A review of potential image fusion methods for remote sensing-based irrigation management: Part II

USDA-ARS?s Scientific Manuscript database

Satellite-based sensors provide data at either greater spectral and coarser spatial resolutions, or lower spectral and finer spatial resolutions due to complementary spectral and spatial characteristics of optical sensor systems. In order to overcome this limitation, image fusion has been suggested ...

Research on optimal path planning algorithm of task-oriented optical remote sensing satellites

NASA Astrophysics Data System (ADS)

Liu, Yunhe; Xu, Shengli; Liu, Fengjing; Yuan, Jingpeng

2015-08-01

GEO task-oriented optical remote sensing satellite, is very suitable for long-term continuous monitoring and quick access to imaging. With the development of high resolution optical payload technology and satellite attitude control technology, GEO optical remote sensing satellites will become an important developing trend for aerospace remote sensing satellite in the near future. In the paper, we focused on GEO optical remote sensing satellite plane array stare imaging characteristics and real-time leading mission of earth observation mode, targeted on satisfying needs of the user with the minimum cost of maneuver, and put forward the optimal path planning algorithm centered on transformation from geographic coordinate space to Field of plane, and finally reduced the burden of the control system. In this algorithm, bounded irregular closed area on the ground would be transformed based on coordinate transformation relations in to the reference plane for field of the satellite payload, and then using the branch and bound method to search for feasible solutions, cutting off the non-feasible solution in the solution space based on pruning strategy; and finally trimming some suboptimal feasible solutions based on the optimization index until a feasible solution for the global optimum. Simulation and visualization presentation software testing results verified the feasibility and effectiveness of the strategy.

Geometric registration of remotely sensed data with SAMIR

NASA Astrophysics Data System (ADS)

Gianinetto, Marco; Barazzetti, Luigi; Dini, Luigi; Fusiello, Andrea; Toldo, Roberto

2015-06-01

The commercial market offers several software packages for the registration of remotely sensed data through standard one-to-one image matching. Although very rapid and simple, this strategy does not take into consideration all the interconnections among the images of a multi-temporal data set. This paper presents a new scientific software, called Satellite Automatic Multi-Image Registration (SAMIR), able to extend the traditional registration approach towards multi-image global processing. Tests carried out with high-resolution optical (IKONOS) and high-resolution radar (COSMO-SkyMed) data showed that SAMIR can improve the registration phase with a more rigorous and robust workflow without initial approximations, user's interaction or limitation in spatial/spectral data size. The validation highlighted a sub-pixel accuracy in image co-registration for the considered imaging technologies, including optical and radar imagery.

Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

USGS Publications Warehouse

Stow, Douglas A.; Hope, Allen; McGuire, David; Verbyla, David; Gamon, John A.; Huemmrich, Fred; Houston, Stan; Racine, Charles H.; Sturm, Matthew; Tape, Ken D.; Hinzman, Larry D.; Yoshikawa, Kenji; Tweedie, Craig E.; Noyle, Brian; Silapaswan, Cherie; Douglas, David C.; Griffith, Brad; Jia, Gensuo; Howard E. Epstein,; Walker, Donald A.; Daeschner, Scott; Petersen, Aaron; Zhou, Liming; Myneni, Ranga B.

2004-01-01

The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land–Air–Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations.The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored.

Atmospheric Effect on Remote Sensing of the Earth's Surface

NASA Technical Reports Server (NTRS)

Fraser, R. S.; Kaufman, Y. J. (Principal Investigator)

1985-01-01

Radiative transfer theory (RT) for an atmosphere with a nonuniform surface is the basis for understanding and correcting for the atmospheric effect on remote sensing of surface properties. In the present work the theory is generalized and tested successfully against laboratory and field measurements. There is still a need to generalize the RT approximation for off-nadir directions and to take into account anisotropic reflectance at the surface. The reflectance at the surface. The adjacency effect results in a significant modification of spectral signatures of the surface, and therefore results in modification of classifications, of separability of field classes, and of spatial resolution. For example, the 30 m resolution of the Thematic Mapper is reduced to 100 m by a hazy atmosphere. The adjacency effect depends on several optical parameters of aerosols: optical thickness, depth of aerosol layer, scattering phase function, and absorption. Remote sensing in general depends on these parameter, not just adjacency effects, but they are not known well enough for making accurate atmospheric corrections. It is important to establish methods for estimating these parameters in order to develop correction methods for atmospheric effects. Such estimations can be based on climatological data, which are not available yet, correlations between the optical parameters and meteorological data, and the same satellite measurements of radiances that are used for estimating surface properties. Knowledge about the atmospheric parameters important for remote sensing is being enlarged with current measurements of them.

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.

Cloud-Free Satellite Image Mosaics with Regression Trees and Histogram Matching.

Treesearch

E.H. Helmer; B. Ruefenacht

2005-01-01

Cloud-free optical satellite imagery simplifies remote sensing, but land-cover phenology limits existing solutions to persistent cloudiness to compositing temporally resolute, spatially coarser imagery. Here, a new strategy for developing cloud-free imagery at finer resolution permits simple automatic change detection. The strategy uses regression trees to predict...

NASA Cold Land Processes Experiment (CLPX 2002/03): Spaceborne remote sensing

Treesearch

Robert E. Davis; Thomas H. Painter; Don Cline; Richard Armstrong; Terry Haran; Kyle McDonald; Rick Forster; Kelly Elder

2008-01-01

This paper describes satellite data collected as part of the 2002/03 Cold Land Processes Experiment (CLPX). These data include multispectral and hyperspectral optical imaging, and passive and active microwave observations of the test areas. The CLPX multispectral optical data include the Advanced Very High Resolution Radiometer (AVHRR), the Landsat Thematic Mapper/...

Bringing the Coastal Zone into Finer Focus

NASA Astrophysics Data System (ADS)

Guild, L. S.; Hooker, S. B.; Kudela, R. M.; Morrow, J. H.; Torres-Perez, J. L.; Palacios, S. L.; Negrey, K.; Dungan, J. L.

2015-12-01

Measurements over extents from submeter to 10s of meters are critical science requirements for the design and integration of remote sensing instruments for coastal zone research. Various coastal ocean phenomena operate at different scales (e.g. meters to kilometers). For example, river plumes and algal blooms have typical extents of 10s of meters and therefore can be resolved with satellite data, however, shallow benthic ecosystem (e.g., coral, seagrass, and kelp) biodiversity and change are best studied at resolutions of submeter to meter, below the pixel size of typical satellite products. The delineation of natural phenomena do not fit nicely into gridded pixels and the coastal zone is complicated by mixed pixels at the land-sea interface with a range of bio-optical signals from terrestrial and water components. In many standard satellite products, these coastal mixed pixels are masked out because they confound algorithms for the ocean color parameter suite. In order to obtain data at the land/sea interface, finer spatial resolution satellite data can be achieved yet spectral resolution is sacrificed. This remote sensing resolution challenge thwarts the advancement of research in the coastal zone. Further, remote sensing of benthic ecosystems and shallow sub-surface phenomena are challenged by the requirements to sense through the sea surface and through a water column with varying light conditions from the open ocean to the water's edge. For coastal waters, >80% of the remote sensing signal is scattered/absorbed due to the atmospheric constituents, sun glint from the sea surface, and water column components. In addition to in-water measurements from various platforms (e.g., ship, glider, mooring, and divers), low altitude aircraft outfitted with high quality bio-optical radiometer sensors and targeted channels matched with in-water sensors and higher altitude platform sensors for ocean color products, bridge the sea-truth measurements to the pixels acquired from satellite and high altitude platforms. We highlight a novel NASA airborne calibration, validation, and research capability for addressing the coastal remote sensing resolution challenge.

[Application of optical flow dynamic texture in land use/cover change detection].

PubMed

Yan, Li; Gong, Yi-Long; Zhang, Yi; Duan, Wei

2014-11-01

In the present study, a novel change detection approach for high resolution remote sensing images is proposed based on the optical flow dynamic texture (OFDT), which could achieve the land use & land cover change information automatically with a dynamic description of ground-object changes. This paper describes the ground-object gradual change process from the principle using optical flow theory, which breaks the ground-object sudden change hypothesis in remote sensing change detection methods in the past. As the steps of this method are simple, it could be integrated in the systems and software such as Land Resource Management and Urban Planning software that needs to find ground-object changes. This method takes into account the temporal dimension feature between remote sensing images, which provides a richer set of information for remote sensing change detection, thereby improving the status that most of the change detection methods are mainly dependent on the spatial dimension information. In this article, optical flow dynamic texture is the basic reflection of changes, and it is used in high resolution remote sensing image support vector machine post-classification change detection, combined with spectral information. The texture in the temporal dimension which is considered in this article has a smaller amount of data than most of the textures in the spatial dimensions. The highly automated texture computing has only one parameter to set, which could relax the onerous manual evaluation present status. The effectiveness of the proposed approach is evaluated with the 2011 and 2012 QuickBird datasets covering Duerbert Mongolian Autonomous County of Daqing City, China. Then, the effects of different optical flow smooth coefficient and the impact on the description of the ground-object changes in the method are deeply analyzed: The experiment result is satisfactory, with an 87.29% overall accuracy and an 0.850 7 Kappa index, and the method achieves better performance than the post-classification change detection methods using spectral information only.

An Airborne A-Band Spectrometer for Remote Sensing Of Aerosol and Cloud Optical Properties

NASA Technical Reports Server (NTRS)

Pitts, Michael; Hostetler, Chris; Poole, Lamont; Holden, Carl; Rault, Didier

2000-01-01

Atmospheric remote sensing with the O2 A-band has a relatively long history, but most of these studies were attempting to estimate surface pressure or cloud-top pressure. Recent conceptual studies have demonstrated the potential of spaceborne high spectral resolution O2 A-band spectrometers for retrieval of aerosol and cloud optical properties. The physical rationale of this new approach is that information on the scattering properties of the atmosphere is embedded in the detailed line structure of the O2 A-band reflected radiance spectrum. The key to extracting this information is to measure the radiance spectrum at very high spectral resolution. Instrument performance requirement studies indicate that, in addition to high spectral resolution, the successful retrieval of aerosol and cloud properties from A-band radiance spectra will also require high radiometric accuracy, instrument stability, and high signal-to-noise measurements. To experimentally assess the capabilities of this promising new remote sensing application, the NASA Langley Research Center is developing an airborne high spectral resolution A-band spectrometer. The spectrometer uses a plane holographic grating with a folded Littrow geometry to achieve high spectral resolution (0.5 cm-1) and low stray light in a compact package. This instrument will be flown in a series of field campaigns beginning in 2001 to evaluate the overall feasibility of this new technique. Results from these campaigns should be particularly valuable for future spaceborne applications of A-band spectrometers for aerosol and cloud retrievals.

[Research on symmetrical optical waveguide based surface plasmon resonance sensing with spectral interrogation].

PubMed

Zhang, Yi-long; Liu, Le; Guo, Jun; Zhang, Peng-fei; Guo, Ji-hua; Ma, Hui; He, Yong-hong

2015-02-01

Surface plasmon resonance (SPR) sensors with spectral interrogation can adopt fiber to transmit light signals, thus leaving the sensing part separated, which is very convenient for miniaturization, remote-sensing and on-site analysis. Symmetrical optical waveguide (SOW) SPR has the same refractive index of the-two buffer media layers adjacent to the metal film, resulting in longer propagation distance, deeper penetration depth and better performance compared to conventional SPR In the present paper, we developed a symmetrical optical, waveguide (SOW) SPR sensor with wavelength interrogation. In the system, MgF2-Au-MgF2 film was used as SOW module for glucose sensing, and a fiber based light source and detection was used in the spectral interrogation. In the experiment, a refractive index resolution of 2.8 x 10(-7) RIU in fluid protocol was acquired. This technique provides advantages of high resolution and could have potential use in compact design, on-site analysis and remote sensing.

Design and performance evaluation of the imaging payload for a remote sensing satellite

NASA Astrophysics Data System (ADS)

Abolghasemi, Mojtaba; Abbasi-Moghadam, Dariush

2012-11-01

In this paper an analysis method and corresponding analytical tools for design of the experimental imaging payload (IMPL) of a remote sensing satellite (SINA-1) are presented. We begin with top-level customer system performance requirements and constraints and derive the critical system and component parameters, then analyze imaging payload performance until a preliminary design that meets customer requirements. We consider system parameters and components composing the image chain for imaging payload system which includes aperture, focal length, field of view, image plane dimensions, pixel dimensions, detection quantum efficiency, and optical filter requirements. The performance analysis is accomplished by calculating the imaging payload's SNR (signal-to-noise ratio), and imaging resolution. The noise components include photon noise due to signal scene and atmospheric background, cold shield, out-of-band optical filter leakage and electronic noise. System resolution is simulated through cascaded modulation transfer functions (MTFs) and includes effects due to optics, image sampling, and system motion. Calculations results for the SINA-1 satellite are also presented.

Optical assessment of nonimaging concentrators.

PubMed

Timinger, A; Kribus, A; Ries, H; Smith, T; Walther, M

2000-11-01

An optical measurement method for nonimaging radiation concentrators is proposed. A Lambertian light source is placed in the exit aperture of the concentrator. Looking into the concentrator's entrance aperture from a remote position, one can photograph the transmission patterns. The patterns show the transmission of radiation through the concentrator with the full resolution of the four-dimensional phase space of geometric optics. By matching ray-tracing simulations to the measurement, one can achieve detailed and accurate information about the geometry of the concentrator. This is a remote, noncontact measurement and can be performed in situ for installed concentrators. Additional information regarding small-scale reflector waviness and surface reflectivity can also be obtained from the same measurement with additional analysis.

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.

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.

Research on active imaging information transmission technology of satellite borne quantum remote sensing

NASA Astrophysics Data System (ADS)

Bi, Siwen; Zhen, Ming; Yang, Song; Lin, Xuling; Wu, Zhiqiang

2017-08-01

According to the development and application needs of Remote Sensing Science and technology, Prof. Siwen Bi proposed quantum remote sensing. Firstly, the paper gives a brief introduction of the background of quantum remote sensing, the research status and related researches at home and abroad on the theory, information mechanism and imaging experiments of quantum remote sensing and the production of principle prototype.Then, the quantization of pure remote sensing radiation field, the state function and squeezing effect of quantum remote sensing radiation field are emphasized. It also describes the squeezing optical operator of quantum light field in active imaging information transmission experiment and imaging experiments, achieving 2-3 times higher resolution than that of coherent light detection imaging and completing the production of quantum remote sensing imaging prototype. The application of quantum remote sensing technology can significantly improve both the signal-to-noise ratio of information transmission imaging and the spatial resolution of quantum remote sensing .On the above basis, Prof.Bi proposed the technical solution of active imaging information transmission technology of satellite borne quantum remote sensing, launched researches on its system composition and operation principle and on quantum noiseless amplifying devices, providing solutions and technical basis for implementing active imaging information technology of satellite borne Quantum Remote Sensing.

Remote sensing of water quality and contaminants in the California Bay-Delta

NASA Astrophysics Data System (ADS)

Fichot, C. G.; Downing, B. D.; Windham-Myers, L.; Marvin-DiPasquale, M. C.; Bergamaschi, B. A.; Thompson, D. R.; Gierach, M. M.

2014-12-01

The California Bay-Delta is a highly altered ecosystem largely reclaimed from wetlands for agriculture, and millions of acres of farmland and Californians rely on the Bay-Delta for their water supply. The Bay-Delta also harbors important habitats for many organisms, including commercial and endangered species. Recently, the Delta Stewardship Council developed a two component mission (coequal goals) to 1) provide a more reliable water supply for California while 2) protecting, restoring, and enhancing the Bay-Delta ecosystem. Dissolved organic carbon, turbidity, and contaminants such as methylmercury represent important water quality issues for water management and in the context of wetland restoration in the Bay-Delta, and can threaten the achievement of the coequal goals. Here, we use field measurements of optical properties, chemical analyses, and remotely sensed data acquired with the airborne Portable Remote Imaging SpectroMeter (PRISM ; http://prism.jpl.nasa.gov/index.html) to demonstrate these water quality parameters and the study of their dynamics in the Bay-Delta are amenable to remote sensing. PRISM provides high signal-to-noise, high spatial resolution (~2 m), hyperspectral measurements of remote-sensing reflectance in the 350-1050 nm range, and therefore has the adequate resolutions for water quality monitoring in inland, optically complex waters. Remote sensing of water quality will represent a valuable complement to existing in situ water quality monitoring programs in this region and will help with decision-making to achieve the co-equal goals.

Application of Remote Sensors in Mapping Rice Area and Forecasting Its Production: A Review

PubMed Central

Mosleh, Mostafa K.; Hassan, Quazi K.; Chowdhury, Ehsan H.

2015-01-01

Rice is one of the staple foods for more than three billion people worldwide. Rice paddies accounted for approximately 11.5% of the World's arable land area during 2012. Rice provided ∼19% of the global dietary energy in recent times and its annual average consumption per capita was ∼65 kg during 2010–2011. Therefore, rice area mapping and forecasting its production is important for food security, where demands often exceed production due to an ever increasing population. Timely and accurate estimation of rice areas and forecasting its production can provide invaluable information for governments, planners, and decision makers in formulating policies in regard to import/export in the event of shortfall and/or surplus. The aim of this paper was to review the applicability of the remote sensing-based imagery for rice area mapping and forecasting its production. Recent advances on the resolutions (i.e., spectral, spatial, radiometric, and temporal) and availability of remote sensing imagery have allowed us timely collection of information on the growth and development stages of the rice crop. For elaborative understanding of the application of remote sensing sensors, following issues were described: the rice area mapping and forecasting its production using optical and microwave imagery, synergy between remote sensing-based methods and other developments, and their implications as an operational one. The overview of the studies to date indicated that remote sensing-based methods using optical and microwave imagery found to be encouraging. However, there were having some limitations, such as: (i) optical remote sensing imagery had relatively low spatial resolution led to inaccurate estimation of rice areas; and (ii) radar imagery would suffer from speckles, which potentially would degrade the quality of the images; and also the brightness of the backscatters were sensitive to the interacting surface. In addition, most of the methods used in forecasting rice yield were empirical in nature, so thus it would require further calibration and validation prior to implement over other geographical locations. PMID:25569753

Application of remote sensors in mapping rice area and forecasting its production: a review.

PubMed

Mosleh, Mostafa K; Hassan, Quazi K; Chowdhury, Ehsan H

2015-01-05

Rice is one of the staple foods for more than three billion people worldwide. Rice paddies accounted for approximately 11.5% of the World's arable land area during 2012. Rice provided ~19% of the global dietary energy in recent times and its annual average consumption per capita was ~65 kg during 2010-2011. Therefore, rice area mapping and forecasting its production is important for food security, where demands often exceed production due to an ever increasing population. Timely and accurate estimation of rice areas and forecasting its production can provide invaluable information for governments, planners, and decision makers in formulating policies in regard to import/export in the event of shortfall and/or surplus. The aim of this paper was to review the applicability of the remote sensing-based imagery for rice area mapping and forecasting its production. Recent advances on the resolutions (i.e., spectral, spatial, radiometric, and temporal) and availability of remote sensing imagery have allowed us timely collection of information on the growth and development stages of the rice crop. For elaborative understanding of the application of remote sensing sensors, following issues were described: the rice area mapping and forecasting its production using optical and microwave imagery, synergy between remote sensing-based methods and other developments, and their implications as an operational one. The overview of the studies to date indicated that remote sensing-based methods using optical and microwave imagery found to be encouraging. However, there were having some limitations, such as: (i) optical remote sensing imagery had relatively low spatial resolution led to inaccurate estimation of rice areas; and (ii) radar imagery would suffer from speckles, which potentially would degrade the quality of the images; and also the brightness of the backscatters were sensitive to the interacting surface. In addition, most of the methods used in forecasting rice yield were empirical in nature, so thus it would require further calibration and validation prior to implement over other geographical locations.

Estimation of Soil Moisture from Optical and Thermal Remote Sensing: A Review

PubMed Central

Zhang, Dianjun; Zhou, Guoqing

2016-01-01

As an important parameter in recent and numerous environmental studies, soil moisture (SM) influences the exchange of water and energy at the interface between the land surface and atmosphere. Accurate estimate of the spatio-temporal variations of SM is critical for numerous large-scale terrestrial studies. Although microwave remote sensing provides many algorithms to obtain SM at large scale, such as SMOS and SMAP etc., resulting in many data products, they are almost low resolution and not applicable in small catchment or field scale. Estimations of SM from optical and thermal remote sensing have been studied for many years and significant progress has been made. In contrast to previous reviews, this paper presents a new, comprehensive and systematic review of using optical and thermal remote sensing for estimating SM. The physical basis and status of the estimation methods are analyzed and summarized in detail. The most important and latest advances in soil moisture estimation using temporal information have been shown in this paper. SM estimation from optical and thermal remote sensing mainly depends on the relationship between SM and the surface reflectance or vegetation index. The thermal infrared remote sensing methods uses the relationship between SM and the surface temperature or variations of surface temperature/vegetation index. These approaches often have complex derivation processes and many approximations. Therefore, combinations of optical and thermal infrared remotely sensed data can provide more valuable information for SM estimation. Moreover, the advantages and weaknesses of different approaches are compared and applicable conditions as well as key issues in current soil moisture estimation algorithms are discussed. Finally, key problems and suggested solutions are proposed for future research. PMID:27548168

Estimation of Soil Moisture from Optical and Thermal Remote Sensing: A Review.

PubMed

Zhang, Dianjun; Zhou, Guoqing

2016-08-17

As an important parameter in recent and numerous environmental studies, soil moisture (SM) influences the exchange of water and energy at the interface between the land surface and atmosphere. Accurate estimate of the spatio-temporal variations of SM is critical for numerous large-scale terrestrial studies. Although microwave remote sensing provides many algorithms to obtain SM at large scale, such as SMOS and SMAP etc., resulting in many data products, they are almost low resolution and not applicable in small catchment or field scale. Estimations of SM from optical and thermal remote sensing have been studied for many years and significant progress has been made. In contrast to previous reviews, this paper presents a new, comprehensive and systematic review of using optical and thermal remote sensing for estimating SM. The physical basis and status of the estimation methods are analyzed and summarized in detail. The most important and latest advances in soil moisture estimation using temporal information have been shown in this paper. SM estimation from optical and thermal remote sensing mainly depends on the relationship between SM and the surface reflectance or vegetation index. The thermal infrared remote sensing methods uses the relationship between SM and the surface temperature or variations of surface temperature/vegetation index. These approaches often have complex derivation processes and many approximations. Therefore, combinations of optical and thermal infrared remotely sensed data can provide more valuable information for SM estimation. Moreover, the advantages and weaknesses of different approaches are compared and applicable conditions as well as key issues in current soil moisture estimation algorithms are discussed. Finally, key problems and suggested solutions are proposed for future research.

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

Fluid Lensing, Applications to High-Resolution 3D Subaqueous Imaging & Automated Remote Biosphere Assessment from Airborne and Space-borne Platforms

NASA Astrophysics Data System (ADS)

Chirayath, V.

2014-12-01

Fluid Lensing is a theoretical model and algorithm I present for fluid-optical interactions in turbulent flows as well as two-fluid surface boundaries that, when coupled with an unique computer vision and image-processing pipeline, may be used to significantly enhance the angular resolution of a remote sensing optical system with applicability to high-resolution 3D imaging of subaqueous regions and through turbulent fluid flows. This novel remote sensing technology has recently been implemented on a quadcopter-based UAS for imaging shallow benthic systems to create the first dataset of a biosphere with unprecedented sub-cm-level imagery in 3D over areas as large as 15 square kilometers. Perturbed two-fluid boundaries with different refractive indices, such as the surface between the ocean and air, may be exploited for use as lensing elements for imaging targets on either side of the interface with enhanced angular resolution. I present theoretical developments behind Fluid Lensing and experimental results from its recent implementation for the Reactive Reefs project to image shallow reef ecosystems at cm scales. Preliminary results from petabyte-scale aerial survey efforts using Fluid Lensing to image at-risk coral reefs in American Samoa (August, 2013) show broad applicability to large-scale automated species identification, morphology studies and reef ecosystem characterization for shallow marine environments and terrestrial biospheres, of crucial importance to understanding climate change's impact on coastal zones, global oxygen production and carbon sequestration.

Developing Remote Sensing Products for Monitoring and Modeling Great Lakes Coastal Wetland Vulnerability to Climate Change and Land Use

NASA Astrophysics Data System (ADS)

Bourgeau-Chavez, L. L.; Miller, M. E.; Battaglia, M.; Banda, E.; Endres, S.; Currie, W. S.; Elgersma, K. J.; French, N. H. F.; Goldberg, D. E.; Hyndman, D. W.

2014-12-01

Spread of invasive plant species in the coastal wetlands of the Great Lakes is degrading wetland habitat, decreasing biodiversity, and decreasing ecosystem services. An understanding of the mechanisms of invasion is crucial to gaining control of this growing threat. To better understand the effects of land use and climatic drivers on the vulnerability of coastal zones to invasion, as well as to develop an understanding of the mechanisms of invasion, research is being conducted that integrates field studies, process-based ecosystem and hydrological models, and remote sensing. Spatial data from remote sensing is needed to parameterize the hydrological model and to test the outputs of the linked models. We will present several new remote sensing products that are providing important physiological, biochemical, and landscape information to parameterize and verify models. This includes a novel hybrid radar-optical technique to delineate stands of invasives, as well as natural wetland cover types; using radar to map seasonally inundated areas not hydrologically connected; and developing new algorithms to estimate leaf area index (LAI) using Landsat. A coastal map delineating wetland types including monocultures of the invaders (Typha spp. and Phragmites austrailis) was created using satellite radar (ALOS PALSAR, 20 m resolution) and optical data (Landsat 5, 30 m resolution) fusion from multiple dates in a Random Forests classifier. These maps provide verification of the integrated model showing areas at high risk of invasion. For parameterizing the hydrological model, maps of seasonal wetness are being developed using spring (wet) imagery and differencing that with summer (dry) imagery to detect the seasonally wet areas. Finally, development of LAI remote sensing high resolution algorithms for uplands and wetlands is underway. LAI algorithms for wetlands have not been previously developed due to the difficulty of a water background. These products are being used to improve the hydrological model through higher resolution products and parameterization of variables that have previously been largely unknown.

EXPERIMENTS IN LITHOGRAPHY FROM REMOTE SENSOR IMAGERY.

USGS Publications Warehouse

Kidwell, R. H.; McSweeney, J.; Warren, A.; Zang, E.; Vickers, E.

1983-01-01

Imagery from remote sensing systems such as the Landsat multispectral scanner and return beam vidicon, as well as synthetic aperture radar and conventional optical camera systems, contains information at resolutions far in excess of that which can be reproduced by the lithographic printing process. The data often require special handling to produce both standard and special map products. Some conclusions have been drawn regarding processing techniques, procedures for production, and printing limitations.

Ghost imaging via optical parametric amplification

NASA Astrophysics Data System (ADS)

Li, Hong-Guo; Zhang, De-Jian; Xu, De-Qin; Zhao, Qiu-Li; Wang, Sen; Wang, Hai-Bo; Xiong, Jun; Wang, Kaige

2015-10-01

We investigate theoretically and experimentally thermal light ghost imaging where the light transmitted through the object as the seed light is amplified by an optical parametric amplifier (OPA). In conventional lens imaging systems with OPA, the spectral bandwidth of OPA dominates the image resolution. Theoretically, we prove that in ghost imaging via optical parametric amplification (GIOPA) the bandwidth of OPA will not affect the image resolution. The experimental results show that for weak seed light the image quality in GIOPA is better than that of conventional ghost imaging. Our work may be valuable in remote sensing with ghost imaging technique, where the light passed through the object is weak after a long-distance propagation.

Potential of Sentinel Satellites for Schistosomiasis Monitoring

NASA Astrophysics Data System (ADS)

Li, C.-R.; Tang, L.-L.; Niu, H.-B.; Zhou, X.-N.; Liu, Z.-Y.; Ma, L.-L.; Zhou, Y.-S.

2012-04-01

Schistosomiasis is a parasitic disease that menaces human health. In terms of impact this disease is second only to malaria as the most devastating parasitic disease. Oncomelania hupensis is the unique intermediate host of Schistosoma, and hence monitoring and controlling of the number of oncomelania is key to reduce the risk of schistosomiasis transmission. Remote sensing technology can real-timely access the large-scale environmental factors related to oncomelania breeding and reproduction, such as temperature, moisture, vegetation, soil, and rainfall, and can also provide the efficient information to determine the location, area, and spread tendency of oncomelania. Many studies show that the correlation coefficient between oncomelania densities and remote sensing environmental factors depends largely on suitable and high quality remote sensing data used in retrieve environmental factors. Research achievements on retrieving environmental factors (which are related to the living, multiplying and transmission of oncomelania) by multi-source remote data are shown firstly, including: (a) Vegetation information (e.g., Modified Soil-Adjusted Vegetation Index, Normalized Difference Moisture Index, Fractional Vegetation Cover) extracted from optical remote sensing data, such as Landsat TM, HJ-1A/HSI image; (b) Surface temperature retrieval from Thermal Infrared (TIR) and passive-microwave remote sensing data; (c) Water region, soil moisture, forest height retrieval from synthetic aperture radar data, such as Envisat SAR, DLR's ESAR image. Base on which, the requirements of environmental factor accuracy for schistosomiasis monitoring will be analyzed and summarized. Our work on applying remote sensing technique to schistosomiasis monitoring is then presented. The fuzzy information theory is employed to analyze the sensitivity and feasibility relation between oncomelania densities and environmental factors. Then a mechanism model of predicting oncomelania distribution and densities is developed. The new model is validated with field data of Dongting Lake and the dynamic monitoring of schistosomiasis breeding in Dongting Lake region is presented. Finally, emphasis are placed on analyzing the potential of Sentinel satellites for schistosomiasis monitoring. The requirements of optical high resolution data on spectral resolution, spatial resolution, radiometric resolution/accuracy, as well as the requirements of synthetic aperture radar data on operation frequency, spatial resolution, polarization, radiometric accuracy, repeat cycle are presented and then compared with the parameters of Sentinel satellites. The parameters of Sentinel satellites are also compared with those of available remote satellites, such as Envisat, Landsat, whose data are being used for schistosomiasis monitoring. The application potential of Sentinel satellites for the schistosomiasis monitoring will be concluded in the end, which will benefit for the mission operation, model development, etc.

Coastal High-resolution Observations and Remote Sensing of Ecosystems (C-HORSE)

NASA Technical Reports Server (NTRS)

Guild, Liane

2016-01-01

Coastal benthic marine ecosystems, such as coral reefs, seagrass beds, and kelp forests are highly productive as well as ecologically and commercially important resources. These systems are vulnerable to degraded water quality due to coastal development, terrestrial run-off, and harmful algal blooms. Measurements of these features are important for understanding linkages with land-based sources of pollution and impacts to coastal ecosystems. Challenges for accurate remote sensing of coastal benthic (shallow water) ecosystems and water quality are complicated by atmospheric scattering/absorption (approximately 80+% of the signal), sun glint from the sea surface, and water column scattering (e.g., turbidity). Further, sensor challenges related to signal to noise (SNR) over optically dark targets as well as insufficient radiometric calibration thwart the value of coastal remotely-sensed data. Atmospheric correction of satellite and airborne remotely-sensed radiance data is crucial for deriving accurate water-leaving radiance in coastal waters. C-HORSE seeks to optimize coastal remote sensing measurements by using a novel airborne instrument suite that will bridge calibration, validation, and research capabilities of bio-optical measurements from the sea to the high altitude remote sensing platform. The primary goal of C-HORSE is to facilitate enhanced optical observations of coastal ecosystems using state of the art portable microradiometers with 19 targeted spectral channels and flight planning to optimize measurements further supporting current and future remote sensing missions.

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.

Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer

NASA Astrophysics Data System (ADS)

Kaufman, Y. J.; Tanré, D.; Remer, L. A.; Vermote, E. F.; Chu, A.; Holben, B. N.

1997-07-01

Daily distribution of the aerosol optical thickness and columnar mass concentration will be derived over the continents, from the EOS moderate resolution imaging spectroradiometer (MODIS) using dark land targets. Dark land covers are mainly vegetated areas and dark soils observed in the red and blue channels; therefore the method will be limited to the moist parts of the continents (excluding water and ice cover). After the launch of MODIS the distribution of elevated aerosol concentrations, for example, biomass burning in the tropics or urban industrial aerosol in the midlatitudes, will be continuously monitored. The algorithm takes advantage of the MODIS wide spectral range and high spatial resolution and the strong spectral dependence of the aerosol opacity for most aerosol types that result in low optical thickness in the mid-IR (2.1 and 3.8 μm). The main steps of the algorithm are (1) identification of dark pixels in the mid-IR; (2) estimation of their reflectance at 0.47 and 0.66 μm; and (3) derivation of the optical thickness and mass concentration of the accumulation mode from the detected radiance. To differentiate between dust and aerosol dominated by accumulation mode particles, for example, smoke or sulfates, ratios of the aerosol path radiance at 0.47 and 0.66 μm are used. New dynamic aerosol models for biomass burning aerosol, dust and aerosol from industrial/urban origin, are used to determine the aerosol optical properties used in the algorithm. The error in the retrieved aerosol optical thicknesses, τa is expected to be Δτa = 0.05±0.2τa. Daily values are stored on a resolution of 10×10 pixels (1 km nadir resolution). Weighted and gridded 8-day and monthly composites of the optical thickness, the aerosol mass concentration and spectral radiative forcing are generated for selected scattering angles to increase the accuracy. The daily aerosol information over land and oceans [Tanré et al., this issue], combined with continuous aerosol remote sensing from the ground, will be used to study aerosol climatology, to monitor the sources and sinks of specific aerosol types, and to study the interaction of aerosol with water vapor and clouds and their radiative forcing of climate. The aerosol information will also be used for atmospheric corrections of remotely sensed surface reflectance. In this paper, examples of applications and validations are provided.

24-channel dual microcontroller-based voltage controller for ion optics remote control

NASA Astrophysics Data System (ADS)

Bengtsson, L.

2018-05-01

The design of a 24-channel voltage control instrument for Wenzel Elektronik N1130 NIM modules is described. This instrument is remote controlled from a LabVIEW GUI on a host Windows computer and is intended for ion optics control in electron affinity measurements on negative ions at the CERN-ISOLDE facility. Each channel has a resolution of 12 bits and has a normally distributed noise with a standard deviation of <1 mV. The instrument is designed as a standard 2-unit NIM module where the electronic hardware consists of a printed circuit board with two asynchronously operating microcontrollers.

Mirrors design, analysis and manufacturing of the 550mm Korsch telescope experimental model

NASA Astrophysics Data System (ADS)

Huang, Po-Hsuan; Huang, Yi-Kai; Ling, Jer

2017-08-01

In 2015, NSPO (National Space Organization) began to develop the sub-meter resolution optical remote sensing instrument of the next generation optical remote sensing satellite which follow-on to FORMOSAT-5. Upgraded from the Ritchey-Chrétien Cassegrain telescope optical system of FORMOSAT-5, the experimental optical system of the advanced optical remote sensing instrument was enhanced to an off-axis Korsch telescope optical system which consists of five mirrors. It contains: (1) M1: 550mm diameter aperture primary mirror, (2) M2: secondary mirror, (3) M3: off-axis tertiary mirror, (4) FM1 and FM2: two folding flat mirrors, for purpose of limiting the overall volume, reducing the mass, and providing a long focal length and excellent optical performance. By the end of 2015, we implemented several important techniques including optical system design, opto-mechanical design, FEM and multi-physics analysis and optimization system in order to do a preliminary study and begin to develop and design these large-size lightweight aspheric mirrors and flat mirrors. The lightweight mirror design and opto-mechanical interface design were completed in August 2016. We then manufactured and polished these experimental model mirrors in Taiwan; all five mirrors ware completed as spherical surfaces by the end of 2016. Aspheric figuring, assembling tests and optical alignment verification of these mirrors will be done with a Korsch telescope experimental structure model in 2018.

Fast Spectrometer Construction and Testing

NASA Astrophysics Data System (ADS)

Menke, John

2012-05-01

This paper describes the construction and operation of a medium resolution spectrometer used in the visual wavelength range. It is homebuilt, but has built in guiding and calibration, is fully remote operable, and operates at a resolution R=3000. It features a fast f3.5 system, which allows it to be used with a fast telescope (18 inch f3.5) with no Barlow or other optical matching devices.

Optical flows method for lightweight agile remote sensor design and instrumentation

NASA Astrophysics Data System (ADS)

Wang, Chong; Xing, Fei; Wang, Hongjian; You, Zheng

2013-08-01

Lightweight agile remote sensors have become one type of the most important payloads and were widely utilized in space reconnaissance and resource survey. These imaging sensors are designed to obtain the high spatial, temporary and spectral resolution imageries. Key techniques in instrumentation include flexible maneuvering, advanced imaging control algorithms and integrative measuring techniques, which are closely correlative or even acting as the bottle-necks for each other. Therefore, mutual restrictive problems must be solved and optimized. Optical flow is the critical model which to be fully represented in the information transferring as well as radiation energy flowing in dynamic imaging. For agile sensors, especially with wide-field-of view, imaging optical flows may distort and deviate seriously when they perform large angle attitude maneuvering imaging. The phenomena are mainly attributed to the geometrical characteristics of the three-dimensional earth surface as well as the coupled effects due to the complicated relative motion between the sensor and scene. Under this circumstance, velocity fields distribute nonlinearly, the imageries may badly be smeared or probably the geometrical structures are changed since the image velocity matching errors are not having been eliminated perfectly. In this paper, precise imaging optical flow model is established for agile remote sensors, for which optical flows evolving is factorized by two forms, which respectively due to translational movement and image shape changing. Moreover, base on that, agile remote sensors instrumentation was investigated. The main techniques which concern optical flow modeling include integrative design with lightweight star sensors along with micro inertial measurement units and corresponding data fusion, the assemblies of focal plane layout and control, imageries post processing for agile remote sensors etc. Some experiments show that the optical analyzing method is effective to eliminate the limitations for the performance indexes, and succeeded to be applied for integrative system design. Finally, a principle prototype of agile remote sensor designed by the method is discussed.

Fast Spectrometer Construction and Testing (Abstract)

NASA Astrophysics Data System (ADS)

Menke, J.

2012-12-01

This paper describes the construction and operation of a medium resolution spectrometer used in the visual wavelength range. It is homebuilt, but has built in guiding and calibration, is fully remote-operable, and operates at a resolution R = 3000. It features a fast f/3.5 system, which allows it to be used with a fast telescope (18-inch f/3.5) with no Barlow or other optical matching devices.

Single-Fiber Optical Link For Video And Control

NASA Technical Reports Server (NTRS)

Galloway, F. Houston

1993-01-01

Single optical fiber carries control signals to remote television cameras and video signals from cameras. Fiber replaces multiconductor copper cable, with consequent reduction in size. Repeaters not needed. System works with either multimode- or single-mode fiber types. Nonmetallic fiber provides immunity to electromagnetic interference at suboptical frequencies and much less vulnerable to electronic eavesdropping and lightning strikes. Multigigahertz bandwidth more than adequate for high-resolution television signals.

Remotely operable compact instruments for measuring atmospheric CO2 and CH4 column densities at surface monitoring sites

NASA Astrophysics Data System (ADS)

Kobayashi, N.; Inoue, G.; Kawasaki, M.; Yoshioka, H.; Minomura, M.; Murata, I.; Nagahama, T.; Matsumi, Y.; Tanaka, T.; Morino, I.; Ibuki, T.

2010-08-01

Remotely operable compact instruments for measuring atmospheric CO2 and CH4 column densities were developed in two independent systems: one utilizing a grating-based desktop optical spectrum analyzer (OSA) with a resolution enough to resolve rotational lines of CO2 and CH4 in the regions of 1565-1585 and 1674-1682 nm, respectively; the other is an application of an optical fiber Fabry-Perot interferometer (FFPI) to obtain the CO2 column density. Direct sunlight was collimated via a small telescope installed on a portable sun tracker and then transmitted through an optical fiber into the OSA or the FFPI for optical analysis. The near infrared spectra of the OSA were retrieved by a least squares spectral fitting algorithm. The CO2 and CH4 column densities deduced were in excellent agreement with those measured by a Fourier transform spectrometer with high resolution. The rovibronic lines in the wavelength region of 1570-1575 nm were analyzed by the FFPI. The I0 and I values in the Beer-Lambert law equation to obtain CO2 column density were deduced by modulating temperature of the FFPI, which offered column CO2 with the statistical error less than 0.2% for six hours measurement.

Land use/cover classification in the Brazilian Amazon using satellite images.

PubMed

Lu, Dengsheng; Batistella, Mateus; Li, Guiying; Moran, Emilio; Hetrick, Scott; Freitas, Corina da Costa; Dutra, Luciano Vieira; Sant'anna, Sidnei João Siqueira

2012-09-01

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation-based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi-resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical-based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Land use/cover classification in the Brazilian Amazon using satellite images

PubMed Central

Lu, Dengsheng; Batistella, Mateus; Li, Guiying; Moran, Emilio; Hetrick, Scott; Freitas, Corina da Costa; Dutra, Luciano Vieira; Sant’Anna, Sidnei João Siqueira

2013-01-01

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation-based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi-resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical-based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data. PMID:24353353

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.

Bio-Optical and Remote Sensing Observations in Chesapeake Bay. Chapter 7

NASA Technical Reports Server (NTRS)

Harding, Lawrence W., Jr.; Magnuson, Andrea

2003-01-01

The high temporal and spatial resolution of satellite ocean color observations will prove invaluable for monitoring the health of coastal ecosystems where physical and biological variability demands sampling scales beyond that possible by ship. However, ocean color remote sensing of Case 2 waters is a challenging undertaking due to the optical complexity of the water. The focus of this SIMBIOS support has been to provide in situ optical measurements from Chesapeake Bay (CB) and adjacent mid-Atlantic bight (MAB) waters for use in algorithm development and validation efforts to improve the satellite retrieval of chlorophyll (chl a) in Case 2 waters. CB provides a valuable site for validation of data from ocean color sensors for a number of reasons. First, the physical dimensions of the Bay (> 6,500 km2) make retrievals from satellites with a spatial resolution of approx. 1 km (i.e., SeaWiFS) or less (i.e., MODIS) reasonable for most of the ecosystem. Second, CB is highly influenced by freshwater flow from major rivers, making it a classic Case 2 water body with significant concentrations of chlorophyll, particulates and chromophoric dissolved organic matter (CDOM) that highly impact the shape of reflectance spectra.

Pan Sharpening Quality Investigation of Turkish In-Operation Remote Sensing Satellites: Applications with Rasat and GÖKTÜRK-2 Images

NASA Astrophysics Data System (ADS)

Ozendi, Mustafa; Topan, Hüseyin; Cam, Ali; Bayık, Çağlar

2016-10-01

Recently two optical remote sensing satellites, RASAT and GÖKTÜRK-2, launched successfully by the Republic of Turkey. RASAT has 7.5 m panchromatic, and 15 m visible bands whereas GÖKTÜRK-2 has 2.5 m panchromatic and 5 m VNIR (Visible and Near Infrared) bands. These bands with various resolutions can be fused by pan-sharpening methods which is an important application area of optical remote sensing imagery. So that, the high geometric resolution of panchromatic band and the high spectral resolution of VNIR bands can be merged. In the literature there are many pan-sharpening methods. However, there is not a standard framework for quality investigation of pan-sharpened imagery. The aim of this study is to investigate pan-sharpening performance of RASAT and GÖKTÜRK-2 images. For this purpose, pan-sharpened images are generated using most popular pan-sharpening methods IHS, Brovey and PCA at first. This procedure is followed by quantitative evaluation of pan-sharpened images using Correlation Coefficient (CC), Root Mean Square Error (RMSE), Relative Average Spectral Error (RASE), Spectral Angle Mapper (SAM) and Erreur Relative Globale Adimensionnelle de Synthése (ERGAS) metrics. For generation of pan-sharpened images and computation of metrics SharpQ tool is used which is developed with MATLAB computing language. According to metrics, PCA derived pan-sharpened image is the most similar one to multispectral image for RASAT, and Brovey derived pan-sharpened image is the most similar one to multispectral image for GÖKTÜRK-2. Finally, pan-sharpened images are evaluated qualitatively in terms of object availability and completeness for various land covers (such as urban, forest and flat areas) by a group of operators who are experienced in remote sensing imagery.

The Oasis impact structure, Libya: geological characteristics from ALOS PALSAR-2 data interpretation

NASA Astrophysics Data System (ADS)

van Gasselt, Stephan; Kim, Jung Rack; Choi, Yun-Soo; Kim, Jaemyeong

2017-02-01

Optical and infrared remote sensing may provide first-order clues for the identification of potential impact structures on the Earth. Despite the free availability of at least optical image data at highest resolution, research has shown that remote sensing analysis always remains inconclusive and extensive groundwork is needed for the confirmation of the impact origin of such structures. Commonly, optical image data and digital terrain models have been employed mainly for such remote sensing studies of impact structures. With the advent of imaging radar data, a few excursions have been made to also employ radar datasets. Despite its long use, capabilities of imaging radar for studying surface and subsurface structures have not been exploited quantitatively when applied for the identification and description of such features due to the inherent complexity of backscatter processes. In this work, we make use of higher-level derived radar datasets in order to gain clearer qualitative insights that help to describe and identify potential impact structures. We make use of high-resolution data products from the ALOS PALSAR-1 and ALOS PALSAR-2 L-band sensors to describe the heavily eroded Oasis impact structure located in the Libyan Desert. While amplitude radar data with single polarization have usually been utilized to accompany the suite of remote sensing datasets when interpreting impact structures in the past, we conclude that the integration of amplitude data with HH/HV/HH-HV polarization modes in standard and, in particular, in Ultra-Fine mode, as well as entropy-alpha decomposition data, significantly helps to identify and discriminate surface units based on their consolidation. Based on the overarching structural pattern, we determined the diameter of the eroded Oasis structure at 15.6 ± 0.5 km.

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

NASA Technical Reports Server (NTRS)

1990-01-01

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

A extract method of mountainous area settlement place information from GF-1 high resolution optical remote sensing image under semantic constraints

NASA Astrophysics Data System (ADS)

Guo, H., II

2016-12-01

Spatial distribution information of mountainous area settlement place is of great significance to the earthquake emergency work because most of the key earthquake hazardous areas of china are located in the mountainous area. Remote sensing has the advantages of large coverage and low cost, it is an important way to obtain the spatial distribution information of mountainous area settlement place. At present, fully considering the geometric information, spectral information and texture information, most studies have applied object-oriented methods to extract settlement place information, In this article, semantic constraints is to be added on the basis of object-oriented methods. The experimental data is one scene remote sensing image of domestic high resolution satellite (simply as GF-1), with a resolution of 2 meters. The main processing consists of 3 steps, the first is pretreatment, including ortho rectification and image fusion, the second is Object oriented information extraction, including Image segmentation and information extraction, the last step is removing the error elements under semantic constraints, in order to formulate these semantic constraints, the distribution characteristics of mountainous area settlement place must be analyzed and the spatial logic relation between settlement place and other objects must be considered. The extraction accuracy calculation result shows that the extraction accuracy of object oriented method is 49% and rise up to 86% after the use of semantic constraints. As can be seen from the extraction accuracy, the extract method under semantic constraints can effectively improve the accuracy of mountainous area settlement place information extraction. The result shows that it is feasible to extract mountainous area settlement place information form GF-1 image, so the article proves that it has a certain practicality to use domestic high resolution optical remote sensing image in earthquake emergency preparedness.

Modeling plant composition as community continua in a forest landscape with LiDAR and hyperspectral remote sensing.

PubMed

Hakkenberg, C R; Peet, R K; Urban, D L; Song, C

2018-01-01

In light of the need to operationalize the mapping of forest composition at landscape scales, this study uses multi-scale nested vegetation sampling in conjunction with LiDAR-hyperspectral remotely sensed data from the G-LiHT airborne sensor to map vascular plant compositional turnover in a compositionally and structurally complex North Carolina Piedmont forest. Reflecting a shift in emphasis from remotely sensing individual crowns to detecting aggregate optical-structural properties of forest stands, predictive maps reflect the composition of entire vascular plant communities, inclusive of those species smaller than the resolution of the remotely sensed imagery, intertwined with proximate taxa, or otherwise obscured from optical sensors by dense upper canopies. Stand-scale vascular plant composition is modeled as community continua: where discrete community-unit classes at different compositional resolutions provide interpretable context for continuous gradient maps that depict n-dimensional compositional complexity as a single, consistent RGB color combination. In total, derived remotely sensed predictors explain 71%, 54%, and 48% of the variation in the first three components of vascular plant composition, respectively. Among all remotely sensed environmental gradients, topography derived from LiDAR ground returns, forest structure estimated from LiDAR all returns, and morphological-biochemical traits determined from hyperspectral imagery each significantly correspond to the three primary axes of floristic composition in the study site. Results confirm the complementarity of LiDAR and hyperspectral sensors for modeling the environmental gradients constraining landscape turnover in vascular plant composition and hold promise for predictive mapping applications spanning local land management to global ecosystem modeling. © 2017 by the Ecological Society of America.

Aerosol Optical Depth Retrieval With AVIRIS Data: A Test of Tafkaa

DTIC Science & Technology

2002-09-01

the spatial resolution . Clearly there is a need for a method of AOD retrieval that can cover more of the globe in a...imagers lack sufficient spectral resolution for some scientific applications. The future of remote sensing is in the ability to collect and interpret...AVIRIS is by using a data cube with two axes for the spatial dimensions and the third axis representing the 224 channels that make up the spectral

Magnetic resonance imaging with an optical atomic magnetometer

PubMed Central

Xu, Shoujun; Yashchuk, Valeriy V.; Donaldson, Marcus H.; Rochester, Simon M.; Budker, Dmitry; Pines, Alexander

2006-01-01

We report an approach for the detection of magnetic resonance imaging without superconducting magnets and cryogenics: optical atomic magnetometry. This technique possesses a high sensitivity independent of the strength of the static magnetic field, extending the applicability of magnetic resonance imaging to low magnetic fields and eliminating imaging artifacts associated with high fields. By coupling with a remote-detection scheme, thereby improving the filling factor of the sample, we obtained time-resolved flow images of water with a temporal resolution of 0.1 s and spatial resolutions of 1.6 mm perpendicular to the flow and 4.5 mm along the flow. Potentially inexpensive, compact, and mobile, our technique provides a viable alternative for MRI detection with substantially enhanced sensitivity and time resolution for various situations where traditional MRI is not optimal. PMID:16885210

Criteria for the optimal selection of remote sensing optical images to map event landslides

NASA Astrophysics Data System (ADS)

Fiorucci, Federica; Giordan, Daniele; Santangelo, Michele; Dutto, Furio; Rossi, Mauro; Guzzetti, Fausto

2018-01-01

Landslides leave discernible signs on the land surface, most of which can be captured in remote sensing images. Trained geomorphologists analyse remote sensing images and map landslides through heuristic interpretation of photographic and morphological characteristics. Despite a wide use of remote sensing images for landslide mapping, no attempt to evaluate how the image characteristics influence landslide identification and mapping exists. This paper presents an experiment to determine the effects of optical image characteristics, such as spatial resolution, spectral content and image type (monoscopic or stereoscopic), on landslide mapping. We considered eight maps of the same landslide in central Italy: (i) six maps obtained through expert heuristic visual interpretation of remote sensing images, (ii) one map through a reconnaissance field survey, and (iii) one map obtained through a real-time kinematic (RTK) differential global positioning system (dGPS) survey, which served as a benchmark. The eight maps were compared pairwise and to a benchmark. The mismatch between each map pair was quantified by the error index, E. Results show that the map closest to the benchmark delineation of the landslide was obtained using the higher resolution image, where the landslide signature was primarily photographical (in the landslide source and transport area). Conversely, where the landslide signature was mainly morphological (in the landslide deposit) the best mapping result was obtained using the stereoscopic images. Albeit conducted on a single landslide, the experiment results are general, and provide useful information to decide on the optimal imagery for the production of event, seasonal and multi-temporal landslide inventory maps.

Dynamic optical modulation of an electron beam on a photocathode RF gun: Toward intensity-modulated radiation therapy (IMRT)

NASA Astrophysics Data System (ADS)

Kondoh, Takafumi; Kashima, Hiroaki; Yang, Jinfeng; Yoshida, Yoichi; Tagawa, Seiichi

2008-10-01

In intensity-modulated radiation therapy (IMRT), the aim is to deliver reduced doses of radiation to normal tissue. As a step toward IMRT, we examined dynamic optical modulation of an electron beam produced by a photocathode RF gun. Images on photomasks were transferred onto a photocathode by relay imaging. The resulting beam was controlled by a remote mirror. The modulated electron beam maintained its shape on acceleration, had a fine spatial resolution, and could be moved dynamically by optical methods.

Characterizing Aerosol Distributions and Optical Properties Using the NASA Langley High Spectral Resolution Lidar

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

Hostetler, Chris; Ferrare, Richard

The objective of this project was to provide vertically and horizontally resolved data on aerosol optical properties to assess and ultimately improve how models represent these aerosol properties and their impacts on atmospheric radiation. The approach was to deploy the NASA Langley Airborne High Spectral Resolution Lidar (HSRL) and other synergistic remote sensors on DOE Atmospheric Science Research (ASR) sponsored airborne field campaigns and synergistic field campaigns sponsored by other agencies to remotely measure aerosol backscattering, extinction, and optical thickness profiles. Synergistic sensors included a nadir-viewing digital camera for context imagery, and, later in the project, the NASA Goddard Institutemore » for Space Studies (GISS) Research Scanning Polarimeter (RSP). The information from the remote sensing instruments was used to map the horizontal and vertical distribution of aerosol properties and type. The retrieved lidar parameters include profiles of aerosol extinction, backscatter, depolarization, and optical depth. Products produced in subsequent analyses included aerosol mixed layer height, aerosol type, and the partition of aerosol optical depth by type. The lidar products provided vertical context for in situ and remote sensing measurements from other airborne and ground-based platforms employed in the field campaigns and was used to assess the predictions of transport models. Also, the measurements provide a data base for future evaluation of techniques to combine active (lidar) and passive (polarimeter) measurements in advanced retrieval schemes to remotely characterize aerosol microphysical properties. The project was initiated as a 3-year project starting 1 January 2005. It was later awarded continuation funding for another 3 years (i.e., through 31 December 2010) followed by a 1-year no-cost extension (through 31 December 2011). This project supported logistical and flight costs of the NASA sensors on a dedicated aircraft, the subsequent analysis and archival of the data, and the presentation of results in conferences, workshops, and publications. DOE ASR field campaigns supported under this project included - MAX-Mex /MILAGRO (2006) - TexAQS 2006/GoMACCS (2006) - CHAPS (2007) - RACORO (2009) - CARE/CalNex (2010) In addition, data acquired on HSRL airborne field campaigns sponsored by other agencies were used extensively to fulfill the science objectives of this project and the data acquired have been made available to other DOE ASR investigators upon request.« less

[Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].

PubMed

Wang, Cong; Du, Hua-qiang; Zhou, Guo-mo; Xu, Xiao-jun; Sun, Shao-bo; Gao, Guo-long

2015-05-01

This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest.

[Object-oriented segmentation and classification of forest gap based on QuickBird remote sensing image.

PubMed

Mao, Xue Gang; Du, Zi Han; Liu, Jia Qian; Chen, Shu Xin; Hou, Ji Yu

2018-01-01

Traditional field investigation and artificial interpretation could not satisfy the need of forest gaps extraction at regional scale. High spatial resolution remote sensing image provides the possibility for regional forest gaps extraction. In this study, we used object-oriented classification method to segment and classify forest gaps based on QuickBird high resolution optical remote sensing image in Jiangle National Forestry Farm of Fujian Province. In the process of object-oriented classification, 10 scales (10-100, with a step length of 10) were adopted to segment QuickBird remote sensing image; and the intersection area of reference object (RA or ) and intersection area of segmented object (RA os ) were adopted to evaluate the segmentation result at each scale. For segmentation result at each scale, 16 spectral characteristics and support vector machine classifier (SVM) were further used to classify forest gaps, non-forest gaps and others. The results showed that the optimal segmentation scale was 40 when RA or was equal to RA os . The accuracy difference between the maximum and minimum at different segmentation scales was 22%. At optimal scale, the overall classification accuracy was 88% (Kappa=0.82) based on SVM classifier. Combining high resolution remote sensing image data with object-oriented classification method could replace the traditional field investigation and artificial interpretation method to identify and classify forest gaps at regional scale.

Scalable ion-photon quantum interface based on integrated diffractive mirrors

NASA Astrophysics Data System (ADS)

Ghadimi, Moji; Blūms, Valdis; Norton, Benjamin G.; Fisher, Paul M.; Connell, Steven C.; Amini, Jason M.; Volin, Curtis; Hayden, Harley; Pai, Chien-Shing; Kielpinski, David; Lobino, Mirko; Streed, Erik W.

2017-12-01

Quantum networking links quantum processors through remote entanglement for distributed quantum information processing and secure long-range communication. Trapped ions are a leading quantum information processing platform, having demonstrated universal small-scale processors and roadmaps for large-scale implementation. Overall rates of ion-photon entanglement generation, essential for remote trapped ion entanglement, are limited by coupling efficiency into single mode fibers and scaling to many ions. Here, we show a microfabricated trap with integrated diffractive mirrors that couples 4.1(6)% of the fluorescence from a 174Yb+ ion into a single mode fiber, nearly triple the demonstrated bulk optics efficiency. The integrated optic collects 5.8(8)% of the π transition fluorescence, images the ion with sub-wavelength resolution, and couples 71(5)% of the collected light into the fiber. Our technology is suitable for entangling multiple ions in parallel and overcomes mode quality limitations of existing integrated optical interconnects.

Remote observations with FLUOR and the CHARA Array

NASA Astrophysics Data System (ADS)

Merand, Antoine; Birlan, Mirel; Lelu de Brach, Remi; Coudé du Foresto, Vincent

2004-10-01

Two years ago, the FLUOR interferometric beam combiner moved from IOTA (Infrared Optical Telescopes Array, Mount Hopkins, AZ) to the Center for High Angular Resolution Astronomy (CHARA) Array (Mount Wilson, CA). Apart from offering the largest baselines in the northern hemisphere, this array can be fully operated remotely to allow observations from a distant place. We present here the automations added to the FLUOR hardware, as well as software modifications made in order to allow us to observe from Paris Observatory. We required the remote service to be as reactive as local observations, implying frequent communications between the instrument and the remote observer. We took particular attention to the available bandwidth and reactivity imposed by the secured connection (Virtual Private Network). The first tests are presented.

Enhanced Satellite Remote Sensing of Coastal Waters Using Spatially Improved Bio-Optical Products from SNPP-VIIRS

DTIC Science & Technology

2015-01-01

a spatial resolution of 250-m. The Gumley et al. computation for MODIS sharpening is given as a ratio of high to low resolution top of the atmosphere...NIR) correction (Stumpf, Arnone, Gould, Martinolich, & Ransibrahamanakul, 2003). Standard flagswere used tomask interference from land, clouds , sun...technique This new approach expands on the methodology described by Gumley et al. (2010), with somemodifications. We will compute a sim- ilar spatial

Current LWIR HSI Remote Sensing Activities at Defence R&D Canada - Valcartier

DTIC Science & Technology

2009-10-01

measures the IR radiation from a target scene which is optically combined onto a single detector out-of-phase with the IR radiation from a corresponding...Hyper-Cam-LW. The MODDIFS project involves the development of a leading edge infrared ( IR ) hyperspectral sensor optimized for the standoff detection...essentially offer the optical subtraction capability of the CATSI system but at high-spatial resolution using an MCT focal plane array of 8484

Multi- and hyperspectral remote sensing of tropical marine benthic habitats

NASA Astrophysics Data System (ADS)

Mishra, Deepak R.

Tropical marine benthic habitats such as coral reef and associated environments are severely endangered because of the environmental degradation coupled with hurricanes, El Nino events, coastal pollution and runoff, tourism, and economic development. To monitor and protect this diverse environment it is important to not only develop baseline maps depicting their spatial distribution but also to document their changing conditions over time. Remote sensing offers an important means of delineating and monitoring coral reef ecosystems. Over the last twenty years the scientific community has been investigating the use and potential of remote sensing techniques to determine the conditions of the coral reefs by analyzing their spectral characteristics from space. One of the problems in monitoring coral reefs from space is the effect of the water column on the remotely sensed signal. When light penetrates water its intensity decreases exponentially with increasing depth. This process, known as water column attenuation, exerts a profound effect on remotely sensed data collected over water bodies. The approach presented in this research focuses on the development of semi-analytical models that resolves the confounding influence water column attenuation on substrate reflectance to characterize benthic habitats from high resolution remotely sensed imagery on a per-pixel basis. High spatial resolution satellite and airborne imagery were used as inputs in the models to derive water depth and water column optical properties (e.g., absorption and backscattering coefficients). These parameters were subsequently used in various bio-optical algorithms to deduce bottom albedo and then to classify the benthos, generating a detailed map of benthic habitats. IKONOS and QuickBird multispectral satellite data and AISA Eagle hyperspectral airborne data were used in this research for benthic habitat mapping along the north shore of Roatan Island, Honduras. The AISA Eagle classification was consistently more accurate (84%) including finer definition of geomorphological features than the satellite sensors. IKONOS (81%) and QuickBird (81%) sensors showed similar accuracy to AISA, however, such similarity was only reached at the coarse classification levels of 5 and 6 habitats. These results confirm the potential of an effective combination of high spectral and spatial resolution sensor, for accurate benthic habitat mapping.

Hybrid Microscopy: Enabling Inexpensive High-Performance Imaging through Combined Physical and Optical Magnifications.

PubMed

Zhang, Yu Shrike; Chang, Jae-Byum; Alvarez, Mario Moisés; Trujillo-de Santiago, Grissel; Aleman, Julio; Batzaya, Byambaa; Krishnadoss, Vaishali; Ramanujam, Aishwarya Aravamudhan; Kazemzadeh-Narbat, Mehdi; Chen, Fei; Tillberg, Paul W; Dokmeci, Mehmet Remzi; Boyden, Edward S; Khademhosseini, Ali

2016-03-15

To date, much effort has been expended on making high-performance microscopes through better instrumentation. Recently, it was discovered that physical magnification of specimens was possible, through a technique called expansion microscopy (ExM), raising the question of whether physical magnification, coupled to inexpensive optics, could together match the performance of high-end optical equipment, at a tiny fraction of the price. Here we show that such "hybrid microscopy" methods--combining physical and optical magnifications--can indeed achieve high performance at low cost. By physically magnifying objects, then imaging them on cheap miniature fluorescence microscopes ("mini-microscopes"), it is possible to image at a resolution comparable to that previously attainable only with benchtop microscopes that present costs orders of magnitude higher. We believe that this unprecedented hybrid technology that combines expansion microscopy, based on physical magnification, and mini-microscopy, relying on conventional optics--a process we refer to as Expansion Mini-Microscopy (ExMM)--is a highly promising alternative method for performing cost-effective, high-resolution imaging of biological samples. With further advancement of the technology, we believe that ExMM will find widespread applications for high-resolution imaging particularly in research and healthcare scenarios in undeveloped countries or remote places.

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.

Calibration of passive remote observing optical and microwave instrumentation; Proceedings of the Meeting, Orlando, FL, Apr. 3-5, 1991

NASA Technical Reports Server (NTRS)

Guenther, Bruce W. (Editor)

1991-01-01

Various papers on the calibration of passive remote observing optical and microwave instrumentation are presented. Individual topics addressed include: on-board calibration device for a wide field-of-view instrument, calibration for the medium-resolution imaging spectrometer, cryogenic radiometers and intensity-stabilized lasers for EOS radiometric calibrations, radiometric stability of the Shuttle-borne solar backscatter ultraviolet spectrometer, ratioing radiometer for use with a solar diffuser, requirements of a solar diffuser and measurements of some candidate materials, reflectance stability analysis of Spectralon diffuse calibration panels, stray light effects on calibrations using a solar diffuser, radiometric calibration of SPOT 23 HRVs, surface and aerosol models for use in radiative transfer codes. Also addressed are: calibrated intercepts for solar radiometers used in remote sensor calibration, radiometric calibration of an airborne multispectral scanner, in-flight calibration of a helicopter-mounted Daedalus multispectral scanner, technique for improving the calibration of large-area sphere sources, remote colorimetry and its applications, spatial sampling errors for a satellite-borne scanning radiometer, calibration of EOS multispectral imaging sensors and solar irradiance variability.

Radar and optical remote sensing in offshore domain to detect, characterize, and quantify ocean surface oil slicks

NASA Astrophysics Data System (ADS)

Angelliaume, S.; Ceamanos, X.; Viallefont-Robinet, F.; Baqué, R.; Déliot, Ph.; Miegebielle, V.

2017-10-01

Radar and optical sensors are operationally used by authorities or petroleum companies for detecting and characterizing maritime pollution. The interest lies not only in exploration but also in the monitoring of the maritime environment. Occurrence of natural seeps on the sea surface is a key indicator of the presence of mature source rock in the subsurface. These natural seeps, as well as the oil slicks, are commonly detected using radar sensors but the addition of optical imagery can deliver extra information such as the oil real fraction, which is critical for both exploration purposes and efficient cleanup operations. Today state-of-the-art approaches combine multiple data collected by optical and radar sensors embedded on-board different airborne and spaceborne platforms, to ensure wide spatial coverage and high frequency revisit time. Multi-wavelength imaging system may create a breakthrough in remote sensing applications, but it requires adapted processing techniques that need to be developed. To explore performances offered by multi-wavelength radar and optical sensors for oil slick monitoring, remote sensing data have been collected by SETHI, the airborne system developed by ONERA, during an oil spill cleanup exercise carried out in 2015 in the North Sea, Europe. The uniqueness of this data set lies in its high spatial resolution, low noise level and quasi-simultaneous acquisitions of different part of the electromagnetic spectrum. Specific processing techniques have been developed in order to extract meaningful information associated with oil-covered sea surface. Analysis of this unique and rich dataset demonstrates that remote sensing imagery, collected in both optical and microwave domains, allows to estimate slick surface properties such as the spatial abundance of oil and the relative concentration of hydrocarbons on the sea surface.

Optical polarimetry: Instrumentation and applications; Proceedings of the Seminar, San Diego, Calif., August 23, 24, 1977

NASA Technical Reports Server (NTRS)

Azzam, R. M. A. (Editor); Coffeen, D. L.

1977-01-01

Instrumentation used in optical polarimetry is discussed with reference to high-resolution spectropolarimetry, an orbiter cloud photopolarimeter, X-ray polarimeters, and the design of a self-nulling ellipsometer. Consideration is given to surface and thin-film ellipsometry noting studies of electrochemical surface layers, surface anisotropy, polish layers on infrared window materials, and anodic films. Papers on biological, chemical, and physical polarimetry are presented including birefringence in biological materials, vibrational optical activity, and the optical determination of the thermodynamic phase diagram of a metamagnet. Remote sensing is discussed in terms of polarization imagery, the optical polarimetry of particulate surfaces, and techniques and applications of elliptical polarimetry in astronomy and atmospheric studies.

Investigation of breadboard temperature profiling system for SSME fuel preburner diagnostics

NASA Technical Reports Server (NTRS)

Shirley, J. A.

1986-01-01

The feasibility of measuring temperatures in the space shuttle main engine (SSME) fuel preburner using spontaneous Raman scattering from molecular hydrogen was studied. Laser radiation is transmitted to the preburner through a multimode optical fiber. Backscattered Raman-shifted light is collected and focused into a second fiber which connects to a remote-located spectrograph and a mutlichannel optical detector. Optics collimate and focus laser light from the transmitter fiber defining the probe volume. The high pressure, high temperature preburner environment was simulated by a heated pressure cell. Temperatures determined by the distribution of Q-branch co-vibrational transitions demonstrate precision and accuracy of 3%. It is indicated heat preburner temperatures can be determined with 5% accuracy with spatial resolution less than 1 cm and temporal resolution of 10 millisec at the nominal preburner operation conditions.

Payload Configurations for Efficient Image Acquisition - Indian Perspective

NASA Astrophysics Data System (ADS)

Samudraiah, D. R. M.; Saxena, M.; Paul, S.; Narayanababu, P.; Kuriakose, S.; Kiran Kumar, A. S.

2014-11-01

The world is increasingly depending on remotely sensed data. The data is regularly used for monitoring the earth resources and also for solving problems of the world like disasters, climate degradation, etc. Remotely sensed data has changed our perspective of understanding of other planets. With innovative approaches in data utilization, the demands of remote sensing data are ever increasing. More and more research and developments are taken up for data utilization. The satellite resources are scarce and each launch costs heavily. Each launch is also associated with large effort for developing the hardware prior to launch. It is also associated with large number of software elements and mathematical algorithms post-launch. The proliferation of low-earth and geostationary satellites has led to increased scarcity in the available orbital slots for the newer satellites. Indian Space Research Organization has always tried to maximize the utility of satellites. Multiple sensors are flown on each satellite. In each of the satellites, sensors are designed to cater to various spectral bands/frequencies, spatial and temporal resolutions. Bhaskara-1, the first experimental satellite started with 2 bands in electro-optical spectrum and 3 bands in microwave spectrum. The recent Resourcesat-2 incorporates very efficient image acquisition approach with multi-resolution (3 types of spatial resolution) multi-band (4 spectral bands) electro-optical sensors (LISS-4, LISS-3* and AWiFS). The system has been designed to provide data globally with various data reception stations and onboard data storage capabilities. Oceansat-2 satellite has unique sensor combination with 8 band electro-optical high sensitive ocean colour monitor (catering to ocean and land) along with Ku band scatterometer to acquire information on ocean winds. INSAT- 3D launched recently provides high resolution 6 band image data in visible, short-wave, mid-wave and long-wave infrared spectrum. It also has 19 band sounder for providing vertical profile of water vapour, temperature, etc. The same system has data relay transponders for acquiring data from weather stations. The payload configurations have gone through significant changes over the years to increase data rate per kilogram of payload. Future Indian remote sensing systems are planned with very high efficient ways of image acquisition. This paper analyses the strides taken by ISRO (Indian Space research Organisation) in achieving high efficiency in remote sensing image data acquisition. Parameters related to efficiency of image data acquisition are defined and a methodology is worked out to compute the same. Some of the Indian payloads are analysed with respect to some of the system/ subsystem parameters that decide the configuration of payload. Based on the analysis, possible configuration approaches that can provide high efficiency are identified. A case study is carried out with improved configuration and the results of efficiency improvements are reported. This methodology may be used for assessing other electro-optical payloads or missions and can be extended to other types of payloads and missions.

Improving the analysis of biogeochemical patterns associated with internal waves in the strait of Gibraltar using remote sensing images

NASA Astrophysics Data System (ADS)

Navarro, Gabriel; Vicent, Jorge; Caballero, Isabel; Gómez-Enri, Jesús; Morris, Edward P.; Sabater, Neus; Macías, Diego; Bolado-Penagos, Marina; Gomiz, Juan Jesús; Bruno, Miguel; Caldeira, Rui; Vázquez, Águeda

2018-05-01

High Amplitude Internal Waves (HAIWs) are physical processes observed in the Strait of Gibraltar (the narrow channel between the Atlantic Ocean and the Mediterranean Sea). These internal waves are generated over the Camarinal Sill (western side of the strait) during the tidal outflow (toward the Atlantic Ocean) when critical hydraulic conditions are established. HAIWs remain over the sill for up to 4 h until the outflow slackens, being then released (mostly) towards the Mediterranean Sea. These have been previously observed using Synthetic Aperture Radar (SAR), which captures variations in surface water roughness. However, in this work we use high resolution optical remote sensing, with the aim of examining the influence of HAIWs on biogeochemical processes. We used hyperspectral images from the Hyperspectral Imager for the Coastal Ocean (HICO) and high spatial resolution (10 m) images from the MultiSpectral Instrument (MSI) onboard the Sentinel-2A satellite. This work represents the first attempt to examine the relation between internal wave generation and the water constituents of the Camarinal Sill using hyperspectral and high spatial resolution remote sensing images. This enhanced spatial and spectral resolution revealed the detailed biogeochemical patterns associated with the internal waves and suggests local enhancements of productivity associated with internal waves trains.

Rice Crop Monitoring Using Microwave and Optical Remotely Sensed Image Data

NASA Astrophysics Data System (ADS)

Suga, Y.; Konishi, T.; Takeuchi, S.; Kitano, Y.; Ito, S.

Hiroshima Institute of Technology HIT is operating the direct down-links of microwave and optical satellite data in Japan This study focuses on the validation for rice crop monitoring using microwave and optical remotely sensed image data acquired by satellites referring to ground truth data such as height of crop ratio of crop vegetation cover and leaf area index in the test sites of Japan ENVISAT-1 ASAR data has a capability to capture regularly and to monitor during the rice growing cycle by alternating cross polarization mode images However ASAR data is influenced by several parameters such as landcover structure direction and alignment of rice crop fields in the test sites In this study the validation was carried out combined with microwave and optical satellite image data and ground truth data regarding rice crop fields to investigate the above parameters Multi-temporal multi-direction descending and ascending and multi-angle ASAR alternating cross polarization mode images were used to investigate rice crop growing cycle LANDSAT data were used to detect landcover structure direction and alignment of rice crop fields corresponding to the backscatter of ASAR As the result of this study it was indicated that rice crop growth can be precisely monitored using multiple remotely sensed data and ground truth data considering with spatial spectral temporal and radiometric resolutions

Quantifying sub-pixel urban impervious surface through fusion of optical and inSAR imagery

USGS Publications Warehouse

Yang, L.; Jiang, L.; Lin, H.; Liao, M.

2009-01-01

In this study, we explored the potential to improve urban impervious surface modeling and mapping with the synergistic use of optical and Interferometric Synthetic Aperture Radar (InSAR) imagery. We used a Classification and Regression Tree (CART)-based approach to test the feasibility and accuracy of quantifying Impervious Surface Percentage (ISP) using four spectral bands of SPOT 5 high-resolution geometric (HRG) imagery and three parameters derived from the European Remote Sensing (ERS)-2 Single Look Complex (SLC) SAR image pair. Validated by an independent ISP reference dataset derived from the 33 cm-resolution digital aerial photographs, results show that the addition of InSAR data reduced the ISP modeling error rate from 15.5% to 12.9% and increased the correlation coefficient from 0.71 to 0.77. Spatially, the improvement is especially noted in areas of vacant land and bare ground, which were incorrectly mapped as urban impervious surfaces when using the optical remote sensing data. In addition, the accuracy of ISP prediction using InSAR images alone is only marginally less than that obtained by using SPOT imagery. The finding indicates the potential of using InSAR data for frequent monitoring of urban settings located in cloud-prone areas.

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.

A perspective of synthetic aperture radar for remote sensing

NASA Technical Reports Server (NTRS)

Skolnik, M. I.

1978-01-01

The characteristics and capabilities of synthetic aperture radar are discussed so as to identify those features particularly unique to SAR. The SAR and Optical images were compared. The SAR is an example of radar that provides more information about a target than simply its location. It is the spatial resolution and imaging capability of SAR that has made its application of interest, especially from spaceborne platforms. However, for maximum utility to remote sensing, it was proposed that other information be extracted from SAR data, such as the cross section with frequency and polarization.

A System for Photon-Counting Spectrophotometry of Prompt Optical Emission from Gamma-Ray Bursts

NASA Astrophysics Data System (ADS)

Vestrand, W. T.; Albright, K.; Casperson, D.; Fenimore, E.; Ho, C.; Priedhorsky, W.; White, R.; Wren, J.

2003-04-01

With the launch of HETE-2 and the coming launch of the Swift satellite, there will be many new opportunities to study the physics of the prompt optical emission with robotic ground-based telescopes. Time-resolved spectrophotometry of the rapidly varying optical emission is likely to be a rich area for discovery. We describe a program to apply state-of-the-art photon-counting imaging technology to the study of prompt optical emission from gamma-ray bursts. The Remote Ultra-Low Light Imaging (RULLI) project at Los Alamos National Laboratory has developed an imaging sensor which employs stacked microchannel plates and a crossed delay line readout with 200 picosecond photon timing to measure the time of arrival and positions for individual optical photons. RULLI detectors, when coupled with a transmission grating having 300 grooves/mm, can make photon-counting spectroscopic observations with spectral resolution that is an order of magnitude greater and temporal resolution three orders of magnitude greater than the most capable photon-counting imaging detectors that have been used for optical astronomy.

Remote atmospheric probing by ground to ground line of sight optical methods

NASA Technical Reports Server (NTRS)

Lawrence, R. S.

1969-01-01

The optical effects arising from refractive-index variations in the clear air are qualitatively described, and the possibilities are discussed of using those effects for remotely sensing the physical properties of the atmosphere. The effects include scintillations, path length fluctuations, spreading of a laser beam, deflection of the beam, and depolarization. The physical properties that may be measured include the average temperature along the path, the vertical temperature gradient, and the distribution along the path of the strength of turbulence and the transverse wind velocity. Line-of-sight laser beam methods are clearly effective in measuring the average properties, but less effective in measuring distributions along the path. Fundamental limitations to the resolution are pointed out and experiments are recommended to investigate the practicality of the methods.

Optically based technique for producing merged spectra of water-leaving radiances from ocean color remote sensing.

PubMed

Mélin, Frédéric; Zibordi, Giuseppe

2007-06-20

An optically based technique is presented that produces merged spectra of normalized water-leaving radiances L(WN) by combining spectral data provided by independent satellite ocean color missions. The assessment of the merging technique is based on a four-year field data series collected by an autonomous above-water radiometer located on the Acqua Alta Oceanographic Tower in the Adriatic Sea. The uncertainties associated with the merged L(WN) obtained from the Sea-viewing Wide Field-of-view Sensor and the Moderate Resolution Imaging Spectroradiometer are consistent with the validation statistics of the individual sensor products. The merging including the third mission Medium Resolution Imaging Spectrometer is also addressed for a reduced ensemble of matchups.

Evaluation of Bio-optical Models for Discriminating Phytoplankton Functional Types and Size Classes in Eastern U.S. Coastal Waters with Approaches to Remote Sensing Applications

NASA Astrophysics Data System (ADS)

Neeley, A. R.; Goes, J. I.; Jenkins, C. A.; Harris, L.

2016-02-01

Phytoplankton species can be separated into phytoplankton functional types (PFTs) or size classes (PSCs; Micro-, Nano-, and Picoplankton). Bio-optical models have been developed to use satellite-derived products to discriminate PSCs and PFTs, a recommended field measurement for the future NASA PACE mission. The proposed 5 nm spectral resolution of the PACE ocean color sensor will improve detection of PSCs and PFTs by discriminating finer optical features not detected at the spectral resolution of current satellite-borne instruments. In preparation for PACE, new and advanced models are under development that require accurate data for validation. Phytoplankton pigment data have long been collected from aquatic environments and are widely used to model PSC and PFT abundances using two well-known methods: Diagnostic Pigment Analysis (DPA) and Chemical Taxonomy (ChemTax), respectively. Here we present the results of an effort to evaluate five bio-optical PFT models using data from a field campaign off the coast of the Eastern U.S. in November 2014: two based on biomass (Chlorophyll a), two based on light absorption properties of phytoplankton and one based the inversion of remote sensing reflectances. PFT model performance is evaluated using phytoplankton taxonomic data from a FlowCam sensor and DPA and ChemTax analyses using pigment data collected during the field campaign in a variety of water types and optical complexities (e.g., coastal, blue water, eddies and fronts). Relative strengths of the model approaches will be presented as a model validation exercise using both in situ and satellite derived input products.

Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery

NASA Astrophysics Data System (ADS)

Qiu, Chunping; Schmitt, Michael; Zhu, Xiao Xiang

2018-04-01

In this paper we discuss the potential and challenges regarding SAR-optical stereogrammetry for urban areas, using very-high-resolution (VHR) remote sensing imagery. Since we do this mainly from a geometrical point of view, we first analyze the height reconstruction accuracy to be expected for different stereogrammetric configurations. Then, we propose a strategy for simultaneous tie point matching and 3D reconstruction, which exploits an epipolar-like search window constraint. To drive the matching and ensure some robustness, we combine different established hand-crafted similarity measures. For the experiments, we use real test data acquired by the Worldview-2, TerraSAR-X and MEMPHIS sensors. Our results show that SAR-optical stereogrammetry using VHR imagery is generally feasible with 3D positioning accuracies in the meter-domain, although the matching of these strongly hetereogeneous multi-sensor data remains very challenging.

Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery.

PubMed

Qiu, Chunping; Schmitt, Michael; Zhu, Xiao Xiang

2018-04-01

In this paper we discuss the potential and challenges regarding SAR-optical stereogrammetry for urban areas, using very-high-resolution (VHR) remote sensing imagery. Since we do this mainly from a geometrical point of view, we first analyze the height reconstruction accuracy to be expected for different stereogrammetric configurations. Then, we propose a strategy for simultaneous tie point matching and 3D reconstruction, which exploits an epipolar-like search window constraint. To drive the matching and ensure some robustness, we combine different established hand-crafted similarity measures. For the experiments, we use real test data acquired by the Worldview-2, TerraSAR-X and MEMPHIS sensors. Our results show that SAR-optical stereogrammetry using VHR imagery is generally feasible with 3D positioning accuracies in the meter-domain, although the matching of these strongly hetereogeneous multi-sensor data remains very challenging.

Self-Referenced Fiber Optic System For Remote Methane Detection

NASA Astrophysics Data System (ADS)

Zientkiewicz, Jacek K.

1989-10-01

The paper discusses a fiber optic multisensor methane detection system matched to topology and environment of the underground mine. The system involves time domain multiplexed (TDM) methane sensors based on selective absorption of source radiation by atomic/molecular species in the gas sensing heads. A two-wavelength ratiometric approach allows simple self-referencing, cancels out errors arising from other contaminants, and improves the measurement contrast. The laboratory system consists of a high radiance LED source, multimode fiber, optical sensing head, optical bandpass filters, and involves synchronous detection with low noise photodiodes and a lock-in amplifier. Detection sensitivity versus spectral resolution of the optical filters has also been investigated and described. The system performance was evaluated and the results are presented.

Uncertainties in mapping forest carbon in urban ecosystems.

PubMed

Chen, Gang; Ozelkan, Emre; Singh, Kunwar K; Zhou, Jun; Brown, Marilyn R; Meentemeyer, Ross K

2017-02-01

Spatially explicit urban forest carbon estimation provides a baseline map for understanding the variation in forest vertical structure, informing sustainable forest management and urban planning. While high-resolution remote sensing has proven promising for carbon mapping in highly fragmented urban landscapes, data cost and availability are the major obstacle prohibiting accurate, consistent, and repeated measurement of forest carbon pools in cities. This study aims to evaluate the uncertainties of forest carbon estimation in response to the combined impacts of remote sensing data resolution and neighborhood spatial patterns in Charlotte, North Carolina. The remote sensing data for carbon mapping were resampled to a range of resolutions, i.e., LiDAR point cloud density - 5.8, 4.6, 2.3, and 1.2 pt s/m 2 , aerial optical NAIP (National Agricultural Imagery Program) imagery - 1, 5, 10, and 20 m. Urban spatial patterns were extracted to represent area, shape complexity, dispersion/interspersion, diversity, and connectivity of landscape patches across the residential neighborhoods with built-up densities from low, medium-low, medium-high, to high. Through statistical analyses, we found that changing remote sensing data resolution introduced noticeable uncertainties (variation) in forest carbon estimation at the neighborhood level. Higher uncertainties were caused by the change of LiDAR point density (causing 8.7-11.0% of variation) than changing NAIP image resolution (causing 6.2-8.6% of variation). For both LiDAR and NAIP, urban neighborhoods with a higher degree of anthropogenic disturbance unveiled a higher level of uncertainty in carbon mapping. However, LiDAR-based results were more likely to be affected by landscape patch connectivity, and the NAIP-based estimation was found to be significantly influenced by the complexity of patch shape. Copyright © 2016 Elsevier Ltd. All rights reserved.

Arecibo Optical Laboratory Upgrade: imaging FPI first results

NASA Astrophysics Data System (ADS)

Noto, J.; Kerr, R. B.; Migliozzi, M. A.; Tepley, C. A.; Friedman, J.; Garcia, R.; Robles, E.; Waldrop, L. S.

2006-05-01

The Optical Laboratory at the Arecibo Observatory is being upgraded to permit remote operation, to improve Fabry-Perot Interferometer (FPI) sensitivity, and to permit FPI response in the near infrared. Integration of a 2048 x 2048 Andor CCD array into the existing low-resolution Fabry Perot Interferometer is complete. Remote operation and data acquisition for this FPI is accomplished by transition from the obsolete PDP-11 data acquisition system to PC-based, internet aware control. Another upgrade stage, adding a near-infrared focal plane array to a second FPI is scheduled for the fall of this year. Configured with a spectral resolution of 0.0086 nm at 656.3 nm, the low resolution FPI sampled the geocoronal Balmer-alpha emission during three new moon periods in November and December, 2005, and January, 2006. The latter two observation campaigns were conducted using the new remote control capability. The single etalon FPI produces three orders at the CCD plane corresponding to a full field-of-view of 0.92 degrees. The FPI Hadinger ring pattern is summed annularly, and the three orders are subsequently summed, producing an instrument sensitivity that is 43 times better than the previous single channel photomultiplier detection system. Raw detector response is corrected using both linear (chip bias) and non-linear techniques (flat-field) prior to ring-summing. A frequency stabilized HeNe laser at 632.8 nm is remotely operated to establish the FPI response function. Effective exospheric temperature and line profile asymmetries are determined after decomposition of the instrument response function from the measured airglow emission. Identification and climatological characterization of non-Maxwellian H distributions, with simultaneous quantification of H+ abundance and flow in the topside ionosphere by the Arecibo incoherent scatter radar, are measurements central to our goal of improved understanding of H on H+ charge exchange escape of H.

Remote sounding of tropospheric minor constituents

NASA Technical Reports Server (NTRS)

Drayson, S. Roland; Hays, Paul B.; Wang, Jinxue

1993-01-01

The etalon interferometer, or Fabry-Perot interferometer (FPI), with its high throughput and high spectral resolution was widely used in the remote-sensing measurements of the earth's atmospheric composition, winds, and temperatures. The most recent satellite instruments include the Fabry-Perot interferometer flown on the Dynamics Explorer-2 (DE-2) and the High Resolution Doppler Imager (HRDI) to be flown on the Upper Atmosphere Research Satellite (UARS). These instruments measure the Doppler line profiles of the emission and absorption of certain atmospheric species (such as atomic oxygen) in the visible spectral region. The successful space flight of DE-FPI and the test and delivery of UARS-HRDI demonstrated the extremely high spectral resolution and ruggedness of the etalon system for the remote sensing of earth and planetary atmospheres. Recently, an innovative FPI focal plane detection technique called the Circle-to-Line Interferometer Optical (CLIO) system was invented at the Space Physics Research Laboratory (SPRL). The CLIO simplifies the FPI focal plane detection process by converting the circular rings or fringes into a linear pattern similar to that produced by a conventional spectrometer, while retaining the throughput advantage of the etalon interferometer. CLIO makes the use of linear array detectors more practical and efficient with FPI, the combination of FPI and CLIO represents a very promising new technique for the remote sensing of the lower atmospheres of Earth, Mars, Venus, Neptune, and other planets. The Multiorder Etalon Spectrometer (MOES), as a combination of the rugged etalon and the CLIO, compares very favorably to other spaceborne optical instruments in terms of performance versus complexity. The feasibility of an advanced etalon spectrometer for the remote sensing of tropospheric trace species, particularly carbon monoxide (CO), nitrous oxide (N2O), and methane (CH4) was discussed. The etalon atmospheric spectroscopy techniques are described, instrument design and related technical issues are discussed. The primary objective is to establish the concept of atmospheric spectroscopy with the CLIO and etalon system and its applications for the measurements of tropospheric trace species analyze system requirements and performance, determine the feasibility of components and subsystem implementation with available technology, and develop inversion algorithm for retrieval simulation and data analysis.

GRACES, the Gemini remote access CFHT ESPaDOnS spectrograph: initial design and testing

NASA Astrophysics Data System (ADS)

Tollestrup, Eric V.; Pazder, John; Barrick, Gregory; Martioli, Eder; Schiavon, Ricardo; Anthony, André; Halman, Mark; Veillet, Christian

2012-09-01

The Gemini Remote Access CFHT ESPaDOnS Spectrograph (GRACES) is an innovative instrumentation experiment that will demonstrate if ESPaDOnS, a bench-mounted high-resolution optical spectrograph at CFHT, can be fed by a 270-m long fiber from the Gemini-North telescope with low enough losses to remain competitive with conventional spectrographs on other 8 to 10-m telescopes. Detailed simulations have shown that GRACES should be more sensitive than the HIRES spectrograph at Keck Observatory at wavelengths longer than about 600-700 nm. This result is possible by using FPB-type of optical fibers made by Polymicro Technologies and by keeping the critical focal ratio degradation (FRD) losses to less than 10%. Laboratory tests on these FPB optical fibers are underway and show that for 36-m lengths that the FRD losses are as low as 0.8% with a repeatability of 1%. Tests are currently underway on 280-m lengths.

Holographic pixel super-resolution in portable lensless on-chip microscopy using a fiber-optic array.

PubMed

Bishara, Waheb; Sikora, Uzair; Mudanyali, Onur; Su, Ting-Wei; Yaglidere, Oguzhan; Luckhart, Shirley; Ozcan, Aydogan

2011-04-07

We report a portable lensless on-chip microscope that can achieve <1 µm resolution over a wide field-of-view of ∼ 24 mm(2) without the use of any mechanical scanning. This compact on-chip microscope weighs ∼ 95 g and is based on partially coherent digital in-line holography. Multiple fiber-optic waveguides are butt-coupled to light emitting diodes, which are controlled by a low-cost micro-controller to sequentially illuminate the sample. The resulting lensfree holograms are then captured by a digital sensor-array and are rapidly processed using a pixel super-resolution algorithm to generate much higher resolution holographic images (both phase and amplitude) of the objects. This wide-field and high-resolution on-chip microscope, being compact and light-weight, would be important for global health problems such as diagnosis of infectious diseases in remote locations. Toward this end, we validate the performance of this field-portable microscope by imaging human malaria parasites (Plasmodium falciparum) in thin blood smears. Our results constitute the first-time that a lensfree on-chip microscope has successfully imaged malaria parasites.

Fiber optically isolated and remotely stabilized data transmission system

DOEpatents

Nelson, Melvin A.

1992-01-01

A fiber optically isolated and remotely stabilized data transmission system s described wherein optical data may be transmitted over an optical data fiber from a remote source which includes a data transmitter and a power supply at the remote source. The transmitter may be remotely calibrated and stabilized via an optical control fiber, and the power source may be remotely cycled between duty and standby modes via an optical control fiber.

Fiber optically isolated and remotely stabilized data transmission system

DOEpatents

Nelson, M.A.

1992-11-10

A fiber optically isolated and remotely stabilized data transmission systems described wherein optical data may be transmitted over an optical data fiber from a remote source which includes a data transmitter and a power supply at the remote source. The transmitter may be remotely calibrated and stabilized via an optical control fiber, and the power source may be remotely cycled between duty and standby modes via an optical control fiber. 3 figs.

Remote Sensing of Vineyard FPAR, with Implications for Irrigation Scheduling

NASA Technical Reports Server (NTRS)

Johnson, Lee F.; Scholasch, Thibaut

2004-01-01

Normalized difference vegetation index (NDVI) data, acquired at two-meter resolution by an airborne ADAR System 5500, were compared with fraction of photosynthetically active radiation (FPAR) absorbed by commercial vineyards in Napa Valley, California. An empirical line correction was used to transform image digital counts to surface reflectance. "Apparent" NDVI (generated from digital counts) and "corrected" NDVI (from reflectance) were both strongly related to FPAR of range 0.14-0.50 (both r(sup 2) = 0.97, P < 0.01). By suppressing noise, corrected NDVI should form a more spatially and temporally stable relationship with FPAR, reducing the need for repeated field support. Study results suggest the possibility of using optical remote sensing to monitor the transpiration crop coefficient, thus providing an enhanced spatial resolution component to crop water budget calculations and irrigation management.

Different atmospheric effects in remote sensing of uniform and nonuniform surfaces

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Fraser, R. S.

1982-01-01

The atmospheric effect on the radiance of sunlight scattered from the earth-atmosphere system is greatly dependent on the surface reflectance pattern, the contrast between adjacent fields, and the optical properties of the atmosphere. In addition, the atmospheric effect is described by the range and magnitude of the adjacency effects, the atmospheric modulation transfer function, and the apparent spatial resolution of remotely sensed imagery. This paper discusses the atmospheric effect on classification of surface features and shows that surface nonuniformity can be used for developing procedures to remove the atmospheric effect from the satellite imagery.

Interferometric fiber-optic temperature sensor with spiral polarization couplers

NASA Astrophysics Data System (ADS)

Cortés, R.; Khomenko, A. V.; Starodumov, A. N.; Arzate, N.; Zenteno, L. A.

1998-09-01

A fiber optic temperature sensor, for which the changes in modal birefringence of a short section of a long birefringent fiber are monitored remotely, is described. It employs a white light interferometer, which is formed by two concatenated spiral polarization mode couplers. A new method for white light interferometer output signal processing is described which provides a high accuracy absolute temperature measurement even in discontinuous operation of the sensor. Experimental results are presented for temperature measurements over a 100°C range with resolution of 3×10 -3 °C.

Combining optical remote sensing, agricultural statistics and field observations for culture recognition over a peri-urban region

NASA Astrophysics Data System (ADS)

Delbart, Nicolas; Emmanuelle, Vaudour; Fabienne, Maignan; Catherine, Ottlé; Jean-Marc, Gilliot

2017-04-01

This study explores the potential of multi-temporal optical remote sensing, with high revisit frequency, to derive missing information on agricultural calendar and crop types over the agricultural lands in the Versailles plain in the western Paris suburbs. This study comes besides past and ongoing studies on the use of radar and high spatial resolution optical remote sensing to monitor agricultural practices in this study area (e.g. Vaudour et al. 2014). Agricultural statistics, such as the Land Parcel Identification System (LPIS) for France, permit to know the nature of annual crops for each digitized declared field of this land parcel registry. However, within each declared field several cropped plots and a diversity of practices may exist, being marked by agricultural rotations which vary both spatially and temporally within it and differ from one year to the other. Even though the new LPIS to be released in 2016 is expected to describe individual plots within declared fields, its attributes may not enable to discriminate between winter and spring crops. Here we evaluate the potential of high observation frequency remote sensing to differentiate seasonal crops based essentially on the seasonality of the spectral properties. In particular, we use the Landsat data to spatially disaggregate the LPIS statistical data, on the basis of the analysis of the remote sensing spectral seasonality measured on a number of selected ground-observed fields. This work is carried out in the framework of the CNES TOSCA-PLEIADES-CO of the French Space Agency.

Regional glacier changes in the Ötztal Alps (Tyrol, Austria) - Results from different remote sensing techniques

NASA Astrophysics Data System (ADS)

Klug, Christoph; Rieg, Lorenzo; Sailer, Rudolf

2017-04-01

Climate change will pose a variety of challenges in the future, with global sea level rise among the most important ones. Out of all contributions to sea level rise, the contribution from glaciers is the one with the highest uncertainty. This is mainly because only very few and not necessarily representative glaciers are measured regularly. Among others, this limits the validation of extrapolation models. On a regional scale, remote sensing data offer several possibilities for the mapping and monitoring of glaciers. Especially with the advent of very high resolution data, new possibilities can be exploited. The monitoring of glacier area, the calculation of the geodetic glacier mass balances and the tracking of changes in the seasonal snow and firn bodies of glaciers on a regional scale can not only help to enhance the spatial, but also the temporal coverage of observations. The Ötztal Alps in Tyrol, Austria have been a research focus for the University of Innsbruck for several decades. Ongoing glaciological field measurements at two reference glaciers (Hintereisferner and Kesselwandferner) and data from different remote sensing techniques provide a valuable basis for a variety of research. The presented study analyses high-resolution airborne laser scanning (ALS) data, with more than 10 years of annual campaigns on Hintereisferner (2001-2013) and two campaigns covering all of the Ötztal Alps (2006 and 2010) in combination with orthoimages and optical satellite data. Furthermore Pléiades tri-stereo data (2015 and 2016) are available to calculate very high resolution and high quality digital terrain models (DTM). These DTM can be used to extend the time series in combination with the DTM based on ALS data and enable the calculation of the geodetic glacier mass balance for over 150 glaciers within the study area. Furthermore, the optical information (ALS intensity, orthoimages and optical satellite data) is used for surface classification in order to monitor the glacier surfaces. This enables either a monitoring of changes in glacier area or in changes of the extent of firn-bodies on the glaciers. We will present an overview of glacier changes in the Ötztal Alps during the last 15 years and also discuss the uncertainties in the used remote-sensing techniques as well as the error management. In addition, the potential of extending our investigations to other mountain areas is intended.

Assessing diversity of prairie plants using remote sensing

NASA Astrophysics Data System (ADS)

Gamon, J. A.; Wang, R.

2017-12-01

Biodiversity loss endangers ecosystem services and is considered as a global change that may generate unacceptable environmental consequences for the Earth system. Global biodiversity observations are needed to provide a better understanding of biodiversity - ecosystem services relationships and to provide a stronger foundation for conserving the Earth's biodiversity. While remote sensing metrics have been applied to estimate α biodiversity directly through optical diversity, a better understanding of the mechanisms behind the optical diversity-biodiversity relationship is needed. We designed a series of experiments at Cedar Creek Ecosystem Science Reserve, MN, to investigate the scale dependence of optical diversity and explore how species richness, evenness, and composition affect optical diversity. We collected hyperspectral reflectance of 16 prairie species using both a full-range field spectrometer fitted with a leaf clip, and an imaging spectrometer carried by a tram system to simulate plot-level images with different species richness, evenness, and composition. Two indicators of spectral diversity were explored: the coefficient of variation (CV) of spectral reflectance in space, and spectral classification using a Partial Least Squares Discriminant Analysis (PLS-DA). Our results showed that sampling methods (leaf clip-derived data vs. image-derived data) affected the optical diversity estimation. Both optical diversity indices were affected by species richness and evenness (P<0.001 for each case). At fine spatial scales, species composition also had a substantial influence on optical diversity. CV was sensitive to the background soil influence, but the spectral classification method was insensitive to background. These results provide a critical foundation for assessing biodiversity using imaging spectrometry and these findings can be used to guide regional studies of biodiversity estimation using high spatial and spectral resolution remote sensing.

NASA's Future Active Remote Sensing Missing for Earth Science

NASA Technical Reports Server (NTRS)

Hartley, Jonathan B.

2000-01-01

Since the beginning of space remote sensing of the earth, there has been a natural progression widening the range of electromagnetic radiation used to sense the earth, and slowly, steadily increasing the spatial, spectral, and radiometric resolution of the measurements. There has also been a somewhat slower trend toward active measurements across the electromagnetic spectrum, motivated in part by increased resolution, but also by the ability to make new measurements. Active microwave instruments have been used to measure ocean topography, to study the land surface. and to study rainfall from space. Future NASA active microwave missions may add detail to the topographical studies, sense soil moisture, and better characterize the cryosphere. Only recently have active optical instruments been flown in space by NASA; however, there are currently several missions in development which will sense the earth with lasers and many more conceptual active optical missions which address the priorities of NASA's earth science program. Missions are under development to investigate the structure of the terrestrial vegetation canopy, to characterize the earth's ice caps, and to study clouds and aerosols. Future NASA missions may measure tropospheric vector winds and make vastly improved measurements of the chemical components of the earth's atmosphere.

A review of progress in identifying and characterizing biocrusts using proximal and remote sensing

NASA Astrophysics Data System (ADS)

Rozenstein, Offer; Adamowski, Jan

2017-05-01

Biocrusts are critical components of desert ecosystems, significantly modifying the surfaces they occupy. The mixture of biological components and soil particles that form the crust, in conjunction with moisture, determines the biocrusts' spectral signatures. Proximal and remote sensing in complementary spectral regions, namely the reflective region, and the thermal region, have been used to study biocrusts in a non-destructive manner, in the laboratory, in the field, and from space. The objectives of this review paper are to present the spectral characteristics of biocrusts across the optical domain, and to discuss significant developments in the application of proximal and remote sensing for biocrust studies in the last few years. The motivation for using proximal and remote sensing in biocrust studies is discussed. Next, the application of reflectance spectroscopy to the study of biocrusts is presented followed by a review of the emergence of high spectral resolution thermal remote sensing, which facilitates the application of thermal spectroscopy for biocrust studies. Four specific topics at the forefront of proximal and remote sensing of biocrusts are discussed: (1) The use of remote sensing in determining the role of biocrusts in global biogeochemical cycles; (2) Monitoring the inceptive establishment of biocrusts; (3) Identifying and characterizing biocrusts using Longwave infrared spectroscopy; and (4) Diurnal emissivity dynamics of biocrusts in a sand dune environment. The paper concludes by identifying innovative technologies such as low altitude and high resolution imagery that are increasingly used in remote sensing science, and are expected to be used in future biocrusts studies.

Cybernetic group method of data handling (GMDH) statistical learning for hyperspectral remote sensing inverse problems in coastal ocean optics

NASA Astrophysics Data System (ADS)

Filippi, Anthony Matthew

For complex systems, sufficient a priori knowledge is often lacking about the mathematical or empirical relationship between cause and effect or between inputs and outputs of a given system. Automated machine learning may offer a useful solution in such cases. Coastal marine optical environments represent such a case, as the optical remote sensing inverse problem remains largely unsolved. A self-organizing, cybernetic mathematical modeling approach known as the group method of data handling (GMDH), a type of statistical learning network (SLN), was used to generate explicit spectral inversion models for optically shallow coastal waters. Optically shallow water light fields represent a particularly difficult challenge in oceanographic remote sensing. Several algorithm-input data treatment combinations were utilized in multiple experiments to automatically generate inverse solutions for various inherent optical property (IOP), bottom optical property (BOP), constituent concentration, and bottom depth estimations. The objective was to identify the optimal remote-sensing reflectance Rrs(lambda) inversion algorithm. The GMDH also has the potential of inductive discovery of physical hydro-optical laws. Simulated data were used to develop generalized, quasi-universal relationships. The Hydrolight numerical forward model, based on radiative transfer theory, was used to compute simulated above-water remote-sensing reflectance Rrs(lambda) psuedodata, matching the spectral channels and resolution of the experimental Naval Research Laboratory Ocean PHILLS (Portable Hyperspectral Imager for Low-Light Spectroscopy) sensor. The input-output pairs were for GMDH and artificial neural network (ANN) model development, the latter of which was used as a baseline, or control, algorithm. Both types of models were applied to in situ and aircraft data. Also, in situ spectroradiometer-derived Rrs(lambda) were used as input to an optimization-based inversion procedure. Target variables included bottom depth z b, chlorophyll a concentration [chl- a], spectral bottom irradiance reflectance Rb(lambda), and spectral total absorption a(lambda) and spectral total backscattering bb(lambda) coefficients. When applying the cybernetic and neural models to in situ HyperTSRB-derived Rrs, the difference in the means of the absolute error of the inversion estimates for zb was significant (alpha = 0.05). GMDH yielded significantly better zb than the ANN. The ANN model posted a mean absolute error (MAE) of 0.62214 m, compared with 0.55161 m for GMDH.

Hybrid photonic signal processing

NASA Astrophysics Data System (ADS)

Ghauri, Farzan Naseer

This thesis proposes research of novel hybrid photonic signal processing systems in the areas of optical communications, test and measurement, RF signal processing and extreme environment optical sensors. It will be shown that use of innovative hybrid techniques allows design of photonic signal processing systems with superior performance parameters and enhanced capabilities. These applications can be divided into domains of analog-digital hybrid signal processing applications and free-space---fiber-coupled hybrid optical sensors. The analog-digital hybrid signal processing applications include a high-performance analog-digital hybrid MEMS variable optical attenuator that can simultaneously provide high dynamic range as well as high resolution attenuation controls; an analog-digital hybrid MEMS beam profiler that allows high-power watt-level laser beam profiling and also provides both submicron-level high resolution and wide area profiling coverage; and all optical transversal RF filters that operate on the principle of broadband optical spectral control using MEMS and/or Acousto-Optic tunable Filters (AOTF) devices which can provide continuous, digital or hybrid signal time delay and weight selection. The hybrid optical sensors presented in the thesis are extreme environment pressure sensors and dual temperature-pressure sensors. The sensors employ hybrid free-space and fiber-coupled techniques for remotely monitoring a system under simultaneous extremely high temperatures and pressures.

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2018-01-01

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

Vroom: designing an augmented environment for remote collaboration in digital cinema production

NASA Astrophysics Data System (ADS)

Margolis, Todd; Cornish, Tracy

2013-03-01

As media technologies become increasingly affordable, compact and inherently networked, new generations of telecollaborative platforms continue to arise which integrate these new affordances. Virtual reality has been primarily concerned with creating simulations of environments that can transport participants to real or imagined spaces that replace the "real world". Meanwhile Augmented Reality systems have evolved to interleave objects from Virtual Reality environments into the physical landscape. Perhaps now there is a new class of systems that reverse this precept to enhance dynamic media landscapes and immersive physical display environments to enable intuitive data exploration through collaboration. Vroom (Virtual Room) is a next-generation reconfigurable tiled display environment in development at the California Institute for Telecommunications and Information Technology (Calit2) at the University of California, San Diego. Vroom enables freely scalable digital collaboratories, connecting distributed, high-resolution visualization resources for collaborative work in the sciences, engineering and the arts. Vroom transforms a physical space into an immersive media environment with large format interactive display surfaces, video teleconferencing and spatialized audio built on a highspeed optical network backbone. Vroom enables group collaboration for local and remote participants to share knowledge and experiences. Possible applications include: remote learning, command and control, storyboarding, post-production editorial review, high resolution video playback, 3D visualization, screencasting and image, video and multimedia file sharing. To support these various scenarios, Vroom features support for multiple user interfaces (optical tracking, touch UI, gesture interface, etc.), support for directional and spatialized audio, giga-pixel image interactivity, 4K video streaming, 3D visualization and telematic production. This paper explains the design process that has been utilized to make Vroom an accessible and intuitive immersive environment for remote collaboration specifically for digital cinema production.

A random optimization approach for inherent optic properties of nearshore waters

NASA Astrophysics Data System (ADS)

Zhou, Aijun; Hao, Yongshuai; Xu, Kuo; Zhou, Heng

2016-10-01

Traditional method of water quality sampling is time-consuming and highly cost. It can not meet the needs of social development. Hyperspectral remote sensing technology has well time resolution, spatial coverage and more general segment information on spectrum. It has a good potential in water quality supervision. Via the method of semi-analytical, remote sensing information can be related with the water quality. The inherent optical properties are used to quantify the water quality, and an optical model inside the water is established to analysis the features of water. By stochastic optimization algorithm Threshold Acceptance, a global optimization of the unknown model parameters can be determined to obtain the distribution of chlorophyll, organic solution and suspended particles in water. Via the improvement of the optimization algorithm in the search step, the processing time will be obviously reduced, and it will create more opportunity for the increasing the number of parameter. For the innovation definition of the optimization steps and standard, the whole inversion process become more targeted, thus improving the accuracy of inversion. According to the application result for simulated data given by IOCCG and field date provided by NASA, the approach model get continuous improvement and enhancement. Finally, a low-cost, effective retrieval model of water quality from hyper-spectral remote sensing can be achieved.

Remote sensing estimation of terrestrially derived colored dissolved organic matterinput to the Arctic Ocean

NASA Astrophysics Data System (ADS)

Li, J.; Yu, Q.; Tian, Y. Q.

2017-12-01

The DOC flux from land to the Arctic Ocean has remarkable implication on the carbon cycle, biogeochemical & ecological processes in the Arctic. This lateral carbon flux is required to be monitored with high spatial & temporal resolution. However, the current studies in the Arctic regions were obstructed by the factors of the low spatial coverages. The remote sensing could provide an alternative bio-optical approach to field sampling for DOC dynamics monitoring through the observation of the colored dissolved organic matter (CDOM). The DOC and CDOM were found highly correlated based on the analysis of the field sampling data from the Arctic-GRO. These provide the solid foundation of the remote sensing observation. In this study, six major Arctic Rivers (Yukon, Kolyma, Lena, Mackenzie, Ob', Yenisey) were selected to derive the CDOM dynamics along four years. Our newly developed SBOP algorithm was applied to the large Landsat-8 OLI image data (nearly 100 images) for getting the high spatial resolution results. The SBOP algorithm is the first approach developing for the Shallow Water Bio-optical properties estimation. The CDOM absorption derived from the satellite images were verified with the field sampling results with high accuracy (R2 = 0.87). The distinct CDOM dynamics were found in different Rivers. The CDOM absorptions were found highly related to the hydrological activities and the terrestrially environmental dynamics. Our study helps to build the reliable system for studying the carbon cycle at Arctic regions.

MODIS Direct Broadcast and Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee

2004-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard both Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). Equipped with direct broadcast capability, the MODIS measurements can be received worldwide real time. There are 82 ingest sites (over 900 users, listed on the Direct Readout Portal) around the world for Terra/Aqua-MODIS Direct Broadcast DB) downlink. This represents 27 (6 from EOS science team members) science research organizations for DB land, ocean and atmospheric processing, and 53 companies that base their application algorithms and value added products on DB data. In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of aerosol/cloud optical properties, especially optical thickness and effective particle size. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Preliminary results will be presented and discussed their implications in regional-to-global climatic effects.

A High Resolution TDI CCD Camera forMicrosatellite (HRCM)

NASA Astrophysics Data System (ADS)

Hao, Yuncai; Zheng, You; Dong, Ying; Li, Tao; Yu, Shijie

In resent years it is a important development direction in the commercial remote sensing field to obtain (1-5)m high ground resolution from space using microsatellite. Thanks to progress of new technologies, new materials and new detectors it is possible to develop 1m ground resolution space imaging system with weight less than 20kg. Based on many years works on optical system design a project of very high resolution TDI CCD camera using in space was proposed by the authors of this paper. The performance parameters and optical lay-out of the HRCM was presented. A compact optical design and results analysis for the system was given in the paper also. and small fold mirror to take a line field of view usable for TDI CCD and short outer size. The length along the largest size direction is about 1/4 of the focal length. And two 4096X96(grades) line TDI CCD will be used as the focal plane detector. The special optical parts are fixed near before the final image for getting the ground pixel resolution higher than the Nyquist resolution of the detector using the sub-pixel technique which will be explained in the paper. In the system optical SiC will be used as the mirror material, the C-C composite material will be used as the material of the mechanical structure framework. The circle frame of the primary and secondary mirrors will use one time turning on a machine tool in order to assuring concentric request for alignment of the system. In general the HRCM have the performance parameters with 2.5m focal length, 20 FOV, 1/11relative aperture, (0.4-0.8) micrometer spectral range, 10 micron pixel size of TDI CCD, weight less than 20kg, 1m ground pixel resolution at flying orbit 500km high. Design and analysis of the HRCM put up in the paper indicate that HRCM have many advantages to use it in space. Keywords High resolution TDI CCD Sub-pixel imaging Light-weighted optical system SiC mirror

Improving Coastal Ocean Color Validation Capabilities through Application of Inherent Optical Properties (IOPs)

NASA Technical Reports Server (NTRS)

Mannino, Antonio

2008-01-01

Understanding how the different components of seawater alter the path of incident sunlight through scattering and absorption is essential to using remotely sensed ocean color observations effectively. This is particularly apropos in coastal waters where the different optically significant components (phytoplankton, detrital material, inorganic minerals, etc.) vary widely in concentration, often independently from one another. Inherent Optical Properties (IOPs) form the link between these biogeochemical constituents and the Apparent Optical Properties (AOPs). understanding this interrelationship is at the heart of successfully carrying out inversions of satellite-measured radiance to biogeochemical properties. While sufficient covariation of seawater constituents in case I waters typically allows empirical algorithms connecting AOPs and biogeochemical parameters to behave well, these empirical algorithms normally do not hold for case I1 regimes (Carder et al. 2003). Validation in the context of ocean color remote sensing refers to in-situ measurements used to verify or characterize algorithm products or any assumption used as input to an algorithm. In this project, validation capabilities are considered those measurement capabilities, techniques, methods, models, etc. that allow effective validation. Enhancing current validation capabilities by incorporating state-of-the-art IOP measurements and optical models is the purpose of this work. Involved in this pursuit is improving core IOP measurement capabilities (spectral, angular, spatio-temporal resolutions), improving our understanding of the behavior of analytical AOP-IOP approximations in complex coastal waters, and improving the spatial and temporal resolution of biogeochemical data for validation by applying biogeochemical-IOP inversion models so that these parameters can be computed from real-time IOP sensors with high sampling rates. Research cruises supported by this project provides for collection and processing of seawater samples for biogeochemical (pigments, DOC and POC) and optical (CDOM and POM absorption coefficients) analyses to enhance our understanding of the linkages between in-water optical measurements (IOPs and AOPs) and biogeochemical constituents and to provide a more comprehensive suite of validation products.

Optical telescope refocussing mechanism concept design on remote sensing satellite

NASA Astrophysics Data System (ADS)

Kuo, Jen-Chueh; Ling, Jer

2017-09-01

The optical telescope system in remote sensing satellite must be precisely aligned to obtain high quality images during its mission life. In practical, because the telescope mirrors could be misaligned due to launch loads, thermal distortion on supporting structures or hygroscopic distortion effect in some composite materials, the optical telescope system is often equipped with refocussing mechanism to re-align the optical elements while optical element positions are out of range during image acquisition. This paper is to introduce satellite Refocussing mechanism function model design development process and the engineering models. The design concept of the refocussing mechanism can be applied on either cassegrain type telescope or korsch type telescope, and the refocussing mechanism is located at the rear of the secondary mirror in this paper. The purpose to put the refocussing mechanism on the secondary mirror is due to its higher sensitivity on MTF degradation than other optical elements. There are two types of refocussing mechanism model to be introduced: linear type model and rotation type model. For the linear refocussing mechanism function model, the model is composed of ceramic piezoelectric linear step motor, optical rule as well as controller. The secondary mirror is designed to be precisely moved in telescope despace direction through refocussing mechanism. For the rotation refocussing mechanism function model, the model is assembled with two ceramic piezoelectric rotational motors around two orthogonal directions in order to adjust the secondary mirror attitude in tilt angle and yaw angle. From the validation test results, the linear type refocussing mechanism function model can be operated to adjust the secondary mirror position with minimum 500 nm resolution with close loop control. For the rotation type model, the attitude angle of the secondary mirror can be adjusted with the minimum 6 sec of arc resolution and 5°/sec of angle velocity.

Estimating Coastal Turbidity using MODIS 250 m Band Observations

NASA Technical Reports Server (NTRS)

Davies, James E.; Moeller, Christopher C.; Gunshor, Mathew M.; Menzel, W. Paul; Walker, Nan D.

2004-01-01

Terra MODIS 250 m observations are being applied to a Suspended Sediment Concentration (SSC) algorithm that is under development for coastal case 2 waters where reflectance is dominated by sediment entrained in major fluvial outflows. An atmospheric correction based on MODIS observations in the 500 m resolution 1.6 and 2.1 micron bands is used to isolate the remote sensing reflectance in the MODIS 25Om resolution 650 and 865 nanometer bands. SSC estimates from remote sensing reflectance are based on accepted inherent optical properties of sediment types known to be prevalent in the U.S. Gulf of Mexico coastal zone. We present our findings for the Atchafalaya Bay region of the Louisiana Coast, in the form of processed imagery over the annual cycle. We also apply our algorithm to selected sites worldwide with a goal of extending the utility of our approach to the global direct broadcast community.

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.

MODIS Cloud Products Derived from Terra and Aqua During CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, S.; Riedi, J. C.; Ackerman, S. A.; Menzel, W. P.

2003-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), developed as part of the Earth Observing System (EOS) and launched on Terra in December 1999 and Aqua in May 2002, is designed to meet the scientific needs for satellite remote sensing of clouds, aerosols, water vapor, and land and ocean surface properties. During the CRYSTAL-FACE experiment, numerous aircraft coordinated both in situ and remote sensing observations with the Terra and Aqua spacecraft. In this paper we will emphasize the optical, microphysical, and physical properties of both liquid water and ice clouds obtained from an analysis of the satellite observations over Florida and the Gulf of Mexico during July 2002. We will present the frequency distribution of liquid water and ice cloud microphysical properties throughout the region, separating the results over land and ocean. Probability distributions of effective radius and cloud optical thickness will also be shown.

Compact Hyperspectral Mapper for Environmental Remote Sensing Applications (CHyMERA) End-of-phase Data Review Package

NASA Technical Reports Server (NTRS)

Janz, Scott J.; Hilsenrath, Ernest; Mount, George; Heath, Donald

2000-01-01

CHYMERA is an Instrument Incubator concept to design, build, and test an instrument that will reduce size, mass, and cost and increase science potential and flexibility for future atmospheric remote sensing missions within the focus of NASA's Earth Science Enterprise (ESE). The primary effort of the development plan will be on high spatial resolution ozone, N02, S02, aerosol, and cloud measurements, but it is hoped that the techniques developed will prove useful for other measurements as well. The core design will involve a high performance, wide field-of-view (FOV) front end telescope which will illuminate a filter/focal plane array (FFPA) package. The use of a non-dispersive optical configuration will reduce size, mass and complexity. The wide FOV optics will permit short duration global coverage (1-2 days) without the need for a scanner.

Hybrid Microscopy: Enabling Inexpensive High-Performance Imaging through Combined Physical and Optical Magnifications

NASA Astrophysics Data System (ADS)

Zhang, Yu Shrike; Chang, Jae-Byum; Alvarez, Mario Moisés; Trujillo-de Santiago, Grissel; Aleman, Julio; Batzaya, Byambaa; Krishnadoss, Vaishali; Ramanujam, Aishwarya Aravamudhan; Kazemzadeh-Narbat, Mehdi; Chen, Fei; Tillberg, Paul W.; Dokmeci, Mehmet Remzi; Boyden, Edward S.; Khademhosseini, Ali

2016-03-01

To date, much effort has been expended on making high-performance microscopes through better instrumentation. Recently, it was discovered that physical magnification of specimens was possible, through a technique called expansion microscopy (ExM), raising the question of whether physical magnification, coupled to inexpensive optics, could together match the performance of high-end optical equipment, at a tiny fraction of the price. Here we show that such “hybrid microscopy” methods—combining physical and optical magnifications—can indeed achieve high performance at low cost. By physically magnifying objects, then imaging them on cheap miniature fluorescence microscopes (“mini-microscopes”), it is possible to image at a resolution comparable to that previously attainable only with benchtop microscopes that present costs orders of magnitude higher. We believe that this unprecedented hybrid technology that combines expansion microscopy, based on physical magnification, and mini-microscopy, relying on conventional optics—a process we refer to as Expansion Mini-Microscopy (ExMM)—is a highly promising alternative method for performing cost-effective, high-resolution imaging of biological samples. With further advancement of the technology, we believe that ExMM will find widespread applications for high-resolution imaging particularly in research and healthcare scenarios in undeveloped countries or remote places.

Fiber optic cable-based high-resolution, long-distance VGA extenders

NASA Astrophysics Data System (ADS)

Rhee, Jin-Geun; Lee, Iksoo; Kim, Heejoon; Kim, Sungjoon; Koh, Yeon-Wan; Kim, Hoik; Lim, Jiseok; Kim, Chur; Kim, Jungwon

2013-02-01

Remote transfer of high-resolution video information finds more applications in detached display applications for large facilities such as theaters, sports complex, airports, and security facilities. Active optical cables (AOCs) provide a promising approach for enhancing both the transmittable resolution and distance that standard copper-based cables cannot reach. In addition to the standard digital formats such as HDMI, the high-resolution, long-distance transfer of VGA format signals is important for applications where high-resolution analog video ports should be also supported, such as military/defense applications and high-resolution video camera links. In this presentation we present the development of a compressionless, high-resolution (up to WUXGA, 1920x1200), long-distance (up to 2 km) VGA extenders based on serialized technique. We employed asynchronous serial transmission and clock regeneration techniques, which enables lower cost implementation of VGA extenders by removing the necessity for clock transmission and large memory at the receiver. Two 3.125-Gbps transceivers are used in parallel to meet the required maximum video data rate of 6.25 Gbps. As the data are transmitted asynchronously, 24-bit pixel clock time stamp is employed to regenerate video pixel clock accurately at the receiver side. In parallel to the video information, stereo audio and RS-232 control signals are transmitted as well.

Polar research from satellites

NASA Technical Reports Server (NTRS)

Thomas, Robert H.

1991-01-01

In the polar regions and climate change section, the topics of ocean/atmosphere heat transfer, trace gases, surface albedo, and response to climate warming are discussed. The satellite instruments section is divided into three parts. Part one is about basic principles and covers, choice of frequencies, algorithms, orbits, and remote sensing techniques. Part two is about passive sensors and covers microwave radiometers, medium-resolution visible and infrared sensors, advanced very high resolution radiometers, optical line scanners, earth radiation budget experiment, coastal zone color scanner, high-resolution imagers, and atmospheric sounding. Part three is about active sensors and covers synthetic aperture radar, radar altimeters, scatterometers, and lidar. There is also a next decade section that is followed by a summary and recommendations section.

Controlling ionotropic and metabotropic glutamate receptors with light: principles and potential

PubMed Central

Reiner, Andreas; Levitz, Joshua; Isacoff, Ehud Y.

2014-01-01

Light offers unique advantages for studying and manipulating biomolecules and the cellular processes that they control. Optical control of ionotropic and metabotropic glutamate receptors has garnered significant interest, since these receptors are central to signaling at neuronal synapses and only optical approaches provide the spatial and temporal resolution required to directly probe receptor function in cells and tissue. Following the classical method of glutamate photo-uncaging, recently developed methods have added other forms of remote control, including those with high molecular specificity and genetic targeting. These tools open the door to the direct optical control of synaptic transmission and plasticity, as well as the probing of native receptor function in intact neural circuits. PMID:25573450

Remote sensing of plant trait responses to field-based plant-soil feedback using UAV-based optical sensors

NASA Astrophysics Data System (ADS)

van der Meij, Bob; Kooistra, Lammert; Suomalainen, Juha; Barel, Janna M.; De Deyn, Gerlinde B.

2017-02-01

Plant responses to biotic and abiotic legacies left in soil by preceding plants is known as plant-soil feedback (PSF). PSF is an important mechanism to explain plant community dynamics and plant performance in natural and agricultural systems. However, most PSF studies are short-term and small-scale due to practical constraints for field-scale quantification of PSF effects, yet field experiments are warranted to assess actual PSF effects under less controlled conditions. Here we used unmanned aerial vehicle (UAV)-based optical sensors to test whether PSF effects on plant traits can be quantified remotely. We established a randomized agro-ecological field experiment in which six different cover crop species and species combinations from three different plant families (Poaceae, Fabaceae, Brassicaceae) were grown. The feedback effects on plant traits were tested in oat (Avena sativa) by quantifying the cover crop legacy effects on key plant traits: height, fresh biomass, nitrogen content, and leaf chlorophyll content. Prior to destructive sampling, hyperspectral data were acquired and used for calibration and independent validation of regression models to retrieve plant traits from optical data. Subsequently, for each trait the model with highest precision and accuracy was selected. We used the hyperspectral analyses to predict the directly measured plant height (RMSE = 5.12 cm, R2 = 0.79), chlorophyll content (RMSE = 0.11 g m-2, R2 = 0.80), N-content (RMSE = 1.94 g m-2, R2 = 0.68), and fresh biomass (RMSE = 0.72 kg m-2, R2 = 0.56). Overall the PSF effects of the different cover crop treatments based on the remote sensing data matched the results based on in situ measurements. The average oat canopy was tallest and its leaf chlorophyll content highest in response to legacy of Vicia sativa monocultures (100 cm, 0.95 g m-2, respectively) and in mixture with Raphanus sativus (100 cm, 1.09 g m-2, respectively), while the lowest values (76 cm, 0.41 g m-2, respectively) were found in response to legacy of Lolium perenne monoculture, and intermediate responses to the legacy of the other treatments. We show that PSF effects in the field occur and alter several important plant traits that can be sensed remotely and quantified in a non-destructive way using UAV-based optical sensors; these can be repeated over the growing season to increase temporal resolution. Remote sensing thereby offers great potential for studying PSF effects at field scale and relevant spatial-temporal resolutions which will facilitate the elucidation of the underlying mechanisms.

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.

Selected configuration tradeoffs of contour optical instruments

NASA Astrophysics Data System (ADS)

Warren, J.; Strohbehn, K.; Murchie, S.; Fort, D.; Reynolds, E.; Heyler, G.; Peacock, K.; Boldt, J.; Darlington, E.; Hayes, J.; Henshaw, R.; Izenberg, N.; Kardian, C.; Lees, J.; Lohr, D.; Mehoke, D.; Schaefer, E.; Sholar, T.; Spisz, T.; Willey, C.; Veverka, J.; Bell, J.; Cochran, A.

2003-01-01

The Comet Nucleus Tour (CONTOUR) is a low-cost NASA Discovery mission designed to conduct three close flybys of comet nuclei. Selected configuration tradeoffs conducted to balance science requirements with low mission cost are reviewed. The tradeoffs discussed focus on the optical instruments and related spacecraft considerations. Two instruments are under development. The CONTOUR Forward Imager (CFI) is designed to perform optical navigation, moderate resolution nucleus/jet imaging, and imaging of faint molecular emission bands in the coma. The CONTOUR Remote Imager and Spectrometer (CRISP) is designed to obtain high-resolution multispectral images of the nucleus, conduct spectral mapping of the nucleus surface, and provide a backup optical navigation capability. Tradeoffs discussed are: (1) the impact on the optical instruments of not using reaction wheels on the spacecraft, (2) the improved performance and simplification gained by implementing a dedicated star tracker instead of including this function in CFI, (3) the improved flexibility and robustness of switching to a low frame rate tracker for CRISP, (4) the improved performance and simplification of replacing a visible imaging spectrometer by enhanced multispectral imaging in CRISP, and (5) the impact on spacecraft resources of these and other tradeoffs.

Nanoimprinting on optical fiber end faces for chemical sensing

NASA Astrophysics Data System (ADS)

Kostovski, G.; White, D. J.; Mitchell, A.; Austin, M. W.; Stoddart, P. R.

2008-04-01

Optical fiber surface-enhanced Raman scattering (SERS) sensors offer a potential solution to monitoring low chemical concentrations in-situ or in remote sensing scenarios. We demonstrate the use of nanoimprint lithography to fabricate SERS-compatible nanoarrays on the end faces of standard silica optical fibers. The antireflective nanostructure found on cicada wings was used as a convenient template for the nanoarray, as high sensitivity SERS substrates have previously been demonstrated on these surfaces. Coating the high fidelity replicas with silver creates a dense array of regular nanoscale plasmonic resonators. A monolayer of thiophenol was used as a low concentration analyte, from which strong Raman spectra were collected using both direct endface illumination and through-fiber interrogation. This unique combination of nanoscale replication with optical fibers demonstrates a high-resolution, low-cost approach to fabricating high-performance optical fiber chemical sensors.

Fiber Optic Communication System For Medical Images

NASA Astrophysics Data System (ADS)

Arenson, Ronald L.; Morton, Dan E.; London, Jack W.

1982-01-01

This paper discusses a fiber optic communication system linking ultrasound devices, Computerized tomography scanners, Nuclear Medicine computer system, and a digital fluoro-graphic system to a central radiology research computer. These centrally archived images are available for near instantaneous recall at various display consoles. When a suitable laser optical disk is available for mass storage, more extensive image archiving will be added to the network including digitized images of standard radiographs for comparison purposes and for remote display in such areas as the intensive care units, the operating room, and selected outpatient departments. This fiber optic system allows for a transfer of high resolution images in less than a second over distances exceeding 2,000 feet. The advantages of using fiber optic cables instead of typical parallel or serial communication techniques will be described. The switching methodology and communication protocols will also be discussed.

Disaggregation Of Passive Microwave Soil Moisture For Use In Watershed Hydrology Applications

NASA Astrophysics Data System (ADS)

Fang, Bin

In recent years the passive microwave remote sensing has been providing soil moisture products using instruments on board satellite/airborne platforms. Spatial resolution has been restricted by the diameter of antenna which is inversely proportional to resolution. As a result, typical products have a spatial resolution of tens of kilometers, which is not compatible for some hydrological research applications. For this reason, the dissertation explores three disaggregation algorithms that estimate L-band passive microwave soil moisture at the subpixel level by using high spatial resolution remote sensing products from other optical and radar instruments were proposed and implemented in this investigation. The first technique utilized a thermal inertia theory to establish a relationship between daily temperature change and average soil moisture modulated by the vegetation condition was developed by using NLDAS, AVHRR, SPOT and MODIS data were applied to disaggregate the 25 km AMSR-E soil moisture to 1 km in Oklahoma. The second algorithm was built on semi empirical physical models (NP89 and LP92) derived from numerical experiments between soil evaporation efficiency and soil moisture over the surface skin sensing depth (a few millimeters) by using simulated soil temperature derived from MODIS and NLDAS as well as AMSR-E soil moisture at 25 km to disaggregate the coarse resolution soil moisture to 1 km in Oklahoma. The third algorithm modeled the relationship between the change in co-polarized radar backscatter and the remotely sensed microwave change in soil moisture retrievals and assumed that change in soil moisture was a function of only the canopy opacity. The change detection algorithm was implemented using aircraft based the remote sensing data from PALS and UAVSAR that were collected in SMPAVEX12 in southern Manitoba, Canada. The PALS L-band h-polarization radiometer soil moisture retrievals were disaggregated by combining them with the PALS and UAVSAR L-band hh-polarization radar spatial resolutions of 1500 m and 5 m/800 m, respectively. All three algorithms were validated using ground measurements from network in situ stations or handheld hydra probes. The validation results demonstrate the practicability on coarse resolution passive microwave soil moisture products.

Optical and morphological properties of Cirrus clouds determined by the high spectral resolution lidar during FIRE

NASA Technical Reports Server (NTRS)

Grund, Christian John; Eloranta, Edwin W.

1990-01-01

Cirrus clouds reflect incoming solar radiation and trap outgoing terrestrial radiation; therefore, accurate estimation of the global energy balance depends upon knowledge of the optical and physical properties of these clouds. Scattering and absorption by cirrus clouds affect measurements made by many satellite-borne and ground based remote sensors. Scattering of ambient light by the cloud, and thermal emissions from the cloud can increase measurement background noise. Multiple scattering processes can adversely affect the divergence of optical beams propagating through these clouds. Determination of the optical thickness and the vertical and horizontal extent of cirrus clouds is necessary to the evaluation of all of these effects. Lidar can be an effective tool for investigating these properties. During the FIRE cirrus IFO in Oct. to Nov. 1986, the High Spectral Resolution Lidar (HSRL) was operated from a rooftop site on the campus of the University of Wisconsin at Madison, Wisconsin. Approximately 124 hours of fall season data were acquired under a variety of cloud optical thickness conditions. Since the IFO, the HSRL data set was expanded by more than 63.5 hours of additional data acquired during all seasons. Measurements are presented for the range in optical thickness and backscattering phase function of the cirrus clouds, as well as contour maps of extinction corrected backscatter cross sections indicating cloud morphology. Color enhanced images of range-time indicator (RTI) displays a variety of cirrus clouds with approximately 30 sec time resolution are presented. The importance of extinction correction on the interpretation of cloud height and structure from lidar observations of optically thick cirrus are demonstrated.

Fiber optic sensors IV; Proceedings of the Third European Congress on Optics, The Hague, Netherlands, Mar. 13, 14, 1990

NASA Technical Reports Server (NTRS)

Kersten, Ralf T. (Editor)

1990-01-01

Recent advances in fiber-optic sensor (FOS) technology are examined in reviews and reports. Sections are devoted to components for FOSs, special fibers for FOSs, interferometry, FOS applications, and sensing principles and influence. Particular attention is given to solder glass sealing technology for FOS packaging, the design of optical-fiber current sensors, pressure and temperature effects on beat length in highly birefringent optical fibers, a pressure FOS based on vibrating-quartz-crystal technology, remote sensing of flammable gases using a fluoride-fiber evanescent probe, a displacement sensor with electronically scanned white-light interferometer, the use of multimode laser diodes in low-coherence coupled-cavity interferometry, electronic speckle interferometry compensated for environmentally induced phase noise, a dual-resolution noncontact vibration and displacement sensor based on a two-wavelength source, and fiber optics in composite materials.

Modeling and Simulation of High Resolution Optical Remote Sensing Satellite Geometric Chain

NASA Astrophysics Data System (ADS)

Xia, Z.; Cheng, S.; Huang, Q.; Tian, G.

2018-04-01

The high resolution satellite with the longer focal length and the larger aperture has been widely used in georeferencing of the observed scene in recent years. The consistent end to end model of high resolution remote sensing satellite geometric chain is presented, which consists of the scene, the three line array camera, the platform including attitude and position information, the time system and the processing algorithm. The integrated design of the camera and the star tracker is considered and the simulation method of the geolocation accuracy is put forward by introduce the new index of the angle between the camera and the star tracker. The model is validated by the geolocation accuracy simulation according to the test method of the ZY-3 satellite imagery rigorously. The simulation results show that the geolocation accuracy is within 25m, which is highly consistent with the test results. The geolocation accuracy can be improved about 7 m by the integrated design. The model combined with the simulation method is applicable to the geolocation accuracy estimate before the satellite launching.

Aerosol optical properties over the Svalbard region of Arctic: ground-based measurements and satellite remote sensing

NASA Astrophysics Data System (ADS)

Gogoi, Mukunda M.; Babu, S. Suresh

2016-05-01

In view of the increasing anthropogenic presence and influence of aerosols in the northern polar regions, long-term continuous measurements of aerosol optical parameters have been investigated over the Svalbard region of Norwegian Arctic (Ny-Ålesund, 79°N, 12°E, 8 m ASL). This study has shown a consistent enhancement in the aerosol scattering and absorption coefficients during spring. The relative dominance of absorbing aerosols is more near the surface (lower single scattering albedo), compared to that at the higher altitude. This is indicative of the presence of local anthropogenic activities. In addition, long-range transported biomass burning aerosols (inferred from the spectral variation of absorption coefficient) also contribute significantly to the higher aerosol absorption in the Arctic spring. Aerosol optical depth (AOD) estimates from ground based Microtop sun-photometer measurements reveals that the columnar abundance of aerosols reaches the peak during spring season. Comparison of AODs between ground based and satellite remote sensing indicates that deep blue algorithm of Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals over Arctic snow surfaces overestimate the columnar AOD.

The visible absorption spectrum of NO3 measured by high-resolution Fourier transform spectroscopy

NASA Astrophysics Data System (ADS)

Orphal, J.; Fellows, C. E.; Flaud, P.-M.

2003-02-01

The visible absorption spectrum of the nitrate radical NO3 has been measured using high-resolution Fourier transform spectroscopy. The spectrum was recorded at 294 K using a resolution of 0.6 cm-1 (corresponding to 0.026 nm at 662 nm) and covers the 12600-21500 cm-1 region (465-794 nm). Compared to absorption spectra of NO3 recorded previously, the new data show improvements concerning absolute wavelength calibration (uncertainty 0.02 cm-1), and spectral resolution. A new interpretation and model of the temperature dependence of the strong (0-0) band around 662 nm are proposed. The results are important for long-path tropospheric absorption measurements of NO3 and optical remote sensing of the Earth's atmosphere from space.

Image Mosaicking Approach for a Double-Camera System in the GaoFen2 Optical Remote Sensing Satellite Based on the Big Virtual Camera.

PubMed

Cheng, Yufeng; Jin, Shuying; Wang, Mi; Zhu, Ying; Dong, Zhipeng

2017-06-20

The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy image mosaicking is the key factor of the geometrical quality of complete stitched satellite imagery. This paper proposes a high accuracy image mosaicking approach based on the big virtual camera (BVC) in the double-camera system on the GaoFen2 optical remote sensing satellite (GF2). A big virtual camera can be built according to the rigorous imaging model of a single camera; then, each single image strip obtained by each TDI-CCD detector can be re-projected to the virtual detector of the big virtual camera coordinate system using forward-projection and backward-projection to obtain the corresponding single virtual image. After an on-orbit calibration and relative orientation, the complete final virtual image can be obtained by stitching the single virtual images together based on their coordinate information on the big virtual detector image plane. The paper subtly uses the concept of the big virtual camera to obtain a stitched image and the corresponding high accuracy rational function model (RFM) for concurrent post processing. Experiments verified that the proposed method can achieve seamless mosaicking while maintaining the geometric accuracy.

Image quality enhancement method for on-orbit remote sensing cameras using invariable modulation transfer function.

PubMed

Li, Jin; Liu, Zilong

2017-07-24

Remote sensing cameras in the visible/near infrared range are essential tools in Earth-observation, deep-space exploration, and celestial navigation. Their imaging performance, i.e. image quality here, directly determines the target-observation performance of a spacecraft, and even the successful completion of a space mission. Unfortunately, the camera itself, such as a optical system, a image sensor, and a electronic system, limits the on-orbit imaging performance. Here, we demonstrate an on-orbit high-resolution imaging method based on the invariable modulation transfer function (IMTF) of cameras. The IMTF, which is stable and invariable to the changing of ground targets, atmosphere, and environment on orbit or on the ground, depending on the camera itself, is extracted using a pixel optical focal-plane (PFP). The PFP produces multiple spatial frequency targets, which are used to calculate the IMTF at different frequencies. The resulting IMTF in combination with a constrained least-squares filter compensates for the IMTF, which represents the removal of the imaging effects limited by the camera itself. This method is experimentally confirmed. Experiments on an on-orbit panchromatic camera indicate that the proposed method increases 6.5 times of the average gradient, 3.3 times of the edge intensity, and 1.56 times of the MTF value compared to the case when IMTF is not used. This opens a door to push the limitation of a camera itself, enabling high-resolution on-orbit optical imaging.

Remote Sensing of Cloud, Aerosol, and Land Properties from MODIS: Applications to the East Asia Region

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Moody, Eric G.

2002-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999 and the Aqua satellite in May 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper we will describe the various methods being used for the remote sensing of cloud, aerosol, and surface properties using MODIS data, focusing primarily on (i) the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, (ii) cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals, (iii) aerosol optical thickness and size characteristics both over land and ocean, and (iv) ecosystem classification and surface spectral reflectance. The physical principles behind the determination of each of these products will be described, together with an example of their application using MODIS observations to the east Asian region. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 min (Level-3 products).

Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors

PubMed Central

Zheng, Guang; Moskal, L. Monika

2009-01-01

The ability to accurately and rapidly acquire leaf area index (LAI) is an indispensable component of process-based ecological research facilitating the understanding of gas-vegetation exchange phenomenon at an array of spatial scales from the leaf to the landscape. However, LAI is difficult to directly acquire for large spatial extents due to its time consuming and work intensive nature. Such efforts have been significantly improved by the emergence of optical and active remote sensing techniques. This paper reviews the definitions and theories of LAI measurement with respect to direct and indirect methods. Then, the methodologies for LAI retrieval with regard to the characteristics of a range of remotely sensed datasets are discussed. Remote sensing indirect methods are subdivided into two categories of passive and active remote sensing, which are further categorized as terrestrial, aerial and satellite-born platforms. Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling issue of LAI is discussed and special consideration is given to extrapolation of measurement to landscape and regional levels. PMID:22574042

Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors.

PubMed

Zheng, Guang; Moskal, L Monika

2009-01-01

The ability to accurately and rapidly acquire leaf area index (LAI) is an indispensable component of process-based ecological research facilitating the understanding of gas-vegetation exchange phenomenon at an array of spatial scales from the leaf to the landscape. However, LAI is difficult to directly acquire for large spatial extents due to its time consuming and work intensive nature. Such efforts have been significantly improved by the emergence of optical and active remote sensing techniques. This paper reviews the definitions and theories of LAI measurement with respect to direct and indirect methods. Then, the methodologies for LAI retrieval with regard to the characteristics of a range of remotely sensed datasets are discussed. Remote sensing indirect methods are subdivided into two categories of passive and active remote sensing, which are further categorized as terrestrial, aerial and satellite-born platforms. Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling issue of LAI is discussed and special consideration is given to extrapolation of measurement to landscape and regional levels.

Optical Fiber Networks for Remote Fiber Optic Sensors

PubMed Central

Fernandez-Vallejo, Montserrat; Lopez-Amo, Manuel

2012-01-01

This paper presents an overview of optical fiber sensor networks for remote sensing. Firstly, the state of the art of remote fiber sensor systems has been considered. We have summarized the great evolution of these systems in recent years; this progress confirms that fiber-optic remote sensing is a promising technology with a wide field of practical applications. Afterwards, the most representative remote fiber-optic sensor systems are briefly explained, discussing their schemes, challenges, pros and cons. Finally, a synopsis of the main factors to take into consideration in the design of a remote sensor system is gathered. PMID:22666011

Estimation de la superficie du couvert nival a partir d'une combinaison des donnees de teledetection MODIS et AMSR-E dans un contexte de prevision des crues printanieres au Quebec

NASA Astrophysics Data System (ADS)

Bergeron, Jean

Snow cover estimation is a principal source of error for spring streamflow simulations in Québec, Canada. Optical and near infrared remote sensing can improve snow cover area (SCA) estimation due to high spatial resolution but is limited by cloud cover and incoming solar radiation. Passive microwave remote sensing is complementary by its near-transparence to cloud cover and independence to incoming solar radiation, but is limited by its coarse spatial resolution. The study aims to create an improved SCA product from blended passive microwave (AMSR-E daily L3 Brightness Temperature) and optical (MODIS Terra and Aqua daily snow cover L3) remote sensing data in order to improve estimation of river streamflow caused by snowmelt with Québec's operational MOHYSE hydrological model through direct-insertion of the blended SCA product in a coupled snowmelt module (SPH-AV). SCA estimated from AMSR-E data is first compared with SCA estimated with MODIS, as well as with in situ snow depth measurements. Results show good agreement (+95%) between AMSR-E-derived and MODIS-derived SCA products in spring but comparisons with Environment Canada ground stations and SCA derived from Advanced Very High Resolution Radiometer (AVHRR) data show lesser agreements (83 % and 74% respectively). Results also show that AMSR-E generally underestimates SCA. Assimilating the blended snow product in SPH-AV coupled with MOHYSE yields significant improvement of simulated streamflow for the aux Écorces et au Saumon rivers overall when compared with simulations with no update during thaw events, These improvements are similar to results driven by biweekly ground data. Assimilation of remotely-sensed passive microwave data was also found to have little positive impact on springflood forecast due to the difficulty in differentiating melting snow from snow-free surfaces. Considering the direct-insertion and Newtonian nudging assimilation methods, the study also shows the latter method to be superior to the former, notably when assimilating noisy data. Keywords: Snow cover, spring streamflow, MODIS, AMSR-E, hydrological model.

Optical and Microphysical Retrievals of Marine Stratocumulus Clouds off the Coast of Namibia from Satellite and Aircraft

NASA Technical Reports Server (NTRS)

Platnick, Steven E.

2010-01-01

Though the emphasis of the Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign was largely on emission sources and transport, the assemblage of aircraft (including the high altitude NASA ER-2 remote sensing platform and the University of Washington CV-580, UK MRF C-130, and South African Weather Bureau JRA in situ aircrafts) provided a unique opportunity for cloud studies. Therefore, as part of the SAFARI initiative, investigations were undertaken to assess regional aerosol-cloud interactions and cloud remote sensing algorithms. In particular, the latter part of the experiment concentrated on marine boundary layer stratocumulus clouds off the southwest coast of Africa. Associated with cold water upwelling along the Benguela current, the Namibian stratocumulus regime has received limited attention but appears to be unique for several reasons. During the dry season, outflow of continental fires and industrial pollution over this area can be extreme. From below, upwelling provides a rich nutrient source for phytoplankton (a source of atmospheric sulfur through DMS production as well as from decay processes). The impact of these natural and anthropogenic sources on the microphysical and optical properties of the stratocumulus is unknown. Continental and Indian Ocean cloud systems of opportunity were also studied during the campaign. SAFARI 2000 aircraft flights off the coast of Namibia were coordinated with NASA Terra Satellite overpasses for synergy with the Moderate Resolution Imaging Spectroradiometer (MODIS) and other Terra instruments. MODIS was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 (and Aqua spacecraft on May 4, 2002). Among the remote sensing algorithms developed and applied to this sensor are cloud optical and microphysical properties that include cloud thermodynamic phase, optical thickness, and effective particle radius of both liquid water and ice clouds. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, and fundamental atmospheric research. The archived MODIS Collection 5 cloud products processing stream will be used to analyze low water cloud scenes off the Namibian and Angolan coasts during SAFARI 2000 time period, as well as other years. Pixel-level Terra and Aqua MODIS retrievals (l. km spatial resolution at nadir) and gridded (1' uniform grid) statistics of cloud optical thickness and effective particle radius will be presented, including joint probability distributions between the two quantities. In addition, perspectives from the MODIS Airborne Simulator, which flew on the ER-2 during SAFARI 2000 providing high spatial resolution retrievals (50 m at nadir), will be presented as appropriate. The H-SAF Program requires an experimental operational European-centric Satellite Precipitation Algorithm System (E-SPAS) that produces medium spatial resolution and high temporal resolution surface rainfall and snowfall estimates over the Greater European Region including the Greater Mediterranean Basin. Currently, there are various types of experimental operational algorithm methods of differing spatiotemporal resolutions that generate global precipitation estimates. This address will first assess the current status of these methods and then recommend a methodology for the H-SAF Program that deviates somewhat from the current approach under development but one that takes advantage of existing techniques and existing software developed for the TRMM Project and available through the public domain.

Multi-sensor data processing method for improved satellite retrievals

NASA Astrophysics Data System (ADS)

Fan, Xingwang

2017-04-01

Satellite remote sensing has provided massive data that improve the overall accuracy and extend the time series of environmental studies. In reflective solar bands, satellite data are related to land surface properties via radiative transfer (RT) equations. These equations generally include sensor-related (calibration coefficients), atmosphere-related (aerosol optical thickness) and surface-related (surface reflectance) parameters. It is an ill-posed problem to solve three parameters with only one RT equation. Even if there are two RT equations (dual-sensor data), the problem is still unsolvable. However, a robust solution can be obtained when any two parameters are known. If surface and atmosphere are known, sensor intercalibration can be performed. For example, the Advanced Very High Resolution Radiometer (AVHRR) was calibrated to the MODerate-resolution Imaging Spectroradiometer (MODIS) in Fan and Liu (2014) [Fan, X., and Liu, Y. (2014). Quantifying the relationship between intersensor images in solar reflective bands: Implications for intercalibration. IEEE Transactions on Geoscience and Remote Sensing, 52(12), 7727-7737.]. If sensor and surface are known, atmospheric data can be retrieved. For example, aerosol data were retrieved using tandem TERRA and AQUA MODIS images in Fan and Liu (2016a) [Fan, X., and Liu, Y. (2016a). Exploiting TERRA-AQUA MODIS relationship in the reflective solar bands for aerosol retrieval. Remote Sensing, 8(12), 996.]. If sensor and atmosphere are known, data consistency can be obtained. For example, Normalized Difference Vegetation Index (NDVI) data were intercalibrated among coarse-resolution sensors in Fan and Liu (2016b) [Fan, X., and Liu, Y. (2016b). A global study of NDVI difference among moderate-resolution satellite sensors. ISPRS Journal of Photogrammetry and Remote Sensing, 121, 177-191.], and among fine-resolution sensors in Fan and Liu (2017) [Fan, X., and Liu, Y. (2017). A generalized model for intersensor NDVI calibration and its comparison with regression approaches. IEEE Transactions on Geoscience and Remote Sensing, 55(3), doi: 10.1109/TGRS.2016.2635802.]. These studies demonstrate the success of multi-sensor data and novel methods in the research domain of geoscience. These data will benefit remote sensing of terrestrial parameters in decadal timescales, such as soil salinity content in Fan et al. (2016) [Fan, X., Weng, Y., and Tao, J. (2016). Towards decadal soil salinity mapping using Landsat time series data. International Journal of Applied Earth Observation and Geoinformation, 52, 32-41.].

Formation Flying: The Future of Remote Sensing from Space

NASA Technical Reports Server (NTRS)

Leitner, Jesse

2004-01-01

Over the next two decades a revolution is likely to occur in how remote sensing of Earth, other planets or bodies, and a range of phenomena in the universe is performed from space. In particular, current launch vehicle fairing volume and mass constraints will continue to restrict the size of monolithic telescope apertures which can be launched to accommodate only slightly more performance capability than is achievable today, such as by the Hubble Space Telescope. Systems under formulation today, such as the James Webb Space Telescope will be able to increase aperture size and, hence, imaging resolution, by deploying segmented optics. However, this approach is limited as well, by ow ability to control such segments to optical tolerances over long distances with highly uncertain structural dynamics connecting them. Consequently, for orders of magnitude improved resolution as required for imaging black holes, imaging planets, or performing asteroseismology, the only viable approach will be to fly a collection of spacecraft in formation to synthesize a virtual segmented telescope or interferometer with very large baselines. This presentation describes some of the strategic science missions planned in the National Aeronautics and Space Administration, and identifies some of the critical technologies needed to enable some of the most challenging space missions ever conceived which have realistic hopes of flying.

Monolithic liquid crystal waveguide Fourier transform spectrometer for gas species sensing

NASA Astrophysics Data System (ADS)

Chao, Tien-Hsin; Lu, Thomas T.; Davis, Scott R.; Rommel, Scott D.; Farca, George; Luey, Ben; Martin, Alan; Anderson, Michael H.

2011-04-01

Jet Propulsion Lab and Vescent Photonics Inc. and are jointly developing an innovative ultracompact (volume < 10 cm3), ultra-low power (<10-3 Watt-hours per measurement and zero power consumption when not measuring), completely non-mechanical Liquid Crystal Waveguide Fourier Transform Spectrometer (LCWFTS) that will be suitable for a variety of remote-platform, in-situ measurements. These devices are made possible by novel electro-evanescent waveguide architecture, enabling "monolithic chip-scale" Electro Optic-FTS (EO-FTS) sensors. The potential performance of these EO-FTS sensors include: i) a spectral range throughout 0.4-5 μm (25000 - 2000 cm-1), ii) high-resolution (Δλ <= 0.1 nm), iii) high-speed (< 1 ms) measurements, and iv) rugged integrated optical construction. This performance potential enables the detection and quantification of a large number of different atmospheric gases simultaneously in the same air mass and the rugged construction will enable deployment on previously inaccessible platforms. The sensor construction is also amenable for analyzing aqueous samples on remote floating or submerged platforms. We will report a proof-of-principle prototype LCWFTS sensor that has been demonstrated in the near-IR (range of 1450-1700 nm) with a 5 nm resolution. This performance is in good agreement with theoretical models, which are being used to design and build the next generation LCWFTS devices.

Fast and accurate denoising method applied to very high resolution optical remote sensing images

NASA Astrophysics Data System (ADS)

Masse, Antoine; Lefèvre, Sébastien; Binet, Renaud; Artigues, Stéphanie; Lassalle, Pierre; Blanchet, Gwendoline; Baillarin, Simon

2017-10-01

Restoration of Very High Resolution (VHR) optical Remote Sensing Image (RSI) is critical and leads to the problem of removing instrumental noise while keeping integrity of relevant information. Improving denoising in an image processing chain implies increasing image quality and improving performance of all following tasks operated by experts (photo-interpretation, cartography, etc.) or by algorithms (land cover mapping, change detection, 3D reconstruction, etc.). In a context of large industrial VHR image production, the selected denoising method should optimized accuracy and robustness with relevant information and saliency conservation, and rapidity due to the huge amount of data acquired and/or archived. Very recent research in image processing leads to a fast and accurate algorithm called Non Local Bayes (NLB) that we propose to adapt and optimize for VHR RSIs. This method is well suited for mass production thanks to its best trade-off between accuracy and computational complexity compared to other state-of-the-art methods. NLB is based on a simple principle: similar structures in an image have similar noise distribution and thus can be denoised with the same noise estimation. In this paper, we describe in details algorithm operations and performances, and analyze parameter sensibilities on various typical real areas observed in VHR RSIs.

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. T.; King, Michael D. (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper I will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of cloud drops and ice crystals. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

Multispectral Cloud Retrievals from MODIS on Terra and Aqua

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.

2002-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and the Aqua spacecraft on April 26, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from each polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. Thomas

2001-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun- synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at 100 m Resolution.

PubMed

Gao, Qi; Zribi, Mehrez; Escorihuela, Maria Jose; Baghdadi, Nicolas

2017-08-26

The recent deployment of ESA's Sentinel operational satellites has established a new paradigm for remote sensing applications. In this context, Sentinel-1 radar images have made it possible to retrieve surface soil moisture with a high spatial and temporal resolution. This paper presents two methodologies for the retrieval of soil moisture from remotely-sensed SAR images, with a spatial resolution of 100 m. These algorithms are based on the interpretation of Sentinel-1 data recorded in the VV polarization, which is combined with Sentinel-2 optical data for the analysis of vegetation effects over a site in Urgell (Catalunya, Spain). The first algorithm has already been applied to observations in West Africa by Zribi et al., 2008, using low spatial resolution ERS scatterometer data, and is based on change detection approach. In the present study, this approach is applied to Sentinel-1 data and optimizes the inversion process by taking advantage of the high repeat frequency of the Sentinel observations. The second algorithm relies on a new method, based on the difference between backscattered Sentinel-1 radar signals observed on two consecutive days, expressed as a function of NDVI optical index. Both methods are applied to almost 1.5 years of satellite data (July 2015-November 2016), and are validated using field data acquired at a study site. This leads to an RMS error in volumetric moisture of approximately 0.087 m³/m³ and 0.059 m³/m³ for the first and second methods, respectively. No site calibrations are needed with these techniques, and they can be applied to any vegetation-covered area for which time series of SAR data have been recorded.

Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at 100 m Resolution

PubMed Central

Gao, Qi; Zribi, Mehrez

2017-01-01

The recent deployment of ESA’s Sentinel operational satellites has established a new paradigm for remote sensing applications. In this context, Sentinel-1 radar images have made it possible to retrieve surface soil moisture with a high spatial and temporal resolution. This paper presents two methodologies for the retrieval of soil moisture from remotely-sensed SAR images, with a spatial resolution of 100 m. These algorithms are based on the interpretation of Sentinel-1 data recorded in the VV polarization, which is combined with Sentinel-2 optical data for the analysis of vegetation effects over a site in Urgell (Catalunya, Spain). The first algorithm has already been applied to observations in West Africa by Zribi et al., 2008, using low spatial resolution ERS scatterometer data, and is based on change detection approach. In the present study, this approach is applied to Sentinel-1 data and optimizes the inversion process by taking advantage of the high repeat frequency of the Sentinel observations. The second algorithm relies on a new method, based on the difference between backscattered Sentinel-1 radar signals observed on two consecutive days, expressed as a function of NDVI optical index. Both methods are applied to almost 1.5 years of satellite data (July 2015–November 2016), and are validated using field data acquired at a study site. This leads to an RMS error in volumetric moisture of approximately 0.087 m3/m3 and 0.059 m3/m3 for the first and second methods, respectively. No site calibrations are needed with these techniques, and they can be applied to any vegetation-covered area for which time series of SAR data have been recorded. PMID:28846601

Remote fluorescence imaging of dynamic concentration profiles with micrometer resolution using a coherent optical fiber bundle.

PubMed

Amatore, Christian; Chovin, Arnaud; Garrigue, Patrick; Servant, Laurent; Sojic, Neso; Szunerits, Sabine; Thouin, Laurent

2004-12-15

Dynamic concentration profiles within the diffusion layer of an electrode were imaged in situ using fluorescence detection through a multichannel imaging fiber. In this work, a coherent optical fiber bundle is positioned orthogonal to the surface of an electrode and is used to report spatial and temporal micrometric changes in the fluorescence intensity of an initial fluorescent species. The fluorescence signal is directly related to the local concentration of a redox fluorescent reagent, which is electrochemically modulated by the electrode. Fluorescence images are collected through the optical fiber bundle during the oxidation of tris(2,2'-bipyridine)ruthenium(II) to ruthenium(III) at a diffusion-limited rate and allow the concentration profiles of Ru(II) reagent to be monitored in situ as a function of time. Tris(2,2'-bipyridine)ruthenium(II) is excited at 485 nm and emits fluorescence at 605 nm, whereas the Ru(III) oxidation state is not fluorescent. Our experiments emphasize the influence of two parameters on the micrometer spatial resolution: the numerical aperture of optical fibers within the bundle and the Ru(II) bulk concentration. The extent of the volume probed by each individual fiber of the bundle is discussed qualitatively in terms of a primary inner-filter effect and refractive index gradient. Experimentally measured fluorescence intensity profiles were found to be in very good agreement with concentration profiles predicted upon considering planar diffusion and thus validate the concept of this new application of imaging fibers. The originality of this remote approach is to provide a global view of the entire diffusion layer at a given time through one single image and to allow the time expansion of the diffusion layer to be followed quantitatively in real time.

Validation of Cloud Optical Parameters from Passive Remote Sensing in the Arctic by using the Aircraft Measurements

NASA Astrophysics Data System (ADS)

Chen, H.; Schmidt, S.; Coddington, O.; Wind, G.; Bucholtz, A.; Segal-Rosenhaimer, M.; LeBlanc, S. E.

2017-12-01

Cloud Optical Parameters (COPs: e.g., cloud optical thickness and cloud effective radius) and surface albedo are the most important inputs for determining the Cloud Radiative Effect (CRE) at the surface. In the Arctic, the COPs derived from passive remote sensing such as from the Moderate Resolution Imaging Spectroradiometer (MODIS) are difficult to obtain with adequate accuracy owing mainly to insufficient knowledge about the snow/ice surface, but also because of the low solar zenith angle. This study aims to validate COPs derived from passive remote sensing in the Arctic by using aircraft measurements collected during two field campaigns based in Fairbanks, Alaska. During both experiments, ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) and ARISE (Arctic Radiation-IceBridge Sea and Ice Experiment), the Solar Spectral Flux Radiometer (SSFR) measured upwelling and downwelling shortwave spectral irradiances, which can be used to derive surface and cloud albedo, as well as the irradiance transmitted by clouds. We assess the variability of the Arctic sea ice/snow surfaces albedo through these aircraft measurements and incorporate this variability into cloud retrievals for SSFR. We then compare COPs as derived from SSFR and MODIS for all suitable aircraft underpasses of the satellites. Finally, the sensitivities of the COPs to surface albedo and solar zenith angle are investigated.

NASA Fluid Lensing & MiDAR: Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2018-01-01

We present two recent instrument technology developments at NASA, Fluid Lensing and MiDAR, and their application to remote sensing of Earth's aquatic systems. Fluid Lensing is the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions. MiDAR is a next-generation active hyperspectral remote sensing and optical communications instrument capable of active fluid lensing. Fluid Lensing has been used to provide 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) to enable a new method for remote sensing of living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an objectâ€"TM"s non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Previously, MiDAR was developed into a TRL 2 laboratory instrument capable of imaging in thirty-two narrowband channels across the VNIR spectrum (400-950nm). Recently, MiDAR UV was raised to TRL4 and expanded to include five ultraviolet bands from 280-400nm, permitting UV remote sensing capabilities in UV A, B, and C bands and enabling mineral identification and stimulated fluorescence measurements of organic proteins and compounds, such as green fluorescent proteins in terrestrial and aquatic organics.

Does the Data Resolution/origin Matter? Satellite, Airborne and Uav Imagery to Tackle Plant Invasions

NASA Astrophysics Data System (ADS)

Müllerová, Jana; Brůna, Josef; Dvořák, Petr; Bartaloš, Tomáš; Vítková, Michaela

2016-06-01

Invasive plant species represent a serious threat to biodiversity and landscape as well as human health and socio-economy. To successfully fight plant invasions, new methods enabling fast and efficient monitoring, such as remote sensing, are needed. In an ongoing project, optical remote sensing (RS) data of different origin (satellite, aerial and UAV), spectral (panchromatic, multispectral and color), spatial (very high to medium) and temporal resolution, and various technical approaches (object-, pixelbased and combined) are tested to choose the best strategies for monitoring of four invasive plant species (giant hogweed, black locust, tree of heaven and exotic knotweeds). In our study, we address trade-offs between spectral, spatial and temporal resolutions required for balance between the precision of detection and economic feasibility. For the best results, it is necessary to choose best combination of spatial and spectral resolution and phenological stage of the plant in focus. For species forming distinct inflorescences such as giant hogweed iterative semi-automated object-oriented approach was successfully applied even for low spectral resolution data (if pixel size was sufficient) whereas for lower spatial resolution satellite imagery or less distinct species with complicated architecture such as knotweed, combination of pixel and object based approaches was used. High accuracies achieved for very high resolution data indicate the possible application of described methodology for monitoring invasions and their long-term dynamics elsewhere, making management measures comparably precise, fast and efficient. This knowledge serves as a basis for prediction, monitoring and prioritization of management targets.

Miniature high-resolution guided-wave spectrometer for atmospheric remote sensing

NASA Astrophysics Data System (ADS)

Sloan, James; Kruzelecky, Roman; Wong, Brian; Zou, Jing; Jamroz, Wes; Haddad, Emile; Poirier, Michel

This paper describes the design and application of an innovative spectrometer in which a guided-wave integrated optical spectrometer (IOSPEC) has been coupled with a Fabry-Perot (FP) interferometer. This miniature spectrometer has a net mass under 3 kg, but is capable of broadband operation at spectral resolutions below 0.03 nm full width half maximum (FWHM). The tuneable FP filter provides very high spectral resolution combined with a large input aper-ture. The solid state guided-wave spectrometer is currently configured for a 512-channel array detector, which provides sub-nm coarse resolution. The ultimate resolution is determined by the FP filter, which is tuned across the desired spectral bands, thereby providing a signal-to-noise ratio (SNR) advantage over scanned spectrometer systems of the square root of the number of detector channels. The guided-wave optics provides robust, long-term optical alignment, while minimising the mechanical complexity. The miniaturisation of the FP-IOSPEC spectrometer allows multiple spectrometers to be accommodated on a single MicroSat. Each of these can be optimised for selected measurement tasks and views, thereby enabling more flexible data acquisition strategies with enhanced information content, while minimizing the mission cost. The application of this innovative technology in the proposed Miniature Earth Observation Satellite (MEOS) mission will also be discussed. The MEOS mission, which is designed for the investigation of the carbon and water cycles, relies on multiple IO-SPEC instruments for the simultaneous measurement of a range of atmospheric and surface properties important to climate change.

Optical Technologies for UV Remote Sensing Instruments

NASA Technical Reports Server (NTRS)

Keski-Kuha, R. A. M.; Osantowski, J. F.; Leviton, D. B.; Saha, T. T.; Content, D. A.; Boucarut, R. A.; Gum, J. S.; Wright, G. A.; Fleetwood, C. M.; Madison, T. J.

1993-01-01

Over the last decade significant advances in technology have made possible development of instruments with substantially improved efficiency in the UV spectral region. In the area of optical coatings and materials, the importance of recent developments in chemical vapor deposited (CVD) silicon carbide (SiC) mirrors, SiC films, and multilayer coatings in the context of ultraviolet instrumentation design are discussed. For example, the development of chemically vapor deposited (CVD) silicon carbide (SiC) mirrors, with high ultraviolet (UV) reflectance and low scatter surfaces, provides the opportunity to extend higher spectral/spatial resolution capability into the 50-nm region. Optical coatings for normal incidence diffraction gratings are particularly important for the evolution of efficient extreme ultraviolet (EUV) spectrographs. SiC films are important for optimizing the spectrograph performance in the 90 nm spectral region. The performance evaluation of the flight optical components for the Solar Ultraviolet Measurements of Emitted Radiation (SUMER) instrument, a spectroscopic instrument to fly aboard the Solar and Heliospheric Observatory (SOHO) mission, designed to study dynamic processes, temperatures, and densities in the plasma of the upper atmosphere of the Sun in the wavelength range from 50 nm to 160 nm, is discussed. The optical components were evaluated for imaging and scatter in the UV. The performance evaluation of SOHO/CDS (Coronal Diagnostic Spectrometer) flight gratings tested for spectral resolution and scatter in the DGEF is reviewed and preliminary results on resolution and scatter testing of Space Telescope Imaging Spectrograph (STIS) technology development diffraction gratings are presented.

Controlling ionotropic and metabotropic glutamate receptors with light: principles and potential.

PubMed

Reiner, Andreas; Levitz, Joshua; Isacoff, Ehud Y

2015-02-01

Light offers unique advantages for studying and manipulating biomolecules and the cellular processes that they control. Optical control of ionotropic and metabotropic glutamate receptors has garnered significant interest, since these receptors are central to signaling at neuronal synapses and only optical approaches provide the spatial and temporal resolution required to directly probe receptor function in cells and tissue. Following the classical method of glutamate photo-uncaging, recently developed methods have added other forms of remote control, including those with high molecular specificity and genetic targeting. These tools open the door to the direct optical control of synaptic transmission and plasticity, as well as the probing of native receptor function in intact neural circuits. Copyright © 2014 Elsevier Ltd. All rights reserved.

Reducing the uncertainty in the projection of the terrestrial carbon cycle by fusing models with remote sensing data

NASA Astrophysics Data System (ADS)

Serbin, S.; Shiklomanov, A. N.; Viskari, T.; Desai, A. R.; Townsend, P. A.; Dietze, M.

2015-12-01

Modeling global change requires accurate representation of terrestrial carbon (C), energy and water fluxes. In particular, capturing the properties of vegetation canopies that describe the radiation regime are a key focus for global change research because the properties related to radiation utilization and penetration within plant canopies provide an important constraint on terrestrial ecosystem productivity, as well as the fluxes of water and energy from vegetation to the atmosphere. As such, optical remote sensing observations present an important, and as yet relatively untapped, source of observations that can be used to inform modeling activities. In particular, high-spectral resolution optical data at the leaf and canopy scales offers the potential for an important and direct data constraint on the parameterization and structure of the radiative transfer model (RTM) scheme within ecosystem models across diverse vegetation types, disturbance and management histories. In this presentation we highlight ongoing work to integrate optical remote sensing observations, specifically leaf and imaging spectroscopy (IS) data across a range of forest ecosystems, into complex ecosystem process models within an efficient computational assimilation framework as a means to improve the description of canopy optical properties, vegetation composition, and modeled radiation balance. Our work leverages the Predictive Ecosystem Analyzer (PEcAn; http://www.pecanproject.org/) ecoinformatics toolbox together with a RTM module designed for efficient assimilation of leaf and IS observations to inform vegetation optical properties as well as associated plant traits. Ultimately, an improved understanding of the radiation balance of ecosystems will provide a better constraint on model projections of energy balance, vegetation composition, and carbon pools and fluxes thus allowing for a better diagnosis of the vulnerability of terrestrial ecosystems in response to global change.

Computational Ghost Imaging for Remote Sensing

NASA Technical Reports Server (NTRS)

Erkmen, Baris I.

2012-01-01

This work relates to the generic problem of remote active imaging; that is, a source illuminates a target of interest and a receiver collects the scattered light off the target to obtain an image. Conventional imaging systems consist of an imaging lens and a high-resolution detector array [e.g., a CCD (charge coupled device) array] to register the image. However, conventional imaging systems for remote sensing require high-quality optics and need to support large detector arrays and associated electronics. This results in suboptimal size, weight, and power consumption. Computational ghost imaging (CGI) is a computational alternative to this traditional imaging concept that has a very simple receiver structure. In CGI, the transmitter illuminates the target with a modulated light source. A single-pixel (bucket) detector collects the scattered light. Then, via computation (i.e., postprocessing), the receiver can reconstruct the image using the knowledge of the modulation that was projected onto the target by the transmitter. This way, one can construct a very simple receiver that, in principle, requires no lens to image a target. Ghost imaging is a transverse imaging modality that has been receiving much attention owing to a rich interconnection of novel physical characteristics and novel signal processing algorithms suitable for active computational imaging. The original ghost imaging experiments consisted of two correlated optical beams traversing distinct paths and impinging on two spatially-separated photodetectors: one beam interacts with the target and then illuminates on a single-pixel (bucket) detector that provides no spatial resolution, whereas the other beam traverses an independent path and impinges on a high-resolution camera without any interaction with the target. The term ghost imaging was coined soon after the initial experiments were reported, to emphasize the fact that by cross-correlating two photocurrents, one generates an image of the target. In CGI, the measurement obtained from the reference arm (with the high-resolution detector) is replaced by a computational derivation of the measurement-plane intensity profile of the reference-arm beam. The algorithms applied to computational ghost imaging have diversified beyond simple correlation measurements, and now include modern reconstruction algorithms based on compressive sensing.

Radar remote sensing for archaeology in Hangu Frontier Pass in Xin’an, China

NASA Astrophysics Data System (ADS)

Jiang, A. H.; Chen, F. L.; Tang, P. P.; Liu, G. L.; Liu, W. K.; Wang, H. C.; Lu, X.; Zhao, X. L.

2017-02-01

As a non-invasive tool, remote sensing can be applied to archaeology taking the advantage of large scale covering, in-time acquisition, high spatial-temporal resolution and etc. In archaeological research, optical approaches have been widely used. However, the capability of Synthetic Aperture Radar (SAR) for archaeological detection has not been fully exploded so far. In this study, we chose Hangu Frontier Pass of Han Dynasty located in Henan Province as the experimental site (included into the cluster of Silk Roads World Heritage sites). An exploratory study to detect the historical remains was conducted. Firstly, TanDEM-X SAR data were applied to generate high resolution DEM of Hangu Frontier Pass; and then the relationship between the pass and derived ridge lines was analyzed. Second, the temporal-averaged amplitude SAR images highlighted archaeological traces owing to the depressed speckle noise. For instance, the processing of 20-scene PALSAR data (spanning from 2007 to 2011) enabled us to detect unknown archaeological features. Finally, the heritage remains detected by SAR data were verified by Ground Penetrating Radar (GPR) prospecting, implying the potential of the space-to-ground radar remote sensing for archaeological applications.

Relating remotely sensed optical variability to marine benthic biodiversity.

PubMed

Herkül, Kristjan; Kotta, Jonne; Kutser, Tiit; Vahtmäe, Ele

2013-01-01

Biodiversity is important in maintaining ecosystem viability, and the availability of adequate biodiversity data is a prerequisite for the sustainable management of natural resources. As such, there is a clear need to map biodiversity at high spatial resolutions across large areas. Airborne and spaceborne optical remote sensing is a potential tool to provide such biodiversity data. The spectral variation hypothesis (SVH) predicts a positive correlation between spectral variability (SV) of a remotely sensed image and biodiversity. The SVH has only been tested on a few terrestrial plant communities. Our study is the first attempt to apply the SVH in the marine environment using hyperspectral imagery recorded by Compact Airborne Spectrographic Imager (CASI). All coverage-based diversity measures of benthic macrophytes and invertebrates showed low but statistically significant positive correlations with SV whereas the relationship between biomass-based diversity measures and SV were weak or lacking. The observed relationships did not vary with spatial scale. SV had the highest independent effect among predictor variables in the statistical models of coverage-derived total benthic species richness and Shannon index. Thus, the relevance of SVH in marine benthic habitats was proved and this forms a prerequisite for the future use of SV in benthic biodiversity assessments.

Characterizing Open Water Bodies and Their Color Properties Through Optical Remote Sensing to Identify Areas of Vector-Borne Disease Risk

NASA Astrophysics Data System (ADS)

Podest, E.; De La Torre Juarez, M.; McDonald, K. C.; Jensen, K.; Ceccato, P.

2014-12-01

Predicting the risk of vector-borne disease outbreaks is a required step towards their control and eradication. Satellite observations can provide needed data to support agency decisions with respect to deployment of preventative measures and control resources. The coverage and persistence of open water is one of the primary indicators of conditions suitable for mosquito breeding habitats. This is currently a poorly measured variable due to its spatial and temporal variability across landscapes, especially in remote areas. Here we develop a methodology for monitoring these conditions through optical remote sensing images from Landsat. We pansharpen the images and apply a decision tree classification approach using Random Forests to generate 15 meter resolution maps of open water. In addition, since some mosquitos breed in clear water while others in turbid water, we classify water bodies according to their water color properties and we validate the results using field knowledge. We focus in East Africa where we assses the usefulness of these products to improve prediction of malaria outbreaks. Portions of this work were carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

Detection and Monitoring of Small-Scale Mining Operations in the Eastern Democratic Republic of the Congo (DRC) Using Multi-Temporal, Multi-Sensor Remote Sensing Data

NASA Astrophysics Data System (ADS)

Walther, Christian; Frei, Michaela

2017-04-01

Mining of so-called "conflict minerals" is often related with small-scale mining activities. The here discussed activities are located in forested areas in the eastern DRC, which are often remote, difficult to access and insecure for traditional geological field inspection. In order to accelerate their CTC (Certified Trading Chain)-certification process, remote sensing data are used for detection and monitoring of these small-scale mining operations. This requires a high image acquisition frequency due to mining site relocations and for compensation of year-round high cloud coverage, especially for optical data evaluation. Freely available medium resolution optical data of Sentinel-2 and Landsat-8 as well as SAR data of Sentinel-1 are used for detecting small mining targets with a minimum size of approximately 0.5 km2. The developed method enables a robust multi-temporal detection of mining sites, monitoring of mining site spatio-temporal relocations and environmental changes. Since qualitative and quantitative comparable results are generated, the followed change detection approach is objective and transparent and may push the certification process forward.

Remote Sensing and Wetland Ecology: a South African Case Study.

PubMed

De Roeck, Els R; Verhoest, Niko E C; Miya, Mtemi H; Lievens, Hans; Batelaan, Okke; Thomas, Abraham; Brendonck, Luc

2008-05-26

Remote sensing offers a cost efficient means for identifying and monitoring wetlands over a large area and at different moments in time. In this study, we aim at providing ecologically relevant information on characteristics of temporary and permanent isolated open water wetlands, obtained by standard techniques and relatively cheap imagery. The number, surface area, nearest distance, and dynamics of isolated temporary and permanent wetlands were determined for the Western Cape, South Africa. Open water bodies (wetlands) were mapped from seven Landsat images (acquired during 1987 - 2002) using supervised maximum likelihood classification. The number of wetlands fluctuated over time. Most wetlands were detected in the winter of 2000 and 2002, probably related to road constructions. Imagery acquired in summer contained fewer wetlands than in winter. Most wetlands identified from Landsat images were smaller than one hectare. The average distance to the nearest wetland was larger in summer. In comparison to temporary wetlands, fewer, but larger permanent wetlands were detected. In addition, classification of non-vegetated wetlands on an Envisat ASAR radar image (acquired in June 2005) was evaluated. The number of detected small wetlands was lower for radar imagery than optical imagery (acquired in June 2002), probably because of deterioration of the spatial information content due the extensive pre-processing requirements of the radar image. Both optical and radar classifications allow to assess wetland characteristics that potentially influence plant and animal metacommunity structure. Envisat imagery, however, was less suitable than Landsat imagery for the extraction of detailed ecological information, as only large wetlands can be detected. This study has indicated that ecologically relevant data can be generated for the larger wetlands through relatively cheap imagery and standard techniques, despite the relatively low resolution of Landsat and Envisat imagery. For the characterisation of very small wetlands, high spatial resolution optical or radar images are needed. This study exemplifies the benefits of integrating remote sensing and ecology and hence stimulates interdisciplinary research of isolated wetlands.

Compact Microwave Fourier Spectrum Analyzer

NASA Technical Reports Server (NTRS)

Savchenkov, Anatoliy; Matsko, Andrey; Strekalov, Dmitry

2009-01-01

A compact photonic microwave Fourier spectrum analyzer [a Fourier-transform microwave spectrometer, (FTMWS)] with no moving parts has been proposed for use in remote sensing of weak, natural microwave emissions from the surfaces and atmospheres of planets to enable remote analysis and determination of chemical composition and abundances of critical molecular constituents in space. The instrument is based on a Bessel beam (light modes with non-zero angular momenta) fiber-optic elements. It features low power consumption, low mass, and high resolution, without a need for any cryogenics, beyond what is achievable by the current state-of-the-art in space instruments. The instrument can also be used in a wide-band scatterometer mode in active radar systems.

Assessment of the Accuracy of the Conventional Ray-Tracing Technique: Implications in Remote Sensing and Radiative Transfer Involving Ice Clouds.

NASA Technical Reports Server (NTRS)

Bi, Lei; Yang, Ping; Liu, Chao; Yi, Bingqi; Baum, Bryan A.; Van Diedenhoven, Bastiaan; Iwabuchi, Hironobu

2014-01-01

A fundamental problem in remote sensing and radiative transfer simulations involving ice clouds is the ability to compute accurate optical properties for individual ice particles. While relatively simple and intuitively appealing, the conventional geometric-optics method (CGOM) is used frequently for the solution of light scattering by ice crystals. Due to the approximations in the ray-tracing technique, the CGOM accuracy is not well quantified. The result is that the uncertainties are introduced that can impact many applications. Improvements in the Invariant Imbedding T-matrix method (II-TM) and the Improved Geometric-Optics Method (IGOM) provide a mechanism to assess the aforementioned uncertainties. The results computed by the II-TMþIGOM are considered as a benchmark because the IITM solves Maxwell's equations from first principles and is applicable to particle size parameters ranging into the domain at which the IGOM has reasonable accuracy. To assess the uncertainties with the CGOM in remote sensing and radiative transfer simulations, two independent optical property datasets of hexagonal columns are developed for sensitivity studies by using the CGOM and the II-TMþIGOM, respectively. Ice cloud bulk optical properties obtained from the two datasets are compared and subsequently applied to retrieve the optical thickness and effective diameter from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Additionally, the bulk optical properties are tested in broadband radiative transfer (RT) simulations using the general circulation model (GCM) version of the Rapid Radiative Transfer Model (RRTMG) that is adopted in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM, version 5.1). For MODIS retrievals, the mean bias of uncertainties of applying the CGOM in shortwave bands (0.86 and 2.13 micrometers) can be up to 5% in the optical thickness and as high as 20% in the effective diameter, depending on cloud optical thickness and effective diameter. In the MODIS infrared window bands centered at 8.5, 11, and 12 micrometers biases in the optical thickness and effective diameter are up to 12% and 10%, respectively. The CGOM-based simulation errors in ice cloud radiative forcing calculations are on the order of 10Wm(exp 2).

Aqueye+: a new ultrafast single photon counter for optical high time resolution astrophysics

NASA Astrophysics Data System (ADS)

Zampieri, L.; Naletto, G.; Barbieri, C.; Verroi, E.; Barbieri, M.; Ceribella, G.; D'Alessandro, M.; Farisato, G.; Di Paola, A.; Zoccarato, P.

2015-05-01

Aqueye+ is a new ultrafast optical single photon counter, based on single photon avalanche photodiodes (SPAD) and a 4- fold split-pupil concept. It is a completely revisited version of its predecessor, Aqueye, successfully mounted at the 182 cm Copernicus telescope in Asiago. Here we will present the new technological features implemented on Aqueye+, namely a state of the art timing system, a dedicated and optimized optical train, a high sensitivity and high frame rate field camera and remote control, which will give Aqueye plus much superior performances with respect to its predecessor, unparalleled by any other existing fast photometer. The instrument will host also an optical vorticity module to achieve high performance astronomical coronography and a real time acquisition of atmospheric seeing unit. The present paper describes the instrument and its first performances.

Fluid Lensing based Machine Learning for Augmenting Earth Science Coral Datasets

NASA Astrophysics Data System (ADS)

Li, A.; Instrella, R.; Chirayath, V.

2016-12-01

Recently, there has been increased interest in monitoring the effects of climate change upon the world's marine ecosystems, particularly coral reefs. These delicate ecosystems are especially threatened due to their sensitivity to ocean warming and acidification, leading to unprecedented levels of coral bleaching and die-off in recent years. However, current global aquatic remote sensing datasets are unable to quantify changes in marine ecosystems at spatial and temporal scales relevant to their growth. In this project, we employ various supervised and unsupervised machine learning algorithms to augment existing datasets from NASA's Earth Observing System (EOS), using high resolution airborne imagery. This method utilizes NASA's ongoing airborne campaigns as well as its spaceborne assets to collect remote sensing data over these afflicted regions, and employs Fluid Lensing algorithms to resolve optical distortions caused by the fluid surface, producing cm-scale resolution imagery of these diverse ecosystems from airborne platforms. Support Vector Machines (SVMs) and K-mean clustering methods were applied to satellite imagery at 0.5m resolution, producing segmented maps classifying coral based on percent cover and morphology. Compared to a previous study using multidimensional maximum a posteriori (MAP) estimation to separate these features in high resolution airborne datasets, SVMs are able to achieve above 75% accuracy when augmented with existing MAP estimates, while unsupervised methods such as K-means achieve roughly 68% accuracy, verified by manually segmented reference data provided by a marine biologist. This effort thus has broad applications for coastal remote sensing, by helping marine biologists quantify behavioral trends spanning large areas and over longer timescales, and to assess the health of coral reefs worldwide.

Evaluating Global Aerosol Models and Aerosol and Water Vapor Properties Near Clouds

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

Richard A. Ferrare; David D. Turner

Project goals: (1) Use the routine surface and airborne measurements at the ARM SGP site, and the routine surface measurements at the NSA site, to continue our evaluations of model aerosol simulations; (2) Determine the degree to which the Raman lidar measurements of water vapor and aerosol scattering and extinction can be used to remotely characterize the aerosol humidification factor; (3) Use the high temporal resolution CARL data to examine how aerosol properties vary near clouds; and (4) Use the high temporal resolution CARL and Atmospheric Emitted Radiance Interferometer (AERI) data to quantify entrainment in optically thin continental cumulus clouds.

In-service communication channel sensing based on reflectometry for TWDM-PON systems

NASA Astrophysics Data System (ADS)

Iida, Daisuke; Kuwano, Shigeru; Terada, Jun

2014-05-01

Many base stations are accommodated in TWDM-PON based mobile backhaul and fronthaul networks for future radio access, and failed connections in an optical network unit (ONU) wavelength channel severely degrade system performance. A cost effective in-service ONU wavelength channel monitor is essential to ensure proper system operation without failed connections. To address this issue we propose a reflectometry-based remote sensing method that provides wavelength channel information with the optical line terminal (OLT)-ONU distance. The method realizes real-time monitoring of ONU wavelength channels without signal quality degradation. Experimental results show it achieves wavelength channel distinction with high distance resolution.

Reflective ghost imaging through turbulence

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

Hardy, Nicholas D.; Shapiro, Jeffrey H.

2011-12-15

Recent work has indicated that ghost imaging may have applications in standoff sensing. However, most theoretical work has addressed transmission-based ghost imaging. To be a viable remote-sensing system, the ghost imager needs to image rough-surfaced targets in reflection through long, turbulent optical paths. We develop, within a Gaussian-state framework, expressions for the spatial resolution, image contrast, and signal-to-noise ratio of such a system. We consider rough-surfaced targets that create fully developed speckle in their returns and Kolmogorov-spectrum turbulence that is uniformly distributed along all propagation paths. We address both classical and nonclassical optical sources, as well as a computational ghostmore » imager.« less

Gap formation and carbon cycling in the Brazilian Amazon: measurement using high-resolution optical remote sensing and studies in large forest plots

Treesearch

F. D. B. Espirito-Santo; M. M. Keller; E. Linder; R. C. Oliveira Junior; C. Pereira; C. G. Oliveira

2013-01-01

Background: The dynamics of gaps plays a role in the regimes of tree mortality, production of coarse woody debris (CWD) and the variability of light in the forest understory. Aims: To quantify the area affected by, and the carbon fluxes associated with, natural gap-phase disturbances in a tropical lowland evergreen rain forest by use of ground measurements and high-...

Developing Remote Sensing Capabilities for Meter-Scale Sea Ice Properties

DTIC Science & Technology

2013-09-30

such as MODIS . APPROACH 1. Task and acquire high resolution panchromatic and multispectral optical (e.g. Quickbird, Worldview, National Assets...does not display a currently valid OMB control number. 1. REPORT DATE 30 SEP 2013 2. REPORT TYPE 3. DATES COVERED 00-00-2013 to 00-00-2013 4...cloud cover , an excessive percentage of the imagery acquired over drifting sites was cloud covered , and the vendor did not delay acquisitions or

Coarse-to-fine wavelet-based airport detection

NASA Astrophysics Data System (ADS)

Li, Cheng; Wang, Shuigen; Pang, Zhaofeng; Zhao, Baojun

2015-10-01

Airport detection on optical remote sensing images has attracted great interest in the applications of military optics scout and traffic control. However, most of the popular techniques for airport detection from optical remote sensing images have three weaknesses: 1) Due to the characteristics of optical images, the detection results are often affected by imaging conditions, like weather situation and imaging distortion; and 2) optical images contain comprehensive information of targets, so that it is difficult for extracting robust features (e.g., intensity and textural information) to represent airport area; 3) the high resolution results in large data volume, which makes real-time processing limited. Most of the previous works mainly focus on solving one of those problems, and thus, the previous methods cannot achieve the balance of performance and complexity. In this paper, we propose a novel coarse-to-fine airport detection framework to solve aforementioned three issues using wavelet coefficients. The framework includes two stages: 1) an efficient wavelet-based feature extraction is adopted for multi-scale textural feature representation, and support vector machine(SVM) is exploited for classifying and coarsely deciding airport candidate region; and then 2) refined line segment detection is used to obtain runway and landing field of airport. Finally, airport recognition is achieved by applying the fine runway positioning to the candidate regions. Experimental results show that the proposed approach outperforms the existing algorithms in terms of detection accuracy and processing efficiency.

Analysis of flood inundation in ungauged basins based on multi-source remote sensing data.

PubMed

Gao, Wei; Shen, Qiu; Zhou, Yuehua; Li, Xin

2018-02-09

Floods are among the most expensive natural hazards experienced in many places of the world and can result in heavy losses of life and economic damages. The objective of this study is to analyze flood inundation in ungauged basins by performing near-real-time detection with flood extent and depth based on multi-source remote sensing data. Via spatial distribution analysis of flood extent and depth in a time series, the inundation condition and the characteristics of flood disaster can be reflected. The results show that the multi-source remote sensing data can make up the lack of hydrological data in ungauged basins, which is helpful to reconstruct hydrological sequence; the combination of MODIS (moderate-resolution imaging spectroradiometer) surface reflectance productions and the DFO (Dartmouth Flood Observatory) flood database can achieve the macro-dynamic monitoring of the flood inundation in ungauged basins, and then the differential technique of high-resolution optical and microwave images before and after floods can be used to calculate flood extent to reflect spatial changes of inundation; the monitoring algorithm for the flood depth combining RS and GIS is simple and easy and can quickly calculate the depth with a known flood extent that is obtained from remote sensing images in ungauged basins. Relevant results can provide effective help for the disaster relief work performed by government departments.

Performance of an untethered micro-optical pressure sensor

NASA Astrophysics Data System (ADS)

Ioppolo, Tindaro; Manzo, Maurizio; Krueger, Paul

2012-11-01

We present analytical and computational studies of the performance of a novel untethered micro-optical pressure sensor for fluid dynamics measurements. In particular, resolution and dynamic range will be presented. The sensor concept is based on the whispering galley mode (WGM) shifts that are observed in micro-scale dielectric optical cavities. A micro-spherical optical cavity (liquid or solid) is embedded in a thin polymeric sheet. The applied external pressure perturbs the morphology of the optical cavity leading to a shift in its optical resonances. The optical sensors are interrogated remotely, by embedding quantum dots or fluorescent dye in the micro-optical cavity. This allows a free space coupling of excitation and monitoring of the optical modes without the need of optical fibers or other cabling. With appropriate excitation and monitoring equipment, the micro-scale sensors can be distributed over a surface (e.g., including flexible biological surfaces) to monitor the local pressure field. We acknowledge the financial support from the National Science Foundation through grant CBET-1133876 with Dr. Horst Henning Winter as the program director.

[A snow depth inversion method for the HJ-1B satellite data].

PubMed

Dong, Ting-Xu; Jiang, Hong-Bo; Chen, Chao; Qin, Qi-Ming

2011-10-01

The importance of the snow is self-evident, while the harms caused by the snow have also received more and more attention. At present, the retrieval of snow depth mainly focused on the use of microwave remote sensing data or a small amount of optical remote sensing data, such as the meteorological data or the MODIS data. The small satellites for environment and disaster monitoring of China are quite different form the meteorological data and MODIS data, both in the spectral resolution or spatial resolution. In this paper, aimed at the HJ-1B data, snow spectral of different underlying surfaces and depths were surveyed. The correlation between snow cover index and snow depth was also analyzed to establish the model for the snow depth retrieval using the HJ-1B data. The validation results showed that it can meet the requirements of real-time monitoring the snow depth on the condition of conventional snow depth.

Imaging IR spectrometer, phase 2

NASA Technical Reports Server (NTRS)

Gradie, Jonathan; Lewis, Ralph; Lundeen, Thomas; Wang, Shu-I

1990-01-01

The development is examined of a prototype multi-channel infrared imaging spectrometer. The design, construction and preliminary performance is described. This instrument is intended for use with JPL Table Mountain telescope as well as the 88 inch UH telescope on Mauna Kea. The instrument is capable of sampling simultaneously the spectral region of 0.9 to 2.6 um at an average spectral resolution of 1 percent using a cooled (77 K) optical bench, a concave holographic grating and a special order sorting filter to allow the acquisition of the full spectral range on a 128 x 128 HgCdTe infrared detector array. The field of view of the spectrometer is 0.5 arcsec/pixel in mapping mode and designed to be 5 arcsec/pixel in spot mode. The innovative optical design has resulted in a small, transportable spectrometer, capable of remote operation. Commercial applications of this spectrometer design include remote sensing from both space and aircraft platforms as well as groundbased astronomical observations.

The Retrieval of Aerosol Optical Thickness Using the MERIS Instrument

NASA Astrophysics Data System (ADS)

Mei, L.; Rozanov, V. V.; Vountas, M.; Burrows, J. P.; Levy, R. C.; Lotz, W.

2015-12-01

Retrieval of aerosol properties for satellite instruments without shortwave-IR spectral information, multi-viewing, polarization and/or high-temporal observation ability is a challenging problem for spaceborne aerosol remote sensing. However, space based instruments like the MEdium Resolution Imaging Spectrometer (MERIS) and the successor, Ocean and Land Colour Instrument (OLCI) with high calibration accuracy and high spatial resolution provide unique abilities for obtaining valuable aerosol information for a better understanding of the impact of aerosols on climate, which is still one of the largest uncertainties of global climate change evaluation. In this study, a new Aerosol Optical Thickness (AOT) retrieval algorithm (XBAER: eXtensible Bremen AErosol Retrieval) is presented. XBAER utilizes the global surface spectral library database for the determination of surface properties while the MODIS collection 6 aerosol type treatment is adapted for the aerosol type selection. In order to take the surface Bidirectional Reflectance Distribution Function (BRDF) effect into account for the MERIS reduce resolution (1km) retrieval, a modified Ross-Li mode is used. The AOT is determined in the algorithm using lookup tables including polarization created using Radiative Transfer Model SCIATRAN3.4, by minimizing the difference between atmospheric corrected surface reflectance with given AOT and the surface reflectance calculated from the spectral library. The global comparison with operational MODIS C6 product, Multi-angle Imaging SpectroRadiometer (MISR) product, Advanced Along-Track Scanning Radiometer (AATSR) aerosol product and the validation using AErosol RObotic NETwork (AERONET) show promising results. The current XBAER algorithm is only valid for aerosol remote sensing over land and a similar method will be extended to ocean later.

An Enhanced Algorithm for Automatic Radiometric Harmonization of High-Resolution Optical Satellite Imagery Using Pseudoinvariant Features and Linear Regression

NASA Astrophysics Data System (ADS)

Langheinrich, M.; Fischer, P.; Probeck, M.; Ramminger, G.; Wagner, T.; Krauß, T.

2017-05-01

The growing number of available optical remote sensing data providing large spatial and temporal coverage enables the coherent and gapless observation of the earth's surface on the scale of whole countries or continents. To produce datasets of that size, individual satellite scenes have to be stitched together forming so-called mosaics. Here the problem arises that the different images feature varying radiometric properties depending on the momentary acquisition conditions. The interpretation of optical remote sensing data is to a great extent based on the analysis of the spectral composition of an observed surface reflection. Therefore the normalization of all images included in a large image mosaic is necessary to ensure consistent results concerning the application of procedures to the whole dataset. In this work an algorithm is described which enables the automated spectral harmonization of satellite images to a reference scene. As the stable and satisfying functionality of the proposed algorithm was already put to operational use to process a high number of SPOT-4/-5, IRS LISS-III and Landsat-5 scenes in the frame of the European Environment Agency's Copernicus/GMES Initial Operations (GIO) High-Resolution Layer (HRL) mapping of the HRL Forest for 20 Western, Central and (South)Eastern European countries, it is further evaluated on its reliability concerning the application to newer Sentinel-2 multispectral imaging products. The results show that the algorithm is comparably efficient for the processing of satellite image data from sources other than the sensor configurations it was originally designed for.

High Spectral Resolution Lidar: System Calibration

NASA Astrophysics Data System (ADS)

Vivek Vivekanandan, J.; Morley, Bruce; Spuler, Scott; Eloranta, Edwin

2015-04-01

One of the unique features of the high spectral resolution lidar (HSRL) is simultaneous measurements of backscatter and extinction of atmosphere. It separates molecular scattering from aerosol and cloud particle backscatter based on their Doppler spectrum width. Scattering from aerosol and cloud particle are referred as Mie scattering. Molecular or Rayleigh scattering is used as a reference for estimating aerosol extinction and backscatter cross-section. Absolute accuracy of the backscattered signals and their separation into Rayleigh and Mie scattering depends on spectral purity of the transmitted signals, accurate measurement of transmit power, and precise performance of filters. Internal calibration is used to characterize optical subsystems Descriptions of high spectral resolution lidar system and its measurement technique can be found in Eloronta (2005) and Hair et al.(2001). Four photon counting detectors are used to measure the backscatter from the combined Rayleigh and molecular scattering (high and low gain), molecular scattering and cross-polarized signal. All of the detectors are sensitive to crosstalk or leakage through the optical filters used to separate the received signals and special data files are used to remove these effects as much as possible. Received signals are normalized with respect to the combined channel response to Mie and Rayleigh scattering. The laser transmit frequency is continually monitored and tuned to the 1109 Iodine absorption line. Aerosol backscatter cross-section is measured by referencing the aerosol return signal to the molecular return signal. Extinction measurements are calculated based on the differences between the expected (theoretical) and actual change in the molecular return. In this paper an overview of calibration of the HSRL is presented. References: Eloranta, E. W., High Spectral Resolution Lidar in Lidar: Range-Resolved Optical Remote Sensing of the Atmosphere, Klaus Weitkamp editor, Springer Series in Optical Sciences, Springer-Verlag, New York, 2005. Hair, JW; Caldwell, LM; Krueger, D. A.Krueger, and C.Y. She 2001: High-spectral-resolution lidar with iodine-vapor filters: measurement of atmospheric-state and aerosol profiles. Appl. Optics, 40, 5280-5294.

Low-cost 3D printed 1  nm resolution smartphone sensor-based spectrometer: instrument design and application in ultraviolet spectroscopy.

PubMed

Wilkes, Thomas C; McGonigle, Andrew J S; Willmott, Jon R; Pering, Tom D; Cook, Joseph M

2017-11-01

We report on the development of a low-cost spectrometer, based on off-the-shelf optical components, a 3D printed housing, and a modified Raspberry Pi camera module. With a bandwidth and spectral resolution of ≈60  nm and 1 nm, respectively, this device was designed for ultraviolet (UV) remote sensing of atmospheric sulphur dioxide (SO 2 ), ≈310  nm. To the best of our knowledge, this is the first report of both a UV spectrometer and a nanometer resolution spectrometer based on smartphone sensor technology. The device performance was assessed and validated by measuring column amounts of SO 2 within quartz cells with a differential optical absorption spectroscopy processing routine. This system could easily be reconfigured to cover other UV-visible-near-infrared spectral regions, as well as alternate spectral ranges and/or linewidths. Hence, our intention is also to highlight how this framework could be applied to build bespoke, low-cost, spectrometers for a range of scientific applications.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features.

PubMed

Li, Linyi; Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features

PubMed Central

Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images. PMID:28761440

A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers

PubMed Central

Huemmrich, K. Fred; Ensminger, Ingo; Garrity, Steven; Noormets, Asko; Peñuelas, Josep

2016-01-01

In evergreen conifers, where the foliage amount changes little with season, accurate detection of the underlying “photosynthetic phenology” from satellite remote sensing has been difficult, presenting challenges for global models of ecosystem carbon uptake. Here, we report a close correspondence between seasonally changing foliar pigment levels, expressed as chlorophyll/carotenoid ratios, and evergreen photosynthetic activity, leading to a “chlorophyll/carotenoid index” (CCI) that tracks evergreen photosynthesis at multiple spatial scales. When calculated from NASA’s Moderate Resolution Imaging Spectroradiometer satellite sensor, the CCI closely follows the seasonal patterns of daily gross primary productivity of evergreen conifer stands measured by eddy covariance. This discovery provides a way of monitoring evergreen photosynthetic activity from optical remote sensing, and indicates an important regulatory role for carotenoid pigments in evergreen photosynthesis. Improved methods of monitoring photosynthesis from space can improve our understanding of the global carbon budget in a warming world of changing vegetation phenology. PMID:27803333

A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers.

PubMed

Gamon, John A; Huemmrich, K Fred; Wong, Christopher Y S; Ensminger, Ingo; Garrity, Steven; Hollinger, David Y; Noormets, Asko; Peñuelas, Josep

2016-11-15

In evergreen conifers, where the foliage amount changes little with season, accurate detection of the underlying "photosynthetic phenology" from satellite remote sensing has been difficult, presenting challenges for global models of ecosystem carbon uptake. Here, we report a close correspondence between seasonally changing foliar pigment levels, expressed as chlorophyll/carotenoid ratios, and evergreen photosynthetic activity, leading to a "chlorophyll/carotenoid index" (CCI) that tracks evergreen photosynthesis at multiple spatial scales. When calculated from NASA's Moderate Resolution Imaging Spectroradiometer satellite sensor, the CCI closely follows the seasonal patterns of daily gross primary productivity of evergreen conifer stands measured by eddy covariance. This discovery provides a way of monitoring evergreen photosynthetic activity from optical remote sensing, and indicates an important regulatory role for carotenoid pigments in evergreen photosynthesis. Improved methods of monitoring photosynthesis from space can improve our understanding of the global carbon budget in a warming world of changing vegetation phenology.

Inland and coastal waters

NASA Astrophysics Data System (ADS)

Mouw, Colleen; Greb, Steven

2012-09-01

Workshop for Remote Sensing of Coastal and Inland Waters;Madison, Wisconsin, 20-22 June 2012 Coastal and inland water bodies, which have great value for recreation, food supply, commerce, transportation, and human health, have been experiencing external pressure from direct human activities and climate change. Given their societal and economic value, understanding issues of water quality, water quantity, and the impact of environmental change on the ecological and biogeochemical functioning of these water bodies is of interest to a broad range of communities. Remote sensing offers one of the most spatially and temporally comprehensive tools for observing these waters. While there has been some success with remotely observing these water bodies, many challenges still remain, including algorithm performance, atmospheric correction, the relationships between optical properties and biogeochemical parameters, sufficient spatial and spectral resolution, and a lack of uncertainty estimates over the wide range of environmental conditions encountered across these coastal and inland water bodies.

Research on airborne infrared leakage detection of natural gas pipeline

NASA Astrophysics Data System (ADS)

Tan, Dongjie; Xu, Bin; Xu, Xu; Wang, Hongchao; Yu, Dongliang; Tian, Shengjie

2011-12-01

An airborne laser remote sensing technology is proposed to detect natural gas pipeline leakage in helicopter which carrying a detector, and the detector can detect a high spatial resolution of trace of methane on the ground. The principle of the airborne laser remote sensing system is based on tunable diode laser absorption spectroscopy (TDLAS). The system consists of an optical unit containing the laser, camera, helicopter mount, electronic unit with DGPS antenna, a notebook computer and a pilot monitor. And the system is mounted on a helicopter. The principle and the architecture of the airborne laser remote sensing system are presented. Field test experiments are carried out on West-East Natural Gas Pipeline of China, and the results show that airborne detection method is suitable for detecting gas leak of pipeline on plain, desert, hills but unfit for the area with large altitude diversification.

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users

PubMed Central

Calera, Alfonso; Campos, Isidro; Osann, Anna; D’Urso, Guido; Menenti, Massimo

2017-01-01

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools. PMID:28492515

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users.

PubMed

Calera, Alfonso; Campos, Isidro; Osann, Anna; D'Urso, Guido; Menenti, Massimo

2017-05-11

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.

Comparison of in-situ and optical current-meter estimates of rip-current circulation

NASA Astrophysics Data System (ADS)

Moulton, M.; Chickadel, C. C.; Elgar, S.; Raubenheimer, B.

2016-12-01

Rip currents are fast, narrow, seaward flows that transport material from the shoreline to the shelf. Spatially and temporally complex rip current circulation patterns are difficult to resolve with in-situ instrument arrays. Here, high spatial-resolution estimates of rip current circulation from remotely sensed optical images of the sea surface are compared with in-situ estimates of currents in and near channels ( 1- to 2-m deep and 30-m wide) dredged across the surf zone. Alongshore flows are estimated using the optical current-meter method, and cross-shore flows are derived with the assumption of continuity. The observations span a range of wave conditions, tidal elevations, and flow patterns, including meandering alongshore currents near and in the channel, and 0.5 m/s alongshore flows converging at a 0.8 m/s rip jet in the channel. In addition, the remotely sensed velocities are used to investigate features of the spatially complex flow patterns not resolved by the spatially sparse in-situ sensors, including the spatial extent of feeder current zones and the width, alongshore position, and cross-shore extent of rip current jets. Funded by ASD(R&E) and NSF.

Asian Dust Weather Categorization with Satellite and Surface Observations

NASA Technical Reports Server (NTRS)

Lin, Tang-Huang; Hsu, N. Christina; Tsay, Si-Chee; Huang, Shih-Jen

2011-01-01

This study categorizes various dust weather types by means of satellite remote sensing over central Asia. Airborne dust particles can be identified by satellite remote sensing because of the different optical properties exhibited by coarse and fine particles (i.e. varying particle sizes). If a correlation can be established between the retrieved aerosol optical properties and surface visibility, the intensity of dust weather can be more effectively and consistently discerned using satellite rather than surface observations. In this article, datasets consisting of collocated products from Moderate Resolution Imaging Spectroradiometer Aqua and surface measurements are analysed. The results indicate an exponential relationship between the surface visibility and the satellite-retrieved aerosol optical depth, which is subsequently used to categorize the dust weather. The satellite-derived spatial frequency distributions in the dust weather types are consistent with China s weather station reports during 2003, indicating that dust weather classification using satellite data is highly feasible. Although the period during the springtime from 2004 to 2007 may be not sufficient for statistical significance, our results reveal an increasing tendency in both intensity and frequency of dust weather over central Asia during this time period.

Remote sensing of deep hermatypic coral reefs in Puerto Rico and the U.S. Virgin Islands using the Seabed autonomous underwater vehicle

NASA Astrophysics Data System (ADS)

Armstrong, Roy A.; Singh, Hanumant

2006-09-01

Optical imaging of coral reefs and other benthic communities present below one attenuation depth, the limit of effective airborne and satellite remote sensing, requires the use of in situ platforms such as autonomous underwater vehicles (AUVs). The Seabed AUV, which was designed for high-resolution underwater optical and acoustic imaging, was used to characterize several deep insular shelf reefs of Puerto Rico and the US Virgin Islands using digital imagery. The digital photo transects obtained by the Seabed AUV provided quantitative data on living coral, sponge, gorgonian, and macroalgal cover as well as coral species richness and diversity. Rugosity, an index of structural complexity, was derived from the pencil-beam acoustic data. The AUV benthic assessments could provide the required information for selecting unique areas of high coral cover, biodiversity and structural complexity for habitat protection and ecosystem-based management. Data from Seabed sensors and related imaging technologies are being used to conduct multi-beam sonar surveys, 3-D image reconstruction from a single camera, photo mosaicking, image based navigation, and multi-sensor fusion of acoustic and optical data.

Optical Power Transfer System for Powering a Remote Mobility System for Multiple Missions

NASA Technical Reports Server (NTRS)

Hogan, Bartholomew P. (Inventor); Stone, William C. (Inventor)

2016-01-01

An optical power transfer system for powering a remote mobility system for multiple missions comprising a high power source and a chilling station connected to a laser source. The laser source transmits a high optical energy to a beam switch assembly via an optical fiber. The beam switch assembly is optically connected to actively cooled fiber spoolers. Docking stations are adapted for securing the fiber spoolers until alternatively ready for use by a remote mobility system. The remote mobility system is optically connected to the fiber spoolers and has a receiving port adapted for securing the fiber spoolers thereon. The fiber spooler transmits the optical energy to a power conversion system which converts the optical energy received to another usable form of energy. More than one power source may be used where the remote mobility system transfers from one source to another while maintaining an operational radius to each source.

The impact of turbulent fluctuations on light propagation in a controlled environment

NASA Astrophysics Data System (ADS)

Matt, Silvia; Hou, Weilin; Goode, Wesley

2014-05-01

Underwater temperature and salinity microstructure can lead to localized changes in the index of refraction and can be a limiting factor in oceanic environments. This optical turbulence can affect electro-optical (EO) signal transmissions that impact various applications, from diver visibility to active and passive remote sensing. To quantify the scope of the impacts from turbulent flows on EO signal transmission, and to examine and mitigate turbulence effects, we perform experiments in a controlled turbulence environment allowing the variation of turbulence intensity. This controlled turbulence setup is implemented at the Naval Research Laboratory Stennis Space Center (NRLSSC). Convective turbulence is generated in a classical Rayleigh-Benard tank and the turbulent flow is quantified using a state-of-the-art suite of sensors that includes high-resolution Acoustic Doppler Velocimeter profilers and fast thermistor probes. The measurements are complemented by very high- resolution non-hydrostatic numerical simulations. These computational fluid dynamics simulations allow for a more complete characterization of the convective flow in the laboratory tank than would be provided by measurements alone. Optical image degradation in the tank is assessed in relation to turbulence intensity. The unique approach of integrating optical techniques, turbulence measurements and numerical simulations helps advance our understanding of how to mitigate the effects of turbulence impacts on underwater optical signal transmission, as well as of the use of optical techniques to probe oceanic processes.

Cloud and Radiation Studies during SAFARI 2000

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, M. D.; Hobbs, P. V.; Osborne, S.; Piketh, S.; Bruintjes, R.; Lau, William K. M. (Technical Monitor)

2001-01-01

Though the emphasis of the Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign was largely on emission sources and transport, the assemblage of aircraft (including the high altitude NASA ER-2 remote sensing platform and the University of Washington CV-580, UK MRF C130, and South African Weather Bureau JRA in situ aircrafts) provided a unique opportunity for cloud studies. Therefore, as part of the SAFARI initiative, investigations were undertaken to assess regional aerosol-cloud interactions and cloud remote sensing algorithms. In particular, the latter part of the experiment concentrated on marine boundary layer stratocumulus clouds off the southwest coast of Africa. Associated with cold water upwelling along the Benguela current, the Namibian stratocumulus regime has received limited attention but appears to be unique for several reasons. During the dry season, outflow of continental fires and industrial pollution over this area can be extreme. From below, upwelling provides a rich nutrient source for phytoplankton (a source of atmospheric sulphur through DMS production as well as from decay processes). The impact of these natural and anthropogenic sources on the microphysical and optical properties of the stratocumulus is unknown. Continental and Indian Ocean cloud systems of opportunity were also studied during the campaign. Aircraft flights were coordinated with NASA Terra Satellite overpasses for synergy with the Moderate Resolution Imaging Spectroradiometer (MODIS) and other Terra instruments. An operational MODIS algorithm for the retrieval of cloud optical and physical properties (including optical thickness, effective particle radius, and water path) has been developed. Pixel-level MODIS retrievals (11 km spatial resolution at nadir) and gridded statistics of clouds in th SAFARI region will be presented. In addition, the MODIS Airborne Simulator flown on the ER-2 provided high spatial resolution retrievals (50 m at nadir). These retrievals will be discussed and compared with in situ observations.

Integration of TerraSAR-X, RapidEye and airborne lidar for remote sensing of intertidal bedforms on the upper flats of Norderney (German Wadden Sea)

NASA Astrophysics Data System (ADS)

Adolph, Winny; Jung, Richard; Schmidt, Alena; Ehlers, Manfred; Heipke, Christian; Bartholomä, Alexander; Farke, Hubert

2017-04-01

The Wadden Sea is a large coastal transition area adjoining the southern North Sea uniting ecological key functions with an important role in coastal protection. The region is strictly protected by EU directives and national law and is a UNESCO World Heritage Site, requiring frequent quality assessments and regular monitoring. In 2014 an intertidal bedform area characterised by alternating crests and water-covered troughs on the tidal flats of the island of Norderney (German Wadden Sea sector) was chosen to test different remote sensing methods for habitat mapping: airborne lidar, satellite-based radar (TerraSAR-X) and electro-optical sensors (RapidEye). The results revealed that, although sensitive to different surface qualities, all sensors were able to image the bedforms. A digital terrain model generated from the lidar data shows crests and slopes of the bedforms with high geometric accuracy in the centimetre range, but high costs limit the operation area. TerraSAR-X data enabled identifying the positions of the bedforms reflecting the residual water in the troughs also with a high resolution of up to 1.1 m, but with larger footprints and much higher temporal availability. RapidEye data are sensitive to differences in sediment moisture employed to identify crest areas, slopes and troughs, with high spatial coverage but the lowest resolution (6.5 m). Monitoring concepts may differ in their remote sensing requirements regarding areal coverage, spatial and temporal resolution, sensitivity and geometric accuracy. Also financial budgets limit the selection of sensors. Thus, combining differing assets into an integrated concept of remote sensing contributes to solving these issues.

Using remote sensing in support of environmental management: A framework for selecting products, algorithms and methods.

PubMed

de Klerk, Helen M; Gilbertson, Jason; Lück-Vogel, Melanie; Kemp, Jaco; Munch, Zahn

2016-11-01

Traditionally, to map environmental features using remote sensing, practitioners will use training data to develop models on various satellite data sets using a number of classification approaches and use test data to select a single 'best performer' from which the final map is made. We use a combination of an omission/commission plot to evaluate various results and compile a probability map based on consistently strong performing models across a range of standard accuracy measures. We suggest that this easy-to-use approach can be applied in any study using remote sensing to map natural features for management action. We demonstrate this approach using optical remote sensing products of different spatial and spectral resolution to map the endemic and threatened flora of quartz patches in the Knersvlakte, South Africa. Quartz patches can be mapped using either SPOT 5 (used due to its relatively fine spatial resolution) or Landsat8 imagery (used because it is freely accessible and has higher spectral resolution). Of the variety of classification algorithms available, we tested maximum likelihood and support vector machine, and applied these to raw spectral data, the first three PCA summaries of the data, and the standard normalised difference vegetation index. We found that there is no 'one size fits all' solution to the choice of a 'best fit' model (i.e. combination of classification algorithm or data sets), which is in agreement with the literature that classifier performance will vary with data properties. We feel this lends support to our suggestion that rather than the identification of a 'single best' model and a map based on this result alone, a probability map based on the range of consistently top performing models provides a rigorous solution to environmental mapping. Copyright © 2016 Elsevier Ltd. All rights reserved.

Combined Analysis of SENTINEL-1 and Rapideye Data for Improved Crop Type Classification: AN Early Season Approach for Rapeseed and Cereals

NASA Astrophysics Data System (ADS)

Lussem, U.; Hütt, C.; Waldhoff, G.

2016-06-01

Timely availability of crop acreage estimation is crucial for maintaining economic and ecological sustainability or modelling purposes. Remote sensing data has proven to be a reliable source for crop mapping and acreage estimation on parcel-level. However, when relying on a single source of remote sensing data, e.g. multispectral sensors like RapidEye or Landsat, several obstacles can hamper the desired outcome, for example cloud cover or haze. Another limitation may be a similarity in optical reflectance patterns of crops, especially in an early season approach by the end of March, early April. Usually, a reliable crop type map for winter-crops (winter wheat/rye, winter barley and rapeseed) in Central Europe can be obtained by using optical remote sensing data from late April to early May, given a full coverage of the study area and cloudless conditions. These prerequisites can often not be met. By integrating dual-polarimetric SAR-sensors with high temporal and spatial resolution, these limitations can be overcome. SAR-sensors are not influenced by clouds or haze and provide an additional source of information due to the signal-interaction with plant-architecture. The overall goal of this study is to investigate the contribution of Sentinel-1 SAR-data to regional crop type mapping for an early season map of disaggregated winter-crops for a subset of the Rur-Catchment in North Rhine-Westphalia (Germany). For this reason, RapidEye data and Sentinel-1 data are combined and the performance of Support Vector Machine and Maximum Likelihood classifiers are compared. Our results show that a combination of Sentinel-1 and RapidEye is a promising approach for most crops, but consideration of phenology for data selection can improve results. Thus the combination of optical and radar remote sensing data indicates advances for crop-type classification, especially when optical data availability is limited.

Hyperspectral and Radar Airborne Imagery over Controlled Release of Oil at Sea.

PubMed

Angelliaume, Sébastien; Ceamanos, Xavier; Viallefont-Robinet, Françoise; Baqué, Rémi; Déliot, Philippe; Miegebielle, Véronique

2017-08-02

Remote sensing techniques are commonly used by Oil and Gas companies to monitor hydrocarbon on the ocean surface. The interest lies not only in exploration but also in the monitoring of the maritime environment. Occurrence of natural seeps on the sea surface is a key indicator of the presence of mature source rock in the subsurface. These natural seeps, as well as the oil slicks, are commonly detected using radar sensors but the addition of optical imagery can deliver extra information such as thickness and composition of the detected oil, which is critical for both exploration purposes and efficient cleanup operations. Today, state-of-the-art approaches combine multiple data collected by optical and radar sensors embedded on-board different airborne and spaceborne platforms, to ensure wide spatial coverage and high frequency revisit time. Multi-wavelength imaging system may create a breakthrough in remote sensing applications, but it requires adapted processing techniques that need to be developed. To explore performances offered by multi-wavelength radar and optical sensors for oil slick monitoring, remote sensing data have been collected by SETHI (Système Expérimental de Télédection Hyperfréquence Imageur), the airborne system developed by ONERA (the French Aerospace Lab), during an oil spill cleanup exercise carried out in 2015 in the North Sea, Europe. The uniqueness of this dataset lies in its high spatial resolution, low noise level and quasi-simultaneous acquisitions of different part of the EM spectrum. Specific processing techniques have been developed to extract meaningful information associated with oil-covered sea surface. Analysis of this unique and rich dataset demonstrates that remote sensing imagery, collected in both optical and microwave domains, allows estimating slick surface properties such as the age of the emulsion released at sea, the spatial abundance of oil and the relative concentration of hydrocarbons remaining on the sea surface.

Hyperspectral and Radar Airborne Imagery over Controlled Release of Oil at Sea

PubMed Central

Angelliaume, Sébastien; Ceamanos, Xavier; Viallefont-Robinet, Françoise; Baqué, Rémi; Déliot, Philippe

2017-01-01

Remote sensing techniques are commonly used by Oil and Gas companies to monitor hydrocarbon on the ocean surface. The interest lies not only in exploration but also in the monitoring of the maritime environment. Occurrence of natural seeps on the sea surface is a key indicator of the presence of mature source rock in the subsurface. These natural seeps, as well as the oil slicks, are commonly detected using radar sensors but the addition of optical imagery can deliver extra information such as thickness and composition of the detected oil, which is critical for both exploration purposes and efficient cleanup operations. Today, state-of-the-art approaches combine multiple data collected by optical and radar sensors embedded on-board different airborne and spaceborne platforms, to ensure wide spatial coverage and high frequency revisit time. Multi-wavelength imaging system may create a breakthrough in remote sensing applications, but it requires adapted processing techniques that need to be developed. To explore performances offered by multi-wavelength radar and optical sensors for oil slick monitoring, remote sensing data have been collected by SETHI (Système Expérimental de Télédection Hyperfréquence Imageur), the airborne system developed by ONERA (the French Aerospace Lab), during an oil spill cleanup exercise carried out in 2015 in the North Sea, Europe. The uniqueness of this dataset lies in its high spatial resolution, low noise level and quasi-simultaneous acquisitions of different part of the EM spectrum. Specific processing techniques have been developed to extract meaningful information associated with oil-covered sea surface. Analysis of this unique and rich dataset demonstrates that remote sensing imagery, collected in both optical and microwave domains, allows estimating slick surface properties such as the age of the emulsion released at sea, the spatial abundance of oil and the relative concentration of hydrocarbons remaining on the sea surface. PMID:28767059

Impact of plant-soil feedback on plant traits at field scale, testing the use of UAV-based optical sensors

NASA Astrophysics Data System (ADS)

De Deyn, Gerlinde B.; van der Meij, Bob; Barel, Janna M.; Suomalainen, Juha; Kooistra, Lammert

2017-04-01

Plant responses to biotic and abiotic legacies left in soil by preceding plants is known as plant-soil feedback (PSF). PSF is an important mechanism to explain plant community dynamics and plant performance in natural and agricultural systems. However, most PSF studies are short-term and small-scale due to practical constraints for field scale quantification of PSF effects, yet field experiments are warranted to asses actual PSF effects under less controlled conditions. Here we used Unmanned Aerial Vehicle (UAV)-based optical sensors to test whether PSF effects on plant traits can be quantified remotely. We established a randomized agro-ecological field experiment in which six different cover crop species and species combinations from three different plant families (Poaceae, Fabaceae, Brassicaceae) were grown. The feedback effects on plant traits were tested in oat (Avena sativa) by quantifying the cover crop legacy effects on key plant traits: height, fresh biomass, nitrogen content and leaf chlorophyll content. Prior to destructive sampling, hyperspectral data was acquired and used for calibration and independent validation of regression models to retrieve plant traits from optical data. Subsequently, for each trait the model with highest precision and accuracy was selected. We used the hyperspectral analyses to predict the directly measured plant height (RMSE= 5.12 cm, R2= 0.79), chlorophyll content (RMSE= 0.11 g m-2, R2= 0.80), N-content (RMSE= 1.94 g m-2, R2= 0.68), and fresh biomass (RMSE= 0.72 kg m-2, R2=0.56). Overall the PSF effects of the different cover crop treatments based on the remote sensing data matched the results based on in situ measurements. The average oat canopy was tallest and its leaf chlorophyll content highest in response to legacy of Vicia sativa monocultures (100 cm, 0.95 g m-2, respectively) and in mixture with Raphanus sativus (100 cm, 1.09 g m-2, respectively), while the lowest values (76 cm, 0.41 g m-2, respectively) were found in response to legacy of Lolium perenne monoculture, and intermediate responses to the legacy of the other treatments. We show that PSF effects in the field occur and alter several important plant traits that can be sensed remotely and quantified in a non-destructive way using UAV-based optical sensors; these can be repeated over the growing season to increase temporal resolution. Remote sensing thereby offers great potential for studying PSF effects at field scale and relevant spatial-temporal resolutions which will facilitate the elucidation of the underlying mechanisms.

Evaluating the potential of image fusion of multispectral and radar remote sensing data for the assessment of water body structure

NASA Astrophysics Data System (ADS)

Hunger, Sebastian; Karrasch, Pierre; Wessollek, Christine

2016-10-01

The European Water Framework Directive (Directive 2000/60/EC) is a mandatory agreement that guides the member states of the European Union in the field of water policy to fulfill the requirements for reaching the aim of the good ecological status of water bodies. In the last years several workflows and methods were developed to determine and evaluate the characteristics and the status of the water bodies. Due to their area measurements remote sensing methods are a promising approach to constitute a substantial additional value. With increasing availability of optical and radar remote sensing data the development of new methods to extract information from both types of remote sensing data is still in progress. Since most limitations of these data sets do not agree the fusion of both data sets to gain data with higher spectral resolution features the potential to obtain additional information in contrast to the separate processing of the data. Based thereupon this study shall research the potential of multispectral and radar remote sensing data and the potential of their fusion for the assessment of the parameters of water body structure. Due to the medium spatial resolution of the freely available multispectral Sentinel-2 data sets especially the surroundings of the water bodies and their land use are part of this study. SAR data is provided by the Sentinel-1 satellite. Different image fusion methods are tested and the combined products of both data sets are evaluated afterwards. The evaluation of the single data sets and the fused data sets is performed by means of a maximum-likelihood classification and several statistical measurements. The results indicate that the combined use of different remote sensing data sets can have an added value.

Remote Sensing of Cloud, Aerosol, and Land Properties from MODIS: Applications to the East Asia Region

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Chu, D. Allen; Moody, Eric G.

2001-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation we review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations to the east Asian region in Spring 2001. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 degree (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented.

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Menzel, W. Paul; Kaufman, Yoram J.; Ackerman, Steven A.; Tanre, Didier; Gao, Bo-Cai

2001-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar orbiting, sun-synchronous, platform at an altitude of 705 kilometers, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 meters (2 bands), 500 meters (5 bands) and 1000 meters (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation we review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 degree (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented.

The Large UV/Optical/Infrared Surveyor (LUVOIR): Decadal Mission concept design update

NASA Astrophysics Data System (ADS)

Bolcar, Matthew R.; Aloezos, Steve; Bly, Vincent T.; Collins, Christine; Crooke, Julie; Dressing, Courtney D.; Fantano, Lou; Feinberg, Lee D.; France, Kevin; Gochar, Gene; Gong, Qian; Hylan, Jason E.; Jones, Andrew; Linares, Irving; Postman, Marc; Pueyo, Laurent; Roberge, Aki; Sacks, Lia; Tompkins, Steven; West, Garrett

2017-09-01

In preparation for the 2020 Astrophysics Decadal Survey, NASA has commissioned the study of four large mission concepts, including the Large Ultraviolet / Optical / Infrared (LUVOIR) Surveyor. The LUVOIR Science and Technology Definition Team (STDT) has identified a broad range of science objectives including the direct imaging and spectral characterization of habitable exoplanets around sun-like stars, the study of galaxy formation and evolution, the epoch of reionization, star and planet formation, and the remote sensing of Solar System bodies. NASA's Goddard Space Flight Center (GSFC) is providing the design and engineering support to develop executable and feasible mission concepts that are capable of the identified science objectives. We present an update on the first of two architectures being studied: a 15- meter-diameter segmented-aperture telescope with a suite of serviceable instruments operating over a range of wavelengths between 100 nm to 2.5 μm. Four instruments are being developed for this architecture: an optical / near-infrared coronagraph capable of 10-10 contrast at inner working angles as small as 2 λ/D the LUVOIR UV Multi-object Spectrograph (LUMOS), which will provide low- and medium-resolution UV (100 - 400 nm) multi-object imaging spectroscopy in addition to far-UV imaging; the High Definition Imager (HDI), a high-resolution wide-field-of-view NUV-Optical-IR imager; and a UV spectro-polarimeter being contributed by Centre National d'Etudes Spatiales (CNES). A fifth instrument, a multi-resolution optical-NIR spectrograph, is planned as part of a second architecture to be studied in late 2017.

Formation Flying: The Future of Remote Sensing from Space

NASA Technical Reports Server (NTRS)

Leitner, Jesse

2004-01-01

Over the next two decades a revolution is likely to occur in how remote sensing of Earth, other planets or bodies, and a range of phenomena in the universe is performed from space. In particular, current launch vehicle fairing volume and mass constraints will continue to restrict the size of monolithic telescope apertures which can be launched to little or no greater size than that of the Hubble Space Telescope, the largest aperture currently flying in space. Systems under formulation today, such as the James Webb Space Telescope will be able to increase aperture size and, hence, imaging resolution, by deploying segmented optics. However, this approach is limited as well, by our ability to control such segments to optical tolerances over long distances with highly uncertain structural dynamics connecting them. Consequently, for orders of magnitude improved resolution as required for imaging black holes, imaging planets, or performing asteroseismology, the only viable approach will be to fly a collection of spacecraft in formation to synthesize a virtual segmented telescope or interferometer with very large baselines. This paper provides some basic definitions in the area of formation flying, describes some of the strategic science missions planned in the National Aeronautics and Space Administration, and identifies some of the critical technologies needed to enable some of the most challenging space missions ever conceived which have realistic hopes of flying.

Research on application of photoelectric rotary encoder in space optical remote sensor

NASA Astrophysics Data System (ADS)

Zheng, Jun; Qi, Shao-fan; Wang, Yuan-yuan; Zhang, Zhan-dong

2016-11-01

For space optical remote sensor, especially wide swath detecting sensor, the focusing control system for the focal plane should be well designed to obtain the best image quality. The crucial part of this system is the measuring instrument. For previous implements, the potentiometer, which is essentially a voltage divider, is usually introduced to conduct the position in feedback closed-loop control process system. However, the performances of both electro-mechanical and digital potentiometers is limited in accuracy, temperature coefficients, and scale range. To have a better performance of focal plane moving detection, this article presents a new measuring implement with photoelectric rotary encoder, which consists of the photoelectric conversion system and the signal process system. In this novel focusing control system, the photoelectric conversion system is fixed on main axis, which can transform the angle information into a certain analog signal. Through the signal process system, after analog-to-digital converting and data format processing of the certain analog signal, the focusing control system can receive the digital precision angle position which can be used to deduct the current moving position of the focal plane. For utilization of space optical remote sensor in aerospace areas, the reliability design of photoelectric rotary encoder system should be considered with highest priority. As mentioned above, this photoelectric digital precision angle measurement device is well designed for this real-time control and dynamic measurement system, because its characters of high resolution, high accuracy, long endurance, and easy to maintain.

On the feasibility of comprehensive high-resolution 3D remote dosimetry

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

Juang, Titania; Grant, Ryan; Adamovics, John

2014-07-15

Purpose: This study investigates the feasibility of remote high-resolution 3D dosimetry with the PRESAGE®/Optical-CT system. In remote dosimetry, dosimeters are shipped out from a central base institution to a remote institution for irradiation, then shipped back to the base institution for subsequent readout and analysis. Methods: Two nominally identical optical-CT scanners for 3D dosimetry were constructed and placed at the base (Duke University) and remote (Radiological Physics Center) institutions. Two formulations of PRESAGE® (SS1, SS2) radiochromic dosimeters were investigated. Higher sensitivity was expected in SS1, which had higher initiator content (0.25% bromotrichloromethane), while greater temporal stability was expected in SS2.more » Four unirradiated PRESAGE® dosimeters (two per formulation, cylindrical dimensions 11 cm diameter, 8.5–9.5 cm length) were imaged at the base institution, then shipped to the remote institution for planning and irradiation. Each dosimeter was irradiated with the same simple treatment plan: an isocentric 3-field “cross” arrangement of 4 × 4 cm open 6 MV beams configured as parallel opposed laterals with an anterior beam. This simple plan was amenable to accurate and repeatable setup, as well as accurate dose modeling by a commissioned treatment planning system (Pinnacle). After irradiation and subsequent (within 1 h) optical-CT readout at the remote institution, the dosimeters were shipped back to the base institution for remote dosimetry readout 3 days postirradiation. Measured on-site and remote relative 3D dose distributions were registered to the Pinnacle dose calculation, which served as the reference distribution for 3D gamma calculations with passing criteria of 5%/2 mm, 3%/3 mm, and 3%/2 mm with a 10% dose threshold. Gamma passing rates, dose profiles, and color-maps were all used to assess and compare the performance of both PRESAGE® formulations for remote dosimetry. Results: The best agreements between the Pinnacle plan and dosimeter readout were observed in PRESAGE® formulation SS2. Under 3%/3 mm 3D gamma passing criteria, passing rates were 91.5% ± 3.6% (SS1) and 97.4% ± 2.2% (SS2) for immediate on-site dosimetry, 96.7% ± 2.4% (SS1) and 97.6% ± 0.6% (SS2) for remote dosimetry. These passing rates are well within TG119 recommendations (88%–90% passing). Under the more stringent criteria of 3%/2 mm, there is a pronounced difference [8.0 percentage points (pp)] between SS1 formulation passing rates for immediate and remote dosimetry while the SS2 formulation maintains both higher passing rates and consistency between immediate and remote results (differences ≤ 1.2 pp) at all metrics. Both PRESAGE® formulations under study maintained high linearity of dose response (R{sup 2} > 0.996) for 1–8 Gy over 14 days with response slope consistency within 4.9% (SS1) and 6.6% (SS2), and a relative dose distribution that remained stable over time was demonstrated in the SS2 dosimeters. Conclusions: Remote 3D dosimetry was shown to be feasible with a PRESAGE® dosimeter formulation (SS2) that exhibited relative temporal stability and high accuracy when read off-site 3 days postirradiation. Characterization of the SS2 dose response demonstrated linearity (R{sup 2} > 0.998) over 14 days and suggests accurate readout over longer periods of time would be possible. This result provides a foundation for future investigations using remote dosimetry to study the accuracy of advanced radiation treatments. Further work is planned to characterize dosimeter reproducibility and dose response over longer periods of time.« less

Effect of a timebase mismatch in two-way optical frequency transfer

NASA Astrophysics Data System (ADS)

Tampellini, Anna; Clivati, Cecilia; Levi, Filippo; Mura, Alberto; Calonico, Davide

2017-12-01

Two-way frequency transfer on optical fibers is a powerful technique for the comparison of distant clocks over long and ultra-long hauls. In contrast to traditional Doppler noise cancellation, it is capable of sustaining higher link attenuation, mitigating the need of optical amplification and regeneration and thus reducing the setup complexity. We investigate the ultimate limitations of the two-way approach on a 300 km multiplexed fiber haul, considering fully independent setups and acquisition systems at the two link ends. We derive a theoretical model to predict the performance deterioration due to a bad synchronisation of the measurements, which is confirmed by experimental results. This study demonstrates that two-way optical frequency transfer is a reliable and performing technique, capable of sustaining remote clocks comparisons at the 10-19 resolution, and is relevant for the development of a fiber network of continental scale for frequency metrology in Europe.

Passive optical remote sensing of Congo River bathymetry using Landsat

NASA Astrophysics Data System (ADS)

Ache Rocha Lopes, V.; Trigg, M. A.; O'Loughlin, F.; Laraque, A.

2014-12-01

While there have been notable advances in deriving river characteristics such as width, using satellite remote sensing datasets, deriving river bathymetry remains a significant challenge. Bathymetry is fundamental to hydrodynamic modelling of river systems and being able to estimate this parameter remotely would be of great benefit, especially when attempting to model hard to access areas where the collection of field data is difficult. One such region is the Congo Basin, where due to past political instability and large scale there are few studies that characterise river bathymetry. In this study we test whether it is possible to use passive optical remote sensing to estimate the depth of the Congo River using Landsat 8 imagery in the region around Malebo Pool, located just upstream of the Kinshasa gauging station. Methods of estimating bathymetry using remotely sensed datasets have been used extensively for coastal regions and now more recently have been demonstrated as feasible for optically shallow rivers. Previous river bathymetry studies have focused on shallow rivers and have generally used aerial imagery with a finer spatial resolution than Landsat. While the Congo River has relatively low suspended sediment concentration values the application of passive bathymetry estimation to a river of this scale has not been attempted before. Three different analysis methods are tested in this study: 1) a single band algorithm; 2) a log ratio method; and 3) a linear transform method. All three methods require depth data for calibration and in this study area bathymetry measurements are available for three cross-sections resulting in approximately 300 in-situ measurements of depth, which are used in the calibration and validation. The performance of each method is assessed, allowing the feasibility of passive depth measurement in the Congo River to be determined. Considering the scarcity of in-situ bathymetry measurements on the Congo River, even an approximate estimate of depths from these methods will be of considerable value in its hydraulic characterisation.

Object-Based Change Detection Using High-Resolution Remotely Sensed Data and GIS

NASA Astrophysics Data System (ADS)

Sofina, N.; Ehlers, M.

2012-08-01

High resolution remotely sensed images provide current, detailed, and accurate information for large areas of the earth surface which can be used for change detection analyses. Conventional methods of image processing permit detection of changes by comparing remotely sensed multitemporal images. However, for performing a successful analysis it is desirable to take images from the same sensor which should be acquired at the same time of season, at the same time of a day, and - for electro-optical sensors - in cloudless conditions. Thus, a change detection analysis could be problematic especially for sudden catastrophic events. A promising alternative is the use of vector-based maps containing information about the original urban layout which can be related to a single image obtained after the catastrophe. The paper describes a methodology for an object-based search of destroyed buildings as a consequence of a natural or man-made catastrophe (e.g., earthquakes, flooding, civil war). The analysis is based on remotely sensed and vector GIS data. It includes three main steps: (i) generation of features describing the state of buildings; (ii) classification of building conditions; and (iii) data import into a GIS. One of the proposed features is a newly developed 'Detected Part of Contour' (DPC). Additionally, several features based on the analysis of textural information corresponding to the investigated vector objects are calculated. The method is applied to remotely sensed images of areas that have been subjected to an earthquake. The results show the high reliability of the DPC feature as an indicator for change.

Coherent dual-frequency lidar system design for distance and speed measurements

NASA Astrophysics Data System (ADS)

Zheng, Xingyuan; Zhao, Changming; Zhang, Haiyang; Zheng, Zheng; Yang, Hongzhi

2018-01-01

Lidars have a wide range of applications in military detection and civilian remote sensing. Coherent Dual-Frequency Lidar (CDFL) is a new concept of laser radar that is using electrical coherence instead of optical coherence. It uses laser with two coherent frequency components as transmitting wave. The method is based on the use of an optically-carried radio frequency (RF) signal, which is the frequency difference between the two components, which is specially designed for distance and speed measurements. It not only ensures the system has the characteristics of high spatial resolution, high ranging and velocity precision of laser radar, but also can use mature signal processing technology of microwave radar, and it is a research direction that attracts more concern in recent years. A CDFL detection system is constructed and field experiment is carried out. In the system, a narrow linewidth fiber laser with a wavelength of 1064nm is adopted. The dual-frequency laser with frequency difference of 200MHz and 200.6MHz is obtained by acousto-optic frequency shift and recombination. The maximum output power of dual frequency laser is 200mW. The receiver consists of all-fiber balanced InGaAs photo-detector and homemade analog signal processing board. The experimental results show that the distance resolution and velocity resolution of the system are 0.1m and 0.1m/s separately when the working distance is greater than 200m, and the spatial resolution is 0.5mrad.

High-resolution flying-PIV with optical fiber laser delivery

NASA Astrophysics Data System (ADS)

Weichselbaum, Noah A.; André, Matthieu A.; Rahimi-Abkenar, Morteza; Manzari, Majid T.; Bardet, Philippe M.

2016-05-01

Implementation of non-intrusive optical measurement techniques, such as particle image velocimetry (PIV), in harsh environments requires specialized techniques for introducing controlled laser sheets to the region of interest. Large earthquake shake tables are a particularly challenging environment. Lasers must be mounted away from the table, and the laser sheet has to be delivered precisely and stably to the measurement station. Here, high-power multi-mode step-index fiber optics enable introduction of light from an Nd:YLF pulsed laser to a remote test section. Such lasers are suitable for coupling to optical fibers, which presents a portable, flexible, and safe manner to deliver a PIV light sheet. Best practices for their implementation are reviewed. Particular attention is focused on obtaining a collimated beam of acceptable quality at the output of the fiber. To achieve high spatial resolution, the PIV camera is directly mounted on the moving shake table with care to minimize its vibrations. A special arrangement of PIV planes is deployed for precise in-situ PIV alignment and to monitor and account for residual structure vibrations and beam wandering. The design of the instruments is detailed. Here, an experimental facility for the study of nuclear fuel bundle response to seismic forcing near prototypical conditions is instrumented. Only through integration of a high-resolution flying-PIV system can velocity fields be acquired. Data indicate that in the presence of a mean axial flow, a secondary oscillatory flow develops as the bundle oscillates. Instantaneous, phase-averaged, and fluctuating velocity fields illustrate this phenomenon.

Evaluating the Impact 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, R. K.; Domke, G. M.; Russell, M.; Woodall, C. W.

2017-12-01

Landsat data have been widely used to support strategic forest inventory and management decisions despite the limited success of passive optical remote sensing for accurate estimation of aboveground biomass (AGB). The archive of publicly available Landsat data, available at 30-m spatial resolutions since 1984, has been a valuable resource for cost-effective large-area estimation of AGB to inform national requirements such as for the US national greenhouse gas inventory (NGHGI). In addition, other optical satellite data such as MODIS imagery of wider spatial coverage and higher temporal resolution are enriching the domain of spatial predictors for regional scale mapping of AGB. Because NGHGIs require national scale AGB information and there are tradeoffs in the prediction accuracy versus operational efficiency of Landsat, this study evaluated the impact of various resolutions of Landsat predictors on the accuracy of regional AGB models across three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We used recent national forest inventory (NFI) data with numerous Landsat-derived predictors at ten different spatial resolutions ranging from 30 to 1000 m to understand the optimal spatial resolution of the optical data for enhanced spatial inventory of AGB for NGHGI reporting. Ten generic spatial models at different spatial resolutions were developed for all sites and large-area estimates were evaluated (i) at the county-level against the independent designed-based estimates via the US NFI Evalidator tool and (ii) within a large number of strips ( 1 km wide) predicted via LiDAR metrics at a high spatial resolution. The county-level estimates by the Evalidator and Landsat models were statistically equivalent and produced coefficients of determination (R2) above 0.85 that varied with sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of decreasing resolutions. The Landsat-based total AGB estimates within the strips against the total AGB obtained using LiDAR metrics did not differ significantly and were within ±15 Mg/ha for each of the sites. We conclude that the optical satellite data at resolutions up to 1000 m provide acceptable accuracy for the US' NGHGI.

NIAC Phase II Orbiting Rainbows: Future Space Imaging with Granular Systems

NASA Technical Reports Server (NTRS)

Quadrelli, Marco B.; Basinger, Scott; Arumugam, Darmindra; Swartzlander, Grover

2017-01-01

Inspired by the light scattering and focusing properties of distributed optical assemblies in Nature, such as rainbows and aerosols, and by recent laboratory successes in optical trapping and manipulation, we propose a unique combination of space optics and autonomous robotic system technology, to enable a new vision of space system architecture with applications to ultra-lightweight space optics and, ultimately, in-situ space system fabrication. Typically, the cost of an optical system is driven by the size and mass of the primary aperture. The ideal system is a cloud of spatially disordered dust-like objects that can be optically manipulated: it is highly reconfigurable, fault-tolerant, and allows very large aperture sizes at low cost. This new concept is based on recent understandings in the physics of optical manipulation of small particles in the laboratory and the engineering of distributed ensembles of spacecraft swarms to shape an orbiting cloud of micron-sized objects. In the same way that optical tweezers have revolutionized micro- and nano-manipulation of objects, our breakthrough concept will enable new large scale NASA mission applications and develop new technology in the areas of Astrophysical Imaging Systems and Remote Sensing because the cloud can operate as an adaptive optical imaging sensor. While achieving the feasibility of constructing one single aperture out of the cloud is the main topic of this work, it is clear that multiple orbiting aerosol lenses could also combine their power to synthesize a much larger aperture in space to enable challenging goals such as exo-planet detection. Furthermore, this effort could establish feasibility of key issues related to material properties, remote manipulation, and autonomy characteristics of cloud in orbit. There are several types of endeavors (science missions) that could be enabled by this type of approach, i.e. it can enable new astrophysical imaging systems, exo-planet search, large apertures allow for unprecedented high resolution to discern continents and important features of other planets, hyperspectral imaging, adaptive systems, spectroscopy imaging through limb, and stable optical systems from Lagrange-points. Furthermore, future micro-miniaturization might hold promise of a further extension of our dust aperture concept to other more exciting smart dust concepts with other associated capabilities. Our objective in Phase II was to experimentally and numerically investigate how to optically manipulate and maintain the shape of an orbiting cloud of dust-like matter so that it can function as an adaptable ultra-lightweight surface. Our solution is based on the aperture being an engineered granular medium, instead of a conventional monolithic aperture. This allows building of apertures at a reduced cost, enables extremely fault-tolerant apertures that cannot otherwise be made, and directly enables classes of missions for exoplanet detection based on Fourier spectroscopy with tight angular resolution and innovative radar systems for remote sensing. In this task, we have examined the advanced feasibility of a crosscutting concept that contributes new technological approaches for space imaging systems, autonomous systems, and space applications of optical manipulation. The proposed investigation has matured the concept that we started in Phase I to TRL 3, identifying technology gaps and candidate system architectures for the space-borne cloud as an aperture.

Monitoring terrestrial dissolved organic carbon export at land-water interfaces using remote sensing

NASA Astrophysics Data System (ADS)

Yu, Q.; Li, J.; Tian, Y. Q.

2017-12-01

Carbon flux from land to oceans and lakes is a crucial component of carbon cycling. However, this lateral carbon flow at land-water interface is often neglected in the terrestrial carbon cycle budget, mainly because observations of the carbon dynamics are very limited. Monitoring CDOM/DOC dynamics using remote sensing and assessing DOC export from land to water remains a challenge. Current CDOM retrieval algorithms in the field of ocean color are not simply applicable to inland aquatic ecosystems since they were developed for coarse resolution ocean-viewing imagery and less complex water types in open-sea. We developed a new semi-analytical algorithm, called SBOP (Shallow water Bio-Optical Properties algorithm) to adapt to shallow inland waters. SBOP was first developed and calibrated based on in situ hyperspectral radiometer data. Then we applied it to the Landsat-8 OLI images and evaluated the effectiveness of the multispectral images on inversion of CDOM absorption based on our field sampling at the Saginaw Bay in the Lake Huron. The algorithm performances (RMSE = 0.17 and R2 = 0.87 in the Saginaw Bay; R2 = 0.80 in the northeastern US lakes) is promising and we conclude the CDOM absorption can be derived from Landsat-8 OLI image in both optically deep and optically shallow waters with high accuracy. Our method addressed challenges on employing appropriate atmospheric correction, determining bottom reflectance influence for shallow waters, and improving for bio-optical properties retrieval, as well as adapting to both hyperspectral and the multispectral remote sensing imagery. Over 100 Landsat-8 images in Lake Huron, northeastern US lakes, and the Arctic major rivers were processed to understand the CDOM spatio-temporal dynamics and its associated driving factors.

Millimeter-wave imaging diagnostics systems on the EAST tokamak (invited)

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

Zhu, Y. L.; Xie, J. L., E-mail: jlxie@ustc.edu.cn; Yu, C. X.

2016-11-15

Millimeter-wave imaging diagnostics, with large poloidal span and wide radial range, have been developed on the EAST tokamak for visualization of 2D electron temperature and density fluctuations. A 384 channel (24 poloidal × 16 radial) Electron Cyclotron Emission Imaging (ECEI) system in F-band (90-140 GHz) was installed on the EAST tokamak in 2012 to provide 2D electron temperature fluctuation images with high spatial and temporal resolution. A co-located Microwave Imaging Reflectometry (MIR) will be installed for imaging of density fluctuations by December 2016. This “4th generation” MIR system has eight independent frequency illumination beams in W-band (75-110 GHz) driven bymore » fast tuning synthesizers and active multipliers. Both of these advanced millimeter-wave imaging diagnostic systems have applied the latest techniques. A novel design philosophy “general optics structure” has been employed for the design of the ECEI and MIR receiver optics with large aperture. The extended radial and poloidal coverage of ECEI on EAST is made possible by innovations in the design of front-end optics. The front-end optical structures of the two imaging diagnostics, ECEI and MIR, have been integrated into a compact system, including the ECEI receiver and MIR transmitter and receiver. Two imaging systems share the same mid-plane port for simultaneous, co-located 2D fluctuation measurements of electron density and temperature. An intelligent remote-control is utilized in the MIR electronics systems to maintain focusing at the desired radial region even with density variations by remotely tuning the probe frequencies in about 200 μs. A similar intelligent technique has also been applied on the ECEI IF system, with remote configuration of the attenuations for each channel.« less

Millimeter-wave imaging diagnostics systems on the EAST tokamak (invited)

NASA Astrophysics Data System (ADS)

Zhu, Y. L.; Xie, J. L.; Yu, C. X.; Zhao, Z. L.; Gao, B. X.; Chen, D. X.; Liu, W. D.; Liao, W.; Qu, C. M.; Luo, C.; Hu, X.; Spear, A. G.; Luhmann, N. C.; Domier, C. W.; Chen, M.; Ren, X.; Tobias, B. J.

2016-11-01

Millimeter-wave imaging diagnostics, with large poloidal span and wide radial range, have been developed on the EAST tokamak for visualization of 2D electron temperature and density fluctuations. A 384 channel (24 poloidal × 16 radial) Electron Cyclotron Emission Imaging (ECEI) system in F-band (90-140 GHz) was installed on the EAST tokamak in 2012 to provide 2D electron temperature fluctuation images with high spatial and temporal resolution. A co-located Microwave Imaging Reflectometry (MIR) will be installed for imaging of density fluctuations by December 2016. This "4th generation" MIR system has eight independent frequency illumination beams in W-band (75-110 GHz) driven by fast tuning synthesizers and active multipliers. Both of these advanced millimeter-wave imaging diagnostic systems have applied the latest techniques. A novel design philosophy "general optics structure" has been employed for the design of the ECEI and MIR receiver optics with large aperture. The extended radial and poloidal coverage of ECEI on EAST is made possible by innovations in the design of front-end optics. The front-end optical structures of the two imaging diagnostics, ECEI and MIR, have been integrated into a compact system, including the ECEI receiver and MIR transmitter and receiver. Two imaging systems share the same mid-plane port for simultaneous, co-located 2D fluctuation measurements of electron density and temperature. An intelligent remote-control is utilized in the MIR electronics systems to maintain focusing at the desired radial region even with density variations by remotely tuning the probe frequencies in about 200 μs. A similar intelligent technique has also been applied on the ECEI IF system, with remote configuration of the attenuations for each channel.

Remote Optical Control of an Optical Flip-Flop

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

Maywar, D.N.; Solomon, K.P.; Agrawal, G.P.

2007-11-01

We experimentally demonstrate control of a holding-beam–enabled optical flip-flop by means of optical signals that act in a remote fashion. These optical-control signals vary the holding-beam power by means of cross-gain modulation within a remotely located semiconductor optical amplifier (SOA). The power-modulated holding beam then travels through a resonant-type SOA, where flip-flop action occurs as the holding-beam power falls above and below the switching thresholds of the bistable hysteresis. Control is demonstrated using submilliwatt pulses whose wavelengths are not restricted to the vicinity of the holding beam. Benefits of remote control include the potential for controlling multiple flip-flops with amore » single pair of optical signals and for realizing all-optical control of any holding-beam–enabled flip-flop.« less

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.

Surface compositional variation on the comet 67P/Churyumov-Gerasimenko by OSIRIS data

NASA Astrophysics Data System (ADS)

Barucci, M. A.; Fornasier, S.; Feller, C.; Perna, D.; Hasselmann, H.; Deshapriya, J. D. P.; Fulchignoni, M.; Besse, S.; Sierks, H.; Forgia, F.; Lazzarin, M.; Pommerol, A.; Oklay, N.; Lara, L.; Scholten, F.; Preusker, F.; Leyrat, C.; Pajola, M.; Osiris-Rosetta Team

2015-10-01

Since the Rosetta mission arrived at the comet 67P/Churyumov-Gerasimenko (67/P C-G) on July 2014, the comet nucleus has been mapped by both OSIRIS (Optical, Spectroscopic, and Infrared Remote Imaging System, [1]) NAC (Narrow Angle Camera) and WAC (Wide Angle Camera) acquiring a huge quantity of surface's images at different wavelength bands, under variable illumination conditions and spatial resolution, and producing the most detailed maps at the highest spatial resolution of a comet nucleus surface.67/P C-G's nucleus shows an irregular bi-lobed shape of complex morphology with terrains showing intricate features [2, 3] and a heterogeneity surface at different scales.

The Effect of Remote Sensor Spatial Resolution in Monitoring U.S. Army Training Maneuver Sites

DTIC Science & Technology

1990-12-01

THE EFFECT OF REMOTE SENSOR SPATIAL RESOLUTION IN MONITORING U.S. ARMY...Multispectral Scanner with 6.5 meter spatial resolution provided the most effective digital data set for enhancing tank trails. However, this Airborne Scanner...primary objective of this research was to determine the capabilities and limitations of remote sensor systems having different spatial resolutions to

Multiple channel optical data acquisition system

DOEpatents

Fasching, G.E.; Goff, D.R.

1985-02-22

A multiple channel optical data acquisition system is provided in which a plurality of remote sensors monitoring specific process variable are interrogated by means of a single optical fiber connecting the remote station/sensors to a base station. The remote station/sensors derive all power from light transmitted through the fiber from the base station. Each station/sensor is individually accessed by means of a light modulated address code sent over the fiber. The remote station/sensors use a single light emitting diode to both send and receive light signals to communicate with the base station and provide power for the remote station. The system described can power at least 100 remote station/sensors over an optical fiber one mile in length.

A micro-vibration generated method for testing the imaging quality on ground of space remote sensing

NASA Astrophysics Data System (ADS)

Gu, Yingying; Wang, Li; Wu, Qingwen

2018-03-01

In this paper, a novel method is proposed, which can simulate satellite platform micro-vibration and test the impact of satellite micro-vibration on imaging quality of space optical remote sensor on ground. The method can generate micro-vibration of satellite platform in orbit from vibrational degrees of freedom, spectrum, magnitude, and coupling path. Experiment results show that the relative error of acceleration control is within 7%, in frequencies from 7Hz to 40Hz. Utilizing this method, the system level test about the micro-vibration impact on imaging quality of space optical remote sensor can be realized. This method will have an important applications in testing micro-vibration tolerance margin of optical remote sensor, verifying vibration isolation and suppression performance of optical remote sensor, exploring the principle of micro-vibration impact on imaging quality of optical remote sensor.

A clock network for geodesy and fundamental science

PubMed Central

Lisdat, C.; Grosche, G.; Quintin, N.; Shi, C.; Raupach, S.M.F.; Grebing, C.; Nicolodi, D.; Stefani, F.; Al-Masoudi, A.; Dörscher, S.; Häfner, S.; Robyr, J.-L.; Chiodo, N.; Bilicki, S.; Bookjans, E.; Koczwara, A.; Koke, S.; Kuhl, A.; Wiotte, F.; Meynadier, F.; Camisard, E.; Abgrall, M.; Lours, M.; Legero, T.; Schnatz, H.; Sterr, U.; Denker, H.; Chardonnet, C.; Le Coq, Y.; Santarelli, G.; Amy-Klein, A.; Le Targat, R.; Lodewyck, J.; Lopez, O; Pottie, P.-E.

2016-01-01

Leveraging the unrivalled performance of optical clocks as key tools for geo-science, for astronomy and for fundamental physics beyond the standard model requires comparing the frequency of distant optical clocks faithfully. Here, we report on the comparison and agreement of two strontium optical clocks at an uncertainty of 5 × 10−17 via a newly established phase-coherent frequency link connecting Paris and Braunschweig using 1,415 km of telecom fibre. The remote comparison is limited only by the instability and uncertainty of the strontium lattice clocks themselves, with negligible contributions from the optical frequency transfer. A fractional precision of 3 × 10−17 is reached after only 1,000 s averaging time, which is already 10 times better and more than four orders of magnitude faster than any previous long-distance clock comparison. The capability of performing high resolution international clock comparisons paves the way for a redefinition of the unit of time and an all-optical dissemination of the SI-second. PMID:27503795

A clock network for geodesy and fundamental science.

PubMed

Lisdat, C; Grosche, G; Quintin, N; Shi, C; Raupach, S M F; Grebing, C; Nicolodi, D; Stefani, F; Al-Masoudi, A; Dörscher, S; Häfner, S; Robyr, J-L; Chiodo, N; Bilicki, S; Bookjans, E; Koczwara, A; Koke, S; Kuhl, A; Wiotte, F; Meynadier, F; Camisard, E; Abgrall, M; Lours, M; Legero, T; Schnatz, H; Sterr, U; Denker, H; Chardonnet, C; Le Coq, Y; Santarelli, G; Amy-Klein, A; Le Targat, R; Lodewyck, J; Lopez, O; Pottie, P-E

2016-08-09

Leveraging the unrivalled performance of optical clocks as key tools for geo-science, for astronomy and for fundamental physics beyond the standard model requires comparing the frequency of distant optical clocks faithfully. Here, we report on the comparison and agreement of two strontium optical clocks at an uncertainty of 5 × 10(-17) via a newly established phase-coherent frequency link connecting Paris and Braunschweig using 1,415 km of telecom fibre. The remote comparison is limited only by the instability and uncertainty of the strontium lattice clocks themselves, with negligible contributions from the optical frequency transfer. A fractional precision of 3 × 10(-17) is reached after only 1,000 s averaging time, which is already 10 times better and more than four orders of magnitude faster than any previous long-distance clock comparison. The capability of performing high resolution international clock comparisons paves the way for a redefinition of the unit of time and an all-optical dissemination of the SI-second.

Temporal Data Fusion Approaches to Remote Sensing-Based Wetland Classification

NASA Astrophysics Data System (ADS)

Montgomery, Joshua S. M.

This thesis investigates the ecology of wetlands and associated classification in prairie and boreal environments of Alberta, Canada, using remote sensing technology to enhance classification of wetlands in the province. Objectives of the thesis are divided into two case studies, 1) examining how satellite borne Synthetic Aperture Radar (SAR), optical (RapidEye & SPOT) can be used to evaluate surface water trends in a prairie pothole environment (Shepard Slough); and 2) investigating a data fusion methodology combining SAR, optical and Lidar data to characterize wetland vegetation and surface water attributes in a boreal environment (Utikuma Regional Study Area (URSA)). Surface water extent and hydroperiod products were derived from SAR data, and validated using optical imagery with high accuracies (76-97% overall) for both case studies. High resolution Lidar Digital Elevation Models (DEM), Digital Surface Models (DSM), and Canopy Height Model (CHM) products provided the means for data fusion to extract riparian vegetation communities and surface water; producing model accuracies of (R2 0.90) for URSA, and RMSE of 0.2m to 0.7m at Shepard Slough when compared to field and optical validation data. Integration of Alberta and Canadian wetland classifications systems used to classify and determine economic value of wetlands into the methodology produced thematic maps relevant for policy and decision makers for potential wetland monitoring and policy development.

Quantitative retrieval of aerosol optical thickness from FY-2 VISSR data

NASA Astrophysics Data System (ADS)

Bai, Linyan; Xue, Yong; Cao, Chunxiang; Feng, Jianzhong; Zhang, Hao; Guang, Jie; Wang, Ying; Li, Yingjie; Mei, Linlu; Ai, Jianwen

2010-11-01

Atmospheric aerosol, as particulate matter suspended in the air, exists in a variety of forms such as dust, fume and mist. It deeply affects climate and land surface environment in both regional and global scales, and furthermore, lead to be hugely much influence on human health. For the sake of effectively monitoring it, many atmospheric aerosol observation networks are set up and provide associated informational services in the wide world, as well-known Aerosol robotic network (AERONET), Canadian Sunphotometer Network (AeroCan) and so forth. Given large-scale atmospheric aerosol monitoring, that satellite remote sensing data are used to inverse aerosol optical depth is one of available and effective approaches. Nowadays, special types of instruments aboard running satellites are applied to obtain related remote sensing data of retrieving atmospheric aerosol. However, atmospheric aerosol real-timely or near real-timely monitoring hasn't been accomplished. Nevertheless, retrievals, using Fengyun-2 VISSR data, are carried out and the above problem resolved to certain extent, especially over China. In this paper, the authors have developed a new retrieving model/mode to retrieve aerosol optical depth, using Fengyun-2 satellite data that were obtained by the VISSR aboard FY-2C and FY-2D. A series of the aerosol optical depth distribution maps with high time resolution were able to obtained, is helpful for understanding the forming mechanism, transport, influence and controlling approach of atmospheric aerosol.

DARLA: Data Assimilation and Remote Sensing for Littoral Applications

NASA Astrophysics Data System (ADS)

Jessup, A.; Holman, R. A.; Chickadel, C.; Elgar, S.; Farquharson, G.; Haller, M. C.; Kurapov, A. L.; Özkan-Haller, H. T.; Raubenheimer, B.; Thomson, J. M.

2012-12-01

DARLA is 5-year collaborative project that couples state-of-the-art remote sensing and in situ measurements with advanced data assimilation (DA) modeling to (a) evaluate and improve remote sensing retrieval algorithms for environmental parameters, (b) determine the extent to which remote sensing data can be used in place of in situ data in models, and (c) infer bathymetry for littoral environments by combining remotely-sensed parameters and data assimilation models. The project uses microwave, electro-optical, and infrared techniques to characterize the littoral ocean with a focus on wave and current parameters required for DA modeling. In conjunction with the RIVET (River and Inlets) Project, extensive in situ measurements provide ground truth for both the remote sensing retrieval algorithms and the DA modeling. Our goal is to use remote sensing to constrain data assimilation models of wave and circulation dynamics in a tidal inlet and surrounding beaches. We seek to improve environmental parameter estimation via remote sensing fusion, determine the success of using remote sensing data to drive DA models, and produce a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments. The objectives are to test the following three hypotheses: 1. Environmental parameter estimation using remote sensing techniques can be significantly improved by fusion of multiple sensor products. 2. Data assimilation models can be adequately constrained (i.e., forced or guided) with environmental parameters derived from remote sensing measurements. 3. Bathymetry on open beaches, river mouths, and at tidal inlets can be inferred from a combination of remotely-sensed parameters and data assimilation models. Our approach is to conduct a series of field experiments combining remote sensing and in situ measurements to investigate signature physics and to gather data for developing and testing DA models. A preliminary experiment conducted at the Field Research Facility at Duck, NC in September 2010 focused on assimilation of tower-based electo-optical, infrared, and radar measurements in predictions of longshore currents. Here we provide an overview of our contribution to the RIVET I experiment at New River Inlet, NC in May 2012. During the course of the 3-week measurement period, continuous tower-based remote sensing measurements were made using electro-optical, infrared, and radar techniques covering the nearshore zone and the inlet mouth. A total of 50 hours of airborne measurements were made using high-resolution infrared imagers and a customized along track interferometric synthetic aperture radar (ATI SAR). The airborne IR imagery provides kilometer-scale mapping of frontal features that evolve as the inlet flow interacts with the oceanic wave and current fields. The ATI SAR provides maps of the two-dimensional surface currents. Near-surface measurements of turbulent velocities and surface waves using SWIFT drifters, designed to measures near-surface properties relevant to remote sensing, complimented the extensive in situ measurements by RIVET investigators.

Remote sensing of aerosols in the Arctic for an evaluation of global climate model simulations

PubMed Central

Glantz, Paul; Bourassa, Adam; Herber, Andreas; Iversen, Trond; Karlsson, Johannes; Kirkevåg, Alf; Maturilli, Marion; Seland, Øyvind; Stebel, Kerstin; Struthers, Hamish; Tesche, Matthias; Thomason, Larry

2014-01-01

In this study Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua retrievals of aerosol optical thickness (AOT) at 555 nm are compared to Sun photometer measurements from Svalbard for a period of 9 years. For the 642 daily coincident measurements that were obtained, MODIS AOT generally varies within the predicted uncertainty of the retrieval over ocean (ΔAOT = ±0.03 ± 0.05 · AOT). The results from the remote sensing have been used to examine the accuracy in estimates of aerosol optical properties in the Arctic, generated by global climate models and from in situ measurements at the Zeppelin station, Svalbard. AOT simulated with the Norwegian Earth System Model/Community Atmosphere Model version 4 Oslo global climate model does not reproduce the observed seasonal variability of the Arctic aerosol. The model overestimates clear-sky AOT by nearly a factor of 2 for the background summer season, while tending to underestimate the values in the spring season. Furthermore, large differences in all-sky AOT of up to 1 order of magnitude are found for the Coupled Model Intercomparison Project phase 5 model ensemble for the spring and summer seasons. Large differences between satellite/ground-based remote sensing of AOT and AOT estimated from dry and humidified scattering coefficients are found for the subarctic marine boundary layer in summer. Key Points Remote sensing of AOT is very useful in validation of climate models PMID:25821664

Global cloud database from VIRS and MODIS for CERES

NASA Astrophysics Data System (ADS)

Minnis, Patrick; Young, David F.; Wielicki, Bruce A.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Heck, Patrick W.; Dong, Xiquan

2003-04-01

The NASA CERES Project has developed a combined radiation and cloud property dataset using the CERES scanners and matched spectral data from high-resolution imagers, the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The diurnal cycle can be well-characterized over most of the globe using the combinations of TRMM, Aqua, and Terra data. The cloud properties are derived from the imagers using state-of-the-art methods and include cloud fraction, height, optical depth, phase, effective particle size, emissivity, and ice or liquid water path. These cloud products are convolved into the matching CERES fields of view to provide simultaneous cloud and radiation data at an unprecedented accuracy. Results are available for at least 3 years of VIRS data and 1 year of Terra MODIS data. The various cloud products are compared with similar quantities from climatological sources and instantaneous active remote sensors. The cloud amounts are very similar to those from surface observer climatologies and are 6-7% less than those from a satellite-based climatology. Optical depths are 2-3 times smaller than those from the satellite climatology, but are within 5% of those from the surface remote sensing. Cloud droplet sizes and liquid water paths are within 10% of the surface results on average for stratus clouds. The VIRS and MODIS retrievals are very consistent with differences that usually can be explained by sampling, calibration, or resolution differences. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters. Part 1; Equivalent Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, Galina; DaSilva, Arlindo M.; Norris, Peter M.; Platnick, Steven E.

2013-01-01

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

2013-01-01

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

Fiber-optic apparatus and method for measurement of luminescence and raman scattering

DOEpatents

Myrick, Michael L.; Angel, Stanley M.

1993-01-01

A dual fiber forward scattering optrode for Raman spectroscopy with the remote ends of the fibers in opposed, spaced relationship to each other to form a analyte sampling space therebetween and the method of measuring Raman spectra utilizing same. One optical fiber is for sending an exciting signal to the remote sampling space and, at its remote end, has a collimating microlens and an optical filter for filtering out background emissions generated in the fiber. The other optical fiber is for collecting the Raman scattering signal at the remote sampling space and, at its remote end, has a collimating microlens and an optical filter to prevent the exciting signal from the exciting fiber from entering the collection fiber and to thereby prevent the generation of background emissions in the collecting fiber.

A mobile system for active otpical pollution monitoring

NASA Technical Reports Server (NTRS)

Sunesson, A.; Edner, H.; Svanberg, S.; Uneus, L.; Wendt, W.; Fredriksson, K.

1986-01-01

The remote monitoring of atmospheric pollutants can now be performed in several ways. Laser radar techniques have proven their ability to reveal the spatial distribution of different species or particles. Classical optical techniques can also be used, but yield the average concentration over a given path and hence no range resolution. One such technique is Differential Optical Absorption Spectroscopy, DOAS. Such schemes can be used to monitor paths that a preliminary lidar investigation has shown to be of interest. Having previously had access to a mobile lidar system, a new system has been completed. The construction builds on experience from using the other system and it is meant to be more of a mobile optical laboratory than just a lidar system. A complete system description is given along with some preliminary usage. Future uses are contemplated.

Optical Techniques for the Remote Detection of Biological Aerosols

DTIC Science & Technology

1974-08-01

1) Laboratory exneriments (2) Remote detection experiments. In the first phase , the optical characteristics of several selected biological...the-art optical sensor system. The estimates were favorable, and a second research phase was initiated. Remote detection experiments were conducted...that of phase fluorometry. The fluorescence is excited by 3. continuous light source, the output of which is modulated at a high freeuency by an optical

Model for the Interpretation of Hyperspectral Remote-Sensing Reflectance

NASA Technical Reports Server (NTRS)

Lee, Zhongping; Carder, Kendall L.; Hawes, Steve K.; Steward, Robert G.; Peacock, Thomas G.; Davis, Curtiss O.

1994-01-01

Remote-sensing reflectance is easier to interpret for the open ocean than for coastal regions because the optical signals are highly coupled to the phytoplankton (e.g., chlorophyll) concentrations. For estuarine or coastal waters, variable terrigenous colored dissolved organic matter (CDOM), suspended sediments, and bottom reflectance, all factors that do not covary with the pigment concentration, confound data interpretation. In this research, remote-sensing reflectance models are suggested for coastal waters, to which contributions that are due to bottom reflectance, CDOM fluorescence, and water Raman scattering are included. Through the use of two parameters to model the combination of the backscattering coefficient and the Q factor, excellent agreement was achieved between the measured and modeled remote-sensing reflectance for waters from the West Florida Shelf to the Mississippi River plume. These waters cover a range of chlorophyll of 0.2-40 mg/cu m and gelbstoff absorption at 440 nm from 0.02-0.4/m. Data with a spectral resolution of 10 nm or better, which is consistent with that provided by the airborne visible and infrared imaging spectrometer (AVIRIS) and spacecraft spectrometers, were used in the model evaluation.

Miniature Raman spectrometer development

NASA Astrophysics Data System (ADS)

Bonvallet, Joseph; Auz, Bryan; Rodriguez, John; Olmstead, Ty

2018-02-01

The development of techniques to rapidly identify samples ranging from, molecule and particle imaging to detection of high explosive materials, has surged in recent years. Due to this growing want, Raman spectroscopy gives a molecular fingerprint, with no sample preparation, and can be done remotely. These systems can be small, compact, lightweight, and with a user interface that allows for easy use and sample identification. Ocean Optics Inc. has developed several systems that would meet all these end user requirements. This talk will describe the development of different Ocean Optics Inc miniature Raman spectrometers. The spectrometer on a phone (SOAP) system was designed using commercial off the shelf (COTS) components, in a rapid product development cycle. The footprint of the system measures 40x40x14 mm (LxWxH) and was coupled directly to the cell phone detector camera optics. However, it gets roughly only 40 cm-1 resolution. The Accuman system is the largest (290x220X100 mm) of the three, but uses our QEPro spectrometer and get 7-11 cm-1 resolution. Finally, the HRS-30 measuring 165x85x40 mm is a combination of the other two systems. This system uses a modified EMBED spectrometer and gets 7-12 cm-1 resolution. Each of these units uses a peak matching algorithm that then correlates the results to the pre-loaded and customizable spectral libraries.

The interpretation of remotely sensed cloud properties from a model paramterization perspective

NASA Technical Reports Server (NTRS)

HARSHVARDHAN; Wielicki, Bruce A.; Ginger, Kathryn M.

1994-01-01

A study has been made of the relationship between mean cloud radiative properties and cloud fraction in stratocumulus cloud systems. The analysis is of several Land Resources Satellite System (LANDSAT) images and three hourly International Satellite Cloud Climatology Project (ISCCP) C-1 data during daylight hours for two grid boxes covering an area typical of a general circulation model (GCM) grid increment. Cloud properties were inferred from the LANDSAT images using two thresholds and several pixel resolutions ranging from roughly 0.0625 km to 8 km. At the finest resolution, the analysis shows that mean cloud optical depth (or liquid water path) increases somewhat with increasing cloud fraction up to 20% cloud coverage. More striking, however, is the lack of correlation between the two quantities for cloud fractions between roughly 0.2 and 0.8. When the scene is essentially overcast, the mean cloud optical tends to be higher. Coarse resolution LANDSAT analysis and the ISCCP 8-km data show lack of correlation between mean cloud optical depth and cloud fraction for coverage less than about 90%. This study shows that there is perhaps a local mean liquid water path (LWP) associated with partly cloudy areas of stratocumulus clouds. A method has been suggested to use this property to construct the cloud fraction paramterization in a GCM when the model computes a grid-box-mean LWP.

Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments.

PubMed

Lee, ZhongPing; Carder, Kendall; Arnone, Robert; He, MingXia

2007-12-20

About 30 years ago, NASA launched the first ocean-color observing satellite:the Coastal Zone Color Scanner. CZCS had 5 bands in the visible-infrared domain with anobjective to detect changes of phytoplankton (measured by concentration of chlorophyll) inthe oceans. Twenty years later, for the same objective but with advanced technology, theSea-viewing Wide Field-of-view Sensor (SeaWiFS, 7 bands), the Moderate-ResolutionImaging Spectrometer (MODIS, 8 bands), and the Medium Resolution ImagingSpectrometer (MERIS, 12 bands) were launched. The selection of the number of bands andtheir positions was based on experimental and theoretical results achieved before thedesign of these satellite sensors. Recently, Lee and Carder (2002) demonstrated that foradequate derivation of major properties (phytoplankton biomass, colored dissolved organicmatter, suspended sediments, and bottom properties) in both oceanic and coastalenvironments from observation of water color, it is better for a sensor to have ~15 bands inthe 400 - 800 nm range. In that study, however, it did not provide detailed analysesregarding the spectral locations of the 15 bands. Here, from nearly 400 hyperspectral (~ 3-nm resolution) measurements of remote-sensing reflectance (a measure of water color)taken in both coastal and oceanic waters covering both optically deep and optically shallowwaters, first- and second-order derivatives were calculated after interpolating themeasurements to 1-nm resolution. From these derivatives, the frequency of zero values foreach wavelength was accounted for, and the distribution spectrum of such frequencies wasobtained. Furthermore, the wavelengths that have the highest appearance of zeros wereidentified. Because these spectral locations indicate extrema (a local maximum orminimum) of the reflectance spectrum or inflections of the spectral curvature, placing the bands of a sensor at these wavelengths maximizes the potential of capturing (and then restoring) the spectral curve, and thus maximizes the potential of accurately deriving properties of the water column and/or bottom of various aquatic environments with a multi-band sensor.

Estimating Above-Ground Carbon Biomass in a Newly Restored Coastal Plain Wetland Using Remote Sensing

PubMed Central

Riegel, Joseph B.; Bernhardt, Emily; Swenson, Jennifer

2013-01-01

Developing accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented in the United States. Previous studies have shown that LiDAR (light detection and ranging) is well-suited for modeling above-ground biomass in mature forests; however, there has been little previous research on the ability of LiDAR to model above-ground biomass in areas with young, aggrading vegetation. This study compared the abilities of discrete-return LiDAR and high resolution optical imagery to model above-ground carbon biomass at a young restored forested wetland site in eastern North Carolina. We found that the optical imagery model explained more of the observed variation in carbon biomass than the LiDAR model (adj-R2 values of 0.34 and 0.18 respectively; root mean squared errors of 0.14 Mg C/ha and 0.17 Mg C/ha respectively). Optical imagery was also better able to predict high and low biomass extremes than the LiDAR model. Combining both the optical and LiDAR improved upon the optical model but only marginally (adj-R2 of 0.37). These results suggest that the ability of discrete-return LiDAR to model above-ground biomass may be rather limited in areas with young, small trees and that high spatial resolution optical imagery may be the better tool in such areas. PMID:23840837

Optical registration of spaceborne low light remote sensing camera

NASA Astrophysics Data System (ADS)

Li, Chong-yang; Hao, Yan-hui; Xu, Peng-mei; Wang, Dong-jie; Ma, Li-na; Zhao, Ying-long

2018-02-01

For the high precision requirement of spaceborne low light remote sensing camera optical registration, optical registration of dual channel for CCD and EMCCD is achieved by the high magnification optical registration system. System integration optical registration and accuracy of optical registration scheme for spaceborne low light remote sensing camera with short focal depth and wide field of view is proposed in this paper. It also includes analysis of parallel misalignment of CCD and accuracy of optical registration. Actual registration results show that imaging clearly, MTF and accuracy of optical registration meet requirements, it provide important guarantee to get high quality image data in orbit.

Virtual and remote experiments for radiometric and photometric measurements

NASA Astrophysics Data System (ADS)

Thoms, L.-J.; Girwidz, R.

2017-09-01

The analysis of spectra is fundamental to our modern understanding of wave optics and colour perception. Since spectrometers are expensive, and accurate calibration is necessary to achieve high quality spectra, we developed a remote lab on optical spectrometry. With this tool, students can carry out real experiments over the Internet. In this article the pros and cons of remote labs, the physical background of optical spectrometry, and the development and use of a radiometric remote lab for higher education are discussed. The remote lab is freely accessible to everyone at http://virtualremotelab.net.

Deriving aerosol parameters from in-situ spectrometer measurements for validation of remote sensing products

NASA Astrophysics Data System (ADS)

Riedel, Sebastian; Janas, Joanna; Gege, Peter; Oppelt, Natascha

2017-10-01

Uncertainties of aerosol parameters are the limiting factor for atmospheric correction over inland and coastal waters. For validating remote sensing products from these optically complex and spatially inhomogeneous waters the spatial resolution of automated sun photometer networks like AERONET is too coarse and additional measurements on the test site are required. We have developed a method which allows the derivation of aerosol parameters from measurements with any spectrometer with suitable spectral range and resolution. This method uses a pair of downwelling irradiance and sky radiance measurements for the extraction of the turbidity coefficient and aerosol Ångström exponent. The data can be acquired fast and reliable at almost any place during a wide range of weather conditions. A comparison to aerosol parameters measured with a Cimel sun photometer provided by AERONET shows a reasonable agreement for the Ångström exponent. The turbidity coefficient did not agree well with AERONET values due to fit ambiguities, indicating that future research should focus on methods to handle parameter correlations within the underlying model.

Current Research in Lidar Technology Used for the Remote Sensing of Atmospheric Aerosols

PubMed Central

Comerón, Adolfo; Muñoz-Porcar, Constantino; Rocadenbosch, Francesc; Rodríguez-Gómez, Alejandro; Sicard, Michaël

2017-01-01

Lidars are active optical remote sensing instruments with unique capabilities for atmospheric sounding. A manifold of atmospheric variables can be profiled using different types of lidar: concentration of species, wind speed, temperature, etc. Among them, measurement of the properties of aerosol particles, whose influence in many atmospheric processes is important but is still poorly stated, stands as one of the main fields of application of current lidar systems. This paper presents a review on fundamentals, technology, methodologies and state-of-the art of the lidar systems used to obtain aerosol information. Retrieval of structural (aerosol layers profiling), optical (backscatter and extinction coefficients) and microphysical (size, shape and type) properties requires however different levels of instrumental complexity; this general outlook is structured following a classification that attends these criteria. Thus, elastic systems (detection only of emitted frequencies), Raman systems (detection also of Raman frequency-shifted spectral lines), high spectral resolution lidars, systems with depolarization measurement capabilities and multi-wavelength instruments are described, and the fundamentals in which the retrieval of aerosol parameters is based is in each case detailed. PMID:28632170

Impact of metal gates on remote phonon scattering in titanium nitride/hafnium dioxide n-channel metal-oxide-semiconductor field effect transistors-low temperature electron mobility study

NASA Astrophysics Data System (ADS)

Maitra, Kingsuk; Frank, Martin M.; Narayanan, Vijay; Misra, Veena; Cartier, Eduard A.

2007-12-01

We report low temperature (40-300 K) electron mobility measurements on aggressively scaled [equivalent oxide thickness (EOT)=1 nm] n-channel metal-oxide-semiconductor field effect transistors (nMOSFETs) with HfO2 gate dielectrics and metal gate electrodes (TiN). A comparison is made with conventional nMOSFETs containing HfO2 with polycrystalline Si (poly-Si) gate electrodes. No substantial change in the temperature acceleration factor is observed when poly-Si is replaced with a metal gate, showing that soft optical phonons are not significantly screened by metal gates. A qualitative argument based on an analogy between remote phonon scattering and high-resolution electron energy-loss spectroscopy (HREELS) is provided to explain the underlying physics of the observed phenomenon. It is also shown that soft optical phonon scattering is strongly damped by thin SiO2 interface layers, such that room temperature electron mobility values at EOT=1 nm become competitive with values measured in nMOSFETs with SiON gate dielectrics used in current high performance processors.

Remote Optical Switch for Localized and Selective Control of Gene Interference

PubMed Central

Lee, Somin Eunice; Liu, Gang Logan; Kim, Franklin; Lee, Luke P.

2009-01-01

Near infrared-absorbing gold nanoplasmonic particles (GNPs) are used as optical switches of gene interference and are remotely controlled using light. We have tuned optical switches to a wavelength where cellular photodamage is minimized. Optical switches are functionalized with double-stranded oligonucleotides. At desired times and at specific intracellular locations, remote optical excitation is used to liberate gene-interfering oligonucleotides. We demonstrate a novel gene-interfering technique offering spatial and temporal control, which is otherwise impossible using conventional gene-interfering techniques. PMID:19128006

Exploring multi-scale forest above ground biomass estimation with optical remote sensing imageries

NASA Astrophysics Data System (ADS)

Koju, U.; Zhang, J.; Gilani, H.

2017-02-01

Forest shares 80% of total exchange of carbon between the atmosphere and the terrestrial ecosystem. Due to this monitoring of forest above ground biomass (as carbon can be calculated as 0.47 part of total biomass) has become very important. Forest above ground biomass as being the major portion of total forest biomass should be given a very careful consideration in its estimation. It is hoped to be useful in addressing the ongoing problems of deforestation and degradation and to gain carbon mitigation benefits through mechanisms like Reducing Emissions from Deforestation and Forest Degradation (REDD+). Many methods of above ground biomass estimation are in used ranging from use of optical remote sensing imageries of very high to very low resolution to SAR data and LIDAR. This paper describes a multi-scale approach for assessing forest above ground biomass, and ultimately carbon stocks, using very high imageries, open source medium resolution and medium resolution satellite datasets with a very limited number of field plots. We found this method is one of the most promising method for forest above ground biomass estimation with higher accuracy and low cost budget. Pilot study was conducted in Chitwan district of Nepal on the estimation of biomass using this technique. The GeoEye-1 (0.5m), Landsat (30m) and Google Earth (GE) images were used remote sensing imageries. Object-based image analysis (OBIA) classification technique was done on Geo-eye imagery for the tree crown delineation at the watershed level. After then, crown projection area (CPA) vs. biomass model was developed and validated at the watershed level. Open source GE imageries were used to calculate the CPA and biomass from virtual plots at district level. Using data mining technique, different parameters from Landsat imageries along with the virtual sample biomass were used for upscaling biomass estimation at district level. We found, this approach can considerably reduce field data requirements for estimation of biomass and carbon in comparison with inventory methods based on enumeration of all trees in a plot. The proposed methodology is very cost effective and can be replicated with limited resources and time.

Depth Estimation of Submerged Aquatic Vegetation in Clear Water Streams Using Low-Altitude Optical Remote Sensing

PubMed Central

Visser, Fleur; Buis, Kerst; Verschoren, Veerle; Meire, Patrick

2015-01-01

UAVs and other low-altitude remote sensing platforms are proving very useful tools for remote sensing of river systems. Currently consumer grade cameras are still the most commonly used sensors for this purpose. In particular, progress is being made to obtain river bathymetry from the optical image data collected with such cameras, using the strong attenuation of light in water. No studies have yet applied this method to map submergence depth of aquatic vegetation, which has rather different reflectance characteristics from river bed substrate. This study therefore looked at the possibilities to use the optical image data to map submerged aquatic vegetation (SAV) depth in shallow clear water streams. We first applied the Optimal Band Ratio Analysis method (OBRA) of Legleiter et al. (2009) to a dataset of spectral signatures from three macrophyte species in a clear water stream. The results showed that for each species the ratio of certain wavelengths were strongly associated with depth. A combined assessment of all species resulted in equally strong associations, indicating that the effect of spectral variation in vegetation is subsidiary to spectral variation due to depth changes. Strongest associations (R2-values ranging from 0.67 to 0.90 for different species) were found for combinations including one band in the near infrared (NIR) region between 825 and 925 nm and one band in the visible light region. Currently data of both high spatial and spectral resolution is not commonly available to apply the OBRA results directly to image data for SAV depth mapping. Instead a novel, low-cost data acquisition method was used to obtain six-band high spatial resolution image composites using a NIR sensitive DSLR camera. A field dataset of SAV submergence depths was used to develop regression models for the mapping of submergence depth from image pixel values. Band (combinations) providing the best performing models (R2-values up to 0.77) corresponded with the OBRA findings. A 10% error was achieved under sub-optimal data collection conditions, which indicates that the method could be suitable for many SAV mapping applications. PMID:26437410

Depth Estimation of Submerged Aquatic Vegetation in Clear Water Streams Using Low-Altitude Optical Remote Sensing.

PubMed

Visser, Fleur; Buis, Kerst; Verschoren, Veerle; Meire, Patrick

2015-09-30

UAVs and other low-altitude remote sensing platforms are proving very useful tools for remote sensing of river systems. Currently consumer grade cameras are still the most commonly used sensors for this purpose. In particular, progress is being made to obtain river bathymetry from the optical image data collected with such cameras, using the strong attenuation of light in water. No studies have yet applied this method to map submergence depth of aquatic vegetation, which has rather different reflectance characteristics from river bed substrate. This study therefore looked at the possibilities to use the optical image data to map submerged aquatic vegetation (SAV) depth in shallow clear water streams. We first applied the Optimal Band Ratio Analysis method (OBRA) of Legleiter et al. (2009) to a dataset of spectral signatures from three macrophyte species in a clear water stream. The results showed that for each species the ratio of certain wavelengths were strongly associated with depth. A combined assessment of all species resulted in equally strong associations, indicating that the effect of spectral variation in vegetation is subsidiary to spectral variation due to depth changes. Strongest associations (R²-values ranging from 0.67 to 0.90 for different species) were found for combinations including one band in the near infrared (NIR) region between 825 and 925 nm and one band in the visible light region. Currently data of both high spatial and spectral resolution is not commonly available to apply the OBRA results directly to image data for SAV depth mapping. Instead a novel, low-cost data acquisition method was used to obtain six-band high spatial resolution image composites using a NIR sensitive DSLR camera. A field dataset of SAV submergence depths was used to develop regression models for the mapping of submergence depth from image pixel values. Band (combinations) providing the best performing models (R²-values up to 0.77) corresponded with the OBRA findings. A 10% error was achieved under sub-optimal data collection conditions, which indicates that the method could be suitable for many SAV mapping applications.

A l% and 1cm Perspective Leads to a Novel CDOM Absorption Algorithm

NASA Technical Reports Server (NTRS)

Morrow, J. H.; Hooker, S. B.; Matsuoka, A.

2012-01-01

A next-generation in-water profiler designed to measure the apparent optical properties of seawater was developed and validated across a wide dynamic range of water properties. This new Compact-Optical Profiling System (C-OPS) design uses a novel, kite-shaped, free-falling backplane with adjustable buoyancy and is based on 19 state-of-the-art microradiometers, spanning 320-780 nm. Data collected as part of the field commissioning were of a previously unachievable quality and showed that systematic uncertainties in the sampling protocols were discernible at the 1% optical and 1cm depth resolution levels. A sensitivity analysis as a function of three water types, established by the peak in the remote sensing reflectance spectra, revealed which water types and spectral domains were the most indicative of data acquisition uncertainties. The unprecedented vertical resolution of C-OPS measurements provided near-surface data products at the spectral endpoints with a quality level that has not been obtainable. The improved data allowed development of an algorithm for predicting the spectral absorption due to chromophoric dissolved organic matter (CDOM) using ratios of diffuse attenuation coefficients with over 99% of the variance in the data explained.

[Estimation of desert vegetation coverage based on multi-source remote sensing data].

PubMed

Wan, Hong-Mei; Li, Xia; Dong, Dao-Rui

2012-12-01

Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study areaAbstract: Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study area and based on the ground investigation and the multi-source remote sensing data of different resolutions, the estimation models for desert vegetation coverage were built, with the precisions of different estimation methods and models compared. The results showed that with the increasing spatial resolution of remote sensing data, the precisions of the estimation models increased. The estimation precision of the models based on the high, middle-high, and middle-low resolution remote sensing data was 89.5%, 87.0%, and 84.56%, respectively, and the precisions of the remote sensing models were higher than that of vegetation index method. This study revealed the change patterns of the estimation precision of desert vegetation coverage based on different spatial resolution remote sensing data, and realized the quantitative conversion of the parameters and scales among the high, middle, and low spatial resolution remote sensing data of desert vegetation coverage, which would provide direct evidence for establishing and implementing comprehensive remote sensing monitoring scheme for the ecological restoration in the study area.

Classification of high resolution remote sensing image based on geo-ontology and conditional random fields

NASA Astrophysics Data System (ADS)

Hong, Liang

2013-10-01

The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.

UAV-based remote sensing of the Heumoes landslide, Austria Vorarlberg

NASA Astrophysics Data System (ADS)

Niethammer, U.; Joswig, M.

2009-04-01

The Heumoes landslide, is located in the eastern Vorarlberg Alps, Austria, 10 km southeast of Dornbirn. The extension of the landslide is about 2000 m in west to east direction and about 500 m at its widest extent in north to south direction. It occurs between an elevation of 940 m in the east and 1360 m in the west, slope angles of more than 60 % can be observed as well as almost flat areas. Its total volume is estimated to be 9.400.000 cubic meters and its average velocities amount to some centimeter per year. Surface signatures or 'photolineations' of creeping landslides, e.g. fractures and rupture lines in sediments and street pavings, and vegetation contrasts by changes of water table in shallow vegetation in principle can be resolved by remote sensing. The necessary ground cell resolution of few centimeters, however, generally can't be achieved by routine areal or satellite imagery. The fast technological progress of unmanned areal vehicles (UAV) and the reduced payload by miniaturized optical cameras now allow for UAV remote sensing applications that are below the high financial limits of military intelligence. Even with 'low-cost' equipment, the necessary centimeter-scale ground cell resolution can be achieved by adapting the flight altitude to some ten to one hundred meters. Operated by scientists experienced in remote-control flight models, UAV remote sensing can now be performed routinely, and campaign-wise after any significant event of, e.g., heavy rainfall, or partial mudflow. We have investigated a concept of UAV-borne remote sensing based on motorized gliders, and four-propeller helicopters or 'quad-rotors'. Several missions were flown over the Heumoes landslide. Between 2006 and 2008 three series UAV-borne photographs of the Heumoes landslide were taken and could be combined to orto-mosaics of the slope area within few centimeters ground cell resolution. We will present the concept of our low cost quad-rotor UAV system and first results of the image-processing based evaluation of the acquired images to characterize spatial and temporal details of landslide behaviour. We will also sketch first schemes of joint interpretation or 'data fusion' of UAV-based remote sensing with the results from geophysical mapping of underground distribution of soil moisture and fracture processes (Walter & Joswig, EGU 2009).

Remote Sensing of Energy Distribution Characteristics over the Tibet

NASA Astrophysics Data System (ADS)

Shi, J.; Husi, L.; Wang, T.

2017-12-01

The overall objective of our study is to quantify the spatiotemporal characteristics and changes of typical factors dominating water and energy cycles in the Tibet region. Especially, we focus on variables of clouds optical & microphysical parameters, surface shortwave and longwave radiation. Clouds play a key role in the Tibetan region's water and energy cycles. They seriously impact the precipitation, temperature and surface energy distribution. Considering that proper cloud products with relatively higher spatial and temporal sampling and with satisfactory accuracy are serious lacking in the Tibet region, except cloud optical thickness, cloud effective radius and liquid/ice water content, the cloud coverage dynamics at hourly scales also analyzed jointly based on measurements of Himawari-8, and MODIS. Surface radiation, as an important energy source in perturbating the Tibet's evapotranspiration, snow and glacier melting, is a controlling factor in energy balance in the Tibet region. All currently available radiation products in this area are not suitable for regional scale study of water and energy exchange and snow/glacier melting due to their coarse resolution and low accuracies because of cloud and topography. A strategy for deriving land surface upward and downward radiation by fusing optical and microwave remote sensing data is proposed. At the same time, the big topographic effect on the surface radiation are also modelled and analyzed over the Tibet region.

Fiber-optic apparatus and method for measurement of luminescence and Raman scattering

DOEpatents

Myrick, M.L.; Angel, S.M.

1993-03-16

A dual fiber forward scattering optrode for Raman spectroscopy with the remote ends of the fibers in opposed, spaced relationship to each other to form a analyte sampling space therebetween and the method of measuring Raman spectra utilizing same are described. One optical fiber is for sending an exciting signal to the remote sampling space and, at its remote end, has a collimating microlens and an optical filter for filtering out background emissions generated in the fiber. The other optical fiber is for collecting the Raman scattering signal at the remote sampling space and, at its remote end, has a collimating microlens and an optical filter to prevent the exciting signal from the exciting fiber from entering the collection fiber and to thereby prevent the generation of background emissions in the collecting fiber.

Six years of surface remote sensing of stratiform warm clouds in marine and continental air over Mace Head, Ireland

NASA Astrophysics Data System (ADS)

Preißler, Jana; Martucci, Giovanni; Saponaro, Giulia; Ovadnevaite, Jurgita; Vaishya, Aditya; Kolmonen, Pekka; Ceburnis, Darius; Sogacheva, Larisa; de Leeuw, Gerrit; O'Dowd, Colin

2016-12-01

A total of 118 stratiform water clouds were observed by ground-based remote sensing instruments at the Mace Head Atmospheric Research Station on the west coast of Ireland from 2009 to 2015. Microphysical and optical characteristics of these clouds were studied as well as the impact of aerosols on these properties. Microphysical and optical cloud properties were derived using the algorithm SYRSOC (SYnergistic Remote Sensing Of Clouds). Ground-based in situ measurements of aerosol concentrations and the transport path of air masses at cloud level were investigated as well. The cloud properties were studied in dependence of the prevailing air mass at cloud level and season. We found higher cloud droplet number concentrations (CDNC) and smaller effective radii (reff) with greater pollution. Median CDNC ranged from 60 cm-3 in marine air masses to 160 cm-3 in continental air. Median reff ranged from 8 μm in polluted conditions to 10 μm in marine air. Effective droplet size distributions were broader in marine than in continental cases. Cloud optical thickness (COT) and albedo were lower in cleaner air masses and higher in more polluted conditions, with medians ranging from 2.1 to 4.9 and 0.22 to 0.39, respectively. However, calculation of COT and albedo was strongly affected by liquid water path (LWP) and departure from adiabatic conditions. A comparison of SYRSOC results with MODIS (Moderate-Resolution Imaging Spectroradiometer) observations showed large differences for LWP and COT but good agreement for reff with a linear fit with slope near 1 and offset of -1 μm.

Spectral Variability of Oil Slicks under Different Observing Conditions: Examples from Satellite and Airborne Measurement

NASA Astrophysics Data System (ADS)

Sun, S.; Hu, C.

2017-12-01

Optical remote sensing is one of the most commonly used techniques in detecting oil in the surface ocean. This is because that oil has different optical properties from the surrounding oil-free water and oil can also modulate surface waves, thus providing a spatial contrast to facilitate delineating the oil-water boundary. Estimating oil volume or thickness from the delineated oil footprint, on the other hand, is much more difficult and currently represents a major challenge in remote sensing of oil spills. Several studies have attempted to associate reflectance spectra (magnitude and spectral shape) with oil thickness from experiments under controlled conditions, where such established relationships were used to quantify oil thickness. However, it is unclear whether or how these experiment derived relationships could be used in the real environment. Here, oil pixel spectra were extracted from several satellite sensors including Landsat, MERIS, MODIS and MISR together with airborne sensor AVIRIS that captured during the Deepwater Horizon oil spill in 2010. Same day imagery of these sensors were co-registered to compare spectra difference of oil under different observing conditions. Combining those resulted spectra with laboratory-measured oil spectra in previous study, oil's diverse spectral magnitudes and shapes were presented. Besides oil thickness, we concluded several other potential factors that may contribute significantly to the spectral response of oil slicks in the marine environment, which include sun glint strength, oil emulsification state, optical properties of oil covered water and remote sensing imagery's spatial resolution as well. And future perspectives for more accurate estimation of oil thickness are proposed.

Discrete Angle Radiative Transfer in Uniform and Extremely Variable Clouds.

NASA Astrophysics Data System (ADS)

Gabriel, Philip Mitri

The transfer of radiant energy in highly inhomogeneous media is a difficult problem that is encountered in many geophysical applications. It is the purpose of this thesis to study some problems connected with the scattering of solar radiation in natural clouds. Extreme variability in the optical density of these clouds is often believed to occur regularly. In order to facilitate study of very inhomogeneous optical media such as clouds, the difficult angular part of radiative transfer calculations is simplified by considering a series of models in which conservative scattering only occurs in discrete directions. Analytic and numerical results for the radiative properties of these Discrete Angle Radiative Transfer (DART) systems are obtained in the limits of both optically thin and thick media. Specific results include: (a) In thick homogeneous media, the albedo (reflection coefficient), unlike the transmission, cannot be obtained by a diffusion equation. (b) With the aid of an exact analogy with an early model of conductor/superconductor mixtures, it is argued that inhomogeneous media with embedded holes, neither the transmission, nor the albedo can be described by diffusive random walks. (c) Using renormalization methods, it is shown that thin cloud behaviour is sensitive to the scattering phase functions since it is associated with a repelling fixed point, whereas, the thick cloud limit is universal in that it is phase function independent, and associated with an attracting fixed point. (d) In fractal media, the optical thickness required for a given albedo or transmission can differ by large factors from that required in the corresponding plane parallel geometry. The relevant scaling exponents have been calculated in a very simple example. (e) Important global meteorological and climatological implications of the above are discussed when applied to the scattering of visible light in clouds. In the remote sensing context, an analysis of satellite data reveals that augmenting a satellite's resolution reveals increasingly detailed structures that are found to occupy a decreasing fraction of the image, while simultaneously brightening to compensate. By systematically degrading the resolution of visible and infra red satellite cloud and surface data as well as radar rain data, resolution -independent co-dimension functions were defined which were useful in describing the spatial distribution of image features as well as the resolution dependence of the intensities themselves. The scale invariant functions so obtained fit into theoretically predicted functional forms. These multifractal techniques have implications for our ability to meaningfully estimate cloud brightness fraction, total cloud amount, as well as other remotely sensed quantities.

Developing particle emission inventories using remote sensing (PEIRS).

PubMed

Tang, Chia-Hsi; Coull, Brent A; Schwartz, Joel; Lyapustin, Alexei I; Di, Qian; Koutrakis, Petros

2017-01-01

Information regarding the magnitude and distribution of PM 2.5 emissions is crucial in establishing effective PM regulations and assessing the associated risk to human health and the ecosystem. At present, emission data is obtained from measured or estimated emission factors of various source types. Collecting such information for every known source is costly and time-consuming. For this reason, emission inventories are reported periodically and unknown or smaller sources are often omitted or aggregated at large spatial scale. To address these limitations, we have developed and evaluated a novel method that uses remote sensing data to construct spatially resolved emission inventories for PM 2.5 . This approach enables us to account for all sources within a fixed area, which renders source classification unnecessary. We applied this method to predict emissions in the northeastern United States during the period 2002-2013 using high-resolution 1 km × 1 km aerosol optical depth (AOD). Emission estimates moderately agreed with the EPA National Emission Inventory (R 2 = 0.66-0.71, CV = 17.7-20%). Predicted emissions are found to correlate with land use parameters, suggesting that our method can capture emissions from land-use-related sources. In addition, we distinguished small-scale intra-urban variation in emissions reflecting distribution of metropolitan sources. In essence, this study demonstrates the great potential of remote sensing data to predict particle source emissions cost-effectively. We present a novel method, particle emission inventories using remote sensing (PEIRS), using remote sensing data to construct spatially resolved PM 2.5 emission inventories. Both primary emissions and secondary formations are captured and predicted at a high spatial resolution of 1 km × 1 km. Using PEIRS, large and comprehensive data sets can be generated cost-effectively and can inform development of air quality regulations.

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. 

Optical remote measurement of toxic gases

NASA Technical Reports Server (NTRS)

Grant, W. B.; Kagann, R. H.; McClenny, W. A.

1992-01-01

Enactment of the Clean Air Act Amendments (CAAA) of 1990 has resulted in increased ambient air monitoring needs for industry, some of which may be met efficiently using open-path optical remote sensing techniques. These techniques include Fourier transform spectroscopy, differential optical absorption spectroscopy, laser long-path absorption, differential absorption lidar, and gas cell correlation spectroscopy. With this regulatory impetus, it is an opportune time to consider applying these technologies to the remote and/or path-averaged measurement and monitoring of toxic gases covered by the CAAA. This article reviews the optical remote sensing technology and literature for that application.

Automated Glacier Surface Velocity using Multi-Image/Multi-Chip (MIMC) Feature Tracking

NASA Astrophysics Data System (ADS)

Ahn, Y.; Howat, I. M.

2009-12-01

Remote sensing from space has enabled effective monitoring of remote and inhospitable polar regions. Glacier velocity, and its variation in time, is one of the most important parameters needed to understand glacier dynamics, glacier mass balance and contribution to sea level rise. Regular measurements of ice velocity are possible from large and accessible satellite data set archives, such as ASTER and LANDSAT-7. Among satellite imagery, optical imagery (i.e. passive, visible to near-infrared band sensors) provides abundant data with optimal spatial resolution and repeat interval for tracking glacier motion at high temporal resolution. Due to massive amounts of data, computation of ice velocity from feature tracking requires 1) user-friendly interface, 2) minimum local/user parameter inputs and 3) results that need minimum editing. We focus on robust feature tracking, applicable to all currently available optical satellite imagery, that is ASTER, SPOT and LANDSAT etc. We introduce the MIMC (multiple images/multiple chip sizes) matching approach that does not involve any user defined local/empirical parameters except approximate average glacier speed. We also introduce a method for extracting velocity from LANDSAT-7 SLC-off data, which has 22 percent of scene data missing in slanted strips due to failure of the scan line corrector. We apply our approach to major outlet glaciers in west/east Greenland and assess our MIMC feature tracking technique by comparison with conventional correlation matching and other methods (e.g. InSAR).

Resolution verification targets for airborne and spaceborne imaging systems at the Stennis Space Center

NASA Astrophysics Data System (ADS)

McKellip, Rodney; Yuan, Ding; Graham, William; Holland, Donald E.; Stone, David; Walser, William E.; Mao, Chengye

1997-06-01

The number of available spaceborne and airborne systems will dramatically increase over the next few years. A common systematic approach toward verification of these systems will become important for comparing the systems' operational performance. The Commercial Remote Sensing Program at the John C. Stennis Space Center (SSC) in Mississippi has developed design requirements for a remote sensing verification target range to provide a means to evaluate spatial, spectral, and radiometric performance of optical digital remote sensing systems. The verification target range consists of spatial, spectral, and radiometric targets painted on a 150- by 150-meter concrete pad located at SSC. The design criteria for this target range are based upon work over a smaller, prototypical target range at SSC during 1996. This paper outlines the purpose and design of the verification target range based upon an understanding of the systems to be evaluated as well as data analysis results from the prototypical target range.

Remote Sensing of Aerosol and Aerosol Radiative Forcing of Climate from EOS Terra MODIS Instrument

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Tanre, Didier; Remer, Lorraine; Einaudi, Franco (Technical Monitor)

2000-01-01

The recent launch of EOS-Terra into polar orbit has begun to revolutionize remote sensing of aerosol and their effect on climate. Terra has five instruments, two of them,Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectro-Radiometer (MISR) are designed to monitor global aerosol in two different complementary ways. Here we shall discuss the use of the multispectral measurements of MODIS to derive: (1) the global distribution of aerosol load (and optical thickness) over ocean and land; (2) to measure the impact of aerosol on reflection of sunlight to space; and (3) to measure the ability of aerosol to absorb solar radiation. These measurements have direct applications on the understanding of the effect of aerosol on climate, the ability to predict climate change, and on the monitoring of dust episodes and man-made pollution. Principles of remote sensing of aerosol from MODIS will be discussed and first examples of measurements from MODIS will be provided.

Remote Sensing Reflectance and Inherent Optical Properties in the Mid-mesohaline Chesapeake Bay

NASA Technical Reports Server (NTRS)

Tzortziou, Maria; Subramaniam, Ajit; Herman, Jay R.; Gallegos, Charles L.; Neal, Patrick J.; Harding, Lawrence W., Jr.

2006-01-01

We used an extensive set of bio-optical data and radiative transfer (RT) model simulations of radiation fields to investigate relationships between inherent optical properties and remotely sensed quantities in the optically complex, mid-mesohaline Chesapeake Bay waters. Field observations showed that the chlorophyll algorithms used by the MODIS (MODerate resolution Imaging Spectroradiometer) ocean color sensor (i.e. Chlor_a, chlor_MODIS, chlor_a_3 products) do not perform accurately in these Case 2 waters. This is because, when applied to waters with high concentrations of chlorophyll, all MODIS algorithms are based on empirical relationships between chlorophyll concentration and blue-green wavelength remote sensing reflectance (Rrs) ratios that do not account for the typically strong blue-wavelength absorption by non-covarying, dissolved and non-algal particulate components. Stronger correlation was observed between chlorophyll concentration and Rrs ratios in the red (i.e. Rrs(677)/Rrs(554)) where dissolved and non-algal particulate absorption become exponentially smaller. Regionally-specific algorithms that are based on the phytoplankton optical properties in the red wavelength region provide a better basis for satellite monitoring of phytoplankton blooms in these Case 2 waters. Good optical closure was obtained between independently measured Rrs spectra and the optical properties of backscattering, b(sub b), and absorption, a, over the wide range of in-water conditions observed in the Chesapeake Bay. Observed variability in the quantity f/Q (proportionality factor in the relationship between Rrs and the water inherent optical properties ratio b(sub b)/(a+b(sub b)) was consistent with RT model calculations for the specific measurement geometry and water bio-optical characteristics. Data and model results showed that f/Q values in these Case 2 coastal waters are not considerably different from those estimated in previous studies for Case 1 waters. Variation in surface backscattering significantly affected Rrs magnitude across the visible spectrum and was most strongly correlated (R(sup 2)=0.88) with observed variability in Rrs at 670 nm. Surface values of particulate backscattering were strongly correlated with non-algal particulate absorption, a(sub nap), in the blue wavelengths (R(sup 2)=0.83). These results, along with the measured values of backscattering fraction magnitude and non-algal particulate absorption spectral slope, suggest that suspended non-algal particles with high inorganic content are the major water constituents regulating b(sub b) variability in the mid-mesohaline Chesapeake Bay. Remote retrieval of surface b(sub b) and (a(sub nap), from Rrs(670) can be used in regionally-specific satellite algorithms to separate contribution by non-algal particles and dissolved organic matter to total light absorption in the blue, and monitor non-algal suspended particle concentration and distribution in these Case 2 waters.

Colors of active regions on comet 67P

NASA Astrophysics Data System (ADS)

Oklay, N.; Vincent, J.-B.; Sierks, H.; Besse, S.; Fornasier, S.; Barucci, M. A.; Lara, L.; Scholten, F.; Preusker, F.; Lazzarin, M.; Pajola, M.; La Forgia, F.

2015-10-01

The OSIRIS (Optical, Spectroscopic, and Infrared Remote Imaging System) scientific imager (Keller et al. 2007) is successfully delivering images of comet 67P/Churyumov-Gerasimenko from its both wide angle camera (WAC) and narrow angle camera (NAC) since ESA's spacecraft Rosetta's arrival to the comet. Both cameras are equipped with filters covering the wavelength range of about 200 nm to 1000 nm. The comet nucleus is mapped with different combination of the filters in resolutions up to 15 cm/px. Besides the determination of the surface morphology in great details (Thomas et al. 2015), such high resolution images provided us a mean to unambiguously link some activity in the coma to a series of pits on the nucleus surface (Vincent et al. 2015).

Normalizing Landsat and ASTER Data Using MODIS Data Products for Forest Change Detection

NASA Technical Reports Server (NTRS)

Gao, Feng; Masek, Jeffrey G.; Wolfe, Robert E.; Tan, Bin

2010-01-01

Monitoring forest cover and its changes are a major application for optical remote sensing. In this paper, we present an approach to integrate Landsat, ASTER and MODIS data for forest change detection. Moderate resolution (10-100m) images (e.g. Landsat and ASTER) acquired from different seasons and times are normalized to one "standard" date using MODIS data products as reference. The normalized data are then used to compute forest disturbance index for forest change detection. Comparing to the results from original data, forest disturbance index from the normalized images is more consistent spatially and temporally. This work demonstrates an effective approach for mapping forest change over a large area from multiple moderate resolution sensors on various acquisition dates.

Electro-optic Imaging Fourier Transform Spectrometer

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

2005-01-01

JPL is developing an innovative compact, low mass, Electro-Optic Imaging Fourier Transform Spectrometer (E-O IFTS) for hyperspectral imaging applications. The spectral region of this spectrometer will be 1 - 2.5 micron (1000-4000/cm) to allow high-resolution, high-speed hyperspectral imaging applications. One application will be the remote sensing of the measurement of a large number of different atmospheric gases simultaneously in the same airmass. Due to the use of a combination of birefringent phase retarders and multiple achromatic phase switches to achieve phase delay, this spectrometer is capable of hyperspectral measurements similar to that of the conventional Fourier transform spectrometer but without any moving parts. In this paper, the principle of operations, system architecture and recent experimental progress will be presented.

Satellite remote sensing of dust aerosol indirect effects on ice cloud formation.

PubMed

Ou, Steve Szu-Cheng; Liou, Kuo-Nan; Wang, Xingjuan; Hansell, Richard; Lefevre, Randy; Cocks, Stephen

2009-01-20

We undertook a new approach to investigate the aerosol indirect effect of the first kind on ice cloud formation by using available data products from the Moderate-Resolution Imaging Spectrometer (MODIS) and obtained physical understanding about the interaction between aerosols and ice clouds. Our analysis focused on the examination of the variability in the correlation between ice cloud parameters (optical depth, effective particle size, cloud water path, and cloud particle number concentration) and aerosol optical depth and number concentration that were inferred from available satellite cloud and aerosol data products. Correlation results for a number of selected scenes containing dust and ice clouds are presented, and dust aerosol indirect effects on ice clouds are directly demonstrated from satellite observations.

Hydraulic description of a flood event with optical remote sensors: a constructive constraint on modelling uncertainties

NASA Astrophysics Data System (ADS)

Battiston, Stéphanie; Allenbach, Bernard

2010-05-01

The exceptional characteristics of the December 2003 Rhône flood event (particularly high water flows, extent of the affected area, important damages especially in the region of Arles) make it be considered as a reference flood episode of this French river and a very well-known event. During the crisis, the International Charter "Space and Major Disasters" was triggered by the French Civil Protection for the rapid mapping of the flooding using Earth Observation imagery in order to facilitate crisis operations. As a result, more than 60 satellite images covering the flood were acquired over a 10 days period following the peak flow. Using the opportunity provided by this incomparable data coverage, the French Ministry of the Environment ordered a study on the evaluation of remote sensing's potential benefits for flood management. One of the questions asked by the risk managers was: what type of flood information can be provided by the different remote sensing platforms? Elements of response were delivered mainly in the form of a comprehensive compilation of maps and illustrations, displaying the main hydraulic elements (static ones as well as dynamic ones), initially listed and requested by hydrologists (more precisely, by a regional engineering society specialised in hydraulics and hydrology and in charge of a field campaign during the event), observed on different optical images of the flood event having affected the plain between Tarascon (upstream) and Arles (downstream). It is seen that a careful mapping of all flood traces visible on remote sensing event imagery - apparent water, moisture traces, breaches, overflows, stream directions, impermeable boundaries … - delivers a valuable vision of the flood's occurrence combining accuracy and comprehensiveness. In fact, optical imagery offers a detailed vision of the event : moisture traces complete flood traces extent; the observation of draw-off directions through waterproof barriers reveals hydraulic compartments; high resolution optical imagery allow the exhaustive inventory of breaches and overflows; turbidity variations and draw-off give information on stream directions. These facts are of primary interest to help in deriving a firm understanding of the flooding processes, but also comprise a powerful source for the necessary parameterization and/or calibration of hydraulic models. Thus the accuracy of flood extents derived from remote sensing data could, on the one hand, be valuable inputs to historical flood info-bases within overall risk-linked databases, and on the other hand, test the validity of hydrological modelling, while helping to lift equifinality uncertainties. These first investigations highlight that space imagery of events constitutes an unrivalled tool for flood disaster observation. This 2D record is complementary to all field measurements and the integration of "space derived flood products" is valuable for all stages of risk management. This potential of EO optical sensors for flood monitoring is also confirmed in a detailed analysis making a qualitative and quantitative evaluation of the results, confronting ten optical and radar remote sensing platforms with field observations.

Field Test on the Feasibility of Remoting HF Antenna with Fiber Optics

DTIC Science & Technology

2008-07-31

Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/5652--08-9137 Field Test on the Feasibility of Remoting HF Antenna with Fiber Optics July...NUMBER (include area code) b. ABSTRACT c. THIS PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT Field Test on the Feasibility of Remoting HF Antenna...optic link was employed to remote a high-frequency ( HF , 2-30 MHz) direction-finding (DF) array. The test link comprised a seven-element “L” array

High-resolution LIDAR and ground observations of snow cover in a complex forested terrain in the Sierra Nevada - implications for optical remote sensing of seasonal snow.

NASA Astrophysics Data System (ADS)

Kostadinov, T. S.; Harpold, A.; Hill, R.; McGwire, K.

2017-12-01

Seasonal snow cover is a key component of the hydrologic regime in many regions of the world, especially those in temperate latitudes with mountainous terrain and dry summers. Such regions support large human populations which depend on the mountain snowpack for their water supplies. It is thus important to quantify snow cover accurately and continuously in these regions. Optical remote-sensing methods are able to detect snow and leverage space-borne spectroradiometers with global coverage such as MODIS to produce global snow cover maps. However, snow is harder to detect accurately in mountainous forested terrain, where topography influences retrieval algorithms, and importantly - forest canopies complicate radiative transfer and obfuscate the snow. Current satellite snow cover algorithms assume that fractional snow-covered area (fSCA) under the canopy is the same as the fSCA in the visible portion of the pixel. In-situ observations and first principles considerations indicate otherwise, therefore there is a need for improvement of the under-canopy correction of snow cover. Here, we leverage multiple LIDAR overflights and in-situ observations with a distributed fiber-optic temperature sensor (DTS) to quantify snow cover under canopy as opposed to gap areas at the Sagehen Experimental Forest in the Northern Sierra Nevada, California, USA. Snow-off LIDAR overflights from 2014 are used to create a baseline high-resolution digital elevation model and classify pixels at 1 m resolution as canopy-covered or gap. Low canopy pixels are excluded from the analysis. Snow-on LIDAR overflights conducted by the Airborne Snow Observatory in 2016 are then used to classify all pixels as snow-covered or not and quantify fSCA under canopies vs. in gap areas over the Sagehen watershed. DTS observations are classified as snow-covered or not based on diel temperature fluctuations and used as validation for the LIDAR observations. LIDAR- and DTS-derived fSCA is also compared with retrievals from hyperspectral imaging spectroradiometer (AVIRIS) data. Initial evidence suggest fSCA was generally lower under canopy and that overall snow cover estimates were overestimated as a result. Implications for a canopy correction applicable to coarser-resolution sensors like MODIS are discussed, as are topography and view angle effects.

Optical arc sensor using energy harvesting power source

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

Choi, Kyoo Nam, E-mail: knchoi@inu.ac.kr; Rho, Hee Hyuk, E-mail: rdoubleh0902@inu.ac.kr

Wireless sensors without external power supply gained considerable attention due to convenience both in installation and operation. Optical arc detecting sensor equipping with self sustaining power supply using energy harvesting method was investigated. Continuous energy harvesting method was attempted using thermoelectric generator to supply standby power in micro ampere scale and operating power in mA scale. Peltier module with heat-sink was used for high efficiency electricity generator. Optical arc detecting sensor with hybrid filter showed insensitivity to fluorescent and incandescent lamps under simulated distribution panel condition. Signal processing using integrating function showed selective arc discharge detection capability to different arcmore » energy levels, with a resolution below 17 J energy difference, unaffected by bursting arc waveform. The sensor showed possibility for application to arc discharge detecting sensor in power distribution panel. Also experiment with proposed continuous energy harvesting method using thermoelectric power showed possibility as a self sustainable power source of remote sensor.« less

Optical arc sensor using energy harvesting power source

NASA Astrophysics Data System (ADS)

Choi, Kyoo Nam; Rho, Hee Hyuk

2016-06-01

Wireless sensors without external power supply gained considerable attention due to convenience both in installation and operation. Optical arc detecting sensor equipping with self sustaining power supply using energy harvesting method was investigated. Continuous energy harvesting method was attempted using thermoelectric generator to supply standby power in micro ampere scale and operating power in mA scale. Peltier module with heat-sink was used for high efficiency electricity generator. Optical arc detecting sensor with hybrid filter showed insensitivity to fluorescent and incandescent lamps under simulated distribution panel condition. Signal processing using integrating function showed selective arc discharge detection capability to different arc energy levels, with a resolution below 17J energy difference, unaffected by bursting arc waveform. The sensor showed possibility for application to arc discharge detecting sensor in power distribution panel. Also experiment with proposed continuous energy harvesting method using thermoelectric power showed possibility as a self sustainable power source of remote sensor.

Parametrization of Land Surface Temperature Fields with Optical and Microwave Remote Sensing in Brazil's Atlantic Forest

NASA Astrophysics Data System (ADS)

McDonald, K. C.; Khan, A.; Carnaval, A. C.

2016-12-01

Brazil is home to two of the largest and most biodiverse ecosystems in the world, primarily encompassed in forests and wetlands. A main region of interest in this project is Brazil's Atlantic Forest (AF). Although this forest is only a fraction of the size of the Amazon rainforest, it harbors significant biological richness, making it one of the world's major hotspots for biodiversity. The AF is located on the East to Southeast region of Brazil, bordering the Atlantic Ocean. As luscious and biologically rich as this region is, the area covered by the Atlantic Forest has been diminishing over past decades, mainly due to human influences and effects of climate change. We examine 1 km resolution Land Surface Temperature (LST) data from NASA's Moderate-resolution Imaging Spectroradiometer (MODIS) combined with 25 km resolution radiometric temperature derived from NASA's Advanced Microwave Scanning Radiometer on EOS (AMSR-E) to develop a capability employing both in combination to assess LST. Since AMSR-E is a microwave remote sensing instrument, products derived from its measurements are minimally effected by cloud cover. On the other hand, MODIS data are heavily influenced by cloud cover. We employ a statistical downscaling technique to the coarse-resolution AMSR-E datasets to enhance its spatial resolution to match that of MODIS. Our approach employs 16-day composite MODIS LST data in combination with synergistic ASMR-E radiometric brightness temperature data to develop a combined, downscaled dataset. Our goal is to use this integrated LST retrieval with complementary in situ station data to examine associated influences on regional biodiversity

Damage extraction of buildings in the 2015 Gorkha, Nepal earthquake from high-resolution SAR data

NASA Astrophysics Data System (ADS)

Yamazaki, Fumio; Bahri, Rendy; Liu, Wen; Sasagawa, Tadashi

2016-05-01

Satellite remote sensing is recognized as one of the effective tools for detecting and monitoring affected areas due to natural disasters. Since SAR sensors can capture images not only at daytime but also at nighttime and under cloud-cover conditions, they are especially useful at an emergency response period. In this study, multi-temporal high-resolution TerraSAR-X images were used for damage inspection of the Kathmandu area, which was severely affected by the April 25, 2015 Gorkha Earthquake. The SAR images obtained before and after the earthquake were utilized for calculating the difference and correlation coefficient of backscatter. The affected areas were identified by high values of the absolute difference and low values of the correlation coefficient. The post-event high-resolution optical satellite images were employed as ground truth data to verify our results. Although it was difficult to estimate the damage levels for individual buildings, the high resolution SAR images could illustrate their capability in detecting collapsed buildings at emergency response times.

Three-dimensional laser microvision.

PubMed

Shimotahira, H; Iizuka, K; Chu, S C; Wah, C; Costen, F; Yoshikuni, Y

2001-04-10

A three-dimensional (3-D) optical imaging system offering high resolution in all three dimensions, requiring minimum manipulation and capable of real-time operation, is presented. The system derives its capabilities from use of the superstructure grating laser source in the implementation of a laser step frequency radar for depth information acquisition. A synthetic aperture radar technique was also used to further enhance its lateral resolution as well as extend the depth of focus. High-speed operation was made possible by a dual computer system consisting of a host and a remote microcomputer supported by a dual-channel Small Computer System Interface parallel data transfer system. The system is capable of operating near real time. The 3-D display of a tunneling diode, a microwave integrated circuit, and a see-through image taken by the system operating near real time are included. The depth resolution is 40 mum; lateral resolution with a synthetic aperture approach is a fraction of a micrometer and that without it is approximately 10 mum.

Exploitation of commercial remote sensing images: reality ignored?

NASA Astrophysics Data System (ADS)

Allen, Paul C.

1999-12-01

The remote sensing market is on the verge of being awash in commercial high-resolution images. Market estimates are based on the growing numbers of planned commercial remote sensing electro-optical, radar, and hyperspectral satellites and aircraft. EarthWatch, Space Imaging, SPOT, and RDL among others are all working towards launch and service of one to five meter panchromatic or radar-imaging satellites. Additionally, new advances in digital air surveillance and reconnaissance systems, both manned and unmanned, are also expected to expand the geospatial customer base. Regardless of platform, image type, or location, each system promises images with some combination of increased resolution, greater spectral coverage, reduced turn-around time (request-to- delivery), and/or reduced image cost. For the most part, however, market estimates for these new sources focus on the raw digital images (from collection to the ground station) while ignoring the requirements for a processing and exploitation infrastructure comprised of exploitation tools, exploitation training, library systems, and image management systems. From this it would appear the commercial imaging community has failed to learn the hard lessons of national government experience choosing instead to ignore reality and replicate the bias of collection over processing and exploitation. While this trend may be not impact the small quantity users that exist today it will certainly adversely affect the mid- to large-sized users of the future.

Using machine learning for real-time estimates of snow water equivalent in the watersheds of Afghanistan

NASA Astrophysics Data System (ADS)

Bair, Edward H.; Abreu Calfa, Andre; Rittger, Karl; Dozier, Jeff

2018-05-01

In the mountains, snowmelt often provides most of the runoff. Operational estimates use imagery from optical and passive microwave sensors, but each has its limitations. An accurate approach, which we validate in Afghanistan and the Sierra Nevada USA, reconstructs spatially distributed snow water equivalent (SWE) by calculating snowmelt backward from a remotely sensed date of disappearance. However, reconstructed SWE estimates are available only retrospectively; they do not provide a forecast. To estimate SWE throughout the snowmelt season, we consider physiographic and remotely sensed information as predictors and reconstructed SWE as the target. The period of analysis matches the AMSR-E radiometer's lifetime from 2003 to 2011, for the months of April through June. The spatial resolution of the predictions is 3.125 km, to match the resolution of a microwave brightness temperature product. Two machine learning techniques - bagged regression trees and feed-forward neural networks - produced similar mean results, with 0-14 % bias and 46-48 mm RMSE on average. Nash-Sutcliffe efficiencies averaged 0.68 for all years. Daily SWE climatology and fractional snow-covered area are the most important predictors. We conclude that these methods can accurately estimate SWE during the snow season in remote mountains, and thereby provide an independent estimate to forecast runoff and validate other methods to assess the snow resource.

Design of refractive fore-optics with wide field of view and waveband for miniature imaging spectrometer

NASA Astrophysics Data System (ADS)

Mao, Jingchao; Xu, Minyi; Liu, Qinghan; Shen, Weimin

2016-10-01

With the development of unmanned airborne vehicle (UAV) remote sensing technology, miniature high-resolution imaging spectrometers are greatly needed. In order to improve remote sensing efficiency and get wider coverage, it's urgent to design and develop fore-optics with wide field of view and waveband for imaging spectrometer. As the refractive system has no central obscuration and it's conducive to manufacture and assemble, so it's used for our fore-optics. The key is the correction of secondary spectrum of systems working in broad waveband and meeting the requirement of imagery telecentricity to be appropriate for linear pushbroom imaging system. Suitable glasses are selected on the Glass Map, from where each glass has an Abbe number υd and Partial Dispersion. Based on the theory of Gaussian Optics and Seidel third-order aberration theory, the paper derives apochromatic formula, and the power of individual lenses can be calculated. Then with a required value of spherical aberration and coma, this paper derives equations to calculate the initial structure of apochromatic optical systems. Finally, optimized refractive SWIR fore-optics working in 1μm-2.5μm with effective focal length (EFFL) of 11mm is reported. Its full field and F-number are respectively 40°, F/2.8. The system has many advantages such as simple and compact structure, small size, near diffraction-limited imaging quality, small secondary spectrum and imagery telecentricity. Especially it consists of spherical surfaces that can greatly reduce the difficulty and the cost of manufacture as well as test, which is applicable for SWIR imaging spectrometer with wide field of view.

Fusion of radar and optical data for mapping and monitoring of water bodies

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyn

2017-10-01

Remote sensing techniques owe their great popularity to the possibility to obtain of rapid, accurate and information over large areas with optimal time, spatial and spectral resolutions. The main areas of interest for remote sensing research had always been concerned with environmental studies, especially water bodies monitoring. Many methods that are using visible and near- an infrared band of the electromagnetic spectrum had been already developed to detect surface water reservoirs. Moreover, the usage of an image obtained in visible and infrared spectrum allows quality monitoring of water bodies. Nevertheless, retrieval of water boundaries and mapping surface water reservoirs with optical sensors is still quite demanding. Therefore, the microwave data could be the perfect complement to data obtained with passive optical sensors to detect and monitor aquatic environment especially surface water bodies. This research presents the methodology to detect water bodies with open- source satellite imagery acquired with both optical and microwave sensors. The SAR Sentinel- 1 and multispectral Sentinel- 2 imagery were used to detect and monitor chosen reservoirs in Poland. In the research Level, 1 Sentinel- 2 data and Level 1 SAR images were used. SAR data were mainly used for mapping water bodies. Next, the results of water boundaries extraction with Sentinel-1 data were compared to results obtained after application of modified spectral indices for Sentinel- 2 data. The multispectral optical data can be used in the future for the evaluation of the quality of the reservoirs. Preliminary results obtained in the research had shown, that the fusion of data obtained with optical and microwave sensors allow for the complex detection of water bodies and could be used in the future quality monitoring of water reservoirs.

Remote sensing of nutrient deficiency in Lactuca sativa using neural networks for terrestrial and advanced life support applications

NASA Astrophysics Data System (ADS)

Sears, Edie Seldon

2000-12-01

A remote sensing study using reflectance and fluorescence spectra of hydroponically grown Lactuca sativa (lettuce) canopies was conducted. An optical receiver was designed and constructed to interface with a commercial fiber optic spectrometer for data acquisition. Optical parameters were varied to determine effects of field of view and distance to target on vegetation stress assessment over the test plant growth cycle. Feedforward backpropagation neural networks (NN) were implemented to predict the presence of canopy stress. Effects of spatial and spectral resolutions on stress predictions of the neural network were also examined. Visual inspection and fresh mass values failed to differentiate among controls, plants cultivated with 25% of the recommended concentration of phosphorous (P), and those cultivated with 25% nitrogen (N) based on fresh mass and visual inspection. The NN's were trained on input vectors created using reflectance and test day, fluorescence and test day, and reflectance, fluorescence, and test day. Four networks were created representing four levels of spectral resolution: 100-nm NN, 10-nm NN, 1-nm NN, and 0.1-nm NN. The 10-nm resolution was found to be sufficient for classifying extreme nitrogen deficiency in freestanding hydroponic lettuce. As a result of leaf angle and canopy structure broadband scattering intensity in the 700-nm to 1000-nm range was found to be the most useful portion of the spectrum in this study. More subtle effects of "greenness" and fluorescence emission were believed to be obscured by canopy structure and leaf orientation. As field of view was not as found to be as significant as originally believed, systems implementing higher repetitions over more uniformly oriented, i.e. smaller, flatter, target areas would provide for more discernible neural network input vectors. It is believed that this technique holds considerable promise for early detection of extreme nitrogen deficiency. Further research is recommended using stereoscopic digital cameras to quantify leaf area index, leaf shape, and leaf orientation as well as reflectance. Given this additional information fluorescence emission may also prove a more useful biological assay of freestanding vegetation.

Detecting ecological change on coral reefs

NASA Astrophysics Data System (ADS)

Dustan, P.

2011-12-01

Remote sensing offers the potential to observe the response of coral reef ecosystems to environmental perturbations on a geographical scale not previously accessible. However, coral reef environments are optically, spatially, and temporally complex habitats which all present significant challenges for extracting meaningful information. Virtually every member of the reef community possesses some degree of photosynthetic capability. The community thus generates a matrix of fine scale features with bio-optical signatures that blend as the scale of observation increases. Furthermore, to have any validity, the remotely sensed signal must be "calibrated" to the bio-optics of the reef, a difficult and resource intensive process due to a convergence of photosynthetic light harvesting by green, red, and brown algal pigment systems. To make matters more complex, reefs are overlain by a seawater skin with its own set of hydrological optical challenges. Rather than concentrating on classification, my research has attempted to track change by following the variation in geo-referenced pixel brightness over time with a technique termed temporal texture. Environmental periodicities impart a phenology to the variation in brightness and departures from the norm are easily detected as statistical outliers. This opens the door to using current orbiting technology to efficiently examine large areas of sea for change. If hot spots are detected, higher resolution sensors and field studies can be focused as resources permit. While this technique does not identify the type of change, it is sensitive, simple to compute, easy to automate and grounded in ecological niche theory

A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling

NASA Astrophysics Data System (ADS)

Dorigo, W. A.; Zurita-Milla, R.; de Wit, A. J. W.; Brazile, J.; Singh, R.; Schaepman, M. E.

2007-05-01

During the last 50 years, the management of agroecosystems has been undergoing major changes to meet the growing demand for food, timber, fibre and fuel. As a result of this intensified use, the ecological status of many agroecosystems has been severely deteriorated. Modeling the behavior of agroecosystems is, therefore, of great help since it allows the definition of management strategies that maximize (crop) production while minimizing the environmental impacts. Remote sensing can support such modeling by offering information on the spatial and temporal variation of important canopy state variables which would be very difficult to obtain otherwise. In this paper, we present an overview of different methods that can be used to derive biophysical and biochemical canopy state variables from optical remote sensing data in the VNIR-SWIR regions. The overview is based on an extensive literature review where both statistical-empirical and physically based methods are discussed. Subsequently, the prevailing techniques of assimilating remote sensing data into agroecosystem models are outlined. The increasing complexity of data assimilation methods and of models describing agroecosystem functioning has significantly increased computational demands. For this reason, we include a short section on the potential of parallel processing to deal with the complex and computationally intensive algorithms described in the preceding sections. The studied literature reveals that many valuable techniques have been developed both for the retrieval of canopy state variables from reflective remote sensing data as for assimilating the retrieved variables in agroecosystem models. However, for agroecosystem modeling and remote sensing data assimilation to be commonly employed on a global operational basis, emphasis will have to be put on bridging the mismatch between data availability and accuracy on one hand, and model and user requirements on the other. This could be achieved by integrating imagery with different spatial, temporal, spectral, and angular resolutions, and the fusion of optical data with data of different origin, such as LIDAR and radar/microwave.

Remote sensing of forest dynamics and land use in Amazonia

NASA Astrophysics Data System (ADS)

Toomey, Michael Paul

The rich, vast Amazonian ecosystem is directly and indirectly threatened by human activities; remote sensing serves as an essential tool for monitoring, understanding and mitigating these threats. A multi-faceted body of work is described here, addressing three major issues that employ and advance remote sensing techniques for the study of Amazonia and other tropical rainforest regions. In Chapter 2, canopy reflectance modeling and satellite observations were used to quantify the effect of epiphylls on remote sensing of humid forests. Modeling simulations demonstrated sensitivity of canopy-level near infrared and green reflectance to epiphylls on leaves. Time series of Moderate Resolution Imaging Spectrometer (MODIS) data corroborated the modeling results, suggesting a degree of coupling between epiphyll cover and vegetation indices which must be accounted for when using optical remote sensing in humid forests. In Chapter 4, 11 years (2000--2010) of MODIS land surface temperature (LST) data covering the entire Amazon basin were used to ascertain the role of heat stress during droughts in 2005 and 2010. Preliminary accuracy assessments showed that LST data provided reasonably accurate estimates of daytime air temperatures (RMSE = 1.45°C; Chapter 3). There were moderate to strong correlations between LST-based air temperature estimates and tower measurements (mean r = 0.64), illustrating a sensitivity to temporal variability. During both droughts, MODIS LST data detected anomalously high daytime and nighttime canopy temperatures throughout drought-affected regions. Multivariate linear models of LST and precipitation anomalies explained 65.1% of the variability in forest biomass losses, as determined from a wide network of forest inventory plots. These results suggest that models should incorporate both heat and moisture to predict drought effects on tropical forests. In Chapter 5, I performed high spatial and temporal resolution modeling of carbon stocks and fluxes in the state of Rondonia, Brazil for the period 1985--2009. Based on this analysis, Rondonia contributed ˜4% of pan-tropical humid forest deforestation emissions while carbon uptake by secondary forest was negligible due to limited spatial extent and high turnover rates. Spatial analysis of land cover change demonstrated the necessity for fine resolution carbon monitoring in tropical regions dominated by non-mechanized, smallholder land uses.

Algorithm and Application of Gcp-Independent Block Adjustment for Super Large-Scale Domestic High Resolution Optical Satellite Imagery

NASA Astrophysics Data System (ADS)

Sun, Y. S.; Zhang, L.; Xu, B.; Zhang, Y.

2018-04-01

The accurate positioning of optical satellite image without control is the precondition for remote sensing application and small/medium scale mapping in large abroad areas or with large-scale images. In this paper, aiming at the geometric features of optical satellite image, based on a widely used optimization method of constraint problem which is called Alternating Direction Method of Multipliers (ADMM) and RFM least-squares block adjustment, we propose a GCP independent block adjustment method for the large-scale domestic high resolution optical satellite image - GISIBA (GCP-Independent Satellite Imagery Block Adjustment), which is easy to parallelize and highly efficient. In this method, the virtual "average" control points are built to solve the rank defect problem and qualitative and quantitative analysis in block adjustment without control. The test results prove that the horizontal and vertical accuracy of multi-covered and multi-temporal satellite images are better than 10 m and 6 m. Meanwhile the mosaic problem of the adjacent areas in large area DOM production can be solved if the public geographic information data is introduced as horizontal and vertical constraints in the block adjustment process. Finally, through the experiments by using GF-1 and ZY-3 satellite images over several typical test areas, the reliability, accuracy and performance of our developed procedure will be presented and studied in this paper.

Historical Analysis of Melt Pond Fraction on Arctic Sea Ice Through the Synthesis of High- and Medium- Resolution Optical Satellite Remote Sensing.

NASA Astrophysics Data System (ADS)

Wright, N.; Polashenski, C. M.

2017-12-01

Snow, ice, and melt ponds cover the surface of the Arctic Ocean in fractions that change throughout the seasons. These surfaces exert tremendous influence over the energy balance of the Arctic Ocean by controlling the absorption of solar radiation. Here we demonstrate the use of a newly released, open source, image classification algorithm designed to identify surface features in high resolution optical satellite imagery of sea ice. Through explicitly resolving individual features on the surface, the algorithm can determine the percentage of ice that is covered by melt ponds with a high degree of certainty. We then compare observations of melt pond fraction extracted from these images with an established method of estimating melt pond fraction from medium resolution satellite images (e.g. MODIS). Because high resolution satellite imagery does not provide the spatial footprint needed to examine the entire Arctic basin, we propose a method of synthesizing both high and medium resolution satellite imagery for an improved determination of melt pond fraction across whole Arctic. We assess the historical trends of melt pond fraction in the Arctic ocean, and address the question: Is pond coverage changing in response to changing ice conditions? Furthermore, we explore the image area that must be observed in order to get a locally representative sample (i.e. the aggregate scale), and show that it is possible to determine accurate estimates of melt pond fraction by observing sample areas significantly smaller than the typical footprint of high-resolution satellite imagery.

Design of a multispectral, wedge filter, remote-sensing instrument incorporating a multiport, thinned, CCD area array

NASA Astrophysics Data System (ADS)

Demro, James C.; Hartshorne, Richard; Woody, Loren M.; Levine, Peter A.; Tower, John R.

1995-06-01

The next generation Wedge Imaging Spectrometer (WIS) instruments currently in integration at Hughes SBRD incorporate advanced features to increase operation flexibility for remotely sensed hyperspectral imagery collection and use. These features include: a) multiple linear wedge filters to tailor the spectral bands to the scene phenomenology; b) simple, replaceable fore-optics to allow different spatial resolutions and coverages; c) data acquisition system (DAS) that collects the full data stream simultaneously from both WIS instruments (VNIR and SWIR/MWIR), stores the data in a RAID storage, and provides for down-loading of the data to MO disks; the WIS DAS also allows selection of the spectral band sets to be stored; d) high-performance VNIR camera subsystem based upon a 512 X 512 CCD area array and associated electronics.

Scanning lidar fluorosensor for remote diagnostic of surfaces

NASA Astrophysics Data System (ADS)

Caneve, Luisa; Colao, Francesco; Fantoni, Roberta; Fiorani, Luca

2013-08-01

Scanning hyperspectral systems based on laser induced fluorescence (LIF) have been developed and realized at the ENEA allowing to obtain information of analytical and qualitative interest on different materials by the study of the emission of fluorescence. This technique, for a surface analysis, is fast, remote, not invasive and specific. A new compact setup capable of fast 2D monochromatic images acquisition on up to 90 different spectral channels in the visible/UV range will be presented. It has been recently built with the aim to increase the performances in terms of space resolution, time resolved capabilities and data acquisition speed. Major achievements have been reached by a critical review of the optical design. The results recently obtained with in-situ measurements of interest for applications in the field of cultural heritage will be shown. 2001 Elsevier Science. All rights reserved

Application of Convolutional Neural Network in Classification of High Resolution Agricultural Remote Sensing Images

NASA Astrophysics Data System (ADS)

Yao, C.; Zhang, Y.; Zhang, Y.; Liu, H.

2017-09-01

With the rapid development of Precision Agriculture (PA) promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN). For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.

Final Technical Report for Interagency Agreement No. DE-SC0005453 “Characterizing Aerosol Distributions, Types, and Optical and Microphysical Properties using the NASA Airborne High Spectral Resolution Lidar (HSRL) and the Research Scanning Polarimeter (RSP)”

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

Hostetler, Chris; Ferrare, Richard

Measurements of the vertical profile of atmospheric aerosols and aerosol optical and microphysical characteristics are required to: 1) determine aerosol direct and indirect radiative forcing, 2) compute radiative flux and heating rate profiles, 3) assess model simulations of aerosol distributions and types, and 4) establish the ability of surface and space-based remote sensors to measure the indirect effect. Consequently the ASR program calls for a combination of remote sensing and in situ measurements to determine aerosol properties and aerosol influences on clouds and radiation. As part of our previous DOE ASP project, we deployed the NASA Langley airborne High Spectralmore » Resolution Lidar (HSRL) on the NASA B200 King Air aircraft during major field experiments in 2006 (MILAGRO and MaxTEX), 2007 (CHAPS), 2009 (RACORO), and 2010 (CalNex and CARES). The HSRL provided measurements of aerosol extinction (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm). These measurements were typically made in close temporal and spatial coincidence with measurements made from DOE-funded and other participating aircraft and ground sites. On the RACORO, CARES, and CalNEX missions, we also deployed the NASA Goddard Institute for Space Studies (GISS) Research Scanning Polarimeter (RSP). RSP provided intensity and degree of linear polarization over a broad spectral and angular range enabling column-average retrievals of aerosol optical and microphysical properties. Under this project, we analyzed observations and model results from RACORO, CARES, and CalNex and accomplished the following objectives. 1. Identified aerosol types, characterize the vertical distribution of the aerosol types, and partition aerosol optical depth by type, for CARES and CalNex using HSRL data as we have done for previous missions. 2. Investigated aerosol microphysical and macrophysical properties using the RSP. 3. Used the aerosol backscatter and extinction profiles measured by the HSRL to characterize the planetary boundary layer height (PBL) and the transition zone thickness, for the RACORO and CARES and CalNex campaigns as we have done for previous campaigns. 4. Investigated how optical properties measured by HSRL vary near clouds. 5. Assessed model simulations of aerosol spatial distributions and optical and microphysical properties.« less

First results from ground-based CO2 remote sounding using high-resolution thermal IR laser heterodyne radiometry

NASA Astrophysics Data System (ADS)

Hoffmann, Alex; Huebner, Marko; Macleod, Neil; Weidmann, Damien

2016-04-01

Over the course of the last decade, the Laser Spectroscopy Group at RAL Space has considerably furthered the passive remote sensing technique of thermal IR Laser Heterodyne Radiometry (LHR), and applied it successfully to the ground-based sounding of atmospheric profiles of a variety of trace gases, including methane. LHR is underpinned by coherent detection technology and ideally shot noise-limited, which can significantly enhance the signal-to-noise ratio of acquired atmospheric spectra over conventional direct detection spectrometers when high spectral (>500,000 resolving power) and high spatial resolutions are needed. These benefits allow probing optimized narrow spectral windows (1 cm-1) with full absorption lineshape information, useful for trace gas vertical profiling. Furthermore, LHR has a high potential for miniaturization into a rugged, unprecedentedly compact package, through hollow waveguide optical integration, facilitating its deployment in ground-based observation networks, as well as on a variety of airborne and spaceborne platforms, whilst retaining its high specifications. This makes LHR well-suited to the remote sounding of key greenhouse gases, in particular carbon dioxide, as observations with high precision and accuracy are crucial to discriminate trends and small variations over a substantial background concentration, and in order to contribute to flux estimations in top-down carbon cycle inversion approaches and anthropogenic emission monitoring. Here, we present a new optical bench-based LHR prototype that has been specifically built to demonstrate CO2 sounding in the thermal IR. The instrument has been coupled to a new permanently installed solar tracker to take a long-term measurement series in solar occultation mode, and to assess the performance of the instrument. We discuss its theoretical performance modelled using an Observation System Simulator, and showcase first results from a 6 months' archive, with observations undergoing gradual refinement as the retrieval method is improved.

Assessing biomass of diverse coastal marsh ecosystems using statistical and machine learning models

NASA Astrophysics Data System (ADS)

Mo, Yu; Kearney, Michael S.; Riter, J. C. Alexis; Zhao, Feng; Tilley, David R.

2018-06-01

The importance and vulnerability of coastal marshes necessitate effective ways to closely monitor them. Optical remote sensing is a powerful tool for this task, yet its application to diverse coastal marsh ecosystems consisting of different marsh types is limited. This study samples spectral and biophysical data from freshwater, intermediate, brackish, and saline marshes in Louisiana, and develops statistical and machine learning models to assess the marshes' biomass with combined ground, airborne, and spaceborne remote sensing data. It is found that linear models derived from NDVI and EVI are most favorable for assessing Leaf Area Index (LAI) using multispectral data (R2 = 0.7 and 0.67, respectively), and the random forest models are most useful in retrieving LAI and Aboveground Green Biomass (AGB) using hyperspectral data (R2 = 0.91 and 0.84, respectively). It is also found that marsh type and plant species significantly impact the linear model development (P < .05 in both cases). Sensors with coarser spatial resolution yield lower LAI values because the fine water networks are not detected and mixed into the vegetation pixels. The Landsat OLI-derived map shows the LAI of coastal mashes in Louisiana mostly ranges from 0 to 5.0, and is highest for freshwater marshes and for marshes in the Atchafalaya Bay delta. The CASI-derived maps show that LAI of saline marshes at Bay Batiste typically ranges from 0.9 to 1.5, and the AGB is mostly less than 900 g/m2. This study provides solutions for assessing the biomass of Louisiana's coastal marshes using various optical remote sensing techniques, and highlights the impacts of the marshes' species composition on the model development and the sensors' spatial resolution on biomass mapping, thereby providing useful tools for monitoring the biomass of coastal marshes in Louisiana and diverse coastal marsh ecosystems elsewhere.

Retrieval Analysis of the CO2 1.6 μm Band in Solar Absorption Spectra Measured by a Ground-Based High-Resolution Fourier Transform Spectrometer at Tsukuba

NASA Astrophysics Data System (ADS)

Ohyama, H.; Morino, I.; Nagahama, T.; Suto, H.; Oguma, H.; Machida, T.; Sugimoto, N.; Nakane, H.; Nakagawa, K.

2006-12-01

The global measurements of greenhouse gases from space are being planned, such as GOSAT (Greenhouse gases Observing SATellite) and OCO (Orbiting Carbon Observatory). Satellite remote sensing needs validations with other measurement techniques, for example, in-situ or sampling measurement by aircraft or ground station, or remote sensing measurement by ground-based Fourier Transform Spectrometer (FTS). The ground-based FTS measurement can provide the column amounts of atmospheric composition by a retrieval analysis with relatively high precision. In 2001, we started a project to observe the atmospheric compositions in solar absorption spectra by a ground- based high-resolution FTS (Bruker IFS 120 HR) located at Tsukuba, Japan. Three years ago, optical components of the FTS were replaced for measuring greenhouse gases such as carbon dioxide (CO2) and methane (CH4) in the near-infrared region: a CaF2 beam splitter, an InSb detector, and a 1.4-2.4 μm optical filter. The measurements were carried out once a day for ~100 days per year. We also made simultaneous FTS and aircraft in-situ measurements on August 10, 2004 and March 30, 2005. The retrieval analysis was performed for the measured spectra in the CO2 1.6 μm band. We used SEASCRAPE PLUS (Sequential Evaluation Algorithm for Simultaneous and Concurrent Retrieval of Atmospheric Parameter Estimates PLUS, Remote Sensing Analysis Systems, Inc.) as a retrieval analysis program. The column amounts were compared with those derived from in-situ measurements complemented by model data; differences are less than 1%. We have derived the diurnal variations of CO2 on the same days as in-situ measurements, and they showed tendencies similar to the tower measurements at the Meteorological Research Institute in Tsukuba.

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.

2001-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands from 0.415 to 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation I will review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of: (1) developing a cloud mask for distinguishing clear sky from clouds, (2) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (3) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (4) determining atmospheric profiles of moisture and temperature, and (5) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 deg (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented. Finally, I will present some highlights from the land and ocean algorithms developed for processing global MODIS observations, including: (1) surface reflectance, (2) vegetation indices, leaf area index, and FPAR, (3) albedo and nadir BRDF-adjusted reflectance, (4) normalized water-leaving radiance, (5) chlorophyll-a concentration, and (6) sea surface temperature.

High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

NASA Astrophysics Data System (ADS)

Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

2018-04-01

With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

In Situ Caging of Biomolecules in Graphene Hybrids for Light Modulated Bioactivity.

PubMed

Cheng, Gong; Han, Xiao-Hui; Hao, Si-Jie; Nisic, Merisa; Zheng, Si-Yang

2018-01-31

Remote and noninvasive modulation of protein activity is essential for applications in biotechnology and medicine. Optical control has emerged as the most attractive approach owing to its high spatial and temporal resolutions; however, it is challenging to engineer light responsive proteins. In this work, a near-infrared (NIR) light-responsive graphene-silica-trypsin (GST) nanoreactor is developed for modulating the bioactivity of trypsin molecules. Biomolecules are spatially confined and protected in the rationally designed compartment architecture, which not only reduces the possible interference but also boosts the bioreaction efficiency. Upon NIR irradiation, the photothermal effect of the GST nanoreactor enables the ultrafast in situ heating for remote activation and tuning of the bioactivity. We apply the GST nanoreactor for remote and ultrafast proteolysis of proteins, which remarkably enhances the proteolysis efficiency and reduces the bioreaction time from the overnight of using free trypsin to seconds. We envision that this work not only provides a promising tool of ultrafast and remotely controllable proteolysis for in vivo proteomics in study of tissue microenvironment and other biomedical applications but also paves the way for exploring smart artificial nanoreactors in biomolecular modulation to gain insight in dynamic biological transformation.

An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

NASA Astrophysics Data System (ADS)

Holben, Brent N.; Kim, Jhoon; Sano, Itaru; Mukai, Sonoyo; Eck, Thomas F.; Giles, David M.; Schafer, Joel S.; Sinyuk, Aliaksandr; Slutsker, Ilya; Smirnov, Alexander; Sorokin, Mikhail; Anderson, Bruce E.; Che, Huizheng; Choi, Myungje; Crawford, James H.; Ferrare, Richard A.; Garay, Michael J.; Jeong, Ukkyo; Kim, Mijin; Kim, Woogyung; Knox, Nichola; Li, Zhengqiang; Lim, Hwee S.; Liu, Yang; Maring, Hal; Nakata, Makiko; Pickering, Kenneth E.; Piketh, Stuart; Redemann, Jens; Reid, Jeffrey S.; Salinas, Santo; Seo, Sora; Tan, Fuyi; Tripathi, Sachchida N.; Toon, Owen B.; Xiao, Qingyang

2018-01-01

Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

Mapping wood density globally using remote sensing and climatological data

NASA Astrophysics Data System (ADS)

Moreno, A.; Camps-Valls, G.; Carvalhais, N.; Kattge, J.; Robinson, N.; Reichstein, M.; Allred, B. W.; Running, S. W.

2017-12-01

Wood density (WD) is defined as the oven-dry mass divided by fresh volume, varies between individuals, and describes the carbon investment per unit volume of stem. WD has been proven to be a key functional trait in carbon cycle research and correlates with numerous morphological, mechanical, physiological, and ecological properties. In spite of the utility and importance of this trait, there is a lack of an operational framework to spatialize plant WD measurements at a global scale. In this work, we present a consistent modular processing chain to derive global maps (500 m) of WD using modern machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data using the Google Earth Engine platform. The developed approach uses a hierarchical Bayesian approach to fill in gaps in the plant measured WD data set to maximize its global representativeness. WD plant species are then aggregated to Plant Functional Types (PFT). The spatial abundance of PFT at 500 m spatial resolution (MODIS) is calculated using a high resolution (30 m) PFT map developed using Landsat data. Based on these PFT abundances, representative WD values are estimated for each MODIS pixel with nearby measured data. Finally, random forests are used to globally estimate WD from these MODIS pixels using remote sensing and climate. The validation and assessment of the applied methods indicate that the model explains more than 72% of the spatial variance of the calculated community aggregated WD estimates with virtually unbiased estimates and low RMSE (<15%). The maps thus offer new opportunities to study and analyze the global patterns of variation of WD at an unprecedented spatial coverage and spatial resolution.

Nonlinear Photonic Systems for V- and W-Band Antenna Remoting Applications

DTIC Science & Technology

2016-10-22

for commercial, academic, and military purposes delivering microwaves through fibers to remote areas for wireless sensing , imaging, and detection...academic, and military purposes, which use optical carriers to deliver microwave signals to remote areas for wireless sensing , imaging, and...and military purposes, which use optical carriers to deliver microwave signals to remote areas for wireless sensing , imaging, and detection

Automated detection of snow avalanche deposits: segmentation and classification of optical remote sensing imagery

NASA Astrophysics Data System (ADS)

Lato, M. J.; Frauenfelder, R.; Bühler, Y.

2012-09-01

Snow avalanches in mountainous areas pose a significant threat to infrastructure (roads, railways, energy transmission corridors), personal property (homes) and recreational areas as well as for lives of people living and moving in alpine terrain. The impacts of snow avalanches range from delays and financial loss through road and railway closures, destruction of property and infrastructure, to loss of life. Avalanche warnings today are mainly based on meteorological information, snow pack information, field observations, historically recorded avalanche events as well as experience and expert knowledge. The ability to automatically identify snow avalanches using Very High Resolution (VHR) optical remote sensing imagery has the potential to assist in the development of accurate, spatially widespread, detailed maps of zones prone to avalanches as well as to build up data bases of past avalanche events in poorly accessible regions. This would provide decision makers with improved knowledge of the frequency and size distributions of avalanches in such areas. We used an object-oriented image interpretation approach, which employs segmentation and classification methodologies, to detect recent snow avalanche deposits within VHR panchromatic optical remote sensing imagery. This produces avalanche deposit maps, which can be integrated with other spatial mapping and terrain data. The object-oriented approach has been tested and validated against manually generated maps in which avalanches are visually recognized and digitized. The accuracy (both users and producers) are over 0.9 with errors of commission less than 0.05. Future research is directed to widespread testing of the algorithm on data generated by various sensors and improvement of the algorithm in high noise regions as well as the mapping of avalanche paths alongside their deposits.

A light and faster regional convolutional neural network for object detection in optical remote sensing images

NASA Astrophysics Data System (ADS)

Ding, Peng; Zhang, Ye; Deng, Wei-Jian; Jia, Ping; Kuijper, Arjan

2018-07-01

Detection of objects from satellite optical remote sensing images is very important for many commercial and governmental applications. With the development of deep convolutional neural networks (deep CNNs), the field of object detection has seen tremendous advances. Currently, objects in satellite remote sensing images can be detected using deep CNNs. In general, optical remote sensing images contain many dense and small objects, and the use of the original Faster Regional CNN framework does not yield a suitably high precision. Therefore, after careful analysis we adopt dense convoluted networks, a multi-scale representation and various combinations of improvement schemes to enhance the structure of the base VGG16-Net for improving the precision. We propose an approach to reduce the test-time (detection time) and memory requirements. To validate the effectiveness of our approach, we perform experiments using satellite remote sensing image datasets of aircraft and automobiles. The results show that the improved network structure can detect objects in satellite optical remote sensing images more accurately and efficiently.

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.

Photon-efficient super-resolution laser radar

NASA Astrophysics Data System (ADS)

Shin, Dongeek; Shapiro, Jeffrey H.; Goyal, Vivek K.

2017-08-01

The resolution achieved in photon-efficient active optical range imaging systems can be low due to non-idealities such as propagation through a diffuse scattering medium. We propose a constrained optimization-based frame- work to address extremes in scarcity of photons and blurring by a forward imaging kernel. We provide two algorithms for the resulting inverse problem: a greedy algorithm, inspired by sparse pursuit algorithms; and a convex optimization heuristic that incorporates image total variation regularization. We demonstrate that our framework outperforms existing deconvolution imaging techniques in terms of peak signal-to-noise ratio. Since our proposed method is able to super-resolve depth features using small numbers of photon counts, it can be useful for observing fine-scale phenomena in remote sensing through a scattering medium and through-the-skin biomedical imaging applications.

Hyperspectral Remote Sensing of the Coastal Ocean: Adaptive Sampling and Forecasting of In situ Optical Properties

DTIC Science & Technology

2002-09-30

integrated observation system that is being coupled to a data assimilative hydrodynamic bio-optical ecosystem model. The system was used adaptively to develop hyperspectral remote sensing techniques in optically complex nearshore coastal waters.

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.

Portable open-path optical remote sensing (ORS) Fourier transform infrared (FTIR) instrumentation miniaturization and software for point and click real-time analysis

NASA Astrophysics Data System (ADS)

Zemek, Peter G.; Plowman, Steven V.

2010-04-01

Advances in hardware have miniaturized the emissions spectrometer and associated optics, rendering them easily deployed in the field. Such systems are also suitable for vehicle mounting, and can provide high quality data and concentration information in minutes. Advances in software have accompanied this hardware evolution, enabling the development of portable point-and-click OP-FTIR systems that weigh less than 16 lbs. These systems are ideal for first-responders, military, law enforcement, forensics, and screening applications using optical remote sensing (ORS) methodologies. With canned methods and interchangeable detectors, the new generation of OP-FTIR technology is coupled to the latest forward reference-type model software to provide point-and-click technology. These software models have been established for some time. However, refined user-friendly models that use active, passive, and solar occultation methodologies now allow the user to quickly field-screen and quantify plumes, fence-lines, and combustion incident scenarios in high-temporal-resolution. Synthetic background generation is now redundant as the models use highly accurate instrument line shape (ILS) convolutions and several other parameters, in conjunction with radiative transfer model databases to model a single calibration spectrum to collected sample spectra. Data retrievals are performed directly on single beam spectra using non-linear classical least squares (NLCLS). Typically, the Hitran line database is used to generate the initial calibration spectrum contained within the software.

Expected Improvements in the Quantitative Remote Sensing of Optically Complex Waters with the Use of an Optically Fast Hyperspectral Spectrometer—A Modeling Study

PubMed Central

Moses, Wesley J.; Bowles, Jeffrey H.; Corson, Michael R.

2015-01-01

Using simulated data, we investigated the effect of noise in a spaceborne hyperspectral sensor on the accuracy of the atmospheric correction of at-sensor radiances and the consequent uncertainties in retrieved water quality parameters. Specifically, we investigated the improvement expected as the F-number of the sensor is changed from 3.5, which is the smallest among existing operational spaceborne hyperspectral sensors, to 1.0, which is foreseeable in the near future. With the change in F-number, the uncertainties in the atmospherically corrected reflectance decreased by more than 90% across the visible-near-infrared spectrum, the number of pixels with negative reflectance (caused by over-correction) decreased to almost one-third, and the uncertainties in the retrieved water quality parameters decreased by more than 50% and up to 92%. The analysis was based on the sensor model of the Hyperspectral Imager for the Coastal Ocean (HICO) but using a 30-m spatial resolution instead of HICO’s 96 m. Atmospheric correction was performed using Tafkaa. Water quality parameters were retrieved using a numerical method and a semi-analytical algorithm. The results emphasize the effect of sensor noise on water quality parameter retrieval and the need for sensors with high Signal-to-Noise Ratio for quantitative remote sensing of optically complex waters. PMID:25781507

Towards non-contact photo-acoustic endoscopy using speckle pattern analysis

NASA Astrophysics Data System (ADS)

Lengenfelder, Benjamin; Mehari, Fanuel; Tang, Yuqi; Klämpfl, Florian; Zalevsky, Zeev; Schmidt, Michael

2017-03-01

Photoacoustic Tomography combines the advantages of optical and acoustic imaging as it makes use of the high optical contrast of tissue and the high resolution of ultrasound. Furthermore, high penetration depths in tissue in the order of several centimeters can be achieved by the combination of these modalities. Extensive research is being done in the field of miniaturization of photoacoustic devices, as photoacoustic imaging could be of significant benefits for the physician during endoscopic interventions. All the existing miniature systems are based on contact transducers for signal detection that are placed at the distal end of an endoscopic device. This makes the manufacturing process difficult and impedance matching to the inspected surface a requirement. The requirement for contact limits the view of the physician during the intervention. Consequently, a fiber based non-contact optical sensing technique would be highly beneficial for the development of miniaturized photoacoustic endoscopic devices. This work demonstrates the feasibility of surface displacement detection using remote speckle-sensing using a high speed camera and an imaging fiber bundle that is used in commercially available video endoscopes. The feasibility of displacement sensing is demonstrated by analysis of phantom vibrations which are induced by loudspeaker membrane oscillations. Since the usability of the remote speckle-sensing for photo-acoustic signal detection was already demonstrated, the fiber bundle approach demonstrates the potential for non-contact photoacoustic detections during endoscopy.

Las Cumbres Observatory 1-Meter Global Science Telescope Network

NASA Astrophysics Data System (ADS)

Pickles, Andrew; Dubberley, M.; Haldeman, B.; Haynes, R.; Posner, V.; Rosing, W.; staff, LCOGT

2009-05-01

We present the optical, mechanical and electronic design of the LCOGT 1-m telescope. These telescopes are planned to go in pairs to each of 6 sites worldwide, complementing 0.4m telescopes and 2-m telescopes at two existing sites. This science network is designed to provide continuously available photometric monitoring and spectroscopy of variable sources. The 1-m optical design is an f/8 quasi-RC system, with a doublet corrector and field flattener to provide good image quality out to 0.8 degrees. The field of view of the Fairchild 4K science CCD is 27 arcmin, with 0.39 arcsec pixels. The mechanical design includes a stiff C-ring equatorial mount and friction drive rollers, mounted on a triangular base that can be adjusted for latitude. Another friction drive is coupled at the Declination axis to the M1 mirror cell, that forms the main Optical Tube Assembly (OTA) structural element. The OTA design includes a stiff carbon fiber truss assembly, with offset vanes to an M2 drive that provides remote focus, tilt and collimation. The tube assembly weighs about 600 Kg, including Hextek mirrors, 4K science CCD, filter wheel, autoguiders and medium resolution spectrograph pick-off fiber. The telescopes will be housed in domes at existing observatory sites. They are designed to operate remotely and reliably under centralized control for automatic, optimized scheduling of observations with available hardware.

Evaluation and Validation of Case 2 Algorithms in Chesapeake Bay

NASA Technical Reports Server (NTRS)

Harding, Lawrence W., Jr.; Magnuson, Adrea

2004-01-01

The high temporal and spatial resolution of satellite ocean color observations will prove invaluable for monitoring the health of coastal ecosystems where physical and biological variability demands sampling scales beyond that possible by ship. However, ocean color remote sensing of Case 2 waters is a challenging undertaking due to the optical complexity of the water. The focus of this SIMBIOS support has been to provide in situ optical measurements form Chesapeake Bay (CB) and adjacent mid-Atlantic bight (MAB) waters for use in algorithm development and validation efforts to improve the satellite retrieval of chlorophyll (chl a) in Case 2 waters. CB provides a valuable site for validation of data from ocean color sensors for a number of reasons. First, the physical dimensions of the Bay (greater than 6,500 square kilometers) make retrievals from satellites with a spatial resolution of approximately 1 kilometer (i.e., SeaWiFS) or less (i.e., MODIS) reasonable for most of the ecosystem. Second, CB is highly influenced by freshwater flow from major rivers, making it a classic Case 2 water body with significant concentrations of chlorophyll, particulates and chromophoric dissolved organic matter (CDOM) that highly impact the shape of reflectance spectra. Finally, past and ongoing research efforts provided an expensive data set of optical observations that support the goal of this project.

Object-based classification of earthquake damage from high-resolution optical imagery using machine learning

NASA Astrophysics Data System (ADS)

Bialas, James; Oommen, Thomas; Rebbapragada, Umaa; Levin, Eugene

2016-07-01

Object-based approaches in the segmentation and classification of remotely sensed images yield more promising results compared to pixel-based approaches. However, the development of an object-based approach presents challenges in terms of algorithm selection and parameter tuning. Subjective methods are often used, but yield less than optimal results. Objective methods are warranted, especially for rapid deployment in time-sensitive applications, such as earthquake damage assessment. Herein, we used a systematic approach in evaluating object-based image segmentation and machine learning algorithms for the classification of earthquake damage in remotely sensed imagery. We tested a variety of algorithms and parameters on post-event aerial imagery for the 2011 earthquake in Christchurch, New Zealand. Results were compared against manually selected test cases representing different classes. In doing so, we can evaluate the effectiveness of the segmentation and classification of different classes and compare different levels of multistep image segmentations. Our classifier is compared against recent pixel-based and object-based classification studies for postevent imagery of earthquake damage. Our results show an improvement against both pixel-based and object-based methods for classifying earthquake damage in high resolution, post-event imagery.

Multiorder etalon sounder (MOES) development and test for balloon experiment

NASA Technical Reports Server (NTRS)

Hays, Paul B.; Wnag, Jinxue; Wu, Jian

1993-01-01

The Fabry-Perot interferometer (FPI), with its high throughput and high spectral resolution has been used in the remote-sensing measurements of the earth's atmospheric composition, winds, and temperatures. The most recent satellite instruments include the Fabry-Perot interferometer flown on the Dynamics Explorer-2 (DE-2), the High Resolution Doppler Imager (HRDI), and the Cryogenic Limb Array Etalon Spectrometer (CLAES) flown on the Upper Atmosphere Research Satellite (UARS). These instruments measure the Doppler line profiles of the emission and absorption of certain atmospheric species (such as atomic oxygen) in the visible and infrared spectral region. The successful space flight of DE-FPI, HRDI, and CLAES on UARS demonstrated the extremely high spectral resolution and ruggedness of the etalon system for the remote sensing of earth and planetary atmospheres. Recently, an innovative FPI focal plane detection technique called the Circle-to-Line Interferometer Optical (CLIO) system was invented at the Space Physics Research Laboratory. The CLIO simplifies the FPI focal plane detection process by converting the circular rings or fringes into a linear pattern similar to that produced by a conventional spectrometer, while retaining the throughput advantage of the etalon interferometer. The combination of FPI and CLIO allows the development of more sensitive Fabry-Perot interferometers in the infrared for the remote sensing of the lower atmospheres of Earth and possibly other planets. The Multiorder Etalon Sounder (MOES), a combination of the rugged etalon and the CLIO, compares very favorably to other space-borne optical instruments in terms of performance versus complexity. The new instrument is expected to be rugged, compact, and very suitable for an operational temperature and moisture sounder. With this technique, the contamination of radiance measurements by emissions of other gases is also minimized. At the Space Physics Research Laboratory (SPRL), the MOES concept and laboratory experiments were worked on for the past several years. Both theoretical studies and laboratory prototype experiments showed that MOES is very competitive compared with other high resolution sounders in terms of complexity and performance and has great potential as a compact and rugged high resolution atmospheric temperature and trace species sounder from the polar platform or the geostationary platform. The logical next step is to convert our laboratory prototype to a balloon instrument, so that field test of MOES can be carried out to prove the feasibility and capability of this new technology. Some of the activities related to the development of MOES for a possible balloon flight demonstration are described. Those research activities include the imaging quality study on the CLIO, the design and construction of a MOES laboratory prototype, the test and calibration of the MOES prototype, and the design of the balloon flight gondola.

Towards identification of relevant variables in the observed aerosol optical depth bias between MODIS and AERONET observations

NASA Astrophysics Data System (ADS)

Malakar, N. K.; Lary, D. J.; Gencaga, D.; Albayrak, A.; Wei, J.

2013-08-01

Measurements made by satellite remote sensing, Moderate Resolution Imaging Spectroradiometer (MODIS), and globally distributed Aerosol Robotic Network (AERONET) are compared. Comparison of the two datasets measurements for aerosol optical depth values show that there are biases between the two data products. In this paper, we present a general framework towards identifying relevant set of variables responsible for the observed bias. We present a general framework to identify the possible factors influencing the bias, which might be associated with the measurement conditions such as the solar and sensor zenith angles, the solar and sensor azimuth, scattering angles, and surface reflectivity at the various measured wavelengths, etc. Specifically, we performed analysis for remote sensing Aqua-Land data set, and used machine learning technique, neural network in this case, to perform multivariate regression between the ground-truth and the training data sets. Finally, we used mutual information between the observed and the predicted values as the measure of similarity to identify the most relevant set of variables. The search is brute force method as we have to consider all possible combinations. The computations involves a huge number crunching exercise, and we implemented it by writing a job-parallel program.

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...

SU-E-T-675: Remote Dosimetry with a Novel PRESAGE Formulation

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

Mein, S; Juang, T; Malcolm, J

2015-06-15

Purpose: 3D-gel dosimetry provides high-resolution treatment validation; however, scanners aren’t widely available. In remote dosimetry, dosimeters are shipped out from a central base institution to a remote site for irradiation, then shipped back for scanning and analysis, affording a convenient service for treatment validation to institutions lacking the necessary equipment and resources. Previous works demonstrated the high-resolution performance and temporal stability of PRESAGE. Here the newest formulation is investigated for remote dosimetry use. Methods: A new formulation of PRESAGE was created with the aim of improved color stability post irradiation. Dose sensitivity was determined by irradiating cuvettes on a Varianmore » Linac (6MV) from 0–15Gy and measuring change in optical density at 633nm. Sensitivity readings were tracked over time in a temperature control study to determine long-term stability. A large volume study was performed to evaluate the accuracy for remote dosimetry. A 1kg dosimeter was pre-scanned, irradiated on-site with an 8Gy 4field box treatment, post-scanned and shipped to Princess Margaret Hospital for remote reading on an identical scanner. Results: Dose sensitivities ranged from 0.0194–0.0295 ΔOD/(Gy*cm)—similar to previous formulations. Post-irradiated cuvettes stored at 10°C retained 100% initial sensitivity over 5 days and 98.6% over 10 weeks while cuvettes stored at room temperature fell to 95.8% after 5 days and 37.4% after 10 weeks. The immediate and 5-day scans of the 4field box dosimeter data was reconstructed, registered to the corresponding eclipse dose-distribution, and compared with analytical tools in CERR. Immediate and 5-day scans looked visually similar. Line profiles revealed close agreement aside from a slight elevation in dose at the edge in the 5-day readout. Conclusion: The remote dosimetry formulation exhibits excellent temporal stability in small volumes. While immediate and 5-day readout scans of large volume dosimeters show promising agreement, further development is required to reduce an apparent time dependent edge elevation.« less

Charactering lidar optical subsystem using four quadrants method

NASA Astrophysics Data System (ADS)

Tian, Xiaomin; Liu, Dong; Xu, Jiwei; Wang, Zhenzhu; Wang, Bangxin; Wu, Decheng; Zhong, Zhiqing; Xie, Chenbo; Wang, Yingjian

2018-02-01

Lidar is a kind of active optical remote sensing instruments , can be applied to sound atmosphere with a high spatial and temporal resolution. Many parameter of atmosphere can be get by using different inverse algorithm with lidar backscatter signal. The basic setup of a lidar consist of a transmitter and a receiver. To make sure the quality of lidar signal data, the lidar must be calibrated before being used to measure the atmospheric variables. It is really significant to character and analyze lidar optical subsystem because a well equiped lidar optical subsystem contributes to high quality lidar signal data. we pay close attention to telecover test to character and analyze lidar optical subsystem.The telecover test is called four quadrants method consisting in dividing the telescope aperture in four quarants. when a lidar is well configured with lidar optical subsystem, the normalized signal from four qudrants will agree with each other on some level. Testing our WARL-II lidar by four quadrants method ,we find the signals of the four basically consistent with each other both in near range and in far range. But in detail, the signals in near range have some slight distinctions resulting from overlap function, some signals distinctions are induced by atmospheric instability.

Multispectral remote sensing from unmanned aircraft: image processing workflows and applications for rangeland environments

USDA-ARS?s Scientific Manuscript database

Using unmanned aircraft systems (UAS) as remote sensing platforms offers the unique ability for repeated deployment for acquisition of high temporal resolution data at very high spatial resolution. Most image acquisitions from UAS have been in the visible bands, while multispectral remote sensing ap...

Remote Sensing of Ocean Color in the Arctic: Algorithm Development and Comparative Validation. Chapter 9

NASA Technical Reports Server (NTRS)

Cota, Glenn F.

2001-01-01

The overall goal of this effort is to acquire a large bio-optical database, encompassing most environmental variability in the Arctic, to develop algorithms for phytoplankton biomass and production and other optically active constituents. A large suite of bio-optical and biogeochemical observations have been collected in a variety of high latitude ecosystems at different seasons. The Ocean Research Consortium of the Arctic (ORCA) is a collaborative effort between G.F. Cota of Old Dominion University (ODU), W.G. Harrison and T. Platt of the Bedford Institute of Oceanography (BIO), S. Sathyendranath of Dalhousie University and S. Saitoh of Hokkaido University. ORCA has now conducted 12 cruises and collected over 500 in-water optical profiles plus a variety of ancillary data. Observational suites typically include apparent optical properties (AOPs), inherent optical property (IOPs), and a variety of ancillary observations including sun photometry, biogeochemical profiles, and productivity measurements. All quality-assured data have been submitted to NASA's SeaWIFS Bio-Optical Archive and Storage System (SeaBASS) data archive. Our algorithm development efforts address most of the potential bio-optical data products for the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and GLI, and provides validation for a specific areas of concern, i.e., high latitudes and coastal waters.

Assessment of Spacecraft Operational Status Using Electro-Optical Predictive Techniques

DTIC Science & Technology

2010-09-01

panel appendages, may require enhanced preflight characterization processes to support monitoring by passive, remote, nonimaging optical sensors...observing and characterizing key spacecraft features. The simulation results are based on electro-optical signatures apparent to nonimaging sensors, along...and communication equipment, may require enhanced preflight characterization processes to support monitoring by passive, remote, nonimaging optical

Mobile inductively coupled plasma system

DOEpatents

D'Silva, Arthur P.; Jaselskis, Edward J.

1999-03-30

A system for sampling and analyzing a material located at a hazardous site. A laser located remote from the hazardous site is connected to an optical fiber, which directs laser radiation proximate the material at the hazardous site. The laser radiation abates a sample of the material. An inductively coupled plasma is located remotely from the material. An aerosol transport system carries the ablated particles to a plasma, where they are dissociated, atomized and excited to provide characteristic optical reduction of the elemental constituents of the sample. An optical spectrometer is located remotely from the site. A second optical fiber is connected to the optical spectrometer at one end and the plasma source at the other end to carry the optical radiation from the plasma source to the spectrometer.

Examining the Impact of Overlying Aerosols on the Retrieval of Cloud Optical Properties from Passive Remote Sensing

NASA Technical Reports Server (NTRS)

Coddington, O. M.; Pilewskie, P.; Redemann, J.; Platnick, S.; Russell, P. B.; Schmidt, K. S.; Gore, W. J.; Livingston, J.; Wind, G.; Vukicevic, T.

2010-01-01

Haywood et al. (2004) show that an aerosol layer above a cloud can cause a bias in the retrieved cloud optical thickness and effective radius. Monitoring for this potential bias is difficult because space ]based passive remote sensing cannot unambiguously detect or characterize aerosol above cloud. We show that cloud retrievals from aircraft measurements above cloud and below an overlying aerosol layer are a means to test this bias. The data were collected during the Intercontinental Chemical Transport Experiment (INTEX-A) study based out of Portsmouth, New Hampshire, United States, above extensive, marine stratus cloud banks affected by industrial outflow. Solar Spectral Flux Radiometer (SSFR) irradiance measurements taken along a lower level flight leg above cloud and below aerosol were unaffected by the overlying aerosol. Along upper level flight legs, the irradiance reflected from cloud top was transmitted through an aerosol layer. We compare SSFR cloud retrievals from below ]aerosol legs to satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to detect an aerosol ]induced bias. In regions of small variation in cloud properties, we find that SSFR and MODIS-retrieved cloud optical thickness compares within the uncertainty range for each instrument while SSFR effective radius tend to be smaller than MODIS values (by 1-2 microns) and at the low end of MODIS uncertainty estimates. In regions of large variation in cloud properties, differences in SSFR and MODIS ]retrieved cloud optical thickness and effective radius can reach values of 10 and 10 microns, respectively. We include aerosols in forward modeling to test the sensitivity of SSFR cloud retrievals to overlying aerosol layers. We find an overlying absorbing aerosol layer biases SSFR cloud retrievals to smaller effective radii and optical thickness while nonabsorbing aerosols had no impact.

Object-oriented recognition of high-resolution remote sensing image

NASA Astrophysics Data System (ADS)

Wang, Yongyan; Li, Haitao; Chen, Hong; Xu, Yuannan

2016-01-01

With the development of remote sensing imaging technology and the improvement of multi-source image's resolution in satellite visible light, multi-spectral and hyper spectral , the high resolution remote sensing image has been widely used in various fields, for example military field, surveying and mapping, geophysical prospecting, environment and so forth. In remote sensing image, the segmentation of ground targets, feature extraction and the technology of automatic recognition are the hotspot and difficulty in the research of modern information technology. This paper also presents an object-oriented remote sensing image scene classification method. The method is consist of vehicles typical objects classification generation, nonparametric density estimation theory, mean shift segmentation theory, multi-scale corner detection algorithm, local shape matching algorithm based on template. Remote sensing vehicles image classification software system is designed and implemented to meet the requirements .

Active Ground Optical Remote Sensing for Improved Monitoring of Seedling Stress in Nurseries

USDA-ARS?s Scientific Manuscript database

Active ground optical remote sensing (AGORS) devices mounted on overhead irrigation booms could help to improve seedling quality by autonomously monitoring seedling stress. In contrast to traditionally used passive optical sensors, AGORS devices operate independently of ambient light conditions and ...

Cloud Radiative Forcing at the ARM Climate Research Facility. Part 1; Technique, Validation, and Comparison to Satellite-derived Diagnostic Quantities

NASA Technical Reports Server (NTRS)

Mace, Gerald G.; Benson, Sally; Sonntag, Karen L.; Kato, Seiji; Min, Qilong; Minnis, Patrick; Twohy, Cynthia H.; Poellot, Michael; Dong, Xiquan; Long, Charles;

A mission-oriented orbit design method of remote sensing satellite for region monitoring mission based on evolutionary algorithm

NASA Astrophysics Data System (ADS)

Shen, Xin; Zhang, Jing; Yao, Huang

2015-12-01

Remote sensing satellites play an increasingly prominent role in environmental monitoring and disaster rescue. Taking advantage of almost the same sunshine condition to same place and global coverage, most of these satellites are operated on the sun-synchronous orbit. However, it brings some problems inevitably, the most significant one is that the temporal resolution of sun-synchronous orbit satellite can't satisfy the demand of specific region monitoring mission. To overcome the disadvantages, two methods are exploited: the first one is to build satellite constellation which contains multiple sunsynchronous satellites, just like the CHARTER mechanism has done; the second is to design non-predetermined orbit based on the concrete mission demand. An effective method for remote sensing satellite orbit design based on multiobjective evolution algorithm is presented in this paper. Orbit design problem is converted into a multi-objective optimization problem, and a fast and elitist multi-objective genetic algorithm is utilized to solve this problem. Firstly, the demand of the mission is transformed into multiple objective functions, and the six orbit elements of the satellite are taken as genes in design space, then a simulate evolution process is performed. An optimal resolution can be obtained after specified generation via evolution operation (selection, crossover, and mutation). To examine validity of the proposed method, a case study is introduced: Orbit design of an optical satellite for regional disaster monitoring, the mission demand include both minimizing the average revisit time internal of two objectives. The simulation result shows that the solution for this mission obtained by our method meet the demand the users' demand. We can draw a conclusion that the method presented in this paper is efficient for remote sensing orbit design.

UniScan technology for innovative laboratory at a university for acquisition data from space in real-time

NASA Astrophysics Data System (ADS)

Gershenzon, V.; Gershenzon, O.; Sergeeva, M.; Ippolitov, V.; Targulyan, O.

2012-04-01

Keywords: Remote Sensing, UniScan ground station, Education, Monitoring. Remote Sensing Centers allowing real-time imagery acquisition from Earth observing satellites within the structure of Universities provides proper environment for innovative education. It delivers the efficient training for scientific and academic and teaching personnel, secure the role of the young professionals in science, education and hi-tech, and maintain the continuity of generations in science and education. Article is based on experience for creation such centers in more than 20 higher education institutions in Russia, Kazakhstan, and Spain on the base of UniScan ground station by R&D Center ScanEx. These stations serve as the basis for Earth monitoring from space providing the training and advanced training to produce the specialists having the state-of-the-art knowledge in Earth Remote Sensing and GIS, as well as the land-use monitoring and geo-data service for the economic operators in such diverse areas as the nature resource management, agriculture, land property management, disasters monitoring, etc. Currently our proposal of UniScan for universities all over the world allows to receive low resolution free of charge MODIS data from Terra and Aqua satellites, VIIRS from the NPP mission, and also high resolution optical images from EROS A and radar images from Radarsat-1 satellites, including the telemetry for the first year of operation, within the footprint of up to 2,500 kilometers in radius. Creation remote sensing centers at universities will lead to a new quality level for education and scientific studies and will enable to make education system in such innovation institutions open to modern research work and economy.

Evaluation of 3-D Air Quality System Remotely-Sensed Aerosol Optical Depth for the Baltimore/Washington Metropolitan Air Shed

NASA Astrophysics Data System (ADS)

Weber, S. A.; Engel-Cox, J. A.; Hoff, R. M.; Prados, A.; Zhang, H.

2008-12-01

Integrating satellite- and ground-based aerosol optical depth (AOD) observations with surface total fine particulate (PM2.5) and sulfate concentrations allows for a more comprehensive understanding of local- and urban-scale air quality. This study evaluates the utility of integrated databases being developed for NOAA and EPA through the 3D-AQS project by examining the relationship between remotely-sensed AOD and PM2.5 concentrations for each platform for the summer of 2004 and the entire year of 2005. We compare results for the Baltimore, MD/Washington, DC metropolitan air shed, incorporating AOD products from the Terra and GOES-12 satellites, AERONET sunphotometer, and ground-based lidar, and PM2.5 concentrations from five surface monitoring sites. The satellite-derived products include AOD from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR), as well as the GOES Aerosol/Smoke Product (GASP). The vertical profile of lidar backscatter is used to retrieve the planetary boundary layer (PBL) height in an attempt to capture only that fraction of the AOD arising from near surface aerosols. Adjusting the AOD data using platform- and season-specific ratios, calculated using the parameters of the regression equations, for two case studies resulted in a more accurate representation of surface PM2.5 concentrations when compared to a constant ratio that is currently being used in the NOAA IDEA product. This work demonstrates that quantitative relationships between remotely-sensed and in-situ aerosol observations in an integrated database can be computed and applied to improve the use of remotely-sensed observations for estimating surface concentrations.

Creating Aerosol Types from CHemistry (CATCH): A New Algorithm to Extend the Link Between Remote Sensing and Models

NASA Astrophysics Data System (ADS)

Dawson, K. W.; Meskhidze, N.; Burton, S. P.; Johnson, M. S.; Kacenelenbogen, M. S.; Hostetler, C. A.; Hu, Y.

2017-11-01

Current remote sensing methods can identify aerosol types within an atmospheric column, presenting an opportunity to incrementally bridge the gap between remote sensing and models. Here a new algorithm was designed for Creating Aerosol Types from CHemistry (CATCH). CATCH-derived aerosol types—dusty mix, maritime, urban, smoke, and fresh smoke—are based on first-generation airborne High Spectral Resolution Lidar (HSRL-1) retrievals during the Ship-Aircraft Bio-Optical Research (SABOR) campaign, July/August 2014. CATCH is designed to derive aerosol types from model output of chemical composition. CATCH-derived aerosol types are determined by multivariate clustering of model-calculated variables that have been trained using retrievals of aerosol types from HSRL-1. CATCH-derived aerosol types (with the exception of smoke) compare well with HSRL-1 retrievals during SABOR with an average difference in aerosol optical depth (AOD) <0.03. Data analysis shows that episodic free tropospheric transport of smoke is underpredicted by the Goddard Earth Observing System- with Chemistry (GEOS-Chem) model. Spatial distributions of CATCH-derived aerosol types for the North American model domain during July/August 2014 show that aerosol type-specific AOD values occurred over representative locations: urban over areas with large population, maritime over oceans, smoke, and fresh smoke over typical biomass burning regions. This study demonstrates that model-generated information on aerosol chemical composition can be translated into aerosol types analogous to those retrieved from remote sensing methods. In the future, spaceborne HSRL-1 and CATCH can be used to gain insight into chemical composition of aerosol types, reducing uncertainties in estimates of aerosol radiative forcing.

Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments

PubMed Central

Lee, ZhongPing; Carder, Kendall; Arnone, Robert; He, MingXia

2007-01-01

About 30 years ago, NASA launched the first ocean-color observing satellite: the Coastal Zone Color Scanner. CZCS had 5 bands in the visible-infrared domain with an objective to detect changes of phytoplankton (measured by concentration of chlorophyll) in the oceans. Twenty years later, for the same objective but with advanced technology, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 7 bands), the Moderate-Resolution Imaging Spectrometer (MODIS, 8 bands), and the Medium Resolution Imaging Spectrometer (MERIS, 12 bands) were launched. The selection of the number of bands and their positions was based on experimental and theoretical results achieved before the design of these satellite sensors. Recently, Lee and Carder (2002) demonstrated that for adequate derivation of major properties (phytoplankton biomass, colored dissolved organic matter, suspended sediments, and bottom properties) in both oceanic and coastal environments from observation of water color, it is better for a sensor to have ∼15 bands in the 400 – 800 nm range. In that study, however, it did not provide detailed analyses regarding the spectral locations of the 15 bands. Here, from nearly 400 hyperspectral (∼ 3-nm resolution) measurements of remote-sensing reflectance (a measure of water color) taken in both coastal and oceanic waters covering both optically deep and optically shallow waters, first- and second-order derivatives were calculated after interpolating the measurements to 1-nm resolution. From these derivatives, the frequency of zero values for each wavelength was accounted for, and the distribution spectrum of such frequencies was obtained. Furthermore, the wavelengths that have the highest appearance of zeros were identified. Because these spectral locations indicate extrema (a local maximum or minimum) of the reflectance spectrum or inflections of the spectral curvature, placing the bands of a sensor at these wavelengths maximizes the potential of capturing (and then restoring) the spectral curve, and thus maximizes the potential of accurately deriving properties of the water column and/or bottom of various aquatic environments with a multi-band sensor. PMID:28903303

Fluid Lensing and Applications to Remote Sensing of Aquatic Environments

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2017-01-01

The use of fluid lensing technology on UAVs is presented as a novel means for 3D imaging of aquatic ecosystems from above the water's surface at the centimeter scale. Preliminary results are presented from airborne fluid lensing campaigns conducted over the coral reefs of Ofu Island, American Samoa (2013) and the stromatolite reefs of Shark Bay, Western Australia (2014), covering a combined area of 15km2. These reef ecosystems were revealed with centimetre-scale 2D resolution, and an accompanying 3D bathymetry model was derived using fluid lensing, Structure from Motion and UAV position data. Data products were validated from in-situ survey methods including underwater calibration targets, depth measurements and millimetre-scale high-dynamic range gigapixel photogrammetry. Fluid lensing is an experimental technology that uses water transmitting wavelengths to passively image underwater objects at high-resolution by exploiting time-varying optical lensing events caused by surface waves. Fluid lensing data are captured from low-altitude, cost-effective electric UAVs to achieve multispectral imagery and bathymetry models at the centimetre scale over regional areas. As a passive system, fluid lensing is presently limited by signal-to-noise ratio and water column inherent optical properties to approximately 10 m depth over visible wavelengths in clear waters. The datasets derived from fluid lensing present the first centimetre-scale images of a reef acquired from above the ocean surface, without wave distortion. The 3D multispectral data distinguish coral, fish and invertebrates in American Samoa, and reveal previously undocumented, morphologically distinct, stromatolite structures in Shark Bay. These findings suggest fluid lensing and multirotor electric drones represent a promising advance in the remote sensing of aquatic environments at the centimetre scale, or 'reef scale' relevant to the conservation of reef ecosystems. Pending further development and validation of fluid lensing methods, these technologies present a solution for large-scale 3D surveys of shallow aquatic habitats with centimetre-scale spatial resolution and hourly temporal sampling.

Monitoring flood extent and area through multi-sensor, multi-temporal remote sensing: the Strymonas (Greece) river flood

NASA Astrophysics Data System (ADS)

Refice, Alberto; Tijani, Khalid; Lovergine, Francesco P.; D'Addabbo, Annarita; Nutricato, Raffaele; Morea, Alberto

2017-04-01

Satellite monitoring of flood events at high spatial and temporal resolution is considered a difficult problem, mainly due to the lack of data with sufficient acquisition frequency and timeliness. The problem is worsened by the typically cloudy weather conditions associated to floods, which obstacle the propagation of e.m. waves in the optical spectral range, forbidding acquisitions by optical sensors. This problem is not present for longer wavelengths, so that radar imaging sensors are recognized as viable solutions for long-term flood monitoring. In selected cases, however, weather conditions may remain clear for sufficient amounts of time, enabling monitoring of the evolution of flood events through long time series of satellite images, both optical and radar. In this contribution, we present a case study of long-term integrated monitoring of a flood event which affected part of the Strymonas river basin, a transboundary river with source in Bulgaria, which flows then through Greece up to the Aegean Sea. The event, which affected the floodplain close to the river mouth, started at the beginning of April 2015, due to heavy rain, and lasted for several months, with some water pools still present at the beginning of September. Due to the arid climate characterizing the area, weather conditions were cloud-free for most of the period covering the event. We collected one high-resolution, X-band, COSMO-SkyMed, 5 C-band, Sentinel-1 SAR images, and 11 optical Landsat-8 images of the area. SAR images were calibrated, speckle-filtered and precisely geocoded; optical images were radiometrically corrected to obtain ground reflectance values from which NDVI maps were derived. The images were then thresholded to obtain binary flood maps for each day. Threshold values for microwave and optical data were calibrated by comparing one SAR and one optical image acquired on the same date. Results allow to draw a multi-temporal map of the flood evolution with high temporal resolution. The extension of flooded area can also be tracked in time, allowing to envisage testing of evapotranspiration/absorption models.

International Space Station Remote Sensing Pointing Analysis

NASA Technical Reports Server (NTRS)

Jacobson, Craig A.

2007-01-01

This paper analyzes the geometric and disturbance aspects of utilizing the International Space Station for remote sensing of earth targets. The proposed instrument (in prototype development) is SHORE (Station High-Performance Ocean Research Experiment), a multiband optical spectrometer with 15 m pixel resolution. The analysis investigates the contribution of the error effects to the quality of data collected by the instrument. This analysis supported the preliminary studies to determine feasibility of utilizing the International Space Station as an observing platform for a SHORE type of instrument. Rigorous analyses will be performed if a SHORE flight program is initiated. The analysis begins with the discussion of the coordinate systems involved and then conversion from the target coordinate system to the instrument coordinate system. Next the geometry of remote observations from the Space Station is investigated including the effects of the instrument location in Space Station and the effects of the line of sight to the target. The disturbance and error environment on Space Station is discussed covering factors contributing to drift and jitter, accuracy of pointing data and target and instrument accuracies.

Progress in remote sensing of global land surface heat fluxes and evaporations with a turbulent heat exchange parameterization method

NASA Astrophysics Data System (ADS)

Chen, Xuelong; Su, Bob

2017-04-01

Remote sensing has provided us an opportunity to observe Earth land surface with a much higher resolution than any of GCM simulation. Due to scarcity of information for land surface physical parameters, up-to-date GCMs still have large uncertainties in the coupled land surface process modeling. One critical issue is a large amount of parameters used in their land surface models. Thus remote sensing of land surface spectral information can be used to provide information on these parameters or assimilated to decrease the model uncertainties. Satellite imager could observe the Earth land surface with optical, thermal and microwave bands. Some basic Earth land surface status (land surface temperature, canopy height, canopy leaf area index, soil moisture etc.) has been produced with remote sensing technique, which already help scientists understanding Earth land and atmosphere interaction more precisely. However, there are some challenges when applying remote sensing variables to calculate global land-air heat and water exchange fluxes. Firstly, a global turbulent exchange parameterization scheme needs to be developed and verified, especially for global momentum and heat roughness length calculation with remote sensing information. Secondly, a compromise needs to be innovated to overcome the spatial-temporal gaps in remote sensing variables to make the remote sensing based land surface fluxes applicable for GCM model verification or comparison. A flux network data library (more 200 flux towers) was collected to verify the designed method. Important progress in remote sensing of global land flux and evaporation will be presented and its benefits for GCM models will also be discussed. Some in-situ studies on the Tibetan Plateau and problems of land surface process simulation will also be discussed.

Remote sensing-based Information for crop monitoring: contribution of SAR and Moderate resolution optical data on Asian rice production

NASA Astrophysics Data System (ADS)

Boschetti, Mirco; Holectz, Francesco; Manfron, Giacinto; Collivignarelli, Francesco; Nelson, Andrew

2013-04-01

Updated information on crop typology and status are strongly required to support suitable action to better manage agriculture production and reduce food insecurity. In this field, remote sensing has been demonstrated to be a suitable tool to monitor crop condition however rarely the tested system became really operative. The ones today available, such as the European Commission MARS, are mainly based on the analysis of NDVI time series and required ancillary external information like crop mask to interpret the seasonal signal. This condition is not always guarantied worldwide reducing the potentiality of the remote sensing monitoring. Moreover in tropical countries cloud contamination strongly reduce the possibility of using optical remote sensing data for crop monitoring. In this framework we focused our analysis on the rice production monitoring in Asian tropical area. Rice is in fact the staple food for half of the world population (FAO 2004), in Asia almost 90% of the world's rice is produced and consumed and Rice and poverty often coincide. In this contest the production of reliable rice production information is of extreme interest. We tried to address two important issue in terms of required geospatial information for crop monitoring: rice crop detection (rice map) and seasonal dynamics analysis (phenology). We use both SAR and Optical data in order to exploit the potential complementarity of this system. Multi-temporal ASAR Wide Swath data are in fact the best option to deal with cloud contamination. SAR can easily penetrate the clouds providing information on the surface target. Temporal analysis of archive ASAR data allowed to derived accurate map, at 100m spatial resolution, of permanent rice cultivated areas. On the other and high frequency revisiting optical data, in this case MODIS, have been used to extract seasonal information for the year under analysis. MOD09A1 Surface Reflectance 8-Day L3 Global 500m have been exploited to derive time series of Vegetation Index. A temporal smoothing procedure based on Savitzky-Golay polynomial filter function was applied to the original 8-day composite VI data (EVI and NDVI) in order to eliminate spurious data which affect the time series and to produce an interpolated VI temporal profile. Finally within the area previously identify as rice by SAR analysis phenological estimation have been conducted. Crop growth minima and maxima, respectively indicator of rice transplanting and heading, have been identify from the derivative analysis time series. This procedure was tested in Bangladesh for the year 2011. Results showed that the combined use of both data typology represents the more suitable multisource framework to provide reliable information on rice crop growth. Preliminary maps analysis reveals how SAR rice detection was in agreement with local information and phenology extracted by MODIS data provided spatially distributed data comparable with local knowledge of crop calendar.

Accuracy of remote electrocardiogram interpretation with the use of Google Glass technology.

PubMed

Jeroudi, Omar M; Christakopoulos, George; Christopoulos, George; Kotsia, Anna; Kypreos, Megan A; Rangan, Bavana V; Banerjee, Subhash; Brilakis, Emmanouil S

2015-02-01

We sought to investigate the accuracy of remote electrocardiogram (ECG) interpretation using Google Glass (Google, Mountain View, California). Google Glass is an optical head mounted display device with growing applications in medicine. We compared interpretation of 10 ECGs with 21 clinically important findings by faculty and fellow cardiologists by (1) viewing the electrocardiographic image at the Google Glass screen; (2) viewing a photograph of the ECG taken using Google Glass and interpreted on a mobile device; (3) viewing the original paper ECG; and (4) viewing a photograph of the ECG taken with a high-resolution camera and interpreted on a mobile device. One point was given for identification of each correct finding. Subjective rating of the user experience was also recorded. Twelve physicians (4 faculty and 8 fellow cardiologists) participated. The average electrocardiographic interpretation score (maximum 21 points) as viewed through the Google Glass, Google Glass photograph on a mobile device, on paper, and high-resolution photograph on a mobile device was 13.5 ± 1.8, 16.1 ± 2.6, 18.3 ± 1.7, and 18.6 ± 1.5, respectively (p = 0.0005 between Google Glass and mobile device, p = 0.0005 between Google Glass and paper, and p = 0.002 between mobile device and paper). Of the 12 physicians, 9 (75%) were dissatisfied with ECGs viewing on the prism display of Google Glass. In conclusion, further improvements are needed before Google Glass can be reliably used for remote electrocardiographic analysis. Published by Elsevier Inc.

Remote sensing of methane with OSAS-lidar on the 2ν3 band Q-branch: Experimental proof

NASA Astrophysics Data System (ADS)

Galtier, Sandrine; Anselmo, Christophe; Welschinger, Jean-Yves; Sivignon, J. F.; Cariou, Jean-Pierre; Miffre, Alain; Rairoux, Patrick

2018-06-01

Optical sensors based on absorption spectroscopy play a central role in the detection and monitoring of atmospheric trace gases. We here present for the first time the experimental demonstration of OSAS-Lidar on the remote sensing of CH4 in the atmosphere. This new methodology, the OSAS-Lidar, couples the Optical Similitude Absorption Spectroscopy (OSAS) methodology with a light detection and ranging device. It is based on the differential absorption of spectrally integrated signals following Beer Lambert-Bouguer law, which are range-resolved. Its novelty originates from the use of broadband laser spectroscopy and from the mathematical approach used to retrieve the trace gas concentration. We previously applied the OSAS methodology in laboratory on the 2ν3 methane absorption band, centered at the 1665 nm wavelength and demonstrated that the OSAS-methodology is almost independent from atmospheric temperature and pressure. In this paper, we achieve an OSAS-Lidar device capable of observing large concentrations of CH4 released from a methane source directly into the atmosphere. Comparison with a standard in-situ measurement device shows that the path-integrated concentrations retrieved from OSAS-Lidar methodology exhibit sufficient sensitivity (2 000 ppm m) and observational time resolution (1 s) to remotely sense methane leaks in the atmosphere. The coupling of OSAS-lidar with a wind measurement device opens the way to monitor time-resolved methane flux emissions, which is important in regards to future climate mitigation involving regional reduction of CH4 flux emissions.

Impact of dam failure-induced flood on road network using combined remote sensing and geospatial approach

NASA Astrophysics Data System (ADS)

Foumelis, Michael

2017-01-01

The applicability of the normalized difference water index (NDWI) to the delineation of dam failure-induced floods is demonstrated for the case of the Sparmos dam (Larissa, Central Greece). The approach followed was based on the differentiation of NDWI maps to accurately define the extent of the inundated area over different time spans using multimission Earth observation optical data. Besides using Landsat data, for which the index was initially designed, higher spatial resolution data from Sentinel-2 mission were also successfully exploited. A geospatial analysis approach was then introduced to rapidly identify potentially affected segments of the road network. This allowed for further correlation to actual damages in the following damage assessment and remediation activities. The proposed combination of geographic information systems and remote sensing techniques can be easily implemented by local authorities and civil protection agencies for mapping and monitoring flood events.

Advanced Multispectral Scanner (AMS) study. [aircraft remote sensing

NASA Technical Reports Server (NTRS)

1978-01-01

The status of aircraft multispectral scanner technology was accessed in order to develop preliminary design specifications for an advanced instrument to be used for remote sensing data collection by aircraft in the 1980 time frame. The system designed provides a no-moving parts multispectral scanning capability through the exploitation of linear array charge coupled device technology and advanced electronic signal processing techniques. Major advantages include: 10:1 V/H rate capability; 120 deg FOV at V/H = 0.25 rad/sec; 1 to 2 rad resolution; high sensitivity; large dynamic range capability; geometric fidelity; roll compensation; modularity; long life; and 24 channel data acquisition capability. The field flattening techniques of the optical design allow wide field view to be achieved at fast f/nos for both the long and short wavelength regions. The digital signal averaging technique permits maximization of signal to noise performance over the entire V/H rate range.

SENTINEL-1 and SENTINEL-2 Data Fusion for Wetlands Mapping: Balikdami, Turkey

NASA Astrophysics Data System (ADS)

Kaplan, G.; Avdan, U.

2018-04-01

Wetlands provide a number of environmental and socio-economic benefits such as their ability to store floodwaters and improve water quality, providing habitats for wildlife and supporting biodiversity, as well as aesthetic values. Remote sensing technology has proven to be a useful and frequent application in monitoring and mapping wetlands. Combining optical and microwave satellite data can help with mapping and monitoring the biophysical characteristics of wetlands and wetlands` vegetation. Also, fusing radar and optical remote sensing data can increase the wetland classification accuracy. In this paper, data from the fine spatial resolution optical satellite, Sentinel-2 and the Synthetic Aperture Radar Satellite, Sentinel-1, were fused for mapping wetlands. Both Sentinel-1 and Sentinel-2 images were pre-processed. After the pre-processing, vegetation indices were calculated using the Sentinel-2 bands and the results were included in the fusion data set. For the classification of the fused data, three different classification approaches were used and compared. The results showed significant improvement in the wetland classification using both multispectral and microwave data. Also, the presence of the red edge bands and the vegetation indices used in the data set showed significant improvement in the discrimination between wetlands and other vegetated areas. The statistical results of the fusion of the optical and radar data showed high wetland mapping accuracy, showing an overall classification accuracy of approximately 90 % in the object-based classification method. For future research, we recommend multi-temporal image use, terrain data collection, as well as a comparison of the used method with the traditional image fusion techniques.

Disaggregation of remotely sensed soil moisture under all sky condition using machine learning approach in Northeast Asia

NASA Astrophysics Data System (ADS)

Kim, S.; Kim, H.; Choi, M.; Kim, K.

2016-12-01

Estimating spatiotemporal variation of soil moisture is crucial to hydrological applications such as flood, drought, and near real-time climate forecasting. Recent advances in space-based passive microwave measurements allow the frequent monitoring of the surface soil moisture at a global scale and downscaling approaches have been applied to improve the spatial resolution of passive microwave products available at local scale applications. However, most downscaling methods using optical and thermal dataset, are valid only in cloud-free conditions; thus renewed downscaling method under all sky condition is necessary for the establishment of spatiotemporal continuity of datasets at fine resolution. In present study Support Vector Machine (SVM) technique was utilized to downscale a satellite-based soil moisture retrievals. The 0.1 and 0.25-degree resolution of daily Land Parameter Retrieval Model (LPRM) L3 soil moisture datasets from Advanced Microwave Scanning Radiometer 2 (AMSR2) were disaggregated over Northeast Asia in 2015. Optically derived estimates of surface temperature (LST), normalized difference vegetation index (NDVI), and its cloud products were obtained from MODerate Resolution Imaging Spectroradiometer (MODIS) for the purpose of downscaling soil moisture in finer resolution under all sky condition. Furthermore, a comparison analysis between in situ and downscaled soil moisture products was also conducted for quantitatively assessing its accuracy. Results showed that downscaled soil moisture under all sky condition not only preserves the quality of AMSR2 LPRM soil moisture at 1km resolution, but also attains higher spatial data coverage. From this research we expect that time continuous monitoring of soil moisture at fine scale regardless of weather conditions would be available.

VizieR Online Data Catalog: Spectroscopy of EG And over roughly 14 years (Kenyon+, 2016)

NASA Astrophysics Data System (ADS)

Kenyon, S. J.; Garcia, M. R.

2016-08-01

From 1994 September to 2016 January, P. Berlind, M. Calkins, and other observers acquired 480 low-resolution optical spectra of EG And with FAST, a high throughput, slit spectrograph mounted at the Fred L. Whipple Observatory 1.5m telescope on Mount Hopkins, Arizona They used a 300g/mm grating blazed at 4750Å, a 3'' slit, and a thinned 512*2688 CCD. These spectra cover 3800-7500Å at a resolution of 6Å. The full wavelength solution is derived from calibration lamps acquired immediately after each exposure. The wavelength solution for each frame has a probable error of <~+/-0.5Å. Most of the resulting spectra have moderate signal-to-noise ratio, S/N >~15-30 per pixel. Prior to the start of the FAST observations, we obtained occasional optical spectrophotometric observations of EG And throughout 1982-1989 with the cooled dual-beam intensified Reticon scanner (IRS) mounted on the white spectrograph at the KPNO No. 1 and No. 2 90cm telescopes. Various remote observers acquired high-resolution spectroscopic observations of EG And with the echelle spectrographs and Reticon detectors on the 1.5m telescopes of the Fred L. Whipple Observatory on Mount Hopkins, Arizona and the Oak Ridge Observatory in Harvard, Massachusetts. These spectra cover a 44Å bandpass centered near 5190Å or 5200Å and have a resolution of roughly 12km/s. (1 data file).

The use of EO Optical data for the Italian Supersites volcanoes monitoring

NASA Astrophysics Data System (ADS)

Silvestri, Malvina

2016-04-01

This work describes the INGV experience in the capability to import many different EO optical data into in house developed systems and to maintain a repository where the acquired data have been stored. These data are used for generating selected products which are functional to face the different volcanic activity phases. Examples on the processing of long time series based EO data of Mt Etna activity and Campi Flegrei observation by using remote sensing techniques and at different spatial resolution data (ASTER - 90mt, AVHRR -1km, MODIS-1km, MSG SEVIRI-3km) are also showed. Both volcanoes belong to Italian Supersites initiative of the geohazard scientific community. In the frame of the EC FP7 MED-SUV project (call FP7 ENV.2012.6.4-2), this work wants to describe the main activities concerning the generation of brightness temperature map from the satellite data acquired in real-time from INGV MEOS Multi-mission Antenna (for MODIS, Moderate Resolution Imaging Spectroradiometer and geostationary satellite data) and AVHRR-TERASCAN (for AVHRR, Advanced Very High Resolution Radiometer data). The advantage of direct download of EO data by means INGV antennas (with particular attention to AVHRR and MODIS) even though low spatial resolution offers the possibility of a systematic data processing having a daily updating of information for prompt response and hazard mitigation. At the same time it has been necessary the use of large archives to inventory and monitor dynamic and dangerous phenomena, like volcanic activity, globally.

Laser And Nonlinear Optical Materials For Laser Remote Sensing

NASA Technical Reports Server (NTRS)

Barnes, Norman P.

2005-01-01

NASA remote sensing missions involving laser systems and their economic impact are outlined. Potential remote sensing missions include: green house gasses, tropospheric winds, ozone, water vapor, and ice cap thickness. Systems to perform these measurements use lanthanide series lasers and nonlinear devices including second harmonic generators and parametric oscillators. Demands these missions place on the laser and nonlinear optical materials are discussed from a materials point of view. Methods of designing new laser and nonlinear optical materials to meet these demands are presented.

The research of road and vehicle information extraction algorithm based on high resolution remote sensing image

NASA Astrophysics Data System (ADS)

Zhou, Tingting; Gu, Lingjia; Ren, Ruizhi; Cao, Qiong

2016-09-01

With the rapid development of remote sensing technology, the spatial resolution and temporal resolution of satellite imagery also have a huge increase. Meanwhile, High-spatial-resolution images are becoming increasingly popular for commercial applications. The remote sensing image technology has broad application prospects in intelligent traffic. Compared with traditional traffic information collection methods, vehicle information extraction using high-resolution remote sensing image has the advantages of high resolution and wide coverage. This has great guiding significance to urban planning, transportation management, travel route choice and so on. Firstly, this paper preprocessed the acquired high-resolution multi-spectral and panchromatic remote sensing images. After that, on the one hand, in order to get the optimal thresholding for image segmentation, histogram equalization and linear enhancement technologies were applied into the preprocessing results. On the other hand, considering distribution characteristics of road, the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to suppress water and vegetation information of preprocessing results. Then, the above two processing result were combined. Finally, the geometric characteristics were used to completed road information extraction. The road vector extracted was used to limit the target vehicle area. Target vehicle extraction was divided into bright vehicles extraction and dark vehicles extraction. Eventually, the extraction results of the two kinds of vehicles were combined to get the final results. The experiment results demonstrated that the proposed algorithm has a high precision for the vehicle information extraction for different high resolution remote sensing images. Among these results, the average fault detection rate was about 5.36%, the average residual rate was about 13.60% and the average accuracy was approximately 91.26%.

Construction of a small and lightweight hyperspectral imaging system

NASA Astrophysics Data System (ADS)

Vogel, Britta; Hünniger, Dirk; Bastian, Georg

2014-05-01

The analysis of the reflected sunlight offers great opportunity to gain information about the environment, including vegetation and soil. In the case of plants the wavelength ratio of the reflected light usually undergoes a change if the state of growth or state of health changes. So the measurement of the reflected light allows drawing conclusions about the state of, amongst others, vegetation. Using a hyperspectral imaging system for data acquisition leads to a large dataset, which can be evaluated with respect to several different questions to obtain various information by one measurement. Based on commercially available plain optical components we developed a small and lightweight hyperspectral imaging system within the INTERREG IV A-Project SMART INSPECTORS. The project SMART INSPECTORS [Smart Aerial Test Rigs with Infrared Spectrometers and Radar] deals with the fusion of airborne visible and infrared imaging remote sensing instruments and wireless sensor networks for precision agriculture and environmental research. A high performance camera was required in terms of good signal, good wavelength resolution and good spatial resolution, while severe constraints of size, proportions and mass had to be met due to the intended use on small unmanned aerial vehicles. The detector was chosen to operate without additional cooling. The refractive and focusing optical components were identified by supporting works with an optical raytracing software and a self-developed program. We present details of design and construction of our camera system, test results to confirm the optical simulation predictions as well as our first measurements.

Hyperspectral Remote Sensing of Atmospheric Profiles from Satellites and Aircraft

NASA Technical Reports Server (NTRS)

Smith, W. L.; Zhou, D. K.; Harrison, F. W.; Revercomb, H. E.; Larar, A. M.; Huang, H. L.; Huang, B.

2001-01-01

A future hyperspectral resolution remote imaging and sounding system, called the GIFTS (Geostationary Imaging Fourier Transform Spectrometer), is described. An airborne system, which produces the type of hyperspectral resolution sounding data to be achieved with the GIFTS, has been flown on high altitude aircraft. Results from simulations and from the airborne measurements are presented to demonstrate the revolutionary remote sounding capabilities to be realized with future satellite hyperspectral remote imaging/sounding systems.

Mobile inductively coupled plasma system

DOEpatents

D`Silva, A.P.; Jaselskis, E.J.

1999-03-30

A system is described for sampling and analyzing a material located at a hazardous site. A laser located remotely from the hazardous site is connected to an optical fiber, which directs laser radiation proximate the material at the hazardous site. The laser radiation abates a sample of the material. An inductively coupled plasma is located remotely from the material. An aerosol transport system carries the ablated particles to a plasma, where they are dissociated, atomized and excited to provide characteristic optical reduction of the elemental constituents of the sample. An optical spectrometer is located remotely from the site. A second optical fiber is connected to the optical spectrometer at one end and the plasma source at the other end to carry the optical radiation from the plasma source to the spectrometer. 10 figs.

Global Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Riedi, Jerome C.; Baum, Bryan A.

2003-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4,2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua, and will show characteristics of cloud optical and microphysical properties as a function of latitude for land and ocean separately, and contrast the statistical properties of similar cloud types in various parts of the world.

Review on Photonic Generation of Chirp Arbitrary Microwave Waveforms for Remote Sensing Application

NASA Astrophysics Data System (ADS)

Raghuwanshi, Sanjeev Kumar; Srivastav, Akash; Athokpam, Bidhanshel Singh

2017-12-01

A novel technique to generate an arbitrary chirped waveform by harnessing features of lithium niobate (LiNb O_3) Mach-Zehnder modulator is proposed and demonstrated. The most important application of chirped microwave waveform is that, it improves the range resolution of radar. Microwave photonics system provides high bandwidth capabilities of fiber-optic systems and also contains the ability to provide interconnect transmission properties, which are virtually independent of length. The low-loss wide bandwidth capability of optoelectronic systems makes them attractive for the transmission and processing of microwave signals, while the development of high-capacity optical communication systems has required the use of microwave techniques in optical transmitters and receivers. These two strands have led to the development of the research area of microwave photonics. So, it should be consider that microwave photonics as the field that studies the interaction between microwave and optical waves for applications such as communications, radars, sensors and instrumentations. In this paper, we have thoroughly reviewed the arbitrary chirped microwave generation techniques by using photonics technology.

Very high resolution observations of waves in the OH airglow at low latitudes.

NASA Astrophysics Data System (ADS)

Franzen, Christoph; Espy, Patrick J.; Hibbins, Robert E.; Djupvik, Amanda A.

2017-04-01

Vibrationally excited hydroxyl (OH) is produced in the mesosphere by the reaction of atomic hydrogen and ozone. This excited OH radiates a strong, near-infrared airglow emission in a thin ( 8 km thick) layer near 87 km. In the past, remote sensing of perturbations in the OH Meinel airglow has often been used to observe gravity, tidal and planetary waves travelling through this region. However, information on the highest frequency gravity waves is often limited by the temporal and spatial resolution of the available observations. In an effort to expand the wave scales present near the mesopause, we present a series of observations of the OH Meinel (9,7) transition that were executed with the Nordic Optical Telescope on La Palma (18°W, 29°N). These measurements are taken with a 10 s integration time (24 s repetition rate), and the spatial resolution at 87 km is as small as 10 m, allowing us to quantify the transition between the gravity and acoustic wave domains in the mesosphere.

OPTiM: Optical projection tomography integrated microscope using open-source hardware and software

PubMed Central

Andrews, Natalie; Davis, Samuel; Bugeon, Laurence; Dallman, Margaret D.; McGinty, James

2017-01-01

We describe the implementation of an OPT plate to perform optical projection tomography (OPT) on a commercial wide-field inverted microscope, using our open-source hardware and software. The OPT plate includes a tilt adjustment for alignment and a stepper motor for sample rotation as required by standard projection tomography. Depending on magnification requirements, three methods of performing OPT are detailed using this adaptor plate: a conventional direct OPT method requiring only the addition of a limiting aperture behind the objective lens; an external optical-relay method allowing conventional OPT to be performed at magnifications >4x; a remote focal scanning and region-of-interest method for improved spatial resolution OPT (up to ~1.6 μm). All three methods use the microscope’s existing incoherent light source (i.e. arc-lamp) and all of its inherent functionality is maintained for day-to-day use. OPT acquisitions are performed on in vivo zebrafish embryos to demonstrate the implementations’ viability. PMID:28700724

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

PubMed Central

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

PubMed

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

TH-CD-BRA-11: Implementation and Evaluation of a New 3D Dosimetry Protocol for Validating MRI Guided Radiation Therapy Treatments

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

Mein, S; Rankine, L; Department of Radiation Oncology, Washington University School of Medicine

Purpose: To develop, evaluate and apply a novel high-resolution 3D remote dosimetry protocol for validation of MRI guided radiation therapy treatments (MRIdian by ViewRay™). We demonstrate the first application of the protocol (including two small but required new correction terms) utilizing radiochromic 3D plastic PRESAGE™ with optical-CT readout. Methods: A detailed study of PRESAGE™ dosimeters (2kg) was conducted to investigate the temporal and spatial stability of radiation induced optical density change (ΔOD) over 8 days. Temporal stability was investigated on 3 dosimeters irradiated with four equally-spaced square 6MV fields delivering doses between 10cGy and 300cGy. Doses were imaged (read-out) bymore » optical-CT at multiple intervals. Spatial stability of ΔOD response was investigated on 3 other dosimeters irradiated uniformly with 15MV extended-SSD fields with doses of 15cGy, 30cGy and 60cGy. Temporal and spatial (radial) changes were investigated using CERR and MATLAB’s Curve Fitting Tool-box. A protocol was developed to extrapolate measured ΔOD readings at t=48hr (the typical shipment time in remote dosimetry) to time t=1hr. Results: All dosimeters were observed to gradually darken with time (<5% per day). Consistent intra-batch sensitivity (0.0930±0.002 ΔOD/cm/Gy) and linearity (R2=0.9996) was observed at t=1hr. A small radial effect (<3%) was observed, attributed to curing thermodynamics during manufacture. The refined remote dosimetry protocol (including polynomial correction terms for temporal and spatial effects, CT and CR) was then applied to independent dosimeters irradiated with MR-IGRT treatments. Excellent line profile agreement and 3D-gamma results for 3%/3mm, 10% threshold were observed, with an average passing rate 96.5%± 3.43%. Conclusion: A novel 3D remote dosimetry protocol is presented capable of validation of advanced radiation treatments (including MR-IGRT). The protocol uses 2kg radiochromic plastic dosimeters read-out by optical-CT within a week of treatment. The protocol requires small corrections for temporal and spatially-dependent behaviors observed between irradiation and readout.« less

Fiber-Coupled Acousto-Optical-Filter Spectrometer

NASA Technical Reports Server (NTRS)

Levin, Kenneth H.; Li, Frank Yanan

1993-01-01

Fiber-coupled acousto-optical-filter spectrometer steps rapidly through commanded sequence of wavelengths. Sample cell located remotely from monochromator and associated electronic circuitry, connected to them with optical fibers. Optical-fiber coupling makes possible to monitor samples in remote, hazardous, or confined locations. Advantages include compactness, speed, and no moving parts. Potential applications include control of chemical processes, medical diagnoses, spectral imaging, and sampling of atmospheres.

Remote artificial eyes using micro-optical circuit for long-distance 3D imaging perception.

PubMed

Thammawongsa, Nopparat; Yupapin, Preecha P

2016-01-01

A small-scale optical device incorporated with an optical nano-antenna is designed to operate as the remote artificial eye using a tiny conjugate mirror. A basic device known as a conjugate mirror can be formed using the artificial eye device, the partially reflected light intensities from input source are interfered and the 3D whispering gallery modes formed within the ring centers, which can be modulated and propagated to the object. The image pixel is obtained at the center ring and linked with the optic nerve in the remote area via the nano-antenna, which is useful for blind people.

A consideration of the use of optical fibers to remotely couple photometers to telescopes

NASA Technical Reports Server (NTRS)

Heacox, William D.

1988-01-01

The possible use of optical fibers to remotely couple photometers to telescopes is considered. Such an application offers the apparent prospect of enhancing photometric stability as a consequence of the benefits of remote operation and decreased sensitivity to image details. A properly designed fiber optic coupler will probably show no significant changes in optical transmisssion due to normal variations in the fiber configuration. It may be more difficult to eliminate configuration-dependent effects on the pupil of the transmitted beam, and thus achieve photometric stability to guiding and seeing errors. In addition, there is some evidence for significant changes in the optical throughputs of fibers over the temperature range normally encountered in astronomical observatories.

Spatial and Temporal Distribution of Tropospheric Clouds and Aerosols Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Menzel, W. Paul; Ackerman, Steven A.; Remer, Lorraine A.

2006-01-01

Remote sensing of cloud and aerosol optical properties is routinely obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites. Instruments that are being used to enhance our ability to characterize the global distribution of cloud and aerosol properties include well-calibrated multispectral radiometers that measure in the visible, near-infrared, and thermal infrared. The availability of thermal channels to enhance detection of cloud when estimating aerosol properties is an important improvement. In this paper, we describe the radiative properties of clouds as currently determined from satellites (cloud fraction, optical thickness, cloud top pressure, and cloud particle effective radius) and highlight the global/regional cloud microphysical properties currently available for assessing climate variability and forcing. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective particle radius for selected geographical locations around the world. In addition, we will illustrate the radiative and microphysical properties of aerosol particles (in cloud free regions) that are currently available from space-based observations, and show the latitudinal distribution of aerosol optical properties over both land and ocean surfaces.

Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.

2005-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven

2005-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

Experimental demonstration of 1.5Hz passive isolation system for precision optical payloads

NASA Astrophysics Data System (ADS)

Guan, Xin; Wang, Guang-yuan; Cao, Dong-jing; Tang, Shao-fan; Chen, Xiang; Liang, Lu; Zheng, Gang-tie

2017-11-01

The ground resolution of remote sensing satellite has been raised from hundreds of meters to less than one meter in recent few decades. As a result, the precision optical payload becomes more and more sensitive to structure vibrations of satellite buses. Although these vibrations generally have extremely low magnitude, they can result in significant image quality degradation to an optical payload. The suggestion of using vibration isolators to isolate payload from the satellite bus has been put forward in 1980s'[1]. Recently, WorldView-2 achieved its perfect image quality via using a set of low frequency isolators[2]. Recently, some of the optical payload manufacturers begin to provide vibration isolators as standard parts together with their main products . During the prototype testing of an earth resource satellite, the image of the optical payload was found to jitter for 5 10 pixels due to disturbances transmitted from the satellite bus structure. Test results indicated that the acceleration level of the vibration was of mG magnitude. To solve the problem, a highly sensitive vibration isolation system was developed to reduce the transmission of disturbances. Integrated isolation performance tests showed that the image jitter can be decreased to below 0.3 pixels.

Combined imaging and chemical sensing using a single optical imaging fiber.

PubMed

Bronk, K S; Michael, K L; Pantano, P; Walt, D R

1995-09-01

Despite many innovations and developments in the field of fiber-optic chemical sensors, optical fibers have not been employed to both view a sample and concurrently detect an analyte of interest. While chemical sensors employing a single optical fiber or a noncoherent fiberoptic bundle have been applied to a wide variety of analytical determinations, they cannot be used for imaging. Similarly, coherent imaging fibers have been employed only for their originally intended purpose, image transmission. We herein report a new technique for viewing a sample and measuring surface chemical concentrations that employs a coherent imaging fiber. The method is based on the deposition of a thin, analyte-sensitive polymer layer on the distal surface of a 350-microns-diameter imaging fiber. We present results from a pH sensor array and an acetylcholine biosensor array, each of which contains approximately 6000 optical sensors. The acetylcholine biosensor has a detection limit of 35 microM and a fast (< 1 s) response time. In association with an epifluorescence microscope and a charge-coupled device, these modified imaging fibers can display visual information of a remote sample with 4-microns spatial resolution, allowing for alternating acquisition of both chemical analysis and visual histology.

Surface rupture and slip distribution of the 2016 Mw7.8 Kaikoura earthquake (New Zealand) from optical satellite image correlation using MicMac

NASA Astrophysics Data System (ADS)

Champenois, Johann; Klinger, Yann; Grandin, Raphaël; Satriano, Claudio; Baize, Stéphane; Delorme, Arthur; Scotti, Oona

2017-04-01

Remote sensing techniques, like optical satellite image correlation, are very efficient methods to localize and quantify surface displacements due to earthquakes. In this study, we use the french sub-pixel correlator MicMac (Multi Images Correspondances par Méthodes Automatiques de Corrélation). This free open-source software, developed by IGN, was recently adapted to process satellite images. This correlator uses regularization, and that provides good results especially in near-fault area with a high spatial resolution. We use co-seismic pair of ortho-images to measure the horizontal displacement field during the recent 2016 Mw7.8 Kaikoura earthquake. Optical satellite images from different satellites are processed (Sentinel-2A, Landsat8, etc.) to present a dense map of the surface ruptures and to analyze high density slip distribution along all major ruptures. We also provide a detail pattern of deformation along these main surface ruptures. Moreover, 2D displacement from optical correlation is compared to co-seismic measurements from GPS, static displacement from accelerometric records, geodetic marks and field investigations. Last but not least, we investigate the reconstruction of 3D displacement from combining InSAR, GPS and optic.

Mapping Land Cover and Land Use Changes in the Congo Basin Forests with Optical Satellite Remote Sensing: a Pilot Project Exploring Methodologies that Improve Spatial Resolution and Map Accuracy

NASA Astrophysics Data System (ADS)

Molinario, G.; Baraldi, A.; Altstatt, A. L.; Nackoney, J.

2011-12-01

The University of Maryland has been a USAID Central Africa Rregional Program for the Environment (CARPE) cross-cutting partner for many years, providing remote sensing derived information on forest cover and forest cover changes in support of CARPE's objectives of diminishing forest degradation, loss and biodiversity loss as a result of poor or inexistent land use planning strategies. Together with South Dakota State University, Congo Basin-wide maps have been provided that map forest cover loss at a maximum of 60m resolution, using Landsat imagery and higher resolution imagery for algorithm training and validation. However, to better meet the needs within the CARPE Landscapes, which call for higher resolution, more accurate land cover change maps, UMD has been exploring the use of the SIAM automatic spectral -rule classifier together with pan-sharpened Landsat data (15m resolution) and Very High Resolution imagery from various sources. The pilot project is being developed in collaboration with the African Wildlife Foundation in the Maringa Lopori Wamba CARPE Landscape. If successful in the future this methodology will make the creation of high resolution change maps faster and easier, making it accessible to other entities in the Congo Basin that need accurate land cover and land use change maps in order, for example, to create sustainable land use plans, conserve biodiversity and resources and prepare Reducing Emissions from forest Degradation and Deforestation (REDD) Measurement, Reporting and Verification (MRV) projects. The paper describes the need for higher resolution land cover change maps that focus on forest change dynamics such as the cycling between primary forests, secondary forest, agriculture and other expanding and intensifying land uses in the Maringa Lopori Wamba CARPE Landscape in the Equateur Province of the Democratic Republic of Congo. The Methodology uses the SIAM remote sensing imagery automatic spectral rule classifier, together with pan-sharpened Landsat imagery with 15m resolution and Very High Resolution imagery from different sensors, obtained from the Department of Defense database that was recently opened to NASA and its Earth Observation partners. Particular emphasis is placed on the detection of agricultural fields and their expansion in primary forests or intensification in secondary forests and fallow fields, as this is the primary driver of deforestation in this area. Fields in this area area also of very small size and irregular shapes, often partly obscured by neighboring forest canopy, hence the technical challenge of correctly detecting them and tracking them through time. Finally, the potential for use of this methodology in other regions where information on land cover changes is needed for land use sustainability planning, is also addressed.

Bridging the Scales from Field to Region with Practical Tools to Couple Time- and Space-Synchronized Data from Flux Towers and Networks with Proximal and Remote Sensing Data

NASA Astrophysics Data System (ADS)

Burba, G. G.; Avenson, T.; Burkart, A.; Gamon, J. A.; Guan, K.; Julitta, T.; Pastorello, G.; Sakowska, K.

2017-12-01

Many hundreds of flux towers are presently operational as standalone projects and as parts of regional networks. However, the vast majority of these towers do not allow straightforward coupling with remote sensing (drone, aircraft, satellite, etc.) data, and even fewer have optical sensors for validation of remote sensing products, and upscaling from field to regional levels. In 2016-2017, new tools to collect, process, and share time-synchronized flux data from multiple towers were developed and deployed globally. Originally designed to automate site and data management, and to streamline flux data analysis, these tools allow relatively easy matching of tower data with remote sensing data: GPS-driven PTP time protocol synchronizes instrumentation within the station, different stations with each other, and all of these to remote sensing data to precisely align remote sensing and flux data in time Footprint size and coordinates computed and stored with flux data help correctly align tower flux footprints and drone, aircraft or satellite motion to precisely align optical and flux data in space Full snapshot of the remote sensing pixel can then be constructed, including leaf-level, ground optical sensor, and flux tower measurements from the same footprint area, closely coupled with the remote sensing measurements to help interpret remote sensing data, validate models, and improve upscaling Additionally, current flux towers can be augmented with advanced ground optical sensors and can use standard routines to deliver continuous products (e.g. SIF, PRI, NDVI, etc.) based on automated field spectrometers (e.g., FloX and RoX, etc.) and other optical systems. Several dozens of new towers already operational globally can be readily used for the proposed workflow. Over 500 active traditional flux towers can be updated to synchronize their data with remote sensing measurements. This presentation will show how the new tools are used by major networks, and describe how this approach can be utilized for matching remote sensing and tower data to aid in ground truthing, improve scientific interactions, and promote joint grant writing and other forms of collaboration between the flux and remote sensing communities.

Compact liquid crystal waveguide based fourier transform spectrometer for in-situ and remote gas and chemical sensing

NASA Astrophysics Data System (ADS)

Chao, Tien-Hsin; Davis, Scott R.; Rommel, Scott D.; Farca, George; Luey, Ben; Martin, Alan; Anderson, Michael H.

2009-11-01

Jet Propulsion Lab and Vescent Photonics Inc. are jointly developing an innovative ultra-compact (volume < 10 cm3), ultra-low power (<10-3 Watt-hours per measurement and zero power consumption when not measuring), completely nonmechanical electro-optic Fourier transform spectrometers (EO-FTS) that will be suitable for a variety of remoteplatform, in-situ measurements. This EO-FTS consists of: i) a novel electro-evanescent waveguide architecture as the solid-state time delay device whose optical path difference (OPD) can be precisely varied utilizing voltage control, ii) a photodetector diode, and iii) an external light/sample collecting devices tailored for either in-situ gas and/or rock sample analysis or for remote atmospheric gas analysis. These devices are made possible by a novel electro-evanescent waveguide architecture, enabling "chip-scale" EO-FTS sensors. The potential performance of these EO-FTS sensors include: i) a spectral range throughout 0.4-5 μm (25000 - 2000 cm-1), ii) high-resolution ▵λ <= 0.1 nm), iii) high-speed (< 1 ms) measurements, and iv) rugged integrated optical construction. This performance potential enables the detection and quantification of a large number of different atmospheric gases simultaneously in the same air mass and the rugged construction will enable deployment on previously inaccessible platforms. In this paper, the up-to-date EO-FTS sensor development status will be presented; initial experimental results will also be demonstrated.

UAS-Borne Photogrammetry for Surface Topographic Characterization: A Ground-Truth Baseline for Future Change Detection and Refinement of Scaled Remotely-Sensed Datasets

NASA Astrophysics Data System (ADS)

Coppersmith, R.; Schultz-Fellenz, E. S.; Sussman, A. J.; Vigil, S.; Dzur, R.; Norskog, K.; Kelley, R.; Miller, L.

2015-12-01

While long-term objectives of monitoring and verification regimes include remote characterization and discrimination of surficial geologic and topographic features at sites of interest, ground truth data is required to advance development of remote sensing techniques. Increasingly, it is desirable for these ground-based or ground-proximal characterization methodologies to be as nimble, efficient, non-invasive, and non-destructive as their higher-altitude airborne counterparts while ideally providing superior resolution. For this study, the area of interest is an alluvial site at the Nevada National Security Site intended for use in the Source Physics Experiment's (Snelson et al., 2013) second phase. Ground-truth surface topographic characterization was performed using a DJI Inspire 1 unmanned aerial system (UAS), at very low altitude (< 5-30m AGL). 2D photographs captured by the standard UAS camera payload were imported into Agisoft Photoscan to create three-dimensional point clouds. Within the area of interest, careful installation of surveyed ground control fiducial markers supplied necessary targets for field collection, and information for model georectification. The resulting model includes a Digital Elevation Model derived from 2D imagery. It is anticipated that this flexible and versatile characterization process will provide point cloud data resolution equivalent to a purely ground-based LiDAR scanning deployment (e.g., 1-2cm horizontal and vertical resolution; e.g., Sussman et al., 2012; Schultz-Fellenz et al., 2013). In addition to drastically increasing time efficiency in the field, the UAS method also allows for more complete coverage of the study area when compared to ground-based LiDAR. Comparison and integration of these data with conventionally-acquired airborne LiDAR data from a higher-altitude (~ 450m) platform will aid significantly in the refinement of technologies and detection capabilities of remote optical systems to identify and detect surface geologic and topographic signatures of interest. This work includes a preliminary comparison of surface signatures detected from varying standoff distances to assess current sensor performance and benefits.

Using Remote Sensing to Visualize and Extract Building Inventories of Urban Areas for Disaster Planning and Response

NASA Astrophysics Data System (ADS)

Lang, A. F.; Salvaggio, C.

2016-12-01

Climate change, skyrocketing global population, and increasing urbanization have set the stage for more so-called "mega-disasters." We possess the knowledge to mitigate and predict the scope of these events, and recent advancements in remote sensing can inform these efforts. Satellite and aerial imagery can be obtained anywhere of interest; unmanned aerial systems can be deployed quickly; and improved sensor resolutions and image processing techniques allow close examination of the built environment. Combined, these technologies offer an unprecedented ability for the disaster community to visualize, assess, and communicate risk. Disaster mitigation and response efforts rely on an accurate representation of the built environment, including knowledge of building types, structural characteristics, and juxtapositions to known hazards. The use of remote sensing to extract these inventory data has come far in the last five years. Researchers in the Digital Imaging and Remote Sensing (DIRS) group at the Rochester Institute of Technology are meeting the needs of the disaster community through the development of novel image processing methods capable of extracting detailed information of individual buildings. DIRS researchers have pioneered the ability to generate three-dimensional building models from point cloud imagery (e.g., LiDAR). This method can process an urban area and recreate it in a navigable virtual reality environment such as Google Earth within hours. Detailed geometry is obtained for individual structures (e.g., footprint, elevation). In a recent step forward, these geometric data can now be combined with imagery from other sources, such as high resolution or multispectral imagery. The latter ascribes a spectral signature to individual pixels, suggesting construction material. Ultimately, these individual building data are amassed over an entire region, facilitating aggregation and risk modeling analyses. The downtown region of Rochester, New York is presented as a case study. High resolution optical, LiDAR, and multi-spectral imagery was captured of this region. Using the techniques described, these imagery sources are combined and processed to produce a holistic representation of the built environment, inclusive of individual building characteristics.

Vegetation optical depth measured by microwave radiometry as an indicator of tree mortality risk

NASA Astrophysics Data System (ADS)

Rao, K.; Anderegg, W.; Sala, A.; Martínez-Vilalta, J.; Konings, A. G.

2017-12-01

Increased drought-related tree mortality has been observed across several regions in recent years. Vast spatial extent and high temporal variability makes field monitoring of tree mortality cumbersome and expensive. With global coverage and high temporal revisit, satellite remote sensing offers an unprecedented tool to monitor terrestrial ecosystems and identify areas at risk of large drought-driven tree mortality events. To date, studies that use remote sensing data to monitor tree mortality have focused on external climatic thresholds such as temperature and evapotranspiration. However, this approach fails to consider internal water stress in vegetation - which can vary across trees even for similar climatic conditions due to differences in hydraulic behavior, soil type, etc - and may therefore be a poor basis for measuring mortality events. There is a consensus that xylem hydraulic failure often precedes drought-induced mortality, suggesting depleted canopy water content shortly before onset of mortality. Observations of vegetation optical depth (VOD) derived from passive microwave are proportional to canopy water content. In this study, we propose to use variations in VOD as an indicator of potential tree mortality. Since VOD accounts for intrinsic water stress undergone by vegetation, it is expected to be more accurate than external climatic stress indicators. Analysis of tree mortality events in California, USA observed by airborne detection shows a consistent relationship between mortality and the proposed VOD metric. Although this approach is limited by the kilometer-scale resolution of passive microwave radiometry, our results nevertheless demonstrate that microwave-derived estimates of vegetation water content can be used to study drought-driven tree mortality, and may be a valuable tool for mortality predictions if they can be combined with higher-resolution variables.

Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P

2017-09-15

Major end users of Digital Soil Mapping (DSM) such as policy makers and agricultural extension workers are faced with choosing the appropriate remote sensing data. The objective of this research is to analyze the spatial resolution effects of different remote sensing images on soil prediction models in two smallholder farms in Southern India called Kothapally (Telangana State), and Masuti (Karnataka State), and provide empirical guidelines to choose the appropriate remote sensing images in DSM. Bayesian kriging (BK) was utilized to characterize the spatial pattern of exchangeable potassium (K ex ) in the topsoil (0-15 cm) at different spatial resolutions by incorporating spectral indices from Landsat 8 (30 m), RapidEye (5 m), and WorldView-2/GeoEye-1/Pleiades-1A images (2 m). Some spectral indices such as band reflectances, band ratios, Crust Index and Atmospherically Resistant Vegetation Index from multiple images showed relatively strong correlations with soil K ex in two study areas. The research also suggested that fine spatial resolution WorldView-2/GeoEye-1/Pleiades-1A-based and RapidEye-based soil prediction models would not necessarily have higher prediction performance than coarse spatial resolution Landsat 8-based soil prediction models. The end users of DSM in smallholder farm settings need select the appropriate spectral indices and consider different factors such as the spatial resolution, band width, spectral resolution, temporal frequency, cost, and processing time of different remote sensing images. Overall, remote sensing-based Digital Soil Mapping has potential to be promoted to smallholder farm settings all over the world and help smallholder farmers implement sustainable and field-specific soil nutrient management scheme. Copyright © 2017 Elsevier Ltd. All rights reserved.

Radar Remote Sensing of Waves and Currents in the Nearshore Zone

DTIC Science & Technology

2006-01-01

and application of novel microwave, acoustic, and optical remote sensing techniques. The objectives of this effort are to determine the extent to which...Doppler radar techniques are useful for nearshore remote sensing applications. Of particular interest are estimates of surf zone location and extent...surface currents, waves, and bathymetry. To date, optical (video) techniques have been the primary remote sensing technology used for these applications. A key advantage of the radar is its all weather day-night operability.

Optical Remote Sensing Algorithm Validation using High-Frequency Underway Biogeochemical Measurements in Three Large Global River Systems

NASA Astrophysics Data System (ADS)

Kuhn, C.; Richey, J. E.; Striegl, R. G.; Ward, N.; Sawakuchi, H. O.; Crawford, J.; Loken, L. C.; Stadler, P.; Dornblaser, M.; Butman, D. E.

2017-12-01

More than 93% of the world's river-water volume occurs in basins impacted by large dams and about 43% of river water discharge is impacted by flow regulation. Human land use also alters nutrient and carbon cycling and the emission of carbon dioxide from inland reservoirs. Increased water residence times and warmer temperatures in reservoirs fundamentally alter the physical settings for biogeochemical processing in large rivers, yet river biogeochemistry for many large systems remains undersampled. Satellite remote sensing holds promise as a methodology for responsive regional and global water resources management. Decades of ocean optics research has laid the foundation for the use of remote sensing reflectance in optical wavelengths (400 - 700 nm) to produce satellite-derived, near-surface estimates of phytoplankton chlorophyll concentration. Significant improvements between successive generations of ocean color sensors have enabled the scientific community to document changes in global ocean productivity (NPP) and estimate ocean biomass with increasing accuracy. Despite large advances in ocean optics, application of optical methods to inland waters has been limited to date due to their optical complexity and small spatial scale. To test this frontier, we present a study evaluating the accuracy and suitability of empirical inversion approaches for estimating chlorophyll-a, turbidity and temperature for the Amazon, Columbia and Mississippi rivers using satellite remote sensing. We demonstrate how riverine biogeochemical measurements collected at high frequencies from underway vessels can be used as in situ matchups to evaluate remotely-sensed, near-surface temperature, turbidity, chlorophyll-a derived from the Landsat 8 (NASA) and Sentinel 2 (ESA) satellites. We investigate the use of remote sensing water reflectance to infer trophic status as well as tributary influences on the optical characteristics of the Amazon, Mississippi and Columbia rivers.

High-performance fiber optic link for ECM antenna remoting

NASA Astrophysics Data System (ADS)

Edge, Colin; Burgess, John W.; Wale, Michael J.; Try, Nicholas W.

1998-11-01

The ability to remotely radiate microwave signals has become an essential feature of modern electronic counter-measures (ECM) systems. The use of fiber optics allows remote microwave links to be constructed which have very low propagation loss and dispersion, are very flexible and light in weight, and have a high degree of immunity from external electromagnetic fields, crosstalk and environmental effects. This combination of desirable characteristics are very beneficial to avionic ECM antenna remoting as well as many other applications. GEC-Marconi have developed high performance fiber components for use in a towed radar decoy. The resulting rugged and compact optical transmitter and receiver modules have been developed and proven to maintain the required performance over the full hostile range of environmental conditions encountered on a fast jet. Packaged fiber optic links have been produced which can achieve a compression dynamic range of greater than 87 dB in 1 MHz bandwidth over a 2 to 18 GHz.

Remote optical stethoscope and optomyography sensing device

NASA Astrophysics Data System (ADS)

Golberg, Mark; Polani, Sagi; Ozana, Nisan; Beiderman, Yevgeny; Garcia, Javier; Ruiz-Rivas Onses, Joaquin; Sanz Sabater, Martin; Shatsky, Max; Zalevsky, Zeev

2017-02-01

In this paper we present the usage of photonic remote laser based device for sensing nano-vibrations for detection of muscle contraction and fatigue, eye movements and in-vivo estimation of glucose concentration. The same concept is also used to realize a remote optical stethoscope. The advantage of doing the measurements from a distance is in preventing passage of infections as in the case of optical stethoscope or in the capability to monitor e.g. sleep quality without disturbing the patient. The remote monitoring of glucose concentration in the blood stream and the capability to perform opto-myography for the Messer muscles (chewing) is very useful for nutrition and weight control. The optical configuration for sensing the nano-vibrations is based upon analyzing the statistics of the secondary speckle patterns reflected from various tissues along the body of the subjects. Experimental results present the preliminary capability of the proposed configuration for the above mentioned applications.

Validation of Spaceborne Radar Surface Water Mapping with Optical sUAS Images

NASA Astrophysics Data System (ADS)

Li-Chee-Ming, J.; Murnaghan, K.; Sherman, D.; Poncos, V.; Brisco, B.; Armenakis, C.

2015-08-01

The Canada Centre for Remote Sensing (CCRS) has over 40 years of experience with airborne and spaceborne sensors and is now starting to use small Unmanned Aerial Systems (sUAS) to validate products from large coverage area sensors and create new methodologies for very high resolution products. Wetlands have several functions including water storage and retention which can reduce flooding and provide continuous flow for hydroelectric generation and irrigation for agriculture. Synthetic Aperture Radar is well suited as a tool for monitoring surface water by supplying acquisitions irrespective of cloud cover or time of day. Wetlands can be subdivided into three classes: open water, flooded vegetation and upland which can vary seasonally with time and water level changes. RADARSAT-2 data from the Wide-Ultra Fine, Spotlight and Fine Quad-Pol modes has been used to map the open water in the Peace-Athabasca Delta, Alberta using intensity thresholding. We also use spotlight modes for higher resolution and the fully polarimetric mode (FQ) for polarimetric decomposition. Validation of these products will be done using a low altitude flying sUAS to generate optical georeferenced images. This project provides methodologies which could be used for flood mapping as well as ecological monitoring.

Remote Sensing of Global Fire Patterns, Aerosol Optical Thickness, and Carbon Monoxide During April 1994

NASA Technical Reports Server (NTRS)

Christopher, Sundar A.; Wang, Min; Klich, Donna V.; Welch, Ronald M.; Nolf, Scott; Connors, Vickie S.

1997-01-01

Fires play a crucial role in several ecosystems. They are routinely used to burn forests in order to accommodate the needs of the expanding population, clear land for agricultural purposes, eliminate weeds and pests, regenerate nutrients in grazing and crop lands and produce energy for cooking and heating purposes. Most of the fires on earth are related to biomass burning in the tropics, although they are not confined to these latitudes. The boreal and tundra regions also experience fires on a yearly basis. The current study examines global fire patterns, Aerosol Optical Thickness (AOT) and carbon monoxide concentrations during April 9-19, 1994. Recently, global Advanced Very High Resolution Radiometer (AVHRR) data at nadir ground spatial resolution of 1 km are made available through the NASA/NOAA Pathfinder project. These data from April 9-19, 1994 are used to map fires over the earth. In summary, our analysis shows that fires from biomass burning appear to be the dominant factor for increased tropospheric CO concentrations as measured by the MAPS. The vertical transport of CO by convective activities, along with horizontal transport due to the prevailing winds, are responsible for the observed spatial distribution of CO.

The Brazilian wide field imaging camera (WFI) for the China/Brazil earth resources satellite: CBERS 3 and 4

NASA Astrophysics Data System (ADS)

Scaduto, L. C. N.; Carvalho, E. G.; Modugno, R. G.; Cartolano, R.; Evangelista, S. H.; Segoria, D.; Santos, A. G.; Stefani, M. A.; Castro Neto, J. C.

2017-11-01

The purpose of this paper is to present the optical system developed for the Wide Field imaging Camera - WFI that will be integrated to the CBERS 3 and 4 satellites (China Brazil Earth resources Satellite). This camera will be used for remote sensing of the Earth and it is aimed to work at an altitude of 778 km. The optical system is designed for four spectral bands covering the range of wavelengths from blue to near infrared and its field of view is +/-28.63°, which covers 866 km, with a ground resolution of 64 m at nadir. WFI has been developed through a consortium formed by Opto Electrônica S. A. and Equatorial Sistemas. In particular, we will present the optical analysis based on the Modulation Transfer Function (MTF) obtained during the Engineering Model phase (EM) and the optical tests performed to evaluate the requirements. Measurements of the optical system MTF have been performed using an interferometer at the wavelength of 632.8nm and global MTF tests (including the CCD and signal processing electronic) have been performed by using a collimator with a slit target. The obtained results showed that the performance of the optical system meets the requirements of project.

Evaluation of eelgrass beds mapping using a high-resolution airborne multispectral scanner

USGS Publications Warehouse

Su, H.; Karna, D.; Fraim, E.; Fitzgerald, M.; Dominguez, R.; Myers, J.S.; Coffland, B.; Handley, L.R.; Mace, T.

2006-01-01

Eelgrass (Zostera marina) can provide vital ecological functions in stabilizing sediments, influencing current dynamics, and contributing significant amounts of biomass to numerous food webs in coastal ecosystems. Mapping eelgrass beds is important for coastal water and nearshore estuarine monitoring, management, and planning. This study demonstrated the possible use of high spatial (approximately 5 m) and temporal (maximum low tide) resolution airborne multispectral scanner on mapping eelgrass beds in Northern Puget Sound, Washington. A combination of supervised and unsupervised classification approaches were performed on the multispectral scanner imagery. A normalized difference vegetation index (NDVI) derived from the red and near-infrared bands and ancillary spatial information, were used to extract and mask eelgrass beds and other submerged aquatic vegetation (SAV) in the study area. We evaluated the resulting thematic map (geocoded, classified image) against a conventional aerial photograph interpretation using 260 point locations randomly stratified over five defined classes from the thematic map. We achieved an overall accuracy of 92 percent with 0.92 Kappa Coefficient in the study area. This study demonstrates that the airborne multispectral scanner can be useful for mapping eelgrass beds in a local or regional scale, especially in regions for which optical remote sensing from space is constrained by climatic and tidal conditions. ?? 2006 American Society for Photogrammetry and Remote Sensing.

A Sparse Dictionary Learning-Based Adaptive Patch Inpainting Method for Thick Clouds Removal from High-Spatial Resolution Remote Sensing Imagery

PubMed Central

Yang, Xiaomei; Zhou, Chenghu; Li, Zhi

2017-01-01

Cloud cover is inevitable in optical remote sensing (RS) imagery on account of the influence of observation conditions, which limits the availability of RS data. Therefore, it is of great significance to be able to reconstruct the cloud-contaminated ground information. This paper presents a sparse dictionary learning-based image inpainting method for adaptively recovering the missing information corrupted by thick clouds patch-by-patch. A feature dictionary was learned from exemplars in the cloud-free regions, which was later utilized to infer the missing patches via sparse representation. To maintain the coherence of structures, structure sparsity was brought in to encourage first filling-in of missing patches on image structures. The optimization model of patch inpainting was formulated under the adaptive neighborhood-consistency constraint, which was solved by a modified orthogonal matching pursuit (OMP) algorithm. In light of these ideas, the thick-cloud removal scheme was designed and applied to images with simulated and true clouds. Comparisons and experiments show that our method can not only keep structures and textures consistent with the surrounding ground information, but also yield rare smoothing effect and block effect, which is more suitable for the removal of clouds from high-spatial resolution RS imagery with salient structures and abundant textured features. PMID:28914787

A Sparse Dictionary Learning-Based Adaptive Patch Inpainting Method for Thick Clouds Removal from High-Spatial Resolution Remote Sensing Imagery.

PubMed

Meng, Fan; Yang, Xiaomei; Zhou, Chenghu; Li, Zhi

2017-09-15

Cloud cover is inevitable in optical remote sensing (RS) imagery on account of the influence of observation conditions, which limits the availability of RS data. Therefore, it is of great significance to be able to reconstruct the cloud-contaminated ground information. This paper presents a sparse dictionary learning-based image inpainting method for adaptively recovering the missing information corrupted by thick clouds patch-by-patch. A feature dictionary was learned from exemplars in the cloud-free regions, which was later utilized to infer the missing patches via sparse representation. To maintain the coherence of structures, structure sparsity was brought in to encourage first filling-in of missing patches on image structures. The optimization model of patch inpainting was formulated under the adaptive neighborhood-consistency constraint, which was solved by a modified orthogonal matching pursuit (OMP) algorithm. In light of these ideas, the thick-cloud removal scheme was designed and applied to images with simulated and true clouds. Comparisons and experiments show that our method can not only keep structures and textures consistent with the surrounding ground information, but also yield rare smoothing effect and block effect, which is more suitable for the removal of clouds from high-spatial resolution RS imagery with salient structures and abundant textured features.

Modeling of aircraft exhaust emissions and infrared spectra for remote measurement of nitrogen oxides

NASA Astrophysics Data System (ADS)

Beier, K.; Schreier, F.

1994-10-01

Infrared (IR) molecular spectroscopy is proposed to perform remote measurements of NOx concentrations in the exhaust plume and wake of aircraft. The computer model NIRATAM is applied to simulate the physical and chemical properties of the exhaust plume and to generate low resolution IR spectra and synthetical thermal images of the aircraft in its natural surroundings. High-resolution IR spectra of the plume, including atmospheric absorption and emission, are simulated using the molecular line-by-line radiation model FASCODE2. Simulated IR spectra of a Boeing 747-400 at cruising altitude for different axial and radial positions in the jet region of the exhaust plume are presented. A number of spectral lines of NO can be identified that can be discriminated from lines of other exhaust gases and the natural atmospheric background in the region around 5.2 µm. These lines can be used to determine NO concentration profiles in the plume. The possibility of measuring nitrogen dioxide NO2 is also discussed briefly, although measurements turn out to be substantially less likely than those of NO. This feasibility study compiles fundamental data for the optical and radiometric design of an airborne Fourier transform spectrometer and the preparation of in-flight measurements for monitoring of aircraft pollutants

Evaporation Using Planet Cubesats and the PT-JPL Model: A Precision Agriculture Application

NASA Astrophysics Data System (ADS)

Aragon, B.; Houborg, R.; Tu, K. P.; Fisher, J.; McCabe, M.

2017-12-01

With an increasing demand to feed growing populations, coupled with the overexploitation of aquifers that supply water to irrigated agriculture, we require an improved understanding of the availability and use of water resources: particularly in arid and semi-arid environments. Remote sensing techniques can provide detail into farm-scale hydrological systems by computing the crop-water use via estimating the evaporation and transpiration (ET). However, remote sensing driven ET retrievals have often been limited by spatial and temporal scales. The launches of Sentinel-2A/B provide some of the best satellite data platforms for optical imagery, with 10m pixel resolution and a 5-day revisit time. However, even with the considerable improvements that these provide over comparable systems such as Landsat, cloud cover and other atmospheric influences can reduce image availability. CubeSats, such as those from Planet, are relaxing such constraints by offering daily global coverage at 3m spatial resolution. Here we examine the performance of the first ET retrievals derived from Planet data using the Priestly-Taylor Jet Propulsion Lab (PT-JPL) model, adapted to instantaneous measurements. The retrievals were assessed across a range of crop-cover, moisture and meteorological conditions using an eddy covariance flux tower installed over an irrigated farmland in Saudi Arabia.

Optical Delineation of Benthic Habitat Using an Autonomous Underwater Vehicle

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

Moline, Mark A.; Woodruff, Dana L.; Evans, Nathan R.

To improve understanding and characterization of coastal regions, there has been an increasing emphasis on autonomous systems that can sample the ocean on relevant scales. Autonomous underwater vehicles (AUVs) with active propulsion are especially well suited for studies of the coastal ocean because they are able to provide systematic and near-synoptic spatial observations. With this capability, science users are beginning to integrate sensor suits for a broad range of specific and often novel applications. Here, the relatively mature Remote Environmental Monitoring Units (REMUS) AUV system is configured with multi-spectral radiometers to delineate benthic habitat in Sequim Bay, WA. The vehiclemore » was deployed in a grid pattern along 5 km of coastline in depths from 30 to less than 2 meters. Similar to satellite and/or aerial remote sensing, the bandwidth ratios from the downward looking radiance sensor and upward looking irradiance sensor were used to identify beds of eelgrass on sub-meter scales. Strong correlations were found between the optical reflectance signals and the geo-referenced in situ data collected with underwater video within the grid. Results demonstrate the ability of AUVs to map littoral habitats at high resolution and highlight the overall utility of the REMUS vehicle for nearshore oceanography.« less

Remote sensing of a dynamic sub-arctic peatland reservoir using optical and synthetic aperture radar data

NASA Astrophysics Data System (ADS)

Larter, Jarod Lee

Stephens Lake, Manitoba is an example of a peatland reservoir that has undergone physical changes related to mineral erosion and peatland disintegration processes since its initial impoundment. In this thesis I focused on the processes of peatland upheaval, transport, and disintegration as the primary drivers of dynamic change within the reservoir. The changes related to these processes are most frequent after initial reservoir impoundment and decline over time. They continue to occur over 35 years after initial flooding. I developed a remote sensing approach that employs both optical and microwave sensors for discriminating land (Le. floating peatlands, forested land, and barren land) from open water within the reservoir. High spatial resolution visible and near-infrared (VNIR) optical data obtained from the QuickBird satellite, and synthetic aperture radar (SAR) microwave data obtained from the RADARSAT-1 satellite were implemented. The approach was facilitated with a Geographic Information System (GIS) based validation map for the extraction of optical and SAR pixel data. Each sensor's extracted data set was first analyzed separately using univariate and multivariate statistical methods to determine the discriminant ability of each sensor. The initial analyses were followed by an integrated sensor approach; the development of an image classification model; and a change detection analysis. Results showed excellent (> 95%) classification accuracy using QuickBird satellite image data. Discrimination and classification of studied land cover classes using SAR image texture data resulted in lower overall classification accuracies (˜ 60%). SAR data classification accuracy improved to > 90% when classifying only land and water, demonstrating SAR's utility as a land and water mapping tool. An integrated sensor data approach showed no considerable improvement over the use of optical satellite image data alone. An image classification model was developed that could be used to map both detailed land cover classes and the land and water interface within the reservoir. Change detection analysis over a seven year period indicated that physical changes related to mineral erosion, peatland upheaval, transport, and disintegration, and operational water level variation continue to take place in the reservoir some 35 years after initial flooding. This thesis demonstrates the ability of optical and SAR satellite image remote sensing data sets to be used in an operational context for the routine discrimination of the land and water boundaries within a dynamic peatland reservoir. Future monitoring programs would benefit most from a complementary image acquisition program in which SAR images, known for their acquisition reliability under cloud cover, are acquired along with optical images given their ability to discriminate land cover classes in greater detail.

Geographic information system for fusion and analysis of high-resolution remote sensing and ground truth data

NASA Technical Reports Server (NTRS)

Freeman, Anthony; Dubois, Pascale; Leberl, Franz; Norikane, L.; Way, Jobea

1991-01-01

Viewgraphs on Geographic Information System for fusion and analysis of high-resolution remote sensing and ground truth data are presented. Topics covered include: scientific objectives; schedule; and Geographic Information System.

INTERCOMPARISON OF OPTICAL REMOTE SENSING SYSTEMS FOR ROADSIDE MEASUREMENTS

EPA Science Inventory

The presentation describes results of an intercomparison of three optical remote sensing systems for measurements of nitric oxide emitted from passenger cars and light-duty trucks. The intercomparison included a standards comparison to establish comparability of standards, follo...

OPTICAL REMOTE SENSING FOR AIR QUALITY MONITORING

EPA Science Inventory

The paper outlines recent developments in using optical remote sensing (ORS) instruments for air quality monitoring both for gaseous pollutants and airborne particulate matter (PM). The U.S. Environmental Protection Agency (EPA) has been using open-path Fourier transform infrared...

A simple optical model to estimate suspended particulate matter in Yellow River Estuary.

PubMed

Qiu, Zhongfeng

2013-11-18

Distribution of the suspended particulate matter (SPM) concentration is a key issue for analyzing the deposition and erosion variety of the estuary and evaluating the material fluxes from river to sea. Satellite remote sensing is a useful tool to investigate the spatial variation of SPM concentration in estuarial zones. However, algorithm developments and validations of the SPM concentrations in Yellow River Estuary (YRE) have been seldom performed before and therefore our knowledge on the quality of retrieval of SPM concentration is poor. In this study, we developed a new simple optical model to estimate SPM concentration in YRE by specifying the optimal wavelength ratios (600-710 nm)/ (530-590 nm) based on observations of 5 cruises during 2004 and 2011. The simple optical model was attentively calibrated and the optimal band ratios were selected for application to multiple sensors, 678/551 for the Moderate Resolution Imaging Spectroradiometer (MODIS), 705/560 for the Medium Resolution Imaging Spectrometer (MERIS) and 680/555 for the Geostationary Ocean Color Imager (GOCI). With the simple optical model, the relative percentage difference and the mean absolute error were 35.4% and 15.6 gm(-3) respectively for MODIS, 42.2% and 16.3 gm(-3) for MERIS, and 34.2% and 14.7 gm(-3) for GOCI, based on an independent validation data set. Our results showed a good precision of estimation for SPM concentration using the new simple optical model, contrasting with the poor estimations derived from existing empirical models. Providing an available atmospheric correction scheme for satellite imagery, our simple model could be used for quantitative monitoring of SPM concentrations in YRE.

Multi-spectral image analysis for improved space object characterization

NASA Astrophysics Data System (ADS)

Glass, William; Duggin, Michael J.; Motes, Raymond A.; Bush, Keith A.; Klein, Meiling

2009-08-01

The Air Force Research Laboratory (AFRL) is studying the application and utility of various ground-based and space-based optical sensors for improving surveillance of space objects in both Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO). This information can be used to improve our catalog of space objects and will be helpful in the resolution of satellite anomalies. At present, ground-based optical and radar sensors provide the bulk of remotely sensed information on satellites and space debris, and will continue to do so into the foreseeable future. However, in recent years, the Space-Based Visible (SBV) sensor was used to demonstrate that a synthesis of space-based visible data with ground-based sensor data could provide enhancements to information obtained from any one source in isolation. The incentives for space-based sensing include improved spatial resolution due to the absence of atmospheric effects and cloud cover and increased flexibility for observations. Though ground-based optical sensors can use adaptive optics to somewhat compensate for atmospheric turbulence, cloud cover and absorption are unavoidable. With recent advances in technology, we are in a far better position to consider what might constitute an ideal system to monitor our surroundings in space. This work has begun at the AFRL using detailed optical sensor simulations and analysis techniques to explore the trade space involved in acquiring and processing data from a variety of hypothetical space-based and ground-based sensor systems. In this paper, we briefly review the phenomenology and trade space aspects of what might be required in order to use multiple band-passes, sensor characteristics, and observation and illumination geometries to increase our awareness of objects in space.

Downscaling of Seasonal Landsat-8 and MODIS Land Surface Temperature (LST) in Kolkata, India

NASA Astrophysics Data System (ADS)

Garg, R. D.; Guha, S.; Mondal, A.; Lakshmi, V.; Kundu, S.

2017-12-01

The quality of life of urban people is affected by urban heat environment. The urban heat studies can be carried out using remotely sensed thermal infrared imagery for retrieving Land Surface Temperature (LST). Currently, high spatial resolution (<200 m) thermal images are limited and their temporal resolution is low (e.g., 17 days of Landsat-8). Coarse spatial resolution (1000 m) and high temporal resolution (daily) thermal images of MODIS (Moderate Resolution Imaging Spectroradiometer) are frequently available. The present study is to downscale spatially coarser resolution of the thermal image to fine resolution thermal image using regression based downscaling technique. This method is based on the relationship between (LST) and vegetation indices (e.g., Normalized Difference Vegetation Index or NDVI) over a heterogeneous landscape. The Kolkata metropolitan city, which experiences a tropical wet-and-dry type of climate has been selected for the study. This study applied different seasonal open source satellite images viz., Landsat-8 and Terra MODIS. The Landsat-8 images are aggregated at 960 m resolution and downscaled into 480, 240 120 and 60 m. Optical and thermal resolution of Landsat-8 and MODIS are 30 m and 60 m; 250 m and 1000 m respectively. The homogeneous land cover areas have shown better accuracy than heterogeneous land cover areas. The downscaling method plays a crucial role while the spatial resolution of thermal band renders it unable for advanced study. Key words: Land Surface Temperature (LST), Downscale, MODIS, Landsat, Kolkata

Performance Simulations for a Spaceborne Methane Lidar Mission

NASA Technical Reports Server (NTRS)

Kiemle, C.; Kawa, Stephan Randolph; Quatrevalet, Mathieu; Browell, Edward V.

2014-01-01

Future spaceborne lidar measurements of key anthropogenic greenhouse gases are expected to close current observational gaps particularly over remote, polar, and aerosol-contaminated regions, where actual in situ and passive remote sensing observation techniques have difficulties. For methane, a "Methane Remote Lidar Mission" was proposed by Deutsches Zentrum fuer Luft- und Raumfahrt and Centre National d'Etudes Spatiales in the frame of a German-French climate monitoring initiative. Simulations assess the performance of this mission with the help of Moderate Resolution Imaging Spectroradiometer and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations of the earth's surface albedo and atmospheric optical depth. These are key environmental parameters for integrated path differential absorption lidar which uses the surface backscatter to measure the total atmospheric methane column. Results showthat a lidar with an average optical power of 0.45W at 1.6 µm wavelength and a telescope diameter of 0.55 m, installed on a low Earth orbit platform(506 km), will measure methane columns at precisions of 1.2%, 1.7%, and 2.1% over land, water, and snow or ice surfaces, respectively, for monthly aggregated measurement samples within areas of 50 × 50 km2. Globally, the mean precision for the simulated year 2007 is 1.6%, with a standard deviation of 0.7%. At high latitudes, a lower reflectance due to snow and ice is compensated by denser measurements, owing to the orbital pattern. Over key methane source regions such as densely populated areas, boreal and tropical wetlands, or permafrost, our simulations show that the measurement precision will be between 1 and 2%.

Predictive modeling of hazardous waste landfill total above-ground biomass using passive optical and LIDAR remotely sensed data

NASA Astrophysics Data System (ADS)

Hadley, Brian Christopher

This dissertation assessed remotely sensed data and geospatial modeling technique(s) to map the spatial distribution of total above-ground biomass present on the surface of the Savannah River National Laboratory's (SRNL) Mixed Waste Management Facility (MWMF) hazardous waste landfill. Ordinary least squares (OLS) regression, regression kriging, and tree-structured regression were employed to model the empirical relationship between in-situ measured Bahia (Paspalum notatum Flugge) and Centipede [Eremochloa ophiuroides (Munro) Hack.] grass biomass against an assortment of explanatory variables extracted from fine spatial resolution passive optical and LIDAR remotely sensed data. Explanatory variables included: (1) discrete channels of visible, near-infrared (NIR), and short-wave infrared (SWIR) reflectance, (2) spectral vegetation indices (SVI), (3) spectral mixture analysis (SMA) modeled fractions, (4) narrow-band derivative-based vegetation indices, and (5) LIDAR derived topographic variables (i.e. elevation, slope, and aspect). Results showed that a linear combination of the first- (1DZ_DGVI), second- (2DZ_DGVI), and third-derivative of green vegetation indices (3DZ_DGVI) calculated from hyperspectral data recorded over the 400--960 nm wavelengths of the electromagnetic spectrum explained the largest percentage of statistical variation (R2 = 0.5184) in the total above-ground biomass measurements. In general, the topographic variables did not correlate well with the MWMF biomass data, accounting for less than five percent of the statistical variation. It was concluded that tree-structured regression represented the optimum geospatial modeling technique due to a combination of model performance and efficiency/flexibility factors.

New Statistical Model for Variability of Aerosol Optical Thickness: Theory and Application to MODIS Data over Ocean

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail Dmitrievic; Geogdzhayev, Igor V.; Tsigaridis, Konstantinos; Marshak, Alexander; Levy, Robert; Cairns, Brian

2016-01-01

A novel model for the variability in aerosol optical thickness (AOT) is presented. This model is based on the consideration of AOT fields as realizations of a stochastic process, that is the exponent of an underlying Gaussian process with a specific autocorrelation function. In this approach AOT fields have lognormal PDFs and structure functions having the correct asymptotic behavior at large scales. The latter is an advantage compared with fractal (scale-invariant) approaches. The simple analytical form of the structure function in the proposed model facilitates its use for the parameterization of AOT statistics derived from remote sensing data. The new approach is illustrated using a month-long global MODIS AOT dataset (over ocean) with 10 km resolution. It was used to compute AOT statistics for sample cells forming a grid with 5deg spacing. The observed shapes of the structure functions indicated that in a large number of cases the AOT variability is split into two regimes that exhibit different patterns of behavior: small-scale stationary processes and trends reflecting variations at larger scales. The small-scale patterns are suggested to be generated by local aerosols within the marine boundary layer, while the large-scale trends are indicative of elevated aerosols transported from remote continental sources. This assumption is evaluated by comparison of the geographical distributions of these patterns derived from MODIS data with those obtained from the GISS GCM. This study shows considerable potential to enhance comparisons between remote sensing datasets and climate models beyond regional mean AOTs.

Moderate resolution remote sensing alternatives: a review of Landsat-like sensors and their applications

Treesearch

Scott L. Powell; Dirk Pflugmacher; Alan A. Kirschbaum; Yunsuk Kim; Warren B. Cohen

2007-01-01

Earth observation with Landsat and other moderate resolution sensors is a vital component of a wide variety of applications across disciplines. Despite the widespread success of the Landsat program, recent problems with Landsat 5 and Landsat 7 create uncertainty about the future of moderate resolution remote sensing. Several other Landsat-like sensors have demonstrated...

Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis

PubMed Central

Hu, Mao-Gui; Wang, Jin-Feng; Ge, Yong

2009-01-01

Satellite remote sensing (RS) is an important contributor to Earth observation, providing various kinds of imagery every day, but low spatial resolution remains a critical bottleneck in a lot of applications, restricting higher spatial resolution analysis (e.g., intra-urban). In this study, a multifractal-based super-resolution reconstruction method is proposed to alleviate this problem. The multifractal characteristic is common in Nature. The self-similarity or self-affinity presented in the image is useful to estimate details at larger and smaller scales than the original. We first look for the presence of multifractal characteristics in the images. Then we estimate parameters of the information transfer function and noise of the low resolution image. Finally, a noise-free, spatial resolution-enhanced image is generated by a fractal coding-based denoising and downscaling method. The empirical case shows that the reconstructed super-resolution image performs well in detail enhancement. This method is not only useful for remote sensing in investigating Earth, but also for other images with multifractal characteristics. PMID:22291530

Visually Lossless JPEG 2000 for Remote Image Browsing

PubMed Central

Oh, Han; Bilgin, Ali; Marcellin, Michael

2017-01-01

Image sizes have increased exponentially in recent years. The resulting high-resolution images are often viewed via remote image browsing. Zooming and panning are desirable features in this context, which result in disparate spatial regions of an image being displayed at a variety of (spatial) resolutions. When an image is displayed at a reduced resolution, the quantization step sizes needed for visually lossless quality generally increase. This paper investigates the quantization step sizes needed for visually lossless display as a function of resolution, and proposes a method that effectively incorporates the resulting (multiple) quantization step sizes into a single JPEG2000 codestream. This codestream is JPEG2000 Part 1 compliant and allows for visually lossless decoding at all resolutions natively supported by the wavelet transform as well as arbitrary intermediate resolutions, using only a fraction of the full-resolution codestream. When images are browsed remotely using the JPEG2000 Interactive Protocol (JPIP), the required bandwidth is significantly reduced, as demonstrated by extensive experimental results. PMID:28748112

Monitoring the spatial and temporal evolution of slope instability with Digital Image Correlation

NASA Astrophysics Data System (ADS)

Manconi, Andrea; Glueer, Franziska; Loew, Simon

2017-04-01

The identification and monitoring of ground deformation is important for an appropriate analysis and interpretation of unstable slopes. Displacements are usually monitored with in-situ techniques (e.g., extensometers, inclinometers, geodetic leveling, tachymeters and D-GPS), and/or active remote sensing methods (e.g., LiDAR and radar interferometry). In particular situations, however, the choice of the appropriate monitoring system is constrained by site-specific conditions. Slope areas can be very remote and/or affected by rapid surface changes, thus hardly accessible, often unsafe, for field installations. In many cases the use of remote sensing approaches might be also hindered because of unsuitable acquisition geometries, poor spatial resolution and revisit times, and/or high costs. The increasing availability of digital imagery acquired from terrestrial photo and video cameras allows us nowadays for an additional source of data. The latter can be exploited to visually identify changes of the scene occurring over time, but also to quantify the evolution of surface displacements. Image processing analyses, such as Digital Image Correlation (known also as pixel-offset or feature-tracking), have demonstrated to provide a suitable alternative to detect and monitor surface deformation at high spatial and temporal resolutions. However, a number of intrinsic limitations have to be considered when dealing with optical imagery acquisition and processing, including the effects of light conditions, shadowing, and/or meteorological variables. Here we propose an algorithm to automatically select and process images acquired from time-lapse cameras. We aim at maximizing the results obtainable from large datasets of digital images acquired with different light and meteorological conditions, and at retrieving accurate information on the evolution of surface deformation. We show a successful example of application of our approach in the Swiss Alps, more specifically in the Great Aletsch area, where slope instability was recently reactivated due to the progressive glacier retreat. At this location, time-lapse cameras have been installed during the last two years, ranging from low-cost and low-resolution webcams to more expensive high-resolution reflex cameras. Our results confirm that time-lapse cameras provide quantitative and accurate measurements of surface deformation evolution over space and time, especially in situations when other monitoring instruments fail.

Photo-induced spatial modulation of THz waves: opportunities and limitations.

PubMed

Kannegulla, Akash; Shams, Md Itrat Bin; Liu, Lei; Cheng, Li-Jing

2015-12-14

Programmable conductive patterns created by photoexcitation of semiconductor substrates using digital light processing (DLP) provides a versatile approach for spatial and temporal modulation of THz waves. The reconfigurable nature of the technology has great potential in implementing several promising THz applications, such as THz beam steering, THz imaging or THz remote sensing, in a simple, cost-effective manner. In this paper, we provide physical insight about how the semiconducting materials, substrate dimension, optical illumination wavelength and illumination size impact the performance of THz modulation, including modulation depth, modulation speed and spatial resolution. The analysis establishes design guidelines for the development of photo-induced THz modulation technology. Evolved from the theoretical analysis, a new mesa array technology composed by a matrix of sub-THz wavelength structures is introduced to maximize both spatial resolution and modulation depth for THz modulation with low-power photoexcitation by prohibiting the lateral diffusion of photogenerated carriers.

Amplified OTDR systems for multipoint corrosion monitoring.

PubMed

Nascimento, Jehan F; Silva, Marcionilo J; Coêlho, Isnaldo J S; Cipriano, Eliel; Martins-Filho, Joaquim F

2012-01-01

We present two configurations of an amplified fiber-optic-based corrosion sensor using the optical time domain reflectometry (OTDR) technique as the interrogation method. The sensor system is multipoint, self-referenced, has no moving parts and can measure the corrosion rate several kilometers away from the OTDR equipment. The first OTDR monitoring system employs a remotely pumped in-line EDFA and it is used to evaluate the increase in system reach compared to a non-amplified configuration. The other amplified monitoring system uses an EDFA in booster configuration and we perform corrosion measurements and evaluations of system sensitivity to amplifier gain variations. Our experimental results obtained under controlled laboratory conditions show the advantages of the amplified system in terms of longer system reach with better spatial resolution, and also that the corrosion measurements obtained from our system are not sensitive to 3 dB gain variations.

Amplified OTDR Systems for Multipoint Corrosion Monitoring

PubMed Central

Nascimento, Jehan F.; Silva, Marcionilo J.; Coêlho, Isnaldo J. S.; Cipriano, Eliel; Martins-Filho, Joaquim F.

2012-01-01

We present two configurations of an amplified fiber-optic-based corrosion sensor using the optical time domain reflectometry (OTDR) technique as the interrogation method. The sensor system is multipoint, self-referenced, has no moving parts and can measure the corrosion rate several kilometers away from the OTDR equipment. The first OTDR monitoring system employs a remotely pumped in-line EDFA and it is used to evaluate the increase in system reach compared to a non-amplified configuration. The other amplified monitoring system uses an EDFA in booster configuration and we perform corrosion measurements and evaluations of system sensitivity to amplifier gain variations. Our experimental results obtained under controlled laboratory conditions show the advantages of the amplified system in terms of longer system reach with better spatial resolution, and also that the corrosion measurements obtained from our system are not sensitive to 3 dB gain variations. PMID:22737017

Ultra-compact fiber-optic two-photon microscope for functional fluorescence imaging in vivo.

PubMed

Engelbrecht, Christoph J; Johnston, Richard S; Seibel, Eric J; Helmchen, Fritjof

2008-04-14

We present a small, lightweight two-photon fiberscope and demonstrate its suitability for functional imaging in the intact brain. Our device consists of a hollow-core photonic crystal fiber for efficient delivery of near-IR femtosecond laser pulses, a spiral fiber-scanner for resonant beam steering, and a gradient-index lens system for fluorescence excitation, dichroic beam splitting, and signal collection. Fluorescence light is remotely detected using a standard photomultiplier tube. All optical components have 1 mm dimensions and the microscope's headpiece weighs only 0.6 grams. The instrument achieves micrometer resolution at frame rates of typically 25 Hz with a field-of-view of up to 200 microns. We demonstrate functional imaging of calcium signals in Purkinje cell dendrites in the cerebellum of anesthetized rats. The microscope will be easily portable by a rat or mouse and thus should enable functional imaging in freely behaving animals.

Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy

PubMed Central

Pottier, Julien; Malenovský, Zbyněk; Psomas, Achilleas; Homolová, Lucie; Schaepman, Michael E.; Choler, Philippe; Thuiller, Wilfried; Guisan, Antoine; Zimmermann, Niklaus E.

2014-01-01

Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data. PMID:25079495

Fiber-Optic Sensor-Based Remote Acoustic Emission Measurement in a 1000 °C Environment.

PubMed

Yu, Fengming; Okabe, Yoji

2017-12-14

Recently, the authors have proposed a remote acoustic emission (AE) measurement configuration using a sensitive fiber-optic Bragg grating (FBG) sensor. In the configuration, the FBG sensor was remotely bonded on a plate, and an optical fiber was used as the waveguide to propagate AE waves from the adhesive point to the sensor. The previous work (Yu et al., Smart Materials and Structures 25 (10), 105,033 (2016)) has clarified the sensing principle behind the special remote measurement system that enables accurate remote sensing of AE signals. Since the silica-glass optical fibers have a high heat-resistance exceeding 1000 °C, this work presents a preliminary high-temperature AE detection method by using the optical fiber-based ultrasonic waveguide to propagate the AE from a high-temperature environment to a room-temperature environment, in which the FBG sensor could function as the receiver of the guided wave. As a result, the novel measurement configuration successfully achieved highly sensitive and stable AE detection in an alumina plate at elevated temperatures in the 100 °C to 1000 °C range. Due to its good performance, this detection method will be potentially useful for the non-destructive testing that can be performed in high-temperature environments to evaluate the microscopic damage in heat-resistant materials.

Tele-transmission of stereoscopic images of the optic nerve head in glaucoma via Internet.

PubMed

Bergua, Antonio; Mardin, Christian Y; Horn, Folkert K

2009-06-01

The objective was to describe an inexpensive system to visualize stereoscopic photographs of the optic nerve head on computer displays and to transmit such images via the Internet for collaborative research or remote clinical diagnosis in glaucoma. Stereoscopic images of glaucoma patients were digitized and stored in a file format (joint photographic stereoimage [jps]) containing all three-dimensional information for both eyes on an Internet Web site (www.trizax.com). The size of jps files was between 0.4 to 1.4 MB (corresponding to a diagonal stereo image size between 900 and 1400 pixels) suitable for Internet protocols. A conventional personal computer system equipped with wireless stereoscopic LCD shutter glasses and a CRT-monitor with high refresh rate (120 Hz) can be used to obtain flicker-free stereo visualization of true-color images with high resolution. Modern thin-film transistor-LCD displays in combination with inexpensive red-cyan goggles achieve stereoscopic visualization with the same resolution but reduced color quality and contrast. The primary aim of our study was met to transmit stereoscopic images via the Internet. Additionally, we found that with both stereoscopic visualization techniques, cup depth, neuroretinal rim shape, and slope of the inner wall of the optic nerve head, can be qualitatively better perceived and interpreted than with monoscopic images. This study demonstrates high-quality and low-cost Internet transmission of stereoscopic images of the optic nerve head from glaucoma patients. The technique allows exchange of stereoscopic images and can be applied to tele-diagnostic and glaucoma research.

Coherent optical modulation for antenna remoting

NASA Technical Reports Server (NTRS)

Fitzmartin, D. J.; Gels, R. G.; Balboni, E. J.

1991-01-01

A coherent fiber optic link employing wideband frequency modulation (FM) of the optical carrier is used to transfer radio frequency (RF) or microwave signals. This system is used to link a remotely located antenna to a conveniently located electronics processing site. The advantages of coherent analog fiber optic systems over non-coherent intensity modulated fiber optic analog transmission systems are described. An optical FM link employing an indirect transmitter to frequency modulate the optical carrier and a microwave delay line discriminator receiver is described. Measured performance data for a video signal centered at 60 MHz is presented showing the use of wideband FM in the link.

Validation of satellite-based operational flood monitoring in Southern Queensland, Australia

NASA Astrophysics Data System (ADS)

Gouweleeuw, Ben; Ticehurst, Catherine; Lerat, Julien; Thew, Peter

2010-05-01

The integration of remote sensing observations with stage data and flood modeling has the potential to provide improved support to a number of disciplines, such as flood warning emergency response and operational water resources management. The ability of remote sensing technology to monitor the dynamics of hydrological events lies in its capacity to map surface water. For flood monitoring, remote sensing imagery needs to be available sufficiently frequently to capture subsequent inundation stages. MODIS optical data are available at a moderately high spatial and temporal resolution (250m-1km, twice daily), but are affected by cloud cover. AMSR-E passive microwave observations are available at comparable temporal resolution, but coarse spatial resolution (5-70km), where the smaller footprints corresponds with the higher frequency bands, which are affected by precipitating clouds. A novel operational technique to monitor flood extent combines MODIS reflectance and AMSR-E passive microwave imagery to optimize data continuity. Flood extent is subsequently combined with a DEM to obtain total flood water volume. The flood extent and volume product is operational for the lower-Balonne floodplain in Southern Queensland, Australia. For validation purposes, two moderate flood events coinciding with the MODIS and AMSR-E sensor lifetime are evaluated. The flood volume estimated from MODIS/AMSR-E images gives an accurate indication of both the timing and the magnitude of the flood peak compared to the net volume from recorded flow. In the flood recession, however, satellite-derived water volume declines rapidly, while the net flow volume remains level. This may be explained by a combination of ungauged outflows, soil infiltration, evaporation and diversion of flood water into many large open reservoirs for irrigation purposes. The open water storage extent unchanged, the water volume product is not sensitive enough to capture the change in storage water level. Additional information on the latter, e.g. via telemetered buoys, may circumvent this limitation.

Remote Sensing of Wind Fields and Aerosol Distribution with Airborne Scanning Doppler Lidar

NASA Technical Reports Server (NTRS)

Rothermel, Jeffry; Cutten, Dean R.; Johnson, Steven C.; Jazembski, Maurice; Arnold, James E. (Technical Monitor)

2001-01-01

The coherent Doppler laser radar (lidar), when operated from an airborne platform, is a unique tool for the study of atmospheric and surface processes and features. This is especially true for scientific objectives requiring measurements in optically-clear air, where other remote sensing technologies such as Doppler radar are typically at a disadvantage. The atmospheric lidar remote sensing groups of several US institutions, led by Marshall Space Flight Center, have developed an airborne coherent Doppler lidar capable of mapping the wind field and aerosol structure in three dimensions. The instrument consists of an eye-safe approx. 1 Joule/pulse lidar transceiver, telescope, scanner, inertial measurement unit, and flight computer system to orchestrate all subsystem functions and tasks. The scanner is capable of directing the expanded lidar beam in a variety of ways, in order to extract vertically-resolved wind fields. Horizontal resolution is approx. 1 km; vertical resolution is even finer. Winds are obtained by measuring backscattered, Doppler-shifted laser radiation from naturally-occurring aerosol particles (of order 1 micron diameter). Measurement coverage depends on aerosol spatial distribution and composition. Velocity accuracy has been verified to be approx. 1 meter per second. A variety of applications have been demonstrated during the three flight campaigns conducted during 1995-1998. Examples will be shown during the presentation. In 1995, boundary layer winds over the ocean were mapped with unprecedented resolution. In 1996, unique measurements were made of. flow over the complex terrain of the Aleutian Islands; interaction of the marine boundary layer jet with the California coastal mountain range; a weak dry line in Texas - New Mexico; the angular dependence of sea surface scattering; and in-flight radiometric calibration using the surface of White Sands National Monument. In 1998, the first measurements of eyewall and boundary layer winds within a hurricane were made with the airborne Doppler lidar. Potential applications and plans for improvement will also be described.

A review of surface energy balance models for estimating actual evapotranspiration with remote sensing at high spatiotemporal resolution over large extents

Treesearch

Ryan R. McShane; Katelyn P. Driscoll; Roy Sando

2017-01-01

Many approaches have been developed for measuring or estimating actual evapotranspiration (ETa), and research over many years has led to the development of remote sensing methods that are reliably reproducible and effective in estimating ETa. Several remote sensing methods can be used to estimate ETa at the high spatial resolution of agricultural fields and the large...

Modeling, simulation, and analysis of optical remote sensing systems

NASA Technical Reports Server (NTRS)

Kerekes, John Paul; Landgrebe, David A.

1989-01-01

Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.

Grapevine Remote Sensing Analysis of Phylloxera Early Stress (GRAPES): Remote Sensing Analysis Summary

NASA Technical Reports Server (NTRS)

Lobitz, Brad; Johnson, Lee; Hlavka, Chris; Armstrong, Roy; Bell, Cindy

1997-01-01

High spatial resolution airborne imagery was acquired in California's Napa Valley in 1993 and 1994 as part of the Grapevine Remote sensing Analysis of Phylloxera Early Stress (GRAPES) project. Investigators from NASA, the University of California, the California State University, and Robert Mondavi Winery examined the application of airborne digital imaging technology to vineyard management, with emphasis on detecting the phylloxera infestation in California vineyards. Because the root louse causes vine stress that leads to grapevine death in three to five years, the infested areas must be replanted with resistant rootstock. Early detection of infestation and changing cultural practices can compensate for vine damage. Vineyard managers need improved information to decide where and when to replant fields or sections of fields to minimize crop financial losses. Annual relative changes in leaf area due to phylloxera infestation were determined by using information obtained from computing Normalized Difference Vegetation Index (NDVI) images. Two other methods of monitoring vineyards through imagery were also investigated: optical sensing of the Red Edge Inflection Point (REIP), and thermal sensing. These did not convey the stress patterns as well as the NDVI imagery and require specialized sensor configurations. NDVI-derived products are recommended for monitoring phylloxera infestations.

Developing Initial Response Products Using Data from Optical and SAR Earth Observing Platforms for Natural Disaster Response

NASA Astrophysics Data System (ADS)

Bell, J. R.; Molthan, A.; Dabboor, M.

2016-12-01

After a disaster occurs, decision makers require timely information to assist decision making and support. Earth observing satellites provide tools including optical remote sensors that sample in various spectral bands within the visible, near-infrared, and thermal infrared. However, views from optical sensors can be blocked when clouds are present, and cloud-free observations can be significantly delayed depending upon on their repeat cycle. Synthetic aperture radar (SAR) offers several advantages over optical sensors in terms of spatial resolution and the ability to map the Earth's surface whether skies are clear or cloudy. In cases where both SAR and cloud-free optical data are available, these instruments can be used together to provide additional confidence in what is being observed at the surface. This presentation demonstrates cases where SAR imagery can enhance the usefulness for mapping natural disasters and their impacts to the land surface, specifically from severe weather and flooding. The Missouri and Mississippi River flooding from early in 2016 and damage from hail swath in northwestern Iowa on 17 June 2016 are just two events that will be explored. Data collected specifically from the EO-1 (optical), Landsat (optical) and Sentinel 1 (SAR) missions are used to explore several applicable methodologies to determine which products and methodologies may provide decision makers with the best information to provide actionable information in a timely manner.

Sensitivity of atmospheric correction to loading and model of the aerosol

NASA Astrophysics Data System (ADS)

Bassani, Cristiana; Braga, Federica; Bresciani, Mariano; Giardino, Claudia; Adamo, Maria; Ananasso, Cristina; Alberotanza, Luigi

2013-04-01

The physically-based atmospheric correction requires knowledge of the atmospheric conditions during the remotely data acquisitions [Guanter et al., 2007; Gao et al., 2009; Kotchenova et al. 2009; Bassani et al., 2010]. The propagation of solar radiation in the atmospheric window of visible and near-infrared spectral domain, depends on the aerosol scattering. The effects of solar beam extinction are related to the aerosol loading, by the aerosol optical thickness @550nm (AOT) parameter [Kaufman et al., 1997; Vermote et al., 1997; Kotchenova et al., 2008; Kokhanovsky et al. 2010], and also to the aerosol model. Recently, the atmospheric correction of hyperspectral data is considered sensitive to the micro-physical and optical characteristics of aerosol, as reported in [Bassani et al., 2012]. Within the framework of CLAM-PHYM (Coasts and Lake Assessment and Monitoring by PRISMA HYperspectral Mission) project, funded by Italian Space Agency (ASI), the role of the aerosol model on the accuracy of the atmospheric correction of hyperspectral image acquired over water target is investigated. In this work, the results of the atmospheric correction of HICO (Hyperspectral Imager for the Coastal Ocean) images acquired on Northern Adriatic Sea in the Mediterranean are presented. The atmospheric correction has been performed by an algorithm specifically developed for HICO sensor. The algorithm is based on the equation presented in [Vermote et al., 1997; Bassani et al., 2010] by using the last generation of the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) radiative transfer code [Kotchenova et al., 2008; Vermote et al., 2009]. The sensitive analysis of the atmospheric correction of HICO data is performed with respect to the aerosol optical and micro-physical properties used to define the aerosol model. In particular, a variable mixture of the four basic components: dust- like, oceanic, water-soluble, and soot, has been considered. The water reflectance, obtained from the atmospheric correction with variable model and fixed loading of the aerosol, has been compared. The results highlight the requirements to define the aerosol characteristics, loading and model, to simulate the radiative field in the atmosphere system for an accurate atmospheric correction of hyperspectral data, improving the accuracy of the results for surface reflectance process over water, a dark-target. As conclusion, the aerosol model plays a crucial role for an accurate physically-based atmospheric correction of hyperspectral data over water. Currently, the PRISMA mission provides valuable opportunities to study aerosol and their radiative effects on the hyperspectral data. Bibliography Guanter, L.; Estellès, V.; Moreno, J. Spectral calibration and atmospheric correction of ultra-fine spectral and spatial resolution remote sensing data. Application to CASI-1500 data. Remote Sens. Environ. 2007, 109, 54-65. Gao, B.-C.; Montes, M.J.; Davis, C.O.; Goetz, A.F.H. Atmospheric correction algorithms for hyperspectral remote sensing data of land and ocean. Remote Sens. Environ. 2009, 113, S17-S24. Kotchenova, S. Atmospheric correction for the monitoring of land surfaces. J. Geophys. Res. 2009, 113, D23. Bassani C.; Cavalli, R.M.; Pignatti S. Aerosol optical retrieval and surface reflectance from airborne remote sensing data over land. Sens. 2010, 10, 6421-6438. Kaufman, Y. J., Tanrè, D., Gordon H. R., Nakajima T., Lenoble J., Frouin R., Grassl H., Herman B.M., King M., and Teillet P.M.: Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer, J. Geophys. Res., 102(D14), 17051-17067, 1997. Vermote, E.F.; Tanrè , D.; Deuzè´ , J.L.; Herman M.; Morcrette J.J. Second simulation of the satellite signal in the solar spectrum, 6S: An overview. IEEE Trans. Geosci. Remote Sens. 1997, 35, 675-686. Kotchenova, S.Y.; Vermote, E.F.; Levy, R.; Lyapustin, A. Radiative transfer codes for atmospheric correction and aerosol retrieval: Intercomparison study. Appl. Optics 2008, 47, 2215-2226. Kokhanovsky A.A., Deuzè J.L., Diner D.J., Dubovik O., Ducos F., Emde C., Garay M.J., Grainger R.G., Heckel A., Herman M., Katsev I.L., Keller J., Levy R., North P.R.J., Prikhach A.S., Rozanov V.V., Sayer A.M., Ota Y., Tanrè D., Thomas G.E., Zege E.P. The inter-comparison of major satellite aerosol retrieval algorithms using simulated intensity and polarization characteristics of reflected light. Atmos. Meas. Tech., 3, 909-932, 2010. Bassani C.; Cavalli, R.M.; Antonelli, P. Influence of aerosol and surface reflectance variability on hyperspectral observed radiance. Atmos. Meas. Tech. 2012, 5, 1193-1203. Vermote , E.F.; Kotchenova, S. Atmospheric correction for the monitoring of land surfaces. J. Geophys. Res. 2009, 113, D23.

Timely detection and monitoring of oil leakage by satellite optical data.

NASA Astrophysics Data System (ADS)

Grimaldi, C. S. L.; Coviello, I.; Lacava, T.; Pergola, N.; Tramutoli, V.

2009-04-01

Sea oil pollution can derive from different sources. Accidental release of oil into the oceans caused by "human errors" (tankers collisions and/or shipwrecks) or natural hazards (hurricanes, landslides, earthquakes) have remarkable ecological impact on maritime and coastal environments. Katrina Hurricane, for example, hitting oil and gas infrastructures off USA coasts caused the destruction of more than 100 platforms and the release into the sea of more than 10,000 gallons of crude oil. In order to reduce the environmental impact of such kind of technological hazards, timely detection and continuously updated information are fundamental. Satellite remote sensing can give a significant contribution in such a direction. Nowadays, SAR (Synthetic Aperture Radar) technology has been recognized as the most efficient for oil spill detection and mapping, thanks to the high spatial resolution and all-time/weather capability of the present operational sensors. Anyway, due to their current revisiting cycles, SAR systems cannot be profitably used for a rapid detection and for a continuous and near real-time monitoring of these phenomena. Until COSMO-Skymed SAR constellation, that will be able to improve SAR observational frequency, will not be fully operational, passive optical sensors on board meteorological satellites, thanks to their high temporal resolution, may represent a suitable alternative for early detection and continuous monitoring of oil spills, provided that adequate and reliable data analysis techniques exist. Recently, an innovative technique for oil spill detection and monitoring, based on the general Robust Satellite Techniques (RST) approach, has been proposed. It exploits the multi-temporal analysis of optical data acquired by both AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) sensors in order to detect, automatically and timely, the presence of oil spill over the sea surface, trying to minimize the "false-detections" possibly caused by spurious effects (e.g. clouds). In this paper, preliminary results obtained applying the proposed methodology to different test-cases are shown and discussed.

EVALUATION OF FUGITIVE EMISSIONS USING GROUND-BASED OPTICAL REMOTE SENSING TECHNOLOGY

EPA Science Inventory

EPA has developed and evaluated a method for characterizing fugitive emissions from large area sources. The method, known as radial plume mapping (RPM) uses multiple-beam, scanning, optical remote sensing (ORS) instrumentation such as open-path Fourier transform infrared spectro...

Public Good or Commercial Opportunity: Case Studies in Remote Sensing Commercialization

NASA Technical Reports Server (NTRS)

Johnston, Shaida; Cordes, Joseph

2002-01-01

The U.S. Government is once again attempting to commercialize the Landsat program and is asking the private sector to develop a next generation mid-resolution remote sensing system that will provide continuity with the thirty-year data archive of Landsat data. Much of the case for commercializing the Landsat program rests on the apparently successful commercialization of high-resolution remote sensing activities coupled with the belief that conditions have changed since the failed attempt to commercialize Landsat in the 1980s. This paper analyzes the economic, political and technical conditions that prevailed in the 1980s as well as conditions that might account for the apparent success of the emerging high-resolution remote sensing industry today. Lessons are gleaned for the future of the Landsat program.

Mapping rice extent map with crop intensity in south China through integration of optical and microwave images based on google earth engine

NASA Astrophysics Data System (ADS)

Zhang, X.; Wu, B.; Zhang, M.; Zeng, H.

2017-12-01

Rice is one of the main staple foods in East Asia and Southeast Asia, which has occupied more than half of the world's population with 11% of cultivated land. Study on rice can provide direct or indirect information on food security and water source management. Remote sensing has proven to be the most effective method to monitoring the cropland in large scale by using temporary and spectral information. There are two main kinds of satellite have been used to mapping rice including microwave and optical. Rice, as the main crop of paddy fields, the main feature different from other crops is flooding phenomenon at planning stage (Figure 1). Microwave satellites can penetrate through clouds and efficiency on monitoring flooding phenomenon. Meanwhile, the vegetation index based on optical satellite can well distinguish rice from other vegetation. Google Earth Engine is a cloud-based platform that makes it easy to access high-performance computing resources for processing very large geospatial datasets. Google has collected large number of remote sensing satellite data around the world, which providing researchers with the possibility of doing application by using multi-source remote sensing data in a large area. In this work, we map rice planting area in south China through integration of Landsat-8 OLI, Sentienl-2, and Sentinel-1 Synthetic Aperture Radar (SAR) images. The flowchart is shown in figure 2. First, a threshold method the VH polarized backscatter from SAR sensor and vegetation index including normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) from optical sensor were used the classify the rice extent map. The forest and water surface extent map provided by earth engine were used to mask forest and water. To overcome the problem of the "salt and pepper effect" by Pixel-based classification when the spatial resolution increased, we segment the optical image and use the pixel- based classification results to merge the object-oriented segmentation data, and finally get the rice extent map. At last, by using the time series analysis, the peak count was obtained for each rice area to ensure the crop intensity. In this work, the rice ground point from a GVG crowdsourcing smartphone and rice area statistical results from National Bureau of Statistics were used to validate and evaluate our result.

Enhancing Spatial Resolution of Remotely Sensed Imagery Using Deep Learning

NASA Astrophysics Data System (ADS)

Beck, J. M.; Bridges, S.; Collins, C.; Rushing, J.; Graves, S. J.

2017-12-01

Researchers at the Information Technology and Systems Center at the University of Alabama in Huntsville are using Deep Learning with Convolutional Neural Networks (CNNs) to develop a method for enhancing the spatial resolutions of moderate resolution (10-60m) multispectral satellite imagery. This enhancement will effectively match the resolutions of imagery from multiple sensors to provide increased global temporal-spatial coverage for a variety of Earth science products. Our research is centered on using Deep Learning for automatically generating transformations for increasing the spatial resolution of remotely sensed images with different spatial, spectral, and temporal resolutions. One of the most important steps in using images from multiple sensors is to transform the different image layers into the same spatial resolution, preferably the highest spatial resolution, without compromising the spectral information. Recent advances in Deep Learning have shown that CNNs can be used to effectively and efficiently upscale or enhance the spatial resolution of multispectral images with the use of an auxiliary data source such as a high spatial resolution panchromatic image. In contrast, we are using both the spatial and spectral details inherent in low spatial resolution multispectral images for image enhancement without the use of a panchromatic image. This presentation will discuss how this technology will benefit many Earth Science applications that use remotely sensed images with moderate spatial resolutions.

The family of micro sensors for remote control the pollution in liquids and gases

NASA Astrophysics Data System (ADS)

Tulaikova, Tamara; Kocharyun, Gevorg; Rogerson, Graham; Burmistrova, Ludmyla; Sychugov, Vladimir; Dorojkin, Peter

2005-10-01

There are the results for the 3 groups of fiber-optical sensors. First is the fiber-optical sensor with changed sensitive heads on the base on porous polymer with clamped activated dye. Vibration method for fiber-optical sensors provides more convenient output measurements of resonant frequency changes, in comparison with the first device. The self-focusing of the living sells into optical wave-guides in laser road in water will be considered as a new touch method for environment remote sensing.

Hyperspectral Remote Sensing of the Coastal Ocean: Adaptive Sampling and Forecasting of In situ Optical Properties

DTIC Science & Technology

2003-09-30

We are developing an integrated rapid environmental assessment capability that will be used to feed an ocean nowcast/forecast system. The goal is to develop a capacity for predicting the dynamics in inherent optical properties in coastal waters. This is being accomplished by developing an integrated observation system that is being coupled to a data assimilative hydrodynamic bio-optical ecosystem model. The system was used adaptively to calibrate hyperspectral remote sensing sensors in optically complex nearshore coastal waters.

Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005-2015

NASA Astrophysics Data System (ADS)

Thompson, David R.; Kahn, Brian H.; Green, Robert O.; Chien, Steve A.; Middleton, Elizabeth M.; Tran, Daniel Q.

2018-02-01

The distribution of ice, liquid, and mixed phase clouds is important for Earth's planetary radiation budget, impacting cloud optical properties, evolution, and solar reflectivity. Most remote orbital thermodynamic phase measurements observe kilometer scales and are insensitive to mixed phases. This under-constrains important processes with outsize radiative forcing impact, such as spatial partitioning in mixed phase clouds. To date, the fine spatial structure of cloud phase has not been measured at global scales. Imaging spectroscopy of reflected solar energy from 1.4 to 1.8 µm can address this gap: it directly measures ice and water absorption, a robust indicator of cloud top thermodynamic phase, with spatial resolution of tens to hundreds of meters. We report the first such global high spatial resolution survey based on data from 2005 to 2015 acquired by the Hyperion imaging spectrometer onboard NASA's Earth Observer 1 (EO-1) spacecraft. Seasonal and latitudinal distributions corroborate observations by the Atmospheric Infrared Sounder (AIRS). For extratropical cloud systems, just 25 % of variance observed at GCM grid scales of 100 km was related to irreducible measurement error, while 75 % was explained by spatial correlations possible at finer resolutions.

BTDI detector technology for reconnaissance application

NASA Astrophysics Data System (ADS)

Hilbert, Stefan; Eckardt, Andreas; Krutz, David

2017-11-01

The Institute of Optical Sensor Systems (OS) at the Robotics and Mechatronics Center of the German Aerospace Center (DLR) has more than 30 years of experience with high-resolution imaging technology. This paper shows the institute's scientific results of the leading-edge detector design in a BTDI (Bidirectional Time Delay and Integration) architecture. This project demonstrates an approved technological design for high or multi-spectral resolution spaceborne instruments. DLR OS and BAE Systems were driving the technology of new detectors and the FPA design for future projects, new manufacturing accuracy in order to keep pace with ambitious scientific and user requirements. Resulting from customer requirements and available technologies the current generation of space borne sensor systems is focusing on VIS/NIR high spectral resolution to meet the requirements on earth and planetary observation systems. The combination of large swath and high-spectral resolution with intelligent control applications and new focal plane concepts opens the door to new remote sensing and smart deep space instruments. The paper gives an overview of the detector development and verification program at DLR on detector module level and key parameters like SNR, linearity, spectral response, quantum efficiency, PRNU, DSNU and MTF.

Remote Sensing and Reflectance Profiling in Entomology.

PubMed

Nansen, Christian; Elliott, Norman

2016-01-01

Remote sensing describes the characterization of the status of objects and/or the classification of their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be benchtop based, and therefore acquired at a high spatial resolution, or airborne at lower spatial resolution to cover large areas. Despite important challenges, airborne remote sensing technologies will undoubtedly be of major importance in optimized management of agricultural systems in the twenty-first century. Benchtop remote sensing applications are becoming important in insect systematics and in phenomics studies of insect behavior and physiology. This review highlights how remote sensing influences entomological research by enabling scientists to nondestructively monitor how individual insects respond to treatments and ambient conditions. Furthermore, novel remote sensing technologies are creating intriguing interdisciplinary bridges between entomology and disciplines such as informatics and electrical engineering.

Identifying Corresponding Patches in SAR and Optical Images With a Pseudo-Siamese CNN

NASA Astrophysics Data System (ADS)

Hughes, Lloyd H.; Schmitt, Michael; Mou, Lichao; Wang, Yuanyuan; Zhu, Xiao Xiang

2018-05-01

In this letter, we propose a pseudo-siamese convolutional neural network (CNN) architecture that enables to solve the task of identifying corresponding patches in very-high-resolution (VHR) optical and synthetic aperture radar (SAR) remote sensing imagery. Using eight convolutional layers each in two parallel network streams, a fully connected layer for the fusion of the features learned in each stream, and a loss function based on binary cross-entropy, we achieve a one-hot indication if two patches correspond or not. The network is trained and tested on an automatically generated dataset that is based on a deterministic alignment of SAR and optical imagery via previously reconstructed and subsequently co-registered 3D point clouds. The satellite images, from which the patches comprising our dataset are extracted, show a complex urban scene containing many elevated objects (i.e. buildings), thus providing one of the most difficult experimental environments. The achieved results show that the network is able to predict corresponding patches with high accuracy, thus indicating great potential for further development towards a generalized multi-sensor key-point matching procedure. Index Terms-synthetic aperture radar (SAR), optical imagery, data fusion, deep learning, convolutional neural networks (CNN), image matching, deep matching

Cal/Val Study for Geostationary Ocean Color Imager

NASA Astrophysics Data System (ADS)

Ryu, J.; Moon, J.; Min, J.; Cho, S.; Ahn, Y.

2009-12-01

GOCI, the first Geostationary Ocean Color Imager, shall be operated in a staring-frame capture mode onboard its Communication Ocean and Meteorological Satellite (COMS) and tentatively scheduled for launch in 2010. The mission concept includes eight visible-to-near-infrared bands, 0.5 km pixel resolution, and a coverage region of 2,500 × 2,500 km2 centered at Korea. The GOCI is expected to provide SeaWiFS quality observations for a single study area with imaging interval of 1 hour from 10 am to 5 pm. Due to optically more complex waters of GOCI swath area, we developed new atmospheric correction and bio-optical algorithms for GOCI. The 1st objective is to compare and validate the water-leaving radiance using the radiometric data from spectroradiometer installed in Ieodo and Gaegeocho ocean research station. The 2nd objective is to calibrate and validate the bio-optical product by GDPS using the Dokdo buoy and in situ measurements. As the result of comparison of spectrum shape using the remote reflectance normalized 555 nm, most of all data was well matched. Validation result of local bio-optical algorithms installed in GDPS showed the less than 20 %.

Satellite remote sensing of air quality in winter of Lanzhou

NASA Astrophysics Data System (ADS)

Wang, Dawei; Han, Tao; Jiang, Youyan; Li, Lili; Ren, Shuyuan

2018-03-01

Fine particulate matter (aerodynamic diameters of less than 2.5 μm, PM2.5) air pollution has become one of the global environmental problem, endangering the existence of residents living, climate, and public health. Estimation Particulate Matter (aerodynamic diameters of less than 10 μm, PM10) concentration and aerosol absorption was the key point in air quality and climate studies. In this study, we retrieve the Aerosol Optical Depth (AOD) from the Earth Observing System (EOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS), and PM2.5, PM10 in winter on 2014 and 2015, using Extended Dense Dark Vegetation Algorithm and 6S radiation model to analysis the correlation. The result showed that at the condition of non-considering the influence of primary pollutants, the correlation of two Polynomials between aerosol optical depth and PM2.5 and PM10 was poor; taking the influence of the primary pollutants into consideration, the aerosol optical depth has a good correlation with PM2.5 and PM10. The version of PM10 by aerosol optical depth is higher than that of PM2.5, so the model can be used to realize the high precision inversion of winter PM10 in Lanzhou.

High-resolution remotely sensed small target detection by imitating fly visual perception mechanism.

PubMed

Huang, Fengchen; Xu, Lizhong; Li, Min; Tang, Min

2012-01-01

The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.

Sun glint requirement for the remote detection of surface oil films

NASA Astrophysics Data System (ADS)

Sun, Shaojie; Hu, Chuanmin

2016-01-01

Natural oil slicks in the western Gulf of Mexico are used to determine the sun glint threshold required for optical remote sensing of oil films. The threshold is determined using the same-day image pairs collected by Moderate Resolution Imaging Spectroradiometer (MODIS) Terra (MODIST), MODIS Aqua (MODISA), and Visible Infrared Imaging Radiometer Suite (VIIRS) (N = 2297 images) over the same oil slick locations where at least one of the sensors captures the oil slicks. For each sensor, statistics of sun glint strengths, represented by the normalized glint reflectance (LGN, sr-1), when oil slicks can and cannot be observed are generated. The LGN threshold for oil film detections is determined to be 10-5-10-6 sr-1 for MODIST and MODISA, and 10-6-10-7 sr-1 for VIIRS. Below these thresholds, no oil films can be detected, while above these thresholds, oil films can always be detected except near the critical-angle zone where oil slicks reverse their contrast against the background water.

Experimental research on thermal conductive fillers for CCD module in space borne optical remote sensor

NASA Astrophysics Data System (ADS)

Zeng, Yi; Han, Xue-bing; Yang, Dong-shang; Gui, Li-jia; Zhao, Xiao-xiang; Si, Fu-qi

2016-03-01

A space-borne differential optical absorption spectrometer is a high precision aerospace optical remote sensor. It obtains the hyper-spectral，high spatial resolution radiation information by using the spectrometer with CCD（Charge Coupled Device）array detectors. Since a few CCDs are used as the key detector, the performance of the entire instrument is greatly affected by working condition of CCDs. The temperature of CCD modules has a great impact on the instrument measurement accuracy. It requires strict temperature control. The selection of the thermal conductive filler sticking CCD to the radiator is important in the CCD thermal design. Besides，due tothe complex and compact structure, it needs to take into account the anti-pollution of the optical system. Therefore, it puts forward high requirements on the selection of the conductive filler. In this paper, according to the structure characteristics of the CCD modules and the distribution of heat consumption, the thermal analysis tool I-DEAS/TMG is utilized to compute and simulate the temperature level of the CCD modules, while filling in thermal grease and thermal pad respectively. The temperature distribution of CCD heat dissipation in typical operating conditions is obtained. In addition, the heat balance test was carried out under the condition of two kinds of thermal conductive fillers. The thermal control of CCD was tested under various conditions, and the results were compared with the results of thermal analysis. The results show that there are some differences in thermal performance between the two kinds of thermal conductive fillers. Although they both can meet the thermal performance requirements of the instrument, either would be chosen taking account of other conditions and requirements such as anti-pollution and insulation. The content and results of this paper will be a good reference for the thermal design of the CCD in the aerospace optical payload.

Estimating Gross Primary Production in Cropland with High Spatial and Temporal Scale Remote Sensing Data

NASA Astrophysics Data System (ADS)

Lin, S.; Li, J.; Liu, Q.

2018-04-01

Satellite remote sensing data provide spatially continuous and temporally repetitive observations of land surfaces, and they have become increasingly important for monitoring large region of vegetation photosynthetic dynamic. But remote sensing data have their limitation on spatial and temporal scale, for example, higher spatial resolution data as Landsat data have 30-m spatial resolution but 16 days revisit period, while high temporal scale data such as geostationary data have 30-minute imaging period, which has lower spatial resolution (> 1 km). The objective of this study is to investigate whether combining high spatial and temporal resolution remote sensing data can improve the gross primary production (GPP) estimation accuracy in cropland. For this analysis we used three years (from 2010 to 2012) Landsat based NDVI data, MOD13 vegetation index product and Geostationary Operational Environmental Satellite (GOES) geostationary data as input parameters to estimate GPP in a small region cropland of Nebraska, US. Then we validated the remote sensing based GPP with the in-situ measurement carbon flux data. Results showed that: 1) the overall correlation between GOES visible band and in-situ measurement photosynthesis active radiation (PAR) is about 50 % (R2 = 0.52) and the European Center for Medium-Range Weather Forecasts ERA-Interim reanalysis data can explain 64 % of PAR variance (R2 = 0.64); 2) estimating GPP with Landsat 30-m spatial resolution data and ERA daily meteorology data has the highest accuracy(R2 = 0.85, RMSE < 3 gC/m2/day), which has better performance than using MODIS 1-km NDVI/EVI product import; 3) using daily meteorology data as input for GPP estimation in high spatial resolution data would have higher relevance than 8-day and 16-day input. Generally speaking, using the high spatial resolution and high frequency satellite based remote sensing data can improve GPP estimation accuracy in cropland.

Compositing multitemporal remote sensing data sets

USGS Publications Warehouse

Qi, J.; Huete, A.R.; Hood, J.; Kerr, Y.

1993-01-01

To eliminate cloud and atmosphere-affected pixels, the compositing of multi temporal remote sensing data sets is done by selecting the maximum vale of the normalized different vegetation index (NDVI) within a compositing period. The NDVI classifier, however, is strongly affected by surface type and anisotropic properties, sensor viewing geometries, and atmospheric conditions. Consequently, the composited, multi temporal, remote sensing data contain substantial noise from these external conditions. Consequently, the composited, multi temporal, remote sensing data contain substantial noise from these external effects. To improve the accuracy of compositing products, two key approaches can be taken: one is to refine the compositing classifier (NDVI) and the other is to improve existing compositing algorithms. In this project, an alternative classifier was developed and an alternative pixel selection criterion was proposed for compositing. The new classifier and the alternative compositing algorithm were applied to an advanced very high resolution radiometer data set of different biome types in the United States. The results were compared with the maximum value compositing and the best index slope extraction algorithms. The new approaches greatly reduced the high frequency noises related to the external factors and repainted more reliable data. The results suggest that the geometric-optical canopy properties of specific biomes may be needed in compositing. Limitations of the new approaches include the dependency of pixel selection on the length of the composite period and data discontinuity.

Estimating dissolved organic carbon concentration in turbid coastal waters using optical remote sensing observations

NASA Astrophysics Data System (ADS)

Cherukuru, Nagur; Ford, Phillip W.; Matear, Richard J.; Oubelkheir, Kadija; Clementson, Lesley A.; Suber, Ken; Steven, Andrew D. L.

2016-10-01

Dissolved Organic Carbon (DOC) is an important component in the global carbon cycle. It also plays an important role in influencing the coastal ocean biogeochemical (BGC) cycles and light environment. Studies focussing on DOC dynamics in coastal waters are data constrained due to the high costs associated with in situ water sampling campaigns. Satellite optical remote sensing has the potential to provide continuous, cost-effective DOC estimates. In this study we used a bio-optics dataset collected in turbid coastal waters of Moreton Bay (MB), Australia, during 2011 to develop a remote sensing algorithm to estimate DOC. This dataset includes data from flood and non-flood conditions. In MB, DOC concentration varied over a wide range (20-520 μM C) and had a good correlation (R2 = 0.78) with absorption due to coloured dissolved organic matter (CDOM) and remote sensing reflectance. Using this data set we developed an empirical algorithm to derive DOC concentrations from the ratio of Rrs(412)/Rrs(488) and tested it with independent datasets. In this study, we demonstrate the ability to estimate DOC using remotely sensed optical observations in turbid coastal waters.

Spatial and Temporal Distribution of Tropospheric Clouds and Aerosols Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Remer, Lorraine A.; Kaufman, Yoram J.

2004-01-01

Remote sensing of cloud and aerosol optical properties is routinely obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites. Techniques that are being used to enhance our ability to characterize the global distribution of cloud and aerosol properties include well-calibrated multispectral radiometers that rely on visible, near-infrared, and thermal infrared channels. The availability of thermal channels to aid in cloud screening for aerosol properties is an important additional piece of information that has not always been incorporated into sensor designs. In this paper, we describe the radiative properties of clouds as currently determined from satellites (cloud fraction, optical thickness, cloud top pressure, and cloud effective radius), and highlight the global and regional cloud microphysical properties currently available for assessing climate variability and forcing. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world. In addition, we will illustrate the radiative and microphysical properties of aerosol particles that are currently available from space-based observations, and show selected cases in which aerosol particles are observed to modify the cloud optical properties.

A Self-Referenced Optical Intensity Sensor Network Using POFBGs for Biomedical Applications

PubMed Central

Moraleda, Alberto Tapetado; Montero, David Sánchez; Webb, David J.; García, Carmen Vázquez

2014-01-01

This work bridges the gap between the remote interrogation of multiple optical sensors and the advantages of using inherently biocompatible low-cost polymer optical fiber (POF)-based photonic sensing. A novel hybrid sensor network combining both silica fiber Bragg gratings (FBG) and polymer FBGs (POFBG) is analyzed. The topology is compatible with WDM networks so multiple remote sensors can be addressed providing high scalability. A central monitoring unit with virtual data processing is implemented, which could be remotely located up to units of km away. The feasibility of the proposed solution for potential medical environments and biomedical applications is shown. PMID:25615736

A self-referenced optical intensity sensor network using POFBGs for biomedical applications.

PubMed

Tapetado Moraleda, Alberto; Sánchez Montero, David; Webb, David J; Vázquez García, Carmen

2014-12-12

This work bridges the gap between the remote interrogation of multiple optical sensors and the advantages of using inherently biocompatible low-cost polymer optical fiber (POF)-based photonic sensing. A novel hybrid sensor network combining both silica fiber Bragg gratings (FBG) and polymer FBGs (POFBG) is analyzed. The topology is compatible with WDM networks so multiple remote sensors can be addressed providing high scalability. A central monitoring unit with virtual data processing is implemented, which could be remotely located up to units of km away. The feasibility of the proposed solution for potential medical environments and biomedical applications is shown.

Optically powered remote gas monitor

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

Dubaniewicz, T.H. Jr.; Chilton, J.E.

1995-12-31

Many mines rely on toxic gas sensors to help maintain a safe and healthy work environment. This report describes a prototype monitoring system developed by the US Bureau of Mines (USBM) that uses light to power and communicate with several remote toxic gas sensors. The design is based on state-of-art optical-to-electrical power converters, solid-state diode lasers, and fiber optics. This design overcomes several problems associated with conventional wire-based systems by providing complete electrical isolation between the remote sensors and the central monitor. The prototype performed well during a 2-week field trial in the USBM Pittsburgh Research Center Safety Research Coalmore » Mine.« less

In-situ spectrophotometric probe

DOEpatents

Prather, William S.

1992-01-01

A spectrophotometric probe for in situ absorption spectra measurements comprising a first optical fiber carrying light from a remote light source, a second optical fiber carrying light to a remote spectrophotometer, the proximal ends of the first and second optical fibers parallel and coterminal, a planoconvex lens to collimate light from the first optical fiber, a reflecting grid positioned a short distance from the lens to reflect the collimated light back to the lens for focussing on the second optical fiber. The lens is positioned with the convex side toward the optical fibers. A substrate for absorbing analyte or an analyte and reagent mixture may be positioned between the lens and the reflecting grid.

Remote sensing with intense filaments enhanced by adaptive optics

NASA Astrophysics Data System (ADS)

Daigle, J.-F.; Kamali, Y.; Châteauneuf, M.; Tremblay, G.; Théberge, F.; Dubois, J.; Roy, G.; Chin, S. L.

2009-11-01

A method involving a closed loop adaptive optic system is investigated as a tool to significantly enhance the collected optical emissions, for remote sensing applications involving ultrafast laser filamentation. The technique combines beam expansion and geometrical focusing, assisted by an adaptive optics system to correct the wavefront aberrations. Targets, such as a gaseous mixture of air and hydrocarbons, solid lead and airborne clouds of contaminated aqueous aerosols, were remotely probed with filaments generated at distances up to 118 m after the focusing beam expander. The integrated backscattered signals collected by the detection system (15-28 m from the filaments) were increased up to a factor of 7, for atmospheric N2 and solid lead, when the wavefronts were corrected by the adaptive optic system. Moreover, an extrapolation based on a simplified version of the LIDAR equation showed that the adaptive optic system improved the detection distance for N2 molecular fluorescence, from 45 m for uncorrected wavefronts to 125 m for corrected.

High resolution remote sensing for reducing uncertainties in urban forest carbon offset life cycle assessments.

PubMed

Tigges, Jan; Lakes, Tobia

2017-10-04

Urban forests reduce greenhouse gas emissions by storing and sequestering considerable amounts of carbon. However, few studies have considered the local scale of urban forests to effectively evaluate their potential long-term carbon offset. The lack of precise, consistent and up-to-date forest details is challenging for long-term prognoses. Therefore, this review aims to identify uncertainties in urban forest carbon offset assessment and discuss the extent to which such uncertainties can be reduced by recent progress in high resolution remote sensing. We do this by performing an extensive literature review and a case study combining remote sensing and life cycle assessment of urban forest carbon offset in Berlin, Germany. Recent progress in high resolution remote sensing and methods is adequate for delivering more precise details on the urban tree canopy, individual tree metrics, species, and age structures compared to conventional land use/cover class approaches. These area-wide consistent details can update life cycle inventories for more precise future prognoses. Additional improvements in classification accuracy can be achieved by a higher number of features derived from remote sensing data of increasing resolution, but first studies on this subject indicated that a smart selection of features already provides sufficient data that avoids redundancies and enables more efficient data processing. Our case study from Berlin could use remotely sensed individual tree species as consistent inventory of a life cycle assessment. However, a lack of growth, mortality and planting data forced us to make assumptions, therefore creating uncertainty in the long-term prognoses. Regarding temporal changes and reliable long-term estimates, more attention is required to detect changes of gradual growth, pruning and abrupt changes in tree planting and mortality. As such, precise long-term urban ecological monitoring using high resolution remote sensing should be intensified, especially due to increasing climate change effects. This is important for calibrating and validating recent prognoses of urban forest carbon offset, which have so far scarcely addressed longer timeframes. Additionally, higher resolution remote sensing of urban forest carbon estimates can improve upscaling approaches, which should be extended to reach a more precise global estimate for the first time. Urban forest carbon offset can be made more relevant by making more standardized assessments available for science and professional practitioners, and the increasing availability of high resolution remote sensing data and the progress in data processing allows for precisely that.

Use of UAS remote sensing data to estimate crop ET at high spatial resolution

USDA-ARS?s Scientific Manuscript database

Estimation of the spatial distribution of evapotranspiration (ET) based on remotely sensed imagery has become useful for managing water in irrigated agricultural at various spatial scales. However, data acquired by conventional satellites (Landsat, ASTER, etc.) lack the spatial resolution to capture...

RADIAL COMPUTED TOMOGRAPHY OF AIR CONTAMINANTS USING OPTICAL REMOTE SENSING

EPA Science Inventory

The paper describes the application of an optical remote-sensing (ORS) system to map air contaminants and locate fugitive emissions. Many ORD systems may utilize radial non-overlapping beam geometry and a computed tomography (CT) algorithm to map the concentrations in a plane. In...

TerraSAR-X high-resolution radar remote sensing: an operational warning system for Rift Valley fever risk.

PubMed

Vignolles, Cécile; Tourre, Yves M; Mora, Oscar; Imanache, Laurent; Lafaye, Murielle

2010-11-01

In the vicinity of the Barkedji village (in the Ferlo region of Senegal), the abundance and aggressiveness of the vector mosquitoes for Rift Valley fever (RVF) are strongly linked to rainfall events and associated ponds dynamics. Initially, these results were obtained from spectral analysis of high-resolution (~10 m) Spot-5 images, but, as a part of the French AdaptFVR project, identification of the free water dynamics within ponds was made with the new high-resolution (down to 3-meter pixels), Synthetic Aperture Radar satellite (TerraSAR-X) produced by Infoterra GmbH, Friedrichshafen/Potsdam, Germany. During summer 2008, within a 30 x 50 km radar image, it was found that identified free water fell well within the footprints of ponds localized by optical data (i.e. Spot-5 images), which increased the confidence in this new and complementary remote sensing technique. Moreover, by using near real-time rainfall data from the Tropical Rainfall Measuring Mission (TRMM), NASA/JAXA joint mission, the filling-up and flushing-out rates of the ponds can be accurately determined. The latter allows for a precise, spatio-temporal mapping of the zones potentially occupied by mosquitoes capable of revealing the variability of pond surfaces. The risk for RVF infection of gathered bovines and small ruminants (~1 park/km(2)) can thus be assessed. This new operational approach (which is independent of weather conditions) is an important development in the mapping of risk components (i.e. hazards plus vulnerability) related to RVF transmission during the summer monsoon, thus contributing to a RVF early warning system.

Data fusion in data scarce areas using a back-propagation artificial neural network model: a case study of the South China Sea

NASA Astrophysics Data System (ADS)

Wang, Zheng; Mao, Zhihua; Xia, Junshi; Du, Peijun; Shi, Liangliang; Huang, Haiqing; Wang, Tianyu; Gong, Fang; Zhu, Qiankun

2018-06-01

The cloud cover for the South China Sea and its coastal area is relatively large throughout the year, which limits the potential application of optical remote sensing. A HJ-charge-coupled device (HJ-CCD) has the advantages of wide field, high temporal resolution, and short repeat cycle. However, this instrument suffers from its use of only four relatively low-quality bands which can't adequately resolve the features of long wavelengths. The Landsat Enhanced Thematic Mapper-plus (ETM+) provides high-quality data, however, the Scan Line Corrector (SLC) stopped working and caused striping of remote sensed images, which dramatically reduced the coverage of the ETM+ data. In order to combine the advantages of the HJ-CCD and Landsat ETM+ data, we adopted a back-propagation artificial neural network (BP-ANN) to fuse these two data types for this study. The results showed that the fused output data not only have the advantage of data intactness for the HJ-CCD, but also have the advantages of the multi-spectral and high radiometric resolution of the ETM+ data. Moreover, the fused data were analyzed qualitatively, quantitatively and from a practical application point of view. Experimental studies indicated that the fused data have a full spatial distribution, multi-spectral bands, high radiometric resolution, a small difference between the observed and fused output data, and a high correlation between the observed and fused data. The excellent performance in its practical application is a further demonstration that the fused data are of high quality.

Effects of ice crystal surface roughness and air bubble inclusions on cirrus cloud radiative properties from remote sensing perspective

NASA Astrophysics Data System (ADS)

Tang, Guanglin; Panetta, R. Lee; Yang, Ping; Kattawar, George W.; Zhai, Peng-Wang

2017-07-01

We study the combined effects of surface roughness and inhomogeneity on the optical scattering properties of ice crystals and explore the consequent implications to remote sensing of cirrus cloud properties. Specifically, surface roughness and inhomogeneity are added to the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 (MC6) cirrus cloud particle habit model. Light scattering properties of the new habit model are simulated using a modified version of the Improved Geometric Optics Method (IGOM). Both inhomogeneity and surface roughness affect the single scattering properties significantly. In visible bands, inhomogeneity and surface roughness both tend to smooth the phase function and eliminate halos and the backscattering peak. The asymmetry parameter varies with the degree of surface roughness following a U shape - decreases and then increases - with a minimum at around 0.15, whereas it decreases monotonically with the air bubble volume fraction. Air bubble inclusions significantly increase phase matrix element -P12 for scattering angles between 20°-120°, whereas surface roughness has a much weaker effect, increasing -P12 slightly from 60°-120°. Radiative transfer simulations and cirrus cloud property retrievals are conducted by including both the factors. In terms of surface roughness and air bubble volume fraction, retrievals of cirrus cloud optical thickness or the asymmetry parameter using solar bands show similar patterns of variation. Polarimetric simulations using the MC6 cirrus cloud particle habit model are shown to be more consistent with observations when both surface roughness and inhomogeneity are simultaneously considered.

Ground-based imaging spectrometry of canopy phenology and chemistry in a deciduous forest

NASA Astrophysics Data System (ADS)

Toomey, M. P.; Friedl, M. A.; Frolking, S. E.; Hilker, T.; O'Keefe, J.; Richardson, A. D.

2013-12-01

Phenology, annual life cycles of plants and animals, is a dynamic ecosystem attribute and an important feedback to climate change. Vegetation phenology is commonly monitored at canopy to continental scales using ground based digital repeat photography and satellite remote sensing, respectively. Existing systems which provide sufficient temporal resolution for phenological monitoring, however, lack the spectral resolution necessary to investigate the coupling of phenology with canopy chemistry (e.g. chlorophyll, nitrogen, lignin-cellulose content). Some researchers have used narrowband (<10 nm resolution) spectrometers at phenology monitoring sites, yielding new insights into seasonal changes in leaf biochemistry. Such instruments integrate the spectral characteristics of the entire canopy, however, masking considerable variability between species and plant functional types. There is an opportunity, then, for exploring the potential of imaging spectrometers to investigate the coupling of canopy phenology and the leaf biochemistry of individual trees. During the growing season of April-October 2013 we deployed an imaging spectrometer with a spectral range of 371-1042 nm and resolution of ~5 nm (Surface Optics Corporation 710; San Diego, CA) on a 35 m tall tower at the Harvard Forest, Massachusetts. The image resolution was ~0.25 megapixels and the field of view encompassed approximately 20 individual tree crowns at a distance of 20-40 m. The instrument was focused on a mixed hardwoods canopy composed of 4 deciduous tree species and one coniferous tree species. Scanning was performed daily with an acquisition frequency of 30 minutes during daylight hours. Derived imagery were used to calculate a suite of published spectral indices used to estimate foliar content of key pigments: cholorophyll, carotenoids and anthocyanins. Additionally, we calculated the photochemical reflectance index (PRI) as well as the position and slope of the red edge as indicators of mid- to late-summer plant stress. Changes in the spectral shape and indices throughout the growing season revealed coupling of leaf biochemistry and phenology, as visually observed in situ. Further, the spectrally rich imagery provided well calibrated reflectance data to simulate vegetation index time series of common spaceborne remote sensing platforms such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat. Comparisons between the simulated time series and in situ phenology observations yielded an enhanced interpretation of vegetation indices for determining phenological transition dates. This study demonstrates an advance in our ability to relate canopy phenology to leaf-level dynamics and demonstrates the role that ground-based imaging spectrometry can play in advancing spaceborne remote sensing of vegetation phenology.

Vectorial point spread function and optical transfer function in oblique plane imaging.

PubMed

Kim, Jeongmin; Li, Tongcang; Wang, Yuan; Zhang, Xiang

2014-05-05

Oblique plane imaging, using remote focusing with a tilted mirror, enables direct two-dimensional (2D) imaging of any inclined plane of interest in three-dimensional (3D) specimens. It can image real-time dynamics of a living sample that changes rapidly or evolves its structure along arbitrary orientations. It also allows direct observations of any tilted target plane in an object of which orientational information is inaccessible during sample preparation. In this work, we study the optical resolution of this innovative wide-field imaging method. Using the vectorial diffraction theory, we formulate the vectorial point spread function (PSF) of direct oblique plane imaging. The anisotropic lateral resolving power caused by light clipping from the tilted mirror is theoretically analyzed for all oblique angles. We show that the 2D PSF in oblique plane imaging is conceptually different from the inclined 2D slice of the 3D PSF in conventional lateral imaging. Vectorial optical transfer function (OTF) of oblique plane imaging is also calculated by the fast Fourier transform (FFT) method to study effects of oblique angles on frequency responses.

What is the value of biomass remote sensing data for blue carbon inventories?

NASA Astrophysics Data System (ADS)

Byrd, K. B.; Simard, M.; Crooks, S.; Windham-Myers, L.

2015-12-01

The U.S. is testing approaches for accounting for carbon emissions and removals associated with wetland management according to 2013 IPCC Wetlands Supplement guidelines. Quality of reporting is measured from low (Tier 1) to high (Tier 3) depending upon data availability and analytical capacity. The use of satellite remote sensing data to derive carbon stocks and flux provides a practical approach for moving beyond IPCC Tier 1, the global default factor approach, to support Tier 2 or Tier 3 quantification of carbon emissions or removals. We are determining the "price of precision," or the extent to which improved satellite data will continue to increase the accuracy of "blue carbon" accounting. Tidal marsh biomass values are needed to quantify aboveground carbon stocks and stock changes, and to run process-based models of carbon accumulation. Maps of tidal marsh biomass have been produced from high resolution commercial and moderate resolution Landsat satellite data with relatively low error [percent normalized RMSE (%RMSE) from 7 to 14%]. Recently for a brackish marsh in Suisun Bay, California, we used Landsat 8 data to produce a biomass map that applied the Wide Dynamic Range Vegetation Index (WDRVI) (ρNIR*0.2 - ρR)/(ρNIR*0.2+ρR) to fully vegetated pixels and the Simple Ratio index (ρRed/ρGreen) to pixels with a mix of vegetation and water. Overall RMSE was 208 g/m2, while %RMSE = 13.7%. Also, preliminary use of airborne and spaceborne RADAR data in coastal Louisiana produced a marsh biomass map with 30% error. The integration of RADAR and LiDAR with optical remote sensing data has the potential to further reduce error in biomass estimation. In 2017, nations will report back to the U.N. Framework Convention on Climate Change on their experience in applying the Wetlands Supplement guidelines. These remote sensing efforts will mark an important step toward quantifying human impacts to wetlands within the global carbon cycle.

The ChemCam Instrument Suite on the Mars Science Laboratory (MSL) Rover: Science Objectives and Mast Unit Description

USGS Publications Warehouse

Maurice, S.; Wiens, R.C.; Saccoccio, M.; Barraclough, B.; Gasnault, O.; Forni, O.; Mangold, N.; Baratoux, D.; Bender, S.; Berger, G.; Bernardin, J.; Berthé, M.; Bridges, N.; Blaney, D.; Bouyé, M.; Caïs, P.; Clark, B.; Clegg, S.; Cousin, A.; Cremers, D.; Cros, A.; DeFlores, L.; Derycke, C.; Dingler, B.; Dromart, G.; Dubois, B.; Dupieux, M.; Durand, E.; d'Uston, L.; Fabre, C.; Faure, B.; Gaboriaud, A.; Gharsa, T.; Herkenhoff, K.; Kan, E.; Kirkland, L.; Kouach, D.; Lacour, J.-L.; Langevin, Y.; Lasue, J.; Le Mouélic, S.; Lescure, M.; Lewin, E.; Limonadi, D.; Manhès, G.; Mauchien, P.; McKay, C.; Meslin, P.-Y.; Michel, Y.; Miller, E.; Newsom, Horton E.; Orttner, G.; Paillet, A.; Parès, L.; Parot, Y.; Pérez, R.; Pinet, P.; Poitrasson, F.; Quertier, B.; Sallé, B.; Sotin, Christophe; Sautter, V.; Séran, H.; Simmonds, J.J.; Sirven, J.-B.; Stiglich, R.; Striebig, N.; Thocaven, J.-J.; Toplis, M.J.; Vaniman, D.

2012-01-01

ChemCam is a remote sensing instrument suite on board the "Curiosity" rover (NASA) that uses Laser-Induced Breakdown Spectroscopy (LIBS) to provide the elemental composition of soils and rocks at the surface of Mars from a distance of 1.3 to 7 m, and a telescopic imager to return high resolution context and micro-images at distances greater than 1.16 m. We describe five analytical capabilities: rock classification, quantitative composition, depth profiling, context imaging, and passive spectroscopy. They serve as a toolbox to address most of the science questions at Gale crater. ChemCam consists of a Mast-Unit (laser, telescope, camera, and electronics) and a Body-Unit (spectrometers, digital processing unit, and optical demultiplexer), which are connected by an optical fiber and an electrical interface. We then report on the development, integration, and testing of the Mast-Unit, and summarize some key characteristics of ChemCam. This confirmed that nominal or better than nominal performances were achieved for critical parameters, in particular power density (>1 GW/cm2). The analysis spot diameter varies from 350 μm at 2 m to 550 μm at 7 m distance. For remote imaging, the camera field of view is 20 mrad for 1024×1024 pixels. Field tests demonstrated that the resolution (˜90 μrad) made it possible to identify laser shots on a wide variety of images. This is sufficient for visualizing laser shot pits and textures of rocks and soils. An auto-exposure capability optimizes the dynamical range of the images. Dedicated hardware and software focus the telescope, with precision that is appropriate for the LIBS and imaging depths-of-field. The light emitted by the plasma is collected and sent to the Body-Unit via a 6 m optical fiber. The companion to this paper (Wiens et al. this issue) reports on the development of the Body-Unit, on the analysis of the emitted light, and on the good match between instrument performance and science specifications.

Liquid crystal waveguides: new devices enabled by >1000 waves of optical phase control

NASA Astrophysics Data System (ADS)

Davis, Scott R.; Farca, George; Rommel, Scott D.; Johnson, Seth; Anderson, Michael H.

2010-02-01

A new electro-optic waveguide platform, which provides unprecedented voltage control over optical phase delays (> 2mm), with very low loss (< 0.5 dB/cm) and rapid response time (sub millisecond), will be presented. This technology, developed by Vescent Photonics, is based upon a unique liquid-crystal waveguide geometry, which exploits the tremendous electro-optic response of liquid crystals while circumventing their historic limitations. The waveguide geometry provides nematic relaxation speeds in the 10's of microseconds and LC scattering losses that are reduced by orders of magnitude from bulk transmissive LC optics. The exceedingly large optical phase delays accessible with this technology enable the design and construction of a new class of previously unrealizable photonic devices. Examples include: 2-D analog non-mechanical beamsteerers, chip-scale widely tunable lasers, chip-scale Fourier transform spectrometer (< 5 nm resolution demonstrated), widely tunable micro-ring resonators, tunable lenses, ultra-low power (< 5 microWatts) optical switches, true optical time delay devices for phased array antennas, and many more. All of these devices may benefit from established manufacturing technologies and ultimately may be as inexpensive as a calculator display. Furthermore, this new integrated photonic architecture has applications in a wide array of commercial and defense markets including: remote sensing, micro-LADAR, OCT, FSO, laser illumination, phased array radar, etc. Performance attributes of several example devices and application data will be presented. In particular, we will present a non-mechanical beamsteerer that steers light in both the horizontal and vertical dimensions.

Potential of high resolution satellite imagery, remote weather data and 1D hydraulic modeling to evaluate flood areas in Gonaives, Haiti

NASA Astrophysics Data System (ADS)

Bozza, Andrea; Durand, Arnaud; Allenbach, Bernard; Confortola, Gabriele; Bocchiola, Daniele

2013-04-01

We present a feasibility study to explore potential of high-resolution imagery, coupled with hydraulic flood modeling to predict flooding risks, applied to the case study of Gonaives basins (585 km²), Haiti. We propose a methodology working at different scales, providing accurate results and a faster intervention during extreme flood events. The 'Hispaniola' island, in the Caribbean tropical zone, is often affected by extreme floods events. Floods are caused by tropical springs and hurricanes, and may lead to several damages, including cholera epidemics, as recently occurred, in the wake of the earthquake upon January 12th 2010 (magnitude 7.0). Floods studies based upon hydrological and hydraulic modeling are hampered by almost complete lack of ground data. Thenceforth, and given the noticeable cost involved in the organization of field measurement campaigns, the need for exploitation of remote sensing images data. HEC-RAS 1D modeling is carried out under different scenarios of available Digital Elevation Models. The DEMs are generated using optical remote sensing satellite (WorldView-1) and SRTM, combined with information from an open source database (Open Street Map). We study two recent flood episodes, where flood maps from remote sensing were available. Flood extent and land use have been assessed by way of data from SPOT-5 satellite, after hurricane Jeanne in 2004 and hurricane Hanna in 2008. A semi-distributed, DEM based hydrological model is used to simulate flood flows during the hurricanes. Precipitation input is taken from daily rainfall data derived from TRMM satellite, plus proper downscaling. The hydraulic model is calibrated using floodplain friction as tuning parameters against the observed flooded area. We compare different scenarios of flood simulation, and the predictive power of model calibration. The method provide acceptable results in depicting flooded areas, especially considering the tremendous lack of ground data, and show the potential of remote sensing information in prediction of flood events in this area, for the purpose of risk assessment and land use planning, and possibly for flood forecast during extreme events.

Focal plane AIT sequence: evolution from HRG-Spot 5 to Pleiades HR

NASA Astrophysics Data System (ADS)

Le Goff, Roland; Pranyies, Pascal; Toubhans, Isabelle

2017-11-01

Optical and geometrical image qualities of Focal Planes, for "push-broom" high resolution remote sensing satellites, require the implementation of specific means and methods for the AIT sequence. Indeed the geometric performances of the focal plane mainly axial focusing and transverse registration, are duly obtained on the basis of adjustment, setting and measurement of optical and CCD components with an accuracy of a few microns. Since the end of the 1970s, EADS-SODERN has developed a series of detection units for earth observation instruments like SPOT and Helios. And EADS-SODERN is now responsible for the development of the Pleiades High Resolution Focal Plane assembly. This paper presents the AIT sequences. We introduce all the efforts, innovative solutions and improvements made on the assembly facilities to match the technical evolutions and breakthrough of the Pleiades HR FP concept in comparison with the previous High Resolution Geometric SPOT 5 Focal Plane. The main evolution drivers are the implementation of strip filters and the realization of 400 mm continuous retinas. For Pleiades HR AIT sequence, three specific integration and measuring benches, corresponding with the different assembly stages, are used: a 3-D non-contact measurement machine for the assembly of detection module, a 3-D measurement machine for mirror integration on the main Focal Plane SiC structure, and a 3-D geometric coordinates control bench to focus detection module lines and to ensure they are well registered together.

High-resolution all-optical photoacoustic imaging system for remote interrogation of biological specimens

NASA Astrophysics Data System (ADS)

Sampathkumar, Ashwin

2014-05-01

Conventional photoacoustic imaging (PAI) employs light pulses to produce a photoacoustic (PA) effect and detects the resulting acoustic waves using an ultrasound transducer acoustically coupled to the target tissue. The resolution of conventional PAI is limited by the sensitivity and bandwidth of the ultrasound transducer. We have developed an all-optical versatile PAI system for characterizing ex vivo and in vivo biological specimens. The system employs noncontact interferometric detection of the acoustic signals that overcomes limitations of conventional PAI. A 532-nm pump laser with a pulse duration of 5 ns excited the PA effect in tissue. Resulting acoustic waves produced surface displacements that were sensed using a 532-nm continuous-wave (CW) probe laser in a Michelson interferometer with a GHz bandwidth. The pump and probe beams were coaxially focused using a 50X objective giving a diffraction-limited spot size of 0.48 μm. The phase-encoded probe beam was demodulated using a homodyne interferometer. The detected time-domain signal was time reversed using k-space wave-propagation methods to produce a spatial distribution of PA sources in the target tissue. Performance was assessed using PA images of ex vivo rabbit lymph node specimens and human tooth samples. A minimum peak surface displacement sensitivity of 0.19 pm was measured. The all-optical PAI (AOPAI) system is well suited for assessment of retinal diseases, caries lesion detection, skin burns, section less histology and pressure or friction ulcers.

Improving crop condition monitoring at field scale by using optimal Landsat and MODIS images

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing data at coarse resolution (kilometers) have been widely used in monitoring crop condition for decades. However, crop condition monitoring at field scale requires high resolution data in both time and space. Although a large number of remote sensing instruments with different...

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.

SIMULATION STUDY FOR GASEOUS FLUXES FROM AN AREA SOURCE USING COMPUTED TOMOGRAPHY AND OPTICAL REMOTE SENSING

EPA Science Inventory

The paper presents a new approach to quantifying emissions from fugitive gaseous air pollution sources. Computed tomography (CT) and path-integrated optical remote sensing (PI-ORS) concentration data are combined in a new field beam geometry. Path-integrated concentrations are ...

Remote-controlled optics experiment for supporting senior high school and undergraduate teaching

NASA Astrophysics Data System (ADS)

Choy, S. H.; Jim, K. L.; Mak, C. L.; Leung, C. W.

2017-08-01

This paper reports the development of a remote laboratory (RemoteLab) platform for practising technologyenhanced learning of optics. The development of RemoteLab enhances students' understanding of experimental methodologies and outcomes, and enable students to conduct experiments everywhere at all times. While the initial goal of the system was for physics major undergradutes, the sytem was also made available for senior secondary school students. To gauge the impact of the RemoteLab, we evaluated two groups of students, which included 109 physics 1st-year undergraduates and 11 students from a local secondary school. After the experiments, evaluation including questionnaire survey and interviews were conducted to collect data on students' perceptions on RemoteLab and implementation issues related to the platform. The surveys focused on four main topics, including user interface, experiment setup, booking system and learning process. The survey results indicated that most of the participants' views towards RemoteLab was positive.

Design of a novel passive flexure-based mechanism for microelectromechanical system optical switch assembly

NASA Astrophysics Data System (ADS)

Zhang, Jianbin; Sun, Xiantao; Chen, Weihai; Chen, Wenjie; Jiang, Lusha

2014-12-01

In microelectromechanical system (MEMS) optical switch assembly, the collision always exists between the optical fiber and the edges of the U-groove due to the positioning errors between them. It will cause the irreparable damage since the optical fiber and the silicon-made U-groove are usually very fragile. Typical solution is first to detect the positioning errors by the machine vision or high-resolution sensors and then to actively eliminate them with the aid of the motion of precision mechanisms. However, this method will increase the cost and complexity of the system. In this paper, we present a passive compensation method to accommodate the positioning errors. First, we study the insertion process of the optical fiber into the U-groove to analyze all possible positioning errors as well as the conditions of successful insertion. Then, a novel passive flexure-based mechanism based on the remote center of compliance concept is designed to satisfy the required insertion condition. The pseudo-rigid-body-model method is utilized to calculate the stiffness of the mechanism along the different directions, which is verified by finite element analysis (FEA). Finally, a prototype of the passive flexure-based mechanism is fabricated for performance tests. Both FEA and experimental results indicate that the designed mechanism can be used to the MEMS optical switch assembly.

Design of a novel passive flexure-based mechanism for microelectromechanical system optical switch assembly.

PubMed

Zhang, Jianbin; Sun, Xiantao; Chen, Weihai; Chen, Wenjie; Jiang, Lusha

2014-12-01

In microelectromechanical system (MEMS) optical switch assembly, the collision always exists between the optical fiber and the edges of the U-groove due to the positioning errors between them. It will cause the irreparable damage since the optical fiber and the silicon-made U-groove are usually very fragile. Typical solution is first to detect the positioning errors by the machine vision or high-resolution sensors and then to actively eliminate them with the aid of the motion of precision mechanisms. However, this method will increase the cost and complexity of the system. In this paper, we present a passive compensation method to accommodate the positioning errors. First, we study the insertion process of the optical fiber into the U-groove to analyze all possible positioning errors as well as the conditions of successful insertion. Then, a novel passive flexure-based mechanism based on the remote center of compliance concept is designed to satisfy the required insertion condition. The pseudo-rigid-body-model method is utilized to calculate the stiffness of the mechanism along the different directions, which is verified by finite element analysis (FEA). Finally, a prototype of the passive flexure-based mechanism is fabricated for performance tests. Both FEA and experimental results indicate that the designed mechanism can be used to the MEMS optical switch assembly.

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.

Curved CCD detector devices and arrays for multispectral astrophysical applications and terrestrial stereo panoramic cameras

NASA Astrophysics Data System (ADS)

Swain, Pradyumna; Mark, David

2004-09-01

The emergence of curved CCD detectors as individual devices or as contoured mosaics assembled to match the curved focal planes of astronomical telescopes and terrestrial stereo panoramic cameras represents a major optical design advancement that greatly enhances the scientific potential of such instruments. In altering the primary detection surface within the telescope"s optical instrumentation system from flat to curved, and conforming the applied CCD"s shape precisely to the contour of the telescope"s curved focal plane, a major increase in the amount of transmittable light at various wavelengths through the system is achieved. This in turn enables multi-spectral ultra-sensitive imaging with much greater spatial resolution necessary for large and very large telescope applications, including those involving infrared image acquisition and spectroscopy, conducted over very wide fields of view. For earth-based and space-borne optical telescopes, the advent of curved CCD"s as the principle detectors provides a simplification of the telescope"s adjoining optics, reducing the number of optical elements and the occurrence of optical aberrations associated with large corrective optics used to conform to flat detectors. New astronomical experiments may be devised in the presence of curved CCD applications, in conjunction with large format cameras and curved mosaics, including three dimensional imaging spectroscopy conducted over multiple wavelengths simultaneously, wide field real-time stereoscopic tracking of remote objects within the solar system at high resolution, and deep field survey mapping of distant objects such as galaxies with much greater multi-band spatial precision over larger sky regions. Terrestrial stereo panoramic cameras equipped with arrays of curved CCD"s joined with associative wide field optics will require less optical glass and no mechanically moving parts to maintain continuous proper stereo convergence over wider perspective viewing fields than their flat CCD counterparts, lightening the cameras and enabling faster scanning and 3D integration of objects moving within a planetary terrain environment. Preliminary experiments conducted at the Sarnoff Corporation indicate the feasibility of curved CCD imagers with acceptable electro-optic integrity. Currently, we are in the process of evaluating the electro-optic performance of a curved wafer scale CCD imager. Detailed ray trace modeling and experimental electro-optical data performance obtained from the curved imager will be presented at the conference.

Development of a generalized multi-pixel and multi-parameter satellite remote sensing algorithm for aerosol properties

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Nakajima, T.; Takenaka, H.; Higurashi, A.

2013-12-01

We develop a new satellite remote sensing algorithm to retrieve the properties of aerosol particles in the atmosphere. In late years, high resolution and multi-wavelength, and multiple-angle observation data have been obtained by grand-based spectral radiometers and imaging sensors on board the satellite. With this development, optimized multi-parameter remote sensing methods based on the Bayesian theory have become popularly used (Turchin and Nozik, 1969; Rodgers, 2000; Dubovik et al., 2000). Additionally, a direct use of radiation transfer calculation has been employed for non-linear remote sensing problems taking place of look up table methods supported by the progress of computing technology (Dubovik et al., 2011; Yoshida et al., 2011). We are developing a flexible multi-pixel and multi-parameter remote sensing algorithm for aerosol optical properties. In this algorithm, the inversion method is a combination of the MAP method (Maximum a posteriori method, Rodgers, 2000) and the Phillips-Twomey method (Phillips, 1962; Twomey, 1963) as a smoothing constraint for the state vector. Furthermore, we include a radiation transfer calculation code, Rstar (Nakajima and Tanaka, 1986, 1988), numerically solved each time in iteration for solution search. The Rstar-code has been directly used in the AERONET operational processing system (Dubovik and King, 2000). Retrieved parameters in our algorithm are aerosol optical properties, such as aerosol optical thickness (AOT) of fine mode, sea salt, and dust particles, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength. We simultaneously retrieve all the parameters that characterize pixels in each of horizontal sub-domains consisting the target area. Then we successively apply the retrieval method to all the sub-domains in the target area. We conducted numerical tests for the retrieval of aerosol properties and ground surface albedo for GOSAT/CAI imager data to test the algorithm for the land area. In this test, we simulated satellite-observed radiances for a sub-domain consisting of 5 by 5 pixels by the Rstar code assuming wavelengths of 380, 674, 870 and 1600 [nm], atmospheric condition of the US standard atmosphere, and the several aerosol and ground surface conditions. The result of the experiment showed that AOTs of fine mode and dust particles, soot fraction and ground surface albedo at the wavelength of 674 [nm] are retrieved within absolute value differences of 0.04, 0.01, 0.06 and 0.006 from the true value, respectively, for the case of dark surface, and also, for the case of blight surface, 0.06, 0.03, 0.04 and 0.10 from the true value, respectively. We will conduct more tests to study the information contents of parameters needed for aerosol and land surface remote sensing with different boundary conditions among sub-domains.

Mini-lidar sensor for the remote stand-off sensing of chemical/biological substances and method for sensing same

DOEpatents

Ray, Mark D.; Sedlacek, Arthur J.

2003-08-19

A method and apparatus for remote, stand-off, and high efficiency spectroscopic detection of biological and chemical substances. The apparatus including an optical beam transmitter which transmits a beam having an axis of transmission to a target, the beam comprising at least a laser emission. An optical detector having an optical detection path to the target is provided for gathering optical information. The optical detection path has an axis of optical detection. A beam alignment device fixes the transmitter proximal to the detector and directs the beam to the target along the optical detection path such that the axis of transmission is within the optical detection path. Optical information gathered by the optical detector is analyzed by an analyzer which is operatively connected to the detector.

Smoke over haze: Comparative analysis of satellite, surface radiometer, and airborne in situ measurements of aerosol optical properties and radiative forcing over the eastern United States

NASA Astrophysics Data System (ADS)

Vant-Hull, Brian; Li, Zhanqing; Taubman, Brett F.; Levy, Robert; Marufu, Lackson; Chang, Fu-Lung; Doddridge, Bruce G.; Dickerson, Russell R.

2005-05-01

In July 2002 Canadian forest fires produced a major smoke episode that blanketed the east coast of the United States. Properties of the smoke aerosol were measured in situ from aircraft, complementing operational Aerosol Robotic Network (AERONET), and Moderate Resolution Imaging Spectroradiometer (MODIS) remotely sensed aerosol retrievals. This study compares single scattering albedo and phase function derived from the in situ measurements and AERONET retrievals in order to evaluate their consistency for application to satellite retrievals of optical depth and radiative forcing. These optical properties were combined with MODIS reflectance observations to calculate optical depth. The use of AERONET optical properties yielded optical depths 2-16% lower than those directly measured by AERONET. The use of in situ-derived optical properties resulted in optical depths 22-43% higher than AERONET measurements. These higher optical depths are attributed primarily to the higher absorption measured in situ, which is roughly twice that retrieved by AERONET. The resulting satellite retrieved optical depths were in turn used to calculate integrated radiative forcing at both the surface and top of atmosphere. Comparisons to surface (Surface Radiation Budget Network (SURFRAD) and ISIS) and to satellite (Clouds and Earth Radiant Energy System CERES) broadband radiometer measurements demonstrate that the use of optical properties derived from the aircraft measurements provided a better broadband forcing estimate (21% error) than those derived from AERONET (33% error). Thus AERONET-derived optical properties produced better fits to optical depth measurements, while in situ properties resulted in better fits to forcing measurements. These apparent inconsistencies underline the significant challenges facing the aerosol community in achieving column closure between narrow and broadband measurements and calculations.

Wide-area remote-sensing system of pollution and gas dispersal by near-infrared absorption based on low-loss optical fiber network

NASA Technical Reports Server (NTRS)

Inaba, H.

1986-01-01

An all optical remote sensing system utilizing long distance, ultralow loss optical fiber networks is studied and discussed for near infrared absorption measurements of combustible and/or explosive gases such as CH4 and C3H8 in our environment, including experimental results achieved in a diameter more than 20 km. The use of a near infrared wavelength range is emphasized.

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation.

PubMed

Qin, Changbo; Jia, Yangwen; Su, Z; Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-07-29

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems.

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

PubMed Central

Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-01-01

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946

Comparative evaluation of polarimetric and bi-spectral cloud microphysics retrievals: Retrieval closure experiments and comparisons based on idealized and LES case studies

NASA Astrophysics Data System (ADS)

Miller, D. J.; Zhang, Z.; Ackerman, A. S.; Platnick, S. E.; Cornet, C.

2016-12-01

A remote sensing cloud retrieval simulator, created by coupling an LES cloud model with vector radiative transfer (RT) models is the ideal framework for assessing cloud remote sensing techniques. This simulator serves as a tool for understanding bi-spectral and polarimetric retrievals by comparing them directly to LES cloud properties (retrieval closure comparison) and for comparing the retrieval techniques to one another. Our simulator utilizes the DHARMA LES [Ackerman et al., 2004] with cloud properties based on marine boundary layer (MBL) clouds observed during the DYCOMS-II and ATEX field campaigns. The cloud reflectances are produced by the vectorized RT models based on polarized doubling adding and monte carlo techniques (PDA, MCPOL). Retrievals are performed utilizing techniques as similar as possible to those implemented on their corresponding well known instruments; polarimetric retrievals are based on techniques implemented for polarimeters (POLDER, AirMSPI, and RSP) and bi-spectral retrievals are performed using the Nakajima-King LUT method utilized on a number of spectral instruments (MODIS and VIIRS). Retrieval comparisons focus on cloud droplet effective radius (re), effective variance (ve), and cloud optical thickness (τ). This work explores the sensitivities of these two retrieval techniques to various observation limitations, such as spatial resolution/cloud inhomogeneity, impact of 3D radiative effects, and angular resolution requirements. With future remote sensing missions like NASA's Aerosols/Clouds/Ecosystems (ACE) planning to feature advanced polarimetric instruments it is important to understand how these retrieval techniques compare to one another. The cloud retrieval simulator we've developed allows us to probe these important questions in a realistically relevant test bed.

Fire Impacts on Mixed Pine-oak Forests Assessed with High Spatial Resolution Imagery, Imaging Spectroscopy, and LiDAR

NASA Astrophysics Data System (ADS)

Meng, R.; Wu, J.; Zhao, F. R.; Kathy, S. L.; Dennison, P. E.; Cook, B.; Hanavan, R. P.; Serbin, S.

2016-12-01

As a primary disturbance agent, fire significantly influences forest ecosystems, including the modification or resetting of vegetation composition and structure, which can then significantly impact landscape-scale plant function and carbon stocks. Most ecological processes associated with fire effects (e.g. tree damage, mortality, and vegetation recovery) display fine-scale, species specific responses but can also vary spatially within the boundary of the perturbation. For example, both oak and pine species are fire-adapted, but fire can still induce changes in composition, structure, and dominance in a mixed pine-oak forest, mainly because of their varying degrees of fire adaption. Evidence of post-fire shifts in dominance between oak and pine species has been documented in mixed pine-oak forests, but these processes have been poorly investigated in a spatially explicit manner. In addition, traditional field-based means of quantifying the response of partially damaged trees across space and time is logistically challenging. Here we show how combining high resolution satellite imagery (i.e. Worldview-2,WV-2) and airborne imaging spectroscopy and LiDAR (i.e. NASA Goddard's Lidar, Hyperspectral and Thermal airborne imager, G-LiHT) can be effectively used to remotely quantify spatial and temporal patterns of vegetation recovery following a top-killing fire that occurred in 2012 within mixed pine-oak forests in the Long Island Central Pine Barrens Region, New York. We explore the following questions: 1) what are the impacts of fire on species composition, dominance, plant health, and vertical structure; 2) what are the recovery trajectories of forest biomass, structure, and spectral properties for three years following the fire; and 3) to what extent can fire impacts be captured and characterized by multi-sensor remote sensing techniques from active and passive optical remote sensing.

Lidar detection of carbon dioxide in volcanic plumes

NASA Astrophysics Data System (ADS)

Fiorani, Luca; Santoro, Simone; Parracino, Stefano; Maio, Giovanni; Del Franco, Mario; Aiuppa, Alessandro

2015-06-01

Volcanic gases give information on magmatic processes. In particular, anomalous releases of carbon dioxide precede volcanic eruptions. Up to now, this gas has been measured in volcanic plumes with conventional measurements that imply the severe risks of local sampling and can last many hours. For these reasons and for the great advantages of laser sensing, the thorough development of volcanic lidar has been undertaken at the Diagnostics and Metrology Laboratory (UTAPRAD-DIM) of the Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA). In fact, lidar profiling allows one to scan remotely volcanic plumes in a fast and continuous way, and with high spatial and temporal resolution. Two differential absorption lidar instruments will be presented in this paper: BILLI (BrIdge voLcanic LIdar), based on injection seeded Nd:YAG laser, double grating dye laser, difference frequency mixing (DFM) and optical parametric amplifier (OPA), and VULLI (VULcamed Lidar), based on injection seeded Nd:YAG laser and optical parametric oscillator (OPO). The first one is funded by the ERC (European Research Council) project BRIDGE and the second one by the ERDF (European Regional Development Fund) project VULCAMED. While VULLI has not yet been tested in a volcanic site, BILLI scanned the gas emitted by Pozzuoli Solfatara (Campi Flegrei volcanic area, Naples, Italy) during a field campaign carried out from 13 to 17 October 2014. Carbon dioxide concentration maps were retrieved remotely in few minutes in the crater area. Lidar measurements were in good agreement with well-established techniques, based on different operating principles. To our knowledge, it is the first time that carbon dioxide in a volcanic plume is retrieved by lidar, representing the first direct measurement of this kind ever performed on an active volcano and showing the high potential of laser remote sensing in geophysical research.

Chlorophyll-a Estimation Around the Antarctica Peninsula Using Satellite Algorithms: Hints from Field Water Leaving Reflectance

PubMed Central

Zeng, Chen; Xu, Huiping; Fischer, Andrew M.

2016-01-01

Ocean color remote sensing significantly contributes to our understanding of phytoplankton distribution and abundance and primary productivity in the Southern Ocean (SO). However, the current SO in situ optical database is still insufficient and unevenly distributed. This limits the ability to produce robust and accurate measurements of satellite-based chlorophyll. Based on data collected on cruises around the Antarctica Peninsula (AP) on January 2014 and 2016, this research intends to enhance our knowledge of SO water and atmospheric optical characteristics and address satellite algorithm deficiency of ocean color products. We collected high resolution in situ water leaving reflectance (±1 nm band resolution), simultaneous in situ chlorophyll-a concentrations and satellite (MODIS and VIIRS) water leaving reflectance. Field samples show that clouds have a great impact on the visible green bands and are difficult to detect because NASA protocols apply the NIR band as a cloud contamination threshold. When compared to global case I water, water around the AP has lower water leaving reflectance and a narrower blue-green band ratio, which explains chlorophyll-a underestimation in high chlorophyll-a regions and overestimation in low chlorophyll-a regions. VIIRS shows higher spatial coverage and detection accuracy than MODIS. After coefficient improvement, VIIRS is able to predict chlorophyll a with 53% accuracy. PMID:27941596

Chlorophyll-a Estimation Around the Antarctica Peninsula Using Satellite Algorithms: Hints from Field Water Leaving Reflectance.

PubMed

Zeng, Chen; Xu, Huiping; Fischer, Andrew M

2016-12-07

Ocean color remote sensing significantly contributes to our understanding of phytoplankton distribution and abundance and primary productivity in the Southern Ocean (SO). However, the current SO in situ optical database is still insufficient and unevenly distributed. This limits the ability to produce robust and accurate measurements of satellite-based chlorophyll. Based on data collected on cruises around the Antarctica Peninsula (AP) on January 2014 and 2016, this research intends to enhance our knowledge of SO water and atmospheric optical characteristics and address satellite algorithm deficiency of ocean color products. We collected high resolution in situ water leaving reflectance (±1 nm band resolution), simultaneous in situ chlorophyll-a concentrations and satellite (MODIS and VIIRS) water leaving reflectance. Field samples show that clouds have a great impact on the visible green bands and are difficult to detect because NASA protocols apply the NIR band as a cloud contamination threshold. When compared to global case I water, water around the AP has lower water leaving reflectance and a narrower blue-green band ratio, which explains chlorophyll-a underestimation in high chlorophyll-a regions and overestimation in low chlorophyll-a regions. VIIRS shows higher spatial coverage and detection accuracy than MODIS. After coefficient improvement, VIIRS is able to predict chlorophyll a with 53% accuracy.

Malaria Diagnosis Using a Mobile Phone Polarized Microscope

NASA Astrophysics Data System (ADS)

Pirnstill, Casey W.; Coté, Gerard L.

2015-08-01

Malaria remains a major global health burden, and new methods for low-cost, high-sensitivity, diagnosis are essential, particularly in remote areas with low-resource around the world. In this paper, a cost effective, optical cell-phone based transmission polarized light microscope system is presented for imaging the malaria pigment known as hemozoin. It can be difficult to determine the presence of the pigment from background and other artifacts, even for skilled microscopy technicians. The pigment is much easier to observe using polarized light microscopy. However, implementation of polarized light microscopy lacks widespread adoption because the existing commercial devices have complicated designs, require sophisticated maintenance, tend to be bulky, can be expensive, and would require re-training for existing microscopy technicians. To this end, a high fidelity and high optical resolution cell-phone based polarized light microscopy system is presented which is comparable to larger bench-top polarized microscopy systems but at much lower cost and complexity. The detection of malaria in fixed and stained blood smears is presented using both, a conventional polarized microscope and our cell-phone based system. The cell-phone based polarimetric microscopy design shows the potential to have both the resolution and specificity to detect malaria in a low-cost, easy-to-use, modular platform.

Spacecraft Formation Flying: An Overview of Missions and Technologies

NASA Technical Reports Server (NTRS)

Leitner, Jesse

2007-01-01

Over the next two decades a revolution is likely to occur in how remote sensing of Earth, other planets or bodies, and a range of phenomena in the universe is performed from space. In particular, current launch vehicle fairing volume and mass constraints will continue to restrict the size of monolithic telescope apertures which can be launched to accommodate only slightly more performance capability than is achievable today, such as by the Hubble Space Telescope. Systems under formulation today, such as the James Webb Space Telescope, will be able to increase aperture size and, hence, imaging resolution, by deploying segmented optics. However, this approach is limited as well, by our ability to control such segments to optical tolerances over long distances with highly uncertain structural dynamics connecting them. Consequently, for orders of magnitude improved resolution as required for imaging black holes, imaging planets, or performing asteroseismology, the only viable approach will be to fly a collection of spacecraft in formation to synthesize a virtual segmented telescope or interferometer with very large baselines. This presentation highlights some of the strategic science missions planned in the National Aeronautics and Space Administration, and identifies some of the critical technologies needed to enable some of the most challenging space missions ever conceived which have realistic hopes of flying.

Malaria Diagnosis Using a Mobile Phone Polarized Microscope

PubMed Central

Pirnstill, Casey W.; Coté, Gerard L.

2015-01-01

Malaria remains a major global health burden, and new methods for low-cost, high-sensitivity, diagnosis are essential, particularly in remote areas with low-resource around the world. In this paper, a cost effective, optical cell-phone based transmission polarized light microscope system is presented for imaging the malaria pigment known as hemozoin. It can be difficult to determine the presence of the pigment from background and other artifacts, even for skilled microscopy technicians. The pigment is much easier to observe using polarized light microscopy. However, implementation of polarized light microscopy lacks widespread adoption because the existing commercial devices have complicated designs, require sophisticated maintenance, tend to be bulky, can be expensive, and would require re-training for existing microscopy technicians. To this end, a high fidelity and high optical resolution cell-phone based polarized light microscopy system is presented which is comparable to larger bench-top polarized microscopy systems but at much lower cost and complexity. The detection of malaria in fixed and stained blood smears is presented using both, a conventional polarized microscope and our cell-phone based system. The cell-phone based polarimetric microscopy design shows the potential to have both the resolution and specificity to detect malaria in a low-cost, easy-to-use, modular platform. PMID:26303238

Measurement Sets and Sites Commonly Used for High Spatial Resolution Image Product Characterization

NASA Technical Reports Server (NTRS)

Pagnutti, Mary

2006-01-01

Scientists within NASA's Applied Sciences Directorate have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site has enabled the in-flight characterization of satellite high spatial resolution remote sensing system products form Space Imaging IKONOS, Digital Globe QuickBird, and ORBIMAGE OrbView, as well as advanced multispectral airborne digital camera products. SSC utilizes engineered geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment and their Instrument Validation Laboratory to characterize high spatial resolution remote sensing data products. This presentation describes the SSC characterization capabilities and techniques in the visible through near infrared spectrum and examples of calibration results.

Accessing, Utilizing and Visualizing NASA Remote Sensing Data for Malaria Modeling and Surveillance

NASA Technical Reports Server (NTRS)

Kiang, Richard K.; Adimi, Farida; Kempler, Steven

2007-01-01

This poster presentation reviews the use of NASA remote sensing data that can be used to extract environmental information for modeling malaria transmission. The authors discuss the remote sensing data from Landsat, Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), Tropical Rainfall Measuring Mission (TRMM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Earth Observing One (EO-1), Advanced Land Imager (ALI) and Seasonal to Interannual Earth Science Information Partner (SIESIP) dataset.

Remote sensing of ecosystem health: opportunities, challenges, and future perspectives.

PubMed

Li, Zhaoqin; Xu, Dandan; Guo, Xulin

2014-11-07

Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1) scale issue; (2) transportability issue; (3) data availability; and (4) uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges.

In-situ spectrophotometric probe

DOEpatents

Prather, W.S.

1992-12-15

A spectrophotometric probe is described for in situ absorption spectra measurements comprising a first optical fiber carrying light from a remote light source, a second optical fiber carrying light to a remote spectrophotometer, the proximal ends of the first and second optical fibers parallel and co-terminal, a planoconvex lens to collimate light from the first optical fiber, a reflecting grid positioned a short distance from the lens to reflect the collimated light back to the lens for focusing on the second optical fiber. The lens is positioned with the convex side toward the optical fibers. A substrate for absorbing analyte or an analyte and reagent mixture may be positioned between the lens and the reflecting grid. 5 figs.

Sedimentary Environments Mapping in the Yellow Sea Using TanDEM-X and Optic Satellites

NASA Astrophysics Data System (ADS)

Ryu, J. H.; Lee, Y. K.; Kim, S. W.

2017-12-01

Due to land reclamation and dredging, 57% of China's coastal wetlands have disappeared since the 1950s, and the total area of tidal flats in South Korea decreased from approximately 2,800km2 in 1990 to 2392km2 in 2005(Qiu, 2011 and MLTM, 2010). Intertidal DEM and sedimentary facies are useful for understanding intertidal functions and monitoring their response to natural and anthropogenic actions. Highly accurate intertidal DEMs with 5-m resolution were generated based on the TanDEM-X interferometric SAR (InSAR) technique because TanDEM-X allows the acquisition of the coherent InSAR pairs with no time lag or approximately 10-second temporal baseline between master and slave SAR image. We successfully generated intertidal zone DEMs with 5-7-m spatial resolutions and interferometric height accuracies better than 0.15 m for three representative tidal flats on the west coast of the Korean Peninsula and one site of chinese coastal region in the Yellow Sea. Surface sediment classification based on remotely sensed data must circumspectly consider an effective critical grain size, water content, local topography, and intertidal structures. The earlier studies have some limitation that the classification map is not considered to analysis various environmental conditions. Therefore, the purpose of this study was minutely to mapping the surface sedimentary facies by analyzing the tidal channel, topography with multi-sensor remotely sensed data and in-situ data.

UrtheCast Second-Generation Earth Observation Sensors

NASA Astrophysics Data System (ADS)

Beckett, K.

2015-04-01

UrtheCast's Second-Generation state-of-the-art Earth Observation (EO) remote sensing platform will be hosted on the NASA segment of International Space Station (ISS). This platform comprises a high-resolution dual-mode (pushbroom and video) optical camera and a dual-band (X and L) Synthetic Aperture RADAR (SAR) instrument. These new sensors will complement the firstgeneration medium-resolution pushbroom and high-definition video cameras that were mounted on the Russian segment of the ISS in early 2014. The new cameras are expected to be launched to the ISS in late 2017 via the Space Exploration Technologies Corporation Dragon spacecraft. The Canadarm will then be used to install the remote sensing platform onto a CBM (Common Berthing Mechanism) hatch on Node 3, allowing the sensor electronics to be accessible from the inside of the station, thus limiting their exposure to the space environment and allowing for future capability upgrades. The UrtheCast second-generation system will be able to take full advantage of the strengths that each of the individual sensors offers, such that the data exploitation capabilities of the combined sensors is significantly greater than from either sensor alone. This represents a truly novel platform that will lead to significant advances in many other Earth Observation applications such as environmental monitoring, energy and natural resources management, and humanitarian response, with data availability anticipated to begin after commissioning is completed in early 2018.

A Novel Method of Aircraft Detection Based on High-Resolution Panchromatic Optical Remote Sensing Images.

PubMed

Wang, Wensheng; Nie, Ting; Fu, Tianjiao; Ren, Jianyue; Jin, Longxu

2017-05-06

In target detection of optical remote sensing images, two main obstacles for aircraft target detection are how to extract the candidates in complex gray-scale-multi background and how to confirm the targets in case the target shapes are deformed, irregular or asymmetric, such as that caused by natural conditions (low signal-to-noise ratio, illumination condition or swaying photographing) and occlusion by surrounding objects (boarding bridge, equipment). To solve these issues, an improved active contours algorithm, namely region-scalable fitting energy based threshold (TRSF), and a corner-convex hull based segmentation algorithm (CCHS) are proposed in this paper. Firstly, the maximal variance between-cluster algorithm (Otsu's algorithm) and region-scalable fitting energy (RSF) algorithm are combined to solve the difficulty of targets extraction in complex and gray-scale-multi backgrounds. Secondly, based on inherent shapes and prominent corners, aircrafts are divided into five fragments by utilizing convex hulls and Harris corner points. Furthermore, a series of new structure features, which describe the proportion of targets part in the fragment to the whole fragment and the proportion of fragment to the whole hull, are identified to judge whether the targets are true or not. Experimental results show that TRSF algorithm could improve extraction accuracy in complex background, and that it is faster than some traditional active contours algorithms. The CCHS is effective to suppress the detection difficulties caused by the irregular shape.

Compact liquid crystal waveguide Fourier transform spectrometer for real-time gas sensing in NIR spectral band

NASA Astrophysics Data System (ADS)

Chao, Tien-Hsin; Lu, Thomas T.; Davis, Scott R.; Rommel, Scott D.; Farca, George; Luey, Ben; Martin, Alan; Anderson, Michael H.

2012-04-01

Jet Propulsion Lab and Vescent Photonics Inc. and are jointly developing an innovative ultra-compact (volume < 10 cm3), ultra-low power (<10 -3 Watt-hours per measurement and zero power consumption when not measuring), completely non-mechanical Liquid Crystal Waveguide Fourier Transform Spectrometer (LCWFTS) that will be suitable for a variety of remote-platform, in-situ measurements. These devices are made possible by novel electro-evanescent waveguide architecture, enabling "monolithic chip-scale" Electro Optic-FTS (EO-FTS) sensors. The potential performance of these EO-FTS sensors include: i) a spectral range throughout 0.4-5 μm (25000 - 2000 cm-1), ii) highresolution (Δλ<= 0.1 nm), iii) high-speed (< 1 ms) measurements, and iv) rugged integrated optical construction. This performance potential enables the detection and quantification of a large number of different atmospheric gases simultaneously in the same air mass and the rugged construction will enable deployment on previously inaccessible platforms. The sensor construction is also amenable for analyzing aqueous samples on remote floating or submerged platforms. We have reported [1] a proof-of-principle prototype LCWFTS sensor that has been demonstrated in the near- IR (range of 1450-1600 nm) with a 5 nm resolution. In this paper, we will report the recently built and tested LCWFTS test bed and the demonstration of a real-time gas sensing applications.

A method for the evaluation of image quality according to the recognition effectiveness of objects in the optical remote sensing image using machine learning algorithm.

PubMed

Yuan, Tao; Zheng, Xinqi; Hu, Xuan; Zhou, Wei; Wang, Wei

2014-01-01

Objective and effective image quality assessment (IQA) is directly related to the application of optical remote sensing images (ORSI). In this study, a new IQA method of standardizing the target object recognition rate (ORR) is presented to reflect quality. First, several quality degradation treatments with high-resolution ORSIs are implemented to model the ORSIs obtained in different imaging conditions; then, a machine learning algorithm is adopted for recognition experiments on a chosen target object to obtain ORRs; finally, a comparison with commonly used IQA indicators was performed to reveal their applicability and limitations. The results showed that the ORR of the original ORSI was calculated to be up to 81.95%, whereas the ORR ratios of the quality-degraded images to the original images were 65.52%, 64.58%, 71.21%, and 73.11%. The results show that these data can more accurately reflect the advantages and disadvantages of different images in object identification and information extraction when compared with conventional digital image assessment indexes. By recognizing the difference in image quality from the application effect perspective, using a machine learning algorithm to extract regional gray scale features of typical objects in the image for analysis, and quantitatively assessing quality of ORSI according to the difference, this method provides a new approach for objective ORSI assessment.

Remote Marine Aerosol: A Characterization of Physical, Chemical and Optical Properties and their Relation to Radiative Transfer in the Troposphere

NASA Technical Reports Server (NTRS)

Clarke, Antony D.; Porter, John N.

1997-01-01

Our research effort is focused on improving our understanding of aerosol properties needed for optical models for remote marine regions. This includes in-situ and vertical column optical closure and involves a redundancy of approaches to measure and model optical properties that must be self consistent. The model is based upon measured in-situ aerosol properties and will be tested and constrained by the vertically measured spectral differential optical depth of the marine boundary layer, MBL. Both measured and modeled column optical properties for the boundary layer, when added to the free-troposphere and stratospheric optical depth, will be used to establish spectral optical depth over the entire atmospheric column for comparison to and validation of satellite derived radiances (AVHRR).

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.

Occurrence of weak, sub-micron, tropospheric aerosol events at high Arctic latitudes

NASA Astrophysics Data System (ADS)

O'Neill, N. T.; Pancrati, O.; Baibakov, K.; Eloranta, E.; Batchelor, R. L.; Freemantle, J.; McArthur, L. J. B.; Strong, K.; Lindenmaier, R.

2008-07-01

Numerous fine mode (sub-micron) aerosol optical events were observed during the summer of 2007 at the High Arctic atmospheric observatory (PEARL) located at Eureka, Nunavut, Canada. Half of these events could be traced to forest fires in southern and eastern Russia and the Northwest Territories of Canada. The most notable findings were that (a) a combination of ground-based measurements (passive sunphotometry, high spectral resolution lidar) could be employed to determine that weak (near sub-visual) fine mode events had occurred, and (b) this data combined with remote sensing imagery products (MODIS, OMI-AI, FLAMBE fire sources), Fourier transform spectroscopy and back trajectories could be employed to identify the smoke events.

The remote measurement of tornado-like flows employing a scanning laser Doppler system

NASA Technical Reports Server (NTRS)

Jeffreys, H. B.; Bilbro, J. W.; Dimarzio, C.; Sonnenschein, C.; Toomey, D.

1977-01-01

The paper deals with a scanning laser Doppler velocimeter system employed in a test program for measuring naturally occurring tornado-like phenomena, known as dust devils. A description of the system and the test program is followed by a discussion of the data processing techniques and data analysis. The system uses a stable 15-W CO2 laser with the beam expanded and focused by a 12-inch telescope. Range resolution is obtained by focusing the optical system. The velocity of each volume of air (scanned in a horizontal plane) is determined from spectral analysis of the heterodyne signal. Results derived from the measurement program and data/system analyses are examined.

Some emerging applications of lasers

NASA Astrophysics Data System (ADS)

Christensen, C. P.

1982-10-01

Applications of lasers in photochemistry, advanced instrumentation, and information storage are discussed. Laser microchemistry offers a number of new methods for altering the morphology of a solid surface with high spatial resolution. Recent experiments in material deposition, material removal, and alloying and doping are reviewed. A basic optical disk storage system is described and the problems faced by this application are discussed, in particular those pertaining to recording media. An advanced erasable system based on the magnetooptic effect is described. Applications of lasers for remote sensing are discussed, including various lidar systems, the use of laser-induced fluorescence for oil spill characterization and uranium exploration, and the use of differential absorption for detection of atmospheric constituents, temperature, and humidity.