WorldWideScience

Sample records for optical remote sensing

  1. 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...

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. MTF online compensation in space optical remote sensing camera

    Science.gov (United States)

    Qu, Youshan; Zhai, Bo; Han, Yameng; Zhou, Jiang

    2015-02-01

    An ordinary space optical remote sensing camera is an optical diffraction-limited system and a low-pass filter from the theory of Fourier Optics, and all the digital imaging sensors, whether the CCD or CMOS, are low-pass filters as well. Therefore, when the optical image with abundant high-frequency components passes through an optical imaging system, the profuse middle-frequency information is attenuated and the rich high-frequency information is lost, which will blur the remote sensing image. In order to overcome this shortcoming of the space optical remote sensing camera, an online compensating approach of the Modulation Transfer Function in the space cameras is designed. The designed method was realized by a hardware analog circuit placed before the A/D converter, which was composed of adjustable low-pass filters with a calculated value of quality factor Q. Through the adjustment of the quality factor Q of the filters, the MTF of the processed image is compensated. The experiment results display that the realized compensating circuit in a space optical camera is capable of improving the MTF of an optical remote sensing imaging system 30% higher than that of no compensation. This quantized principle can efficiently instruct the MTF compensating circuit design in practice.

  7. 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

  8. Application of optical remote sensing in the Wenchuan earthquake assessment

    Science.gov (United States)

    Zhang, Bing; Lei, Liping; Zhang, Li; Liu, Liangyun; Zhu, Boqin; Zuo, Zhengli

    2009-06-01

    A mega-earthquake of magnitude 8 of Richter scale occurred in Wenchuan County, Sichuan Province, China on May 12, 2008. The earthquake inflicted heavy loss of human lives and properties. The Wenchuan earthquake induced geological disasters, house collapse, and road blockage. In this paper, we demonstrate an application of optical remote sensing images acquired from airborne and satellite platforms in assessing the earthquake damages. The high-resolution airborne images were acquired by the Chinese Academy of Sciences (CAS). The pre- and post-earthquake satellite images of QuickBird, IKONOS, Landsat TM, ALOS, and SPOT were collected by the Center for Earth Observation & Digital Earth (CEODE), CAS, and some of the satellite data were provided by the United States, Japan, and the European Space Agency. The pre- and post-earthquake remote sensing images integrated with DEM and GIS data were adopted to monitor and analyze various earthquake disasters, such as road blockage, house collapse, landslides, avalanches, rock debris flows, and barrier lakes. The results showed that airborne optical images provide a convenient tool for quick and timely monitoring and assessing of the distribution and dynamic changes of the disasters over the earthquake-struck regions. In addition, our study showed that the optical remote sensing data integrated with GIS data can be used to assess disaster conditions such as damaged farmlands, soil erosion, etc, which in turn provides useful information for the postdisaster reconstruction.

  9. 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

  10. 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.

  11. Modern fibre-optic coherent lidars for remote sensing

    Science.gov (United States)

    Hill, Chris

    2015-10-01

    This paper surveys some growth areas in optical sensing that exploit near-IR coherent laser sources and fibreoptic hardware from the telecoms industry. Advances in component availability and performance are promising benefits in several military and commercial applications. Previous work has emphasised Doppler wind speed measurements and wind / turbulence profiling for air safety, with recent sharp increases in numbers of lidar units sold and installed, and with wider recognition that different lidar / radar wavebands can and should complement each other. These advances are also enabling fields such as microDoppler measurement of sub-wavelength vibrations and acoustic waves, including non-lineof- sight acoustic sensing in challenging environments. To shed light on these different applications we review some fundamentals of coherent detection, measurement probe volume, and parameter estimation - starting with familiar similarities and differences between "radar" and "laser radar". The consequences of changing the operating wavelength by three or four orders of magnitude - from millimetric or centimetric radar to a typical fibre-optic lidar working near 1.5 μm - need regular review, partly because of continuing advances in telecoms technology and computing. Modern fibre-optic lidars tend to be less complicated, more reliable, and cheaper than their predecessors; and they more closely obey the textbook principles of easily adjusted and aligned Gaussian beams. The behaviours of noises and signals, and the appropriate processing strategies, are as expected different for the different wavelengths and applications. For example, the effective probe volumes are easily varied (e.g. by translating a fibre facet) through six or eight orders of magnitude; as the average number of contributing scatterers varies, from >1, we should review any assumptions about "many" scatterers and Gaussian statistics. Finally, some much older but still relevant scientific work (by A G Bell, E H

  12. 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)

  13. Realistic Instrumentation Platform for Active and Passive Optical Remote Sensing.

    Science.gov (United States)

    Brydegaard, Mikkel; Merdasa, Aboma; Gebru, Alem; Jayaweera, Hiran; Svanberg, Sune

    2016-02-01

    We describe the development of a novel versatile optical platform for active and passive remote sensing of environmental parameters. Applications include assessment of vegetation status and water quality. The system is also adapted for ecological studies, such as identification of flying insects including agricultural pests. The system is based on two mid-size amateur astronomy telescopes, continuous-wave diode lasers at different wavelengths ranging from violet to the near infrared, and detector facilities including quadrant photodiodes, two-dimensional and line scan charge-coupled device cameras, and a compact digital spectrometer. Application examples include remote Ramanlaser-induced fluorescence monitoring of water quality at 120 m distance, and insect identification at kilometer ranges using the recorded wing beat frequency and its spectrum of overtones. Because of the low cost this developmental platform is very suitable for advanced research projects in developing countries and has, in fact, been multiplied during hands-on workshops and is now being used by a number of groups at African universities. © The Author(s) 2016.

  14. REMOTE SENSING OF WATER QUALITY IN OPTICALLY COMPLEX LAKES

    Directory of Open Access Journals (Sweden)

    T. Kutser

    2012-07-01

    Full Text Available Solving of several global and regional problems requires adequate data about lake water quality parameters like the amount and type of phytoplankton dominating in the lakes, the amount of dissolved and coloured dissolved organic matter and/or concentration of suspended sediment. Remote sensing is the only practical way to study many lakes provided it can produce sufficiently accurate estimates of the water characteristics. We studied optically very variable lakes in order to test both physics based methods and conventional band-ratio type algorithms in retrieval of water parameters. The modelled spectral library used in the physics based approach provided very good results for chlorophyll-a retrieval. The number of different concentrations of CDOM and suspended matter used in the simulations was too low to provide good estimates of these parameters. Extending the spectral library is currently in progress. Band-ratio type algorithms worked well in chlorophyll-a and CDOM retrieval. None of the algorithms tested for total suspended matter, organic suspended matter and inorganic suspended matter retrieval performed well enough and there is need in further testing.

  15. A survey on object detection in optical remote sensing images

    Science.gov (United States)

    Cheng, Gong; Han, Junwei

    2016-07-01

    Object detection in optical remote sensing images, being a fundamental but challenging problem in the field of aerial and satellite image analysis, plays an important role for a wide range of applications and is receiving significant attention in recent years. While enormous methods exist, a deep review of the literature concerning generic object detection is still lacking. This paper aims to provide a review of the recent progress in this field. Different from several previously published surveys that focus on a specific object class such as building and road, we concentrate on more generic object categories including, but are not limited to, road, building, tree, vehicle, ship, airport, urban-area. Covering about 270 publications we survey (1) template matching-based object detection methods, (2) knowledge-based object detection methods, (3) object-based image analysis (OBIA)-based object detection methods, (4) machine learning-based object detection methods, and (5) five publicly available datasets and three standard evaluation metrics. We also discuss the challenges of current studies and propose two promising research directions, namely deep learning-based feature representation and weakly supervised learning-based geospatial object detection. It is our hope that this survey will be beneficial for the researchers to have better understanding of this research field.

  16. [Effects of aerosol optical thickness on the optical remote sensing imaging quality].

    Science.gov (United States)

    Hu, Xin-Li; Gu, Xing-Fa; Yu, Tao; Zhang, Zhou-Wei; Li, Juan; Luan, Hai-Jun

    2014-03-01

    In recent years, due to changes in atmospheric environment, atmospheric aerosol affection on optical sensor imaging quality is increasingly considered by the load developed departments. Space-based remote sensing system imaging process, atmospheric aerosol makes optical sensor imaging quality deterioration. Atmospheric medium causing image degradation is mainly forward light scattering effect caused by the aerosol turbid medium. Based on the turbid medium radiation transfer equation, the point spread function models were derived contained aerosol optical properties of atmosphere in order to analyze and evaluate the atmospheric blurring effect on optical sensor imaging system. It was found that atmospheric aerosol medium have effect on not only energy decay of atmospheric transmittance, but also the degradation of image quality due to the scattering effect. Increase of atmospheric aerosol optical thickness makes aerosol scattering intensity enhanced, variation of aerosol optical thickness is also strongly influences the point spread function of the spatial distribution. it is because the degradation of aerosol in spatial domain, which reduces the quality of remote sensing image, in particularly reduction of the sharpness of image. Meanwhile, it would provide a method to optimize and improve simulation of atmospheric chain.

  17. Optical remote sensing of sound in the ocean

    Science.gov (United States)

    Churnside, James H.; Naugolnykh, Konstantin; Marchbanks, Richard D.

    2014-05-01

    We are proposing a novel remote sensing technique to measure sound in the upper ocean. The objective is a system that can be flown on an aircraft. Conventional acoustic sensors are ineffective in this application, because almost none (~ 0.1 %) of the sound in the ocean is transmitted through the water/air interface. The technique is based on the acoustic modulation of bubbles near the sea surface. It is clear from the ideal gas law that the volume of a bubble will decrease if the pressure is increased, as long as the number of gas molecules and temperature remain constant. The pressure variations associated with the acoustic field will therefore induce proportional volume fluctuations of the insonified bubbles. The lidar return from a collection of bubbles has been shown to be proportional to the total void fraction, independent of the bubble size distribution. This implies that the lidar return from a collection of insonified bubbles will be modulated at the acoustic frequencies, independent of the bubble size distribution. Moreover, that modulation is linearly related to the sound pressure. The basic principles have been demonstrated in the laboratory, and these results will be presented. Estimates of signal-to-noise ratio suggest that the technique should work in the open ocean. Design considerations and signal-to-noise ratios will also be presented.

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

    Science.gov (United States)

    Zhang, Dianjun; Zhou, Guoqing

    2016-08-17

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

  19. Red tide optical index: in situ optics and remote sensing models

    Science.gov (United States)

    Cetinic, I.; Karp-Boss, L.; Boss, E.; Ragan, M. A.; Jones, B. H.

    2007-05-01

    Harmful Algal Blooms (HABs) are recurring events in the coastal ocean, and local economies that depend on beach and coastal use are often adversely affected by these events. Inherent optical properties (absorption and backscattering) of the HAB dinoflagellate Lingulodinium polyedrum were measured in order to develop specific index that would enable easier detection of this HAB organism in the field. It has been noticed that red to blue and red to green ratio of absorption in this species is much lower then other measured species. A red tide ratio was tested in the field during a red tide episode in the San Pedro Channel, using a Wetlabs acS flow-through system. The red tide index gave a distinguishable signal in areas where L.polyedrum was present. Remote sensing reflectance was calculated from field and laboratory IOP measurements, using reverse Quasi-Analythical Alghoritm and Hydrolight to evaluate if the red tide index can be detected in the remote sensing ocean color measurements.

  20. Classification of remotely sensed data using OCR-inspired neural network techniques. [Optical Character Recognition

    Science.gov (United States)

    Kiang, Richard K.

    1992-01-01

    Neural networks have been applied to classifications of remotely sensed data with some success. To improve the performance of this approach, an examination was made of how neural networks are applied to the optical character recognition (OCR) of handwritten digits and letters. A three-layer, feedforward network, along with techniques adopted from OCR, was used to classify Landsat-4 Thematic Mapper data. Good results were obtained. To overcome the difficulties that are characteristic of remote sensing applications and to attain significant improvements in classification accuracy, a special network architecture may be required.

  1. Optical Properties of Mineral Particles and Their Effect on Remote-Sensing Reflectance in Coastal Waters

    Science.gov (United States)

    2001-09-30

    1997. Photometric immersion refractometry : A method for determining the refractive index of marine microbial particles from beam attenuation...light is collected by the absorption meter due to geometry of instrument. In the previous report we described our effort to develop a method for...bulk optical properties in coastal waters, (2) develop reliable remote sensing algorithms for coastal waters, (3) develop improved methods for optical

  2. Estimating dissolved organic carbon concentration in turbid coastal waters using optical remote sensing observations

    Science.gov (United States)

    Cherukuru, Nagur; Ford, Phillip W.; Matear, Richard J.; Oubelkheir, Kadija; Clementson, Lesley A.; Suber, Ken; Steven, Andrew D. L.

    2016-10-01

    Dissolved Organic Carbon (DOC) is an important component in the global carbon cycle. It also plays an important role in influencing the coastal ocean biogeochemical (BGC) cycles and light environment. Studies focussing on DOC dynamics in coastal waters are data constrained due to the high costs associated with in situ water sampling campaigns. Satellite optical remote sensing has the potential to provide continuous, cost-effective DOC estimates. In this study we used a bio-optics dataset collected in turbid coastal waters of Moreton Bay (MB), Australia, during 2011 to develop a remote sensing algorithm to estimate DOC. This dataset includes data from flood and non-flood conditions. In MB, DOC concentration varied over a wide range (20-520 μM C) and had a good correlation (R2 = 0.78) with absorption due to coloured dissolved organic matter (CDOM) and remote sensing reflectance. Using this data set we developed an empirical algorithm to derive DOC concentrations from the ratio of Rrs(412)/Rrs(488) and tested it with independent datasets. In this study, we demonstrate the ability to estimate DOC using remotely sensed optical observations in turbid coastal waters.

  3. Research on the distributed optical remote sensing of methane employing single laser source

    Institute of Scientific and Technical Information of China (English)

    Wangbao Yin(尹王保); Weiguang Ma(马维光); Lirong Wang(汪丽蓉); Jianming Zhao(赵建明); Liantuan Xiao(肖连团); Suotang Jia(贾锁堂)

    2004-01-01

    @@ A design and testing of a cost-effective distributed optical remote sensing methane system,which will helpone to detect gas leaks from multi-coal face in mines simultaneously,is presented.The fundamentals ofthe remote detection are based on frequency-modulation spectroscopy(FMS)and harmonic detection.Byutilizing fiber-optic splitting technique and reference-signal restoring circuit,the remote sensing system isfeasible to employ single laser source to get multi-spot measurement in the near infrared region so thatthe system described here shows sufficient sensibility,considerably increased reliability and marketabilityover the presently available system.The minimum measurable path-integrated concentration is estimatedto be about 423 ppb-m by experimentation.

  4. 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

  5. Lidar: range-resolved optical remote sensing of the atmosphere

    National Research Council Canada - National Science Library

    Weitkamp, Claus; Walther, Herbert

    2005-01-01

    "Written by leading experts in optical radar, or lidar, this book brings all the recent practices up-to-date and covers a multitude of applications, from atmospheric sciences to environmental protection...

  6. Characterizing the Absorption Properties for Remote Sensing of Three Small Optically-Diverse South African Reservoirs

    Directory of Open Access Journals (Sweden)

    Mark William Matthews

    2013-09-01

    Full Text Available Characterizing the specific inherent optical properties (SIOPs of water constituents is fundamental to remote sensing applications. Therefore, this paper presents the absorption properties of phytoplankton, gelbstoff and tripton for three small, optically-diverse South African inland waters. The three reservoirs,  Hartbeespoort, Loskop and Theewaterskloof, are challenging for remote sensing, due to differences in phytoplankton assemblage and the considerable range of constituent concentrations. Relationships between the absorption properties and biogeophysical parameters, chlorophyll-a (chl-a, TChl (chl-a plus  phaeopigments,  seston,  minerals  and  tripton, are established. The value determined for the mass-specific tripton absorption coefficient at 442 nm, a∗ (442, ranges from 0.024 to 0.263 m2·g−1. The value of the TChl-specific phytoplankton absorption coefficient (a∗ was strongly influenced by phytoplankton species, size, accessory pigmentation and biomass. a∗ (440 ranged from 0.056 to 0.018 m2·mg−1 in oligotrophic to hypertrophic waters. The positive relationship between cell size and trophic state observed in open ocean waters was violated by significant small cyanobacterial populations. The phycocyanin-specific phytoplankton  absorption  at  620  nm,  a∗ (620, was determined as 0.007 m2·g−1 in a M. aeruginosa bloom. Chl-a was a better indicator of phytoplankton biomass than phycocyanin (PC in surface scums, due to reduced accessory pigment production. Absorption budgets demonstrate that monospecific blooms of M. aeruginosa and C. hirundinella may be treated as “cultures”, removing some complexities for remote sensing applications.   These results contribute toward a better understanding of IOPs and remote sensing applications in hypertrophic inland waters. However, the majority of the water is optically complex, requiring the usage of all the SIOPs derived here for remote sensing applications. The

  7. Philosophy and key features of 'Hodoyoshi' concept for optical remote sensing using 50kg class satellites

    Science.gov (United States)

    Enokuchi, A.; Takeyama, N.; Nakamura, Y.; Nojiri, Y.; Miyamura, N.; Iwasaki, A.; Nakasuka, S.

    2010-10-01

    Remote sensing missions have been conventionally performed by using satellite-onboard optical sensors with extraordinarily high reliability, on huge satellites. On the other hand, small satellites for remote-sensing missions have recently been developed intensely and operated all over the world. This paper gives a Japanese concept of the development of nano-satellites(10kg to 50kg) based on "Hodoyoshi" (Japanese word for "reasonable") reliability engineering aiming at cost-effective design of optical sensors, buses and satellites. The concept is named as "Hodoyoshi" concept. We focus on the philosophy and the key features of the concept. These are conveniently applicable to the development of optical sensors on nano-satellites. As major advantages, the optical sensors based on the "Hodoyoshi" concept are "flexible" in terms of selectability of wavelength bands, adaptability to the required ground sample distance, and optimal performance under a wide range of environmental temperatures. The first and second features mentioned above can be realized by dividing the functions of the optical sensor into modularized functional groups reasonably. The third feature becomes possible by adopting the athermal and apochromatic optics design. By utilizing these features, the development of the optical sensors become possible without exact information on the launcher or the orbit. Furthermore, this philosophy leads to truly quick delivery of nano-satellites for remote-sensing missions. On the basis of the concept, we are now developing nano-satellite technologies and five nano-satellites to realize the concept in a four-year-long governmentally funded project. In this paper, the specification of the optical sensor on the first satellite is also reported.

  8. Remote sensing reflectance model of optically active components of turbid waters

    Science.gov (United States)

    Kutser, Tiit; Arst, Helgi

    1994-12-01

    A mathematical model that simulates the spectral curves of remote sensing reflectance is developed. The model is compared to measurements obtained from research vessel or boat in the Baltic Sea and Estonian lakes. The model simulates the effects of light backscattering from water and suspended matter, and the effects of its absorption due to water, phytoplankton, suspended matter and yellow substance. Measured by remote sensing spectral curves are compared by multiple of spectra obtained from model calculations to find the theoretical spectrum which is closest to experimental. It is assumed that in case of coincidence of the spectral curves concentrations of optically active substances in the model correspond to real ones. Preliminary testing of the model demonstrates that this model is useful for estimation of concentration of optically active substances in the waters of the Baltic Sea and Estonian lakes.

  9. Joint Change Detection and Image Registration for Optical Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Wang Luo

    2012-03-01

    Full Text Available In this letter, a novel method is proposed for jointly unsupervised change detection and image registration over multi-temporal optical remote sensing images. An iterative energy minimization scheme is employed to extract the pixel opacity. Specifically, we extract the consistent points which provide the initial seed nodes and the feature nodes for random walker image segmentation and image registration, respectively. And the seed nodes will be updated according to the analysis of the changed and unchanged regions. Experimental results demonstrate that the proposed method can perform change detection as well as the state of the art methods. In particular, it can perform change detection rapidly and automatically over unregistered optical remote sensing images.

  10. A new method of inshore ship detection in high-resolution optical remote sensing images

    Science.gov (United States)

    Hu, Qifeng; Du, Yaling; Jiang, Yunqiu; Ming, Delie

    2015-10-01

    Ship as an important military target and water transportation, of which the detection has great significance. In the military field, the automatic detection of ships can be used to monitor ship dynamic in the harbor and maritime of enemy, and then analyze the enemy naval power. In civilian field, the automatic detection of ships can be used in monitoring transportation of harbor and illegal behaviors such as illegal fishing, smuggling and pirates, etc. In recent years, research of ship detection is mainly concentrated in three categories: forward-looking infrared images, downward-looking SAR image, and optical remote sensing images with sea background. Little research has been done into ship detection of optical remote sensing images with harbor background, as the gray-scale and texture features of ships are similar to the coast in high-resolution optical remote sensing images. In this paper, we put forward an effective harbor ship target detection method. First of all, in order to overcome the shortage of the traditional difference method in obtaining histogram valley as the segmentation threshold, we propose an iterative histogram valley segmentation method which separates the harbor and ships from the water quite well. Secondly, as landing ships in optical remote sensing images usually lead to discontinuous harbor edges, we use Hough Transform method to extract harbor edges. First, lines are detected by Hough Transform. Then, lines that have similar slope are connected into a new line, thus we access continuous harbor edges. Secondary segmentation on the result of the land-and-sea separation, we eventually get the ships. At last, we calculate the aspect ratio of the ROIs, thereby remove those targets which are not ship. The experiment results show that our method has good robustness and can tolerate a certain degree of noise and occlusion.

  11. Lidar Range-Resolved Optical Remote Sensing of the Atmosphere

    CERN Document Server

    Weitkamp, Claus

    2005-01-01

    Written by leading experts in optical radar, or lidar, this book brings all the recent practices up-to-date and covers a multitude of applications, from atmospheric sciences to environmental protection. Its broad cross-disciplinary scope should appeal to both the experienced scientist and the novice in the field. The Foreword is by one of the early pioneers in the area, Herbert Walther.

  12. Deployable large aperture optics system for remote sensing applications.

    Energy Technology Data Exchange (ETDEWEB)

    Sumali, Anton Hartono; Martin, Jeffrey W.; Main, John A. (University of Kentucky, Lexington, KY); Macke, Benjamin T.; Massad, Jordan Elias; Chaplya, Pavel Mikhail

    2004-04-01

    This report summarizes research into effects of electron gun control on piezoelectric polyvinylidene fluoride (PVDF) structures. The experimental apparatus specific to the electron gun control of this structure is detailed, and the equipment developed for the remote examination of the bimorph surface profile is outlined. Experiments conducted to determine the optimum electron beam characteristics for control are summarized. Clearer boundaries on the bimorphs control output capabilities were determined, as was the closed loop response. Further controllability analysis of the bimorph is outlined, and the results are examined. In this research, the bimorph response was tested through a matrix of control inputs of varying current, frequency, and amplitude. Experiments also studied the response to electron gun actuation of piezoelectric bimorph thin film covered with multiple spatial regions of control. Parameter ranges that yielded predictable control under certain circumstances were determined. Research has shown that electron gun control can be used to make macrocontrol and nanocontrol adjustments for PVDF structures. The control response and hysteresis are more linear for a small range of energy levels. Current levels needed for optimum control are established, and the generalized controllability of a PVDF bimorph structure is shown.

  13. Microwave and optical remote sensing of forest vegetation

    Science.gov (United States)

    Hoffer, R. M.; Bauer, M. E.; Biehl, L. L.; Mroczynski, R. P.

    1984-01-01

    The objectives and anticipated results of a study to define the strengths and limitations of microwave (SIR-B) and optical (thematic Mapper) data, singly and in combination, for the purpose of characterizing forest cover types and condition classes are described. Other specific objectives include: (1) the assessment of the effectiveness of a contextual classification algorithm (SECHO); (2) evaluation of the utility of different look angles of SAR data in determining differences in stand density of commercial forests; and (3) the determination of the effectiveness of the L-band HH polarized SIR-B data in differentiating forest-stand densities.

  14. Integrating remote sensing data from multiple optical sensors for ecological and crop condition monitoring

    Science.gov (United States)

    Ecological and crop condition monitoring requires high temporal and spatial resolution remote sensing data. Due to technical limitations and budget constraints, remote sensing instruments trade spatial resolution for swath width. As a result, it is difficult to acquire remotely sensed data with both...

  15. AIRBORNE, OPTICAL REMOTE SENSING OF METHANE AND ETHANE FOR NATURAL GAS PIPELINE LEAK DETECTION

    Energy Technology Data Exchange (ETDEWEB)

    Jerry Myers

    2003-11-12

    Ophir Corporation was awarded a contract by the U. S. Department of Energy, National Energy Technology Laboratory under the Project Title ''Airborne, Optical Remote Sensing of Methane and Ethane for Natural Gas Pipeline Leak Detection'' on October 14, 2002. This second six-month technical report summarizes the progress made towards defining, designing, and developing the hardware and software segments of the airborne, optical remote methane and ethane sensor. The most challenging task to date has been to identify a vendor capable of designing and developing a light source with the appropriate output wavelength and power. This report will document the work that has been done to identify design requirements, and potential vendors for the light source. Significant progress has also been made in characterizing the amount of light return available from a remote target at various distances from the light source. A great deal of time has been spent conducting laboratory and long-optical path target reflectance measurements. This is important since it helps to establish the overall optical output requirements for the sensor. It also reduces the relative uncertainty and risk associated with developing a custom light source. The data gathered from the optical path testing has been translated to the airborne transceiver design in such areas as: fiber coupling, optical detector selection, gas filters, and software analysis. Ophir will next, summarize the design progress of the transceiver hardware and software development. Finally, Ophir will discuss remaining project issues that may impact the success of the project.

  16. Sensor Performance Requirements for the Retrieval of Atmospheric Aerosols by Airborne Optical Remote Sensing.

    Science.gov (United States)

    Seidel, Felix; Schläpfer, Daniel; Nieke, Jens; Itten, Klaus I

    2008-03-18

    This study explores performance requirements for the retrieval of the atmospheric aerosol optical depth (AOD) by airborne optical remote sensing instruments. Independent of any retrieval techniques, the calculated AOD retrieval requirements are compared with the expected performance parameters of the upcoming hyperspectral sensor APEX at the reference wavelength of 550nm. The AOD accuracy requirements are defined to be capable of resolving transmittance differences of 0.01 to 0.04 according to the demands of atmospheric corrections for remote sensing applications. For the purposes of this analysis, the signal at the sensor level is simulated by radiation transfer equations. The resulting radiances are translated into the AOD retrieval sensitivity (Δτλ(aer) ) and compared to the available measuring sensitivity of the sensor (NE ΔLλ(sensor)). This is done for multiple signal-to-noise ratios (SNR) and surface reflectance values. It is shown that an SNR of 100 is adequate for AOD retrieval at 550nm under typical remote sensing conditions and a surface reflectance of 10% or less. Such dark surfaces require the lowest SNR values and therefore offer the best sensitivity for measuring AOD. Brighter surfaces with up to 30% reflectance require an SNR of around 300. It is shown that AOD retrieval for targets above 50% surface reflectance is more problematic with the current sensor performance as it may require an SNR larger than 1000. In general, feasibility is proven for the analyzed cases under simulated conditions.

  17. Modeling the land surface reflectance for optical remote sensing data in rugged terrain

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A model for topographic correction and land surface reflectance estimation for optical remote sensing data in rugged terrian is presented.Considering a directional-directional reflectance that is used for direct solar irradiance correction and a hemispheric-directional reflectance that is used for atmospheric diffuse irradiance and terrain background reflected irradiance correction respectively,the directional reflectance-based model for topographic effects removing and land surface reflectance calculation is developed by deducing the directional reflectance with topographic effects and using a radiative transfer model.A canopy reflectance simulated by GOMS model and Landsat/TM raw data covering Jiangxi rugged area were taken to validate the performance of the model presented in the paper.The validation results show that the model presented here has a remarkable ability to correct topography and estimate land surface reflectance and also provides a technique method for sequently quantitative remote sensing application in terrain area.

  18. Modeling the land surface reflectance for optical remote sensing data in rugged terrain

    Institute of Scientific and Technical Information of China (English)

    WEN JianGuang; LIU QinHuo; XIAO Qing; LIU Qiang; LI XiaoWen

    2008-01-01

    A model for topographic correction and land surface reflectance estimation for optical remote sensing data in rugged terrian is presented. Considering a directional-directional reflectance that is used for direct solar irradiance correction and a hemispheric-directional reflectance that is used for atmospheric diffuse irradiance and terrain background reflected irradiance correction respectively, the directional reflectance-based model for topographic effects removing and land surface reflectance calculation is developed by deducing the directional reflectance with topographic effects and using a radiative transfer model. A canopy reflectance simulated by GOMS model and Landsat/TM raw data covering Jiangxi rugged area were taken to validate the performance of the model presented in the paper. The validation results show that the model presented here has a remarkable ability to correct topography and estimate land surface reflectance and also provides a technique method for sequently quantitative remote sensing application in terrain area.

  19. Biological processes and optical measurements near the sea surface: Some issues relevant to remote sensing

    Science.gov (United States)

    Cullen, John J.; Lewis, Marlon R.

    1995-01-01

    The advent of remote sensing, the develpmemt of new optical instrumentation, and the associated advances in hydrological optics have transformed oceanography; it is now feasible to describe ocean-scale biogeochemical dynamcis from satellite observations, verified and complemented by measurements from optical sensors on profilers, moorings, and drifters. Only near-surface observations are common to both remote sensing and in situ observation, so it is critical to understand processes in the upper euphotic zone. Unfortunately, the biological principles that must be used to interpret optical variability near the sea surface are weaker than we would like, because relatively few experiments and analyses have examined bio-optical relationships under high irradiance characteristic of the upper optical depth. Special consideration of this stratum is justified, because there is good evidence that bio-optical relationships are altered near the surface; (1) the fluorescence yield from chlorophyll declines, leading to bias in the estimation of pigment from fluorometry; (2) the modeled relationship between solar-stimulated fluorecence and photosynthesis seems to deviate significantly from that presented for the lower euphotic zone; and (3) carbon-specific and cellular attenuation cross sections of phytoplankton change substantially during exposures to bright light. Even the measurement of primary productivity is problematic near the sea surface, because vertical mixing is not simulated and artifactual inhibition of photosynthesis can result. These problems can be addressed by focusing more sampling effort, experimental simulation, and analytical consideration on the upper optical depth, and by shortening timescales for the measurement of marine photosynthesis. Special efforts to study near-surface processes are justified, because new bio-optical algorithms will require quantitaitve descriptions of the responses of phytoplankton to bright light.

  20. 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

  1. Image fusion of microwave and optical remote sensing data for topographic map updating in the tropics

    Science.gov (United States)

    Pohl, Christine; van Genderen, John L.

    1995-11-01

    Temporal monitoring using remote sensing for topographic mapping requires continuous acquisition of image data. In many countries, but especially in the human Tropics, the heavy cloud cover is a major drawback for visible and infrared remote sensing. The research project presented in this paper uses the idea of integrating data from optical and microwave sensors using digital image fusion techniques to overcome the cloud cover problem. Additionally the combination of radar with optical data increases the interpretation capabilities and the reliability of the results due to the complementary nature of microwave and optical images. While optical data represents the reflectance of ground cover in visible and near-infrared, the radar is very sensitive to the shape, orientation, roughness and moisture content of the illuminated ground objects. This research investigates the geometric aspect of image fusion for topographic map updating. The paper describes experiences gained from an area in the north of The Netherlands (`Friesland') as calibration test site in comparison with first results from the research test site (`Bengkulu'), located on the south west coast of Sumatra in Indonesia. The data used for this investigated was acquired by SPOT, Landsat, ERS-1 and JERS-1.

  2. 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.

  3. Removing sun glint from optical remote sensing images of shallow rivers

    Science.gov (United States)

    Overstreet, Brandon T.; Legleiter, Carl

    2017-01-01

    Sun glint is the specular reflection of light from the water surface, which often causes unusually bright pixel values that can dominate fluvial remote sensing imagery and obscure the water-leaving radiance signal of interest for mapping bathymetry, bottom type, or water column optical characteristics. Although sun glint is ubiquitous in fluvial remote sensing imagery, river-specific methods for removing sun glint are not yet available. We show that existing sun glint-removal methods developed for multispectral images of marine shallow water environments over-correct shallow portions of fluvial remote sensing imagery resulting in regions of unreliable data along channel margins. We build on existing marine glint-removal methods to develop a river-specific technique that removes sun glint from shallow areas of the channel without overcorrection by accounting for non-negligible water-leaving near-infrared radiance. This new sun glint-removal method can improve the accuracy of spectrally-based depth retrieval in cases where sun glint dominates the at-sensor radiance. For an example image of the gravel-bed Snake River, Wyoming, USA, observed-vs.-predicted R2 values for depth retrieval improved from 0.66 to 0.76 following sun glint removal. The methodology presented here is straightforward to implement and could be incorporated into image processing workflows for multispectral images that include a near-infrared band.

  4. All-Optical Frequency Modulated High Pressure MEMS Sensor for Remote and Distributed Sensing

    DEFF Research Database (Denmark)

    Reck, Kasper; Thomsen, Erik Vilain; Hansen, Ole

    2011-01-01

    a shift in the Bragg wavelength. The simple and robust design combined with the small chip area of 1 × 1.8 mm2 makes the sensor ideally suited for remote and distributed sensing in harsh environments and where miniaturized sensors are required. The sensor is designed for high pressure applications up......We present the design, fabrication and characterization of a new all-optical frequency modulated pressure sensor. Using the tangential strain in a circular membrane, a waveguide with an integrated nanoscale Bragg grating is strained longitudinally proportional to the applied pressure causing...

  5. Classification of Several Optically Complex Waters in China Using in Situ Remote Sensing Reflectance

    Directory of Open Access Journals (Sweden)

    Qian Shen

    2015-11-01

    Full Text Available Determining the dominant optically active substances in water bodies via classification can improve the accuracy of bio-optical and water quality parameters estimated by remote sensing. This study provides four robust centroid sets from in situ remote sensing reflectance (Rrs (λ data presenting typical optical types obtained by plugging different similarity measures into fuzzy c-means (FCM clustering. Four typical types of waters were studied: (1 highly mixed eutrophic waters, with the proportion of absorption of colored dissolved organic matter (CDOM, phytoplankton, and non-living particulate matter at approximately 20%, 20%, and 60% respectively; (2 CDOM-dominated relatively clear waters, with approximately 45% by proportion of CDOM absorption; (3 nonliving solids-dominated waters, with approximately 88% by proportion of absorption of nonliving particulate matter; and (4 cyanobacteria-composed scum. We also simulated spectra from seven ocean color satellite sensors to assess their classification ability. POLarization and Directionality of the Earth's Reflectances (POLDER, Sentinel-2A, and MEdium Resolution Imaging Spectrometer (MERIS were found to perform better than the rest. Further, a classification tree for MERIS, in which the characteristics of Rrs (709/Rrs (681, Rrs (560/Rrs (709, Rrs (560/Rrs (620, and Rrs (709/Rrs (761 are integrated, is also proposed in this paper. The overall accuracy and Kappa coefficient of the proposed classification tree are 76.2% and 0.632, respectively.

  6. AIRBORNE, OPTICAL REMOTE SENSING OF METHANE AND ETHANE FOR NATURAL GAS PIPLINE LEAK DETECTION

    Energy Technology Data Exchange (ETDEWEB)

    Jerry Myers

    2004-05-12

    Ophir Corporation was awarded a contract by the U. S. Department of Energy, National Energy Technology Laboratory under the Project Title ''Airborne, Optical Remote Sensing of Methane and Ethane for Natural Gas Pipeline Leak Detection'' on October 14, 2002. The third six-month technical report contains a summary of the progress made towards finalizing the design and assembling the airborne, remote methane and ethane sensor. The vendor has been chosen and is on contract to develop the light source with the appropriate linewidth and spectral shape to best utilize the Ophir gas correlation software. Ophir has expanded upon the target reflectance testing begun in the previous performance period by replacing the experimental receiving optics with the proposed airborne large aperture telescope, which is theoretically capable of capturing many times more signal return. The data gathered from these tests has shown the importance of optimizing the fiber optic receiving fiber to the receiving optic and has helped Ophir to optimize the design of the gas cells and narrowband optical filters. Finally, Ophir will discuss remaining project issues that may impact the success of the project.

  7. Mapping agricultural phenology using repetitive optical remote sensing over a peri-urban region

    Science.gov (United States)

    Delbart, Nicolas; Vaudour, Emmanuelle; Dragoi, Mihaela; Maignan, Fabienne; Ottlé, Catherine

    2016-04-01

    This study explores the potential of multi-temporal optical remote sensing, with high revisit frequency, to derive missing information on agricultural practices necessary to model soil organic carbon content, over the agricultural lands in the Versailles plain in the western Paris suburbs. This study comes besides past and ongoing studies on the use of radar and high spatial resolution optical remote sensing to monitor agricultural practices in this study area (e.g. Vaudour et al. 2014). Agricultural statistics, such as the Land Parcel Identification System (LPIS) for France, permit to know the nature of annual crops for each digitized declared field of this land parcel registry. However, within each declared field, several cropped plots and a diversity of practices may exist, being marked by agricultural rotations which vary both spatially and temporally within it and differ from one year to the other. Very high spatial resolution Pléiades satellite data has allowed delineating crops plots, and identifying crops within declared fields, revealing this fine spatial crop pattern. Here we evaluate the potential of high observation frequency remote sensing to differentiate seasonal crops (e.g. winter barley from spring barley) and to evaluate key phenological moments. In particular, in addition to a dataset of field observations, we use three datasets at three complementary spatial resolutions: the CNES SPOT4-TAKE5 at ten meters in the 2013 winter and spring, the Landsat data at 30m, and the large-swath PROBA-V central camera data at 100m available since May 2013. The analysis of each dataset is done first on a pixel-based approach and second on a within-plot approach on the basis of the above described crop map. This work is carried out in the framework of the CNES TOSCA-PLEIADES-CO of the French Space Agency.

  8. Sensor Performance Requirements for the Retrieval of Atmospheric Aerosols by Airborne Optical Remote Sensing

    Directory of Open Access Journals (Sweden)

    Klaus I. Itten

    2008-03-01

    Full Text Available This study explores performance requirements for the retrieval of the atmospheric aerosol optical depth (AOD by airborne optical remote sensing instruments. Independent of any retrieval techniques, the calculated AOD retrieval requirements are compared with the expected performance parameters of the upcoming hyperspectral sensor APEX at the reference wavelength of 550nm. The AOD accuracy requirements are defined to be capable of resolving transmittance differences of 0.01 to 0.04 according to the demands of atmospheric corrections for remote sensing applications. For the purposes of this analysis, the signal at the sensor level is simulated by radiation transfer equations. The resulting radiances are translated into the AOD retrieval sensitivity (Δτλaer and compared to the available measuring sensitivity of the sensor (NE ΔLλsensor. This is done for multiple signal-to-noise ratios (SNR and surface reflectance values. It is shown that an SNR of 100 is adequate for AOD retrieval at 550nm under typical remote sensing conditions and a surface reflectance of 10% or less. Such dark surfaces require the lowest SNR values and therefore offer the best sensitivity for measuring AOD. Brighter surfaces with up to 30% reflectance require an SNR of around 300. It is shown that AOD retrieval for targets above 50% surface reflectance is more problematic with the current sensor performance as it may require an SNR larger than 1000. In general, feasibility is proven for the analyzed cases under simulated conditions.

  9. A low-cost large-aperture optical receiver for remote sensing and imaging applications

    Science.gov (United States)

    Hanes, Stephen A.

    2003-03-01

    An inexpensive large aperture (10 m class) receiver for optical wavelength imaging and remote sensing applications is discussed. The design was developed for active (laser illumination) imaging of remote objects using pupil plane measurement techniques, where relatively low optical quality collecting elements can be used. The approach is also well suited for conventional imaging at lower resolutions when light collection capability is of primary importance. The approach relies on a large aperture heliostat consisting of an array of flat mirror segments, like those used in solar collector systems, to collect light from the region of interest. The heliostat segments are tilted in a manner to concentrate the light, by making the light from all segments overlap at a common point, resulting in a region of higher intensity about the size of a segment at the heliostat "focus". A smaller secondary collector, consisting of a concave mirror located at the overlap point, further concentrates the light and forms a pupil image of the heliostat. Additional optics near the pupil image collimate the light for efficient transmission though a narrow band interference filter used to reduce sky background, and focus the light onto a PMT, or other sensor, for detection. Several design approaches for the collimating optics are discussed as well as system performance and limitations.

  10. Flood mapping by combining the strengths of optical and Sentinel active radar remote sensing

    Science.gov (United States)

    Winsemius, H. C.; Brakenridge, G. R.; Westerhoff, R.; Huizinga, J.; Villars, N.; Bishop, C.

    2012-04-01

    Flood mapping with remote sensing plays an important role in large scale disaster management procedures. For this purpose, the Dartmouth Flood Observatory (DFO) gained experience since 1993 with the production of flood maps from optical satellite imagery and has currently established, together with NASA collaborators, a fully automated, global, near real-time service. Another consortium is also presently working on an automated, near real-time, global flood mapping procedure called the 'Global Flood Observatory' (GFO), which will make use of high resolution Sentinel data. The procedure is currently tested on Envisat active radar (ASAR) imagery. Both the DFO and GFO projects provide open data output of their data and maps. The optical and radar approaches to flood mapping each have advantages and suffer from shortcomings. Optical remote sensing via the U.S. MODIS and VIIRS sensors is constrained by cloud cover but can attain a high revisit frequency (>2 /day), whereas the Envisat ASAR is not affected by cloud cover, but uses a lower revisit frequency (generally once/3 days, depending on the location). In this contribution, we demonstrate the combination of both approaches into one flood mapping result. This results in improved flood mapping in a case study over the Chao Phraya basin (Bangkok surroundings) during the recent October-November 2011 extreme flooding. The combined map shows that during overpass, ASAR reveals flooded regions over cloud-obscured areas, which clearly follow elevated features in the landscape such as roads, embankments and railways. Meanwhile, the high frequency of delivery of the optical information ensures timely information. Also, the quite different water classification methods used for the optical and ASAR data sources show good agreement and have been successfully merged into one GIS data product. This can also be automatically generated and disseminated on a global basis.

  11. Assimilation of remotely-sensed optical properties to improve marine biogeochemistry modelling

    Science.gov (United States)

    Ciavatta, Stefano; Torres, Ricardo; Martinez-Vicente, Victor; Smyth, Timothy; Dall'Olmo, Giorgio; Polimene, Luca; Allen, J. Icarus

    2014-09-01

    In this paper we evaluate whether the assimilation of remotely-sensed optical data into a marine ecosystem model improves the simulation of biogeochemistry in a shelf sea. A localized Ensemble Kalman filter was used to assimilate weekly diffuse light attenuation coefficient data, Kd(443) from SeaWiFs, into an ecosystem model of the western English Channel. The spatial distributions of (unassimilated) surface chlorophyll from satellite, and a multivariate time series of eighteen biogeochemical and optical variables measured in situ at one long-term monitoring site were used to evaluate the system performance for the year 2006. Assimilation reduced the root mean square error and improved the correlation with the assimilated Kd(443) observations, for both the analysis and, to a lesser extent, the forecast estimates, when compared to the reference model simulation. Improvements in the simulation of (unassimilated) ocean colour chlorophyll were less evident, and in some parts of the Channel the simulation of this data deteriorated. The estimation errors for the (unassimilated) in situ data were reduced for most variables with some exceptions, e.g. dissolved nitrogen. Importantly, the assimilation adjusted the balance of ecosystem processes by shifting the simulated food web towards the microbial loop, thus improving the estimation of some properties, e.g. total particulate carbon. Assimilation of Kd(443) outperformed a comparative chlorophyll assimilation experiment, in both the estimation of ocean colour data and in the simulation of independent in situ data. These results are related to relatively low error in Kd(443) data, and because it is a bulk optical property of marine ecosystems. Assimilation of remotely-sensed optical properties is a promising approach to improve the simulation of biogeochemical and optical variables that are relevant for ecosystem functioning and climate change studies.

  12. Remote sensing of atmospheric properties with the Modular Optical Scanner (MOS)

    Science.gov (United States)

    Krawczyk, Harald; Pflug, Bringfried M.; Gerasch, Birgit

    1998-12-01

    Satellite remote sensing of atmospheric properties is important for investigation of atmospheric pollution and also for remote sensing of the underlying surface, where an atmospheric correction is needed. For the proof of new methodological concepts the multispectral imaging spectrometer MOS was developed in the DLR Institute of Space Sensor Technology and launched on the Indian satellite IRS- P3. It has 13 bands in the VIS/NIR region with 10nm bandwidth. MOS successfully provides data for more than 2 years over European and Northern African coasts. The paper will introduce a standard atmospheric correction scheme for MOS data over water regions using measurements in the near IR form 685 nm to 1000 nm. This method is based on a 2- channel correction, estimating the aerosol optical depth and the Angstrom coefficient for the spectral behavior of the optical thickness. After extrapolation of the visible region the atmospheric correction is applied. Examples will be shown from the Baltic and North Sea regions. The obtained result will be compared and discussed with available in situ measurements taken simultaneously with MOS overflights. Lastly, this algorithm is applied to an observation of forest fire smoke over Malaysia.

  13. Ship Detection and Classification on Optical Remote Sensing Images Using Deep Learning

    Directory of Open Access Journals (Sweden)

    Liu Ying

    2017-01-01

    Full Text Available Ship detection and classification is critical for national maritime security and national defense. Although some SAR (Synthetic Aperture Radar image-based ship detection approaches have been proposed and used, they are not able to satisfy the requirement of real-world applications as the number of SAR sensors is limited, the resolution is low, and the revisit cycle is long. As massive optical remote sensing images of high resolution are available, ship detection and classification on theses images is becoming a promising technique, and has attracted great attention on applications including maritime security and traffic control. Some digital image processing methods have been proposed to detect ships in optical remote sensing images, but most of them face difficulty in terms of accuracy, performance and complexity. Recently, an autoencoder-based deep neural network with extreme learning machine was proposed, but it cannot meet the requirement of real-world applications as it only works with simple and small-scaled data sets. Therefore, in this paper, we propose a novel ship detection and classification approach which utilizes deep convolutional neural network (CNN as the ship classifier. The performance of our proposed ship detection and classification approach was evaluated on a set of images downloaded from Google Earth at the resolution 0.5m. 99% detection accuracy and 95% classification accuracy were achieved. In model training, 75× speedup is achieved on 1 Nvidia Titanx GPU.

  14. Advances in estimation methods of vegetation water content based on optical remote sensing techniques

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Quantitative estimation of vegetation water content(VWC) using optical remote sensing techniques is helpful in forest fire as-sessment,agricultural drought monitoring and crop yield estimation.This paper reviews the research advances of VWC retrieval using spectral reflectance,spectral water index and radiative transfer model(RTM) methods.It also evaluates the reli-ability of VWC estimation using spectral water index from the observation data and the RTM.Focusing on two main definitions of VWC-the fuel moisture content(FMC) and the equivalent water thickness(EWT),the retrieval accuracies of FMC and EWT using vegetation water indices are analyzed.Moreover,the measured information and the dataset are used to estimate VWC,the results show there are significant correlations among three kinds of vegetation water indices(i.e.,WSI,NDⅡ,NDWI1640,WI/NDVI) and canopy FMC of winter wheat(n=45).Finally,the future development directions of VWC detection based on optical remote sensing techniques are also summarized.

  15. Research on estimation crop planting area by integrating the optical and microwave remote sensing data

    Science.gov (United States)

    Liu, Jiang; Yu, Fan; Liu, Dandan; Tian, Jing; Zhang, Weicheng; Wang, Qiang; Yang, Jinling; Zhang, Lei

    2015-12-01

    Considering the problem in monitoring agricultural condition in the semi-arid areas of Northwest of China, we propose a new method for estimation of crop planting area, using the single phase optical and microwave remote sensing data collaboratively, which have demonstrated their respective advantages in the extraction of surface features. In the model, the ASAR backscatter coefficient is normalized by the incident angle at first, then the classifier based on Bayesian network is developed, and the VV, VH polarization of ASAR and all the 7 TM bands are taken as the input of the classifier to get the class labels of each pixel of the images. Moreover the crop planting areas can be extracted by the classification results. At last, the model is validated for the necessities of normalization by the incident angle and integration of TM and ASAR respectively. It results that the estimation accuracy of crop planting area of corn and other crops garden are 98.47% and 78.25% respectively using the proposed method, with an improvement of estimation accuracy of about 3.28% and 4.18% relative to single TM classification. These illustrate that synthesis of optical and microwave remote sensing data is efficient and potential in estimation crop planting area.

  16. Optical Remote Sensing Measurements of Air Pollution in Mexico City During MCMA- 2006

    Science.gov (United States)

    Galle, B.; Mellqvist, J.; Johansson, M.; Rivera, C.; Samuelsson, J.; Zhang, Y.

    2007-05-01

    During March 2006 the Optical Remote sensing group at Chalmers University of Technology participated in the MCMA-2006 field campaign in Mexico City, performing measurements of air pollution using a set of different optical remote sensing instruments. This poster gives an overview of the techniques applied and results obtained. The techniques applied were: Solar Occultation FTIR and UV spectroscopy from fixed locations throughout the MCMA area, yielding total columns of CO, CH2O, SO2 and NO2. Long Path FTIR measurements from site T0 located in the north part of central Mexico City. With this instrument line-averaged concentration measurements of CO and CO2 was obtained in parallel with DOAS measurements performed by other partners. MAX-DOAS measurements from site T0, yielding total column and spatial distributions of SO2 and NO2. Mobile DOAS scattered Sunlight measurements of total columns of SO2 and NO2 in and around the MCMA area. Mobile and stationary DOAS measurements in the vicinity of Tula and Popocatépetl in order to quantify emissions from industry and volcano.

  17. 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

  18. Development and processing of hyperspectral images in optical-electronic remote sensing systems

    Science.gov (United States)

    Kozinov, I. A.; Maltsev, G. N.

    2016-12-01

    The development and processing of three-dimensional images as a "hypercube" of spectral data in hyperspectral optical-electronic remote sensing systems are described in a formalized manner. The correlation identification of observed objects on the basis of spectral features is considered. The criterion for determining of similarity between vectors of recorded and reference spectral images of objects is based on their cross-correlation. Taking into the fact that the total spectral data array recorded by currently applicable hyperspectrometers is excessive for the solution of many issues related to remote sensing of the Earth, this paper proposes a method making it possible to reduce spectral data redundancy by selection of the most informative spectral channels. The essential dimension of the spectral data makes it possible to solve issues related to identification and classification of objects by spectral features through a limited number of very informative spectral channels selected in the areas where the function describing a spectral image of the observed object undergoes well-defined changes in behavior. The algorithm for selection of the most informative spectral channels, which is based on the determination of jump coordinates (major changes) of a spectral image, is substantiated. The selected channels meet the maximum likelihood criterion. The obtained experimental research data on object identification quality with involvement of real hyperspectral data of aerospace Earth remote sensing systems are reported. Five to twenty spectral readouts are needed to provide identification by a limited number of very informative spectral channels. This confirms the idea of existing essential dimensionality of the spectral data.

  19. Cereal Yield Modeling in Finland Using Optical and Radar Remote Sensing

    Directory of Open Access Journals (Sweden)

    Jouko Kleemola

    2010-09-01

    Full Text Available During 1996–2006, the Ministry of Agriculture and Forestry in Finland (MAFF, MTT Agrifood Research and the Finnish Geodetic Institute performed a joint remote sensing satellite research project. It evaluated the applicability of optical satellite (Landsat, SPOT data for cereal yield estimations in the annual crop inventory program. Four Optical Vegetation Indices models (I: Infrared polynomial, II: NDVI, III: GEMI, IV: PARND/FAPAR were validated to estimate cereal baseline yield levels (yb using solely optical harmonized satellite data (Optical Minimum Dataset. The optimized Model II (NDVI yb level was 4,240 kg/ha (R2 0.73, RMSE 297 kg/ha for wheat and 4390 kg/ha (R2 0.61, RMSE 449 kg/ha for barley and Model I yb was 3,480 kg/ha for oats (R2 0.76, RMSE 258 kg/ha. Optical VGI yield estimates were validated with CropWatN crop model yield estimates using SPOT and NOAA data (mean R2 0.71, RMSE 436 kg/ha and with composite SAR/ASAR and NDVI models (mean R2 0.61, RMSE 402 kg/ha using both reflectance and backscattering data. CropWatN and Composite SAR/ASAR & NDVI model mean yields were 4,754/4,170 kg/ha for wheat, 4,192/3,848 kg/ha for barley and 4,992/2,935 kg/ha for oats.

  20. Integrating SAR with Optical and Thermal Remote Sensing for Operational Near Real-Time Volcano Monitoring

    Science.gov (United States)

    Meyer, F. J.; Webley, P.; Dehn, J.; Arko, S. A.; McAlpin, D. B.

    2013-12-01

    Volcanic eruptions are among the most significant hazards to human society, capable of triggering natural disasters on regional to global scales. In the last decade, remote sensing techniques have become established in operational forecasting, monitoring, and managing of volcanic hazards. Monitoring organizations, like the Alaska Volcano Observatory (AVO), are nowadays heavily relying on remote sensing data from a variety of optical and thermal sensors to provide time-critical hazard information. Despite the high utilization of these remote sensing data to detect and monitor volcanic eruptions, the presence of clouds and a dependence on solar illumination often limit their impact on decision making processes. Synthetic Aperture Radar (SAR) systems are widely believed to be superior to optical sensors in operational monitoring situations, due to the weather and illumination independence of their observations and the sensitivity of SAR to surface changes and deformation. Despite these benefits, the contributions of SAR to operational volcano monitoring have been limited in the past due to (1) high SAR data costs, (2) traditionally long data processing times, and (3) the low temporal sampling frequencies inherent to most SAR systems. In this study, we present improved data access, data processing, and data integration techniques that mitigate some of the above mentioned limitations and allow, for the first time, a meaningful integration of SAR into operational volcano monitoring systems. We will introduce a new database interface that was developed in cooperation with the Alaska Satellite Facility (ASF) and allows for rapid and seamless data access to all of ASF's SAR data holdings. We will also present processing techniques that improve the temporal frequency with which hazard-related products can be produced. These techniques take advantage of modern signal processing technology as well as new radiometric normalization schemes, both enabling the combination of

  1. 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.

  2. In-shore ship extraction from HR optical remote sensing image via salience structure and GIS information

    Science.gov (United States)

    Ren, Xiaoyuan; Jiang, Libing; Tang, Xiao-an

    2015-12-01

    In order to solve the problem of in-shore ship extraction from remote sensing image, a novel method for in-shore ship extraction from high resolution (HR) optical remote sensing image is proposed via salience structure feature and GIS information. Firstly, the berth ROI is located in the image with the aid of the prior GIS auxiliary information. Secondly, the salient corner features at ship bow are extracted from the berth ROI precisely. Finally, a recursive algorithm concerning the symmetric geometry of the ship target is conducted to discriminate the multi docked in-shore targets into mono in-shore ships. The results of the experiments show that the method proposed in this paper can detect the majority of large and medium scale in-shore ships from the optical remote sensing image, including both the mono and the multi adjacent docked in-shore ship cases.

  3. Optical properties of algal blooms in an eutrophicated coastal area and its relevance to remote sensing

    Science.gov (United States)

    Astoreca, Rosa; Rousseau, Veronique; Ruddick, Kevin; Van Mol, Barbara; Parent, Jean-Yves; Lancelot, Christiane

    2005-08-01

    The Southern Bight of the North Sea is characterised by a large influence of river inputs, which results in eutrophication of the area. High concentrations of plankton biomass and suspended matter have been reported for this area, in relation with blooms of different species and resuspension of bottom sediments. In spring the haptophyte Phaeocystis globosa blooms throughout the area reaching up to 30 mg Chlorophyll m-3 or more nearshore. This event is followed in June by red tides of the dinoflagellate Noctiluca scintillans. These blooms are concurrent with different species of diatoms. The strong optical signature of these blooms is clear to human observers making them potentially detectable in satellite imagery. As a first step in this direction, sampling has been carried out in the area, during Phaeocystis and Noctiluca blooms in 2003 and 2004. Phytoplankton pigments and inherent optical properties (particle, detrital and phytoplankton absorption) have been measured spectrophotometrically, and in situ using an ac-9 for total absorption and particle scattering. Field data were compared with optical properties of pure species obtained in laboratory. In parallel, water-leaving reflectance has been also measured. In this paper we characterise the optical signatures of diatoms, Phaeocystis and Noctiluca and their contribution to total absorption. The impact on water-leaving reflectance spectra is evaluated; in order to assess the conditions in which remote sensing can provide information for monitoring the timing, extent and magnitude of blooms in this coastal area.

  4. AIRBORNE, OPTICAL REMOTE SENSING OF METHANE AND ETHANE FOR NATURAL GAS PIPELINE LEAK DETECTION

    Energy Technology Data Exchange (ETDEWEB)

    Jerry Myers

    2003-05-13

    Ophir Corporation was awarded a contract by the U. S. Department of Energy, National Energy Technology Laboratory under the Project Title ''Airborne, Optical Remote Sensing of Methane and Ethane for Natural Gas Pipeline Leak Detection'' on October 14, 2002. This six-month technical report summarizes the progress for each of the proposed tasks, discusses project concerns, and outlines near-term goals. Ophir has completed a data survey of two major natural gas pipeline companies on the design requirements for an airborne, optical remote sensor. The results of this survey are disclosed in this report. A substantial amount of time was spent on modeling the expected optical signal at the receiver at different absorption wavelengths, and determining the impact of noise sources such as solar background, signal shot noise, and electronic noise on methane and ethane gas detection. Based upon the signal to noise modeling and industry input, Ophir finalized the design requirements for the airborne sensor, and released the critical sensor light source design requirements to qualified vendors. Responses from the vendors indicated that the light source was not commercially available, and will require a research and development effort to produce. Three vendors have responded positively with proposed design solutions. Ophir has decided to conduct short path optical laboratory experiments to verify the existence of methane and absorption at the specified wavelength, prior to proceeding with the light source selection. Techniques to eliminate common mode noise were also evaluated during the laboratory tests. Finally, Ophir has included a summary of the potential concerns for project success and has established future goals.

  5. An Optical Model for Estimating the Underwater Light Field from Remote Sensing

    Science.gov (United States)

    Liu, Cheng-Chien; Miller, Richard L.

    2002-01-01

    A model of the wavelength-integrated scalar irradiance for a vertically homogeneous water column is developed. It runs twenty thousand times faster than simulations obtained using full Hydrolight code and limits the percentage error to less than 3.7%. Both the distribution of incident sky radiance and a wind-roughened surface are integrated in the model. Our model removes common limitations of earlier models and can be applied to waters with any composition of the inherent optical properties. Implementation of this new model, as well as the ancillary information required for processing global-scale satellite data, is discussed. This new model is fast, accurate, and flexible and therefore provides important information of the underwater light field from remote sensing.

  6. 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...

  7. Structured nonlinear optical materials for LIDAR-based remote sensing Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This NASA Phase II STTR effort will develop domain-engineered magnesium oxide doped lithium niobate (MgO:LN) for LIDAR-based remote sensing and communication...

  8. Vegetation structure from quantitative fusion of hyperspectral optical and radar interferometric remote sensing

    Science.gov (United States)

    Asner, G. P.; Treuhaft, R. N.; Law, B. E.

    2000-01-01

    One of today's principle objecdtives of remote sensing is carbon accounting in the world's forests via biomass monitoring. Determining carbon sequestration by forest ecosystems requires understanding the carbon budgets of these ecosystems.

  9. A review of the application of optical and radar remote sensing data fusion to land use mapping and monitoring

    NARCIS (Netherlands)

    Joshi, Neha; Baumann, Matthias; Ehammer, Andrea; Reiche, Johannes

    2016-01-01

    The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral

  10. A Method to Analyze the Potential of Optical Remote Sensing for Benthic Habitat Mapping

    Directory of Open Access Journals (Sweden)

    Rodrigo A. Garcia

    2015-10-01

    Full Text Available Quantifying the number and type of benthic classes that are able to be spectrally identified in shallow water remote sensing is important in understanding its potential for habitat mapping. Factors that impact the effectiveness of shallow water habitat mapping include water column turbidity, depth, sensor and environmental noise, spectral resolution of the sensor and spectral variability of the benthic classes. In this paper, we present a simple hierarchical clustering method coupled with a shallow water forward model to generate water-column specific spectral libraries. This technique requires no prior decision on the number of classes to output: the resultant classes are optically separable above the spectral noise introduced by the sensor, image based radiometric corrections, the benthos’ natural spectral variability and the attenuating properties of a variable water column at depth. The modeling reveals the effect reducing the spectral resolution has on the number and type of classes that are optically distinct. We illustrate the potential of this clustering algorithm in an analysis of the conditions, including clustering accuracy, sensor spectral resolution and water column optical properties and depth that enabled the spectral distinction of the seagrass Amphibolis antartica from benthic algae.

  11. Large range rotation distortion measurement for remote sensing images based on volume holographic optical correlator

    Science.gov (United States)

    Zheng, Tianxiang; Cao, Liangcai; Zhao, Tian; He, Qingsheng; Jin, Guofan

    2012-10-01

    Volume holographic optical correlator can compute the correlation results between images at a super-high speed. In the application of remote imaging processing such as scene matching, 6,000 template images have been angularly multiplexed in the photorefractive crystal and the 6,000 parallel processing channels are achieved. In order to detect the correlation pattern of images precisely and distinguishingly, an on-off pixel inverted technology of images is proposed. It can fully use the CCD's linear range for detection and expand the normalized correlation value differences as the target image rotates. Due to the natural characteristics of the remote sensing images, the statistical formulas between the rotation distortions and the correlation results can be estimated. The rotation distortion components can be estimated by curve fitting method with the data of correlation results. The intensities of the correlation spots are related to the distortion between the two images. The rotation distortion could be derived from the intensities in the post processing procedure. With 18 rotations of the input image and sending them into the volume holographic system, the detection of the rotation variation in the range of 180° can be fulfilled. So the large range rotation distortion detection is firstly realized. It offers a fast, large range rotation measurement method for image distortions.

  12. Ultra-fast coherent optical system for active remote sensing applications

    Science.gov (United States)

    Datta, Shubhashish; Becker, Don; Joshi, Abhay; Howard, Roy

    2008-04-01

    Active optical remote sensing has numerous applications including battlefield target recognition and tracking, atmospheric monitoring, structural monitoring, collision avoidance systems, and terrestrial mapping. The maximum propagation distance in LIDAR sensors is limited by the signal attenuation. Sensor range could be improved by increasing the transmitted pulse energy, at the expense of reduced resolution and information bandwidth. Coherent detection can operate at low optical power levels without sacrificing sensor bandwidth. Utilizing a high power LO laser to increase the receiver gain, coherent systems provide shot noise-limited gain thereby increasing the sensing range. To fully exploit high LO powers without incurring performance penalties due to the RIN of the LO, high power handling balanced photodiodes are used. The coherent system has superior dynamic range, bandwidth, and noise performance than small-signal APD-based systems. Coherent detection is a linear process that is sensitive to the amplitude, phase and polarization of the received signal. Therefore, Doppler shifts and vibration signatures can be easily recovered. RF adaptive filtering following photodetection enables channel equalization, atmospheric turbulence compensation, and efficient background light filtering. We demonstrate a coherent optical transmission system using 15mA high power handling balanced photodetectors. This system has an IF linewidth <1Hz, employing a proprietary phase locked loop design. Data is presented for 100ps pulsed transmission. We have demonstrated amplitude and phase modulated 10Gb/s communication links with sensitivities of 132 and 72 photons per bit respectively. Investigations into system performance in the presence of laboratory induced atmospheric turbulence are shown.

  13. Analysis of Spectral Characteristics Based on Optical Remote Sensing and SAR Image Fusion

    Institute of Scientific and Technical Information of China (English)

    Weiguo LI; Nan JIANG; Guangxiu GE

    2014-01-01

    Because of cloudy and rainy weather in south China, optical remote sens-ing images often can't be obtained easily. With the regional trial results in Baoying, Jiangsu province, this paper explored the fusion model and effect of ENVISAT/SAR and HJ-1A satel ite multispectral remote sensing images. Based on the ARSIS strat-egy, using the wavelet transform and the Interaction between the Band Structure Model (IBSM), the research progressed the ENVISAT satel ite SAR and the HJ-1A satel ite CCD images wavelet decomposition, and low/high frequency coefficient re-construction, and obtained the fusion images through the inverse wavelet transform. In the light of low and high-frequency images have different characteristics in differ-ent areas, different fusion rules which can enhance the integration process of self-adaptive were taken, with comparisons with the PCA transformation, IHS transfor-mation and other traditional methods by subjective and the corresponding quantita-tive evaluation. Furthermore, the research extracted the bands and NDVI values around the fusion with GPS samples, analyzed and explained the fusion effect. The results showed that the spectral distortion of wavelet fusion, IHS transform, PCA transform images was 0.101 6, 0.326 1 and 1.277 2, respectively and entropy was 14.701 5, 11.899 3 and 13.229 3, respectively, the wavelet fusion is the highest. The method of wavelet maintained good spectral capability, and visual effects while improved the spatial resolution, the information interpretation effect was much better than other two methods.

  14. Toward Aboveground Biomass Estimation with RADAR, Lidar and Optical Remote Sensing Data in Southern Mexico

    Science.gov (United States)

    Urbazaev, M.; Thiel, C. J.; Schmullius, C.

    2014-12-01

    Information on the spatial distribution of aboveground biomass (AGB) over large areas is needed (1) for understanding and managing the processes involved in the carbon cycle, and (2) supporting international policies for climate change mitigation and adaption. Using remote sensing techniques it is possible to provide spatially explicit information of AGB from local to global scales. In this work we present the first results on the use of multi-sensor remote sensing data to estimate AGB over three test sites in southern Mexico. In order to develop a set of AGB retrieval algorithms, we firstly compared different SAR parameters (e.g. multi-polarized backscatter intensities and interferometric coherence) obtained from ALOS PALSAR sensor and Landsat imagery with field-based AGB estimates using empirical regressions and analyzed the relationships between them. The next steps of the work will be development of a two-stage up-scaling approach: firstly, to enlarge the cal/val data, we propose to estimate AGB along airborne LiDAR (from G-LiHT sensor) transects using field-based AGB and LiDAR height metrics. With LiDAR-based AGB we will then calibrate SAR parameters in a non-parametric model (e.g., randomForest) to create AGB maps over the study areas. An overall aim of the study is the analysis of capabilities and limitations of SAR data for AGB mapping and the investigation of the potential synergistic use of SAR, LiDAR and optical systems.The proposed monitoring tool will facilitate quantitative estimations in loss of carbon storage and support the selection of terrestrial (e.g. tropical dry forests, shrublands) sites for conservation priorities with high value for the national carbon budget.

  15. Influences of Atmospheric Turbulence on Image Resolution of Airborne and Space-Borne Optical Remote Sensing System

    Institute of Scientific and Technical Information of China (English)

    ZHANG Xiao-fang; YU Xin; YAN Ji-xiang

    2006-01-01

    A new way is proposed to evaluate the influence of atmospheric turbulence on image resolution of airborne and space-borne optical remote sensing system, which is called as arrival angle-method. Applying this method, some engineering examples are selected to analyze the turbulence influences on image resolution based on three different atmospheric turbulence models quantificationally, for the air borne remote sensing system, the resolution errors caused by the atmospheric turbulence are less than 1cm, and for the space-borne remote sensing system, the errors are around 1cm. The results are similar to that obtained by the previous Fried-method. Compared with the Fried-method, the arrival angle-method is rather simple and can be easily used in engineering fields.

  16. 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.

  17. Ce-doped SiO2 optical fibers for remote radiation sensing and measurement

    Science.gov (United States)

    Chiodini, Norberto; Vedda, Anna; Fasoli, Mauro; Moretti, Federico; Lauria, Alessandro; Cantone, Marie Claire; Veronese, Ivan; Tosi, Giampiero; Brambilla, Marco; Cannillo, Barbara; Mones, Eleonora; Brambilla, Gilberto; Petrovich, Marco

    2009-05-01

    Scintillating materials, able to convert energy of ionizing radiation into light in the visible-UV interval, are presently used in a wide class of applications such as medical imaging, industrial inspection, security controls and high energy physics detectors. In the last few years we studied and developed a new radiation sensor based on silica-glass fiber-optic technology. In its simplest configuration such device is composed by a short portion (about 10 mm) of scintillating fiber coupled to a photomultiplier through a suitably long passive silica fiber. In this work, we present new results concerning the characterization of silica based Ce and Eu doped fibers glasses obtained by a modified sol-gel method and drawn by a conventional drawing tower for optical fibers. The radio-luminescence of Eu doped fibers is rather weak; moreover it displays a marked sensitivity increase during subsequent irradiations, preventing the use of such fibers in dosimetry. On the other hand Ce-doped fibers show very high radiation hardness, signal stability and reproducibility, and high sensitivity to radiations with energies from 10 keV to several tens of MeV. Numerous tests with photons (X and gamma rays), electrons, and protons have already been successfully performed. At the early stage of its market introduction it is the smallest radiation sensor, also compared to MOSFET and diode technology and it appears to be the ideal choice for in vivo measurements in medical field or remote sensing.

  18. Multilayer Markov Random Field models for change detection in optical remote sensing images

    Science.gov (United States)

    Benedek, Csaba; Shadaydeh, Maha; Kato, Zoltan; Szirányi, Tamás; Zerubia, Josiane

    2015-09-01

    In this paper, we give a comparative study on three Multilayer Markov Random Field (MRF) based solutions proposed for change detection in optical remote sensing images, called Multicue MRF, Conditional Mixed Markov model, and Fusion MRF. Our purposes are twofold. On one hand, we highlight the significance of the focused model family and we set them against various state-of-the-art approaches through a thematic analysis and quantitative tests. We discuss the advantages and drawbacks of class comparison vs. direct approaches, usage of training data, various targeted application fields and different ways of Ground Truth generation, meantime informing the Reader in which roles the Multilayer MRFs can be efficiently applied. On the other hand we also emphasize the differences between the three focused models at various levels, considering the model structures, feature extraction, layer interpretation, change concept definition, parameter tuning and performance. We provide qualitative and quantitative comparison results using principally a publicly available change detection database which contains aerial image pairs and Ground Truth change masks. We conclude that the discussed models are competitive against alternative state-of-the-art solutions, if one uses them as pre-processing filters in multitemporal optical image analysis. In addition, they cover together a large range of applications, considering the different usage options of the three approaches.

  19. Spatial distribution of soil water content from airborne thermal and optical remote sensing data

    Science.gov (United States)

    Richter, Katja; Palladino, Mario; Vuolo, Francesco; Dini, Luigi; D'Urso, Guido

    2009-09-01

    Spatial and temporal information of soil water content is of essential importance for modelling of land surface processes in hydrological studies and applications for operative systems of irrigation management. In the last decades, several remote sensing domains have been considered in the context of soil water content monitoring, ranging from active and passive microwave to optical and thermal spectral bands. In the framework of an experimental campaign in Southern Italy in 2007, two innovative methodologies to retrieve soil water content information from airborne earth observation (E.O.) data were exploited: a) analyses of the dependence of surface temperature of vegetation with soil water content using thermal infrared radiometer (TIR), and b) estimation of superficial soil moisture content using reflectance in the visible and near infrared regions acquired from optical sensors. The first method (a) is applicable especially at surfaces completely covered with vegetation, whereas the second method is preferably applicable at surfaces without or with sparse vegetation. The synergy of both methods allows the establishment of maps of spatially distributed soil water content. Results of the analyses are presented and discussed, in particular in view of an operative context in irrigation studies.

  20. The Inylchek Glacier in Kyrgyzstan, Central Asia: Insight on Surface Kinematics from Optical Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Mohamad Nobakht

    2014-01-01

    Full Text Available Mountain chains of Central Asia host a large number of glaciated areas that provide critical water supplies to the semi-arid populated foothills and lowlands of this region. Spatio-temporal variations of glacier flows are a key indicator of the impact of climate change on water resources as the glaciers react sensitively to climate. Satellite remote sensing using optical imagery is an efficient method for studying ice-velocity fields on mountain glaciers. In this study, temporal and spatial changes in surface velocity associated with the Inylchek glacier in Kyrgyzstan are investigated. We present a detailed map for the kinematics of the Inylchek glacier obtained by cross-correlation analysis of Landsat images, acquired between 2000 and 2011, and a set of ASTER images covering the time period between 2001 and 2007. Our results indicate a high-velocity region in the elevated part of the glacier, moving up to a rate of about 0.5 m/day. Time series analysis of optical data reveals some annual variations in the mean surface velocity of the Inylchek during 2000–2011. In particular, our findings suggest an opposite trend between periods of the northward glacial flow in Proletarskyi and Zvezdochka glacier, and the rate of westward motion observed for the main stream of the Inylchek.

  1. OPUS: A Comprehensive Search Tool for Remote Sensing Observations of the Outer Planets. Now with Enhanced Geometric Metadata for Cassini and New Horizons Optical Remote Sensing Instruments.

    Science.gov (United States)

    Gordon, M. K.; Showalter, M. R.; Ballard, L.; Tiscareno, M.; French, R. S.; Olson, D.

    2017-06-01

    The PDS RMS Node hosts OPUS - an accurate, comprehensive search tool for spacecraft remote sensing observations. OPUS supports Cassini: CIRS, ISS, UVIS, VIMS; New Horizons: LORRI, MVIC; Galileo SSI; Voyager ISS; and Hubble: ACS, STIS, WFC3, WFPC2.

  2. 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.

  3. Optical Remote Sensing of Glacier Characteristics: A Review with Focus on the Himalaya

    Directory of Open Access Journals (Sweden)

    Roger G. Barry

    2008-05-01

    Full Text Available The increased availability of remote sensing platforms with appropriate spatial and temporal resolution, global coverage and low financial costs allows for fast, semi-automated, and cost-effective estimates of changes in glacier parameters over large areas. Remote sensing approaches allow for regular monitoring of the properties of alpine glaciers such as ice extent, terminus position, volume and surface elevation, from which glacier mass balance can be inferred. Such methods are particularly useful in remote areas with limited field-based glaciological measurements. This paper reviews advances in the use of visible and infrared remote sensing combined with field methods for estimating glacier parameters, with emphasis on volume/area changes and glacier mass balance. The focus is on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER sensor and its applicability for monitoring Himalayan glaciers. The methods reviewed are: volumetric changes inferred from digital elevation models (DEMs, glacier delineation algorithms from multi-spectral analysis, changes in glacier area at decadal time scales, and AAR/ELA methods used to calculate yearly mass balances. The current limitations and on-going challenges in using remote sensing for mapping characteristics of mountain glaciers also discussed, specifically in the context of the Himalaya.

  4. 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

  5. Extractive sampling and optical remote sensing of F100 aircraft engine emissions.

    Science.gov (United States)

    Cowen, Kenneth; Goodwin, Bradley; Joseph, Darrell; Tefend, Matthew; Satola, Jan; Kagann, Robert; Hashmonay, Ram; Spicer, Chester; Holdren, Michael; Mayfield, Howard

    2009-05-01

    The Strategic Environmental Research and Development Program (SERDP) has initiated several programs to develop and evaluate techniques to characterize emissions from military aircraft to meet increasingly stringent regulatory requirements. This paper describes the results of a recent field study using extractive and optical remote sensing (ORS) techniques to measure emissions from six F-15 fighter aircraft. Testing was performed between November 14 and 16, 2006 on the trim-pad facility at Tyndall Air Force Base in Panama City, FL. Measurements were made on eight different F100 engines, and the engines were tested on-wing of in-use aircraft. A total of 39 test runs were performed at engine power levels that ranged from idle to military power. The approach adopted for these tests involved extractive sampling with collocated ORS measurements at a distance of approximately 20-25 nozzle diameters downstream of the engine exit plane. The emission indices calculated for carbon dioxide, carbon monoxide, nitric oxide, and several volatile organic compounds showed very good agreement when comparing the extractive and ORS sampling methods.

  6. Forest above Ground Biomass Inversion by Fusing GLAS with Optical Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Xiaohuan Xi

    2016-03-01

    Full Text Available Forest biomass is an important parameter for quantifying and understanding biological and physical processes on the Earth’s surface. Rapid, reliable, and objective estimations of forest biomass are essential to terrestrial ecosystem research. The Geoscience Laser Altimeter System (GLAS produced substantial scientific data for detecting the vegetation structure at the footprint level. This study combined GLAS data with MODIS/BRDF (Bidirectional Reflectance Distribution Function and ASTER GDEM data to estimate forest aboveground biomass (AGB in Xishuangbanna, Yunnan Province, China. The GLAS waveform characteristic parameters were extracted using the wavelet method. The ASTER DEM was used to compute the terrain index for reducing the topographic influence on the GLAS canopy height estimation. A neural network method was applied to assimilate the MODIS BRDF data with the canopy heights for estimating continuous forest heights. Forest leaf area indices (LAIs were derived from Landsat TM imagery. A series of biomass estimation models were developed and validated using regression analyses between field-estimated biomass, canopy height, and LAI. The GLAS-derived canopy heights in Xishuangbanna correlated well with the field-estimated AGB (R2 = 0.61, RMSE = 52.79 Mg/ha. Combining the GLAS estimated canopy heights and LAI yielded a stronger correlation with the field-estimated AGB (R2 = 0.73, RMSE = 38.20 Mg/ha, which indicates that the accuracy of the estimated biomass in complex terrains can be improved significantly by integrating GLAS and optical remote sensing data.

  7. Retrieval and Validation of Aerosol Optical Depth by using the GF-1 Remote Sensing Data

    Science.gov (United States)

    Zhang, L.; Xu, S.; Wang, L.; Cai, K.; Ge, Q.

    2017-05-01

    Based on the characteristics of GF-1 remote sensing data, the method and data processing procedure to retrieve the Aerosol Optical Depth (AOD) are developed in this study. The surface contribution over dense vegetation and urban bright target areas are respectively removed by using the dark target and deep blue algorithms. Our method is applied for the three serious polluted Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions. The retrieved AOD are validated by ground-based AERONET data from Beijing, Hangzhou, Hong Kong sites. Our results show that, 1) the heavy aerosol loadings are usually distributed in high industrial emission and dense populated cities, with the AOD value near 1. 2) There is a good agreement between satellite-retrievals and in-site observations, with the coefficient factors of 0.71 (BTH), 0.55 (YRD) and 0.54(PRD). 3) The GF-1 retrieval uncertainties are mainly from the impact of cloud contamination, high surface reflectance and assumed aerosol model.

  8. Measurement of Oil and Natural Gas Well Pad Enclosed Combustor Emissions Using Optical Remote Sensing Technologies

    Science.gov (United States)

    The U.S. Environmental Protection Agency (EPA), Office of Research and Development (ORD) and EPA Region 8 are collaborating under the EPA’s Regional Applied Research Effort (RARE) program to evaluate ground-based remote sensing technologies that could be used to characterize emis...

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

    Science.gov (United States)

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

    2017-02-01

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

  10. Inherent optical properties and remote sensing reflectance of Pomeranian lakes (Poland

    Directory of Open Access Journals (Sweden)

    Dariusz Ficek

    2012-11-01

    Full Text Available This paper describes the results of comprehensive empirical studies of theinherent optical properties (IOPs, the remote sensing reflectance Rrs(λ andthe contents of the principal optically active components (OAC i.e. coloureddissolved organic matter (CDOM, suspended particulate matter (SPM andchlorophyll a, in the waters of 15 lakes in Polish Pomerania in 2007-2010.It presents numerous spectra of the total absorption a(λ andscattering b(λ ≈ bp(λ of light in the visibleband (400-700 nm for surface waters, and separately, spectra of absorptionby CDOM aCDOM(λ and spectra of the mass-specificcoefficients of absorption ap*(SPM(λ and scatteringbp*(SPM(λ by SPM. The properties of these lake waters are highly diverse, but all of them can beclassified as Case 2 waters (according to the optical classification by Morel& Prieur 1977 and they all have a relatively high OAC content. The lakeswere conventionally divided into three types: Type I lakes have the lowestOAC concentrations (chlorophyll concentration Ca = (8.76 ± 7.4 mg m-3 and CDOM absorption coefficientsaCDOM(440 = (0.57 ± 0.22 m-1 (i.e. mean and standarddeviation, and optical properties (including spectra of Rrs(λresembling those of Baltic waters. Type II waters have exceptionally highcontents of CDOM (aCDOM(440 = (15.37 ± 1.54 m-1,and hence appear brown in daylight and have very low reflectancesRrs(λ (of the order of 0.001 sr-1. Type III waters arehighly eutrophic and contain large amounts of suspended matter, includingphytoplankton ((CSPM = (47.0 ± 39.4 g m-3,Ca = (86.6 ± 61.5 mg m-3; aCDOM(440 = (2.77 ± 0.86 m-1. Hence the reflectances Rrs(λof these type of waters are on average one order of magnitude higher thanthose of the other natural waters, reaching maximum values of 0.03 sr-1in λ bands 560-580 nm and 690-720 nm (see Ficek et al. 2011. Thearticle provides a number of empirical formulas approximating therelationships between the properties of these lake waters.

  11. Mapping the bathymetry of shallow coastal water using single-frame fine-resolution optical remote sensing imagery

    Institute of Scientific and Technical Information of China (English)

    LI Jiran; ZHANG Huaguo; HOU Pengfei; FU Bin; ZHENG Gang

    2016-01-01

    This paper presents a bathymetry inversion method using single-frame fine-resolution optical remote sensing imagery based on ocean-wave refraction and shallow-water wave theory. First, the relationship among water depth, wavelength and wave radian frequency in shallow water was deduced based on shallow-water wave theory. Considering the complex wave distribution in the optical remote sensing imagery, Fast Fourier Transform (FFT) and spatial profile measurements were applied for measuring the wavelengths. Then, the wave radian frequency was calculated by analyzing the long-distance fluctuation in the wavelength, which solved a key problem in obtaining the wave radian frequency in a single-frame image. A case study was conducted for Sanya Bay of Hainan Island, China. Single-frame fine-resolution optical remote sensing imagery from QuickBird satellite was used to invert the bathymetry without external input parameters. The result of the digital elevation model (DEM) was evaluated against a sea chart with a scale of 1:25 000. The root-mean-square error of the inverted bathymetry was 1.07 m, and the relative error was 16.2%. Therefore, the proposed method has the advantages including no requirement for true depths and environmental parameters, and is feasible for mapping the bathymetry of shallow coastal water.

  12. 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...

  13. 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

  14. Remote optical sensing on the nanometer scale with a bowtie aperture nano-antenna on a SNOM fiber tip

    CERN Document Server

    Atie, Elie M; Eter, Ali El; Salut, Roland; Nedeljkovic, Dusan; Tannous, Tony; Baida, Fadi I; Grosjean, Thierry

    2015-01-01

    Plasmonic nano-antennas have proven the outstanding ability of sensing chemical and physical processes down to the nano-meter scale. Sensing is usually achieved within the highly confined optical fields generated resonantly by the nano-antennas, i.e. in contact to the nano-structures. In these paper, We demonstrate the sensing capability of nano-antennas to their larger scale environment, well beyond their plasmonic confinement volume, leading to the concept of 'remote' (non contact) sensing on the nano-meter scale. On the basis of a bowtie-aperture nano-antenna (BNA) integrated at the apex of a SNOM fiber tip, we introduce an ultra-compact, move-able and background-free optical nano-sensor for the remote sensing of a silicon surface (up to distance of 300 nm). Sensitivity of the BNA to its large scale environment is high enough to expect the monitoring and control of the spacing between the nano-antenna and a silicon surface with sub-nano-meter accuracy. This work paves the way towards a new class of nano-po...

  15. Characterization of glacier debris cover via in situ and optical remote sensing methods: a case study in the Khumbu Himalaya, Nepal

    OpenAIRE

    K. A. Casey; A. Kääb; D. I. Benn

    2011-01-01

    Field spectrometry and physical samples of debris, snow and ice were collected from the ablation zones of Ngozumpa and Khumbu glaciers of the Khumbu Himalaya, Nepal in November and December 2009. Field acquired spectral reflectances and mineral and chemical composition of samples were used as ground truth for comparison with satellite optical remote sensing data. Supraglacial debris was characterized by several optical remote sensing methods, including hyperspectral reflectance analys...

  16. Novel Technique and Technologies for Active Optical Remote Sensing of Greenhouse Gases

    Science.gov (United States)

    Singh, Upendra N.; Refaat, Tamer F.; Petros, Mulugeta

    2017-01-01

    The societal benefits of understanding climate change through identification of global carbon dioxide sources and sinks led to the desired NASA's active sensing of carbon dioxide emissions over nights, days, and seasons (ASCENDS) space-based missions of global carbon dioxide measurements. For more than 15 years, NASA Langley Research Center (LaRC) have developed several carbon dioxide active remote sensors using the differential absorption lidar (DIAL) technique operating at the two-micron wavelength. Currently, an airborne two-micron triple-pulse integrated path differential absorption (IPDA) lidar is under development. This IPDA lidar measures carbon dioxide as well as water vapor, the dominant interfering molecule on carbon dioxide remote sensing. Advancement of this triple-pulse IPDA lidar development is presented.

  17. 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...

  18. 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...

  19. 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.

  20. Supraglacial dust and debris characterization via in situ and optical remote sensing methods

    OpenAIRE

    Casey, Kimberly Ann

    2011-01-01

    Supraglacial dust and debris affects many glaciologic variables, including radiative absorption, ablation, generation of supraglacial melt as well as mass flux. Earth observing satellite technology has advanced greatly in recent decades and allows for unprecedented spatial, temporal and spectral imaging of Earth’s glaciers. While remote sensing of ‘clean’ glacier ice can be done quite successfully, strategies for satellite mapping of supraglacial debris remain in development. This work provid...

  1. Computed tomography and optical remote sensing: Development for the study of indoor air pollutant transport and dispersion

    Energy Technology Data Exchange (ETDEWEB)

    Drescher, Anushka Christina [Univ. of California, Berkeley, CA (United States)

    1995-06-01

    This thesis investigates the mixing and dispersion of indoor air pollutants under a variety of conditions using standard experimental methods. It also extensively tests and improves a novel technique for measuring contaminant concentrations that has the potential for more rapid, non-intrusive measurements with higher spatial resolution than previously possible. Experiments conducted in a sealed room support the hypothesis that the mixing time of an instantaneously released tracer gas is inversely proportional to the cube root of the mechanical power transferred to the room air. One table-top and several room-scale experiments are performed to test the concept of employing optical remote sensing (ORS) and computed tomography (CT) to measure steady-state gas concentrations in a horizontal plane. Various remote sensing instruments, scanning geometries and reconstruction algorithms are employed. Reconstructed concentration distributions based on existing iterative CT techniques contain a high degree of unrealistic spatial variability and do not agree well with simultaneously gathered point-sample data.

  2. Optical remote sensing of the thermosphere with HF pumped artificial airglow

    Science.gov (United States)

    Bernhardt, P. A.; Wong, M.; Huba, J. D.; Fejer, B. G.; Wagner, L. S.; Goldstein, J. A.; Selcher, C. A.; Frolov, V. L.; Sergeev, E. N.

    2000-05-01

    Optical emissions excited by high-power radio waves in the ionosphere can be used to measure a wide variety of parameters in the thermosphere. Powerful high-frequency (HF) radio waves produce energetic electrons in the region where the waves reflect in the F region. These hot or suprathermal electrons collide with atomic oxygen atoms to produce localized regions of metastable O(1D) and O(1S) atoms. These metastables subsequently radiate 630.0 and 557.7 nm, respectively, to produce clouds of HF pumped artificial airglow (HPAA). The shapes of the HPAA clouds are determined by the structure of large-scale (~10 km) plasma irregularities that occur naturally or that develop during ionospheric heating. When the HF wave is operated continuously, the motion of the airglow clouds follows the E×B drift of the plasma. When the HF wave is turned off, the airglow clouds decay by collisional quenching and radiation, expand by neutral diffusion, and drift in response to neutral winds. Images of HPAA clouds, obtained using both continuous and stepped radio wave transmissions, are processed to yield the electric fields, neutral wind vectors, and diffusion coefficients in the upper atmosphere. This technique is illustrated using data that were obtained in March 1993 and 1995 at the ionospheric modification facility near Nizhny Novgorod, Russia. Analysis of HPAA clouds yields zonal plasma drifts of 70 m s-1 eastward at night. On the basis of artificial airglow from energetic electrons generated at 260 km the zonal neutral wind speed was estimated to be 96 m s-1 and the O(1D) diffusion coefficient was determined to be between 0.8 and 1.4×1011cm2s-1. The quenched lifetime of the O(1D) was determined to be 29.4 s. The diffusion and quenching rates are directly related to the atomic and molecular concentrations in the thermosphere. Improvements in the remote-sensing technique may be obtained if the intensity of the artificial airglow emissions is increased. High-power radio

  3. Remote optical sensing on the nanometer scale with a bowtie aperture nano-antenna on a fiber tip of scanning near-field optical microscopy

    Science.gov (United States)

    Atie, Elie M.; Xie, Zhihua; El Eter, Ali; Salut, Roland; Nedeljkovic, Dusan; Tannous, Tony; Baida, Fadi I.; Grosjean, Thierry

    2015-04-01

    Plasmonic nano-antennas have proven the outstanding ability of sensing chemical and physical processes down to the nanometer scale. Sensing is usually achieved within the highly confined optical fields generated resonantly by the nano-antennas, i.e., in contact to the nanostructures. In this paper, we demonstrate the sensing capability of nano-antennas to their larger scale environment, well beyond their plasmonic confinement volume, leading to the concept of "remote" (non contact) sensing on the nanometer scale. On the basis of a bowtie-aperture nano-antenna (BNA) integrated at the apex of a SNOM (Scanning Near-field Optical Microscopy) fiber tip, we introduce an ultra-compact, moveable, and background-free optical nanosensor for the remote sensing of a silicon surface (up to distance of 300 nm). Sensitivity of the BNA to its large scale environment is high enough to expect the monitoring and control of the spacing between the nano-antenna and a silicon surface with sub-nanometer accuracy. This work paves the way towards an alternative class of nanopositioning techniques, based on the monitoring of diffraction-free plasmon resonance, that are alternative to nanomechanical and diffraction-limited optical interference-based devices.

  4. Integrating artificial neural network and classical methods for unsupervised classification of optical remote sensing data

    Science.gov (United States)

    Tahir, Ahmed AK

    2012-12-01

    A novel system named unsupervised multiple classifier system (UMCS) for unsupervised classification of optical remote sensing data is presented. The system is based on integrating two or more individual classifiers. A new dynamic selection-based method is developed for integrating the decisions of the individual classifiers. It is based on competition distance arranged in a table named class-distance map (CDM) associated to each individual classifier. These maps are derived from the class-to-class-distance measures which represent the distances between each class and the remaining classes for each individual classifier. Three individual classifiers are used for the development of the system, K-means and K-medians clustering of the classical approach and Kohonen network of the artificial neural network approach. The system is applied to ETM + images of an area North to Mosul dam in northern part of Iraq. To show the significance of increasing the number of individual classifiers, the application covered three modes, UMCS@, UMCS#, and UMCS*. In UMCS@, K-means and Kohonen are used as individual classifiers. In UMCS#, K-medians and Kohonen are used as individual classifiers. In UMCS*, K-means, K-medians and Kohonen are used as individual classifiers. The performance of the system for the three modes is evaluated by comparing the outputs of individual classifiers to the outputs of UMCSs using test data extracted by visual interpretation of color composite images. The evaluation has shown that the performance of the system with all three modes outrages the performance of the individual classifiers. However, the improvement in the class and average accuracy for UMCS* was significant compared to the improvements made by UMCS@, and UMCS#. For UMCS*, the accuracy of all classes were improved over the accuracy achieved by each of the individual classifiers and the average improvements reached (4.27, 3.70, and 6.41%) over the average accuracy achieved by K-means, K-medians and

  5. 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.

  6. Automatic Registration Method for Optical Remote Sensing Images with Large Background Variations Using Line Segments

    Directory of Open Access Journals (Sweden)

    Xiaolong Shi

    2016-05-01

    Full Text Available Image registration is an essential step in the process of image fusion, environment surveillance and change detection. Finding correct feature matches during the registration process proves to be difficult, especially for remote sensing images with large background variations (e.g., images taken pre and post an earthquake or flood. Traditional registration methods based on local intensity probably cannot maintain steady performances, as differences are significant in the same area of the corresponding images, and ground control points are not always available in many disaster images. In this paper, an automatic image registration method based on the line segments on the main shape contours (e.g., coastal lines, long roads and mountain ridges is proposed for remote sensing images with large background variations because the main shape contours can hold relatively more invariant information. First, a line segment detector called EDLines (Edge Drawing Lines, which was proposed by Akinlar et al. in 2011, is used to extract line segments from two corresponding images, and a line validation step is performed to remove meaningless and fragmented line segments. Then, a novel line segment descriptor with a new histogram binning strategy, which is robust to global geometrical distortions, is generated for each line segment based on the geometrical relationships,including both the locations and orientations of theremaining line segments relative to it. As a result of the invariance of the main shape contours, correct line segment matches will have similar descriptors and can be obtained by cross-matching among the descriptors. Finally, a spatial consistency measure is used to remove incorrect matches, and transformation parameters between the reference and sensed images can be figured out. Experiments with images from different types of satellite datasets, such as Landsat7, QuickBird, WorldView, and so on, demonstrate that the proposed algorithm is

  7. 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.…

  8. 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.…

  9. Evaluation and application of passive and active optical remote sensing methods for the measurement of atmospheric aerosol properties

    Energy Technology Data Exchange (ETDEWEB)

    Mielonen, T.

    2010-07-01

    Atmospheric aerosol particles affect the atmosphere's radiation balance by scattering and absorbing sunlight. Moreover, the particles act as condensation nuclei for clouds and affect their reflectivity. In addition, aerosols have negative health effects and they reduce visibility. Aerosols are emitted into the atmosphere from both natural and anthropogenic sources. Different types of aerosols have different effects on the radiation balance, thus global monitoring and typing of aerosols is of vital importance. In this thesis, several remote sensing methods used in the measurement of atmospheric aerosols are evaluated. Remote sensing of aerosols can be done with active and passive instruments. Passive instruments measure radiation emitted by the sun and the Earth while active instruments have their own radiation source, for example a black body radiator or laser. The instruments utilized in these studies were sun photometers (PFR, Cimel), lidars (POLLYXT, CALIOP), transmissiometer (OLAF) and a spectroradiometer (MODIS). Retrieval results from spaceborne instruments (MODIS, CALIOP) were evaluated with ground based measurements (PFR, Cimel). In addition, effects of indicative aerosol model assumptions on the calculated radiative transfer were studied. Finally, aerosol particle mass at the ground level was approximated from satellite measurements and vertical profiles of aerosols measured with a lidar were analyzed. For the evaluation part, these studies show that the calculation of aerosol induced attenuation of radiation based on aerosol size distribution measurements is not a trivial task. In addition to dry aerosol size distribution, the effect of ambient relative humidity on the size distribution and the optical properties of the aerosols need to be known in order to achieve correct results from the calculations. Furthermore, the results suggest that aerosol size parameters retrieved from passive spaceborne measurements depend heavily on surgace reflectance

  10. Spatial scales of optical variability in the coastal ocean: Implications for remote sensing and in situ sampling

    Science.gov (United States)

    Moses, Wesley J.; Ackleson, Steven G.; Hair, Johnathan W.; Hostetler, Chris A.; Miller, W. David

    2016-06-01

    Use of ocean color remote sensing to understand the effects of environmental changes and anthropogenic activities on estuarine and coastal waters requires the capability to measure and track optically detectable complex biogeochemical processes. An important remote sensor design consideration is the minimum spatial resolution required to resolve key ocean features of physical and biological significance. The spatial scale of variability in optical properties of coastal waters has been investigated using continuous, along-track measurements collected using instruments deployed from ships, aircraft, and satellites. We defined the average coefficient of variance, CV¯a, within an image pixel as the primary statistical measure of subpixel variability and investigated how CV¯a changes as a function of the Ground Sampling Distance (GSD). In general, dCV¯a/dGSD is positive, indicating that the subpixel variability increases with GSD. The relationship between CV¯a and GSD is generally nonlinear and the greatest rate of change occurs at small spatial scales. Points of distinct transition in the relationship between CV¯a and GSD are evident between 75 and 600 m, varying depending on the location and the optical parameter, and representing the GSD above which most of the spatial variability due to small-scale features is subsumed within a pixel. At GSDs greater than the transition point, most of the small-scale variability occurs at subpixel scales and, therefore, cannot be resolved. On average, the transition GSD is around 200 m. The results have application in both sensor design and in situ sampling strategy in support of coastal remote sensing operations.

  11. Profiling aerosol optical, microphysical and hygroscopic properties in ambient conditions by combining in situ and remote sensing

    Science.gov (United States)

    Tsekeri, Alexandra; Amiridis, Vassilis; Marenco, Franco; Nenes, Athanasios; Marinou, Eleni; Solomos, Stavros; Rosenberg, Phil; Trembath, Jamie; Nott, Graeme J.; Allan, James; Le Breton, Michael; Bacak, Asan; Coe, Hugh; Percival, Carl; Mihalopoulos, Nikolaos

    2017-01-01

    We present the In situ/Remote sensing aerosol Retrieval Algorithm (IRRA) that combines airborne in situ and lidar remote sensing data to retrieve vertical profiles of ambient aerosol optical, microphysical and hygroscopic properties, employing the ISORROPIA II model for acquiring the particle hygroscopic growth. Here we apply the algorithm on data collected from the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 research aircraft during the ACEMED campaign in the Eastern Mediterranean. Vertical profiles of aerosol microphysical properties have been derived successfully for an aged smoke plume near the city of Thessaloniki with aerosol optical depth of ˜ 0.4 at 532 nm, single scattering albedos of ˜ 0.9-0.95 at 550 nm and typical lidar ratios for smoke of ˜ 60-80 sr at 532 nm. IRRA retrieves highly hydrated particles above land, with 55 and 80 % water volume content for ambient relative humidity of 80 and 90 %, respectively. The proposed methodology is highly advantageous for aerosol characterization in humid conditions and can find valuable applications in aerosol-cloud interaction schemes. Moreover, it can be used for the validation of active space-borne sensors, as is demonstrated here for the case of CALIPSO.

  12. Optical remote sensing and correlation of office equipment functional state and stress levels via power quality disturbances inefficiencies

    Science.gov (United States)

    Sternberg, Oren; Bednarski, Valerie R.; Perez, Israel; Wheeland, Sara; Rockway, John D.

    2016-09-01

    Non-invasive optical techniques pertaining to the remote sensing of power quality disturbances (PQD) are part of an emerging technology field typically dominated by radio frequency (RF) and invasive-based techniques. Algorithms and methods to analyze and address PQD such as probabilistic neural networks and fully informed particle swarms have been explored in industry and academia. Such methods are tuned to work with RF equipment and electronics in existing power grids. As both commercial and defense assets are heavily power-dependent, understanding electrical transients and failure events using non-invasive detection techniques is crucial. In this paper we correlate power quality empirical models to the observed optical response. We also empirically demonstrate a first-order approach to map household, office and commercial equipment PQD to user functions and stress levels. We employ a physics-based image and signal processing approach, which demonstrates measured non-invasive (remote sensing) techniques to detect and map the base frequency associated with the power source to the various PQD on a calibrated source.

  13. Remote optical sensing on the nanometer scale with a bowtie aperture nano-antenna on a fiber tip of scanning near-field optical microscopy

    Energy Technology Data Exchange (ETDEWEB)

    Atie, Elie M.; Xie, Zhihua; El Eter, Ali; Salut, Roland; Baida, Fadi I.; Grosjean, Thierry, E-mail: thierry.grosjean@univ-fcomte.fr [Institut FEMTO-ST, UMR CNRS 6174, Université de Franche-Comté, Département d' Optique P.M. Duffieux, 15B avenue des Montboucons, 25030 Besançon cedex (France); Nedeljkovic, Dusan [Lovalite s.a.s., 7 rue Xavier Marmier, 25000 Besançon (France); Tannous, Tony [Department of Physics, University of Balamand, P.O. Box 100 Tripoli (Lebanon)

    2015-04-13

    Plasmonic nano-antennas have proven the outstanding ability of sensing chemical and physical processes down to the nanometer scale. Sensing is usually achieved within the highly confined optical fields generated resonantly by the nano-antennas, i.e., in contact to the nanostructures. In this paper, we demonstrate the sensing capability of nano-antennas to their larger scale environment, well beyond their plasmonic confinement volume, leading to the concept of “remote” (non contact) sensing on the nanometer scale. On the basis of a bowtie-aperture nano-antenna (BNA) integrated at the apex of a SNOM (Scanning Near-field Optical Microscopy) fiber tip, we introduce an ultra-compact, moveable, and background-free optical nanosensor for the remote sensing of a silicon surface (up to distance of 300 nm). Sensitivity of the BNA to its large scale environment is high enough to expect the monitoring and control of the spacing between the nano-antenna and a silicon surface with sub-nanometer accuracy. This work paves the way towards an alternative class of nanopositioning techniques, based on the monitoring of diffraction-free plasmon resonance, that are alternative to nanomechanical and diffraction-limited optical interference-based devices.

  14. Optical and Radar Satellite Remote Sensing for Large Area Analysis of Landslide Activity in Southern Kyrgyzstan, Central Asia

    Science.gov (United States)

    Roessner, S.; Behling, R.; Teshebaeva, K. O.; Motagh, M.; Wetzel, H. U.

    2014-12-01

    The presented work has been investigating the potential of optical and radar satellite remote sensing for the spatio-temporal analysis of landslide activity at a regional scale along the eastern rim of the Fergana Basin representing the area of highest landslide activity in Kyrgyzstan. For this purpose a multi-temporal satellite remote sensing database has been established for a 12.000 km2 study area in Southern Kyrgyzstan containing a multitude of optical data acquired during the last 28 years as well as TerraSAR-X and ALOS-PALSAR acquired since 2007. The optical data have been mainly used for creating a multi-temporal inventory of backdated landslide activity. For this purpose an automated approach for object-oriented multi-temporal landslide detection has been developed which is based on the analysis of temporal NDVI-trajectories complemented by relief information to separate landslide-related surface changes from other land cover changes. Applying the approach to the whole study area using temporal high resolution RapidEye time series data has resulted in the automated detection of 612 landslide objects covering a total area of approx. 7.3 km². Currently, the approach is extended to the whole multi-sensor time-series database for systematic analysis of longer-term landslide occurrence at a regional scale. Radar remote sensing has been focussing on SAR Interferometry (InSAR) to detect landslide related surface deformation. InSAR data were processed by repeat-pass interferometry using the DORIS and SARScape software. To better assess ground deformation related to individual landslide objects, InSAR time-series analysis has been applied using the Small Baseline Subset (SBAS) method. Analysis of the results in combination with optical data and DEM information has revealed that most of the derived deformations are caused by slow movements in areas of already existing landslides indicating the reactivation of older slope failures. This way, InSAR analysis can

  15. 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

  16. Temporal and spatial variability of aerosol optical depth in the Sahel region in relation to vegetation remote sensing

    Science.gov (United States)

    Holben, B. N.; Fraser, R. S.; Eck, T. F.

    1991-01-01

    In order to monitor the aerosol characteristics needed for atmospheric correction of remotely sensed data, a network of sun photometers was established in the Sahel region of Senegal, Mali, and Niger. Data analysis suggests that there is a high spatial variability of the aerosol optical thickness tau(a) in the western Sahel region. At a 67 percent confidence level the instantaneous values of tau(a) can be extrapolated approximately 270-400 km with an error tolerance of 50 percent. Spatial variability in the dry season is found to be of a similar magnitude. The ranges of variations in the NDVI in the Sahel region are shown to be approximately 0.02 and 0.01, respectively, due to commonly observed fluctuations in the aerosol optical thickness and aerosol size distribution.

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

    Science.gov (United States)

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

    2017-02-01

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

  18. Joint Multi-Image Saliency Analysis for Region of Interest Detection in Optical Multispectral Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Jie Chen

    2016-05-01

    Full Text Available The automatic detection of regions of interest (ROI is useful for remote sensing image analysis, such as land cover classification, object recognition, image compression, and various computer vision related applications. Recently, approaches based on visual saliency have been utilized for ROI detection. However, most existing methods focus on detecting ROIs from a single image, which generally cannot precisely extract ROIs against a complicated background or exclude images with no ROIs. In this paper, we propose a joint multi-image saliency (JMS algorithm to simultaneously extract the common ROIs in a set of optical multispectral remote sensing images with the additional ability to identify images that do not contain the common ROIs. First, bisecting K-means clustering on the entire image set allows us to extract the global correspondence among multiple images in RGB and CIELab color spaces. Second, clusterwise saliency computation aggregating global color and shape contrast efficiently assigns common ROIs with high saliency, while effectively depressing interfering background that is salient only within its own image. Finally, binary ROI masks are generated by thresholding saliency maps. In addition, we construct an edge-preserving JMS model through edge-preserving mask optimization strategy, so as to facilitate the generation of a uniformly highlighted ROI mask with sharp borders. Experimental results demonstrate the advantages of our model in detection accuracy consistency and runtime efficiency.

  19. 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…

  20. 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…

  1. Mapping soil salinity in irrigated land using optical remote sensing data

    Directory of Open Access Journals (Sweden)

    Rachid Lhissoui

    2014-04-01

    Full Text Available Soil salinity caused by natural or human-induced processes is certainly a severe environmental problem that already affects 400 million hectares and seriously threatens an equivalent surface. Salinization causes negative effects on the ground; it affects agricultural production, infrastructure, water resources and biodiversity. In semi-arid and arid areas, 21% of irrigated lands suffer from waterlogging, salinity and/or sodicity that reduce their yields. 77 million hectares are saline soils induced by human activity, including 58% in the irrigated areas. In the irrigated perimeter of Tadla plain (central Morocco, the increased use of saline groundwater and surface water, coupled with agricultural intensification leads to the deterioration of soil quality. Experimental methods for monitoring soil salinity by direct measurements in situ are very demanding of time and resources, and also very limited in terms of spatial coverage. Several studies have described the usefulness of remote sensing for mapping salinity by its synoptic coverage and the sensitivity of the electromagnetic signal to surface soil parameters. In this study, we used an image of the TM Landsat sensor and field measurements of electrical conductivity (EC, the correlation between the image data and field measurements allowed us to develop a semi-empirical model allowing the mapping of soil salinity in the irrigated perimeter of Tadla plain. The validation of this model by the ground truth provides a correlation coefficient r² = 0.90. Map obtained from this model allows the identification of different salinization classes in the study area.

  2. An optical remote sensing approach for ecological monitoring of red and green Noctiluca scintillans.

    Science.gov (United States)

    Baliarsingh, S K; Dwivedi, R M; Lotliker, Aneesh A; Sahu, K C; Kumar, T Srinivasa; Shenoi, S S C

    2017-07-01

    An ecosystem disruptive bloom of red Noctiluca scintillans (hereafter Noctiluca) was observed in coastal waters of the north-western Bay of Bengal during April 2014. Based on the principle of phytoplankton group/species specific remote sensing reflectance (Rrs), a technique of detecting green Noctiluca and diatom was developed earlier using Rrs at 443, 488, and 531 nm of Moderate Imaging Spectroradiometer-Aqua (MODIS). This was appropriately modified to detect bloom of red Noctiluca in coastal waters of the Bay of Bengal. Additional Rrs data at longer wavelengths viz. 667 and 678 nm were included in the existing algorithm, and the spectral shapes were accounted to detect the bloom of red Noctiluca. The classification scheme discriminates red Noctiluca from the green form of the same species and diatom. Phytoplankton group/species products were generated using the modified approach and validated with the reported events of red and green Noctiluca blooms in the Indian coastal waters. The present study also highlights two specific results based on MODIS retrieved time-series phytoplankton group/species image analysis: first, the observation of coexistence of diatom, red, and green Noctiluca in coastal waters of the north-western Bay of Bengal, and the second, phytoplankton community shift resulting in red/green Noctiluca proliferation following diatom.

  3. A global comparison of GEOS-Chem predicted and remotely-sensed mineral dust aerosol optical depth

    Directory of Open Access Journals (Sweden)

    Matthew S Johnson

    2012-07-01

    Full Text Available Dust aerosol optical depth (AOD and vertical distribution of aerosol extinction predicted by a global chemical transport model (GEOS-Chem are compared to space-borne data from the Moderate-resolution Imaging Spectroradiometer (MODIS, Multi-Angle Imaging SpectroRadiometer (MISR, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO for March 2009 to February 2010. Model-predicted and remotely-sensed AOD/aerosol extinction profiles are compared over six regions where aerosol abundances are dominated by mineral dust. Calculations indicate that over the regions examined in this study (with the exception of Middle Eastern dust sources GEOS-Chem predicts higher AOD values compared to MODIS and MISR. The positive bias is particularly pronounced over the Saharan dust source regions, where model-predicted AOD values are a factor of 2 to 3 higher. The comparison with CALIPSO-derived dust aerosol extinction profiles revealed that the model overestimations of dust abundances over the study regions primarily occur below ~4 km, suggesting excessive emissions of mineral dust and/or uncertainties in dust optical properties. The implementation of a new dust size distribution scheme into GEOS-Chem reduced the yearly-mean positive bias in model-predicted AOD values over the study regions. The results were most noticeable over the Saharan dust source regions where the differences between model-predicted and MODIS/MISR retrieved AOD values were reduced from 0.22 and 0.17 to 0.02 and -0.04, respectively. Our results suggest that positive/negative biases between satellite and model-predicted aerosol extinction values at different altitudes can sometimes even out, giving a false impression for the agreement between remotely-sensed and model-predicted column-integrated AOD data.

  4. Remote sensing of bio-optical water types, phytoplankton seasonality, and algal pigments in ocean margin waters

    Science.gov (United States)

    Bontempi, Paula Susan

    A frontal edge detection algorithm was applied to remotely sensed ocean color satellite data to identify incorrect retrievals of phytoplankton chl a concentrations, and refine estimates of primary producer abundance in bio-optically complex ocean margin waters. Improvement of the remotely sensed biological signal will facilitate establishment of more accurate daily to decadal phytoplankton spatial patterns in these waters, and enable prediction of phytoplankton blooms or features from space. Spatial patterns of chlorophyll a (chl a) and water-leaving radiance (Lwn) from 1998 SeaWiFS (Sea-Viewing Wide Field-of-View Sensor) images were examined from ocean margin waters off the southeastern continental United States (SEC). Ocean margin waters are bio-optically complex due to riverine input, terrestrial runoff, and associated dissolved and particulate materials. Dissolved and particulate materials affect water-leaving radiance values in regions of the electromagnetic spectrum (412, 443, 555 nm) where their absorption and scattering properties are strongest. The radiative signal of non chlorophyll-containing fractions is misinterpreted as chl a. Waters are bio-optically classified as dominated by phytoplankton and derivative products (Morel Case I), or non chlorophyll-containing in-water constituents (Morel Case II). An edge detection algorithm delineated bio-optical water masses. Spatial congruence of Lwn(555) and chl a fronts defined Case II waters, and residual chl a fronts identified Case I waters. Monthly phytoplankton spatial variability was examined during January, March, May, August, and November, representing major seasonal periods. Phytoplankton were associated with a shelf region based on their response to local physical forcings. River flow and wind stress affect inner shelf chl a distributions, while offshore chl a distributions are controlled by Gulf Stream meanders. Carolina Capes' oceanography influenced chl a frontal variability. Radiance data at 443nm

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

    Science.gov (United States)

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

    2016-12-01

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

  6. Maritime Semantic Labeling of Optical Remote Sensing Images with Multi-Scale Fully Convolutional Network

    Directory of Open Access Journals (Sweden)

    Haoning Lin

    2017-05-01

    Full Text Available In current remote sensing literature, the problems of sea-land segmentation and ship detection (including in-dock ships are investigated separately despite the high correlation between them. This inhibits joint optimization and makes the implementation of the methods highly complicated. In this paper, we propose a novel fully convolutional network to accomplish the two tasks simultaneously, in a semantic labeling fashion, i.e., to label every pixel of the image into 3 classes, sea, land and ships. A multi-scale structure for the network is proposed to address the huge scale gap between different classes of targets, i.e., sea/land and ships. Conventional multi-scale structure utilizes shortcuts to connect low level, fine scale feature maps to high level ones to increase the network’s ability to produce finer results. In contrast, our proposed multi-scale structure focuses on increasing the receptive field of the network while maintaining the ability towards fine scale details. The multi-scale convolution network accommodates the huge scale difference between sea-land and ships and provides comprehensive features, and is able to accomplish the tasks in an end-to-end manner that is easy for implementation and feasible for joint optimization. In the network, the input forks into fine-scale and coarse-scale paths, which share the same convolution layers to minimize network parameter increase, and then are joined together to produce the final result. The experiments show that the network tackles the semantic labeling problem with improved performance.

  7. Optical remote sensing of properties and concentrations of atmospheric trace constituents

    Science.gov (United States)

    Vladutescu, Daniela Viviana

    The effect of human activities on the global climate may lead to large disturbances of the economic, social and political circumstances in the middle and long term. Understanding the dynamics of the Earth's climate is therefore of high importance and one of the major scientific challenges of our time. The estimation of the contribution of the Earth's climate system components needs observation and continuous monitoring of various atmospheric physical and chemical parameters. Temperature, water vapor and greenhouse gases concentration, aerosol and clouds loads, and atmospheric dynamics are parameters of particular importance in this respect. The quantification of the anthropogenic influence on the dynamics of these above-mentioned parameters is of crucial importance nowadays but still affected by significant uncertainties. In the present context of these huge uncertainties in our understanding of how these different atmospheric compounds contribute to the radiative forcing, a significant part of my research interest is related to the following topics: (1) Development of lidar (Light Detection and Ranging)-based remote sensing techniques for monitoring atmospheric compounds and processes; (2) Aerosols hygroscopic properties and atmospheric modeling; (3) Water vapor mixing ratio and relative humidity estimation in the troposphere; (4) Characterization of the long-range transported aerosols; (5) Ambient gases detection using Fourier Transform Interferometers (FTIR); (6) Design of inexpensive Fabry Perot Interferometer for visible and near infrared for land and ocean surface remote sensing applications. The lidar-based remote sensing measurement techniques for the monitoring of climate change parameters where implemented at the City College of the City University of New York (CCNY/CUNY) LIDAR station and are presented in the second section of the paper. The geographical location of the CCNY lidar station is 40.86N, -73.86W. Among the lidar retrievals one important

  8. 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

  9. Space-Based CO2 Active Optical Remote Sensing using 2-μm Triple-Pulse IPDA Lidar

    Science.gov (United States)

    Singh, Upendra; Refaat, Tamer; Ismail, Syed; Petros, Mulugeta

    2017-04-01

    Sustained high-quality column CO2 measurements from space are required to improve estimates of regional and global scale sources and sinks to attribute them to specific biogeochemical processes for improving models of carbon-climate interactions and to reduce uncertainties in projecting future change. Several studies show that space-borne CO2 measurements offer many advantages particularly over high altitudes, tropics and southern oceans. Current satellite-based sensing provides rapid CO2 monitoring with global-scale coverage and high spatial resolution. However, these sensors are based on passive remote sensing, which involves limitations such as full seasonal and high latitude coverage, poor sensitivity to the lower atmosphere, retrieval complexities and radiation path length uncertainties. CO2 active optical remote sensing is an alternative technique that has the potential to overcome these limitations. The need for space-based CO2 active optical remote sensing using the Integrated Path Differential Absorption (IPDA) lidar has been advocated by the Advanced Space Carbon and Climate Observation of Planet Earth (A-Scope) and Active Sensing of CO2 Emission over Nights, Days, and Seasons (ASCENDS) studies in Europe and the USA. Space-based IPDA systems can provide sustained, high precision and low-bias column CO2 in presence of thin clouds and aerosols while covering critical regions such as high latitude ecosystems, tropical ecosystems, southern ocean, managed ecosystems, urban and industrial systems and coastal systems. At NASA Langley Research Center, technology developments are in progress to provide high pulse energy 2-μm IPDA that enables optimum, lower troposphere weighted column CO2 measurements from space. This system provides simultaneous ranging; information on aerosol and cloud distributions; measurements over region of broken clouds; and reduces influences of surface complexities. Through the continual support from NASA Earth Science Technology Office

  10. 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

  11. 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...

  12. Inference of atomic oxygen concentration from remote sensing of optical aurora

    Science.gov (United States)

    Shepherd, M. G.; McConnell, J. C.; Tobiska, W. K.; Gladstone, G. R.; Chakrabarti, S.; Schmidtke, G.

    1995-09-01

    A remote sensing method has been developed for the determination of the [O]/[O-MSIS] ratio in aurora, using ratios of the O I (557.7 nm) and N+2 (391.4 nm) emissions. It is shown that the method can be used for the analysis of measurements integrated along the line of sight, provided data only above the emission rate peak are used. The method is applied to the case of horizontal viewing from a vertically oriented rocket so that a large volume of space was sampled around the rocket. The method can potentially be applied to satellite limb images, provided some independent information about the location of the aurora is available, as it was for the rocket observations. Photometric measurements of the N+2 (391.4 nm) and O I (557.7 nm) emissions obtained during the Energy Budget Campaign 1980 on flight E-2 with the instrument EF11 and its reflight in 1981 were used in the analysis presented. During the first flight the rocket horizontally viewed two distinct aurorae, a nearby diffuse patch, and a more distant pulsating aurora. Results obtained by the same EF11 instrument on a second flight through an auroral arc in 1981 are also presented. Two types of atomic oxygen variability were found in both of the flights. In the first type, [O] is increased above [O-MSIS] by a factor of 1.5 at 180 km, is equal to the MSIS model at 160 km, and is less than MSIS below that; that is, the scale height of [O] was increased. The experimental I(557.7)/I(391.4) ratio was constant with altitude. In the second type, the [O] was depleted by about a factor of 2 over the altitude range of 120-180 km, while the I(557.7)/I(391.4) ratio decreased with altitude. The inferred atomic oxygen concentrations of 0.5 to 2 with respect to MSIS suggested different vertical flows on the two cases. Independent evidence is provided by atmospheric composition measurements made during the same campaign.

  13. 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...

  14. Optics and remote sensing of Bahamian carbonate sediment whitings and potential relationship to wind-driven Langmuir circulation

    Directory of Open Access Journals (Sweden)

    H. M. Dierssen

    2008-12-01

    Full Text Available Regions of milky white seas or "whitings" periodically occur to the west of Andros Island along the Great Bahama Bank where the bottom sediment consists of fine-grained aragonite mud. We present comprehensive measurements of inherent optical properties within a whiting patch and discuss the potential for monitoring the frequency, extent, and quantity of suspended matter from ocean colour satellite imagery. Sea spectral reflectance measured in situ and remotely from space revealed highly reflective waters elevated across the visible spectrum (i.e., "whitened" with a peak at 490 nm. Particulate backscattering was an order of magnitude higher than that measured at other stations throughout the region. The whiting also had one of the highest backscattering ratios measured in natural waters (0.05–0.06 consistent with water dominated by aragonite particles with a high index of refraction. Regular periodicity of 40 and 212 s evident in the light attenuation coefficient over the sampling period indicated patches of fluctuating turbidity on spatial scales that could be produced from regular rows of Langmuir cells penetrating the 5-m water column. We suggest that previously described mechanisms for sediment resuspension in whitings, such as tidal bursting and fish activity, are not fully consistent with these data and propose that wind-driven Langmuir cells reaching the full-depth of the water column may represent a plausible mechanism for sediment resuspension and subsequent whiting formation. Optics and remote sensing provide important tools for quantifying the linkages between physical and biogeochemical processes in these dynamic shallow water ecosystems.

  15. Optics and remote sensing of Bahamian carbonate sediment whitings and potential relationship to wind-driven Langmuir circulation

    Directory of Open Access Journals (Sweden)

    H. M. Dierssen

    2009-03-01

    Full Text Available Regions of milky white seas or "whitings" periodically occur to the west of Andros Island along the Great Bahama Bank where the bottom sediment consists of fine-grained aragonite mud. We present measurements of inherent optical properties within a sediment whiting patch and discuss the potential for monitoring the frequency, extent, and quantity of suspended matter from ocean colour satellite imagery. Sea spectral reflectance measured in situ and remotely from space revealed highly reflective waters elevated across the visible spectrum (i.e., "whitened" with a peak at 490 nm. Particulate backscattering was an order of magnitude higher than that measured at other stations throughout the region. The whiting also had one of the highest backscattering ratios measured in natural waters (0.05–0.06 consistent with water dominated by aragonite particles with a high index of refraction. Regular periodicity of 40 and 212 s evident in the light attenuation coefficient over the sampling period indicated patches of fluctuating turbidity on spatial scales that could be produced from regular rows of Langmuir cells penetrating the 5-m water column. We suggest that previously described mechanisms for sediment resuspension in whitings, such as tidal bursting and fish activity, are not fully consistent with these data and propose that wind-driven Langmuir cells reaching the full-depth of the water column may represent a plausible mechanism for sediment resuspension and subsequent whiting formation. Optics and remote sensing provide important tools for quantifying the linkages between physical and biogeochemical processes in these dynamic shallow water ecosystems.

  16. 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.

  17. The Atlantic Meridional Transect: Spatially Extensive Calibration and Validation of Optical Properties and Remotely Sensed Measurements of Ocean Colour

    Science.gov (United States)

    Aiken, James; Hooker, Stanford

    1997-01-01

    Twice a year, the Royal Research Ship (RRS) James Clark Ross (JCR) steams a meridional transect of the atlantic Ocean between Grimsly (UK) and Stanley (Falkland Islands) with a port call in Montevideo (Uruguay), as part of the annual research activities of the British Antarctic Survey (BAS). In September, the JCR sails from the UK, and the following April it makes the return trip. The ship is operated by the BAS for the Natural Environment Research Council (NERC). The Atlantic Meridional Transect (AMT) Program exploits the passage of the JCR from approximately 50 deg. N to 50 deg. S with a primary objective to investigate physical and biological processes, as well as to measure the mesi-to-basin-scale bio-optical properties of the atlantic Ocean. The calibration and validation of remotely sensed observations of ocean colour is an inherent objective of these studies: first, by relating in situ measurements of water leaving radiance to satellite measurement, and second, by measuring the bio-optically active constituents of the water.

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

    Science.gov (United States)

    Gogoi, Mukunda M.; Babu, S. Suresh

    2016-05-01

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

  19. Synergy between optical and microwave remote sensing to derive soil and vegetation parameters from MAC Europe 1991 Experiment

    Science.gov (United States)

    Taconet, O.; Benallegue, M.; Vidal, A.; Vidal-Madjar, D.; Prevot, L.; Normand, M.

    1993-01-01

    The ability of remote sensing for monitoring vegetation density and soil moisture for agricultural applications is extensively studied. In optical bands, vegetation indices (NDVI, WDVI) in visible and near infrared reflectances are related to biophysical quantities as the leaf area index, the biomass. In active microwave bands, the quantitative assessment of crop parameters and soil moisture over agricultural areas by radar multiconfiguration algorithms remains prospective. Furthermore the main results are mostly validated on small test sites, but have still to be demonstrated in an operational way at a regional scale. In this study, a large data set of radar backscattering has been achieved at a regional scale on a French pilot watershed, the Orgeval, along two growing seasons in 1988 and 1989 (mainly wheat and corn). The radar backscattering was provided by the airborne scatterometer ERASME, designed at CRPE, (C and X bands and HH and VV polarizations). Empirical relationships to estimate water crop and soil moisture over wheat in CHH band under actual field conditions and at a watershed scale are investigated. Therefore, the algorithms developed in CHH band are applied for mapping the surface conditions over wheat fields using the AIRSAR and TMS images collected during the MAC EUROPE 1991 experiment. The synergy between optical and microwave bands is analyzed.

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

    Science.gov (United States)

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

    2013-04-01

    Updated information on crop typology and status are strongly required to support suitable action to better manage agriculture production and reduce food insecurity. In this field, remote sensing has been demonstrated to be a suitable tool to monitor crop condition however rarely the tested system became really operative. The ones today available, such as the European Commission MARS, are mainly based on the analysis of NDVI time series and required ancillary external information like crop mask to interpret the seasonal signal. This condition is not always guarantied worldwide reducing the potentiality of the remote sensing monitoring. Moreover in tropical countries cloud contamination strongly reduce the possibility of using optical remote sensing data for crop monitoring. In this framework we focused our analysis on the rice production monitoring in Asian tropical area. Rice is in fact the staple food for half of the world population (FAO 2004), in Asia almost 90% of the world's rice is produced and consumed and Rice and poverty often coincide. In this contest the production of reliable rice production information is of extreme interest. We tried to address two important issue in terms of required geospatial information for crop monitoring: rice crop detection (rice map) and seasonal dynamics analysis (phenology). We use both SAR and Optical data in order to exploit the potential complementarity of this system. Multi-temporal ASAR Wide Swath data are in fact the best option to deal with cloud contamination. SAR can easily penetrate the clouds providing information on the surface target. Temporal analysis of archive ASAR data allowed to derived accurate map, at 100m spatial resolution, of permanent rice cultivated areas. On the other and high frequency revisiting optical data, in this case MODIS, have been used to extract seasonal information for the year under analysis. MOD09A1 Surface Reflectance 8-Day L3 Global 500m have been exploited to derive time series of

  1. 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

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

    Directory of Open Access Journals (Sweden)

    Fleur Visser

    2015-09-01

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

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

    Science.gov (United States)

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

    2015-09-30

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

  4. 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.

  5. 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.

  6. 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

  7. 光学遥感压缩成像技术%Compressive Imaging Techniques in Optical Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    严奉霞; 朱炬波; 刘吉英; 王泽龙

    2014-01-01

    Compressive sampling provides a new way for increasing the capability of information acqui-sition. Compressive sampling asserts that it is possible to accurately reconstruct signals from sub-Nyquist sam-pling, provided we make some additional assumptions(sparse or compressible) about the signal in question. The compressive imaging technology, which is based on the compressive sampling theory, integrates the proc-esses of sampling, compression and processing perfectly, avoiding resource waste caused by a traditional“sam-ple-then-compress”mode, and is a potential imaging technique for optical remote sensing. This paper first re-views the basic theory of compressive sampling. Then, several optical compressive imaging systems are intro-duced. Finally three physical experiments are designed to validate the principle of compressive imaging and the experiment results can be used as reference for the future optical remote compressive imaging system.%基于Shannon采样定理的传统信息获取系统在高空间、时间和谱分辨率及系统其它性能上存在难以突破的瓶颈,压缩采样理论为提升航天遥感信息获取能力提供了新的思路。基于压缩采样理论的成像技术(压缩成像)将采样、压缩和数据处理3个过程完美的结合在一起,避免了传统遥感成像系统“先采样再压缩”方式带来的传感器和计算资源浪费,是未来光学遥感极具潜力的成像方式。文章在简要介绍压缩采样基本理论的基础上,总结和分析了国际上目前提出的光学压缩成像系统原型,设计开展了3组压缩成像物理实验,特别结合航天遥感需求设计了推扫式压缩成像方案,实验结果验证了压缩采样的基本原理,并为未来光学遥感压缩成像系统的设计提供了借鉴。

  8. 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.

  9. A Review of the Application of Optical and Radar Remote Sensing Data Fusion to Land Use Mapping and Monitoring

    Directory of Open Access Journals (Sweden)

    Neha Joshi

    2016-01-01

    Full Text Available The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral and structural information, for land cover and use assessments. Contrary to our expectations, only 50 studies specifically addressed land use, and five assessed land use changes, while the majority addressed land cover. The advantages of fusion for land use analysis were assessed in 32 studies, and a large majority (28 studies concluded that fusion improved results compared to using single data sources. Study sites were small, frequently 300–3000 km 2 or individual plots, with a lack of comparison of results and accuracies across sites. Although a variety of fusion techniques were used, pre-classification fusion followed by pixel-level inputs in traditional classification algorithms (e.g., Gaussian maximum likelihood classification was common, but often without a concrete rationale on the applicability of the method to the land use theme being studied. Progress in this field of research requires the development of robust techniques of fusion to map the intricacies of land uses and changes therein and systematic procedures to assess the benefits of fusion over larger spatial scales.

  10. Evaluating land use and aboveground biomass dynamics in an oil palm-dominated landscape in Borneo using optical remote sensing

    Science.gov (United States)

    Singh, Minerva; Malhi, Yadvinder; Bhagwat, Shonil

    2014-01-01

    The focus of this study is to assess the efficacy of using optical remote sensing (RS) in evaluating disparities in forest composition and aboveground biomass (AGB). The research was carried out in the East Sabah region, Malaysia, which constitutes a disturbance gradient ranging from pristine old growth forests to forests that have experienced varying levels of disturbances. Additionally, a significant proportion of the area consists of oil palm plantations. In accordance with local laws, riparian forest (RF) zones have been retained within oil palm plantations and other forest types. The RS imagery was used to assess forest stand structure and AGB. Band reflectance, vegetation indicators, and gray-level co-occurrence matrix (GLCM) consistency features were used as predictor variables in regression analysis. Results indicate that the spectral variables were limited in their effectiveness in differentiating between forest types and in calculating biomass. However, GLCM based variables illustrated strong correlations with the forest stand structures as well as with the biomass of the various forest types in the study area. The present study provides new insights into the efficacy of texture examination methods in differentiating between various land-use types (including small, isolated forest zones such as RFs) as well as their AGB stocks.

  11. Temporal dynamics of sand dune bidirectional reflectance characteristics for absolute radiometric calibration of optical remote sensing data

    Science.gov (United States)

    Coburn, Craig A.; Logie, Gordon; Beaver, Jason

    2016-09-01

    The use of Pseudo Invariant Calibration Sites (PICS) for establishing the radiometric trending of optical remote sensing systems has a long history of successful implementation. Past studies have shown that the PICS method is useful for evaluating the trend of sensors over time or cross-calibration of sensors but was not considered until recently for deriving absolute calibration. Current interest in using this approach to establish absolute radiometric calibration stems from recent research that indicates that with empirically derived models of the surface properties and careful atmospheric characterisation Top of Atmosphere (TOA) reflectance values can be predicted and used for absolute sensor radiometric calibration. Critical to the continued development of this approach is the accurate characterization of the Bidirectional Reflectance Distribution Function (BRDF) of PICS sites. This paper presents BRDF data collected by a high-performance portable goniometer system in order to develop a temporal BRDF model for the Algodones Dunes in California. The results demonstrated that the BRDF of a reasonably simple sand surface was complex with changes in anisotropy taking place in response to changing solar zenith angles. The nature of these complex interactions would present challenges to future model development.

  12. 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.

  13. Reducing classification error of grassland overgrowth by combing low-density lidar acquisitions and optical remote sensing data

    Science.gov (United States)

    Pitkänen, T. P.; Käyhkö, N.

    2017-08-01

    Mapping structural changes in vegetation dynamics has, for a long time, been carried out using satellite images, orthophotos and, more recently, airborne lidar acquisitions. Lidar has established its position as providing accurate material for structure-based analyses but its limited availability, relatively short history, and lack of spectral information, however, are generally impeding the use of lidar data for change detection purposes. A potential solution in respect of detecting both contemporary vegetation structures and their previous trajectories is to combine lidar acquisitions with optical remote sensing data, which can substantially extend the coverage, span and spectral range needed for vegetation mapping. In this study, we tested the simultaneous use of a single low-density lidar data set, a series of Landsat satellite frames and two high-resolution orthophotos to detect vegetation succession related to grassland overgrowth, i.e. encroachment of woody plants into semi-natural grasslands. We built several alternative Random Forest models with different sets of variables and tested the applicability of respective data sources for change detection purposes, aiming at distinguishing unchanged grassland and woodland areas from overgrown grasslands. Our results show that while lidar alone provides a solid basis for indicating structural differences between grassland and woodland vegetation, and orthophoto-generated variables alone are better in detecting successional changes, their combination works considerably better than its respective parts. More specifically, a model combining all the used data sets reduces the total error from 17.0% to 11.0% and omission error of detecting overgrown grasslands from 56.9% to 31.2%, when compared to model constructed solely based on lidar data. This pinpoints the efficiency of the approach where lidar-generated structural metrics are combined with optical and multitemporal observations, providing a workable framework to

  14. 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....

  15. 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....

  16. 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....

  17. 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....

  18. 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.

  19. A fractional snow cover mapping method for optical remote sensing data, applicable to continental scale

    OpenAIRE

    2013-01-01

    This thesis focuses on the determination of fractional snow cover (FSC) from optical data provided by satellite instruments. It describes the method development, starting from a simple regionally applicable linear interpolation method and ending at a globally applicable, semi-empirical modeling approach. The development work was motivated by the need for an easily implementable and feasible snow mapping method that could provide reliable information particularly for forested areas. The con...

  20. A fractional snow cover mapping method for optical remote sensing data, applicable to continental scale

    OpenAIRE

    2013-01-01

    This thesis focuses on the determination of fractional snow cover (FSC) from optical data provided by satellite instruments. It describes the method development, starting from a simple regionally applicable linear interpolation method and ending at a globally applicable, semi-empirical modeling approach. The development work was motivated by the need for an easily implementable and feasible snow mapping method that could provide reliable information particularly for forested areas. The co...

  1. Characterizing Status of Selected Ecosystems Using Optical and Microwave Remote Sensing Data

    Science.gov (United States)

    Dabrowska-Zielinska, Katarzyna; Budzynska, Maria; Kowalik, Wanda; Malek, Iwona; Turlej, Konrad

    2010-12-01

    Wetlands areas are one of the most sensitive ecosystem. This study was conducted in the Biebrza Valley, a NATURA 2000 and Ramsar Convention test site situated in Northeast Poland. The paper presents monitoring and mapping of various soil-vegetation variables using optical and microwave satellite data. Satellite data applied for the study included: ENVISAT ASAR and MERIS, ALOS.PALSAR, NOAA.AVHRR. Optical images were used for classification of wetlands communities and calculation of vegetation indices. The method of estimating Latent Heat Flux (LE) from NOAA.AVHRR and meteorological data and calculation of soil moisture index as ratio of Sensible Heat Flux (H) to LE were also applied. Parallel to satellite observations the soil-vegetation variables were measured at the test site. Data from optical and microwave satellite images and soil-vegetation ground truth measurements were analysed to develop methods for the Leaf Area Index (LAI) and soil moisture estimates over wetlands. The presented results allow monitoring and mapping soil-vegetation parameters of wetlands and its changes over the time. The methodology developed is suitable for applications to the system of monitoring wetlands in Europe. The studied areas can be recognized as a reference for other wetlands. The examined ecosystem is of great importance in nature conservation and water storage capability in Europe. The Project was carried out in the framework of the national grant N N526 0217 33. The satellite images have been obtained for ESA projects AO ID 122 and AOALO.3742.

  2. 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

  3. Airborne Optical and Thermal Remote Sensing for Wildfire Detection and Monitoring

    Science.gov (United States)

    Allison, Robert S.; Johnston, Joshua M.; Craig, Gregory; Jennings, Sion

    2016-01-01

    For decades detection and monitoring of forest and other wildland fires has relied heavily on aircraft (and satellites). Technical advances and improved affordability of both sensors and sensor platforms promise to revolutionize the way aircraft detect, monitor and help suppress wildfires. Sensor systems like hyperspectral cameras, image intensifiers and thermal cameras that have previously been limited in use due to cost or technology considerations are now becoming widely available and affordable. Similarly, new airborne sensor platforms, particularly small, unmanned aircraft or drones, are enabling new applications for airborne fire sensing. In this review we outline the state of the art in direct, semi-automated and automated fire detection from both manned and unmanned aerial platforms. We discuss the operational constraints and opportunities provided by these sensor systems including a discussion of the objective evaluation of these systems in a realistic context. PMID:27548174

  4. Airborne Optical and Thermal Remote Sensing for Wildfire Detection and Monitoring

    Directory of Open Access Journals (Sweden)

    Robert S. Allison

    2016-08-01

    Full Text Available For decades detection and monitoring of forest and other wildland fires has relied heavily on aircraft (and satellites. Technical advances and improved affordability of both sensors and sensor platforms promise to revolutionize the way aircraft detect, monitor and help suppress wildfires. Sensor systems like hyperspectral cameras, image intensifiers and thermal cameras that have previously been limited in use due to cost or technology considerations are now becoming widely available and affordable. Similarly, new airborne sensor platforms, particularly small, unmanned aircraft or drones, are enabling new applications for airborne fire sensing. In this review we outline the state of the art in direct, semi-automated and automated fire detection from both manned and unmanned aerial platforms. We discuss the operational constraints and opportunities provided by these sensor systems including a discussion of the objective evaluation of these systems in a realistic context.

  5. The aerosol optical properties measurement by ground remote sensing in Zhejiang, China

    Science.gov (United States)

    Wang, Bin; Jiang, Hong; Chen, Jian; Jiang, Zishan; Yu, Shuquan; Ma, Yuandan

    2009-10-01

    The aerosol optical depth was affected by the chemical composition, the particle size and the shape of aerosol as well as the water vapor in the atmosphere; it is an important indicator for air pollution. The special and temporal characteristics of aerosol optical depth (AOD) was measured by CE318 sun-photometer, Angstrom wavelength exponent (Alpha) and the aerosol turbidity coefficient (β) were calculated in Ningbo, Lin'an and Qiandaohu of Zhejiang province from 2007 to 2008. We also analyzed the relationship between AOD and Angstrom wavelength exponent (Alpha) in these stations. The results show that there are different pattern of AOD in this gradient of urban and suburban region. Lin'an station had two peaks of AOD, but Ningbo and Qiandaohu stations had single peak of AOD in measurement year. The difference of AOD seasonal pattern exists in three sites. The Angstrom wavelength exponent (Alpha) analysis suggests that the aerosol sizes in three stations various from fine particle in autumn to coarse particle in spring. The seasonal patterns show that spring air pollution is serious, summer is relatively clean, and autumn and winter are relative serious in three stations.

  6. 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.

  7. Comparing mesoscale chemistry-transport model and remote-sensed Aerosol Optical Depth

    CERN Document Server

    Carnevale, C; Pisoni, E; Volta, M

    2010-01-01

    A comparison of modeled and observed Aerosol Optical Depth (AOD) is presented. 3D Eulerian multiphase chemistry-transport model TCAM is employed for simulating AOD at mesoscale. MODIS satellite sensor and AERONET photometer AOD are used for comparing spatial patterns and temporal timeseries. TCAM simulations for year 2004 over a domain containing Po-Valley and nearly whole Northern Italy are employed. For the computation of AOD, a configuration of external mixing of the chemical species is considered. Furthermore, a parametrization of the effect of moisture affecting both aerosol size and composition is used. An analysis of the contributions of the granulometric classes to the extinction coefficient reveals the dominant role of the inorganic compounds of submicron size. For the analysis of spatial patterns, summer and winter case study are considered. TCAM AOD reproduces spatial patterns similar to those retrieved from space, but AOD values are generally smaller by an order of magnitude. However, accounting a...

  8. Automated Solar Tracking Spectrophotometer for Remote Sensing of Column Aerosol Optical Depth

    Science.gov (United States)

    Rainwater, B.; Arnott, W. P.; Moosmuller, H.; Karr, D.

    2012-12-01

    Aerosols in the atmosphere are poorly understood in terms of how they affect weather and climate. In an effort to advance this knowledge, an automated solar tracking spectrophotometer has been constructed to measure direct solar radiation from the ultraviolet to infrared. This instrument facilitates determination of solar irradiance, precipitable water, aerosol optical depth (AOD), and the Ångström turbidity exponent related to aerosol size distribution. Measurements with a CIMEL CE-318 sun photometer (part of the global NASA AERONET network) and a manual solar spectrophotometer are being used to evaluate the accuracy of our instrument. Upon successful evaluation, this instrument will provide a basis for research into spectral information that will supplement CIMEL measurements. Presented is the design of this instrument and measurement comparisons with the aforementioned instruments for the air above Reno, Nevada, USA.

  9. Research and implementation of simulation for TDICCD remote sensing in vibration of optical axis

    Science.gov (United States)

    Liu, Zhi-hong; Kang, Xiao-jun; Lin, Zhe; Song, Li

    2013-12-01

    During the exposure time, the charge transfer speed in the push-broom direction and the line-by-lines canning speed of the sensor are required to match each other strictly for a space-borne TDICCD push-broom camera. However, as attitude disturbance of satellite and vibration of camera are inevitable, it is impossible to eliminate the speed mismatch, which will make the signal of different targets overlay each other and result in a decline of image resolution. The effects of velocity mismatch will be visually observed and analyzed by simulating the degradation of image quality caused by the vibration of the optical axis, and it is significant for the evaluation of image quality and design of the image restoration algorithm. How to give a model in time domain and space domain during the imaging time is the problem needed to be solved firstly. As vibration information for simulation is usually given by a continuous curve, the pixels of original image matrix and sensor matrix are discrete, as a result, they cannot always match each other well. The effect of simulation will also be influenced by the discrete sampling in integration time. In conclusion, it is quite significant for improving simulation accuracy and efficiency to give an appropriate discrete modeling and simulation method. The paper analyses discretization schemes in time domain and space domain and presents a method to simulate the quality of image of the optical system in the vibration of the line of sight, which is based on the principle of TDICCD sensor. The gray value of pixels in sensor matrix is obtained by a weighted arithmetic, which solves the problem of pixels dismatch. The result which compared with the experiment of hardware test indicate that this simulation system performances well in accuracy and reliability.

  10. Monitoring of Emissions From a Refinery Tank Farm Using a Combination of Optical Remote Sensing Techniques

    Science.gov (United States)

    Polidori, A.; Tisopulos, L.; Pikelnaya, O.; Mellqvist, J.; Samuelsson, J.; Marianne, E.; Robinson, R. A.; Innocenti, F.; Finlayson, A.; Hashmonay, R.

    2016-12-01

    Despite great advances in reducing air pollution, the South Coast Air Basin (SCAB) still faces challenges to attain federal health standards for air quality. Refineries are large sources of ozone precursors and, hence contribute to the air quality problems of the region. Additionally, petrochemical facilities are also sources of other hazardous air pollutants (HAP) that adversely affect human health, for example aromatic hydrocarbons. In order to assure safe operation, decrease air pollution and minimize population exposure to HAP the South Coast Air Quality Management District (SCAQMD) has a number of regulations for petrochemical facilities. However, significant uncertainties still exist in emission estimates and traditional monitoring techniques often do not allow for real-time emission monitoring. In the fall of 2015 the SCAQMD, Fluxsense Inc., the National Physical Laboratory (NPL), and Atmosfir Optics Ltd. conducted a measurement study to characterize and quantify gaseous emissions from the tank farm of one of the largest oil refineries in the SCAB. Fluxsense used a vehicle equipped with Solar Occultation Flux (SOF), Differential Optical Absorption Spectroscopy (DOAS), and Extractive Fourier Transform Infrared (FTIR) spectroscopy instruments. Concurrently, NPL operated their Differential Absorption Lidar (DIAL) system. Both research groups quantified emissions from the entire tank farm and identified fugitive emission sources within the farm. At the same time, Atmosfir operated an Open Path FTIR (OP-FTIR) spectrometer along the fenceline of the tank farm. During this presentation we will discuss the results of the emission measurements from the tank farm of the petrochemical facility. Emission rates resulting from measurements by different ORS methods will be compared and discussed in detail.

  11. Optical Characterisation of Suspended Particles in the Mackenzie River Plume (Canadian Arctic Ocean) and Implications for Ocean Colour Remote Sensing

    Science.gov (United States)

    Doxaran, D.; Ehn, J.; Belanger, S.; Matsuoka, A.; Hooker, S.; Babin, M.

    2012-01-01

    Climate change significantly impacts Arctic shelf regions in terms of air temperature, ultraviolet radiation, melting of sea ice, precipitation, thawing of permafrost and coastal erosion. Direct consequences have been observed on the increasing Arctic river flow and a large amount of organic carbon sequestered in soils at high latitudes since the last glacial maximum can be expected to be delivered to the Arctic Ocean during the coming decade. Monitoring the fluxes and fate of this terrigenous organic carbon is problematic in such sparsely populated regions unless remote sensing techniques can be developed and proved to be operational. The main objective of this study is to develop an ocean colour algorithm to operationally monitor dynamics of suspended particulate matter (SPM) on the Mackenzie River continental shelf (Canadian Arctic Ocean) using satellite imagery. The water optical properties are documented across the study area and related to concentrations of SPM and particulate organic carbon (POC). Robust SPM and POC : SPM proxies are identified, such as the light backscattering and attenuation coefficients, and relationships are established between these optical and biogeochemical parameters. Following a semi-analytical approach, a regional SPM quantification relationship is obtained for the inversion of the water reflectance signal into SPM concentration. This relationship is reproduced based on independent field optical measurements. It is successfully applied to a selection of MODIS satellite data which allow estimating fluxes at the river mouth and monitoring the extension and dynamics of the Mackenzie River surface plume in 2009, 2010 and 2011. Good agreement is obtained with field observations representative of the whole water column in the river delta zone where terrigenous SPM is mainly constrained (out of short periods of maximum river outflow). Most of the seaward export of SPM is observed to occur within the west side of the river mouth. Future

  12. Optical characterisation of suspended particles in the Mackenzie River plume (Canadian Arctic Ocean and implications for ocean colour remote sensing

    Directory of Open Access Journals (Sweden)

    D. Doxaran

    2012-08-01

    Full Text Available Climate change significantly impacts Arctic shelf regions in terms of air temperature, ultraviolet radiation, melting of sea ice, precipitation, thawing of permafrost and coastal erosion. Direct consequences have been observed on the increasing Arctic river flow and a large amount of organic carbon sequestered in soils at high latitudes since the last glacial maximum can be expected to be delivered to the Arctic Ocean during the coming decade. Monitoring the fluxes and fate of this terrigenous organic carbon is problematic in such sparsely populated regions unless remote sensing techniques can be developed and proved to be operational.

    The main objective of this study is to develop an ocean colour algorithm to operationally monitor dynamics of suspended particulate matter (SPM on the Mackenzie River continental shelf (Canadian Arctic Ocean using satellite imagery. The water optical properties are documented across the study area and related to concentrations of SPM and particulate organic carbon (POC. Robust SPM and POC : SPM proxies are identified, such as the light backscattering and attenuation coefficients, and relationships are established between these optical and biogeochemical parameters. Following a semi-analytical approach, a regional SPM quantification relationship is obtained for the inversion of the water reflectance signal into SPM concentration. This relationship is reproduced based on independent field optical measurements. It is successfully applied to a selection of MODIS satellite data which allow estimating fluxes at the river mouth and monitoring the extension and dynamics of the Mackenzie River surface plume in 2009, 2010 and 2011. Good agreement is obtained with field observations representative of the whole water column in the river delta zone where terrigenous SPM is mainly constrained (out of short periods of maximum river outflow. Most of the seaward export of SPM is observed to occur within the west side of

  13. Optical characterisation of suspended particles in the Mackenzie River plume (Canadian Arctic Ocean) and implications for ocean colour remote sensing

    Science.gov (United States)

    Doxaran, D.; Ehn, J.; Bélanger, S.; Matsuoka, A.; Hooker, S.; Babin, M.

    2012-08-01

    Climate change significantly impacts Arctic shelf regions in terms of air temperature, ultraviolet radiation, melting of sea ice, precipitation, thawing of permafrost and coastal erosion. Direct consequences have been observed on the increasing Arctic river flow and a large amount of organic carbon sequestered in soils at high latitudes since the last glacial maximum can be expected to be delivered to the Arctic Ocean during the coming decade. Monitoring the fluxes and fate of this terrigenous organic carbon is problematic in such sparsely populated regions unless remote sensing techniques can be developed and proved to be operational. The main objective of this study is to develop an ocean colour algorithm to operationally monitor dynamics of suspended particulate matter (SPM) on the Mackenzie River continental shelf (Canadian Arctic Ocean) using satellite imagery. The water optical properties are documented across the study area and related to concentrations of SPM and particulate organic carbon (POC). Robust SPM and POC : SPM proxies are identified, such as the light backscattering and attenuation coefficients, and relationships are established between these optical and biogeochemical parameters. Following a semi-analytical approach, a regional SPM quantification relationship is obtained for the inversion of the water reflectance signal into SPM concentration. This relationship is reproduced based on independent field optical measurements. It is successfully applied to a selection of MODIS satellite data which allow estimating fluxes at the river mouth and monitoring the extension and dynamics of the Mackenzie River surface plume in 2009, 2010 and 2011. Good agreement is obtained with field observations representative of the whole water column in the river delta zone where terrigenous SPM is mainly constrained (out of short periods of maximum river outflow). Most of the seaward export of SPM is observed to occur within the west side of the river mouth. Future

  14. Remotely Sensed Optical Water Quality for Water Quality Assessment and Seagrass Protection in Florida's Big Bend Region

    Science.gov (United States)

    Carlson, P. R.; Hu, C.; Cannizarro, J.; Yarbro, L. A.; English, D. C.; Magley, W.; Charbonneau, M.; Barnes, B.

    2012-12-01

    Florida's Big Bend coastal region contains the second largest contiguous seagrass bed in the continental US. Approximately 250,000 ha of seagrass have been mapped in the region, but the total area of offshore seagrass beds might be several times greater. The Suwannee River drains a largely agricultural watershed (26,000 km2) in Georgia and Florida, and its discharge (x= 280 m3/s) affects water clarity over most of the Big Bend seagrass beds. Seagrass density, species composition and areal extent were severely affected by discharge associated with tropical cyclones in 2004 and 2005, focusing attention on this important resource and the near- and far-field impacts of the Suwannee River discharge. The Lower Suwannee River also has been identified by the Florida Department of Environmental Protection as an impaired water body due to high nitrogen and algal biomass. This project attempts to improve water quality and to protect Big Bend seagrasses by making remotely sensed optical water quality data more accessible to managers and stakeholders involved in the process of regulating nutrient loads in the Suwannee River and to provide data to assess effectiveness of management actions. To accomplish these goals, we have developed and tested new algorithms for retrieval of Kd, chlorophyll, and CDOM from Modis imagery, created a time series of optical water quality (OWQ) for the Suwannee River Estuary (SRE), and related seagrass gains and losses to annual variations in optical water quality. During two years of bimonthly ground-truth cruises, chlorophyll concentrations, Aph, Ad, and Acdom in the SRE were 0.3-38.3 mgm-3, 0.013-1.056, 0.013-0.735, and 0.042-7.24, respectively. For most locations and most cruises, CDOM was the dominant determinant of Kd. In the Modis time series, Kd488 estimates (calculated using the Quasi-Analytic Algorithm of Lee et al. 2006) covaried with Suwannee River discharge between 2002 and 2011 with an overall r2 value of 0.64. This relationship is

  15. Remote sensing of natural phenomena

    Directory of Open Access Journals (Sweden)

    Miodrag D. Regodić

    2014-06-01

    Full Text Available There has always been a need to directly perceive and study the events whose extent is beyond people's possibilities. In order to get new data and to make observations and studying much more objective in comparison with past syntheses - a new method of examination called remote sensing has been adopted. The paper deals with the principles and elements of remote sensing, as well as with the basic aspects of using remote research in examining meteorological (weather parameters and the conditions of the atmosphere. The usage of satellite images is possible in all phases of the global and systematic research of different natural phenomena when airplane and satellite images of different characteristics are used and their analysis and interpretation is carried out by viewing and computer added procedures. Introduction Remote sensing of the Earth enables observing and studying global and local events that occur on it. Satellite images are nowadays used in geology, agriculture, forestry, geodesy, meteorology, spatial and urbanism planning, designing of infrastructure and other objects, protection from natural and technological catastrophes, etc. It it possible to use satellite images in all phases of global and systematic research of different natural phenomena. Basics of remote sensing Remote sensing is a method of the acquisition and interpretation of information about remote objects without making a physical contact with them. The term Daljinska detekcija is a literal translation of the English term Remote Sensing. In French it isTeledetection, in German - Fernerkundung, in Russian - дистанционие иследования. We also use terms such as: remote survailance, remote research, teledetection, remote methods, and distance research. The basic elements included in Remote Sensing are: object, electromagnetic energy, sensor, platform, image, analysis, interpretation and the information (data, fact. Usage of satellite remote research in

  16. A Low-Cost Optical Remote Sensing Application for Glacier Deformation Monitoring in an Alpine Environment

    Directory of Open Access Journals (Sweden)

    Daniele Giordan

    2016-10-01

    Full Text Available In this work, we present the results of a low-cost optical monitoring station designed for monitoring the kinematics of glaciers in an Alpine environment. We developed a complete hardware/software data acquisition and processing chain that automatically acquires, stores and co-registers images. The system was installed in September 2013 to monitor the evolution of the Planpincieux glacier, within the open-air laboratory of the Grandes Jorasses, Mont Blanc massif (NW Italy, and collected data with an hourly frequency. The acquisition equipment consists of a high-resolution DSLR camera operating in the visible band. The data are processed with a Pixel Offset algorithm based on normalized cross-correlation, to estimate the deformation of the observed glacier. We propose a method for the pixel-to-metric conversion and present the results of the projection on the mean slope of the glacier. The method performances are compared with measurements obtained by GB-SAR, and exhibit good agreement. The system provides good support for the analysis of the glacier evolution and allows the creation of daily displacement maps.

  17. Assessment of SPOT-6 optical remote sensing data against GF-1 using NNDiffuse image fusion algorithm

    Science.gov (United States)

    Zhao, Jinling; Guo, Junjie; Cheng, Wenjie; Xu, Chao; Huang, Linsheng

    2017-07-01

    A cross-comparison method was used to assess the SPOT-6 optical satellite imagery against Chinese GF-1 imagery using three types of indicators: spectral and color quality, fusion effect and identification potential. More specifically, spectral response function (SRF) curves were used to compare the two imagery, showing that the SRF curve shape of SPOT-6 is more like a rectangle compared to GF-1 in blue, green, red and near-infrared bands. NNDiffuse image fusion algorithm was used to evaluate the capability of information conservation in comparison with wavelet transform (WT) and principal component (PC) algorithms. The results show that NNDiffuse fused image has extremely similar entropy vales than original image (1.849 versus 1.852) and better color quality. In addition, the object-oriented classification toolset (ENVI EX) was used to identify greenlands for comparing the effect of self-fusion image of SPOT-6 and inter-fusion image between SPOT-6 and GF-1 based on the NNDiffuse algorithm. The overall accuracy is 97.27% and 76.88%, respectively, showing that self-fused image of SPOT-6 has better identification capability.

  18. 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

  19. 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.

  20. 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

  1. Geochemical characterization of supraglacial debris via in situ and optical remote sensing methods: a case study in Khumbu Himalaya, Nepal

    OpenAIRE

    K. A. Casey; A. Kääb; D. I. Benn

    2012-01-01

    Surface glacier debris samples and field spectra were collected from the ablation zones of Nepal Himalaya Ngozumpa and Khumbu glaciers in November and December 2009. Geochemical and mineral compositions of supraglacial debris were determined by X-ray diffraction and X-ray fluorescence spectroscopy. This composition data was used as ground truth in evaluating field spectra and satellite supraglacial debris composition and mapping methods. Satellite remote sensing methods for ...

  2. Adjusted normalized emissivity method for surface temperature and emissivity retrieval from optical and thermal infrared remote sensing data

    OpenAIRE

    Coll Company, César; Valor i Micó, Enric; Caselles Miralles, Vicente; Niclòs Corts, Raquel

    2003-01-01

    A methodology for the retrieval of surface temperatures and emissivities combining visible, near infrared and thermal infrared remote sensing data was applied to Digital Airborne Imaging Spectrometer (DAIS) data and validated with coincident ground measurements acquired in a multiyear experiment held in an agricultural site in Barrax, Spain. The Adjusted Normalized Emissivity Method (ANEM) is based on the use of visible and near infrared data to estimate the vegetation cover and model the max...

  3. 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.

  4. [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.

  5. Remote sensing using airships

    Energy Technology Data Exchange (ETDEWEB)

    Lavan, C.K. Jr. [Loral Defense Systems-Akron, OH (United States)

    1996-10-01

    Loral Defense Systems-Akron (LDSA) has developed a laser-based mine detection system in response to the US Navy`s requirements for detecting, localizing and classifying mines in deep water shipping channels. This sensor system was tested recently at the Navy`s David Taylor Research Center (DTRC) at Bethesda, MD and at the US Army`s Camp Perry near Lake Erie. The testing at Camp Perry involved installation of the sensor system on the Goodyear Tim & Rubber Company`s airship {open_quotes}Spirit of Akron{close_quotes} and the conduct of control flight test experiments over Lake Erie. Resultant imagery has been analyzed in terms of water optical properties. Further tests are planned in a multispectral mode incorporating both active illumination and passive detection. The system can be extended to the detection of Unexploded Ordnance (UXO) in government test ranges and to detection of other devices both buried and at the surface. The utility of the airship (blimp) makes the approach practical due to long endurance, wide speed range and platform flexibility. 14 figs.

  6. 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...

  7. 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...

  8. 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...

  9. 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.

  10. 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.

  11. 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)

  12. 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.

  13. Prediction of grain yield using optical remote sensing and a growth model: application on Merguellil catchment (Tunisia)

    Science.gov (United States)

    Chahbi, A.; Zribi, M.; Lili-Chabaane, Z.; Duchemin, B.; Shabou, M.; Mougenot, B.; Boulet, G.

    2012-04-01

    In semi-arid region and especially in irrigated areas, agriculture represents a major contribution to food security. These areas significantly contribute to the increase of global production. A challenging objective is thus to ensure food security. Therefore an operational forecasting system for the grain yields is required and could help decision-makers to make early decisions and plan annual imports. In this context, remote sensing is a very interesting tool for giving information on the development of vegetation. The main objective is to analyze and predict the average grain yield, based on different indices measured or modelled during the growing season. Thus, we used three lines of research: the first is based on analysing a relationship between normalized vegetation index (NDVI) which is determined from optical satellite imagery and the leaf area index (LAI) measured in situ. The second axis is based on the estimation of the relation between wheat yields and normalized vegetation index NDVI. The third axis is based on the application of a growth model SAFY « Simple Algorithm For Yield Estimate » developed to simulate LAI, dry aboveground phytomass (DAM) and the grain yield (GY). For the first axis, we used optical data at high resolution. A series of 7 SPOT / HRV during the 2010-2011 agricultural seasons was acquired in the Merguellil catchment (Tunisia). At the same time we realised experimental measurements made on 27 test plots of dry or irrigated cereals carried out in study area. These measurements are mainly: the water content of the vegetation, the vegetation height, wheat density and leaf area index LAI (estimated using a hemispherical camera). From satellite data, a profile of the normalized difference vegetation index (NDVI) was generated for each pixel. For both types of cereal, a relationship is established between NDVI and leaf area index LAI. This relationship is exponential and it allows connecting the satellite observations with a variable

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

    Directory of Open Access Journals (Sweden)

    Wesley J. Moses

    2015-03-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  16. Potentialities of laser systems for remote sensing of the atmosphere at a wide variability of optical and physical characteristics: dimensionless-parametric modelling

    Science.gov (United States)

    Agishev, R. R.

    2017-02-01

    Within the framework of generalisation of different approaches to the modelling of atmospheric lidars, the methodology capabilities for dimensionless-parametric analysis are expanded. The developed approach simplifies the analysis of the signal-to-noise ratio and potential capabilities of existing and newly developed monitoring systems with a wide variability of atmospheric and optical conditions and a great variety of modern lidars. Its applicability to the problems of remote atmospheric sensing, environmental monitoring and lidar navigation in providing the eye safety, noise immunity and reliability is discussed.

  17. 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.

  18. Web tools concerning performance analysis and planning support for solar energy plants starting from remotely sensed optical images

    Energy Technology Data Exchange (ETDEWEB)

    Morelli, Marco, E-mail: marco.morelli1@unimi.it [Department of Physics, University of Milano, Via Celoria 16, 20133 Milano (Italy); Masini, Andrea, E-mail: andrea.masini@flyby.it [Flyby S.r.l., Via Puini 97, 57128 Livorno (Italy); Ruffini, Fabrizio, E-mail: fabrizio.ruffini@i-em.eu [i-EM S.r.l., Via Lampredi 45, 57121 Livorno (Italy); Potenza, Marco Alberto Carlo, E-mail: marco.potenza@unimi.it [Department of Physics, University of Milano, Via Celoria 16, 20133 Milano (Italy)

    2015-04-15

    We present innovative web tools, developed also in the frame of the FP7 ENDORSE (ENergy DOwnstReam SErvices) project, for the performance analysis and the support in planning of solar energy plants (PV, CSP, CPV). These services are based on the combination between the detailed physical model of each part of the plants and the near real-time satellite remote sensing of incident solar irradiance. Starting from the solar Global Horizontal Irradiance (GHI) data provided by the Monitoring Atmospheric Composition and Climate (GMES-MACC) Core Service and based on the elaboration of Meteosat Second Generation (MSG) satellite optical imagery, the Global Tilted Irradiance (GTI) or the Beam Normal Irradiance (BNI) incident on plant's solar PV panels (or solar receivers for CSP or CPV) is calculated. Combining these parameters with the model of the solar power plant, using also air temperature values, we can assess in near-real-time the daily evolution of the alternate current (AC) power produced by the plant. We are therefore able to compare this satellite-based AC power yield with the actually measured one and, consequently, to readily detect any possible malfunctions and to evaluate the performances of the plant (so-called “Controller” service). Besides, the same method can be applied to satellite-based averaged environmental data (solar irradiance and air temperature) in order to provide a Return on Investment analysis in support to the planning of new solar energy plants (so-called “Planner” service). This method has been successfully applied to three test solar plants (in North, Centre and South Italy respectively) and it has been validated by comparing satellite-based and in-situ measured hourly AC power data for several months in 2013 and 2014. The results show a good accuracy: the overall Normalized Bias (NB) is − 0.41%, the overall Normalized Mean Absolute Error (NMAE) is 4.90%, the Normalized Root Mean Square Error (NRMSE) is 7.66% and the overall

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Characterization of glacier debris cover via in situ and optical remote sensing methods: a case study in the Khumbu Himalaya, Nepal

    Directory of Open Access Journals (Sweden)

    K. A. Casey

    2011-02-01

    Full Text Available Field spectrometry and physical samples of debris, snow and ice were collected from the ablation zones of Ngozumpa and Khumbu glaciers of the Khumbu Himalaya, Nepal in November and December 2009. Field acquired spectral reflectances and mineral and chemical composition of samples were used as ground truth for comparison with satellite optical remote sensing data. Supraglacial debris was characterized by several optical remote sensing methods, including hyperspectral reflectance analysis, multispectral band composites and indices, spectral angle relationships, thermal band temperature and emissivity analysis, as well as repeat image derived glacier velocity and theoretical supraglacial particle transport. Supraglacial mineral components were identified and mineral abundances were estimated on Khumbu Himalayan glaciers. Mass flux was estimated by false color composites and glacier velocity displacement fields. Supraglacial temperatures were compared with mineral abundances, implying potential parameters to estimate differential melt. Overall, glaciologic implications of debris cover characterizations are applicable to (1 glacier energy balance, (2 glacial kinematics and (3 mapping glacial extent. The methods presented can be used in synergy to improve supraglacial debris quantification and reduce errors associated with debris covered ice extent mapping, surface radiative properties, as well as debris covered ice mass flux and loss estimations.

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

    Science.gov (United States)

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

    2015-05-01

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

  5. 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.

  6. 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.

  7. 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

  8. 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...

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 遥感卫星光电传感器参数%The Optical Parameters of Remote Sensing Satellite

    Institute of Scientific and Technical Information of China (English)

    陈虹; 李世忠; 张武; 张丽

    2000-01-01

    自1990年以来,人类发射了多颗性能良好的遥感卫星,为了充分利用不同传感器特有的优势,需要对来自不同传感器的数据进行融合,其关键是提高融合数据之间的关联性和依赖性。如果全球能有标准一致的传感器参数,便可使遥感信息得到最大程度的利用。从与空间分辨率、辐射分辨率、光谱分辨率和时间分辨率有关的参数等几个方面探讨了遥感卫星光电传感器的参数。%Since America launched the first real earth observing satellite in 1972, and with the wide use of the data received from it in the fields of monitor and all kinds of resource management, the research results showed that the performance of the observation system need to be improved. Data users want the remote data to have higher spatial resolution, radiation resolution, spectrum resolution and temporal resolution. Human being has launched a number of remote sensing satellites with improved capabilities since 1990. Because they carries different types of sensors, in order to make full use of various sensors’ advantage, the fusion of data from various sensors should be done and the key point is to increase the relevance and dependence of the fusion. Of all parameters listed in the paper, the main factors which affect the relevance and dependence of the fusion are instantaneous geometry field of view (IGFOV), radiate accuracy instantaneous field of view (RAIFOV), center wave length, band width, radiate accuracy and repeat period. If the sensor parameters are standardized globally, the information can be maximal used. The paper discussed the parameters of remote sensing satellites in terms of spatial, radiometric, spectral and temporal resolution.

  14. Remote Atmospheric Nonlinear Optical Magnetometry

    Science.gov (United States)

    2014-04-28

    Boyd , Nonlinear Optics (Elsevier, Burlington, MA, 2008). [13] M. Scully and S. Zubairy, Quantum Optics (Cambridge U. Press, Cambridge, UK, 1997...Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/6703--14-9548 Remote Atmospheric Nonlinear Optical Magnetometry PhilliP SPrangle...b. ABSTRACT c. THIS PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT Remote Atmospheric Nonlinear Optical Magnetometry Phillip Sprangle, Luke

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

    Science.gov (United States)

    Guo, H., II

    2016-12-01

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

  16. Using High Spatio-Temporal Optical Remote Sensing to Monitor Dissolved Organic Carbon in the Arctic River Yenisei

    Directory of Open Access Journals (Sweden)

    Pierre-Alexis Herrault

    2016-09-01

    Full Text Available In Arctic regions, a major concern is the release of carbon from melting permafrost that could greatly exceed current human carbon emissions. Arctic rivers drain these organic-rich watersheds (Ob, Lena, Yenisei, Mackenzie, Yukon but field measurements at the outlets of these great Arctic rivers are constrained by limited accessibility of sampling sites. In particular, the highest dissolved organic carbon (DOC fluxes are observed throughout the ice breakup period that occurs over a short two to three-week period in late May or early June during the snowmelt-generated peak flow. The colored fraction of dissolved organic carbon (DOC which absorbs UV and visible light is designed as chromophoric dissolved organic matter (CDOM. It is highly correlated to DOC in large arctic rivers and streams, allowing for remote sensing to monitor DOC concentrations from satellite imagery. High temporal and spatial resolutions remote sensing tools are highly relevant for the study of DOC fluxes in a large Arctic river. The high temporal resolution allows for correctly assessing this highly dynamic process, especially the spring freshet event (a few weeks in May. The high spatial resolution allows for assessing the spatial variability within the stream and quantifying DOC transfer during the ice break period when the access to the river is almost impossible. In this study, we develop a CDOM retrieval algorithm at a high spatial and a high temporal resolution in the Yenisei River. We used extensive DOC and DOM spectral absorbance datasets from 2014 and 2015. Twelve SPOT5 (Take5 and Landsat 8 (OLI images from 2014 and 2015 were examined for this investigation. Relationships between CDOM and spectral variables were explored using linear models (LM. Results demonstrated the capacity of a CDOM algorithm retrieval to monitor DOC fluxes in the Yenisei River during a whole open water season with a special focus on the peak flow period. Overall, future Sentinel2/Landsat8

  17. 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.

  18. 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

  19. An Optical Flow Method Applied to Co-Registration of Remote Sensing Images: Example for SAR/SAR, SAR/LIDAR, SAR/Optical Images of BIOSAR 2010 Campaign

    Science.gov (United States)

    Colin-Koeniguer, Elise

    2016-08-01

    This article proposes an optical flow type method for coregistration of forest remote sensing images. The principle of the algorithm called GeFolki is first explained. Results are shown on the images of the BioSAR 3 campaign, for the production of SAR interferograms, the coregistration a SAR and LIDAR image, and the coregistration an optical image and SAR image.The advantages of such an algorithm over conventional algorithms are explained. Finally, we propose various applications within the operating data for future BIOMASS mission: massive interferometry, ground truth production, upscaling by fusion of LIDAR and SAR data, and image mining.

  20. 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…

  1. 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...

  2. 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.

  3. 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.

  4. 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.

  5. Simple statistical formulas for estimating biogeochemical properties of suspended particulate matter in the southern Baltic Sea potentially useful for optical remote sensing applications

    Directory of Open Access Journals (Sweden)

    Sławomir B. Woźniak

    2014-01-01

    Full Text Available Simple statistical formulas for estimating various biogeochemical properties of suspended particulate matter in the southern Baltic Sea are presented in this paper. These include formulas for estimating mass concentrations of suspended particulate matter (SPM, particulate organic matter (POM, particulate organic carbon (POC and total chlorophyll a (Chl a. Two different approaches have been adopted. The first approach was to use the available empirical material (the results of field measurements and laboratory analyses of discrete water samples and find statistical formulas for estimating the biogeochemical properties of suspended particulate matter from those of inherent optical properties (IOPs, which are potentially retrievable from remote sensing measurements. The second approach was to find formulas that would enable biogeochemical properties of suspended particulate matter to be estimated directly from spectral values of the remote-sensing reflectance Rrs. The latter was based on statistical analyses of a synthetic data set of Rrs obtained from numerical simulations of radiative transfer for which the available empirical material on seawater IOPs and biogeochemistry served as input data. Among the empirical formulas based on seawater IOPs that could be used as a step in two-stage remote sensing algorithms (the other step is estimating certain IOPs from reflectance, the best error statistics are found for estimates of SPM and POM from the particulate backscattering coefficient bbp in the blue region of light wavelengths (443 nm, and for estimates of POC and Chl a from the coefficient of light absorption by the sum of all non-water (i.e. suspended and dissolved constituents of seawater an, in the blue (443 nm and green (555 nm parts of the spectrum respectively. For the semi-empirical formulas under consideration, which could serve as starting points in the development of local one-stage (direct remote sensing algorithms, the best error

  6. Geochemical characterization of supraglacial debris via in situ and optical remote sensing methods: a case study in Khumbu Himalaya, Nepal

    Directory of Open Access Journals (Sweden)

    K. A. Casey

    2012-01-01

    Full Text Available Surface glacier debris samples and field spectra were collected from the ablation zones of Nepal Himalaya Ngozumpa and Khumbu glaciers in November and December 2009. Geochemical and mineral compositions of supraglacial debris were determined by X-ray diffraction and X-ray fluorescence spectroscopy. This composition data was used as ground truth in evaluating field spectra and satellite supraglacial debris composition and mapping methods. Satellite remote sensing methods for characterizing glacial surface debris include visible to thermal infrared hyper- and multispectral reflectance and emission signature identification, semi-quantitative mineral abundance indicies and spectral image composites. Satellite derived supraglacial debris mineral maps displayed the predominance of layered silicates, hydroxyl-bearing and calcite minerals on Khumbu Himalayan glaciers. Supraglacial mineral maps compared with satellite thermal data revealed correlations between glacier surface composition and glacier surface temperature. Glacier velocity displacement fields and shortwave, thermal infrared false color composites indicated the magnitude of mass flux at glacier confluences. The supraglacial debris mapping methods presented in this study can be used on a broader scale to improve, supplement and potentially reduce errors associated with glacier debris radiative property, composition, areal extent and mass flux quantifications.

  7. Geochemical characterization of supraglacial debris via in situ and optical remote sensing methods: a case study in Khumbu Himalaya, Nepal

    Science.gov (United States)

    Casey, K. A.; Kääb, A.; Benn, D. I.

    2012-01-01

    Surface glacier debris samples and field spectra were collected from the ablation zones of Nepal Himalaya Ngozumpa and Khumbu glaciers in November and December 2009. Geochemical and mineral compositions of supraglacial debris were determined by X-ray diffraction and X-ray fluorescence spectroscopy. This composition data was used as ground truth in evaluating field spectra and satellite supraglacial debris composition and mapping methods. Satellite remote sensing methods for characterizing glacial surface debris include visible to thermal infrared hyper- and multispectral reflectance and emission signature identification, semi-quantitative mineral abundance indicies and spectral image composites. Satellite derived supraglacial debris mineral maps displayed the predominance of layered silicates, hydroxyl-bearing and calcite minerals on Khumbu Himalayan glaciers. Supraglacial mineral maps compared with satellite thermal data revealed correlations between glacier surface composition and glacier surface temperature. Glacier velocity displacement fields and shortwave, thermal infrared false color composites indicated the magnitude of mass flux at glacier confluences. The supraglacial debris mapping methods presented in this study can be used on a broader scale to improve, supplement and potentially reduce errors associated with glacier debris radiative property, composition, areal extent and mass flux quantifications.

  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. 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.

  10. Design and Research on Aerospace Remote Sensing Optical System%航天遥感光学系统设计与研究

    Institute of Scientific and Technical Information of China (English)

    赵亮; 李朝荣

    2015-01-01

    According to the design requirements and common structure analysis of aerospace remote sensing system, the off-axis three reflective optical system structure is chosen. MATLAB software is used to calculate the ini⁃tial structure of the optical system. And the imaging quality in full field of view of the optical system is analyzed. Two measurement standards such as modulation transfer function (MTF) and spot diagram are used respectively to analyze the imaging quality of the optical system.%根据航天遥感系统设计要求,以及航天遥感光学的常用结构分析,最终选用用离轴三镜反射镜光学系统结构。使用MATLAB软件编程计算光学系统的初始结构。并对光学系统全视场成量进行分析,分别用MTF和点列图两种衡量标准对光学系统成像质量分析。

  11. 光学遥感舰船目标识别方法%Method for ship recognition using optical remote sensing data

    Institute of Scientific and Technical Information of China (English)

    杜春; 孙即祥; 李智勇; 滕书华

    2012-01-01

    提出一种基于粗糙集理论和分层判别回归技术的光学遥感舰船目标识别方法.该方法首先提出新的光学遥感舰船识别特征——面积比编码,并与四类特征组合作为备选特征;然后基于粗糙集理论按同可区分度来计算各备选特征的重要性权值,自动选择出对正确识别贡献较大的特征组合;最后根据分层判别回归原理生成分类判决树来识别光学遥感舰船目标.实验结果表明,本文方法在识别精度和速度方面优于最近邻和支持向量机方法,且通用可行.%A new method for ship recognition using optical remote sensing data based on rough set and hierarchical discriminant regression ( HDR) is presented in this paper. First, a new shape feature called area ratio code ( ARC) is proposed and extracted as a candidate feature. Based on the rough set theory, the common discernibility degree is used to compute the significance weight of each candidate feature and select valid recognition features automatically. Ultimately, a decision tree based on the HDR theory is built to recognize ships in data from optical remote sensing systems. Experimental results on real data show that the proposed method is generalizable and can get better classification rates at a higher speed than the KNN or SVM method.

  12. 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.

  13. 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.

  14. Bio-optical profiling floats as new observational tools for biogeochemical and ecosystem studies: Potential synergies with ocean color remote sensing

    Energy Technology Data Exchange (ETDEWEB)

    Claustre, H.; Bishop, J.; Boss, E.; Bernard, S.; Berthon, J.-F.; Coatanoan, C.; Johnson, K.; Lotiker, A.; Ulloa, O.; Perry, M.J.; D' Ortenzio, F.; D' andon, O.H.F.; Uitz, J.

    2009-10-01

    Profiling floats now represent a mature technology. In parallel with their emergence, the field of miniature, low power bio-optical and biogeochemical sensors is rapidly evolving. Over recent years, the bio-geochemical and bio-optical community has begun to benefit from the increase in observational capacities by developing profiling floats that allow the measurement of key biooptical variables and subsequent products of biogeochemical and ecosystem relevance like Chlorophyll a (Chla), optical backscattering or attenuation coefficients which are proxies of Particulate Organic Carbon (POC), Colored Dissolved Organic Matter (CDOM). Thanks to recent algorithmic improvements, new bio-optical variables such as backscattering coefficient or absorption by CDOM, at present can also be extracted from space observations of ocean color. In the future, an intensification of in situ measurements by bio-optical profiling floats would permit the elaboration of unique 3D/4D bio-optical climatologies, linking surface (remotely detected) properties to their vertical distribution (measured by autonomous platforms), with which key questions in the role of the ocean in climate could be addressed. In this context, the objective of the IOCCG (International Ocean Color Coordinating Group) BIO-Argo working group is to elaborate recommendations in view of a future use of bio-optical profiling floats as part of a network that would include a global array that could be 'Argo-relevant', and specific arrays that would have more focused objectives or regional targets. The overall network, realizing true multi-scale sustained observations of global marine biogeochemistry and biooptics, should satisfy the requirements for validation of ocean color remote sensing as well as the needs of a wider community investigating the impact of global change on biogeochemical cycles and ecosystems. Regarding the global profiling float array, the recommendation is that Chla as well as POC should be the

  15. 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.

  16. 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.

  17. 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.

  18. 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.

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

    Science.gov (United States)

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

    2014-12-01

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

  20. Quantum enhanced optical sensing

    DEFF Research Database (Denmark)

    Schäfermeier, Clemens

    The work in this thesis is embedded in the framework of quantum metrology and explores quantum effects in solid state emitters and optical sensing. Specifically, the thesis comprises studies on silicon vacancy centres in nanodiamonds, phase measurements and cavity optomechanics utilising optical...... squeezed states, and a theoretical study on quantum amplifiers. Due to its similarity to single atoms, colour centres in diamond are ideal objects for exploring and exploiting quantum effects, because they are comparably easy to produce, probe and maintain. While nitrogen vacancy centres are the most...... identified spectral diffusion as the main hindrance in extending spin coherence times. Overcoming this issue will provide a promising candidate as an emitter for quantum information. Next, the question of how squeezed states of light can improve optical sensing was addressed. For this purpose, a squeezed...

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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...

  14. 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...

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

    Science.gov (United States)

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

    2017-06-20

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

  16. 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

  17. 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.

  18. 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

  19. Optical fiber rotation sensing

    CERN Document Server

    Burns, William K; Kelley, Paul

    1993-01-01

    Optical Fiber Rotation Sensing is the first book devoted to Interferometric Fiber Optic Gyros (IFOG). This book provides a complete overview of IFOGs, beginning with a historical review of IFOG development and including a fundamental exposition of basic principles, a discussion of devices and components, and concluding with industry reports on state-of-the-art activity. With several chapters contributed by principal developers of this solid-state device, the result is an authoritative work which will serve as the resource for researchers, students, and users of IFOGs.* * State-of-t

  20. 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.

  1. 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.

  2. Remote opto-chemical sensing with extreme sensitivity: design, fabrication and performance of a pigtailed integrated optical phase-modulated Mach–Zehnder interferometer system

    NARCIS (Netherlands)

    Heideman, R.G.; Lambeck, P.V.

    1999-01-01

    This paper describes the design, fabrication and testing of a pigtailed integrated optical (IO) phase-modulated Mach–Zehnder interferometer (MZI) including both the optical chip and the electronics. The optical chip is realised in SiON technology. The IO components (the sensing function, the straigh

  3. 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.

  4. Characterization of Aerosols and Atmospheric Parameters From Space-Borne and Surface-Based Remote Sensing

    Science.gov (United States)

    2016-06-07

    Characterization Of Aerosols And Atmospheric Parameters From Space-Borne And Surface-Based Remote Sensing Si-Chee Tsay Yoram J. Kaufman 301-614-6188...term goal for this project is threefold: (i) to develop remote sensing procedures for determinng aerosol loading and optical properties over land and...can lead to the best results. OBJECTIVES In preparation for the era of hyperspectral sensors in remote sensing , we need to establish a climatology of

  5. 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).

  6. 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.

  7. Remote sensing of agricultural drought monitoring: A state of art review

    Directory of Open Access Journals (Sweden)

    Khaled Hazaymeh

    2016-09-01

    Full Text Available Agricultural drought is a natural hazard that can be characterized by shortage of water supply. In the scope of this paper, we synthesized the importance of agricultural drought and methods commonly employed to monitor agricultural drought conditions. These include: (i in-situ based methods, (ii optical remote sensing methods, (iii thermal remote sensing methods, (iv microwave remote sensing methods, (v combined remote sensing methods, and (vi synergy between in-situ and remote sensing based methods. The in-situ indices can provide accurate results at the point of measurements; however, unable to provide spatial dynamics over large area. This can potentially be addressed by using remote sensing based methods because remote sensing platforms have the ability to view large area at a near continuous fashion. The remote sensing derived agricultural drought related indicators primarily depend on the characteristics of reflected/emitted energy from the earth surface, thus the results can be relatively less accurate in comparison to the in-situ derived outcomes. Despite a significant amount of research and development has been accomplished in particular to the area of remote sensing of agricultural drought, still there are several challenges. Those include: monitoring relatively small area, filling gaps in the data, developing consistent historical dataset, developing remote sensing-based agricultural drought forecasting system, integrating the recently launched and upcoming remote sensors, and developing standard validation schema, among others.

  8. A method for the evaluation of image quality according to the recognition effectiveness of objects in the optical remote sensing image using machine learning algorithm.

    Directory of Open Access Journals (Sweden)

    Tao Yuan

    Full Text Available Objective and effective image quality assessment (IQA is directly related to the application of optical remote sensing images (ORSI. In this study, a new IQA method of standardizing the target object recognition rate (ORR is presented to reflect quality. First, several quality degradation treatments with high-resolution ORSIs are implemented to model the ORSIs obtained in different imaging conditions; then, a machine learning algorithm is adopted for recognition experiments on a chosen target object to obtain ORRs; finally, a comparison with commonly used IQA indicators was performed to reveal their applicability and limitations. The results showed that the ORR of the original ORSI was calculated to be up to 81.95%, whereas the ORR ratios of the quality-degraded images to the original images were 65.52%, 64.58%, 71.21%, and 73.11%. The results show that these data can more accurately reflect the advantages and disadvantages of different images in object identification and information extraction when compared with conventional digital image assessment indexes. By recognizing the difference in image quality from the application effect perspective, using a machine learning algorithm to extract regional gray scale features of typical objects in the image for analysis, and quantitatively assessing quality of ORSI according to the difference, this method provides a new approach for objective ORSI assessment.

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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...

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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…

  1. 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…

  2. Effect of atmospheric interference and sensor noise in retrieval of optically active materials in the ocean by hyperspectral remote sensing.

    Science.gov (United States)

    Levin, Iosif M; Levina, Elizaveta

    2007-10-01

    We present a method to construct the best linear estimate of optically active material concentration from ocean radiance spectra measured through an arbitrary atmosphere layer by a hyperspectral sensor. The algorithm accounts for sensor noise. Optical models of seawater and maritime atmosphere were used to obtain the joint distribution of spectra and concentrations required for the algorithm. The accuracy of phytoplankton retrieval is shown to be substantially lower than that of sediment and dissolved matter. In all cases, the sensor noise noticeably reduces the retrieval accuracy. Additional errors due to atmospheric interference are analyzed, and possible ways to increase the accuracy of retrieval are suggested, such as changing sensor parameters and including a priori information about observation conditions.

  3. Investigation of aerosol optical properties for remote sensing through DRAGON (distributed regional aerosol gridded observation networks) campaign in Korea

    Science.gov (United States)

    Lim, Jae-Hyun; Ahn, Joon Young; Park, Jin-Soo; Hong, You-Deok; Han, Jin-Seok; Kim, Jhoon; Kim, Sang-Woo

    2014-11-01

    Aerosols in the atmosphere, including dust and pollutants, scatters/absorbs solar radiation and change the microphysics of clouds, thus influencing the Earth's energy budget, climate, air quality, visibility, agriculture and water circulation. Pollutants have also been reported to threaten the human health. The present research collaborated with the U.S. NASA and the U.S. Aerosol Robotic Network (AERONET) is to study the aerosol characteristics in East Asia and improve the long-distance transportation monitoring technology by analyzing the observations of aerosol characteristics in East Asia during Distributed Regional Aerosol Gridded Observation Networks (DRAGON) Campaign (March 2012-May 2012). The sun photometers that measure the aerosol optical characteristics were placed evenly throughout the Korean Peninsula and concentrated in Seoul and the metropolitan area. Observation data are obtained from the DRAGON campaign and the first year (2012) observation data (aerosol optical depth and aerosol spatial distribution) are analyzed. Sun photometer observations, including aerosol optical depth (AOD), are utilized to validate satellite observations from Geostationary Ocean Color Imager (GOCI) and Moderate Resolution Imaging Spectroradiometer (MODIS). Additional analysis is performed associated with the Northeast Asia, the Korean Peninsula in particular, to determine the spatial distribution of the aerosol.

  4. Aerosol optical properties in a rural environment near the mega-city Guangzhou, China: implications for regional air pollution, radiative forcing and remote sensing

    Directory of Open Access Journals (Sweden)

    Y. H. Zhang

    2008-09-01

    strongly influenced by fresh emissions into a shallow nocturnal boundary layer. In spite of high photochemical activity during daytime, we found no evidence for strong local production of secondary aerosol mass.

    The average mass scattering efficiencies with respect to PM10 and PM1 concentrations derived from particle size distribution measurements were 2.8 m2 g−1 and 4.1 m2 g−1, respectively. The Ångström exponent exhibited a wavelength dependence (curvature that was related to the ratio of fine and coarse particle mass (PM1/PM10 as well as the surface mode diameter of the fine particle fraction. The results demonstrate consistency between in situ measurements and a remote sensing formalism with regard to the fine particle fraction and volume mode diameter, but there are also systematic deviations for the larger mode diameters. Thus we suggest that more data sets from in situ measurements of aerosol optical parameters and particle size distributions should be used to evaluate formalisms applied in aerosol remote sensing. Moreover, we observed a negative correlation between single scattering albedo and backscatter fraction, and we found that it affects the impact that these parameters have on aerosol radiative forcing efficiency and should be considered in model studies of the PRD and similarly polluted mega-city regions.

  5. 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.

  6. 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)

  7. The Impact of Drone Technology on Arctic Remote Sensing Data

    Science.gov (United States)

    Ruthkoski, T.; Greaves, H.

    2016-12-01

    Unmanned Aircraft Systems (UAS), more commonly known as drones, present unique remote sensing capabilities. In the harsh climate and remoteness of the Alaskan Arctic, UAS are expected to dramatically advance data collection methods. In August 2016, the Federal Aviation Administration (FAA) will begin to allow small UAS to be used in research activities beyond aviation technology development. However, the quality of remote sensing data collected by drone is still a matter of speculation and flight operations protocol is in early stages. This project presents preliminary evidence that consumer-grade optics mounted on small UAS are able to produce valid scientific data. Lessons learned from Toolik Field Station flight operations development in accordance with current FAA guidelines will also be discussed.

  8. Contribution of High Resolution Microwave and Optical Remote Sensing Observations in Detecting and Monitoring Ocean Coastal Features

    Science.gov (United States)

    Gagliardini, D. A.

    Synthetic Aperture Radar SAR satellite sensors have demonstrated their ability to observe ocean features related to dynamical processes Because of the high resolution of available SAR sensors circulation details and small-scale processes can be detected that are not observable by other sensors more frequently used for ocean research such as the NOAA AVHRR and the ORBVIEW2 SeaWiFS In contrast to these LANDSAT-TM thermal and optical channels can be used to observe sea surface temperatures surface layer ocean color upwelled radiance as well as sun glint reflected radiance patterns of surface roughness at a spatial resolution comparable to that of SAR Several examples of TM images obtained in 1997-2003 over the Argentine coastal ocean region where selected from an extensive data set These images were analyzed and compared with a series of SAR images acquired over the same region by the ERS satellites and in some cases near coincident with the TM data This time period allowed the examination of the seasonal cycles as well as interesting episodic events of different ocean processes including currents fronts upwellings algal blooms eddies internal waves and bathymetry signatures Due in situ observations are scarce over this region some of these processes have been documented for first time helping to improve our understanding of some dynamical and biological aspects Therefore it can be concluded that high resolution optical thermal and microwave data have the ability of providing consistent and complementary high-resolution

  9. Remote sensing: A green illusion

    Science.gov (United States)

    Soudani, Kamel; François, Christophe

    2014-02-01

    An analysis reveals that satellite-observed increases in canopy greenness during dry seasons, which were previously interpreted as positive responses of Amazon forests to more sunlight, are in fact an optical artefact. See Letter p.221

  10. Sensitive and accurate dual wavelength UV-VIS polarization detector for optical remote sensing of tropospheric aerosols

    CERN Document Server

    David, G; Thomas, B; Rairoux, P

    2012-01-01

    An UV-VIS polarization Lidar has been designed and specified for aerosols monitoring in the troposphere, showing the ability to precisely address low particle depolarization ratios, in the range of a few percents. Non-spherical particle backscattering coefficients as low as 5 {\\times} 10-8 m-1.sr-1 have been measured and the particle depolarization ratio detection limit is 0.6 %. This achievement is based on a well-designed detector with laser-specified optical components (polarizers, dichroic beamsplitters) summarized in a synthetic detector transfer matrix. Hence, systematic biases are drastically minimized. The detector matrix being diagonal, robust polarization calibration has been achieved under real atmospheric conditions. This UV-VIS polarization detector measures particle depolarization ratios over two orders of magnitude, from 0.6 up to 40 %, which is new, especially in the UV where molecular scattering is strong. Hence, a calibrated UV polarization-resolved time-altitude map is proposed for urban an...

  11. Remote sensing needs and capabilities in West Africa

    Institute of Scientific and Technical Information of China (English)

    Edward M.Osei,Jr.

    2004-01-01

    The greatest advantage of remote sensing over conventional measurements lies in the opportunity to carry out detailed spatio-temporal analysis of land and ocean features on a very frequent basis. This paper analyses the contribution of satellite imagery to atmospheric, geophysical and ocean studies and management in West Africa since the early 1980s.The detailed application of data from optical sensors (e.g. Meteosat,NOAA/AVHRR, SPOT,L andsat TM, etc.) for weather prediction, hydrogeological, landuse/cover and cartographic studies has been acknowledged. However, the use of microwave (e.g. SAR) and optical data for ocean monitoring and studies in the sub-region is still very limited. Even though sufficient remote sensing expertise and infrastructure is perceived in the region, no clearly defined networking or database exists.

  12. A new bio-optical algorithm for the remote sensing of algal blooms in complex ocean waters

    Science.gov (United States)

    Shanmugam, Palanisamy

    2011-04-01

    A new bio-optical algorithm has been developed to provide accurate assessments of chlorophyll a (Chl a) concentration for detection and mapping of algal blooms from satellite data in optically complex waters, where the presence of suspended sediments and dissolved substances can interfere with phytoplankton signal and thus confound conventional band ratio algorithms. A global data set of concurrent measurements of pigment concentration and radiometric reflectance was compiled and used to develop this algorithm that uses the normalized water-leaving radiance ratios along with an algal bloom index (ABI) between three visible bands to determine Chl a concentrations. The algorithm is derived using Sea-viewing Wide Field-of-view Sensor bands, and it is subsequently tuned to be applicable to Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua data. When compared with large in situ data sets and satellite matchups in a variety of coastal and ocean waters the present algorithm makes good retrievals of the Chl a concentration and shows statistically significant improvement over current global algorithms (e.g., OC3 and OC4v4). An examination of the performance of these algorithms on several MODIS/Aqua images in complex waters of the Arabian Sea and west Florida shelf shows that the new algorithm provides a better means for detecting and differentiating algal blooms from other turbid features, whereas the OC3 algorithm has significant errors although yielding relatively consistent results in clear waters. These findings imply that, provided that an accurate atmospheric correction scheme is available to deal with complex waters, the current MODIS/Aqua, MERIS and OCM data could be extensively used for quantitative and operational monitoring of algal blooms in various regional and global waters.

  13. 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...

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. 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.

  19. 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...

  20. Light absorption by phytoplankton in the southern Baltic and Pomeranian lakes: mathematical expressions for remote sensing applications

    Directory of Open Access Journals (Sweden)

    Justyna Meler

    2017-07-01

    The relationships derived here are applicable in local remote sensing algorithms used for monitoring the Baltic Sea and coastal lakes and can substantially improve the accuracy of the remotely determined optical and biogeochemical characteristics of these waters.

  1. Improving Crop Classification Techniques Using Optical Remote Sensing Imagery, High-Resolution Agriculture Resource Inventory Shapefiles and Decision Trees

    Science.gov (United States)

    Melnychuk, A. L.; Berg, A. A.; Sweeney, S.

    2010-12-01

    Recognition of anthropogenic effects of land use management practices on bodies of water is important for remediating and preventing eutrophication. In the case of Lake Simcoe, Ontario the main surrounding landuse is agriculture. To better manage the nutrient flow into the lake, knowledge of the management of the agricultural land is important. For this basin, a comprehensive agricultural resource inventory is required for assessment of policy and for input into water quality management and assessment tools. Supervised decision tree classification schemes, used in many previous applications, have yielded reliable classifications in agricultural land-use systems. However, when using these classification techniques the user is confronted with numerous data sources. In this study we use a large inventory of optical satellite image products (Landsat, AWiFS, SPOT and MODIS) and ancillary data sources (temporal MODIS-NDVI product signatures, digital elevation models and soil maps) at various spatial and temporal resolutions in a decision tree classification scheme. The sensitivity of the classification accuracy to various products is assessed to identify optimal data sources for classifying crop systems.

  2. Sensing via optical interference

    Directory of Open Access Journals (Sweden)

    Ryan C. Bailey

    2005-04-01

    Full Text Available Chemical and biological sensing are problems of tremendous contemporary technological importance in multiple regulatory and human health contexts, including environmental monitoring, water quality assurance, workplace air quality assessment, food quality control, many aspects of biodiagnostics, and, of course, homeland security. Frequently, what is needed, or at least wanted, are sensors that are simultaneously cheap, fast, reliable, selective, sensitive, robust, and easy to use. Unfortunately, these are often conflicting requirements. Over the past few years, however, a number of promising ideas based on optical interference effects have emerged. Each is based to some extent on advances in the design and fabrication of functional materials. Generally, the advances are of two kinds: chemo- and bio-selective recognition and binding, and efficient methods for micropatterning or microstructuring.

  3. 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.

  4. SO2 emissions from Popocatépetl volcano: emission rates and plume imaging using optical remote sensing techniques

    Science.gov (United States)

    Grutter, M.; Basaldud, R.; Rivera, C.; Harig, R.; Junkerman, W.; Caetano, E.; Delgado-Granados, H.

    2008-11-01

    Sulfur dioxide emissions from the Popocatépetl volcano in central Mexico were measured during the MILAGRO field campaign in March 2006. A stationary scanning DOAS (Differential Optical Absorption Spectrometer) was used to monitor the SO2 emissions from the volcano and the results were compared with traverses done with a COSPEC from the ground and a DOAS instrument on board an ultra-light aircraft. Daytime evolutions as well as day-to-day variation of the SO2 emissions are reported. A value of 2.45±1.39 Gg/day of SO2 is reported from all the daily averages obtained during the month of March 2006, with large variation in maximum and minimum daily averages of 5.97 and 0.56 Gg/day, respectively. The large short-term fluctuations in the SO2 emissions obtained could be confirmed through 2-D visualizations of the SO2 plume measured with a scanning imaging infrared spectrometer. This instrument, based on the passive detection of thermal radiation from the volcanic gas and analysis with FTIR spectrometry, is used for the first time for plume visualization of a specific volcanic gas. A 48-h forward trajectory analysis indicates that the volcanic plume was predominantly directed towards the Puebla/Tlaxcala region (63%), followed by the Mexico City and Cuernavaca/Cuautla regions with 19 and 18% occurrences, respectively. 25% of the modeled trajectories going towards the Puebla region reached altitudes lower than 4000 m a.s.l. but all trajectories remained over this altitude for the other two regions.

  5. Validation of high-resolution aerosol optical thickness simulated by a global non-hydrostatic model against remote sensing measurements

    Science.gov (United States)

    Goto, Daisuke; Sato, Yousuke; Yashiro, Hisashi; Suzuki, Kentaroh; Nakajima, Teruyuki

    2017-02-01

    A high-performance computing resource allows us to conduct numerical simulations with a horizontal grid spacing that is sufficiently high to resolve cloud systems. The cutting-edge computational capability, which was provided by the K computer at RIKEN in Japan, enabled the authors to perform long-term, global simulations of air pollutions and clouds with unprecedentedly high horizontal resolutions. In this study, a next generation model capable of simulating global air pollutions with O(10 km) grid spacing by coupling an atmospheric chemistry model to the Non-hydrostatic Icosahedral Atmospheric Model (NICAM) was performed. Using the newly developed model, month-long simulations for July were conducted with 14 km grid spacing on the K computer. Regarding the global distributions of aerosol optical thickness (AOT), it was found that the correlation coefficient (CC) between the simulation and AERONET measurements was approximately 0.7, and the normalized mean bias was -10%. The simulated AOT was also compared with satellite-retrieved values; the CC was approximately 0.6. The radiative effects due to each chemical species (dust, sea salt, organics, and sulfate) were also calculated and compared with multiple measurements. As a result, the simulated fluxes of upward shortwave radiation at the top of atmosphere and the surface compared well with the observed values, whereas those of downward shortwave radiation at the surface were underestimated, even if all aerosol components were considered. However, the aerosol radiative effects on the downward shortwave flux at the surface were found to be as high as 10 W/m2 in a global scale; thus, simulated aerosol distributions can strongly affect the simulated air temperature and dynamic circulation.

  6. SO2 emissions from Popocatépetl volcano: emission rates and plume imaging using optical remote sensing techniques

    Directory of Open Access Journals (Sweden)

    H. Delgado-Granados

    2008-11-01

    Full Text Available Sulfur dioxide emissions from the Popocatépetl volcano in central Mexico were measured during the MILAGRO field campaign in March 2006. A stationary scanning DOAS (Differential Optical Absorption Spectrometer was used to monitor the SO2 emissions from the volcano and the results were compared with traverses done with a COSPEC from the ground and a DOAS instrument on board an ultra-light aircraft. Daytime evolutions as well as day-to-day variation of the SO2 emissions are reported. A value of 2.45±1.39 Gg/day of SO2 is reported from all the daily averages obtained during the month of March 2006, with large variation in maximum and minimum daily averages of 5.97 and 0.56 Gg/day, respectively. The large short-term fluctuations in the SO2 emissions obtained could be confirmed through 2-D visualizations of the SO2 plume measured with a scanning imaging infrared spectrometer. This instrument, based on the passive detection of thermal radiation from the volcanic gas and analysis with FTIR spectrometry, is used for the first time for plume visualization of a specific volcanic gas. A 48-h forward trajectory analysis indicates that the volcanic plume was predominantly directed towards the Puebla/Tlaxcala region (63%, followed by the Mexico City and Cuernavaca/Cuautla regions with 19 and 18% occurrences, respectively. 25% of the modeled trajectories going towards the Puebla region reached altitudes lower than 4000 m a.s.l. but all trajectories remained over this altitude for the other two regions.

  7. SO2 emissions from Popocatépetl volcano: emission rates and plume imaging using optical remote sensing techniques

    Directory of Open Access Journals (Sweden)

    E. Caetano

    2008-04-01

    Full Text Available Sulfur dioxide emissions from Popocatépetl volcano in central Mexico were measured during the MILAGRO field campaign in March 2006. A stationary scanning DOAS (Differential Optical Absorption Spectrometer was used to monitor the SO2 emissions from the volcano and the results were compared with traverses done with a COSPEC from the ground and a DOAS instrument on board an ultra-light aircraft. Daytime evolutions as well as day-to-day variation of the SO2 emissions are reported. A value of 2.45±1.39 Gg/day of SO2 is reported from all the daily averages obtained during the month of March 2006, with large variation in maximum and minimum daily averages of 5.97 and 0.56 Gg/day, respectively. The large short-term fluctuations in the SO2 emissions obtained could be confirmed through 2-D visualizations of the SO2 plume measured with a scanning imaging infrared spectrometer. This instrument, based on the passive detection of thermal radiation from the volcanic gas and analysis with FTIR spectrometry, is used for the first time for plume visualization of a specific volcanic gas. A 48-h forward trajectory analysis indicates that the volcanic plume was predominately directed towards the Puebla/Tlaxcala region (63%, followed by the Mexico City and Cuernavaca/Cuautla regions with 19 and 18% occurrences, respectively. 25% of the modeled trajectories going towards the Puebla region reached altitudes lower than 4000 m a.s.l. and all trajectories remained over this altitude for the other two regions.

  8. 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.

  9. Improving the extraction of crisis information in the context of flood, fire, and landslide rapid mapping using SAR and optical remote sensing data

    Science.gov (United States)

    Martinis, Sandro; Clandillon, Stephen; Twele, André; Huber, Claire; Plank, Simon; Maxant, Jérôme; Cao, Wenxi; Caspard, Mathilde; May, Stéphane

    2016-04-01

    Optical and radar satellite remote sensing have proven to provide essential crisis information in case of natural disasters, humanitarian relief activities and civil security issues in a growing number of cases through mechanisms such as the Copernicus Emergency Management Service (EMS) of the European Commission or the International Charter 'Space and Major Disasters'. The aforementioned programs and initiatives make use of satellite-based rapid mapping services aimed at delivering reliable and accurate crisis information after natural hazards. Although these services are increasingly operational, they need to be continuously updated and improved through research and development (R&D) activities. The principal objective of ASAPTERRA (Advancing SAR and Optical Methods for Rapid Mapping), the ESA-funded R&D project being described here, is to improve, automate and, hence, speed-up geo-information extraction procedures in the context of natural hazards response. This is performed through the development, implementation, testing and validation of novel image processing methods using optical and Synthetic Aperture Radar (SAR) data. The methods are mainly developed based on data of the German radar satellites TerraSAR-X and TanDEM-X, the French satellite missions Pléiades-1A/1B as well as the ESA missions Sentinel-1/2 with the aim to better characterize the potential and limitations of these sensors and their synergy. The resulting algorithms and techniques are evaluated in real case applications during rapid mapping activities. The project is focussed on three types of natural hazards: floods, landslides and fires. Within this presentation an overview of the main methodological developments in each topic is given and demonstrated in selected test areas. The following developments are presented in the context of flood mapping: a fully automated Sentinel-1 based processing chain for detecting open flood surfaces, a method for the improved detection of flooded vegetation

  10. A Geostatistical Data Fusion Technique for Merging Remote Sensing and Ground-Based Observations of Aerosol Optical Thickness

    Science.gov (United States)

    Chatterjee, Abhishek; Michalak, Anna M.; Kahn, Ralph A.; Paradise, Susan R.; Braverman, Amy J.; Miller, Charles E.

    2010-01-01

    Particles in the atmosphere reflect incoming sunlight, tending to cool the Earth below. Some particles, such as soot, also absorb sunlight, which tens to warm the ambient atmosphere. Aerosol optical depth (AOD) is a measure of the amount of particulate matter in the atmosphere, and is a key input to computer models that simulate and predict Earth's changing climate. The global AOD products from the Multi-angle Imaging SpectroRadiometer (MISR) and the MODerate resolution Imaging Spectroradiometer (MODIS), both of which fly on the NASA Earth Observing System's Terra satellite, provide complementary views of the particles in the atmosphere. Whereas MODIS offers global coverage about four times as frequent as MISR, the multi-angle data makes it possible to separate the surface and atmospheric contributions to the observed top-of-atmosphere radiances, and also to more effectively discriminate particle type. Surface-based AERONET sun photometers retrieve AOD with smaller uncertainties than the satellite instruments, but only at a few fixed locations. So there are clear reasons to combine these data sets in a way that takes advantage of their respective strengths. This paper represents an effort at combining MISR, MODIS and AERONET AOD products over the continental US, using a common spatial statistical technique called kriging. The technique uses the correlation between the satellite data and the "ground-truth" sun photometer observations to assign uncertainty to the satellite data on a region-by-region basis. The larger fraction of the sun photometer variance that is duplicated by the satellite data, the higher the confidence assigned to the satellite data in that region. In the Western and Central US, MISR AOD correlation with AERONET are significantly higher than those with MODIS, likely due to bright surfaces in these regions, which pose greater challenges for the single-view MODIS retrievals. In the east, MODIS correlations are higher, due to more frequent sampling

  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. 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.

  13. 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

  14. 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.

  15. 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.

  16. REMOTE SENSING MEASUREMENTS OF AEROSOL OPTICAL THICKNESS AND CORRELATION WITH IN-SITU AIR QUALITY PARAMETERS DURING A SMOKE HAZE EPISODE IN SOUTHEAST ASIA

    Science.gov (United States)

    Chew, B.; Salinas Cortijo, S. V.; Liew, S.

    2009-12-01

    Transboundary smoke haze due to biomass burning is a major environmental problem in Southeast Asia which has not only affected air quality in the source region, but also in the surrounding countries. Air quality monitoring stations and meteorological stations can provide valuable information on the concentrations of criteria pollutants such as sulphur dioxide, nitrogen oxide, carbon monoxide, ozone and particulate mass (PM10) as well as health advisory to the general public during the haze episodes. Characteristics of aerosol particles in the smoke haze such as the aerosol optical thickness (AOT), aerosol size distribution and Angstrom exponent are also measured or retrieved by sun-tracking photometers, such as those deployed in the world-wide AErosol RObotic NETwork (AERONET). However, due to the limited spatial coverage by the air quality monitoring stations and AERONET sites, it is difficult to study and monitor the spatial and temporal variability of the smoke haze during a biomass burning episode, especially in areas without ground-based instrumentation. As such, we combine the standard in-situ measurements of PM10 by air quality monitoring stations with the remote sensing imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA's Terra and Aqua satellites. The columnar AOT is first derived from the MODIS images for regions where PM10 measurements are available. Empirical correlations between AOT and PM10 measurements are then established for 50 sites in both Malaysia and Singapore during the smoke haze episode in 2006. When available, vertical feature information from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) is used to examine the validity of the correlations. Aloft transport of aerosols, which can weaken the correlations between AOT and PM10 measurements, is also identified by CALIPSO and taken into consideration for the analysis. With this integrated approach, we hope to enhance and

  17. Computational optical sensing and imaging: introduction to feature issue.

    Science.gov (United States)

    Gerwe, David R; Harvey, Andrew; Gehm, Michael E

    2013-04-01

    The 2012 Computational Optical Sensing and Imaging (COSI) conference of the Optical Society of America was one of six colocated meetings composing the Imaging and Applied Optics Congress held in Monterey, California, 24-28 June. COSI, together with the Imaging Systems and Applications, Optical Sensors, Applied Industrial Optics, and Optical Remote Sensing of the Environment conferences, brought together a diverse group of scientists and engineers sharing a common interest in measuring and processing of information carried by optical fields. This special feature includes several papers based on presentations given at the 2012 COSI conference as well as independent contributions, which together highlight several important trends.

  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. Fiber optic sensing and imaging

    CERN Document Server

    2013-01-01

    This book is designed to highlight the basic principles of fiber optic imaging and sensing devices. The editor has organized the book to provide the reader with a solid foundation in fiber optic imaging and sensing devices. It begins with an introductory chapter that starts from Maxwell’s equations and ends with the derivation of the basic optical fiber characteristic equations and solutions (i.e. fiber modes). Chapter 2 reviews most common fiber optic interferometric devices and Chapter 3 discusses the basics of fiber optic imagers with emphasis on fiber optic confocal microscope. The fiber optic interferometric sensors are discussed in detail in chapter 4 and 5. Chapter 6 covers optical coherence tomography and goes into the details of signal processing and systems level approach of the real-time OCT implementation. Also useful forms of device characteristic equations are provided so that this book can be used as a reference for scientists and engineers in the optics and related fields.

  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. An empirical approach to the remote sensing of the chlorophyll in the optically complex waters of the Estuary and Gulf of Saint-Lawrence

    Science.gov (United States)

    Yayla, K. Mehmet

    Data from five research cruises performed between 1997 and 2001 were processed in order to investigate the potential for improving remote sensing algorithms in the Estuary and Gulf of St. Lawrence. Measured in situ parameters included concentration-dependent indicators of the three critical, optically-active constituents, chlorophyll, Coloured Dissolved Organic Matter (CDOM) and Suspended Particulate Matter (SPM). The radiometric dataset used to investigate different types of algorithms consisted of multi-band above-surface remote sensing reflectance (Rrs) estimates. These estimates were computed from downwelling surface irradiance and upwelling sub-surface radiance measurements acquired using a SeaWiFS Profiler Multichannel Radiometer (SPMR). The chlorophyll data varied from approximately 0.1 to 17.3 mg.m -3 in the study region which extended from stations near the Saguenay River to the outer extremes of the Gulf of St. Lawrence. The CDOM and SPM concentration indicators were lower in the Gulf compared to the Estuary. Moderate correlation between in situ measurements was found between chlorophyll and SPM, as well as between CDOM and SPM. Chlorophyll and CDOM were virtually uncorrelated. The standard SeaWiFS Case-I chlorophyll retrieval algorithm, OC4v4, was applied to SPMR data acquired over a significant number of sampling stations (N=169). Algorithm shortcomings were noted when the OC4v4 algorithm was applied directly to the study region. Specific shortcomings, the overestimation of low, and underestimation of high chlorophyll concentrations were consistent with previous findings in coastal regions and particularly with previous findings in the NW Atlantic and in high latitude regions. In addition, the algorithmic output was found to be fairly strongly correlated with CDOM and SPM. A perturbation approach, based on the analysis of residuals between OC4v4 estimates and in situ data, showed that the retrieved chlorophyll biases (overestimates) were dependent on

  8. Remote sensing of vegetation canopy photosynthetic and stomatal conductance efficiencies

    Science.gov (United States)

    Myneni, R. B.; Ganapol, B. D.; Asrar, G.

    1992-01-01

    The problem of remote sensing the canopy photosynthetic and stomatal conductance efficiencies is investigated with the aid of one- and three-dimensional radiative transfer methods coupled to a semi-empirical mechanistic model of leaf photosynthesis and stomatal conductance. Desertlike vegetation is modeled as clumps of leaves randomly distributed on a bright dry soil with partial ground cover. Normalized difference vegetation index (NDVI), canopy photosynthetic (Ep), and stomatal efficiencies (Es) are calculated for various geometrical, optical, and illumination conditions. The contribution of various radiative fluxes to estimates of Ep is evaluated and the magnitude of errors in bulk canopy formulation of problem parameters are quantified. The nature and sensitivity of the relationship between Ep and Es to NDVI is investigated, and an algorithm is proposed for use in operational remote sensing.

  9. 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.

  10. 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.

  11. 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

  12. Optical Remote Sensing Image Registration Based on SG-SIFT%基于SG-SIFT的光学遥感影像配准

    Institute of Scientific and Technical Information of China (English)

    余先川; 吕中华; 胡丹; 张立保; 徐金东

    2014-01-01

    A new optical remote sensing image registration method signal gridding-scale invariant feature transform ( SG-SIFT) based on signal theory and gridding is proposed. According to relationships among the image layers in the difference of Gaussians scale space, the feature points’ number of each image is set in proportion to make the their distribution uniform in the scale space. In addition, a regular gridding method is introduced to achieve the well distribution of feature points in the image space. Then, error matching pairs are eliminated by a correspondence error checking. Statistical and visual results show that SG-SIFT is superior to standard scale invariant feature transform ( SIFT) according to the feature points distribution, while the number of correct matching pairs from SG-SIFT is 17. 47% more than that of uni-form robust-scale invariant feature transform ( UR-SIFT) in average and the evaluation indicator of root-mean square error confirms its superior performance to SIFT and UR-SIFT.%提出了一种基于信号理论和网格化的尺度不变特征变换( SG-SIFT)光学遥感图像配准算法.根据高斯差分尺度空间中各图像层间的频域关系设定各图像提取特征点的数目,使特征点在尺度域上分布均匀;再将各图像层网格化,使特征点在图像空间中分布均匀;然后用一致性检测法剔除有明显错误的匹配对.实验结果表明,利用SG-SIFT算法得到的特征点比尺度不变特征变换( SIFT)算法的特征点分布更均匀,正确匹配对数目比均匀鲁棒尺度不变特征变换( UR-SIFT)算法均多17.47%,且SG-SIFT算法的均方误差明显低于SIFT和UR-SIFT算法.

  13. Daily and seasonal dynamics of suspended particles in the Rhône River plume based on remote sensing and field optical measurements

    Science.gov (United States)

    Lorthiois, Thomas; Doxaran, David; Chami, Malik

    2012-04-01

    Satellite ocean colour remote sensing can serve as a powerful tool to assess river plume characteristics because it provides daily mapping of surface suspended particulate matter (SPM) concentration at high spatial resolution. This study's ultimate objective was to better understand daily and seasonal particle dynamics in a coastal area strongly influenced by freshwater discharge and wind—the Rhône River (France), this being the major source of terrestrial input to the Mediterranean Sea. SPM concentrations and biogenic composition (chlorophyll a, organic carbon) were investigated during several bio-optical field campaigns conducted in spring-autumn of 2010 both from aboard a research vessel and by means of an autonomous profiling float. Freshwater discharge and wind velocities varied significantly during the year, associated with marked fluctuations in surface SPM (upper 1 m), even within hours and not restricted to any specific season. Thus, the range was ca. 12-25 g m-3 (dry mass basis) on 9 April (spring), and ca. 3-39 g m-3 on 4-5 November (late autumn). Short-term variations were observed also in SPM composition in terms of POC (albeit not chl a), with POC/SPM ratios ranging between ca. 3 and 11% over ca. 3 weeks in spring. Nevertheless, the particulate backscattering coefficient ( b bp) proved to be a robust proxy of SPM concentration in the river plume ( b bp(770) = 0.0076 × SPM, R2 = 0.80, N = 56). It has recently been demonstrated that 80% of the Rhône's terrestrial discharge occurs during flood events. The results of the present study revealed that, under these conditions, SPM is constrained largely within surface waters (i.e. at depths <5 m), with only weak daily vertical variability. By implication, ocean colour satellite data are highly suitable in meaningfully estimating the overall SPM load exported by the Rhône River to the Mediterranean. These findings make a solid contribution to future improvements of three-dimensional sediment transport

  14. Hyperspectral Remote Sensing for Shallow Waters. I. A Semianalytical Model

    Science.gov (United States)

    Lee, Zhongping; Carder, Kendall L.; Mobley, Curtis D.; Steward, Robert G.; Patch, Jennifer S.

    1998-09-01

    For analytical or semianalytical retrieval of shallow-water bathymetry and or optical properties of the water column from remote sensing, the contribution to the remotely sensed signal from the water column has to be separated from that of the bottom. The mathematical separation involves three diffuse attenuation coefficients: one for the downwelling irradiance ( K d ), one for the upwelling radiance of the water column ( K u C ), and one for the upwelling radiance from bottom reflection ( K u B ). Because of the differences in photon origination and path lengths, these three coefficients in general are not equal, although their equality has been assumed in many previous studies. By use of the Hydrolight radiative-transfer numerical model with a particle phase function typical of coastal waters, the remote-sensing reflectance above ( R rs ) and below ( r rs ) the surface is calculated for various combinations of optical properties, bottom albedos, bottom depths, and solar zenith angles. A semianalytical (SA) model for r rs of shallow waters is then developed, in which the diffuse attenuation coefficients are explicitly expressed as functions of in-water absorption ( a ) and backscattering ( b b ). For remote-sensing inversion, parameters connecting R rs and r rs are also derived. It is found that r rs values determined by the SA model agree well with the exact values computed by Hydrolight ( 3% error), even for Hydrolight r rs values calculated with different particle phase functions. The Hydrolight calculations included b b a values as high as 1.5 to simulate high-turbidity situations that are occasionally found in coastal regions.

  15. 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

  16. Optical time-domain reflectometer based multiplexed sensing scheme for environmental sensing

    Science.gov (United States)

    Carvalho, J. P.; Gouveia, C.; Santos, J. L.; Jorge, P. A. S.; Baptista, J. M.

    2012-04-01

    In our study, remote environmental sensing is presented using a standard optical time domain reflectometer (OTDR). The measurement of environmental parameters using optical sensors is an expanding area of research with growing importance. Fiber optic sensors are an interesting solution for that due to their high sensitivity, small size, and capability for on-site, real-time, remote, and distributed sensing capabilities. Our multiplexing sensing scheme approach uses transmissive filters (long period gratings - LPGs) interrogated by the OTDR return pulses. The loss induced at the resonance wavelengths varies with changes in the environment refractive index, temperature or other physical parameters. Experimental results show that the insertion of an erbium amplifier improves the measurement resolution in certain situations. Further analysis show that a remote multiplexed sensing scheme allows us to perform simple and low cost real time measurement of refractive index and temperature over long distances.

  17. Predicting wheat production at regional scale by integration of remote sensing data with a simulation model

    NARCIS (Netherlands)

    Jongschaap, R.E.E.; Schouten, L.S.M.

    2005-01-01

    Optical remote sensing satellite data (SPOT HRV XS, Landsat 5 TM) were used to estimate winter wheat area in a pilot area of 5 × 5 km in the Southeast of France. The approach was scaled up to a larger area of 45 × 50 km and finally to the regional level covering several departments. Microwave remote

  18. Predicting wheat production at regional scale by integration of remote sensing data with a simulation model

    NARCIS (Netherlands)

    Jongschaap, R.E.E.; Schouten, L.S.M.

    2005-01-01

    Optical remote sensing satellite data (SPOT HRV XS, Landsat 5 TM) were used to estimate winter wheat area in a pilot area of 5 × 5 km in the Southeast of France. The approach was scaled up to a larger area of 45 × 50 km and finally to the regional level covering several departments. Microwave remote

  19. Remote sensing of Akashiwo sanguinea in the vertical column

    Science.gov (United States)

    Moore, K.; Broughton, J.; Kudela, R. M.

    2013-12-01

    Harmful algal blooms can be extremely damaging to both humans and marine organisms. Harmful algal blooms have been known to cause deleterious effects due to either toxin production or enhanced biomass; mass mortalities of sea birds, dolphins and other creatures often result. Incidences of harmful algal blooms are increasing, so quantifying their locations is a pressing need for human health and the health of marine ecosystems. Past studies have used remote sensing to image dinoflagellate blooms at the ocean surface, but due to migrations of the dinoflagellates in the water column, surface blooms often correspond to non-optimal solar zenith angles for remote sensing imaging. Here we demonstrate a way to locate the blooms of Akashiwo sanguinea at depth in turbid, coastal water (Case II ocean water). Using Hydrolight to simulate the optical properties of A. sanguinea in Monterey Bay, we develop spectral profiles of dinoflagellate blooms in the vertical column. Spectral mixing analysis is used to process aerial data in ENVI-IDL image analysis software. Application of the model to SAMSON remote sensing imagery reveals strong biological and physical coupling in Monterey Bay, and distinguishes dinoflagellates at the surface from those at greater depth. The model is robust and holds up well under various atmospheric forcings and ocean conditions. This work suggests that harmful algal blooms can be detected far below the ocean surface, with the possibility of tracking dinoflagellate diel migrations in the vertical column from outer space.

  20. Remote Sensing Image Registration with Line Segments and Their Intersections

    Directory of Open Access Journals (Sweden)

    Chengjin Lyu

    2017-05-01

    Full Text Available Image registration is a basic but essential step for remote sensing image processing, and finding stable features in multitemporal images is one of the most considerable challenges in the field. The main shape contours of artificial objects (e.g., roads, buildings, farmlands, and airports can be generally described as a group of line segments, which are stable features, even in images with evident background changes (e.g., images taken before and after a disaster. In this study, a registration method that uses line segments and their intersections is proposed for multitemporal remote sensing images. First, line segments are extracted in image pyramids to unify the scales of the reference image and the test image. Then, a line descriptor based on the gradient distribution of local areas is constructed, and the segments are matched in image pyramids. Lastly, triplets of intersections of matching lines are selected to estimate affine transformation between two images. Additional corresponding intersections are provided based on the estimated transformation, and an iterative process is adopted to remove outliers. The performance of the proposed method is tested on a variety of optical remote sensing image pairs, including synthetic and real data. Compared with existing methods, our method can provide more accurate registration results, even in images with significant background changes.

  1. Model for the Interpretation of Hyperspectral Remote-Sensing Reflectance

    Science.gov (United States)

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

    1994-01-01

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

  2. An overview of remote sensing of chlorophyll fluorescence

    Science.gov (United States)

    Xing, Xiao-Gang; Zhao, Dong-Zhi; Liu, Yu-Guang; Yang, Jian-Hong; Xiu, Peng; Wang, Lin

    2007-03-01

    Besides empirical algorithms with the blue-green ratio, the algorithms based on fluorescence are also important and valid methods for retrieving chlorophyll-a concentration in the ocean waters, especially for Case II waters and the sea with algal blooming. This study reviews the history of initial cognitions, investigations and detailed approaches towards chlorophyll fluorescence, and then introduces the biological mechanism of fluorescence remote sensing and main spectral characteristics such as the positive correlation between fluorescence and chlorophyll concentration, the red shift phenomena. Meanwhile, there exist many influence factors that increase complexity of fluorescence remote sensing, such as fluorescence quantum yield, physiological status of various algae, substances with related optical property in the ocean, atmospheric absorption etc. Based on these cognitions, scientists have found two ways to calculate the amount of fluorescence detected by ocean color sensors: fluorescence line height and reflectance ratio. These two ways are currently the foundation for retrieval of chlorophyl l - a concentration in the ocean. As the in-situ measurements and synchronous satellite data are continuously being accumulated, the fluorescence remote sensing of chlorophyll-a concentration in Case II waters should be recognized more thoroughly and new algorithms could be expected.

  3. 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.

  4. 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

  5. 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

  6. 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…

  7. 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

  8. 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

  9. Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria.

    Science.gov (United States)

    Stumpf, Richard P; Davis, Timothy W; Wynne, Timothy T; Graham, Jennifer L; Loftin, Keith A; Johengen, Thomas H; Gossiaux, Duane; Palladino, Danna; Burtner, Ashley

    2016-04-01

    Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments - since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins - especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates of

  10. Developing particle emission inventories using remote sensing (PEIRS).

    Science.gov (United States)

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

    2017-01-01

    Information regarding the magnitude and distribution of PM2.5 emissions is crucial in establishing effective PM regulations and assessing the associated risk to human health and the ecosystem. At present, emission data is obtained from measured or estimated emission factors of various source types. Collecting such information for every known source is costly and time-consuming. For this reason, emission inventories are reported periodically and unknown or smaller sources are often omitted or aggregated at large spatial scale. To address these limitations, we have developed and evaluated a novel method that uses remote sensing data to construct spatially resolved emission inventories for PM2.5. This approach enables us to account for all sources within a fixed area, which renders source classification unnecessary. We applied this method to predict emissions in the northeastern United States during the period 2002-2013 using high-resolution 1 km × 1 km aerosol optical depth (AOD). Emission estimates moderately agreed with the EPA National Emission Inventory (R(2) = 0.66-0.71, CV = 17.7-20%). Predicted emissions are found to correlate with land use parameters, suggesting that our method can capture emissions from land-use-related sources. In addition, we distinguished small-scale intra-urban variation in emissions reflecting distribution of metropolitan sources. In essence, this study demonstrates the great potential of remote sensing data to predict particle source emissions cost-effectively. We present a novel method, particle emission inventories using remote sensing (PEIRS), using remote sensing data to construct spatially resolved PM2.5 emission inventories. Both primary emissions and secondary formations are captured and predicted at a high spatial resolution of 1 km × 1 km. Using PEIRS, large and comprehensive data sets can be generated cost-effectively and can inform development of air quality regulations.

  11. Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria

    Science.gov (United States)

    Stumpf, Rick P; Davis, Timothy W.; Wynne, Timothy T.; Graham, Jennifer; Loftin, Keith A.; Johengen, T.H.; Gossiaux, D.; Palladino, D.; Burtner, A.

    2016-01-01

    Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments – since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins – especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates

  12. Remote sensing methods for power line corridor surveys

    Science.gov (United States)

    Matikainen, Leena; Lehtomäki, Matti; Ahokas, Eero; Hyyppä, Juha; Karjalainen, Mika; Jaakkola, Anttoni; Kukko, Antero; Heinonen, Tero

    2016-09-01

    To secure uninterrupted distribution of electricity, effective monitoring and maintenance of power lines are needed. This literature review article aims to give a wide overview of the possibilities provided by modern remote sensing sensors in power line corridor surveys and to discuss the potential and limitations of different approaches. Monitoring of both power line components and vegetation around them is included. Remotely sensed data sources discussed in the review include synthetic aperture radar (SAR) images, optical satellite and aerial images, thermal images, airborne laser scanner (ALS) data, land-based mobile mapping data, and unmanned aerial vehicle (UAV) data. The review shows that most previous studies have concentrated on the mapping and analysis of network components. In particular, automated extraction of power line conductors has achieved much attention, and promising results have been reported. For example, accuracy levels above 90% have been presented for the extraction of conductors from ALS data or aerial images. However, in many studies datasets have been small and numerical quality analyses have been omitted. Mapping of vegetation near power lines has been a less common research topic than mapping of the components, but several studies have also been carried out in this field, especially using optical aerial and satellite images. Based on the review we conclude that in future research more attention should be given to an integrated use of various data sources to benefit from the various techniques in an optimal way. Knowledge in related fields, such as vegetation monitoring from ALS, SAR and optical image data should be better exploited to develop useful monitoring approaches. Special attention should be given to rapidly developing remote sensing techniques such as UAVs and laser scanning from airborne and land-based platforms. To demonstrate and verify the capabilities of automated monitoring approaches, large tests in various environments

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. Multi- and hyperspectral remote sensing of tropical marine benthic habitats

    Science.gov (United States)

    Mishra, Deepak R.

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

  1. 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.

  2. 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.

  3. On Emissivity of Reference Source of IR Radiometer for Remote Sensing

    OpenAIRE

    高木, 亨; 松井, 松長; 宮武, 将浩; タカギ, トオル; マツイ, マツナガ; ミヤタケ, マサヒロ; Tohru, TAKAGI; Matsunaga, MATSUI; Masahiro, MIYATAKE

    1980-01-01

    The reference source of the radiometer for remote sensing should be small and light the emissivity high and the field of view of the optical system wide. In this paper, the theoretical and experimental consideration on emissivity of the cavity type reference source of radiometer for remote sensing is performed. The results are as follows: 1) The simplified equation for calculation of emissivity of cavity type source is introduced. 2) The equation for emissivity of cavity type source at variou...

  4. 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.

  5. 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

  6. 空间相机光学窗口热光学性能的仿真分析%Thermal optics property simulation of optical window for remote sensing

    Institute of Scientific and Technical Information of China (English)

    廖志波; 焦文春; 伏瑞敏

    2011-01-01

    Optical window of remote sensing system has thermal exchange with ambient environment and it causes non-uniformity thermal distribution, including system average temperature shift as well as circumferential, radial and axial temperature differences, which degrade the image quality. A new method was presented to analyze this effect on the optical system wavefront error by building segments made up of complex pupils. Each segment can be effectively analyzed because of only the radial temperature being processed by non-sequential ray trace. Then all the separate impacts of the segments were calculated on the entire optical window. An example of the optical window is given, and the result shows that the method is feasible, the optical system quality is reduced by this effect and its MTF can not be completely compensated by focus shift.%空间相机光学窗口与周围环境进行热交换,导致窗口的温度发生不均匀变化,包括整体温度水平的变化以及产生径向温差、周向温差和抽向温差.这些温度梯度将影响相机的光学系统质量.针对某相机光学窗口温度分布不均匀的特点,提出利用非顺序光路建立复杂光瞳的方法对光学窗口进行分区,在各子区域上建立温度的径向分布特征,然后将各子区域的变化再统一到整个元件中,进而评判对整个系统的影响.结果表明,新方法合理可行,温度周向不均匀分布会降低光学系统质量,并且不能完全通过离焦来补偿.

  7. 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".

  8. 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

  9. 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

  10. 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".

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

    Science.gov (United States)

    Guild, Liane

    2016-01-01

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

  12. Remote optical detection using microcantilevers

    Energy Technology Data Exchange (ETDEWEB)

    Wachter, E.A.; Thundat, T.; Oden, P.I.; Warmack, R.J. [Health Sciences Research Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Datskos, P.G.; Sharp, S.L. [Consultec Scientific, Inc., Knoxville, Tennessee 37932 (United States)

    1996-10-01

    The feasibility of microcantilever-based optical detection is demonstrated. Microcantilevers may provide a simple means for developing single-element and multielement infrared sensors that are smaller, more sensitive, and lower in cost than quantum well, thermoelectric, or bolometric sensors. Here we specifically report here on an evaluation of laboratory prototypes that are based on commercially available microcantilevers, such as those used in atomic force microscopy. In this work, optical transduction techniques were used to measure microcantilever response to remote sources of thermal energy. The noise equivalent power at 20 Hz for room temperature microcantilevers was found to be approximately 3.5 nW/{radical}Hz, with a specific detectivity of 3.6{times}10{sup 7} cm Hz{sup 1/2}/W, when an uncoated microcantilever was irradiated by a low-power diode laser operating at 786 nm. Operation is shown to be possible from dc to kHz frequencies, and the effect of cantilever shape and the role of absorptive coatings are discussed. Finally, spectral response in the midinfrared is evaluated using both coated and uncoated microcantilevers. {copyright} {ital 1996 American Institute of Physics.}

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. Nanostructured Substrates for Optical Sensing

    OpenAIRE

    Kemling, Jonathan W.; Qavi, Abraham J.; Bailey, Ryan C.; Suslick, Kenneth S

    2011-01-01

    Sensors that change color have the advantages of versatility, ease of use, high sensitivity, and low cost. The recent development of optically based chemical sensing platforms has increasingly employed substrates manufactured with advanced processing or fabrication techniques to provide precise control over shape and morphology of the sensor micro- and nano-structure. New sensors have resulted with improved capabilities for a number of sensing applications, including the detection of biomolec...

  3. A Multi-Depth Underwater Spectroradiometer for Validation of Remotely-Sensed Ocean Color and Estimation of Seawater Biogeochemical Properties Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Remote sensing of optical properties of coastal waters provides essential information for various scientific questions & applications as monitoring biological...

  4. 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

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

    Science.gov (United States)

    Rozenstein, Offer; Adamowski, Jan

    2017-05-01

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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  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. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Remote sensing of atmospheric chemistry; Proceedings of the Meeting, Orlando, FL, Apr. 1-3, 1991

    Science.gov (United States)

    Mcelroy, James L. (Editor); Mcneal, Robert J. (Editor)

    1991-01-01

    The present volume on remote sensing of atmospheric chemistry discusses special remote sensing space observations and field experiments to study chemical change in the atmosphere, network monitoring for detection of stratospheric chemical change, stratospheric chemistry studies, and the combining of model, in situ, and remote sensing in atmospheric chemistry. Attention is given to the measurement of tropospheric carbon monoxide using gas filter radiometers, long-path differential absorption measurements of tropospheric molecules, air quality monitoring with the differential optical absorption spectrometer, and a characterization of tropospheric methane through space-based remote sensing. Topics addressed include microwave limb sounder experiments for UARS and EOS, an overview of the spectroscopy of the atmosphere using an FIR emission experiment, the detection of stratospheric ozone trends by ground-based microwave observations, and a FIR Fabry-Perot spectrometer for OH measurements.

  20. The Archaeological Application of Multi-Sensor Remote Sensing Data in Qin Yongcheng Site

    Science.gov (United States)

    Wang, M.; Wan, Y.; Zhao, Z.

    2017-09-01

    Remote sensing archaeology bases on the use of remote sensing images and interpretation of the principles. The historic relics and sites are resulted from human activities and have constantly caused influences on the soil component, moisture content, temperature, vegetation growth and so on. Based on this thought, this paper proposed a new remote sensing model and approach that integrates optical and thermal infrared remote sensing data for archaeology. Taking the Qin Yongcheng site as the example, this method conducts a comprehensive analysis of key factors affecting archaeological application, that is, LST estimated with Landsat TM data, soil brightness, humidity and greenness obtained from GF-1 data, and then interprets the potential site targets. By conducting the field verification, it is shown that the interpreted potential sites are well consisted with the field investigations and have a high interpretation precision. It can provide a guide for further archaeological research.

  1. 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.

  2. 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

  3. 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.

  4. 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...

  5. 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...

  6. 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.

  7. 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

  8. 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

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Improved FTIR open-path remote sensing data reduction technique

    Science.gov (United States)

    Phillips, Bill; Moyers, Rick; Lay, Lori T.

    1995-05-01

    Progress on the developement of a nonlinear curve fitting computer algorithm for data reduction of optical remote sensing Fourier transform spectrometer (FTS) data is presented. This new algorithm is an adaptation of an existing algorithm employed at the Arnold Engineering Development Center for the analysis of infrared plume signature and optical gas diagnostic data on rocket and turbine engine exhaust. Because it is a nonlinear model, the algorithm can be used to determine parameters not readily determined by linear methods such as classical least squares. Unlike linear methods this procedure can simultaneously determine atmospheric gas concetrations, spectral resolution, spectral shift, and the background or (Io(omega) spectrum. Additionally, species which possess spectra that are strongly masked by atmospheric absorption features such as BTX can also be incorporated into the procedure. The basic theory behind the algorithm is presented as well as test results on FTS data and synthetic data containing benzene and toluene spectral features.

  15. Coherence brightened laser source for atmospheric remote sensing.

    Science.gov (United States)

    Traverso, Andrew J; Sanchez-Gonzalez, Rodrigo; Yuan, Luqi; Wang, Kai; Voronine, Dmitri V; Zheltikov, Aleksei M; Rostovtsev, Yuri; Sautenkov, Vladimir A; Sokolov, Alexei V; North, Simon W; Scully, Marlan O

    2012-09-18

    We have studied coherent emission from ambient air and demonstrated efficient generation of laser-like beams directed both forward and backward with respect to a nanosecond ultraviolet pumping laser beam. The generated optical gain is a result of two-photon photolysis of atmospheric O(2), followed by two-photon excitation of atomic oxygen. We have analyzed the temporal shapes of the emitted pulses and have observed very short duration intensity spikes as well as a large Rabi frequency that corresponds to the emitted field. Our results suggest that the emission process exhibits nonadiabatic atomic coherence, which is similar in nature to Dicke superradiance where atomic coherence is large and can be contrasted with ordinary lasing where atomic coherence is negligible. This atomic coherence in oxygen adds insight to the optical emission physics and holds promise for remote sensing techniques employing nonlinear spectroscopy.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. ESTIMATION OF INSULATOR CONTAMINATIONS BY MEANS OF REMOTE SENSING TECHNIQUE

    Directory of Open Access Journals (Sweden)

    G. Han

    2016-06-01

    Full Text Available The accurate estimation of deposits adhering on insulators is critical to prevent pollution flashovers which cause huge costs worldwide. The traditional evaluation method of insulator contaminations (IC is based sparse manual in-situ measurements, resulting in insufficient spatial representativeness and poor timeliness. Filling that gap, we proposed a novel evaluation framework of IC based on remote sensing and data mining. Varieties of products derived from satellite data, such as aerosol optical depth (AOD, digital elevation model (DEM, land use and land cover and normalized difference vegetation index were obtained to estimate the severity of IC along with the necessary field investigation inventory (pollution sources, ambient atmosphere and meteorological data. Rough set theory was utilized to minimize input sets under the prerequisite that the resultant set is equivalent to the full sets in terms of the decision ability to distinguish severity levels of IC. We found that AOD, the strength of pollution source and the precipitation are the top 3 decisive factors to estimate insulator contaminations. On that basis, different classification algorithm such as mahalanobis minimum distance, support vector machine (SVM and maximum likelihood method were utilized to estimate severity levels of IC. 10-fold cross-validation was carried out to evaluate the performances of different methods. SVM yielded the best overall accuracy among three algorithms. An overall accuracy of more than 70% was witnessed, suggesting a promising application of remote sensing in power maintenance. To our knowledge, this is the first trial to introduce remote sensing and relevant data analysis technique into the estimation of electrical insulator contaminations.

  5. Estimation of Insulator Contaminations by Means of Remote Sensing Technique

    Science.gov (United States)

    Han, Ge; Gong, Wei; Cui, Xiaohui; Zhang, Miao; Chen, Jun

    2016-06-01

    The accurate estimation of deposits adhering on insulators is critical to prevent pollution flashovers which cause huge costs worldwide. The traditional evaluation method of insulator contaminations (IC) is based sparse manual in-situ measurements, resulting in insufficient spatial representativeness and poor timeliness. Filling that gap, we proposed a novel evaluation framework of IC based on remote sensing and data mining. Varieties of products derived from satellite data, such as aerosol optical depth (AOD), digital elevation model (DEM), land use and land cover and normalized difference vegetation index were obtained to estimate the severity of IC along with the necessary field investigation inventory (pollution sources, ambient atmosphere and meteorological data). Rough set theory was utilized to minimize input sets under the prerequisite that the resultant set is equivalent to the full sets in terms of the decision ability to distinguish severity levels of IC. We found that AOD, the strength of pollution source and the precipitation are the top 3 decisive factors to estimate insulator contaminations. On that basis, different classification algorithm such as mahalanobis minimum distance, support vector machine (SVM) and maximum likelihood method were utilized to estimate severity levels of IC. 10-fold cross-validation was carried out to evaluate the performances of different methods. SVM yielded the best overall accuracy among three algorithms. An overall accuracy of more than 70% was witnessed, suggesting a promising application of remote sensing in power maintenance. To our knowledge, this is the first trial to introduce remote sensing and relevant data analysis technique into the estimation of electrical insulator contaminations.

  6. Remote sensing validation through SOOP technology: implementation of Spectra system

    Science.gov (United States)

    Piermattei, Viviana; Madonia, Alice; Bonamano, Simone; Consalvi, Natalizia; Caligiore, Aurelio; Falcone, Daniela; Puri, Pio; Sarti, Fabio; Spaccavento, Giovanni; Lucarini, Diego; Pacci, Giacomo; Amitrano, Luigi; Iacullo, Salvatore; D'Andrea, Salvatore; Marcelli, Marco

    2017-04-01

    The development of low-cost instrumentation plays a key role in marine environmental studies and represents one of the most innovative aspects of marine research. The availability of low-cost technologies allows the realization of extended observatory networks for the study of marine phenomena through an integrated approach merging observations, remote sensing and operational oceanography. Marine services and practical applications critically depends on the availability of large amount of data collected with sufficiently dense spatial and temporal sampling. This issue directly influences the robustness both of ocean forecasting models and remote sensing observations through data assimilation and validation processes, particularly in the biological domain. For this reason it is necessary the development of cheap, small and integrated smart sensors, which could be functional both for satellite data validation and forecasting models data assimilation as well as to support early warning systems for environmental pollution control and prevention. This is particularly true in coastal areas, which are subjected to multiple anthropic pressures. Moreover, coastal waters can be classified like case 2 waters, where the optical properties of inorganic suspended matter and chromophoric dissolved organic matter must be considered and separated by the chlorophyll a contribution. Due to the high costs of mooring systems, research vessels, measure platforms and instrumentation a big effort was dedicated to the design, development and realization of a new low cost mini-FerryBox system: Spectra. Thanks to the modularity and user-friendly employment of the system, Spectra allows to acquire continuous in situ measures of temperature, conductivity, turbidity, chlorophyll a and chromophoric dissolved organic matter (CDOM) fluorescences from voluntary vessels, even by non specialized operators (Marcelli et al., 2014; 2016). This work shows the preliminary application of this technology to

  7. Modified Michelson fiber-optic interferometer: A remote low-coherence distributed strain sensor array

    Science.gov (United States)

    Yuan, Libo

    2003-01-01

    A simple modified Michelson fiber-optic low-coherence interferometric quasi-distributed sensing system permitting absolute length measurement in remote reflective sensor array is proposed. The sensor reflective signals characteristics have been analyzed and the relationship between light signal intensities and sensors number was given for multiplexing potential evaluation. The proposed sensing scheme will be useful for the remote measurement of strain. An important application could be deformation sensing in smart structures. Experimentally, a three sensors array has been demonstrated.

  8. 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.

  9. 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

  10. 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...

  11. Automatic Registration and Mosaicking System for Remotely Sensed Imagery

    Directory of Open Access Journals (Sweden)

    Emiliano Castejon

    2006-04-01

    Full Text Available Image registration is an important operation in many remote sensing applications and it, besides other tasks, involves the identification of corresponding control points in the images. As manual identification of control points may be time-consuming and tiring, several automatic techniques have been developed. This paper describes a system for automatic registration and mosaic of remote sensing images under development at The National Institute for Space Research (INPE and at The University of California, Santa Barbara (UCSB. The user can provide information to the system in order to speed up the registration process as well as to avoid mismatched control points. Based on statistical procedure, the system gives an indication of the registration quality. This allows users to stop the processing, to modify the registration parameters or to continue the processing. Extensive system tests have been performed with different types of data (optical, radar, multi-sensor, high-resolution images and video sequences in order to check the system performance. An online demo system is available on the internet ( which contains several examples that can be carried out using web browser.

  12. Remote sensing of forest dynamics and land use in Amazonia

    Science.gov (United States)

    Toomey, Michael Paul

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

  13. Optical Waveguide Sensing and Imaging

    CERN Document Server

    Bock, Wojtek J; Tanev, Stoyan

    2008-01-01

    The book explores various aspects of existing and emerging fiber and waveguide optics sensing and imaging technologies including recent advances in nanobiophotonics. The focus is both on fundamental and applied research as well as on applications in civil engineering, biomedical sciences, environment, security and defence. The main goal of the multi-disciplinarry team of Editors was to provide an useful reference of state-of-the-art overviews covering a variety of complementary topics on the interface of engineering and biomedical sciences.

  14. 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

  15. 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.

  16. 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.

  17. Assessment and statistical modeling of the relationship between remotely sensed aerosol optical depth and PM2.5 in the eastern United States.

    Science.gov (United States)

    Paciorek, Christopher J; Liu, Yang

    2012-05-01

    Research in scientific, public health, and policy disciplines relating to the environment increasingly makes use of high-dimensional remote sensing and the output of numerical models in conjunction with traditional observations. Given the public health and resultant public policy implications of the potential health effects of particulate matter (PM*) air pollution, specifically fine PM with an aerodynamic diameter contributing a second likelihood to a Bayesian statistical model, as well as a data source on which we could directly regress. Previous consideration of satellite AOD has largely focused on the National Aeronautics and Space Administration (NASA) moderate resolution imaging spectroradiometer (MODIS) and multiangle imaging spectroradiometer (MISR) instruments. One contribution of our work is more extensive consideration of AOD derived from the Geostationary Operational Environmental Satellite East Aerosol/Smoke Product (GOES GASP) AOD and its relationship with PM2.5. In addition to empirically assessing the spatiotemporal relationship between GASP AOD and PM2.5, we considered new statistical techniques to screen anomalous GOES reflectance measurements and account for background surface reflectance. In our statistical work, we developed a new model structure that allowed for more flexible modeling of the proxy discrepancy than previous statistical efforts have had, with a computationally efficient implementation. We also suggested a diagnostic for assessing the scales of the spatial relationship between the proxy and the spatial process of interest (e.g., PM2.5). In brief, we had little success in improving predictions in our eastern-United States domain for use in epidemiologic applications. We found positive correlations of AOD with PM2.5 over time, but less correlation for long-term averages over space, unless we used calibration that adjusted for large-scale discrepancy between AOD and PM2.5 (see sections 3, 4, and 5). Statistical models that combined

  18. 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.

  19. Technical Note: Use of remote sensing for landslide studies in Europe

    Directory of Open Access Journals (Sweden)

    V. Tofani

    2013-02-01

    Full Text Available Within the framework of FP7, an EU-funded SafeLand project, a questionnaire was prepared to collect information about the use of remote sensing for landslide study and to evaluate its actual application in landslide detection, mapping and monitoring. The questionnaire was designed using a Google form and was disseminated among end-users and researchers involved in landslide studies in Europe. In total, 49 answers from 17 different European countries were collected. 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. Remote sensing is mainly used for detection/mapping and monitoring of slides, flows and lateral spreads with a preferably large scale of analysis (1:5000–1:25 000. All the compilers integrate remote sensing data with other thematic data, mainly geological maps, landslide inventory maps and DTMs and derived maps. According to the research and working experience of the compilers, remote sensing is generally considered to have a medium effectiveness/reliability for landslide studies.

    The results of the questionnaire can contribute to an overall sketch of the use of remote sensing in current landslide studies and show that remote sensing can be considered a powerful and well-established instrument for landslide mapping, monitoring and hazard analysis.

  20. BOMBER: A tool for estimating water quality and bottom properties from remote sensing images

    Science.gov (United States)

    Giardino, Claudia; Candiani, Gabriele; Bresciani, Mariano; Lee, Zhongping; Gagliano, Stefano; Pepe, Monica

    2012-08-01

    BOMBER (Bio-Optical Model Based tool for Estimating water quality and bottom properties from Remote sensing images) is a software package for simultaneous retrieval of the optical properties of water column and bottom from remotely sensed imagery, which makes use of bio-optical models for optically deep and optically shallow waters. Several menus allow the user to choose the model type, to specify the input and output files, and to set all of the variables involved in the model parameterization and inversion. The optimization technique allows the user to retrieve the maps of chlorophyll concentration, suspended particulate matter concentration, coloured dissolved organic matter absorption and, in case of shallow waters, bottom depth and distributions of up to three different types of substrate, defined by the user according to their albedo. The software requires input image data that must be atmospherically corrected to remote sensing reflectance values. For both deep and shallow water models, a map of the relative error involved in the inversion procedure is also given. The tool was originally intended to estimate water quality in lakes; however thanks to its general design, it can be applied to any other aquatic environments (e.g., coastal zones, estuaries, lagoons) for which remote sensing reflectance values are known. BOMBER is fully programmed in IDL (Interactive Data Language) and uses IDL widgets as graphical user interface. It runs as an add-on tool for the ENVI+IDL image processing software and is available on request.

  1. 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.

  2. 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,.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 光学浅水遥感水底反射校正研究进展%Review of Correction of Bottom Effects of Optical Shallow Water Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    周冠华

    2011-01-01

    Until recently, optical processes in shallow water, where the sea bottom is shallow enough to be optically detected, has received little attention outside of a relatively small number of modeling and remote sensing investigations . The contribution from the bottom of optical shallow water changes the intensity and spectral distribution of remotely sensed signal above water surface, which became one of the key problems for water quality remote sensing inversion accuracy. In shallow water, where the depth is much less than the potential for light to penetrate, a large fraction of the subsurface light reaches the ocean floor, where portions of the light energy are absorbed, reflected back into the overlying water column, or re-emitted as fluorescence. So variability in the subsurface light field is not only determined by the distribution of optically important matter dissolved and suspended in the water column , but also of the function of the depth and properties of the ocean floor. It is important to understand how light interacts with the sea floor. Though many of the techniques and approaches to investigate light in the deep water are relevant in the shallow water, they are insufficient to address the entire problem, and the treatment of remote sensing reflectance is more complex than for optically deep waters, when water bottom effects are considered. In order to completely understand the details of how light is distributed within the shallow water and to determine the interrelationships and variability of optical properties of water bottom and water-leaving radiance, the measurements of spectral bidirectional reflectance distribution function (BRDF) along with concurrent measurements of the sediment properties ( composition, grain size, etc. ) should be taken. The foundation of spectral database of typical sediment types in the typical coastal areas by experiment is necessary work to do, which can provide the basic data for modeling and application in optically

  11. 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...

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

    Science.gov (United States)

    1978-01-01

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

  13. Geotechnical applications of remote sensing and remote data transmission; Proceedings of the Symposium, Cocoa Beach, FL, Jan. 31-Feb. 1, 1986

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, A.I.; Pettersson, C.B.

    1988-01-01

    Papers and discussions concerning the geotechnical applications of remote sensing and remote data transmission, sources of remotely sensed data, and glossaries of remote sensing and remote data transmission terms, acronyms, and abbreviations are presented. Aspects of remote sensing use covered include the significance of lineaments and their effects on ground-water systems, waste-site use and geotechnical characterization, the estimation of reservoir submerging losses using CIR aerial photographs, and satellite-based investigation of the significance of surficial deposits for surface mining operations. Other topics presented include the location of potential ground subsidence and collapse features in soluble carbonate rock, optical Fourier analysis of surface features of interest in geotechnical engineering, geotechnical applications of U.S. Government remote sensing programs, updating the data base for a Geographic Information System, the joint NASA/Geosat Test Case Project, the selection of remote data telemetry methods for geotechnical applications, the standardization of remote sensing data collection and transmission, and a comparison of airborne Goodyear electronic mapping system/SAR with satelliteborne Seasat/SAR radar imagery.

  14. 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 ...

  15. 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.

  16. 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,...

  17. 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.

  18. 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.

  19. 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...

  20. 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.

  1. 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 ...

  2. 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...

  3. 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...

  4. Optical display for radar sensing

    Science.gov (United States)

    Szu, Harold; Hsu, Charles; Willey, Jefferson; Landa, Joseph; Hsieh, Minder; Larsen, Louis V.; Krzywicki, Alan T.; Tran, Binh Q.; Hoekstra, Philip; Dillard, John T.; Krapels, Keith A.; Wardlaw, Michael; Chu, Kai-Dee

    2015-05-01

    Boltzmann headstone S = kB Log W turns out to be the Rosette stone for Greek physics translation optical display of the microwave sensing hieroglyphics. The LHS is the molecular entropy S measuring the degree of uniformity scattering off the sensing cross sections. The RHS is the inverse relationship (equation) predicting the Planck radiation spectral distribution parameterized by the Kelvin temperature T. Use is made of the conservation energy law of the heat capacity of Reservoir (RV) change T Δ S = -ΔE equals to the internal energy change of black box (bb) subsystem. Moreover, an irreversible thermodynamics Δ S > 0 for collision mixing toward totally larger uniformity of heat death, asserted by Boltzmann, that derived the so-called Maxwell-Boltzmann canonical probability. Given the zero boundary condition black box, Planck solved a discrete standing wave eigenstates (equation). Together with the canonical partition function (equation) an average ensemble average of all possible internal energy yielded the celebrated Planck radiation spectral (equation) where the density of states (equation). In summary, given the multispectral sensing data (equation), we applied Lagrange Constraint Neural Network (LCNN) to solve the Blind Sources Separation (BSS) for a set of equivalent bb target temperatures. From the measurements of specific value, slopes and shapes we can fit a set of Kelvin temperatures T's for each bb targets. As a result, we could apply the analytical continuation for each entropy sources along the temperature-unique Planck spectral curves always toward the RGB color temperature display for any sensing probing frequency.

  5. Self-Calibrating High Resolution Tunable Filter for Remote Gas Sensing Applications Project

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to develop a compact, robust, optically-based sensor for local and remote sensing of oxygen (O2) at 1.26 5m, carbon dioxide (CO2) at 1.56 5m and other...

  6. Integrating crop growth simulation and remote sensing to improve resource use efficiency in farming systems

    NARCIS (Netherlands)

    Jongschaap, R.E.E.

    2006-01-01

    Keywords: simulation; model; calibration; remote sensing; radar; optical; satellite; spatial; up-scaling; LAI; nitrogen; chlorophyll; fertilization; precision agriculture; maize; potato; wheat

    This study investigated the scope and constraints for integrated

  7. Coniferous needle-leaves, shots and canopies : a remote sensing approach

    NARCIS (Netherlands)

    Yanez Rausell, L.

    2014-01-01

    Coniferous forests are important in the regulation of the Earth’s climate and thus continuous monitoring of these ecosystems is crucial to better understand potential responses to climate change. Optical remote sensing (RS) provides powerful methods for the estimation of essential climate

  8. 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

  9. Coniferous needle-leaves, shots and canopies : a remote sensing approach

    NARCIS (Netherlands)

    Yanez Rausell, L.

    2014-01-01

    Coniferous forests are important in the regulation of the Earth’s climate and thus continuous monitoring of these ecosystems is crucial to better understand potential responses to climate change. Optical remote sensing (RS) provides powerful methods for the estimation of essential climate vari

  10. Compressive Sensing with Optical Chaos

    Science.gov (United States)

    Rontani, D.; Choi, D.; Chang, C.-Y.; Locquet, A.; Citrin, D. S.

    2016-12-01

    Compressive sensing (CS) is a technique to sample a sparse signal below the Nyquist-Shannon limit, yet still enabling its reconstruction. As such, CS permits an extremely parsimonious way to store and transmit large and important classes of signals and images that would be far more data intensive should they be sampled following the prescription of the Nyquist-Shannon theorem. CS has found applications as diverse as seismology and biomedical imaging. In this work, we use actual optical signals generated from temporal intensity chaos from external-cavity semiconductor lasers (ECSL) to construct the sensing matrix that is employed to compress a sparse signal. The chaotic time series produced having their relevant dynamics on the 100 ps timescale, our results open the way to ultrahigh-speed compression of sparse signals.

  11. 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.

  12. 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...

  13. 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 ...

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. Aerosol optical properties relevant to regional remote sensing of CCN activity and links to their organic mass fraction: airborne observations over Central Mexico and the US West Coast during MILAGRO/INTEX-B

    Directory of Open Access Journals (Sweden)

    Y. Shinozuka

    2009-05-01

    Full Text Available Remote sensing of cloud condensation nuclei (CCN would help evaluate the indirect effects of tropospheric aerosols on clouds and climate. To assess its feasibility, we examined relationships of submicron aerosol composition to CCN activity and optical properties observed during the MILAGRO/INTEX-B aircraft campaigns. An indicator of CCN activity, κ, was calculated from hygroscopicity measured under saturation. κ for dry 100-nm particles decreased with the organic fraction of non-refractory mass of submicron particles (OMF as 10(−0.43−0.44*OMF over Central Mexico and 10(−0.29−0.70*OMF over the US West Coast. These fits represent the critical dry diameter, centered near 100 nm for 0.2% supersaturation but varied as κ(−1/3, within measurement uncertainty (~20%. The decreasing trends of CCN activity with the organic content, evident also in our direct CCN counts, were consistent with previous ground and laboratory observations of highly organic particles. The wider range of OMF, 0–0.8, for our research areas means that aerosol composition will be more critical for estimation of CCN concentration than at the fixed sites previously studied. Furthermore, the wavelength dependence of extinction was anti-correlated with OMF as −0.70*OMF+2.0 for Central Mexico's urban and industrial pollution air masses, for unclear reasons. The Angstrom exponent of absorption increased with OMF, more rapidly under higher single scattering albedo, as expected for the interplay between soot and colored weak absorbers (some organic species and dust. Because remote sensing products currently use the wavelength dependence of extinction albeit in the column integral form and may potentially include that of absorption, these regional spectral dependencies are expected to facilitate retrievals of aerosol bulk chemistry and CCN activity over Central Mexico.

  20. Aerosol optical properties relevant to regional remote sensing of CCN activity and links to their organic mass fraction: airborne observations over Central Mexico and the US West Coast during MILAGRO/INTEX-B

    Directory of Open Access Journals (Sweden)

    Y. Shinozuka

    2009-09-01

    Full Text Available Remote sensing of cloud condensation nuclei (CCN would help evaluate the indirect effects of tropospheric aerosols on clouds and climate. To assess its feasibility, we examined relationships of submicron aerosol composition to CCN activity and optical properties observed during the MILAGRO/INTEX-B aircraft campaigns. An indicator of CCN activity, κ, was calculated from hygroscopicity measured under saturation. κ for dry 100 nm particles decreased with increasing organic fraction of non-refractory mass of submicron particles (OMF as 0.34–0.20×OMF over Central Mexico and 0.47–0.43×OMF over the US West Coast. These fits represent the critical dry diameter, centered near 100 nm for 0.2% supersaturation but varied as κ(−1/3, within measurement uncertainty (~20%. The decreasing trends of CCN activity with the organic content, evident also in our direct CCN counts, were consistent with previous ground and laboratory observations of highly organic particles. The wider range of OMF, 0–0.8, for our research areas means that aerosol composition will be more critical for estimation of CCN concentration than at the fixed sites previously studied. Furthermore, the wavelength dependence of extinction was anti-correlated with OMF as −0.70×OMF+2.0 for Central Mexico's urban and industrial pollution air masses, for unclear reasons. The Angstrom exponent of absorption increased with OMF, more rapidly under higher single scattering albedo, as expected for the interplay between soot and colored weak absorbers (some organic species and dust. Because remote sensing products currently use the wavelength dependence of extinction albeit in the column integral form and may potentially include that of absorption, these regional spectral dependencies are expected to facilitate retrievals of aerosol bulk chemical composition and CCN activity over Central Mexico.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Wavefront sensing reveals optical coherence.

    Science.gov (United States)

    Stoklasa, B; Motka, L; Rehacek, J; Hradil, Z; Sánchez-Soto, L L

    2014-01-01

    Wavefront sensing is a set of techniques providing efficient means to ascertain the shape of an optical wavefront or its deviation from an ideal reference. Owing to its wide dynamical range and high optical efficiency, the Shack-Hartmann wavefront sensor is nowadays the most widely used of these sensors. Here we show that it actually performs a simultaneous measurement of position and angular spectrum of the incident radiation and, therefore, when combined with tomographic techniques previously developed for quantum information processing, the Shack-Hartmann wavefront sensor can be instrumental in reconstructing the complete coherence properties of the signal. We confirm these predictions with an experimental characterization of partially coherent vortex beams, a case that cannot be treated with the standard tools. This seems to indicate that classical methods employed hitherto do not fully exploit the potential of the registered data.

  8. Field calibration and validation of remote-sensing surveys

    Science.gov (United States)

    Pe'eri, Shachak; McLeod, Andy; Lavoie, Paul; Ackerman, Seth D.; Gardner, James; Parrish, Christopher

    2013-01-01

    The Optical Collection Suite (OCS) is a ground-truth sampling system designed to perform in situ measurements that help calibrate and validate optical remote-sensing and swath-sonar surveys for mapping and monitoring coastal ecosystems and ocean planning. The OCS system enables researchers to collect underwater imagery with real-time feedback, measure the spectral response, and quantify the water clarity with simple and relatively inexpensive instruments that can be hand-deployed from a small vessel. This article reviews the design and performance of the system, based on operational and logistical considerations, as well as the data requirements to support a number of coastal science and management projects. The OCS system has been operational since 2009 and has been used in several ground-truth missions that overlapped with airborne lidar bathymetry (ALB), hyperspectral imagery (HSI), and swath-sonar bathymetric surveys in the Gulf of Maine, southwest Alaska, and the US Virgin Islands (USVI). Research projects that have used the system include a comparison of backscatter intensity derived from acoustic (multibeam/interferometric sonars) versus active optical (ALB) sensors, ALB bottom detection, and seafloor characterization using HSI and ALB.

  9. 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.

  10. Polarization Invariants and Retrieval of Surface Parameters Using Polarization Measurements in Remote Sensing Applications

    CERN Document Server

    Shestopaloff, Yu K

    2012-01-01

    Using polarization measurements in remote sensing and optical studies allows retrieving more information. We consider relationship between the reflection coefficients of plane and rough surfaces for linearly polarized waves. Certain polarization properties of reflected waves and polarization invariants, in particular at incident angle of forty five degrees, allow finding amplitude and phase characteristics of reflected waves. Based on this study, we introduce methods for finding dielectric permittivity, temperature and geometrical characteristics of observed surfaces. Experimental results prove that these methods can be used for different practical purposes in technological and remote sensing applications, in a broad range of electromagnetic spectrum.

  11. Advancing the quantification of humid tropical forest cover loss with multi-resolution optical remote sensing data: Sampling & wall-to-wall mapping

    Science.gov (United States)

    Broich, Mark

    Humid tropical forest cover loss is threatening the sustainability of ecosystem goods and services as vast forest areas are rapidly cleared for industrial scale agriculture and tree plantations. Despite the importance of humid tropical forest in the provision of ecosystem services and economic development opportunities, the spatial and temporal distribution of forest cover loss across large areas is not well quantified. Here I improve the quantification of humid tropical forest cover loss using two remote sensing-based methods: sampling and wall-to-wall mapping. In all of the presented studies, the integration of coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data enable advances in quantifying forest cover loss in the humid tropics. Imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used as the source of coarse spatial resolution, high temporal resolution data and imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor are used as the source of moderate spatial, low temporal resolution data. In a first study, I compare the precision of different sampling designs for the Brazilian Amazon using the annual deforestation maps derived by the Brazilian Space Agency for reference. I show that sampling designs can provide reliable deforestation estimates; furthermore, sampling designs guided by MODIS data can provide more efficient estimates than the systematic design used for the United Nations Food and Agricultural Organization Forest Resource Assessment 2010. Sampling approaches, such as the one demonstrated, are viable in regions where data limitations, such as cloud contamination, limit exhaustive mapping methods. Cloud-contaminated regions experiencing high rates of change include Insular Southeast Asia, specifically Indonesia and Malaysia. Due to persistent cloud cover, forest cover loss in Indonesia has only been mapped at a 5-10 year interval using photo interpretation of single

  12. Evaluation of a Modified SEBAL Algorithm to Estimate Actual Evapotranspiration in Cotton Ecosystems of Central Asia using Microwave and Optical Remote Sensing Data

    Science.gov (United States)

    Knoefel, Patrick; Conrad, Christopher

    2015-04-01

    Being recognized as an essential component of both the water and the energy cycle, actual evapotranspiration (ETa) plays in important role in order to describe the complex interactions within the climate system of the Earth. Here, remote sensing is a powerful tool to estimate regional ETa to support the regional water management. For instance, the water withdrawal of the agricultural sector in OECD countries is on average about 44 %, but in the states of Central Asia it achieves more than 90 %. This fact is identified as one of the main reasons for the increasing water scarcity in this region. An accuracy assessment of the methods used for determining ETa is necessary concerning an appropriate use of the model results to support agriculture and irrigation management. Within Central Asia the Khorezm region in Uzbekistan is a case study region for the problems of irrigated agriculture. For Khorezm the seasonal ETa based on MODIS data was calculated for the years 2009 - 2011 using a partly modified surface energy balance algorithm for land (SEBAL). SEBAL was implemented based on MODIS time series to calculate the energy balance components like net radiation (Rn), sensible heat (H), latent heat (LE), and soil heat flux (G). Whilst SEBAL is using an empirical equation for the estimation of G, a more physically based method was introduced in this study. This method uses microwave soil moisture products (ASAR and ASCAT-SSM) as an additional model input. The input parameters and the model results of all energy balance components (Rn, H, LE, and G) were intensively validated by field measurements with an eddy covariance system and soil sensors. The model shows very good performance for Rn with average model efficiency (NSE) of 0.68 and small relative errors (rRMSE) of about 10%. For turbulent heat fluxes good results can be achieved with NSE of 0.31 for H and 0.55 for LE, the rRMSE are about 21% (H) and 18% (LE). Soil heat flux estimation could be improved using the

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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…

  18. 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

  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 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