(3) (1) Department of Earth Physics and Thermodynamics, University of Valencia, Spain (2) Centre d'Etudes Spatiales de la BIOsphère (CESBIO), France (3) Department of Earth Physics and Thermodynamics, University of Valencia, Spain Soil moisture products from active sensors are not operationally available. Passive remote sensors return more accurate estimates, but their resolution is much coarser. One solution to overcome this problem is the synergy between radar and radiometric data by using disaggregation (downscaling) techniques. Few studies have been conducted to merge high resolution radar and coarse resolution radiometer measurements in order to obtain an intermediate resolution product. In this paper we present an algorithm using combined available SMAP (Soil Moisture Active and Passive) radar and SMOS (Soil Moisture and Ocean Salinity) radiometer measurements to estimate surface soil moisture over the Valencia Anchor Station (VAS), Valencia, Spain. The goal is to combine the respective attributes of the radar and radiometer observations to estimate soil moisture at a resolution of 3 km. The algorithm disaggregates the coarse resolution SMOS (15 km) radiometer brightness temperature product based on the spatial variation of the high resolution SMAP (3 km) radar backscatter. The disaggregation of the radiometer brightness temperature uses the radar backscatter spatial patterns within the radiometer footprint that are inferred from the radar measurements. For this reason the radar measurements within the radiometer footprint are scaled by parameters that are derived from the temporal fluctuations in the radar and radiometer measurements.

In-situ device integration of large-area patterned organic nanowire arrays for high-performance optical sensors

PubMed Central

Wu, Yiming; Zhang, Xiujuan; Pan, Huanhuan; Deng, Wei; Zhang, Xiaohong; Zhang, Xiwei; Jie, Jiansheng

2013-01-01

Single-crystalline organic nanowires (NWs) are important building blocks for future low-cost and efficient nano-optoelectronic devices due to their extraordinary properties. However, it remains a critical challenge to achieve large-scale organic NW array assembly and device integration. Herein, we demonstrate a feasible one-step method for large-area patterned growth of cross-aligned single-crystalline organic NW arrays and their in-situ device integration for optical image sensors. The integrated image sensor circuitry contained a 10 × 10 pixel array in an area of 1.3 × 1.3 mm2, showing high spatial resolution, excellent stability and reproducibility. More importantly, 100% of the pixels successfully operated at a high response speed and relatively small pixel-to-pixel variation. The high yield and high spatial resolution of the operational pixels, along with the high integration level of the device, clearly demonstrate the great potential of the one-step organic NW array growth and device construction approach for large-scale optoelectronic device integration. PMID:24287887

Introduction to the Special Session on Thermal Remote Sensing Data for Earth Science Research: The Critical Need for Continued Data Collection and Development of Future Thermal Satellite Sensors

NASA Technical Reports Server (NTRS)

Quattrochi, Dale a.; Luvall, Jeffrey C.; Anderson, Martha; Hook, Simon

2006-01-01

There is a rich and long history of thermal infrared (TIR) remote sensing data for multidisciplinary Earth science research. The continuity of TIR data collection, however, is now in jeopardy given there are no planned future Earth observing TIR remote sensing satellite systems with moderately high spatial resolutions to replace those currently in orbit on NASA's Terra suite of sensors. This session will convene researchers who have actively worked in the field of TIR remote sensing to present results that elucidate the importance of thermal remote sensing to the wider Earth science research community. Additionally, this session will also exist as a forum for presenting concepts and ideas for new thermal sensing systems with high spatial resolutions for future Earth science satellite missions, as opposed to planned systems such as the Visible/Infrared Imager/Radiometer (VIIRS) suite of sensors on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) that will collect TIR data at very coarse iairesolutions.

Solutions Network Formulation Report. Visible/Infrared Imager/Radiometer Suite and Landsat Data Continuity Mission Simulated Data Products for the Great Lakes Basin Ecological Team

NASA Technical Reports Server (NTRS)

Estep, Leland

2007-01-01

The proposed solution would simulate VIIRS and LDCM sensor data for use in the USGS/USFWS GLBET DST. The VIIRS sensor possesses a spectral range that provides water-penetrating bands that could be used to assess water clarity on a regional spatial scale. The LDCM sensor possesses suitable spectral bands in a range of wavelengths that could be used to map water quality at finer spatial scales relative to VIIRS. Water quality, alongshore sediment transport and pollutant discharge tracking into the Great Lakes system are targeted as the primary products to be developed. A principal benefit of water quality monitoring via satellite imagery is its economy compared to field-data collection methods. Additionally, higher resolution satellite imagery provides a baseline dataset(s) against which later imagery can be overlaid in GIS-based DST programs. Further, information derived from higher resolution satellite imagery can be used to address public concerns and to confirm environmental compliance. The candidate solution supports the Public Health, Coastal Management, and Water Management National Applications.

Remote Sensing Product Verification and Validation at the NASA Stennis Space Center

NASA Technical Reports Server (NTRS)

Stanley, Thomas M.

2005-01-01

Remote sensing data product verification and validation (V&V) is critical to successful science research and applications development. People who use remote sensing products to make policy, economic, or scientific decisions require confidence in and an understanding of the products' characteristics to make informed decisions about the products' use. NASA data products of coarse to moderate spatial resolution are validated by NASA science teams. NASA's Stennis Space Center (SSC) serves as the science validation team lead for validating commercial data products of moderate to high spatial resolution. At SSC, the Applications Research Toolbox simulates sensors and targets, and the Instrument Validation Laboratory validates critical sensors. The SSC V&V Site consists of radiometric tarps, a network of ground control points, a water surface temperature sensor, an atmospheric measurement system, painted concrete radial target and edge targets, and other instrumentation. NASA's Applied Sciences Directorate participates in the Joint Agency Commercial Imagery Evaluation (JACIE) team formed by NASA, the U.S. Geological Survey, and the National Geospatial-Intelligence Agency to characterize commercial systems and imagery.

Mapping the distribution of mangrove species in the Core Zone of Mai Po Marshes Nature Reserve, Hong Kong, using hyperspectral data and high-resolution data

NASA Astrophysics Data System (ADS)

Jia, Mingming; Zhang, Yuanzhi; Wang, Zongming; Song, Kaishan; Ren, Chunying

2014-12-01

Mangrove species compositions and distributions are essential for conservation and restoration efforts. In this study, hyperspectral data of EO-1 HYPERION sensor and high spatial resolution data of SPOT-5 sensor were used in Mai Po mangrove species mapping. Objected-oriented method was used in mangrove species classification processing. Firstly, mangrove objects were obtained via segmenting high spatial resolution data of SPOT-5. Then the objects were classified into different mangrove species based on the spectral differences of HYPERION image. The classification result showed that in the top canopy, Kandelia obovata and Avicennia marina dominated Mai Po Marshes Natural Reserve, with area of 196.8 ha and 110.8 ha, respectively, Acanthus ilicifolius and Aegiceras corniculatum were mixed together and living at the edge of channels with an area of 11.7 ha. Additionally, mangrove species shows clearly zonations and associations in the Mai Po Core Zone. The overall accuracy of our mangrove map was 88% and the Kappa confidence was 0.83, which indicated great potential of using hyperspectral and high-resolution data for distinguishing and mapping mangrove species.

Fusion of Laser Altimetry Data with Dems Derived from Stereo Imaging Systems

NASA Astrophysics Data System (ADS)

Schenk, T.; Csatho, B. M.; Duncan, K.

2016-06-01

During the last two decades surface elevation data have been gathered over the Greenland Ice Sheet (GrIS) from a variety of different sensors including spaceborne and airborne laser altimetry, such as NASA's Ice Cloud and land Elevation Satellite (ICESat), Airborne Topographic Mapper (ATM) and Laser Vegetation Imaging Sensor (LVIS), as well as from stereo satellite imaging systems, most notably from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Worldview. The spatio-temporal resolution, the accuracy, and the spatial coverage of all these data differ widely. For example, laser altimetry systems are much more accurate than DEMs derived by correlation from imaging systems. On the other hand, DEMs usually have a superior spatial resolution and extended spatial coverage. We present in this paper an overview of the SERAC (Surface Elevation Reconstruction And Change detection) system, designed to cope with the data complexity and the computation of elevation change histories. SERAC simultaneously determines the ice sheet surface shape and the time-series of elevation changes for surface patches whose size depends on the ruggedness of the surface and the point distribution of the sensors involved. By incorporating different sensors, SERAC is a true fusion system that generates the best plausible result (time series of elevation changes) a result that is better than the sum of its individual parts. We follow this up with an example of the Helmheim gacier, involving ICESat, ATM and LVIS laser altimetry data, together with ASTER DEMs.

New technology revolutionizing how we understand the air around us

EPA Science Inventory

This presentation covers various technologies that I have been involved with, that have increased the spatial resolution possible for air pollution measurements. This includes the GMAP, Village Green Project, and emerging sensor technology.

A Simple Downscaling Algorithm for Remotely Sensed Land Surface Temperature

NASA Astrophysics Data System (ADS)

Sandholt, I.; Nielsen, C.; Stisen, S.

2009-05-01

The method is illustrated using a combination of MODIS NDVI data with a spatial resolution of 250m and 3 Km Meteosat Second Generation SEVIRI LST data. Geostationary Earth Observation data carry a large potential for assessment of surface state variables. Not the least the European Meteosat Second Generation platform with its SEVIRI sensor is well suited for studies of the dynamics of land surfaces due to its high temporal frequency (15 minutes) and its red, Near Infrared (NIR) channels that provides vegetation indices, and its two split window channels in the thermal infrared for assessment of Land Surface Temperature (LST). For some applications the spatial resolution in geostationary data is too coarse. Due to the low statial resolution of 4.8 km at nadir for the SEVIRI sensor, a means of providing sub pixel information is sought for. By combining and properly scaling two types of satellite images, namely data from the MODIS sensor onboard the polar orbiting platforms TERRA and AQUA and the coarse resolution MSG-SEVIRI, we exploit the best from two worlds. The vegetation index/surface temperature space has been used in a vast number of studies for assessment of air temperature, soil moisture, dryness indices, evapotranspiration and for studies of land use change. In this paper, we present an improved method to derive a finer resolution Land Surface Temperature (LST). A new, deterministic scaling method has been applied, and is compared to existing deterministic downscaling methods based on LST and NDVI. We also compare our results from in situ measurements of LST from the Dahra test site in West Africa.

Improvements in Virtual Sensors: Using Spatial Information to Estimate Remote Sensing Spectra

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.; Srivastava, Ashok N.; Stroeve, Julienne

2005-01-01

Various instruments are used to create images of the Earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. Sometimes these instruments are built in a phased approach, with additional measurement capabilities added in later phases. In other cases, technology may mature to the point that the instrument offers new measurement capabilities that were not planned in the original design of the instrument. In still other cases, high resolution spectral measurements may be too costly to perform on a large sample and therefore lower resolution spectral instruments are used to take the majority of measurements. Many applied science questions that are relevant to the earth science remote sensing community require analysis of enormous amounts of data that were generated by instruments with disparate measurement capabilities. In past work [1], we addressed this problem using Virtual Sensors: a method that uses models trained on spectrally rich (high spectral resolution) data to "fill in" unmeasured spectral channels in spectrally poor (low spectral resolution) data. We demonstrated this method by using models trained on the high spectral resolution Terra MODIS instrument to estimate what the equivalent of the MODIS 1.6 micron channel would be for the NOAA AVHRR2 instrument. The scientific motivation for the simulation of the 1.6 micron channel is to improve the ability of the AVHRR2 sensor to detect clouds over snow and ice. This work contains preliminary experiments demonstrating that the use of spatial information can improve our ability to estimate these spectra.

Efficient dynamic events discrimination technique for fiber distributed Brillouin sensors.

PubMed

Galindez, Carlos A; Madruga, Francisco J; Lopez-Higuera, Jose M

2011-09-26

A technique to detect real time variations of temperature or strain in Brillouin based distributed fiber sensors is proposed and is investigated in this paper. The technique is based on anomaly detection methods such as the RX-algorithm. Detection and isolation of dynamic events from the static ones are demonstrated by a proper processing of the Brillouin gain values obtained by using a standard BOTDA system. Results also suggest that better signal to noise ratio, dynamic range and spatial resolution can be obtained. For a pump pulse of 5 ns the spatial resolution is enhanced, (from 0.541 m obtained by direct gain measurement, to 0.418 m obtained with the technique here exposed) since the analysis is concentrated in the variation of the Brillouin gain and not only on the averaging of the signal along the time. © 2011 Optical Society of America

Novel Handheld Magnetometer Probe Based on Magnetic Tunnelling Junction Sensors for Intraoperative Sentinel Lymph Node Identification

PubMed Central

Cousins, A.; Balalis, G. L.; Thompson, S. K.; Forero Morales, D.; Mohtar, A.; Wedding, A. B.; Thierry, B.

2015-01-01

Using magnetic tunnelling junction sensors, a novel magnetometer probe for the identification of the sentinel lymph node using magnetic tracers was developed. Probe performance was characterised in vitro and validated in a preclinical swine model. Compared to conventional gamma probes, the magnetometer probe showed excellent spatial resolution of 4.0 mm, and the potential to detect as few as 5 μg of magnetic tracer. Due to the high sensitivity of the magnetometer, all first-tier nodes were identified in the preclinical experiments, and there were no instances of false positive or false negative detection. Furthermore, these preliminary data encourage the application of the magnetometer probe for use in more complex lymphatic environments, such as in gastrointestinal cancers, where the sentinel node is often in close proximity to other non-sentinel nodes, and high spatial resolution detection is required. PMID:26038833

Multi-dimensional water quality assessment of an urban drinking water source elucidated by high resolution underwater towed vehicle mapping.

PubMed

Lock, Alan; Spiers, Graeme; Hostetler, Blair; Ray, James; Wallschläger, Dirk

2016-04-15

Spatial surveys of Ramsey Lake, Sudbury, Ontario water quality were conducted using an innovative underwater towed vehicle (UTV) equipped with a multi-parameter probe providing real-time water quality data. The UTV revealed underwater vent sites through high resolution monitoring of different spatial chemical characteristics using common sensors (turbidity, chloride, dissolved oxygen, and oxidation/reduction sensors) that would not be feasible with traditional water sampling methods. Multi-parameter probe vent site identification is supported by elevated alkalinity and silica concentrations at these sites. The identified groundwater vent sites appear to be controlled by bedrock fractures that transport water from different sources with different contaminants of concern. Elevated contaminants, such as, arsenic and nickel and/or nutrient concentrations are evident at the vent sites, illustrating the potential of these sources to degrade water quality. Copyright © 2016 Elsevier Ltd. All rights reserved.

Propagation phasor approach for holographic image reconstruction

PubMed Central

Luo, Wei; Zhang, Yibo; Göröcs, Zoltán; Feizi, Alborz; Ozcan, Aydogan

2016-01-01

To achieve high-resolution and wide field-of-view, digital holographic imaging techniques need to tackle two major challenges: phase recovery and spatial undersampling. Previously, these challenges were separately addressed using phase retrieval and pixel super-resolution algorithms, which utilize the diversity of different imaging parameters. Although existing holographic imaging methods can achieve large space-bandwidth-products by performing pixel super-resolution and phase retrieval sequentially, they require large amounts of data, which might be a limitation in high-speed or cost-effective imaging applications. Here we report a propagation phasor approach, which for the first time combines phase retrieval and pixel super-resolution into a unified mathematical framework and enables the synthesis of new holographic image reconstruction methods with significantly improved data efficiency. In this approach, twin image and spatial aliasing signals, along with other digital artifacts, are interpreted as noise terms that are modulated by phasors that analytically depend on the lateral displacement between hologram and sensor planes, sample-to-sensor distance, wavelength, and the illumination angle. Compared to previous holographic reconstruction techniques, this new framework results in five- to seven-fold reduced number of raw measurements, while still achieving a competitive resolution and space-bandwidth-product. We also demonstrated the success of this approach by imaging biological specimens including Papanicolaou and blood smears. PMID:26964671

Spatially Resolving Ocean Color and Sediment Dispersion in River Plumes, Coastal Systems, and Continental Shelf Waters

NASA Technical Reports Server (NTRS)

Aurin, Dirk Alexander; Mannino, Antonio; Franz, Bryan

2013-01-01

Satellite remote sensing of ocean color in dynamic coastal, inland, and nearshorewaters is impeded by high variability in optical constituents, demands specialized atmospheric correction, and is limited by instrument sensitivity. To accurately detect dispersion of bio-optical properties, remote sensors require ample signal-to-noise ratio (SNR) to sense small variations in ocean color without saturating over bright pixels, an atmospheric correction that can accommodate significantwater-leaving radiance in the near infrared (NIR), and spatial and temporal resolution that coincides with the scales of variability in the environment. Several current and historic space-borne sensors have met these requirements with success in the open ocean, but are not optimized for highly red-reflective and heterogeneous waters such as those found near river outflows or in the presence of sediment resuspension. Here we apply analytical approaches for determining optimal spatial resolution, dominant spatial scales of variability ("patches"), and proportions of patch variability that can be resolved from four river plumes around the world between 2008 and 2011. An offshore region in the Sargasso Sea is analyzed for comparison. A method is presented for processing Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Terra imagery including cloud detection, stray lightmasking, faulty detector avoidance, and dynamic aerosol correction using short-wave- and near-infrared wavebands in extremely turbid regions which pose distinct optical and technical challenges. Results showthat a pixel size of approx. 520 mor smaller is generally required to resolve spatial heterogeneity in ocean color and total suspended materials in river plumes. Optimal pixel size increases with distance from shore to approx. 630 m in nearshore regions, approx 750 m on the continental shelf, and approx. 1350 m in the open ocean. Greater than 90% of the optical variability within plume regions is resolvable with 500 m resolution, and small, but significant, differences were found between peak and nadir river flow periods in terms of optimal resolution and resolvable proportion of variability.

Single-Image Super Resolution for Multispectral Remote Sensing Data Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Liebel, L.; Körner, M.

2016-06-01

In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN), can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.

EKOSAT/DIAMANT - The Earth Observation Programme at OHB- System

NASA Astrophysics Data System (ADS)

Penne, B.; Tobehn, C.; Kassebom, M.; Luebberstedt

This paper covers the EKOSAT / DIAMANT programme heading for superspectral geo-information products. The EKOSAT / DIAMANT programme is based on a commercial strategy just before the realization of the first step - the EKOSAT launch in 2004. Further, we give an overview on OHB-System earth observation prime activities especially for infrared and radar. The EKOSAT/ DIAMANT is based on the MSRS sensor featuring 12 user dedicated spectral bands in the VIS/NIR with 5m spatial resolution and 26 km swath at an orbit of 670 km. The operational demonstrator mission EKOSAT is a Korean-Israelean-German-Russian initiative that aims in utilizing the existing proto-flight model of the KOMPSAT-1 spacecraft for the MSRS sensor, which development is finished. The EKOSAT pointing capability will allow a revisit time of 3 days. DIAMANT stands for the future full operational system based on dedicated small satellites. The basic constellation relying on 2-3 satellites with about one day revisit is extendend on market demand. EKOSAT/ DIAMANT is designed to fill the gap between modern high spatial resolution multispectral (MS) systems and hyperspectral systems with moderate spatial resolution. On European level, there is currently no remote sensing system operational with comparable features and capabilities concerning applications especially in the field of environmental issues, vegetation, agriculture and water bodies. The Space Segment has been designed to satisfy the user requirements based on a balance between commercial aspects and scientific approaches. For example eight spectral bands have been identified to cover almost the entire product range for the current market. Additional four bands have been implemented to be prepared for future applications as for example the improved red edge detection, which give better results regarding environmental conditions. The spacecraft design and its subsystems are still reasonable small in order to keep the mass below 200 kg. This is an important cost saving approach that surely offers higher viability of the system. The Intelligent Infrared Sensor System - FOCUS - aims at the reliable autonomous on-board detection of High Temperature Events (HTE) on Earth surface. The key to this task is the simultaneous co-registration of a combination of infrared (IR) and visible (VIS) channels. Furthermore there are ecology-oriented objectives mainly related to the sophisticated data fusion of spectrometric &imaging remote inspection and parameter extraction of selected HTEs, and to the assessment of ecological consequences of HTEs, such as aerosol and gas emission. The FOCUS Multi Sensor consists of two sensor systems: The Fore Field Sensor (FFS) will perform the wide-angle hot spot detection and mapping. For the on-board detected and selected hot spots, the Main Sensor (MS) will be targeted with a tiltable mirror and deliver detailed spatial high resolution observation. The MS is composed of an imaging system and a Fourier Spectrometer. The SAR-Lupe satellite system - under development by OHB-System - will generate high resolution SAR- (Synthetic Aperture Radar) images for military reconnaissance purposes. SAR-Lupe relies on a constellation of small satellites in low earth orbit, 1 control and 1 user ground segment.

NDVI, scale invariance and the modifiable areal unit problem: An assessment of vegetation in the Adelaide Parklands.

PubMed

Nouri, Hamideh; Anderson, Sharolyn; Sutton, Paul; Beecham, Simon; Nagler, Pamela; Jarchow, Christopher J; Roberts, Dar A

2017-04-15

This research addresses the question as to whether or not the Normalised Difference Vegetation Index (NDVI) is scale invariant (i.e. constant over spatial aggregation) for pure pixels of urban vegetation. It has been long recognized that there are issues related to the modifiable areal unit problem (MAUP) pertaining to indices such as NDVI and images at varying spatial resolutions. These issues are relevant to using NDVI values in spatial analyses. We compare two different methods of calculation of a mean NDVI: 1) using pixel values of NDVI within feature/object boundaries and 2) first calculating the mean red and mean near-infrared across all feature pixels and then calculating NDVI. We explore the nature and magnitude of these differences for images taken from two sensors, a 1.24m resolution WorldView-3 and a 0.1m resolution digital aerial image. We apply these methods over an urban park located in the Adelaide Parklands of South Australia. We demonstrate that the MAUP is not an issue for calculation of NDVI within a sensor for pure urban vegetation pixels. This may prove useful for future rule-based monitoring of the ecosystem functioning of green infrastructure. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluating an image-fusion algorithm with synthetic-image-generation tools

NASA Astrophysics Data System (ADS)

Gross, Harry N.; Schott, John R.

1996-06-01

An algorithm that combines spectral mixing and nonlinear optimization is used to fuse multiresolution images. Image fusion merges images of different spatial and spectral resolutions to create a high spatial resolution multispectral combination. High spectral resolution allows identification of materials in the scene, while high spatial resolution locates those materials. In this algorithm, conventional spectral mixing estimates the percentage of each material (called endmembers) within each low resolution pixel. Three spectral mixing models are compared; unconstrained, partially constrained, and fully constrained. In the partially constrained application, the endmember fractions are required to sum to one. In the fully constrained application, all fractions are additionally required to lie between zero and one. While negative fractions seem inappropriate, they can arise from random spectral realizations of the materials. In the second part of the algorithm, the low resolution fractions are used as inputs to a constrained nonlinear optimization that calculates the endmember fractions for the high resolution pixels. The constraints mirror the low resolution constraints and maintain consistency with the low resolution fraction results. The algorithm can use one or more higher resolution sharpening images to locate the endmembers to high spatial accuracy. The algorithm was evaluated with synthetic image generation (SIG) tools. A SIG developed image can be used to control the various error sources that are likely to impair the algorithm performance. These error sources include atmospheric effects, mismodeled spectral endmembers, and variability in topography and illumination. By controlling the introduction of these errors, the robustness of the algorithm can be studied and improved upon. The motivation for this research is to take advantage of the next generation of multi/hyperspectral sensors. Although the hyperspectral images will be of modest to low resolution, fusing them with high resolution sharpening images will produce a higher spatial resolution land cover or material map.

The Performance Analysis of Distributed Brillouin Corrosion Sensors for Steel Reinforced Concrete Structures

PubMed Central

Wei, Heming; Zhao, Xuefeng; Kong, Xianglong; Zhang, Pinglei; Cui, Yanjun; Sun, Changsen

2014-01-01

The Brillouin optical time-domain analysis (BOTDA)-based optical fiber method has been proposed to measure strain variations caused by corrosion expansion. Spatial resolutions of 1 m can be achieved with this kind of Brillouin sensor for detecting the distributed strain. However, when the sensing fiber is wound around the steel rebar in a number of circles in a range of several meters, this spatial resolution still has limitations for corrosion monitoring. Here, we employed a low-coherent fiber-optic strain sensor (LCFS) to survey the performance of Brillouin sensors based on the fact that the deformation measured by the LCFS equals the integral of the strains obtained from Brillouin sensors. An electrochemical accelerated corrosion experiment was carried out and the corrosion expansion was monitored by both BOTDA and the LCFS. Results demonstrated that the BOTDA can only measure the expansion strain of about 1,000 με, which was generated by the 18 mm steel rebar corrosion, but, the LCFS had high sensitivity from the beginning of corrosion to the destruction of the structure, and no obvious difference in expansion speed was observed during the acceleration stage of the corrosion developed in the reinforced concrete (RC) specimens. These results proved that the BOTDA method could only be employed to monitor the corrosion inside the structure in the early stage. PMID:24379048

The performance analysis of distributed Brillouin corrosion sensors for steel reinforced concrete structures.

PubMed

Wei, Heming; Zhao, Xuefeng; Kong, Xianglong; Zhang, Pinglei; Cui, Yanjun; Sun, Changsen

2013-12-27

The Brillouin optical time-domain analysis (BOTDA)-based optical fiber method has been proposed to measure strain variations caused by corrosion expansion. Spatial resolutions of 1 m can be achieved with this kind of Brillouin sensor for detecting the distributed strain. However, when the sensing fiber is wound around the steel rebar in a number of circles in a range of several meters, this spatial resolution still has limitations for corrosion monitoring. Here, we employed a low-coherent fiber-optic strain sensor (LCFS) to survey the performance of Brillouin sensors based on the fact that the deformation measured by the LCFS equals the integral of the strains obtained from Brillouin sensors. An electrochemical accelerated corrosion experiment was carried out and the corrosion expansion was monitored by both BOTDA and the LCFS. Results demonstrated that the BOTDA can only measure the expansion strain of about 1,000 με, which was generated by the 18 mm steel rebar corrosion, but, the LCFS had high sensitivity from the beginning of corrosion to the destruction of the structure, and no obvious difference in expansion speed was observed during the acceleration stage of the corrosion developed in the reinforced concrete (RC) specimens. These results proved that the BOTDA method could only be employed to monitor the corrosion inside the structure in the early stage.

x-y curvature wavefront sensor.

PubMed

Cagigal, Manuel P; Valle, Pedro J

2015-04-15

In this Letter, we propose a new curvature wavefront sensor based on the principles of optical differentiation. The theoretically modeled setup consists of a diffractive optical mask placed at the intermediate plane of a classical two-lens coherent optical processor. The resulting image is composed of a number of local derivatives of the entrance pupil function whose proper combination provides the wavefront curvature. In contrast to the common radial curvature sensors, this one is able to provide the x and y wavefront curvature maps simultaneously. The sensor offers other additional advantages like having high spatial resolution, adjustable dynamic range, and not being sensitive to misalignment.

CAOS: the nested catchment soil-vegetation-atmosphere observation platform

NASA Astrophysics Data System (ADS)

Weiler, Markus; Blume, Theresa

2016-04-01

Most catchment based observations linking hydrometeorology, ecohydrology, soil hydrology and hydrogeology are typically not integrated with each other and lack a consistent and appropriate spatial-temporal resolution. Within the research network CAOS (Catchments As Organized Systems), we have initiated and developed a novel and integrated observation platform in several catchments in Luxembourg. In 20 nested catchments covering three distinct geologies the subscale processes at the bedrock-soil-vegetation-atmosphere interface are being monitored at 46 sensor cluster locations. Each sensor cluster is designed to observe a variety of different fluxes and state variables above and below ground, in the saturated and unsaturated zone. The numbers of sensors are chosen to capture the spatial variability as well the average dynamics. At each of these sensor clusters three soil moisture profiles with sensors at different depths, four soil temperature profiles as well as matric potential, air temperature, relative humidity, global radiation, rainfall/throughfall, sapflow and shallow groundwater and stream water levels are measured continuously. In addition, most sensors also measure temperature (water, soil, atmosphere) and electrical conductivity. This setup allows us to determine the local water and energy balance at each of these sites. The discharge gauging sites in the nested catchments are also equipped with automatic water samplers to monitor water quality and water stable isotopes continuously. Furthermore, water temperature and electrical conductivity observations are extended to over 120 locations distributed across the entire stream network to capture the energy exchange between the groundwater, stream water and atmosphere. The measurements at the sensor clusters are complemented by hydrometeorological observations (rain radar, network of distrometers and dense network of precipitation gauges) and linked with high resolution meteorological models. In this presentation, we will highlight the potential of this integrated observation platform to estimate energy and water exchange between the terrestrial and aquatic systems and the atmosphere, to trace water flow pathways in the unsaturated and saturated zone, and to understand the organization of processes and fluxes and thus runoff generation at different temporal and spatial scales.

Spatial and spectral resolution necessary for remotely sensed vegetation studies

NASA Technical Reports Server (NTRS)

Rock, B. N.

1982-01-01

An outline is presented of the required spatial and spectral resolution needed for accurate vegetation discrimination and mapping studies as well as for determination of state of health (i.e., detection of stress symptoms) of actively growing vegetation. Good success was achieved in vegetation discrimination and mapping of a heterogeneous forest cover in the ridge and valley portion of the Appalachians using multispectral data acquired with a spatial resolution of 15 m (IFOV). A sensor system delivering 10 to 15 m spatial resolution is needed for both vegetation mapping and detection of stress symptoms. Based on the vegetation discrimination and mapping exercises conducted at the Lost River site, accurate products (vegetation maps) are produced using broad-band spectral data ranging from the .500 to 2.500 micron portion of the spectrum. In order of decreasing utility for vegetation discrimination, the four most valuable TM simulator VNIR bands are: 6 (1.55 to 1.75 microns), 3 (0.63 to 0.69 microns), 5 (1.00 to 1.30 microns) and 4 (0.76 to 0.90 microns).

MOS Circuitry Would Detect Low-Energy Charged Particles

NASA Technical Reports Server (NTRS)

Sinha, Mahadeva; Wadsworth, Mark

2003-01-01

Metal oxide semiconductor (MOS) circuits for measuring spatially varying intensities of beams of low-energy charged particles have been developed. These circuits are intended especially for use in measuring fluxes of ions with spatial resolution along the focal planes of mass spectrometers. Unlike prior mass spectrometer focal-plane detectors, these MOS circuits would not be based on ion-induced generation of electrons, and photons; instead, they would be based on direct detection of the electric charges of the ions. Hence, there would be no need for microchannel plates (for ion-to-electron conversion), phosphors (for electron-to-photon conversion), and photodetectors (for final detection) -- components that degrade spatial resolution and contribute to complexity and size. The developmental circuits are based on linear arrays of charge-coupled devices (CCDs) with associated readout circuitry (see figure). They resemble linear CCD photodetector arrays, except that instead of a photodetector, each pixel contains a capacitive charge sensor. The capacitor in each sensor comprises two electrodes (typically made of aluminum) separated by a layer of insulating material. The exposed electrode captures ions and accumulates their electric charges during signal-integration periods.

Improving spatial resolution in skin-contact thermography: comparison between a spline based and linear interpolation.

PubMed

Giansanti, Daniele

2008-07-01

A wearable device for skin-contact thermography [Giansanti D, Maccioni G. Development and testing of a wearable integrated thermometer sensor for skin contact thermography. Med Eng Phys 2006 [ahead of print

Optical signal processing of spatially distributed sensor data in smart structures

NASA Technical Reports Server (NTRS)

Bennett, K. D.; Claus, R. O.; Murphy, K. A.; Goette, A. M.

1989-01-01

Smart structures which contain dense two- or three-dimensional arrays of attached or embedded sensor elements inherently require signal multiplexing and processing capabilities to permit good spatial data resolution as well as the adequately short calculation times demanded by real time active feedback actuator drive circuitry. This paper reports the implementation of an in-line optical signal processor and its application in a structural sensing system which incorporates multiple discrete optical fiber sensor elements. The signal processor consists of an array of optical fiber couplers having tailored s-parameters and arranged to allow gray code amplitude scaling of sensor inputs. The use of this signal processor in systems designed to indicate the location of distributed strain and damage in composite materials, as well as to quantitatively characterize that damage, is described. Extension of similar signal processing methods to more complicated smart materials and structures applications are discussed.

A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light

PubMed Central

Yao, Huimin; Ge, Chenyang; Xue, Jianru; Zheng, Nanning

2017-01-01

Depth information has been used in many fields because of its low cost and easy availability, since the Microsoft Kinect was released. However, the Kinect and Kinect-like RGB-D sensors show limited performance in certain applications and place high demands on accuracy and robustness of depth information. In this paper, we propose a depth sensing system that contains a laser projector similar to that used in the Kinect, and two infrared cameras located on both sides of the laser projector, to obtain higher spatial resolution depth information. We apply the block-matching algorithm to estimate the disparity. To improve the spatial resolution, we reduce the size of matching blocks, but smaller matching blocks generate lower matching precision. To address this problem, we combine two matching modes (binocular mode and monocular mode) in the disparity estimation process. Experimental results show that our method can obtain higher spatial resolution depth without loss of the quality of the range image, compared with the Kinect. Furthermore, our algorithm is implemented on a low-cost hardware platform, and the system can support the resolution of 1280 × 960, and up to a speed of 60 frames per second, for depth image sequences. PMID:28397759

Application of Geostatistical Simulation to Enhance Satellite Image Products

NASA Technical Reports Server (NTRS)

Hlavka, Christine A.; Dungan, Jennifer L.; Thirulanambi, Rajkumar; Roy, David

2004-01-01

With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.

Development of a Dual-PIV system for high-speed flow applications

NASA Astrophysics Data System (ADS)

Schreyer, Anne-Marie; Lasserre, Jean J.; Dupont, Pierre

2015-10-01

A new Dual-particle image velocimetry (Dual-PIV) system for application in supersonic flows was developed. The system was designed for shock wave/turbulent boundary layer interactions with separation. This type of flow places demanding requirements on the system, from the large range of characteristic frequencies O(100 Hz-100 kHz) to spatial and temporal resolutions necessary for the measurement of turbulent quantities (Dolling in AIAA J 39(8):1517-1531, 2001; Dupont et al. in J Fluid Mech 559:255-277, 2006; Smits and Dussauge in Turbulent shear layers in supersonic flow, 2nd edn. Springer, New York, 2006). While classic PIV systems using high-resolution CCD sensors allow high spatial resolution, these systems cannot provide the required temporal resolution. Existing high-speed PIV systems provide temporal and CMOS sensor resolutions, and even laser pulse energies, that are not adapted to our needs. The only obvious solution allowing sufficiently high spatial resolution, access to high frequencies, and a high laser pulse energy is a multi-frame system: a Dual-PIV system, consisting of two synchronized PIV systems observing the same field of view, will give access to temporal characteristics of the flow. The key technology of our system is frequency-based image separation: two lasers of different wavelengths illuminate the field of view. The cross-pollution with laser light from the respective other branches was quantified during system validation. The overall system noise was quantified, and the prevailing error of only 2 % reflects the good spatial and temporal alignment. The quality of the measurement system is demonstrated with some results on a subsonic jet flow including the spatio-temporal inter-correlation functions between the systems. First measurements in a turbulent flat-plate boundary layer at Mach 2 show the same satisfactory data quality and are also presented and discussed.

Towards a real-time wide area motion imagery system

NASA Astrophysics Data System (ADS)

Young, R. I.; Foulkes, S. B.

2015-10-01

It is becoming increasingly important in both the defence and security domains to conduct persistent wide area surveillance (PWAS) of large populations of targets. Wide Area Motion Imagery (WAMI) is a key technique for achieving this wide area surveillance. The recent development of multi-million pixel sensors has provided sensors with wide field of view replete with sufficient resolution for detection and tracking of objects of interest to be achieved across these extended areas of interest. WAMI sensors simultaneously provide high spatial and temporal resolutions, giving extreme pixel counts over large geographical areas. The high temporal resolution is required to enable effective tracking of targets. The provision of wide area coverage with high frame rates generates data deluge issues; these are especially profound if the sensor is mounted on an airborne platform, with finite data-link bandwidth and processing power that is constrained by size, weight and power (SWAP) limitations. These issues manifest themselves either as bottlenecks in the transmission of the imagery off-board or as latency in the time taken to analyse the data due to limited computational processing power.

Multiplexed 3D FRET imaging in deep tissue of live embryos

PubMed Central

Zhao, Ming; Wan, Xiaoyang; Li, Yu; Zhou, Weibin; Peng, Leilei

2015-01-01

Current deep tissue microscopy techniques are mostly restricted to intensity mapping of fluorophores, which significantly limit their applications in investigating biochemical processes in vivo. We present a deep tissue multiplexed functional imaging method that probes multiple Förster resonant energy transfer (FRET) sensors in live embryos with high spatial resolution. The method simultaneously images fluorescence lifetimes in 3D with multiple excitation lasers. Through quantitative analysis of triple-channel intensity and lifetime images, we demonstrated that Ca2+ and cAMP levels of live embryos expressing dual FRET sensors can be monitored simultaneously at microscopic resolution. The method is compatible with a broad range of FRET sensors currently available for probing various cellular biochemical functions. It opens the door to imaging complex cellular circuitries in whole live organisms. PMID:26387920

Satellite-Derived Sea Surface Temperature: Workshop-2

NASA Technical Reports Server (NTRS)

Njoku, E. G.

1984-01-01

Global accuracies and error characteristics of presently orbiting satellite sensors are examined. The workshops are intended to lead to a better understanding of present capabilities for sea surface temperature measurement and to improve measurement concepts for the future. Data from the Advanced Very High Resolution Radiometer AVHRR and Scanning Multichannel Microwave Radiometer is emphasized. Some data from the High Resolution Infrared Sounder HIRS and AVHRR are also examined. Comparisons of satellite data with ship and eXpendable BathyThermograph XBT measurement show standard deviations in the range 0.5 to 1.3 C with biases of less than 0.4 C, depending on the sensor, ocean region, and spatial/temporal averaging. The Sea Surface Temperature SST anomaly maps show good agreement in some cases, but a number of sensor related problems are identified.

All-optical endoscopic probe for high resolution 3D photoacoustic tomography

NASA Astrophysics Data System (ADS)

Ansari, R.; Zhang, E.; Desjardins, A. E.; Beard, P. C.

2017-03-01

A novel all-optical forward-viewing photoacoustic probe using a flexible coherent fibre-optic bundle and a Fabry- Perot (FP) ultrasound sensor has been developed. The fibre bundle, along with the FP sensor at its distal end, synthesizes a high density 2D array of wideband ultrasound detectors. Photoacoustic waves arriving at the sensor are spatially mapped by optically scanning the proximal end face of the bundle in 2D with a CW wavelength-tunable interrogation laser. 3D images are formed from the detected signals using a time-reversal image reconstruction algorithm. The system has been characterized in terms of its PSF, noise-equivalent pressure and field of view. Finally, the high resolution 3D imaging capability has been demonstrated using arbitrary shaped phantoms and duck embryo.

Role of Satellite Sensors in Groundwater Exploration

PubMed Central

Mukherjee, Saumitra

2008-01-01

Spatial as well as spectral resolution has a very important role to play in water resource management. It was a challenge to explore the groundwater and rainwater harvesting sites in the Aravalli Quartzite-Granite-Pegmatite Precambrian terrain of Delhi, India. Use of only panchromatic sensor data of IRS-1D satellite with 5.8-meter spatial resolution has the potential to infer lineaments and faults in this hard rock area. It is essential to identify the location of interconnected lineaments below buried pediment plains in the hard rock area for targeting sub-surface water resources. Linear Image Self Scanning sensor data of the same satellite with 23.5-meter resolution when merged with the panchromatic data has produced very good results in delineation of interconnected lineaments over buried pediment plains as vegetation anomaly. These specific locations of vegetation anomaly were detected as dark red patches in various hard rock areas of Delhi. Field investigation was carried out on these patches by resistivity and magnetic survey in parts of Jawaharlal Nehru University (JNU), Indira Gandhi national Open University, Research and Referral Hospital and Humayuns Tomb areas. Drilling was carried out in four locations of JNU that proved to be the most potential site with ground water discharge ranging from 20,000 to 30,000 liters per hour with 2 to 4 meters draw down. Further the impact of urbanization on groundwater recharging in the terrain was studied by generating Normalized difference Vegetation Index (NDVI) map which was possible to generate by using the LISS-III sensor of IRS-1D satellite. Selection of suitable sensors has definitely a cutting edge on natural resource exploration and management including groundwater. PMID:27879808

Acoustic Sensing of Ocean Turbulence

DTIC Science & Technology

1991-12-01

quantities and of fast varying quantities, requiring high spatial resolution, fast response sensors and stable observation platforms. A classical approach to...with this type of sensor . Moum et.al. [Ref.l0] performed upper ocean observations with this instrument where they were able to 60 characterize the fine...platform orientation using the 3 axis accelerometer as tiltmeters . E. NON-ACOUSTIC DATA The non-acoustic channels on the CDV package are: 3 component

Commercial Applications Multispectral Sensor System

NASA Technical Reports Server (NTRS)

Birk, Ronald J.; Spiering, Bruce

1993-01-01

NASA's Office of Commercial Programs is funding a multispectral sensor system to be used in the development of remote sensing applications. The Airborne Terrestrial Applications Sensor (ATLAS) is designed to provide versatility in acquiring spectral and spatial information. The ATLAS system will be a test bed for the development of specifications for airborne and spaceborne remote sensing instrumentation for dedicated applications. This objective requires spectral coverage from the visible through thermal infrared wavelengths, variable spatial resolution from 2-25 meters; high geometric and geo-location accuracy; on-board radiometric calibration; digital recording; and optimized performance for minimized cost, size, and weight. ATLAS is scheduled to be available in 3rd quarter 1992 for acquisition of data for applications such as environmental monitoring, facilities management, geographic information systems data base development, and mineral exploration.

Development of high-resolution (250 m) historical daily gridded air temperature data using reanalysis and distributed sensor networks for the US northern Rocky Mountains

Treesearch

Zachary A. Holden; Alan Swanson; Anna E. Klene; John T. Abatzoglou; Solomon Z. Dobrowski; Samuel A. Cushman; John Squires; Gretchen G. Moisen; Jared W. Oyler

2016-01-01

Gridded temperature data sets are typically produced at spatial resolutions that cannot fully resolve fine-scale variation in surface air temperature in regions of complex topography. These data limitations have become increasingly important as scientists and managers attempt to understand and plan for potential climate change impacts. Here, we describe the...

Bayesian model for matching the radiometric measurements of aerospace and field ocean color sensors.

PubMed

Salama, Mhd Suhyb; Su, Zhongbo

2010-01-01

A Bayesian model is developed to match aerospace ocean color observation to field measurements and derive the spatial variability of match-up sites. The performance of the model is tested against populations of synthesized spectra and full and reduced resolutions of MERIS data. The model derived the scale difference between synthesized satellite pixel and point measurements with R(2) > 0.88 and relative error < 21% in the spectral range from 400 nm to 695 nm. The sub-pixel variabilities of reduced resolution MERIS image are derived with less than 12% of relative errors in heterogeneous region. The method is generic and applicable to different sensors.

Optical fiber distributed temperature sensor in cardiological surgeries

NASA Astrophysics Data System (ADS)

Skapa, Jan; Látal, Jan; Penhaker, Marek; Koudelka, Petr; Hancek, František; Vasinek, Vladimír

2010-04-01

In those days a lot of cardiological surgeries is made every day. It is a matter of very significant importance keeping the temperature of the hearth low during the surgery because it decides whether the cells of the muscle will die or not. The hearth is cooled by the ice placed around the hearth muscle during the surgery and cooling liquid is injected into the hearth also. In these days the temperature is measured only in some points of the hearth using sensors based on the pH measurements. This article describes new method for measurement of temperature of the hearth muscle during the cardiological surgery. We use a multimode optical fiber and distributed temperature sensor (DTS) based on the stimulated Raman scattering in temperature measurements. This principle allows us to measure the temperature and to determine where the temperature changes during the surgery. Resolution in the temperature is about 0.1 degrees of Celsius. Resolution in length is about 1 meter. The resolution in length implies that the fiber must be wound to ensure the spatial resolution about 5 by 5 centimeters.

Global Monitoring of Air Pollution Using Spaceborne Sensors

NASA Technical Reports Server (NTRS)

Chu, D. A.; Kaufman, Y. J.; Tanre, D.; Remer, L. A.; Einaudi, Franco (Technical Monitor)

2000-01-01

The MODIS sensor onboard EOS-Terra satellite provides not only daily global coverage but also high spectral (36 channels from 0.41 to 14 microns wavelength) and spatial (250m, 500m and 1km) resolution measurements. A similar MODIS instrument will be also configured into EOS-Aqua satellite to be launched soon. Using the complementary EOS-Terra and EOS-Aqua sun-synchronous orbits (10:30 AM and 1:30 PM equator-crossing time respectively), it enables us also to study the diurnal changes of the Earth system. It is unprecedented for the derivation of aerosol properties with such high spatial resolution and daily global converge. Aerosol optical depth and other aerosol properties, e.g., Angstrom coefficient over land and particle size over ocean, are derived as standard products at a spatial resolution of 10 x 10 sq km. The high resolution results are found surprisingly useful in detecting aerosols in both urban and rural regions as a result of urban/industrial pollution and biomass burning. For long-lived aerosols, the ability to monitoring the evolution of these aerosol events could help us to establish an system of air quality especially for highly populated areas. Aerosol scenarios with city pollution and biomass burning will be presented. Also presented are the method used in the derivation of aerosol optical properties and preliminary results will be presented, and issue as well as obstacles in validating aerosol optical depth with AERONET ground-based observations.

Land cover mapping at sub-pixel scales

NASA Astrophysics Data System (ADS)

Makido, Yasuyo Kato

One of the biggest drawbacks of land cover mapping from remotely sensed images relates to spatial resolution, which determines the level of spatial details depicted in an image. Fine spatial resolution images from satellite sensors such as IKONOS and QuickBird are now available. However, these images are not suitable for large-area studies, since a single image is very small and therefore it is costly for large area studies. Much research has focused on attempting to extract land cover types at sub-pixel scale, and little research has been conducted concerning the spatial allocation of land cover types within a pixel. This study is devoted to the development of new algorithms for predicting land cover distribution using remote sensory imagery at sub-pixel level. The "pixel-swapping" optimization algorithm, which was proposed by Atkinson for predicting sub-pixel land cover distribution, is investigated in this study. Two limitations of this method, the arbitrary spatial range value and the arbitrary exponential model of spatial autocorrelation, are assessed. Various weighting functions, as alternatives to the exponential model, are evaluated in order to derive the optimum weighting function. Two different simulation models were employed to develop spatially autocorrelated binary class maps. In all tested models, Gaussian, Exponential, and IDW, the pixel swapping method improved classification accuracy compared with the initial random allocation of sub-pixels. However the results suggested that equal weight could be used to increase accuracy and sub-pixel spatial autocorrelation instead of using these more complex models of spatial structure. New algorithms for modeling the spatial distribution of multiple land cover classes at sub-pixel scales are developed and evaluated. Three methods are examined: sequential categorical swapping, simultaneous categorical swapping, and simulated annealing. These three methods are applied to classified Landsat ETM+ data that has been resampled to 210 meters. The result suggested that the simultaneous method can be considered as the optimum method in terms of accuracy performance and computation time. The case study employs remote sensing imagery at the following sites: tropical forests in Brazil and temperate multiple land mosaic in East China. Sub-areas for both sites are used to examine how the characteristics of the landscape affect the ability of the optimum technique. Three types of measurement: Moran's I, mean patch size (MPS), and patch size standard deviation (STDEV), are used to characterize the landscape. All results suggested that this technique could increase the classification accuracy more than traditional hard classification. The methods developed in this study can benefit researchers who employ coarse remote sensing imagery but are interested in detailed landscape information. In many cases, the satellite sensor that provides large spatial coverage has insufficient spatial detail to identify landscape patterns. Application of the super-resolution technique described in this dissertation could potentially solve this problem by providing detailed land cover predictions from the coarse resolution satellite sensor imagery.

Electron-bombarded CCD detectors for ultraviolet atmospheric remote sensing

NASA Technical Reports Server (NTRS)

Carruthers, G. R.; Opal, C. B.

1983-01-01

Electronic image sensors based on charge coupled devices operated in electron-bombarded mode, yielding real-time, remote-readout, photon-limited UV imaging capability are being developed. The sensors also incorporate fast-focal-ratio Schmidt optics and opaque photocathodes, giving nearly the ultimate possible diffuse-source sensitivity. They can be used for direct imagery of atmospheric emission phenomena, and for imaging spectrography with moderate spatial and spectral resolution. The current state of instrument development, laboratory results, planned future developments and proposed applications of the sensors in space flight instrumentation is described.

Wavelength-division and spatial multiplexing using tandem interferometers for Bragg grating sensor networks

NASA Astrophysics Data System (ADS)

Kalli, K.; Brady, G. P.; Webb, D. J.; Jackson, D. A.; Zhang, L.; Bennion, I.

1995-12-01

We present a new method for the interrogation of large arrays of Bragg grating sensors. Eight gratings operating between the wavelengths of 1533 and 1555 nm have been demultiplexed. An unbalanced Mach-Zehnder interferometer illuminated by a single low-coherence source provides a high-phase-resolution output for each sensor, the outputs of which are sequentially selected in wavelength by a tunable Fabry-Perot interferometer. The minimum detectable strain measured was 90 n 3 / \\radical Hz \\end-radical at 7 Hz for a wavelength of 1535 nm.

Microfabricated optically pumped magnetometer arrays for biomedical imaging

NASA Astrophysics Data System (ADS)

Perry, A. R.; Sheng, D.; Krzyzewski, S. P.; Geller, S.; Knappe, S.

2017-02-01

Optically-pumped magnetometers have demonstrated magnetic field measurements as precise as the best superconducting quantum interference device magnetometers. Our group develops miniature alkali atom-based magnetic sensors using microfabrication technology. Our sensors do not require cryogenic cooling, and can be positioned very close to the sample, making these sensors an attractive option for development in the medical community. We will present our latest chip-scale optically-pumped gradiometer developed for array applications to image magnetic fields from the brain noninvasively. These developments should lead to improved spatial resolution, and potentially sensitive measurements in unshielded environments.

Wavefront sensor-driven variable-geometry pupil for ground-based aperture synthesis imaging

NASA Astrophysics Data System (ADS)

Tyler, David W.

2000-07-01

I describe a variable-geometry pupil (VGP) to increase image resolution for ground-based near-IR and optical imaging. In this scheme, a curvature-type wavefront sensor provides an estimate of the wavefront curvature to the controller of a high-resolution spatial light modulator (SLM) or micro- electromechanical (MEM) mirror, positioned at an image of the telescope pupil. This optical element, the VGP, passes or reflects the incident beam only where the wavefront phase is sufficiently smooth, viz., where the curvature is sufficiently low. Using a computer simulation, I show the VGP can sharpen and smooth the long-exposure PSF and increase the OTF SNR for tilt-only and low-order AO systems, allowing higher resolution and more stable deconvolution with dimmer AO guidestars.

Detecting tents to estimate the displaced populations for post-disaster relief using high resolution satellite imagery

NASA Astrophysics Data System (ADS)

Wang, Shifeng; So, Emily; Smith, Pete

2015-04-01

Estimating the number of refugees and internally displaced persons is important for planning and managing an efficient relief operation following disasters and conflicts. Accurate estimates of refugee numbers can be inferred from the number of tents. Extracting tents from high-resolution satellite imagery has recently been suggested. However, it is still a significant challenge to extract tents automatically and reliably from remote sensing imagery. This paper describes a novel automated method, which is based on mathematical morphology, to generate a camp map to estimate the refugee numbers by counting tents on the camp map. The method is especially useful in detecting objects with a clear shape, size, and significant spectral contrast with their surroundings. Results for two study sites with different satellite sensors and different spatial resolutions demonstrate that the method achieves good performance in detecting tents. The overall accuracy can be up to 81% in this study. Further improvements should be possible if over-identified isolated single pixel objects can be filtered. The performance of the method is impacted by spectral characteristics of satellite sensors and image scenes, such as the extent of area of interest and the spatial arrangement of tents. It is expected that the image scene would have a much higher influence on the performance of the method than the sensor characteristics.

Extracting and compensating dispersion mismatch in ultrahigh-resolution Fourier domain OCT imaging of the retina

PubMed Central

Choi, WooJhon; Baumann, Bernhard; Swanson, Eric A.; Fujimoto, James G.

2012-01-01

We present a numerical approach to extract the dispersion mismatch in ultrahigh-resolution Fourier domain optical coherence tomography (OCT) imaging of the retina. The method draws upon an analogy with a Shack-Hartmann wavefront sensor. By exploiting mathematical similarities between the expressions for aberration in optical imaging and dispersion mismatch in spectral / Fourier domain OCT, Shack-Hartmann principles can be extended from the two-dimensional paraxial wavevector space (or the x-y plane in the spatial domain) to the one-dimensional wavenumber space (or the z-axis in the spatial domain). For OCT imaging of the retina, different retinal layers, such as the retinal nerve fiber layer (RNFL), the photoreceptor inner and outer segment junction (IS/OS), or all the retinal layers near the retinal pigment epithelium (RPE) can be used as point source beacons in the axial direction, analogous to point source beacons used in conventional two-dimensional Shack-Hartman wavefront sensors for aberration characterization. Subtleties regarding speckle phenomena in optical imaging, which affect the Shack-Hartmann wavefront sensor used in adaptive optics, also occur analogously in this application. Using this approach and carefully suppressing speckle, the dispersion mismatch in spectral / Fourier domain OCT retinal imaging can be successfully extracted numerically and used for numerical dispersion compensation to generate sharper, ultrahigh-resolution OCT images. PMID:23187353

Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands, USA

USGS Publications Warehouse

Boyte, Stephen; Wylie, Bruce K.; Rigge, Matthew B.; Dahal, Devendra

2018-01-01

Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R2 values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.

Imaging performance of a Timepix detector based on semi-insulating GaAs

NASA Astrophysics Data System (ADS)

Zaťko, B.; Zápražný, Z.; Jakůbek, J.; Šagátová, A.; Boháček, P.; Sekáčová, M.; Korytár, D.; Nečas, V.; Žemlička, J.; Mora, Y.; Pichotka, M.

2018-01-01

This work focused on a Timepix chip [1] coupled with a bulk semi-insulating GaAs sensor. The sensor consisted of a matrix of 256 × 256 pixels with a pitch of 55 μm bump-bonded to a Timepix ASIC. The sensor was processed on a 350 μm-thick SI GaAs wafer. We carried out detector adjustment to optimize its performance. This included threshold equalization with setting up parameters of the Timepix chip, such as Ikrum, Pream, Vfbk, and so on. The energy calibration of the GaAs Timepix detector was realized using a 241Am radioisotope in two Timepix detector modes: time-over-threshold and threshold scan. An energy resolution of 4.4 keV in FWHM (Full Width at Half Maximum) was observed for 59.5 keV γ-photons using threshold scan mode. The X-ray imaging quality of the GaAs Timepix detector was tested using various samples irradiated by an X-ray source with a focal spot size smaller than 8 μm and accelerating voltage up to 80 kV. A 700 μm × 700 μm gold testing object (X-500-200-16Au with Siemens star) fabricated with high precision was used for the spatial resolution testing at different values of X-ray image magnification (up to 45). The measured spatial resolution of our X-ray imaging system was about 4 μm.

Performance study of double SOI image sensors

NASA Astrophysics Data System (ADS)

Miyoshi, T.; Arai, Y.; Fujita, Y.; Hamasaki, R.; Hara, K.; Ikegami, Y.; Kurachi, I.; Nishimura, R.; Ono, S.; Tauchi, K.; Tsuboyama, T.; Yamada, M.

2018-02-01

Double silicon-on-insulator (DSOI) sensors composed of two thin silicon layers and one thick silicon layer have been developed since 2011. The thick substrate consists of high resistivity silicon with p-n junctions while the thin layers are used as SOI-CMOS circuitry and as shielding to reduce the back-gate effect and crosstalk between the sensor and the circuitry. In 2014, a high-resolution integration-type pixel sensor, INTPIX8, was developed based on the DSOI concept. This device is fabricated using a Czochralski p-type (Cz-p) substrate in contrast to a single SOI (SSOI) device having a single thin silicon layer and a Float Zone p-type (FZ-p) substrate. In the present work, X-ray spectra of both DSOI and SSOI sensors were obtained using an Am-241 radiation source at four gain settings. The gain of the DSOI sensor was found to be approximately three times that of the SSOI device because the coupling capacitance is reduced by the DSOI structure. An X-ray imaging demonstration was also performed and high spatial resolution X-ray images were obtained.

Merging climate and multi-sensor time-series data in real-time drought monitoring across the U.S.A.

USGS Publications Warehouse

Brown, Jesslyn F.; Miura, T.; Wardlow, B.; Gu, Yingxin

2011-01-01

Droughts occur repeatedly in the United States resulting in billions of dollars of damage. Monitoring and reporting on drought conditions is a necessary function of government agencies at multiple levels. A team of Federal and university partners developed a drought decision- support tool with higher spatial resolution relative to traditional climate-based drought maps. The Vegetation Drought Response Index (VegDRI) indicates general canopy vegetation condition assimilation of climate, satellite, and biophysical data via geospatial modeling. In VegDRI, complementary drought-related data are merged to provide a comprehensive, detailed representation of drought stress on vegetation. Time-series data from daily polar-orbiting earth observing systems [Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS)] providing global measurements of land surface conditions are ingested into VegDRI. Inter-sensor compatibility is required to extend multi-sensor data records; thus, translations were developed using overlapping observations to create consistent, long-term data time series. 

A bio-image sensor for simultaneous detection of multi-neurotransmitters.

PubMed

Lee, You-Na; Okumura, Koichi; Horio, Tomoko; Iwata, Tatsuya; Takahashi, Kazuhiro; Hattori, Toshiaki; Sawada, Kazuaki

2018-03-01

We report here a new bio-image sensor for simultaneous detection of spatial and temporal distribution of multi-neurotransmitters. It consists of multiple enzyme-immobilized membranes on a 128 × 128 pixel array with read-out circuit. Apyrase and acetylcholinesterase (AChE), as selective elements, are used to recognize adenosine 5'-triphosphate (ATP) and acetylcholine (ACh), respectively. To enhance the spatial resolution, hydrogen ion (H + ) diffusion barrier layers are deposited on top of the bio-image sensor and demonstrated their prevention capability. The results are used to design the space among enzyme-immobilized pixels and the null H + sensor to minimize the undesired signal overlap by H + diffusion. Using this bio-image sensor, we can obtain H + diffusion-independent imaging of concentration gradients of ATP and ACh in real-time. The sensing characteristics, such as sensitivity and detection of limit, are determined experimentally. With the proposed bio-image sensor the possibility exists for customizable monitoring of the activities of various neurochemicals by using different kinds of proton-consuming or generating enzymes. Copyright © 2017 Elsevier B.V. All rights reserved.

Resolution enhancement in integral microscopy by physical interpolation.

PubMed

Llavador, Anabel; Sánchez-Ortiga, Emilio; Barreiro, Juan Carlos; Saavedra, Genaro; Martínez-Corral, Manuel

2015-08-01

Integral-imaging technology has demonstrated its capability for computing depth images from the microimages recorded after a single shot. This capability has been shown in macroscopic imaging and also in microscopy. Despite the possibility of refocusing different planes from one snap-shot is crucial for the study of some biological processes, the main drawback in integral imaging is the substantial reduction of the spatial resolution. In this contribution we report a technique, which permits to increase the two-dimensional spatial resolution of the computed depth images in integral microscopy by a factor of √2. This is made by a double-shot approach, carried out by means of a rotating glass plate, which shifts the microimages in the sensor plane. We experimentally validate the resolution enhancement as well as we show the benefit of applying the technique to biological specimens.

Resolution enhancement in integral microscopy by physical interpolation

PubMed Central

Llavador, Anabel; Sánchez-Ortiga, Emilio; Barreiro, Juan Carlos; Saavedra, Genaro; Martínez-Corral, Manuel

2015-01-01

Integral-imaging technology has demonstrated its capability for computing depth images from the microimages recorded after a single shot. This capability has been shown in macroscopic imaging and also in microscopy. Despite the possibility of refocusing different planes from one snap-shot is crucial for the study of some biological processes, the main drawback in integral imaging is the substantial reduction of the spatial resolution. In this contribution we report a technique, which permits to increase the two-dimensional spatial resolution of the computed depth images in integral microscopy by a factor of √2. This is made by a double-shot approach, carried out by means of a rotating glass plate, which shifts the microimages in the sensor plane. We experimentally validate the resolution enhancement as well as we show the benefit of applying the technique to biological specimens. PMID:26309749

High Temporal Resolution Permafrost Monitoring Using a Multiple Stack Insar Technique

NASA Astrophysics Data System (ADS)

Eppler, J.; Kubanski, M.; Sharma, J.; Busler, J.

2015-04-01

The combined effect of climate change and accelerated economic development in Northern regions increases the threat of permafrost related surface deformation to buildings and transportation infrastructure. Satellite based InSAR provides a means for monitoring infrastructure that may be both remote and spatially extensive. However, permafrost poses challenges for InSAR monitoring due to the complex temporal deformation patterns caused by both seasonal active layer fluctuations and long-term changes in permafrost thickness. These dynamics suggest a need for increasing the temporal resolution of multi-temporal InSAR methods. To address this issue we have developed a method that combines and jointly processes two or more same side geometry InSAR stacks to provide a high-temporal resolution estimate of surface deformation. The method allows for combining stacks from more than a single SAR sensor and for a combination of frequency bands. Data for this work have been collected and analysed for an area near the community of Umiujaq, Quebec in Northern Canada and include scenes from RADARSAT-2, TerraSAR-X and COSMO-SkyMed. Multiple stack based surface deformation estimates are compared for several cases including results from the three sensors individually and for all sensors combined. The test cases show substantially similar surface deformation results which correlate well with surficial geology. The best spatial coverage of coherent targets was achieved when data from all sensors were combined. The proposed multiple stack method is demonstrated to improve the estimation of surface deformation in permafrost affected areas and shows potential for deriving InSAR based permafrost classification maps to aid in the monitoring of Northern infrastructure.

Coastal and Inland Water Applications of High Resolution Optical Satellite Data from Landsat-8 and Sentinel-2

NASA Astrophysics Data System (ADS)

Vanhellemont, Q.

2016-02-01

Since the launch of Landsat-8 (L8) in 2013, a joint NASA/USGS programme, new applications of high resolution imagery for coastal and inland waters have become apparent. The optical imaging instrument on L8, the Operational Land Imager (OLI), is much improved compared to its predecessors on L5 and L7, especially with regards to SNR and digitization, and is therefore well suited for retrieving water reflectances and derived parameters such as turbidity and suspended sediment concentration. In June 2015, the European Space Agency (ESA) successfully launched a similar instrument, the MultiSpectral Imager (MSI), on board of Sentinel-2A (S2A). Imagery from both L8 and S2A are free of charge and publicly available (S2A starting at the end of 2015). Atmospheric correction schemes and processing software is under development in the EC-FP7 HIGHROC project. The spatial resolution of these instruments (10-60 m) is a great improvement over typical moderate resolution ocean colour sensors such as MODIS and MERIS (0.25 - 1 km). At higher resolution, many more lakes, rivers, ports and estuaries are spatially resolved, and can thus now be studied using satellite data, unlocking potential for mandatory monitoring e.g. under European Directives such as the Marine Strategy Framework Directive and the Water Framework Directive. We present new applications of these high resolution data, such as monitoring of offshore constructions, wind farms, sediment transport, dredging and dumping, shipping and fishing activities. The spatial variability at sub moderate resolution (0.25 - 1 km) scales can be assessed, as well as the impact of sub grid scale variability (including ships and platforms used for validation) on the moderate pixel retrieval. While the daily revisit time of the moderate resolution sensors is vastly superior to those of the high resolution satellites, at the equator respectively 16 and 10 days for L8 and S2A, the low revisit times can be partially mitigated by combining data streams. Time-series of L8 and S2A imagery are presented to show the power of combining the two satellite missions. With the launch of Sentinel-2B (expected mid-2016), the time-series will be extended with another high resolution sensor. S2B will be on the same orbit as S2A, spaced 180 degrees apart, bringing the S2A+B combined revisit time down to 5 days.

Recent Advances in the Design of Electro-Optic Sensors for Minimally Destructive Microwave Field Probing

PubMed Central

Lee, Dong-Joon; Kang, No-Weon; Choi, Jun-Ho; Kim, Junyeon; Whitaker, John F.

2011-01-01

In this paper we review recent design methodologies for fully dielectric electro-optic sensors that have applications in non-destructive evaluation (NDE) of devices and materials that radiate, guide, or otherwise may be impacted by microwave fields. In many practical NDE situations, fiber-coupled-sensor configurations are preferred due to their advantages over free-space bulk sensors in terms of optical alignment, spatial resolution, and especially, a low degree of field invasiveness. We propose and review five distinct types of fiber-coupled electro-optic sensor probes. The design guidelines for each probe type and their performances in absolute electric-field measurements are compared and summarized. PMID:22346604

Ultralong fibre-optic distributed Raman temperature sensor

NASA Astrophysics Data System (ADS)

Kuznetsov, A. G.; Kharenko, D. S.; Babin, S. A.; Tsydenzhapov, I. B.; Shelemba, I. S.

2017-11-01

We have demonstrated an ultralong (up to 85 km in length) all-fibre Raman temperature sensor which utilises SMF-28 standard single-mode telecom fibre and a 1.63-μm probe signal source. The probe signal from the laser diode is amplified by a Raman fibre amplifier. The temperature along a 85-km-long fibre line has been measured with an accuracy of 8°C and spatial resolution of 800 m or better.

LANDSAT D to test thematic mapper, inaugurate operational system

NASA Technical Reports Server (NTRS)

1982-01-01

NASA will launch the Landsat D spacecraft on July 9, 1982 aboard a new, up-rated Delta 3920 expendable launch vehicle. LANDSAT D will incorporate two highly sophisticated sensors; the flight proven multispectral scanner; and a new instrument expected to advance considerably the remote sensing capabilities of Earth resources satellites. The new sensor, the thematic mapper, provides data in seven spectral (light) bands with greatly improved spectral, spatial and radiometric resolution.

A weighted optimization approach to time-of-flight sensor fusion.

PubMed

Schwarz, Sebastian; Sjostrom, Marten; Olsson, Roger

2014-01-01

Acquiring scenery depth is a fundamental task in computer vision, with many applications in manufacturing, surveillance, or robotics relying on accurate scenery information. Time-of-flight cameras can provide depth information in real-time and overcome short-comings of traditional stereo analysis. However, they provide limited spatial resolution and sophisticated upscaling algorithms are sought after. In this paper, we present a sensor fusion approach to time-of-flight super resolution, based on the combination of depth and texture sources. Unlike other texture guided approaches, we interpret the depth upscaling process as a weighted energy optimization problem. Three different weights are introduced, employing different available sensor data. The individual weights address object boundaries in depth, depth sensor noise, and temporal consistency. Applied in consecutive order, they form three weighting strategies for time-of-flight super resolution. Objective evaluations show advantages in depth accuracy and for depth image based rendering compared with state-of-the-art depth upscaling. Subjective view synthesis evaluation shows a significant increase in viewer preference by a factor of four in stereoscopic viewing conditions. To the best of our knowledge, this is the first extensive subjective test performed on time-of-flight depth upscaling. Objective and subjective results proof the suitability of our approach to time-of-flight super resolution approach for depth scenery capture.

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Nagarajaiah, Satish; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-03-01

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30-60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. The proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

Simulating the directional, spectral and textural properties of a large-scale scene at high resolution using a MODIS BRDF product

NASA Astrophysics Data System (ADS)

Rengarajan, Rajagopalan; Goodenough, Adam A.; Schott, John R.

2016-10-01

Many remote sensing applications rely on simulated scenes to perform complex interaction and sensitivity studies that are not possible with real-world scenes. These applications include the development and validation of new and existing algorithms, understanding of the sensor's performance prior to launch, and trade studies to determine ideal sensor configurations. The accuracy of these applications is dependent on the realism of the modeled scenes and sensors. The Digital Image and Remote Sensing Image Generation (DIRSIG) tool has been used extensively to model the complex spectral and spatial texture variation expected in large city-scale scenes and natural biomes. In the past, material properties that were used to represent targets in the simulated scenes were often assumed to be Lambertian in the absence of hand-measured directional data. However, this assumption presents a limitation for new algorithms that need to recognize the anisotropic behavior of targets. We have developed a new method to model and simulate large-scale high-resolution terrestrial scenes by combining bi-directional reflectance distribution function (BRDF) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data, high spatial resolution data, and hyperspectral data. The high spatial resolution data is used to separate materials and add textural variations to the scene, and the directional hemispherical reflectance from the hyperspectral data is used to adjust the magnitude of the MODIS BRDF. In this method, the shape of the BRDF is preserved since it changes very slowly, but its magnitude is varied based on the high resolution texture and hyperspectral data. In addition to the MODIS derived BRDF, target/class specific BRDF values or functions can also be applied to features of specific interest. The purpose of this paper is to discuss the techniques and the methodology used to model a forest region at a high resolution. The simulated scenes using this method for varying view angles show the expected variations in the reflectance due to the BRDF effects of the Harvard forest. The effectiveness of this technique to simulate real sensor data is evaluated by comparing the simulated data with the Landsat 8 Operational Land Image (OLI) data over the Harvard forest. Regions of interest were selected from the simulated and the real data for different targets and their Top-of-Atmospheric (TOA) radiance were compared. After adjusting for scaling correction due to the difference in atmospheric conditions between the simulated and the real data, the TOA radiance is found to agree within 5 % in the NIR band and 10 % in the visible bands for forest targets under similar illumination conditions. The technique presented in this paper can be extended for other biomes (e.g. desert regions and agricultural regions) by using the appropriate geographic regions. Since the entire scene is constructed in a simulated environment, parameters such as BRDF or its effects can be analyzed for general or target specific algorithm improvements. Also, the modeling and simulation techniques can be used as a baseline for the development and comparison of new sensor designs and to investigate the operational and environmental factors that affects the sensor constellations such as Sentinel and Landsat missions.

High spatial resolution passive microwave sounding systems

NASA Technical Reports Server (NTRS)

Staelin, D. H.; Rosenkranz, P. W.; Bonanni, P. G.; Gasiewski, A. W.

1986-01-01

Two extensive series of flights aboard the ER-2 aircraft were conducted with the MIT 118 GHz imaging spectrometer together with a 53.6 GHz nadir channel and a TV camera record of the mission. Other microwave sensors, including a 183 GHz imaging spectrometer were flown simultaneously by other research groups. Work also continued on evaluating the impact of high-resolution passive microwave soundings upon numerical weather prediction models.

Investigation of image distortion due to MCP electronic readout misalignment and correction via customized GUI application

NASA Astrophysics Data System (ADS)

Vitucci, G.; Minniti, T.; Tremsin, A. S.; Kockelmann, W.; Gorini, G.

2018-04-01

The MCP-based neutron counting detector is a novel device that allows high spatial resolution and time-resolved neutron radiography and tomography with epithermal, thermal and cold neutrons. Time resolution is possible by the high readout speeds of ~ 1200 frames/sec, allowing high resolution event counting with relatively high rates without spatial resolution degradation due to event overlaps. The electronic readout is based on a Timepix sensor, a CMOS pixel readout chip developed at CERN. Currently, a geometry of a quad Timepix detector is used with an active format of 28 × 28 mm2 limited by the size of the Timepix quad (2 × 2 chips) readout. Measurements of a set of high-precision micrometers test samples have been performed at the Imaging and Materials Science & Engineering (IMAT) beamline operating at the ISIS spallation neutron source (U.K.). The aim of these experiments was the full characterization of the chip misalignment and of the gaps between each pad in the quad Timepix sensor. Such misalignment causes distortions of the recorded shape of the sample analyzed. We present in this work a post-processing image procedure that considers and corrects these effects. Results of the correction will be discussed and the efficacy of this method evaluated.

Analysis of a commercial small unmanned airborne system (sUAS) in support of the Radiometric Calibration Test Site (RadCaTS) at Railroad Valley

NASA Astrophysics Data System (ADS)

Czapla-Myers, Jeffrey S.; Anderson, Nikolaus J.

2017-09-01

The Radiometric Calibration Test Site (RadCaTS) is an automated facility developed by the Remote Sensing Group (RSG) at the University of Arizona to provide radiometric calibration data for airborne and satellite sensors. RadCaTS uses stationary ground-viewing radiometers (GVRs) to spatially sample the surface reflectance of the site. The number and location of the GVRs is based on previous spatial, spectral, and temporal analyses of Railroad Valley. With the increase in high-resolution satellite sensors, there is renewed interest in examining the spatial uniformity the 1-km2 RadCaTS area at scales smaller than a typical 30-m sensor. RadCaTS is one of the four instrumented sites currently in the CEOS WGCV Radiometric Calibration Network (RadCalNet), which aims to harmonize the post-launch radiometric calibration of satellite sensors through the use of a global network of automated calibration sites. A better understanding of the RadCaTS spatial uniformity as a function of pixel size will also benefit the RadCalNet work. RSG has recently acquired a commercially-available small unmanned airborne system (sUAS) system, with which preliminary spatial homogeneity measurements of the 1-km2 RadCaTS area were made. This work describes an initial assessment of the airborne platform and integrated camera for spatial studies of RadCaTS using data that were collected in 2016 and 2017.

Shack-Hartmann wavefront sensor with large dynamic range by adaptive spot search method.

PubMed

Shinto, Hironobu; Saita, Yusuke; Nomura, Takanori

2016-07-10

A Shack-Hartmann wavefront sensor (SHWFS) that consists of a microlens array and an image sensor has been used to measure the wavefront aberrations of human eyes. However, a conventional SHWFS has finite dynamic range depending on the diameter of the each microlens. The dynamic range cannot be easily expanded without a decrease of the spatial resolution. In this study, an adaptive spot search method to expand the dynamic range of an SHWFS is proposed. In the proposed method, spots are searched with the help of their approximate displacements measured with low spatial resolution and large dynamic range. By the proposed method, a wavefront can be correctly measured even if the spot is beyond the detection area. The adaptive spot search method is realized by using the special microlens array that generates both spots and discriminable patterns. The proposed method enables expanding the dynamic range of an SHWFS with a single shot and short processing time. The performance of the proposed method is compared with that of a conventional SHWFS by optical experiments. Furthermore, the dynamic range of the proposed method is quantitatively evaluated by numerical simulations.

Development of a MODIS-Derived Surface Albedo Data Set: An Improved Model Input for Processing the NSRDB

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maclaurin, Galen; Sengupta, Manajit; Xie, Yu

A significant source of bias in the transposition of global horizontal irradiance to plane-of-array (POA) irradiance arises from inaccurate estimations of surface albedo. The current physics-based model used to produce the National Solar Radiation Database (NSRDB) relies on model estimations of surface albedo from a reanalysis climatalogy produced at relatively coarse spatial resolution compared to that of the NSRDB. As an input to spectral decomposition and transposition models, more accurate surface albedo data from remotely sensed imagery at finer spatial resolutions would improve accuracy in the final product. The National Renewable Energy Laboratory (NREL) developed an improved white-sky (bi-hemispherical reflectance)more » broadband (0.3-5.0 ..mu..m) surface albedo data set for processing the NSRDB from two existing data sets: a gap-filled albedo product and a daily snow cover product. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellites have provided high-quality measurements of surface albedo at 30 arc-second spatial resolution and 8-day temporal resolution since 2001. The high spatial and temporal resolutions and the temporal coverage of the MODIS sensor will allow for improved modeling of POA irradiance in the NSRDB. However, cloud and snow cover interfere with MODIS observations of ground surface albedo, and thus they require post-processing. The MODIS production team applied a gap-filling methodology to interpolate observations obscured by clouds or ephemeral snow. This approach filled pixels with ephemeral snow cover because the 8-day temporal resolution is too coarse to accurately capture the variability of snow cover and its impact on albedo estimates. However, for this project, accurate representation of daily snow cover change is important in producing the NSRDB. Therefore, NREL also used the Integrated Multisensor Snow and Ice Mapping System data set, which provides daily snow cover observations of the Northern Hemisphere for the temporal extent of the NSRDB (1998-2015). We provide a review of validation studies conducted on these two products and describe the methodology developed by NREL to remap the data products to the NSRDB grid and integrate them into a seamless daily data set.« less

Integrated GNSS Attitude Determination and Positioning for Direct Geo-Referencing

PubMed Central

Nadarajah, Nandakumaran; Paffenholz, Jens-André; Teunissen, Peter J. G.

2014-01-01

Direct geo-referencing is an efficient methodology for the fast acquisition of 3D spatial data. It requires the fusion of spatial data acquisition sensors with navigation sensors, such as Global Navigation Satellite System (GNSS) receivers. In this contribution, we consider an integrated GNSS navigation system to provide estimates of the position and attitude (orientation) of a 3D laser scanner. The proposed multi-sensor system (MSS) consists of multiple GNSS antennas rigidly mounted on the frame of a rotating laser scanner and a reference GNSS station with known coordinates. Precise GNSS navigation requires the resolution of the carrier phase ambiguities. The proposed method uses the multivariate constrained integer least-squares (MC-LAMBDA) method for the estimation of rotating frame ambiguities and attitude angles. MC-LAMBDA makes use of the known antenna geometry to strengthen the underlying attitude model and, hence, to enhance the reliability of rotating frame ambiguity resolution and attitude determination. The reliable estimation of rotating frame ambiguities is consequently utilized to enhance the relative positioning of the rotating frame with respect to the reference station. This integrated (array-aided) method improves ambiguity resolution, as well as positioning accuracy between the rotating frame and the reference station. Numerical analyses of GNSS data from a real-data campaign confirm the improved performance of the proposed method over the existing method. In particular, the integrated method yields reliable ambiguity resolution and reduces position standard deviation by a factor of about 0.8, matching the theoretical gain of 3/4 for two antennas on the rotating frame and a single antenna at the reference station. PMID:25036330

Potential improvement for forest cover and forest degradation mapping with the forthcoming Sentinel-2 program

NASA Astrophysics Data System (ADS)

Hojas-Gascon, L.; Belward, A.; Eva, H.; Ceccherini, G.; Hagolle, O.; Garcia, J.; Cerutti, P.

2015-04-01

The forthcoming European Space Agency's Sentinel-2 mission promises to provide high (10 m) resolution optical data at higher temporal frequencies (5 day revisit with two operational satellites) than previously available. CNES, the French national space agency, launched a program in 2013, 'SPOT4 take 5', to simulate such a dataflow using the SPOT HRV sensor, which has similar spectral characteristics to the Sentinel sensor, but lower (20m) spatial resolution. Such data flow enables the analysis of the satellite images using temporal analysis, an approach previously restricted to lower spatial resolution sensors. We acquired 23 such images over Tanzania for the period from February to June 2013. The data were analysed with aim of discriminating between different forest cover percentages for landscape units of 0.5 ha over a site characterised by deciduous intact and degraded forests. The SPOT data were processed by one extracting temporal vegetation indices. We assessed the impact of the high acquisition rate with respect to the current rate of one image every 16 days. Validation data, giving the percentage of forest canopy cover in each land unit were provided by very high resolution satellite data. Results show that using the full temporal series it is possible to discriminate between forest units with differences of more than 40% tree cover or more. Classification errors fell exclusively into the adjacent forest canopy cover class of 20% or less. The analyses show that forestation mapping and degradation monitoring will be substantially improved with the Sentinel-2 program.

Integrated GNSS attitude determination and positioning for direct geo-referencing.

PubMed

Nadarajah, Nandakumaran; Paffenholz, Jens-André; Teunissen, Peter J G

2014-07-17

Direct geo-referencing is an efficient methodology for the fast acquisition of 3D spatial data. It requires the fusion of spatial data acquisition sensors with navigation sensors, such as Global Navigation Satellite System (GNSS) receivers. In this contribution, we consider an integrated GNSS navigation system to provide estimates of the position and attitude (orientation) of a 3D laser scanner. The proposed multi-sensor system (MSS) consists of multiple GNSS antennas rigidly mounted on the frame of a rotating laser scanner and a reference GNSS station with known coordinates. Precise GNSS navigation requires the resolution of the carrier phase ambiguities. The proposed method uses the multivariate constrained integer least-squares (MC-LAMBDA) method for the estimation of rotating frame ambiguities and attitude angles. MC-LAMBDA makes use of the known antenna geometry to strengthen the underlying attitude model and, hence, to enhance the reliability of rotating frame ambiguity resolution and attitude determination. The reliable estimation of rotating frame ambiguities is consequently utilized to enhance the relative positioning of the rotating frame with respect to the reference station. This integrated (array-aided) method improves ambiguity resolution, as well as positioning accuracy between the rotating frame and the reference station. Numerical analyses of GNSS data from a real-data campaign confirm the improved performance of the proposed method over the existing method. In particular, the integrated method yields reliable ambiguity resolution and reduces position standard deviation by a factor of about 0:8, matching the theoretical gain of √ 3/4 for two antennas on the rotating frame and a single antenna at the reference station.

Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A. P.; Bhartia, P. K.; Wind, G.; Platnick, S.; Menzel, W. P.

2010-01-01

The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with ocean, particularly in the tropics and summer hemisphere.

Evanescent Properties of Optical Diffraction from 2-Dimensional Hexagonal Photonic Crystals and Their Sensor Applications.

PubMed

Liao, Yu-Yang; Chen, Yung-Tsan; Chen, Chien-Chun; Huang, Jian-Jang

2018-04-03

The sensitivity of traditional diffraction grating sensors is limited by the spatial resolution of the measurement setup. Thus, a large space is required to improve sensor performance. Here, we demonstrate a compact hexagonal photonic crystal (PhC) optical sensor with high sensitivity. PhCs are able to diffract optical beams to various angles in azimuthal space. The critical wavelength that satisfies the phase matching or becomes evanescent was used to benchmark the refractive index of a target analyte applied on a PhC sensor. Using a glucose solution as an example, our sensor demonstrated very high sensitivity and a low limit of detection. This shows that the diffraction mechanism of hexagonal photonic crystals can be used for sensors when compact size is a concern.

Neural Network for Image-to-Image Control of Optical Tweezers

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Anderson, Robert C.; Weiland, Kenneth E.; Wrbanek, Susan Y.

2004-01-01

A method is discussed for using neural networks to control optical tweezers. Neural-net outputs are combined with scaling and tiling to generate 480 by 480-pixel control patterns for a spatial light modulator (SLM). The SLM can be combined in various ways with a microscope to create movable tweezers traps with controllable profiles. The neural nets are intended to respond to scattered light from carbon and silicon carbide nanotube sensors. The nanotube sensors are to be held by the traps for manipulation and calibration. Scaling and tiling allow the 100 by 100-pixel maximum resolution of the neural-net software to be applied in stages to exploit the full 480 by 480-pixel resolution of the SLM. One of these stages is intended to create sensitive null detectors for detecting variations in the scattered light from the nanotube sensors.

Obtaining high-resolution stage forecasts by coupling large-scale hydrologic models with sensor data

NASA Astrophysics Data System (ADS)

Fries, K. J.; Kerkez, B.

2017-12-01

We investigate how "big" quantities of distributed sensor data can be coupled with a large-scale hydrologic model, in particular the National Water Model (NWM), to obtain hyper-resolution forecasts. The recent launch of the NWM provides a great example of how growing computational capacity is enabling a new generation of massive hydrologic models. While the NWM spans an unprecedented spatial extent, there remain many questions about how to improve forecast at the street-level, the resolution at which many stakeholders make critical decisions. Further, the NWM runs on supercomputers, so water managers who may have access to their own high-resolution measurements may not readily be able to assimilate them into the model. To that end, we ask the question: how can the advances of the large-scale NWM be coupled with new local observations to enable hyper-resolution hydrologic forecasts? A methodology is proposed whereby the flow forecasts of the NWM are directly mapped to high-resolution stream levels using Dynamical System Identification. We apply the methodology across a sensor network of 182 gages in Iowa. Of these sites, approximately one third have shown to perform well in high-resolution flood forecasting when coupled with the outputs of the NWM. The quality of these forecasts is characterized using Principal Component Analysis and Random Forests to identify where the NWM may benefit from new sources of local observations. We also discuss how this approach can help municipalities identify where they should place low-cost sensors to most benefit from flood forecasts of the NWM.

Three-dimensional cascaded system analysis of a 50 µm pixel pitch wafer-scale CMOS active pixel sensor x-ray detector for digital breast tomosynthesis.

PubMed

Zhao, C; Vassiljev, N; Konstantinidis, A C; Speller, R D; Kanicki, J

2017-03-07

High-resolution, low-noise x-ray detectors based on the complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) technology have been developed and proposed for digital breast tomosynthesis (DBT). In this study, we evaluated the three-dimensional (3D) imaging performance of a 50 µm pixel pitch CMOS APS x-ray detector named DynAMITe (Dynamic Range Adjustable for Medical Imaging Technology). The two-dimensional (2D) angle-dependent modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE) were experimentally characterized and modeled using the cascaded system analysis at oblique incident angles up to 30°. The cascaded system model was extended to the 3D spatial frequency space in combination with the filtered back-projection (FBP) reconstruction method to calculate the 3D and in-plane MTF, NNPS and DQE parameters. The results demonstrate that the beam obliquity blurs the 2D MTF and DQE in the high spatial frequency range. However, this effect can be eliminated after FBP image reconstruction. In addition, impacts of the image acquisition geometry and detector parameters were evaluated using the 3D cascaded system analysis for DBT. The result shows that a wider projection angle range (e.g.  ±30°) improves the low spatial frequency (below 5 mm -1 ) performance of the CMOS APS detector. In addition, to maintain a high spatial resolution for DBT, a focal spot size of smaller than 0.3 mm should be used. Theoretical analysis suggests that a pixelated scintillator in combination with the 50 µm pixel pitch CMOS APS detector could further improve the 3D image resolution. Finally, the 3D imaging performance of the CMOS APS and an indirect amorphous silicon (a-Si:H) thin-film transistor (TFT) passive pixel sensor (PPS) detector was simulated and compared.

Three-dimensional cascaded system analysis of a 50 µm pixel pitch wafer-scale CMOS active pixel sensor x-ray detector for digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Zhao, C.; Vassiljev, N.; Konstantinidis, A. C.; Speller, R. D.; Kanicki, J.

2017-03-01

High-resolution, low-noise x-ray detectors based on the complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) technology have been developed and proposed for digital breast tomosynthesis (DBT). In this study, we evaluated the three-dimensional (3D) imaging performance of a 50 µm pixel pitch CMOS APS x-ray detector named DynAMITe (Dynamic Range Adjustable for Medical Imaging Technology). The two-dimensional (2D) angle-dependent modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE) were experimentally characterized and modeled using the cascaded system analysis at oblique incident angles up to 30°. The cascaded system model was extended to the 3D spatial frequency space in combination with the filtered back-projection (FBP) reconstruction method to calculate the 3D and in-plane MTF, NNPS and DQE parameters. The results demonstrate that the beam obliquity blurs the 2D MTF and DQE in the high spatial frequency range. However, this effect can be eliminated after FBP image reconstruction. In addition, impacts of the image acquisition geometry and detector parameters were evaluated using the 3D cascaded system analysis for DBT. The result shows that a wider projection angle range (e.g.  ±30°) improves the low spatial frequency (below 5 mm-1) performance of the CMOS APS detector. In addition, to maintain a high spatial resolution for DBT, a focal spot size of smaller than 0.3 mm should be used. Theoretical analysis suggests that a pixelated scintillator in combination with the 50 µm pixel pitch CMOS APS detector could further improve the 3D image resolution. Finally, the 3D imaging performance of the CMOS APS and an indirect amorphous silicon (a-Si:H) thin-film transistor (TFT) passive pixel sensor (PPS) detector was simulated and compared.

Comparing SMAP to Macro-scale and Hyper-resolution Land Surface Models over Continental U. S.

NASA Astrophysics Data System (ADS)

Pan, Ming; Cai, Xitian; Chaney, Nathaniel; Wood, Eric

2016-04-01

SMAP sensors collect moisture information in top soil at the spatial resolution of ~40 km (radiometer) and ~1 to 3 km (radar, before its failure in July 2015). Such information is extremely valuable for understanding various terrestrial hydrologic processes and their implications on human life. At the same time, soil moisture is a joint consequence of numerous physical processes (precipitation, temperature, radiation, topography, crop/vegetation dynamics, soil properties, etc.) that happen at a wide range of scales from tens of kilometers down to tens of meters. Therefore, a full and thorough analysis/exploration of SMAP data products calls for investigations at multiple spatial scales - from regional, to catchment, and to field scales. Here we first compare the SMAP retrievals to the Variable Infiltration Capacity (VIC) macro-scale land surface model simulations over the continental U. S. region at 3 km resolution. The forcing inputs to the model are merged/downscaled from a suite of best available data products including the NLDAS-2 forcing, Stage IV and Stage II precipitation, GOES Surface and Insolation Products, and fine elevation data. The near real time VIC simulation is intended to provide a source of large scale comparisons at the active sensor resolution. Beyond the VIC model scale, we perform comparisons at 30 m resolution against the recently developed HydroBloks hyper-resolution land surface model over several densely gauged USDA experimental watersheds. Comparisons are also made against in-situ point-scale observations from various SMAP Cal/Val and field campaign sites.

Towards large dynamic range and ultrahigh measurement resolution in distributed fiber sensing based on multicore fiber.

PubMed

Dang, Yunli; Zhao, Zhiyong; Tang, Ming; Zhao, Can; Gan, Lin; Fu, Songnian; Liu, Tongqing; Tong, Weijun; Shum, Perry Ping; Liu, Deming

2017-08-21

Featuring a dependence of Brillouin frequency shift (BFS) on temperature and strain changes over a wide range, Brillouin distributed optical fiber sensors are however essentially subjected to the relatively poor temperature/strain measurement resolution. On the other hand, phase-sensitive optical time-domain reflectometry (Φ-OTDR) offers ultrahigh temperature/strain measurement resolution, but the available frequency scanning range is normally narrow thereby severely restricts its measurement dynamic range. In order to achieve large dynamic range and high measurement resolution simultaneously, we propose to employ both the Brillouin optical time domain analysis (BOTDA) and Φ-OTDR through space-division multiplexed (SDM) configuration based on the multicore fiber (MCF), in which the two sensors are spatially separately implemented in the central core and a side core, respectively. As a proof of concept, the temperature sensing has been performed for validation with 2.5 m spatial resolution over 1.565 km MCF. Large temperature range (10 °C) has been measured by BOTDA and the 0.1 °C small temperature variation is successfully identified by Φ-OTDR with ~0.001 °C resolution. Moreover, the temperature changing process has been recorded by continuously performing the measurement of Φ-OTDR with 80 s frequency scanning period, showing about 0.02 °C temperature spacing at the monitored profile. The proposed system enables the capability to see finer and/or farther upon requirement in distributed optical fiber sensing.

Time stamping of single optical photons with 10 ns resolution

NASA Astrophysics Data System (ADS)

Chakaberia, Irakli; Cotlet, Mircea; Fisher-Levine, Merlin; Hodges, Diedra R.; Nguyen, Jayke; Nomerotski, Andrei

2017-05-01

High spatial and temporal resolution are key features for many modern applications, e.g. mass spectrometry, probing the structure of materials via neutron scattering, studying molecular structure, etc.1-5 Fast imaging also provides the capability of coincidence detection, and the further addition of sensitivity to single optical photons with the capability of timestamping them further broadens the field of potential applications. Photon counting is already widely used in X-ray imaging,6 where the high energy of the photons makes their detection easier. TimepixCam is a novel optical imager,7 which achieves high spatial resolution using an array of 256×256 55 μm × 55μm pixels which have individually controlled functionality. It is based on a thin-entrance-window silicon sensor, bump-bonded to a Timepix ASIC.8 TimepixCam provides high quantum efficiency in the optical wavelength range (400-1000 nm). We perform the timestamping of single photons with a time resolution of 20 ns, by coupling TimepixCam to a fast image-intensifier with a P47 phosphor screen. The fast emission time of the P479 allows us to preserve good time resolution while maintaining the capability to focus the optical output of the intensifier onto the 256×256 pixel Timepix sensor area. We demonstrate the capability of the (TimepixCam + image intensifier) setup to provide high-resolution single-photon timestamping, with an effective frame rate of 50 MHz.

Energy dispersive CdTe and CdZnTe detectors for spectral clinical CT and NDT applications

NASA Astrophysics Data System (ADS)

Barber, W. C.; Wessel, J. C.; Nygard, E.; Iwanczyk, J. S.

2015-06-01

We are developing room temperature compound semiconductor detectors for applications in energy-resolved high-flux single x-ray photon-counting spectral computed tomography (CT), including functional imaging with nanoparticle contrast agents for medical applications and non-destructive testing (NDT) for security applications. Energy-resolved photon-counting can provide reduced patient dose through optimal energy weighting for a particular imaging task in CT, functional contrast enhancement through spectroscopic imaging of metal nanoparticles in CT, and compositional analysis through multiple basis function material decomposition in CT and NDT. These applications produce high input count rates from an x-ray generator delivered to the detector. Therefore, in order to achieve energy-resolved single photon counting in these applications, a high output count rate (OCR) for an energy-dispersive detector must be achieved at the required spatial resolution and across the required dynamic range for the application. The required performance in terms of the OCR, spatial resolution, and dynamic range must be obtained with sufficient field of view (FOV) for the application thus requiring the tiling of pixel arrays and scanning techniques. Room temperature cadmium telluride (CdTe) and cadmium zinc telluride (CdZnTe) compound semiconductors, operating as direct conversion x-ray sensors, can provide the required speed when connected to application specific integrated circuits (ASICs) operating at fast peaking times with multiple fixed thresholds per pixel provided the sensors are designed for rapid signal formation across the x-ray energy ranges of the application at the required energy and spatial resolutions, and at a sufficiently high detective quantum efficiency (DQE). We have developed high-flux energy-resolved photon-counting x-ray imaging array sensors using pixellated CdTe and CdZnTe semiconductors optimized for clinical CT and security NDT. We have also fabricated high-flux ASICs with a two dimensional (2D) array of inputs for readout from the sensors. The sensors are guard ring free and have a 2D array of pixels and can be tiled in 2D while preserving pixel pitch. The 2D ASICs have four energy bins with a linear energy response across sufficient dynamic range for clinical CT and some NDT applications. The ASICs can also be tiled in 2D and are designed to fit within the active area of the sensors. We have measured several important performance parameters including: the output count rate (OCR) in excess of 20 million counts per second per square mm with a minimum loss of counts due to pulse pile-up, an energy resolution of 7 keV full width at half-maximum (FWHM) across the entire dynamic range, and a noise floor about 20 keV. This is achieved by directly interconnecting the ASIC inputs to the pixels of the CdZnTe sensors incurring very little input capacitance to the ASICs. We present measurements of the performance of the CdTe and CdZnTe sensors including the OCR, FWHM energy resolution, noise floor, as well as the temporal stability and uniformity under the rapidly varying high flux expected in CT and NDT applications.

Energy dispersive CdTe and CdZnTe detectors for spectral clinical CT and NDT applications

PubMed Central

Barber, W. C.; Wessel, J. C.; Nygard, E.; Iwanczyk, J. S.

2014-01-01

We are developing room temperature compound semiconductor detectors for applications in energy-resolved high-flux single x-ray photon-counting spectral computed tomography (CT), including functional imaging with nanoparticle contrast agents for medical applications and non destructive testing (NDT) for security applications. Energy-resolved photon-counting can provide reduced patient dose through optimal energy weighting for a particular imaging task in CT, functional contrast enhancement through spectroscopic imaging of metal nanoparticles in CT, and compositional analysis through multiple basis function material decomposition in CT and NDT. These applications produce high input count rates from an x-ray generator delivered to the detector. Therefore, in order to achieve energy-resolved single photon counting in these applications, a high output count rate (OCR) for an energy-dispersive detector must be achieved at the required spatial resolution and across the required dynamic range for the application. The required performance in terms of the OCR, spatial resolution, and dynamic range must be obtained with sufficient field of view (FOV) for the application thus requiring the tiling of pixel arrays and scanning techniques. Room temperature cadmium telluride (CdTe) and cadmium zinc telluride (CdZnTe) compound semiconductors, operating as direct conversion x-ray sensors, can provide the required speed when connected to application specific integrated circuits (ASICs) operating at fast peaking times with multiple fixed thresholds per pixel provided the sensors are designed for rapid signal formation across the x-ray energy ranges of the application at the required energy and spatial resolutions, and at a sufficiently high detective quantum efficiency (DQE). We have developed high-flux energy-resolved photon-counting x-ray imaging array sensors using pixellated CdTe and CdZnTe semiconductors optimized for clinical CT and security NDT. We have also fabricated high-flux ASICs with a two dimensional (2D) array of inputs for readout from the sensors. The sensors are guard ring free and have a 2D array of pixels and can be tiled in 2D while preserving pixel pitch. The 2D ASICs have four energy bins with a linear energy response across sufficient dynamic range for clinical CT and some NDT applications. The ASICs can also be tiled in 2D and are designed to fit within the active area of the sensors. We have measured several important performance parameters including; the output count rate (OCR) in excess of 20 million counts per second per square mm with a minimum loss of counts due to pulse pile-up, an energy resolution of 7 keV full width at half maximum (FWHM) across the entire dynamic range, and a noise floor about 20keV. This is achieved by directly interconnecting the ASIC inputs to the pixels of the CdZnTe sensors incurring very little input capacitance to the ASICs. We present measurements of the performance of the CdTe and CdZnTe sensors including the OCR, FWHM energy resolution, noise floor, as well as the temporal stability and uniformity under the rapidly varying high flux expected in CT and NDT applications. PMID:25937684

Energy dispersive CdTe and CdZnTe detectors for spectral clinical CT and NDT applications.

PubMed

Barber, W C; Wessel, J C; Nygard, E; Iwanczyk, J S

2015-06-01

We are developing room temperature compound semiconductor detectors for applications in energy-resolved high-flux single x-ray photon-counting spectral computed tomography (CT), including functional imaging with nanoparticle contrast agents for medical applications and non destructive testing (NDT) for security applications. Energy-resolved photon-counting can provide reduced patient dose through optimal energy weighting for a particular imaging task in CT, functional contrast enhancement through spectroscopic imaging of metal nanoparticles in CT, and compositional analysis through multiple basis function material decomposition in CT and NDT. These applications produce high input count rates from an x-ray generator delivered to the detector. Therefore, in order to achieve energy-resolved single photon counting in these applications, a high output count rate (OCR) for an energy-dispersive detector must be achieved at the required spatial resolution and across the required dynamic range for the application. The required performance in terms of the OCR, spatial resolution, and dynamic range must be obtained with sufficient field of view (FOV) for the application thus requiring the tiling of pixel arrays and scanning techniques. Room temperature cadmium telluride (CdTe) and cadmium zinc telluride (CdZnTe) compound semiconductors, operating as direct conversion x-ray sensors, can provide the required speed when connected to application specific integrated circuits (ASICs) operating at fast peaking times with multiple fixed thresholds per pixel provided the sensors are designed for rapid signal formation across the x-ray energy ranges of the application at the required energy and spatial resolutions, and at a sufficiently high detective quantum efficiency (DQE). We have developed high-flux energy-resolved photon-counting x-ray imaging array sensors using pixellated CdTe and CdZnTe semiconductors optimized for clinical CT and security NDT. We have also fabricated high-flux ASICs with a two dimensional (2D) array of inputs for readout from the sensors. The sensors are guard ring free and have a 2D array of pixels and can be tiled in 2D while preserving pixel pitch. The 2D ASICs have four energy bins with a linear energy response across sufficient dynamic range for clinical CT and some NDT applications. The ASICs can also be tiled in 2D and are designed to fit within the active area of the sensors. We have measured several important performance parameters including; the output count rate (OCR) in excess of 20 million counts per second per square mm with a minimum loss of counts due to pulse pile-up, an energy resolution of 7 keV full width at half maximum (FWHM) across the entire dynamic range, and a noise floor about 20keV. This is achieved by directly interconnecting the ASIC inputs to the pixels of the CdZnTe sensors incurring very little input capacitance to the ASICs. We present measurements of the performance of the CdTe and CdZnTe sensors including the OCR, FWHM energy resolution, noise floor, as well as the temporal stability and uniformity under the rapidly varying high flux expected in CT and NDT applications.

Advanced Image Processing for NASA Applications

NASA Technical Reports Server (NTRS)

LeMoign, Jacqueline

2007-01-01

The future of space exploration will involve cooperating fleets of spacecraft or sensor webs geared towards coordinated and optimal observation of Earth Science phenomena. The main advantage of such systems is to utilize multiple viewing angles as well as multiple spatial and spectral resolutions of sensors carried on multiple spacecraft but acting collaboratively as a single system. Within this framework, our research focuses on all areas related to sensing in collaborative environments, which means systems utilizing intracommunicating spatially distributed sensor pods or crafts being deployed to monitor or explore different environments. This talk will describe the general concept of sensing in collaborative environments, will give a brief overview of several technologies developed at NASA Goddard Space Flight Center in this area, and then will concentrate on specific image processing research related to that domain, specifically image registration and image fusion.

Exploiting MISR products at the full spatial resolution (275m) to document changes in land properties in and around the Kruger National Park, South Africa

NASA Astrophysics Data System (ADS)

Verstraete, M. M.; Hunt, L. A.; Pinty, B.; Clerici, M.; Scholes, R. J.

2009-12-01

The MISR instrument on NASA's Terra platform has been acquiring data globally and continuously for almost 10 years. A wide range of atmospheric and land products are operationally generated at the LaRC ASDC, at spatial resolutions of 1.1 km or coarser. Yet, the intrinsic spatial resolution of that sensor is 275m and 12 out of the 36 spectro-directional data channels are transmitted to the ground segment at that resolution. Recent algorithmic developments have permitted us to reconstruct reasonable estimates of the other 24 channels and to account for atmospheric effects at the full original spatial resolution. Spectro-directional reflectances have been processed to characterize the anisotropy of observed land surfaces and then optimally estimate various geophysical properties of the environment such as the fluxes of radiation in and out of plant canopies, the albedo, FAPAR, etc. These detailed products allow us to investigate ecological and environmental changes in much greater spatial and thematic detail than was previously possible. The paper outlines the various methodological steps implemented and exhibits concrete results for a region of moderate size (280 by 380 km) in South Africa. Practical downstream applications of this approach include monitoring desertification and biomass burning, documenting urbanization or characterizing the phenology of vegetation.

A dynamic aerodynamic resistance approach to calculate high resolution sensible heat fluxes in urban areas

NASA Astrophysics Data System (ADS)

Crawford, Ben; Grimmond, Sue; Kent, Christoph; Gabey, Andrew; Ward, Helen; Sun, Ting; Morrison, William

2017-04-01

Remotely sensed data from satellites have potential to enable high-resolution, automated calculation of urban surface energy balance terms and inform decisions about urban adaptations to environmental change. However, aerodynamic resistance methods to estimate sensible heat flux (QH) in cities using satellite-derived observations of surface temperature are difficult in part due to spatial and temporal variability of the thermal aerodynamic resistance term (rah). In this work, we extend an empirical function to estimate rah using observational data from several cities with a broad range of surface vegetation land cover properties. We then use this function to calculate spatially and temporally variable rah in London based on high-resolution (100 m) land cover datasets and in situ meteorological observations. In order to calculate high-resolution QH based on satellite-observed land surface temperatures, we also develop and employ novel methods to i) apply source area-weighted averaging of surface and meteorological variables across the study spatial domain, ii) calculate spatially variable, high-resolution meteorological variables (wind speed, friction velocity, and Obukhov length), iii) incorporate spatially interpolated urban air temperatures from a distributed sensor network, and iv) apply a modified Monte Carlo approach to assess uncertainties with our results, methods, and input variables. Modeled QH using the aerodynamic resistance method is then compared to in situ observations in central London from a unique network of scintillometers and eddy-covariance measurements.

High-speed imaging using CMOS image sensor with quasi pixel-wise exposure

NASA Astrophysics Data System (ADS)

Sonoda, T.; Nagahara, H.; Endo, K.; Sugiyama, Y.; Taniguchi, R.

2017-02-01

Several recent studies in compressive video sensing have realized scene capture beyond the fundamental trade-off limit between spatial resolution and temporal resolution using random space-time sampling. However, most of these studies showed results for higher frame rate video that were produced by simulation experiments or using an optically simulated random sampling camera, because there are currently no commercially available image sensors with random exposure or sampling capabilities. We fabricated a prototype complementary metal oxide semiconductor (CMOS) image sensor with quasi pixel-wise exposure timing that can realize nonuniform space-time sampling. The prototype sensor can reset exposures independently by columns and fix these amount of exposure by rows for each 8x8 pixel block. This CMOS sensor is not fully controllable via the pixels, and has line-dependent controls, but it offers flexibility when compared with regular CMOS or charge-coupled device sensors with global or rolling shutters. We propose a method to realize pseudo-random sampling for high-speed video acquisition that uses the flexibility of the CMOS sensor. We reconstruct the high-speed video sequence from the images produced by pseudo-random sampling using an over-complete dictionary.

Spatial optical crosstalk in CMOS image sensors integrated with plasmonic color filters.

PubMed

Yu, Yan; Chen, Qin; Wen, Long; Hu, Xin; Zhang, Hui-Fang

2015-08-24

Imaging resolution of complementary metal oxide semiconductor (CMOS) image sensor (CIS) keeps increasing to approximately 7k × 4k. As a result, the pixel size shrinks down to sub-2μm, which greatly increases the spatial optical crosstalk. Recently, plasmonic color filter was proposed as an alternative to conventional colorant pigmented ones. However, there is little work on its size effect and the spatial optical crosstalk in a model of CIS. By numerical simulation, we investigate the size effect of nanocross array plasmonic color filters and analyze the spatial optical crosstalk of each pixel in a Bayer array of a CIS with a pixel size of 1μm. It is found that the small pixel size deteriorates the filtering performance of nanocross color filters and induces substantial spatial color crosstalk. By integrating the plasmonic filters in the low Metal layer in standard CMOS process, the crosstalk reduces significantly, which is compatible to pigmented filters in a state-of-the-art backside illumination CIS.

Wavelet compression techniques for hyperspectral data

NASA Technical Reports Server (NTRS)

Evans, Bruce; Ringer, Brian; Yeates, Mathew

1994-01-01

Hyperspectral sensors are electro-optic sensors which typically operate in visible and near infrared bands. Their characteristic property is the ability to resolve a relatively large number (i.e., tens to hundreds) of contiguous spectral bands to produce a detailed profile of the electromagnetic spectrum. In contrast, multispectral sensors measure relatively few non-contiguous spectral bands. Like multispectral sensors, hyperspectral sensors are often also imaging sensors, measuring spectra over an array of spatial resolution cells. The data produced may thus be viewed as a three dimensional array of samples in which two dimensions correspond to spatial position and the third to wavelength. Because they multiply the already large storage/transmission bandwidth requirements of conventional digital images, hyperspectral sensors generate formidable torrents of data. Their fine spectral resolution typically results in high redundancy in the spectral dimension, so that hyperspectral data sets are excellent candidates for compression. Although there have been a number of studies of compression algorithms for multispectral data, we are not aware of any published results for hyperspectral data. Three algorithms for hyperspectral data compression are compared. They were selected as representatives of three major approaches for extending conventional lossy image compression techniques to hyperspectral data. The simplest approach treats the data as an ensemble of images and compresses each image independently, ignoring the correlation between spectral bands. The second approach transforms the data to decorrelate the spectral bands, and then compresses the transformed data as a set of independent images. The third approach directly generalizes two-dimensional transform coding by applying a three-dimensional transform as part of the usual transform-quantize-entropy code procedure. The algorithms studied all use the discrete wavelet transform. In the first two cases, a wavelet transform coder was used for the two-dimensional compression. The third case used a three dimensional extension of this same algorithm.

Radiometric cross-calibration of the Terra MODIS and Landsat 7 ETM+ using an invariant desert site

USGS Publications Warehouse

Choi, T.; Angal, A.; Chander, G.; Xiong, X.

2008-01-01

A methodology for long-term radiometric cross-calibration between the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors was developed. The approach involves calibration of near-simultaneous surface observations between 2000 and 2007. Fifty-seven cloud-free image pairs were carefully selected over the Libyan desert for this study. The Libyan desert site (+28.55??, +23.39??), located in northern Africa, is a high reflectance site with high spatial, spectral, and temporal uniformity. Because the test site covers about 12 kmx13 km, accurate geometric preprocessing is required to match the footprint size between the two sensors to avoid uncertainties due to residual image misregistration. MODIS Level IB radiometrically corrected products were reprojected to the corresponding ETM+ image's Universal Transverse Mercator (UTM) grid projection. The 30 m pixels from the ETM+ images were aggregated to match the MODIS spatial resolution (250 m in Bands 1 and 2, or 500 m in Bands 3 to 7). The image data from both sensors were converted to absolute units of at-sensor radiance and top-ofatmosphere (TOA) reflectance for the spectrally matching band pairs. For each band pair, a set of fitted coefficients (slope and offset) is provided to quantify the relationships between the testing sensors. This work focuses on long-term stability and correlation of the Terra MODIS and L7 ETM+ sensors using absolute calibration results over the entire mission of the two sensors. Possible uncertainties are also discussed such as spectral differences in matching band pairs, solar zenith angle change during a collection, and differences in solar irradiance models.

Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA

NASA Astrophysics Data System (ADS)

Deo, Ram K.; Domke, Grant M.; Russell, Matthew B.; Woodall, Christopher W.; Andersen, Hans-Erik

2018-05-01

Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, the accuracy of AGB predictions based on passive optical data depends on spatial resolution and spatial extent of target area as fine resolution (small pixels) data are associated with smaller coverage and longer repeat cycles compared to coarse resolution data. This study evaluated various spatial resolutions of Landsat-derived predictors on the accuracy of regional AGB models at three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We combined national forest inventory data with Landsat-derived predictors at spatial resolutions ranging from 30–1000 m to understand the optimal spatial resolution of optical data for large-area (regional) AGB estimation. Ten generic models were developed using the data collected in 2014, 2015 and 2016, and the predictions were evaluated (i) at the county-level against the estimates of the USFS Forest Inventory and Analysis Program which relied on EVALIDator tool and national forest inventory data from the 2009–2013 cycle and (ii) within a large number of strips (~1 km wide) predicted via LiDAR metrics at 30 m spatial resolution. The county-level estimates by the EVALIDator and Landsat models were highly related (R 2 > 0.66), although the R 2 varied significantly across sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of coarser resolution. The Landsat-based total AGB estimates were larger than the LiDAR-based total estimates within the strips, however the mean of AGB predictions by LiDAR were mostly within one-standard deviations of the mean predictions obtained from the Landsat-based model at any of the resolutions. We conclude that satellite data at resolutions up to 1000 m provide acceptable accuracy for continental scale analysis of AGB.

Fast and compact internal scanning CMOS-based hyperspectral camera: the Snapscan

NASA Astrophysics Data System (ADS)

Pichette, Julien; Charle, Wouter; Lambrechts, Andy

2017-02-01

Imec has developed a process for the monolithic integration of optical filters on top of CMOS image sensors, leading to compact, cost-efficient and faster hyperspectral cameras. Linescan cameras are typically used in remote sensing or for conveyor belt applications. Translation of the target is not always possible for large objects or in many medical applications. Therefore, we introduce a novel camera, the Snapscan (patent pending), exploiting internal movement of a linescan sensor enabling fast and convenient acquisition of high-resolution hyperspectral cubes (up to 2048x3652x150 in spectral range 475-925 nm). The Snapscan combines the spectral and spatial resolutions of a linescan system with the convenience of a snapshot camera.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stutman, D.; Tritz, K.; Finkenthal, M.

New diagnostic and sensor designs are needed for future burning plasma (BP) fusion experiments, having good space and time resolution and capable of prolonged operation in the harsh BP environment. We evaluate the potential of multi-energy x-ray imaging with filtered detector arrays for BP diagnostic and control. Experimental studies show that this simple and robust technique enables measuring with good accuracy, speed, and spatial resolution the T{sub e} profile, impurity content, and MHD activity in a tokamak. Applied to the BP this diagnostic could also serve for non-magnetic sensing of the plasma position, centroid, ELM, and RWM instability. BP compatiblemore » x-ray sensors are proposed using 'optical array' or 'bi-cell' detectors.« less

Bayesian Model for Matching the Radiometric Measurements of Aerospace and Field Ocean Color Sensors

PubMed Central

Salama, Mhd. Suhyb; Su, Zhongbo

2010-01-01

A Bayesian model is developed to match aerospace ocean color observation to field measurements and derive the spatial variability of match-up sites. The performance of the model is tested against populations of synthesized spectra and full and reduced resolutions of MERIS data. The model derived the scale difference between synthesized satellite pixel and point measurements with R2 > 0.88 and relative error < 21% in the spectral range from 400 nm to 695 nm. The sub-pixel variabilities of reduced resolution MERIS image are derived with less than 12% of relative errors in heterogeneous region. The method is generic and applicable to different sensors. PMID:22163615

Distributed fiber optical sensing of oxygen with optical time domain reflectometry.

PubMed

Eich, Susanne; Schmälzlin, Elmar; Löhmannsröben, Hans-Gerd

2013-05-31

In many biological and environmental applications spatially resolved sensing of molecular oxygen is desirable. A powerful tool for distributed measurements is optical time domain reflectometry (OTDR) which is often used in the field of telecommunications. We combine this technique with a novel optical oxygen sensor dye, triangular-[4] phenylene (TP), immobilized in a polymer matrix. The TP luminescence decay time is 86 ns. The short decay time of the sensor dye is suitable to achieve a spatial resolution of some meters. In this paper we present the development and characterization of a reflectometer in the UV range of the electromagnetic spectrum as well as optical oxygen sensing with different fiber arrangements.

Distributed Fiber Optical Sensing of Oxygen with Optical Time Domain Reflectometry

PubMed Central

Eich, Susanne; Schmälzlin, Elmar; Löhmannsröben, Hans-Gerd

2013-01-01

In many biological and environmental applications spatially resolved sensing of molecular oxygen is desirable. A powerful tool for distributed measurements is optical time domain reflectometry (OTDR) which is often used in the field of telecommunications. We combine this technique with a novel optical oxygen sensor dye, triangular-[4] phenylene (TP), immobilized in a polymer matrix. The TP luminescence decay time is 86 ns. The short decay time of the sensor dye is suitable to achieve a spatial resolution of some meters. In this paper we present the development and characterization of a reflectometer in the UV range of the electromagnetic spectrum as well as optical oxygen sensing with different fiber arrangements. PMID:23727953

Edge method for on-orbit defocus assessment.

PubMed

Viallefont-Robinet, Françoise

2010-09-27

In the earth observation domain, two classes of sensors may be distinguished: a class for which sensor performances are driven by radiometric accuracy of the images and a class for which sensor performances are driven by spatial resolution. In this latter case, as spatial resolution depends on the triplet constituted by the Ground Sampling Distance (GSD), Modulation Transfer Function (MTF), and Signal to Noise Ratio (SNR), refocusing, acting as an MTF improvement, is very important. Refocusing is not difficult by itself as far as the on-board mechanism is reliable. The difficulty is on the defocus assessment side. Some methods such as those used for the SPOT family rely on the ability of the satellite to image the same landscape with two focusing positions. This can be done with a bi-sensor configuration, with adequate focal plane, or with the satellite agility. A new generation of refocusing mechanism will be taken aboard Pleiades. As the speed of this mechanism will be much slower than the speed of the older generation, it won't be possible, despite the agility of the satellite, to image the same landscape with two focusing positions on the same orbit. That's why methods relying on MTF measurement with edge method have been studied. This paper describes the methods and the work done to assess the defocus measurement accuracy in the Pleiades context.

Pressure mapping with textile sensors for compression therapy monitoring.

PubMed

Baldoli, Ilaria; Mazzocchi, Tommaso; Paoletti, Clara; Ricotti, Leonardo; Salvo, Pietro; Dini, Valentina; Laschi, Cecilia; Francesco, Fabio Di; Menciassi, Arianna

2016-08-01

Compression therapy is the cornerstone of treatment in the case of venous leg ulcers. The therapy outcome is strictly dependent on the pressure distribution produced by bandages along the lower limb length. To date, pressure monitoring has been carried out using sensors that present considerable drawbacks, such as single point instead of distributed sensing, no shape conformability, bulkiness and constraints on patient's movements. In this work, matrix textile sensing technologies were explored in terms of their ability to measure the sub-bandage pressure with a suitable temporal and spatial resolution. A multilayered textile matrix based on a piezoresistive sensing principle was developed, calibrated and tested with human subjects, with the aim of assessing real-time distributed pressure sensing at the skin/bandage interface. Experimental tests were carried out on three healthy volunteers, using two different bandage types, from among those most commonly used. Such tests allowed the trends of pressure distribution to be evaluated over time, both at rest and during daily life activities. Results revealed that the proposed device enables the dynamic assessment of compression mapping, with a suitable spatial and temporal resolution (20 mm and 10 Hz, respectively). In addition, the sensor is flexible and conformable, thus well accepted by the patient. Overall, this study demonstrates the adequacy of the proposed piezoresistive textile sensor for the real-time monitoring of bandage-based therapeutic treatments. © IMechE 2016.

High-resolution CCD imaging alternatives

NASA Astrophysics Data System (ADS)

Brown, D. L.; Acker, D. E.

1992-08-01

High resolution CCD color cameras have recently stimulated the interest of a large number of potential end-users for a wide range of practical applications. Real-time High Definition Television (HDTV) systems are now being used or considered for use in applications ranging from entertainment program origination through digital image storage to medical and scientific research. HDTV generation of electronic images offers significant cost and time-saving advantages over the use of film in such applications. Further in still image systems electronic image capture is faster and more efficient than conventional image scanners. The CCD still camera can capture 3-dimensional objects into the computing environment directly without having to shoot a picture on film develop it and then scan the image into a computer. 2. EXTENDING CCD TECHNOLOGY BEYOND BROADCAST Most standard production CCD sensor chips are made for broadcast-compatible systems. One popular CCD and the basis for this discussion offers arrays of roughly 750 x 580 picture elements (pixels) or a total array of approximately 435 pixels (see Fig. 1). FOR. A has developed a technique to increase the number of available pixels for a given image compared to that produced by the standard CCD itself. Using an inter-lined CCD with an overall spatial structure several times larger than the photo-sensitive sensor areas each of the CCD sensors is shifted in two dimensions in order to fill in spatial gaps between adjacent sensors.

Evaluation of thin discontinuities in planar conducting materials using the diffraction of electromagnetic field

NASA Astrophysics Data System (ADS)

Savin, A.; Novy, F.; Fintova, S.; Steigmann, R.

2017-08-01

The current stage of nondestructive evaluation techniques imposes the development of new electromagnetic (EM) methods that are based on high spatial resolution and increased sensitivity. In order to achieve high performance, the work frequencies must be either radifrequencies or microwaves. At these frequencies, at the dielectric/conductor interface, plasmon polaritons can appear, propagating between conductive regions as evanescent waves. In order to use the evanescent wave that can appear even if the slits width is much smaller that the wavwelength of incident EM wave, a sensor with metamaterial (MM) is used. The study of the EM field diffraction against the edge of long thin discontinuity placed under the inspected surface of a conductive plate has been performed using the geometrical optics principles. This type of sensor having the reception coils shielded by a conductive screen with a circular aperture placed in the front of reception coil of emission reception sensor has been developed and “transported” information for obtaining of magnified image of the conductive structures inspected. This work presents a sensor, using MM conical Swiss roll type that allows the propagation of evanescent waves and the electromagnetic images are magnified. The test method can be successfully applied in a variety of applications of maxim importance such as defect/damage detection in materials used in automotive and aviation technologies. Applying this testing method, spatial resolution can be improved.

A Two-Axis Direct Fluid Shear Stress Sensor

NASA Technical Reports Server (NTRS)

Adcock, Edward E.; Scott, Michael A.; Bajikar, Sateesh S.

2010-01-01

This innovation is a miniature or micro sized semiconductor sensor design that provides two axis direct non-intrusive measurement of skin friction or wall shear stress in fluid flow. The sensor is fabricated by micro-electro-mechanical system (MEMS) technology, enabling small size and low cost reproductions. The sensors have been fabricated by utilizing MEMS fabrication processes to bond a sensing element wafer to a fluid coupling wafer. This layering technique provides for an out of plane dimension that is on the same order of length as the inplane dimensions. The sensor design has the following characteristics: a shear force collecting plate with dimensions that can be tailored to various application specific requirements such as spatial resolution, temporal resolution and shear force range and resolution. This plate is located coplanar to both the sensor body and flow boundary, and is connected to a dual axis gimbal structure by a connecting column or lever arm. The dual axis gimbal structure has torsional hinges with embedded piezoresistive torsional strain gauges which provide a voltage output that is correlated to the applied shear stress (and excitation current) on force collection plate that is located on the flow boundary surface (hence the transduction method). This combination of design elements create a force concentration and resolution structure that enables the generation of a large stress on the strain gauge from the small shear stress on the flow boundary wall. This design as well as the use of back side electrical contacts establishes a non-intrusive method to quantitatively measure the shear force vector on aerodynamic bodies.

Scaling effect of fraction of vegetation cover retrieved by algorithms based on linear mixture model

NASA Astrophysics Data System (ADS)

Obata, Kenta; Miura, Munenori; Yoshioka, Hiroki

2010-08-01

Differences in spatial resolution among sensors have been a source of error among satellite data products, known as a scaling effect. This study investigates the mechanism of the scaling effect on fraction of vegetation cover retrieved by a linear mixture model which employs NDVI as one of the constraints. The scaling effect is induced by the differences in texture, and the differences between the true endmember spectra and the endmember spectra assumed during retrievals. A mechanism of the scaling effect was analyzed by focusing on the monotonic behavior of spatially averaged FVC as a function of spatial resolution. The number of endmember is limited into two to proceed the investigation analytically. Although the spatially-averaged NDVI varies monotonically along with spatial resolution, the corresponding FVC values does not always vary monotonically. The conditions under which the averaged FVC varies monotonically for a certain sequence of spatial resolutions, were derived analytically. The increasing and decreasing trend of monotonic behavior can be predicted from the true and assumed endmember spectra of vegetation and non-vegetation classes regardless the distributions of the vegetation class within a fixed area. The results imply that the scaling effect on FVC is more complicated than that on NDVI, since, unlike NDVI, FVC becomes non-monotonic under a certain condition determined by the true and assumed endmember spectra.

High resolution observations of low contrast phenomena from an Advanced Geosynchronous Platform (AGP)

NASA Technical Reports Server (NTRS)

Maxwell, M. S.

1984-01-01

Present technology allows radiometric monitoring of the Earth, ocean and atmosphere from a geosynchronous platform with good spatial, spectral and temporal resolution. The proposed system could provide a capability for multispectral remote sensing with a 50 m nadir spatial resolution in the visible bands, 250 m in the 4 micron band and 1 km in the 11 micron thermal infrared band. The diffraction limited telescope has a 1 m aperture, a 10 m focal length (with a shorter focal length in the infrared) and linear and area arrays of detectors. The diffraction limited resolution applies to scenes of any brightness but for a dark low contrast scenes, the good signal to noise ratio of the system contribute to the observation capability. The capabilities of the AGP system are assessed for quantitative observations of ocean scenes. Instrument and ground system configuration are presented and projected sensor capabilities are analyzed.

Experimental investigation of leak detection using mobile distributed monitoring system

NASA Astrophysics Data System (ADS)

Chen, Jiang; Zheng, Junli; Xiong, Feng; Ge, Qi; Yan, Qixiang; Cheng, Fei

2018-01-01

The leak detection of rockfill dams is currently hindered by spatial and temporal randomness and wide monitoring range. The spatial resolution of fiber Bragg grating (FBG) temperature sensing technology is related to the distance between measuring points. As a result, the number of measuring points should be increased to ensure that the precise location of the leak is detected. However, this leads to a higher monitoring cost. Consequently, it is difficult to promote and apply this technology to effectively monitor rockfill dam leakage. In this paper, a practical mobile distributed monitoring system with dual-tubes is used by combining the FBG sensing system and hydrothermal cycling system. This dual-tube structure is composed of an outer polyethylene of raised temperature resistance heating pipe, an inner polytetrafluoroethylene tube, and a FBG sensor string, among which, the FBG sensor string can be dragged freely in the internal tube to change the position of the measuring points and improve the spatial resolution. In order to test the effectiveness of the system, the large-scale model test of concentrated leakage in 13 working conditions is carried out by identifying the location, quantity, and leakage rate of leakage passage. Based on Newton’s law of cooling, the leakage state is identified using the seepage identification index ζ v that was confirmed according to the cooling curve. Results suggested that the monitoring system shows high sensitivity and can improve the spatial resolution with limited measuring points, and thus better locate the leakage area. In addition, the seepage identification index ζ v correlated well with the leakage rate qualitatively.

Configuration and Specifications of AN Unmanned Aerial Vehicle for Precision Agriculture

NASA Astrophysics Data System (ADS)

Erena, M.; Montesinos, S.; Portillo, D.; Alvarez, J.; Marin, C.; Fernandez, L.; Henarejos, J. M.; Ruiz, L. A.

2016-06-01

Unmanned Aerial Vehicles (UAVs) with multispectral sensors are increasingly attractive in geosciences for data capture and map updating at high spatial and temporal resolutions. These autonomously-flying systems can be equipped with different sensors, such as a six-band multispectral camera (Tetracam mini-MCA-6), GPS Ublox M8N, and MEMS gyroscopes, and miniaturized sensor systems for navigation, positioning, and mapping purposes. These systems can be used for data collection in precision viticulture. In this study, the efficiency of a light UAV system for data collection, processing, and map updating in small areas is evaluated, generating correlations between classification maps derived from remote sensing and production maps. Based on the comparison of the indices derived from UAVs incorporating infrared sensors with those obtained by satellites (Sentinel 2A and Landsat 8), UAVs show promise for the characterization of vineyard plots with high spatial variability, despite the low vegetative coverage of these crops. Consequently, a procedure for zoning map production based on UAV/UV images could provide important information for farmers.

Distributed dynamic large strain optical fiber sensor based on the detection of spontaneous Brillouin scattering.

PubMed

Masoudi, Ali; Belal, Mohammad; Newson, Trevor P

2013-09-01

A Brillouin-based distributed optical fiber dynamic strain sensor is described which converts strain-induced Brillouin frequency shift into optical intensity variations by using an imbalanced Mach-Zhender interferometer. A 3×3 coupler is used at the output of this interferometer to permit differentiate and cross multiply demodulation. The demonstrated sensor is capable of probing dynamic strain disturbances over 2 km of sensing length every 0.5 s up to a strain of 10 mε with an accuracy of ±50 με and spatial resolution of 1.3 m.

Snapshot Imaging Spectrometry in the Visible and Long Wave Infrared

NASA Astrophysics Data System (ADS)

Maione, Bryan David

Imaging spectrometry is an optical technique in which the spectral content of an object is measured at each location in space. The main advantage of this modality is that it enables characterization beyond what is possible with a conventional camera, since spectral information is generally related to the chemical composition of the object. Due to this, imaging spectrometers are often capable of detecting targets that are either morphologically inconsistent, or even under resolved. A specific class of imaging spectrometer, known as a snapshot system, seeks to measure all spatial and spectral information simultaneously, thereby rectifying artifacts associated with scanning designs, and enabling the measurement of temporally dynamic scenes. Snapshot designs are the focus of this dissertation. Three designs for snapshot imaging spectrometers are developed, each providing novel contributions to the field of imaging spectrometry. In chapter 2, the first spatially heterodyned snapshot imaging spectrometer is modeled and experimentally validated. Spatial heterodyning is a technique commonly implemented in non-imaging Fourier transform spectrometry. For Fourier transform imaging spectrometers, spatial heterodyning improves the spectral resolution trade space. Additionally, in this chapter a unique neural network based spectral calibration is developed and determined to be an improvement beyond Fourier and linear operator based techniques. Leveraging spatial heterodyning as developed in chapter 2, in chapter 3, a high spectral resolution snapshot Fourier transform imaging spectrometer, based on a Savart plate interferometer, is developed and experimentally validated. The sensor presented in this chapter is the highest spectral resolution sensor in its class. High spectral resolution enables the sensor to discriminate narrowly spaced spectral lines. The capabilities of neural networks in imaging spectrometry are further explored in this chapter. Neural networks are used to perform single target detection on raw instrument data, thereby eliminating the need for an explicit spectral calibration step. As an extension of the results in chapter 2, neural networks are once again demonstrated to be an improvement when compared to linear operator based detection. In chapter 4 a non-interferometric design is developed for the long wave infrared (wavelengths spanning 8-12 microns). The imaging spectrometer developed in this chapter is a multi-aperture filtered microbolometer. Since the detector is uncooled, the presented design is ultra-compact and low power. Additionally, cost effective polymer absorption filters are used in lieu of interference filters. Since, each measurement of the system is spectrally multiplexed, an SNR advantage is realized. A theoretical model for the filtered design is developed, and the performance of the sensor for detecting liquid contaminants is investigated. Similar to past chapters, neural networks are used and achieve false detection rates of less than 1%. Lastly, this dissertation is concluded with a discussion on future work and potential impact of these devices.

Nanophotonic Image Sensors

PubMed Central

Hu, Xin; Wen, Long; Yu, Yan; Cumming, David R. S.

2016-01-01

The increasing miniaturization and resolution of image sensors bring challenges to conventional optical elements such as spectral filters and polarizers, the properties of which are determined mainly by the materials used, including dye polymers. Recent developments in spectral filtering and optical manipulating techniques based on nanophotonics have opened up the possibility of an alternative method to control light spectrally and spatially. By integrating these technologies into image sensors, it will become possible to achieve high compactness, improved process compatibility, robust stability and tunable functionality. In this Review, recent representative achievements on nanophotonic image sensors are presented and analyzed including image sensors with nanophotonic color filters and polarizers, metamaterial‐based THz image sensors, filter‐free nanowire image sensors and nanostructured‐based multispectral image sensors. This novel combination of cutting edge photonics research and well‐developed commercial products may not only lead to an important application of nanophotonics but also offer great potential for next generation image sensors beyond Moore's Law expectations. PMID:27239941

Characterization of fiber Bragg grating-based sensor array for high resolution manometry

NASA Astrophysics Data System (ADS)

Becker, Martin; Rothhardt, Manfred; Schröder, Kerstin; Voigt, Sebastian; Mehner, Jan; Teubner, Andreas; Lüpke, Thomas; Thieroff, Christoph; Krüger, Matthias; Chojetzki, Christoph; Bartelt, Hartmut

2012-04-01

The combination of fiber Bragg grating arrays integrated in a soft plastic tube is promising for high resolution manometry (HRM) where pressure measurements are done with high spatial resolution. The application as a medical device and in vivo experiments have to be anticipated by characterization with a measurement setup that simulates natural conditions. Good results are achieved with a pressure chamber which applies a well-defined pressure with a soft tubular membrane. It is shown that the proposed catheter design reaches accuracies down to 1 mbar and 1 cm.

High Spatial Resolution Bidirectional Reflectance Retrieval Using Satellite Data

DTIC Science & Technology

2010-12-01

of a region of interest (ROI), also known as its revisit time. It is useful for change detection in imagery. For example, deforestation studies do...hyperspectral sensors are disadvantageous as they increase processing and increase the complexity and cost of the satellite’s operation; however

Green Bay: Spatial patterns in water quality and landscape correlations

EPA Science Inventory

We conducted a high-resolution survey along the nearshore (369 km) in Green Bay using towed electronic instrumentation at approximately the 15 m depth contour, with additional transects of the bay that were oriented cross-contour (49 km). Electronic sensor data provided an effic...

Agricultural Land Use mapping by multi-sensor approach for hydrological water quality monitoring

NASA Astrophysics Data System (ADS)

Brodsky, Lukas; Kodesova, Radka; Kodes, Vit

2010-05-01

The main objective of this study is to demonstrate potential of operational use of the high and medium resolution remote sensing data for hydrological water quality monitoring by mapping agriculture intensity and crop structures. In particular use of remote sensing mapping for optimization of pesticide monitoring. The agricultural mapping task is tackled by means of medium spatial and high temporal resolution ESA Envisat MERIS FR images together with single high spatial resolution IRS AWiFS image covering the whole area of interest (the Czech Republic). High resolution data (e.g. SPOT, ALOS, Landsat) are often used for agricultural land use classification, but usually only at regional or local level due to data availability and financial constraints. AWiFS data (nominal spatial resolution 56 m) due to the wide satellite swath seems to be more suitable for use at national level. Nevertheless, one of the critical issues for such a classification is to have sufficient image acquisitions over the whole vegetation period to describe crop development in appropriate way. ESA MERIS middle-resolution data were used in several studies for crop classification. The high temporal and also spectral resolution of MERIS data has indisputable advantage for crop classification. However, spatial resolution of 300 m results in mixture signal in a single pixel. AWiFS-MERIS data synergy brings new perspectives in agricultural Land Use mapping. Also, the developed methodology procedure is fully compatible with future use of ESA (GMES) Sentinel satellite images. The applied methodology of hybrid multi-sensor approach consists of these main stages: a/ parcel segmentation and spectral pre-classification of high resolution image (AWiFS); b/ ingestion of middle resolution (MERIS) vegetation spectro-temporal features; c/ vegetation signatures unmixing; and d/ semantic object-oriented classification of vegetation classes into final classification scheme. These crop groups were selected to be classified: winter crops, spring crops, oilseed rape, legumes, summer and other crops. This study highlights operational potentials of high temporal full resolution MERIS images in agricultural land use monitoring. Practical application of this methodology is foreseen, among others, in the water quality monitoring. Effective pesticide monitoring relies also on spatial distribution of applied pesticides, which can be derived from crop - plant protection product relationship. Knowledge of areas with predominant occurrence of specific crop based on remote sensing data described above can be used for a forecast of probable plant protection product application, thus cost-effective pesticide monitoring. The remote sensing data used on a continuous basis can be used in other long-term water management issues and provide valuable data for decision makers. Acknowledgement: Authors acknowledge the financial support of the Ministry of Education, Youth and Sports of the Czech Republic (grants No. 2B06095 and No. MSM 6046070901). The study was also supported by ESA CAT-1 (ref. 4358) and SOSI projects (Spatial Observation Services and Infrastructure; ref. GSTP-RTDA-EOPG-SW-08-0004).

Geosensors to Support Crop Production: Current Applications and User Requirements

PubMed Central

Thessler, Sirpa; Kooistra, Lammert; Teye, Frederick; Huitu, Hanna; Bregt, Arnold K.

2011-01-01

Sensor technology, which benefits from high temporal measuring resolution, real-time data transfer and high spatial resolution of sensor data that shows in-field variations, has the potential to provide added value for crop production. The present paper explores how sensors and sensor networks have been utilised in the crop production process and what their added-value and the main bottlenecks are from the perspective of users. The focus is on sensor based applications and on requirements that users pose for them. Literature and two use cases were reviewed and applications were classified according to the crop production process: sensing of growth conditions, fertilising, irrigation, plant protection, harvesting and fleet control. The potential of sensor technology was widely acknowledged along the crop production chain. Users of the sensors require easy-to-use and reliable applications that are actionable in crop production at reasonable costs. The challenges are to develop sensor technology, data interoperability and management tools as well as data and measurement services in a way that requirements can be met, and potential benefits and added value can be realized in the farms in terms of higher yields, improved quality of yields, decreased input costs and production risks, and less work time and load. PMID:22163978

Parametric Investigation of Laser Doppler Microphones

NASA Astrophysics Data System (ADS)

Daoud, M.; Naguib, A.

2002-11-01

The concept of a Laser Doppler Microphone (LDM) is based on utilizing the Doppler frequency shift of a focused laser beam to measure the unsteady velocity of the center point of a flexible polymer diaphragm that is mounted on top of a hole and subjected to the unsteady pressure. Time integration of the velocity signal yields a time series of the diaphragm displacement, which can be converted to pressure from knowledge of the sensor's deflection sensitivity. In our APS/DFD presentation last year, the stringent frequency resolution requirement of these new sensors and methods to meet this requirement were discussed. Here, the dependence of the sensor characteristics (sensitivity, bandwidth, and noise floor) on various significant parameters is investigated in detail by calibrating the sensor in a plane wave tube in the frequency range of 50 - 5000 Hz. Parameters investigated include sensor diaphragm material and thickness, sensor size, damping of the diaphragm motion and laser beam spot size. The results shed light on the operating limits of the new sensor and demonstrate its ability to conduct high-spatial-resolution measurements in typical high-Reynolds-number test facilities. Moreover, calibrated LDM sensors were used to conduct measurements in a separating/reattaching flow and the results are compared to classical electret-type microphones with a similar sensing diameter.

A thin wideband high-spatial-resolution focusing metasurface for near-field passive millimeter-wave imaging

NASA Astrophysics Data System (ADS)

Chu, Hongjun; Qi, Jiaran; Xiao, Shanshan; Qiu, Jinghui

2018-04-01

In this paper, we present a flat transmission-type focusing metasurface for the near-field passive millimeter-wave (PMMW) imaging systems. Considering the non-uniform wavefront of the actual feeding horn, the metasurface is configured by unit cells consisting of coaxial annular apertures and is optimized to achieve broadband, high spatial resolution, and polarization insensitive properties important for PMMW imaging applications in the frequency range from 33 GHz to 37 GHz, with the focal spot as small as 0.43λ0 (@35 GHz). A prototype of the proposed metasurface is fabricated, and the measurement results fairly agree with the simulation ones. Furthermore, an experimental single-sensor PMMW imaging system is constructed based on the metasurface and a Ka-band direct detection radiometer. The experimental results show that the azimuth resolution of the system can reach approximately 4 mm (≈0.47λ0). It is shown that the proposed metasurface can potentially replace the bulky dielectric-lens or reflector antenna to achieve possibly more compact PMMW imaging systems with high spatial resolution approaching the diffraction-limit.

A High-Resolution Aerosol Retrieval Method for Urban Areas Using MISR Data

NASA Astrophysics Data System (ADS)

Moon, T.; Wang, Y.; Liu, Y.; Yu, B.

2012-12-01

Satellite-retrieved Aerosol Optical Depth (AOD) can provide a cost-effective way to monitor particulate air pollution without using expensive ground measurement sensors. One of the current state-of-the-art AOD retrieval method is NASA's Multi-angle Imaging SpectroRadiometer (MISR) operational algorithm, which has the spatial resolution of 17.6 km x 17.6 km. While the MISR baseline scheme already leads to exciting research opportunities to study particle compositions at regional scale, its spatial resolution is too coarse for analyzing urban areas where the AOD level has stronger spatial variations. We develop a novel high-resolution AOD retrieval algorithm that still uses MISR's radiance observations but has the resolution of 4.4km x 4.4km. We achieve the high resolution AOD retrieval by implementing a hierarchical Bayesian model and Monte-Carlo Markov Chain (MCMC) inference method. Our algorithm not only improves the spatial resolution, but also extends the coverage of AOD retrieval and provides with additional composition information of aerosol components that contribute to the AOD. We validate our method using the recent NASA's DISCOVER-AQ mission data, which contains the ground measured AOD values for Washington DC and Baltimore area. The validation result shows that, compared to the operational MISR retrievals, our scheme has 41.1% more AOD retrieval coverage for the DISCOVER-AQ data points and 24.2% improvement in mean-squared error (MSE) with respect to the AERONET ground measurements.

Scanning magnetic tunnel junction microscope for high-resolution imaging of remanent magnetization fields

NASA Astrophysics Data System (ADS)

Lima, E. A.; Bruno, A. C.; Carvalho, H. R.; Weiss, B. P.

2014-10-01

Scanning magnetic microscopy is a new methodology for mapping magnetic fields with high spatial resolution and field sensitivity. An important goal has been to develop high-performance instruments that do not require cryogenic technology due to its high cost, complexity, and limitation on sensor-to-sample distance. Here we report the development of a low-cost scanning magnetic microscope based on commercial room-temperature magnetic tunnel junction (MTJ) sensors that typically achieves spatial resolution better than 7 µm. By comparing different bias and detection schemes, optimal performance was obtained when biasing the MTJ sensor with a modulated current at 1.0 kHz in a Wheatstone bridge configuration while using a lock-in amplifier in conjunction with a low-noise custom-made preamplifier. A precision horizontal (x-y) scanning stage comprising two coupled nanopositioners controls the position of the sample and a linear actuator adjusts the sensor-to-sample distance. We obtained magnetic field sensitivities better than 150 nT/Hz1/2 between 0.1 and 10 Hz, which is a critical frequency range for scanning magnetic microscopy. This corresponds to a magnetic moment sensitivity of 10-14 A m2, a factor of 100 better than achievable with typical commercial superconducting moment magnetometers. It also represents an improvement in sensitivity by a factor between 10 and 30 compared to similar scanning MTJ microscopes based on conventional bias-detection schemes. To demonstrate the capabilities of the instrument, two polished thin sections of representative geological samples were scanned along with a synthetic sample containing magnetic microparticles. The instrument is usable for a diversity of applications that require mapping of samples at room temperature to preserve magnetic properties or viability, including paleomagnetism and rock magnetism, nondestructive evaluation of materials, and biological assays.

Vegetation Coverage and Impervious Surface Area Estimated Based on the Estarfm Model and Remote Sensing Monitoring

NASA Astrophysics Data System (ADS)

Hu, Rongming; Wang, Shu; Guo, Jiao; Guo, Liankun

2018-04-01

Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC) and impervious layer with high spatiotemporal resolution (30 m, 8 day) were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1) ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2) The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.

Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Dube, Timothy; Mutanga, Onisimo

2015-03-01

Aboveground biomass estimation is critical in understanding forest contribution to regional carbon cycles. Despite the successful application of high spatial and spectral resolution sensors in aboveground biomass (AGB) estimation, there are challenges related to high acquisition costs, small area coverage, multicollinearity and limited availability. These challenges hamper the successful regional scale AGB quantification. The aim of this study was to assess the utility of the newly-launched medium-resolution multispectral Landsat 8 Operational Land Imager (OLI) dataset with a large swath width, in quantifying AGB in a forest plantation. We applied different sets of spectral analysis (test I: spectral bands; test II: spectral vegetation indices and test III: spectral bands + spectral vegetation indices) in testing the utility of Landsat 8 OLI using two non-parametric algorithms: stochastic gradient boosting and the random forest ensembles. The results of the study show that the medium-resolution multispectral Landsat 8 OLI dataset provides better AGB estimates for Eucalyptus dunii, Eucalyptus grandis and Pinus taeda especially when using the extracted spectral information together with the derived spectral vegetation indices. We also noted that incorporating the optimal subset of the most important selected medium-resolution multispectral Landsat 8 OLI bands improved AGB accuracies. We compared medium-resolution multispectral Landsat 8 OLI AGB estimates with Landsat 7 ETM + estimates and the latter yielded lower estimation accuracies. Overall, this study demonstrates the invaluable potential and strength of applying the relatively affordable and readily available newly-launched medium-resolution Landsat 8 OLI dataset, with a large swath width (185-km) in precisely estimating AGB. This strength of the Landsat OLI dataset is crucial especially in sub-Saharan Africa where high-resolution remote sensing data availability remains a challenge.

Fiber Fabry-Perot tip sensor based on multimode photonic crystal fiber

NASA Astrophysics Data System (ADS)

Wu, Di; Huang, Yu; Fu, Jian-Yu; Wang, Guo-Yin

2015-03-01

We propose a novel Fabry-Perot interferometer (FPI) sensor for simultaneous measurement of refractive index (RI) and temperature based on Fresnel reflection and the thermo-optic effect of silica. The sensor head consists of a short section of multimode photonic crystal fiber (MPCF) and a conventional single mode fiber (SMF), where two thin films are formed by collapsing the air holes of MPCF with a commercialized fusion splicer. Experimental results show that such a device has a linear RI sensitivity of ~21.52 dB/RIU (RI unit) and a linear optical path difference (OPD) temperature sensitivity of ~25 nm/°C. In addition, a high RI resolution of about ~1.7×10-5 is obtained by using the Fourier transformation to decompose the spectral response in different spatial frequencies. Low-cost, easy fabrication and high resolution make it appropriate for practical applications.

Passive wireless antenna sensors for crack detection and shear/compression sensing

NASA Astrophysics Data System (ADS)

Mohammad, Irshad

Despite the fact that engineering components and structures are carefully designed against fatigue failures, 50 to 90% of mechanical failures are due to fatigue crack development. The severity of the failure depends on both the crack length and its orientation. Many types of sensors are available that can detect fatigue crack propagation. However, crack orientation detection has been rarely reported in the literature. We evaluated a patch antenna sensor capable of detecting crack propagation as well as crack orientation changes. The aim of these sensors would be to evaluate the real-time health condition of metallic structures to avoid catastrophic failures. The proposed crack sensing system consists of a dielectric substrate with a ground plane on one side of the substrate and an antenna patch printed on the other side of the substrate. The ground plane and the antenna patch, both conductive in nature, form an electromagnetic resonant cavity that radiates at distinct frequencies. These frequencies are monitored to evaluate the condition of cracks. A wireless sensor array can be realized by implementing a wireless interrogation unit. The scientific merits of this research are: 1) high sensitivity: it was demonstrated that the antenna sensors can detect crack growth with a sub-millimeter resolution; 2) passive wireless operation: based on microstrip antennas, the antenna sensors encode the sensing information in the backscattered antenna signal and thus can transmit the information without needing a local battery; 3) thin and conformal: the entire sensor unit is less than a millimeter thick and highly conformal; 4) crack orientation detection: the crack orientation on the structure can be precisely evaluated based on a single parameter, which only few sensors can accomplish. In addition to crack detection, the patch antenna sensors are also investigated for measuring shear and pressure forces, with an aim to study the formation, diagnostics and prevention of foot ulcers in diabetic patients. These sensors were vertically integrated and embedded in the insole of shoes for measuring plantar pressure/shear distribution. The scientific merits of this proposed research are: 1) simultaneous shear/pressure measurement : current smart shoe technology can only measure shear and pressure separately due to the size of the shear sensor. The proposed sensor can measure shear and pressure deformation simultaneously; 2) high sensitivity and spatial resolution: these sensors are very sensitive and have compact size that enables measuring stress distribution with fine spatial resolution; 3) passive and un-tethered operation: the sensor transponder was mounted on the top surface of the shoe to facilitate wireless interrogation of the sensor array embedded in the insole of the shoe, eliminating external wiring completely.

High-speed three-dimensional measurements with a fringe projection-based optical sensor

NASA Astrophysics Data System (ADS)

Bräuer-Burchardt, Christian; Breitbarth, Andreas; Kühmstedt, Peter; Notni, Gunther

2014-11-01

An optical three-dimensional (3-D) sensor based on a fringe projection technique that realizes the acquisition of the surface geometry of small objects was developed for highly resolved and ultrafast measurements. It realizes a data acquisition rate up to 60 high-resolution 3-D datasets per second. The high measurement velocity was achieved by consequent fringe code reduction and parallel data processing. The reduction of the length of the fringe image sequence was obtained by omission of the Gray code sequence using the geometric restrictions of the measurement objects and the geometric constraints of the sensor arrangement. The sensor covers three different measurement fields between 20 mm×20 mm and 40 mm×40 mm with a spatial resolution between 10 and 20 μm, respectively. In order to obtain a robust and fast recalibration of the sensor after change of the measurement field, a calibration procedure based on single shot analysis of a special test object was applied which works with low effort and time. The sensor may be used, e.g., for quality inspection of conductor boards or plugs in real-time industrial applications.

Behavior analysis for elderly care using a network of low-resolution visual sensors

NASA Astrophysics Data System (ADS)

Eldib, Mohamed; Deboeverie, Francis; Philips, Wilfried; Aghajan, Hamid

2016-07-01

Recent advancements in visual sensor technologies have made behavior analysis practical for in-home monitoring systems. The current in-home monitoring systems face several challenges: (1) visual sensor calibration is a difficult task and not practical in real-life because of the need for recalibration when the visual sensors are moved accidentally by a caregiver or the senior citizen, (2) privacy concerns, and (3) the high hardware installation cost. We propose to use a network of cheap low-resolution visual sensors (30×30 pixels) for long-term behavior analysis. The behavior analysis starts by visual feature selection based on foreground/background detection to track the motion level in each visual sensor. Then a hidden Markov model (HMM) is used to estimate the user's locations without calibration. Finally, an activity discovery approach is proposed using spatial and temporal contexts. We performed experiments on 10 months of real-life data. We show that the HMM approach outperforms the k-nearest neighbor classifier against ground truth for 30 days. Our framework is able to discover 13 activities of daily livings (ADL parameters). More specifically, we analyze mobility patterns and some of the key ADL parameters to detect increasing or decreasing health conditions.

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 1: A cloud ensemble/radiative parameterization for sensor response (report version)

NASA Technical Reports Server (NTRS)

Olson, William S.; Raymond, William H.

1990-01-01

The physical retrieval of geophysical parameters based upon remotely sensed data requires a sensor response model which relates the upwelling radiances that the sensor observes to the parameters to be retrieved. In the retrieval of precipitation water contents from satellite passive microwave observations, the sensor response model has two basic components. First, a description of the radiative transfer of microwaves through a precipitating atmosphere must be considered, because it is necessary to establish the physical relationship between precipitation water content and upwelling microwave brightness temperature. Also the spatial response of the satellite microwave sensor (or antenna pattern) must be included in the description of sensor response, since precipitation and the associated brightness temperature field can vary over a typical microwave sensor resolution footprint. A 'population' of convective cells, as well as stratiform clouds, are simulated using a computationally-efficient multi-cylinder cloud model. Ensembles of clouds selected at random from the population, distributed over a 25 km x 25 km model domain, serve as the basis for radiative transfer calculations of upwelling brightness temperatures at the SSM/I frequencies. Sensor spatial response is treated explicitly by convolving the upwelling brightness temperature by the domain-integrated SSM/I antenna patterns. The sensor response model is utilized in precipitation water content retrievals.

A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape.

PubMed

Lausch, Angela; Pause, Marion; Merbach, Ines; Zacharias, Steffen; Doktor, Daniel; Volk, Martin; Seppelt, Ralf

2013-02-01

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the "One Sensor at Different Scales" (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R (2) of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.

Synthetic Scene Generation of the Stennis V and V Target Range for the Calibration of Remote Sensing Systems

NASA Technical Reports Server (NTRS)

Cao, Chang-Yong; Blonski, Slawomir; Ryan, Robert; Gasser, Jerry; Zanoni, Vicki

1999-01-01

The verification and validation (V&V) target range developed at Stennis Space Center is a useful test site for the calibration of remote sensing systems. In this paper, we present a simple algorithm for generating synthetic radiance scenes or digital models of this target range. The radiation propagation for the target in the solar reflective and thermal infrared spectral regions is modeled using the atmospheric radiative transfer code MODTRAN 4. The at-sensor, in-band radiance and spectral radiance for a given sensor at a given altitude is predicted. Software is developed to generate scenes with different spatial and spectral resolutions using the simulated at-sensor radiance values. The radiometric accuracy of the simulation is evaluated by comparing simulated with AVIRIS acquired radiance values. The results show that in general there is a good match between AVIRIS sensor measured and MODTRAN predicted radiance values for the target despite the fact that some anomalies exist. Synthetic scenes provide a cost-effective way for in-flight validation of the spatial and radiometric accuracy of the data. Other applications include mission planning, sensor simulation, and trade-off analysis in sensor design.

Generation of Ground Truth Datasets for the Analysis of 3d Point Clouds in Urban Scenes Acquired via Different Sensors

NASA Astrophysics Data System (ADS)

Xu, Y.; Sun, Z.; Boerner, R.; Koch, T.; Hoegner, L.; Stilla, U.

2018-04-01

In this work, we report a novel way of generating ground truth dataset for analyzing point cloud from different sensors and the validation of algorithms. Instead of directly labeling large amount of 3D points requiring time consuming manual work, a multi-resolution 3D voxel grid for the testing site is generated. Then, with the help of a set of basic labeled points from the reference dataset, we can generate a 3D labeled space of the entire testing site with different resolutions. Specifically, an octree-based voxel structure is applied to voxelize the annotated reference point cloud, by which all the points are organized by 3D grids of multi-resolutions. When automatically annotating the new testing point clouds, a voting based approach is adopted to the labeled points within multiple resolution voxels, in order to assign a semantic label to the 3D space represented by the voxel. Lastly, robust line- and plane-based fast registration methods are developed for aligning point clouds obtained via various sensors. Benefiting from the labeled 3D spatial information, we can easily create new annotated 3D point clouds of different sensors of the same scene directly by considering the corresponding labels of 3D space the points located, which would be convenient for the validation and evaluation of algorithms related to point cloud interpretation and semantic segmentation.

Phase-based, high spatial resolution and distributed, static and dynamic strain sensing using Brillouin dynamic gratings in optical fibers.

PubMed

Bergman, Arik; Langer, Tomi; Tur, Moshe

2017-03-06

A novel technique combining Brillouin phase-shift measurements with Brillouin dynamic gratings (BDGs) reflectometry in polarization-maintaining fibers is presented here for the first time. While a direct measurement of the optical phase in standard BDG setups is impractical due to non-local phase contributions, their detrimental effect is reduced by ~4 orders of magnitude through the coherent addition of Stokes and anti-Stokes reflections from two counter-propagating BDGs in the fiber. The technique advantageously combines the high-spatial-resolution of BDGs reflectometry with the increased tolerance to optical power fluctuations of phasorial measurements, to enhance the performance of fiber-optic strain sensors. We demonstrate a distributed measurement (20cm spatial-resolution) of both static and dynamic (5kHz of vibrations at a sampling rate of 1MHz) strain fields acting on the fiber, in good agreement with theory and (for the static case) with the results of commercial reflectometers.

Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework

PubMed Central

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-01-01

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859

Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (WSN) framework.

PubMed

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-11-27

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.

Time-resolved quantitative-phase microscopy of laser-material interactions using a wavefront sensor.

PubMed

Gallais, Laurent; Monneret, Serge

2016-07-15

We report on a simple and efficient technique based on a wavefront sensor to obtain time-resolved amplitude and phase images of laser-material interactions. The main interest of the technique is to obtain quantitative self-calibrated phase measurements in one shot at the femtosecond time-scale, with high spatial resolution. The technique is used for direct observation and quantitative measurement of the Kerr effect in a fused silica substrate and free electron generation by photo-ionization processes in an optical coating.

High performance and highly reliable Raman-based distributed temperature sensors based on correlation-coded OTDR and multimode graded-index fibers

NASA Astrophysics Data System (ADS)

Soto, M. A.; Sahu, P. K.; Faralli, S.; Sacchi, G.; Bolognini, G.; Di Pasquale, F.; Nebendahl, B.; Rueck, C.

2007-07-01

The performance of distributed temperature sensor systems based on spontaneous Raman scattering and coded OTDR are investigated. The evaluated DTS system, which is based on correlation coding, uses graded-index multimode fibers, operates over short-to-medium distances (up to 8 km) with high spatial and temperature resolutions (better than 1 m and 0.3 K at 4 km distance with 10 min measuring time) and high repeatability even throughout a wide temperature range.

Development of a Dynamic Web Mapping Service for Vegetation Productivity Using Earth Observation and in situ Sensors in a Sensor Web Based Approach

PubMed Central

Kooistra, Lammert; Bergsma, Aldo; Chuma, Beatus; de Bruin, Sytze

2009-01-01

This paper describes the development of a sensor web based approach which combines earth observation and in situ sensor data to derive typical information offered by a dynamic web mapping service (WMS). A prototype has been developed which provides daily maps of vegetation productivity for the Netherlands with a spatial resolution of 250 m. Daily available MODIS surface reflectance products and meteorological parameters obtained through a Sensor Observation Service (SOS) were used as input for a vegetation productivity model. This paper presents the vegetation productivity model, the sensor data sources and the implementation of the automated processing facility. Finally, an evaluation is made of the opportunities and limitations of sensor web based approaches for the development of web services which combine both satellite and in situ sensor sources. PMID:22574019

Monitoring algal blooms in drinking water reservoirs using the Landsat-8 Operational Land Imager

EPA Science Inventory

In this study, we demonstrated that the Landsat-8 Operational Land Imager (OLI) sensor is a powerful tool that can provide periodic and system-wide information on the condition of drinking water reservoirs. The OLI is a multispectral radiometer (30 m spatial resolution) that allo...

Investigating trends in water use over the Choptank River watershed using a multi-satellite data fusion approach

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing technologies have been widely used to map spatiotemporal variability in consumptive water use (or evapotranspiration; ET) for agricultural water management applications. However, current satellite-based sensors with the high spatial resolution required to map ET at sub-field...

Investigating water use over the Choptank River Watershed using a multi-satellite data fusion approach

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing technologies have been widely used to map spatiotemporal variability in consumptive water use (or evapotranspiration; ET) for agricultural water management applications. However, current satellite-based sensors with the high spatial resolution required to map ET at sub-field...

Passive microwave soil moisture downscaling using vegetation index and skin surface temperature

USDA-ARS?s Scientific Manuscript database

Soil moisture satellite estimates are available from a variety of passive microwave satellite sensors, but their spatial resolution is frequently too coarse for use by land managers and other decision makers. In this paper, a soil moisture downscaling algorithm based on a regression relationship bet...

An Integrated Set of Observations to Link Conditions of Great Lakes Nearshore Waters to their Coastal Watersheds

EPA Science Inventory

We combine three elements for a comprehensive characterization that links nearshore conditions with coastal watershed disturbance metrics. The three elements are: 1) a shore-parallel, high-resolution nearshore survey using continuous in situ towed sensors; 2) a spatially-balanc...

Variations in the Sea Ice Edge and the Marginal Ice Zone on Different Spatial Scales as Observed from Different Satellite Sensor

NASA Technical Reports Server (NTRS)

Markus, Thorsten; Henrichs, John

2006-01-01

The Marginal sea Ice Zone (MIZ) and the sea ice edge are the most dynamic areas of the sea ice cover. Knowledge of the sea ice edge location is vital for routing shipping in the polar regions. The ice edge is the location of recurrent plankton blooms, and is the habitat for a number of animals, including several which are under severe ecological threat. Polar lows are known to preferentially form along the sea ice edge because of induced atmospheric baroclinicity, and the ice edge is also the location of both vertical and horizontal ocean currents driven by thermal and salinity gradients. Finally, sea ice is both a driver and indicator of climate change and monitoring the position of the ice edge accurately over long time periods enables assessment of the impact of global and regional warming near the poles. Several sensors are currently in orbit that can monitor the sea ice edge. These sensors, though, have different spatial resolutions, different limitations, and different repeat frequencies. Satellite passive microwave sensors can monitor the ice edge on a daily or even twice-daily basis, albeit with low spatial resolution - 25 km for the Special Sensor Microwave Imager (SSM/I) or 12.5 km for the Advanced Microwave Scanning Radiometer (AMSR-E). Although special methods exist that allow the detection of the sea ice edge at a quarter of that nominal resolution (PSSM). Visible and infrared data from the Advanced Very High Resolution Radiometer (AVHRR) and from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide daily coverage at 1 km and 250 m, respectively, but the surface observations me limited to cloud-free periods. The Landsat 7 Enhanced Thematic Mapper (ETM+) has a resolution of 15 to 30 m but is limited to cloud-free periods as well, and does not provide daily coverage. Imagery from Synthetic Aperture Radar (SAR) instruments has resolutions of tens of meters to 100 m, and can be used to distinguish open water and sea ice on the basis of surface and volume scattering characteristics. The Canadian RADARSAT C-band SAR provides data that cover the Arctic Ocean and the MIZ every 3 days. A change-point detection approach was utilized to obtain an ice edge estimate from the RADARSAT data The Quickscat scatterometer provides ice edge information with a resolution of a few kilometers on a near-daily basis. During portions of March and April of 2003 a series of aircraft flights were conducted over the ice edge in the Bering Sea carrying the Polarimetric Scanning Radiometer (PSR), which provides spectral coverage identical with the AMSR-E instrument at a resolution of 500 meters. In this study we investigated these different data sets and analyzed differences in their definition of the sea ice edge and the marginal ice zone and how these differences as well as their individual limitations affect the monitoring of the ice edge dynamics. We also examined how the nature of the sea ice edge, including its location, compactness and shape, changes over the seasons. Our approach was based on calculation of distances between ice edges derived from the satellite and aircraft data sets listed above as well as spectral coherence methods and shape parameters such as tortuosity, curvature, and fractional dimension.

Comparison of FLAASH and QUAC atmospheric correction methods for Resourcesat-2 LISS-IV data

NASA Astrophysics Data System (ADS)

Saini, V.; Tiwari, R. K.; Gupta, R. P.

2016-05-01

The LISS-IV sensor aboard Resourcesat-2 is a modern relatively high resolution multispectral sensor having immense potential for generation of good quality land use land cover maps. It generates data in high (10-bit) radiometric resolution and 5.8 m spatial resolution and has three bands in the visible-near infrared region. This is of particular importance to global community as the data are provided at highly competitive prices. However, no literature describing the atmospheric correction of Resourcesat-2-LISS-IV data could be found. Further, without atmospheric correction full radiometric potential of any remote sensing data remains underutilized. The FLAASH and QUAC module of ENVI software are highly used by researchers for atmospheric correction of popular remote sensing data such as Landsat, SPOT, IKONOS, LISS-I, III etc. This article outlines a methodology for atmospheric correction of Resourcesat-2-LISS-IV data. Also, a comparison of reflectance from different atmospheric correction modules (FLAASH and QUAC) with TOA and standard data has been made to determine the best suitable method for reflectance estimation for this sensor.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors.

PubMed

Lange, Maximilian; Dechant, Benjamin; Rebmann, Corinna; Vohland, Michael; Cuntz, Matthias; Doktor, Daniel

2017-08-11

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors

PubMed Central

Lange, Maximilian; Rebmann, Corinna; Cuntz, Matthias; Doktor, Daniel

2017-01-01

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure. PMID:28800065

MTF analysis of LANDSAT-4 Thematic Mapper

NASA Technical Reports Server (NTRS)

Schowengerdt, R.

1983-01-01

The spatial radiance distribution of a ground target must be known to a resolution at least four to five times greater than that of the system under test when measuring a satellite sensor's modulation transfer function. Calibration of the target requires either the use of man-made special purpose targets with known properties, e.g., a small reflective mirror or a dark-light linear pattern such as line or edge, or use of relatively high resolution underflight imagery to calibrate an arbitrary ground scene. Both approaches are to be used in addition a technique that utilizes an analytical model for the scene spatial frequency power spectrum is being investigated as an alternative to calibration of the scene.

MTF Analysis of LANDSAT-4 Thematic Mapper

NASA Technical Reports Server (NTRS)

Schowengerdt, R.

1985-01-01

The spatial radiance distribution of a ground target must be known to a resolution at least four to five times greater than that of the system under test when measuring a satellite sensor's modulation transfer function. Calibration of the target requires either the use of man-made special purpose targets with known properties, e.g., a small reflective mirror or a dark-light linear pattern such as line or edge, or use of relatively high resolution underflight imagery to calibrate an arbitrary ground scene. Both approaches are to be used, in addition a technique that utilizes an analytical model of the scene spatial frequency power spectrum is being investigated as an alternative to calibration of the scene.

Long-Term Large-Scale Bias-Adjusted Precipitation Estimates at High Spatial and Temporal Resolution Derived from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Precipitation Reanalysis over CONUS

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Seo, D. J.; Kim, B.

2014-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over Continental United States (CONUS) is nearly completed for the period covering from 2000 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network - Daily (GHCN-D) are used to adjust for those biases and to merge with the radar only product to provide a multi-sensor estimate. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. After assessing the bias and applying reduction or elimination techniques, we are investigating the kriging method and its variants such as simple kriging (SK), ordinary kriging (OK), and conditional bias-penalized Kriging (CBPK) among others. In addition we hope to generate estimates of uncertainty for the gridded estimate. In this work the methodology is presented as well as a comparison between the radar-only product and the final multi-sensor QPE product. The comparison is performed at various time scales from the sub-hourly, to annual. In addition, comparisons over the same period with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) and satellite products (TMPA, CMORPH, PERSIANN) are provided in order to give a detailed picture of the improvements and remaining challenges.

Wave Dissipation over Nearshore Beach Morphology: Insights from High-Resolution LIDAR Observations and the SWASH Wave Model

NASA Astrophysics Data System (ADS)

Mulligan, R. P.; Gomes, E.; McNinch, J.; Brodie, K. L.

2016-02-01

Numerical modelling of the nearshore zone can be computationally intensive due to the complexity of wave breaking, and the need for high temporal and spatial resolution. In this study we apply the SWASH non-hydrostatic wave-flow model that phase-resolves the free surface and fluid motions in the water column at high resolution. The model is forced using observed directional energy spectra, and results are compared to wave observations during moderate storm events. Observations are collected outside the surf zone using acoustic wave and currents sensors, and inside the surf zone over a 100 m transect using high-resolution LIDAR measurements of the sea surface from a sensor mounted on a tower on the beach dune at the Field Research Facility in Duck, NC. The model is applied to four cases with different wave conditions and bathymetry, and used to predict the spatial variability in wave breaking, and correlation between energy dissipation and morphologic features. Model results compare well with observations of spectral evolution outside the surf zone, and with the remotely sensed observations of wave transformation inside the surf zone. The results indicate the importance of nearshore bars, rip-channels, and larger features (major scour depression under the pier following large waves from Hurricane Irene) on the location of wave breaking and alongshore variability in wave energy dissipation.

Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2015-01-01

The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODIS land surface products robust and reliable. The long-term 30-m Landsat data provide spatial detailed information for characterizing human-scale processes and have been used for land cover and land change studies. The main goal of this study is to combine 250-m MODIS GSN and 30-m Landsat observations to generate a quality-improved high spatial resolution (30-m) GSN database. A rule-based piecewise regression GSN model based on MODIS and Landsat data was developed. Results show a strong correlation between predicted GSN and actual GSN (r = 0.97, average error = 0.026). The most important Landsat variables in the GSN model are Normalized Difference Vegetation Indices (NDVIs) in May and August. The derived MODIS-Landsat-based 30-m GSN map provides biophysical information for moderate-scale ecological features. This multiple sensor study retains the detailed seasonal dynamic information captured by MODIS and leverages the high-resolution information from Landsat, which will be useful for regional ecosystem studies.

A Buoy for Continuous Monitoring of Suspended Sediment Dynamics

PubMed Central

Mueller, Philip; Thoss, Heiko; Kaempf, Lucas; Güntner, Andreas

2013-01-01

Knowledge of Suspended Sediments Dynamics (SSD) across spatial scales is relevant for several fields of hydrology, such as eco-hydrological processes, the operation of hydrotechnical facilities and research on varved lake sediments as geoarchives. Understanding the connectivity of sediment flux between source areas in a catchment and sink areas in lakes or reservoirs is of primary importance to these fields. Lacustrine sediments may serve as a valuable expansion of instrumental hydrological records for flood frequencies and magnitudes, but depositional processes and detrital layer formation in lakes are not yet fully understood. This study presents a novel buoy system designed to continuously measure suspended sediment concentration and relevant boundary conditions at a high spatial and temporal resolution in surface water bodies. The buoy sensors continuously record turbidity as an indirect measure of suspended sediment concentrations, water temperature and electrical conductivity at up to nine different water depths. Acoustic Doppler current meters and profilers measure current velocities along a vertical profile from the water surface to the lake bottom. Meteorological sensors capture the atmospheric boundary conditions as main drivers of lake dynamics. It is the high spatial resolution of multi-point turbidity measurements, the dual-sensor velocity measurements and the temporally synchronous recording of all sensors along the water column that sets the system apart from existing buoy systems. Buoy data collected during a 4-month field campaign in Lake Mondsee demonstrate the potential and effectiveness of the system in monitoring suspended sediment dynamics. Observations were related to stratification and mixing processes in the lake and increased turbidity close to a catchment outlet during flood events. The rugged buoy design assures continuous operation in terms of stability, energy management and sensor logging throughout the study period. We conclude that the buoy is a suitable tool for continuous monitoring of suspended sediment concentrations and general dynamics in fresh water bodies. PMID:24129017

Planar implantable sensor for in vivo measurement of cellular oxygen metabolism in brain tissue.

PubMed

Tsytsarev, Vassiliy; Akkentli, Fatih; Pumbo, Elena; Tang, Qinggong; Chen, Yu; Erzurumlu, Reha S; Papkovsky, Dmitri B

2017-04-01

Brain imaging methods are continually improving. Imaging of the cerebral cortex is widely used in both animal experiments and charting human brain function in health and disease. Among the animal models, the rodent cerebral cortex has been widely used because of patterned neural representation of the whiskers on the snout and relative ease of activating cortical tissue with whisker stimulation. We tested a new planar solid-state oxygen sensor comprising a polymeric film with a phosphorescent oxygen-sensitive coating on the working side, to monitor dynamics of oxygen metabolism in the cerebral cortex following sensory stimulation. Sensory stimulation led to changes in oxygenation and deoxygenation processes of activated areas in the barrel cortex. We demonstrate the possibility of dynamic mapping of relative changes in oxygenation in live mouse brain tissue with such a sensor. Oxygenation-based functional magnetic resonance imaging (fMRI) is very effective method for functional brain mapping but have high costs and limited spatial resolution. Optical imaging of intrinsic signal (IOS) does not provide the required sensitivity, and voltage-sensitive dye optical imaging (VSDi) has limited applicability due to significant toxicity of the voltage-sensitive dye. Our planar solid-state oxygen sensor imaging approach circumvents these limitations, providing a simple optical contrast agent with low toxicity and rapid application. The planar solid-state oxygen sensor described here can be used as a tool in visualization and real-time analysis of sensory-evoked neural activity in vivo. Further, this approach allows visualization of local neural activity with high temporal and spatial resolution. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-energy x-ray imaging and sensing for diagnostic and control of the burning plasma.

PubMed

Stutman, D; Tritz, K; Finkenthal, M

2012-10-01

New diagnostic and sensor designs are needed for future burning plasma (BP) fusion experiments, having good space and time resolution and capable of prolonged operation in the harsh BP environment. We evaluate the potential of multi-energy x-ray imaging with filtered detector arrays for BP diagnostic and control. Experimental studies show that this simple and robust technique enables measuring with good accuracy, speed, and spatial resolution the T(e) profile, impurity content, and MHD activity in a tokamak. Applied to the BP this diagnostic could also serve for non-magnetic sensing of the plasma position, centroid, ELM, and RWM instability. BP compatible x-ray sensors are proposed using "optical array" or "bi-cell" detectors.

Distributed fiber strain and vibration sensor based on Brillouin optical time-domain reflectometry and polarization optical time-domain reflectometry.

PubMed

Wang, Feng; Zhang, Xuping; Wang, Xiangchuan; Chen, Haisheng

2013-07-15

A distributed fiber strain and vibration sensor which effectively combines Brillouin optical time-domain reflectometry and polarization optical time-domain reflectometry is proposed. Two reference beams with orthogonal polarization states are, respectively, used to perform the measurement. By using the signal obtained from either reference beam, the vibration of fiber can be measured from the polarization effect. After combining the signals obtained by both reference beams, the strain can be measured from the Brillouin effect. In the experiment, 10 m spatial resolution, 0.6 kHz frequency measurement range, 2.5 Hz frequency resolution, and 0.2 MHz uncertainty of Brillouin frequency measurement are realized for a 4 km sensing distance.

Automatic Registration of GF4 Pms: a High Resolution Multi-Spectral Sensor on Board a Satellite on Geostationary Orbit

NASA Astrophysics Data System (ADS)

Gao, M.; Li, J.

2018-04-01

Geometric correction is an important preprocessing process in the application of GF4 PMS image. The method of geometric correction that is based on the manual selection of geometric control points is time-consuming and laborious. The more common method, based on a reference image, is automatic image registration. This method involves several steps and parameters. For the multi-spectral sensor GF4 PMS, it is necessary for us to identify the best combination of parameters and steps. This study mainly focuses on the following issues: necessity of Rational Polynomial Coefficients (RPC) correction before automatic registration, base band in the automatic registration and configuration of GF4 PMS spatial resolution.

Predicting Near Real-Time Inundation Occurrence from Complimentary Satellite Microwave Brightness Temperature Observations

NASA Astrophysics Data System (ADS)

Fisher, C. K.; Pan, M.; Wood, E. F.

2017-12-01

Throughout the world, there is an increasing need for new methods and data that can aid decision makers, emergency responders and scientists in the monitoring of flood events as they happen. In many regions, it is possible to examine the extent of historical and real-time inundation occurrence from visible and infrared imagery provided by sensors such as MODIS or the Landsat TM; however, this is not possible in regions that are densely vegetated or are under persistent cloud cover. In addition, there is often a temporal mismatch between the sampling of a particular sensor and a given flood event, leading to limited observations in near real-time. As a result, there is a need for alternative methods that take full advantage of complimentary remotely sensed data sources, such as available microwave brightness temperature observations (e.g., SMAP, SMOS, AMSR2, AMSR-E, and GMI), to aid in the estimation of global flooding. The objective of this work was to develop a high-resolution mapping of inundated areas derived from multiple satellite microwave sensor observations with a daily temporal resolution. This system consists of first retrieving water fractions from complimentary microwave sensors (AMSR-2 and SMAP) which may spatially and temporally overlap in the region of interest. Using additional information in a Random Forest classifier, including high resolution topography and multiple datasets of inundated area (both historical and empirical), the resulting retrievals are spatially downscaled to derive estimates of the extent of inundation at a scale relevant to management and flood response activities ( 90m or better) instead of the relatively coarse resolution water fractions, which are limited by the microwave sensor footprints ( 5-50km). Here we present the training and validation of this method for the 2015 floods that occurred in Houston, Texas. Comparing the predicted inundation against historical occurrence maps derived from the Landsat TM record and MODIS imagery, we find good agreement for most areas and are able to provide a daily mapping given the increased temporal coverage. These results illustrate the feasibility of a near real-time inundation prediction system driven by multi-sensor satellite microwave observations, which can be extended to provide a daily estimate of global flooding.

Joint Estimation of Effective Brain Wave Activation Modes Using EEG/MEG Sensor Arrays and Multimodal MRI Volumes.

PubMed

Galinsky, Vitaly L; Martinez, Antigona; Paulus, Martin P; Frank, Lawrence R

2018-04-13

In this letter, we present a new method for integration of sensor-based multifrequency bands of electroencephalography and magnetoencephalography data sets into a voxel-based structural-temporal magnetic resonance imaging analysis by utilizing the general joint estimation using entropy regularization (JESTER) framework. This allows enhancement of the spatial-temporal localization of brain function and the ability to relate it to morphological features and structural connectivity. This method has broad implications for both basic neuroscience research and clinical neuroscience focused on identifying disease-relevant biomarkers by enhancing the spatial-temporal resolution of the estimates derived from current neuroimaging modalities, thereby providing a better picture of the normal human brain in basic neuroimaging experiments and variations associated with disease states.

Beam test results of the BTeV silicon pixel detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gabriele Chiodini et al.

2000-09-28

The authors have described the results of the BTeV silicon pixel detector beam test. The pixel detectors under test used samples of the first two generations of Fermilab pixel readout chips, FPIX0 and FPIX1, (indium bump-bonded to ATLAS sensor prototypes). The spatial resolution achieved using analog charge information is excellent for a large range of track inclination. The resolution is still very good using only 2-bit charge information. A relatively small dependence of the resolution on bias voltage is observed. The resolution is observed to depend dramatically on the discriminator threshold, and it deteriorates rapidly for threshold above 4000e{sup {minus}}.

A semiparametric spatio-temporal model for solar irradiance data

DOE PAGES

Patrick, Joshua D.; Harvill, Jane L.; Hansen, Clifford W.

2016-03-01

Here, we evaluate semiparametric spatio-temporal models for global horizontal irradiance at high spatial and temporal resolution. These models represent the spatial domain as a lattice and are capable of predicting irradiance at lattice points, given data measured at other lattice points. Using data from a 1.2 MW PV plant located in Lanai, Hawaii, we show that a semiparametric model can be more accurate than simple interpolation between sensor locations. We investigate spatio-temporal models with separable and nonseparable covariance structures and find no evidence to support assuming a separable covariance structure. These results indicate a promising approach for modeling irradiance atmore » high spatial resolution consistent with available ground-based measurements. Moreover, this kind of modeling may find application in design, valuation, and operation of fleets of utility-scale photovoltaic power systems.« less

Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

NASA Astrophysics Data System (ADS)

Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

2017-03-01

Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

Intelligent data processing of an ultrasonic sensor system for pattern recognition improvements

NASA Astrophysics Data System (ADS)

Na, Seung You; Park, Min-Sang; Hwang, Won-Gul; Kee, Chang-Doo

1999-05-01

Though conventional time-of-flight ultrasonic sensor systems are popular due to the advantages of low cost and simplicity, the usage of the sensors is rather narrowly restricted within object detection and distance readings. There is a strong need to enlarge the amount of environmental information for mobile applications to provide intelligent autonomy. Wide sectors of such neighboring object recognition problems can be satisfactorily handled with coarse vision data such as sonar maps instead of accurate laser or optic measurements. For the usage of object pattern recognition, ultrasonic senors have inherent shortcomings of poor directionality and specularity which result in low spatial resolution and indistinctiveness of object patterns. To resolve these problems an array of increased number of sensor elements has been used for large objects. In this paper we propose a method of sensor array system with improved recognition capability using electronic circuits accompanying the sensor array and neuro-fuzzy processing of data fusion. The circuit changes transmitter output voltages of array elements in several steps. Relying upon the known sensor characteristics, a set of different return signals from neighboring senors is manipulated to provide an enhanced pattern recognition in the aspects of inclination angle, size and shift as well as distance of objects. The results show improved resolution of the measurements for smaller targets.

Combined use of remote sensing and continuous monitoring to analyse the variability of suspended-sediment concentrations in San Francisco Bay, California

USGS Publications Warehouse

Ruhl, C.A.; Schoellhamer, D.H.; Stumpf, R.P.; Lindsay, C.L.

2001-01-01

Analysis of suspended-sediment concentration data in San Francisco Bay is complicated by spatial and temporal variability. In situ optical backscatterance sensors provide continuous suspended-sediment concentration data, but inaccessibility, vandalism, and cost limit the number of potential monitoring stations. Satellite imagery reveals the spatial distribution of surficial-suspended sediment concentrations in the Bay; however, temporal resolution is poor. Analysis of the in situ sensor data in conjunction with the satellite reflectance data shows the effects of physical processes on both the spatial and temporal distribution of suspended sediment in San Francisco Bay. Plumes can be created by large freshwater flows. Zones of high suspended-sediment concentrations in shallow subembayments are associated with wind-wave resuspension and the spring-neap cycle. Filaments of clear and turbid water are caused by different transport processes in deep channels, as opposed to adjacent shallow water.

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers havemore » high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.« less

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

DOE PAGES

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; ...

2016-12-05

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers havemore » high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.« less

Change of spatial information under rescaling: A case study using multi-resolution image series

NASA Astrophysics Data System (ADS)

Chen, Weirong; Henebry, Geoffrey M.

Spatial structure in imagery depends on a complicated interaction between the observational regime and the types and arrangements of entities within the scene that the image portrays. Although block averaging of pixels has commonly been used to simulate coarser resolution imagery, relatively little attention has been focused on the effects of simple rescaling on spatial structure and the explanation and a possible solution to the problem. Yet, if there are significant differences in spatial variance between rescaled and observed images, it may affect the reliability of retrieved biogeophysical quantities. To investigate these issues, a nested series of high spatial resolution digital imagery was collected at a research site in eastern Nebraska in 2001. An airborne Kodak DCS420IR camera acquired imagery at three altitudes, yielding nominal spatial resolutions ranging from 0.187 m to 1 m. The red and near infrared (NIR) bands of the co-registered image series were normalized using pseudo-invariant features, and the normalized difference vegetation index (NDVI) was calculated. Plots of grain sorghum planted in orthogonal crop row orientations were extracted from the image series. The finest spatial resolution data were then rescaled by averaging blocks of pixels to produce a rescaled image series that closely matched the spatial resolution of the observed image series. Spatial structures of the observed and rescaled image series were characterized using semivariogram analysis. Results for NDVI and its component bands show, as expected, that decreasing spatial resolution leads to decreasing spatial variability and increasing spatial dependence. However, compared to the observed data, the rescaled images contain more persistent spatial structure that exhibits limited variation in both spatial dependence and spatial heterogeneity. Rescaling via simple block averaging fails to consider the effect of scene object shape and extent on spatial information. As the features portrayed by pixels are equally weighted regardless of the shape and extent of the underlying scene objects, the rescaled image retains more of the original spatial information than would occur through direct observation at a coarser sensor spatial resolution. In contrast, for the observed images, due to the effect of the modulation transfer function (MTF) of the imaging system, high frequency features like edges are blurred or lost as the pixel size increases, resulting in greater variation in spatial structure. Successive applications of a low-pass spatial convolution filter are shown to mimic a MTF. Accordingly, it is recommended that such a procedure be applied prior to rescaling by simple block averaging, if insufficient image metadata exist to replicate the net MTF of the imaging system, as might be expected in land cover change analysis studies using historical imagery.

Fiber-Optic Continuous Liquid Sensor for Cryogenic Propellant Gauging

NASA Technical Reports Server (NTRS)

Xu. Wei

2010-01-01

An innovative fiber-optic sensor has been developed for low-thrust-level settled mass gauging with measurement uncertainty <0.5 percent over cryogenic propellant tank fill levels from 2 to 98 percent. The proposed sensor uses a single optical fiber to measure liquid level and liquid distribution of cryogenic propellants. Every point of the sensing fiber is a point sensor that not only distinguishes liquid and vapor, but also measures temperature. This sensor is able to determine the physical location of each point sensor with 1-mm spatial resolution. Acting as a continuous array of numerous liquid/vapor point sensors, the truly distributed optical sensing fiber can be installed in a propellant tank in the same manner as silicon diode point sensor stripes using only a single feedthrough to connect to an optical signal interrogation unit outside the tank. Either water or liquid nitrogen levels can be measured within 1-mm spatial resolution up to a distance of 70 meters from the optical interrogation unit. This liquid-level sensing technique was also compared to the pressure gauge measurement technique in water and liquid nitrogen contained in a vertical copper pipe with a reasonable degree of accuracy. It has been demonstrated that the sensor can measure liquid levels in multiple containers containing water or liquid nitrogen with one signal interrogation unit. The liquid levels measured by the multiple fiber sensors were consistent with those virtually measured by a ruler. The sensing performance of various optical fibers has been measured, and has demonstrated that they can survive after immersion at cryogenic temperatures. The fiber strength in liquid nitrogen has also been measured. Multiple water level tests were also conducted under various actual and theoretical vibration conditions, and demonstrated that the signal-to-noise ratio under these vibration conditions, insofar as it affects measurement accuracy, is manageable and robust enough for a wide variety of spacecraft applications. A simple solution has been developed to absorb optical energy at the termination of the optical sensor, thereby avoiding any feedback to the optical interrogation unit

Estimating the spatial resolution of fNIRS sensors for BCI purposes

NASA Astrophysics Data System (ADS)

Almajidy, Rand Kasim; Kirch, Robert D.; Christ, Olaf; Hofmann, Ulrich G.

2014-03-01

Differential near infrared sensors recently sparked a growing interest as a promising measuring modality for brain computer interfacing. In our study we present the design and characterization of novel, differential functional NIRS sensors, intended to record hemodynamic changes of the human motor cortex in the hand-area during motor imagery tasks. We report on the spatial characterization of a portable, multi-channel NIRS system with one module consisting of two central light emitting diodes (LED) (770 nm and 850 nm) and four symmetric pairs of radially aligned photodiodes (PD) resembling a plus symbol. The other sensor module features four similar, differential light paths crossing in the center of a star. Characterization was performed on a concentric, double beaker phantom, featuring a PBS/intralipid/blood mixture (97/1/2%). In extension of previous work, the inner, oxygenated beaker was covered by neoprene sleeves with holes of various sizes, thus giving an estimate on the spatial limits of the NIRS sensor's measurement volume. The star shaped sensor module formed a diffuse focus of approximately 3 cm in diameter at 1.4 cm depth, whereas the plus shaped arrangement suggested a concentric ring of four separate regions of interest, overall larger than 6 cm. The systems measurement sensitivity could be improved by removing ambient light from the sensing photodiodes by optical filtering. Altogether, we conclude that both our novel fNIRS design as well as its electronics perform well in the double-layered oxygenation phantom and are thus suitable for in-vivo testing.

Dynamic Range and Sensitivity Requirements of Satellite Ocean Color Sensors: Learning from the Past

NASA Technical Reports Server (NTRS)

Hu, Chuanmin; Feng, Lian; Lee, Zhongping; Davis, Curtiss O.; Mannino, Antonio; McClain, Charles R.; Franz, Bryan A.

2012-01-01

Sensor design and mission planning for satellite ocean color measurements requires careful consideration of the signal dynamic range and sensitivity (specifically here signal-to-noise ratio or SNR) so that small changes of ocean properties (e.g., surface chlorophyll-a concentrations or Chl) can be quantified while most measurements are not saturated. Past and current sensors used different signal levels, formats, and conventions to specify these critical parameters, making it difficult to make cross-sensor comparisons or to establish standards for future sensor design. The goal of this study is to quantify these parameters under uniform conditions for widely used past and current sensors in order to provide a reference for the design of future ocean color radiometers. Using measurements from the Moderate Resolution Imaging Spectroradiometer onboard the Aqua satellite (MODISA) under various solar zenith angles (SZAs), typical (L(sub typical)) and maximum (L(sub max)) at-sensor radiances from the visible to the shortwave IR were determined. The Ltypical values at an SZA of 45 deg were used as constraints to calculate SNRs of 10 multiband sensors at the same L(sub typical) radiance input and 2 hyperspectral sensors at a similar radiance input. The calculations were based on clear-water scenes with an objective method of selecting pixels with minimal cross-pixel variations to assure target homogeneity. Among the widely used ocean color sensors that have routine global coverage, MODISA ocean bands (1 km) showed 2-4 times higher SNRs than the Sea-viewing Wide Field-of-view Sensor (Sea-WiFS) (1 km) and comparable SNRs to the Medium Resolution Imaging Spectrometer (MERIS)-RR (reduced resolution, 1.2 km), leading to different levels of precision in the retrieved Chl data product. MERIS-FR (full resolution, 300 m) showed SNRs lower than MODISA and MERIS-RR with the gain in spatial resolution. SNRs of all MODISA ocean bands and SeaWiFS bands (except the SeaWiFS near-IR bands) exceeded those from prelaunch sensor specifications after adjusting the input radiance to L(sub typical). The tabulated L(sub typical), L(sub max), and SNRs of the various multiband and hyperspectral sensors under the same or similar radiance input provide references to compare sensor performance in product precision and to help design future missions such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission and the Pre-Aerosol-Clouds-Ecosystems (PACE) mission currently being planned by the U.S. National Aeronautics and Space Administration (NASA).

Where can pixel counting area estimates meet user-defined accuracy requirements?

NASA Astrophysics Data System (ADS)

Waldner, François; Defourny, Pierre

2017-08-01

Pixel counting is probably the most popular way to estimate class areas from satellite-derived maps. It involves determining the number of pixels allocated to a specific thematic class and multiplying it by the pixel area. In the presence of asymmetric classification errors, the pixel counting estimator is biased. The overarching objective of this article is to define the applicability conditions of pixel counting so that the estimates are below a user-defined accuracy target. By reasoning in terms of landscape fragmentation and spatial resolution, the proposed framework decouples the resolution bias and the classifier bias from the overall classification bias. The consequence is that prior to any classification, part of the tolerated bias is already committed due to the choice of the spatial resolution of the imagery. How much classification bias is affordable depends on the joint interaction of spatial resolution and fragmentation. The method was implemented over South Africa for cropland mapping, demonstrating its operational applicability. Particular attention was paid to modeling a realistic sensor's spatial response by explicitly accounting for the effect of its point spread function. The diagnostic capabilities offered by this framework have multiple potential domains of application such as guiding users in their choice of imagery and providing guidelines for space agencies to elaborate the design specifications of future instruments.

Mapping Crop Patterns in Central US Agricultural Systems from 2000 to 2014 Based on Landsat Data: To What Degree Does Fusing MODIS Data Improve Classification Accuracies?

NASA Astrophysics Data System (ADS)

Zhu, L.; Radeloff, V.; Ives, A. R.; Barton, B.

2015-12-01

Deriving crop pattern with high accuracy is of great importance for characterizing landscape diversity, which affects the resilience of food webs in agricultural systems in the face of climatic and land cover changes. Landsat sensors were originally designed to monitor agricultural areas, and both radiometric and spatial resolution are optimized for monitoring large agricultural fields. Unfortunately, few clear Landsat images per year are available, which has limited the use of Landsat for making crop classification, and this situation is worse in cloudy areas of the Earth. Meanwhile, the MODerate Resolution Imaging Spectroradiometer (MODIS) data has better temporal resolution but cannot capture fine spatial heterogeneity of agricultural systems. Our question was to what extent fusing imagery from both sensors could improve crop classifications. We utilized the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to simulate Landsat-like images at MODIS temporal resolution. Based on Random Forests (RF) classifier, we tested whether and by what degree crop maps from 2000 to 2014 of the Arlington Agricultural Research Station (Wisconsin, USA) were improved by integrating available clear Landsat images each year with synthetic images. We predicted that the degree to which classification accuracy can be improved by incorporating synthetic imagery depends on the number and acquisition time of clear Landsat images. Moreover, multi-season data are essential for mapping crop types by capturing their phenological dynamics, and STARFM-simulated images can be used to compensate for missing Landsat observations. Our study is helpful for eliminating the limits of the use of Landsat data in mapping crop patterns, and can provide a benchmark of accuracy when choosing STARFM-simulated images to make crop classification at broader scales.

Development of a portable wireless system for bipolar concentric ECG recording

NASA Astrophysics Data System (ADS)

Prats-Boluda, G.; Ye-Lin, Y.; Bueno Barrachina, J. M.; Senent, E.; Rodriguez de Sanabria, R.; Garcia-Casado, J.

2015-07-01

Cardiovascular diseases (CVDs) remain the biggest cause of deaths worldwide. ECG monitoring is a key tool for early diagnosis of CVDs. Conventional monitors use monopolar electrodes resulting in poor spatial resolution surface recordings and requiring extensive wiring. High-spatial resolution surface electrocardiographic recordings provide valuable information for the diagnosis of a wide range of cardiac abnormalities, including infarction and arrhythmia. The aim of this work was to develop and test a wireless recording system for acquiring high spatial resolution ECG signals, based on a flexible tripolar concentric electrode (TCE) without cable wiring or external reference electrode which would make more comnfortable its use in clinical practice. For this, a portable, wireless sensor node for analogue conditioning, digitalization and transmission of a bipolar concentric ECG signal (BC-ECG) using a TCE and a Mason-likar Lead-I ECG (ML-Lead-I ECG) signal was developed. Experimental results from a total of 32 healthy volunteers showed that the ECG fiducial points in the BC-ECG signals, recorded with external and internal reference electrode, are consistent with those of simultaneous ML-Lead-I ECG. No statistically significant difference was found in either signal amplitude or morphology, regardless of the reference electrode used, being the signal-to-noise similar to that of ML-Lead-I ECG. Furthermore, it has been observed that BC-ECG signals contain information that could not available in conventional records, specially related to atria activity. The proposed wireless sensor node provides non-invasive high-local resolution ECG signals using only a TCE without additional wiring, which would have great potential in medical diagnosis of diseases such as atrial or ventricular fibrillations or arrhythmias that currently require invasive diagnostic procedures (catheterization).

High-resolution hot-film measurement of surface heat flux to an impinging jet

NASA Astrophysics Data System (ADS)

O'Donovan, T. S.; Persoons, T.; Murray, D. B.

2011-10-01

To investigate the complex coupling between surface heat transfer and local fluid velocity in convective heat transfer, advanced techniques are required to measure the surface heat flux at high spatial and temporal resolution. Several established flow velocity techniques such as laser Doppler anemometry, particle image velocimetry and hot wire anemometry can measure fluid velocities at high spatial resolution (µm) and have a high-frequency response (up to 100 kHz) characteristic. Equivalent advanced surface heat transfer measurement techniques, however, are not available; even the latest advances in high speed thermal imaging do not offer equivalent data capture rates. The current research presents a method of measuring point surface heat flux with a hot film that is flush mounted on a heated flat surface. The film works in conjunction with a constant temperature anemometer which has a bandwidth of 100 kHz. The bandwidth of this technique therefore is likely to be in excess of more established surface heat flux measurement techniques. Although the frequency response of the sensor is not reported here, it is expected to be significantly less than 100 kHz due to its physical size and capacitance. To demonstrate the efficacy of the technique, a cooling impinging air jet is directed at the heated surface, and the power required to maintain the hot-film temperature is related to the local heat flux to the fluid air flow. The technique is validated experimentally using a more established surface heat flux measurement technique. The thermal performance of the sensor is also investigated numerically. It has been shown that, with some limitations, the measurement technique accurately measures the surface heat transfer to an impinging air jet with improved spatial resolution for a wide range of experimental parameters.

Multispectral multisensor image fusion using wavelet transforms

USGS Publications Warehouse

Lemeshewsky, George P.

1999-01-01

Fusion techniques can be applied to multispectral and higher spatial resolution panchromatic images to create a composite image that is easier to interpret than the individual images. Wavelet transform-based multisensor, multiresolution fusion (a type of band sharpening) was applied to Landsat thematic mapper (TM) multispectral and coregistered higher resolution SPOT panchromatic images. The objective was to obtain increased spatial resolution, false color composite products to support the interpretation of land cover types wherein the spectral characteristics of the imagery are preserved to provide the spectral clues needed for interpretation. Since the fusion process should not introduce artifacts, a shift invariant implementation of the discrete wavelet transform (SIDWT) was used. These results were compared with those using the shift variant, discrete wavelet transform (DWT). Overall, the process includes a hue, saturation, and value color space transform to minimize color changes, and a reported point-wise maximum selection rule to combine transform coefficients. The performance of fusion based on the SIDWT and DWT was evaluated with a simulated TM 30-m spatial resolution test image and a higher resolution reference. Simulated imagery was made by blurring higher resolution color-infrared photography with the TM sensors' point spread function. The SIDWT based technique produced imagery with fewer artifacts and lower error between fused images and the full resolution reference. Image examples with TM and SPOT 10-m panchromatic illustrate the reduction in artifacts due to the SIDWT based fusion.

Advanced sensors and instrumentation

NASA Technical Reports Server (NTRS)

Calloway, Raymond S.; Zimmerman, Joe E.; Douglas, Kevin R.; Morrison, Rusty

1990-01-01

NASA is currently investigating the readiness of Advanced Sensors and Instrumentation to meet the requirements of new initiatives in space. The following technical objectives and technologies are briefly discussed: smart and nonintrusive sensors; onboard signal and data processing; high capacity and rate adaptive data acquisition systems; onboard computing; high capacity and rate onboard storage; efficient onboard data distribution; high capacity telemetry; ground and flight test support instrumentation; power distribution; and workstations, video/lighting. The requirements for high fidelity data (accuracy, frequency, quantity, spatial resolution) in hostile environments will continue to push the technology developers and users to extend the performance of their products and to develop new generations.

Ocean Color and Earth Science Data Records

NASA Astrophysics Data System (ADS)

Maritorena, S.

2014-12-01

The development of consistent, high quality time series of biogeochemical products from a single ocean color sensor is a difficult task that involves many aspects related to pre- and post-launch instrument calibration and characterization, stability monitoring and the removal of the contribution of the atmosphere which represents most of the signal measured at the sensor. It is even more challenging to build Climate Data Records (CDRs) or Earth Science Data Records (ESDRs) from multiple sensors as design, technology and methodologies (bands, spectral/spatial resolution, Cal/Val, algorithms) differ from sensor to sensor. NASA MEaSUREs, ESA Climate Change Initiative (CCI) and IOCCG Virtual Constellation are some of the underway efforts that investigate or produce ocean color CDRs or ESDRs from the recent and current global missions (SeaWiFS, MODIS, MERIS). These studies look at key aspects of the development of unified data records from multiple sensors, e.g. the concatenation of the "best" individual records vs. the merging of multiple records or band homogenization vs. spectral diversity. The pros and cons of the different approaches are closely dependent upon the overall science purpose of the data record and its temporal resolution. While monthly data are generally adequate for biogeochemical modeling or to assess decadal trends, higher temporal resolution data records are required to look into changes in phenology or the dynamics of phytoplankton blooms. Similarly, short temporal resolution (daily to weekly) time series may benefit more from being built through the merging of data from multiple sensors while a simple concatenation of data from individual sensors might be better suited for longer temporal resolution (e.g. monthly time series). Several Ocean Color ESDRs were developed as part of the NASA MEaSUREs project. Some of these time series are built by merging the reflectance data from SeaWiFS, MODIS-Aqua and Envisat-MERIS in a semi-analytical ocean color model that generates both merged reflectance and merged biogeochemical products. The benefits and limitations of this merging approach to develop ESDRs will be presented and discussed along with those of alternative approaches.

UAV remote sening for precision agriculture

NASA Astrophysics Data System (ADS)

Vigneau, Nathalie; Chéron, Corentin; Mainfroy, Florent; Faroux, Romain

2014-05-01

Airinov offers to farmers, scientists and experimenters (plant breeders, etc.) its technical skills about UAVs, cartography and agronomic remote sensing. The UAV is a 2-m-wingspan flying wing. It can carry away either a RGB camera or a multispectral sensor, which records reflectance in 4 spectral bands. The spectral characteristics of the sensor are modular. Each spectral band is comprised between 400 and 850 nm and the FWHM (Full Width at Half Maximum) is between 10 and 40 nm. The spatial resolution varies according to sensor, flying height and user needs from 15cm/px for multispectral sensor at 150m to 1.5cm/px for RGB camera at 50m. The flight is totally automatic thanks to on-board autopilot, IMU (Inertial Measurement Unit) and GPS. Data processing (unvignetting, mosaicking, correction in reflectance) leads to agronomic variables as LAI (Leaf Area Index) or chlorophyll content for barley, wheat, rape and maize as well as vegetation indices as NDVI (Normalized Difference Vegetation Index). Using these data, Airinov can product advices for farmers as nitrogen preconisation for rape. For scientists, Airinov offers trial plot monitoring by micro-plots vectorisation and numerical data exctraction micro-plot by micro-plot. This can lead to kinetic curve for LAI or NDVI to compare cover establishment for different genotypes for example. Airinov's system is a new way to monitor plots with a lot of data (biophysical or biochemical parameters) at high rate, high spatial resolution and high precision.

Radioactive Quality Evaluation and Cross Validation of Data from the HJ-1A/B Satellites' CCD Sensors

PubMed Central

Zhang, Xin; Zhao, Xiang; Liu, Guodong; Kang, Qian; Wu, Donghai

2013-01-01

Data from multiple sensors are frequently used in Earth science to gain a more complete understanding of spatial information changes. Higher quality and mutual consistency are prerequisites when multiple sensors are jointly used. The HJ-1A/B satellites successfully launched on 6 September 2008. There are four charge-coupled device (CCD) sensors with uniform spatial resolutions and spectral range onboard the HJ-A/B satellites. Whether these data are keeping consistency is a major issue before they are used. This research aims to evaluate the data consistency and radioactive quality from the four CCDs. First, images of urban, desert, lake and ocean are chosen as the objects of evaluation. Second, objective evaluation variables, such as mean, variance and angular second moment, are used to identify image performance. Finally, a cross validation method are used to ensure the correlation of the data from the four HJ-1A/B CCDs and that which is gathered from the moderate resolution imaging spectro-radiometer (MODIS). The results show that the image quality of HJ-1A/B CCDs is stable, and the digital number distribution of CCD data is relatively low. In cross validation with MODIS, the root mean square errors of bands 1, 2 and 3 range from 0.055 to 0.065, and for band 4 it is 0.101. The data from HJ-1A/B CCD have better consistency. PMID:23881127

Cross delay line sensor characterization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Owens, Israel J; Remelius, Dennis K; Tiee, Joe J

There exists a wealth of information in the scientific literature on the physical properties and device characterization procedures for complementary metal oxide semiconductor (CMOS), charge coupled device (CCD) and avalanche photodiode (APD) format detectors. Numerous papers and books have also treated photocathode operation in the context of photomultiplier tube (PMT) operation for either non imaging applications or limited night vision capability. However, much less information has been reported in the literature about the characterization procedures and properties of photocathode detectors with novel cross delay line (XDL) anode structures. These allow one to detect single photons and create images by recordingmore » space and time coordinate (X, Y & T) information. In this paper, we report on the physical characteristics and performance of a cross delay line anode sensor with an enhanced near infrared wavelength response photocathode and high dynamic range micro channel plate (MCP) gain (> 10{sup 6}) multiplier stage. Measurement procedures and results including the device dark event rate (DER), pulse height distribution, quantum and electronic device efficiency (QE & DQE) and spatial resolution per effective pixel region in a 25 mm sensor array are presented. The overall knowledge and information obtained from XDL sensor characterization allow us to optimize device performance and assess capability. These device performance properties and capabilities make XDL detectors ideal for remote sensing field applications that require single photon detection, imaging, sub nano-second timing response, high spatial resolution (10's of microns) and large effective image format.« less

Radioactive quality evaluation and cross validation of data from the HJ-1A/B satellites' CCD sensors.

PubMed

Zhang, Xin; Zhao, Xiang; Liu, Guodong; Kang, Qian; Wu, Donghai

2013-07-05

Data from multiple sensors are frequently used in Earth science to gain a more complete understanding of spatial information changes. Higher quality and mutual consistency are prerequisites when multiple sensors are jointly used. The HJ-1A/B satellites successfully launched on 6 September 2008. There are four charge-coupled device (CCD) sensors with uniform spatial resolutions and spectral range onboard the HJ-A/B satellites. Whether these data are keeping consistency is a major issue before they are used. This research aims to evaluate the data consistency and radioactive quality from the four CCDs. First, images of urban, desert, lake and ocean are chosen as the objects of evaluation. Second, objective evaluation variables, such as mean, variance and angular second moment, are used to identify image performance. Finally, a cross validation method are used to ensure the correlation of the data from the four HJ-1A/B CCDs and that which is gathered from the moderate resolution imaging spectro-radiometer (MODIS). The results show that the image quality of HJ-1A/B CCDs is stable, and the digital number distribution of CCD data is relatively low. In cross validation with MODIS, the root mean square errors of bands 1, 2 and 3 range from 0.055 to 0.065, and for band 4 it is 0.101. The data from HJ-1A/B CCD have better consistency.

Review of the development of diamond radiation sensors

NASA Astrophysics Data System (ADS)

Adam, W.; Bauer, C.; Berdermann, E.; Bergonzo, P.; Bogani, F.; Borchi, E.; Brambilla, A.; Bruzzi, M.; Colledani, C.; Conway, J.; Dabrowski, W.; Delpierre, P.; Deneuville, A.; Dulinski, W.; van Eijk, B.; Fallou, A.; Fizzotti, F.; Foulon, F.; Friedl, M.; Gan, K. K.; Gheeraert, E.; Grigoriev, E.; Hallewell, G.; Hall-Wilton, R.; Han, S.; Hartjes, F.; Hrubec, J.; Husson, D.; Kagan, H.; Kania, D.; Kaplon, J.; Karl, C.; Kass, R.; Knöpfle, K. T.; Krammer, M.; Logiudice, A.; Lu, R.; Manfredi, P. F.; Manfredotti, C.; Marshall, R. D.; Meier, D.; Mishina, M.; Oh, A.; Pan, L. S.; Palmieri, V. G.; Pernicka, M.; Peitz, A.; Pirollo, S.; Polesello, P.; Pretzl, K.; Re, V.; Riester, J. L.; Roe, S.; Roff, D.; Rudge, A.; Schnetzer, S.; Sciortino, S.; Speziali, V.; Stelzer, H.; Stone, R.; Tapper, R. J.; Tesarek, R.; Thomson, G. B.; Trawick, M.; Trischuk, W.; Vittone, E.; Walsh, A. M.; Wedenig, R.; Weilhammer, P.; Ziock, H.; Zoeller, M.; RD42 Collaboration

1999-09-01

Diamond radiation sensors produced by chemical vapour deposition are studied for the application as tracking detectors in high luminosity experiments. Sensors with a charge collection distance up to 250 μm have been manufactured. Their radiation hardness has been studied with pions, proton and neutrons up to fluences of 1.9×10 15 π cm -2, 5×10 15 p cm -2 and 1.35×10 15 n cm -2, respectively. Diamond micro-strip detectors with 50 μm pitch have been exposed in a high-energy test beam in order to investigate their charge collection properties. The measured spatial resolution using a centre-of-gravity position finding algorithm corresponds to the digital resolution for this strip pitch. First results from a strip tracker with a 2×4 cm 2 surface area are reported as well as the performance of a diamond tracker read out by radiation-hard electronics with 25 ns shaping time. Diamond pixel sensors have been prepared to match the geometries of the recently available read-out chip prototypes for ATLAS and CMS. Beam test results are shown from a diamond detector bump-bonded to an ATLAS prototype read-out. They demonstrate a 98% bump-bonding efficiency and a digital resolution in both dimensions.

Mapping turbidity in the Charles River, Boston using a high-resolution satellite.

PubMed

Hellweger, Ferdi L; Miller, Will; Oshodi, Kehinde Sarat

2007-09-01

The usability of high-resolution satellite imagery for estimating spatial water quality patterns in urban water bodies is evaluated using turbidity in the lower Charles River, Boston as a case study. Water turbidity was surveyed using a boat-mounted optical sensor (YSI) at 5 m spatial resolution, resulting in about 4,000 data points. The ground data were collected coincidently with a satellite imagery acquisition (IKONOS), which consists of multispectral (R, G, B) reflectance at 1 m resolution. The original correlation between the raw ground and satellite data was poor (R2 = 0.05). Ground data were processed by removing points affected by contamination (e.g., sensor encounters a particle floc), which were identified visually. Also, the ground data were corrected for the memory effect introduced by the sensor's protective casing using an analytical model. Satellite data were processed to remove pixels affected by permanent non-water features (e.g., shoreline). In addition, water pixels within a certain buffer distance from permanent non-water features were removed due to contamination by the adjacency effect. To determine the appropriate buffer distance, a procedure that explicitly considers the distance of pixels to the permanent non-water features was applied. Two automatic methods for removing the effect of temporary non-water features (e.g., boats) were investigated, including (1) creating a water-only mask based on an unsupervised classification and (2) removing (filling) all local maxima in reflectance. After the various processing steps, the correlation between the ground and satellite data was significantly better (R2 = 0.70). The correlation was applied to the satellite image to develop a map of turbidity in the lower Charles River, which reveals large-scale patterns in water clarity. However, the adjacency effect prevented the application of this method to near-shore areas, where high-resolution patterns were expected (e.g., outfall plumes).

Application of airborne thermal imagery to surveys of Pacific walrus

USGS Publications Warehouse

Burn, D.M.; Webber, M.A.; Udevitz, M.S.

2006-01-01

We conducted tests of airborne thermal imagery of Pacific walrus to determine if this technology can be used to detect walrus groups on sea ice and estimate the number of walruses present in each group. In April 2002 we collected thermal imagery of 37 walrus groups in the Bering Sea at spatial resolutions ranging from 1-4 m. We also collected high-resolution digital aerial photographs of the same groups. Walruses were considerably warmer than the background environment of ice, snow, and seawater and were easily detected in thermal imagery. We found a significant linear relation between walrus group size and the amount of heat measured by the thermal sensor at all 4 spatial resolutions tested. This relation can be used in a double-sampling framework to estimate total walrus numbers from a thermal survey of a sample of units within an area and photographs from a subsample of the thermally detected groups. Previous methods used in visual aerial surveys of Pacific walrus have sampled only a small percentage of available habitat, resulting in population estimates with low precision. Results of this study indicate that an aerial survey using a thermal sensor can cover as much as 4 times the area per hour of flight time with greater reliability than visual observation.

A CMOS-based large-area high-resolution imaging system for high-energy x-ray applications

NASA Astrophysics Data System (ADS)

Rodricks, Brian; Fowler, Boyd; Liu, Chiao; Lowes, John; Haeffner, Dean; Lienert, Ulrich; Almer, John

2008-08-01

CCDs have been the primary sensor in imaging systems for x-ray diffraction and imaging applications in recent years. CCDs have met the fundamental requirements of low noise, high-sensitivity, high dynamic range and spatial resolution necessary for these scientific applications. State-of-the-art CMOS image sensor (CIS) technology has experienced dramatic improvements recently and their performance is rivaling or surpassing that of most CCDs. The advancement of CIS technology is at an ever-accelerating pace and is driven by the multi-billion dollar consumer market. There are several advantages of CIS over traditional CCDs and other solid-state imaging devices; they include low power, high-speed operation, system-on-chip integration and lower manufacturing costs. The combination of superior imaging performance and system advantages makes CIS a good candidate for high-sensitivity imaging system development. This paper will describe a 1344 x 1212 CIS imaging system with a 19.5μm pitch optimized for x-ray scattering studies at high-energies. Fundamental metrics of linearity, dynamic range, spatial resolution, conversion gain, sensitivity are estimated. The Detective Quantum Efficiency (DQE) is also estimated. Representative x-ray diffraction images are presented. Diffraction images are compared against a CCD-based imaging system.

An Overview of the CBERS-2 Satellite and Comparison of the CBERS-2 CCD Data with the L5 TM Data

NASA Technical Reports Server (NTRS)

Chandler, Gyanesh

2007-01-01

CBERS satellite carries on-board a multi sensor payload with different spatial resolutions and collection frequencies. HRCCD (High Resolution CCD Camera), IRMSS (Infrared Multispectral Scanner), and WFI (Wide-Field Imager). The CCD and the WFI camera operate in the VNIR regions, while the IRMSS operates in SWIR and thermal region. In addition to the imaging payload, the satellite carries a Data Collection System (DCS) and Space Environment Monitor (SEM).

Pathfinder in flight over Hawaii

NASA Image and Video Library

1997-08-28

Pathfinder, NASA's solar-powered, remotely-piloted aircraft is shown while it was conducting a series of science flights to highlight the aircraft's science capabilities while collecting imagery of forest and coastal zone ecosystems on Kauai, Hawaii. The flights also tested two new scientific instruments, a high spectral resolution Digital Array Scanned Interferometer (DASI) and a high spatial resolution Airborne Real-Time Imaging System (ARTIS). The remote sensor payloads were designed by NASA's Ames Research Center, Moffett Field, California, to support NASA's Mission to Planet Earth science programs.

Pathfinder over runway in Hawaii

NASA Image and Video Library

1997-08-28

Pathfinder, NASA's solar-powered, remotely-piloted aircraft is shown while it was conducting a series of science flights to highlight the aircraft's science capabilities while collecting imagery of forest and coastal zone ecosystems on Kauai, Hawaii. The flights also tested two new scientific instruments, a high-spectral-resolution Digital Array Scanned Interferometer (DASI) and a high-spatial-resolution Airborne Real-Time Imaging System (ARTIS). The remote sensor payloads were designed by NASA's Ames Research Center, Moffett Field, California, to support NASA's Mission to Planet Earth science programs.

Application of future remote sensing systems to irrigation

NASA Technical Reports Server (NTRS)

Miller, L. D.

1982-01-01

Area estimates of irrigated crops and knowledge of crop type are required for modeling water consumption to assist farmers, rangers, and agricultural consultants in scheduling irrigation for distributed management of crop yields. Information on canopy physiology and soil moisture status on a spatial basis is potentially available from remote sensors, so the questions to be addressed relate to: (1) timing (data frequency, instantaneous and integrated measurement); and scheduling (widely distributed spatial demands); (2) spatial resolution; (3) radiometric and geometric accuracy and geoencoding; and (4) information/data distribution. This latter should be overnight, with no central storage, onsite capture, and low cost.

Generating Daily Synthetic Landsat Imagery by Combining Landsat and MODIS Data

PubMed Central

Wu, Mingquan; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-01-01

Owing to low temporal resolution and cloud interference, there is a shortage of high spatial resolution remote sensing data. To address this problem, this study introduces a modified spatial and temporal data fusion approach (MSTDFA) to generate daily synthetic Landsat imagery. This algorithm was designed to avoid the limitations of the conditional spatial temporal data fusion approach (STDFA) including the constant window for disaggregation and the sensor difference. An adaptive window size selection method is proposed in this study to select the best window size and moving steps for the disaggregation of coarse pixels. The linear regression method is used to remove the influence of differences in sensor systems using disaggregated mean coarse reflectance by testing and validation in two study areas located in Xinjiang Province, China. The results show that the MSTDFA algorithm can generate daily synthetic Landsat imagery with a high correlation coefficient (R) ranged from 0.646 to 0.986 between synthetic images and the actual observations. We further show that MSTDFA can be applied to 250 m 16-day MODIS MOD13Q1 products and the Landsat Normalized Different Vegetation Index (NDVI) data by generating a synthetic NDVI image highly similar to actual Landsat NDVI observation with a high R of 0.97. PMID:26393607

Generating Daily Synthetic Landsat Imagery by Combining Landsat and MODIS Data.

PubMed

Wu, Mingquan; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-09-18

Owing to low temporal resolution and cloud interference, there is a shortage of high spatial resolution remote sensing data. To address this problem, this study introduces a modified spatial and temporal data fusion approach (MSTDFA) to generate daily synthetic Landsat imagery. This algorithm was designed to avoid the limitations of the conditional spatial temporal data fusion approach (STDFA) including the constant window for disaggregation and the sensor difference. An adaptive window size selection method is proposed in this study to select the best window size and moving steps for the disaggregation of coarse pixels. The linear regression method is used to remove the influence of differences in sensor systems using disaggregated mean coarse reflectance by testing and validation in two study areas located in Xinjiang Province, China. The results show that the MSTDFA algorithm can generate daily synthetic Landsat imagery with a high correlation coefficient (R) ranged from 0.646 to 0.986 between synthetic images and the actual observations. We further show that MSTDFA can be applied to 250 m 16-day MODIS MOD13Q1 products and the Landsat Normalized Different Vegetation Index (NDVI) data by generating a synthetic NDVI image highly similar to actual Landsat NDVI observation with a high R of 0.97.

An integrated approach for high spatial resolution mapping of water and carbon fluxes using multi-sensor data

USDA-ARS?s Scientific Manuscript database

In the last few years, modeling of surface processes, such as water and carbon balances, vegetation growth and energy budgets, has focused on integrated approaches that combine aspects of hydrology, biology and meteorology into unified analyses. In this context, remotely sensed data often have a cor...

A new framework for UAV-based remote sensing data processing and its application in almond water stress quantification

USDA-ARS?s Scientific Manuscript database

With the rapid development of small imaging sensors and unmanned aerial vehicles (UAVs), remote sensing is undergoing a revolution with greatly increased spatial and temporal resolutions. While more relevant detail becomes available, it is a challenge to analyze the large number of images to extract...

Scales of heterogeneity of water quality in rivers: Insights from high resolution maps based on integrated geospatial, sensor and ROV technologies

EPA Science Inventory

While the spatial heterogeneity of many aquatic ecosystems is acknowledged, rivers are often mistakenly described as homogenous and well-mixed. The collection and visualization of attributes like water quality is key to our perception and management of these ecosystems. The ass...

Modification of measurement methods for evaluation of tissue-engineered cartilage function and biochemical properties using nanosecond pulsed laser

NASA Astrophysics Data System (ADS)

Ishihara, Miya; Sato, Masato; Kutsuna, Toshiharu; Ishihara, Masayuki; Mochida, Joji; Kikuchi, Makoto

2008-02-01

There is a demand in the field of regenerative medicine for measurement technology that enables determination of functions and components of engineered tissue. To meet this demand, we developed a method for extracellular matrix characterization using time-resolved autofluorescence spectroscopy, which enabled simultaneous measurements with mechanical properties using relaxation of laser-induced stress wave. In this study, in addition to time-resolved fluorescent spectroscopy, hyperspectral sensor, which enables to capture both spectral and spatial information, was used for evaluation of biochemical characterization of tissue-engineered cartilage. Hyperspectral imaging system provides spectral resolution of 1.2 nm and image rate of 100 images/sec. The imaging system consisted of the hyperspectral sensor, a scanner for x-y plane imaging, magnifying optics and Xenon lamp for transmmissive lighting. Cellular imaging using the hyperspectral image system has been achieved by improvement in spatial resolution up to 9 micrometer. The spectroscopic cellular imaging could be observed using cultured chondrocytes as sample. At early stage of culture, the hyperspectral imaging offered information about cellular function associated with endogeneous fluorescent biomolecules.

SeaWiFS Technical Report Series. Volume 7: Cloud screening for polar orbiting visible and infrared (IR) satellite sensors

NASA Technical Reports Server (NTRS)

Darzi, Michael; Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor)

1992-01-01

Methods for detecting and screening cloud contamination from satellite derived visible and infrared data are reviewed in this document. The methods are applicable to past, present, and future polar orbiting satellite radiometers. Such instruments include the Coastal Zone Color Scanner (CZCS), operational from 1978 through 1986; the Advanced Very High Resolution Radiometer (AVHRR); the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), scheduled for launch in August 1993; and the Moderate Resolution Imaging Spectrometer (IMODIS). Constant threshold methods are the least demanding computationally, and often provide adequate results. An improvement to these methods are the least demanding computationally, and often provide adequate results. An improvement to these methods is to determine the thresholds dynamically by adjusting them according to the areal and temporal distributions of the surrounding pixels. Spatial coherence methods set thresholds based on the expected spatial variability of the data. Other statistically derived methods and various combinations of basic methods are also reviewed. The complexity of the methods is ultimately limited by the computing resources. Finally, some criteria for evaluating cloud screening methods are discussed.

A look at motion in the frequency domain

NASA Technical Reports Server (NTRS)

Watson, A. B.; Ahumada, A. J., Jr.

1983-01-01

A moving image can be specified by a contrast distribution, c(x,y,t), over the dimensions of space x,y, and time t. Alternatively, it can be specified by the distribution C(u,v,w) over spatial frequency u,v and temporal frequency w. The frequency representation of a moving image is shown to have a characteristic form. This permits two useful observations. The first is that the apparent smoothness of time-sampled moving images (apparent motion) can be explained by the filtering action of the human visual system. This leads to the following formula for the required update rate for time-sampled displays. W(c)=W(l)+ru(l) where w(c) is the required update rate in Hz, W(l) is the limit of human temporal resolution in Hz, r is the velocity of the moving image in degrees/sec, and u(l) is the limit of human spatial resolution in cycles/deg. The second observation is that it is possible to construct a linear sensor that responds to images moving in a particular direction. The sensor is derived and its properties are discussed.

Low-cost, high-density sensor network for urban emission monitoring: BEACO2N

NASA Astrophysics Data System (ADS)

Kim, J.; Shusterman, A.; Lieschke, K.; Newman, C.; Cohen, R. C.

2017-12-01

In urban environments, air quality is spatially and temporally heterogeneous as diverse emission sources create a high degree of variability even at the neighborhood scale. Conventional air quality monitoring relies on continuous measurements with limited spatial resolution or passive sampling with high-density and low temporal resolution. Either approach averages the air quality information over space or time and hinders our attempts to understand emissions, chemistry, and human exposure in the near-field of emission sources. To better capture the true spatio-temporal heterogeneity of urban conditions, we have deployed a low-cost, high-density air quality monitoring network in San Francisco Bay Area distributed at 2km horizontal spacing. The BErkeley Atmospheric CO2 Observation Network (BEACO2N) consists of approximately 50 sensor nodes, measuring CO2, CO, NO, NO2, O­3, and aerosol. Here we describe field-based calibration approaches that are consistent with the low-cost strategy of the monitoring network. Observations that allow inference of emission factors and identification of specific local emission sources will also be presented.

Monitoring of shallow landslides by distributed optical fibers: insights from a physical model

NASA Astrophysics Data System (ADS)

Luca, Schenato; Matteo, Camporese; Luca, Palmieri; Alessandro, Pasuto; Salandin, Paolo

2017-04-01

Shallow landslides represent an extreme risk for individuals and structures due to their fast propagation and the very short time between appearance of warning signs and collapse. A lot of attention has been paid in the last decades to the analysis of activation mechanisms and to the implementation of appropriate early warning systems. Intense rainfall, stream erosion, flash floods, etc, are only few of the possible triggering factors that have been identified. All those factors may induce an increase in the forces acting and/or in the pore water pressure that eventually trigger the collapse. Due to the decrease of the shear resistance of soils, significant stresses develop at the sliding surface, determining local anomalous strain even before the collapse. This highlights the importance of monitoring the early appearance of hazardous strain fields. In light of the intrinsic lack of control and reproducibility in real cases, strain sensors have been applied in small-scale physical models and testbeds. Nonetheless, it has been observed that a reliable correlation between the landslide evolution and the strain field can be determined only by using minimally invasive sensors, while comprehensive information can be achieved at the cost of very fine spatial sampling, which represents the primary issue with small-to-medium scale physical models. It is evident how the two requirements, i.e., minimal invasiveness and high spatial resolution, are a limiting factor for standard sensor technology. In this regard, strain is one of the first variable addressed by optical fiber sensors, yet only recently for geotechnical applications and in very few case for landslide monitoring. In particular, the technology of distributed fiber optic sensors, with centimeter scale resolution, has the potential to address the aforementioned needs of small scale physical testing. In this work, for the first time, the strain field at the failure surface of a shallow landslide, reproduced in an artificial experimental hillslope, has been monitored by a distributed optical fiber sensing system based on optical fiber domain reflectometry with centimeter spatial resolution. The optical sensing system has been integrated with hydrological sensors for pore water pressure and moisture content, to the aim of supporting the data analysis. From the whole monitoring system a thorough knowledge of the collapsing mechanism has been achieved and it has been possible to identify precursory signs of the soil collapse well before its actual occurrence. The deployment of the sensing system and analysis of the collected data are discussed, together with possible potential for field installation.

Monitoring Crop Phenology and Growth Stages from Space: Opportunities and Challenges

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.; Mladenova, I. E.; Kustas, W. P.; Alfieri, J. G.

2014-12-01

Crop growth stages in concert with weather and soil moisture conditions can have a significant impact on crop yields. In the U.S., crop growth stages and conditions are reported by farmers at the county level. These reports are somewhat subjective and fluctuate between different reporters, locations and times. Remote sensing data provide an alternative approach to monitoring crop growth over large areas in a more consistent and quantitative way. In the recent years, remote sensing data have been used to detect vegetation phenology at 1-km spatial resolution globally. However, agricultural applications at field scale require finer spatial resolution remote sensing data. Landsat (30-m) data have been successfully used for agricultural applications. There are many medium resolution sensors available today or in near future. These include Landsat, SPOT, RapidEye, ASTER and future Sentinel-2 etc. Approaches have been developed in the past several years to integrate remote sensing data from different sensors which may have different sensor characteristics, and spatial and temporal resolutions. This allows us opportunities today to map crop growth stages and conditions using dense time-series remote sensing at field scales. However, remotely sensed phenology (or phenological metrics) is normally derived based on the mathematical functions of the time-series data. The phenological metrics are determined by either identifying inflection (curvature) points or some pre-defined thresholds in the remote sensing phenology algorithms. Furthermore, physiological crop growth stages may not be directly correlated to the remotely sensed phenology. The relationship between remotely sensed phenology and crop growth stages is likely to vary for specific crop types and varieties, growing stages, conditions and even locations. In this presentation, we will examine the relationship between remotely sensed phenology and crop growth stages using in-situ measurements from Fluxnet sites and crop progress reports from USDA NASS. We will present remote sensing approaches and focus on: 1) integrating multiple sources of remote sensing data; and 2) extracting crop phenology at field scales. An example in the U.S. Corn Belt area will be presented and analyzed. Future directions for mapping crop growth stages will be discussed.

Quantitative imaging with fluorescent biosensors.

PubMed

Okumoto, Sakiko; Jones, Alexander; Frommer, Wolf B

2012-01-01

Molecular activities are highly dynamic and can occur locally in subcellular domains or compartments. Neighboring cells in the same tissue can exist in different states. Therefore, quantitative information on the cellular and subcellular dynamics of ions, signaling molecules, and metabolites is critical for functional understanding of organisms. Mass spectrometry is generally used for monitoring ions and metabolites; however, its temporal and spatial resolution are limited. Fluorescent proteins have revolutionized many areas of biology-e.g., fluorescent proteins can report on gene expression or protein localization in real time-yet promoter-based reporters are often slow to report physiologically relevant changes such as calcium oscillations. Therefore, novel tools are required that can be deployed in specific cells and targeted to subcellular compartments in order to quantify target molecule dynamics directly. We require tools that can measure enzyme activities, protein dynamics, and biophysical processes (e.g., membrane potential or molecular tension) with subcellular resolution. Today, we have an extensive suite of tools at our disposal to address these challenges, including translocation sensors, fluorescence-intensity sensors, and Förster resonance energy transfer sensors. This review summarizes sensor design principles, provides a database of sensors for more than 70 different analytes/processes, and gives examples of applications in quantitative live cell imaging.

Map Matching and Real World Integrated Sensor Data Warehousing (Presentation)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burton, E.

2014-02-01

The inclusion of interlinked temporal and spatial elements within integrated sensor data enables a tremendous degree of flexibility when analyzing multi-component datasets. The presentation illustrates how to warehouse, process, and analyze high-resolution integrated sensor datasets to support complex system analysis at the entity and system levels. The example cases presented utilizes in-vehicle sensor system data to assess vehicle performance, while integrating a map matching algorithm to link vehicle data to roads to demonstrate the enhanced analysis possible via interlinking data elements. Furthermore, in addition to the flexibility provided, the examples presented illustrate concepts of maintaining proprietary operational information (Fleet DNA)more » and privacy of study participants (Transportation Secure Data Center) while producing widely distributed data products. Should real-time operational data be logged at high resolution across multiple infrastructure types, map matched to their associated infrastructure, and distributed employing a similar approach; dependencies between urban environment infrastructures components could be better understood. This understanding is especially crucial for the cities of the future where transportation will rely more on grid infrastructure to support its energy demands.« less

Advanced radiometric and interferometric milimeter-wave scene simulations

NASA Technical Reports Server (NTRS)

Hauss, B. I.; Moffa, P. J.; Steele, W. G.; Agravante, H.; Davidheiser, R.; Samec, T.; Young, S. K.

1993-01-01

Smart munitions and weapons utilize various imaging sensors (including passive IR, active and passive millimeter-wave, and visible wavebands) to detect/identify targets at short standoff ranges and in varied terrain backgrounds. In order to design and evaluate these sensors under a variety of conditions, a high-fidelity scene simulation capability is necessary. Such a capability for passive millimeter-wave scene simulation exists at TRW. TRW's Advanced Radiometric Millimeter-Wave Scene Simulation (ARMSS) code is a rigorous, benchmarked, end-to-end passive millimeter-wave scene simulation code for interpreting millimeter-wave data, establishing scene signatures and evaluating sensor performance. In passive millimeter-wave imaging, resolution is limited due to wavelength and aperture size. Where high resolution is required, the utility of passive millimeter-wave imaging is confined to short ranges. Recent developments in interferometry have made possible high resolution applications on military platforms. Interferometry or synthetic aperture radiometry allows the creation of a high resolution image with a sparsely filled aperture. Borrowing from research work in radio astronomy, we have developed and tested at TRW scene reconstruction algorithms that allow the recovery of the scene from a relatively small number of spatial frequency components. In this paper, the TRW modeling capability is described and numerical results are presented.

3D track reconstruction capability of a silicon hybrid active pixel detector

NASA Astrophysics Data System (ADS)

Bergmann, Benedikt; Pichotka, Martin; Pospisil, Stanislav; Vycpalek, Jiri; Burian, Petr; Broulim, Pavel; Jakubek, Jan

2017-06-01

Timepix3 detectors are the latest generation of hybrid active pixel detectors of the Medipix/Timepix family. Such detectors consist of an active sensor layer which is connected to the readout ASIC (application specific integrated circuit), segmenting the detector into a square matrix of 256 × 256 pixels (pixel pitch 55 μm). Particles interacting in the active sensor material create charge carriers, which drift towards the pixelated electrode, where they are collected. In each pixel, the time of the interaction (time resolution 1.56 ns) and the amount of created charge carriers are measured. Such a device was employed in an experiment in a 120 GeV/c pion beam. It is demonstrated, how the drift time information can be used for "4D" particle tracking, with the three spatial dimensions and the energy losses along the particle trajectory (dE/dx). Since the coordinates in the detector plane are given by the pixelation ( x, y), the x- and y-resolution is determined by the pixel pitch (55 μm). A z-resolution of 50.4 μm could be achieved (for a 500 μm thick silicon sensor at 130 V bias), whereby the drift time model independent z-resolution was found to be 28.5 μm.

Integrated approach using multi-platform sensors for enhanced high-resolution daily ice cover product

NASA Astrophysics Data System (ADS)

Bonev, George; Gladkova, Irina; Grossberg, Michael; Romanov, Peter; Helfrich, Sean

2016-09-01

The ultimate objective of this work is to improve characterization of the ice cover distribution in the polar areas, to improve sea ice mapping and to develop a new automated real-time high spatial resolution multi-sensor ice extent and ice edge product for use in operational applications. Despite a large number of currently available automated satellite-based sea ice extent datasets, analysts at the National Ice Center tend to rely on original satellite imagery (provided by satellite optical, passive microwave and active microwave sensors) mainly because the automated products derived from satellite optical data have gaps in the area coverage due to clouds and darkness, passive microwave products have poor spatial resolution, automated ice identifications based on radar data are not quite reliable due to a considerable difficulty in discriminating between the ice cover and rough ice-free ocean surface due to winds. We have developed a multisensor algorithm that first extracts maximum information on the sea ice cover from imaging instruments VIIRS and MODIS, including regions covered by thin, semitransparent clouds, then supplements the output by the microwave measurements and finally aggregates the results into a cloud gap free daily product. This ability to identify ice cover underneath thin clouds, which is usually masked out by traditional cloud detection algorithms, allows for expansion of the effective coverage of the sea ice maps and thus more accurate and detailed delineation of the ice edge. We have also developed a web-based monitoring system that allows comparison of our daily ice extent product with the several other independent operational daily products.

Transitioning from MODIS to VIIRS: an analysis of inter-consistency of NDVI data sets for agricultural monitoring.

PubMed

Skakun, Sergii; Justice, Christopher O; Vermote, Eric; Roger, Jean-Claude

2018-01-01

The Visible/Infrared Imager/Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite was launched in 2011, in part to provide continuity with the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard National Aeronautics and Space Administration's (NASA) Terra and Aqua remote sensing satellites. The VIIRS will eventually replace MODIS for both land science and applications and add to the coarse-resolution, long term data record. It is, therefore, important to provide the user community with an assessment of the consistency of equivalent products from the two sensors. For this study, we do this in the context of example agricultural monitoring applications. Surface reflectance that is routinely delivered within the M{O,Y}D09 and VNP09 series of products provide critical input for generating downstream products. Given the range of applications utilizing the normalized difference vegetation index (NDVI) generated from M{O,Y}D09 and VNP09 products and the inherent differences between MODIS and VIIRS sensors in calibration, spatial sampling, and spectral bands, the main objective of this study is to quantify uncertainties related the transitioning from using MODIS to VIIRS-based NDVI's. In particular, we compare NDVI's derived from two sets of Level 3 MYD09 and VNP09 products with various spatial-temporal characteristics, namely 8-day composites at 500 m spatial resolution and daily Climate Modelling Grid (CMG) images at 0.05° spatial resolution. Spectral adjustment of VIIRS I1 (red) and I2 (near infra-red - NIR) bands to match MODIS/Aqua b1 (red) and b2 (NIR) bands is performed to remove a bias between MODIS and VIIRS-based red, NIR, and NDVI estimates. Overall, red reflectance, NIR reflectance, NDVI uncertainties were 0.014, 0.029 and 0.056 respectively for the 500 m product and 0.013, 0.016 and 0.032 for the 0.05° product. The study shows that MODIS and VIIRS NDVI data can be used interchangeably for applications with an uncertainty of less than 0.02 to 0.05, depending on the scale of spatial aggregation, which is typically the uncertainty of the individual dataset.

Nanophotonic Image Sensors.

PubMed

Chen, Qin; Hu, Xin; Wen, Long; Yu, Yan; Cumming, David R S

2016-09-01

The increasing miniaturization and resolution of image sensors bring challenges to conventional optical elements such as spectral filters and polarizers, the properties of which are determined mainly by the materials used, including dye polymers. Recent developments in spectral filtering and optical manipulating techniques based on nanophotonics have opened up the possibility of an alternative method to control light spectrally and spatially. By integrating these technologies into image sensors, it will become possible to achieve high compactness, improved process compatibility, robust stability and tunable functionality. In this Review, recent representative achievements on nanophotonic image sensors are presented and analyzed including image sensors with nanophotonic color filters and polarizers, metamaterial-based THz image sensors, filter-free nanowire image sensors and nanostructured-based multispectral image sensors. This novel combination of cutting edge photonics research and well-developed commercial products may not only lead to an important application of nanophotonics but also offer great potential for next generation image sensors beyond Moore's Law expectations. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Robot Equipped with a High-Speed LSPR Gas Sensor Module for Collecting Spatial Odor Information from On-Ground Invisible Odor Sources.

PubMed

Yang, Zhongyuan; Sassa, Fumihiro; Hayashi, Kenshi

2018-06-22

Improving the efficiency of detecting the spatial distribution of gas information with a mobile robot is a great challenge that requires rapid sample collection, which is basically determined by the speed of operation of gas sensors. The present work developed a robot equipped with a high-speed gas sensor module based on localized surface plasmon resonance. The sensor module is designed to sample gases from an on-ground odor source, such as a footprint material or artificial odor marker, via a fine sampling tubing. The tip of the sampling tubing was placed close to the ground to reduce the sampling time and the effect of natural gas diffusion. On-ground ethanol odor sources were detected by the robot at high resolution (i.e., 2.5 cm when the robot moved at 10 cm/s), and the reading of gas information was demonstrated experimentally. This work may help in the development of environmental sensing robots, such as the development of odor source mapping and multirobot systems with pheromone tracing.

High-spatial-resolution mapping of precipitable water vapour using SAR interferograms, GPS observations and ERA-Interim reanalysis

NASA Astrophysics Data System (ADS)

Tang, Wei; Liao, Mingsheng; Zhang, Lu; Li, Wei; Yu, Weimin

2016-09-01

A high spatial and temporal resolution of the precipitable water vapour (PWV) in the atmosphere is a key requirement for the short-scale weather forecasting and climate research. The aim of this work is to derive temporally differenced maps of the spatial distribution of PWV by analysing the tropospheric delay "noise" in interferometric synthetic aperture radar (InSAR). Time series maps of differential PWV were obtained by processing a set of ENVISAT ASAR (Advanced Synthetic Aperture Radar) images covering the area of southern California, USA from 6 October 2007 to 29 November 2008. To get a more accurate PWV, the component of hydrostatic delay was calculated and subtracted by using ERA-Interim reanalysis products. In addition, the ERA-Interim was used to compute the conversion factors required to convert the zenith wet delay to water vapour. The InSAR-derived differential PWV maps were calibrated by means of the GPS PWV measurements over the study area. We validated our results against the measurements of PWV derived from the Medium Resolution Imaging Spectrometer (MERIS) which was located together with the ASAR sensor on board the ENVISAT satellite. Our comparative results show strong spatial correlations between the two data sets. The difference maps have Gaussian distributions with mean values close to zero and standard deviations below 2 mm. The advantage of the InSAR technique is that it provides water vapour distribution with a spatial resolution as fine as 20 m and an accuracy of ˜ 2 mm. Such high-spatial-resolution maps of PWV could lead to much greater accuracy in meteorological understanding and quantitative precipitation forecasts. With the launch of Sentinel-1A and Sentinel-1B satellites, every few days (6 days) new SAR images can be acquired with a wide swath up to 250 km, enabling a unique operational service for InSAR-based water vapour maps with unprecedented spatial and temporal resolution.

Evaluating Climate Causation of Conflict in Darfur Using Multi-temporal, Multi-resolution Satellite Image Datasets With Novel Analyses

NASA Astrophysics Data System (ADS)

Brown, I.; Wennbom, M.

2013-12-01

Climate change, population growth and changes in traditional lifestyles have led to instabilities in traditional demarcations between neighboring ethic and religious groups in the Sahel region. This has resulted in a number of conflicts as groups resort to arms to settle disputes. Such disputes often centre on or are justified by competition for resources. The conflict in Darfur has been controversially explained by resource scarcity resulting from climate change. Here we analyse established methods of using satellite imagery to assess vegetation health in Darfur. Multi-decadal time series of observations are available using low spatial resolution visible-near infrared imagery. Typically normalized difference vegetation index (NDVI) analyses are produced to describe changes in vegetation ';greenness' or ';health'. Such approaches have been widely used to evaluate the long term development of vegetation in relation to climate variations across a wide range of environments from the Arctic to the Sahel. These datasets typically measure peak NDVI observed over a given interval and may introduce bias. It is furthermore unclear how the spatial organization of sparse vegetation may affect low resolution NDVI products. We develop and assess alternative measures of vegetation including descriptors of the growing season, wetness and resource availability. Expanding the range of parameters used in the analysis reduces our dependence on peak NDVI. Furthermore, these descriptors provide a better characterization of the growing season than the single NDVI measure. Using multi-sensor data we combine high temporal/moderate spatial resolution data with low temporal/high spatial resolution data to improve the spatial representativity of the observations and to provide improved spatial analysis of vegetation patterns. The approach places the high resolution observations in the NDVI context space using a longer time series of lower resolution imagery. The vegetation descriptors derived are evaluated using independent high spatial resolution datasets that reveal the pattern and health of vegetation at metre scales. We also use climate variables to support the interpretation of these data. We conclude that the spatio-temporal patterns in Darfur vegetation and climate datasets suggest that labelling the conflict a climate-change conflict is inaccurate and premature.

Mapping snow cover using multi-source satellite data on big data platforms

NASA Astrophysics Data System (ADS)

Lhermitte, Stef

2017-04-01

Snowmelt is an important and dynamically changing water resource in mountainous regions around the world. In this framework, remote sensing data of snow cover data provides an essential input for hydrological models to model the water contribution from remote mountain areas and to understand how this water resource might alter as a result of climate change. Traditionally, however, many of these remote sensing products show a trade-off between spatial and temporal resolution (e.g., 16-day Landsat at 30m vs. daily MODIS at 500m resolution). With the advent of Sentinel-1 and 2 and the PROBA-V 100m products this trade-off can partially be tackled by having data that corresponds more closely to the spatial and temporal variations in snow cover typically observed over complex mountain areas. This study provides first a quantitative analysis of the trade-offs between the state-of-the-art snow cover mapping methodologies for Landsat, MODIS, PROBA-V, Sentinel-1 and 2 and applies them on big data platforms such as Google Earth Engine (GEE), RSS (ESA Research Service & Support) CloudToolbox, and the PROBA-V Mission Exploitation Platform (MEP). Second, it combines the different sensor data-cubes in one multi-sensor classification approach using newly developed spatio-temporal probability classifiers within the big data platform environments. Analysis of the spatio-temporal differences in derived snow cover areas from the different sensors reveals the importance of understanding the spatial and temporal scales at which variations occur. Moreover, it shows the importance of i) temporal resolution when monitoring highly dynamical properties such as snow cover and of ii) differences in satellite viewing angles over complex mountain areas. Finally, it highlights the potential and drawbacks of big data platforms for combining multi-source satellite data for monitoring dynamical processes such as snow cover.

Tactile Feedback Display with Spatial and Temporal Resolutions

PubMed Central

Vishniakou, Siarhei; Lewis, Brian W.; Niu, Xiaofan; Kargar, Alireza; Sun, Ke; Kalajian, Michael; Park, Namseok; Yang, Muchuan; Jing, Yi; Brochu, Paul; Sun, Zhelin; Li, Chun; Nguyen, Truong; Pei, Qibing; Wang, Deli

2013-01-01

We report the electronic recording of the touch contact and pressure using an active matrix pressure sensor array made of transparent zinc oxide thin-film transistors and tactile feedback display using an array of diaphragm actuators made of an interpenetrating polymer elastomer network. Digital replay, editing and manipulation of the recorded touch events were demonstrated with both spatial and temporal resolutions. Analog reproduction of the force is also shown possible using the polymer actuators, despite of the high driving voltage. The ability to record, store, edit, and replay touch information adds an additional dimension to digital technologies and extends the capabilities of modern information exchange with the potential to revolutionize physical learning, social networking, e-commerce, robotics, gaming, medical and military applications. PMID:23982053

Tactile feedback display with spatial and temporal resolutions.

PubMed

Vishniakou, Siarhei; Lewis, Brian W; Niu, Xiaofan; Kargar, Alireza; Sun, Ke; Kalajian, Michael; Park, Namseok; Yang, Muchuan; Jing, Yi; Brochu, Paul; Sun, Zhelin; Li, Chun; Nguyen, Truong; Pei, Qibing; Wang, Deli

2013-01-01

We report the electronic recording of the touch contact and pressure using an active matrix pressure sensor array made of transparent zinc oxide thin-film transistors and tactile feedback display using an array of diaphragm actuators made of an interpenetrating polymer elastomer network. Digital replay, editing and manipulation of the recorded touch events were demonstrated with both spatial and temporal resolutions. Analog reproduction of the force is also shown possible using the polymer actuators, despite of the high driving voltage. The ability to record, store, edit, and replay touch information adds an additional dimension to digital technologies and extends the capabilities of modern information exchange with the potential to revolutionize physical learning, social networking, e-commerce, robotics, gaming, medical and military applications.

MTF Analysis of LANDSAT-4 Thematic Mapper

NASA Technical Reports Server (NTRS)

Schowengerdt, R.

1984-01-01

A research program to measure the LANDSAT 4 Thematic Mapper (TM) modulation transfer function (MTF) is described. Measurement of a satellite sensor's MTF requires the use of a calibrated ground target, i.e., the spatial radiance distribution of the target must be known to a resolution at least four to five times greater than that of the system under test. A small reflective mirror or a dark light linear pattern such as line or edge, and relatively high resolution underflight imagery are used to calibrate the target. A technique that utilizes an analytical model for the scene spatial frequency power spectrum will be investigated as an alternative to calibration of the scene. The test sites and analysis techniques are also described.

Tactile Feedback Display with Spatial and Temporal Resolutions

NASA Astrophysics Data System (ADS)

Vishniakou, Siarhei; Lewis, Brian W.; Niu, Xiaofan; Kargar, Alireza; Sun, Ke; Kalajian, Michael; Park, Namseok; Yang, Muchuan; Jing, Yi; Brochu, Paul; Sun, Zhelin; Li, Chun; Nguyen, Truong; Pei, Qibing; Wang, Deli

2013-08-01

We report the electronic recording of the touch contact and pressure using an active matrix pressure sensor array made of transparent zinc oxide thin-film transistors and tactile feedback display using an array of diaphragm actuators made of an interpenetrating polymer elastomer network. Digital replay, editing and manipulation of the recorded touch events were demonstrated with both spatial and temporal resolutions. Analog reproduction of the force is also shown possible using the polymer actuators, despite of the high driving voltage. The ability to record, store, edit, and replay touch information adds an additional dimension to digital technologies and extends the capabilities of modern information exchange with the potential to revolutionize physical learning, social networking, e-commerce, robotics, gaming, medical and military applications.

Thermal neutron detector based on COTS CMOS imagers and a conversion layer containing Gadolinium

NASA Astrophysics Data System (ADS)

Pérez, Martín; Blostein, Juan Jerónimo; Bessia, Fabricio Alcalde; Tartaglione, Aureliano; Sidelnik, Iván; Haro, Miguel Sofo; Suárez, Sergio; Gimenez, Melisa Lucía; Berisso, Mariano Gómez; Lipovetzky, Jose

2018-06-01

In this work we will introduce a novel low cost position sensitive thermal neutron detection technique, based on a Commercial Off The Shelf CMOS image sensor covered with a Gadolinium containing conversion layer. The feasibility of the neutron detection technique implemented in this work has been experimentally demonstrated. A thermal neutron detection efficiency of 11.3% has been experimentally obtained with a conversion layer of 11.6 μm. It was experimentally verified that the thermal neutron detection efficiency of this technique is independent on the intensity of the incident thermal neutron flux, which was confirmed for conversion layers of different thicknesses. Based on the experimental results, a spatial resolution better than 25 μm is expected. This spatial resolution makes the proposed technique specially useful for neutron beam characterization, neutron beam dosimetry, high resolution neutron imaging, and several neutron scattering techniques.

Downscaling Thermal Infrared Radiance for Subpixel Land Surface Temperature Retrieval

PubMed Central

Liu, Desheng; Pu, Ruiliang

2008-01-01

Land surface temperature (LST) retrieved from satellite thermal sensors often consists of mixed temperature components. Retrieving subpixel LST is therefore needed in various environmental and ecological studies. In this paper, we developed two methods for downscaling coarse resolution thermal infrared (TIR) radiance for the purpose of subpixel temperature retrieval. The first method was developed on the basis of a scale-invariant physical model on TIR radiance. The second method was based on a statistical relationship between TIR radiance and land cover fraction at high spatial resolution. The two methods were applied to downscale simulated 990-m ASTER TIR data to 90-m resolution. When validated against the original 90-m ASTER TIR data, the results revealed that both downscaling methods were successful in capturing the general patterns of the original data and resolving considerable spatial details. Further quantitative assessments indicated a strong agreement between the true values and the estimated values by both methods. PMID:27879844

Downscaling Thermal Infrared Radiance for Subpixel Land Surface Temperature Retrieval.

PubMed

Liu, Desheng; Pu, Ruiliang

2008-04-06

Land surface temperature (LST) retrieved from satellite thermal sensors often consists of mixed temperature components. Retrieving subpixel LST is therefore needed in various environmental and ecological studies. In this paper, we developed two methods for downscaling coarse resolution thermal infrared (TIR) radiance for the purpose of subpixel temperature retrieval. The first method was developed on the basis of a scale-invariant physical model on TIR radiance. The second method was based on a statistical relationship between TIR radiance and land cover fraction at high spatial resolution. The two methods were applied to downscale simulated 990-m ASTER TIR data to 90-m resolution. When validated against the original 90-m ASTER TIR data, the results revealed that both downscaling methods were successful in capturing the general patterns of the original data and resolving considerable spatial details. Further quantitative assessments indicated a strong agreement between the true values and the estimated values by both methods.

High-resolution Imaging of pH in Alkaline Sediments and Water Based on a New Rapid Response Fluorescent Planar Optode

NASA Astrophysics Data System (ADS)

Han, Chao; Yao, Lei; Xu, Di; Xie, Xianchuan; Zhang, Chaosheng

2016-05-01

A new dual-lumophore optical sensor combined with a robust RGB referencing method was developed for two-dimensional (2D) pH imaging in alkaline sediments and water. The pH sensor film consisted of a proton-permeable polymer (PVC) in which two dyes with different pH sensitivities and emission colors: (1) chloro phenyl imino propenyl aniline (CPIPA) and (2) the coumarin dye Macrolex® fluorescence yellow 10 GN (MFY-10 GN) were entrapped. Calibration experiments revealed the typical sigmoid function and temperature dependencies. This sensor featured high sensitivity and fast response over the alkaline working ranges from pH 7.5 to pH 10.5. Cross-sensitivity towards ionic strength (IS) was found to be negligible for freshwater when IS <0.1 M. The sensor had a spatial resolution of approximately 22 μm and aresponse time of <120 s when going from pH 7.0 to 9.0. The feasibility of the sensor was demonstrated using the pH microelectrode. An example of pH image obtained in the natrual freshwater sediment and water associated with the photosynthesis of Vallisneria spiral species was also presented, suggesting that the sensor held great promise for the field applications.

High-resolution Imaging of pH in Alkaline Sediments and Water Based on a New Rapid Response Fluorescent Planar Optode

PubMed Central

Han, Chao; Yao, Lei; Xu, Di; Xie, Xianchuan; Zhang, Chaosheng

2016-01-01

A new dual-lumophore optical sensor combined with a robust RGB referencing method was developed for two-dimensional (2D) pH imaging in alkaline sediments and water. The pH sensor film consisted of a proton-permeable polymer (PVC) in which two dyes with different pH sensitivities and emission colors: (1) chloro phenyl imino propenyl aniline (CPIPA) and (2) the coumarin dye Macrolex® fluorescence yellow 10 GN (MFY-10 GN) were entrapped. Calibration experiments revealed the typical sigmoid function and temperature dependencies. This sensor featured high sensitivity and fast response over the alkaline working ranges from pH 7.5 to pH 10.5. Cross-sensitivity towards ionic strength (IS) was found to be negligible for freshwater when IS <0.1 M. The sensor had a spatial resolution of approximately 22 μm and aresponse time of <120 s when going from pH 7.0 to 9.0. The feasibility of the sensor was demonstrated using the pH microelectrode. An example of pH image obtained in the natrual freshwater sediment and water associated with the photosynthesis of Vallisneria spiral species was also presented, suggesting that the sensor held great promise for the field applications. PMID:27199163

Real time quantitative imaging for semiconductor crystal growth, control and characterization

NASA Technical Reports Server (NTRS)

Wargo, Michael J.

1991-01-01

A quantitative real time image processing system has been developed which can be software-reconfigured for semiconductor processing and characterization tasks. In thermal imager mode, 2D temperature distributions of semiconductor melt surfaces (900-1600 C) can be obtained with temperature and spatial resolutions better than 0.5 C and 0.5 mm, respectively, as demonstrated by analysis of melt surface thermal distributions. Temporal and spatial image processing techniques and multitasking computational capabilities convert such thermal imaging into a multimode sensor for crystal growth control. A second configuration of the image processing engine in conjunction with bright and dark field transmission optics is used to nonintrusively determine the microdistribution of free charge carriers and submicron sized crystalline defects in semiconductors. The IR absorption characteristics of wafers are determined with 10-micron spatial resolution and, after calibration, are converted into charge carrier density.

Sub-nano tesla magnetic imaging based on room-temperature magnetic flux sensors with vibrating sample magnetometry

NASA Astrophysics Data System (ADS)

Adachi, Yoshiaki; Oyama, Daisuke

2017-05-01

We developed a two-dimensional imaging method for weak magnetic charge distribution using a commercially available magnetic impedance sensor whose magnetic field resolution is 10 pT/Hz1/2 at 10 Hz. When we applied the vibrating sample magnetometry, giving a minute mechanical vibration to the sample and detecting magnetic signals modulated by the vibration frequency, the effects of 1/f noise and the environmental low-frequency band noise were suppressed, and a weak magnetic charge distribution was obtained without magnetic shielding. Furthermore, improvement in the spatial resolution was also expected when the signals were demodulated at the second harmonic frequency of the vibration. In this paper, a preliminary magnetic charge imaging using the vibrating sample magnetometry and its results are demonstrated.

Automatic optical inspection of regular grid patterns with an inspection camera used below the Shannon-Nyquist criterion for optical resolution

NASA Astrophysics Data System (ADS)

Ferreira, Flávio P.; Forte, Paulo M. F.; Felgueiras, Paulo E. R.; Bret, Boris P. J.; Belsley, Michael S.; Nunes-Pereira, Eduardo J.

2017-02-01

An Automatic Optical Inspection (AOI) system for optical inspection of imaging devices used in automotive industry using an inspecting optics of lower spatial resolution than the device under inspection is described. This system is robust and with no moving parts. The cycle time is small. Its main advantage is that it is capable of detecting and quantifying defects in regular patterns, working below the Shannon-Nyquist criterion for optical resolution, using a single low resolution image sensor. It is easily scalable, which is an important advantage in industrial applications, since the same inspecting sensor can be reused for increasingly higher spatial resolutions of the devices to be inspected. The optical inspection is implemented with a notch multi-band Fourier filter, making the procedure especially fitted for regular patterns, like the ones that can be produced in image displays and Head Up Displays (HUDs). The regular patterns are used in production line only, for inspection purposes. For image displays, functional defects are detected at the level of a sub-image display grid element unit. Functional defects are the ones impairing the function of the display, and are preferred in AOI to the direct geometric imaging, since those are the ones directly related with the end-user experience. The shift in emphasis from geometric imaging to functional imaging is critical, since it is this that allows quantitative inspection, below Shannon-Nyquist. For HUDs, the functional detect detection addresses defects resulting from the combined effect of the image display and the image forming optics.

Spectral Mixture Analysis to map burned areas in Brazil's deforestation arc from 1992 to 2011

NASA Astrophysics Data System (ADS)

Antunes Daldegan, G.; Ribeiro, F.; Roberts, D. A.

2017-12-01

The two most extensive biomes in South America, the Amazon and the Cerrado, are subject to several fire events every dry season. Both are known for their ecological and environmental importance. However, due to the intensive human occupation over the last four decades, they have been facing high deforestation rates. The Cerrado biome is adapted to fire and is considered a fire-dependent landscape. In contrast, the Amazon as a tropical moist broadleaf forest does not display similar characteristics and is classified as a fire-sensitive landscape. Nonetheless, studies have shown that forest areas that have already been burned become more prone to experience recurrent burns. Remote sensing has been extensively used by a large number of researchers studying fire occurrence at a global scale, as well as in both landscapes aforementioned. Digital image processing aiming to map fire activity has been applied to a number of imagery from sensors of various spatial, temporal, and spectral resolutions. More specifically, several studies have used Landsat data to map fire scars in the Amazon forest and in the Cerrado. An advantage of using Landsat data is the potential to map fire scars at a finer spatial resolution, when compared to products derived from imagery of sensors featuring better temporal resolution but coarser spatial resolution, such as MODIS (Moderate Resolution Imaging Spectrometer) and GOES (Geostationary Operational Environmental Satellite). This study aimed to map burned areas present in the Amazon-Cerrado transition zone by applying Spectral Mixture Analysis on Landsat imagery for a period of 20 years (1992-2011). The study area is a subset of this ecotone, centered at the State of Mato Grosso. By taking advantage of the Landsat 5TM and Landsat 7ETM+ imagery collections available in Google Earth Engine platform and applying Spectral Mixture Analysis (SMA) techniques over them permitted to model fire scar fractions and delimitate burned areas. Overlaying yearly burned areas allowed to identify areas with high fire recurrence.

Determination of atmospheric moisture structure and infrared cooling rates from high resolution MAMS radiance data

NASA Technical Reports Server (NTRS)

Menzel, W. Paul; Moeller, Christopher C.; Smith, William L.

1991-01-01

This program has applied Multispectral Atmospheric Mapping Sensor (MAMS) high resolution data to the problem of monitoring atmospheric quantities of moisture and radiative flux at small spatial scales. MAMS, with 100-m horizontal resolution in its four infrared channels, was developed to study small scale atmospheric moisture and surface thermal variability, especially as related to the development of clouds, precipitation, and severe storms. High-resolution Interferometer Sounder (HIS) data has been used to develop a high spectral resolution retrieval algorithm for producing vertical profiles of atmospheric temperature and moisture. The results of this program are summarized and a list of publications resulting from this contract is presented. Selected publications are attached as an appendix.

Piloted studies of Enhanced or Synthetic Vision display parameters

NASA Technical Reports Server (NTRS)

Harris, Randall L., Sr.; Parrish, Russell V.

1992-01-01

This paper summarizes the results of several studies conducted at Langley Research Center over the past few years. The purposes of these studies were to investigate parameters of pictorial displays and imaging sensors that affect pilot approach and landing performance. Pictorial displays have demonstrated exceptional tracking performance and improved the pilots' spatial awareness. Stereopsis cueing improved pilot flight performance and reduced pilot stress. Sensor image parameters such as increased field-of-view. faster image update rate, and aiding symbology improved flare initiation. Finer image resolution and magnification improved attitude control performance parameters.

Fabricatable nanopore sensors with an atomic thickness

NASA Astrophysics Data System (ADS)

Luan, Binquan; Bai, Jingwei; Stolovitzky, Gustavo

2013-10-01

When analyzing biological molecules (such as DNA and proteins) transported through a nanopore sensor, the pore length limits both the sensitivity and the spatial resolution. Atomically thin as a graphene nanopore is, it is difficult to make graphene pores and the scalable-fabrication of those pores has not yet been possible. We theoretically studied a type of atomically thin nanopores that are formed by intersection of two perpendicular nano-slits. Based on theoretical analyses, we demonstrate that slit nanopores behave similarly to graphene pores and can be manufactured at a wafer scale.

Image science team

NASA Technical Reports Server (NTRS)

Ando, K.

1982-01-01

A substantial technology base of solid state pushbroom sensors exists and is in the process of further evolution at both GSFC and JPL. Technologies being developed relate to short wave infrared (SWIR) detector arrays; HgCdTe hybrid detector arrays; InSb linear and area arrays; passive coolers; spectral beam splitters; the deposition of spectral filters on detector arrays; and the functional design of the shuttle/space platform imaging spectrometer (SIS) system. Spatial and spectral characteristics of field, aircraft and space multispectral sensors are summaried. The status, field of view, and resolution of foreign land observing systems are included.

Low-cost rapid miniature optical pressure sensors for blast wave measurements.

PubMed

Wu, Nan; Wang, Wenhui; Tian, Ye; Zou, Xiaotian; Maffeo, Michael; Niezrecki, Christopher; Chen, Julie; Wang, Xingwei

2011-05-23

This paper presents an optical pressure sensor based on a Fabry-Perot (FP) interferometer formed by a 45° angle polished single mode fiber and an external silicon nitride diaphragm. The sensor is comprised of two V-shape grooves with different widths on a silicon chip, a silicon nitride diaphragm released on the surface of the wider V-groove, and a 45° angle polished single mode fiber. The sensor is especially suitable for blast wave measurements: its compact structure ensures a high spatial resolution; its thin diaphragm based design and the optical demodulation scheme allow a fast response to the rapid changing signals experienced during blast events. The sensor shows linearity with the correlation coefficient of 0.9999 as well as a hysteresis of less than 0.3%. The shock tube test demonstrated that the sensor has a rise time of less than 2 µs from 0 kPa to 140 kPa.

Coincidence detection of spatially correlated photon pairs with a monolithic time-resolving detector array.

PubMed

Unternährer, Manuel; Bessire, Bänz; Gasparini, Leonardo; Stoppa, David; Stefanov, André

2016-12-12

We demonstrate coincidence measurements of spatially entangled photons by means of a multi-pixel based detection array. The sensor, originally developed for positron emission tomography applications, is a fully digital 8×16 silicon photomultiplier array allowing not only photon counting but also per-pixel time stamping of the arrived photons with an effective resolution of 265 ps. Together with a frame rate of 500 kfps, this property exceeds the capabilities of conventional charge-coupled device cameras which have become of growing interest for the detection of transversely correlated photon pairs. The sensor is used to measure a second-order correlation function for various non-collinear configurations of entangled photons generated by spontaneous parametric down-conversion. The experimental results are compared to theory.

Reborn quadrant anode image sensor

NASA Astrophysics Data System (ADS)

Prokazov, Yury; Turbin, Evgeny; Vitali, Marco; Herzog, Andreas; Michaelis, Bernd; Zuschratter, Werner; Kemnitz, Klaus

2009-06-01

We describe a position sensitive photon counting microchannel plate based detector with an improved quadrant anode (QA) readout system. The technique relies on a combination of the four planar elements pattern and an additional fifth electrode. The charge cloud induced by single particle detection is split between the electrodes. The measured charge values uniquely define the position of the initial event. QA has been first published in 1976 by Lampton and Malina. This anode configuration was undeservedly forgotten and its potential has been hardly underestimated. The presented approach extends the operating spatial range to the whole sensitive area of the microchannel plate surface and demonstrates good linearity over the field of view. Therefore, the novel image sensor results in spatial resolution better then 50 μm and count rates up to one million events per second.

Nanostructured cavity devices for extracellular stimulation of HL-1 cells

NASA Astrophysics Data System (ADS)

Czeschik, Anna; Rinklin, Philipp; Derra, Ulrike; Ullmann, Sabrina; Holik, Peter; Steltenkamp, Siegfried; Offenhäusser, Andreas; Wolfrum, Bernhard

2015-05-01

Microelectrode arrays (MEAs) are state-of-the-art devices for extracellular recording and stimulation on biological tissue. Furthermore, they are a relevant tool for the development of biomedical applications like retina, cochlear and motor prostheses, cardiac pacemakers and drug screening. Hence, research on functional cell-sensor interfaces, as well as the development of new surface structures and modifications for improved electrode characteristics, is a vivid and well established field. However, combining single-cell resolution with sufficient signal coupling remains challenging due to poor cell-electrode sealing. Furthermore, electrodes with diameters below 20 µm often suffer from a high electrical impedance affecting the noise during voltage recordings. In this study, we report on a nanocavity sensor array for voltage-controlled stimulation and extracellular action potential recordings on cellular networks. Nanocavity devices combine the advantages of low-impedance electrodes with small cell-chip interfaces, preserving a high spatial resolution for recording and stimulation. A reservoir between opening aperture and electrode is provided, allowing the cell to access the structure for a tight cell-sensor sealing. We present the well-controlled fabrication process and the effect of cavity formation and electrode patterning on the sensor's impedance. Further, we demonstrate reliable voltage-controlled stimulation using nanostructured cavity devices by capturing the pacemaker of an HL-1 cell network.Microelectrode arrays (MEAs) are state-of-the-art devices for extracellular recording and stimulation on biological tissue. Furthermore, they are a relevant tool for the development of biomedical applications like retina, cochlear and motor prostheses, cardiac pacemakers and drug screening. Hence, research on functional cell-sensor interfaces, as well as the development of new surface structures and modifications for improved electrode characteristics, is a vivid and well established field. However, combining single-cell resolution with sufficient signal coupling remains challenging due to poor cell-electrode sealing. Furthermore, electrodes with diameters below 20 µm often suffer from a high electrical impedance affecting the noise during voltage recordings. In this study, we report on a nanocavity sensor array for voltage-controlled stimulation and extracellular action potential recordings on cellular networks. Nanocavity devices combine the advantages of low-impedance electrodes with small cell-chip interfaces, preserving a high spatial resolution for recording and stimulation. A reservoir between opening aperture and electrode is provided, allowing the cell to access the structure for a tight cell-sensor sealing. We present the well-controlled fabrication process and the effect of cavity formation and electrode patterning on the sensor's impedance. Further, we demonstrate reliable voltage-controlled stimulation using nanostructured cavity devices by capturing the pacemaker of an HL-1 cell network. Electronic supplementary information (ESI) available: Comparison of non-filtered and Savitzky-Golay filtered action potential recordings, electrical signals and corresponding optical signals. See DOI: 10.1039/c5nr01690h

A mobile sensing system for structural health monitoring: design and validation

NASA Astrophysics Data System (ADS)

Zhu, Dapeng; Yi, Xiaohua; Wang, Yang; Lee, Kok-Meng; Guo, Jiajie

2010-05-01

This paper describes a new approach using mobile sensor networks for structural health monitoring. Compared with static sensors, mobile sensor networks offer flexible system architectures with adaptive spatial resolutions. The paper first describes the design of a mobile sensing node that is capable of maneuvering on structures built with ferromagnetic materials. The mobile sensing node can also attach/detach an accelerometer onto/from the structural surface. The performance of the prototype mobile sensor network has been validated through laboratory experiments. Two mobile sensing nodes are adopted for navigating on a steel portal frame and providing dense acceleration measurements. Transmissibility function analysis is conducted to identify structural damage using data collected by the mobile sensing nodes. This preliminary work is expected to spawn transformative changes in the use of mobile sensors for future structural health monitoring.

Performance of the Multi-Radar Multi-Sensor System over the Lower Colorado River, Texas

NASA Astrophysics Data System (ADS)

Bayabil, H. K.; Sharif, H. O.; Fares, A.; Awal, R.; Risch, E.

2017-12-01

Recently observed increases in intensities and frequencies of climate extremes (e.g., floods, dam failure, and overtopping of river banks) necessitate the development of effective disaster prevention and mitigation strategies. Hydrologic models can be useful tools in predicting such events at different spatial and temporal scales. However, accuracy and prediction capability of such models are often constrained by the availability of high-quality representative hydro-meteorological data (e.g., precipitation) that are required to calibrate and validate such models. Improved technologies and products such as the Multi-Radar Multi-Sensor (MRMS) system that allows gathering and transmission of vast meteorological data have been developed to provide such data needs. While the MRMS data are available with high spatial and temporal resolutions (1 km and 15 min, respectively), its accuracy in estimating precipitation is yet to be fully investigated. Therefore, the main objective of this study is to evaluate the performance of the MRMS system in effectively capturing precipitation over the Lower Colorado River, Texas using observations from a dense rain gauge network. In addition, effects of spatial and temporal aggregation scales on the performance of the MRMS system were evaluated. Point scale comparisons were made at 215 gauging locations using rain gauges and MRMS data from May 2015. Moreover, the effects of temporal and spatial data aggregation scales (30, 45, 60, 75, 90, 105, and 120 min) and (4 to 50 km), respectively on the performance of the MRMS system were tested. Overall, the MRMS system (at 15 min temporal resolution) captured precipitation reasonably well, with an average R2 value of 0.65 and RMSE of 0.5 mm. In addition, spatial and temporal data aggregations resulted in increases in R2 values. However, reduction in RMSE was achieved only with an increase in spatial aggregations.

Mapping urban air quality in near real-time using observations from low-cost sensors and model information.

PubMed

Schneider, Philipp; Castell, Nuria; Vogt, Matthias; Dauge, Franck R; Lahoz, William A; Bartonova, Alena

2017-09-01

The recent emergence of low-cost microsensors measuring various air pollutants has significant potential for carrying out high-resolution mapping of air quality in the urban environment. However, the data obtained by such sensors are generally less reliable than that from standard equipment and they are subject to significant data gaps in both space and time. In order to overcome this issue, we present here a data fusion method based on geostatistics that allows for merging observations of air quality from a network of low-cost sensors with spatial information from an urban-scale air quality model. The performance of the methodology is evaluated for nitrogen dioxide in Oslo, Norway, using both simulated datasets and real-world measurements from a low-cost sensor network for January 2016. The results indicate that the method is capable of producing realistic hourly concentration fields of urban nitrogen dioxide that inherit the spatial patterns from the model and adjust the prior values using the information from the sensor network. The accuracy of the data fusion method is dependent on various factors including the total number of observations, their spatial distribution, their uncertainty (both in terms of systematic biases and random errors), as well as the ability of the model to provide realistic spatial patterns of urban air pollution. A validation against official data from air quality monitoring stations equipped with reference instrumentation indicates that the data fusion method is capable of reproducing city-wide averaged official values with an R 2 of 0.89 and a root mean squared error of 14.3 μg m -3 . It is further capable of reproducing the typical daily cycles of nitrogen dioxide. Overall, the results indicate that the method provides a robust way of extracting useful information from uncertain sensor data using only a time-invariant model dataset and the knowledge contained within an entire sensor network. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Capacitively coupled hybrid pixel assemblies for the CLIC vertex detector

NASA Astrophysics Data System (ADS)

Tehrani, N. Alipour; Arfaoui, S.; Benoit, M.; Dannheim, D.; Dette, K.; Hynds, D.; Kulis, S.; Perić, I.; Petrič, M.; Redford, S.; Sicking, E.; Valerio, P.

2016-07-01

The vertex detector at the proposed CLIC multi-TeV linear e+e- collider must have minimal material content and high spatial resolution, combined with accurate time-stamping to cope with the expected high rate of beam-induced backgrounds. One of the options being considered is the use of active sensors implemented in a commercial high-voltage CMOS process, capacitively coupled to hybrid pixel ASICs. A prototype of such an assembly, using two custom designed chips (CCPDv3 as active sensor glued to a CLICpix readout chip), has been characterised both in the lab and in beam tests at the CERN SPS using 120 GeV/c positively charged hadrons. Results of these characterisation studies are presented both for single and dual amplification stages in the active sensor, where efficiencies of greater than 99% have been achieved at -60 V substrate bias, with a single hit resolution of 6.1 μm . Pixel cross-coupling results are also presented, showing the sensitivity to placement precision and planarity of the glue layer.

A new capacitive long-range displacement nanometer sensor with differential sensing structure based on time-grating

NASA Astrophysics Data System (ADS)

Yu, Zhicheng; Peng, Kai; Liu, Xiaokang; Pu, Hongji; Chen, Ziran

2018-05-01

High-precision displacement sensors, which can measure large displacements with nanometer resolution, are key components in many ultra-precision fabrication machines. In this paper, a new capacitive nanometer displacement sensor with differential sensing structure is proposed for long-range linear displacement measurements based on an approach denoted time grating. Analytical models established using electric field coupling theory and an area integral method indicate that common-mode interference will result in a first-harmonic error in the measurement results. To reduce the common-mode interference, the proposed sensor design employs a differential sensing structure, which adopts a second group of induction electrodes spatially separated from the first group of induction electrodes by a half-pitch length. Experimental results based on a prototype sensor demonstrate that the measurement accuracy and the stability of the sensor are substantially improved after adopting the differential sensing structure. Finally, a prototype sensor achieves a measurement accuracy of  ±200 nm over the full 200 mm measurement range of the sensor.

Intrinsic coincident linear polarimetry using stacked organic photovoltaics.

PubMed

Roy, S Gupta; Awartani, O M; Sen, P; O'Connor, B T; Kudenov, M W

2016-06-27

Polarimetry has widespread applications within atmospheric sensing, telecommunications, biomedical imaging, and target detection. Several existing methods of imaging polarimetry trade off the sensor's spatial resolution for polarimetric resolution, and often have some form of spatial registration error. To mitigate these issues, we have developed a system using oriented polymer-based organic photovoltaics (OPVs) that can preferentially absorb linearly polarized light. Additionally, the OPV cells can be made semitransparent, enabling multiple detectors to be cascaded along the same optical axis. Since each device performs a partial polarization measurement of the same incident beam, high temporal resolution is maintained with the potential for inherent spatial registration. In this paper, a Mueller matrix model of the stacked OPV design is provided. Based on this model, a calibration technique is developed and presented. This calibration technique and model are validated with experimental data, taken with a cascaded three cell OPV Stokes polarimeter, capable of measuring incident linear polarization states. Our results indicate polarization measurement error of 1.2% RMS and an average absolute radiometric accuracy of 2.2% for the demonstrated polarimeter.

Magnetic field sensing with nitrogen-vacancy color centers in diamond

NASA Astrophysics Data System (ADS)

Pham, Linh My

In recent years, the nitrogen-vacancy (NV) center has emerged as a promising magnetic sensor capable of measuring magnetic fields with high sensitivity and spatial resolution under ambient conditions. This combination of characteristics allows NV magnetometers to probe magnetic structures and systems that were previously inaccessible with alternative magnetic sensing technologies This dissertation presents and discusses a number of the initial efforts to demonstrate and improve NV magnetometry. In particular, a wide-field CCD based NV magnetic field imager capable of micron-scale spatial resolution is demonstrated; and magnetic field alignment, preferential NV orientation, and multipulse dynamical decoupling techniques are explored for enhancing magnetic sensitivity. The further application of dynamical decoupling control sequences as a spectral probe to extract information about the dynamics of the NV spin environment is also discussed; such information may be useful for determining optimal diamond sample parameters for different applications. Finally, several proposed and recently demonstrated applications which take advantage of NV magnetometers' sensitivity and spatial resolution at room temperature are presented, with particular focus on bio-magnetic field imaging.

High-Resolution Mapping of Thermal History in Polymer Nanocomposites: Gold Nanorods as Microscale Temperature Sensors.

PubMed

Kennedy, W Joshua; Slinker, Keith A; Volk, Brent L; Koerner, Hilmar; Godar, Trenton J; Ehlert, Gregory J; Baur, Jeffery W

2015-12-23

A technique is reported for measuring and mapping the maximum internal temperature of a structural epoxy resin with high spatial resolution via the optically detected shape transformation of embedded gold nanorods (AuNRs). Spatially resolved absorption spectra of the nanocomposites are used to determine the frequencies of surface plasmon resonances. From these frequencies the AuNR aspect ratio is calculated using a new analytical approximation for the Mie-Gans scattering theory, which takes into account coincident changes in the local dielectric. Despite changes in the chemical environment, the calculated aspect ratio of the embedded nanorods is found to decrease over time to a steady-state value that depends linearly on the temperature over the range of 100-200 °C. Thus, the optical absorption can be used to determine the maximum temperature experienced at a particular location when exposure times exceed the temperature-dependent relaxation time. The usefulness of this approach is demonstrated by mapping the temperature of an internally heated structural epoxy resin with 10 μm lateral spatial resolution.

Introduction and Testing of a Monitoring and Colony-Mapping Method for Waterbird Populations That Uses High-Speed and Ultra-Detailed Aerial Remote Sensing

PubMed Central

Bakó, Gábor; Tolnai, Márton; Takács, Ádám

2014-01-01

Remote sensing is a method that collects data of the Earth's surface without causing disturbances. Thus, it is worthwhile to use remote sensing methods to survey endangered ecosystems, as the studied species will behave naturally while undisturbed. The latest passive optical remote sensing solutions permit surveys from long distances. State-of-the-art highly sensitive sensor systems allow high spatial resolution image acquisition at high altitudes and at high flying speeds, even in low-visibility conditions. As the aerial imagery captured by an airplane covers the entire study area, all the animals present in that area can be recorded. A population assessment is conducted by visual interpretations of an ortho image map. The basic objective of this study is to determine whether small- and medium-sized bird species are recognizable in the ortho images by using high spatial resolution aerial cameras. The spatial resolution needed for identifying the bird species in the ortho image map was studied. The survey was adjusted to determine the number of birds in a colony at a given time. PMID:25046012

Sensors and OBIA synergy for operational monitoring of surface water

NASA Astrophysics Data System (ADS)

Masson, Eric; Thenard, Lucas

2010-05-01

This contribution will focus on combining Object Based Image Analysis (i.e. OBIA with e-Cognition 8) and recent sensors (i.e. Spot 5 XS, Pan and ALOS Prism, Avnir2, Palsar) to address the technical feasibility for an operational monitoring of surface water. Three cases of river meandering (India), flood mapping (Nepal) and dam's seasonal water level monitoring (Morocco) using recent sensors will present various application of surface water monitoring. The operational aspect will be demonstrated either by sensor properties (i.e. spatial resolution and bandwidth), data acquisition properties (i.e. multi sensor, return period and near real-time acquisition) but also with OBIA algorithms (i.e. fusion of multi sensors / multi resolution data and batch processes). In the first case of river meandering (India) we will address multi sensor and multi date satellite acquisition to monitor the river bed mobility within a floodplain using an ALOS dataset. It will demonstrate the possibility of an operational monitoring system that helps the geomorphologist in the analysis of fluvial dynamic and sediment budget for high energy rivers. In the second case of flood mapping (Nepal) we will address near real time Palsar data acquisition at high spatial resolution to monitor and to map a flood extension. This ALOS sensor takes benefit both from SAR and L band properties (i.e. atmospheric transparency, day/night acquisition, low sensibility to surface wind). It's a real achievement compared to optical imagery or even other high resolution SAR properties (i.e. acquisition swath, bandwidth and data price). These advantages meet the operational needs set by crisis management of hydrological disasters but also for the implementation of flood risk management plans. The last case of dam surface water monitoring (Morocco) will address an important issue of water resource management in countries affected by water scarcity. In such countries water users have to cope with over exploitation, frequent drought period and now with foreseen climate change impacts. This third case will demonstrate the efficiency of SPOT 5 programming in synergy with OBIA methodology to assess the evolution of dam surface water within a complete water cycle (i.e. 2008-09). In all those three cases image segmentation and classification algorithms developed with e-Cognition 8 software allow an easy to use implementation of simple to highly sophisticate OBIA rulsets fully operational in batch processes. Finally this contribution foresees the new opportunity of integration of Worldview 2 multispectral imagery (i.e. 8 bands) including its "coastal" band that will also find an application in continental surface water bathymetry. Worldview 2 is a recently launch satellite (e.g. October 2009) that starts to collect earth observation data since January 2010. It is therefore a promising new remote sensing tool to develop operational hydrology in combination high resolution SAR imagery and OBIA methodology. This contribution will conclude on the strong potential for operationalisation in hydrology and water resources management that recent and future sensors and image analysis methodologies are offering to water management and decision makers.

A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

NASA Astrophysics Data System (ADS)

Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús

2011-09-01

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.

Integrating Landsat Data and High-Resolution Imagery for Applied Conservation Assessment of Forest Cover in Latin American Heterogenous Landscapes

NASA Astrophysics Data System (ADS)

Thomas, N.; Rueda, X.; Lambin, E.; Mendenhall, C. D.

2012-12-01

Large intact forested regions of the world are known to be critical to maintaining Earth's climate, ecosystem health, and human livelihoods. Remote sensing has been successfully implemented as a tool to monitor forest cover and landscape dynamics over broad regions. Much of this work has been done using coarse resolution sensors such as AVHRR and MODIS in combination with moderate resolution sensors, particularly Landsat. Finer scale analysis of heterogeneous and fragmented landscapes is commonly performed with medium resolution data and has had varying success depending on many factors including the level of fragmentation, variability of land cover types, patch size, and image availability. Fine scale tree cover in mixed agricultural areas can have a major impact on biodiversity and ecosystem sustainability but may often be inadequately captured with the global to regional (coarse resolution and moderate resolution) satellite sensors and processing techniques widely used to detect land use and land cover changes. This study investigates whether advanced remote sensing methods are able to assess and monitor percent tree canopy cover in spatially complex human-dominated agricultural landscapes that prove challenging for traditional mapping techniques. Our study areas are in high altitude, mixed agricultural coffee-growing regions in Costa Rica and the Colombian Andes. We applied Random Forests regression tree analysis to Landsat data along with additional spectral, environmental, and spatial variables to predict percent tree canopy cover at 30m resolution. Image object-based texture, shape, and neighborhood metrics were generated at the Landsat scale using eCognition and included in the variable suite. Training and validation data was generated using high resolution imagery from digital aerial photography at 1m to 2.5 m resolution. Our results are promising with Pearson's correlation coefficients between observed and predicted percent tree canopy cover of .86 (Costa Rica) and .83 (Colombia). The tree cover mapping developed here supports two distinct projects on sustaining biodiversity and natural and human capital: in Costa Rica the tree canopy cover map is utilized to predict bird community composition; and in Colombia the mapping is performed for two time periods and used to assess the impact of coffee eco-certification programs on the landscape. This research identifies ways to leverage readily available, high quality, and cost-free Landsat data or other medium resolution satellite data sources in combination with high resolution data, such as that frequently available through Google Earth, to monitor and support sustainability efforts in fragmented and heterogeneous landscapes.

Compact SPAD-Based Pixel Architectures for Time-Resolved Image Sensors

PubMed Central

Perenzoni, Matteo; Pancheri, Lucio; Stoppa, David

2016-01-01

This paper reviews the state of the art of single-photon avalanche diode (SPAD) image sensors for time-resolved imaging. The focus of the paper is on pixel architectures featuring small pixel size (<25 μm) and high fill factor (>20%) as a key enabling technology for the successful implementation of high spatial resolution SPAD-based image sensors. A summary of the main CMOS SPAD implementations, their characteristics and integration challenges, is provided from the perspective of targeting large pixel arrays, where one of the key drivers is the spatial uniformity. The main analog techniques aimed at time-gated photon counting and photon timestamping suitable for compact and low-power pixels are critically discussed. The main features of these solutions are the adoption of analog counting techniques and time-to-analog conversion, in NMOS-only pixels. Reliable quantum-limited single-photon counting, self-referenced analog-to-digital conversion, time gating down to 0.75 ns and timestamping with 368 ps jitter are achieved. PMID:27223284

A High Space-Time Resolution Dataset Linking Meteorological Forcing and Hydro-Sedimentary Response in a Mesoscale Mediterranean Catchment (Auzon) of the Ardèche Region, France

NASA Astrophysics Data System (ADS)

Nord, G.; Braud, I.; Boudevillain, B.; Gérard, S.; Molinié, G.; Vandervaere, J. P.; Huza, J.; Le Coz, J.; Dramais, G.; Legout, C.; Berne, A.; Grazioli, J.; Raupach, T.; Van Baelen, J.; Wijbrans, A.; Delrieu, G.; Andrieu, J.; Caliano, M.; Aubert, C.; Teuling, R.; Le Boursicaud, R.; Branger, F.; Vincendon, B.; Horner, I.

2014-12-01

A comprehensive hydrometeorological dataset is presented spanning the period 1 Jan 2011-31 Dec 2014 to improve the understanding and simulation of the hydrological processes leading to flash floods in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain-gages (5 min time step for the research network of 21 rain-gages and 1h time step for the operational network of 9 rain-gages), S-band Doppler dual-polarization radar (1 km2, 5 min resolution), and disdrometers (11 sensors working at 1 min time step). During the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Meteo France at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge and additional physico-chemical variables at a 2-10 min time resolution. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 gauges continuously measures water level and temperature in headwater subcatchments at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding rainfall variability, improving areal rainfall estimations and progress in distributed hydrological modelling.

A High Space-Time Resolution Dataset Linking Meteorological Forcing and Hydro-Sedimentary Response in a Mesoscale Mediterranean Catchment (Auzon) of the Ardèche Region, France

NASA Astrophysics Data System (ADS)

Nord, G.; Braud, I.; Boudevillain, B.; Gérard, S.; Molinié, G.; Vandervaere, J. P.; Huza, J.; Le Coz, J.; Dramais, G.; Legout, C.; Berne, A.; Grazioli, J.; Raupach, T.; Van Baelen, J.; Wijbrans, A.; Delrieu, G.; Andrieu, J.; Caliano, M.; Aubert, C.; Teuling, R.; Le Boursicaud, R.; Branger, F.; Vincendon, B.; Horner, I.

2015-12-01

A comprehensive hydrometeorological dataset is presented spanning the period 1 Jan 2011-31 Dec 2014 to improve the understanding and simulation of the hydrological processes leading to flash floods in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain-gages (5 min time step for the research network of 21 rain-gages and 1h time step for the operational network of 9 rain-gages), S-band Doppler dual-polarization radar (1 km2, 5 min resolution), and disdrometers (11 sensors working at 1 min time step). During the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Meteo France at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge and additional physico-chemical variables at a 2-10 min time resolution. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 gauges continuously measures water level and temperature in headwater subcatchments at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding rainfall variability, improving areal rainfall estimations and progress in distributed hydrological modelling.

New Approaches to the Use and Integration of Multi-Sensor Remote Sensing for Historic Resource Identification and Evaluation

DTIC Science & Technology

2006-11-10

features based on shape are easy to come by. The Great Pyramids at Giza are instantly identified from space, even at the very coarse spatial... Pyramids at Giza , Egypt, are recognized by their triangular faces in this 1 m resolution Ikonos image, as are nearby rectangular tombs (credit: Space

MONITORING LARGE AREAS FOR FOREST CHANGE USING LANDSAT: GENERALIZATION ACROSS SPACE, TIME AND LANDSAT SENSORS. (R828309)

EPA Science Inventory

Landsat 7 ETM+ provides an opportunity to extend the area and frequency with
which we are able to monitor the Earth's surface with fine spatial resolution
data. To take advantage of this opportunity it is necessary to move beyond the
traditional image-by-image approac...