WorldWideScience

Sample records for remotely sensed cloud

  1. OpenRS-Cloud:A remote sensing image processing platform based on cloud computing environment

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    This paper explores the use of cloud computing for remote sensing image processing.The main contribution of our work is to develop a remote sensing image processing platform based on cloud computing technology(OpenRS-Cloud).This paper focuses on enabling methodical investigations into the development pattern,computational model,data management and service model exploring this novel distributed computing model.The experimental INSAR processing flow is implemented to verify the efficiency and feasibility of OpenRS-Cloud platform.The results show that cloud computing is well suited for computationally-intensive and data-intensive remote sensing services.

  2. Cloud vertical distribution from radiosonde, remote sensing, and model simulations

    Science.gov (United States)

    Zhang, Jinqiang; Li, Zhanqing; Chen, Hongbin; Yoo, Hyelim; Cribb, Maureen

    2014-08-01

    Knowledge of cloud vertical structure is important for meteorological and climate studies due to the impact of clouds on both the Earth's radiation budget and atmospheric adiabatic heating. Yet it is among the most difficult quantities to observe. In this study, we develop a long-term (10 years) radiosonde-based cloud profile product over the Southern Great Plains and along with ground-based and space-borne remote sensing products, use it to evaluate cloud layer distributions simulated by the National Centers for Environmental Prediction global forecast system (GFS) model. The primary objective of this study is to identify advantages and limitations associated with different cloud layer detection methods and model simulations. Cloud occurrence frequencies are evaluated on monthly, annual, and seasonal scales. Cloud vertical distributions from all datasets are bimodal with a lower peak located in the boundary layer and an upper peak located in the high troposphere. In general, radiosonde low-level cloud retrievals bear close resemblance to the ground-based remote sensing product in terms of their variability and gross spatial patterns. The ground-based remote sensing approach tends to underestimate high clouds relative to the radiosonde-based estimation and satellite products which tend to underestimate low clouds. As such, caution must be exercised to use any single product. Overall, the GFS model simulates less low-level and more high-level clouds than observations. In terms of total cloud cover, GFS model simulations agree fairly well with the ground-based remote sensing product. A large wet bias is revealed in GFS-simulated relative humidity fields at high levels in the atmosphere.

  3. Remote sensing of Arctic boundary layer clouds above snow surfaces

    Science.gov (United States)

    Ehrlich, André; Bierwirth, Eike; Wendisch, Manfred

    2015-04-01

    In the Arctic remote sensing of clouds using reflected solar radiation is mostly related to high uncertainties as the contrast between the bright sea ice and snow surface and the clouds is low. Additionally, uncertainties result from variation of the snow grain size which changes the absorption of solar radiation similarly to the size of cloud particles. This is a major issue for understanding the response of Arctic clouds to climate warming as the quantification of cloud properties in this remote region mostly relies on satellite observations. We used spectral radiation measurements of the Spectral Modular Airborne Radiation measurement sysTem (SMART-Albedometer) to improve common used cloud remote sensing algorithms in case of snow surfaces. The measurements were collected during the airborne research campaign Vertical distribution of ice in Arctic mixed-phase clouds (VERDI, April/May 2012) above the Canadian Beaufort where both sea ice covered and ice free ocean areas were present during the observation period. Based on the spectral absorption characteristics of snow and clouds (assuming to be dominated by the liquid fraction) a combination of wavelengths was found which allows to separate the impact of clouds and snow surface on the reflected radiation measured above the clouds. While snow grain size dominates the absorption at a wavelength of 1.0 μm, information on cloud optical thickness and cloud particle effective radius can be extracted at wavelengths of 1.7 μm and 2.1 μm, respectively. Based on radiative transfer simulations lookup tables for the retrieval algorithm were calculated and used to estimate the theoretical uncertainties of the retrieval. It was found that using ratios instead of absolute radiances reduces the uncertainties significantly. The new algorithm was applied to a specific case observed during the VERDI campaign where a stratocumulus clouds was located above an ice edge. It could be shown that the method works also over water

  4. New spectral methods in cloud and aerosol remote sensing applications

    Science.gov (United States)

    Schmidt, K. Sebastian; McBride, Patrick; Pilewskie, Peter; Feingold, Graham; Jiang, Hongli

    2010-05-01

    We present new remote sensing techniques that rely on spectral observations of clouds and aerosols in the solar wavelength range. As a first example, we show how the effects of heterogeneous clouds, aerosols of changing optical properties, and the surface within one pixel can be distinguished by means of their spectral signatures. This example is based on data from the Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS, Houston, Texas, 2006), Large Eddy Simulations (LES) of polluted boundary layer clouds, and 3-dimensional radiative transfer calculations. In a second example, we show that the uncertainty of cloud retrievals can be improved considerably by exploiting the spectral information around liquid water absorption features in the near-infrared wavelength range. This is illustrated with spectral transmittance data from the NOAA International Chemistry Experiment in the Arctic LOwer Troposphere (ICEALOT, 2008). In contrast to reflected radiance, transmitted radiance is only weakly sensitive to cloud effective drop radius, and only cloud optical thickness can be obtained from the standard dual-channel technique. We show that effective radius and liquid water path can also be retrieved with the new spectral approach, and validate our results with microwave liquid water path measurements.

  5. An Uneven Illumination Correction Algorithm for Optical Remote Sensing Images Covered with Thin Clouds

    National Research Council Canada - National Science Library

    Xiaole Shen; Qingquan Li; Yingjie Tian; Linlin Shen

    2015-01-01

    .... The imaging model of remote sensing images covered by thin clouds is analyzed. Due to the transmission attenuation, reflection, and scattering, the thin cloud cover usually increases region brightness and reduces saturation and contrast of the image...

  6. Cloud removal of remote sensing image based on multi-output suppor t vector regression

    Institute of Scientific and Technical Information of China (English)

    Gensheng Hu; Xiaoqi Sun; Dong Liang; Yingying Sun

    2014-01-01

    Removal of cloud cover on the satel ite remote sens-ing image can effectively improve the availability of remote sensing images. For thin cloud cover, support vector value contourlet trans-form is used to achieve multi-scale decomposition of the area of thin cloud cover on remote sensing images. Through enhancing coefficients of high frequency and suppressing coefficients of low frequency, the thin cloud is removed. For thick cloud cover, if the areas of thick cloud cover on multi-source or multi-temporal remote sensing images do not overlap, the multi-output support vector regression learning method is used to remove this kind of thick clouds. If the thick cloud cover areas overlap, by using the multi-output learning of the surrounding areas to predict the sur-face features of the overlapped thick cloud cover areas, this kind of thick cloud is removed. Experimental results show that the pro-posed cloud removal method can effectively solve the problems of the cloud overlapping and radiation difference among multi-source images. The cloud removal image is clear and smooth.

  7. Retrieval of liquid water cloud properties from ground-based remote sensing observations

    NARCIS (Netherlands)

    Knist, C.L.

    2014-01-01

    Accurate ground-based remotely sensed microphysical and optical properties of liquid water clouds are essential references to validate satellite-observed cloud properties and to improve cloud parameterizations in weather and climate models. This requires the evaluation of algorithms for retrieval of

  8. Mixed-phase altocumulus clouds over Leipzig: Remote sensing measurements and spectral cloud microphysics simulations

    Science.gov (United States)

    Simmel, Martin; Bühl, Johannes; Ansmann, Albert; Tegen, Ina

    2015-04-01

    The present work combines remote sensing observations and detailed microphysics cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather warm temperatures of -6°C. For comparison, a second mixed phase case at about -25°C is introduced. To further look into the details of cloud microphysical processes a simple dynamics model of the Asai-Kasahara type is combined with detailed spectral microphysics forming the model system AK-SPECS. Temperature and humidity profiles are taken either from observation (radiosonde) or GDAS reanalysis. Vertical velocities are prescribed to force the dynamics as well as main cloud features to be close to the observations. Subsequently, sensitivity studies with respect to dynamical as well as ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity) whereas the ice phase is much more sensitive to the microphysical parameters (ice nuclei (IN) number, ice particle shape). The choice of ice particle shape may induce large uncertainties which are in the same order as those for the temperature-dependent IN number distribution.

  9. An Interactive Web-Based Analysis Framework for Remote Sensing Cloud Computing

    Science.gov (United States)

    Wang, X. Z.; Zhang, H. M.; Zhao, J. H.; Lin, Q. H.; Zhou, Y. C.; Li, J. H.

    2015-07-01

    Spatiotemporal data, especially remote sensing data, are widely used in ecological, geographical, agriculture, and military research and applications. With the development of remote sensing technology, more and more remote sensing data are accumulated and stored in the cloud. An effective way for cloud users to access and analyse these massive spatiotemporal data in the web clients becomes an urgent issue. In this paper, we proposed a new scalable, interactive and web-based cloud computing solution for massive remote sensing data analysis. We build a spatiotemporal analysis platform to provide the end-user with a safe and convenient way to access massive remote sensing data stored in the cloud. The lightweight cloud storage system used to store public data and users' private data is constructed based on open source distributed file system. In it, massive remote sensing data are stored as public data, while the intermediate and input data are stored as private data. The elastic, scalable, and flexible cloud computing environment is built using Docker, which is a technology of open-source lightweight cloud computing container in the Linux operating system. In the Docker container, open-source software such as IPython, NumPy, GDAL, and Grass GIS etc., are deployed. Users can write scripts in the IPython Notebook web page through the web browser to process data, and the scripts will be submitted to IPython kernel to be executed. By comparing the performance of remote sensing data analysis tasks executed in Docker container, KVM virtual machines and physical machines respectively, we can conclude that the cloud computing environment built by Docker makes the greatest use of the host system resources, and can handle more concurrent spatial-temporal computing tasks. Docker technology provides resource isolation mechanism in aspects of IO, CPU, and memory etc., which offers security guarantee when processing remote sensing data in the IPython Notebook. Users can write

  10. Ground-based remote sensing scheme for monitoring aerosol–cloud interactions (discussion)

    NARCIS (Netherlands)

    Sarna, K.; Russchenberg, H.W.J.

    2015-01-01

    A method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of cloud microphysical changes due to the changing aerosol concentration. We use high resolution measurements from lid

  11. Ground-based remote sensing scheme for monitoring aerosol-cloud interactions

    NARCIS (Netherlands)

    Sarna, K.; Russchenberg, H.W.J.

    2016-01-01

    A new method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of the change of the cloud droplet size due to the change in the aerosol concentration. We use high-resolution mea

  12. An Uneven Illumination Correction Algorithm for Optical Remote Sensing Images Covered with Thin Clouds

    Directory of Open Access Journals (Sweden)

    Xiaole Shen

    2015-09-01

    Full Text Available The uneven illumination phenomenon caused by thin clouds will reduce the quality of remote sensing images, and bring adverse effects to the image interpretation. To remove the effect of thin clouds on images, an uneven illumination correction can be applied. In this paper, an effective uneven illumination correction algorithm is proposed to remove the effect of thin clouds and to restore the ground information of the optical remote sensing image. The imaging model of remote sensing images covered by thin clouds is analyzed. Due to the transmission attenuation, reflection, and scattering, the thin cloud cover usually increases region brightness and reduces saturation and contrast of the image. As a result, a wavelet domain enhancement is performed for the image in Hue-Saturation-Value (HSV color space. We use images with thin clouds in Wuhan area captured by QuickBird and ZiYuan-3 (ZY-3 satellites for experiments. Three traditional uneven illumination correction algorithms, i.e., multi-scale Retinex (MSR algorithm, homomorphic filtering (HF-based algorithm, and wavelet transform-based MASK (WT-MASK algorithm are performed for comparison. Five indicators, i.e., mean value, standard deviation, information entropy, average gradient, and hue deviation index (HDI are used to analyze the effect of the algorithms. The experimental results show that the proposed algorithm can effectively eliminate the influences of thin clouds and restore the real color of ground objects under thin clouds.

  13. AN INTERACTIVE WEB-BASED ANALYSIS FRAMEWORK FOR REMOTE SENSING CLOUD COMPUTING

    Directory of Open Access Journals (Sweden)

    X. Z. Wang

    2015-07-01

    Full Text Available Spatiotemporal data, especially remote sensing data, are widely used in ecological, geographical, agriculture, and military research and applications. With the development of remote sensing technology, more and more remote sensing data are accumulated and stored in the cloud. An effective way for cloud users to access and analyse these massive spatiotemporal data in the web clients becomes an urgent issue. In this paper, we proposed a new scalable, interactive and web-based cloud computing solution for massive remote sensing data analysis. We build a spatiotemporal analysis platform to provide the end-user with a safe and convenient way to access massive remote sensing data stored in the cloud. The lightweight cloud storage system used to store public data and users’ private data is constructed based on open source distributed file system. In it, massive remote sensing data are stored as public data, while the intermediate and input data are stored as private data. The elastic, scalable, and flexible cloud computing environment is built using Docker, which is a technology of open-source lightweight cloud computing container in the Linux operating system. In the Docker container, open-source software such as IPython, NumPy, GDAL, and Grass GIS etc., are deployed. Users can write scripts in the IPython Notebook web page through the web browser to process data, and the scripts will be submitted to IPython kernel to be executed. By comparing the performance of remote sensing data analysis tasks executed in Docker container, KVM virtual machines and physical machines respectively, we can conclude that the cloud computing environment built by Docker makes the greatest use of the host system resources, and can handle more concurrent spatial-temporal computing tasks. Docker technology provides resource isolation mechanism in aspects of IO, CPU, and memory etc., which offers security guarantee when processing remote sensing data in the IPython Notebook

  14. Toward the Characterization of Mixed-Phase Clouds Using Remote Sensing

    Science.gov (United States)

    Andronache, C.

    2015-12-01

    Mixed-phase clouds consist of a mixture of ice particles and liquid droplets at temperatures below 0 deg C. They are present in all seasons in many regions of the world, account for about 30% of the global cloud coverage, and are linked to cloud electrification and aircraft icing. The mix of ice particles, liquid droplets, and water vapor is unstable, and such clouds are thought to have a short lifetime. A characteristic parameter is the phase composition of mixed-phase clouds. It affects the cloud life cycle and the rate of precipitation. This parameter is important for cloud parameters retrievals by radar, lidar, and satellite and is relevant for climate modeling. The phase transformation includes the remarkable Wegener-Bergeron-Findeisen (WBF) process. The direction and the rate of the phase transformations depend on the local thermodynamic and microphysical properties. Cloud condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and the dynamic response of clouds to aerosols. The complexity of dynamics and microphysics involved in mixed-phase clouds requires a set of observational and modeling tools that continue to be refined. Among these techniques, the remote sensing methods provide an increasing number of parameters, covering large regions of the world. Thus, a series of studies were dedicated to stratiform mixed-phase clouds revealing longer lifetime than previously thought. Satellite data and aircraft in situ measurements in deep convective clouds suggest that highly supercooled water often occurs in vigorous continental convective storms. In this study, we use cases of convective clouds to discuss the feasibility of mixed-phase clouds characterization and potential advantages of remote sensing.

  15. Comparison of Cloud Resolving Model Simulations to Remote Sensing Data

    Science.gov (United States)

    Randall, David A.; Eitzen, Zachary

    2005-01-01

    The purpose of this research was to evaluate the ability of a cloud-resolving model (CRM) to simulate the dynamical, radiative, and microphysical properties of deep convective cloud objects identified using CERES (Clouds and the Earth s Radiant Energy System) on board the Tropical Rainfall Measuring Mission (TRMM) satellite platform, for many cases. A deep convective cloud object is a contiguous region that is composed of satellite footprints that fulfill the following selection criteria: 100% cloud fraction, cloud optical depth > 10, and a cloud top height of at least 10 km. Selection criteria have also been formed for different types of boundary-layer clouds, as described in Xu et al. (2005). The purpose of the cloud object approach is to identify specific areas of where the cloud properties simulated by the CRM systematically differ from the observed cloud properties. Where these systematic differences exist, concrete steps can be made to improve the CRM s simulation of an entire class of clouds, rather than by tuning the model to correctly simulate a single case study, as is often done. Additional information regarding detailed approaches and findings are presented.

  16. Toward autonomous surface-based infrared remote sensing of polar clouds: cloud-height retrievals

    Science.gov (United States)

    Rowe, Penny M.; Cox, Christopher J.; Walden, Von P.

    2016-08-01

    Polar regions are characterized by their remoteness, making measurements challenging, but an improved knowledge of clouds and radiation is necessary to understand polar climate change. Infrared radiance spectrometers can operate continuously from the surface and have low power requirements relative to active sensors. Here we explore the feasibility of retrieving cloud height with an infrared spectrometer that would be designed for use in remote polar locations. Using a wide variety of simulated spectra of mixed-phase polar clouds at varying instrument resolutions, retrieval accuracy is explored using the CO2 slicing/sorting and the minimum local emissivity variance (MLEV) methods. In the absence of imposed errors and for clouds with optical depths greater than ˜ 0.3, cloud-height retrievals from simulated spectra using CO2 slicing/sorting and MLEV are found to have roughly equivalent high accuracies: at an instrument resolution of 0.5 cm-1, mean biases are found to be ˜ 0.2 km for clouds with bases below 2 and -0.2 km for higher clouds. Accuracy is found to decrease with coarsening resolution and become worse overall for MLEV than for CO2 slicing/sorting; however, the two methods have differing sensitivity to different sources of error, suggesting an approach that combines them. For expected errors in the atmospheric state as well as both instrument noise and bias of 0.2 mW/(m2 sr cm-1), at a resolution of 4 cm-1, average retrieval errors are found to be less than ˜ 0.5 km for cloud bases within 1 km of the surface, increasing to ˜ 1.5 km at 4 km. This sensitivity indicates that a portable, surface-based infrared radiance spectrometer could provide an important complement in remote locations to satellite-based measurements, for which retrievals of low-level cloud are challenging.

  17. Remote Sensing

    CERN Document Server

    Khorram, Siamak; Koch, Frank H; van der Wiele, Cynthia F

    2012-01-01

    Remote Sensing provides information on how remote sensing relates to the natural resources inventory, management, and monitoring, as well as environmental concerns. It explains the role of this new technology in current global challenges. "Remote Sensing" will discuss remotely sensed data application payloads and platforms, along with the methodologies involving image processing techniques as applied to remotely sensed data. This title provides information on image classification techniques and image registration, data integration, and data fusion techniques. How this technology applies to natural resources and environmental concerns will also be discussed.

  18. Remote sensing of contrails and aircraft altered cirrus clouds

    Energy Technology Data Exchange (ETDEWEB)

    Palikonda, R.; Nguyen, L.; Garber, D.P.; Smith, W.L. Jr [Analytical Services and Materials, Inc., Hampton, VA (United States); Minnis, P.; Young, D.F. [National Aeronautics and Space Administration, Hampton, VA (United States). Langley Research Center

    1997-12-31

    Analyses of satellite imagery are used to show that contrails can develop into fully extended cirrus cloud systems. Contrails can be advective on great distances, but would appear to observers as natural cirrus clouds. The conversion of simple contrails into cirrus may help explain the apparent increase of cloudiness over populated areas since the beginning of commercial jet air travel. Statistics describing the typical growth, advection, and lifetime of contrail cirrus is needed to evaluate their effects on climate. (author) 4 refs.

  19. Remote sensing of cloud sides of deep convection: towards a three-dimensional retrieval of cloud particle size profiles

    Directory of Open Access Journals (Sweden)

    T. Zinner

    2008-08-01

    Full Text Available The cloud scanner sensor is a central part of a recently proposed satellite remote sensing concept – the three-dimensional (3-D cloud and aerosol interaction mission (CLAIM-3D combining measurements of aerosol characteristics in the vicinity of clouds and profiles of cloud microphysical characteristics. Such a set of collocated measurements will allow new insights in the complex field of cloud-aerosol interactions affecting directly the development of clouds and precipitation, especially in convection. The cloud scanner measures radiance reflected or emitted by cloud sides at several wavelengths to derive a profile of cloud particle size and thermodynamic phase. For the retrieval of effective size a Bayesian approach was adopted and introduced in a preceding paper.

    In this paper the potential of the approach, which has to account for the complex three-dimensional nature of cloud geometry and radiative transfer, is tested in realistic cloud observing situations. In a fully simulated environment realistic cloud resolving modelling provides complex 3-D structures of ice, water, and mixed phase clouds, from the early stage of convective development to mature deep convection. A three-dimensional Monte Carlo radiative transfer is used to realistically simulate the aspired observations.

    A large number of cloud data sets and related simulated observations provide the database for an experimental Bayesian retrieval. An independent simulation of an additional cloud field serves as a synthetic test bed for the demonstration of the capabilities of the developed retrieval techniques. For this test case only a minimal overall bias in the order of 1% as well as pixel-based uncertainties in the order of 1 μm for droplets and 8 μm for ice particles were found for measurements at a high spatial resolution of 250 m.

  20. Ground-based Remote Sensing of Cloud Liquid Water Path

    Science.gov (United States)

    Crewell, S.; Loehnert, U.

    Within the BALTEX Cloud LIquid WAter NETwork (CLIWA-NET) measurements of cloud parameters were performed to improve/evaluate cloud parameterizations in numerical weather prediction and climate models. The key variable is the cloud liq- uid water path (LWP) which is measured by passive microwave radiometry from the ground during three two-month CLIWA-NET observational periods. Additionally to the high temporal resolution time series from the ground, LWP fields are derived from satellite measurements. During the first two campaigns a continental scale network consisting of 12 stations was established. Most stations included further cloud sen- sitive instruments like infrared radiometer and lidar ceilometer. The third campaign started with a two-week long microwave intercomparison campaign (MICAM) in Cabauw, The Netherlands, and proceeded with a regional network within a 100 by 100 km area. The presentation will focus on the accuracy of LWP derived from the ground by in- vestigating the accuracy of the microwave brightness temperature measurement and examining the LWP retrieval uncertainty. Up to now microwave radiometer are no standard instruments and the seven radiometer involved in MICAM differ in frequen- cies, bandwidths, angular resolution, integration time etc. The influence of this instru- ment specifications on the LWP retrieval will be discussed.

  1. Remote Sensing the Vertical Profile of Cloud Droplet Effective Radius, Thermodynamic Phase, and Temperature

    Science.gov (United States)

    Martins, J. V.; Marshak, A.; Remer, L. A.; Rosenfeld, D.; Kaufman, Y. J.; Fernandez-Borda, R.; Koren, I.; Correia, A. L.; Zubko, V.; Artaxo, P.

    2011-01-01

    Cloud-aerosol interaction is a key issue in the climate system, affecting the water cycle, the weather, and the total energy balance including the spatial and temporal distribution of latent heat release. Information on the vertical distribution of cloud droplet microphysics and thermodynamic phase as a function of temperature or height, can be correlated with details of the aerosol field to provide insight on how these particles are affecting cloud properties and their consequences to cloud lifetime, precipitation, water cycle, and general energy balance. Unfortunately, today's experimental methods still lack the observational tools that can characterize the true evolution of the cloud microphysical, spatial and temporal structure in the cloud droplet scale, and then link these characteristics to environmental factors and properties of the cloud condensation nuclei. Here we propose and demonstrate a new experimental approach (the cloud scanner instrument) that provides the microphysical information missed in current experiments and remote sensing options. Cloud scanner measurements can be performed from aircraft, ground, or satellite by scanning the side of the clouds from the base to the top, providing us with the unique opportunity of obtaining snapshots of the cloud droplet microphysical and thermodynamic states as a function of height and brightness temperature in clouds at several development stages. The brightness temperature profile of the cloud side can be directly associated with the thermodynamic phase of the droplets to provide information on the glaciation temperature as a function of different ambient conditions, aerosol concentration, and type. An aircraft prototype of the cloud scanner was built and flew in a field campaign in Brazil.

  2. Using High-Resolution Airborne Remote Sensing to Study Aerosol Near Clouds

    Science.gov (United States)

    Levy, Robert; Munchak, Leigh; Mattoo, Shana; Marshak, Alexander; Wilcox, Eric; Gao, Lan; Yorks, John; Platnick, Steven

    2016-01-01

    The horizontal space in between clear and cloudy air is very complex. This so-called twilight zone includes activated aerosols that are not quite clouds, thin cloud fragments that are not easily observable, and dying clouds that have not quite disappeared. This is a huge challenge for satellite remote sensing, specifically for retrieval of aerosol properties. Identifying what is cloud versus what is not cloud is critically important for attributing radiative effects and forcings to aerosols. At the same time, the radiative interactions between clouds and the surrounding media (molecules, surface and aerosols themselves) will contaminate retrieval of aerosol properties, even in clear skies. Most studies on aerosol cloud interactions are relevant to moderate resolution imagery (e.g. 500 m) from sensors such as MODIS. Since standard aerosol retrieval algorithms tend to keep a distance (e.g. 1 km) from the nearest detected cloud, it is impossible to evaluate what happens closer to the cloud. During Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), the NASA ER-2 flew with the enhanced MODIS Airborne Simulator (eMAS), providing MODIS-like spectral observations at high (50 m) spatial resolution. We have applied MODIS-like aerosol retrieval for the eMAS data, providing new detail to characterization of aerosol near clouds. Interpretation and evaluation of these eMAS aerosol retrievals is aided by independent MODIS-like cloud retrievals, as well as profiles from the co-flying Cloud Physics Lidar (CPL). Understanding aerosolcloud retrieval at high resolution will lead to better characterization and interpretation of long-term, global products from lower resolution (e.g.MODIS) satellite retrievals.

  3. Remote sensing the vertical profile of cloud droplet effective radius, thermodynamic phase, and temperature

    Directory of Open Access Journals (Sweden)

    J. Vanderlei Martins

    2007-03-01

    Full Text Available Cloud-aerosol interaction is no longer simply a radiative problem, but one affecting the water cycle, the weather, and the total energy balance including the spatial and temporal distribution of latent heat release. Information on the vertical distribution of cloud droplet microphysics and thermodynamic phase as a function of temperature or height, can be correlated with details of the aerosol field to provide insight on how these particles are affecting cloud properties and its consequences to cloud lifetime, precipitation, water cycle, and general energy balance. Unfortunately, today's experimental methods still lack the observational tools that can characterize the true evolution of the cloud microphysical, spatial and temporal structure in the cloud droplet scale, and then link these characteristics to environmental factors and properties of the cloud condensation nuclei.

    Here we propose and demonstrate a new experimental approach (the cloud scanner instrument that provides the microphysical information missed in current experiments and remote sensing options. Cloud scanner measurements can be performed from aircraft, ground, or satellite by scanning the side of the clouds from the base to the top, providing us with the unique opportunity of obtaining snapshots of the cloud droplet microphysical and thermodynamic states as a function of height and brightness temperature in clouds at several development stages. The brightness temperature profile of the cloud side can be directly associated with the thermodynamic phase of the droplets to provide information on the glaciation temperature as a function of different ambient conditions, aerosol concentration, and type. An aircraft prototype of the cloud scanner was built and flew in a field campaign in Brazil.

    The CLAIM-3D (3-Dimensional Cloud Aerosol Interaction Mission satellite concept proposed here combines several techniques to simultaneously measure the vertical

  4. IceCube: CubeSat 883-GHz Radiometry for Future Ice Cloud Remote Sensing

    Science.gov (United States)

    Wu, Dongliang; Esper, Jaime; Ehsan, Negar; Johnson, Thomas; Mast, William; Piepmeier, Jeffery R.; Racette, Paul E.

    2015-01-01

    Ice clouds play a key role in the Earth's radiation budget, mostly through their strong regulation of infrared radiation exchange. Accurate observations of global cloud ice and its distribution have been a challenge from space, and require good instrument sensitivities to both cloud mass and microphysical properties. Despite great advances from recent spaceborne radar and passive sensors, uncertainty of current ice water path (IWP) measurements is still not better than a factor of 2. Submillimeter (submm) wave remote sensing offers great potential for improving cloud ice measurements, with simultaneous retrievals of cloud ice and its microphysical properties. The IceCube project is to enable this cloud ice remote sensing capability in future missions, by raising 874-GHz receiver technology TRL from 5 to 7 in a spaceflight demonstration on 3-U CubeSat in a low Earth orbit (LEO) environment. The NASAs Goddard Space Flight Center (GSFC) is partnering with Virginia Diodes Inc (VDI) on the 874-GHz receiver through its Vector Network Analyzer (VNA) extender module product line, to develop an instrument with precision of 0.2 K over 1-second integration and accuracy of 2.0 K or better. IceCube is scheduled to launch to and subsequent release from the International Space Station (ISS) in mid-2016 for nominal operation of 28 plus days. We will present the updated design of the payload and spacecraft systems, as well as the operation concept. We will also show the simulated 874-GHz radiances from the ISS orbits and cloud scattering signals as expected for the IceCube cloud radiometer.

  5. Modeling the Impact of Drizzle and 3D Cloud Structure on Remote Sensing of Effective Radius

    Science.gov (United States)

    Platnick, Steven; Zinner, Tobias; Ackerman, S.

    2008-01-01

    Remote sensing of cloud particle size with passive sensors like MODIS is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave infrared channels. MODIS observations sometimes show significantly larger effective radii in marine boundary layer cloud fields derived from the 1.6 and 2.1 pm channel observations than for 3.7 pm retrievals. Possible explanations range from 3D radiative transport effects and sub-pixel cloud inhomogeneity to the impact of drizzle formation on the droplet distribution. To investigate the potential influence of these factors, we use LES boundary layer cloud simulations in combination with 3D Monte Carlo simulations of MODIS observations. LES simulations of warm cloud spectral microphysics for cases of marine stratus and broken stratocumulus, each for two different values of cloud condensation nuclei density, produce cloud structures comprising droplet size distributions with and without drizzle size drops. In this study, synthetic MODIS observations generated from 3D radiative transport simulations that consider the full droplet size distribution will be generated for each scene. The operational MODIS effective radius retrievals will then be applied to the simulated reflectances and the results compared with the LES microphysics.

  6. Remote Sensing.

    Science.gov (United States)

    Williams, Richard S., Jr.; Southworth, C. Scott

    1983-01-01

    The Landsat Program became the major event of 1982 in geological remote sensing with the successful launch of Landsat 4. Other 1982 remote sensing accomplishments, research, publications, (including a set of Landsat worldwide reference system index maps), and conferences are highlighted. (JN)

  7. Fuzzy AutoEncode Based Cloud Detection for Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Zhenfeng Shao

    2017-03-01

    Full Text Available Cloud detection of remote sensing imagery is quite challenging due to the influence of complicated underlying surfaces and the variety of cloud types. Currently, most of the methods mainly rely on prior knowledge to extract features artificially for cloud detection. However, these features may not be able to accurately represent the cloud characteristics under complex environment. In this paper, we adopt an innovative model named Fuzzy Autoencode Model (FAEM to integrate the feature learning ability of stacked autoencode networks and the detection ability of fuzzy function for highly accurate cloud detection on remote sensing imagery. Our proposed method begins by selecting and fusing spectral, texture, and structure information. Thereafter, the proposed technique established a FAEM to learn the deep discriminative features from a great deal of selected information. Finally, the learned features are mapped to the corresponding cloud density map with a fuzzy function. To demonstrate the effectiveness of the proposed method, 172 Landsat ETM+ images and 25 GF-1 images with different spatial resolutions are used in this paper. For the convenience of accuracy assessment, ground truth data are manually outlined. Results show that the average RER (ratio of right rate and error rate on Landsat images is greater than 29, while the average RER of Support Vector Machine (SVM is 21.8 and Random Forest (RF is 23. The results on GF-1 images exhibit similar performance as Landsat images with the average RER of 25.9, which is much higher than the results of SVM and RF. Compared to traditional methods, our technique has attained higher average cloud detection accuracy for either different spatial resolutions or various land surfaces.

  8. Ice phase in altocumulus clouds over Leipzig: remote sensing observations and detailed modeling

    Science.gov (United States)

    Simmel, M.; Bühl, J.; Ansmann, A.; Tegen, I.

    2015-09-01

    The present work combines remote sensing observations and detailed cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather high temperatures of -6 °C. For comparison, a second mixed phase case at about -25 °C is introduced. To further look into the details of cloud microphysical processes, a simple dynamics model of the Asai-Kasahara (AK) type is combined with detailed spectral microphysics (SPECS) forming the model system AK-SPECS. Vertical velocities are prescribed to force the dynamics, as well as main cloud features, to be close to the observations. Subsequently, sensitivity studies with respect to ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity), whereas the ice phase is much more sensitive to the microphysical parameters (ice nucleating particle (INP) number, ice particle shape). The choice of ice particle shape may induce large uncertainties that are on the same order as those for the temperature-dependent INP number distribution.

  9. Ice phase in altocumulus clouds over Leipzig: remote sensing observations and detailed modelling

    Science.gov (United States)

    Simmel, M.; Bühl, J.; Ansmann, A.; Tegen, I.

    2015-01-01

    The present work combines remote sensing observations and detailed cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather warm temperatures of -6 °C. For comparison, a second mixed phase case at about -25 °C is introduced. To further look into the details of cloud microphysical processes a simple dynamics model of the Asai-Kasahara type is combined with detailed spectral microphysics forming the model system AK-SPECS. Vertical velocities are prescribed to force the dynamics as well as main cloud features to be close to the observations. Subsequently, sensitivity studies with respect to ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity) whereas the ice phase is much more sensitive to the microphysical parameters (ice nuclei (IN) number, ice particle shape). The choice of ice particle shape may induce large uncertainties which are in the same order as those for the temperature-dependent IN number distribution.

  10. A low-cost digital holographic imager for calibration and validation of cloud microphysics remote sensing

    Science.gov (United States)

    Chambers, Thomas E.; Hamilton, Murray W.; Reid, Iain M.

    2016-10-01

    Clouds cover approximately 70% of the Earth's surface and therefore play a crucial rule in governing both the climate system and the hydrological cycle. The microphysical properties of clouds such as the cloud particle size distribution, shape distribution and spatial homogeneity contribute significantly to the net radiative effect of clouds and these properties must therefore be measured and understood to determine the exact contribution of clouds to the climate system. Significant discrepancies are observed between meteorological models and observations, particularly in polar regions that are most sensitive to changes in climate, suggesting a lack of understanding of these complex microphysical processes. Remote sensing techniques such as polarimetric LIDAR and radar allow microphysical cloud measurements with high temporal and spatial resolution however these instruments must be calibrated and validated by direct in situ measurements. To this end a low cost, light weight holographic imaging device has been developed and experimentally tested that is suitable for deployment on a weather balloon or tower structure to significantly increase the availability of in situ microphysics retrievals.

  11. Cloud glaciation temperature estimation from passive remote sensing data with evolutionary computing

    Science.gov (United States)

    Carro-Calvo, L.; Hoose, C.; Stengel, M.; Salcedo-Sanz, S.

    2016-11-01

    The phase partitioning between supercooled liquid water and ice in clouds in the temperature range between 0 and -37°C influences their optical properties and the efficiency of precipitation formation. Passive remote sensing observations provide long-term records of the cloud top phase at a high spatial resolution. Based on the assumption of a cumulative Gaussian distribution of the ice cloud fraction as a function of temperature, we quantify the cloud glaciation temperature (CGT) as the 50th percentile of the fitted distribution function and its variance for different cloud top pressure intervals, obtained by applying an evolutionary algorithm (EA). EAs are metaheuristics approaches for optimization, used in difficult problems where standard approaches are either not applicable or show poor performance. In this case, the proposed EA is applied to 4 years of Pathfinder Atmospheres-Extended (PATMOS-x) data, aggregated into boxes of 1° × 1° and vertical layers of 5.5 hPa. The resulting vertical profile of CGT shows a characteristic sickle shape, indicating low CGTs close to homogeneous freezing in the upper troposphere and significantly higher values in the midtroposphere. In winter, a pronounced land-sea contrast is found at midlatitudes, with lower CGTs over land. Among this and previous studies, there is disagreement on the sign of the land-sea difference in CGT, suggesting that it is strongly sensitive to the detected and analyzed cloud types, the time of the day, and the phase retrieval method.

  12. Investigation of Arctic mixed-phase clouds during VERDI and RACEPAC: Combining airborne remote sensing and in situ observations

    Science.gov (United States)

    Ehrlich, André; Wendisch, Manfred

    2015-04-01

    To improve our understanding of Arctic mixed-phase clouds in sea-ice covered areas the airborne research campaign Vertical distribution of ice in Arctic mixed-phase clouds (VERDI, April/May 2012) and the Radiation-Aerosol-Cloud Experiment in the Arctic Circle (RACEPAC, April/May 2014) were initiated by a collaboration of German and French research institutes. The aircraft operated by the Alfred Wegener Institute for Polar and Marine Research, Germany were based in Inuvik, Canada from where the research flights of in total 149 flight hours (62 h during VERDI, 87 h during RACEPAC) were able to cover a wide area above the Canadian Beaufort. The aim of both campaigns was to combine remote sensing and in-situ cloud, aerosol and trace gas measurements to investigate interactions between radiation, cloud and aerosol particles. Remote sensing instrumentation contained a backscatter lidar and spectral solar radiation measurements including a hyperspectral camera. In-situ sampling was highlighted by a suit of comprehensive cloud particle probes, aerosol particle counters and mass spectroscopy as well as trace gas detectors. While during VERDI remote sensing and in-situ measurements were performed by one aircraft (Polar 5) subsequently, for RACEPAC two identical aircraft (Polar 5 & 6, Basler BT-67) were coordinated at different altitudes to horizontally collocate both remote sensing and in-situ measurements. In this way not only the combined analysis of radiative and microphysical processes in the clouds can by studied more reliably, also remote sensing methods can be validated efficiently. Here we will illustrate the scientific strategy of both projects including instrumentation and flight patterns of the research flights. Beside flight missions dedicated to sample low level clouds by remote sensing and in situ probing, flights were also coordinated with satellite overpasses and ground based stations. Exemplary results will be highlighted.

  13. LIDAR and atmosphere remote sensing

    CSIR Research Space (South Africa)

    Venkataraman, S

    2008-05-01

    Full Text Available and to consist of theory and practical exercises • Theory: Remote sensing process, Photogrammetry, introduction to multispectral, remote sensing systems, Thermal infra-red remote sensing, Active and passive remote sensing, LIDAR, Application of remotely... Aerosol measurements and cloud characteristics head2right Water vapour measurements in the lower troposphere region up to 8 km head2right Ozone measurements in the troposphere regions up to 18 km Slide 22 © CSIR 2008 www...

  14. Clear-Sky Remote Sensing in the Vicinity of Clouds: What We Learned from MODIS and CALIPSO

    Science.gov (United States)

    Marshak, Alexander; Varnai, Tamas; Wen, Guoyong; Cahalan, Robert

    2010-01-01

    Studies on aerosol direct and indirect effects require a precise separation of cloud-free and cloudy air. However, separation between cloud-free and cloudy areas from remotely-sensed measurements is ambiguous. The transition zone in the regions around clouds often stretches out tens of km, which are neither precisely clear nor precisely cloudy. We study the transition zone between cloud-free and cloudy air using MODerate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements. Both instruments show enhanced clear-sky reflectance (MODIS) and clear-sky backscatterer (CALIPSO) near clouds, Analyzing a large dataset of MODIS observations we examine the effect of three-dimensional (3D) radiative interactions between clouds and cloud-free areas, also known as a cloud adjacency effect. Comparing with CALIPSO clear-sky backscatterer measurements, we show that the cloud adjacency effect may be responsible for a large portion of the enhanced clear sky reflectance observed by MODIS. While aerosol particles are responsible for a large part of the near-cloud enhancements in CALIPSO observations, misidentified or undetected cloud particles are also likely to contribute. As a result, both the nature of these particles (cloud vs. aerosol) and the processes creating them need to be clarified using a quantitative assessment of remote sensing limitations in particle detection and identification. The width and ubiquity of the transition zone near clouds imply that studies of aerosol-cloud interactions and aerosol direct radiative effects need to account for aerosol changes near clouds. Not accounted, these changes can cause systematic biases toward smaller aerosol radiative forcing. On the other hand, including aerosol products near clouds despite their uncertainties may overestimate aerosol radiative forcing. Therefore, there is an urgent need for developing methods that can assess and account for

  15. Clear-Sky Remote Sensing in the Vicinity of Clouds: What Can Be Learned About Aerosol Changes?

    Science.gov (United States)

    Marshak, Alexander; Varnai, Tamas; Wen, Guoyong

    2010-01-01

    Studies on aerosol direct and indirect effects require a precise separation of cloud-free and cloudy air. However, separation between cloud-free and cloudy areas from remotely-sensed measurements is ambiguous. The transition zone in the regions around clouds often stretches out tens of km, which are neither precisely clear nor precisely cloudy. We study the transition zone between cloud-free and cloudy air using MODerate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements. Both instruments show enhanced clear-sky reflectance (MODIS) and clear-sky backscatterer (CALIPSO) near clouds. Analyzing a large dataset of MODIS observations we examine the effect of three-dimensional (3D) radiative interactions between clouds and cloud-free areas, also known as a cloud adjacency effect. Comparing with CALIPSO clear-sky backscatterer measurements, we show that the cloud adjacency effect may be responsible for a large portion of the enhanced clear sky reflectance observed by MODIS. While aerosol particles are responsible for a large part of the near-cloud enhancements in CALIPSO observations, misidentified or undetected cloud particles are also likely to contribute. As a result, both the nature of these particles (cloud vs. aerosol) and the processes creating them need to be clarified using a quantitative assessment of remote sensing limitations in particle detection and identification. "The width and ubiquity of the transition zone near clouds imply that studies of-aerosol-cloud -interactions and aerosol direct radiative effects need to account for aerosol changes near clouds. Not accounted, these changes can cause systematic biases toward smaller aerosol radiative forcing. On the other hand, including aerosol products near clouds despite their uncertainties may overestimate aerosol radiative forcing. Therefore, there is an urgent need for developing methods that can assess and account for

  16. Ground-based imaging remote sensing of ice clouds: uncertainties caused by sensor, method and atmosphere

    Science.gov (United States)

    Zinner, Tobias; Hausmann, Petra; Ewald, Florian; Bugliaro, Luca; Emde, Claudia; Mayer, Bernhard

    2016-09-01

    In this study a method is introduced for the retrieval of optical thickness and effective particle size of ice clouds over a wide range of optical thickness from ground-based transmitted radiance measurements. Low optical thickness of cirrus clouds and their complex microphysics present a challenge for cloud remote sensing. In transmittance, the relationship between optical depth and radiance is ambiguous. To resolve this ambiguity the retrieval utilizes the spectral slope of radiance between 485 and 560 nm in addition to the commonly employed combination of a visible and a short-wave infrared wavelength.An extensive test of retrieval sensitivity was conducted using synthetic test spectra in which all parameters introducing uncertainty into the retrieval were varied systematically: ice crystal habit and aerosol properties, instrument noise, calibration uncertainty and the interpolation in the lookup table required by the retrieval process. The most important source of errors identified are uncertainties due to habit assumption: Averaged over all test spectra, systematic biases in the effective radius retrieval of several micrometre can arise. The statistical uncertainties of any individual retrieval can easily exceed 10 µm. Optical thickness biases are mostly below 1, while statistical uncertainties are in the range of 1 to 2.5.For demonstration and comparison to satellite data the retrieval is applied to observations by the Munich hyperspectral imager specMACS (spectrometer of the Munich Aerosol and Cloud Scanner) at the Schneefernerhaus observatory (2650 m a.s.l.) during the ACRIDICON-Zugspitze campaign in September and October 2012. Results are compared to MODIS and SEVIRI satellite-based cirrus retrievals (ACRIDICON - Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems; MODIS - Moderate Resolution Imaging Spectroradiometer; SEVIRI - Spinning Enhanced Visible and Infrared Imager). Considering the identified

  17. Ground-based remote sensing scheme for monitoring aerosol–cloud interactions

    Directory of Open Access Journals (Sweden)

    K. Sarna

    2015-11-01

    Full Text Available A method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of cloud microphysical changes due to the changing aerosol concentration. We use high resolution measurements from lidar, radar and radiometer which allow to collect and compare data continuously. This method is based on a standardised data format from Cloudnet and can be implemented at any observatory where the Cloudnet data set is available. Two example study cases were chosen from the Atmospheric Radiation Measurement (ARM Program deployment at Graciosa Island, Azores, Portugal in 2009 to present the method. We show the Pearson Product–Moment Correlation Coefficient, r, and the Coefficient of Determination, r2 for data divided into bins of LWP, each of 10 g m−2. We explain why the commonly used way of quantity aerosol cloud interactions by use of an ACI index (ACIr,τ = dln re,τ/dlnα is not the best way of quantifying aerosol–cloud interactions.

  18. A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

    Science.gov (United States)

    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.

  19. Ice formation in altocumulus clouds over Leipzig: Remote sensing measurements and detailed model simulations

    Science.gov (United States)

    Simmel, Martin; Bühl, Johannes; Ansmann, Albert; Tegen, Ina

    2014-05-01

    Over Leipzig, altocumulus clouds are frequently observed using a suite of remote sensing instruments. These observations cover a wide range of heights, temperatures, and microphysical properties of the clouds ranging from purely liquid to heavily frozen. For the current study, two cases were chosen to test the sensitivity of these clouds with respect to several microphysical and dynamical parameters such as aerosol properties (CCN, IN), ice particle shape as well as turbulence. The mixed-phase spectral microphysical model SPECS was coupled to a dynamical model of the Asai-Kasahara type resulting in the model system AK-SPECS. The relatively simple dynamics allows for a fine vertical resolution needed for the rather shallow cloud layers observed. Additionally, the proper description of hydrometeor sedimentation is important especially for the fast growing ice crystals to realistically capture their interaction with the vapour and liquid phase (Bergeron-Findeisen process). Since the focus is on the cloud microphysics, the dynamics in terms of vertical velocity profile is prescribed for the model runs and the feedback of the microphysics on dynamics by release or consumption of latent heat due to phase transfer is not taken into account. The microphysics focuses on (1) ice particle shape allowing hexagonal plates and columns with size-dependant axis ratios and (2) the ice nuclei (IN) budget realized with a prognostic temperature resolved field of potential IN allowing immersion freezing only when active IN and supercooled drops above a certain size threshold are present within a grid cell. Sensitivity studies show for both cases that ice particle shape seems to have the major influence on ice mass formation under otherwise identical conditions. This is due to the effect (1) on terminal fall velocity of the individual ice particle allowing for longer presence times in conditions supersaturated with respect to ice and (2) on water vapour deposition which is enhanced due

  20. Remote sensing of water cloud droplet size distributions using the backscatter glory: a case study

    Directory of Open Access Journals (Sweden)

    B. Mayer

    2004-01-01

    Full Text Available Cloud single scattering properties are mainly determined by the effective radius of the droplet size distribution. There are only few exceptions where the shape of the size distribution affects the optical properties, in particular the rainbow and the glory directions of the scattering phase function. Using observations by the Compact Airborne Spectrographic Imager (CASI in 180° backscatter geometry, we found that high angular resolution aircraft observations of the glory provide unique new information which is not available from traditional remote sensing techniques: Using only one single wavelength, 753nm, we were able to determine not only optical thickness and effective radius, but also the width of the size distribution at cloud top. Applying this novel technique to the ACE-2 CLOUDYCOLUMN experiment, we found that the size distributions were much narrower than usually assumed in radiation calculations which is in agreement with in-situ observations during this campaign. While the shape of the size distribution has only little relevance for the radiative properties of clouds, it is extremely important for understanding their formation and evolution.

  1. Remote sensing of water cloud droplet size distributions using the backscatter glory: a case study

    Directory of Open Access Journals (Sweden)

    B. Mayer

    2004-05-01

    Full Text Available Cloud single scattering properties are mainly determined by the effective radius of the droplet size distribution. There are only few exceptions where the shape of the size distribution affects the optical properties, in particular the rainbow and the glory directions of the scattering phase function. Using observations by the Compact Airborne Spectrographic Imager (CASI in 180° backscatter geometry, we found that high angular resolution aircraft observations of the glory provide unique new information which is not available from traditional remote sensing techniques: Using only one single wavelength, 753 nm, we were able to determine not only optical thickness and effective radius, but also the width of the size distribution at cloud top. Applying this novel technique to the ACE-2 CLOUDYCOLUMN experiment, we found that the size distributions were much narrower than usually assumed in radiation calculations which is in agreement with in-situ observations during this campaign. While the shape of the size distribution has only little relevance for the radiative properties of clouds, it is extremely important for understanding their formation and evolution.

  2. Cloud and precipitation properties from ground-based remote sensing instruments in East Antarctica

    Directory of Open Access Journals (Sweden)

    I. V. Gorodetskaya

    2014-07-01

    Full Text Available A new comprehensive cloud-precipitation-meteorological observatory has been established at Princess Elisabeth base, located in the escarpment zone of Dronning Maud Land, East Antarctica. The observatory consists of a set of ground-based remote sensing instruments (ceilometer, infrared pyrometer and vertically profiling precipitation radar combined with automatic weather station measurements of near-surface meteorology, radiative fluxes, and snow accumulation. In this paper, the observatory is presented and the potential for studying the evolution of clouds and precipitating systems is illustrated by case studies. It is shown that the synergetic use of the set of instruments allows for distinguishing ice, mixed-phase and precipitating clouds, including some information on their vertical extent. In addition, wind-driven blowing snow events can be distinguished from deeper precipitating systems. Cloud properties largely affect the surface radiative fluxes, with liquid-containing clouds dominating the radiative impact. A statistical analysis of all measurements (in total 14 months mainly occurring in summer/autumn indicates that these liquid-containing clouds occur during as much as 20% of the cloudy periods. The cloud occurrence shows a strong bimodal distribution with clear sky conditions 51% of the time and complete overcast conditions 35% of the time. Snowfall occurred 17% of the cloudy periods with a predominance of light precipitation and only rare events with snowfall > 1 mm h−1 water equivalent (w.e.. Three of such intensive snowfall events occurred during 2011 contributing to anomalously large annual snow accumulation. This is the first deployment of a precipitation radar in Antarctica allowing to assess the contribution of the snowfall to the local surface mass balance. It is shown that on the one hand large accumulation events (>10 mm w.e. day−1 during the measurement period of 26 months were always associated with snowfall, but that

  3. Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter

    Science.gov (United States)

    Hilker, Thomas; Lyapustin, Alexei I.; Tucker, Compton J.; Sellers, Piers J.; Hall, Forrest G.; Wang, Yujie

    2012-01-01

    Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased

  4. monthly probabilities for acquiring remote sensed data of indonesia with cloud cover less than 10 , 20 and 30 percent

    OpenAIRE

    J.P. Gastellu- Etcregorry

    2013-01-01

    The Indonesian spatiotemporal cloud cover distribution was quantified with the aid of GMS, Landsat and SPOT data. Iterative interactive factorial analyses grouped pixels with similar profiles into 18 classes for all land areas. For each class, statistics of Landsat and SPOT images, grouped by class, were used to verify, calibrate and improve class profiles. This led to quantified temporal profiles of probability of acquiring remotely sensed data with 10 , 20 and 30 percent cloud cover, for an...

  5. A comparison of cloud layers from ground and satellite active remote sensing at the Southern Great Plains ARM site

    Science.gov (United States)

    Zhang, Jinqiang; Xia, Xiang'ao; Chen, Hongbin

    2017-03-01

    Using the data collected over the Southern Great Plains ARM site from 2006 to 2010, the surface Active Remote Sensing of Cloud (ARSCL) and CloudSat-CALIPSO satellite (CC) retrievals of total cloud and six specified cloud types [low, mid-low (ML), high-mid-low (HML), mid, high-mid (HM) and high] were compared in terms of cloud fraction (CF), cloud-base height (CBH), cloud-top height (CTH) and cloud thickness (CT), on different temporal scales, to identify their respective advantages and limitations. Good agreement between the two methods was exhibited in the total CF. However, large discrepancies were found between the cloud distributions of the two methods at a high (240-m) vertical grid spacing. Compared to the satellites, ARSCL retrievals detected more boundary layer clouds, while they underestimated high clouds. In terms of the six specific cloud types, more low- and mid-level clouds but less HML- and high-level clouds were detected by ARSCL than by CC. In contrast, the ARSCL retrievals of ML- and HM-level clouds agreed more closely with the estimations from the CC product. Lower CBHs tended to be reported by the surface data for low-, ML- and HML-level clouds; however, higher CTHs were often recorded by the satellite product for HML-, HM- and high-level clouds. The mean CTs for low- and ML-level cloud were similar between the two products; however, the mean CTs for HML-, mid-, HM- and high-level clouds from ARSCL were smaller than those from CC.

  6. Terahertz Remote Sensing of Ice Clouds - Sensitivity on Ice Dielectric Properties

    Science.gov (United States)

    Mendrok, J.; Baron, P.; Kasai, Y.

    2007-12-01

    Initiated by current developments in terahertz sensor technology the application of instruments operating in the spectral region between 0.1 - 30 THz is considered for a number of remote sensing issues. Accounting for more than 50 percent of the outgoing longwave radiation and with the major component of cirrus radiative forcing in the far-infrared, satellite measurements in this spectral region will significantly support the determination of the radiation budget of the Earth. Furthermore, spanning the whole range of particle sizes found in tropospheric ice clouds, the Terahertz region bears the potential to complement existing methods and improve our knowlegde and understanding of those clouds. Both, determination of the Earth's radiation budget as well as retrieving ice cloud properties require appropriately accurate calculations of radiative transfer. Hence, a good knowledge of the input parameters to the radiative transfer models is needed. In particular, this includes spectrally dependent properties of the molecular as well as particulate atmospheric matter, i.e., spectroscopic parameters of the molecular absorption lines and continua as well as the dielectric properties of aerosol and cloud particle material. Due to the lack of Terahertz light source and receiver technology in the past, measurements of these parameters have been sparse and the knowledge about them is rather poor. In preparation to evaluate the feasibility of monitoring tropospheric ice clouds using passive Terahertz observations, we study the modeling uncertainties due to the unconfident knowledge of the complex refractive index of ice. We give an overview of the consistency and discrepancies, respectively, of the existing measurements and models for ice refractive index in the Terahertz region. Using calculations of particle optical properties according to Mie theory as well as the radiative transfer models Moliere and SARTre, we estimate the deviations in particle optical properties and

  7. Clouds over the summertime Sahara: an evaluation of Met Office retrievals from Meteosat Second Generation using airborne remote sensing

    Science.gov (United States)

    Kealy, John C.; Marenco, Franco; Marsham, John H.; Garcia-Carreras, Luis; Francis, Pete N.; Cooke, Michael C.; Hocking, James

    2017-05-01

    Novel methods of cloud detection are applied to airborne remote sensing observations from the unique Fennec aircraft dataset, to evaluate the Met Office-derived products on cloud properties over the Sahara based on the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) satellite. Two cloud mask configurations are considered, as well as the retrievals of cloud-top height (CTH), and these products are compared to airborne cloud remote sensing products acquired during the Fennec campaign in June 2011 and June 2012. Most detected clouds (67 % of the total) have a horizontal extent that is smaller than a SEVIRI pixel (3 km × 3 km). We show that, when partially cloud-contaminated pixels are included, a match between the SEVIRI and aircraft datasets is found in 80 ± 8 % of the pixels. Moreover, under clear skies the datasets are shown to agree for more than 90 % of the pixels. The mean cloud field, derived from the satellite cloud mask acquired during the Fennec flights, shows that areas of high surface albedo and orography are preferred sites for Saharan cloud cover, consistent with published theories. Cloud-top height retrievals however show large discrepancies over the region, which are ascribed to limiting factors such as the cloud horizontal extent, the derived effective cloud amount, and the absorption by mineral dust. The results of the CTH analysis presented here may also have further-reaching implications for the techniques employed by other satellite applications facilities across the world.

  8. Remote Sensing of Clouds using Satellites, Lidars, CLF/XLF and IR Cameras at the Pierre Auger Observatory

    Directory of Open Access Journals (Sweden)

    Chirinos J.

    2015-01-01

    Full Text Available Clouds in the field of view of the fluorescence detectors affect the detection of the extensive air showers. Several remote sensing techniques are used to detect night-time clouds over the 3000 km2 of the Pierre Auger Observatory. Four lidars at the fluorescence detector sites are performing different patterns of scans of the surrounding sky detecting clouds. Two laser facilities (CLF and XLF are shooting into the sky delivering cloud cover above them every 15 minutes. Four IR cameras detect the presence of clouds within the FOV of the fluorescence detectors every 5 minutes. A method using GOES-12 and GOES-13 satellites identifies night-time clouds twice per hour with a spatial resolution of 2.4 km by 5.5 km over the Observatory. We upload all this information into several databases to be used for the reconstruction of cosmic ray events and to find exotic events.

  9. Remote Sensing of Clouds using Satellites, Lidars, CLF/XLF and IR Cameras at the Pierre Auger Observatory

    Science.gov (United States)

    Chirinos, J.

    2015-12-01

    Clouds in the field of view of the fluorescence detectors affect the detection of the extensive air showers. Several remote sensing techniques are used to detect night-time clouds over the 3000 km2 of the Pierre Auger Observatory. Four lidars at the fluorescence detector sites are performing different patterns of scans of the surrounding sky detecting clouds. Two laser facilities (CLF and XLF) are shooting into the sky delivering cloud cover above them every 15 minutes. Four IR cameras detect the presence of clouds within the FOV of the fluorescence detectors every 5 minutes. A method using GOES-12 and GOES-13 satellites identifies night-time clouds twice per hour with a spatial resolution of 2.4 km by 5.5 km over the Observatory. We upload all this information into several databases to be used for the reconstruction of cosmic ray events and to find exotic events.

  10. A cloud detection algorithm-generating method for remote sensing data at visible to short-wave infrared wavelengths

    Science.gov (United States)

    Sun, Lin; Mi, Xueting; Wei, Jing; Wang, Jian; Tian, Xinpeng; Yu, Huiyong; Gan, Ping

    2017-02-01

    To realize highly precise and automatic cloud detection from multi-sensors, this paper proposes a cloud detection algorithm-generating (CDAG) method for remote sensing data from visible to short-wave infrared (SWIR) bands. Hyperspectral remote sensing data with high spatial resolution were collected and used as a pixel dataset of cloudy and clear skies. In this paper, multi-temporal AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data with 224 bands at visible to SWIR wavelengths and a 20 m spatial resolution were used for the dataset. Based on the pixel dataset, pixels of different types of clouds and land cover were distinguished artificially and used for the simulation of multispectral sensors. Cloud detection algorithms for the multispectral remote sensing sensors were then generated based on the spectral differences between the cloudy and clear-sky pixels distinguished previously. The possibility of assigning a pixel as cloudy was calculated based on the reliability of each method. Landsat 8 OLI (Operational Land Imager), MODIS (Moderate Resolution Imaging Spectroradiometer) Terra and Suomi NPP VIIRS (Visible/Infrared Imaging Radiometer) were used for the cloud detection test with the CDAG method, and the results from each sensor were compared with the corresponding artificial results, demonstrating an accurate detection rate of more than 85%.

  11. Remote Sensing of chlorophyll fluorescence and the impact of clouds on the retrival

    Science.gov (United States)

    Köhler, Philipp; Guanter, Luis; Frankenberg, Christian

    2013-04-01

    Remote sensing of sun-induced chlorophyll fluorescence (SIF) is a new, alternative option to gain information about terrestrial photosynthesis and CO2 assimilation on a global scale. The SIF is an electromagnetic signal emitted in the aprox. 650-800 nm spectral window by the photosynthesis apparatus, and can therefore be considered as a direct indicator of plant biochemical processes. The general approach to measure SIF from space is the evaluation of the in-filling of solar Fraunhofer lines or atmospheric absorption bands by SIF. To distinguish the SIF signal from the total incoming radiance at the sensor, which is about 100 times more intense, is a challenge and high resolution measurements are required. The high spectral resolution (approx. 0.02 nm) of the Fourier Transform Spectrometer (FTS) on-board the Greenhouse Gases Observing Satellite (GOSAT) enables such a measurement of SIF by means of the evaluation of the in-filling of solar Fraunhofer lines by SIF. The narrow wavelength band from 755 to 759 nm and around 770 nm can be used for this purpose because they are free from atmospheric absorption features, the solar radiation shows several Fraunhofer lines and the SIF values in this region are relatively high. A new SIF retrieval approach (GARLiC, for GOSAT Retrieval of cholorphyll fluorescence) will be presented in this contribution. This method is intended to simplify some of the assumptions of existing retrieval approaches without a loss in accuracy. The comparison of the GARLiC fluorescence retrievals with two state-of-the-art SIR retrieval methods such as those by Frankenberg et al. (2011) and Guanter et al. (2012) from GOSAT data shows corresponding and feasible results. In addition to the basics of SIF remote sensing, this contribution will assess the effect of clouds in the retrieval. To do this, the SIF retrieval has been coupled to a cloud optical thickness (COT) retrieval algorithm adapted to GOSAT-FTS O2A-band measurements, so that SIF and COT

  12. Retrieval algorithm of quantitative analysis of passive Fourier transform infrared (FTRD) remote sensing measurements of chemical gas cloud from measuring the transmissivity by passive remote Fourier transform infrared

    Institute of Scientific and Technical Information of China (English)

    Liu Zhi-Ming; Liu Wen-qing; Gao Ming-Guang; Tong Jing-Jing; Zhang Wian-Shu; Xu Liang; Wei Xiuai

    2008-01-01

    Passive Fourier transform infrared (FTIR) remote sensing measurement of chemical gas cloud is a vital technology.It takes an important part in many fields for the detection of released gases.The principle of concentration measurement is based on the Beer-Lambert law.Unlike the active measurement,for the passive remote sensing,in most cases,the difference between the temperature of the gas cloud and the brightness temperature of the background is usually a few kelvins.The gas cloud emission is almost equal to the background emission,thereby the emission of the gas cloud cannot be ignored.The concentration retrieval algorithm is quite different from the active measurement.In this paper,the concentration retrieval algorithm for the passive FTIR remote measurement of gas cloud is presented in detail,which involves radiative transfer model,radiometric calibration,absorption coefficient calculation,et al.The background spectrum has a broad feature,which is a slowly varying function of frequency.In this paper,the background spectrum is fitted with a polynomial by using the Levenberg-Marquardt method which is a kind of nonlinear least squares fitting algorithm.No background spectra are required.Thus,this method allows mobile,real-time and fast measurements of gas clouds.

  13. Comparing the Cloud Vertical Structure Derived from Several Methods Based on Radiosonde Profiles and Ground-based Remote Sensing Measurements

    Energy Technology Data Exchange (ETDEWEB)

    Costa-Suros, M.; Calbo, J.; Gonzalez, J. A.; Long, Charles N.

    2014-08-27

    The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, is an important characteristic in order to describe the impact of clouds in a changing climate. In this work several methods to estimate the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering number and position of cloud layers, with a ground based system which is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ on the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study these methods are applied to 125 radiosonde profiles acquired at the ARM Southern Great Plains site during all seasons of year 2009 and endorsed by GOES images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The overall agreement for the methods ranges between 44-88%; four methods produce total agreements around 85%. Further tests and improvements are applied on one of these methods. In addition, we attempt to make this method suitable for low resolution vertical profiles, which could be useful in atmospheric modeling. The total agreement, even when using low resolution profiles, can be improved up to 91% if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.

  14. Cloud Properties under Different Synoptic Circulations: Comparison of Radiosonde and Ground-Based Active Remote Sensing Measurements

    Directory of Open Access Journals (Sweden)

    Jinqiang Zhang

    2016-11-01

    Full Text Available In this study, long-term (10 years radiosonde-based cloud data are compared with the ground-based active remote sensing product under six prevailing large-scale synoptic patterns, i.e., cyclonic center (CC, weak pressure pattern (WP, the southeast bottom of cyclonic center (CB, cold front (CF, anticyclone edge (AE and anticyclone center (AC over the Southern Great Plains (SGP site. The synoptic patterns are generated by applying the self-organizing map weather classification method to the daily National Centers for Environmental Protection mean sea level pressure records from the North American Regional Reanalysis. It reveals that the large-scale synoptic circulations can strongly influence the regional cloud formation, and thereby have impact on the consistency of cloud retrievals from the radiosonde and ground-based cloud product. The total cloud cover at the SGP site is characterized by the least in AC and the most in CF. The minimum and maximum differences between the two cloud methods are 10.3% for CC and 13.3% for WP. Compared to the synoptic patterns characterized by scattered cloudy and clear skies (AE and AC, the agreement of collocated cloud boundaries between the two cloud approaches tends to be better under the synoptic patterns dominated by overcast and cloudy skies (CC, WP and CB. The rainy and windy weather conditions in CF synoptic pattern influence the consistency of the two cloud retrieval methods associated with the limited capabilities inherent to the instruments. The cloud thickness distribution from the two cloud datasets compares favorably with each other in all synoptic patterns, with relative discrepancy of ≤0.3 km.

  15. Raman lidar measurements of water vapor and aerosols during the atmospheric radiation measurement (ARM) remote clouds sensing (RCS) intensive observation period (IOP)

    Energy Technology Data Exchange (ETDEWEB)

    Melfi, S.H.; Starr, D.O`C.; Whiteman, D. [NASA Goddard Space Flight Center, Greenbelt, MD (United States)] [and others

    1996-04-01

    The first Atmospheric Radiation Measurement (ARM) remote Cloud Study (RCS) Intensive Operations Period (IOP) was held during April 1994 at the Southern Great Plains (SGP) site. This experiment was conducted to evaluate and calibrate state-of-the-art, ground based remote sensing instruments and to use the data acquired by these instruments to validate retrieval algorithms developed under the ARM program.

  16. A Cloud Computing Workflow for Scalable Integration of Remote Sensing and Social Media Data in Urban Studies

    Science.gov (United States)

    Soliman, A.; Soltani, K.; Yin, J.; Subramaniam, B.; Liu, Y.; Padmanabhan, A.; Riteau, P.; Keahey, K.; Wang, S. W.

    2015-12-01

    Urban ecosystems are unique earth environments because both their physical and social components contribute to the overall dynamics of the system. Up-to-date, remote sensing data (e.g. optical and LiDAR) allowed researchers to monitor the development of impervious surfaces however, it was not adequate to detect associated social dynamics. Geo-located social media (e.g. Twitter) provides a data source to detect population dynamics and understand the interaction of people with their physical environment. Although, integrating social media with remote sensing data has been hindered by large volumes of data and the lack of models for integrating remote sensing products with unstructured social media data. In this research work, we leveraged the NSF chameleon cloud computing platform to provide virtual clusters and elastic auto-scaling of resources that are needed for the synthesis of landuse and geo-located Twitter data. In this context, data synthesis was used to address research questions related to population dynamics in major metropolitan areas. We provide an overview of a cloud computing workflow comprised of a set of coupled scalable synthesis modules for: a) preprocessing data, which includes storage and query of heterogeneous data streams, b) spatial data integration, which matches geo-located Twitter data with user defined landuse maps based on a conceptual model of human mobility and c) visualization of urban mobility patterns. Our results demonstrate the flexibility to connect data, synthesis methods and computing resources using cloud computing, which would be otherwise very difficult for untrained scientists to setup and control. Furthermore, we demonstrate the capabilities of CyberGIS-based workflow using the case study of comparing commuting distances across major US cities from 2013 through the present. We demonstrate how our workflow will support discoveries in urban ecological studies as well as linking human and physical dimensions in environmental

  17. Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

    Science.gov (United States)

    Ehrlich, André; Bierwirth, Eike; Istomina, Larysa; Wendisch, Manfred

    2017-09-01

    The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff

  18. Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

    Directory of Open Access Journals (Sweden)

    A. Ehrlich

    2017-09-01

    Full Text Available The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow. Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C.In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S, λ2 = 1650 nm (sensitive to τ, and λ3 = 2100 nm (sensitive to reff, C are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012 were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice

  19. Volcanic eruptions, hazardous ash clouds and visualization tools for accessing real-time infrared remote sensing data

    Science.gov (United States)

    Webley, P.; Dehn, J.; Dean, K. G.; Macfarlane, S.

    2010-12-01

    Volcanic eruptions are a global hazard, affecting local infrastructure, impacting airports and hindering the aviation community, as seen in Europe during Spring 2010 from the Eyjafjallajokull eruption in Iceland. Here, we show how remote sensing data is used through web-based interfaces for monitoring volcanic activity, both ground based thermal signals and airborne ash clouds. These ‘web tools’, http://avo.images.alaska.edu/, provide timely availability of polar orbiting and geostationary data from US National Aeronautics and Space Administration, National Oceanic and Atmosphere Administration and Japanese Meteorological Agency satellites for the North Pacific (NOPAC) region. This data is used operationally by the Alaska Volcano Observatory (AVO) for monitoring volcanic activity, especially at remote volcanoes and generates ‘alarms’ of any detected volcanic activity and ash clouds. The webtools allow the remote sensing team of AVO to easily perform their twice daily monitoring shifts. The web tools also assist the National Weather Service, Alaska and Kamchatkan Volcanic Emergency Response Team, Russia in their operational duties. Users are able to detect ash clouds, measure the distance from the source, area and signal strength. Within the web tools, there are 40 x 40 km datasets centered on each volcano and a searchable database of all acquired data from 1993 until present with the ability to produce time series data per volcano. Additionally, a data center illustrates the acquired data across the NOPAC within the last 48 hours, http://avo.images.alaska.edu/tools/datacenter/. We will illustrate new visualization tools allowing users to display the satellite imagery within Google Earth/Maps, and ArcGIS Explorer both as static maps and time-animated imagery. We will show these tools in real-time as well as examples of past large volcanic eruptions. In the future, we will develop the tools to produce real-time ash retrievals, run volcanic ash dispersion

  20. CubeSat Cloud: A framework for distributed storage, processing and communication of remote sensing data on cubesat clusters

    Science.gov (United States)

    Challa, Obulapathi Nayudu

    CubeSat Cloud is a novel vision for a space based remote sensing network that includes a collection of small satellites (including CubeSats), ground stations, and a server, where a CubeSat is a miniaturized satellite with a volume of a 10x10x10 cm cube and has a weight of approximately 1 kg. The small form factor of CubeSats limits the processing and communication capabilities. Implemented and deployed CubeSats have demonstrated about 1 GHz processing speed and 9.6 kbps communication speed. A CubeSat in its current state can take hours to process a 100 MB image and more than a day to downlink the same, which prohibits remote sensing, considering the limitations in ground station access time for a CubeSat. This dissertation designs an architecture and supporting networking protocols to create CubeSat Cloud, a distributed processing, storage and communication framework that will enable faster execution of remote sensing missions on CubeSat clusters. The core components of CubeSat Cloud are CubeSat Distributed File System, CubeSat MapMerge, and CubeSat Torrent. The CubeSat Distributed File System has been created for distributing of large amounts of data among the satellites in the cluster. Once the data is distributed, CubeSat MapReduce has been created to process the data in parallel, thereby reducing the processing load for each CubeSat. Finally, CubeSat Torrent has been created to downlink the data at each CubeSat to a distributed set of ground stations, enabling faster asynchronous downloads. Ground stations send the downlinked data to the server to reconstruct the original image and store it for later retrieval. Analysis of the proposed CubeSat Cloud architecture was performed using a custom-designed simulator, called CubeNet and an emulation test bed using Raspberry Pi devices. Results show that for cluster sizes ranging from 5 to 25 small satellites, faster download speeds up to 4 to 22 times faster - can be achieved when using CubeSat Cloud, compared to a

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

    Science.gov (United States)

    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.

  2. Climatology of clouds and precipitation over East Antarctica using ground-based remote sensing at the Princess Elizabeth station

    Science.gov (United States)

    Souverijns, Niels; Gossart, Alexandra; Gorodetskaya, Irina; Lhermitte, Stef; Van Tricht, Kristof; Mangold, Alexander; Laffineur, Quentin; Van Lipzig, Nicole

    2016-04-01

    The surface mass balance of the Antarctic ice sheet is highly dependent on the interaction between clouds and precipitation. Our understanding of these processes is challenged by the limited availability of observations over the area and problems in Antarctic climate simulations by state-of-the-art climate models. Improvements are needed in this field, as the Antarctic ice sheet is expected to become a dominant contributor to sea level rise in the 21st century. In 2010, an observational site was established at the Princess Elisabeth (PE) Antarctic station. PE is located in the escarpment area of Dronning Maud Land, East Antarctica (72°S, 23°E). The instruments consist of several ground-based remote sensing instruments: a ceilometer (measuring cloud-base height and vertical structure), a 24-GHz Micro Rain Radar (MRR; providing vertical profiles of radar effective reflectivity and Doppler velocity), and a pyrometer (measuring effective cloud base temperature). An automatic weather station provides info on boundary-layer meteorology (temperature, wind speed and direction, humidity, pressure), as well as broadband radiative fluxes and snow height changes. This set of instruments can be used to infer the role of clouds in the Antarctic climate system, their interaction with radiation and their impact on precipitation. Cloud and precipitation characteristics are derived from 5-year-long measurement series, which is unprecedented for the Antarctic region. Here, we present an overview of the cloud and precipitation climatology. Statistics on cloud occurrence are calculated on annual / seasonal basis and a distinction between liquid / mixed phase and ice clouds is made. One can discriminate between liquid-bearing and ice-only clouds by investigating the ceilometer attenuated backscatter, since liquid phase clouds have a much higher signal. Furthermore, by using pyrometer measurements, we are able to identify the range of temperatures at which liquid / ice clouds are

  3. Introduction to remote sensing

    CERN Document Server

    Cracknell, Arthur P

    2007-01-01

    Addressing the need for updated information in remote sensing, Introduction to Remote Sensing, Second Edition provides a full and authoritative introduction for scientists who need to know the scope, potential, and limitations in the field. The authors discuss the physical principles of common remote sensing systems and examine the processing, interpretation, and applications of data. This new edition features updated and expanded material, including greater coverage of applications from across earth, environmental, atmospheric, and oceanographic sciences. Illustrated with remotely sensed colo

  4. Remote Cloud Sensing Intensive Observation Period (RCS-IOP) millimeter-wave radar calibration and data intercomparison

    Energy Technology Data Exchange (ETDEWEB)

    Sekelsky, S.M.; Firda, J.M.; McIntosh, R.E. [Univ. of Massachusetts, Amherst, MA (United States)] [and others

    1996-04-01

    During April 1994, the University of Massachusetts (UMass) and the Pennsylvania State University (Penn State) fielded two millimeter-wave atmospheric radars in the Atmospheric Radiation Measurement Remote Cloud Sensing Intensive Operation Period (RCS-IOP) experiment. The UMass Cloud Profiling Radar System (CPRS) operates simultaneously at 33.12 GHz and 94.92 GHz through a single antenna. The Penn State radar operates at 93.95 GHz and has separate transmitting and receiving antennas. The two systems were separated by approximately 75 meters and simultaneously observed a variety of cloud types at verticle incidence over the course of the experiment. This abstract presents some initial results from our calibration efforts. An absolute calibration of the UMass radar was made from radar measurements of a trihedral corner reflector, which has a known radar cross-section. A relative calibration of between the Penn State and UMass radars is made from the statistical comparison of zenith pointing measurements of low altitude liquid clouds. Attenuation is removed with the aid of radiosonde data, and the difference in the calibration between the UMass and Penn State radars is determined by comparing the ratio of 94-GHz and 95-GHz reflectivity values to a model that accounts for parallax effects of the two antennas used in the Penn State system.

  5. Farm Management Support on Cloud Computing Platform: A System for Cropland Monitoring Using Multi-Source Remotely Sensed Data

    Science.gov (United States)

    Coburn, C. A.; Qin, Y.; Zhang, J.; Staenz, K.

    2015-12-01

    Food security is one of the most pressing issues facing humankind. Recent estimates predict that over one billion people don't have enough food to meet their basic nutritional needs. The ability of remote sensing tools to monitor and model crop production and predict crop yield is essential for providing governments and farmers with vital information to ensure food security. Google Earth Engine (GEE) is a cloud computing platform, which integrates storage and processing algorithms for massive remotely sensed imagery and vector data sets. By providing the capabilities of storing and analyzing the data sets, it provides an ideal platform for the development of advanced analytic tools for extracting key variables used in regional and national food security systems. With the high performance computing and storing capabilities of GEE, a cloud-computing based system for near real-time crop land monitoring was developed using multi-source remotely sensed data over large areas. The system is able to process and visualize the MODIS time series NDVI profile in conjunction with Landsat 8 image segmentation for crop monitoring. With multi-temporal Landsat 8 imagery, the crop fields are extracted using the image segmentation algorithm developed by Baatz et al.[1]. The MODIS time series NDVI data are modeled by TIMESAT [2], a software package developed for analyzing time series of satellite data. The seasonality of MODIS time series data, for example, the start date of the growing season, length of growing season, and NDVI peak at a field-level are obtained for evaluating the crop-growth conditions. The system fuses MODIS time series NDVI data and Landsat 8 imagery to provide information of near real-time crop-growth conditions through the visualization of MODIS NDVI time series and comparison of multi-year NDVI profiles. Stakeholders, i.e., farmers and government officers, are able to obtain crop-growth information at crop-field level online. This unique utilization of GEE in

  6. Turning remote sensing to cloud services: Technical research and experiment%遥感云服务平台技术研究与实验

    Institute of Scientific and Technical Information of China (English)

    任伏虎; 王晋年

    2012-01-01

    遥感云服务是基于云计算技术,整合各种遥感信息和技术资源,通过互联网以按需共享的方式提供的遥感应用服务.本文在分析遥感云服务的基本模式和技术特点的基础上,阐述了遥感云服务的技术体系及关键技术,包括遥感数据云存储、遥感数据云处理、遥感应用云服务以及遥感数据云安全技术等,设计了遥感云服务平台总体架构和功能模块,并介绍了作者团队基于云计算技术研发的遥感云服务平台原型系统.该系统支持用户根据业务选择遥感数据和应用软件,在云服务平台自动部署的虚拟机上进行在线使用.实验表明,遥感云服务平台可以汇聚来自不同服务商的遥感信息、应用软件和计算资源,为用户提供一体化的按需应用服务,对于遥感技术的普及应用和产业化发展具有重要意义.%Remote sensing cloud services are the remote sensing application services provided through a network as a way of on-demand sharing of integrated remote sensing information and technological resources based-on cloud computing. Up on the analysis of service models and technical requirements, the author highlights the key technologies of remote sensing cloud services, including remote sensing data cloud storage, processing, application and security. We propose an architecture and functional design of the remote sensing cloud service platform and introduce a prototype developed by our R&D team. This remote sensing cloud service prototype allows users to choose required remote sensing data and software, and automatically deploys them to a virtual computer that users can access through Internet to perform their remote sensing data processing and application. Experiments show that the remote sensing cloud service platform can gather remote sensing information, software and computing resources from different providers, and provides them for sharing on user's demand. Such a remote sensing service

  7. Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors

    Directory of Open Access Journals (Sweden)

    Irfan Mehmood

    2014-09-01

    Full Text Available Wireless capsule endoscopy (WCE has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.

  8. Several thoughts for using new satellite remote sensing and global modeling for aerosol and cloud climate studies

    Science.gov (United States)

    Nakajima, Teruyuki; Hashimoto, Makiko; Takenaka, Hideaki; Goto, Daisuke; Oikawa, Eiji; Suzuki, Kentaroh; Uchida, Junya; Dai, Tie; Shi, Chong

    2017-04-01

    The rapid growth of satellite remote sensing technologies in the last two decades widened the utility of satellite data for understanding climate impacts of aerosols and clouds. The climate modeling community also has received the benefit of the earth observation and nowadays closed-collaboration of the two communities make us possible to challenge various applications for societal problems, such as for global warming and global-scale air pollution and others. I like to give several thoughts of new algorithm developments, model use of satellite data for climate impact studies and societal applications related with aerosols and clouds. Important issues are 1) Better aerosol detection and solar energy application using expanded observation ability of the third generation geostationary satellites, i.e. Himawari-8, GOES-R and future MTG, 2) Various observation functions by directional, polarimetric, and high resolution near-UV band by MISR, POLDER&PARASOL, GOSAT/CAI and future GOSAT2/CAI2, 3) Various applications of general purpose-imagers, MODIS, VIIRS and future GCOM-C/SGLI, and 4) Climate studies of aerosol and cloud stratification and convection with active and passive sensors, especially climate impact of BC aerosols using CLOUDSAT&CALIPSO and future Earth Explorer/EarthCARE.

  9. NARVAL North - Remote Sensing of Postfrontal Convective Clouds and Precipitation over the North Atlantic with the Research Aircraft HALO

    Science.gov (United States)

    Klepp, Christian; Ament, Felix; Bakan, Stephan; Crewell, Susanne; Hagen, Martin; Hirsch, Lutz; Jansen, Friedhelm; Konow, Heike; Mech, Mario; Pfeilsticker, Klaus; Schäfler, Andreas; Stevens, Bjorn

    2014-05-01

    The new German research aircraft HALO (High Altitude and Long Range Research Aircraft) became recently available for measurement flights in atmospheric research. It's capacity of measuring from a high altitude vertical profiles of all components of atmospheric water - like vapor, liquid and ice, in both cloud and precipitation forms, as well as the aerosol particles upon which cloud droplets form - makes it a unique research platform. The aircraft, equipped with advanced radiometers, radar and lidar technology, the HALO Microwave Package (HAMP), is an initiative by German climate and environmental research institutions and is operated by the German Aerospace Center (DLR). One of the first major missions to exploit the capabilities of HALO was conducted for the NARVAL project (Next-generation Aircraft Remote-Sensing for Validation Studies) during January 2014. After studying subtropical clouds one month before in the first NARVAL phase, the interest of NARVAL North focused on the study of cold air convection and precipitation in the form of rain and snow. Based at Keflavik airport (Iceland), several flights were conducted to examine the specific small-scale precipitation structures behind the backsides of cold fronts over the North Atlantic. This should help to narrow the gap in the understanding of substantial differences between satellite observations and model calculations in such situations. First data analysis of these measurements indicate promising results. The poster will describe the HALO instrument packages as well as the collected observations during the campaign and will present preliminary scientific findings.

  10. Remote Sensing of Aerosols from Satellites: Why Has It Been Do Difficult to Quantify Aerosol-Cloud Interactions for Climate Assessment, and How Can We Make Progress?

    Science.gov (United States)

    Kahn, Ralph A.

    2015-01-01

    The organizers of the National Academy of Sciences Arthur M. Sackler Colloquia Series on Improving Our Fundamental Understanding of the Role of Aerosol-Cloud Interactions in the Climate System would like to post Ralph Kahn's presentation entitled Remote Sensing of Aerosols from Satellites: Why has it been so difficult to quantify aerosol-cloud interactions for climate assessment, and how can we make progress? to their public website.

  11. The interpretation of remotely sensed cloud properties from a model parameterization perspective

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-09-01

    The goals of ISCCP and FIRE are, broadly speaking, to provide methods for the retrieval of cloud properties from satellites, and to improve cloud radiation models and the parameterization of clouds in GCMs. This study suggests a direction for GCM cloud parameterizations based on analysis of Landsat and ISCCP satellite data. For low level single layer clouds it is found that the mean retrieved liquid water pathe in cloudy pixels is essentially invariant to the cloud fraction, at least in the range 0.2 - 0.8. This result is very important since it allows the cloud fraction to be estimated if the mean liquid water path of cloud in a general circulation model gridcell is known. 3 figs.

  12. Remote Sensing of Cloud Top Heights Using the Research Scanning Polarimeter

    Science.gov (United States)

    Sinclair, Kenneth; van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John; Wasilewski, Andrzej

    2015-01-01

    Clouds cover roughly two thirds of the globe and act as an important regulator of Earth's radiation budget. Of these, multilayered clouds occur about half of the time and are predominantly two-layered. Changes in cloud top height (CTH) have been predicted by models to have a globally averaged positive feedback, however observational changes in CTH have shown uncertain results. Additional CTH observations are necessary to better and quantify the effect. Improved CTH observations will also allow for improved sub-grid parameterizations in large-scale models and accurate CTH information is important when studying variations in freezing point and cloud microphysics. NASA's airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. RSP scans along the aircraft track and obtains measurements at 152 viewing angles at any aircraft location. The approach presented here aggregates measurements from multiple scans to a single location at cloud altitude using a correlation function designed to identify the location-distinct features in each scan. During NASAs SEAC4RS air campaign, the RSP was mounted on the ER-2 aircraft along with the Cloud Physics Lidar (CPL), which made simultaneous measurements of CTH. The RSPs unique method of determining CTH is presented. The capabilities of using single and combinations of channels within the approach are investigated. A detailed comparison of RSP retrieved CTHs with those of CPL reveal the accuracy of the approach. Results indicate a strong ability for the RSP to accurately identify cloud heights. Interestingly, the analysis reveals an ability for the approach to identify multiple cloud layers in a single scene and estimate the CTH of each layer. Capabilities and limitations of identifying single and multiple cloud layers heights are explored. Special focus is given to sources of error in the method including optically thin clouds, physically thick clouds, multi

  13. Optical remote sensing

    CERN Document Server

    Prasad, Saurabh; Chanussot, Jocelyn

    2011-01-01

    Optical remote sensing relies on exploiting multispectral and hyper spectral imagery possessing high spatial and spectral resolutions respectively. These modalities, although useful for most remote sensing tasks, often present challenges that must be addressed for their effective exploitation. This book presents current state-of-the-art algorithms that address the following key challenges encountered in representation and analysis of such optical remotely sensed data: challenges in pre-processing images, storing and representing high dimensional data, fusing different sensor modalities, patter

  14. REMOTE SENSING IN OCEANOGRAPHY.

    Science.gov (United States)

    remote sensing from satellites. Sensing of oceanographic variables from aircraft began with the photographing of waves and ice. Since then remote measurement of sea surface temperatures and wave heights have become routine. Sensors tested for oceanographic applications include multi-band color cameras, radar scatterometers, infrared spectrometers and scanners, passive microwave radiometers, and radar imagers. Remote sensing has found its greatest application in providing rapid coverage of large oceanographic areas for synoptic and analysis and

  15. The actuality and progress of whole sky infrared cloud remote sensing techniques

    Institute of Scientific and Technical Information of China (English)

    ZHANG; Ting; LIU; Lei; GAO; Taichang; HU; Shuai

    2015-01-01

    Clouds are crucial regulators of both weather and climate. Properties such as the amount,type,height,distribution and movement of them have an impact on the earth’s radiation budget and the hydrological cycle,thus cloud observation is very important. The disadvantages of zenith pointing measuring instruments and whole sky visible imagers limit the application of them.A summary of the actuality and application of ground-based whole sky infrared cloud measuring instruments and analyses of the techniques of radiometric calibrations,removal of atmospheric emission and calculation of cloud cover,amount,type are conducted to promote the automatically observation of the whole sky. Fully considering whole sky infrared cloud sounding theories,techniques and applications,there are still a lot of studies on improving the properties of instruments,enhancing the techniques of cloud base height measurements and establishing instrumental cloud classification criterion before actual operations.

  16. Optical Remote Sensing Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — The Optical Remote Sensing Laboratory deploys rugged, cutting-edge electro-optical instrumentation for the collection of various event signatures, with expertise in...

  17. Cloud parameters using Ground Based Remote Sensing Systems and Satellites over urban coastal area

    Science.gov (United States)

    Han, Z. T.; Gross, B.; Moshary, F.; Wu, Y.; Ahmed, S. A.

    2013-12-01

    Determining cloud radiative and microphysical properties are very important as a means to assess their effect on earths energy balance. While MODIS and GOES have been used for estimating cloud properties, assessing cloud properties directly has been difficult due the lack of consistent ground based sensor measurements except in such established places such as the ARM site in Oklahoma. However, it is known that significant aerosol seeding from urban and/or maritime sources can modify cloud properties such as effective radius and cloud optical depth and therefore evaluation of satellite retrievals in such a unique area offers novel opportunities to assess the potential of satellite retrievals to distinguish these mechanisms In our study, we used a multi-filter rotating shadow band radiometer (MFRSR) and micro wave radiometer (MWR) to retrieve the cloud optical depth and cloud droplets effective radius . In particular, we make a statistical study during summer 2013 where water phase clouds dominate and assess the accuracy of both MODIS and GOES satellite cloud products including LWP, COD and Reff. Most importantly, we assess performance against satellite observing geometries. Much like previous studies at the ARM site, we observe significant biases in the effective radius when the solar zenith angle is too large. In addition, we show that biases are also sensitive to the LWP limiting such measurement s in assessing potential aerosol-cloud signatures Finally, we discuss preliminary aerosol-cloud interactions from our ground system where local lidar is used to assess aerosols below clouds and explore the Aerosol Cloud Index.

  18. Remote Sensing of Multiple Cloud Layer Heights Using Multi-Angular Measurements

    Science.gov (United States)

    Sinclair, Kenneth; Van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John; Wasilewski, Andrzej; Mcgill, Matthew

    2017-01-01

    Cloud top height (CTH) affects the radiative properties of clouds. Improved CTH observations will allow for improved parameterizations in large-scale models and accurate information on CTH is also important when studying variations in freezing point and cloud microphysics. NASAs airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. For the determination of CTH, a set of consecutive nadir reflectances is selected and the cross-correlations between this set and co-located sets at other viewing angles are calculated for a range of assumed cloud top heights, yielding a correlation profile. Under the assumption that cloud reflectances are isotropic, local peaks in the correlation profile indicate cloud layers. This technique can be applied to every RSP footprint and we demonstrate that detection of multiple peaks in the correlation profile allow retrieval of heights of multiple cloud layers within single RSP footprints. This paper provides an in-depth description of the architecture and performance of the RSPs CTH retrieval technique using data obtained during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC(exp. 4)RS) campaign. RSP retrieved cloud heights are evaluated using collocated data from the Cloud Physics Lidar (CPL). The method's accuracy associated with the magnitude of correlation, optical thickness, cloud thickness and cloud height are explored. The technique is applied to measurements at a wavelength of 670 nm and 1880 nm and their combination. The 1880-nm band is virtually insensitive to the lower troposphere due to strong water vapor absorption.

  19. Remote sensing of cloud droplet size distributions in DC3 with the UMBC-LACO Rainbow Polarimetric Imager (RPI)

    Science.gov (United States)

    Buczkowski, S.; Martins, J.; Fernandez-Borda, R.; Cieslak, D.; Hall, J.

    2013-12-01

    The UMBC Rainbow Polarimetric Imager is a small form factor VIS imaging polarimeter suitable for use on a number of platforms. An optical system based on a Phillips prism with three Bayer filter color detectors, each detecting a separate polarization state, allows simultaneous detection of polarization and spectral information. A Mueller matrix-like calibration scheme corrects for polarization artifacts in the optical train and allows retrieval of the polarization state of incoming light to better than 0.5%. Coupled with wide field of view optics (~90°), RPI can capture images of cloudbows over a wide range of aircraft headings and solar zenith angles for retrieval of cloud droplet size distribution (DSD) parameters. In May-June 2012, RPI was flown in a nadir port on the NASA DC-8 during the DC3 field campaign. We will show examples of cloudbow DSD parameter retrievals from the campaign to demonstrate the efficacy of such a system to terrestrial atmospheric remote sensing. RPI image from DC3 06/15/2012 flight. Left panel is raw image from the RPI 90° camera. Middle panel is Stokes 'q' parameter retrieved from full three camera dataset. Right panel is a horizontal cut in 'q' through the glory. Both middle and right panels clearly show cloudbow features which can be fit to infer cloud DSD parameters.

  20. Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm

    Directory of Open Access Journals (Sweden)

    Mengzhao Yang

    2017-07-01

    Full Text Available The rapid development of remote sensing (RS technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

  1. Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm.

    Science.gov (United States)

    Yang, Mengzhao; Song, Wei; Mei, Haibin

    2017-07-23

    The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

  2. 卫星遥感技术在火山灰云监测中的应用%APPLICATION OF SATELLITE REMOTE SENSING IN VOLCANIC ASH CLOUD MONITORING

    Institute of Scientific and Technical Information of China (English)

    尹京苑; 沈迪; 李成范

    2013-01-01

    A large volcanic eruption can produce large amounts of volcanic ash,water vapor and heat,and form the volcanic ash cloud.The volcanic ash cloud is mainly composed of volcanic ash debris in diameter less than 2mm and gases including SO2,H2S,CO2,the mixture of the two can form acidic aerosols which can stay in the atmosphere for a long time.It not only destructs the balance of earth's surface solar radiation and causes the depletion of the ozone layer,the greenhouse effect,air pollution,acid rain,anomalies of air temperature and precipitation,and other major global climate and environmental changes,but also damages and corrodes the structure of an aircraft,reduces the visibility and jams the radio communication system.The most serious problem is that the volcanic ash debris particles are capable of cooling and adhering to the aircraft engine blades after high-temperature melting,resulting in the flameout of aircraft engine.Under the background of globalization and the boom of air-transport industry,the volcanic ash cloud is a serious threat to aviation safety.Remote sensing technology can quickly and accurately obtain the information of the surface's and the atmosphere's changes,therefore it is playing an important role in monitoring volcanic activity.In recent years,with the advancement of sensor technology,the thermal infrared remote sensing technology has become an important means of monitoring the volcanic ash cloud.Currently,there have been a variety of remote sensors for volcanic ash cloud monitoring.Meanwhile,based on that,a series of volcanic ash cloud monitoring algorithms have also been developed for different remote sensors.However,most of the volcanic ash cloud monitoring algorithms have limitations of a low accuracy and a narrow scope.This paper tries to conduct a more comprehensive overview of the different types of remote sensors and the different algorithms for volcanic ash cloud monitoring.First,the damage of volcanic ash cloud to the natural

  3. Analysis of the Interaction and Transport of Aerosols with Cloud or Fog in East Asia from AERONET and Satellite Remote Sensing: 2012 DRAGON Campaigns and Climatological Data

    Science.gov (United States)

    Eck, T. F.; Holben, B. N.; Reid, J. S.; Lynch, P.; Schafer, J.; Giles, D. M.; Kim, J.; Kim, Y. J.; Sano, I.; Arola, A. T.; Munchak, L. A.; O'Neill, N. T.; Lyapustin, A.; Sayer, A. M.; Hsu, N. Y. C.; Randles, C. A.; da Silva, A. M., Jr.; Govindaraju, R.; Hyer, E. J.; Pickering, K. E.; Crawford, J. H.; Sinyuk, A.; Smirnov, A.

    2015-12-01

    Ground-based remote sensing observations from Aerosol Robotic Network (AERONET) sun-sky radiometers have recently shown several instances where cloud-aerosol interaction had resulted in modification of aerosol properties and/or in difficulty identifying some major pollution transport events due to aerosols being imbedded in cloud systems. Major Distributed Regional Aerosol Gridded Observation Networks (DRAGON) field campaigns involving multiple AERONET sites in Japan and South Korea during Spring of 2012 have yielded observations of aerosol transport associated with clouds and/or aerosol properties modification as a result of fog interaction. Analysis of data from the Korean and Japan DRAGON campaigns shows that major fine-mode aerosol transport events are sometimes associated with extensive cloud cover and that cloud-screening of observations often filter out significant pollution aerosol transport events. The Spectral De-convolution Algorithm (SDA) algorithm was utilized to isolate and analyze the fine-mode aerosol optical depth (AODf) signal from AERONET data for these cases of persistent and extensive cloud cover. Satellite retrievals of AOD from MODIS sensors (from Dark Target, Deep Blue and MAIAC algorithms) were also investigated to assess the issue of detectability of high AOD events associated with high cloud fraction. Underestimation of fine mode AOD by the Navy Aerosol Analysis and Prediction System (NAAPS) and by the NASA Modern-Era Retrospective Analysis For Research And Applications Aerosol Re-analysis (MERRAaero) models at very high AOD at sites in China and Korea was observed, especially for observations that are cloud screened by AERONET (Level 2 data). Additionally, multi-year monitoring at several AERONET sites are examined for climatological statistics of cloud screening of fine mode aerosol events. Aerosol that has been affected by clouds or the near-cloud environment may be more prevalent than AERONET data suggest due to inherent difficulty in

  4. Cloud properties retrieved from infrared sounders and their analysis in synergy with active remote sensing

    Science.gov (United States)

    Feofilov, Artem; Stubenrauch, Claudia; Armante, Raymond

    2014-05-01

    Clouds play an important role in the energy budget of the planet: optically thick clouds reflect the incoming solar radiation leading to cooling of the Earth while thinner clouds act as 'greenhouse films' preventing escape of the Earth's infrared radiation to space. Satellite observations provide a continuous survey of clouds over the whole globe and IR sounders have been observing our planet since 1979. The spectral resolution has strongly improved from the TIROS-N Operational Vertical Sounders (TOVS) onboard the NOAA polar satellites to the Atmospheric InfraRed Sounder (AIRS) onboard Aqua (since 2002) and to the InfraRed Atmospheric Sounding Interferometers (IASI) on board the METOP (since 2006). Their spectral resolution along the CO2 absorption band makes IR sounders most sensitive to cirrus, day and night. In addition, they provide atmospheric temperature and water vapour vertical distribution, surface temperature, and dust aerosol properties. The LMD IR sounder cloud property retrievals are based on a weighted Ξ2 method. Once the cloud physical properties (cloud pressure and IR emissivity) are retrieved, cirrus bulk microphysical properties (De and IWP) are determined by investigating their spectral emissivity difference between 8 and 12 μm. The AIRS instrument is a part of the A-Train constellation, which also includes two active sounders, the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar and the CloudSat radar, providing the vertical structure of the clouds. The IASI observations with their improved spectral and, therefore, vertical resolution complement the AIRS observations in the diurnal cycle. In addition to satellite data, we use temperature, water vapor, and wind distributions from the ERA Interim reanalysis to better assess the environmental conditions for the clouds. The analysis of the joint dataset helps to (1) extend the quantitative and global characterization of cloud properties into a statistical model of

  5. Cloud tolerance of remote sensing technologies to measure land surface temperature

    Science.gov (United States)

    Conventional means to estimate land surface temperature (LST) from space relies on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave (MW) obse...

  6. Remote Sensing of Clouds And Precipitation: Event-Based Characterization, Life Cycle Evolution, and Aerosol Influences

    Science.gov (United States)

    Esmaili, Rebekah Bradley

    Global climate models, numerical weather prediction, and flood models rely on accurate satellite precipitation products, which are the only datasets that are continuous in time and space across the globe. While there are more earth observing satellites than ever before, gaps in precipitation retrievals exist due to sensor and orbital limitations of low-earth (LEO) satellites, which are overcome by merging data from different sensors in satellite precipitation products (SPPs). Using cloud tracking at higher resolutions than the spatio-temporal scales of LEO satellites, this thesis examines how clouds typically form in the atmosphere, the rate that cloud size and temperature evolve over the life cycle, and the time of day that cloud development take place. This thesis found that cloud evolution was non-linear, which disagrees with the linear interpolation schemes used in SPPs. Longer lasting clouds tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lasting clouds. Over the ocean, longer lasting clouds were found to occur more frequently at night, while shorter lasting clouds were more common during the daytime. This thesis also examines whether large-scale Saharan dust outbreaks can impact the trajectories and intensity of cloud clusters in the tropical Atlantic, which is predicted by modeling studies. The presented results show that proximity to Saharan dust outbreaks shifts Atlantic cloud development northward and intense storms becoming more common, whereas on days with low dust loading small-scale, warmer clouds are more common. A simplified view of cloud evolution in merged rainfall retrievals is a possible source of errors, which can propagate into higher level analysis. This thesis investigates the difference in the intensity, duration, and frequency of precipitation in IMERG, a next-generation satellite precipitation product with ground radar observations over the

  7. Remote sensing of multiple cloud layer heights using multi-angular measurements

    Science.gov (United States)

    Sinclair, Kenneth; van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John; Wasilewski, Andrzej; McGill, Matthew

    2017-06-01

    Cloud top height (CTH) affects the radiative properties of clouds. Improved CTH observations will allow for improved parameterizations in large-scale models and accurate information on CTH is also important when studying variations in freezing point and cloud microphysics. NASA's airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. For the determination of CTH, a set of consecutive nadir reflectances is selected and the cross correlations between this set and collocated sets at other viewing angles are calculated for a range of assumed cloud top heights, yielding a correlation profile. Under the assumption that cloud reflectances are isotropic, local peaks in the correlation profile indicate cloud layers. This technique can be applied to every RSP footprint and we demonstrate that detection of multiple peaks in the correlation profile allows retrieval of heights of multiple cloud layers within single RSP footprints. This paper provides an in-depth description of the architecture and performance of the RSP's CTH retrieval technique using data obtained during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign. RSP-retrieved cloud heights are evaluated using collocated data from the Cloud Physics Lidar (CPL). The method's accuracy associated with the magnitude of correlation, optical thickness, cloud thickness and cloud height are explored. The technique is applied to measurements at a wavelength of 670 and 1880 nm and their combination. The 1880 nm band is virtually insensitive to the lower troposphere due to strong water vapor absorption. It is found that each band is well suitable for retrieving heights of cloud layers with optical thicknesses above about 0.1 and that RSP cloud layer height retrievals more accurately correspond to CPL cloud middle than cloud top. It is also found that the 1880 nm band yields the most

  8. Investigating mixed phase clouds using a synergy of ground based remote sensing measurements

    Science.gov (United States)

    Gierens, Rosa; Kneifel, Stefan; Löhnert, Ulrich

    2017-04-01

    Low level mixed phase clouds occur frequently in the Arctic, and can persist from hours to several days. However, the processes that lead to the commonality and persistence of these clouds are not well understood. The aim of our work is to get a more detailed understanding of the dynamics of and the processes in Arctic mixed phase clouds using a combination of instruments operating at the AWIPEV station in Svalbard. In addition, an aircraft campaign collecting in situ measurements inside mixed phase clouds above the station is planned for May-June 2017. The in situ data will be used for developing and validating retrievals for microphysical properties from Doppler cloud radar measurements. Once observational data for cloud properties is obtained, it can be used for evaluating model performance, for studies combining modeling and observational approaches, and eventually lead to developing model parameterizations of mixed phase microphysics. To describe the low-level mixed phase clouds, and the atmospheric conditions in which they occur, we present a case study of a persistent mixed phase cloud observed above the AWIPEV station. In the frame of the Arctic Amplification: Climate Relevant Atmospheric and Surface Processes and Feedback Mechanisms ((AC)3) -project, a millimeter wavelength cloud radar was installed at the site in June 2016. The high vertical (4 m in the lowest layer) and temporal (2.5 sec) resolution allows for a detailed description of the structure of the cloud. In addition to radar reflectivity and mean vertical velocity, we also utilize the higher moments of the Doppler spectra, such as skewness and kurtosis. To supplement the radar measurements, a ceilometer is used to detect liquid layers inside the cloud. Liquid water path and integrated water vapor are estimated using a microwave radiometer, which together with soundings can also provide temperature and humidity profiles in the lower troposphere. Moreover, a three-dimensional wind field is be

  9. Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms

    Directory of Open Access Journals (Sweden)

    U. Hamann

    2014-01-01

    Full Text Available The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH – a crucial parameter to estimate the thermal cloud radiative forcing – can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI onboard Meteosat Second Generation (MSG. In the first part we compare the ten SEVIRI cloud top pressure (CTP datasets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas good agreement is found for the cores of the deep convective system having a high optical depth. Furthermore, a good agreement between the algorithms is observed for trade wind cumulus and marine stratocumulus clouds. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP and Cloud Profiling Radar (CPR instruments. It is important to note that the different measurement techniques cause differences in the retrieved CHT data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted signal. Therefore some systematic diffrences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the

  10. Observations of cloud liquid water path over oceans: Optical and microwave remote sensing methods

    Science.gov (United States)

    Lin, Bing; Rossow, William B.

    1994-01-01

    Published estimates of cloud liquid water path (LWP) from satellite-measured microwave radiation show little agreement, even about the relative magnitudes of LWP in the tropics and midlatitudes. To understand these differences and to obtain more reliable estimate, optical and microwave LWP retrieval methods are compared using the International Satellite Cloud Climatology Project (ISCCP) and special sensor microwave/imager (SSM/I) data. Errors in microwave LWP retrieval associated with uncertainties in surface, atmosphere, and cloud properties are assessed. Sea surface temperature may not produce great LWP errors, if accurate contemporaneous measurements are used in the retrieval. An uncertainty of estimated near-surface wind speed as high as 2 m/s produces uncertainty in LWP of about 5 mg/sq cm. Cloud liquid water temperature has only a small effect on LWP retrievals (rms errors less than 2 mg/sq cm), if errors in the temperature are less than 5 C; however, such errors can produce spurious variations of LWP with latitude and season. Errors in atmospheric column water vapor (CWV) are strongly coupled with errors in LWP (for some retrieval methods) causing errors as large as 30 mg/sq cm. Because microwave radiation is much less sensitive to clouds with small LWP (less than 7 mg/sq cm) than visible wavelength radiation, the microwave results are very sensitive to the process used to separate clear and cloudy conditions. Different cloud detection sensitivities in different microwave retrieval methods bias estimated LWP values. Comparing ISCCP and SSM/I LWPs, we find that the two estimated values are consistent in global, zonal, and regional means for warm, nonprecipitating clouds, which have average LWP values of about 5 mg/sq cm and occur much more frequently than precipitating clouds. Ice water path (IWP) can be roughly estimated from the differences between ISCCP total water path and SSM/I LWP for cold, nonprecipitating clouds. IWP in the winter hemisphere is about

  11. Hyperspectral remote sensing

    CERN Document Server

    Eismann, Michael

    2012-01-01

    Hyperspectral remote sensing is an emerging, multidisciplinary field with diverse applications that builds on the principles of material spectroscopy, radiative transfer, imaging spectrometry, and hyperspectral data processing. This book provides a holistic treatment that captures its multidisciplinary nature, emphasizing the physical principles of hyperspectral remote sensing.

  12. Semi-Discrete Wavelet Transforms of Remote Sensing Data Reveal Long-Range Multifractal Correlations in Cloud Structure

    Science.gov (United States)

    Petrov, N. P.; Davis, A. B.

    2001-12-01

    Semi-discrete wavelet transforms are discrete in scale, as in Mallat's multi-resolution analysis, but continuous in position. The number of coefficients and algorithmic complexity then grows only as NlogN where N is the number of points (pixels) in the time-series (image). The redundancy of this representation at each scale has been exploited in denoising and data compression applications but we see it here as an asset when cumulating spatial statistics. Following Arnéodo, the wavelets are normalized in such a way that the scaling exponents of the moments of the coefficients are the same as for structure functions at all orders, at least in nonstationary/stationary-increment signals. We apply 1D and 2D semi-discrete transforms to remote sensing data on cloud structure from a variety of sources: NASA's MODerate Imaging Spectroradiometer (MODIS) on Terra and Thematic Mapper (TM) on LandSat; high-resolution cloud scenes from DOE's Multispectral Thermal Imager (MTI); and an upward-looking mm-radar at one of DOE's climate observation sites supporting the Atmospheric Radiation Measurement (ARM) Program. We show that the scale-dependence of the variance of the wavelet coefficients is always a better discriminator of transition from stationary to nonstationary behavior than conventional methods based on auto-correlation analysis, 2nd-order structure function (a.k.a. the semi-variogram), or spectral analysis. Examples of stationary behavior are (delta-correlated) instrumental noise and large-scale decorrelation of cloudiness; here wavelet coefficients decrease with increasing scale. Examples of nonstationary behavior are the predominant turbulent structure of cloud layers as well as instrumental or physical smoothing in the data; here wavelet coefficients increase with scale. In all of these regimes, we have theoretical expectations and/or empirical evidence of power-law relations for wavelet statistics with respect to scale as is expected in physical (finite

  13. Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms

    Science.gov (United States)

    Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P. N.; Heidinger, A.; Joro, S.; Kniffka, A.; Le Gléau, H.; Lockhoff, M.; Lutz, H.-J.; Meirink, J. F.; Minnis, P.; Palikonda, R.; Roebeling, R.; Thoss, A.; Platnick, S.; Watts, P.; Wind, G.

    2014-09-01

    The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) - a crucial parameter to estimate the thermal cloud radiative forcing - can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0.90. The

  14. Remote Sensing of Cloud Top Height from SEVIRI: Analysis of Eleven Current Retrieval Algorithms

    Science.gov (United States)

    Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P. N.; Heidinger, A.; Joro, S.; Kniffka, A.; hide

    2014-01-01

    The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) - a crucial parameter to estimate the thermal cloud radiative forcing - can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 kilometers lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0

  15. Remote Sensing of Cloud Top Height from SEVIRI: Analysis of Eleven Current Retrieval Algorithms

    Science.gov (United States)

    Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P. N.; Heidinger, A.; Joro, S.; Kniffka, A.; Le Gleau, H.; Lockhoff, M.; Lutz, H.-J.; Meirink, J. F.; Minnis, P.; Palikonda, R.; Roebeling, R.; Thoss, A.; Platnick, S.; Watts, P.; Wind, G.

    2014-01-01

    The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) - a crucial parameter to estimate the thermal cloud radiative forcing - can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 kilometers lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0

  16. Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms

    Directory of Open Access Journals (Sweden)

    U. Hamann

    2014-09-01

    Full Text Available The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH – a crucial parameter to estimate the thermal cloud radiative forcing – can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI onboard Meteosat Second Generation (MSG. In the first part we compare ten SEVIRI cloud top pressure (CTP data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud–Aerosol LIdar with Orthogonal Polarization (CALIOP and Cloud Profiling Radar (CPR instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between

  17. Cloud tolerance of remote-sensing technologies to measure land surface temperature

    Science.gov (United States)

    Holmes, Thomas R. H.; Hain, Christopher R.; Anderson, Martha C.; Crow, Wade T.

    2016-08-01

    Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive-microwave (MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25° resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product.This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR-based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications.

  18. Investigation of Arctic mixed-phase clouds by combining airborne remote sensing and in situ observations during VERDI, RACEPAC and ACLOUD

    Science.gov (United States)

    Ehrlich, André; Bierwirth, Eike; Borrmann, Stephan; Crewell, Susanne; Herber, Andreas; Hoor, Peter; Jourdan, Olivier; Krämer, Martina; Lüpkes, Christof; Mertes, Stephan; Neuber, Roland; Petzold, Andreas; Schnaiter, Martin; Schneider, Johannes; Weigel, Ralf; Weinzierl, Bernadett; Wendisch, Manfred

    2016-04-01

    To improve our understanding of Arctic mixed-phase clouds a series of airborne research campaigns has been initiated by a collaboration of German research institutes. Clouds in areas dominated by a close sea-ice cover were observed during the research campaign Vertical distribution of ice in Arctic mixed-phase clouds (VERDI, April/May 2012) and the Radiation-Aerosol-Cloud Experiment in the Arctic Circle (RACEPAC, April/May 2014) which both were based in Inuvik, Canada. The aircraft (Polar 5 & 6, Basler BT-67) operated by the Alfred Wegener Institute for Polar and Marine Research, Germany did cover a wide area above the Canadian Beaufort with in total 149 flight hours (62h during VERDI, 87h during RACEPAC). For May/June 2017 a third campaign ACLOUD (Arctic Clouds - Characterization of Ice, aerosol Particles and Energy fluxes) with base in Svalbard is planned within the Transregional Collaborative Research Centre TR 172 ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3 to investigate Arctic clouds in the transition zone between open ocean and sea ice. The aim of all campaigns is to combine remote sensing and in-situ cloud, aerosol and trace gas measurements to investigate interactions between radiation, cloud and aerosol particles. While during VERDI remote sensing and in-situ measurements were performed by one aircraft subsequently, for RACEPAC and ACLOUD two identical aircraft are coordinated at different altitudes to horizontally collocate both remote sensing and in-situ measurements. The campaign showed that in this way radiative and microphysical processes in the clouds can by studied more reliably and remote sensing methods can be validated efficiently. Here we will illustrate the scientific strategy of the projects including the progress in instrumentation. Differences in the general synoptic and sea ice situation and related changes in cloud properties at the different locations and seasons will be

  19. Service Oriented Architecture for Remote Sensing Satellite Telemetry Data Implemented on Cloud Computing

    Directory of Open Access Journals (Sweden)

    Abdelfattah El-Sharkawi

    2013-06-01

    Full Text Available This paper articulates how Service Oriented Architecture (SOA and cloud computing together can facilitate technology setup in Telemetry (TM processing with a case study from the Egyptian space program (ESP and a comparative study with space situational awareness (SSA program in European space agency (ESA, Moreover, this paper illustrates how cloud computing services and deployment models enable software and hardware decoupling and making flexible TM data analysis possible. The large amount of available computational resources facilitates a shift in approaches to software development, deployment and operations.

  20. Laser Remote Sensing from ISS: the CATS-CALIPSO Cloud and Aerosol Data Products

    Science.gov (United States)

    Rodier, S. D.; Palm, S. P.; Jensen, M. H.; Yorks, J. E.; McGill, M. J.; Vaughan, M.; Trepte, C. R.

    2014-12-01

    The NASA Cloud Aerosol Transport System (CATS) is a dual-beam, multi-wavelength (1064, 532 and 355 nm), polarization sensitive (1064 and 532 nm) lidar developed at NASA's Goddard Space Flight Center (GSFC) for deployment to the International Space Station (ISS) in late 2014. CATS will be mounted on the Japanese Experiment Module's Exposed Facility and will provide near-continuous, altitude-resolved measurements of clouds and aerosols in the Earth's atmosphere. The ISS orbit path provides a unique opportunity to capture the full diurnal cycle of cloud and aerosol development and transport, allowing for studies that are not possible with the lidar aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, which flies in the sun-synchronous A-Train orbit. One of the primary objectives of CATS is to continue the CALIPSO data record to provide continuity of aerosol and cloud lidar observations during the transition from CALIPSO to EarthCARE. To accomplish this, the CATS project at GSFC and the CALIPSO project at NASA's Langley Research Center are closely collaborating to develop and deliver a full suite of CALIPSO-like level 2 data products generated from the newly acquired CATS level 1B data. Now in its eighth year of on-orbit operations, the CALIPSO project has developed a robust set of mature and well-validated science algorithms to retrieve the spatial and optical properties of clouds and aerosols from multi-wavelength lidar backscatter signal. By leveraging both new and existing NASA technical resources, this joint effort by the CATS-CALIPSO team will enable rapid delivery of high-quality lidar data sets to the user community at the earliest possible opportunity. In this work we outline the development of the CALIPSO- CATS level 2 software and data products and describe the modifications made to the input CATS data stream and the CALIPSO processing algorithms in order to successfully interface two disparate data processing

  1. Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters - Part 2: Aerosols

    Science.gov (United States)

    Wind, Galina; da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

    2016-07-01

    operational remote-sensing algorithms.Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (M{O/Y}D04). The M{O/Y}D04 product is of course normally produced from M{O/Y}D021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a M{O/Y}D021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source.We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

  2. Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters . Part 2; Aerosols

    Science.gov (United States)

    Wind, Galina; Da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

    2016-01-01

    operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

  3. Effects of Cloud Particles on Remote Sensing from Space in the 10-Micrometer Infrared Region.

    Science.gov (United States)

    1977-01-01

    ayers , that is , a plane-parallel atmosphere wi th infinite hori zontal extent . As a matter of fact, this is how the planeta ry atmosphere is being...Remote Probin g of the Atmosphe re, 1973. 43 . Hansen , J. E. and L. D. Travis , 1974 , “Light Scattering in Planeta ry • Atmospheres ,” Goddard

  4. Laser Remote Sensing from ISS: CATS Cloud and Aerosol Level 2 Data Products (Heritage Edition

    Directory of Open Access Journals (Sweden)

    Rodier Sharon

    2016-01-01

    Full Text Available With the recent launch of the Cloud-Aerosol Transport System (CATS we have the opportunity to acquire a continuous record of space based lidar measurements spanning from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO era to the start of the EarthCARE mission. Utilizing existing well-validated science algorithms from the CALIPSO mission, we will ingest the CATS data stream and deliver high-quality lidar data sets to the user community at the earliest possible opportunity. In this paper we present an overview of procedures necessary to generate CALIPSO-like lidar level 2 data products from the CATS level 1 data products.

  5. Simple Models of the Spatial Distribution of Cloud Radiative Properties for Remote Sensing Studies

    Science.gov (United States)

    2004-01-01

    This project aimed to assess the degree to which estimates of three-dimensional cloud structure can be inferred from a time series of profiles obtained at a point. The work was motivated by the desire to understand the extent to which high-frequency profiles of the atmosphere (e.g. ARM data streams) can be used to assess the magnitude of non-plane parallel transfer of radiation in thc atmosphere. We accomplished this by performing an observing system simulation using a large-eddy simulation and a Monte Carlo radiative transfer model. We define the 3D effect as the part of the radiative transfer that isn't captured by one-dimensional radiative transfer calculations. We assess the magnitude of the 3D effect in small cumulus clouds by using a fine-scale cloud model to simulate many hours of cloudiness over a continental site. We then use a Monte Carlo radiative transfer model to compute the broadband shortwave fluxes at the surface twice, once using the complete three-dimensional radiative transfer F(sup 3D), and once using the ICA F (sup ICA); the difference between them is the 3D effect given.

  6. Laser Remote Sensing From ISS: CATS Cloud and Aerosol Level 2 Data Products (Heritage Edition)

    Science.gov (United States)

    Rodier, Sharon; Vaughan, Mark; Palm, Steve; Jensen, Mike; Yorks, John; McGill, Matt; Trepte, Chip; Murray, Tim; Lee, Kam-Pui

    2015-01-01

    The Cloud-Aerosol Transport System (CATS) instrument was developed at NASA's Goddard Space Flight Center (GSFC) and deployed to the International Space Station (ISS) on 10 January 2015. CATS is mounted on the Japanese Experiment Module's Exposed Facility (JEM_EF) and will provide near-continuous, altitude-resolved measurements of clouds and aerosols in the Earth's atmosphere. The CATS ISS orbit path provides a unique opportunity to capture the full diurnal cycle of cloud and aerosol development and transport, allowing for studies that are not possible with the lidar aboard the CALIPSO platform, which flies in the sun-synchronous A-Train orbit." " One of the primary science objectives of CATS is to continue the CALIPSO aerosol and cloud profile data record to provide continuity of lidar climate observations during the transition from CALIPSO to EarthCARE. To accomplish this, the CATS project at NASA's Goddard Space Flight Center (GSFC) and the CALIPSO project at NASA's Langley Research Center (LaRC) are closely collaborating to develop and deliver a full suite of CALIPSO-like level 2 data products that will be produced using the newly acquired CATS level 1B data whenever CATS is operating in science modes 1. The CALIPSO mission is now well into its ninth year of on-orbit operations, and has developed a robust set of mature and well-validated science algorithms to retrieve the spatial and optical properties of clouds and aerosols from multi-wavelength lidar backscatter signals. By leveraging both new and existing NASA technical resources, this joint effort by the CATS and CALIPSO teams will deliver validated lidar data sets to the user community at the earliest possible opportunity. The science community will have access to two sets of CATS Level 2 data products. The "Operational" data products will be produced by the GSFC CATS team utilizing the new instrument capabilities (e.g., multiple FOVs and 1064 nm depolarization), while the "Heritage" data products created

  7. Remote Sensing Information Gateway

    Science.gov (United States)

    Remote Sensing Information Gateway, a tool that allows scientists, researchers and decision makers to access a variety of multi-terabyte, environmental datasets and to subset the data and obtain only needed variables, greatly improving the download time.

  8. Remote sensing of natural phenomena

    Directory of Open Access Journals (Sweden)

    Miodrag D. Regodić

    2014-06-01

    monitoring natural phenomena The images taken from Remote Sensing have helped men to use the environment and natural resources in a better way. It is expected that the developement of new technologies will spread the usage of satellite images for the welfare of mankind as well.  Besides monitoring the surface of the Earth, the satellite monitoring of  the processes inside the Earth itself is of great importance since these processes can  cause different catastrophes such as earthquakes, volcano eruptions, floods, etc. Usage of satellite images in monitoring atmospheric phenomena The launch of artificial earth satellites has opened new possibilities for monitoring and studying atmospheric phenomena. A large number of meteorological satellites have been launched by now (Nimbus, Meteor, SNS, ESSA, Meteosat, Terra, etc.. Since these images are primarily used for weather forecast, meteorologists use them to get information about the characteristics of clouds related to their temperature, the temperature of the cloud layer, the degree of cloudness, the profiles of humidity content, the wind parameters, etc. Meteosat satellites Meteosat is the first European geostationary satellite designed for meteorological research. The use of these satellites enabled the surveying in the visible and the near IR part of the spectrum as well as in the infrared thermal and water steam track. Based on these images, it was possible to obtain data such as:  height of clouds, cloud spreading and moving, sea surface temperature, speed of wind, distribution of the water steam, balance of radiation, etc. Usage of satellite images in monitoring floods Satellite images are an excellent background and an initial phase for preventing severe catastrophic events caused by floods. Due to satellite images, it is possible to manage overflown regions before, during and after floods. This enables prevention, forecasting, detection and elimination of consequences, i.e. demage. Satellite images are of great help

  9. Super-cooled liquid water topped sub-arctic clouds and precipitation - investigation based on combination of ground-based in-situ and remote-sensing observations

    Science.gov (United States)

    Hirsikko, Anne; Brus, David; O'Connor, Ewan J.; Filioglou, Maria; Komppula, Mika; Romakkaniemi, Sami

    2017-04-01

    In the high and mid latitudes super-cooled liquid water layers are frequently observed on top of clouds. These layers are difficult to forecast with numerical weather prediction models, even though, they have strong influence on atmospheric radiative properties, cloud microphysical properties, and subsequently, precipitation. This work investigates properties of super-cooled liquid water layer topped sub-arctic clouds and precipitation observed with ground-based in-situ (cloud probes) and remote-sensing (a cloud radar, Doppler and multi-wavelength lidars) instrumentation during two-month long Pallas Cloud Experiment (PaCE 2015) in autumn 2015. Analysis is based on standard Cloudnet scheme supplemented with new retrieval products of the specific clouds and their properties. Combination of two scales of observation provides new information on properties of clouds and precipitation in the sub-arctic Pallas region. Current status of results will be presented during the conference. The authors acknowledge financial support by the Academy of Finland (Centre of Excellence Programme, grant no 272041; and ICINA project, grant no 285068), the ACTRIS2 - European Union's Horizon 2020 research and innovation programme under grant agreement No 654109, the KONE foundation, and the EU FP7 project BACCHUS (grant no 603445).

  10. The New Cloud Absorption Radiometer (CAR) Software: One Model for NASA Remote Sensing Virtual Instruments

    Science.gov (United States)

    Roth, Don J.; Rapchun, David A.; Jones, Hollis H.

    2001-01-01

    The Cloud Absorption Radiometer (CAR) instrument has been the most frequently used airborne instrument built in-house at NASA Goddard Space Flight Center, having flown scientific research missions on-board various aircraft to many locations in the United States, Azores, Brazil, and Kuwait since 1983. The CAR instrument is capable of measuring scattered light by clouds in fourteen spectral bands in UV, visible and near-infrared region. This document describes the control, data acquisition, display, and file storage software for the new version of CAR. This software completely replaces the prior CAR Data System and Control Panel with a compact and robust virtual instrument computer interface. Additionally, the instrument is now usable for the first time for taking data in an off-aircraft mode. The new instrument is controlled via a LabVIEW v5. 1.1-developed software interface that utilizes, (1) serial port writes to write commands to the controller module of the instrument, and (2) serial port reads to acquire data from the controller module of the instrument. Step-by-step operational procedures are provided in this document. A suite of other software programs has been developed to complement the actual CAR virtual instrument. These programs include: (1) a simulator mode that allows pretesting of new features that might be added in the future, as well as demonstrations to CAR customers, and development at times when the instrument/hardware is off-location, and (2) a post-experiment data viewer that can be used to view all segments of individual data cycles and to locate positions where 'start' and stop' byte sequences were incorrectly formulated by the instrument controller. The CAR software described here is expected to be the basis for CAR operation for many missions and many years to come.

  11. Evaluation of cloud-resolving modeling of haboobs using in-situ and remotely sensed observations

    Science.gov (United States)

    Anisimov, Anatolii; Axisa, Duncan; Mostamandi, Suleiman; Kucera, Paul A.; Stenchikov, Georgiy

    2017-04-01

    Arabian Peninsula is one of the major dust generation regions that at present is severely under-sampled. In this study, we combine unique aircraft observations of aerosol and fine-resolution simulations to better quantify dust generation and transport in deep convective storms called haboobs. The aerosol observations were obtained during the "Kingdom of Saudi Arabia Assessment of Rainfall Augmentation" research program that was conducted in the Central and Southwest regions of Saudi Arabia for the years of 2006 through 2009. We ingest the observations from the first phase of the project conducted in the central Arabian Peninsula near Riyadh in April 2007 and focus on the observational cases when the aircraft sampled high concentrations of dust within haboobs. These data are indispensable for assessment of dust properties during periods of extreme aerosol loading. We perform cloud-resolving 2-km simulations using the coupled meteorology-chemistry WRF-Chem model with 8-bin MOSAIC aerosol microphysics scheme that accounts for direct and indirect aerosol effects. The model is validated using observations from surface weather stations, Doppler weather radar network, AERONET stations, MODIS and SEVIRI satellite aerosol sensors. We also compare the model results with recent MERRA-2 reanalysis that assimilates aerosols and chemical components. The model captures the spatiotemporal variability of atmospheric circulation and aerosol properties and calculates contributions of different aerosol species. We specifically compare the simulated aerosols with the aircraft measurements to evaluate the vertical extent and the structure of dust layers in haboobs. The simulated column-averaged dust size distribution compares reasonably well with AERONET and aircraft measurement. Despite total aerosol optical depth in simulations and MERRA2 reanalysis are quite similar, the vertical distribution and regional dust emission fluxes in the model and reanalysis differ significantly. The

  12. Studies on remote sensing method of particle size and water density distribution in mists and clouds using laser radar techniques

    Science.gov (United States)

    Shimizu, H.; Kobayasi, T.; Inaba, H.

    1979-01-01

    A method of remote measurement of the particle size and density distribution of water droplets was developed. In this method, the size of droplets is measured from the Mie scattering parameter which is defined as the total-to-backscattering ratio of the laser beam. The water density distribution is obtained by a combination of the Mie scattering parameter and the extinction coefficient of the laser beam. This method was examined experimentally for the mist generated by an ultrasonic mist generator and applied to clouds containing rain and snow. Compared with the conventional sampling method, the present method has advantages of remote measurement capability and improvement in accuracy.

  13. Building an Elastic Parallel OGC Web Processing Service on a Cloud-Based Cluster: A Case Study of Remote Sensing Data Processing Service

    Directory of Open Access Journals (Sweden)

    Xicheng Tan

    2015-10-01

    Full Text Available Since the Open Geospatial Consortium (OGC proposed the geospatial Web Processing Service (WPS, standard OGC Web Service (OWS-based geospatial processing has become the major type of distributed geospatial application. However, improving the performance and sustainability of the distributed geospatial applications has become the dominant challenge for OWSs. This paper presents the construction of an elastic parallel OGC WPS service on a cloud-based cluster and the designs of a high-performance, cloud-based WPS service architecture, the scalability scheme of the cloud, and the algorithm of the elastic parallel geoprocessing. Experiments of the remote sensing data processing service demonstrate that our proposed method can provide a higher-performance WPS service that uses less computing resources. Our proposed method can also help institutions reduce hardware costs, raise the rate of hardware usage, and conserve energy, which is important in building green and sustainable geospatial services or applications.

  14. Use of remotely sensed precipitation and leaf area index in a distributed hydrological model

    DEFF Research Database (Denmark)

    Andersen, Jens; Dybkjær, Gorm Ibsen; Jensen, Karsten Høgh

    2002-01-01

    distributed hydrological modelling, remote sensing, precipitation, leaf area index, NOAA AVHRR, cold cloud duration......distributed hydrological modelling, remote sensing, precipitation, leaf area index, NOAA AVHRR, cold cloud duration...

  15. Introduction to remote sensing

    CERN Document Server

    Campbell, James B

    2012-01-01

    A leading text for undergraduate- and graduate-level courses, this book introduces widely used forms of remote sensing imagery and their applications in plant sciences, hydrology, earth sciences, and land use analysis. The text provides comprehensive coverage of principal topics and serves as a framework for organizing the vast amount of remote sensing information available on the Web. Including case studies and review questions, the book's four sections and 21 chapters are carefully designed as independent units that instructors can select from as needed for their courses. Illustrations in

  16. Remote sensing image fusion

    CERN Document Server

    Alparone, Luciano; Baronti, Stefano; Garzelli, Andrea

    2015-01-01

    A synthesis of more than ten years of experience, Remote Sensing Image Fusion covers methods specifically designed for remote sensing imagery. The authors supply a comprehensive classification system and rigorous mathematical description of advanced and state-of-the-art methods for pansharpening of multispectral images, fusion of hyperspectral and panchromatic images, and fusion of data from heterogeneous sensors such as optical and synthetic aperture radar (SAR) images and integration of thermal and visible/near-infrared images. They also explore new trends of signal/image processing, such as

  17. Remote sensing of coastal and ocean studies

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.

    the sensors on board 2 satellites or aircrafts (and vice versa). Hence, they cannot be used in remote sensing. Similarly, long waves like radio waves are also not used in remote sensing because of their poor information carrying capacity. Only visible, infra..., infra-red radiation is also affected by clouds (though less significantly). This requires atmospheric corrections to be applied to such data. At present, sea surface temperatures are routinely being retrieved from the sensor called AVBRR (Advanced Vary...

  18. EPA REMOTE SENSING RESEARCH

    Science.gov (United States)

    The 2006 transgenic corn imaging research campaign has been greatly assisted through a cooperative effort with several Illinois growers who provided planting area and crop composition. This research effort was designed to evaluate the effectiveness of remote sensed imagery of var...

  19. Section summary: Remote sensing

    Science.gov (United States)

    Belinda Arunarwati Margono

    2013-01-01

    Remote sensing is an important data source for monitoring the change of forest cover, in terms of both total removal of forest cover (deforestation), and change of canopy cover, structure and forest ecosystem services that result in forest degradation. In the context of Intergovernmental Panel on Climate Change (IPCC), forest degradation monitoring requires information...

  20. Remote sensing: best practice

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Gareth [Sgurr Energy (Canada)

    2011-07-01

    This paper presents remote sensing best practice in the wind industry. Remote sensing is a technique whereby measurements are obtained from the interaction of laser or acoustic pulses with the atmosphere. There is a vast diversity of tools and techniques available and they offer wide scope for reducing project uncertainty and risk but best practice must take into account versatility and flexibility. It should focus on the outcome in terms of results and data. However, traceability of accuracy requires comparison with conventional instruments. The framework for the Boulder protocol is given. Overviews of the guidelines for IEA SODAR and IEA LIDAR are also mentioned. The important elements of IEC 61400-12-1, an international standard for wind turbines, are given. Bankability is defined based on the Boulder protocol and a pie chart is presented that illustrates the uncertainty area covered by remote sensing. In conclusion it can be said that remote sensing is changing perceptions about how wind energy assessments can be made.

  1. 基于云计算的多源遥感数据服务系统研究%Research on multi-source remote sensing data service system based on cloud computing

    Institute of Scientific and Technical Information of China (English)

    张树凡; 吴新桥; 曹宇; 王英洁; 张贵峰

    2015-01-01

    Based on analysis of remote sensing image data and data usage status,a multi⁃source remote sensing data ser⁃vice system based on cloud computing was designed in consideration of the necessity and feasibility of cloud computing technolo⁃gy application in remote sensing field. The architecture and key business process of the multi⁃source remote sensing data service system are described,including remote sensing data cloud storage,remote sensing data cloud processing,remote sensing data application service and remote sensing business registration. The application of the prototype system proves that the system can protect the original data,reduce the cost of data application,and improve data sharing rate and usage rate.%在分析了遥感影像数据及数据使用现状的基础上,综合考虑了云计算技术在遥感应用领域使用的必要性和可行性,设计了基于云计算的多源遥感数据服务系统。阐述了基于云计算的多源遥感数据服务系统体系结构及关键业务流程,包括遥感数据云存储、遥感数据云处理、遥感数据应用服务及遥感业务注册组装等。最后,通过原型系统的实现验证了系统设计既能保护原始数据的安全,又能降低数据使用的成本,同时还能够提高数据的共享率和用户使用率。

  2. Advanced laser remote sensing

    Energy Technology Data Exchange (ETDEWEB)

    Schultz, J.; Czuchlewski, S.; Karl, R. [and others

    1996-11-01

    This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory. Remote measurement of wind velocities is critical to a wide variety of applications such as environmental studies, weather prediction, aircraft safety, the accuracy of projectiles, bombs, parachute drops, prediction of the dispersal of chemical and biological warfare agents, and the debris from nuclear explosions. Major programs to develop remote sensors for these applications currently exist in the DoD and NASA. At present, however, there are no real-time, three-dimensional wind measurement techniques that are practical for many of these applications and we report on two new promising techniques. The first new technique uses an elastic backscatter lidar to track aerosol patterns in the atmosphere and to calculate three dimensional wind velocities from changes in the positions of the aerosol patterns. This was first done by Professor Ed Eloranta of the University of Wisconsin using post processing techniques and we are adapting Professor Eloranta`s algorithms to a real-time data processor and installing it in an existing elastic backscatter lidar system at Los Alamos (the XM94 helicopter lidar), which has a compatible data processing and control system. The second novel wind sensing technique is based on radio-frequency (RF) modulation and spatial filtering of elastic backscatter lidars. Because of their compactness and reliability, solid state lasers are the lasers of choice for many remote sensing applications, including wind sensing.

  3. Remote Sensing and the Earth.

    Science.gov (United States)

    Brosius, Craig A.; And Others

    This document is designed to help senior high school students study remote sensing technology and techniques in relation to the environmental sciences. It discusses the acquisition, analysis, and use of ecological remote data. Material is divided into three sections and an appendix. Section One is an overview of the basics of remote sensing.…

  4. Remote Sensing and the Earth.

    Science.gov (United States)

    Brosius, Craig A.; And Others

    This document is designed to help senior high school students study remote sensing technology and techniques in relation to the environmental sciences. It discusses the acquisition, analysis, and use of ecological remote data. Material is divided into three sections and an appendix. Section One is an overview of the basics of remote sensing.…

  5. Remote Sensing of Supercooled Cloud Layers in Cold Climate Using Ground Based Integrated Sensors System and Comparison with Pilot Reports and model forecasts

    Science.gov (United States)

    Boudala, Faisal; Wu, Di; Gultepe, Ismail; Anderson, Martha; turcotte, marie-france

    2017-04-01

    In-flight aircraft icing is one of the major weather hazards to aviation . It occurs when an aircraft passes through a cloud layer containing supercooled drops (SD). The SD in contact with the airframe freezes on the surface which degrades the performance of the aircraft.. Prediction of in-flight icing requires accurate prediction of SD sizes, liquid water content (LWC), and temperature. The current numerical weather predicting (NWP) models are not capable of making accurate prediction of SD sizes and associated LWC. Aircraft icing environment is normally studied by flying research aircraft, which is quite expensive. Thus, developing a ground based remote sensing system for detection of supercooled liquid clouds and characterization of their impact on severity of aircraft icing one of the important tasks for improving the NWPs based predictions and validations. In this respect, Environment and Climate Change Canada (ECCC) in cooperation with the Department of National Defense (DND) installed a number of specialized ground based remote sensing platforms and present weather sensors at Cold Lake, Alberta that includes a multi-channel microwave radiometer (MWR), K-band Micro Rain radar (MRR), Ceilometer, Parsivel distrometer and Vaisala PWD22 present weather sensor. In this study, a number of pilot reports confirming icing events and freezing precipitation that occurred at Cold Lake during the 2014-2016 winter periods and associated observation data for the same period are examined. The icing events are also examined using aircraft icing intensity estimated using ice accumulation model which is based on a cylindrical shape approximation of airfoil and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predicted LWC, median volume diameter and temperature. The results related to vertical atmospheric profiling conditions, surface observations, and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model

  6. Remote Sensing and Imaging Physics

    Science.gov (United States)

    2012-03-07

    Program Manager AFOSR/RSE Air Force Research Laboratory Remote Sensing and Imaging Physics 7 March 2012 Report Documentation Page Form...00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Remote Sensing And Imaging Physics 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...Imaging of Space Objects •Information without Imaging •Predicting the Location of Space Objects • Remote Sensing in Extreme Conditions •Propagation

  7. LACROS: the Leipzig Aerosol and Cloud Remote Observations System

    Science.gov (United States)

    Bühl, Johannes; Seifert, Patric; Wandinger, Ulla; Baars, Holger; Kanitz, Thomas; Schmidt, Jörg; Myagkov, Alexander; Engelmann, Ronny; Skupin, Annett; Heese, Birgit; Klepel, André; Althausen, Dietrich; Ansmann, Albert

    2013-10-01

    The study of interactions between aerosol particles, atmospheric dynamics and clouds and their resulting corresponding indirect effects on precipitation and radiative transfer demand new measurement strategies combining the strength of lidar, radar, and in-situ instrumentation. To match this challenge the Leipzig Aerosol and Cloud Remote Observations System (LACROS) has been set up at TROPOS, combining the strengths of a unique set of active and passive remote sensing and in-situ measurement systems.

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

    Science.gov (United States)

    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

  9. A Remote-Sensing Mission

    Science.gov (United States)

    Hotchkiss, Rose; Dickerson, Daniel

    2008-01-01

    Sponsored by NASA and the JASON Education Foundation, the remote Sensing Earth Science Teacher Education Program (RSESTeP) trains teachers to use state-of-the art remote-sensing technology with the idea that participants bring back what they learn and incorporate it into Earth science lessons using technology. The author's participation in the…

  10. A Remote-Sensing Mission

    Science.gov (United States)

    Hotchkiss, Rose; Dickerson, Daniel

    2008-01-01

    Sponsored by NASA and the JASON Education Foundation, the remote Sensing Earth Science Teacher Education Program (RSESTeP) trains teachers to use state-of-the art remote-sensing technology with the idea that participants bring back what they learn and incorporate it into Earth science lessons using technology. The author's participation in the…

  11. 基于GeoSOT网格的遥感影像云量信息精细描述模型%A Model of Remote Sensing Image Cloud-Cover Fine Description Based on GeoSOT Global Subdivsion Grid

    Institute of Scientific and Technical Information of China (English)

    席福彪; 程承旗; 冯洋

    2014-01-01

    针对现有遥感影像缺乏精细化云量描述手段的问题,提出了一种基于GeoSOT网格的遥感影像云量信息精细描述模型。模型建立了遥感影像与GeoSOT网格空间上的映射关系,通过记录每个网格内的影像是否含云,在一定精度上描述云在空间上的分布情况和云量的大小。试验结果表明:该模型能够精细地描述遥感影像云量信息,可实现对影像区域的云量高效检索,提高有云影像使用的效率和影像的可用性。%A model of remote sensing image cloud-cover fine description based on global subdivsion grid was proposed, which is able to cope with the problem of lacking fine description of remote sensing image cloud-cover. This model established a geospatial mapping between remote sensing image and GeoSOT grid. By recording each grid whether or not containing clouds, to describe the cloud-cover on the geospatial distribution. Experimental results show that this model can finely describe cloud-cover on the remote sensing image, achieve efficient retrieval of cloud-cover information, and improved efficiency and availability of cloud images usage.

  12. Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, MODIS, and MISR

    Science.gov (United States)

    King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, G. Thomas; Dominguez, Roseanne T.

    2010-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS Cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.

  13. Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, MODIS, and MISR

    Science.gov (United States)

    King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, G. Thomas; Dominguez, Roseanne T.

    2010-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS Cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.

  14. Signal processing for remote sensing

    CERN Document Server

    Chen, CH

    2007-01-01

    Written by leaders in the field, Signal Processing for Remote Sensing explores the data acquisitions segment of remote sensing. Each chapter presents a major research result or the most up to date development of a topic. The book includes a chapter by Dr. Norden Huang, inventor of the Huang-Hilbert transform who, along with and Dr. Steven Long discusses the application of the transform to remote sensing problems. It also contains a chapter by Dr. Enders A. Robinson, who has made major contributions to seismic signal processing for over half a century, on the basic problem of constructing seism

  15. Classification of remotely sensed images

    CSIR Research Space (South Africa)

    Dudeni, N

    2008-10-01

    Full Text Available (s)) is the data vector for a pixel located at s θ(s) is an unknown ground class to which pixel s belongs Objective is to classify the pixel at location s to the one of the k clusters Classification of remotely sensed images N. Dudeni, P. Debba...(s) is an unknown ground class to which pixel s belongs Objective is to classify the pixel at location s to the one of the k clusters Classification of remotely sensed images N. Dudeni, P. Debba Introduction to Remote Sensing Introduction to Image...

  16. DEVELOPMENT OF IMPROVED TECHNIQUES FOR SATELLITE REMOTE SENSING OF CLOUDS AND RADIATION USING ARM DATA, FINAL REPORT

    Energy Technology Data Exchange (ETDEWEB)

    Minnis, Patrick [NASA Langley Research Center, Hampton, VA

    2013-06-28

    During the period, March 1997 – February 2006, the Principal Investigator and his research team co-authored 47 peer-reviewed papers and presented, at least, 138 papers at conferences, meetings, and workshops that were supported either in whole or in part by this agreement. We developed a state-of-the-art satellite cloud processing system that generates cloud properties over the Atmospheric Radiation (ARM) surface sites and surrounding domains in near-real time and outputs the results on the world wide web in image and digital formats. When the products are quality controlled, they are sent to the ARM archive for further dissemination. These products and raw satellite images can be accessed at http://cloudsgate2.larc.nasa.gov/cgi-bin/site/showdoc?docid=4&cmd=field-experiment-homepage&exp=ARM and are used by many in the ARM science community. The algorithms used in this system to generate cloud properties were validated and improved by the research conducted under this agreement. The team supported, at least, 11 ARM-related or supported field experiments by providing near-real time satellite imagery, cloud products, model results, and interactive analyses for mission planning, execution, and post-experiment scientific analyses. Comparisons of cloud properties derived from satellite, aircraft, and surface measurements were used to evaluate uncertainties in the cloud properties. Multiple-angle satellite retrievals were used to determine the influence of cloud structural and microphysical properties on the exiting radiation field.

  17. The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI: a new tool for aerosol and cloud remote sensing

    Directory of Open Access Journals (Sweden)

    D. J. Diner

    2013-08-01

    Full Text Available The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI is an eight-band (355, 380, 445, 470, 555, 660, 865, 935 nm pushbroom camera, measuring polarization in the 470, 660, and 865 nm bands, mounted on a gimbal to acquire multiangular observations over a ±67° along-track range. The instrument has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. AirMSPI employs a photoelastic modulator-based polarimetric imaging technique to enable accurate measurements of the degree and angle of linear polarization in addition to spectral intensity. A description of the AirMSPI instrument and ground data processing approach is presented. Example images of clear, hazy, and cloudy scenes over the Pacific Ocean and California land targets obtained during flights between 2010 and 2012 are shown, and quantitative interpretations of the data using vector radiative transfer theory and scene models are provided to highlight the instrument's capabilities for determining aerosol and cloud microphysical properties and cloud 3-D spatial distributions. Sensitivity to parameters such as aerosol particle size distribution, ocean surface wind speed and direction, cloud-top and cloud-base height, and cloud droplet size is discussed. AirMSPI represents a major step toward realization of the type of imaging polarimeter envisioned to fly on NASA's Aerosol-Cloud-Ecosystem (ACE mission in the next decade.

  18. The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI: a new tool for aerosol and cloud remote sensing

    Directory of Open Access Journals (Sweden)

    D. J. Diner

    2013-02-01

    Full Text Available The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI is an eight-band (355, 380, 445, 470, 555, 660, 865, 935 nm pushbroom camera, measuring polarization in the 470, 660, and 865 nm bands, mounted on a gimbal to acquire multiangular observations over a ± 67° along-track range. The instrument has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. AirMSPI employs a photoelastic modulator-based polarimetric imaging technique to enable accurate measurements of the degree and angle of linear polarization in addition to spectral intensity. A description of the AirMSPI instrument and ground data processing approach is presented. Example images of clear, hazy, and cloudy scenes over the Pacific Ocean and California land targets obtained during flights between 2010 and 2012 are shown, and quantitative interpretations of the data using vector radiative transfer theory and scene models are provided to highlight the instrument's capabilities for determining aerosol and cloud microphysical properties and cloud 3-D spatial distributions. Sensitivity to parameters such as aerosol particle size distribution, ocean surface wind speed and direction, cloud-top and cloud-base height, and cloud droplet size is discussed. AirMSPI represents a major step toward realization of the type of imaging polarimeter envisioned to fly on NASA's Aerosol-Cloud-Ecosystem (ACE mission in the next decade.

  19. Remote sensing of oil slicks

    Digital Repository Service at National Institute of Oceanography (India)

    Fondekar, S.P.; Rao, L.V.G.

    the drawback of expensive conventional surveying methods. An airborne remote sensing system used for monitoring and surveillance of oil comprises different sensors such as side-looking airborne radar, synthetic aperture radar, infrared/ultraviolet line scanner...

  20. An Overview on Data Mining of Nighttime Light Remote Sensing

    Directory of Open Access Journals (Sweden)

    LI Deren

    2015-06-01

    Full Text Available When observing the Earth from above at night, it is clear that the human settlement and major economic regions emit glorious light. At cloud-free nights, some remote sensing satellites can record visible radiance source, including city light, fishing boat light and fire, and these nighttime cloud-free images are remotely sensed nighttime light images. Different from daytime remote sensing, nighttime light remote sensing provides a unique perspective on human social activities, thus it has been widely used for spatial data mining of socioeconomic domains. Historically, researches on nighttime light remote sensing mostly focus on urban land cover and urban expansion mapping using DMSP/OLS imagery, but the nighttime light images are not the unique remote sensing source to do these works. Through decades of development of nighttime light product, the nighttime light remote sensing application has been extended to numerous interesting and scientific study domains such as econometrics, poverty estimation, light pollution, fishery and armed conflict. Among the application cases, it is surprising to see the Gross Domestic Production (GDP data can be corrected using the nighttime light data, and it is interesting to see mechanism of several diseases can be revealed by nighttime light images, while nighttime light are the unique remote sensing source to do the above works. As the nighttime light remote sensing has numerous applications, it is important to summarize the application of nighttime light remote sensing and its data mining fields. This paper introduced major satellite platform and sensors for observing nighttime light at first. Consequently, the paper summarized the progress of nighttime light remote sensing data mining in socioeconomic parameter estimation, urbanization monitoring, important event evaluation, environmental and healthy effects, fishery dynamic mapping, epidemiological research and natural gas flaring monitoring. Finally, future

  1. Scale issues in remote sensing

    CERN Document Server

    Weng, Qihao

    2014-01-01

    This book provides up-to-date developments, methods, and techniques in the field of GIS and remote sensing and features articles from internationally renowned authorities on three interrelated perspectives of scaling issues: scale in land surface properties, land surface patterns, and land surface processes. The book is ideal as a professional reference for practicing geographic information scientists and remote sensing engineers as well as a supplemental reading for graduate level students.

  2. Advanced Understanding of Convection Initiation and Optimizing Cloud Seeding by Advanced Remote Sensing and Land Cover Modification over the United Arab Emirates

    Science.gov (United States)

    Wulfmeyer, V.; Behrendt, A.; Branch, O.; Schwitalla, T.

    2016-12-01

    A prerequisite for significant precipitation amounts is the presence of convergence zones. These are due to land surface heterogeneity, orography as well as mesoscale and synoptic scale circulations. Only, if these convergence zones are strong enough and interact with an upper level instability, deep convection can be initiated. For the understanding of convection initiation (CI) and optimal cloud seeding deployment, it is essential that these convergence zones are detected before clouds are developing in order to preempt the decisive microphysical processes for liquid water and ice formation. In this presentation, a new project on Optimizing Cloud Seeding by Advanced Remote Sensing and Land Cover Modification (OCAL) is introduced, which is funded by the United Arab Emirates Rain Enhancement Program (UAEREP). This project has two research components. The first component focuses on an improved detection and forecasting of convergence zones and CI by a) operation of scanning Doppler lidar and cloud radar systems during two seasonal field campaigns in orographic terrain and over the desert in the UAE, and b) advanced forecasting of convergence zones and CI with the WRF-NOAHMP model system. Nowcasting to short-range forecasting of convection will be improved by the assimilation of Doppler lidar and the UAE radar network data. For the latter, we will apply a new model forward operator developed at our institute. Forecast uncertainties will be assessed by ensemble simulations driven by ECMWF boundaries. The second research component of OCAL will study whether artificial modifications of land surface heterogeneity are possible through plantations or changes of terrain, leading to an amplification of convergence zones. This is based on our pioneering work on high-resolution modeling of the impact of plantations on weather and climate in arid regions. A specific design of the shape and location of plantations can lead to the formation of convergence zones, which can

  3. Effect of microphysics scheme in cloud resolving models in passive microwave remote sensing of precipitation over ocean

    Science.gov (United States)

    Kim, Ju-Hye; Shin, Dong-Bin; Kummerow, Christian

    2014-05-01

    Physically-based rainfall retrievals from passive microwave sensors often make use of cloud resolving models (CRMs) to build a-priori databases of potential rain structures. Each CRM, however, has its own assumptions on the cloud microphysics. Hence, approximated microphysics may cause uncertainties in the a-priori information resulting in inaccurate rainfall estimates. This study first builds a-priori databases by combining the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) observations and simulations from the Weather Research and Forecasting (WRF) model with six different cloud microphysics schemes. The microphysics schemes include the Purdue Lin (LIN), WRF-Single-Moment 6 (WSM6), Goddard Cumulus Ensemble (GCE), Thompson (THOM), WRF-Double-Moment 6 (WDM6), and Morrison (MORR) schemes. As expected, the characteristics of the a-priori databases are inherited from the individual cloud microphysics schemes. There are several distinct differences in the databases. Particularly, excessive graupel and snow exist with the LIN and THOM schemes, while more rainwater is incorporated into the a-priori information with WDM6 than with any of the other schemes. Major results show that convective rainfall regions are not well captured by the LIN and THOM schemes-based retrievals with correlations of 0.56 and 0.73. Rainfall distributions and their quantities retrieved from the WSM6 and WDM6 schemes-based estimations, however, show relatively better agreement with the PR observations with correlations of 0.79 and 0.81, respectively. Based on the comparisons of the various microphysics schemes in the retrievals, it appears that differences in the a-priori databases considerably affect the properties of rainfall estimations. This study also includes the discrepancy of estimated rain rate from passive radiometer and active radar for two rainfall systems of different cloud microphysics near the Yellow Sea. The first case have high cloud top (HCT) with large ice

  4. Remote Sensing of Environmental Pollution

    Science.gov (United States)

    North, G. W.

    1971-01-01

    Environmental pollution is a problem of international scope and concern. It can be subdivided into problems relating to water, air, or land pollution. Many of the problems in these three categories lend themselves to study and possible solution by remote sensing. Through the use of remote sensing systems and techniques, it is possible to detect and monitor, and in some cases, identify, measure, and study the effects of various environmental pollutants. As a guide for making decisions regarding the use of remote sensors for pollution studies, a special five-dimensional sensor/applications matrix has been designed. The matrix defines an environmental goal, ranks the various remote sensing objectives in terms of their ability to assist in solving environmental problems, lists the environmental problems, ranks the sensors that can be used for collecting data on each problem, and finally ranks the sensor platform options that are currently available.

  5. Investigation of ice particle habits to be used for ice cloud remote sensing for the GCOM-C satellite mission

    OpenAIRE

    H. Letu; Ishimoto, H.; J. Riedi; T. Y. Nakajima; L. C.-Labonnote; A. J. Baran; T. M. Nagao; M. Skiguchi

    2015-01-01

    Various ice particle habits are investigated in conjunction with inferring the optical properties of ice cloud for the Global Change Observation Mission-Climate (GCOM-C) satellite program. A database of the single-scattering properties of five ice particle habits, namely, plates, columns, droxtals, bullet-rosettes, and Voronoi, is developed. The database is based on the specification of the Second Generation Global Imager (SGLI) sensor onboard the GCOM-C satellite, which is ...

  6. Photogrammetry - Remote Sensing and Geoinformation

    Science.gov (United States)

    Lazaridou, M. A.; Patmio, E. N.

    2012-07-01

    Earth and its environment are studied by different scientific disciplines as geosciences, science of engineering, social sciences, geography, etc. The study of the above, beyond pure scientific interest, is useful for the practical needs of man. Photogrammetry and Remote Sensing (defined by Statute II of ISPRS) is the art, science, and technology of obtaining reliable information from non-contact imaging and other sensor systems about the Earth and its environment, and other physical objects and of processes through recording, measuring, analyzing and representation. Therefore, according to this definition, photogrammetry and remote sensing can support studies of the above disciplines for acquisition of geoinformation. This paper concerns basic concepts of geosciences (geomorphology, geology, hydrology etc), and the fundamentals of photogrammetry-remote sensing, in order to aid the understanding of the relationship between photogrammetry-remote sensing and geoinformation and also structure curriculum in a brief, concise and coherent way. This curriculum can represent an appropriate research and educational outline and help to disseminate knowledge in various directions and levels. It resulted from our research and educational experience in graduate and post-graduate level (post-graduate studies relative to the protection of environment and protection of monuments and historical centers) in the Lab. of Photogrammetry - Remote Sensing in Civil Engineering Faculty of Aristotle University of Thessaloniki.

  7. Investigation of ice particle habits to be used for ice cloud remote sensing for the GCOM-C satellite mission

    Science.gov (United States)

    Letu, Husi; Ishimoto, Hiroshi; Riedi, Jerome; Nakajima, Takashi Y.; -Labonnote, Laurent C.; Baran, Anthony J.; Nagao, Takashi M.; Sekiguchi, Miho

    2016-09-01

    In this study, various ice particle habits are investigated in conjunction with inferring the optical properties of ice clouds for use in the Global Change Observation Mission-Climate (GCOM-C) satellite programme. We develop a database of the single-scattering properties of five ice habit models: plates, columns, droxtals, bullet rosettes, and Voronoi. The database is based on the specification of the Second Generation Global Imager (SGLI) sensor on board the GCOM-C satellite, which is scheduled to be launched in 2017 by the Japan Aerospace Exploration Agency. A combination of the finite-difference time-domain method, the geometric optics integral equation technique, and the geometric optics method is applied to compute the single-scattering properties of the selected ice particle habits at 36 wavelengths, from the visible to the infrared spectral regions. This covers the SGLI channels for the size parameter, which is defined as a single-particle radius of an equivalent volume sphere, ranging between 6 and 9000 µm. The database includes the extinction efficiency, absorption efficiency, average geometrical cross section, single-scattering albedo, asymmetry factor, size parameter of a volume-equivalent sphere, maximum distance from the centre of mass, particle volume, and six nonzero elements of the scattering phase matrix. The characteristics of calculated extinction efficiency, single-scattering albedo, and asymmetry factor of the five ice particle habits are compared. Furthermore, size-integrated bulk scattering properties for the five ice particle habit models are calculated from the single-scattering database and microphysical data. Using the five ice particle habit models, the optical thickness and spherical albedo of ice clouds are retrieved from the Polarization and Directionality of the Earth's Reflectances-3 (POLDER-3) measurements, recorded on board the Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a

  8. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    The Remote Sensing in Wind Energy Compendium provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind this compendium began in year 2008 at Risø DTU during the first PhD Summer School: Remote Sensing in Wind Energy. Thus...... of the compendium, and we also acknowledge all our colleagues in the Meteorology and Test and Measurements Programs from the Wind Energy Division at Risø DTU in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly state......-of-the-art compendium available for people involved in Remote Sensing in Wind Energy....

  9. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    The Remote Sensing in Wind Energy Compendium provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind this compendium began in year 2008 at Risø DTU during the first PhD Summer School: Remote Sensing in Wind Energy. Thus...... in the Meteorology and Test and Measurements Programs from the Wind Energy Division at Risø DTU in the PhD Summer Schools. We hope to add more topics in future editions and to update as necessary, to provide a truly state-of-the-art compendium available for people involved in Remote Sensing in Wind Energy....

  10. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    Peña, Alfredo; Hasager, Charlotte Bay; Badger, Merete

    The Remote Sensing in Wind Energy report provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind it began in year 2008 at DTU Wind Energy (formerly Risø) during the first PhD Summer School: Remote Sensing in Wind Energy...... colleagues in the Meteorology and Test and Measurements Sections from DTU Wind Energy in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly state-of-the-art ‘guideline’ available for people involved in Remote Sensing...... in Wind Energy....

  11. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    Peña, Alfredo; Hasager, Charlotte Bay; Lange, Julia

    The Remote Sensing in Wind Energy report provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind it began in year 2008 at DTU Wind Energy (formerly Risø) during the first PhD Summer School: Remote Sensing in Wind Energy...... for their work in the writing of the chapters, and we also acknowledge all our colleagues in the Meteorology and Test and Measurements Sections from DTU Wind Energy in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly...... state-of-the-art ‘guideline’ available for people involved in Remote Sensing in Wind Energy....

  12. Remote sensing for urban planning

    Science.gov (United States)

    Davis, Bruce A.; Schmidt, Nicholas; Jensen, John R.; Cowen, Dave J.; Halls, Joanne; Narumalani, Sunil; Burgess, Bryan

    1994-01-01

    Utility companies are challenged to provide services to a highly dynamic customer base. With factory closures and shifts in employment becoming a routine occurrence, the utility industry must develop new techniques to maintain records and plan for expected growth. BellSouth Telecommunications, the largest of the Bell telephone companies, currently serves over 13 million residences and 2 million commercial customers. Tracking the movement of customers and scheduling the delivery of service are major tasks for BellSouth that require intensive manpower and sophisticated information management techniques. Through NASA's Commercial Remote Sensing Program Office, BellSouth is investigating the utility of remote sensing and geographic information system techniques to forecast residential development. This paper highlights the initial results of this project, which indicate a high correlation between the U.S. Bureau of Census block group statistics and statistics derived from remote sensing data.

  13. Aerosol and cloud microphysics covariability in the northeast Pacific boundary layer estimated with ship-based and satellite remote sensing observations: NE Pacific Aerosol-Cloud Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Painemal, David [Science Systems and Applications, Inc., Hampton Virginia USA; NASA Langley Research Center, Hampton Virginia USA; Chiu, J. -Y. Christine [Department of Meteorology, University of Reading, Reading UK; Minnis, Patrick [NASA Langley Research Center, Hampton Virginia USA; Yost, Christopher [Science Systems and Applications, Inc., Hampton Virginia USA; Zhou, Xiaoli [Department of Atmospheric and Oceanic Sciences, McGill University, Montreal Quebec Canada; Cadeddu, Maria [Environmental Science Division, Argonne National Laboratory, Lemont Illinois USA; Eloranta, Edwin [Space Science and Engineering Center, University of Wisconsin-Madison, Madison Wisconsin USA; Lewis, Ernie R. [Brookhaven National Laboratory, Upton New York USA; Ferrare, Richard [NASA Langley Research Center, Hampton Virginia USA; Kollias, Pavlos [School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook New York USA

    2017-02-27

    Ship measurements collected over the northeast Pacific along transects between the port of Los Angeles (33.7°N, 118.2°W) and Honolulu (21.3°N, 157.8°W) during May to August 2013 were utilized to investigate the covariability between marine low cloud microphysical and aerosol properties. Ship-based retrievals of cloud optical depth (τ) from a Sun photometer and liquid water path (LWP) from a microwave radiometer were combined to derive cloud droplet number concentration Nd and compute a cloud-aerosol interaction (ACI) metric defined as ACICCN = ∂ ln(Nd)/∂ ln(CCN), with CCN denoting the cloud condensation nuclei concentration measured at 0.4% (CCN0.4) and 0.3% (CCN0.3) supersaturation. Analysis of CCN0.4, accumulation mode aerosol concentration (Na), and extinction coefficient (σext) indicates that Na and σext can be used as CCN0.4 proxies for estimating ACI. ACICCN derived from 10 min averaged Nd and CCN0.4 and CCN0.3, and CCN0.4 regressions using Na and σext, produce high ACICCN: near 1.0, that is, a fractional change in aerosols is associated with an equivalent fractional change in Nd. ACICCN computed in deep boundary layers was small (ACICCN = 0.60), indicating that surface aerosol measurements inadequately represent the aerosol variability below clouds. Satellite cloud retrievals from MODerate-resolution Imaging Spectroradiometer and GOES-15 data were compared against ship-based retrievals and further analyzed to compute a satellite-based ACICCN. Satellite data correlated well with their ship-based counterparts with linear correlation coefficients equal to or greater than 0.78. Combined satellite Nd and ship-based CCN0.4 and Na yielded a maximum ACICCN = 0.88–0.92, a value slightly less than the ship-based ACICCN, but still consistent with aircraft-based studies in the eastern Pacific.

  14. 一种基于Linux容器技术的大规模遥感数据云服务平台%A Large-Scale Remote Sensing Data Cloud Service Platform Based on Linux Container

    Institute of Scientific and Technical Information of China (English)

    张品; 张海明; 黎建辉

    2015-01-01

    Remote sensing data cloud service platform is the geographic information processing service platform based on cloud computing technology, integrating computing resources and storage resources of large-scale remote sensing data, to achieve the patterns of resource sharing and on-demand services. This paper present a platform which is implemented based on distributed storage technology, Linux container technology, ownCloud private cloud technology and IPython notebook interactive technology. It is easy to access the large scale remote sensing dada through web as well as to analyze and process the dada using the computation and storage resources on the cloud host.%遥感数据云服务平台是基于云计算技术,整合大规模遥感数据的存储资源和计算资源,实现资源共享和按需使用的服务模式的地理信息处理服务平台.我们基于分布式存储技术实现遥感数据的高效存储、Linux容器技术实现快速部署和资源隔离、ownCloud私有云技术实现高效共享和 IPython notebook交互式技术实现方便易用交互,设计了一种稳定、高效的地理信息云服务平台.用户可通过Web的方式方便的访问大规模遥感数据,并利用云主机的计算、存储资源对所需的遥感数据进行分析和处理.

  15. Fundamentals of polarimetric remote sensing

    CERN Document Server

    Schott, John R

    2009-01-01

    This text is for those who need an introduction to polarimetric signals to begin working in the field of polarimetric remote sensing, particularly where the contrast between manmade objects and natural backgrounds are the subjects of interest. The book takes a systems approach to the physical processes involved with formation, collection, and analysis of polarimetric remote sensing data in the visible through longwave infrared. Beginning with a brief review of the polarized nature of electromagnetic energy and radiometry, Dr. Schott then introduces ways to characterize a beam of polarized ene

  16. Effects of Cloud Horizontal Inhomogeneity and Drizzle on Remote Sensing of Cloud Droplet Effective Radius: Case Studies Based on Large-eddy Simulations

    Science.gov (United States)

    Zhang, Zhibo; Ackerman, Andrew S.; Feingold, Graham; Platnick, Steven; Pincus, Robert; Xue, Huiwen

    2012-01-01

    This study investigates effects of drizzle and cloud horizontal inhomogeneity on cloud effective radius (re) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS). In order to identify the relative importance of various factors, we developed a MODIS cloud property retrieval simulator based on the combination of large-eddy simulations (LES) and radiative transfer computations. The case studies based on synthetic LES cloud fields indicate that at high spatial resolution (100 m) 3-D radiative transfer effects, such as illumination and shadowing, can induce significant differences between retrievals ofre based on reflectance at 2.1 m (re,2.1) and 3.7 m (re,3.7). It is also found that 3-D effects tend to have stronger impact onre,2.1 than re,3.7, leading to positive difference between the two (re,3.72.1) from illumination and negative re,3.72.1from shadowing. The cancellation of opposing 3-D effects leads to overall reasonable agreement betweenre,2.1 and re,3.7 at high spatial resolution as far as domain averages are concerned. At resolutions similar to MODIS, however, re,2.1 is systematically larger than re,3.7when averaged over the LES domain, with the difference exhibiting a threshold-like dependence on bothre,2.1and an index of the sub-pixel variability in reflectance (H), consistent with MODIS observations. In the LES cases studied, drizzle does not strongly impact reretrievals at either wavelength. It is also found that opposing 3-D radiative transfer effects partly cancel each other when cloud reflectance is aggregated from high spatial resolution to MODIS resolution, resulting in a weaker net impact of 3-D radiative effects onre retrievals. The large difference at MODIS resolution between re,3.7 and re,2.1 for highly inhomogeneous pixels with H 0.4 can be largely attributed to what we refer to as the plane-parallelrebias, which is attributable to the impact of sub-pixel level horizontal variability of cloud optical thickness onre retrievals

  17. Airborne Spectral BRDF of Various Surface Types (Ocean, Vegetation, Snow, Desert, Wetlands, Cloud Decks, Smoke Layers) for Remote Sensing Applications

    Science.gov (United States)

    Gatebe, Charles K.; King, Michael D.

    2016-01-01

    In this paper we describe measurements of the bidirectional reflectance-distribution function (BRDF) acquired over a 30-year period (1984-2014) by the National Aeronautics and Space Administration's (NASA's) Cloud Absorption Radiometer (CAR). Our BRDF database encompasses various natural surfaces that are representative of many land cover or ecosystem types found throughout the world. CAR's unique measurement geometry allows a comparison of measurements acquired from different satellite instruments with various geometrical configurations, none of which are capable of obtaining such a complete and nearly instantaneous BRDF. This database is therefore of great value in validating many satellite sensors and assessing corrections of reflectances for angular effects. These data can also be used to evaluate the ability of analytical models to reproduce the observed directional signatures, to develop BRDF models that are suitable for sub-kilometer-scale satellite observations over both homogeneous and heterogeneous landscape types, and to test future spaceborne sensors. All of these BRDF data are publicly available and accessible in hierarchical data format (http:car.gsfc.nasa.gov/).

  18. Integrating Remote Sensing Data, Hybrid-Cloud Computing, and Event Notifications for Advanced Rapid Imaging & Analysis (Invited)

    Science.gov (United States)

    Hua, H.; Owen, S. E.; Yun, S.; Lundgren, P.; Fielding, E. J.; Agram, P.; Manipon, G.; Stough, T. M.; Simons, M.; Rosen, P. A.; Wilson, B. D.; Poland, M. P.; Cervelli, P. F.; Cruz, J.

    2013-12-01

    Space-based geodetic measurement techniques such as Interferometric Synthetic Aperture Radar (InSAR) and Continuous Global Positioning System (CGPS) are now important elements in our toolset for monitoring earthquake-generating faults, volcanic eruptions, hurricane damage, landslides, reservoir subsidence, and other natural and man-made hazards. Geodetic imaging's unique ability to capture surface deformation with high spatial and temporal resolution has revolutionized both earthquake science and volcanology. Continuous monitoring of surface deformation and surface change before, during, and after natural hazards improves decision-making from better forecasts, increased situational awareness, and more informed recovery. However, analyses of InSAR and GPS data sets are currently handcrafted following events and are not generated rapidly and reliably enough for use in operational response to natural disasters. Additionally, the sheer data volumes needed to handle a continuous stream of InSAR data sets also presents a bottleneck. It has been estimated that continuous processing of InSAR coverage of California alone over 3-years would reach PB-scale data volumes. Our Advanced Rapid Imaging and Analysis for Monitoring Hazards (ARIA-MH) science data system enables both science and decision-making communities to monitor areas of interest with derived geodetic data products via seamless data preparation, processing, discovery, and access. We will present our findings on the use of hybrid-cloud computing to improve the timely processing and delivery of geodetic data products, integrating event notifications from USGS to improve the timely processing for response, as well as providing browse results for quick looks with other tools for integrative analysis.

  19. Remote sensing in soil science.

    NARCIS (Netherlands)

    Mulders, M.A.

    1987-01-01

    This book provides coverage of remote sensing techniques and their application in soil science. A clear, step-by-step approach to the various aspects ensures that the reader will gain a good grasp of the subject so that he can apply the techniques to his own field of study. The book opens with an in

  20. Remote Sensing of Water Pollution

    Science.gov (United States)

    White, P. G.

    1971-01-01

    Remote sensing, as a tool to aid in the control of water pollution, offers a means of making rapid, economical surveys of areas that are relatively inaccessible on the ground. At the same time, it offers the only practical means of mapping pollution patterns that cover large areas. Detection of oil slicks, thermal pollution, sewage, and algae are discussed.

  1. Remote Sensing Best Paper Award 2013

    OpenAIRE

    Prasad Thenkabail

    2013-01-01

    Remote Sensing has started to institute a “Best Paper” award to recognize the most outstanding papers in the area of remote sensing techniques, design and applications published in Remote Sensing. We are pleased to announce the first “Remote Sensing Best Paper Award” for 2013. Nominations were selected by the Editor-in-Chief and selected editorial board members from among all the papers published in 2009. Reviews and research papers were evaluated separately.

  2. Remote sensing and water resources

    CERN Document Server

    Champollion, N; Benveniste, J; Chen, J

    2016-01-01

    This book is a collection of overview articles showing how space-based observations, combined with hydrological modeling, have considerably improved our knowledge of the continental water cycle and its sensitivity to climate change. Two main issues are highlighted: (1) the use in combination of space observations for monitoring water storage changes in river basins worldwide, and (2) the use of space data in hydrological modeling either through data assimilation or as external constraints. The water resources aspect is also addressed, as well as the impacts of direct anthropogenic forcing on land hydrology (e.g. ground water depletion, dam building on rivers, crop irrigation, changes in land use and agricultural practices, etc.). Remote sensing observations offer important new information on this important topic as well, which is highly useful for achieving water management objectives. Over the past 15 years, remote sensing techniques have increasingly demonstrated their capability to monitor components of th...

  3. Sensitivity analysis in remote sensing

    CERN Document Server

    Ustinov, Eugene A

    2015-01-01

    This book contains a detailed presentation of general principles of sensitivity analysis as well as their applications to sample cases of remote sensing experiments. An emphasis is made on applications of adjoint problems, because they are more efficient in many practical cases, although their formulation may seem counterintuitive to a beginner. Special attention is paid to forward problems based on higher-order partial differential equations, where a novel matrix operator approach to formulation of corresponding adjoint problems is presented. Sensitivity analysis (SA) serves for quantitative models of physical objects the same purpose, as differential calculus does for functions. SA provides derivatives of model output parameters (observables) with respect to input parameters. In remote sensing SA provides computer-efficient means to compute the jacobians, matrices of partial derivatives of observables with respect to the geophysical parameters of interest. The jacobians are used to solve corresponding inver...

  4. Remote sensing of natural resources

    CERN Document Server

    Wang, Guangxing

    2013-01-01

    "… a comprehensive view on and real world examples of remote sensing technologies in natural resources assessment and monitoring. … state-of-the-art knowledge in this multidisciplinary field. Readers can expect to finish the book armed with the required knowledge to understand the immense literature available and apply their knowledge to the understanding of sampling design, the analysis of multi-source imagery, and the application of the techniques to specific problems relevant to natural resources."-Yuhong He, University of Toronto Mississauga, Ontario, Canada"The list of topics covered is so complete that I would recommend the book to anyone teaching a graduate course on vegetation analysis through digital image analysis. … I recommend this book then for anyone doing advanced digital image analysis and environmental GIS courses who want to cover topics related to applied remote sensing work involving vegetation analysis."-Charles Roberts, Florida Atlantic University, Boca Raton, USA, in Economic Bota...

  5. Remote Sensing Information Science Research

    Science.gov (United States)

    Clarke, Keith C.; Scepan, Joseph; Hemphill, Jeffrey; Herold, Martin; Husak, Gregory; Kline, Karen; Knight, Kevin

    2002-01-01

    This document is the final report summarizing research conducted by the Remote Sensing Research Unit, Department of Geography, University of California, Santa Barbara under National Aeronautics and Space Administration Research Grant NAG5-10457. This document describes work performed during the period of 1 March 2001 thorough 30 September 2002. This report includes a survey of research proposed and performed within RSRU and the UCSB Geography Department during the past 25 years. A broad suite of RSRU research conducted under NAG5-10457 is also described under themes of Applied Research Activities and Information Science Research. This research includes: 1. NASA ESA Research Grant Performance Metrics Reporting. 2. Global Data Set Thematic Accuracy Analysis. 3. ISCGM/Global Map Project Support. 4. Cooperative International Activities. 5. User Model Study of Global Environmental Data Sets. 6. Global Spatial Data Infrastructure. 7. CIESIN Collaboration. 8. On the Value of Coordinating Landsat Operations. 10. The California Marine Protected Areas Database: Compilation and Accuracy Issues. 11. Assessing Landslide Hazard Over a 130-Year Period for La Conchita, California Remote Sensing and Spatial Metrics for Applied Urban Area Analysis, including: (1) IKONOS Data Processing for Urban Analysis. (2) Image Segmentation and Object Oriented Classification. (3) Spectral Properties of Urban Materials. (4) Spatial Scale in Urban Mapping. (5) Variable Scale Spatial and Temporal Urban Growth Signatures. (6) Interpretation and Verification of SLEUTH Modeling Results. (7) Spatial Land Cover Pattern Analysis for Representing Urban Land Use and Socioeconomic Structures. 12. Colorado River Flood Plain Remote Sensing Study Support. 13. African Rainfall Modeling and Assessment. 14. Remote Sensing and GIS Integration.

  6. Remote sensing in biological oceanography

    Science.gov (United States)

    Esaias, W. E.

    1981-01-01

    The main attribute of remote sensing is seen as its ability to measure distributions over large areas on a synoptic basis and to repeat this coverage at required time periods. The way in which the Coastal Zone Color Scanner, by showing the distribution of chlorophyll a, can locate areas productive in both phytoplankton and fishes is described. Lidar techniques are discussed, and it is pointed out that lidar will increase the depth range for observations.

  7. Remote sensing for wind energy

    Energy Technology Data Exchange (ETDEWEB)

    Pena, A.; Bay Hasager, C.; Lange, J. [Technical Univ. of Denmark. DTU Wind Energy, DTU Risoe Campus, Roskilde (Denmark) (and others

    2013-06-15

    The Remote Sensing in Wind Energy report provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind it began in year 2008 at DTU Wind Energy (formerly Risoe) during the first PhD Summer School: Remote Sensing in Wind Energy. Thus it is closely linked to the PhD Summer Schools where state-of-the-art is presented during the lecture sessions. The advantage of the report is to supplement with in-depth, article style information. Thus we strive to provide link from the lectures, field demonstrations, and hands-on exercises to theory. The report will allow alumni to trace back details after the course and benefit from the collection of information. This is the third edition of the report (first externally available), after very successful and demanded first two, and we warmly acknowledge all the contributing authors for their work in the writing of the chapters, and we also acknowledge all our colleagues in the Meteorology and Test and Measurements Sections from DTU Wind Energy in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly state-of-the-art 'guideline' available for people involved in Remote Sensing in Wind Energy. (Author)

  8. An overview of GNSS remote sensing

    Science.gov (United States)

    Yu, Kegen; Rizos, Chris; Burrage, Derek; Dempster, Andrew G.; Zhang, Kefei; Markgraf, Markus

    2014-12-01

    The Global Navigation Satellite System (GNSS) signals are always available, globally, and the signal structures are well known, except for those dedicated to military use. They also have some distinctive characteristics, including the use of L-band frequencies, which are particularly suited for remote sensing purposes. The idea of using GNSS signals for remote sensing - the atmosphere, oceans or Earth surface - was first proposed more than two decades ago. Since then, GNSS remote sensing has been intensively investigated in terms of proof of concept studies, signal processing methodologies, theory and algorithm development, and various satellite-borne, airborne and ground-based experiments. It has been demonstrated that GNSS remote sensing can be used as an alternative passive remote sensing technology. Space agencies such as NASA, NOAA, EUMETSAT and ESA have already funded, or will fund in the future, a number of projects/missions which focus on a variety of GNSS remote sensing applications. It is envisaged that GNSS remote sensing can be either exploited to perform remote sensing tasks on an independent basis or combined with other techniques to address more complex applications. This paper provides an overview of the state of the art of this relatively new and, in some respects, underutilised remote sensing technique. Also addressed are relevant challenging issues associated with GNSS remote sensing services and the performance enhancement of GNSS remote sensing to accurately and reliably retrieve a range of geophysical parameters.

  9. Evaluating stratiform cloud base charge remotely

    Science.gov (United States)

    Harrison, R. Giles; Nicoll, Keri A.; Aplin, Karen L.

    2017-06-01

    Stratiform clouds acquire charge at their upper and lower horizontal boundaries due to vertical current flow in the global electric circuit. Cloud charge is expected to influence microphysical processes, but understanding is restricted by the infrequent in situ measurements available. For stratiform cloud bases below 1 km in altitude, the cloud base charge modifies the surface electric field beneath, allowing a new method of remote determination. Combining continuous cloud height data during 2015-2016 from a laser ceilometer with electric field mill data, cloud base charge is derived using a horizontal charged disk model. The median daily cloud base charge density found was -0.86 nC m-2 from 43 days' data. This is consistent with a uniformly charged region 40 m thick at the cloud base, now confirming that negative cloud base charge is a common feature of terrestrial layer clouds. This technique can also be applied to planetary atmospheres and volcanic plumes.Plain Language SummaryThe idea that clouds in the atmosphere can charge electrically has been appreciated since the time of Benjamin Franklin, but it is less widely recognized that it is not just thunderclouds which contain electric charge. For example, water droplets in simple layer clouds, that are abundant and often responsible for an overcast day, carry electric charges. The droplet charging arises at the upper and lower edges of the layer cloud. This occurs because the small droplets at the edges draw charge from the air outside the cloud. Understanding how strongly layer clouds charge is important in evaluating electrical effects on the development of such clouds, for example, how thick the cloud becomes and whether it generates rain. Previously, cloud charge measurement has required direct measurements within the cloud using weather balloons or aircraft. This work has monitored the lower cloud charge continuously using instruments placed at the surface beneath. From measurements made over 2 years, the

  10. The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce

    Science.gov (United States)

    Chen, Xi; Zhou, Liqing

    2015-12-01

    With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.

  11. Biogeochemical cycling and remote sensing

    Science.gov (United States)

    Peterson, D. L.

    1985-01-01

    Research is underway at the NASA Ames Research Center that is concerned with aspects of the nitrogen cycle in terrestrial ecosystems. An interdisciplinary research group is attempting to correlate nitrogen transformations, processes, and productivity with variables that can be remotely sensed. Recent NASA and other publications concerning biogeochemical cycling at global scales identify attributes of vegetation that could be related or explain the spatial variation in biologically functional variables. These functional variables include net primary productivity, annual nitrogen mineralization, and possibly the emission rate of nitrous oxide from soils.

  12. Remote Sensing Wind and Wind Shear System.

    Science.gov (United States)

    Contents: Remote sensing of wind shear and the theory and development of acoustic doppler; Wind studies; A comparison of methods for the remote detection of winds in the airport environment; Acoustic doppler system development; System calibration; Airport operational tests.

  13. Remote Sensing and Reflectance Profiling in Entomology.

    Science.gov (United States)

    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.

  14. Introductory remote sensing principles and concepts principles and concepts

    CERN Document Server

    Gibson, Paul

    2013-01-01

    Introduction to Remote Sensing Principles and Concepts provides a comprehensive student introduction to both the theory and application of remote sensing. This textbook* introduces the field of remote sensing and traces its historical development and evolution* presents detailed explanations of core remote sensing principles and concepts providing the theory required for a clear understanding of remotely sensed images.* describes important remote sensing platforms - including Landsat, SPOT and NOAA * examines and illustrates many of the applications of remotely sensed images in various fields.

  15. LWIR Microgrid Polarimeter for Remote Sensing Studies

    Science.gov (United States)

    2010-02-28

    Polarimeter for Remote Sensing Studies 5b. GRANT NUMBER FA9550-08-1-0295 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 1. Scott Tyo 5e. TASK...and tested at the University of Arizona, and preliminary images are shown in this final report. 15. SUBJECT TERMS Remote Sensing , polarimetry 16...7.0 LWIR Microgrid Polarimeter for Remote Sensing Studies J. Scott Tyo College of Optical Sciences University of Arizona Tucson, AZ, 85721 tyo

  16. Basic Remote Sensing Investigations for Beach Reconnaissance.

    Science.gov (United States)

    Progress is reported on three tasks designed to develop remote sensing beach reconnaissance techniques applicable to the benthic, beach intertidal...and beach upland zones. Task 1 is designed to develop remote sensing indicators of important beach composition and physical parameters which will...ultimately prove useful in models to predict beach conditions. Task 2 is designed to develop remote sensing techniques for survey of bottom features in

  17. Preface: Remote Sensing in Coastal Environments

    OpenAIRE

    Deepak R. Mishra; Gould, Richard W.

    2016-01-01

    The Special Issue (SI) on “Remote Sensing in Coastal Environments” presents a wide range of articles focusing on a variety of remote sensing models and techniques to address coastal issues and processes ranging for wetlands and water quality to coral reefs and kelp habitats. The SI is comprised of twenty-one papers, covering a broad range of research topics that employ remote sensing imagery, models, and techniques to monitor water quality, vegetation, habitat suitability, and geomorphology i...

  18. Data Quality in Remote Sensing

    Science.gov (United States)

    Batini, C.; Blaschke, T.; Lang, S.; Albrecht, F.; Abdulmutalib, H. M.; Barsi, Á.; Szabó, G.; Kugler, Zs.

    2017-09-01

    The issue of data quality (DQ) is of growing importance in Remote Sensing (RS), due to the widespread use of digital services (incl. apps) that exploit remote sensing data. In this position paper a body of experts from the ISPRS Intercommission working group III/IVb "DQ" identifies, categorises and reasons about issues that are considered as crucial for a RS research and application agenda. This ISPRS initiative ensures to build on earlier work by other organisations such as IEEE, CEOS or GEO, in particular on the meritorious work of the Quality Assurance Framework for Earth Observation (QA4EO) which was established and endorsed by the Committee on Earth Observation Satellites (CEOS) but aims to broaden the view by including experts from computer science and particularly database science. The main activities and outcomes include: providing a taxonomy of DQ dimensions in the RS domain, achieving a global approach to DQ for heterogeneous-format RS data sets, investigate DQ dimensions in use, conceive a methodology for managing cost effective solutions on DQ in RS initiatives, and to address future challenges on RS DQ dimensions arising in the new era of the big Earth data.

  19. Use of remote sensing in agriculture

    Science.gov (United States)

    Pettry, D. E.; Powell, N. L.; Newhouse, M. E.

    1974-01-01

    Remote sensing studies in Virginia and Chesapeake Bay areas to investigate soil and plant conditions via remote sensing technology are reported ant the results given. Remote sensing techniques and interactions are also discussed. Specific studies on the effects of soil moisture and organic matter on energy reflection of extensively occurring Sassafras soils are discussed. Greenhouse and field studies investigating the effects of chlorophyll content of Irish potatoes on infrared reflection are presented. Selected ground truth and environmental monitoring data are shown in summary form. Practical demonstrations of remote sensing technology in agriculture are depicted and future use areas are delineated.

  20. 利用云模型实现FSVM遥感影像分类的隶属度算法%USING CLOUD MODEL TO REALISE MEMBERSHIP ALGORITHM OF FSVM CLASSIFICATION OF REMOTE SENSING IMAGE

    Institute of Scientific and Technical Information of China (English)

    严信; 张月琴

    2013-01-01

    Remote sensing image classification encounters the problems of fuzziness in data boundary and uncertainty in interpretation process of remote sensing information.In light of this,and in combination with the characteristics of fuzzy support vector machine (FSVM) which can effectively avoid the interference of the noise samples in classification applications,we propose a method for solving the membership of fuzzy support vector machine which is based on cloud model.The method inputs the quantitative position of samples by the reverse cloud algorithm without membership requirement to obtain the numerical characteristics of sample categories,and then gets the membership of each sample to its qualitative category according to the positive cloud algorithm.Experimental results show that it is feasible to use membership of the cloud model-based fuzzy support vector machine on the classification of remote sensing image,and this can effectively improve the classification accuracy of the images.%针对遥感影像分类面临的数据边界模糊性以及遥感信息解译过程不确定性的问题,结合模糊支持向量机在分类应用中可以有效避免噪声样本干扰的特点,提出一种基于云模型求解模糊支持向量机隶属度的方法.该方法通过无需隶属度的逆向云算法输入样本的定量位置得到样本类别的数字特征,再根据正向云算法计算得到每个样本对其定性类别的隶属度.实验结果表明,采用基于云模型隶属度的模糊支持向量机对遥感影像的分类方法是可行的,并能够有效提高对遥感影像的分类精度.

  1. Geological remote sensing in Africa

    Science.gov (United States)

    Sabins, Floyd F., Jr.; Bailey, G. Bryan; Abrams, Michael J.

    1987-01-01

    Programs using remote sensing to obtain geologic information in Africa are reviewed. Studies include the use of Landsat MSS data to evaluate petroleum resources in sedimentary rock terrains in Kenya and Sudan and the use of Landsat TM 30-m resolution data to search for mineral deposits in an ophiolite complex in Oman. Digitally enhanced multispectral SPOT data at a scale of 1:62,000 were used to map folds, faults, diapirs, bedding attitudes, and stratigraphic units in the Atlas Mountains in northern Algeria. In another study, SIR-A data over a vegetated and faulted area of Sierra Leone were compared with data collected by the Landsat MSS and TM systems. It was found that the lineaments on the SIR-A data were more easily detected.

  2. Lunar remote sensing and measurements

    Science.gov (United States)

    Moore, H.J.; Boyce, J.M.; Schaber, G.G.; Scott, D.H.

    1980-01-01

    Remote sensing and measurements of the Moon from Apollo orbiting spacecraft and Earth form a basis for extrapolation of Apollo surface data to regions of the Moon where manned and unmanned spacecraft have not been and may be used to discover target regions for future lunar exploration which will produce the highest scientific yields. Orbital remote sensing and measurements discussed include (1) relative ages and inferred absolute ages, (2) gravity, (3) magnetism, (4) chemical composition, and (5) reflection of radar waves (bistatic). Earth-based remote sensing and measurements discussed include (1) reflection of sunlight, (2) reflection and scattering of radar waves, and (3) infrared eclipse temperatures. Photographs from the Apollo missions, Lunar Orbiters, and other sources provide a fundamental source of data on the geology and topography of the Moon and a basis for comparing, correlating, and testing the remote sensing and measurements. Relative ages obtained from crater statistics and then empirically correlated with absolute ages indicate that significant lunar volcanism continued to 2.5 b.y. (billion years) ago-some 600 m.y. (million years) after the youngest volcanic rocks sampled by Apollo-and that intensive bombardment of the Moon occurred in the interval of 3.84 to 3.9 b.y. ago. Estimated fluxes of crater-producing objects during the last 50 m.y. agree fairly well with fluxes measured by the Apollo passive seismic stations. Gravity measurements obtained by observing orbiting spacecraft reveal that mare basins have mass concentrations and that the volume of material ejected from the Orientale basin is near 2 to 5 million km 3 depending on whether there has or has not been isostatic compensation, little or none of which has occurred since 3.84 b.y. ago. Isostatic compensation may have occurred in some of the old large lunar basins, but more data are needed to prove it. Steady fields of remanent magnetism were detected by the Apollo 15 and 16 subsatellites

  3. Natural Resource Information System. Remote Sensing Studies.

    Science.gov (United States)

    Leachtenauer, J.; And Others

    A major design objective of the Natural Resource Information System entailed the use of remote sensing data as an input to the system. Potential applications of remote sensing data were therefore reviewed and available imagery interpreted to provide input to a demonstration data base. A literature review was conducted to determine the types and…

  4. Remote sensing and reflectance profiling in entomology

    Science.gov (United States)

    Remote sensing is about characterizing the status of objects and/or classifies their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be ground-based, and therefore acquired at a high spatial resolutio...

  5. Planning and Implementation of Remote Sensing Experiments.

    Science.gov (United States)

    Contents: TEKTITE II experiment-upwelling detection (NASA Mx 138); Design of oceanographic experiments (Gulf of Mexico, Mx 159); Design of oceanographic experiments (Gulf of Mexico, Mx 165); Experiments on thermal pollution; Remote sensing newsletter; Symposium on remote sensing in marine biology and fishery resources.

  6. Preface: Remote Sensing of Water Resources

    OpenAIRE

    Deepak R. Mishra; Eurico J. D’Sa; Sachidananda Mishra

    2016-01-01

    The Special Issue (SI) on “Remote Sensing of Water Resources” presents a diverse range of papers studying remote sensing tools, methods, and models to better monitor water resources which include inland, coastal, and open ocean waters. The SI is comprised of fifteen articles on widely ranging research topics related to water bodies. This preface summarizes each article published in the SI.

  7. Technology Progress Report for Microwave Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    JIANG Jingshan; DONG Xiaolong; LIU Heguang

    2004-01-01

    In this presentation, technological progress for China's microwave remote sensing is introduced. New developments of the microwave remote sensing instruments for China's lunar exploration satellite (Chang'E-1), meteorological satellite FY-3 and ocean dynamic measurement satellite (HY-2) are reported.

  8. An overview of GNSS remote sensing

    OpenAIRE

    Kegen, Yu; Rizos, Chris; Burrage, Derek; Dempster, Andrew; Zhang, Kefei; Markgraf, Markus

    2014-01-01

    The Global Navigation Satellite System (GNSS) signals are always available, globally, and the signal structures are well known, except for those dedicated to military use. They also have some distinctive characteristics, including the use of L-band frequencies, which are particularly suited for remote sensing purposes. The idea of using GNSS signals for remote sensing - the atmosphere, oceans or Earth surface - was first proposed more than two decades ago. Since then, GNSS remote ...

  9. MICROWAVE REMOTE SENSING IN SOIL QUALITY ASSESSMENT

    Directory of Open Access Journals (Sweden)

    S. K. Saha

    2012-08-01

    Full Text Available Information of spatial and temporal variations of soil quality (soil properties is required for various purposes of sustainable agriculture development and management. Traditionally, soil quality characterization is done by in situ point soil sampling and subsequent laboratory analysis. Such methodology has limitation for assessing the spatial variability of soil quality. Various researchers in recent past showed the potential utility of hyperspectral remote sensing technique for spatial estimation of soil properties. However, limited research studies have been carried out showing the potential of microwave remote sensing data for spatial estimation of various soil properties except soil moisture. This paper reviews the status of microwave remote sensing techniques (active and passive for spatial assessment of soil quality parameters such as soil salinity, soil erosion, soil physical properties (soil texture & hydraulic properties; drainage condition; and soil surface roughness. Past and recent research studies showed that both active and passive microwave remote sensing techniques have great potentials for assessment of these soil qualities (soil properties. However, more research studies on use of multi-frequency and full polarimetric microwave remote sensing data and modelling of interaction of multi-frequency and full polarimetric microwave remote sensing data with soil are very much needed for operational use of satellite microwave remote sensing data in soil quality assessment.

  10. Hyperspectral remote sensing for terrestrial applications

    Science.gov (United States)

    Thenkabail, Prasad S.; Teluguntla, Pardhasaradhi G.; Murali Krishna Gumma,; Venkateswarlu Dheeravath,

    2015-01-01

    Remote sensing data are considered hyperspectral when the data are gathered from numerous wavebands, contiguously over an entire range of the spectrum (e.g., 400–2500 nm). Goetz (1992) defines hyperspectral remote sensing as “The acquisition of images in hundreds of registered, contiguous spectral bands such that for each picture element of an image it is possible to derive a complete reflectance spectrum.” However, Jensen (2004) defines hyperspectral remote sensing as “The simultaneous acquisition of images in many relatively narrow, contiguous and/or non contiguous spectral bands throughout the ultraviolet, visible, and infrared portions of the electromagnetic spectrum.

  11. An international organization for remote sensing

    Science.gov (United States)

    Helm, Neil R.; Edelson, Burton I.

    1991-01-01

    A recommendation is presented for the formation of a new commercially oriented international organization to acquire or develop, coordinate or manage, the space and ground segments for a global operational satellite system to furnish the basic data for remote sensing and meteorological, land, and sea resource applications. The growing numbers of remote sensing programs are examined and possible ways of reducing redundant efforts and improving the coordination and distribution of these global efforts are discussed. This proposed remote sensing organization could play an important role in international cooperation and the distribution of scientific, commercial, and public good data.

  12. Remote sensing and urban public health

    Science.gov (United States)

    Rush, M.; Vernon, S.

    1975-01-01

    The applicability of remote sensing in the form of aerial photography to urban public health problems is examined. Environmental characteristics are analyzed to determine if health differences among areas could be predicted from the visual expression of remote sensing data. The analysis is carried out on a socioeconomic cross-sectional sample of census block groups. Six morbidity and mortality rates are the independent variables while environmental measures from aerial photographs and from the census constitute the two independent variable sets. It is found that environmental data collected by remote sensing are as good as census data in evaluating rates of health outcomes.

  13. Preface: Remote Sensing in Coastal Environments

    Directory of Open Access Journals (Sweden)

    Deepak R. Mishra

    2016-08-01

    Full Text Available The Special Issue (SI on “Remote Sensing in Coastal Environments” presents a wide range of articles focusing on a variety of remote sensing models and techniques to address coastal issues and processes ranging for wetlands and water quality to coral reefs and kelp habitats. The SI is comprised of twenty-one papers, covering a broad range of research topics that employ remote sensing imagery, models, and techniques to monitor water quality, vegetation, habitat suitability, and geomorphology in the coastal zone. This preface provides a brief summary of each article published in the SI.

  14. Suntracker for atmospheric remote sensing

    Science.gov (United States)

    Hawat, Toufic-Michel; Camy-Peyret, Claude; Torguet, Roger J.

    1998-05-01

    A heliostat is designed and built to track the sun for optical remote sensing of the stratosphere from a balloon- borne pointed gondola. The tracking mechanism is controlled by two direct torque motors used to drive a single flat acquisition mirror. A horizontal turntable, rigidly attached to the azimuth drive, supports the elevation assembly. A position sensor receiving a small part of the solar beam reflected off the main acquisition mirror is used for the fine servo control. Using a CCD camera prepointing of the acquisition mirror is achieved when the sun is in the field of view of the heliostat. This system is coupled with a high-resolution (0.02-cm-1) Fourier transform IR spectrometer to retrieve stratospheric trace species concentration profiles. The suntracker directs the solar radiation in a stable direction along the spectrometer optical axis. The pointing precision is 1 arcmin from a stratospheric gondola, which has static and dynamic angular excursions up to 6 deg. The heliostat coupled to the Limb Profile Monitor of the Atmosphere instrument performs successfully on several balloon flights. The description, ground tests, and balloon flight results of the suntracker are presented.

  15. Remote sensing applications to hydrologic modeling

    Science.gov (United States)

    Dozier, J.; Estes, J. E.; Simonett, D. S.; Davis, R.; Frew, J.; Marks, D.; Schiffman, K.; Souza, M.; Witebsky, E.

    1977-01-01

    An energy balance snowmelt model for rugged terrain was devised and coupled to a flow model. A literature review of remote sensing applications to hydrologic modeling was included along with a software development outline.

  16. Hyperspectral remote sensing for light pollution monitoring

    Directory of Open Access Journals (Sweden)

    P. Marcoionni

    2006-06-01

    Full Text Available industries. In this paper we introduce the results from a remote sensing campaign performed in September 2001 at night time. For the first time nocturnal light pollution was measured at high spatial and spectral resolution using two airborne hyperspectral sensors, namely the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS and the Visible InfraRed Scanner (VIRS-200. These imagers, generally employed for day-time Earth remote sensing, were flown over the Tuscany coast (Italy on board of a Casa 212/200 airplane from an altitude of 1.5-2.0 km. We describe the experimental activities which preceded the remote sensing campaign, the optimization of sensor configuration, and the images as far acquired. The obtained results point out the novelty of the performed measurements and highlight the need to employ advanced remote sensing techniques as a spectroscopic tool for light pollution monitoring.

  17. Application of Spaceborne Remote Sensing to Archaeology

    Science.gov (United States)

    Crippen, Robert E.

    1997-01-01

    Spaceborne remote sensing data have been underutilized in archaeology for a variety of seasons that are slowly but surely being overcome. Difficulties have included cost/availability of data, inadequate resolution, and data processing issues.

  18. GNSS remote sensing theory, methods and applications

    CERN Document Server

    Jin, Shuanggen; Xie, Feiqin

    2014-01-01

    This book presents the theory and methods of GNSS remote sensing as well as its applications in the atmosphere, oceans, land and hydrology. It contains detailed theory and study cases to help the reader put the material into practice.

  19. NOAA Coastal Mapping Remote Sensing Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Remote Sensing Division is responsible for providing data to support the Coastal Mapping Program, Emergency Response efforts, and the Aeronautical Survey Program...

  20. Biophysical applications of satellite remote sensing

    CERN Document Server

    Hanes, Jonathan

    2014-01-01

    Including an introduction and historical overview of the field, this comprehensive synthesis of the major biophysical applications of satellite remote sensing includes in-depth discussion of satellite-sourced biophysical metrics such as leaf area index.

  1. Integrating spatial statistics and remote sensing.

    NARCIS (Netherlands)

    Stein, A.; Bastiaanssen, W.G.M.; Bruin, de S.; Cracknell, A.P.; Curran, P.J.; Fabbri, A.G.; Gorte, B.G.H.; Groenigen, van J.W.; Meer, van der F.D.; Saldana, A.

    1998-01-01

    This paper presents an integrated approach towards spatial statistics for remote sensing. Using the layer concept in Geographical Information Systems we treat successively elements of spatial statistics, scale, classification, sampling and decision support. The layer concept allows to combine contin

  2. Remote sensing, imaging, and signal engineering

    Energy Technology Data Exchange (ETDEWEB)

    Brase, J.M.

    1993-03-01

    This report discusses the Remote Sensing, Imaging, and Signal Engineering (RISE) trust area which has been very active in working to define new directions. Signal and image processing have always been important support for existing programs at Lawrence Livermore National Laboratory (LLNL), but now these technologies are becoming central to the formation of new programs. Exciting new applications such as high-resolution telescopes, radar remote sensing, and advanced medical imaging are allowing us to participate in the development of new programs.

  3. Freeware for GIS and Remote Sensing

    Directory of Open Access Journals (Sweden)

    Lena Halounová

    2007-12-01

    Full Text Available Education in remote sensing and GIS is based on software utilization. The software needs to be installed in computer rooms with a certain number of licenses. The commercial software equipment is therefore financially demanding and not only for universities, but especially for students. Internet research brings a long list of free software of various capabilities. The paper shows a present state of GIS, image processing and remote sensing free software.

  4. Preface: Remote Sensing of Water Resources

    Directory of Open Access Journals (Sweden)

    Deepak R. Mishra

    2016-02-01

    Full Text Available The Special Issue (SI on “Remote Sensing of Water Resources” presents a diverse range of papers studying remote sensing tools, methods, and models to better monitor water resources which include inland, coastal, and open ocean waters. The SI is comprised of fifteen articles on widely ranging research topics related to water bodies. This preface summarizes each article published in the SI.

  5. Talisman-Saber 2009 Remote Sensing Experiment

    Science.gov (United States)

    2012-03-30

    Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/7230--12-9404 Talisman -Saber 2009 Remote Sensing Experiment March 30, 2012 Approved for... Talisman -Saber 2009 Remote Sensing Experiment Charles M. Bachmann, Robert A. Fusina, Marcos J. Montes, Rong-Rong Li, Carl Gross, C. Reid Nichols,* John C...sensor were used to build shallow water bathymetric charts and trafficability maps that were provided to military planners during Exercise Talisman

  6. Remote Sensing Digital Image Analysis An Introduction

    CERN Document Server

    Richards, John A

    2013-01-01

    Remote Sensing Digital Image Analysis provides the non-specialist with a treatment of the quantitative analysis of satellite and aircraft derived remotely sensed data. Since the first edition of the book there have been significant developments in the algorithms used for the processing and analysis of remote sensing imagery; nevertheless many of the fundamentals have substantially remained the same.  This new edition presents material that has retained value since those early days, along with new techniques that can be incorporated into an operational framework for the analysis of remote sensing data. The book is designed as a teaching text for the senior undergraduate and postgraduate student, and as a fundamental treatment for those engaged in research using digital image processing in remote sensing.  The presentation level is for the mathematical non-specialist.  Since the very great number of operational users of remote sensing come from the earth sciences communities, the text is pitched at a leve...

  7. 云计算环境下新疆遥感应用数据中心的挑战与机遇%Challenges and Opportunities of Xinjiang Remote Sensing Data Center in the Cloud Computing Environment

    Institute of Scientific and Technical Information of China (English)

    钱育蓉; 于炯; 英昌甜; 杨兴耀; 鲁亮; 卞琛

    2015-01-01

    With the rapid growth of data volume and high energy consumption of data center, the fact that current framework of cloud computing (GFS, HDFS) haven't took into account the energy consumption factors in design process gradually comes into the light. As a result, the entire computing nodes must remain active to maintain the system availability and reliability when the workload is very low. To solve this problem, Combining with the characteristics of heterogeneous remote big sensing data (spatial, spectral resolution, etc.) and application characteristics (browse, display, access, etc.), the author proposes the following suggestions about the storage and management of remote sensing data under cloud computing environment in Xinjiang. On one hand, data organization and replication strategy of node sleep technology are adopted in distributed file system. On the other hand, self-adaptive virtual machine dynamic migration technology could achieve idle node dormancy. In order to improve the adaptability of virtualized cloud computing platform in data layer to the achieve energy conservation calculation, soft energy saving technology is utilized, thus realizing the energy conservation, high efficiency, transparent remote storage management of big remote data in cloud computing environment.%遥感数据量的飞速增长和数据中心的高能耗逐渐暴露出现有云计算框架(GFS、HDFS等)在设计时缺少对能耗因素的考虑,使得负载很低时系统中所有计算节点仍需保持活动状态来维持系统可用性与可靠性.为此本文从新疆云计算数据中心的设计着手,结合异构遥感大数据的数据特征(时空、光谱、分辨率等)和应用特点(浏览,显示,存取等),提出了云计算环境下遥感大数据存储和管理的建议:1.在分布式文件系统中采用节点休眠技术的数据组织和副本策略;2.通过自适应的虚拟机动态迁移技术实现空闲节点休眠.利用软节能技术改进虚拟化

  8. Remote Sensing of Liquid Water and Ice Cloud Optical Thickness and Effective Radius in the Arctic: Application of Airborne Multispectral MAS Data

    Science.gov (United States)

    King, Michael D.; Platnick, Steven; Yang, Ping; Arnold, G. Thomas; Gray, Mark A.; Riedi, Jerome C.; Ackerman, Steven A.; Liou, Kuo-Nan

    2003-01-01

    A multispectral scanning spectrometer was used to obtain measurements of the reflection function and brightness temperature of clouds, sea ice, snow, and tundra surfaces at 50 discrete wavelengths between 0.47 and 14.0 microns. These observations were obtained from the NASA ER-2 aircraft as part of the FIRE Arctic Clouds Experiment, conducted over a 1600 x 500 km region of the north slope of Alaska and surrounding Beaufort and Chukchi Seas between 18 May and 6 June 1998. Multispectral images of the reflection function and brightness temperature in 11 distinct bands of the MODIS Airborne Simulator (MAS) were used to derive a confidence in clear sky (or alternatively the probability of cloud), shadow, and heavy aerosol over five different ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (water, ice, or undetermined phase). Finally, the cloud optical thickness and effective radius were derived for both water and ice clouds that were detected during one flight line on 4 June. This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS data in Alaska, is quite capable of distinguishing clouds from bright sea ice surfaces during daytime conditions in the high Arctic. Results of individual tests, however, make it difficult to distinguish ice clouds over snow and sea ice surfaces, so additional tests were added to enhance the confidence in the thermodynamic phase of clouds over the Beaufort Sea. The cloud optical thickness and effective radius retrievals used 3 distinct bands of the MAS, with the newly developed 1.62 and 2.13 micron bands being used quite successfully over snow and sea ice surfaces. These results are contrasted with a MODIS-based algorithm that relies on spectral reflectance at 0.87 and 2.13 micron.

  9. Tunnel-Site Selection by Remote Sensing Techniques

    Science.gov (United States)

    A study of the role of remote sensing for geologic reconnaissance for tunnel-site selection was commenced. For this study, remote sensing was defined...conventional remote sensing . Future research directions are suggested, and the extension of remote sensing to include airborne passive microwave

  10. Remote Sensing Best Paper Award for the Year 2014

    OpenAIRE

    Prasad Thenkabail

    2014-01-01

    Remote Sensing has started to institute a “Best Paper” award to recognize the most outstanding papers in the area of remote sensing techniques, design and applications published in Remote Sensing. We are pleased to announce the first “Remote Sensing Best Paper Award” for the year 2014.

  11. Research Dynamics of the Classification Methods of Remote Sensing Images

    Institute of Scientific and Technical Information of China (English)

    Yan; ZHANG; Baoguo; WU; Dong; WANG

    2013-01-01

    As the key technology of extracting remote sensing information,the classification of remote sensing images has always been the research focus in the field of remote sensing. The paper introduces the classification process and system of remote sensing images. According to the recent research status of domestic and international remote sensing classification methods,the new study dynamics of remote sensing classification,such as artificial neural networks,support vector machine,active learning and ensemble multi-classifiers,were introduced,providing references for the automatic and intelligent development of remote sensing images classification.

  12. Research Methods on Cloud and Fog Removal Processing of Remote Sensing Images%遥感图像薄云薄雾的去除处理方法

    Institute of Scientific and Technical Information of China (English)

    王敏; 周树道; 刘志华; 黄峰; 梁妙元

    2011-01-01

    Image processing research on cloud and fog removing has become a hot research topic of computer vision. At present,there are many algorithms for cloud and fog removal presented by domestic and international scholars. This article analyzed the influence of the cloud and fog to the image, and summary to the references, then introduced respectively the main principle and research of various existing cloud and fog removal methods, including fog removing methods based on physical model and image processing, multispectral cloud removing, image fusion cloud removing and homomorphic filter cloud removing. Also it discussed the advantage and limit of the processing algorithm. Finally, an outlook to the cloud and fog removing image processing methods was carried on.%分析云雾对图像的影响,对相关文献进行了分析总结,分别介绍了现有的各种薄云薄雾去除方法的主要原理及研究现状等,包括有基于物理模型和基于图像处理的薄雾去除方法,光谱图像去云、图像融合去云、同态滤波去云方法,并讨论了各处理方法的优势及局限.最后,对云雾去除图像处理方法进行了展望.

  13. Remote Sensing of Active Volcanoes

    Science.gov (United States)

    Francis, Peter; Rothery, David

    The synoptic coverage offered by satellites provides unparalleled opportunities for monitoring active volcanoes, and opens new avenues of scientific inquiry. Thermal infrared radiation can be used to monitor levels of activity, which is useful for automated eruption detection and for studying the emplacement of lava flows. Satellite radars can observe volcanoes through clouds or at night, and provide high-resolution topographic data. In favorable conditions, radar inteferometery can be used to measure ground deformation associated with eruptive activity on a centimetric scale. Clouds from explosive eruptions present a pressing hazard to aviation; therefore, techniques are being developed to assess eruption cloud height and to discriminate between ash and meterological clouds. The multitude of sensors to be launched on future generations of space platforms promises to greatly enhance volcanological studies, but a satellite dedicated to volcanology is needed to meet requirements of aviation safety and volcano monitoring.

  14. Near-earth orbital guidance and remote sensing

    Science.gov (United States)

    Powers, W. F.

    1972-01-01

    The curriculum of a short course in remote sensing and parameter optimization is presented. The subjects discussed are: (1) basics of remote sensing and the user community, (2) multivariant spectral analysis, (3) advanced mathematics and physics of remote sensing, (4) the atmospheric environment, (5) imaging sensing, and (6)nonimaging sensing. Mathematical models of optimization techniques are developed.

  15. Sensing our Environment: Remote sensing in a physics classroom

    Science.gov (United States)

    Isaacson, Sivan; Schüttler, Tobias; Cohen-Zada, Aviv L.; Blumberg, Dan G.; Girwidz, Raimund; Maman, Shimrit

    2017-04-01

    Remote sensing is defined as data acquisition of an object, deprived physical contact. Fundamentally, most remote sensing applications are referred to as the use of satellite- or aircraft-based sensor technologies to detect and classify objects mainly on Earth or other planets. In the last years there have been efforts to bring the important subject of remote sensing into schools, however, most of these attempts focused on geography disciplines - restricting to the applications of remote sensing and to a less extent the technique itself and the physics behind it. Optical remote sensing is based on physical principles and technical devices, which are very meaningful from a theoretical point of view as well as for "hands-on" teaching. Some main subjects are radiation, atom and molecular physics, spectroscopy, as well as optics and the semiconductor technology used in modern digital cameras. Thus two objectives were outlined for this project: 1) to investigate the possibilities of using remote sensing techniques in physics teaching, and 2) to identify its impact on pupil's interest in the field of natural sciences. This joint project of the DLR_School_Lab, Oberpfaffenhofen of the German Aerospace Center (DLR) and the Earth and Planetary Image Facility (EPIF) at BGU, was conducted in 2016. Thirty teenagers (ages 16-18) participated in the project and were exposed to the cutting edge methods of earth observation. The pupils on both sides participated in the project voluntarily, knowing that at least some of the project's work had to be done in their leisure time. The pupil's project started with a day at EPIF and DLR respectively, where the project task was explained to the participants and an introduction to remote sensing of vegetation was given. This was realized in lectures and in experimental workshops. During the following two months both groups took several measurements with modern optical remote sensing systems in their home region with a special focus on flora

  16. Drought impacts on the Amazon forest: the remote sensing perspective.

    Science.gov (United States)

    Asner, Gregory P; Alencar, Ane

    2010-08-01

    Drought varies spatially and temporally throughout the Amazon basin, challenging efforts to assess ecological impacts via field measurements alone. Remote sensing offers a range of regional insights into drought-mediated changes in cloud cover and rainfall, canopy physiology, and fire. Here, we summarize remote sensing studies of Amazônia which indicate that: fires and burn scars are more common during drought years; hydrological function including floodplain area is significantly affected by drought; and land use affects the sensitivity of the forest to dry conditions and increases fire susceptibility during drought. We highlight two controversial areas of research centering on canopy physiological responses to drought and changes in subcanopy fires during drought. By comparing findings from field and satellite studies, we contend that current remote sensing observations and techniques cannot resolve these controversies using current satellite observations. We conclude that studies integrating multiple lines of evidence from physiological, disturbance-fire, and hydrological remote sensing, as well as field measurements, are critically needed to narrow our uncertainty of basin-level responses to drought and climate change.

  17. Multiscale and Multitemporal Urban Remote Sensing

    Science.gov (United States)

    Mesev, V.

    2012-07-01

    The remote sensing of urban areas has received much attention from scientists conducting studies on measuring sprawl, congestion, pollution, poverty, and environmental encroachment. Yet much of the research is case and data-specific where results are greatly influenced by prevailing local conditions. There seems to be a lack of epistemological links between remote sensing and conventional theoretical urban geography; in other words, an oversight for the appreciation of how urban theory fuels urban change and how urban change is measured by remotely sensed data. This paper explores basic urban theories such as centrality, mobility, materiality, nature, public space, consumption, segregation and exclusion, and how they can be measured by remote sensing sources. In particular, the link between structure (tangible objects) and function (intangible or immaterial behavior) is addressed as the theory that supports the wellknow contrast between land cover and land use classification from remotely sensed data. The paper then couches these urban theories and contributions from urban remote sensing within two analytical fields. The first is the search for an "appropriate" spatial scale of analysis, which is conveniently divided between micro and macro urban remote sensing for measuring urban structure, understanding urban processes, and perhaps contributions to urban theory at a variety of scales of analysis. The second is on the existence of a temporal lag between materiality of urban objects and the planning process that approved their construction, specifically how time-dependence in urban structural-functional models produce temporal lags that alter the causal links between societal and political functional demands and structural ramifications.

  18. remote sensing data combinations - global AOD maps

    Science.gov (United States)

    Kinne, S.

    2009-04-01

    More accurate and more complete measurement-based data-sets are needed to constrain the freedom of global modeling and raise confidence in model predictions. In remote sensing, different methods and sensors frequently yield estimates for the same (or a strongly related) atmospheric property. For maximum benefit to data-users (e.g. input or evaluation data to modeling) - in the context of differences in sensor capabilities and retrieval limitations - there is a desire to combine the strengths of these individual data sources for superior products. In a demonstration, different multi-annual global monthly maps for aerosol optical depth (AOD) from satellite remote sensing been compared and scored against local quality reference data from ground remote sensing. The regionally best performing satellite data-sets have been combined into global monthly AOD maps. As expected, this satellite composite scores better than any individual satellite retrieval. Further improvements are achieved by merging statistics of ground remote sensing into the composite. The global average mid-visible AOD of this remote sensing composite is near 0.13 annually, with lower values during northern hemispheric fall and winter (0.12) and larger values during northern hemispheric spring and summer (0.14). This measurement based data composite also reveals characteristic deficiencies in global modeling: Modeling tends to overestimates AOD over the northern mid-latitudes and to underestimate AOD over tropical and sub-tropical land regions. Also noteworthy are AOD underestimates by modeling in remote oceanic regions, though only in relative sense as AOD values in that region as small. The AOD remote sensing data composite is far from perfect, but it demonstrates the extra value of data-combinations.

  19. Remote sensing of ecology, biodiversity and conservation: a review from the perspective of remote sensing specialists.

    Science.gov (United States)

    Wang, Kai; Franklin, Steven E; Guo, Xulin; Cattet, Marc

    2010-01-01

    Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC). Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI), inversion algorithm, data fusion, and the integration of remote sensing (RS) and geographic information system (GIS).

  20. Remote Sensing of Ecology, Biodiversity and Conservation: A Review from the Perspective of Remote Sensing Specialists

    Directory of Open Access Journals (Sweden)

    Marc Cattet

    2010-11-01

    Full Text Available Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC. Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI, inversion algorithm, data fusion, and the integration of remote sensing (RS and geographic information system (GIS.

  1. Polarimetric remote sensing of the Earth from satellites: a perspective

    Science.gov (United States)

    Mishchenko, M. I.; Glory APS Science Team

    2011-12-01

    Aerosol and cloud particles exert a strong influence on the regional and global climates of the Earth. More often than not it is impossible to collect samples of such particles and subject them to a laboratory test. Therefore, in most cases one has to rely on theoretical analyses of remote measurements of the electromagnetic radiation scattered by the particles. Fortunately, the scattering and absorption properties of small particles often exhibit a strong dependence on their size, shape, orientation, and refractive index. This factor makes remote sensing an extremely useful and often the only practicable means of physical and chemical particle characterization in atmospheric physics. For a long time remote-sensing studies had relied on measurements of only the scattered intensity and its spectral dependence. Eventually, however, it has become widely recognized that polarimetric characteristics of the scattered radiation contain much more accurate and specific information about such important properties of particles as their size, morphology, and chemical composition. The progress in polarimetric remote-sensing research has always been hampered by the fact that the human eye is "polarization blind" and responds only to the intensity of light impinging on the retina. As a consequence, to give a simple definition of polarization readily intelligible to a non-expert is almost as difficult as to describe color to a color-blind person. However, continuing progress in electromagnetic scattering theory coupled with great advances in the polarization measurement capability has resulted in overwhelming examples of the immense practical power of polarimetric remote sensing which are no longer possible to ignore. As a result of persistent research efforts, polarimetry has become one of the most informative, accurate, and efficient means of terrestrial remote sensing. The only space-borne polarimeter flown around the Earth has been the French instrument POLDER. The recent

  2. Microwave Radiometry in Remote Sensing

    DEFF Research Database (Denmark)

    Gudmandsen, Preben

    1982-01-01

    Microwave radiometry has shown its capabilities of observing and monitoring large-scale geophysical observables from space. Examples are sea surface temperature and surface wind over the ocean, sea ice extent, concentration and category and snow cover extent and water content. At low microwave...... frequencies the atmosphere is virtually transparent even with clouds which make microwave radiometry very valuable in regions with frequent cloud cover such as the temperate and arctic zones. At high frequencies, however, atmospheric absorption will degrade measurements of earth surfaces but this phenomenon...

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

    Science.gov (United States)

    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.

  4. Remote sensing applications in environmental research

    CERN Document Server

    Srivastava, Prashant K; Gupta, Manika; Islam, Tanvir

    2014-01-01

    Remote Sensing Applications in Environmental Research is the basis for advanced Earth Observation (EO) datasets used in environmental monitoring and research. Now that there are a number of satellites in orbit, EO has become imperative in today's sciences, weather and natural disaster prediction. This highly interdisciplinary reference work brings together diverse studies on remote sensing and GIS, from a theoretical background to its applications, represented through various case studies and the findings of new models. The book offers a comprehensive range of contributions by well-known scientists from around the world and opens a new window for students in presenting interdisciplinary and methodological resources on the latest research. It explores various key aspects and offers state-of-the-art research in a simplified form, describing remote sensing and GIS studies for those who are new to the field, as well as for established researchers.

  5. Thermal infrared remote sensing sensors, methods, applications

    CERN Document Server

    Kuenzer, Claudia

    2013-01-01

    This book provides a comprehensive overview of the state of the art in the field of thermal infrared remote sensing. Temperature is one of the most important physical environmental variables monitored by earth observing remote sensing systems. Temperature ranges define the boundaries of habitats on our planet. Thermal hazards endanger our resources and well-being. In this book renowned international experts have contributed chapters on currently available thermal sensors as well as innovative plans for future missions. Further chapters discuss the underlying physics and image processing techni

  6. Remotely sensing the photochemical reflectance index, PRI

    Science.gov (United States)

    Vanderbilt, Vern; Daughtry, Craig; Dahlgren, Robert

    2015-09-01

    In remote sensing, the Photochemical Reflectance Index (PRI) provides insight into physiological processes occurring inside leaves in a plant stand. Developed by1,2, PRI evolved from laboratory reflectance measurements of individual leaves. Yet in a remotely sensed image, a pixel measurement may include light from both reflecting and transmitting leaves. We compared values of PRI based upon polarized reflectance and transmittance measurements of water and nutrient stressed leaves. Our results show the polarized leaf surface reflection should be removed when calculating PRI and that the leaf physiology information is in leaf interior reflectance, not leaf transmittance.

  7. Offshore winds mapped from satellite remote sensing

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    2014-01-01

    the uncertainty on the model results on the offshore wind resource, it is necessary to compare model results with observations. Observations from ground-based wind lidar and satellite remote sensing are the two main technologies that can provide new types of offshore wind data at relatively low cost....... The advantages of microwave satellite remote sensing are 1) horizontal spatial coverage, 2) long data archives and 3) high spatial detail both in the coastal zone and of far-field wind farm wake. Passive microwave ocean wind speed data are available since 1987 with up to 6 observations per day with near...

  8. Monitoring water quality by remote sensing

    Science.gov (United States)

    Brown, R. L. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. A limited study was conducted to determine the applicability of remote sensing for evaluating water quality conditions in the San Francisco Bay and delta. Considerable supporting data were available for the study area from other than overflight sources, but short-term temporal and spatial variability precluded their use. The study results were not sufficient to shed much light on the subject, but it did appear that, with the present state of the art in image analysis and the large amount of ground truth needed, remote sensing has only limited application in monitoring water quality.

  9. Space remote sensing systems an introduction

    CERN Document Server

    Chen, H S

    1985-01-01

    Space Remote Sensing Systems: An Introduction discusses the space remote sensing system, which is a modern high-technology field developed from earth sciences, engineering, and space systems technology for environmental protection, resource monitoring, climate prediction, weather forecasting, ocean measurement, and many other applications. This book consists of 10 chapters. Chapter 1 describes the science of the atmosphere and the earth's surface. Chapter 2 discusses spaceborne radiation collector systems, while Chapter 3 focuses on space detector and CCD systems. The passive space optical rad

  10. Geobotanical Remote Sensing for Geothermal Exploration

    Energy Technology Data Exchange (ETDEWEB)

    Pickles, W L; Kasameyer, P W; Martini, B A; Potts, D C; Silver, E A

    2001-05-22

    This paper presents a plan for increasing the mapped resource base for geothermal exploration in the Western US. We plan to image large areas in the western US with recently developed high resolution hyperspectral geobotanical remote sensing tools. The proposed imaging systems have the ability to map visible faults, surface effluents, historical signatures, and discover subtle hidden faults and hidden thermal systems. Large regions can be imaged at reasonable costs. The technique of geobotanical remote sensing for geothermal signatures is based on recent successes in mapping faults and effluents the Long Valley Caldera and Mammoth Mountain in California.

  11. Remote sensing of land surface phenology

    Science.gov (United States)

    Meier, G.A.; Brown, J.F.

    2014-01-01

    Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

  12. A technology path to distributed remote sensing

    Science.gov (United States)

    Fountain, Glen H.; Gold, Robert E.; Jenkins, Robert E.; Lew, Ark L.; Raney, R. Keith

    2000-03-01

    The Johns Hopkins University Applied Physics Laboratory (APL) has been engaged for over 40 years in Earth science missions spanning geodesy to atmospheric science. In parallel, APL's Advanced Technology Program is supporting research in autonomy, scalable architectures, miniaturization, and instrument innovation. These are key technologies for the development of affordable observation programs that could benefit from distributed remote sensing. This paper brings these applications and technology themes together in the form of an innovative, three-satellite remote sensing scenario. This pathfinding mission fills an important scientific niche, and relies on state-of-the-art small-satellite technology.

  13. Remote sensing/vegetation classification. [California

    Science.gov (United States)

    Parker, I. E.

    1981-01-01

    The CALVEG classification system for identification of vegetation is described. This hierarchical system responds to classification requirements and to interpretation of vegetation at various description levels, from site description to broad identification levels. The system's major strength is its flexibility in application of remote sensing technology to assess, describe and communicate data relative to vegetative resources on a state-wide basis. It is concluded that multilevel remote sensing is a cost effective tool for assessment of the natural resource base. The CLAVEG system is found to be an economically efficient tool for both existing and potential vegetation.

  14. Kite Aerial Photography as a Tool for Remote Sensing

    Science.gov (United States)

    Sallee, Jeff; Meier, Lesley R.

    2010-01-01

    As humans, we perform remote sensing nearly all the time. This is because we acquire most of our information about our surroundings through the senses of sight and hearing. Whether viewed by the unenhanced eye or a military satellite, remote sensing is observing objects from a distance. With our current technology, remote sensing has become a part…

  15. Kite Aerial Photography as a Tool for Remote Sensing

    Science.gov (United States)

    Sallee, Jeff; Meier, Lesley R.

    2010-01-01

    As humans, we perform remote sensing nearly all the time. This is because we acquire most of our information about our surroundings through the senses of sight and hearing. Whether viewed by the unenhanced eye or a military satellite, remote sensing is observing objects from a distance. With our current technology, remote sensing has become a part…

  16. Recent Progresses in Atmospheric Remote Sensing Research in China-- Chinese National Report on Atmospheric Remote Sensing Research in China during 1999-2003

    Institute of Scientific and Technical Information of China (English)

    邱金桓; 陈洪滨

    2004-01-01

    Progresses of atmospheric remote sensing research in China during 1999-2003 are summarily introduced.This research includes: (1) microwave remote sensing of the atmosphere; (2) Lidar remote sensing; (3)remote sensing of aerosol optical properties; and (4) other research related to atmospheric remote sensing,including GPS remote sensing of precipitable water vapor and radiation model development.

  17. Satellite Remote Sensing in Seismology. A Review

    Directory of Open Access Journals (Sweden)

    Andrew A. Tronin

    2009-12-01

    Full Text Available A wide range of satellite methods is applied now in seismology. The first applications of satellite data for earthquake exploration were initiated in the ‘70s, when active faults were mapped on satellite images. It was a pure and simple extrapolation of airphoto geological interpretation methods into space. The modern embodiment of this method is alignment analysis. Time series of alignments on the Earth's surface are investigated before and after the earthquake. A further application of satellite data in seismology is related with geophysical methods. Electromagnetic methods have about the same long history of application for seismology. Stable statistical estimations of ionosphere-lithosphere relation were obtained based on satellite ionozonds. The most successful current project "DEMETER" shows impressive results. Satellite thermal infra-red data were applied for earthquake research in the next step. Numerous results have confirmed previous observations of thermal anomalies on the Earth's surface prior to earthquakes. A modern trend is the application of the outgoing long-wave radiation for earthquake research. In ‘80s a new technology—satellite radar interferometry—opened a new page. Spectacular pictures of co-seismic deformations were presented. Current researches are moving in the direction of pre-earthquake deformation detection. GPS technology is also widely used in seismology both for ionosphere sounding and for ground movement detection. Satellite gravimetry has demonstrated its first very impressive results on the example of the catastrophic Indonesian earthquake in 2004. Relatively new applications of remote sensing for seismology as atmospheric sounding, gas observations, and cloud analysis are considered as possible candidates for applications.

  18. Wind Predictability and Remote Sensing Techniques,

    Science.gov (United States)

    The report presents the unclassified findings from the Investigation of Airborne Wind Sensing Systems conducted under AIRTASK A30303/323/70F17311002. Included is a summary of the current accuracy of wind speed and direction forecasts, a list of possible methods for remote sensing meteorological data, a list of areas of application of the given methods and a list of contacts made for information relevant to this evaluation. (Author)

  19. Studies of 3D-cloud optical depth from small to very large values, and of the radiation and remote sensing impacts of larger-drop clustering

    Energy Technology Data Exchange (ETDEWEB)

    Wiscombe, Warren [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Marshak, Alexander [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Knyazikhin, Yuri [Boston Univ., MA (United States); Chiu, Christine [Univ. of Maryland Baltimore County (UMBC), Baltimore, MD (United States)

    2007-05-04

    We have basically completed all the goals stated in the previous proposal and published or submitted journal papers thereon, the only exception being First-Principles Monte Carlo which has taken more time than expected. We finally finished the comprehensive book on 3D cloud radiative transfer (edited by Marshak and Davis and published by Springer), with many contributions by ARM scientists; this book was highlighted in the 2005 ARM Annual Report. We have also completed (for now) our pioneering work on new models of cloud drop clustering based on ARM aircraft FSSP data, with applications both to radiative transfer and to rainfall. This clustering work was highlighted in the FY07 “Our Changing Planet” (annual report of the US Climate Change Science Program). Our group published 22 papers, one book, and 5 chapters in that book, during this proposal period. All are listed at the end of this section. Below, we give brief highlights of some of those papers.

  20. Satellite Remote Sensing in Offshore Wind Energy

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Astrup, Poul

    2013-01-01

    Satellite remote sensing of ocean surface winds are presented with focus on wind energy applications. The history on operational and research-based satellite ocean wind mapping is briefly described for passive microwave, scatterometer and synthetic aperture radar (SAR). Currently 6 GW installed...

  1. Remote sensing and today's forestry issues

    Science.gov (United States)

    Sayn-Wittgenstein, L.

    1977-01-01

    The actual and the desirable roles of remote sensing in dealing with current forestry issues, such as national forest policy, supply and demand for forest products and competing demands for forest land are discussed. Topics covered include wood shortage, regional timber inventories, forests in tropical and temperate zones, Skylab photography, forest management and protection, available biomass studies, and monitoring.

  2. Satellite Remote Sensing for Monitoring and Assessment

    Science.gov (United States)

    Remote sensing technology has the potential to enhance the engagement of communities and managers in the implementation and performance of best management practices. This presentation will use examples from U.S. numeric criteria development and state water quality monitoring prog...

  3. Multisensor image fusion guidelines in remote sensing

    Science.gov (United States)

    Pohl, C.

    2016-04-01

    Remote sensing delivers multimodal and -temporal data from the Earth's surface. In order to cope with these multidimensional data sources and to make the most of them, image fusion is a valuable tool. It has developed over the past few decades into a usable image processing technique for extracting information of higher quality and reliability. As more sensors and advanced image fusion techniques have become available, researchers have conducted a vast amount of successful studies using image fusion. However, the definition of an appropriate workflow prior to processing the imagery requires knowledge in all related fields - i.e. remote sensing, image fusion and the desired image exploitation processing. From the findings of this research it can be seen that the choice of the appropriate technique, as well as the fine-tuning of the individual parameters of this technique, is crucial. There is still a lack of strategic guidelines due to the complexity and variability of data selection, processing techniques and applications. This paper gives an overview on the state-of-the-art in remote sensing image fusion including sensors and applications. Putting research results in image fusion from the past 15 years into a context provides a new view on the subject and helps other researchers to build their innovation on these findings. Recommendations of experts help to understand further needs to achieve feasible strategies in remote sensing image fusion.

  4. Remote sensing information sciences research group

    Science.gov (United States)

    Estes, John E.; Smith, Terence; Star, Jeffrey L.

    1988-01-01

    Research conducted under this grant was used to extend and expand existing remote sensing activities at the University of California, Santa Barbara in the areas of georeferenced information systems, matching assisted information extraction from image data and large spatial data bases, artificial intelligence, and vegetation analysis and modeling. The research thrusts during the past year are summarized. The projects are discussed in some detail.

  5. Remote Sensing Analysis of Forest Disturbances

    Science.gov (United States)

    Asner, Gregory P. (Inventor)

    2015-01-01

    The present invention provides systems and methods to automatically analyze Landsat satellite data of forests. The present invention can easily be used to monitor any type of forest disturbance such as from selective logging, agriculture, cattle ranching, natural hazards (fire, wind events, storms), etc. The present invention provides a large-scale, high-resolution, automated remote sensing analysis of such disturbances.

  6. Satellite Remote Sensing for Monitoring and Assessment

    Science.gov (United States)

    Remote sensing technology has the potential to enhance the engagement of communities and managers in the implementation and performance of best management practices. This presentation will use examples from U.S. numeric criteria development and state water quality monitoring prog...

  7. Advances in Remote Sensing of Flooding

    Directory of Open Access Journals (Sweden)

    Yong Wang

    2015-11-01

    Full Text Available With the publication of eight original research articles, four types of advances in the remote sensing of floods are achieved. The uncertainty of modeled outputs using precipitation datasets derived from in situ observations and remote sensors is further understood. With the terrestrial laser scanner and airborne light detection and ranging (LiDAR coupled with high resolution optical and radar imagery, researchers improve accuracy levels in estimating the surface water height, extent, and flow of floods. The unmanned aircraft system (UAS can be the game changer in the acquisition and application of remote sensing data. The UAS may fly everywhere and every time when a flood event occurs. With the development of urban structure maps, the flood risk and possible damage is well assessed. The flood mitigation plans and response activities become effective and efficient using geographic information system (GIS-based urban flood vulnerability and risk maps.

  8. Hyperspectral Remote Sensing of Foliar Nitrogen Content

    Science.gov (United States)

    Knyazikhin, Yuri; Schull, Mitchell A.; Stenberg, Pauline; Moettus, Matti; Rautiainen, Miina; Yang, Yan; Marshak, Alexander; Carmona, Pedro Latorre; Kaufmann, Robert K.; Lewis, Philip; Disney, Mathias I.; Vanderbilt, Vern; Davis, Anthony B.; Baret, Frederic; Jacquemoud, Stephane; Lyapustin, Alexei; Myneni, Ranga B.

    2013-01-01

    A strong positive correlation between vegetation canopy bidirectional reflectance factor (BRF) in the near infrared (NIR) spectral region and foliar mass-based nitrogen concentration (%N) has been reported in some temperate and boreal forests. This relationship, if true, would indicate an additional role for nitrogen in the climate system via its influence on surface albedo and may offer a simple approach for monitoring foliar nitrogen using satellite data. We report, however, that the previously reported correlation is an artifact - it is a consequence of variations in canopy structure, rather than of %N. The data underlying this relationship were collected at sites with varying proportions of foliar nitrogen-poor needleleaf and nitrogen-rich broadleaf species, whose canopy structure differs considerably. When the BRF data are corrected for canopy-structure effects, the residual reflectance variations are negatively related to %N at all wavelengths in the interval 423-855 nm. This suggests that the observed positive correlation between BRF and %N conveys no information about %N. We find that to infer leaf biochemical constituents, e.g., N content, from remotely sensed data, BRF spectra in the interval 710-790 nm provide critical information for correction of structural influences. Our analysis also suggests that surface characteristics of leaves impact remote sensing of its internal constituents. This further decreases the ability to remotely sense canopy foliar nitrogen. Finally, the analysis presented here is generic to the problem of remote sensing of leaf-tissue constituents and is therefore not a specific critique of articles espousing remote sensing of foliar %N.

  9. Remote sensing science - new concepts and applications

    Energy Technology Data Exchange (ETDEWEB)

    Gerstl, S.A.; Cooke, B.J.; Henderson, B.G.; Love, S.P.; Zardecki, A.

    1996-10-01

    This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The science and technology of satellite remote sensing is an emerging interdisciplinary field that is growing rapidly with many global and regional applications requiring quantitative sensing of earth`s surface features as well as its atmosphere from space. It is possible today to resolve structures on the earth`s surface as small as one meter from space. If this high spatial resolution is coupled with high spectral resolution, instant object identification can also be achieved. To interpret these spectral signatures correctly, it is necessary to perform a computational correction on the satellite imagery that removes the distorting effects of the atmosphere. This project studied such new concepts and applied innovative new approaches in remote sensing science.

  10. Surveying earth resources by remote sensing from satellites

    Energy Technology Data Exchange (ETDEWEB)

    Otterman, J.; Lowman, P.D.; Salomonson, V.V.

    1976-04-01

    The techniques and recent results of orbital remote sensing, with emphasis on Landsat and Skylab imagery are reviewed. Landsat (formerly ERTS) uses electronic sensors (scanners and television) for repetitive observations with moderate ground resolution. The Skylab flights used a wider range of electro-optical sensors and returned film cameras with moderate and high ground resolution. Data from these programs have been used successfully in many fields. For mineral resources, satellite observations have proven valuable in geologic mapping and in exploration for metal, oil, and gas deposits, generally as a guide for other (conventional) techniques. Water resource monitoring with satellite data has included hydrologic mapping, soil moisture studies, and snow surveys. Marine resources have been studied, with applications in the fishing industry and in ocean transportation. Agricultural applications, benefiting from the repetitive coverage possible with satellites, have been especially promising. Crop inventories are being conducted, as well as inventories of timber and rangeland. Overgrazing has been monitored in several areas. Finally, environmental quality has also proven susceptible to orbital remote sensing; several types of water pollution have been successfully monitored. The effects of mining and other activities on the land can also be studied. The future of orbital remote sensing in global monitoring of the Earth's resources seems assured. However, efforts to extend spectral range, increase resolution, and solve cloud-cover problems must be continued. Broad applications of computer analysis techniques are vital to handle the immense amount of information produced by satellite sensors.

  11. Geometric calibration of high-resolution remote sensing sensors

    Institute of Scientific and Technical Information of China (English)

    LIANG Hong-you; GU Xing-fa; TAO Yu; QIAO Chao-fei

    2007-01-01

    This paper introduces the applications of high-resolution remote sensing imagery and the necessity of geometric calibration for remote sensing sensors considering assurance of the geometric accuracy of remote sensing imagery. Then the paper analyzes the general methodology of geometric calibration. Taking the DMC sensor geometric calibration as an example, the paper discusses the whole calibration procedure. Finally, it gave some concluding remarks on geometric calibration of high-resolution remote sensing sensors.

  12. Additional development of remote sensing techniques for observing morphology, microphysics, and radiative properties of clouds and tests using a new, robust CO{sub 2} lidar. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Eberhard, W.L.; Brewer, W.A.; Intrieri, J.M.

    1998-09-28

    A three-year project with a goal of advancing CO{sub 2} lidar technology and measurement techniques for cloud studies was successfully completed. An eyesafe, infrared lidar with good sensitivity and improved Doppler accuracy was designed, constructed, and demonstrated. Dual-wavelength operation was achieved. A major leap forward in robustness was demonstrated. CO{sub 2} lidars were operated as part of two Intensive Operations Periods at the Southern Great Plains CART site. The first used an older lidar and was intended primarily for measurement technique development. The second used the new lidar and was primarily a demonstration and evaluation of its performance. Progress was demonstrated in the development, evaluation, and application of measurement techniques using CO{sub 2} lidar.

  13. GPS Remote Sensing Measurements Using Aerosonde UAV

    Science.gov (United States)

    Grant, Michael S.; Katzberg, Stephen J.; Lawrence, R. W.

    2005-01-01

    In February 2004, a NASA-Langley GPS Remote Sensor (GPSRS) unit was flown on an Aerosonde unmanned aerial vehicle (UAV) from the Wallops Flight Facility (WFF) in Virginia. Using direct and surface-reflected 1.575 GHz coarse acquisition (C/A) coded GPS signals, remote sensing measurements were obtained over land and portions of open water. The strength of the surface-reflected GPS signal is proportional to the amount of moisture in the surface, and is also influenced by surface roughness. Amplitude and other characteristics of the reflected signal allow an estimate of wind speed over open water. In this paper we provide a synopsis of the instrument accommodation requirements, installation procedures, and preliminary results from what is likely the first-ever flight of a GPS remote sensing instrument on a UAV. The correct operation of the GPSRS unit on this flight indicates that Aerosonde-like UAV's can serve as platforms for future GPS remote sensing science missions.

  14. Towards operational environmental applications using terrestrial remote sensing

    NARCIS (Netherlands)

    Veldkamp JG; Velde RJ van de; LBG

    1996-01-01

    Dit rapport beschrijft de resultaten van het Beleidscommissie Remote Sensing (BCRS) project 'Verankering van toepassingen van terrestrische remote sensing bij RIVM'. Het had ten eerste tot doel te voldoen aan de voorwaarden, zoals gesteld in de inventarisatie van remote sensing als

  15. An introduction to quantitative remote sensing. [data processing

    Science.gov (United States)

    Lindenlaub, J. C.; Russell, J.

    1974-01-01

    The quantitative approach to remote sensing is discussed along with the analysis of remote sensing data. Emphasis is placed on the application of pattern recognition in numerically oriented remote sensing systems. A common background and orientation for users of the LARS computer software system is provided.

  16. The application of hyperspectral remote sensing to coast environment investigation

    Institute of Scientific and Technical Information of China (English)

    ZHANG Liang; ZHANG bing; CHEN Zhengchao; ZHENG Lanfen; TONG Qingxi

    2009-01-01

    Requirements for monitoring the coastal zone environment are first summarized. Then the application of hyperspectral remote sensing to coast environment investigation is introduced, such as the classification of coast beaches and bottom matter, target recognition, mine detection, oil spill identification and ocean color remote sensing. Finally, what is needed to follow on in application of hyperspectral remote sensing to coast environment is recommended.

  17. Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

    Science.gov (United States)

    McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall

    2008-01-01

    The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify

  18. An experiment using mid and thermal infrared in quantum remote sensing

    Institute of Scientific and Technical Information of China (English)

    BI; Siwen; HAN; Jixia

    2006-01-01

    The concept of quantum remote sensing and the differences between quantum remote sensing and remote sensing is introduced, an experiment about the uses of mid and thermal infrared in quantum remote sensing is described and results are analyzed.

  19. Remote Sensing Time Series Product Tool

    Science.gov (United States)

    Predos, Don; Ryan, Robert E.; Ross, Kenton W.

    2006-01-01

    programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

  20. Remote Sensing and Remote Control Activities in Europe and America: Part 2--Remote Sensing Ground Stations in Europe,

    Science.gov (United States)

    2007-11-02

    Development tasks and products of remote sensing ground stations in Europe are represented by the In-Sec Corporation and the Schlumberger Industries Corporation. The article presents the main products of these two corporations.

  1. Remote sensing for disaster mitigation of Sinabung

    Science.gov (United States)

    Tampubolon, T.; Yanti, J.

    2016-05-01

    Indonesia, a country with many active volcanoes, potentially occur natural disaster due to eruptions. One of volcanoes at Indonesia was Sinabung mountain, that located on Karo Regency, North Sumatera 3°10'12″ N 98°23'31" E, 2,460 masl. A fasile and new observation method for mapping the erupted areas was remote sensing. the remote sensing consisted of Landsat 8 OLI that was published on February 8th 2015 as input data ENVI 4.7 and ArcGIS 10 as mapping tools. The Land surface temperature (LST) was applied on mapping this resulted. The highest LST was 90.929657 °C. In addition, the LST distribution indicated that the flowing lava through south east. Therefore, the south east areas should be considered as mitigated areas.

  2. Review of oil spill remote sensing.

    Science.gov (United States)

    Fingas, Merv; Brown, Carl

    2014-06-15

    Remote-sensing for oil spills is reviewed. The use of visible techniques is ubiquitous, however it gives only the same results as visual monitoring. Oil has no particular spectral features that would allow for identification among the many possible background interferences. Cameras are only useful to provide documentation. In daytime oil absorbs light and remits this as thermal energy at temperatures 3-8K above ambient, this is detectable by infrared (IR) cameras. Laser fluorosensors are useful instruments because of their unique capability to identify oil on backgrounds that include water, soil, weeds, ice and snow. They are the only sensor that can positively discriminate oil on most backgrounds. Radar detects oil on water by the fact that oil will dampen water-surface capillary waves under low to moderate wave/wind conditions. Radar offers the only potential for large area searches, day/night and foul weather remote sensing. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. Measurement Strategies for Remote Sensing Applications

    Energy Technology Data Exchange (ETDEWEB)

    Weber, P.G.; Theiler, J.; Smith, B.; Love, S.P.; LaDelfe, P.C.; Cooke, B.J.; Clodius, W.B.; Borel, C.C.; Bender, S.C.

    1999-03-06

    Remote sensing has grown to encompass many instruments and observations, with concomitant data from a huge number of targets. As evidenced by the impressive growth in the number of published papers and presentations in this field, there is a great deal of interest in applying these capabilities. The true challenge is to transition from directly observed data sets to obtaining meaningful and robust information about remotely sensed targets. We use physics-based end-to-end modeling and analysis techniques as a framework for such a transition. Our technique starts with quantified observables and signatures of a target. The signatures are propagated through representative atmospheres to realistically modeled sensors. Simulated data are then propagated through analysis routines, yielding measurements that are directly compared to the original target attributes. We use this approach to develop measurement strategies which ensure that our efforts provide a balanced approach to obtaining substantive information on our targets.

  4. The Fundamental Framework of Remote Sensing Validation System

    Science.gov (United States)

    Jiang, X.-G.; Xi, X.-H.; Wu, M.-J.; Li, Z.-L.

    2009-04-01

    Remote sensing is a very complicated course. It is influenced by many factors, such as speciality of remote sensing sensor, radiant transmission characteristic of atmosphere, work environment of remote sensing platform, data transmission, data reception, data processing, and property of observed object etc. Whether the received data is consistent with the design specifications? Can the data meet the demands of remote sensing applications? How about the accuracy of the data products, retrieval products and application products of remote sensing? It is essential to carry out the validation to assess the data quality and application potential. Validation is effective approach to valuate remote sensing products. It is the significant link between remote sensing data and information. Research on remote sensing validation is very important for sensor development, data quality analysis and control. This paper focuses on the study of remote sensing validation and validation system. Different from the previous work done by other researchers, we study the validation from the viewpoint of systematic engineering considering that validation is involved with many aspects as talked about. Validation is not just a single and simple course. It is complicated system. Validation system is the important part of whole earth observation system. First of all, in this paper the category of remote sensing validation is defined. Remote sensing validation includes not only the data products validation, but also the retrieval products validation and application products validation. Second, the new concept, remote sensing validation system, is proposed. Then, the general framework, software structure and functions of validation system are studied and put forward. The validation system is composed of validation field module, data acquirement module, data processing module, data storage and management module, data scaling module, and remote sensing products validation module. And finally the

  5. Processing Remote Sensing Data with Python

    OpenAIRE

    Dillon, Ryan J., 1984-

    2013-01-01

    With public access available for numerous satellite imaging products, modelling in atmospheric and oceanographic applications has become increasingly more prevalent. Though there are numerous tools available for geospatial development, their use is more commonly applied towards mapping applications. With this being the case, there are a number of valuable texts for using these tools in such mapping applications; though, documentation for processing of remote sensing datasets is limited to ...

  6. Mesoscale Modeling, Forecasting and Remote Sensing Research.

    Science.gov (United States)

    remote sensing , cyclonic scale diagnostic studies and mesoscale numerical modeling and forecasting are summarized. Mechanisms involved in the release of potential instability are discussed and simulated quantitatively, giving particular attention to the convective formulation. The basic mesoscale model is documented including the equations, boundary condition, finite differences and initialization through an idealized frontal zone. Results of tests including a three dimensional test with real data, tests of convective/mesoscale interaction and tests with a detailed

  7. Remote sensing application on geothermal exploration

    Science.gov (United States)

    Gaffar, Eddy Z.

    2013-09-01

    Geothermal energy is produced when water coming down from the surface of the earth and met with magma or hot rocks, which the heat comes from the very high levels of magma rises from the earth. This process produced a heated fluid supplied to a power generator system to finally use as energy. Geothermal field usually associated with volcanic area with a component from igneous rocks and a complex geological structures. The fracture and fault structure are important geological structures associated with geothermal. Furthermore, their geothermal manifestations also need to be evaluated associated their geological structures. The appearance of a geothermal surface manifestation is close to the structure of the fracture and the caldera volcanic areas. The relationship between the fault and geothermal manifestations can be seen in the form of a pattern of alignment between the manifestations of geothermal locations with other locations on the fault system. The use of remote sensing using electromagnetic radiation sensors to record images of the Earth's environment that can be interpreted to be a useful information. In this study, remote sensing was applied to determine the geological structure and mapping of the distribution of rocks and alteration rocks. It was found that remote sensing obtained a better localize areas of geothermal prospects, which in turn could cut the chain of geothermal exploration to reduce a cost of geothermal exploration.

  8. Autofocus method for scanning remote sensing cameras.

    Science.gov (United States)

    Lv, Hengyi; Han, Chengshan; Xue, Xucheng; Hu, Changhong; Yao, Cheng

    2015-07-10

    Autofocus methods are conventionally based on capturing the same scene from a series of positions of the focal plane. As a result, it has been difficult to apply this technique to scanning remote sensing cameras where the scenes change continuously. In order to realize autofocus in scanning remote sensing cameras, a novel autofocus method is investigated in this paper. Instead of introducing additional mechanisms or optics, the overlapped pixels of the adjacent CCD sensors on the focal plane are employed. Two images, corresponding to the same scene on the ground, can be captured at different times. Further, one step of focusing is done during the time interval, so that the two images can be obtained at different focal plane positions. Subsequently, the direction of the next step of focusing is calculated based on the two images. The analysis shows that the method investigated operates without restriction of the time consumption of the algorithm and realizes a total projection for general focus measures and algorithms from digital still cameras to scanning remote sensing cameras. The experiment results show that the proposed method is applicable to the entire focus measure family, and the error ratio is, on average, no more than 0.2% and drops to 0% by reliability improvement, which is lower than that of prevalent approaches (12%). The proposed method is demonstrated to be effective and has potential in other scanning imaging applications.

  9. A Review of Wetland Remote Sensing.

    Science.gov (United States)

    Guo, Meng; Li, Jing; Sheng, Chunlei; Xu, Jiawei; Wu, Li

    2017-04-05

    Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 years, wetlands have been polluted and declined dramatically as land cover has changed in some regions. Remote sensing has been the most useful tool to acquire spatial and temporal information about wetlands. In this paper, seven types of sensors were reviewed: aerial photos coarse-resolution, medium-resolution, high-resolution, hyperspectral imagery, radar, and Light Detection and Ranging (LiDAR) data. This study also discusses the advantage of each sensor for wetland research. Wetland research themes reviewed in this paper include wetland classification, habitat or biodiversity, biomass estimation, plant leaf chemistry, water quality, mangrove forest, and sea level rise. This study also gives an overview of the methods used in wetland research such as supervised and unsupervised classification and decision tree and object-based classification. Finally, this paper provides some advice on future wetland remote sensing. To our knowledge, this paper is the most comprehensive and detailed review of wetland remote sensing and it will be a good reference for wetland researchers.

  10. A Review of Wetland Remote Sensing

    Science.gov (United States)

    Guo, Meng; Li, Jing; Sheng, Chunlei; Xu, Jiawei; Wu, Li

    2017-01-01

    Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 years, wetlands have been polluted and declined dramatically as land cover has changed in some regions. Remote sensing has been the most useful tool to acquire spatial and temporal information about wetlands. In this paper, seven types of sensors were reviewed: aerial photos coarse-resolution, medium-resolution, high-resolution, hyperspectral imagery, radar, and Light Detection and Ranging (LiDAR) data. This study also discusses the advantage of each sensor for wetland research. Wetland research themes reviewed in this paper include wetland classification, habitat or biodiversity, biomass estimation, plant leaf chemistry, water quality, mangrove forest, and sea level rise. This study also gives an overview of the methods used in wetland research such as supervised and unsupervised classification and decision tree and object-based classification. Finally, this paper provides some advice on future wetland remote sensing. To our knowledge, this paper is the most comprehensive and detailed review of wetland remote sensing and it will be a good reference for wetland researchers. PMID:28379174

  11. Research on cloud-based remote measurement and analysis system

    Science.gov (United States)

    Gao, Zhiqiang; He, Lingsong; Su, Wei; Wang, Can; Zhang, Changfan

    2015-02-01

    The promising potential of cloud computing and its convergence with technologies such as cloud storage, cloud push, mobile computing allows for creation and delivery of newer type of cloud service. Combined with the thought of cloud computing, this paper presents a cloud-based remote measurement and analysis system. This system mainly consists of three parts: signal acquisition client, web server deployed on the cloud service, and remote client. This system is a special website developed using asp.net and Flex RIA technology, which solves the selective contradiction between two monitoring modes, B/S and C/S. This platform supplies customer condition monitoring and data analysis service by Internet, which was deployed on the cloud server. Signal acquisition device is responsible for data (sensor data, audio, video, etc.) collection and pushes the monitoring data to the cloud storage database regularly. Data acquisition equipment in this system is only conditioned with the function of data collection and network function such as smartphone and smart sensor. This system's scale can adjust dynamically according to the amount of applications and users, so it won't cause waste of resources. As a representative case study, we developed a prototype system based on Ali cloud service using the rotor test rig as the research object. Experimental results demonstrate that the proposed system architecture is feasible.

  12. Mineralogy and Astrobiology Detection Using Laser Remote Sensing Instrument

    Science.gov (United States)

    Abedin, M. Nurul; Bradley, Arthur T.; Sharma, Shiv K.; Misra, Anupam K.; Lucey, Paul G.; Mckay, Chistopher P.; Ismail, Syed; Sandford, Stephen P.

    2015-01-01

    A multispectral instrument based on Raman, laser-induced fluorescence (LIF), laser-induced breakdown spectroscopy (LIBS), and a lidar system provides high-fidelity scientific investigations, scientific input, and science operation constraints in the context of planetary field campaigns with the Jupiter Europa Robotic Lander and Mars Sample Return mission opportunities. This instrument conducts scientific investigations analogous to investigations anticipated for missions to Mars and Jupiter's icy moons. This combined multispectral instrument is capable of performing Raman and fluorescence spectroscopy out to a >100 m target distance from the rover system and provides single-wavelength atmospheric profiling over long ranges (>20 km). In this article, we will reveal integrated remote Raman, LIF, and lidar technologies for use in robotic and lander-based planetary remote sensing applications. Discussions are focused on recently developed Raman, LIF, and lidar systems in addition to emphasizing surface water ice, surface and subsurface minerals, organics, biogenic, biomarker identification, atmospheric aerosols and clouds distributions, i.e., near-field atmospheric thin layers detection for next robotic-lander based instruments to measure all the above-mentioned parameters. OCIS codes: (120.0280) Remote sensing and sensors; (130.0250) Optoelectronics; (280.3640) Lidar; (300.2530) Fluorescence, laser-induced; (300.6450) Spectroscopy, Raman; (300.6365) Spectroscopy, laser induced breakdown

  13. Research Status and Development Trend of Remote Sensing in China Using Bibliometric Analysis

    Science.gov (United States)

    Zeng, Y.; Zhang, J.; Niu, R.

    2015-06-01

    Remote sensing was introduced into China in 1970s and then began to flourish. At present, China has developed into a big remote sensing country, and remote sensing is increasingly playing an important role in various fields of national economic construction and social development. Based on China Academic Journals Full-text Database and China Citation Database published by China National Knowledge Infrastructure, this paper analyzed academic characteristics of 963 highly cited papers published by 16 professional and academic journals in the field of surveying and mapping from January 2010 to December 2014 in China, which include hot topics, literature authors, research institutions, and fundations. At the same time, it studied a total of 51,149 keywords published by these 16 journals during the same period. Firstly by keyword selection, keyword normalization, keyword consistency and keyword incorporation, and then by analysis of high frequency keywords, the progress and prospect of China's remote sensing technology in data acquisition, data processing and applications during the past five years were further explored and revealed. It can be seen that: highly cited paper analysis and word frequency analysis is complementary on subject progress analysis; in data acquisition phase, research focus is new civilian remote sensing satellite systems and UAV remote sensing system; research focus of data processing and analysis is multi-source information extraction and classification, laser point cloud data processing, objectoriented high resolution image analysis, SAR data and hyper-spectral image processing, etc.; development trend of remote sensing data processing is quantitative, intelligent, automated, and real-time, and the breadth and depth of remote sensing application is gradually increased; parallel computing, cloud computing and geographic conditions monitoring and census are the new research focuses to be paid attention to.

  14. A Preliminary View on the Estimation of Land Surface Temperature Under Cloud Cover from Thermal Remote Sensing Data%热红外遥感图像中云覆盖像元地表温度估算初论

    Institute of Scientific and Technical Information of China (English)

    周义; 覃志豪; 包刚

    2013-01-01

    Land surface temperature (LST) is a very important parameter controlling the energy and water balance between atmosphere and land surface. Since it is difficult to obtain such information from ground-based measurements, it appears to be very attractive by using satellite thermal infrared measurements to estimate LST since it can be used for estimating surface temperature at global or local scale. Moreover, the estimation of LST by using satellite remote sensing data is feasible. Cloud cover is a major obstacle to thermal infrared remote sensing applications and remote sensing quantitative retrieval of land surface temperature. Furthermore, cloud frequently exists in most time and covers roughly half the surface of the Earth even if the sky is clear. This is the case especially in some regions of high latitudes in the north hemisphere, e.g. the tropics are covered by cloud for about 60% of the time. Therefore, the influence of clouds on LST deserves more discussion and how to estimate LST of pixels covered by cloud on thermal remotely sensed imagery is one of the cutting-edge research problems. In this article, based on the theory of surface energy balance (SEB), three methods, which are spatial interpretation adjustment method, the adjustment method by correlations between LST and Vegetation Indices (VIs) and improved surface energy balance method, have been put forward for the estimation of LST when the sky is cloudy. Moreover, the lowland effect of LST spatial distribution under cloud cover and the method for the calculation of its intensity (denoted as SE) were also discussed. Generally speaking, when SE equals to 1, it means that SE reaches its maximum due to thick cloud cover .While SE equals to 0, it means that there is no lowland effect in clear sky. SE is strongly affected by the cloud and surface conditions. That is to say, SE is influenced greatly by cloud properties such as the time it appears and lasts, its shape, thickness and height and surface

  15. NEON Airborne Remote Sensing of Terrestrial Ecosystems

    Science.gov (United States)

    Kampe, T. U.; Leisso, N.; Krause, K.; Karpowicz, B. M.

    2012-12-01

    The National Ecological Observatory Network (NEON) is the continental-scale research platform that will collect information on ecosystems across the United States to advance our understanding and ability to forecast environmental change at the continental scale. One of NEON's observing systems, the Airborne Observation Platform (AOP), will fly an instrument suite consisting of a high-fidelity visible-to-shortwave infrared imaging spectrometer, a full waveform small footprint LiDAR, and a high-resolution digital camera on a low-altitude aircraft platform. NEON AOP is focused on acquiring data on several terrestrial Essential Climate Variables including bioclimate, biodiversity, biogeochemistry, and land use products. These variables are collected throughout a network of 60 sites across the Continental United States, Alaska, Hawaii and Puerto Rico via ground-based and airborne measurements. Airborne remote sensing plays a critical role by providing measurements at the scale of individual shrubs and larger plants over hundreds of square kilometers. The NEON AOP plays the role of bridging the spatial scales from that of individual organisms and stands to the scale of satellite-based remote sensing. NEON is building 3 airborne systems to facilitate the routine coverage of NEON sites and provide the capacity to respond to investigator requests for specific projects. The first NEON imaging spectrometer, a next-generation VSWIR instrument, was recently delivered to NEON by JPL. This instrument has been integrated with a small-footprint waveform LiDAR on the first NEON airborne platform (AOP-1). A series of AOP-1 test flights were conducted during the first year of NEON's construction phase. The goal of these flights was to test out instrument functionality and performance, exercise remote sensing collection protocols, and provide provisional data for algorithm and data product validation. These test flights focused the following questions: What is the optimal remote

  16. International Models and Methods of Remote Sensing Education and Training.

    Science.gov (United States)

    Anderson, Paul S.

    A classification of remote sensing courses throughout the world, the world-wide need for sensing instruction, and alternative instructional methods for meeting those needs are discussed. Remote sensing involves aerial photointerpretation or the use of satellite and other non-photographic imagery; its focus is to interpret what is in the photograph…

  17. Hyperspectral remote sensing of wild oyster reefs

    Science.gov (United States)

    Le Bris, Anthony; Rosa, Philippe; Lerouxel, Astrid; Cognie, Bruno; Gernez, Pierre; Launeau, Patrick; Robin, Marc; Barillé, Laurent

    2016-04-01

    The invasion of the wild oyster Crassostrea gigas along the western European Atlantic coast has generated changes in the structure and functioning of intertidal ecosystems. Considered as an invasive species and a trophic competitor of the cultivated conspecific oyster, it is now seen as a resource by oyster farmers following recurrent mass summer mortalities of oyster spat since 2008. Spatial distribution maps of wild oyster reefs are required by local authorities to help define management strategies. In this work, visible-near infrared (VNIR) hyperspectral and multispectral remote sensing was investigated to map two contrasted intertidal reef structures: clusters of vertical oysters building three-dimensional dense reefs in muddy areas and oysters growing horizontally creating large flat reefs in rocky areas. A spectral library, collected in situ for various conditions with an ASD spectroradiometer, was used to run Spectral Angle Mapper classifications on airborne data obtained with an HySpex sensor (160 spectral bands) and SPOT satellite HRG multispectral data (3 spectral bands). With HySpex spectral/spatial resolution, horizontal oysters in the rocky area were correctly classified but the detection was less efficient for vertical oysters in muddy areas. Poor results were obtained with the multispectral image and from spatially or spectrally degraded HySpex data, it was clear that the spectral resolution was more important than the spatial resolution. In fact, there was a systematic mud deposition on shells of vertical oyster reefs explaining the misclassification of 30% of pixels recognized as mud or microphytobenthos. Spatial distribution maps of oyster reefs were coupled with in situ biomass measurements to illustrate the interest of a remote sensing product to provide stock estimations of wild oyster reefs to be exploited by oyster producers. This work highlights the interest of developing remote sensing techniques for aquaculture applications in coastal

  18. Remote sensing for land management and planning

    Science.gov (United States)

    Woodcock, Curtis E.; Strahler, Alan H.; Franklin, Janet

    1983-05-01

    The primary role of remote sensing in land management and planning has been to provide information concerning the physical characteristics of the land which influence the management of individual land parcels or the allocation of lands to various uses These physical characteristics have typically been assessed through aerial photography, which is used to develop resource maps and to monitor changing environmental conditions These uses are well developed and currently well integrated into the planning infrastructure at local, state, and federal levels in the United States. Many newly emerging uses of remote sensing involve digital images which are collected, stored, and processed automatically by electromechanical scanning devices and electronic computers Some scanning devices operate from aircraft or spacecraft to scan ground scenes directly; others scan conventional aerial transparencies to yield digital images. Digital imagery offers the potential for computer-based automated map production, a process that can significantly increase the amount and timeliness of information available to land managers and planners. Future uses of remote sensing in land planning and management will involve geographic information systems, which store resource information in a geocoded format. Geographic information systems allow the automated integration of disparate types of resource data through various types of spatial models so that with accompanying sample ground data, information in the form of thematic maps and/ or aerially aggregated statistics can be produced Key issues confronting the development and integration of geographic information systems into planning pathways are restoration and rectification of digital images, automated techniques for combining both quantitative and qualitative types of data in information-extracting procedures, and the compatibility of alternative data storage modes

  19. Optical Remote Sensing Potentials for Looting Detection

    Directory of Open Access Journals (Sweden)

    Athos Agapiou

    2017-10-01

    Full Text Available Looting of archaeological sites is illegal and considered a major anthropogenic threat for cultural heritage, entailing undesirable and irreversible damage at several levels, such as landscape disturbance, heritage destruction, and adverse social impact. In recent years, the employment of remote sensing technologies using ground-based and/or space-based sensors has assisted in dealing with this issue. Novel remote sensing techniques have tackled heritage destruction occurring in war-conflicted areas, as well as illicit archeological activity in vast areas of archaeological interest with limited surveillance. The damage performed by illegal activities, as well as the scarcity of reliable information are some of the major concerns that local stakeholders are facing today. This study discusses the potential use of remote sensing technologies based on the results obtained for the archaeological landscape of Ayios Mnason in Politiko village, located in Nicosia district, Cyprus. In this area, more than ten looted tombs have been recorded in the last decade, indicating small-scale, but still systematic, looting. The image analysis, including vegetation indices, fusion, automatic extraction after object-oriented classification, etc., was based on high-resolution WorldView-2 multispectral satellite imagery and RGB high-resolution aerial orthorectified images. Google Earth© images were also used to map and diachronically observe the site. The current research also discusses the potential for wider application of the presented methodology, acting as an early warning system, in an effort to establish a systematic monitoring tool for archaeological areas in Cyprus facing similar threats.

  20. Shape saliency for remote sensing image

    Science.gov (United States)

    Xu, Sheng; Hong, Huo; Fang, Tao; Li, Deren

    2007-11-01

    In this paper, a shape saliency measure for only shape feature of each object in the image is described. Instead biologically-inspired bottom-up Itti model, the dissimilarity is measured by the shape feature. And, Fourier descriptor is used for measuring dissimilarity in this paper. In the model, the object is determined as a salient region, when it is far different from others. Different value of the saliency is ranged to generate a saliency map. It is shown that the attention shift processing can be recorded. Some results from psychological images and remote sensing images are shown and discussed in the paper.

  1. Remote sensing and actuation using unmanned vehicles

    CERN Document Server

    Chao, Haiyang

    2012-01-01

    Unmanned systems and robotics technologies have become very popular recently owing to their ability to replace human beings in dangerous, tedious, or repetitious jobs. This book fill the gap in the field between research and real-world applications, providing scientists and engineers with essential information on how to design and employ networked unmanned vehicles for remote sensing and distributed control purposes. Target scenarios include environmental or agricultural applications such as river/reservoir surveillance, wind profiling measurement, and monitoring/control of chemical leaks.

  2. Characrterizing frozen ground with multisensor remote sensing

    Science.gov (United States)

    Csatho, B. M.; Ping, C.; Everett, L. R.; Kimble, J. M.; Michaelson, G.; Tremper, C.

    2006-12-01

    We have a physically based, conceptual understanding of many of the significant interactions that impact permafrost-affected soils. Our observationally based knowledge, however, is inadequate in many cases to quantify these interactions or to predict their net impact. To pursue key goals, such as understanding the response of permafrost-affected soil systems to global environmental changes and their role in the carbon balance, and to transform our conceptual understanding of these processes into quantitative knowledge, it is necessary to acquire geographically diverse sets of fundamental observations at high spatial and often temporal resolution. The main goals of the research presented here are developing methods for mapping soil and permafrost distributions in polar environment as well as characterizing glacial and perglacial geomorphology from multisensor, multiresolution remotely sensed data. The sheer amount of data and the disparate data sets (e.g., LIDAR, stereo imagery, multi- hyperspectral, and SAR imagery) make the joint interpretation (fusion) a daunting task. We combine remote sensing, pattern recognition and landscape analysis techniques for the delineation of soil landscape units and other geomorphic features, for inferring the physical properties and composition of the surface, and for generating numerical measurements of geomorphic features from remotely sensed data. Examples illustrating the concept are presented from the North Slope of Alaska and from the McMurdo Sound region in Antarctica. (1) On the North Slope, Alaska we separated different vegetative, soil and landscape units along the Haul Road. Point-source soils (pedon) data and field spectrometry data have been acquired at different units to provide ground-truth for the satellite image interpretation. (2) A vast amount of remote sensing data, such as multi- and hyperspectral (Landsat, SPOT, ASTER, HYPERION) and SAR satellite imagery (ERS, RADARSAT and JERS), high resolution topographic

  3. Introduction to Remote Sensing Image Registration

    Science.gov (United States)

    Le Moigne, Jacqueline

    2017-01-01

    For many applications, accurate and fast image registration of large amounts of multi-source data is the first necessary step before subsequent processing and integration. Image registration is defined by several steps and each step can be approached by various methods which all present diverse advantages and drawbacks depending on the type of data, the type of applications, the a prior information known about the data and the type of accuracy that is required. This paper will first present a general overview of remote sensing image registration and then will go over a few specific methods and their applications

  4. Branching model for vegetation. [polarimetric remote sensing

    Science.gov (United States)

    Yueh, Simon H.; Kong, J. A.; Jao, Jen K.; Shin, Robert T.; Le Toan, Thuy

    1992-01-01

    In the present branching model for remote sensing of vegetation, the frequency and angular responses of a two-scale cylinder cluster are calculated to illustrate the importance of vegetation architecture. Attention is given to the implementation of a two-scale branching model for soybeans, where the relative location of soybean plants is described by a pair of distribution functions. Theoretical backscattering coefficients evaluated by means of hole-correction pair distribution are in agreement with extensive data collected from soybean fields. The hole-correction approximation is found to be the more realistic.

  5. Optical remote sensing of the earth

    Science.gov (United States)

    Goetz, A. F. H.; Wellman, J. B.; Barnes, W. L.

    1985-01-01

    In the present assessment of the contributions of optical earth resources remote sensing in the 0.4-15.0 micron region, attention is given to underlying principles, applications to scientific disciplines such as geology, hydrology and oceanography, the recent development history of the requisite sensors, and sensor development trends. Development status characterizations are given for thematic mapping, modular optoelectronic multispectral scanning, the telescope/CCD 'SPOT' program of France, the thermal IR multispectral scanner for mineral signature identification, airborne imaging spectrometry, and the Advanced Visible and IR Imaging Spectrometer that is nearing deployment. Technology development trends and the capabilities they portend are projected.

  6. Branching model for vegetation. [polarimetric remote sensing

    Science.gov (United States)

    Yueh, Simon H.; Kong, J. A.; Jao, Jen K.; Shin, Robert T.; Le Toan, Thuy

    1992-01-01

    In the present branching model for remote sensing of vegetation, the frequency and angular responses of a two-scale cylinder cluster are calculated to illustrate the importance of vegetation architecture. Attention is given to the implementation of a two-scale branching model for soybeans, where the relative location of soybean plants is described by a pair of distribution functions. Theoretical backscattering coefficients evaluated by means of hole-correction pair distribution are in agreement with extensive data collected from soybean fields. The hole-correction approximation is found to be the more realistic.

  7. Remote sensing of vegetation and soil moisture

    Science.gov (United States)

    Kong, J. A.; Shin, R. T. (Principal Investigator)

    1983-01-01

    Progress in the investigation of problems related to the remote sensing of vegetation and soil moisture is reported. Specific topics addressed include: (1) microwave scattering from periodic surfaces using a rigorous modal technique; (2) combined random rough surface and volume scattering effects; (3) the anisotropic effects of vegetation structures; (4) the application of the strong fluctuation theory to the the study of electromagnetic wave scattering from a layer of random discrete scatterers; and (5) the investigation of the scattering of a plane wave obliquely incident on a half space of densely distributed spherical dielectric scatterers using a quantum mechanical potential approach.

  8. Remote shock sensing and notification system

    Science.gov (United States)

    Muralidharan, Govindarajan; Britton, Charles L.; Pearce, James; Jagadish, Usha; Sikka, Vinod K.

    2008-11-11

    A low-power shock sensing system includes at least one shock sensor physically coupled to a chemical storage tank to be monitored for impacts, and an RF transmitter which is in a low-power idle state in the absence of a triggering signal. The system includes interference circuitry including or activated by the shock sensor, wherein an output of the interface circuitry is coupled to an input of the RF transmitter. The interface circuitry triggers the RF transmitting with the triggering signal to transmit an alarm message to at least one remote location when the sensor senses a shock greater than a predetermined threshold. In one embodiment the shock sensor is a shock switch which provides an open and a closed state, the open state being a low power idle state.

  9. Remote shock sensing and notification system

    Energy Technology Data Exchange (ETDEWEB)

    Muralidharan, Govindarajan [Knoxville, TN; Britton, Charles L [Alcoa, TN; Pearce, James [Lenoir City, TN; Jagadish, Usha [Knoxville, TN; Sikka, Vinod K [Oak Ridge, TN

    2010-11-02

    A low-power shock sensing system includes at least one shock sensor physically coupled to a chemical storage tank to be monitored for impacts, and an RF transmitter which is in a low-power idle state in the absence of a triggering signal. The system includes interface circuitry including or activated by the shock sensor, wherein an output of the interface circuitry is coupled to an input of the RF transmitter. The interface circuitry triggers the RF transmitter with the triggering signal to transmit an alarm message to at least one remote location when the sensor senses a shock greater than a predetermined threshold. In one embodiment the shock sensor is a shock switch which provides an open and a closed state, the open state being a low power idle state.

  10. Remote sensing research in geographic education: An alternative view

    Science.gov (United States)

    Wilson, H.; Cary, T. K.; Goward, S. N.

    1981-01-01

    It is noted that within many geography departments remote sensing is viewed as a mere technique a student should learn in order to carry out true geographic research. This view inhibits both students and faculty from investigation of remotely sensed data as a new source of geographic knowledge that may alter our understanding of the Earth. The tendency is for geographers to accept these new data and analysis techniques from engineers and mathematicians without questioning the accompanying premises. This black-box approach hinders geographic applications of the new remotely sensed data and limits the geographer's contribution to further development of remote sensing observation systems. It is suggested that geographers contribute to the development of remote sensing through pursuit of basic research. This research can be encouraged, particularly among students, by demonstrating the links between geographic theory and remotely sensed observations, encouraging a healthy skepticism concerning the current understanding of these data.

  11. Hyperspectral Remote Sensing for Tropical Rain Forest

    Directory of Open Access Journals (Sweden)

    Kamaruzaman Jusoff

    2009-01-01

    Full Text Available Problem statement: Sensing, mapping and monitoring the rain forest in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions and are now included in climate change negotiations. Approach: We reviewed the potential for air and spaceborne hyperspectral sensing to identify and map individual tree species measure carbon stocks, specifically Aboveground Biomass (AGB and provide an overview of a range of approaches that have been developed and used to map tropical rain forest across a diverse set of conditions and geographic areas. We provided a summary of air and spaceborne hyperspectral remote sensing measurements relevant to mapping the tropical forest and assess the relative merits and limitations of each. We then provided an overview of modern techniques of mapping the tropical forest based on species discrimination, leaf chlorophyll content, estimating aboveground forest productivity and monitoring forest health. Results: The challenges in hyperspectral Imaging of tropical forests is thrown out to researchers in such field as to come with the latest techniques of image processing and improved mapping resolution leading towards higher precision mapping accuracy. Some research results from an airborne hyperspectral imaging over Bukit Nanas forest reserve was shared implicating high potential of such very high resolution imaging techniques for tropical mixed dipterocarp forest inventory and mapping for species discrimination, aboveground forest productivity, leaf chlorophyll content and carbon mapping. Conclusion/Recommendations: We concluded that while spaceborne hyperspectral remote sensing has often been discounted as inadequate for the task, attempts to map with airborne sensors are still insufficient in tropical developing countries like Malaysia. However, we demonstrated this with a case

  12. Basic research in the field of thermal infrared remote sensing

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This overview paper points out that one of the problems impeding further development of remote sensing is that not much attention has been paid to basic research.Key contents of basic research in remote sensing,including modeling,inversion,scaling and scientific experiments,are reviewed.Significance of basic research is demonstrated through summarizing the intentions and progress of the project "Quantitative Remote Sensing Research on Land Surface Energy Exchange".

  13. DARLA: Data Assimilation and Remote Sensing for Littoral Applications

    Science.gov (United States)

    2013-09-30

    WA 98105 phone: (206) 685-2609 fax: (206) 543-6785 email: jessup@apl.washington.edu Robert A. Holman Merrick Haller, Alexander Kuropov, Tuba...Ozkan-Haller Oregon State University Corvallis, OR 97331 phone: (541) 737-2914 fax: (541) 737-2064 email: holman @coas.oregonstate.edu Steve...Infrared Remote Sensing and Lidar– UW: Chickadel and Jessup B. Electro-Optical Remote Sensing – OSU: Holman C. Microwave Remote Sensing – UW

  14. [A review on polarization information in the remote sensing detection].

    Science.gov (United States)

    Gong, Jie-Qiong; Zhan, Hai-Gang; Liu, Da-Zhao

    2010-04-01

    Polarization is one of the inherent characteristics. Because the surface of the target structure, internal structure, and the angle of incident light are different, the earth's surface and any target in atmosphere under optical interaction process will have their own characteristic nature of polarization. Polarimetric characteristics of radiation energy from the targets are used in polarization remote sensing detection as detective information. Polarization remote sensing detection can get the seven-dimensional information of targets in complicated backgrounds, detect well-resolved outline of targets and low-reflectance region of objectives, and resolve the problems of atmospheric detection and identification camouflage detection which the traditional remote sensing detection can not solve, having good foreground in applications. This paper introduces the development of polarization information in the remote sensing detection from the following four aspects. The rationale of polarization remote sensing detection is the base of polarization remote sensing detection, so it is firstly introduced. Secondly, the present researches on equipments that are used in polarization remote sensing detection are particularly and completely expatiated. Thirdly, the present exploration of theoretical simulation of polarization remote sensing detection is well detailed. Finally, the authors present the applications research home and abroad of the polarization remote sensing detection technique in the fields of remote sensing, atmospheric sounding, sea surface and underwater detection, biology and medical diagnosis, astronomical observation and military, summing up the current problems in polarization remote sensing detection. The development trend of polarization remote sensing detection technology in the future is pointed out in order to provide a reference for similar studies.

  15. SYMPOSIUM ON REMOTE SENSING IN THE POLAR REGIONS

    Science.gov (United States)

    The Arctic Institute of North America long has been interested in encouraging full and specific attention to applications of remote sensing to polar...research problems. The major purpose of the symposium was to acquaint scientists and technicians concerned with remote sensing with some of the...special problems of the polar areas and, in turn, to acquaint polar scientists with the potential of the use of remote sensing . The Symposium therefore was

  16. Basic research in the field of thermal infrared remote sensing

    Institute of Scientific and Technical Information of China (English)

    徐冠华

    2000-01-01

    This overview paper points out that one of the problems impeding further development of remote sensing is that not much attention has been paid to basic research. Key contents of basic research in remote sensing, including modeling, inversion, scaling and scientific experiments, are reviewed. Significance of basic research is demonstrated through summarizing the intentions and progress of the project "Quantitative Remote Sensing Research on Land Surface Energy Exchange".

  17. River Channel Migration: A Remote Sensing and GIS Analysis

    Science.gov (United States)

    Islam, Tariqul

    2010-12-01

    Remote sensing and geographic information system provide tools for quantitative and qualitative river morphological analysis. Bangladesh is a riverine, flood prone country and, the Padma and the Jamuna are two of major three rivers in the country. The aim of this research is to monitor the channel migration of the Padma and the Jamuna rivers since 1977 to 2004 using remote sensing and GIS. Four scenes for dry season's cloud free Landsat images were used in this study. Images were processed using PCI Geomatica and ArcGIS 9.3 was used for GIS analysis. The Landsat images were visualized and identified nine locations to investigate the channel migration. The images were classified into two broad categories, i.e. water and nonwater body. ArcGIS 9.3 was used to transfer these classified images into GIS layers. A standard measurement tool of ArcGIS was applied to measure the movement of river channel based on initial river channel in 1977. General trend of the Padma and the Jamuna river channel migration at locations A, B, C, D, F, G, H and I towards north, northeast and southwest eventually, north, northeast, east, east, west and west, respectively. The confluence point of the Padma and Jamuna (at location E) migrated toward southeast with high rate. During 1977-2004, it migrated about 9000m toward southeast. Trend of migration of the confluence point was faster than any other locations in the channel of the Padma river.

  18. Estimation of rainfall using remote sensing for Riyadh climate, KSA

    Science.gov (United States)

    AlHassoun, Saleh A.

    2013-05-01

    Rainfall data constitute an important parameter for studying water resources-related problems. Remote sensing techniques could provide rapid and comprehensive overview of the rainfall distribution in a given area. Thus, the infrared data from the LandSat satellite in conjunction with the Scofield-oliver method were used to monitor and model rainfall in Riyadh area as a resemble of any area in the Kingdom of Saudi Arabia(KSA). Four convective clouds that covered two rain gage stations were analyzed. Good estimation of rainfall was obtained from satellite images. The results showed that the satellite rainfall estimations were well correlated to rain gage measurements. The satellite climate data appear to be useful for monitoring and modeling rainfall at any area where no rain gage is available.

  19. Remotely Sensing the Photochemical Reflectance Index (PRI)

    Science.gov (United States)

    Vanderbilt, Vern

    2015-01-01

    In remote sensing, the Photochemical Reflectance Index (PRI) provides insight into physiological processes occurring inside the leaves in a stand of plants. Developed by Gamon et al., (1990 and 1992), PRI evolved from laboratory measurements of the reflectance of individual leaves (Bilger et al.,1989). Yet in a remotely sensed image, a pixel measurement may include light from both reflecting and transmitting leaves. We conducted laboratory experiments comparing values of PRI based upon polarized reflectance and transmittance measurements of water and nutrient stressed leaves. We illuminated single detached leaves using a current controlled light source (Oriel model 66881) and measured the leaf weight using an analytical balance (Mettler model AE 260) and the light reflected and transmitted by the leaf during dry down using two Analytical Spectral Devices spectroradiometers. Polarizers on the incident and reflected light beams allowed us to divide the leaf reflectance into two parts: a polarized surface reflectance and a non-polarized 'leaf interior' reflectance. Our results underscore the importance when calculating PRI of removing the leaf surface reflection, which contains no information about physiological processes ongoing in the leaf interior. The results show that the leaf physiology information is in the leaf interior reflectance, not the leaf transmittance. Applied to a plant stand, these results suggest use of polarization measurements in sun-view directions that minimize the number of sunlit transmitting leaves in the sensor field of view.

  20. Theory of Geological Anomaly in Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Geological anomaly is geological body or complex body with obviously different compositions, structures or orders of genesis as compared with those in the surrounding areas. Geological anomaly, restrained by the geological factors closely associated with ore-forming process, is an important clue to ore deposits. The geological anomaly serves as a geological sign to locate ore deposits. Therefore, it is very important to study how to define the characteristics of geological anomaly and further to locate the changes in these characteristics. In this paper, the authors propose the geological anomaly based on the remote-sensing images and data, and expound systematically such image features as scale, size, boundary, morphology and genesis of geological anomalies. Then the authors introduce the categorization of the geological anomalies according to their geneses. The image characteristics of some types of geological anomalies, such as the underground geological anomaly, are also explained in detail. Based on the remote-sensing interpretation of these geological anomalies, the authors conclude that the forecasting and exploration of ore deposits should be focused on the following three aspects: (1) the analysis of geological setting and geological anomaly; (2) the analysis of circular geological anomaly, and (3) the comprehensive forecasting of ore deposits and the research into multi-source information.

  1. Environmental impact prediction using remote sensing images

    Institute of Scientific and Technical Information of China (English)

    Pezhman ROUDGARMI; Masoud MONAVARI; Jahangir FEGHHI; Jafar NOURI; Nematollah KHORASANI

    2008-01-01

    Environmental impact prediction is an important step in many environmental studies. Awide variety of methods have been developed in this concern. During this study, remote sensing images were used for environmental impact prediction in Robatkarim area, Iran, during the years of 2005~2007. It was assumed that environmental impact could be predicted using time series satellite imageries. Natural vegetation cover was chosen as a main environmental element and a case study. Environmental impacts of the regional development on natural vegetation of the area were investigated considering the changes occurred on the extent of natural vegetation cover and the amount of biomass. Vegetation data, land use and land cover classes (as activity factors) within several years were prepared using satellite images. The amount ofbiomass was measured by Soil-adjusted Vegetation Index (SAVI) and Normalized Difference Vegetation Index (NDVI) based on satellite images. The resulted biomass estimates were tested by the paired samples t-test method. No significant difference was observed between the average biomass of estimated and control samples at the 5% significance level. Finally, regression models were used for the environmental impacts prediction. All obtained regression models for prediction of impacts on natural vegetation cover show values over 0.9 for both correlation coefficient and R-squared. According to the resulted methodology, the prediction models of projects and plans impacts can also be developed for other environmental elements which may be derived using time series remote sensing images.

  2. Machine learning in geosciences and remote sensing

    Institute of Scientific and Technical Information of China (English)

    David J. Lary; Amir H. Alavi; Amir H. Gandomi; Annette L. Walker

    2016-01-01

    Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc.) that can provide multivariate, nonlinear, nonparametric regres-sion or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the ef-ficiency of ML for tackling the geosciences and remote sensing problems.

  3. Machine learning in geosciences and remote sensing

    Directory of Open Access Journals (Sweden)

    David J. Lary

    2016-01-01

    Full Text Available Learning incorporates a broad range of complex procedures. Machine learning (ML is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc. that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems.

  4. Benthic habitat mapping using hyperspectral remote sensing

    Science.gov (United States)

    Vélez-Reyes, Miguel; Goodman, James A.; Castrodad-Carrau, Alexey; Jiménez-Rodriguez, Luis O.; Hunt, Shawn D.; Armstrong, Roy

    2006-09-01

    Benthic habitats are the different bottom environments as defined by distinct physical, geochemical, and biological characteristics. Remote sensing is increasingly being used to map and monitor the complex dynamics associated with estuarine and nearshore benthic habitats. Advantages of remote sensing technology include both the qualitative benefits derived from a visual overview, and more importantly, the quantitative abilities for systematic assessment and monitoring. Advancements in instrument capabilities and analysis methods are continuing to expand the accuracy and level of effectiveness of the resulting data products. Hyperspectral sensors in particular are rapidly emerging as a more complete solution, especially for the analysis of subsurface shallow aquatic systems. The spectral detail offered by hyperspectral instruments facilitates significant improvements in the capacity to differentiate and classify benthic habitats. This paper reviews two techniques for mapping shallow coastal ecosystems that both combine the retrieval of water optical properties with a linear unmixing model to obtain classifications of the seafloor. Example output using AVIRIS hyperspectral imagery of Kaneohe Bay, Hawaii is employed to demonstrate the application potential of the two approaches and compare their respective results.

  5. Remote sensing application for property tax evaluation

    Science.gov (United States)

    Jain, Sadhana

    2008-02-01

    This paper presents a study for linking remotely sensed data with property tax related issues. First, it discusses the key attributes required for property taxation and evaluates the capabilities of remote sensing technology to measure these attributes accurately at parcel level. Next, it presents a detailed case study of six representative wards of different characteristics in Dehradun, India, that illustrates how measurements of several of these attributes supported by field survey can be combined to address the issues related to property taxation. Information derived for various factors quantifies the property taxation contributed by an average dwelling unit of the different income groups. Results show that the property tax calculated in different wards varies between 55% for the high-income group, 32% for the middle-income group, 12% for the low-income group and 1% for squatter units. The study concludes that higher spatial resolution satellite data and integrates social survey helps to assess the socio-economic status of the population for tax contribution purposes.

  6. Land remote sensing commercialization: A status report

    Science.gov (United States)

    Bishop, W. P.; Heacock, E. L.

    1984-01-01

    The current offer by the United States Department of Commerce to transfer the U.S. land remote sensing program to the private sector is described. A Request for Proposals (RFP) was issued, soliciting offers from U.S. firms to provide a commercial land remote sensing satellite system. Proposals must address a complete system including satellite, communications, and ground data processing systems. Offerors are encouraged to propose to take over the Government LANDSAT system which consists of LANDSAT 4 and LANDSAT D'. Also required in proposals are the market development procedures and plans to ensure that commercialization is feasible and the business will become self-supporting at the earliest possible time. As a matter of Federal Policy, the solicitation is designed to protect both national security and foreign policy considerations. In keeping with these concerns, an offeror must be a U.S. Firm. Requirements for data quality, quantity, distribution and delivery are met by current operational procedures. It is the Government's desire that the Offeror be prepared to develop and operate follow-on systems without Government subsidies. However, to facilitate rapid commercialization, an offeror may elect to include in his proposal mechanisms for short term government financial assistance.

  7. Method of determining forest production from remotely sensed forest parameters

    Science.gov (United States)

    Corey, J.C.; Mackey, H.E. Jr.

    1987-08-31

    A method of determining forest production entirely from remotely sensed data in which remotely sensed multispectral scanner (MSS) data on forest 5 composition is combined with remotely sensed radar imaging data on forest stand biophysical parameters to provide a measure of forest production. A high correlation has been found to exist between the remotely sensed radar imaging data and on site measurements of biophysical 10 parameters such as stand height, diameter at breast height, total tree height, mean area per tree, and timber stand volume.

  8. Levee Health Monitoring With Radar Remote Sensing

    Science.gov (United States)

    Jones, C. E.; Bawden, G. W.; Deverel, S. J.; Dudas, J.; Hensley, S.; Yun, S.

    2012-12-01

    Remote sensing offers the potential to augment current levee monitoring programs by providing rapid and consistent data collection over large areas irrespective of the ground accessibility of the sites of interest, at repeat intervals that are difficult or costly to maintain with ground-based surveys, and in rapid response to emergency situations. While synthetic aperture radar (SAR) has long been used for subsidence measurements over large areas, applying this technique directly to regional levee monitoring is a new endeavor, mainly because it requires both a wide imaging swath and fine spatial resolution to resolve individual levees within the scene, a combination that has not historically been available. Application of SAR remote sensing directly to levee monitoring has only been attempted in a few pilot studies. Here we describe how SAR remote sensing can be used to assess levee conditions, such as seepage, drawing from the results of two levee studies: one of the Sacramento-San Joaquin Delta levees in California that has been ongoing since July 2009 and a second that covered the levees near Vicksburg, Mississippi, during the spring 2011 floods. These studies have both used data acquired with NASA's UAVSAR L-band synthetic aperture radar, which has the spatial resolution needed for this application (1.7 m single-look), sufficiently wide imaging swath (22 km), and the longer wavelength (L-band, 0.238 m) required to maintain phase coherence between repeat collections over levees, an essential requirement for applying differential interferometry (DInSAR) to a time series of repeated collections for levee deformation measurement. We report the development and demonstration of new techniques that employ SAR polarimetry and differential interferometry to successfully assess levee health through the quantitative measurement of deformation on and near levees and through detection of areas experiencing seepage. The Sacramento-San Joaquin Delta levee study, which covers

  9. Remote Sensing Training for Middle School through the Center of Excellence in Remote Sensing Education

    Science.gov (United States)

    Hayden, L. B.; Johnson, D.; Baltrop, J.

    2012-12-01

    Remote sensing has steadily become an integral part of multiple disciplines, research, and education. Remote sensing can be defined as the process of acquiring information about an object or area of interest without physical contact. As remote sensing becomes a necessity in solving real world problems and scientific questions an important question to consider is why remote sensing training is significant to education and is it relevant to training students in this discipline. What has been discovered is the interest in Science, Technology, Engineering and Mathematics (STEM) fields, specifically remote sensing, has declined in our youth. The Center of Excellence in Remote Sensing Education and Research (CERSER) continuously strives to provide education and research opportunities on ice sheet, coastal, ocean, and marine science. One of those continued outreach efforts are Center for Remote Sensing of Ice Sheets (CReSIS) Middle School Program. Sponsored by the National Science Foundation CReSIS Middle School Program offers hands on experience for middle school students. CERSER and NSF offer students the opportunity to study and learn about remote sensing and its vital role in today's society as it relate to climate change and real world problems. The CReSIS Middle School Program is an annual two-week effort that offers middle school students experience with remote sensing and its applications. Specifically, participants received training with Global Positioning Systems (GPS) where the students learned the tools, mechanisms, and applications of a Garmin 60 GPS. As a part of the program the students were required to complete a fieldwork assignment where several longitude and latitude points were given throughout campus. The students had to then enter the longitude and latitude points into the Garmin 60 GPS, navigate their way to each location while also accurately reading the GPS to make sure travel was in the right direction. Upon completion of GPS training the

  10. Objected-oriented remote sensing image classification method based on geographic ontology model

    Science.gov (United States)

    Chu, Z.; Liu, Z. J.; Gu, H. Y.

    2016-11-01

    Nowadays, with the development of high resolution remote sensing image and the wide application of laser point cloud data, proceeding objected-oriented remote sensing classification based on the characteristic knowledge of multi-source spatial data has been an important trend on the field of remote sensing image classification, which gradually replaced the traditional method through improving algorithm to optimize image classification results. For this purpose, the paper puts forward a remote sensing image classification method that uses the he characteristic knowledge of multi-source spatial data to build the geographic ontology semantic network model, and carries out the objected-oriented classification experiment to implement urban features classification, the experiment uses protégé software which is developed by Stanford University in the United States, and intelligent image analysis software—eCognition software as the experiment platform, uses hyperspectral image and Lidar data that is obtained through flight in DaFeng City of JiangSu as the main data source, first of all, the experiment uses hyperspectral image to obtain feature knowledge of remote sensing image and related special index, the second, the experiment uses Lidar data to generate nDSM(Normalized DSM, Normalized Digital Surface Model),obtaining elevation information, the last, the experiment bases image feature knowledge, special index and elevation information to build the geographic ontology semantic network model that implement urban features classification, the experiment results show that, this method is significantly higher than the traditional classification algorithm on classification accuracy, especially it performs more evidently on the respect of building classification. The method not only considers the advantage of multi-source spatial data, for example, remote sensing image, Lidar data and so on, but also realizes multi-source spatial data knowledge integration and application

  11. Geographic Information System and Remote Sensing Applications in Flood Hazards Management: A Review

    Directory of Open Access Journals (Sweden)

    Dano Umar Lawal

    2011-09-01

    Full Text Available The purpose of this study is to examine and review the various applications of GIS and remote sensing tools in flood disaster management as opposed to the conventional means of recording the hydrological parameters, which in many cases failed to capture an extreme event. In the recent years, GIS along with remote sensing has become the key tools in flood disaster monitoring and management. Advancement particularly in the area of remote sensing application has developed gradually from optical remote sensing to microwave or radar remote sensing, which has proved a profound capability of penetrating a clouded sky and provided all weather capabilities compared to the later (optical remote sensing in flood monitoring, mapping, and management. The main concern here is delineation of flood prone areas and development of flood hazard maps indicating the risk areas likely to be inundated by significant flooding along with the damageable objects maps for the flood susceptible areas. Actually, flood depth is always considered to be the basic aspect in flood hazard mapping, and therefore in determining or estimating the flood depth, a Digital Elevation Model data (DEM is considered to be the most appropriate means of determining the flood depth from a remotely sensed data or hydrological data. Accuracy of flood depth estimation depends mainly on the resolution of the DEM data in a flat terrain and in the regions that experiences monsoon seasons such as the developing countries of Asia where there is a high dependence on agriculture, which made any effort for flood estimation or flood hazard mapping difficult due to poor availability of high resolution DEM. More so the idea of Web-based GIS is gradually becoming a reality, which plays an important role in the flood hazard management. Therefore, this paper provides a review of applications of GIS and remote sensing technology in flood disaster monitoring and management.

  12. Biomass Burning Emissions from Fire Remote Sensing

    Science.gov (United States)

    Ichoku, Charles

    2010-01-01

    Knowledge of the emission source strengths of different (particulate and gaseous) atmospheric constituents is one of the principal ingredients upon which the modeling and forecasting of their distribution and impacts depend. Biomass burning emissions are complex and difficult to quantify. However, satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP), which has a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. In this presentation, we will show how the satellite measurement of FRP is facilitating the quantitative characterization of biomass burning and smoke emission rates, and the implications of this unique capability for improving our understanding of smoke impacts on air quality, weather, and climate. We will also discuss some of the challenges and uncertainties associated with satellite measurement of FRP and how they are being addressed.

  13. Remote Sensing of Parasitic Nematodes in Plants

    Science.gov (United States)

    Lawrence, Gary W.; King, Roger; Kelley, Amber T.; Vickery, John

    2007-01-01

    A method and apparatus for remote sensing of parasitic nematodes in plants, now undergoing development, is based on measurement of visible and infrared spectral reflectances of fields where the plants are growing. Initial development efforts have been concentrated on detecting reniform nematodes (Rotylenchulus reniformis) in cotton plants, because of the economic importance of cotton crops. The apparatus includes a hand-held spectroradiometer. The readings taken by the radiometer are processed to extract spectral reflectances at sixteen wavelengths between 451 and 949 nm that, taken together, have been found to be indicative of the presence of Rotylenchulus reniformis. The intensities of the spectral reflectances are used to estimate the population density of the nematodes in an area from which readings were taken.

  14. Toward interactive search in remote sensing imagery

    Energy Technology Data Exchange (ETDEWEB)

    Porter, Reid B [Los Alamos National Laboratory; Hush, Do [Los Alamos National Laboratory; Harvey, Neal [Los Alamos National Laboratory; Theile, James [Los Alamos National Laboratory

    2010-01-01

    To move from data to information in almost all science and defense applications requires a human-in-the-loop to validate information products, resolve inconsistencies, and account for incomplete and potentially deceptive sources of information. This is a key motivation for visual analytics which aims to develop techniques that complement and empower human users. By contrast, the vast majority of algorithms developed in machine learning aim to replace human users in data exploitation. In this paper we describe a recently introduced machine learning problem, called rare category detection, which may be a better match to visual analytic environments. We describe a new design criteria for this problem, and present comparisons to existing techniques with both synthetic and real-world datasets. We conclude by describing an application in broad-area search of remote sensing imagery.

  15. Remote sensing and characterization of anomalous debris

    Science.gov (United States)

    Sridharan, R.; Beavers, W.; Lambour, R.; Gaposchkin, E. M.; Kansky, J.; Stansbery, E.

    1997-01-01

    The analysis of orbital debris data shows a band of anomalously high debris concentration in the altitude range between 800 and 1000 km. Analysis indicates that the origin is the leaking coolant fluid from nuclear power sources that powered a now defunct Soviet space-based series of ocean surveillance satellites. A project carried out to detect, track and characterize a sample of the anomalous debris is reported. The nature of the size and shape of the sample set, and the possibility of inferring the composition of the droplets were assessed. The technique used to detect, track and characterize the sample set is described and the results of the characterization analysis are presented. It is concluded that the nature of the debris is consistent with leaked Na-K fluid, although this cannot be proved with the remote sensing techniques used.

  16. Remote sensing of balsam fir forest vigor

    Science.gov (United States)

    Luther, Joan E.; Carroll, Allen L.

    1997-12-01

    The potential of remote sensing to monitor indices of forest health was tested by examining the spectral separability of plots with different balsam fir, Abies balsamea (L.) Mill, vigor. Four levels of vigor were achieved with controlled experimental manipulations of forest stands. In order of increasing vigor, the treatments were root pruning, control, thinning and thinning in combination with fertilization. Spectral reflectance of branchlets from each plot were measured under laboratory conditions using a field portable spectroradiometer with a spectral range from 350 - 2500 nm. Branchlets were discriminated using combinations of factor and discriminant analyses techniques with classification accuracies of 91% and 83% for early and late season analyses, respectively. Relationships between spectral reflectance measurements at canopy levels, stand vigor, and foliage quality for an insect herbivore will be analyzed further in support of future large scale monitoring of balsam fir vulnerability to insect disturbance.

  17. Benefits to world agriculture through remote sensing

    Science.gov (United States)

    Buffalano, A. C.; Kochanowski, P.

    1976-01-01

    Remote sensing of agricultural land permits crop classification and mensuration which can lead to improved forecasts of production. This technique is particularly important for nations which do not already have an accurate agricultural reporting system. Better forecasts have important economic effects. International grain traders can make better decisions about when to store, buy, and sell. Farmers can make better planting decisions by taking advantage of production estimates for areas out of phase with their own agricultural calendar. World economic benefits will accrue to both buyers and sellers because of increased food supply and price stabilization. This paper reviews the econometric models used to establish this scenario and estimates the dollar value of benefits for world wheat as 200 million dollars annually for the United States and 300 to 400 million dollars annually for the rest of the world.

  18. Biomass Burning Emissions from Fire Remote Sensing

    Science.gov (United States)

    Ichoku, Charles

    2010-01-01

    Knowledge of the emission source strengths of different (particulate and gaseous) atmospheric constituents is one of the principal ingredients upon which the modeling and forecasting of their distribution and impacts depend. Biomass burning emissions are complex and difficult to quantify. However, satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP), which has a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. In this presentation, we will show how the satellite measurement of FRP is facilitating the quantitative characterization of biomass burning and smoke emission rates, and the implications of this unique capability for improving our understanding of smoke impacts on air quality, weather, and climate. We will also discuss some of the challenges and uncertainties associated with satellite measurement of FRP and how they are being addressed.

  19. Multisensor image fusion techniques in remote sensing

    Science.gov (United States)

    Ehlers, Manfred

    Current and future remote sensing programs such as Landsat, SPOT, MOS, ERS, JERS, and the space platform's Earth Observing System (Eos) are based on a variety of imaging sensors that will provide timely and repetitive multisensor earth observation data on a global scale. Visible, infrared and microwave images of high spatial and spectral resolution will eventually be available for all parts of the earth. It is essential that efficient processing techniques be developed to cope with the large multisensor data volumes. This paper discusses data fusion techniques that have proved successful for synergistic merging of SPOT HRV, Landsat TM and SIR-B images. It is demonstrated that these techniques can be used to improve rectification accuracies, to depicit greater cartographic detail, and to enhance spatial resolution in multisensor image data sets.

  20. Adaptive Remote Sensing Texture Compression on GPU

    Directory of Open Access Journals (Sweden)

    Xiao-Xia Lu

    2010-11-01

    Full Text Available Considering the properties of remote sensing texture such as strong randomness and weak local correlation, a novel adaptive compression method based on vector quantizer is presented and implemented on GPU. Utilizing the property of Human Visual System (HVS, a new similarity measurement function is designed instead of using Euclid distance. Correlated threshold between blocks can be obtained adaptively according to the property of different images without artificial auxiliary. Furthermore, a self-adaptive threshold adjustment during the compression is designed to improve the reconstruct quality. Experiments show that the method can handle various resolution images adaptively. It can achieve satisfied compression rate and reconstruct quality at the same time. Index is coded to further increase the compression rate. The coding way is designed to guarantee accessing the index randomly too. Furthermore, the compression and decompression process is speed up with the usage of GPU, on account of their parallelism.

  1. Unsupervised classification of remote multispectral sensing data

    Science.gov (United States)

    Su, M. Y.

    1972-01-01

    The new unsupervised classification technique for classifying multispectral remote sensing data which can be either from the multispectral scanner or digitized color-separation aerial photographs consists of two parts: (a) a sequential statistical clustering which is a one-pass sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. Applications of the technique using an IBM-7094 computer on multispectral data sets over Purdue's Flight Line C-1 and the Yellowstone National Park test site have been accomplished. Comparisons between the classification maps by the unsupervised technique and the supervised maximum liklihood technique indicate that the classification accuracies are in agreement.

  2. Recent Progresses of Microwave Marine Remote Sensing

    Science.gov (United States)

    Yang, Jingsong; Ren, Lin; Zheng, Gang; Wang, He; He, Shuangyan; Wang, Juan; Li, Xiaohui

    2016-08-01

    It is presented in this paper the recent progresses of Dragon 3 Program (ID. 10412) in the field of microwave marine remote sensing including (1) ocean surface wind fields from full polarization synthetic aperture radars (SAR), (2) joint retrieval of directional ocean wave spectra from SAR and wave spectrometer, (3) error analysis on ENVISAT ASAR wave mode significant wave height (SWH) retrievals using triple collocation model, (4) typhoon observation from SAR and optical sensors, (5) ocean internal wave observation from SAR and optical sensors, (6) ocean eddy observation from SAR and optical sensors, (7) retrieval models of water vapor and wet tropospheric path delay for the HY-2A calibration microwave radiometer, (8) calibration of SWH from HY-2A satellite altimeter.

  3. Remote sensing with laser spectrum radar

    Science.gov (United States)

    Wang, Tianhe; Zhou, Tao; Jia, Xiaodong

    2016-10-01

    The unmanned airborne (UAV) laser spectrum radar has played a leading role in remote sensing because the transmitter and the receiver are together at laser spectrum radar. The advantages of the integrated transceiver laser spectrum radar is that it can be used in the oil and gas pipeline leak detection patrol line which needs the non-contact reflective detection. The UAV laser spectrum radar can patrol the line and specially detect the swept the area are now in no man's land because most of the oil and gas pipelines are in no man's land. It can save labor costs compared to the manned aircraft and ensure the safety of the pilots. The UAV laser spectrum radar can be also applied in the post disaster relief which detects the gas composition before the firefighters entering the scene of the rescue.

  4. Urban environmental health applications of remote sensing

    Science.gov (United States)

    Rush, M.; Goldstein, J.; Hsi, B. P.; Olsen, C. B.

    1974-01-01

    An urban area was studied through the use of the inventory-by-surrogate method rather than by direct interpretation of photographic imagery. Prior uses of remote sensing in urban and public research are examined. The effects of crowding, poor housing conditions, air pollution, and street conditions on public health are considered. Color infrared photography was used to categorize land use features and the grid method was used in photo interpretation analysis. The incidence of shigella and salmonella, hepatitis, meningitis, tuberculosis, myocardial infarction and veneral disease were studied, together with mortality and morbidity rates. Sample census data were randomly collected and validated. The hypothesis that land use and residential quality are associated with and act as an influence upon health and physical well-being was studied and confirmed.

  5. Remote sensing of vegetation at regional scales

    Science.gov (United States)

    Hall, F. G.

    1984-01-01

    Relations between spectroscopy and the concept of inferring surface cover type and condition from measurements of reflected or emitted radiation are examined, taking into account the observation of 'spectral signatures'. It has now become evident that the paradigm which had provided the basis for the spectroscopic identification of materials, is incomplete when applied to the inference of type and condition of materials in a natural environment. It was found that one could not collect a remote sensing signature from an unknown ground cover class at a particular time and place and match that signature with an a priori catalog value to infer the properties of the unknown cover class. The spectroscopy paradigm was, therefore, largely abandoned in favor of decision theoretic approaches. Attention is given to the temporal greenness profile feature space, the crop stage of development estimation using a temporal greenness profile, the temporal greenness profile for crop yield, and applications to regional scales.

  6. A selected bibliography: Remote sensing applications in wildlife management

    Science.gov (United States)

    Carneggie, David M.; Ohlen, Donald O.; Pettinger, Lawrence R.

    1980-01-01

    Citations of 165 selected technical reports, journal articles, and other publications on remote sensing applications for wildlife management are presented in a bibliography. These materials summarize developments in the use of remotely sensed data for wildlife habitat mapping, habitat inventory, habitat evaluation, and wildlife census. The bibliography contains selected citations published between 1947 and 1979.

  7. Estimation of Areal Soil Water Content through Microwave Remote Sensing

    NARCIS (Netherlands)

    Oevelen, van P.J.

    2000-01-01

    In this thesis the use of microwave remote sensing to estimate soil water content is investigated. A general framework is described which is applicable to both passive and active microwave remote sensing of soil water content. The various steps necessary to estimate areal soil water content are disc

  8. Hydrological Application of Remote Sensing: Surface States -- Snow

    Science.gov (United States)

    Hall, Dorothy K.; Kelly, Richard E. J.; Foster, James L.; Chang, Alfred T. C.

    2004-01-01

    Remote sensing research of snow cover has been accomplished for nearly 40 years. The use of visible, near-infrared, active and passive-microwave remote sensing for the analysis of snow cover is reviewed with an emphasis on the work on the last decade.

  9. Remote sensing observation used in offshore wind energy

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Pena Diaz, Alfredo; Christiansen, Merete Bruun

    2008-01-01

    Remote sensing observations used in offshore wind energy are described in three parts: ground-based techniques and applications, airborne techniques and applications, and satellite-based techniques and applications. Ground-based remote sensing of winds is relevant, in particular, for new large wind...

  10. Deriving harmonised forest information in Europe using remote sensing methods

    DEFF Research Database (Denmark)

    Seebach, Lucia Maria

    the need for harmonised forest information can be satisfied using remote sensing methods. In conclusion, the study showed that it is possible to derive harmonised forest information of high spatial detail in Europe with remote sensing. The study also highlighted the imperative provision of accuracy...

  11. Potential benefits of remote sensing: Theoretical framework and empirical estimate

    Science.gov (United States)

    Eisgruber, L. M.

    1972-01-01

    A theoretical framwork is outlined for estimating social returns from research and application of remote sensing. The approximate dollar magnitude is given of a particular application of remote sensing, namely estimates of corn production, soybeans, and wheat. Finally, some comments are made on the limitations of this procedure and on the implications of results.

  12. Streamflow modelling by remote sensing: a contribution to digital earth

    NARCIS (Netherlands)

    Tan, M.L.; Latif, A.B.; Pohl, C.; Duan, Z.

    2014-01-01

    Remote sensing contributes valuable information to streamflow estimates. This paper discusses its relevance to the digital earth concept. The authors categorize the role of remote sensing in streamflow modelling and estimation. This paper emphasizes the applications and challenges of satellite-based

  13. Application of remote sensing to agricultural field trials.

    NARCIS (Netherlands)

    Clevers, J.G.P.W.

    1986-01-01

    Remote sensing techniques enable quantitative information about a field trial to be obtained instantaneously and non-destructively. The aim of this study was to identify a method that can reduce inaccuracies in field trial analysis, and to identify how remote sensing can support and/or replace conve

  14. Remote sensing fire and fuels in southern California

    Science.gov (United States)

    Philip Riggan; Lynn Wolden; Bob Tissell; David Weise; J. Coen

    2011-01-01

    Airborne remote sensing at infrared wavelengths has the potential to quantify large-fire properties related to energy release or intensity, residence time, fuel-consumption rate, rate of spread, and soil heating. Remote sensing at a high temporal rate can track fire-line outbreaks and acceleration and spotting ahead of a fire front. Yet infrared imagers and imaging...

  15. Study on spectral structure of quantum remote sensing

    Institute of Scientific and Technical Information of China (English)

    BI; Siwen; HAN; Jixia

    2006-01-01

    A study of the use of fine spectral structure in quantum remote sensing, including an expression, begins with a summary of present-day applications of spectrum remote sensing, which is followed by a theoretical discussion of the influence of electronic spin upon hydrogen-like atom energy levels and the calculation of spectral line in the absence of a circumstance field.

  16. Quantitative Application Study on Remote Sensing of Suspended Sediment

    Institute of Scientific and Technical Information of China (English)

    CHEN Yi-mei; XU Su-dong; LIN Qiang

    2012-01-01

    Quantitative application on remote sensing of suspended sediment is an important aspect of the engineering application of remote sensing study.In this paper,the Xiamen Bay is chosen as the study area.Eleven different phases of the remote sensing data are selected to establish a quantitative remote sensing model to map suspended sediment by using remote sensing images and the quasi-synchronous measured sediment data.Based on empirical statistics developed are the conversion models between instantaneous suspended sediment concentration and tidally-averaged suspended sediment concentration as well as the conversion models between surface layer suspended sediment concentration and the depth-averaged suspended sediment concentration.On this basis,the quantitative application integrated model on remote sensing of suspended sediment is developed.By using this model as well as multi-temporal remote sensing images,multi-year averaged suspended sediment concentration of the Xiamen Bay are predicted.The comparison between model prediction and observed data shows that the multi-year averaged suspended sediment concentration of studied sites as well as the concentration difference of neighboring sites can be well predicted by the remote sensing model with an error rate of 21.61% or less,which can satisfy the engineering requirements of channel deposition calculation.

  17. Technology Progress Report for Spaceborne Microwave Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    JHANG Jingshan; LIU Heguang; DONG Xiaolong

    2006-01-01

    In this presentation, technological progress for China's microwave remote sensing is introduced. New developments of the microwave remote sensing instruments formeteorological satellite FY-3, ocean dynamic measurement satellite (HY-2), environment small SAR satellite (H J-1C) and China's lunar exploration satellite (Chang'E-1), are reported.

  18. Progress for Spaceborne Microwave Remote Sensing in China

    Institute of Scientific and Technical Information of China (English)

    JIANG Jingshan; LIU Heguang; DONG Xiaolong

    2008-01-01

    In this paper, technological progress for China's microwave remote sensing is introduced. New developments of the microwave remote sensing instruments for meteorological satellite FY-3, ocean dynamic measurement satellite (HY-2), environment small SAR satellite (HJ-1C) and China's lunar exploration satellite (Chang'E-1), geostationary orbit meteorological satellite FY-4M,are reported.

  19. Acoustic Remote Sensing of Rogue Waves

    Science.gov (United States)

    Parsons, Wade; Kadri, Usama

    2016-04-01

    We propose an early warning system for approaching rogue waves using the remote sensing of acoustic-gravity waves (AGWs) - progressive sound waves that propagate at the speed of sound in the ocean. It is believed that AGWs are generated during the formation of rogue waves, carrying information on the rogue waves at near the speed of sound, i.e. much faster than the rogue wave. The capability of identifying those special sound waves would enable detecting rogue waves most efficiently. A lot of promising work has been reported on AGWs in the last few years, part of which in the context of remote sensing as an early detection of tsunami. However, to our knowledge none of the work addresses the problem of rogue waves directly. Although there remains some uncertainty as to the proper definition of a rogue wave, there is little doubt that they exist and no one can dispute the potential destructive power of rogue waves. An early warning system for such extreme waves would become a demanding safety technology. A closed form expression was developed for the pressure induced by an impulsive source at the free surface (the Green's function) from which the solution for more general sources can be developed. In particular, we used the model of the Draupner Wave of January 1st, 1995 as a source and calculated the induced AGW signature. In particular we studied the AGW signature associated with a special feature of this wave, and characteristic of rogue waves, of the absence of any local set-down beneath the main crest and the presence of a large local set-up.

  20. Remote sensing of sagebrush canopy nitrogen

    Science.gov (United States)

    Mitchell, Jessica J.; Glenn, Nancy F.; Sankey, Temuulen T.; Derryberry, DeWayne R.; Germino, Matthew J.

    2012-01-01

    This paper presents a combination of techniques suitable for remotely sensing foliar Nitrogen (N) in semiarid shrublands – a capability that would significantly improve our limited understanding of vegetation functionality in dryland ecosystems. The ability to estimate foliar N distributions across arid and semi-arid environments could help answer process-driven questions related to topics such as controls on canopy photosynthesis, the influence of N on carbon cycling behavior, nutrient pulse dynamics, and post-fire recovery. Our study determined that further exploration into estimating sagebrush canopy N concentrations from an airborne platform is warranted, despite remote sensing challenges inherent to open canopy systems. Hyperspectral data transformed using standard derivative analysis were capable of quantifying sagebrush canopy N concentrations using partial least squares (PLS) regression with an R2 value of 0.72 and an R2 predicted value of 0.42 (n = 35). Subsetting the dataset to minimize the influence of bare ground (n = 19) increased R2 to 0.95 (R2 predicted = 0.56). Ground-based estimates of canopy N using leaf mass per unit area measurements (LMA) yielded consistently better model fits than ground-based estimates of canopy N using cover and height measurements. The LMA approach is likely a method that could be extended to other semiarid shrublands. Overall, the results of this study are encouraging for future landscape scale N estimates and represent an important step in addressing the confounding influence of bare ground, which we found to be a major influence on predictions of sagebrush canopy N from an airborne platform.

  1. Remote sensing monitoring of the global ozonosphere

    Science.gov (United States)

    Genco, S.; Bortoli, D.; Ravegnani, F.

    2013-10-01

    The use of CFCs, which are the main responsible for the ozone depletion in the upper atmosphere and the formation of the so-called "ozone hole" over Antarctic Region, was phase out by Montreal Protocol (1989). CFCs' concentration is recently reported to decrease in the free atmosphere, but severe episodes of ozone depletion in both Arctic and Antarctic regions are still occurring. Nevertheless the complete recovery of the Ozone layer is expected by about 2050. Recent simulation of perturbations in stratospheric chemistry highlight that circulation, temperature and composition are strictly correlated and they influence the global climate changes. Chemical composition plays an important role in the thermodynamic of the atmosphere, as every gaseous species can absorb and emit in different wavelengths, so their different concentration is responsible for the heating or cooling of the atmosphere. Therefore long-term observations are required to monitor the evolution of the stratospheric ozone layer. Measurements from satellite remote sensing instruments, which provide wide coverage, are supplementary to selective ground-based observations which are usually better calibrated, more stable in time and cover a wider time span. The combination of the data derived from different space-borne instruments calibrated with ground-based sensors is needed to produce homogeneous and consistent long-term data records. These last are required for robust investigations and especially for trend analysis. Here, we perform a review of the major remote-sensing techniques and of the principal datasets available to study the evolution of ozone layer in the past decades and predict future behavio

  2. Remote Sensing of shallow sea floor for digital earth environment

    Science.gov (United States)

    Yahya, N. N.; Hashim, M.; Ahmad, S.

    2014-02-01

    Understanding the sea floor biodiversity requires spatial information that can be acquired from remote sensing satellite data. Species volume, spatial patterns and species coverage are some of the information that can be derived. Current approaches for mapping sea bottom type have evolved from field observation, visual interpretation from aerial photography, mapping from remote sensing satellite data along with field survey and hydrograhic chart. Remote sensing offers most versatile technique to map sea bottom type up to a certain scale. This paper reviews the technical characteristics of signal and light interference within marine features, space and remote sensing satellite. In addition, related image processing techniques that are applicable to remote sensing satellite data for sea bottom type digital mapping is also presented. The sea bottom type can be differentiated by classification method using appropriate spectral bands of satellite data. In order to verify the existence of particular sea bottom type, field observations need to be carried out with proper technique and equipment.

  3. Strategies for using remotely sensed data in hydrologic models

    Science.gov (United States)

    Peck, E. L.; Keefer, T. N.; Johnson, E. R. (Principal Investigator)

    1981-01-01

    Present and planned remote sensing capabilities were evaluated. The usefulness of six remote sensing capabilities (soil moisture, land cover, impervious area, areal extent of snow cover, areal extent of frozen ground, and water equivalent of the snow cover) with seven hydrologic models (API, CREAMS, NWSRFS, STORM, STANFORD, SSARR, and NWSRFS Snowmelt) were reviewed. The results indicate remote sensing information has only limited value for use with the hydrologic models in their present form. With minor modifications to the models the usefulness would be enhanced. Specific recommendations are made for incorporating snow covered area measurements in the NWSRFS Snowmelt model. Recommendations are also made for incorporating soil moisture measurements in NWSRFS. Suggestions are made for incorporating snow covered area, soil moisture, and others in STORM and SSARR. General characteristics of a hydrologic model needed to make maximum use of remotely sensed data are discussed. Suggested goals for improvements in remote sensing for use in models are also established.

  4. Remote Sensing-Derived Bathymetry of Lake Poopó

    Directory of Open Access Journals (Sweden)

    Adalbert Arsen

    2013-12-01

    Full Text Available Located within the Altiplano at 3,686 m above sea level, Lake Poopó is remarkably shallow and very sensitive to hydrologic recharge. Progressive drying has been observed in the entire Titicaca-Poopó-Desaguadero-Salar de Coipasa (TPDS system during the last decade, causing dramatic changes to Lake Poopó’s surface and its regional water supplies. Our research aims to improve understanding of Lake Poopó water storage capacity. Thus, we propose a new method based on freely available remote sensing data to reproduce Lake Poopó bathymetry. Laser ranging altimeter ICESat (Ice, Cloud, and land Elevation Satellite is used during the lake’s lowest stages to measure vertical heights with high precision over dry land. These heights are used to estimate elevations of water contours obtained with Landsat imagery. Contour points with assigned elevation are filtered and grouped in a points cloud. Mesh gridding and interpolation function are then applied to construct 3D bathymetry. Complementary analysis of Moderate Resolution Imaging Spectroradiometer (MODIS surfaces from 2000 to 2012 combined with bathymetry gives water levels and storage evolution every 8 days.

  5. Remote Chemical Sensing Using Quantum Cascade Lasers

    Energy Technology Data Exchange (ETDEWEB)

    Harper, Warren W.; Schultz, John F.

    2003-01-30

    Spectroscopic chemical sensing research at Pacific Northwest National Laboratory (PNNL) is focused on developing advanced sensors for detecting the production of nuclear, chemical, or biological weapons; use of chemical weapons; or the presence of explosives, firearms, narcotics, or other contraband of significance to homeland security in airports, cargo terminals, public buildings, or other sensitive locations. For most of these missions, the signature chemicals are expected to occur in very low concentrations, and in mixture with ambient air or airborne waste streams that contain large numbers of other species that may interfere with spectroscopic detection, or be mistaken for signatures of illicit activity. PNNL’s emphasis is therefore on developing remote and sampling sensors with extreme sensitivity, and resistance to interferents, or selectivity. PNNL’s research activities include: 1. Identification of signature chemicals and quantification of their spectral characteristics, 2. Identification and development of laser and other technologies that enable breakthroughs in sensitivity and selectivity, 3. Development of promising sensing techniques through experimentation and modeling the physical phenomenology and practical engineering limitations affecting their performance, and 4. Development and testing of data collection methods and analysis algorithms. Close coordination of all aspects of the research is important to ensure that all parts are focused on productive avenues of investigation. Close coordination of experimental development and numerical modeling is particularly important because the theoretical component provides understanding and predictive capability, while the experiments validate calculations and ensure that all phenomena and engineering limitations are considered.

  6. Mineralogy and astrobiology detection using laser remote sensing instrument.

    Science.gov (United States)

    Abedin, M Nurul; Bradley, Arthur T; Sharma, Shiv K; Misra, Anupam K; Lucey, Paul G; McKay, Christopher P; Ismail, Syed; Sandford, Stephen P

    2015-09-01

    A multispectral instrument based on Raman, laser-induced fluorescence (LIF), laser-induced breakdown spectroscopy (LIBS), and a lidar system provides high-fidelity scientific investigations, scientific input, and science operation constraints in the context of planetary field campaigns with the Jupiter Europa Robotic Lander and Mars Sample Return mission opportunities. This instrument conducts scientific investigations analogous to investigations anticipated for missions to Mars and Jupiter's icy moons. This combined multispectral instrument is capable of performing Raman and fluorescence spectroscopy out to a >100  m target distance from the rover system and provides single-wavelength atmospheric profiling over long ranges (>20  km). In this article, we will reveal integrated remote Raman, LIF, and lidar technologies for use in robotic and lander-based planetary remote sensing applications. Discussions are focused on recently developed Raman, LIF, and lidar systems in addition to emphasizing surface water ice, surface and subsurface minerals, organics, biogenic, biomarker identification, atmospheric aerosols and clouds distributions, i.e., near-field atmospheric thin layers detection for next robotic-lander based instruments to measure all the above-mentioned parameters.

  7. Satellite remote-sensing technologies used in forest fire management

    Institute of Scientific and Technical Information of China (English)

    TIAN Xiao-rui; Douglas J. Mcrae; SHU Li-fu; WANG Ming-yu; LI Hong

    2005-01-01

    Satellite remote sensing has become a primary data source for fire danger rating prediction, fuel and fire mapping, fire monitoring, and fire ecology research. This paper summarizes the research achievements in these research fields, and discusses the future trend in the use of satellite remote-sensing techniques in wildfire management. Fuel-type maps from remote-sensing data can now be produced at spatial and temporal scales quite adequate for operational fire management applications. US National Oceanic and Atmospheric Administration (NOAA) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellites are being used for fire detection worldwide due to their high temporal resolution and ability to detect fires in remote regions. Results can be quickly presented on many Websites providing a valuable service readily available to fire agency. As cost-effective tools, satellite remote-sensing techniques play an important role in fire mapping. Improved remote-sensing techniques have the potential to date older fire scars and provide estimates of burn severity. Satellite remote sensing is well suited to assessing the extent of biomass burning, a prerequisite for estimating emissions at regional and global scales, which are needed for better understanding the effects of fire on climate change. The types of satellites used in fire research are also discussed in the paper. Suggestions on what remote-sensing efforts should be completed in China to modernize fire management technology in this country are given.

  8. Eucalyptus Cloud to Remotely Provision e-Governance Applications

    Directory of Open Access Journals (Sweden)

    Sreerama Prabhu Chivukula

    2011-01-01

    Full Text Available Remote rural areas are constrained by lack of reliable power supply, essential for setting up advanced IT infrastructure as servers or storage; therefore, cloud computing comprising an Infrastructure-as-a-Service (IaaS is well suited to provide such IT infrastructure in remote rural areas. Additional cloud layers of Platform-as-a-Service (PaaS and Software-as-a-Service (SaaS can be added above IaaS. Cluster-based IaaS cloud can be set up by using open-source middleware Eucalyptus in data centres of NIC. Data centres of the central and state governments can be integrated with State Wide Area Networks and NICNET together to form the e-governance grid of India. Web service repositories at centre, state, and district level can be built over the national e-governance grid of India. Using Globus Toolkit, we can achieve stateful web services with speed and security. Adding the cloud layer over the e-governance grid will make a grid-cloud environment possible through Globus Nimbus. Service delivery can be in terms of web services delivery through heterogeneous client devices. Data mining using Weka4WS and DataMiningGrid can produce meaningful knowledge discovery from data. In this paper, a plan of action is provided for the implementation of the above proposed architecture.

  9. Dynamic integration of remote cloud resources into local computing clusters

    Energy Technology Data Exchange (ETDEWEB)

    Fleig, Georg; Erli, Guenther; Giffels, Manuel; Hauth, Thomas; Quast, Guenter; Schnepf, Matthias [Institut fuer Experimentelle Kernphysik, Karlsruher Institut fuer Technologie (Germany)

    2016-07-01

    In modern high-energy physics (HEP) experiments enormous amounts of data are analyzed and simulated. Traditionally dedicated HEP computing centers are built or extended to meet this steadily increasing demand for computing resources. Nowadays it is more reasonable and more flexible to utilize computing power at remote data centers providing regular cloud services to users as they can be operated in a more efficient manner. This approach uses virtualization and allows the HEP community to run virtual machines containing a dedicated operating system and transparent access to the required software stack on almost any cloud site. The dynamic management of virtual machines depending on the demand for computing power is essential for cost efficient operation and sharing of resources with other communities. For this purpose the EKP developed the on-demand cloud manager ROCED for dynamic instantiation and integration of virtualized worker nodes into the institute's computing cluster. This contribution will report on the concept of our cloud manager and the implementation utilizing a remote OpenStack cloud site and a shared HPC center (bwForCluster located in Freiburg).

  10. Commercial future: making remote sensing a media event

    Science.gov (United States)

    Lurie, Ian

    1999-12-01

    The rapid growth of commercial remote sensing has made high quality digital sensing data widely available -- now, remote sensing must become and remain a strong, commercially viable industry. However, this new industry cannot survive without an educated consumer base. To access markets, remote sensing providers must make their product more accessible, both literally and figuratively: Potential customers must be able to find the data they require, when they require it, and they must understand the utility of the information available to them. The Internet and the World Wide Web offer the perfect medium to educate potential customers and to sell remote sensing data to those customers. A well-designed web presence can provide both an information center and a market place for companies offering their data for sale. A very high potential web-based market for remote sensing lies in media. News agencies, web sites, and a host of other visual media services can use remote sensing data to provide current, relevant information regarding news around the world. This paper will provide a model for promotion and sale of remote sensing data via the Internet.

  11. Ten ways remote sensing can contribute to conservation.

    Science.gov (United States)

    Rose, Robert A; Byler, Dirck; Eastman, J Ron; Fleishman, Erica; Geller, Gary; Goetz, Scott; Guild, Liane; Hamilton, Healy; Hansen, Matt; Headley, Rachel; Hewson, Jennifer; Horning, Ned; Kaplin, Beth A; Laporte, Nadine; Leidner, Allison; Leimgruber, Peter; Morisette, Jeffrey; Musinsky, John; Pintea, Lilian; Prados, Ana; Radeloff, Volker C; Rowen, Mary; Saatchi, Sassan; Schill, Steve; Tabor, Karyn; Turner, Woody; Vodacek, Anthony; Vogelmann, James; Wegmann, Martin; Wilkie, David; Wilson, Cara

    2015-04-01

    In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners' use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to

  12. Remote Oxygen Sensing by Ionospheric Excitation (ROSIE

    Directory of Open Access Journals (Sweden)

    K. S. Kalogerakis

    2009-05-01

    Full Text Available The principal optical observable emission resulting from ionospheric modification (IM experiments is the atomic oxygen red line at 630 nm, originating from the O(1D–3P transition. Because the O(1D atom has a long radiative lifetime, it is sensitive to collisional relaxation and an observed decay faster than the radiative rate can be attributed to collisions with atmospheric species. In contrast to the common practice of ignoring O-atoms in interpreting such observations in the past, recent experimental studies on the relaxation of O(1D by O(3P have revealed the dominant role of oxygen atoms in controlling the lifetime of O(1D at altitudes relevant to IM experiments. Using the most up-to-date rate coefficients for collisional relaxation of O(1D by O, N2, and O2, it is now possible to analyze the red line decays observed in IM experiments and thus probe the local ionospheric composition. In this manner, we can demonstrate an approach to remotely detect O-atoms at the altitudes relevant to IM experiments, which we call remote oxygen sensing by ionospheric excitation (ROSIE. The results can be compared with atmospheric models and used to study the temporal, seasonal, altitude and spatial variation of ionospheric O-atom density in the vicinity of heating facilities. We discuss the relevance to atmospheric observations and ionospheric heating experiments and report an analysis of representative IM data.

  13. Preliminary Findings of Inflight Icing Field Test to Support Icing Remote Sensing Technology Assessment

    Science.gov (United States)

    King, Michael; Reehorst, Andrew; Serke, Dave

    2015-01-01

    NASA and the National Center for Atmospheric Research have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology has recently been extended to provide volumetric coverage surrounding an airport. Building on the existing vertical pointing system, the new method for providing volumetric coverage will utilize a vertical pointing cloud radar, a multifrequency microwave radiometer with azimuth and elevation pointing, and a NEXRAD radar. The new terminal area icing remote sensing system processes the data streams from these instruments to derive temperature, liquid water content, and cloud droplet size for each examined point in space. These data are then combined to ultimately provide icing hazard classification along defined approach paths into an airport.

  14. Retrieval of Remote Sensing Images Using Colour and Texture Attribute

    CERN Document Server

    Maheswary, Priti

    2009-01-01

    Grouping images into semantically meaningful categories using low-level visual feature is a challenging and important problem in content-based image retrieval. The groupings can be used to build effective indices for an image database. Digital image analysis techniques are being used widely in remote sensing assuming that each terrain surface category is characterized with spectral signature observed by remote sensors. Even with the remote sensing images of IRS data, integration of spatial information is expected to assist and to improve the image analysis of remote sensing data. In this paper we present a satellite image retrieval based on a mixture of old fashioned ideas and state of the art learning tools. We have developed a methodology to classify remote sensing images using HSV color features and Haar wavelet texture features and then grouping them on the basis of particular threshold value. The experimental results indicate that the use of color and texture feature extraction is very useful for image r...

  15. Computational Ghost Imaging for Remote Sensing

    Science.gov (United States)

    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

  16. Remote Sensing of Ionosphere by IONOLAB Group

    Science.gov (United States)

    Arikan, Feza

    2016-07-01

    Ionosphere is a temporally and spatially varying, dispersive, anisotropic and inhomogeneous medium that is characterized primarily by its electron density distribution. Electron density is a complex function of spatial and temporal variations of solar, geomagnetic, and seismic activities. Ionosphere is the main source of error for navigation and positioning systems and satellite communication. Therefore, characterization and constant monitoring of variability of the ionosphere is of utmost importance for the performance improvement of these systems. Since ionospheric electron density is not a directly measurable quantity, an important derivable parameter is the Total Electron Content (TEC), which is used widely to characterize the ionosphere. TEC is proportional to the total number of electrons on a line crossing the atmosphere. IONOLAB is a research group is formed by Hacettepe University, Bilkent University and Kastamonu University, Turkey gathered to handle the challenges of the ionosphere using state-of-the-art remote sensing and signal processing techniques. IONOLAB group provides unique space weather services of IONOLAB-TEC, International Reference Ionosphere extended to Plasmasphere (IRI-Plas) model based IRI-Plas-MAP, IRI-Plas-STEC and Online IRI-Plas-2015 model at www.ionolab.org. IONOLAB group has been working for imaging and monitoring of ionospheric structure for the last 15 years. TEC is estimated from dual frequency GPS receivers as IONOLAB-TEC using IONOLAB-BIAS. For high spatio-temporal resolution 2-D imaging or mapping, IONOLAB-MAP algorithm is developed that uses automated Universal Kriging or Ordinary Kriging in which the experimental semivariogram is fitted to Matern Function with Particle Swarm Optimization (PSO). For 3-D imaging of ionosphere and 1-D vertical profiles of electron density, state-of-the-art IRI-Plas model based IONOLAB-CIT algorithm is developed for regional reconstruction that employs Kalman Filters for state

  17. An operational satellite remote sensing system for ocean fishery

    Institute of Scientific and Technical Information of China (English)

    MAOZhihua; ZHUQiankun; PANDelu

    2004-01-01

    Ocean environmental information is very important to supporting the fishermen in fishing and satellite remote sensing technology can provide it in large scale and in near real-time. Ocean fishery locations are always far away beyond the coverage of the satellite data received by a land-based satellite receiving station. A nice idea is to install the satellite ground station on a fishing boat. When the boat moves to a fishery location, the station can receive the satellite data to cover the fishery areas. One satellite remote sensing system was once installed in a fishing boat and served fishing in the North Pacific fishery areas when the boat stayed there. The system can provide some oceanic environmental charts such as sea surface temperature (SST) and relevant derived products which are in most popular use in fishery industry. The accuracy of SST is the most important and affects the performance of the operational system, which is found to be dissatisfactory. Many factors affect the accuracy of SST and it is difficult to increase the accuracy by SST retrieval algorithms and clouds detection technology. A new technology of temperature error control is developed to detect the abnormity of satellite-measured SST. The performance of the technology is evaluated to change the temperature bias from-3.04 to 0.05 ℃ and the root mean square (RMS) from 5.71 to 1.75 ℃. It is suitable for employing in an operational satellite-measured SST system and improves the performance of the system in fishery applications. The system has been running for 3 a and proved to be very useful in fishing. It can help to locate the candidates of the fishery areas and monitor the typhoon which is very dangerous to the safety of fishing boats.

  18. NASA Remote Sensing Research as Applied to Archaeology

    Science.gov (United States)

    Giardino, Marco J.; Thomas, Michael R.

    2002-01-01

    The use of remotely sensed images is not new to archaeology. Ever since balloons and airplanes first flew cameras over archaeological sites, researchers have taken advantage of the elevated observation platforms to understand sites better. When viewed from above, crop marks, soil anomalies and buried features revealed new information that was not readily visible from ground level. Since 1974 and initially under the leadership of Dr. Tom Sever, NASA's Stennis Space Center, located on the Mississippi Gulf Coast, pioneered and expanded the application of remote sensing to archaeological topics, including cultural resource management. Building on remote sensing activities initiated by the National Park Service, archaeologists increasingly used this technology to study the past in greater depth. By the early 1980s, there were sufficient accomplishments in the application of remote sensing to anthropology and archaeology that a chapter on the subject was included in fundamental remote sensing references. Remote sensing technology and image analysis are currently undergoing a profound shift in emphasis from broad classification to detection, identification and condition of specific materials, both organic and inorganic. In the last few years, remote sensing platforms have grown increasingly capable and sophisticated. Sensors currently in use, or nearing deployment, offer significantly finer spatial and spectral resolutions than were previously available. Paired with new techniques of image analysis, this technology may make the direct detection of archaeological sites a realistic goal.

  19. APPLICATION OF REMOTE SENSING TECHNOLOGY TO POPULATION ESTIMATION

    Institute of Scientific and Technical Information of China (English)

    ZHANG Bao-guang

    2003-01-01

    This paper attempts to explore a new avenue of urban small-regional population estimation by remote sensing technology, creatively and comprehensively for the first time using a residence count method, area (density) method and model method, incorporating the application experience of American scholars in the light of the state of our country. Firstly, the author proposes theoretical basis for population estimation by remote sensing, on the basis of analysing and evaluating the history and state quo of application of methods of population estimation by remote sens-ing. Secondly, two original types of mathematical models of population estimation are developed on the basis of remote sensing data, taking Tianjin City as an example. By both of the mathematical models the regional population may be estimated from remote sensing variable values with high accuracy. The number of the independent variables in the lat-ter model is somewhat smaller and the collection of remote sensing data is somewhat easier, but the deviation is a little larger. Finally, some viewpoints on the principled problems about the practical application of remote sensing to popu-lation estimation are put forward.

  20. Environmental monitoring: civilian applications of remote sensing

    Energy Technology Data Exchange (ETDEWEB)

    Bolton, W.; Lapp, M.; Vitko, J. Jr. [Sandia National Labs., Livermore, CA (United States); Phipps, G. [Sandia National Labs., Albuquerque, NM (United States)

    1996-11-01

    This report documents the results of a Laboratory Directed Research and Development (LDRD) program to explore how best to utilize Sandia`s defense-related sensing expertise to meet the Department of Energy`s (DOE) ever-growing needs for environmental monitoring. In particular, we focused on two pressing DOE environmental needs: (1) reducing the uncertainties in global warming predictions, and (2) characterizing atmospheric effluents from a variety of sources. During the course of the study we formulated a concept for using unmanned aerospace vehicles (UAVs) for making key 0798 climate measurements; designed a highly accurate, compact, cloud radiometer to be flown on those UAVs; and established the feasibility of differential absorption Lidar (DIAL) to measure atmospheric effluents from waste sites, manufacturing processes, and potential treaty violations. These concepts have had major impact since first being formulated in this ,study. The DOE has adopted, and DoD`s Strategic Environmental Research Program has funded, much of the UAV work. And the ultraviolet DIAL techniques have already fed into a major DOE non- proliferation program.

  1. Optical Properties of Volcanic Ash: Improving Remote Sensing Observations

    Science.gov (United States)

    Whelley, P.; Colarco, P. R.; Aquila, V.; Krotkov, N. A.; Bleacher, J. E.; Garry, W. B.; Young, K. E.; Lima, A. R.; Martins, J. V.; Carn, S. A.

    2015-12-01

    Many times each year explosive volcanic eruptions loft ash into the atmosphere. Global travel and trade rely on aircraft vulnerable to encounters with airborne ash. Volcanic ash advisory centers (VAACs) rely on dispersion forecasts and satellite data to issue timely warnings. To improve ash forecasts model developers and satellite data providers need realistic information about volcanic ash microphysical and optical properties. In anticipation of future large eruptions we can study smaller events to improve our remote sensing and modeling skills so when the next Pinatubo 1991 or larger eruption occurs, ash can confidently be tracked in a quantitative way. At distances >100km from their sources, drifting ash plumes, often above meteorological clouds, are not easily detected from conventional remote sensing platforms, save deriving their quantitative characteristics, such as mass density. Quantitative interpretation of these observations depends on a priori knowledge of the spectral optical properties of the ash in UV (>0.3μm) and TIR wavelengths (>10μm). Incorrect assumptions about the optical properties result in large errors in inferred column mass loading and size distribution, which misguide operational ash forecasts. Similarly, simulating ash properties in global climate models also requires some knowledge of optical properties to improve aerosol speciation. Recent research has identified a wide range in volcanic ash optical properties among samples collected from the ground after different eruptions. The database of samples investigated remains relatively small, and measurements of optical properties at the relevant particle sizes and spectral channels are far from complete. Generalizing optical properties remains elusive, as does establishing relationships between ash composition and optical properties, which are essential for satellite retrievals. We are building a library of volcanic ash optical and microphysical properties. In this presentation we show

  2. Educational activities of remote sensing archaeology (Conference Presentation)

    Science.gov (United States)

    Hadjimitsis, Diofantos G.; Agapiou, Athos; Lysandrou, Vasilki; Themistocleous, Kyriacos; Cuca, Branka; Nisantzi, Argyro; Lasaponara, Rosa; Masini, Nicola; Krauss, Thomas; Cerra, Daniele; Gessner, Ursula; Schreier, Gunter

    2016-10-01

    Remote sensing science is increasingly being used to support archaeological and cultural heritage research in various ways. Satellite sensors either passive or active are currently used in a systematic basis to detect buried archaeological remains and to systematic monitor tangible heritage. In addition, airborne and low altitude systems are being used for documentation purposes. Ground surveys using remote sensing tools such as spectroradiometers and ground penetrating radars can detect variations of vegetation and soil respectively, which are linked to the presence of underground archaeological features. Education activities and training of remote sensing archaeology to young people is characterized of highly importance. Specific remote sensing tools relevant for archaeological research can be developed including web tools, small libraries, interactive learning games etc. These tools can be then combined and aligned with archaeology and cultural heritage. This can be achieved by presenting historical and pre-historical records, excavated sites or even artifacts under a "remote sensing" approach. Using such non-form educational approach, the students can be involved, ask, read, and seek to learn more about remote sensing and of course to learn about history. The paper aims to present a modern didactical concept and some examples of practical implementation of remote sensing archaeology in secondary schools in Cyprus. The idea was built upon an ongoing project (ATHENA) focused on the sue of remote sensing for archaeological research in Cyprus. Through H2020 ATHENA project, the Remote Sensing Science and Geo-Environment Research Laboratory at the Cyprus University of Technology (CUT), with the support of the National Research Council of Italy (CNR) and the German Aerospace Centre (DLR) aims to enhance its performance in all these new technologies.

  3. Applications of geographic information systems and remote sensing techniques to conservation of amphibians in northwestern Ecuador

    OpenAIRE

    Mariela Palacios González; Elisa Bonaccorso; Monica Papeş

    2015-01-01

    The biodiversity of the Andean Chocó in western Ecuador and Colombia is threatened by anthropogenic changes in land cover. The main goal of this study was to contribute to conservation of 12 threatened species of amphibians at a cloud forest site in northwestern Ecuador, by identifying and proposing protection of critical areas. We used Geographic Information Systems (GIS) and remote sensing techniques to quantify land cover changes over 35 years and outline important areas for amphibian cons...

  4. Quantitative interpretation of Great Lakes remote sensing data

    Science.gov (United States)

    Shook, D. F.; Salzman, J.; Svehla, R. A.; Gedney, R. T.

    1980-01-01

    The paper discusses the quantitative interpretation of Great Lakes remote sensing water quality data. Remote sensing using color information must take into account (1) the existence of many different organic and inorganic species throughout the Great Lakes, (2) the occurrence of a mixture of species in most locations, and (3) spatial variations in types and concentration of species. The radiative transfer model provides a potential method for an orderly analysis of remote sensing data and a physical basis for developing quantitative algorithms. Predictions and field measurements of volume reflectances are presented which show the advantage of using a radiative transfer model. Spectral absorptance and backscattering coefficients for two inorganic sediments are reported.

  5. Remote sensing of rainfall for debris-flow hazard assessment

    Science.gov (United States)

    Wieczorek, G.F.; Coe, J.A.; Godt, J.W.; ,

    2003-01-01

    Recent advances in remote sensing of rainfall provide more detailed temporal and spatial data on rainfall distribution. Four case studies of abundant debris flows over relatively small areas triggered during intense rainstorms are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. Three examples with rainfall estimates from National Weather Service Doppler radar and one example with rainfall estimates from infrared imagery from a National Oceanic and Atmospheric Administration satellite are compared with ground-based measurements of rainfall and with landslide distribution. The advantages and limitations of using remote sensing of rainfall for landslide hazard analysis are discussed. ?? 2003 Millpress,.

  6. A catalog system for remote-sensing data

    Science.gov (United States)

    Singh, R. S.; Scherz, J. P.

    1974-01-01

    The Practical System for Cataloging, Indexing, and Retrieval of Remote Sensing Data developed by the Interdisciplinary Remote Sensing Group at the University of Wisconsin consists of a card catalog, a site-index-map, a site-index-file, an industry-index-file, and a project-index-file. The system is designed for retrieval of remote-sensing data which include imagery, magnetic tapes, flight logs, maps, ground-truth reports, and research reports containing raw data. It can be operated by conventional library methods, but provision has been made for digitizing the system for computer retrieval.

  7. Geostatistical Solutions for Downscaling Remotely Sensed Land Surface Temperature

    Science.gov (United States)

    Wang, Q.; Rodriguez-Galiano, V.; Atkinson, P. M.

    2017-09-01

    Remotely sensed land surface temperature (LST) downscaling is an important issue in remote sensing. Geostatistical methods have shown their applicability in downscaling multi/hyperspectral images. In this paper, four geostatistical solutions, including regression kriging (RK), downscaling cokriging (DSCK), kriging with external drift (KED) and area-to-point regression kriging (ATPRK), are applied for downscaling remotely sensed LST. Their differences are analyzed theoretically and the performances are compared experimentally using a Landsat 7 ETM+ dataset. They are also compared to the classical TsHARP method.

  8. Remote sensing models and methods for image processing

    CERN Document Server

    Schowengerdt, Robert A

    1997-01-01

    This book is a completely updated, greatly expanded version of the previously successful volume by the author. The Second Edition includes new results and data, and discusses a unified framework and rationale for designing and evaluating image processing algorithms.Written from the viewpoint that image processing supports remote sensing science, this book describes physical models for remote sensing phenomenology and sensors and how they contribute to models for remote-sensing data. The text then presents image processing techniques and interprets them in terms of these models. Spectral, s

  9. Anomaly Detection from Hyperspectral Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Qiandong Guo

    2016-12-01

    Full Text Available Hyperspectral remote sensing imagery contains much more information in the spectral domain than does multispectral imagery. The consecutive and abundant spectral signals provide a great potential for classification and anomaly detection. In this study, two real hyperspectral data sets were used for anomaly detection. One data set was an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS data covering the post-attack World Trade Center (WTC and anomalies are fire spots. The other data set called SpecTIR contained fabric panels as anomalies compared to their background. Existing anomaly detection algorithms including the Reed–Xiaoli detector (RXD, the blocked adaptive computation efficient outlier nominator (BACON, the random selection based anomaly detector (RSAD, the weighted-RXD (W-RXD, and the probabilistic anomaly detector (PAD are reviewed here. The RXD generally sets strict assumptions to the background, which cannot be met in many scenarios, while BACON, RSAD, and W-RXD employ strategies to optimize the estimation of background information. The PAD firstly estimates both background information and anomaly information and then uses the information to conduct anomaly detection. Here, the BACON, RSAD, W-RXD, and PAD outperformed the RXD in terms of detection accuracy, and W-RXD and PAD required less time than BACON and RSAD.

  10. Visibility assesment using remote sensing data

    Science.gov (United States)

    Toanca, Florica; Vasilescu, Jeni; Nicolae, Doina; Stefan, Sabina

    2016-04-01

    Severe weather events like fog have a high impact on all kinds of traffic operations. During the last decade was proven the capability of remote sensing equipments to detect fog cases in terms of duration, occurrence and dissipation. Therefore, in this study the data from Väïsälä CL31 ceilometer and Raman Depolarization Lidar installed at Magurele, Romania (44.35 N, 26.03 E) were used. The backscatter coefficient from Ceilometer and extinction coefficient and different lidar ratios (LR) values from Lidar were used in order to determine horizontal visibility during the fog events in Magurele area. Ceilometer backscatter coefficient profiles are obtained with a time resolution of 16 s and up to 7.5 km altitude. . A neural network algorithm was used to calculate the lidar ratio values for different aerosol types and also for different relative humidity. Thus, for continental aerosol the LR value is 58srad, for continental polluted is 60srad and for smoke LR is 55srad. The average visibility computed for radiation fog , dominant type (57 cases) occurring in Magurele, during 2012-2014 was 50m. An important result is that the dependence of horizontal visibility for radiation fog at Magurele on LR is insignificant. This means that radiation, meteorological and geographical factors influence fog generation more much than aerosol type.

  11. Assessment of Watershed Drought Using Remote Sensing

    Science.gov (United States)

    Chataut, S.; Piechota, T.

    2005-12-01

    This paper focuses on drought assessment of the Upper Colorado River Basin (UCRB) using remote sensing. Lee's Ferry discharge data for Colorado river in the UCRB and the various Palmer Drought Indices (PDI) such as Palmer Hydrological Drought Indices (PHDI), Palmer Drought Severity Index (PDSI), and Palmer Z Index (ZINDX) for the five climatic divisions of the UCRB for last 100 years will be analyzed to find out the best climatic division in the UCRB for carrying out the further analysis between the Normalized Difference Vegetation Index (NDVI) obtained from 5 km resolution Advanced Very High Radiometric Radar (AVHRR) data and the various PDI. The multivariate statistical technique called rotated principal component analysis will be carried out in the time series of the NDVI data in order to avoid multicollinearity and to extract the component that significantly explains the variance in the dataset. The corresponding significant principal scores will be correlated with the PDI to derive relationship between the NDVI and PDI. Preliminary analysis has shown that there is significant correlation between the NDVI and the various PDI, which implies that NDVI could be used as an important data source to detect and monitor the drought condition in the UCRB.

  12. Remote sensing applied to forest resources

    Science.gov (United States)

    Hernandezfilho, P. (Principal Investigator)

    1984-01-01

    The development of methodologies to classify reforested areas using remotely sensed data is discussed. A preliminary study was carried out in northeast of the Sao Paulo State in 1978. The reforested areas of Pinus spp and Eucalyptus spp were based on the spectral, spatial and temporal characteristics fo LANDSAT imagery. Afterwards, a more detailed study was carried out in the Mato Grosso do Sul State. The reforested areas were mapped in functions of the age (from: 0 to 1 year, 1 to 2 years, 2 to 3 years, 3 to 4 years, 4 to 5 years and 5 to 6 years) and of the heterogeneity stand (from: 0 to 20%, 20 to 40%, 40 to 60%, 60 to 80% and 80 to 100%). The relative differences between the artificial forest areas, estimated from LANDSAT data and ground information, varied from -8.72 to +9.49%. The estimation of forest volume through a multistage sampling technique, with probability proportional to size, is also discussed.

  13. Digital methods and remote sensing in archaeology archaeology in the age of sensing

    CERN Document Server

    Campana, Stefano

    2016-01-01

    This volume debuts the new scope of Remote Sensing, which was first defined as the analysis of data collected by sensors that were not in physical contact with the objects under investigation (using cameras, scanners, and radar systems operating from spaceborne or airborne platforms). A wider characterization is now possible: Remote Sensing can be any non-destructive approach to viewing the buried and nominally invisible evidence of past activity. Spaceborne and airborne sensors, now supplemented by laser scanning, are united using ground-based geophysical instruments and undersea remote sensing, as well as other non-invasive techniques such as surface collection or field-walking survey. Now, any method that enables observation of evidence on or beneath the surface of the earth, without impact on the surviving stratigraphy, is legitimately within the realm of Remote Sensing. The new interfaces and senses engaged in Remote Sensing appear throughout the book. On a philosophical level, this is about the landscap...

  14. Remote sensing of severe convective storms over Qinghai-Xizang Plateau

    Science.gov (United States)

    Hung, R. J.; Liu, J. M.; Tsao, D. Y.; Smith, R. E.

    1984-01-01

    The American satellite, GOES-1 was moved to the Indian Ocean at 58 deg E during the First GARP Global Experiment (FGGE). The Qinghai-Xizang Plateau significantly affects the initiation and development of heavy rainfall and severe storms in China, just as the Rocky Mountains influence the local storms in the United States. Satelite remote sensing of short-lived, meso-scale convective storms is particularly important for covering a huge area of a high elevation with a low population density, such as the Qinghai-Xizang Plateau. Results of this study show that a high growth rate of the convective clouds, followed by a rapid collapse of the cloud top, is associated with heavy rainfall in the area. The tops of the convective clouds developed over the Plateau lie between the altitudes of the two tropopauses, while the tops of convective clouds associated with severe storms in the United States usually extend much above the tropopause.

  15. Remote measurement of cloud microphysics and its influence in predicting high impact weather events

    Science.gov (United States)

    Bipasha, Paul S.; Jinya, John

    2016-05-01

    Understanding the cloud microphysical processes and precise retrieval of parameters governing the same are crucial for weather and climate prediction. Advanced remote sensing sensors and techniques offer an opportunity for monitoring micro-level developments in cloud structure. . Using the observations from a visible and near-infrared lidar onboard CALIPSO satellite (part of A-train) , the spatial variation of cloud structure has been studied over the Tropical monsoon region . It is found that there is large variability in the cloud microphysical parameters manifesting in distinct precipitation regimes. In particular, the severe storms over this region are driven by processes which range from the synoptic to the microphysical scale. Using INSAT-3D data, retrieval of cloud microphysical parameters like effective radius (CER) and optical depth (COD) were carried out for tropical cyclone Phailine. It was observed that there is a general increase of CER in a top-down direction, characterizing the progressively increasing number and size of precipitation hydrometeors while approaching the cloud base. The distribution of CER relative to cloud top temperature for growing convective clouds has been investigated to reveal the evolution of the particles composing the clouds. It is seen that the relatively high concentration of large particles in the downdraft zone is closely related to the precipitation efficiency of the system. Similar study was also carried using MODIS observations for cyclones over Indian Ocean (2010-2013), in which we find that that the mean effective radius is 24 microns with standard deviation 4.56, mean optical depth is 21 with standard deviation 13.98, mean cloud fraction is 0.92 with standard deviation 0.13 and mainly ice phase is dominant. Thus the remote observations of microstructure of convective storms provide very crucial information about the maintenance and potential devastation likely to be associated with it. With the synergistic

  16. Intelligent Observation Strategies for Geosynchronous Remote Sensing for Natural Hazards

    Science.gov (United States)

    Moe, K.; Cappelaere, P. G.; Frye, S. W.; LeMoigne, J.; Mandl, D.; Flatley, T.; Geist, A.

    2015-12-01

    Geosynchronous satellites offer a unique perspective for monitoring environmental factors important to understanding natural hazards and supporting the disasters management life cycle, namely forecast, detection, response, recovery and mitigation. In the NASA decadal survey for Earth science, the GEO-CAPE mission was proposed to address coastal and air pollution events in geosynchronous orbit, complementing similar initiatives in Asia by the South Koreans and by ESA in Europe, thereby covering the northern hemisphere. In addition to analyzing the challenges of identifying instrument capabilities to meet the science requirements, and the implications of hosting the instrument payloads on commercial geosynchronous satellites, the GEO-CAPE mission design team conducted a short study to explore strategies to optimize the science return for the coastal imaging instrument. The study focused on intelligent scheduling strategies that took into account cloud avoidance techniques as well as onboard processing methods to reduce the data storage and transmission loads. This paper expands the findings of that study to address the use of intelligent scheduling techniques and near-real time data product acquisition of both the coastal water and air pollution events. The topics include the use of onboard processing to refine and execute schedules, to detect cloud contamination in observations, and to reduce data handling operations. Analysis of state of the art flight computing capabilities will be presented, along with an assessment of cloud detection algorithms and their performance characteristics. Tools developed to illustrate operational concepts will be described, including their applicability to environmental monitoring domains with an eye to the future. In the geostationary configuration, the payload becomes a networked "thing" with enough connectivity to exchange data seamlessly with users. This allows the full field of view to be sensed at very high rate under the

  17. Intelligent Observation Strategies for Geosynchronous Remote Sensing for Natural Hazards

    Science.gov (United States)

    Moe, Karen; Cappleare, Patrice; Frye, Stuart; LeMoigne, Jacqueline; Mandl, Daniel; Flatley, Thomas; Geist, Alessandro

    2015-01-01

    Geosynchronous satellites offer a unique perspective for monitoring environmental factors important to understanding natural hazards and supporting the disasters management life cycle, namely forecast, detection, response, recovery and mitigation. In the NASA decadal survey for Earth science, the GEO-CAPE mission was proposed to address coastal and air pollution events in geosynchronous orbit, complementing similar initiatives in Asia by the South Koreans and by ESA in Europe, thereby covering the northern hemisphere. In addition to analyzing the challenges of identifying instrument capabilities to meet the science requirements, and the implications of hosting the instrument payloads on commercial geosynchronous satellites, the GEO-CAPE mission design team conducted a short study to explore strategies to optimize the science return for the coastal imaging instrument. The study focused on intelligent scheduling strategies that took into account cloud avoidance techniques as well as onboard processing methods to reduce the data storage and transmission loads. This paper expands the findings of that study to address the use of intelligent scheduling techniques and near-real time data product acquisition of both the coastal water and air pollution events. The topics include the use of onboard processing to refine and execute schedules, to detect cloud contamination in observations, and to reduce data handling operations. Analysis of state of the art flight computing capabilities will be presented, along with an assessment of cloud detection algorithms and their performance characteristics. Tools developed to illustrate operational concepts will be described, including their applicability to environmental monitoring domains with an eye to the future. In the geostationary configuration, the payload becomes a networked thing with enough connectivity to exchange data seamlessly with users. This allows the full field of view to be sensed at very high rate under the control

  18. Gully Erosion Mapping Using Remote Sensing Techniques in the ...

    African Journals Online (AJOL)

    NdifelaniM

    Gully Features Extraction Using Remote Sensing Techniques. Ndifelani .... catchment area and NDVI as threshold and the accuracy indicated a negligible over estimation. In SA, the use of ..... data and software used in this research. We also ...

  19. The U.S. Geological Survey Land Remote Sensing Program

    Science.gov (United States)

    ,

    2007-01-01

    The fundamental goals of the U.S. Geological Survey's Land Remote Sens-ing (LRS) Program are to provide the Federal Government and the public with a primary source of remotely sensed data and applications and to be a leader in defining the future of land remote sensing, nationally and internationally. Remotely sensed data provide information that enhance the understand-ing of ecosystems and the capabilities for predicting ecosystem change. The data promote an understanding of the role of the environment and wildlife in human health issues, the requirements for disaster response, the effects of climate variability, and the availability of energy and mineral resources. Also, as land satellite systems acquire global coverage, the program coordinates a network of international receiving stations and users of the data. It is the responsibility of the program to assure that data from land imaging satellites, airborne photography, radar, and other technologies are available to the national and global science communities.

  20. A Web-Based Airborne Remote Sensing Telemetry Server Project

    Data.gov (United States)

    National Aeronautics and Space Administration — A Web-based Airborne Remote Sensing Telemetry Server (WARSTS) is proposed to integrate UAV telemetry and web-technology into an innovative communication, command,...

  1. Remote sensing in forestry: Application to the Amazon region

    Science.gov (United States)

    Dejesusparada, N. (Principal Investigator); Tardin, A. T.; Dossantos, A.; Filho, P. H.; Shimabukuro, Y. E.

    1981-01-01

    The utilization of satellite remote sensing in forestry is reviewed with emphasis on studies performed for the Brazilian Amazon Region. Timber identification, deforestation, and pasture degradation after deforestation are discussed.

  2. Models for estimation of land remote sensing satellites operational efficiency

    Science.gov (United States)

    Kurenkov, Vladimir I.; Kucherov, Alexander S.

    2017-01-01

    The paper deals with the problem of estimation of land remote sensing satellites operational efficiency. Appropriate mathematical models have been developed. Some results obtained with the help of the software worked out in Delphi programming support environment are presented.

  3. REMOTE SENSING APPLICATIONS FOR SUSTAINABLE WATERSHED MANAGEMENT AND FOOD SECURITY

    Science.gov (United States)

    The integration of IKONOS satellite data, airborne color infrared remote sensing, visualization, and decision support tools is discussed, within the contexts of management techniques for minimizing non-point source pollution in inland waterways, such s riparian buffer restoration...

  4. Remote sensing and geochemistry techniques for the assessment of ...

    African Journals Online (AJOL)

    Chiedza

    in winter because of thermal inversion. High levels of ... land characterised by vents which as conduit for oxygen and spontaneous combustion ... remote sensing data to map heavy metal enrichment and accumulation near the Emalahleni.

  5. Lidar Remote Sensing for Forest Canopy Studies 2014

    Science.gov (United States)

    Remote sensing has facilitated extraordinary advances in modeling, mapping, and the understanding of ecosystems. Conventional sensors have significant limitations for ecological and forest applications. The sensitivity and accuracy of these devices have repeatedly been shown to fall with increasing ...

  6. REMOTE SENSING APPLICATIONS FOR SUSTAINABLE WATERSHED MANAGEMENT AND FOOD SECURITY

    Science.gov (United States)

    The integration of IKONOS satellite data, airborne color infrared remote sensing, visualization, and decision support tools is discussed, within the contexts of management techniques for minimizing non-point source pollution in inland waterways, such s riparian buffer restoration...

  7. Remote sensing application for delineating coastal vegetation - A case study

    Digital Repository Service at National Institute of Oceanography (India)

    Kunte, P.D.; Wagle, B.G.

    Remote sensing data has been used for mapping coastal vegetation along the Goa Coast, India. The study envisages the use of digital image processing techniques for delineating geomorphic features and associated vegetation, including mangrove, along...

  8. Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications

    Science.gov (United States)

    Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yingcui; Hill, Richard; Guang, Jie; Li, Chi

    2017-01-01

    Workflow for remote sensing quantitative retrieval is the ;bridge; between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation.

  9. Remote Sensing Information Sciences Research Group, year four

    Science.gov (United States)

    Estes, John E.; Smith, Terence; Star, Jeffrey L.

    1987-01-01

    The needs of the remote sensing research and application community which will be served by the Earth Observing System (EOS) and space station, including associated polar and co-orbiting platforms are examined. Research conducted was used to extend and expand existing remote sensing research activities in the areas of georeferenced information systems, machine assisted information extraction from image data, artificial intelligence, and vegetation analysis and modeling. Projects are discussed in detail.

  10. Using remotely-sensed data for optimal field sampling

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2008-09-01

    Full Text Available to carry out a fieldwork sample is an important issue as it avoids subjective judgement and can save on time and costs in the field. STATISTICAL SAMPLING, USING DATA OBTAINED FROM REMOTE SENSING, FINDS APPLICATION IN A VARIETY OF FIELDS... M B E R 2 0 0 8 15 USING REMOTELY- SENSED DATA FOR OPTIMAL FIELD SAMPLING BY DR PRAVESH DEBBA STATISTICS IS THE SCIENCE pertaining to the collection, summary, analysis, interpretation and presentation of data. It is often impractical...

  11. Laser And Nonlinear Optical Materials For Laser Remote Sensing

    Science.gov (United States)

    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.

  12. Validating firn compaction model with remote sensing data

    OpenAIRE

    2011-01-01

    A comprehensive understanding of firn processes is of outmost importance, when estimating present and future changes of the Greenland Ice Sheet. Especially, when remote sensing altimetry is used to assess the state of ice sheets and their contribution to global sea level rise, firn compaction models have been shown to be a key component. Now, remote sensing data can also be used to validate the firn models. Radar penetrating the upper part of the firn column in the interior part of Greenland ...

  13. Remote sensing solutions for when spectrometers no longer are affordable

    Science.gov (United States)

    van Brug, Hedser; Visser, Huib

    2016-10-01

    This paper describes one of the issues that are facing the remote sensing community in the not so far future; scientists ask for certain requirement that cannot be fulfilled either due to cost issues or technological issues. The paper starts with giving a short and quick historical overview of the development of spectrometer based remote sensing systems. Next, the likely end of the spectrometers will be explained, followed by a possible alternative.

  14. Remote Sensing and the Kyoto Protocol: A Workshop Summary

    Science.gov (United States)

    Rosenqvist, Ake; Imhoff, Marc; Milne, Anthony; Dobson, Craig

    2000-01-01

    The Kyoto Protocol to the United Nations Framework Convention on Climate Change contains quantified, legally binding commitments to limit or reduce greenhouse gas emissions to 1990 levels and allows carbon emissions to be balanced by carbon sinks represented by vegetation. The issue of using vegetation cover as an emission offset raises a debate about the adequacy of current remote sensing systems and data archives to both assess carbon stocks/sinks at 1990 levels, and monitor the current and future global status of those stocks. These concerns and the potential ratification of the Protocol among participating countries is stimulating policy debates and underscoring a need for the exchange of information between the international legal community and the remote sensing community. On October 20-22 1999, two working groups of the International Society for Photogrammetry and Remote Sensing (ISPRS) joined with the University of Michigan (Michigan, USA) to convene discussions on how remote sensing technology could contribute to the information requirements raised by implementation of, and compliance with, the Kyoto Protocol. The meeting originated as a joint effort between the Global Monitoring Working Group and the Radar Applications Working Group in Commission VII of the ISPRS, co-sponsored by the University of Michigan. Tile meeting was attended by representatives from national government agencies and international organizations and academic institutions. Some of the key themes addressed were: (1) legal aspects of transnational remote sensing in the context of the Kyoto Protocol; (2) a review of the current and future and remote sensing technologies that could be applied to the Kyoto Protocol; (3) identification of areas where additional research is needed in order to advance and align remote sensing technology with the requirements and expectations of the Protocol; and 94) the bureaucratic and research management approaches needed to align the remote sensing

  15. Can remote sensing help citizen-science based phenological studies?

    Science.gov (United States)

    Delbart, Nicolas; Elisabeth, Beaubien; Laurent, Kergoat; Thuy, Le Toan

    2017-04-01

    Citizen science networks and remote sensing are both efficient to collect massive data related to phenology. However both differ in their advantages and drawbacks for this purpose. Contrarily to remote sensing, citizen science allows distinguishing species-specific phenological responses to climate variability. On the other hand, large portions of territory of a country like Canada are not covered by citizen science networks, and the time series are often incomplete. The main mode of interaction between both types of data consists in validating the maps showing the ecosystem foliage transition times, such as the green-up date, obtained from remote sensing data with field observations, and in particular those collected by citizen scientists. Thus the citizen science phenology data bring confidence to remote sensing based studies. However, one can merely find studies in which remote sensing is used to improve in any way citizen science based study. Here we present bi-directional interactions between both types of data. We first use phenological data from the PlantWatch citizen science network to show that one remote sensing method green-up date relates to the leaf-out date of woody species but also to the whole plant community phenology at the regional level, including flowering phenology. Second we use a remote sensing time series to constrain the analysis of citizen data to overcome the main drawbacks that is the incompleteness of time series. In particular we analyze the interspecies differences in phenology at the scale of so-called "pheno-regions" delineated using remote sensing green-up maps.

  16. Remote sensing and vegetation stress detection - Problems and progress

    Science.gov (United States)

    Duggin, M. J.; Whitehead, V.

    1983-01-01

    Although considerable progress has been made in applying remote sensing technology to vegetation monitoring, considerable problems still exist in the improvement of techniques for crop type discrimination, stress detection on a large scale, and stress quantification. In this paper, some of the problems remaining in the operational use of remote sensing technology for vegetation stress detection are discussed, and directions in which some of these problems might be solved are proposed.

  17. Remote sensing for quantification of agronomic properties

    Science.gov (United States)

    Sullivan, Dana Grace

    Remote sensing (RS) may be used to rapidly assess surface features and facilitate natural resource management, precision agriculture and soil survey. Information obtained in such a way would streamline data collection and improve diagnostic capabilities. Current RS technology has had limited testing, particularly within the Southeast. Our study was designed to evaluate RS as a rapid assessment tool in three different natural resource applications: nitrogen (N) management in a corn crop (Zea mays L.), assessment of in situ crop residue cover, and quantification of near-surface soil properties. In 2000, study sites were established in four physiographic provinces of Alabama: Tennessee Valley, Ridge and Valley, Appalachian Plateau, and Coastal Plain. Spectral measurements were acquired via spectroradiometer (350--1050 nm), airborne ATLAS multispectral scanner (400--12,500 nm), and IKONOS satellite (450--900 nm). Corn plots were established from fresh-tilled ground in a completely randomized design at the Appalachian Plateau and Coastal Plain study sites in 2000. Plots received four N rates (0, 56, 112, and 168 kg N ha-1 ), and were maintained for three consecutive growing seasons. Spectroradiometer data were acquired biweekly from V6-R2 and ATLAS and IKONOS were acquired per availability. Results showed vegetation indices derived from hand-held spectroradiometer measurements as early as V6-V8 were linearly related to yield and tissue N. ATLAS imagery showed promise at the AP site during the V6 stage (r2 = 0.66), but no significant relationships between plant N and IKONOS imagery were observed. Residue plots (15m x 15m) were established at the Appalachian Plateau and Coastal Plain in 2000 and 200. Residue treatments consisted of hand applied wheat straw cover (0, 10 20, 50, or 80%) arranged in a completely randomized design. Spectroradiometer data were acquired monthly and ATLAS and IKONOS were acquired per availability. Residue cover estimates were best with ATLAS

  18. NASA Remote Sensing Data for Epidemiological Studies

    Science.gov (United States)

    Maynard, Nancy G.; Vicente, G. A.

    2002-01-01

    In response to the need for improved observations of environmental factors to better understand the links between human health and the environment, NASA has established a new program to significantly improve the utilization of NASA's diverse array of data, information, and observations of the Earth for health applications. This initiative, lead by Goddard Space Flight Center (GSFC) has the following goals: (1) To encourage interdisciplinary research on the relationships between environmental parameters (e.g., rainfall, vegetation) and health, (2) Develop practical early warning systems, (3) Create a unique system for the exchange of Earth science and health data, (4) Provide an investigator field support system for customers and partners, (5) Facilitate a system for observation, identification, and surveillance of parameters relevant to environment and health issues. The NASA Environment and Health Program is conducting several interdisciplinary projects to examine applications of remote sensing data and information to a variety of health issues, including studies on malaria, Rift Valley Fever, St. Louis Encephalitis, Dengue Fever, Ebola, African Dust and health, meningitis, asthma, and filariasis. In addition, the NASA program is creating a user-friendly data system to help provide the public health community with easy and timely access to space-based environmental data for epidemiological studies. This NASA data system is being designed to bring land, atmosphere, water and ocean satellite data/products to users not familiar with satellite data/products, but who are knowledgeable in the Geographic Information Systems (GIS) environment. This paper discusses the most recent results of the interdisciplinary environment-health research projects and provides an analysis of the usefulness of the satellite data to epidemiological studies. In addition, there will be a summary of presently-available NASA Earth science data and a description of how it may be obtained.

  19. Satellite remote sensing of hailstorms in France

    Science.gov (United States)

    Melcón, Pablo; Merino, Andrés; Sánchez, José Luis; López, Laura; Hermida, Lucía

    2016-12-01

    Hailstorms are meteorological phenomena of great interest to the scientific community, owing to their socioeconomic impact, which is mainly on agricultural production. With its global coverage and high spatial and temporal resolution, satellite remote sensing can contribute to monitoring of such events through the development of appropriate techniques. This paper presents an extensive validation in the south of France of a hail detection tool (HDT) developed for the Middle Ebro Valley (MEV). The HDT is based on consecutive application of two filters, a convection mask (CM) and hail mask (HM), using spectral channels of the Meteosat Second Generation (MSG) satellite. The south of France is an ideal area for studying hailstorms, because there is a robust database of hail falls recorded by an extensive network of hailpads managed by the Association Nationale d'Etude et de Lutte contre les Fleáux Atmosphériques (ANELFA). The results show noticeably poorer performance of the HDT in France relative to that in the MEV, with probability of detection (POD) 60.4% and false alarm rate (FAR) 26.6%. For this reason, a new tool to suit the characteristics of hailstorms in France has been developed. The France Hail Detection Tool (FHDT) was developed using logistic regression from channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor of the MSG. The FHDT was validated, resulting in POD 69.3% and FAR 15.4%, thus improving hail detection in the study area as compared with the previous tool. The new tool was tested in a case study with satisfactory results, supporting its future practical application.

  20. Multiple classifier system for remote sensing image classification: a review.

    Science.gov (United States)

    Du, Peijun; Xia, Junshi; Zhang, Wei; Tan, Kun; Liu, Yi; Liu, Sicong

    2012-01-01

    Over the last two decades, multiple classifier system (MCS) or classifier ensemble has shown great potential to improve the accuracy and reliability of remote sensing image classification. Although there are lots of literatures covering the MCS approaches, there is a lack of a comprehensive literature review which presents an overall architecture of the basic principles and trends behind the design of remote sensing classifier ensemble. Therefore, in order to give a reference point for MCS approaches, this paper attempts to explicitly review the remote sensing implementations of MCS and proposes some modified approaches. The effectiveness of existing and improved algorithms are analyzed and evaluated by multi-source remotely sensed images, including high spatial resolution image (QuickBird), hyperspectral image (OMISII) and multi-spectral image (Landsat ETM+). Experimental results demonstrate that MCS can effectively improve the accuracy and stability of remote sensing image classification, and diversity measures play an active role for the combination of multiple classifiers. Furthermore, this survey provides a roadmap to guide future research, algorithm enhancement and facilitate knowledge accumulation of MCS in remote sensing community.

  1. Multiple Classifier System for Remote Sensing Image Classification: A Review

    Directory of Open Access Journals (Sweden)

    Yi Liu

    2012-04-01

    Full Text Available Over the last two decades, multiple classifier system (MCS or classifier ensemble has shown great potential to improve the accuracy and reliability of remote sensing image classification. Although there are lots of literatures covering the MCS approaches, there is a lack of a comprehensive literature review which presents an overall architecture of the basic principles and trends behind the design of remote sensing classifier ensemble. Therefore, in order to give a reference point for MCS approaches, this paper attempts to explicitly review the remote sensing implementations of MCS and proposes some modified approaches. The effectiveness of existing and improved algorithms are analyzed and evaluated by multi-source remotely sensed images, including high spatial resolution image (QuickBird, hyperspectral image (OMISII and multi-spectral image (Landsat ETM+.Experimental results demonstrate that MCS can effectively improve the accuracy and stability of remote sensing image classification, and diversity measures play an active role for the combination of multiple classifiers. Furthermore, this survey provides a roadmap to guide future research, algorithm enhancement and facilitate knowledge accumulation of MCS in remote sensing community.

  2. KW-SIFT descriptor for remote-sensing image registration

    Institute of Scientific and Technical Information of China (English)

    Xiangzeng Liu; Zheng Tian; Weidong Yan; Xifa Duan

    2011-01-01

    A technique to construct an affine invariant descriptor for remote-sensing image registration based on the scale invariant features transform (SIFT) in a kernel space is proposed.Affine invariant SIFT descriptor is first developed in an elliptical region determined by the Hessian matrix of the feature points.Thereafter,the descriptor is mapped to a feature space induced by a kernel, and a new descriptor is constructed by whitening the mapped descriptor in the feature space, with the transform called KW-SIFT.In a final step, the new descriptor is used to register remote-sensing images.Experimental results for remote-sensing image registration indicate that the proposed method improves the registration performance as compared with other related methods.%@@ A technique to construct an affine invariant descriptor for remote-sensing image registration based on the scale invariant features transform (SIFT) in a kernel space is proposed.Affine invariant SIFT descriptor is first developed in an elliptical region determined by the Hessian matrix of the feature points.Thereafter,the descriptor is mapped to a feature space induced by a kernel, and a new descriptor is constructed by whitening the mapped descriptor in the feature space, with the transform called KW-SIFT.In a final step, the new descriptor is used to register remote-sensing images.Experimental results for remote-sensing image registration indicate that the proposed method improves the registration performance as compared with other related methods.

  3. Remote Sensing of Ecosystem Health: Opportunities, Challenges, and Future Perspectives

    Directory of Open Access Journals (Sweden)

    Zhaoqin Li

    2014-11-01

    Full Text Available 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.

  4. Remote sensing of ecosystem health: opportunities, challenges, and future perspectives.

    Science.gov (United States)

    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.

  5. Remote home sensing and control system based on IOT public cloud platform%基于物联网公共云平台的远程家庭感知与控制系统

    Institute of Scientific and Technical Information of China (English)

    董爱民; 许菁

    2016-01-01

    Since the smart home system has the problems of non⁃unified standards,high purchase and use costs,and poor extension,a solution for the smart home system based on the Internet of Things (IOT) public cloud platform is proposed. An overall structure of the smart home system based on public cloud platform was designed and implemented. Three intelligent termi⁃nals of home comfortable environment,safety and power concumption are put forward,and realized by the convenient switching of voice command. The communication between the intelligent teminal equipment and cloud platform server was accomplished. The functions of uploading data from terminal equipment to cloud platform server and control command from cloud platform to terminal equipment were implemented. In this paper,the intelligent house model was established,and the visual display plat⁃form for the smart home system was designed. The function of the system to remotely control and examine the home intelligent equipment anytime or anywhere through the Internet or mobile intrenet was realized.%针对智能家居系统普遍存在标准不统一、购买及使用成本高、对外不可扩展等问题,提出了一种基于物联网公共云平台的智能家居系统解决方案。设计和实现了一种基于公共云平台的智能家居系统整体架构,提出了家居环境舒适度、安全性、能耗三种智能终端,通过语音指令方便切换,实现了家居环境舒适度、安全性、能耗三个方面的感知与控制。然后,完成了智能终端设备与云平台服务器间的通信流程,实现了终端设备向云平台服务器上传数据以及云平台下发控制指令到终端设备的功能。最后,搭建了房屋模型,设计了智能家居系统可视化的展示平台,实现了设备通过Internet或移动互联网在任何时间、任何地点远程查看和控制家中智能设备。

  6. Towards Dynamic Remote Data Auditing in Computational Clouds

    Directory of Open Access Journals (Sweden)

    Mehdi Sookhak

    2014-01-01

    Full Text Available Cloud computing is a significant shift of computational paradigm where computing as a utility and storing data remotely have a great potential. Enterprise and businesses are now more interested in outsourcing their data to the cloud to lessen the burden of local data storage and maintenance. However, the outsourced data and the computation outcomes are not continuously trustworthy due to the lack of control and physical possession of the data owners. To better streamline this issue, researchers have now focused on designing remote data auditing (RDA techniques. The majority of these techniques, however, are only applicable for static archive data and are not subject to audit the dynamically updated outsourced data. We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete. Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost. The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server.

  7. Barium Nitrate Raman Laser Development for Remote Sensing of Ozone

    Science.gov (United States)

    McCray, Christopher L.; Chyba, Thomas H.

    1997-01-01

    In order to understand the impact of anthropogenic emissions upon the earth's environment, scientists require remote sensing techniques which are capable of providing range-resolved measurements of clouds, aerosols, and the concentrations of several chemical constituents of the atmosphere. The differential absorption lidar (DIAL) technique is a very promising method to measure concentration profiles of chemical species such as ozone and water vapor as well as detect the presence of aerosols and clouds. If a suitable DIAL system could be deployed in space, it would provide a global data set of tremendous value. Such systems, however, need to be compact, reliable, and very efficient. In order to measure atmospheric gases with the DIAL technique, the laser transmitter must generate suitable on-line and off-line wavelength pulse pairs. The on-line pulse is resonant with an absorption feature of the species of interest. The off-line pulse is tuned so that it encounters significantly less absorption. The relative backscattered power for the two pulses enables the range-resolved concentration to be computed. Preliminary experiments at NASA LaRC suggested that the solid state Raman shifting material, Ba(NO3)2, could be utilized to produce these pulse pairs. A Raman oscillator pumped at 532 nm by a frequency-doubled Nd:YAG laser can create first Stokes laser output at 563 nm and second Stokes output at 599 nm. With frequency doublers, UV output at 281 nm and 299 nm can be subsequently obtained. This all-solid state system has the potential to be very efficient, compact, and reliable. Raman shifting in Ba(NO3)2, has previously been performed in both the visible and the infrared. The first Raman oscillator in the visible region was investigated in 1986 with the configurations of plane-plane and unstable telescopic resonators. However, most of the recent research has focused on the development of infrared sources for eye-safe lidar applications.

  8. Suitability Evaluation for Products Generation from Multisource Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Jining Yan

    2016-12-01

    Full Text Available With the arrival of the big data era in Earth observation, the remote sensing communities have accumulated a large amount of invaluable and irreplaceable data for global monitoring. These massive remote sensing data have enabled large-area and long-term series Earth observation, and have, in particular, made standard, automated product generation more popular. However, there is more than one type of data selection for producing a certain remote sensing product; no single remote sensor can cover such a large area at one time. Therefore, we should automatically select the best data source from redundant multisource remote sensing data, or select substitute data if data is lacking, during the generation of remote sensing products. However, the current data selection strategy mainly adopts the empirical model, and has a lack of theoretical support and quantitative analysis. Hence, comprehensively considering the spectral characteristics of ground objects and spectra differences of each remote sensor, by means of spectrum simulation and correlation analysis, we propose a suitability evaluation model for product generation. The model will enable us to obtain the Production Suitability Index (PSI of each remote sensing data. In order to validate the proposed model, two typical value-added information products, NDVI and NDWI, and two similar or complementary remote sensors, Landsat-OLI and HJ1A-CCD1, were chosen, and the verification experiments were performed. Through qualitative and quantitative analysis, the experimental results were consistent with our model calculation results, and strongly proved the validity of the suitability evaluation model. The proposed production suitability evaluation model could assist with standard, automated, serialized product generation. It will play an important role in one-station, value-added information services during the big data era of Earth observation.

  9. Comparison between laboratory and airborne BRDF measurements for remote sensing

    Science.gov (United States)

    Georgiev, Georgi T.; Gatebe, Charles K.; Butler, James J.; King, Michael D.

    2006-08-01

    Samples from soil and leaf litter were obtained at a site located in the savanna biome of South Africa (Skukuza; 25.0°S, 31.5°E) and their bidirectional reflectance distribution functions (BRDF) were measured using the out-of-plane scatterometer located in the National Aeronautics and Space Administration's (NASA's) Goddard Space Flight Center (GSFC) Diffuser Calibration Facility (DCaF). BRDF was measured using P and S incident polarized light over a range of incident and scatter angles. A monochromator-based broadband light source was used in the ultraviolet (uv) and visible (vis) spectral ranges. The diffuse scattered light was collected using an uv-enhanced silicon photodiode detector with output fed to a computer-controlled lock-in amplifier. Typical measurement uncertainties of the reported laboratory BRDF measurements are found to be less than 1% (k=1). These laboratory results were compared with airborne measurements of BRDF from NASA's Cloud Absorption Radiometer (CAR) instrument over the same general site where the samples were obtained. This study presents preliminary results of the comparison between these laboratory and airborne BRDF measurements and identifies areas for future laboratory and airborne BRDF measurements. This paper presents initial results in a study to try to understand BRDF measurements from laboratory, airborne, and satellite measurements in an attempt to improve the consistency of remote sensing models.

  10. Remote sensing of ocean color in the Arctic

    Science.gov (United States)

    Maynard, N. G.

    1988-01-01

    The main objectives of the research are: to increase the understanding of biological production (and carbon fluxes) along the ice edge, in frontal regions, and in open water areas of the Arctic and the physical factors controlling that production through the use of satellite and aircraft remote sensing techniques; and to develop relationships between measured radiances from the Multichannel Aircraft Radiometer System (MARS) and the bio-optical properties of the water in the Arctic and adjacent seas. Several recent Coastal Zone Color Scanner (CZCS) studies in the Arctic have shown that, despite constraints imposed by cloud cover, satellite ocean color is a useful means of studying mesoscale physical and biological oceanographic phenomena at high latitudes. The imagery has provided detailed information on ice edge and frontal processes such as spring breakup and retreat of the ice edge, influence of ice on ice effects of stratification on phytoplankton production, river sediment transport, effects of spring runoff, water mass boundaries, circulation patterns, and eddy formation in Icelandic waters and in the Greenland, Barents, Norwegian, and Bering Seas.

  11. Remote sensing of water vapor within the solar spectrum

    Energy Technology Data Exchange (ETDEWEB)

    Bartsch, B. [Univ. Hamburg (Germany). Meteorologisches Inst.; Bakan, S. [Max-Planck-Inst. fuer Meteorologie, Hamburg (Germany); Fischer, J. [Freie Univ. Berlin (Germany). Inst. fuer Weltraumwissenschaften

    1995-12-31

    Water vapor is the most important natural atmospheric greenhouse gas, influencing strongly solar and thermal infrared radiative transfer, and giving rise for clouds, which have strong influence on weather and climate. Therefore, much effort is devoted to remote sensing of atmospheric water vapor. The detection over water is well established, while the situation over land surfaces is worse. A new method is developed to derive the total atmospheric water vapor content over land surfaces even for higher aerosol contents with the aid of backscattered solar radiances. Numerous radiative transfer simulations with a matrix operator code of vertically backscattered solar radiance were carried out for different vertically stratified atmospheres. From the evaluation of these theoretical calculations it can be concluded that this technique allows the detection of total atmospheric water vapor content over land surfaces with an error of less than 10%. This result is important with regard to future measurements planned with the MERIS imaging spectrometer on board the European satellite ENVISAT, which will be launched in 1998. In addition to these theoretical calculations also various aircraft measurements of the backscattered radiances in the wavelength range from 600 to 1,650 nm were carried out. These measurements are done with the above mentioned OVID, a new multichannel array spectrometer of the Universities of Hamburg and Berlin. First comparisons of these airborne CCD measurements with calculated spectra are shown.

  12. Quarterly literature review of the remote sensing of natural resources

    Science.gov (United States)

    Fears, C. B. (Editor); Inglis, M. H. (Editor)

    1977-01-01

    The Technology Application Center reviewed abstracted literature sources, and selected document data and data gathering techniques which were performed or obtained remotely from space, aircraft or groundbased stations. All of the documentation was related to remote sensing sensors or the remote sensing of the natural resources. Sensors were primarily those operating within the 10 to the minus 8 power to 1 meter wavelength band. Included are NASA Tech Briefs, ARAC Industrial Applications Reports, U.S. Navy Technical Reports, U.S. Patent reports, and other technical articles and reports.

  13. System and method for evaluating wind flow fields using remote sensing devices

    Science.gov (United States)

    Schroeder, John; Hirth, Brian; Guynes, Jerry

    2016-12-13

    The present invention provides a system and method for obtaining data to determine one or more characteristics of a wind field using a first remote sensing device and a second remote sensing device. Coordinated data is collected from the first and second remote sensing devices and analyzed to determine the one or more characteristics of the wind field. The first remote sensing device is positioned to have a portion of the wind field within a first scanning sector of the first remote sensing device. The second remote sensing device is positioned to have the portion of the wind field disposed within a second scanning sector of the second remote sensing device.

  14. System and method for evaluating wind flow fields using remote sensing devices

    Energy Technology Data Exchange (ETDEWEB)

    Schroeder, John; Hirth, Brian; Guynes, Jerry

    2016-12-13

    The present invention provides a system and method for obtaining data to determine one or more characteristics of a wind field using a first remote sensing device and a second remote sensing device. Coordinated data is collected from the first and second remote sensing devices and analyzed to determine the one or more characteristics of the wind field. The first remote sensing device is positioned to have a portion of the wind field within a first scanning sector of the first remote sensing device. The second remote sensing device is positioned to have the portion of the wind field disposed within a second scanning sector of the second remote sensing device.

  15. Remote sensing place : Satellite images as visual spatial imaginaries

    NARCIS (Netherlands)

    Shim, David

    How do people come to know the world? How do they get a sense of place and space? Arguably, one of the ways in which they do this is through the practice of remote sensing, among which satellite imagery is one of the most widespread and potent tools of engaging, representing and constructing space.

  16. Remote Sensing: The View from Above. Know Your Environment.

    Science.gov (United States)

    Academy of Natural Sciences, Philadelphia, PA.

    This publication identifies some of the general concepts of remote sensing and explains the image collection process and computer-generated reconstruction of the data. Monitoring the ecological collapse in coral reefs, weather phenomena like El Nino/La Nina, and U.S. Space Shuttle-based sensing projects are some of the areas for which remote…

  17. TCR backscattering characterization for microwave remote sensing

    Science.gov (United States)

    Riccio, Giovanni; Gennarelli, Claudio

    2014-05-01

    A Trihedral Corner Reflector (TCR) is formed by three mutually orthogonal metal plates of various shapes and is a very important scattering structure since it exhibits a high monostatic Radar Cross Section (RCS) over a wide angular range. Moreover it is a handy passive device with low manufacturing costs and robust geometric construction, the maintenance of its efficiency is not difficult and expensive, and it can be used in all weather conditions (i.e., fog, rain, smoke, and dusty environment). These characteristics make it suitable as reference target and radar enhancement device for satellite- and ground-based microwave remote sensing techniques. For instance, TCRs have been recently employed to improve the signal-to-noise ratio of the backscattered signal in the case of urban ground deformation monitoring [1] and dynamic survey of civil infrastructures without natural corners as the Musmeci bridge in Basilicata, Italy [2]. The region of interest for the calculation of TCR's monostatic RCS is here confined to the first quadrant containing the boresight direction. The backscattering term is presented in closed form by evaluating the far-field scattering integral involving the contributions related to the direct illumination and the internal bouncing mechanisms. The Geometrical Optics (GO) laws allow one to determine the field incident on each TCR plate and the patch (integration domain) illuminated by it, thus enabling the use of a Physical Optics (PO) approximation for the corresponding surface current densities to consider for integration on each patch. Accordingly, five contributions are associated to each TCR plate: one contribution is due to the direct illumination of the whole internal surface; two contributions originate by the impinging rays that are simply reflected by the other two internal surfaces; and two contributions are related to the impinging rays that undergo two internal reflections. It is useful to note that the six contributions due to the

  18. Water Quality Assessment using Satellite Remote Sensing

    Science.gov (United States)

    Haque, Saad Ul

    2016-07-01

    The two main global issues related to water are its declining quality and quantity. Population growth, industrialization, increase in agriculture land and urbanization are the main causes upon which the inland water bodies are confronted with the increasing water demand. The quality of surface water has also been degraded in many countries over the past few decades due to the inputs of nutrients and sediments especially in the lakes and reservoirs. Since water is essential for not only meeting the human needs but also to maintain natural ecosystem health and integrity, there are efforts worldwide to assess and restore quality of surface waters. Remote sensing techniques provide a tool for continuous water quality information in order to identify and minimize sources of pollutants that are harmful for human and aquatic life. The proposed methodology is focused on assessing quality of water at selected lakes in Pakistan (Sindh); namely, HUBDAM, KEENJHAR LAKE, HALEEJI and HADEERO. These lakes are drinking water sources for several major cities of Pakistan including Karachi. Satellite imagery of Landsat 7 (ETM+) is used to identify the variation in water quality of these lakes in terms of their optical properties. All bands of Landsat 7 (ETM+) image are analyzed to select only those that may be correlated with some water quality parameters (e.g. suspended solids, chlorophyll a). The Optimum Index Factor (OIF) developed by Chavez et al. (1982) is used for selection of the optimum combination of bands. The OIF is calculated by dividing the sum of standard deviations of any three bands with the sum of their respective correlation coefficients (absolute values). It is assumed that the band with the higher standard deviation contains the higher amount of 'information' than other bands. Therefore, OIF values are ranked and three bands with the highest OIF are selected for the visual interpretation. A color composite image is created using these three bands. The water quality

  19. Remote sensing of essential ecosystem functional variables

    Science.gov (United States)

    Alcaraz-Segura, D.; Bagnato, C. E.; Paruelo, J. M.; Berbery, E. H.; Cabello, J.; Castro, A.; Cazorla, B. P.; Epstein, H. E.; Fernández, N.; Jobbagy, E. G.; Oyonarte, C.; Pacheco, M.; Peñas, J.; Vallejos, M.

    2016-12-01

    Essential Biodiversity Variables should inform on the status of the three dimensions recognised for biodiversity: composition, structure and function. Whereas composition and structure (from genes to ecosystems) have been traditionally used to assess biodiversity status, functional components of biodiversity, particularly at the ecosystem level, have been scarcely included. Satellite remote sensing can provide multiple descriptors of ecosystem function, though their relevance as essential biodiversity variables still needs to be assessed. Time-series of spectral data derived from satellite images can inform on key attributes of the dynamics of carbon, water, energy balance, disturbance regime or nutrient cycling. These ecosystem functional attributes can be integrated to identify Ecosystem Functional Types (EFTs), defined as groups of ecosystems with similar dynamics of matter and energy exchanges between the biota and the physical environment. Most popular EFTs used the three most informative metrics of the seasonal curves of spectral vegetation indices as surrogates of the most integrative descriptor of ecosystem functioning, the primary production dynamics: annual mean (estimator of primary production), seasonal coefficient of variation (descriptor of seasonality), and date of maximum (indicator of phenology). To search for simple metrics that could be used as a set of highly informative ecosystem functional attributes, we extended the analysis to the global scale across all terrestrial biomes and to other key dimensions of ecosystem functioning, i.e., albedo and surface temperature (related to the energy balance) and evapotranspiration (related to the water cycle and the energy balance). The three first axes of a Principal Component Analysis run on the average seasonal dynamics of each variable and biome explained from 85% to 97% of variance. From more than 20 summary metrics analysed, the annual mean was highly correlated to the first axis (r2>0.9). The second

  20. Footprint Representation of Planetary Remote Sensing Data

    Science.gov (United States)

    Walter, S. H. G.; Gasselt, S. V.; Michael, G.; Neukum, G.

    The geometric outline of remote sensing image data, the so called footprint, can be represented as a number of coordinate tuples. These polygons are associated with according attribute information such as orbit name, ground- and image resolution, solar longitude and illumination conditions to generate a powerful base for classification of planetary experiment data. Speed, handling and extended capabilites are the reasons for using geodatabases to store and access these data types. Techniques for such a spatial database of footprint data are demonstrated using the Relational Database Management System (RDBMS) PostgreSQL, spatially enabled by the PostGIS extension. Exemplary, footprints of the HRSC and OMEGA instruments, both onboard ESA's Mars Express Orbiter, are generated and connected to attribute information. The aim is to provide high-resolution footprints of the OMEGA instrument to the science community for the first time and make them available for web-based mapping applications like the "Planetary Interactive GIS-on-the-Web Analyzable Database" (PIG- WAD), produced by the USGS. Map overlays with HRSC or other instruments like MOC and THEMIS (footprint maps are already available for these instruments and can be integrated into the database) allow on-the-fly intersection and comparison as well as extended statistics of the data. Footprint polygons are generated one by one using standard software provided by the instrument teams. Attribute data is calculated and stored together with the geometric information. In the case of HRSC, the coordinates of the footprints are already available in the VICAR label of each image file. Using the VICAR RTL and PostgreSQL's libpq C library they are loaded into the database using the Well-Known Text (WKT) notation by the Open Geospatial Consortium, Inc. (OGC). For the OMEGA instrument, image data is read using IDL routines developed and distributed by the OMEGA team. Image outlines are exported together with relevant attribute

  1. Research on compressive fusion for remote sensing images

    Science.gov (United States)

    Yang, Senlin; Wan, Guobin; Li, Yuanyuan; Zhao, Xiaoxia; Chong, Xin

    2014-02-01

    A compressive fusion of remote sensing images is presented based on the block compressed sensing (BCS) and non-subsampled contourlet transform (NSCT). Since the BCS requires small memory space and enables fast computation, firstly, the images with large amounts of data can be compressively sampled into block images with structured random matrix. Further, the compressive measurements are decomposed with NSCT and their coefficients are fused by a rule of linear weighting. And finally, the fused image is reconstructed by the gradient projection sparse reconstruction algorithm, together with consideration of blocking artifacts. The field test of remote sensing images fusion shows the validity of the proposed method.

  2. Research on Key Technology of Mining Remote Sensing Dynamic Monitoring Information System

    Science.gov (United States)

    Sun, J.; Xiang, H.

    2017-09-01

    Problems exist in remote sensing dynamic monitoring of mining are expounded, general idea of building remote sensing dynamic monitoring information system is presented, and timely release of service-oriented remote sensing monitoring results is established. Mobile device-based data verification subsystem is developed using mobile GIS, remote sensing dynamic monitoring information system of mining is constructed, and "timely release, fast handling and timely feedback" rapid response mechanism of remote sensing dynamic monitoring is implemented.

  3. Remote sensing strategies for global resource exploration and environmental management

    Science.gov (United States)

    Henderson, Frederick B.

    Since 1972, satellite remote sensing, when integrated with other exploration techniques, has demonstrated operational exploration and engineering cost savings and reduced exploration risks through improved geological mapping. Land and ocean remote sensing satellite systems under development for the 1990's by the United States, France, Japan, Canada, ESA, Russia, China, and others, will significantly increase our ability to explore for, develop, and manage energy and mineral resources worldwide. A major difference between these systems is the "Open Skies" and "Non-Discriminatory Access to Data" policies as have been practiced by the U.S. and France and the restrictive nationalistic data policies as have been practiced by Russia and India. Global exploration will use satellite remote sensing to better map regional structural and basin-like features that control the distribution of energy and mineral resources. Improved sensors will better map lithologic and stratigraphic units and identify alteration effects in rocks, soils, and vegetation cover indicative of undiscovered subsurface resources. These same sensors will also map and monitor resource development. The use of satellite remote sensing data will grow substantially through increasing integration with other geophysical, geochemical, and geologic data using improved geographic information systems (GIS). International exploration will focus on underdeveloped countries rather than on mature exploration areas such as the United States, Europe, and Japan. Energy and mineral companies and government agencies in these countries and others will utilize available remote sensing data to acquire economic intelligence on global resources. If the "Non-Discriminatory Access to Data" principle is observed by satellite producing countries, exploration will remain competitive "on the ground". In this manner, remote sensing technology will continue to be developed to better explore for and manage the world's needed resources

  4. A Prototype Network for Remote Sensing Validation in China

    Directory of Open Access Journals (Sweden)

    Mingguo Ma

    2015-04-01

    Full Text Available Validation is an essential and important step before the application of remote sensing products. This paper introduces a prototype of the validation network for remote sensing products in China (VRPC. The VRPC aims to improve remote sensing products at a regional scale in China. These improvements will enhance the applicability of the key remote sensing products in understanding and interpretation of typical land surface processes in China. The framework of the VRPC is introduced first, including its four basic components. Then, the basic selection principles of the observation sites are described, and the principles for the validation of the remote sensing products are established. The VRPC will be realized in stages. In the first stage, four stations that have improved remote sensing observation facilities have been incorporated according to the selection principles. Certain core observation sites have been constructed at these stations. Next the Heihe Station is introduced in detail as an example. The three levels of observation (the research base, pixel-scale validation sites, and regional coverage adopted by the Heihe Station are carefully explained. The pixel-scale validation sites with nested multi-scale observation systems in this station are the most unique feature, and these sites aim to solve some key scientific problems associated with remote sensing product validation (e.g., the scale effect and scale transformation. Multi-year of in situ measurements will ensure the high accuracy and inter-annual validity of the land products, which will provide dynamic regional monitoring and simulation capabilities in China. The observation sites of the VRPC are open, with the goal of increasing cooperation and exchange with global programs.

  5. Close-range environmental remote sensing with 3D hyperspectral technologies

    Science.gov (United States)

    Nevalainen, O.; Honkavaara, E.; Hakala, T.; Kaasalainen, Sanna; Viljanen, N.; Rosnell, T.; Khoramshahi, E.; Näsi, R.

    2016-10-01

    Estimation of the essential climate variables (ECVs), such as photosynthetically active radiation (FAPAR) and the leaf area index (LAI), is largely based on satellite-based remote sensing and the subsequent inversion of radiative transfer (RT) models. In order to build models that accurately describe the radiative transfer within and below the canopy, detailed 3D structural (geometrical) and spectral (radiometrical) information of the canopy is needed. Close-range remote sensing, such as terrestrial remote sensing and UAV-based 3D spectral measurements, offers significant opportunity to improve the RT modelling and ECV estimation of forests. Finnish Geospatial Research Institute (FGI) has been developing active and passive high resolution 3D hyperspectral measurement technologies that provide reflectance, anisotropy and 3D structure information of forests (i.e. hyperspectral point clouds). Technologies include hyperspectral imaging from unmanned airborne vehicle (UAV), terrestrial hyperspectral lidar (HSL) and terrestrial hyperspectral stereoscopic imaging. A measurement campaign to demonstrate these technologies in ECV estimation with uncertainty propagation was carried out in the Wytham Woods, Oxford, UK, in June 2015. Our objective is to develop traceable processing procedures for generating hyperspectral point clouds with geometric and radiometric uncertainty propagation using hyperspectral aerial and terrestrial imaging and hyperspectral terrestrial laser scanning. The article and presentation will present the methodology, instrumentation and first results of our study.

  6. Acoustic remote sensing of ocean flows

    Digital Repository Service at National Institute of Oceanography (India)

    Joseph, A.; Desa, E.

    Acoustic techniques have become powerful tools for measurement of ocean circulation mainly because of the ability of acoustic signals to travel long distances in water, and the inherently non-invasive nature of measurement. The satellite remote...

  7. User requirements for hydrological models with remote sensing input

    Energy Technology Data Exchange (ETDEWEB)

    Kolberg, Sjur

    1997-10-01

    Monitoring the seasonal snow cover is important for several purposes. This report describes user requirements for hydrological models utilizing remotely sensed snow data. The information is mainly provided by operational users through a questionnaire. The report is primarily intended as a basis for other work packages within the Snow Tools project which aim at developing new remote sensing products for use in hydrological models. The HBV model is the only model mentioned by users in the questionnaire. It is widely used in Northern Scandinavia and Finland, in the fields of hydroelectric power production, flood forecasting and general monitoring of water resources. The current implementation of HBV is not based on remotely sensed data. Even the presently used HBV implementation may benefit from remotely sensed data. However, several improvements can be made to hydrological models to include remotely sensed snow data. Among these the most important are a distributed version, a more physical approach to the snow depletion curve, and a way to combine data from several sources. 1 ref.

  8. Utilization of remote sensing observations in hydrologic models

    Science.gov (United States)

    Ragan, R. M.

    1977-01-01

    Most of the remote sensing related work in hydrologic modeling has centered on modifying existing models to take advantage of the capabilities of new sensor techniques. There has been enough success with this approach to insure that remote sensing is a powerful tool in modeling the watershed processes. Unfortunately, many of the models in use were designed without recognizing the growth of remote sensing technology. Thus, their parameters were selected to be map or field crew definable. It is believed that the real benefits will come through the evolution of new models having new parameters that are developed specifically to take advantage of our capabilities in remote sensing. The ability to define hydrologically active areas could have a significant impact. The ability to define soil moisture and the evolution of new techniques to estimate evoportransportation could significantly modify our approach to hydrologic modeling. Still, without a major educational effort to develop an understanding of the techniques used to extract parameter estimates from remote sensing data, the potential offered by this new technology will not be achieved.

  9. Remote sensing education and Internet/World Wide Web technology

    Science.gov (United States)

    Griffith, J.A.; Egbert, S.L.

    2001-01-01

    Remote sensing education is increasingly in demand across academic and professional disciplines. Meanwhile, Internet technology and the World Wide Web (WWW) are being more frequently employed as teaching tools in remote sensing and other disciplines. The current wealth of information on the Internet and World Wide Web must be distilled, nonetheless, to be useful in remote sensing education. An extensive literature base is developing on the WWW as a tool in education and in teaching remote sensing. This literature reveals benefits and limitations of the WWW, and can guide its implementation. Among the most beneficial aspects of the Web are increased access to remote sensing expertise regardless of geographic location, increased access to current material, and access to extensive archives of satellite imagery and aerial photography. As with other teaching innovations, using the WWW/Internet may well mean more work, not less, for teachers, at least at the stage of early adoption. Also, information posted on Web sites is not always accurate. Development stages of this technology range from on-line posting of syllabi and lecture notes to on-line laboratory exercises and animated landscape flyovers and on-line image processing. The advantages of WWW/Internet technology may likely outweigh the costs of implementing it as a teaching tool.

  10. [Analysis of related factors of slope plant hyperspectral remote sensing].

    Science.gov (United States)

    Sun, Wei-Qi; Zhao, Yun-Sheng; Tu, Lin-Ling

    2014-09-01

    In the present paper, the slope gradient, aspect, detection zenith angle and plant types were analyzed. In order to strengthen the theoretical discussion, the research was under laboratory condition, and modeled uniform slope for slope plant. Through experiments we found that these factors indeed have influence on plant hyperspectral remote sensing. When choosing slope gradient as the variate, the blade reflection first increases and then decreases as the slope gradient changes from 0° to 36°; When keeping other factors constant, and only detection zenith angle increasing from 0° to 60°, the spectral characteristic of slope plants do not change significantly in visible light band, but decreases gradually in near infrared band; With only slope aspect changing, when the dome meets the light direction, the blade reflectance gets maximum, and when the dome meets the backlit direction, the blade reflectance gets minimum, furthermore, setting the line of vertical intersection of incidence plane and the dome as an axis, the reflectance on the axis's both sides shows symmetric distribution; In addition, spectral curves of different plant types have a lot differences between each other, which means that the plant types also affect hyperspectral remote sensing results of slope plants. This research breaks through the limitations of the traditional vertical remote sensing data collection and uses the multi-angle and hyperspectral information to analyze spectral characteristics of slope plants. So this research has theoretical significance to the development of quantitative remote sensing, and has application value to the plant remote sensing monitoring.

  11. Water column correction for coral reef studies by remote sensing.

    Science.gov (United States)

    Zoffoli, Maria Laura; Frouin, Robert; Kampel, Milton

    2014-09-11

    Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application.

  12. Remote Sensing Open Access Journal: Increasing Impact through Quality Publications

    Directory of Open Access Journals (Sweden)

    Prasad S. Thenkabail

    2014-08-01

    Full Text Available Remote Sensing, an open access journal (http://www.mdpi.com/journal/remotesensing has grown at rapid pace since its first publication five years ago, and has acquired a strong reputation. It is a “pathfinder” being the first open access journal in remote sensing. For those academics who were used to waiting a year or two for their peer-reviewed scientific work to be reviewed, revised, edited, and published, Remote Sensing offers a publication time frame that is unheard of (in most cases, less than four months. However, we do this after multiple peer-reviews, multiple revisions, much editorial scrutiny and decision-making, and professional editing by an editorial office before a paper is published online in our tight time frame, bringing a paradigm shift in scientific publication. As a result, there has been a swift increase in submissions of higher and higher quality manuscripts from the best authors and institutes working on Remote Sensing, Geographic Information Systems (GIS, Global Navigation Satellite System (GNSS, GIScience, and all related geospatial science and technologies from around the world. The purpose of this editorial is to update everyone interested in Remote Sensing on the progress made over the last year, and provide an outline of our vision for the immediate future. [...

  13. Combining Citizen Science Phenological Observations with Remote Sensing Data

    Science.gov (United States)

    Delbart, Nicolas; Beaubien, Elisabeth; Kergoat, Laurent; Deront, Lise; Le Toan, Thuy

    2016-08-01

    Citizen science is efficient to collect data about plant phenology across large areas such as Canada and independently for each species. However, such time series are often discontinuous and observations are not evenly distributed. On the other hand, remote sensing provides a synoptic view on phenology but does not inform about inter-species differences in phenological response to climate variability.Existing interactions between the two types of data are so far essentially limited to the evaluation of remote sensing methods by citizen science data, which proved quite efficient. Here we first use such an approach to show that one remote sensing method green-up date relates to the leaf-out date of woody species but also to the whole plant community phenology at the regional level, including flowering phenology. Second we use a remote sensing time series to constrain the analysis of citizen data to overcome the main drawbacks that is the incompleteness of time series. We analyze the interspecies differences in phenology at the scale of so- called "pheno-regions" delineated using remote sensing green-up maps.

  14. Polarization Remote Sensing Physical Mechanism, Key Methods and Application

    Science.gov (United States)

    Yang, B.; Wu, T.; Chen, W.; Li, Y.; Knjazihhin, J.; Asundi, A.; Yan, L.

    2017-09-01

    China's long-term planning major projects "high-resolution earth observation system" has been invested nearly 100 billion and the satellites will reach 100 to 2020. As to 2/3 of China's area covered by mountains it has a higher demand for remote sensing. In addition to light intensity, frequency, phase, polarization is also the main physical characteristics of remote sensing electromagnetic waves. Polarization is an important component of the reflected information from the surface and the atmospheric information, and the polarization effect of the ground object reflection is the basis of the observation of polarization remote sensing. Therefore, the effect of eliminating the polarization effect is very important for remote sensing applications. The main innovations of this paper is as follows: (1) Remote sensing observation method. It is theoretically deduced and verified that the polarization can weaken the light in the strong light region, and then provide the polarization effective information. In turn, the polarization in the low light region can strengthen the weak light, the same can be obtained polarization effective information. (2) Polarization effect of vegetation. By analyzing the structure characteristics of vegetation, polarization information is obtained, then the vegetation structure information directly affects the absorption of biochemical components of leaves. (3) Atmospheric polarization neutral point observation method. It is proved to be effective to achieve the ground-gas separation, which can achieve the effect of eliminating the atmospheric polarization effect and enhancing the polarization effect of the object.

  15. REMOTELY SENSED DATA FUSION IN MODERN AGE ARCHAEOLOGY AND MILITARY HISTORICAL RECONSTRUCTION

    Directory of Open Access Journals (Sweden)

    A. Juhász

    2016-06-01

    Full Text Available LiDAR technology has become one of the major remote sensing methods in the last few years. There are several areas, where the scanned 3D point clouds can be used very efficiently. In our study we review the potential applications of LiDAR data in military historical reconstruction. Obviously, the base of this kind of investigation must be the archive data, but it is an interesting challenge to integrate a cutting edge method into such tasks. The LiDAR technology can be very useful, especially in vegetation covered areas, where the conventional remote sensing technologies are mostly inefficient. We review two typical sample projects where we integrated LiDAR data in military historical GIS reconstruction. Finally, we summarize, how laser scanned data can support the different parts of reconstruction work and define the technological steps of LiDAR data processing.

  16. Remotely Sensed Data Fusion in Modern Age Archaeology and Military Historical Reconstruction

    Science.gov (United States)

    Juhász, A.; Neuberger, H.

    2016-06-01

    LiDAR technology has become one of the major remote sensing methods in the last few years. There are several areas, where the scanned 3D point clouds can be used very efficiently. In our study we review the potential applications of LiDAR data in military historical reconstruction. Obviously, the base of this kind of investigation must be the archive data, but it is an interesting challenge to integrate a cutting edge method into such tasks. The LiDAR technology can be very useful, especially in vegetation covered areas, where the conventional remote sensing technologies are mostly inefficient. We review two typical sample projects where we integrated LiDAR data in military historical GIS reconstruction. Finally, we summarize, how laser scanned data can support the different parts of reconstruction work and define the technological steps of LiDAR data processing.

  17. Best practices in Remote Sensing for REDD+

    DEFF Research Database (Denmark)

    Dons, Klaus; Grogan, Kenneth

    2012-01-01

    The I-REDD+ team has opted for a challenging framework – targeting REDD-related problems in mountainous regions of Southeast Asia and putting a focus on forest degradation processes. The combination of • a region with heavy cloud cover during much of the year, • pronounced illumination difference...

  18. Tasseled cap transformation for HJ multispectral remote sensing data

    Science.gov (United States)

    Han, Ling; Han, Xiaoyong

    2015-12-01

    The tasseled cap transformation of remote sensing data has been widely used in environment, agriculture, forest and ecology. Tasseled cap transformation coefficients matrix of HJ multi-spectrum data has been established through Givens rotation matrix to rotate principal component transform vector to whiteness, greenness and blueness direction of ground object basing on 24 scenes year-round HJ multispectral remote sensing data. The whiteness component enhances the brightness difference of ground object, and the greenness component preserves more detailed information of vegetation change while enhances the vegetation characteristic, and the blueness component significantly enhances factory with blue plastic house roof around the town and also can enhance brightness of water. Tasseled cap transformation coefficients matrix of HJ will enhance the application effect of HJ multispectral remote sensing data in their application fields.

  19. Assessment of biochemical concentrations of vegetation using remote sensing technology

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The main biochemicals (such as lignin, protein, cellulose, sugar, starch, chlorophyll and water) of vegetation are directly or indirectly involved in major ecological processes, such as the functions of terrestrial ecosystems (i.e., nutrient-cycling processes, primary production, and decomposition). Remote sensing techniques provide a very convenient way of data acquisition capable of covering a large area several times during one season, so it can play a unique and essential role provided that we can relate remote sensing measurements to the biochemical characteristics of the Earth surface in a reliable and operational way. The application of remote sensing techniques for the estimation of canopy biochemicals was reviewed. Three methods of estimating biochemical concentrations of vegetation were included in this paper: index, stepwise multiple linear regression, and stepwise multiple linear regression based on a model of the forest crown. In addition, the vitality and potential applying value are stressed.

  20. Scientific Programming Using Java: A Remote Sensing Example

    Science.gov (United States)

    Prados, Don; Mohamed, Mohamed A.; Johnson, Michael; Cao, Changyong; Gasser, Jerry

    1999-01-01

    This paper presents results of a project to port remote sensing code from the C programming language to Java. The advantages and disadvantages of using Java versus C as a scientific programming language in remote sensing applications are discussed. Remote sensing applications deal with voluminous data that require effective memory management, such as buffering operations, when processed. Some of these applications also implement complex computational algorithms, such as Fast Fourier Transformation analysis, that are very performance intensive. Factors considered include performance, precision, complexity, rapidity of development, ease of code reuse, ease of maintenance, memory management, and platform independence. Performance of radiometric calibration code written in Java for the graphical user interface and of using C for the domain model are also presented.

  1. Scientific Programming Using Java: A Remote Sensing Example

    Science.gov (United States)

    Prados, Don; Mohamed, Mohamed A.; Johnson, Michael; Cao, Changyong; Gasser, Jerry

    1999-01-01

    This paper presents results of a project to port remote sensing code from the C programming language to Java. The advantages and disadvantages of using Java versus C as a scientific programming language in remote sensing applications are discussed. Remote sensing applications deal with voluminous data that require effective memory management, such as buffering operations, when processed. Some of these applications also implement complex computational algorithms, such as Fast Fourier Transformation analysis, that are very performance intensive. Factors considered include performance, precision, complexity, rapidity of development, ease of code reuse, ease of maintenance, memory management, and platform independence. Performance of radiometric calibration code written in Java for the graphical user interface and of using C for the domain model are also presented.

  2. Remote Sensing Image Deblurring Based on Grid Computation

    Institute of Scientific and Technical Information of China (English)

    LI Sheng-yang; ZHU Chong-guang; GE Ping-ju

    2006-01-01

    In general, there is a demand for real-time processing of mass quantity remote sensing images. However, the task is not only data-intensive but also computating-intensive. Distributed processing is a hot topic in remote sensing processing and image deblurring is also one of the most important needs. In order to satisfy the demand for quick processing and deblurring of mass quantity satellite images, we developed a distributed, grid computation-based platform as well as a corresponding middleware for grid computation. Both a constrained power spectrum equalization algorithm and effective block processing measures, which can avoid boundary effect, were applied during the processing. The result is satisfactory since computation efficiency and visual effect were greatly improved. It can be concluded that the technology of spatial information grids is effective for mass quantity remote sensing image processing.

  3. Validating firn compaction model with remote sensing data

    DEFF Research Database (Denmark)

    Simonsen, S. B.; Stenseng, Lars; Sørensen, Louise Sandberg

    A comprehensive understanding of firn processes is of outmost importance, when estimating present and future changes of the Greenland Ice Sheet. Especially, when remote sensing altimetry is used to assess the state of ice sheets and their contribution to global sea level rise, firn compaction...... models have been shown to be a key component. Now, remote sensing data can also be used to validate the firn models. Radar penetrating the upper part of the firn column in the interior part of Greenland shows a clear layering. The observed layers from the radar data can be used as an in-situ validation...... correction relative to the changes in the elevation of the surface observed with remote sensing altimetry? What model time resolution is necessary to resolved the observed layering? What model refinements are necessary to give better estimates of the surface mass balance of the Greenland ice sheet from...

  4. Water pollution remote sensing for Pearl River Delta

    Science.gov (United States)

    Deng, Ruru; Xiong, Shouping; Qin, Yan

    2008-10-01

    Water pollution on the Delta of Pearl River is increasingly serious and to command the fact of pollution is the key of the control. A remote sensing model for water pollution base on single scattering is deduced in this paper. To avoid the effect by turbidity of water, by analysis the characteristics of the energy composition of multiple scattering, a factor of second scattering is deduced to build a double scattering model, and the practical arithmetic for the calculation of the model is put forwarded and then used to the pollution remote sensing over the Pearl River Delta. The precision of the result is validated by the synchronous measured data on water surface. The result of remote sensing showed that all of the North River, East River and West River are polluted in Pearl River Delta, and the most serious pollution is take place around Guang Zhou City and Dong Guan City.

  5. Combining interior and exterior characteristics for remote sensing image denoising

    Science.gov (United States)

    Peng, Ni; Sun, Shujin; Wang, Runsheng; Zhong, Ping

    2016-04-01

    Remote sensing image denoising faces many challenges since a remote sensing image usually covers a wide area and thus contains complex contents. Using the patch-based statistical characteristics is a flexible method to improve the denoising performance. There are usually two kinds of statistical characteristics available: interior and exterior characteristics. Different statistical characteristics have their own strengths to restore specific image contents. Combining different statistical characteristics to use their strengths together may have the potential to improve denoising results. This work proposes a method combining statistical characteristics to adaptively select statistical characteristics for different image contents. The proposed approach is implemented through a new characteristics selection criterion learned over training data. Moreover, with the proposed combination method, this work develops a denoising algorithm for remote sensing images. Experimental results show that our method can make full use of the advantages of interior and exterior characteristics for different image contents and thus improve the denoising performance.

  6. Magnetoseismology ground-based remote sensing of Earth's magnetosphere

    CERN Document Server

    Menk, Frederick W

    2013-01-01

    Written by a researcher at the forefront of the field, this first comprehensive account of magnetoseismology conveys the physics behind these movements and waves, and explains how to detect and investigate them. Along the way, it describes the principles as applied to remote sensing of near-Earth space and related remote sensing techniques, while also comparing and intercalibrating magnetoseismology with other techniques. The example applications include advanced data analysis techniques that may find wider used in areas ranging from geophysics to medical imaging, and remote sensing using radar systems that are of relevance to defense surveillance systems. As a result, the book not only reviews the status quo, but also anticipates new developments. With many figures and illustrations, some in full color, plus additional computational codes for analysis and evaluation. Aimed at graduate readers, the text assumes knowledge of electromagnetism and physical processes at degree level, but introductory chapters wil...

  7. Remote sensing surveys design in regional agricultural inventories

    Science.gov (United States)

    Andreev, G. G.; Djemardian, Y. A.; Ezkov, V. V.; Sazanov, N. V.

    In this paper, we consider the methodology problems of remote sensing surveys design in regional agricultural inventories. The strategy of samples, based on the combined use of multispectral aerospace data and ground truth data obtained on test sites in the region under supervision, is used. The strategy of samples includes: selection of areas, which are statistically homogenous with certain agricultural parameters under research, identification of representative test sites grid; remote sensing from aerospace platforms and ground truth data acquisition on test sites as well. The ground measurements of biometrical parameters of certain agricultural crops under research are taken at test sites, maps of anomalies are compiled, spectrometrical and other optico-physical characteristics of vegetation canopies and soils are defined. The derived data are used in automatic interactive imagery processing at the training stages of the procedures of classification and application of thematical remote sensing data processing results to the entire region.

  8. Researching on the process of remote sensing video imagery

    Science.gov (United States)

    Wang, He-rao; Zheng, Xin-qi; Sun, Yi-bo; Jia, Zong-ren; Wang, He-zhan

    Unmanned air vehicle remotely-sensed imagery on the low-altitude has the advantages of higher revolution, easy-shooting, real-time accessing, etc. It's been widely used in mapping , target identification, and other fields in recent years. However, because of conditional limitation, the video images are unstable, the targets move fast, and the shooting background is complex, etc., thus it is difficult to process the video images in this situation. In other fields, especially in the field of computer vision, the researches on video images are more extensive., which is very helpful for processing the remotely-sensed imagery on the low-altitude. Based on this, this paper analyzes and summarizes amounts of video image processing achievement in different fields, including research purposes, data sources, and the pros and cons of technology. Meantime, this paper explores the technology methods more suitable for low-altitude video image processing of remote sensing.

  9. China national space remote sensing infrastructure and its application

    Science.gov (United States)

    Li, Ming

    2016-07-01

    Space Infrastructure is a space system that provides communication, navigation and remote sensing service for broad users. China National Space Remote Sensing Infrastructure includes remote sensing satellites, ground system and related systems. According to the principle of multiple-function on one satellite, multiple satellites in one constellation and collaboration between constellations, series of land observation, ocean observation and atmosphere observation satellites have been suggested to have high, middle and low resolution and fly on different orbits and with different means of payloads to achieve a high ability for global synthetically observation. With such an infrastructure, we can carry out the research on climate change, geophysics global surveying and mapping, water resources management, safety and emergency management, and so on. I This paper gives a detailed introduction about the planning of this infrastructure and its application in different area, especially the international cooperation potential in the so called One Belt and One Road space information corridor.

  10. Target Detection: Remote Sensing Techniques for Defence Applications

    Directory of Open Access Journals (Sweden)

    B. B. Chaudhuri

    1995-10-01

    Full Text Available The tremendous development in remote sensing technology in the recent past has opened up new challenges in defence applications. On important area of such applications is in target detection. This paper describes both classical and newly developed approaches to detect the targets by using remotely-sensed digital images. The classical approach includes statistical classification methods and image processing techniques. The new approach deals with a relatively new sensor technology, namely, synthetic aperture radar (SAR systems and fast developing tools, like neural networks and multisource data integration for analysis and interpretation. With SAR images, it is possible to detect targets or features of a target that is otherwise not possible. Neural networks and multisource data integration tools also have a great potential in analysing and interpreting remote sensing data for target detection.

  11. Remote sensing of aquatic vegetation: theory and applications.

    Science.gov (United States)

    Silva, Thiago S F; Costa, Maycira P F; Melack, John M; Novo, Evlyn M L M

    2008-05-01

    Aquatic vegetation is an important component of wetland and coastal ecosystems, playing a key role in the ecological functions of these environments. Surveys of macrophyte communities are commonly hindered by logistic problems, and remote sensing represents a powerful alternative, allowing comprehensive assessment and monitoring. Also, many vegetation characteristics can be estimated from reflectance measurements, such as species composition, vegetation structure, biomass, and plant physiological parameters. However, proper use of these methods requires an understanding of the physical processes behind the interaction between electromagnetic radiation and vegetation, and remote sensing of aquatic plants have some particular difficulties that have to be properly addressed in order to obtain successful results. The present paper reviews the theoretical background and possible applications of remote sensing techniques to the study of aquatic vegetation.

  12. Remotely Operating a Fourier Transform Spectrometer for Atmospheric Remote Sensing

    Science.gov (United States)

    Blavier, J.-F.; Toon, G. C.; Sen, B.

    2000-01-01

    This paper describes how the MkIV instrument was adapted for remote operation from the Barcroft site, where the harsh winter conditions make access difficult. Some of the main technical challenges will be discussed including, (i) operation from solar panels and batteries, (ii) cooling the detectors with LN2, (iii) instrument control and monitoring over a cellular phone, and (iv) data storage, processing and analysis. Finally, MkIV spectra measured from Barcroft and compared with those measured from JPL to highlight the advantages of the higher altitude site.

  13. A preliminary study of the statistical analyses and sampling strategies associated with the integration of remote sensing capabilities into the current agricultural crop forecasting system

    Science.gov (United States)

    Sand, F.; Christie, R.

    1975-01-01

    Extending the crop survey application of remote sensing from small experimental regions to state and national levels requires that a sample of agricultural fields be chosen for remote sensing of crop acreage, and that a statistical estimate be formulated with measurable characteristics. The critical requirements for the success of the application are reviewed in this report. The problem of sampling in the presence of cloud cover is discussed. Integration of remotely sensed information about crops into current agricultural crop forecasting systems is treated on the basis of the USDA multiple frame survey concepts, with an assumed addition of a new frame derived from remote sensing. Evolution of a crop forecasting system which utilizes LANDSAT and future remote sensing systems is projected for the 1975-1990 time frame.

  14. Risk management support through India Remote Sensing Satellites

    Science.gov (United States)

    Aparna, N.; Ramani, A. V.; Nagaraja, R.

    2014-11-01

    Remote Sensing along with Geographical Information System (GIS) has been proven as a very important tools for the monitoring of the Earth resources and the detection of its temporal variations. A variety of operational National applications in the fields of Crop yield estimation , flood monitoring, forest fire detection, landslide and land cover variations were shown in the last 25 years using the Remote Sensing data. The technology has proven very useful for risk management like by mapping of flood inundated areas identifying of escape routes and for identifying the locations of temporary housing or a-posteriori evaluation of damaged areas etc. The demand and need for Remote Sensing satellite data for such applications has increased tremendously. This can be attributed to the technology adaptation and also the happening of disasters due to the global climate changes or the urbanization. However, the real-time utilization of remote sensing data for emergency situations is still a difficult task because of the lack of a dedicated system (constellation) of satellites providing a day-to-day revisit of any area on the globe. The need of the day is to provide satellite data with the shortest delay. Tasking the satellite to product dissemination to the user is to be done in few hours. Indian Remote Sensing satellites with a range of resolutions from 1 km to 1 m has been supporting disasters both National & International. In this paper, an attempt has been made to describe the expected performance and limitations of the Indian Remote Sensing Satellites available for risk management applications, as well as an analysis of future systems Cartosat-2D, 2E ,Resourcesat-2R &RISAT-1A. This paper also attempts to describe the criteria of satellite selection for programming for the purpose of risk management with a special emphasis on planning RISAT-1(SAR sensor).

  15. Prospecting for coal in China with remote sensing

    Institute of Scientific and Technical Information of China (English)

    TAN Ke-long; WAN Yu-qing; SUN Sun-xin; BAO Gui-bao; KUANG Jing-shui

    2008-01-01

    With the rapid development of China's economy, coal resources are increasingly in great demand. As a result, the remaining coal reserves diminish gradually with large-scale exploitation of coal resources. Easily-found mines which used to be identiffed from outcrops or were buried under shallow overburden are decreasing, especially in the prosperous eastern regions of China,which experience coal shortages. Currently the main targets of coal prospecting are concealed and unidentified underground coal bodies, making it more and more difficult for coal prospecting. It is therefore important to explore coal prospecting by taking advantage of modern remote sensing and geographic information system technologies. Given a theoretical basis for coal prospecting by remote sensing, we demonstrate the methodologies and existing problems systematically by summarizing past practices of coal prospecting with remote sensing. We propose a new theory of coal prospecting with remote sensing. In uncovered areas, coal resources can be prospected for by direct interpretation. In coal beating strata of developed areas covered by thin Quaternary strata or vegetation, prospecting for coal can be carried out by indirect interpretation of geomorphology and vegetation. For deeply buried underground deposits, coal prospecting can rely on tectonic structures, interpretation and analysis of new tectonic clues and regularity of coal formation and preservation controlled by tectonic structures. By applying newly hyper-spectral, multi-polarization, multi-angle, multi-temporal and multi-resolution remote sensing data and carrying out integrated analysis of geographic attributes,ground attributes, geophysical exploration results, geochemical exploration results, geological drilling results and remote sensing data by GIS tools, coal geology resources and mineralogical regularities can be explored and coal resource information can be acquired with some confidence.

  16. Advanced and applied remote sensing of environmental conditions

    Science.gov (United States)

    Slonecker, E. Terrence; Fisher, Gary B.; Marr, David A.; Milheim, Lesley E.; Roig-Silva, Coral M.

    2013-01-01

    "Remote sensing” is a general term for monitoring techniques that collect information without being in physical contact with the object of study. Overhead imagery from aircraft and satellite sensors provides the most common form of remotely sensed data and records the interaction of electromagnetic energy (usually visible light) with matter, such as the Earth’s surface. Remotely sensed data are fundamental to geographic science. The U.S. Geological Survey’s (USGS) Eastern Geographic Science Center (EGSC) is currently conducting and promoting the research and development of several different aspects of remote sensing science in both the laboratory and from overhead instruments. Spectroscopy is the science of recording interactions of energy and matter and is the bench science for all remote sensing. Visible and infrared analysis in the laboratory with special instruments called spectrometers enables the transfer of this research from the laboratory to multispectral (5–15 broad bands) and hyperspectral (50–300 narrow contiguous bands) analyses from aircraft and satellite sensors. In addition, mid-wave (3–5 micrometers, µm) and long-wave (8–14 µm) infrared data analysis, such as attenuated total reflectance (ATR) spectral analysis, are also conducted. ATR is a special form of vibrational infrared spectroscopy that has many applications in chemistry and biology but has recently been shown to be especially diagnostic for vegetation analysis.

  17. The global troposphere - Biogeochemical cycles, chemistry, and remote sensing

    Science.gov (United States)

    Levine, J. S.; Allario, F.

    1982-01-01

    The chemical composition of the troposphere is controlled by various biogeochemical cycles that couple the atmosphere with the oceans, the solid earth and the biosphere, and by atmospheric photochemical/chemical reactions. These cycles and reactions are discussed and a number of key questions concerning tropospheric composition and chemistry for the carbon, nitrogen, oxygen and sulfur species are identified. Next, various remote sensing techniques and instruments capable of measuring and monitoring tropospheric species from the ground, aircraft and space to address some of these key questions are reviewed. Future thrusts in remote sensing of the troposphere are also considered.

  18. Design and construction of a remote sensing apparatus

    Science.gov (United States)

    Maples, D.; Hagewood, J. F.

    1973-01-01

    The methods of identifying plant and soil types using remote sensing techniques are described. The equipment employed consists of a balloon system and a mobile remote sensing laboratory housing a radiometer which is mounted on a turret mechanism. The radiometer is made up of a telescope whose lenses are replaced by mirrors which channel received radiation into a monochromator. The radiation is then focused onto detectors for measurement of the intensity of the electromagnetic energy as a function of wavelength. Measurements from a wavelength of 0.2 microns to 15 microns are obtained with the system. diagrams are provided.

  19. Prototype simulates remote sensing spectral measurements on fruits and vegetables

    Science.gov (United States)

    Hahn, Federico

    1998-09-01

    A prototype was designed to simulate spectral packinghouse measurements in order to simplify fruit and vegetable damage assessment. A computerized spectrometer is used together with lenses and an externally controlled illumination in order to have a remote sensing simulator. A laser is introduced between the spectrometer and the lenses in order to mark the zone where the measurement is being taken. This facilitates further correlation work and can assure that the physical and remote sensing measurements are taken in the same place. Tomato ripening and mango anthracnose spectral signatures are shown.

  20. Remote sensing models and methods for image processing

    CERN Document Server

    Schowengerdt, Robert A

    2007-01-01

    Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. This book, in its 3rd edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standa

  1. Microwave Remote Sensing: Needs and Requirements Concerning Technology

    DEFF Research Database (Denmark)

    Skou, Niels

    2003-01-01

    Spaceborne microwave remote sensing instruments, like the imaging radiometer and the synthetic aperture radar, are over timed faced with two partly conflicting requirements: performance expectations (resolutions, sensitivity, coverage) steadily increase with resource allocations (weight, power, b......, bulk, cost) decrease. This results in needs and requirements to the development of advanced technology thus enabling the future advanced systems to be viable and realistic.......Spaceborne microwave remote sensing instruments, like the imaging radiometer and the synthetic aperture radar, are over timed faced with two partly conflicting requirements: performance expectations (resolutions, sensitivity, coverage) steadily increase with resource allocations (weight, power...

  2. An Approach to Extracting Fractal in Remote Sensing Image

    Institute of Scientific and Technical Information of China (English)

    ZHU Ji; LIN Ziyu; WANG Angsheng; CUI Peng

    2006-01-01

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

  3. Microwave and millimeter-wave remote sensing for security applications

    CERN Document Server

    Nanzer, Jeffrey

    2012-01-01

    Microwave and millimeter-wave remote sensing techniques are fast becoming a necessity in many aspects of security as detection and classification of objects or intruders becomes more difficult. This groundbreaking resource offers you expert guidance in this burgeoning area. It provides you with a thorough treatment of the principles of microwave and millimeter-wave remote sensing for security applications, as well as practical coverage of the design of radiometer, radar, and imaging systems. You learn how to design active and passive sensors for intruder detection, concealed object detection,

  4. The Discrete Fourier Transform on hexagonal remote sensing image

    Science.gov (United States)

    Li, Yalu; Ben, Jin; Wang, Rui; Du, Lingyu

    2016-11-01

    Global discrete grid system will subdivide the earth recursively to form a multi-resolution grid hierarchy with no Overlap and seamless which help build global uniform spatial reference datum and multi-source data processing mode which takes the position as the object and in the aspect of data structure supports the organization, process and analysis of the remote sensing big data. This paper adopts the base transform to realize the mutual transformation of square pixel and hexagonal pixel. This paper designs the corresponding discrete Fourier transform algorithm for any lattice. Finally, the paper show the result of the DFT of the remote sensing image of the hexagonal pixel.

  5. The global troposphere - Biogeochemical cycles, chemistry, and remote sensing

    Science.gov (United States)

    Levine, J. S.; Allario, F.

    1982-01-01

    The chemical composition of the troposphere is controlled by various biogeochemical cycles that couple the atmosphere with the oceans, the solid earth and the biosphere, and by atmospheric photochemical/chemical reactions. These cycles and reactions are discussed and a number of key questions concerning tropospheric composition and chemistry for the carbon, nitrogen, oxygen and sulfur species are identified. Next, various remote sensing techniques and instruments capable of measuring and monitoring tropospheric species from the ground, aircraft and space to address some of these key questions are reviewed. Future thrusts in remote sensing of the troposphere are also considered.

  6. Improving remote sensing flood assessment using volunteered geographical data

    Directory of Open Access Journals (Sweden)

    E. Schnebele

    2013-03-01

    Full Text Available A new methodology for the generation of flood hazard maps is presented fusing remote sensing and volunteered geographical data. Water pixels are identified utilizing a machine learning classification of two Landsat remote sensing scenes, acquired before and during the flooding event as well as a digital elevation model paired with river gage data. A statistical model computes the probability of flooded areas as a function of the number of adjacent pixels classified as water. Volunteered data obtained through Google news, videos and photos are added to modify the contour regions. It is shown that even a small amount of volunteered ground data can dramatically improve results.

  7. Deriving harmonised forest information in Europe using remote sensing methods

    DEFF Research Database (Denmark)

    Seebach, Lucia Maria

    the need for harmonised forest information can be satisfied using remote sensing methods. In conclusion, the study showed that it is possible to derive harmonised forest information of high spatial detail in Europe with remote sensing. The study also highlighted the imperative provision of accuracy...... parameters for the spatial units of any foreseen application, as it is crucial for evaluating the fitness for purpose. Yet, the lack of comprehensive reference data limits large area accuracy assessments. Improvement of reference data availability is, thus, a prerequisite for better decision-making processes...

  8. Advanced remote sensing terrestrial information extraction and applications

    CERN Document Server

    Liang, Shunlin; Wang, Jindi

    2012-01-01

    Advanced Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited application

  9. On MSDT inversion with multi-angle remote sensing data

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    With the wavelet transform, image of multi-angle remote sensing is decomposed into multi-resolution. With data of each resolution, we try target-based multi-stages inversion, taking the inversion result of coarse resolution as the prior information of the next inversion. The result gets finer and finer until the resolution of satellite observation. In this way, the target-based multi-stages inversion can be used in remote sensing inversion of large-scaled coverage. With MISR data, we inverse structure parameters of vegetation in semiarid grassland of the Inner Mongolia Autonomous Region. The result proves that this way is efficient.

  10. [Hyperspectral remote sensing in monitoring the vegetation heavy metal pollution].

    Science.gov (United States)

    Li, Na; Lü, Jian-sheng; Altemann, W

    2010-09-01

    Mine exploitation aggravates the environment pollution. The large amount of heavy metal element in the drainage of slag from the mine pollutes the soil seriously, doing harm to the vegetation growing and human health. The investigation of mining environment pollution is urgent, in which remote sensing, as a new technique, helps a lot. In the present paper, copper mine in Dexing was selected as the study area and China sumac as the study plant. Samples and spectral data in field were gathered and analyzed in lab. The regression model from spectral characteristics for heavy metal content was built, and the feasibility of hyperspectral remote sensing in environment pollution monitoring was testified.

  11. Remote sensing of biomass of salt marsh vegetation in France

    Science.gov (United States)

    Gross, M. F.; Klemas, V.; Levasseur, J. E.

    1988-01-01

    Spectral data (gathered using a hand-held radiometer) and harvest data were collected from four salt marsh vegetation types in Brittany, France, to develop equations predicting live aerial biomass from spectral measurements. Remote sensing estimates of biomass of the general salt marsh community (GSM) and of Spartina alterniflora can be obtained throughout the growing season if separate biomass prediction equations are formulated for different species mixtures (for the GSM) and for different canopy types (for S. alterniflora). Results suggest that remote sensing will not be useful for predicting Halimione portulacoides biomass, but can be used to estimate Puccinellia maritima biomass early in the growing season.

  12. ARIEL - Atmospheric Remote-Sensing Infrared Exoplanet Large-survey

    Science.gov (United States)

    Tinetti, Giovanna; Drossart, Pierre; Eccleston, Paul; Hartogh, Paul; Leconte, Jérémy; Micela, Giusi; Ollivier, Marc; Pilbratt, Göran; Puig, Ludovic; Turrini, Diego; Vandenbussche, Bart; Wolkenberg, Paulina; ARIEL Consortium, ARIEL ESA Study Team

    2016-10-01

    The Atmospheric Remote-Sensing Infrared Exoplanet Large-survey (ARIEL) is one of the three candidate missions selected by the European Space Agency (ESA) for its next medium-class science mission due for launch in 2026. The goal of the ARIEL mission is to investigate the atmospheres of several hundreds planets orbiting distant stars in order to address the fundamental questions on how planetary systems form and evolve.During its four (with a potential extension to six) years mission ARIEL will observe 500+ exoplanets in the visible and the infrared with its meter-class telescope in L2. ARIEL targets will include Jupiter- and Neptune-size down to super-Earth and Earth-size around different types of stars. The main focus of the mission will be on hot and warm planets orbiting very close to their star, as they represent a natural laboratory in which to study the chemistry and formation of exoplanets. In cooler planets, different gases separate out through condensation and sinking into distinct cloud layers. The scorching heat experienced by hot exoplanets overrides these processes and keeps all molecular species circulating throughout the atmosphere.The ARIEL mission concept has been developed by a consortium of more than 50 institutes from 12 countries, which include UK, France, Italy, Germany, the Netherlands, Poland, Spain, Belgium, Austria, Denmark, Ireland and Portugal. The analysis of ARIEL spectra and photometric data will allow to extract the chemical fingerprints of gases and condensates in the planets' atmospheres, including the elemental composition for the most favorable targets. It will also enable the study of thermal and scattering properties of the atmosphere as the planet orbit around the star.ARIEL will have an open data policy, enabling rapid access by the general community to the high-quality exoplanet spectra that the core survey will deliver.

  13. Remote sensing of water vapor within the solar spectrum

    Science.gov (United States)

    Bartsch, Barbara; Bakan, Stephan; Fischer, Juergen

    1995-01-01

    Due to the great importance of atmospheric water vapor for weather and climate, much effort is devoted to remote sensing of atmospheric water vapor. The detection over water is well established, while the situation over land surface is worse. Therefore, a new method is developed to derive the total atmospheric water vapor content over land surfaces even for higher aerosol contents with the aid of backscattered solar radiances. Numerous radiative transfer simulations with a matrix operator code of vertically backscattered solar radiance were carried out for different vertically stratified atmospheres. The resolution of 1.7 nm in the wavelength range from 700 to 1050 nm was adopted to the resolution of our multichannel spectrometer OVID (Optical Visible and near Infrared Detector). Various atmospheric conditions were chosen, which were defined by variable input parameters of: (a) vertical profiles of temperature, pressure, and water vapor, (b) total water vapor content, (c) aerosols, (d) surface reflectance, and (e) sun zenith angle. Clouds were not taken into account. From the evaluation of these theoretical calculations it can be concluded that this technique allows the detection of total atmospheric water vapor content over land surfaces with an error of less than 10%. This result is important with regard to future measurements planed with the MERIS imaging spectrometer on board the european satellite ENVISAT, which will be launched in 1998. In addition to these theoretical calculations also various aircraft measurements of the backscattered radiances in the wavelength range from 600 to 1650 nm were carried out. These measurements are done with the above mentioned OVID, a new multichannel array spectrometer of the Universities of Hamburg and Berlin. First comparisons of these airborne CCD measurements with calculated spectra are shown.

  14. Characterization of clouds and aerosols by lidar remote sensing with regard to the transfer of UV radiation. Final report; Leitthema 4: Solare UV-B-Strahlung. Teilvorhaben: Charakterisierung von Wolken und Aerosolen durch Lidar-Fernerkundung hinsichtlich des UV-Strahlungstransfers. Abschlussbericht

    Energy Technology Data Exchange (ETDEWEB)

    Jaeger, H.; Muecke, R.; Kreipl, S.

    2000-05-01

    The investigations characterize aerosols and clouds over Garmisch-Partenkirchen by lidar remote sensing, and support the interpretation of measurements of the transfer of UV radiation. Extensive tests of calibration procedures were performed, and the lidar system was modified to meet the requirements. The focal point were measurements accompanying the CUVRA (Characteristics of the UV Radiation field in the Alps) campaign at IFU in March 1999. 767 lidar measurements in two wavelength channels were performed on 12 days during this campaign. Aerosol and cloud situations were characterized by determining lower and upper layer heights (time resolution down to 1 minute, height resolution down to 15 meters), multi layer situations from ground to the tropopause region (up to 5 aerosol and cloud layers), optical depths at 532 nm and 355 nm (range 0.01 to 3), wavelength dependences of the optical depth between 532 nm and 355 nm (range of wavelength exponent 0 to -2), and lidar ratios (extinction/backscatter) at 532 nm (range 20 to 38). (orig.) [German] Die Untersuchungen charakterisieren Aerosole und Wolken ueber Garmisch-Partenkirchen durch Lidar-Fernerkundung und dienen der Interpretation von Messungen des UV-Strahlungsflusses. Hierzu waren umfangreiche Arbeiten zum Testen von Eichverfahren notwendig, ebenso wie Modifizerungen des Lidarsystems. Schwerpunkt der Untersuchungen waren Messungen waehrend der CUVRA (Characteristics of the UV Radiation field in the Alps) Messkampagne im Maerz 1999 am IFU. Waehrend dieser Kampagne wurden an 12 Messtagen 767 Lidarmessungen in jeweils zwei Wellenlaengenkanaelen durchgefuehrt. Die Aerosol- und Wolkensituationen wurden charakterisiert durch die Bestimmung von Schichtunter- und obergrenzen (Zeitaufloesung bis zu 1 Minute, Hoehenaufloesung bis zu 15 m), der Mehrschichtigkeit vom Boden bis zum Tropopausenbereich (bis zu 5 Aerosol- und Wolkenschichten), der optischen Dicken bei 532 nm und 355 nm (Bereich 0.01 bis 3), der

  15. Research Advances in Monitoring Agro-meteorological Disasters Using Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    Xueyan; SUI; Rujuan; WANG; Huimin; YAO; Meng; WANG; Shaokun; LI; Xiaodong; ZHANG

    2014-01-01

    Remote sensing is an important method for rapidly obtaining farmland information. Once meteorological disaster occurs,using the remote sensing technology to extract disaster area of crops and monitor disaster level has great significance for evaluating disasters and making a timely remedy. This paper elaborated the importance of monitoring agro-meteorological disasters using remote sensing in current special historical period,overviewed remote sensing methods both at home and abroad,analyzed existing problems,made clear major problems to be solved in monitoring agro-meteorological disasters using remote sensing,and discussed the development prospect of the remote sensing technology.

  16. Remote sensing of aerosols over snow using infrared AATSR observations

    Science.gov (United States)

    Istomina, L. G.; von Hoyningen-Huene, W.; Kokhanovsky, A. A.; Schultz, E.; Burrows, J. P.

    2011-06-01

    Infrared (IR) retrievals of aerosol optical thickness (AOT) are challenging because of the low reflectance of aerosol layer at longer wavelengths. In this paper we present a closer analysis of this problem, performed with radiative transfer (RT) simulations for coarse and accumulation mode of four main aerosol components. It shows the strong angular dependence of aerosol IR reflectance at low solar elevations resulting from the significant asymmetry of aerosol phase function at these wavelengths. This results in detectable values of aerosol IR reflectance at certain non-nadir observation angles providing the advantage of multiangle remote sensing instruments for a retrieval of AOT at longer wavelengths. Such retrievals can be of importance e.g. in case of a very strong effect of the surface on the top of atmosphere (TOA) reflectance in the visible spectral range. In the current work, a new method to retrieve AOT of the coarse and accumulation mode particles over snow has been developed using the measurements of Advanced Along Track Scanning Radiometer (AATSR) on board the ENVISAT satellite. The algorithm uses AATSR channel at 3.7 μm and utilizes its dual-viewing observation technique, implying the forward view with an observation zenith angle of around 55 degrees and the nadir view. It includes cloud/snow discrimination, extraction of the atmospheric reflectance out of measured brightness temperature (BT) at 3.7 μm, and interpolation of look-up tables (LUTs) for a given aerosol reflectance. The algorithm uses LUTs, separately simulated with RT forward calculations. The resulting AOT at 500 nm is estimated from the value at 3.7 μm using a fixed Angström parameter. The presented method has been validated against ground-based Aerosol Robotic Network (AERONET) data for 4 high Arctic stations and shows good agreement. A case study has been performed at W-Greenland on 5 July 2008. The day before was characterized by a noticeable dust event. The retrieved AOT maps of

  17. Remote sensing of aerosols over snow using infrared AATSR observations

    Directory of Open Access Journals (Sweden)

    L. G. Istomina

    2011-01-01

    Full Text Available Infrared (IR retrievals of aerosol optical thickness (AOT are challenging because of the low reflectance of aerosol layer at longer wavelengths. In this paper we present a closer analysis of this problem, performed with radiative transfer (RT simulations for coarse and accumulation mode of four main aerosol components. It shows the strong angular dependence of aerosol IR reflectance at low solar elevations resulting from significant asymmetry of aerosol phase function at these wavelengths. This results in detectable values of aerosol IR reflectance at certain non-nadir observation angles providing the advantage of multiangle remote sensing instruments for a retrieval of AOT at longer wavelengths. Such retrievals can be of importance e.g. in case of a very strong effect of the surface on the top of atmosphere (TOA reflectance in the visible range of spectrum. In current work, a new method to retrieve AOT over snow has been developed using the measurements of Advanced Along Track Scanning Radiometer (AATSR on board the ENVISAT satellite. The algorithm uses AATSR channel at 3.7 μm and utilizes its dual-viewing observation technique implying the forward view with an observation zenith angle around 55 degrees and the nadir view. It includes cloud/snow discrimination, extraction of the atmospheric reflectance out of measured brightness temperature (BT at 3.7 μm, interpolation of look-up tables (LUTs for a given aerosol reflectance. The algorithm uses LUTs, separately simulated with RT forward calculations. The resulting AOT at 500 nm is estimated from the value at 3.7 μm using a fixed Angström parameter.

    The presented method has been validated against ground-based Aerosol Robotic Network (AERONET data for 4 high Arctic stations and shows good agreement.

    A case study has been performed at W-Greenland on 5 July 2008. The day before was characterized by a noticeable dust event. The retrieved AOT maps of the region show a clear

  18. Remote sensing of aerosols over snow using infrared AATSR observations

    Directory of Open Access Journals (Sweden)

    L. G. Istomina

    2011-06-01

    Full Text Available Infrared (IR retrievals of aerosol optical thickness (AOT are challenging because of the low reflectance of aerosol layer at longer wavelengths. In this paper we present a closer analysis of this problem, performed with radiative transfer (RT simulations for coarse and accumulation mode of four main aerosol components. It shows the strong angular dependence of aerosol IR reflectance at low solar elevations resulting from the significant asymmetry of aerosol phase function at these wavelengths. This results in detectable values of aerosol IR reflectance at certain non-nadir observation angles providing the advantage of multiangle remote sensing instruments for a retrieval of AOT at longer wavelengths. Such retrievals can be of importance e.g. in case of a very strong effect of the surface on the top of atmosphere (TOA reflectance in the visible spectral range. In the current work, a new method to retrieve AOT of the coarse and accumulation mode particles over snow has been developed using the measurements of Advanced Along Track Scanning Radiometer (AATSR on board the ENVISAT satellite. The algorithm uses AATSR channel at 3.7 μm and utilizes its dual-viewing observation technique, implying the forward view with an observation zenith angle of around 55 degrees and the nadir view. It includes cloud/snow discrimination, extraction of the atmospheric reflectance out of measured brightness temperature (BT at 3.7 μm, and interpolation of look-up tables (LUTs for a given aerosol reflectance. The algorithm uses LUTs, separately simulated with RT forward calculations. The resulting AOT at 500 nm is estimated from the value at 3.7 μm using a fixed Angström parameter.

    The presented method has been validated against ground-based Aerosol Robotic Network (AERONET data for 4 high Arctic stations and shows good agreement.

    A case study has been performed at W-Greenland on 5 July 2008. The day before was characterized by a noticeable dust

  19. DARLA: Data Assimilation and Remote Sensing for Littoral Applications

    Science.gov (United States)

    2017-03-01

    Numerical simulations were performed 4 using a 3D ocean circulation model (ROMS) two-way coupled to a phase-averaged wave propagation model (SWAN) in...sensing observations to constrain a data assimilation model of wave and circulation dynamics in an area characterized by a river mouth or tidal inlet...success of using remote sensing data to drive DA models, and produced a dynamically consistent representation of the wave, circulation , and

  20. The use of remote sensing for landslide studies in Europe

    Science.gov (United States)

    Tofani, Veronica; Agostini, Andrea; Segoni, Samuele; Catani, Filippo; Casagli, Nicola

    2013-04-01

    The existing remote sensing techniques and their actual application in Europe for landslide detection, mapping and monitoring have been investigated. Data and information necessary to evaluate the subjects have been collected through a questionnaire, designed using a Google form, which was disseminated among end-users and researchers involved in landslide. In total, 49 answers were collected, coming from 17 European countries and from different kinds of institutions (universities, research institutes, public institutes and private companies). The spatial distribution of the answers is consistent with the distribution of landslides in Europe, the significance of landslides impact on society and the estimated landslide susceptibility in the various countries. The outcomes showed that landslide detection and mapping is mainly performed with aerial photos, often associated with optical and radar imagery. Concerning landslide monitoring, satellite radars prevail over the other types of data followed by aerial photos and meteorological sensors. Since subsampling the answers according to the different typology of institutions it is not noticeable a clear gap between research institutes and end users, it is possible to infer that in landslide remote sensing the research is advancing at the same pace as its day-to-day application. Apart from optical and radar imagery, other techniques are less widespread and some of them are not so well established, notwithstanding their performances are increasing at a fast rate as scientific and technological improvements are accomplished. Remote sensing is mainly used for detection/mapping and monitoring of slides, flows and lateral spreads with a preferably large scale of analysis (1:5000 - 1:25000). All the compilers integrate remote sensing data with other thematic data, mainly geological maps, landslide inventory maps and DTMs and derived maps. Concerning landslide monitoring, the results of the questionnaire stressed that the best

  1. The remote sensing needs of Arctic geophysics

    Science.gov (United States)

    Campbell, W. J.

    1970-01-01

    The application of remote sensors for obtaining geophysical information of the Arctic regions is discussed. Two significant requirements are to acquire sequential, synoptic imagery of the Arctic Ocean during all weather and seasons and to measure the strains in the sea ice canopy and the heterogeneous character of the air and water stresses acting on the canopy. The acquisition of geophysical data by side looking radar and microwave sensors in military aircraft is described.

  2. A high throughput geocomputing system for remote sensing quantitative retrieval and a case study

    Science.gov (United States)

    Xue, Yong; Chen, Ziqiang; Xu, Hui; Ai, Jianwen; Jiang, Shuzheng; Li, Yingjie; Wang, Ying; Guang, Jie; Mei, Linlu; Jiao, Xijuan; He, Xingwei; Hou, Tingting

    2011-12-01

    The quality and accuracy of remote sensing instruments have been improved significantly, however, rapid processing of large-scale remote sensing data becomes the bottleneck for remote sensing quantitative retrieval applications. The remote sensing quantitative retrieval is a data-intensive computation application, which is one of the research issues of high throughput computation. The remote sensing quantitative retrieval Grid workflow is a high-level core component of remote sensing Grid, which is used to support the modeling, reconstruction and implementation of large-scale complex applications of remote sensing science. In this paper, we intend to study middleware components of the remote sensing Grid - the dynamic Grid workflow based on the remote sensing quantitative retrieval application on Grid platform. We designed a novel architecture for the remote sensing Grid workflow. According to this architecture, we constructed the Remote Sensing Information Service Grid Node (RSSN) with Condor. We developed a graphic user interface (GUI) tools to compose remote sensing processing Grid workflows, and took the aerosol optical depth (AOD) retrieval as an example. The case study showed that significant improvement in the system performance could be achieved with this implementation. The results also give a perspective on the potential of applying Grid workflow practices to remote sensing quantitative retrieval problems using commodity class PCs.

  3. Balloonborne lidar payloads for remote sensing

    Science.gov (United States)

    Shepherd, O.; Aurilio, G.; Hurd, A. G.; Rappaport, S. A.; Reidy, W. P.; Rieder, R. J.; Bedo, D. E.; Swirbalus, R. A.

    1994-02-01

    A series of lidar experiments has been conducted using the Atmospheric Balloonborne Lidar Experiment payload (ABLE). These experiments included the measurement of atmospheric Rayleigh and Mie backscatter from near space (approximately 30 km) and Raman backscatter measurements of atmospheric constituents as a function of altitude. The ABLE payload consisted of a frequency-tripled Nd:YAG laser transmitter, a 50 cm receiver telescope, and filtered photodetectors in various focal plane configurations. The payload for lidar pointing, thermal control, data handling, and remote control of the lidar system. Comparison of ABLE performance with that of a space lidar shows significant performance advantages and cost effectiveness for balloonborne lidar systems.

  4. Remote sensing in marine geology: Arctic to Caribbean

    Science.gov (United States)

    Carlson, P. R.

    1970-01-01

    The applications of remote sensing to coastal dynamics of both nearshore and offshore waters are discussed. Results of aerial photographic analysis of four areas are presented. The study areas include the Arctic (Beaufort Sea), the Pacific Northwest, San Francisco Bay, and St. John, Virgin Islands (Project Tektite).

  5. Measurement and Mapping of Riverine Environments by Optical Remote Sensing

    Science.gov (United States)

    2011-09-30

    we also 4 conduted a high-resolution, intensive survey of a meander bend that we have monitired each year since 2005 and is now in the midst of a...optical and thermal remote sensing as part of their Riverine Dynamics Experiment 4. Beginning tomorrow (9-30-2011), we will be working with Arete at

  6. Consideration of smoothing techniques for hyperspectral remote sensing

    NARCIS (Netherlands)

    Vaiphasa, C.

    2006-01-01

    Spectral smoothing filters are popularly used in a large number of modern hyperspectral remote sensing studies for removing noise from the data. However, most of these studies subjectively apply ad hoc measures to select filter types and their parameters. We argue that this subjectively minded appro

  7. Activities of the Remote Sensing Information Sciences Research Group

    Science.gov (United States)

    Estes, J. E.; Botkin, D.; Peuquet, D.; Smith, T.; Star, J. L. (Principal Investigator)

    1984-01-01

    Topics on the analysis and processing of remotely sensed data in the areas of vegetation analysis and modelling, georeferenced information systems, machine assisted information extraction from image data, and artificial intelligence are investigated. Discussions on support field data and specific applications of the proposed technologies are also included.

  8. Radar remote sensing to support tropical forest management.

    NARCIS (Netherlands)

    Sanden, van der J.J.

    1997-01-01

    This text describes an investigation into the potential of radar remote sensing for application to tropical forest management. The information content of various radar images is compared and assessed with regard to the information requirements of parties involved in tropical forest management at the

  9. UAS remote sensing for precision agriculture: An independent assessment

    Science.gov (United States)

    Small Unmanned Aircraft Systems (sUAS) are recognized as potentially important remote-sensing platforms for precision agriculture. However, research is required to determine which sensors and data processing methods are required to use sUAS in an efficient and cost-effective manner. Oregon State U...

  10. The interpretation of remote sensing, a feasibility study.

    NARCIS (Netherlands)

    den Dulk, J.A.

    1989-01-01

    This thesis describes research done to ascertain the possibilities and limitations of the use of remote sensing observations for agriculture. The topic is defined in Chapter 1. In Chapter 2 the possible applicability of certain existing models for this study is examined. Three models are developed f

  11. On the remote sensing of small black holes

    CERN Document Server

    Rosu, H C

    1994-01-01

    We support further our arguments on the black hole remote-sensing problem, i.e., finding out `surface'-temperature distributions of various types of non-isolated small (micron-sized) black holes from the spectral measurements of their Hawking-like pulses, that we started in a previous paper [Nuovo Cimento B 108, 1333 (1993)].

  12. Remote sensing estimates of impervious surfaces for pluvial flood modelling

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Drews, Martin

    This paper investigates the accuracy of medium resolution (MR) satellite imagery in estimating impervious surfaces for European cities at the detail required for pluvial flood modelling. Using remote sensing techniques enables precise and systematic quantification of the influence of the past 30...

  13. Cornell University remote sensing program. [New York State

    Science.gov (United States)

    Liang, T.; Philipson, W. R. (Principal Investigator); Stanturf, J. A.

    1980-01-01

    High altitude, color infrared aerial photography as well as imagery from Skylab and LANDSAT were used to inventory timber and assess potential sites for industrial development in New York State. The utility of small scale remotely sensed data for monitoring clearcutting in hardwood forests was also investigated. Consultation was provided regarding the Love Canal Landfill as part of environment protection efforts.

  14. On the remote sensing of Hawking grey pulses

    OpenAIRE

    Rosu, H. C.

    1994-01-01

    This is a short note on the black hole remote-sensing problem, i.e., finding out `surface' temperature distributions of various types of small (micron-sized) black holes from the spectral measurements of their Hawking grey pulses. Chen's modified Moebius inverse transform is illustrated in this context

  15. Preface to: Pan Ocean Remote Sensing Conference (PORSEC)

    Digital Repository Service at National Institute of Oceanography (India)

    Desa, E.; Brown, R.; Shenoi, S.S.C.; Joseph, G.

    stream_size 2404 stream_content_type text/plain stream_name Pre.pdf.txt stream_source_info Pre.pdf.txt Content-Encoding ISO-8859-1 Content-Type text/plain; charset=ISO-8859-1 Preface The Pan Ocean Remote Sensing...

  16. Processing of remote sensing information in cooperative intelligent grid environment

    Science.gov (United States)

    Sun, Jie; Ma, Hongchao; Zhong, Liang

    2008-12-01

    In order to raise the intelligent level and improve cooperative ability of grid. This paper proposes an agent oriented middleware, which is applied to the traditional OGSA architecture to compose a new architecture named CIG (Cooperative Intelligent Grid) and expounds the types of cooperative processing of remote sensing, the architecture of CIG and how to implement the cooperation in the CIG environment.

  17. Satellite remote sensing for water erosion assessment: A review

    NARCIS (Netherlands)

    Vrieling, A.

    2006-01-01

    Water erosion creates negative impacts on agricultural production, infrastructure, and water quality across the world. Regional-scale water erosion assessment is important, but limited by data availability and quality. Satellite remote sensing can contribute through providing spatial data to such as

  18. Cooling Effect of Rivers on Metropolitan Taipei Using Remote Sensing

    Directory of Open Access Journals (Sweden)

    Yen-Chang Chen

    2014-01-01

    Full Text Available This study applied remote sensing technology to analyze how rivers in the urban environment affect the surface temperature of their ambient areas. While surface meteorological stations can supply accurate data points in the city, remote sensing can provide such data in a two-dimensional (2-D manner. The goal of this paper is to apply the remote sensing technique to further our understanding of the relationship between the surface temperature and rivers in urban areas. The 2-D surface temperature data was retrieved from Landsat-7 thermal infrared images, while data collected by Formosat-2 was used to categorize the land uses in the urban area. The land surface temperature distribution is simulated by a sigmoid function with nonlinear regression analysis. Combining the aforementioned data, the range of effect on the surface temperature from rivers can be derived. With the remote sensing data collected for the Taipei Metropolitan area, factors affecting the surface temperature were explored. It indicated that the effect on the developed area was less significant than on the ambient nature zone; moreover, the size of the buffer zone between the river and city, such as the wetlands or flood plain, was found to correlate with the affected distance of the river surface temperature.

  19. Beyond NDVI: Extraction of biophysical variables from remote sensing imagery

    NARCIS (Netherlands)

    Clevers, J.G.P.W.

    2014-01-01

    This chapter provides an overview of methods used for the extraction of biophysical vegetation variables from remote sensing imagery. It starts with the description of the main spectral regions in the optical window of the electromagnetic spectrum based on typical spectral signatures of land surface

  20. Study on retrieve specified objects in massive remote sensing data

    Institute of Scientific and Technical Information of China (English)

    WANG Rongjing; CHEN Ping; ZHANG Wei

    2005-01-01

    In this paper, we show that to retrieve specified objects in massive remote sensing data set is very important in both practice and theory. An algorithm-based content retrieval in the massive data set is studied. To avoid the loss of information, the algorithm based on the Support Vector Machine classification is proposed. Also, the experiment on the real data set is made.