Energy-Efficient Transmissions for Remote Wireless Sensor Networks: An Integrated HAP/Satellite Architecture for Emergency Scenarios

Science.gov (United States)

Dong, Feihong; Li, Hongjun; Gong, Xiangwu; Liu, Quan; Wang, Jingchao

2015-01-01

A typical application scenario of remote wireless sensor networks (WSNs) is identified as an emergency scenario. One of the greatest design challenges for communications in emergency scenarios is energy-efficient transmission, due to scarce electrical energy in large-scale natural and man-made disasters. Integrated high altitude platform (HAP)/satellite networks are expected to optimally meet emergency communication requirements. In this paper, a novel integrated HAP/satellite (IHS) architecture is proposed, and three segments of the architecture are investigated in detail. The concept of link-state advertisement (LSA) is designed in a slow flat Rician fading channel. The LSA is received and processed by the terminal to estimate the link state information, which can significantly reduce the energy consumption at the terminal end. Furthermore, the transmission power requirements of the HAPs and terminals are derived using the gradient descent and differential equation methods. The energy consumption is modeled at both the source and system level. An innovative and adaptive algorithm is given for the energy-efficient path selection. The simulation results validate the effectiveness of the proposed adaptive algorithm. It is shown that the proposed adaptive algorithm can significantly improve energy efficiency when combined with the LSA and the energy consumption estimation. PMID:26404292

Energy-Efficient Transmissions for Remote Wireless Sensor Networks: An Integrated HAP/Satellite Architecture for Emergency Scenarios

Directory of Open Access Journals (Sweden)

Feihong Dong

2015-09-01

Full Text Available A typical application scenario of remote wireless sensor networks (WSNs is identified as an emergency scenario. One of the greatest design challenges for communications in emergency scenarios is energy-efficient transmission, due to scarce electrical energy in large-scale natural and man-made disasters. Integrated high altitude platform (HAP/satellite networks are expected to optimally meet emergency communication requirements. In this paper, a novel integrated HAP/satellite (IHS architecture is proposed, and three segments of the architecture are investigated in detail. The concept of link-state advertisement (LSA is designed in a slow flat Rician fading channel. The LSA is received and processed by the terminal to estimate the link state information, which can significantly reduce the energy consumption at the terminal end. Furthermore, the transmission power requirements of the HAPs and terminals are derived using the gradient descent and differential equation methods. The energy consumption is modeled at both the source and system level. An innovative and adaptive algorithm is given for the energy-efficient path selection. The simulation results validate the effectiveness of the proposed adaptive algorithm. It is shown that the proposed adaptive algorithm can significantly improve energy efficiency when combined with the LSA and the energy consumption estimation.

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.

High Data Rate Satellite Communications for Environmental Remote Sensing

Science.gov (United States)

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

2014-12-01

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

Multiple Usage of Existing Satellite Sensors

National Research Council Canada - National Science Library

Keeney, James T

2006-01-01

.... Space offers a near-perfect vacuum to operate a passive or active sensor. Volume, mass and power on satellites is limited and risk management approaches tended to remove such sensors from satellite systems...

UV ionospheric remote sensing with the Polar BEAR satellite

International Nuclear Information System (INIS)

Delgreco, F.P.; Eastes, R.W.; Huffman, R.E.

1989-01-01

The Polar BEAR satellite carries the Auroral Ionospheric Remote Sensor (AIRS) instrument, which is designed to return four simultaneous images of atmospheric radiation at northern latitudes, has thus far yielded over 5000 images. Polar BEAR was in operation during March, 1987, when the preliminary K(p) reached a value of 9 over a six-hour period; at that time, AIRS was operating at the 1304 A atomic oxygen wavelength and recorded remarkable data, which are here presented. Due to the intense activity, the AIRS data were barely able to register the poleward edge of the aurora. 6 refs

Viewing marine bacteria, their activity and response to environmental drivers from orbit: satellite remote sensing of bacteria.

Science.gov (United States)

Grimes, D Jay; Ford, Tim E; Colwell, Rita R; Baker-Austin, Craig; Martinez-Urtaza, Jaime; Subramaniam, Ajit; Capone, Douglas G

2014-04-01

Satellite-based remote sensing of marine microorganisms has become a useful tool in predicting human health risks associated with these microscopic targets. Early applications were focused on harmful algal blooms, but more recently methods have been developed to interrogate the ocean for bacteria. As satellite-based sensors have become more sophisticated and our ability to interpret information derived from these sensors has advanced, we have progressed from merely making fascinating pictures from space to developing process models with predictive capability. Our understanding of the role of marine microorganisms in primary production and global elemental cycles has been vastly improved as has our ability to use the combination of remote sensing data and models to provide early warning systems for disease outbreaks. This manuscript will discuss current approaches to monitoring cyanobacteria and vibrios, their activity and response to environmental drivers, and will also suggest future directions.

Oil spill remote sensing sensors and aircraft

International Nuclear Information System (INIS)

Fingas, M.; Fruhwirth, M.; Gamble, L.

1992-01-01

The most common form of remote sensing as applied to oil spills is aerial remote sensing. The technology of aerial remote sensing, mainly from aircraft, is reviewed along with aircraft-mounted remote sensors and aircraft modifications. The characteristics, advantages, and limitations of optical techniques, infrared and ultraviolet sensors, fluorosensors, microwave and radar sensors, and slick thickness sensors are discussed. Special attention is paid to remote sensing of oil under difficult circumstances, such as oil in water or oil on ice. An infrared camera is the first sensor recommended for oil spill work, as it is the cheapest and most applicable device, and is the only type of equipment that can be bought off-the-shelf. The second sensor recommended is an ultraviolet and visible-spectrum device. The laser fluorosensor offers the only potential for discriminating between oiled and un-oiled weeds or shoreline, and for positively identifying oil pollution on ice and in a variety of other situations. However, such an instrument is large and expensive. Radar, although low in priority for purchase, offers the only potential for large-area searches and foul-weather remote sensing. Most other sensors are experimental or do not offer good potential for oil detection or mapping. 48 refs., 8 tabs

Remote sensing systems – Platforms and sensors: Aerial, satellites, UAVs, optical, radar, and LiDAR: Chapter 1

Science.gov (United States)

Panda, Sudhanshu S.; Rao, Mahesh N.; Thenkabail, Prasad S.; Fitzerald, James E.

2015-01-01

The American Society of Photogrammetry and Remote Sensing defined remote sensing as the measurement or acquisition of information of some property of an object or phenomenon, by a recording device that is not in physical or intimate contact with the object or phenomenon under study (Colwell et al., 1983). Environmental Systems Research Institute (ESRI) in its geographic information system (GIS) dictionary defines remote sensing as “collecting and interpreting information about the environment and the surface of the earth from a distance, primarily by sensing radiation that is naturally emitted or reflected by the earth’s surface or from the atmosphere, or by sending signals transmitted from a device and reflected back to it (ESRI, 2014).” The usual source of passive remote sensing data is the measurement of reflected or transmitted electromagnetic radiation (EMR) from the sun across the electromagnetic spectrum (EMS); this can also include acoustic or sound energy, gravity, or the magnetic field from or of the objects under consideration. In this context, the simple act of reading this text is considered remote sensing. In this case, the eye acts as a sensor and senses the light reflected from the object to obtain information about the object. It is the same technology used by a handheld camera to take a photograph of a person or a distant scenic view. Active remote sensing, however, involves sending a pulse of energy and then measuring the returned energy through a sensor (e.g., Radio Detection and Ranging [RADAR], Light Detection and Ranging [LiDAR]). Thermal sensors measure emitted energy by different objects. Thus, in general, passive remote sensing involves the measurement of solar energy reflected from the Earth’s surface, while active remote sensing involves synthetic (man-made) energy pulsed at the environment and the return signals are measured and recorded.

Multiple Usage of Existing Satellite Sensors (PREPRINT)

National Research Council Canada - National Science Library

Keeney, James T

2006-01-01

.... Space offers a near-perfect vacuum to operate a passive or active sensor. Volume, mass and power on satellites is limited and risk management approaches tended to remove such sensors from satellite systems...

Multiplatform Mission Planning and Operations Simulation Environment for Adaptive Remote Sensors

Science.gov (United States)

Smith, G.; Ball, C.; O'Brien, A.; Johnson, J. T.

2017-12-01

We report on the design and development of mission simulator libraries to support the emerging field of adaptive remote sensors. We will outline the current state of the art in adaptive sensing, provide analysis of how the current approach to performing observing system simulation experiments (OSSEs) must be changed to enable adaptive sensors for remote sensing, and present an architecture to enable their inclusion in future OSSEs.The growing potential of sensors capable of real-time adaptation of their operational parameters calls for a new class of mission planning and simulation tools. Existing simulation tools used in OSSEs assume a fixed set of sensor parameters in terms of observation geometry, frequencies used, resolution, or observation time, which allows simplifications to be made in the simulation and allows sensor observation errors to be characterized a priori. Adaptive sensors may vary these parameters depending on the details of the scene observed, so that sensor performance is not simple to model without conducting OSSE simulations that include sensor adaptation in response to varying observational environment. Adaptive sensors are of significance to resource-constrained, small satellite platforms because they enable the management of power and data volumes while providing methods for multiple sensors to collaborate.The new class of OSSEs required to utilize adaptive sensors located on multiple platforms must answer the question: If the physical act of sensing has a cost, how does the system determine if the science value of a measurement is worth the cost and how should that cost be shared among the collaborating sensors?Here we propose to answer this question using an architecture structured around three modules: ADAPT, MANAGE and COLLABORATE. The ADAPT module is a set of routines to facilitate modeling of adaptive sensors, the MANAGE module will implement a set of routines to facilitate simulations of sensor resource management when power and data

Multi-sensor satellite and in situ monitoring of phytoplankton development in a eutrophic-mesotrophic lake.

Science.gov (United States)

Dörnhöfer, Katja; Klinger, Philip; Heege, Thomas; Oppelt, Natascha

2018-01-15

Phytoplankton indicated by its photosynthetic pigment chlorophyll-a is an important pointer on lake ecology and a regularly monitored parameter within the European Water Framework Directive. Along with eutrophication and global warming cyanobacteria gain increasing importance concerning human health aspects. Optical remote sensing may support both the monitoring of horizontal distribution of phytoplankton and cyanobacteria at the lake surface and the reduction of spatial uncertainties associated with limited water sample analyses. Temporal and spatial resolution of using only one satellite sensor, however, may constrain its information value. To discuss the advantages of a multi-sensor approach the sensor-independent, physically based model MIP (Modular Inversion and Processing System) was applied at Lake Kummerow, Germany, and lake surface chlorophyll-a was derived from 33 images of five different sensors (MODIS-Terra, MODIS-Aqua, Landsat 8, Landsat 7 and Sentinel-2A). Remotely sensed lake average chlorophyll-a concentration showed a reasonable development and varied between 2.3±0.4 and 35.8±2.0mg·m -3 from July to October 2015. Match-ups between in situ and satellite chlorophyll-a revealed varying performances of Landsat 8 (RMSE: 3.6 and 19.7mg·m -3 ), Landsat 7 (RMSE: 6.2mg·m -3 ), Sentinel-2A (RMSE: 5.1mg·m -3 ) and MODIS (RMSE: 12.8mg·m -3 ), whereas an in situ data uncertainty of 48% needs to be respected. The temporal development of an index on harmful algal blooms corresponded well with the cyanobacteria biomass development during summer months. Satellite chlorophyll-a maps allowed to follow spatial patterns of chlorophyll-a distribution during a phytoplankton bloom event. Wind conditions mainly explained spatial patterns. Integrating satellite chlorophyll-a into trophic state assessment resulted in different trophic classes. Our study endorsed a combined use of satellite and in situ chlorophyll-a data to alleviate weaknesses of both approaches and

Geospatial Analysis and Remote Sensing from Airplanes and Satellites for Cultural Resources Management

Science.gov (United States)

Giardino, Marco J.; Haley, Bryan S.

2005-01-01

Cultural resource management consists of research to identify, evaluate, document and assess cultural resources, planning to assist in decision-making, and stewardship to implement the preservation, protection and interpretation of these decisions and plans. One technique that may be useful in cultural resource management archaeology is remote sensing. It is the acquisition of data and derivative information about objects or materials (targets) located on the Earth's surface or in its atmosphere by using sensor mounted on platforms located at a distance from the targets to make measurements on interactions between the targets and electromagnetic radiation. Included in this definition are systems that acquire imagery by photographic methods and digital multispectral sensors. Data collected by digital multispectral sensors on aircraft and satellite platforms play a prominent role in many earth science applications, including land cover mapping, geology, soil science, agriculture, forestry, water resource management, urban and regional planning, and environmental assessments. Inherent in the analysis of remotely sensed data is the use of computer-based image processing techniques. Geographical information systems (GIS), designed for collecting, managing, and analyzing spatial information, are also useful in the analysis of remotely sensed data. A GIS can be used to integrate diverse types of spatially referenced digital data, including remotely sensed and map data. In archaeology, these tools have been used in various ways to aid in cultural resource projects. For example, they have been used to predict the presence of archaeological resources using modern environmental indicators. Remote sensing techniques have also been used to directly detect the presence of unknown sites based on the impact of past occupation on the Earth's surface. Additionally, remote sensing has been used as a mapping tool aimed at delineating the boundaries of a site or mapping previously

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...

Satellite remote sensing in epidemiological studies.

Science.gov (United States)

Sorek-Hamer, Meytar; Just, Allan C; Kloog, Itai

2016-04-01

Particulate matter air pollution is a ubiquitous exposure linked with multiple adverse health outcomes for children and across the life course. The recent development of satellite-based remote-sensing models for air pollution enables the quantification of these risks and addresses many limitations of previous air pollution research strategies. We review the recent literature on the applications of satellite remote sensing in air quality research, with a focus on their use in epidemiological studies. Aerosol optical depth (AOD) is a focus of this review and a significant number of studies show that ground-level particulate matter can be estimated from columnar AOD. Satellite measurements have been found to be an important source of data for particulate matter model-based exposure estimates, and recently have been used in health studies to increase the spatial breadth and temporal resolution of these estimates. It is suggested that satellite-based models improve our understanding of the spatial characteristics of air quality. Although the adoption of satellite-based measures of air quality in health studies is in its infancy, it is rapidly growing. Nevertheless, further investigation is still needed in order to have a better understanding of the AOD contribution to these prediction models in order to use them with higher accuracy in epidemiological studies.

"Using Satellite Remote Sensing to Derive Numeric Criteria in Coastal and Inland Waters of the United States"

Science.gov (United States)

Crawford, T. N.; Schaeffer, B. A.

2016-12-01

Anthropogenic nutrient pollution is a major stressor of aquatic ecosystems around the world. In the United States, states and tribes can adopt numeric water quality values (i.e. criteria) into their water quality management standards to protect aquatic life from eutrophication impacts. However, budget and resource constraints have limited the ability of many states and tribes to collect the water quality monitoring data needed to derive numeric criteria. Over the last few decades, satellite technology has provided water quality measurements on a global scale over long time periods. Water quality managers are finding the data provided by satellite technology useful in managing eutrophication impacts in coastal waters, estuaries, lakes, and reservoirs. In recent years EPA has worked with states and tribes to derive remotely sensed numeric Chl-a criteria for coastal waters with limited field-based data. This approach is now being expanded and used to derive Chl-a criteria in freshwater systems across the United States. This presentation will cover EPA's approach to derive numeric Chl-a criteria using satellite remote sensing, recommendations to improve satellite sensors to expand applications, potential areas of interest, and the challenges of using remote sensing to establish water quality management goals, as well as provide a case in which this approach has been applied.

Full-Physics Inverse Learning Machine for Satellite Remote Sensing Retrievals

Science.gov (United States)

Loyola, D. G.

2017-12-01

The satellite remote sensing retrievals are usually ill-posed inverse problems that are typically solved by finding a state vector that minimizes the residual between simulated data and real measurements. The classical inversion methods are very time-consuming as they require iterative calls to complex radiative-transfer forward models to simulate radiances and Jacobians, and subsequent inversion of relatively large matrices. In this work we present a novel and extremely fast algorithm for solving inverse problems called full-physics inverse learning machine (FP-ILM). The FP-ILM algorithm consists of a training phase in which machine learning techniques are used to derive an inversion operator based on synthetic data generated using a radiative transfer model (which expresses the "full-physics" component) and the smart sampling technique, and an operational phase in which the inversion operator is applied to real measurements. FP-ILM has been successfully applied to the retrieval of the SO2 plume height during volcanic eruptions and to the retrieval of ozone profile shapes from UV/VIS satellite sensors. Furthermore, FP-ILM will be used for the near-real-time processing of the upcoming generation of European Sentinel sensors with their unprecedented spectral and spatial resolution and associated large increases in the amount of data.

Satellite Remote Sensing Detection of Coastal Pollution in Southern California: Stormwater Runoff and Wastewater Plumes

Science.gov (United States)

Trinh, R. C.; Holt, B.; Gierach, M.

2016-02-01

Coastal pollution poses a major health and environmental hazard, not only for beach goers and coastal communities but for marine organisms as well. Stormwater runoff is the largest source of environmental pollution in coastal waters of the Southern California Bight (SCB) and is of great concern in increasingly urbanized areas. Buoyant wastewater plumes also pose a marine environmental risk. In this study we provide a comprehensive overview of satellite remote sensing capabilities in detecting buoyant coastal pollutants in the form of stormwater runoff and wastewater effluent. The SCB is the final destination of four major urban rivers that act as channels for runoff and pollution during and after rainstorms. We analyzed and compared sea surface roughness data from various Synthetic Aperture Radar (SAR) instruments to ocean color data from the Moderate Imaging System (MODIS) sensor on board the Aqua satellite and correlated the results with existing environmental data in order to create a climatology of naturally occurring stormwater plumes in coastal waters after rain events, from 1992 to 2014 from four major rivers in the area. Heat maps of the primary extent of stormwater plumes were constructed to specify areas that may be subject to the greatest risk of coastal contamination. In conjunction with our efforts to monitor coastal pollution and validate the abilities of satellite remote sensing, a recent Fall 2015 wastewater diversion from the City of Los Angeles Hyperion Treatment Plant (HTP) provided the opportunity to apply these remote sensing methodologies of plume detection to wastewater. During maintenance of their 5-mile long outfall pipe, wastewater is diverted to a shorter outfall pipe that terminates 1-mile offshore and in shallower waters. Sea surface temperature (SST), chlorophyll-a (chl-a) fluorescence, remote sensing reflectance and particulate backscatter signatures were analyzed from MODIS. Terra-ASTER and Landsat-8 thermal infrared data were also

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...

Design of the driving system for visible near-infrared spatial programmable push-broom remote CCD sensor

Science.gov (United States)

Xu, Zhipeng; Wei, Jun; Zhou, Qianting; Weng, Dongshan; Li, Jianwei

2010-11-01

VNIR multi-spectral image sensor has wide applications in remote sensing and imaging spectroscopy. An image spectrometer of a spatial remote programmable push-broom sensing satellite requires visible near infrared band ranges from 0.4μm to 1.04μm which is one of the most important bands in remote sensing. This paper introduces a method of design the driving system for 1024x1024 VNIR CCD sensor for programmable push-broom remote sensing. The digital driving signal is generated by the FPGA device. There are seven modules in the FPGA program and all the modules are coded by VHDL. The driving system have five mainly functions: drive the sensor as the demand of timing schedule, control the AD convert device to work, get the parameter via RS232 from control platform, process the data input from the AD device, output the processed data to PCI sample card to display in computer end. All the modules above succeed working on FPGA device APA600. This paper also introduced several important keys when designing the driving system including module synchronization, critical path optimization.

Use of Openly Available Satellite Images for Remote Sensing Education

Science.gov (United States)

Wang, C.-K.

2011-09-01

With the advent of Google Earth, Google Maps, and Microsoft Bing Maps, high resolution satellite imagery are becoming more easily accessible than ever. It have been the case that the college students may already have wealth experiences with the high resolution satellite imagery by using these software and web services prior to any formal remote sensing education. It is obvious that the remote sensing education should be adjusted to the fact that the audience are already the customers of remote sensing products (through the use of the above mentioned services). This paper reports the use of openly available satellite imagery in an introductory-level remote sensing course in the Department of Geomatics of National Cheng Kung University as a term project. From the experience learned from the fall of 2009 and 2010, it shows that this term project has effectively aroused the students' enthusiastic toward Remote Sensing.

Research on orbit prediction for solar-based calibration proper satellite

Science.gov (United States)

Chen, Xuan; Qi, Wenwen; Xu, Peng

2018-03-01

Utilizing the mathematical model of the orbit mechanics, the orbit prediction is to forecast the space target's orbit information of a certain time based on the orbit of the initial moment. The proper satellite radiometric calibration and calibration orbit prediction process are introduced briefly. On the basis of the research of the calibration space position design method and the radiative transfer model, an orbit prediction method for proper satellite radiometric calibration is proposed to select the appropriate calibration arc for the remote sensor and to predict the orbit information of the proper satellite and the remote sensor. By analyzing the orbit constraint of the proper satellite calibration, the GF-1solar synchronous orbit is chose as the proper satellite orbit in order to simulate the calibration visible durance for different satellites to be calibrated. The results of simulation and analysis provide the basis for the improvement of the radiometric calibration accuracy of the satellite remote sensor, which lays the foundation for the high precision and high frequency radiometric calibration.

Oil-spill remote sensors : new tools that provide solutions to old problems

International Nuclear Information System (INIS)

Brown, C.E.; Fingas, M.F.; Goodman, R.H.

1998-01-01

A review of remote sensors used for oil spill detection and monitoring was presented. New technologies and developments in the area were highlighted. The infrared (IR) camera or a combination infrared/ultraviolet system are the two most commonly used sensors currently being used. They can detect oil under a variety of conditions, discriminate oil from some backgrounds and they have the lowest cost of any sensor. Their weakness is that they cannot identify oil on beaches, among weeds or debris, through fog, or at dawn and dusk. Also, water-in-oil emulsions are often not detected with infrared sensors. The ability of IR sensors to detect the thickness of spills was also discussed. Present day cameras use micro-bolometer technology making them more economical and practical to operate than older IR systems. The use of satellite imagery for tracking oil spills is one important new trend that can prove to be useful for wide-area searching. 37 refs

Automatic Assessment of Acquisition and Transmission Losses in Indian Remote Sensing Satellite Data

Science.gov (United States)

Roy, D.; Purna Kumari, B.; Manju Sarma, M.; Aparna, N.; Gopal Krishna, B.

2016-06-01

The quality of Remote Sensing data is an important parameter that defines the extent of its usability in various applications. The data from Remote Sensing satellites is received as raw data frames at the ground station. This data may be corrupted with data losses due to interferences during data transmission, data acquisition and sensor anomalies. Thus it is important to assess the quality of the raw data before product generation for early anomaly detection, faster corrective actions and product rejection minimization. Manual screening of raw images is a time consuming process and not very accurate. In this paper, an automated process for identification and quantification of losses in raw data like pixel drop out, line loss and data loss due to sensor anomalies is discussed. Quality assessment of raw scenes based on these losses is also explained. This process is introduced in the data pre-processing stage and gives crucial data quality information to users at the time of browsing data for product ordering. It has also improved the product generation workflow by enabling faster and more accurate quality estimation.

Results of agriclimatological studies using multiple satellite sensors like NOAA AVHRR; GMS IR and LANDSAT MSS and TM

International Nuclear Information System (INIS)

Choudhury, A.M.

1990-08-01

Bangladesh Space Research and Remote Sensing Organization (SPARRSO) routinely receives NOAA and GMS imagery and uses them in agrometeorological monitoring, it also uses LANDSAT MSS and TM data for this purpose. Analysis of multiple satellite sensor data shows advantages for high resolution sensors. However, in the ease of crop monitoring, a good correlation has been obtained between results obtained with NOAA AVHRR and LANDSAT MSS for vegetation index. Crop estimation has been made using all kinds of sensors and it has been found that higher resolution data always give more accurate results. (author). 3 refs

National Satellite Land Remote Sensing Data Archive

Science.gov (United States)

Faundeen, John L.; Longhenry, Ryan

2018-06-13

The National Satellite Land Remote Sensing Data Archive is managed on behalf of the Secretary of the Interior by the U.S. Geological Survey’s Earth Resources Observation and Science Center. The Land Remote Sensing Policy Act of 1992 (51 U.S.C. §601) directed the U.S. Department of the Interior to establish a permanent global archive consisting of imagery over land areas obtained from satellites orbiting the Earth. The law also directed the U.S. Department of the Interior, delegated to the U.S. Geological Survey, to ensure proper storage and preservation of imagery, and timely access for all parties. Since 2008, these images have been available at no cost to the user.

Mapping Water Use and Drought with Satellite Remote Sensing

OpenAIRE

Anderson, Martha

2014-01-01

Mapping water use and drought with satellite remote sensing. Martha C. Anderson, Bill Kustas, Feng Gao, Kate Semmens. USDA-Agricultural Research Service Hydrology and Remote Sensing Laboratory, Beltsville, MD. Chris Hain NOAA-NESDIS

Sensors for x-ray astronomy satellite

International Nuclear Information System (INIS)

Makino, Fumiyoshi; Kondo, Ichiro; Nishioka, Yonero; Kameda, Yoshihiko; Kubo, Masaki.

1980-01-01

For the purpose of observing the cosmic X-ray, the cosmic X-ray astronomy satellite (CORSA-b, named ''Hakucho'', Japanese for cygnus,) was launched Feb. 21, 1979 by Institute of Space and Aeronautical Science, University of Tokyo. The primary objectives of the satellite are: to perform panoramic survey of the space for X-ray bursts and to perform the spectral and temporal measurement of X-ray sources. The very soft X-ray sensor for X-ray observation and the horizon sensor for spacecraft attitude sensing were developed by Toshiba Corporation under technical support by University of Tokyo and Nagoya University for ''Hakucho''. The features of these sensors are outlined in this paper. (author)

Mission studies on constellation of LEO satellites with remote-sensing and communication payloads

Science.gov (United States)

Chen, Chia-Ray; Hwang, Feng-Tai; Hsueh, Chuang-Wei

2017-09-01

Revisiting time and global coverage are two major requirements for most of the remote sensing satellites. Constellation of satellites can get the benefit of short revisit time and global coverage. Typically, remote sensing satellites prefer to choose Sun Synchronous Orbit (SSO) because of fixed revisiting time and Sun beta angle. The system design and mission operation will be simple and straightforward. However, if we focus on providing remote sensing and store-and-forward communication services for low latitude countries, Sun Synchronous Orbit will not be the best choice because we need more satellites to cover the communication service gap in low latitude region. Sometimes the design drivers for remote sensing payloads are conflicted with the communication payloads. For example, lower orbit altitude is better for remote sensing payload performance, but the communication service zone will be smaller and we need more satellites to provide all time communication service. The current studies focus on how to provide remote sensing and communication services for low latitude countries. A cost effective approach for the mission, i.e. constellation of microsatellites, will be evaluated in this paper.

Leveraging Machine Learning to Estimate Soil Salinity through Satellite-Based Remote Sensing

Science.gov (United States)

Welle, P.; Ravanbakhsh, S.; Póczos, B.; Mauter, M.

2016-12-01

Human-induced salinization of agricultural soils is a growing problem which now affects an estimated 76 million hectares and causes billions of dollars of lost agricultural revenues annually. While there are indications that soil salinization is increasing in extent, current assessments of global salinity levels are outdated and rely heavily on expert opinion due to the prohibitive cost of a worldwide sampling campaign. A more practical alternative to field sampling may be earth observation through remote sensing, which takes advantage of the distinct spectral signature of salts in order to estimate soil conductivity. Recent efforts to map salinity using remote sensing have been met with limited success due to tractability issues of managing the computational load associated with large amounts of satellite data. In this study, we use Google Earth Engine to create composite satellite soil datasets, which combine data from multiple sources and sensors. These composite datasets contain pixel-level surface reflectance values for dates in which the algorithm is most confident that the surface contains bare soil. We leverage the detailed soil maps created and updated by the United States Geological Survey as label data and apply machine learning regression techniques such as Gaussian processes to learn a smooth mapping from surface reflection to noisy estimates of salinity. We also explore a semi-supervised approach using deep generative convolutional networks to leverage the abundance of unlabeled satellite images in producing better estimates for salinity values where we have relatively fewer measurements across the globe. The general method results in two significant contributions: (1) an algorithm that can be used to predict levels of soil salinity in regions without detailed soil maps and (2) a general framework that serves as an example for how remote sensing can be paired with extensive label data to generate methods for prediction of physical phenomenon.

Smartphone Video Guidance Sensor for Small Satellites

Data.gov (United States)

National Aeronautics and Space Administration — Smartphone Video Guidance Sensor(SVGS) for Small Satellites will provide a low-cost,integrated rendezvous & proximity operations sensor system to allow an...

Satellite Remote Sensing: Aerosol Measurements

Science.gov (United States)

Kahn, Ralph A.

2013-01-01

Aerosols are solid or liquid particles suspended in the air, and those observed by satellite remote sensing are typically between about 0.05 and 10 microns in size. (Note that in traditional aerosol science, the term "aerosol" refers to both the particles and the medium in which they reside, whereas for remote sensing, the term commonly refers to the particles only. In this article, we adopt the remote-sensing definition.) They originate from a great diversity of sources, such as wildfires, volcanoes, soils and desert sands, breaking waves, natural biological activity, agricultural burning, cement production, and fossil fuel combustion. They typically remain in the atmosphere from several days to a week or more, and some travel great distances before returning to Earth's surface via gravitational settling or washout by precipitation. Many aerosol sources exhibit strong seasonal variability, and most experience inter-annual fluctuations. As such, the frequent, global coverage that space-based aerosol remote-sensing instruments can provide is making increasingly important contributions to regional and larger-scale aerosol studies.

Beach erosion control study at Pass Christian. [using remote sensors and satellite observation

Science.gov (United States)

1978-01-01

The methods of measuring the existence of erosion and the effects of sand stabilization control systems are described. The mechanics of sand movement, the nature of sand erosion, and the use of satellite data to measure these factors and their surrogates are discussed using the locational and control aspects of aeolian and litoral erosion zones along the sand beach of the Mississippi coast. The aeolian erosion is highlighted due to the redeposition of the sand which causes high cleanup costs, property damage, and safety and health hazards. The areas of differential erosion and the patterns of beach sand movement are illustrated and the use of remote sensing methods to identify the areas of erosion are evaluated.

Remotely deployable aerial inspection using tactile sensors

Science.gov (United States)

MacLeod, C. N.; Cao, J.; Pierce, S. G.; Sullivan, J. C.; Pipe, A. G.; Dobie, G.; Summan, R.

2014-02-01

For structural monitoring applications, the use of remotely deployable Non-Destructive Evaluation (NDE) inspection platforms offer many advantages, including improved accessibility, greater safety and reduced cost, when compared to traditional manual inspection techniques. The use of such platforms, previously reported by researchers at the University Strathclyde facilitates the potential for rapid scanning of large areas and volumes in hazardous locations. A common problem for both manual and remote deployment approaches lies in the intrinsic stand-off and surface coupling issues of typical NDE probes. The associated complications of these requirements are obviously significantly exacerbated when considering aerial based remote inspection and deployment, resulting in simple visual techniques being the preferred sensor payload. Researchers at Bristol Robotics Laboratory have developed biomimetic tactile sensors modelled on the facial whiskers (vibrissae) of animals such as rats and mice, with the latest sensors actively sweeping their tips across the surface in a back and forth motion. The current work reports on the design and performance of an aerial inspection platform and the suitability of tactile whisking sensors to aerial based surface monitoring applications.

Operational Use of Remote Sensing within USDA

Science.gov (United States)

Bethel, Glenn R.

2007-01-01

A viewgraph presentation of remote sensing imagery within the USDA is shown. USDA Aerial Photography, Digital Sensors, Hurricane imagery, Remote Sensing Sources, Satellites used by Foreign Agricultural Service, Landsat Acquisitions, and Aerial Acquisitions are also shown.

Correlative studies of satellite ozone sensor measurements

International Nuclear Information System (INIS)

Lovill, J.E.; Ellis, J.S.

1983-01-01

Comparisons are made between total ozone measurements made by four satellite ozone sensors (TOMS, SBUV, TOVS and MFR). The comparisons were made during July 1979 when all sensors were operating simultaneously. The TOMS and SBUV sensors were observed to measure less total ozone than the MFR sensor, 10 and 15 Dobson units (DU) respectively. The MFR and TOMS sensors measured less ozone than the TOVS sensor, 19 an 28 DU, respectively. Latitudinal variability of the total ozone comparisons is discussed

Preface to: Pan Ocean Remote Sensing Conference (PORSEC)

Digital Repository Service at National Institute of Oceanography (India)

Desa, E.; Brown, R.; Shenoi, S.S.C.; Joseph, G.

Conference (PORSEC), earlier known as the Paci c Ocean Remote Sensing Conference (PORSEC), was formed in 1992 to provide a venue for international cooperation in the increasingly important area of remote sensing of the ocean. Many countries that border... and ocean dynamics, and modeling with satellite sensor (mainly microwave) data. Some of the presentations are of regional interest, while others will nd an audience beyond the satellite remote sensing community. These rst results through their simple...

Analysis on the status of the application of satellite remote sensing technology to nuclear safeguards

International Nuclear Information System (INIS)

Tao Zhangsheng; Zhao Yingjun

2008-01-01

Based on the application status of satellite remote sensing technology to nuclear safeguards, advantage of satellite remote sensing technology is analyzed, main types of satellite image used in nuclear safeguards are elaborated and the main application of satellite images is regarded to detect, verify and monitor nuclear activities; verify additional protocol declaration and design information, support performing complementary access inspections; investigate alleged undeclared activities based on open source or the third party information. Application examples of satellite image in nuclear safeguards to analyze nuclear facilities by other countries, the ability of remote sensing technology in nuclear safeguards is discussed. (authors)

The role of satellite remote sensing in structured ecosystem risk assessments.

Science.gov (United States)

Murray, Nicholas J; Keith, David A; Bland, Lucie M; Ferrari, Renata; Lyons, Mitchell B; Lucas, Richard; Pettorelli, Nathalie; Nicholson, Emily

2018-04-01

The current set of global conservation targets requires methods for monitoring the changing status of ecosystems. Protocols for ecosystem risk assessment are uniquely suited to this task, providing objective syntheses of a wide range of data to estimate the likelihood of ecosystem collapse. Satellite remote sensing can deliver ecologically relevant, long-term datasets suitable for analysing changes in ecosystem area, structure and function at temporal and spatial scales relevant to risk assessment protocols. However, there is considerable uncertainty about how to select and effectively utilise remotely sensed variables for risk assessment. Here, we review the use of satellite remote sensing for assessing spatial and functional changes of ecosystems, with the aim of providing guidance on the use of these data in ecosystem risk assessment. We suggest that decisions on the use of satellite remote sensing should be made a priori and deductively with the assistance of conceptual ecosystem models that identify the primary indicators representing the dynamics of a focal ecosystem. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Satellite monitoring of remote volcanoes improves study efforts in Alaska

Science.gov (United States)

Dean, K.; Servilla, M.; Roach, A.; Foster, B.; Engle, K.

Satellite monitoring of remote volcanoes is greatly benefitting the Alaska Volcano Observatory (AVO), and last year's eruption of the Okmok Volcano in the Aleutian Islands is a good case in point. The facility was able to issue and refine warnings of the eruption and related activity quickly, something that could not have been done using conventional seismic surveillance techniques, since seismometers have not been installed at these locations.AVO monitors about 100 active volcanoes in the North Pacific (NOPAC) region, but only a handful are observed by costly and logistically complex conventional means. The region is remote and vast, about 5000 × 2500 km, extending from Alaska west to the Kamchatka Peninsula in Russia (Figure 1). Warnings are transmitted to local communities and airlines that might be endangered by eruptions. More than 70,000 passenger and cargo flights fly over the region annually, and airborne volcanic ash is a threat to them. Many remote eruptions have been detected shortly after the initial magmatic activity using satellite data, and eruption clouds have been tracked across air traffic routes. Within minutes after eruptions are detected, information is relayed to government agencies, private companies, and the general public using telephone, fax, and e-mail. Monitoring of volcanoes using satellite image data involves direct reception, real-time monitoring, and data analysis. Two satellite data receiving stations, located at the Geophysical Institute, University of Alaska Fairbanks (UAF), are capable of receiving data from the advanced very high resolution radiometer (AVHRR) on National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites and from synthetic aperture radar (SAR) equipped satellites.

Surface-enhanced Raman fiberoptic sensors for remote monitoring

Energy Technology Data Exchange (ETDEWEB)

Stokes, D.L.; Alarie, J.P.; Vo-Dinh, T. [Oak Ridge National Lab., TN (United States). Health Sciences Research Div.

1995-09-01

A new sensor design for remote surface-enhanced Raman scattering (SERS) measurements has been developed for environmental applications. The design features the modification of an optical fiber using layers of alumina microparticles and silver coatings for inducing the SERS effect at the sensing probe. A single fiber carries both the laser excitation and the SERS signal radiation, keeping optical parameters at the remote tip simple and consistent. The small tip size achievable with this configuration also demonstrates potential of this new design as a microsensor for in-situ measurement in microenvironments. Details of sensor tip fabrication and optical system design are described. SERS spectra of aqueous environmental samples acquired in-situ using the SERS sensor are also presented to illustrate the effectiveness of the SERS sensor.

Online Remote Recording and Monitoring of Sensor Data Using DTMF Technology

Directory of Open Access Journals (Sweden)

Niladri Sekhar TRIPATHY

2011-05-01

Full Text Available Different wireless application platforms are available for remote monitoring and control of systems. In the present paper a system has been described for online remote recording and monitoring of sensor data using DTMF (Dual Tone Multi Frequency technology where acoustic communication has been implemented. One DTMF transceiver in the sensing system has been used to generate and decode the DTMF tone corresponding to the sensor output which in turn is received from the mobile phone in the user side. A separate DTMF decoder has been used in the user side to decode the received DTMF tone corresponding to the sensor output from the sensor side. Microcontroller has been used to store the decoded data from the sensor and to control the whole operation sequentially. Thus online remote recording and monitoring of the sensor data have been possible at any where in the coverage area of the mobile network. Experimental result shows good linearity between data output taken directly from the sensor side and that remotely from user side.

AROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data

Directory of Open Access Journals (Sweden)

Daniel Scheffler

2017-07-01

Full Text Available Geospatial co-registration is a mandatory prerequisite when dealing with remote sensing data. Inter- or intra-sensoral misregistration will negatively affect any subsequent image analysis, specifically when processing multi-sensoral or multi-temporal data. In recent decades, many algorithms have been developed to enable manual, semi- or fully automatic displacement correction. Especially in the context of big data processing and the development of automated processing chains that aim to be applicable to different remote sensing systems, there is a strong need for efficient, accurate and generally usable co-registration. Here, we present AROSICS (Automated and Robust Open-Source Image Co-Registration Software, a Python-based open-source software including an easy-to-use user interface for automatic detection and correction of sub-pixel misalignments between various remote sensing datasets. It is independent of spatial or spectral characteristics and robust against high degrees of cloud coverage and spectral and temporal land cover dynamics. The co-registration is based on phase correlation for sub-pixel shift estimation in the frequency domain utilizing the Fourier shift theorem in a moving-window manner. A dense grid of spatial shift vectors can be created and automatically filtered by combining various validation and quality estimation metrics. Additionally, the software supports the masking of, e.g., clouds and cloud shadows to exclude such areas from spatial shift detection. The software has been tested on more than 9000 satellite images acquired by different sensors. The results are evaluated exemplarily for two inter-sensoral and two intra-sensoral use cases and show registration results in the sub-pixel range with root mean square error fits around 0.3 pixels and better.

Remote powering platform for implantable sensor systems at 2.45 GHz.

Science.gov (United States)

Kazanc, Onur; Yilmaz, Gurkan; Maloberti, Franco; Dehollain, Catherine

2014-01-01

Far-field remotely powered sensor systems enable long distance operation for low-power sensor systems. In this work, we demonstrate a remote powering platform with a miniaturized antenna and remote powering base station operating at 2.45 GHz. The rectenna, which is the energy receiving and conversion element of the sensor system, is designed and measured. The measurements for the tag are performed within 15 cm distance from the remote powering base station. The realized gain of the tag antenna is measured as -3.3 dB, which is 0.5 dB close to the simulations, where simulated realized gain is -2.8 dB.

Testing integrated sensors for cooperative remote monitoring

International Nuclear Information System (INIS)

Filby, E.E.; Smith, T.E.; Albano, R.K.; Andersen, M.K.; Lucero, R.L.; Tolk, K.M.; Andrews, N.S.

1996-01-01

The Modular Integrated Monitoring System (MIMS) program, with Sandia National Laboratory (SNL) as the lead lab, was devised to furnish sensors and integrated multi-sensor systems for cooperative remote monitoring. The Idaho National Engineering Laboratory (INEL), via the Center for Integrated Monitoring and Control (CIMC), provides realistic field tests of the sensors and sensor-integration approach for the MIMS, and for other similar programs. This has two important goals: it helps insure that these systems are truly read for use, and provides a platform so they can be demonstrated for potential users. A remote monitoring test/demonstration has been initiated at the Idaho Chemical Processing Plant (ICPP) to track the movement of spent nuclear fuel from one storage location to another, using a straddle carrier and shielded cask combination. Radiation monitors, motion sensors, videocameras, and other devices from several US Department of Energy (DOE) labs and commercial vendors were linked on the network. Currently, project personnel are collecting raw data from this large array of sensors, without trying to program any special network activities or other responses. These data will be used to determine which devices can actually provide useful information for a cooperative monitoring situation, versus those that may be redundant

Remote Sensing of Selected Water-Quality Indicators with the Hyperspectral Imager for the Coastal Ocean (HICO) Sensor

Science.gov (United States)

2014-01-01

the bands needed for atmospheric correction. Spectral definition files for AVIRIS, HYDICE, HYMAP, HYPERION, CASI, and AISA sensors are included as...Satellite Visible Imagery – A Review.” In Lecture Notes on Coastal and Estuarine Studies, edited by R. T. Barber, N. K. Mooers, M. J. Bowman, and B...In Proceedings of SPIE Coastal Ocean Remote Sensing, edited by Robert J. Frouin, ZhongPing Lee, Vol. 6680, 668013-1-668013-9. doi:10.1117/12.736845

Ultraviolet spectrographs for thermospheric and ionospheric remote sensing

International Nuclear Information System (INIS)

Dymond, K.F.; McCoy, R.P.

1993-01-01

The Naval Research Laboratory (NRL) has been developing far- and extreme-ultraviolet spectrographs for remote sensing the Earth's upper atmosphere and ionosphere. The first of these sensors, called the Special Sensor Ultraviolet Limb Imager (SSULI), will be flying on the Air Force's Defense Meteorological Satellite Program (DMSP) block 5D3 satellites as an operational sensor in the 1997-2010 time frame. A second sensor, called the High-resolution ionospheric and Thermospheric Spectrograph (HITS), will fly in late 1995 on the Air Force Space Test Program's Advanced Research and Global Observation Satellite (ARGOS, also known as P91-1) as part of NRL's High Resolution Airglow and Auroral Spectroscopy (HIRAAS) experiment. Both of these instruments are compact and do not draw much power and would be good candidates for small satellite applications. The instruments and their capabilities are discussed. Possible uses of these instruments in small satellite applications are also presented

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

Science.gov (United States)

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

2013-01-01

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

Small-satellite technology and applications; Proceedings of the Meeting, Orlando, FL, Apr. 4, 5, 1991

Science.gov (United States)

Horais, Brian J.

Remote sensing applications and systems, small satellites for sensing missions, and supporting technologies are the broad topics discussed. Particular papers are presented on small satellites for water cycle experiments, low-cost spacecraft buses for remote sensing applications, Webersat (a low-cost imaging satellite), DARPA initiatives in small-satellite technologies, a solid-state magnetic azimuth sensor for small satellites, and thermal analysis of a small expendable tether satellite package. (For individual items see A93-24152 to A93-24175)

Fusing Mobile In Situ Observations and Satellite Remote Sensing of Chemical Release Emissions to Improve Disaster Response

Directory of Open Access Journals (Sweden)

Ira Leifer

2016-09-01

Full Text Available Chemical release disasters have serious consequences, disrupting ecosystems, society, and causing significant loss of life. Mitigating the destructive impacts relies on identification and mapping, monitoring, and trajectory forecasting. Improvements in sensor capabilities are enabling airborne and spacebased remote sensing to support response activities. Key applications are improving transport models in complex terrain and improved disaster response.Chemical release disasters have serious consequences, disrupting ecosystems, society, and causing significant loss of life. Mitigating the destructive impacts relies on identification and mapping, monitoring, and trajectory forecasting. Improvements in sensor capabilities are enabling airborne and space-based remote sensing to support response activities. Key applications are improving transport models in complex terrain and improved disaster response.Understanding urban atmospheric transport in the Los Angeles Basin, where topographic influences on transport patterns are significant, was improved by leveraging the Aliso Canyon leak as an atmospheric tracer. Plume characterization data was collected by the AutoMObile trace Gas (AMOG Surveyor, a commuter car modified for science. Mobile surface in situ CH4 and winds were measured by AMOG Surveyor under Santa Ana conditions to estimate an emission rate of 365±30% Gg yr-1. Vertical profiles were collected by AMOG Surveyor by leveraging local topography for vertical profiling to identify the planetary boundary layer at ~700 m. Topography significantly constrained plume dispersion by up to a factor of two. The observed plume trajectory was used to validate satellite aerosol optical depth-inferred atmospheric transport, which suggested the plume first was driven offshore, but then veered back towards land. Numerical long-range transport model predictions confirm this interpretation. This study demonstrated a novel application of satellite aerosol remote

Image Positioning Accuracy Analysis for Super Low Altitude Remote Sensing Satellites

Directory of Open Access Journals (Sweden)

Ming Xu

2012-10-01

Full Text Available Super low altitude remote sensing satellites maintain lower flight altitudes by means of ion propulsion in order to improve image resolution and positioning accuracy. The use of engineering data in design for achieving image positioning accuracy is discussed in this paper based on the principles of the photogrammetry theory. The exact line-of-sight rebuilding of each detection element and this direction precisely intersecting with the Earth's elliptical when the camera on the satellite is imaging are both ensured by the combined design of key parameters. These parameters include: orbit determination accuracy, attitude determination accuracy, camera exposure time, accurately synchronizing the reception of ephemeris with attitude data, geometric calibration and precise orbit verification. Precise simulation calculations show that image positioning accuracy of super low altitude remote sensing satellites is not obviously improved. The attitude determination error of a satellite still restricts its positioning accuracy.

High Resolution Satellite Remote Sensing of the 2013-2014 Eruption of Sinabung Volcano, Sumatra, Indonesia

Science.gov (United States)

Wessels, R. L.; Griswold, J. P.

2014-12-01

Satellite remote sensing provided timely observations of the volcanic unrest and several months-long eruption at Sinabung Volcano, Indonesia. Visible to thermal optical and synthetic aperture radar (SAR) systems provided frequent observations of Sinabung. High resolution image data with spatial resolutions from 0.5 to 1.5m offered detailed measurements of early summit deformation and subsequent lava dome and lava flow extrusion. The high resolution data were captured by commercial satellites such as WorldView-1 and -2 visible to near-infrared (VNIR) sensors and by CosmoSkyMed, Radarsat-2, and TerraSar-X SAR systems. Less frequent 90 to 100m spatial resolution night time thermal infrared (TIR) observations were provided by ASTER and Landsat-8. The combination of data from multiple sensors allowed us to construct a more complete timeline of volcanic activity than was available via only ground-based observations. This satellite observation timeline documents estimates of lava volume and effusion rates and major explosive and lava collapse events. Frequent, repeat volume estimates suggest at least three high effusion rate pulses of up to 20 m3/s occurred during the first three months of lava effusion with an average effusion rate of 6m3/s from January 2014 to August 2014. Many of these rates and events show some correlation to variations in the Real-time Seismic-Amplitude Measurement (RSAM) documented by the Indonesian Center for Volcanology and Geologic Hazard Mitigation (CVGHM).

Vacuum Radiance-Temperature Standard Facility for Infrared Remote Sensing at NIM

Science.gov (United States)

Hao, X. P.; Song, J.; Xu, M.; Sun, J. P.; Gong, L. Y.; Yuan, Z. D.; Lu, X. F.

2018-06-01

As infrared remote sensors are very important parts of Earth observation satellites, they must be calibrated based on the radiance temperature of a blackbody in a vacuum chamber prior to launch. The uncertainty of such temperature is thus an essential component of the sensors' uncertainty. This paper describes the vacuum radiance-temperature standard facility (VRTSF) at the National Institute of Metrology of China, which will serve to calibrate infrared remote sensors on Chinese meteorological satellites. The VRTSF can be used to calibrate vacuum blackbody radiance temperature, including those used to calibrate infrared remote sensors. The components of the VRTSF are described in this paper, including the VMTBB, the LNBB, the FTIR spectrometer, the reduced-background optical system, the vacuum chamber used to calibrate customers' blackbody, the vacuum-pumping system and the liquid-nitrogen-support system. The experimental methods and results are expounded. The uncertainty of the radiance temperature of VMTBB is 0.026 °C at 30 °C over 10 μm.

Measuring Radiant Emissions from Entire Prescribed Fires with Ground, Airborne and Satellite Sensors RxCADRE 2012

Science.gov (United States)

Dickinson, Matthew B.; Hudak, Andrew T.; Zajkowski, Thomas; Loudermilk, E. Louise; Schroeder, Wilfrid; Ellison, Luke; Kremens, Robert L.; Holley, William; Martinez, Otto; Paxton, Alexander;

Advances in multi-sensor data fusion: algorithms and applications.

Science.gov (United States)

Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying

2009-01-01

With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.

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

Science.gov (United States)

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

2013-01-01

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

Decision tree approach for classification of remotely sensed satellite

Indian Academy of Sciences (India)

DTC) algorithm for classification of remotely sensed satellite data (Landsat TM) using open source support. The decision tree is constructed by recursively partitioning the spectral distribution of the training dataset using WEKA, open source ...

A remotely interrogatable sensor for chemical monitoring

Science.gov (United States)

Stoyanov, P. G.; Doherty, S. A.; Grimes, C. A.; Seitz, W. R.

1998-01-01

A new type of continuously operating, in-situ, remotely monitored sensor is presented. The sensor is comprised of a thin film array of magnetostatically coupled, magnetically soft ferromagnetic thin film structures, adhered to or encased within a thin polymer layer. The polymer is made so that it swells or shrinks in response to the chemical analyte of interest, which in this case is pH. As the polymer swells or shrinks, the magnetostatic coupling between the magnetic elements changes, resulting in changes in the magnetic switching characteristics of the sensor. Placed within a sinusoidal magnetic field the magnetization vector of the coupled sensor elements periodically reverses directions, generating magnetic flux that can be remotely detected as a series of voltage spikes in appropriately placed pickup coils. one preliminary sensor design consists of four triangles, initially spaced approximately 50 micrometers apart, arranged to form a 12 mm x 12 mm square with the triangle tips centered at a common origin. Our preliminary work has focused on monitoring of pH using a lightly crosslinked pH sensitive polymer layer of hydroxyethylmethacrylate and 2-(dimethylamino) ethylmethacrylate. As the polymer swells or shrinks the magnetostatic coupling between the triangles changes, resulting in measurable changes in the amplitude of the detected voltage spirits.

77 FR 42419 - Airworthiness Directives; Honeywell International, Inc. Global Navigation Satellite Sensor Units

Science.gov (United States)

2012-07-19

... Airworthiness Directives; Honeywell International, Inc. Global Navigation Satellite Sensor Units AGENCY: Federal.... Model KGS200 Mercury\\2\\ wide area augmentation system (WAAS) global navigation satellite sensor units... similar Honeywell global positioning system (GPS) sensor and the same software as the Model KGS200 Mercury...

An Observation Capability Semantic-Associated Approach to the Selection of Remote Sensing Satellite Sensors: A Case Study of Flood Observations in the Jinsha River Basin.

Science.gov (United States)

Hu, Chuli; Li, Jie; Lin, Xin; Chen, Nengcheng; Yang, Chao

2018-05-21

Observation schedules depend upon the accurate understanding of a single sensor’s observation capability and the interrelated observation capability information on multiple sensors. The general ontologies for sensors and observations are abundant. However, few observation capability ontologies for satellite sensors are available, and no study has described the dynamic associations among the observation capabilities of multiple sensors used for integrated observational planning. This limitation results in a failure to realize effective sensor selection. This paper develops a sensor observation capability association (SOCA) ontology model that is resolved around the task-sensor-observation capability (TSOC) ontology pattern. The pattern is developed considering the stimulus-sensor-observation (SSO) ontology design pattern, which focuses on facilitating sensor selection for one observation task. The core aim of the SOCA ontology model is to achieve an observation capability semantic association. A prototype system called SemOCAssociation was developed, and an experiment was conducted for flood observations in the Jinsha River basin in China. The results of this experiment verified that the SOCA ontology based association method can help sensor planners intuitively and accurately make evidence-based sensor selection decisions for a given flood observation task, which facilitates efficient and effective observational planning for flood satellite sensors.

An Observation Capability Semantic-Associated Approach to the Selection of Remote Sensing Satellite Sensors: A Case Study of Flood Observations in the Jinsha River Basin

Directory of Open Access Journals (Sweden)

Chuli Hu

2018-05-01

Full Text Available Observation schedules depend upon the accurate understanding of a single sensor’s observation capability and the interrelated observation capability information on multiple sensors. The general ontologies for sensors and observations are abundant. However, few observation capability ontologies for satellite sensors are available, and no study has described the dynamic associations among the observation capabilities of multiple sensors used for integrated observational planning. This limitation results in a failure to realize effective sensor selection. This paper develops a sensor observation capability association (SOCA ontology model that is resolved around the task-sensor-observation capability (TSOC ontology pattern. The pattern is developed considering the stimulus-sensor-observation (SSO ontology design pattern, which focuses on facilitating sensor selection for one observation task. The core aim of the SOCA ontology model is to achieve an observation capability semantic association. A prototype system called SemOCAssociation was developed, and an experiment was conducted for flood observations in the Jinsha River basin in China. The results of this experiment verified that the SOCA ontology based association method can help sensor planners intuitively and accurately make evidence-based sensor selection decisions for a given flood observation task, which facilitates efficient and effective observational planning for flood satellite sensors.

CameraCast: flexible access to remote video sensors

Science.gov (United States)

Kong, Jiantao; Ganev, Ivan; Schwan, Karsten; Widener, Patrick

2007-01-01

New applications like remote surveillance and online environmental or traffic monitoring are making it increasingly important to provide flexible and protected access to remote video sensor devices. Current systems use application-level codes like web-based solutions to provide such access. This requires adherence to user-level APIs provided by such services, access to remote video information through given application-specific service and server topologies, and that the data being captured and distributed is manipulated by third party service codes. CameraCast is a simple, easily used system-level solution to remote video access. It provides a logical device API so that an application can identically operate on local vs. remote video sensor devices, using its own service and server topologies. In addition, the application can take advantage of API enhancements to protect remote video information, using a capability-based model for differential data protection that offers fine grain control over the information made available to specific codes or machines, thereby limiting their ability to violate privacy or security constraints. Experimental evaluations of CameraCast show that the performance of accessing remote video information approximates that of accesses to local devices, given sufficient networking resources. High performance is also attained when protection restrictions are enforced, due to an efficient kernel-level realization of differential data protection.

Taiwan's second remote sensing satellite

Science.gov (United States)

Chern, Jeng-Shing; Ling, Jer; Weng, Shui-Lin

2008-12-01

FORMOSAT-2 is Taiwan's first remote sensing satellite (RSS). It was launched on 20 May 2004 with five-year mission life and a very unique mission orbit at 891 km altitude. This orbit gives FORMOSAT-2 the daily revisit feature and the capability of imaging the Arctic and Antarctic regions due to the high enough altitude. For more than three years, FORMOSAT-2 has performed outstanding jobs and its global effectiveness is evidenced in many fields such as public education in Taiwan, Earth science and ecological niche research, preservation of the world heritages, contribution to the International Charter: space and major disasters, observation of suspected North Korea and Iranian nuclear facilities, and scientific observation of the atmospheric transient luminous events (TLEs). In order to continue the provision of earth observation images from space, the National Space Organization (NSPO) of Taiwan started to work on the second RSS from 2005. This second RSS will also be Taiwan's first indigenous satellite. Both the bus platform and remote sensing instrument (RSI) shall be designed and manufactured by NSPO and the Instrument Technology Research Center (ITRC) under the supervision of the National Applied Research Laboratories (NARL). Its onboard computer (OBC) shall use Taiwan's indigenous LEON-3 central processing unit (CPU). In order to achieve cost effective design, the commercial off the shelf (COTS) components shall be widely used. NSPO shall impose the up-screening/qualification and validation/verification processes to ensure their normal functions for proper operations in the severe space environments.

Remote sensing for water quality and biological measurements in coastal waters

International Nuclear Information System (INIS)

Johnson, R.W.; Harriss, R.C.

1980-01-01

Recent remote sensing experiments in the United States' coastal waters indicate that certain biological and water quality parameters have distinctive spectral characteristics. Data outputs from remote sensors, to date, include: (1) high resolution measurements to determine concentrations and distributions of total suspended particulates, temperature, salinity, chlorophyll a, and phytoplankton color group associations from airborne and/or satellite platforms, and (2) low resolution measurements of total suspended solids, temperature, ocean color, and possibly chlorophyll from satellite platforms. A summary of platforms, sensors and parameters measured is given. Remote sensing, especially when combined with conventional oceanographic research methods, can be useful in such high priority research areas as estuarine and continental shelf sediment transport dynamics, transport and fate of marine pollutants, marine phytoplankton dynamics, and ocean fronts

Satellite Remote Sensing of Particulate Matter Air Quality: Progress, Potential and Pitfalls (Invited)

Science.gov (United States)

Christopher, S. A.

2009-12-01

Satellite Remote Sensing of Particulate Matter Air Quality: Progress, Potential and Pitfalls Abstract. Fine or respirable particles with particle aerodynamic diameters less than 2.5 µm (PM2.5) affect visibility, change cloud properties, reflect and absorb incoming solar radiation, affect human health and are ubiquitous in the atmosphere. These particles are injected into the atmosphere either as primary emissions or form into the atmosphere by gas to particle conversion. There are various sources of PM2.5 including emissions from automobiles, industrial exhaust, and agricultural fires. In 2006, the United States Environmental Protection Agency (EPA) made the standards stringent by changing the 24-hr averaged PM2.5 mass values from 65µgm-3 to 35µgm-3. This was primarily based on epidemiological studies that showed the long term health benefits of making the PM2.5 standards stringent. Typically PM2.5 mass concentration is measured from surface monitors and in the United States there are nearly 1000 such filter based daily and 600 contiguous stations managed by federal, state, local, and tribal agencies. Worldwide, there are few PM2.5 ground monitors since they are expensive to purchase, maintain and operate. Satellite remote sensing therefore provides a viable method for monitoring PM2.5 from space. Although, there are several hundred satellites currently in orbit and not all of them are suited for PM2.5 air quality assessments. Typically multi-spectral reflected solar radiation measurements from space-borne sensors are converted to aerosol optical depth (AOD) which is a measure of the column (surface to top of atmosphere) integrated extinction (absorption plus scattering). This column AOD (usually at 550 nm) is often converted to PM2.5 mass near the ground using various techniques. In this presentation we discuss the progress over the last decade on assessing PM2.5 from satellites; outline the potential and discuss the various pitfalls that one encounters. We

Applications of FBG sensors on telecom satellites

Science.gov (United States)

Abad, S.; Araújo, F. M.; Ferreira, L. A.; Pedersen, F.; Esteban, M. A.; McKenzie, I.; Karafolas, N.

2017-11-01

Monitoring needs of spacecraft are rapidly increasing due to new and more challenging missions, along with demands to reduce launching costs by minimizing the manufacture, assembly, integration and test time and employing new low weight materials balanced by the need for maximizing system lifetime while maintaining good reliability. Conventional electronic sensors are characterized by their low multiplexing capability and their EMI/RF susceptibility and it is in this scenario that Fiber Optic Sensors (FOS) in general, and more specifically Fiber Bragg Grating (FBG) technology offers important benefits, improving in various ways the already deployed sensing subsystems (e.g. reducing the weight associated with sensor cabling, increasing the number of sensing points) and enabling new monitoring applications that were not possible by using conventional sensing technologies. This work presents the activities performed and the lessons learnt in the frame of ESA's ARTES-5 project "Fiber Optic Sensing Subsystem for Spacecraft Health Monitoring in Telecommunication Satellites". This project finished in July 2009, with the implementation and testing of two different demonstrators employing FBG sensor technology: FBG sensors for temperature monitoring in high voltage environments, and in particular in several parts of electric propulsion subsystems [1], and FBG sensors for thermal monitoring of array-antennas during RF testing [2]. In addition, the contacts performed with different actors within the space community allowed the identification of a special area of interest for the substitution of regular thermocouple instrumentation by FBG technology for thermal vacuum ground testing of satellites.

Push-Broom-Type Very High-Resolution Satellite Sensor Data Correction Using Combined Wavelet-Fourier and Multiscale Non-Local Means Filtering

Science.gov (United States)

Kang, Wonseok; Yu, Soohwan; Seo, Doochun; Jeong, Jaeheon; Paik, Joonki

2015-01-01

In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image from a noisy input is an ill-posed problem, a simple noise removal algorithm cannot preserve the radiometric integrity of satellite data. To solve these problems, we present a novel method to correct VHR data acquired by a push-broom-type sensor by combining wavelet-Fourier and multiscale non-local means (NLM) filters. After the wavelet-Fourier filter separates the stripe noise from the mixed noise in the wavelet low- and selected high-frequency sub-bands, random noise is removed using the multiscale NLM filter in both low- and high-frequency sub-bands without loss of image detail. The performance of the proposed method is compared to various existing methods on a set of push-broom-type sensor data acquired by Korean Multi-Purpose Satellite 3 (KOMPSAT-3) with severe stripe and random noise, and the results of the proposed method show significantly improved enhancement results over existing state-of-the-art methods in terms of both qualitative and quantitative assessments. PMID:26378532

ESTO Investments in Innovative Sensor Technologies for Remote Sensing

Science.gov (United States)

Babu, Sachidananda R.

2017-01-01

For more then 18 years NASA Earth Science Technology Office has been investing in remote sensing technologies. During this period ESTO has invested in more then 900 tasks. These tasks are managed under multiple programs like Instrument Incubator Program (IIP), Advanced Component Technology (ACT), Advanced Information Systems Technology (AIST), In-Space Validation of Earth Science Technologies (InVEST), Sustainable Land Imaging - Technology (SLI-T) and others. This covers the whole spectrum of technologies from component to full up satellite in space and software. Over the years many of these technologies have been infused into space missions like Aquarius, SMAP, CYGNSS, SWOT, TEMPO and others. Over the years ESTO is actively investing in Infrared sensor technologies for space applications. Recent investments have been for SLI-T and InVEST program. On these tasks technology development is from simple Bolometers to Advanced Photonic waveguide based spectrometers. Some of the details on these missions and technologies will be presented.

Future European and Japanese remote-sensing sensors and programs; Proceedings of the Meeting, Orlando, FL, Apr. 1, 2, 1991

Science.gov (United States)

Slater, Philip N.

Consideration is given to the METEOSAT second-generation program, the ESA earth observation polar platform program, a new satellite for a climatology study in the tropics, a medium-resolution imaging spectrometer, a Michelson interferometer for passive atmosphere sounding, an optical mapping instrument, an optical sensor system for Japanese earth resources satellite 1, a synthetic aperture radar of JERS-1, an ocean color and temperature scanner for Advanced Earth-Observing Satellite (ADEOS), an interferometric monitor for greenhouse gasses for ADEOS. Attention is also given to Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) for EOS-A, short-wave infrared subsystem design status of ASTER, ASTER calibration concept, Japanese polar orbit platform program, and airborne and spaceborne thermal multispectral remote sensing. (For individual items see A93-20427 to A93-20452)

A satellite constellation optimization for a regional GNSS remote sensing mission

Science.gov (United States)

Gavili Kilaneh, Narin; Mashhadi Hossainali, Masoud

2017-04-01

Due to the recent advances in the Global Navigation Satellite System Remote sensing (GNSS¬R) applications, optimization of a satellite orbit to investigate the Earth's properties seems significant. The comparison of the GNSS direct and reflected signals received by a Low Earth Orbit (LEO) satellite introduces a new technique to remotely sense the Earth. Several GNSS¬R missions including Cyclone Global Navigation Satellite System (CYGNSS) have been proposed for different applications such as the ocean wind speed and height monitoring. The geometric optimization of the satellite orbit before starting the mission is a key step for every space mission. Since satellite constellation design varies depending on the application, we have focused on the required geometric criteria for oceanography applications in a specified region. Here, the total number of specular points, their spatial distribution and the accuracy of their position are assumed to be sufficient for oceanography applications. Gleason's method is used to determine the position of specular points. We considered the 2-D lattice and 3-D lattice theory of flower constellation to survey whether a circular orbit or an elliptical one is suitable to improve the solution. Genetic algorithm is implemented to solve the problem. To check the visibility condition between the LEO and GPS satellites, the satellite initial state is propagated by a variable step size numerical integration method. Constellation orbit parameters achieved by optimization provide a better resolution and precession for the specular points in the study area of this research.

Design of a temperature control system using incremental PID algorithm for a special homemade shortwave infrared spatial remote sensor based on FPGA

Science.gov (United States)

Xu, Zhipeng; Wei, Jun; Li, Jianwei; Zhou, Qianting

2010-11-01

An image spectrometer of a spatial remote sensing satellite requires shortwave band range from 2.1μm to 3μm which is one of the most important bands in remote sensing. We designed an infrared sub-system of the image spectrometer using a homemade 640x1 InGaAs shortwave infrared sensor working on FPA system which requires high uniformity and low level of dark current. The working temperature should be -15+/-0.2 Degree Celsius. This paper studies the model of noise for focal plane array (FPA) system, investigated the relationship with temperature and dark current noise, and adopts Incremental PID algorithm to generate PWM wave in order to control the temperature of the sensor. There are four modules compose of the FPGA module design. All of the modules are coded by VHDL and implemented in FPGA device APA300. Experiment shows the intelligent temperature control system succeeds in controlling the temperature of the sensor.

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

Science.gov (United States)

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

2017-08-01

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

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.

The determinations of remote sensing satellite data delivery service quality: A positivistic case study in Chinese context

Science.gov (United States)

Jin, Jiahua; Yan, Xiangbin; Tan, Qiaoqiao; Li, Yijun

2014-03-01

With the development of remote sensing technology, remote-sensing satellite has been widely used in many aspects of national construction. Big data with different standards and massive users with different needs, make the satellite data delivery service to be a complex giant system. How to deliver remote-sensing satellite data efficiently and effectively is a big challenge. Based on customer service theory, this paper proposes a hierarchy conceptual model for examining the determinations of remote-sensing satellite data delivery service quality in the Chinese context. Three main dimensions: service expectation, service perception and service environment, and 8 sub-dimensions are included in the model. Large amount of first-hand data on the remote-sensing satellite data delivery service have been obtained through field research, semi-structured questionnaire and focused interview. A positivist case study is conducted to validate and develop the proposed model, as well as to investigate the service status and related influence mechanisms. Findings from the analysis demonstrate the explanatory validity of the model, and provide potentially helpful insights for future practice.

The determinations of remote sensing satellite data delivery service quality: A positivistic case study in Chinese context

International Nuclear Information System (INIS)

Jin, Jiahua; Yan, Xiangbin; Tan, Qiaoqiao; Li, Yijun

2014-01-01

With the development of remote sensing technology, remote-sensing satellite has been widely used in many aspects of national construction. Big data with different standards and massive users with different needs, make the satellite data delivery service to be a complex giant system. How to deliver remote-sensing satellite data efficiently and effectively is a big challenge. Based on customer service theory, this paper proposes a hierarchy conceptual model for examining the determinations of remote-sensing satellite data delivery service quality in the Chinese context. Three main dimensions: service expectation, service perception and service environment, and 8 sub-dimensions are included in the model. Large amount of first-hand data on the remote-sensing satellite data delivery service have been obtained through field research, semi-structured questionnaire and focused interview. A positivist case study is conducted to validate and develop the proposed model, as well as to investigate the service status and related influence mechanisms. Findings from the analysis demonstrate the explanatory validity of the model, and provide potentially helpful insights for future practice

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

Science.gov (United States)

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

2017-04-01

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

Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes

Science.gov (United States)

Gallant, Alisa L.; Sadinski, Walter J.; Brown, Jesslyn F.; Senay, Gabriel B.; Roth, Mark F.

2018-01-01

Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relations between temperature and precipitation and a set of variables measured on the ground at individual wetlands and another set measured via satellite sensors within surrounding 4 km2 landscape blocks. At the block scale, we used evapotranspiration and vegetation greenness as remotely sensed proxies for water availability and to estimate seasonal photosynthetic activity. We used sensors on the ground to coincidentally measure surface-water availability and amphibian calling activity at individual wetlands within blocks. Responses of landscape blocks generally paralleled changes in conditions measured on the ground, but the latter were more dynamic, and changes in ecological conditions on the ground that were critical for biota were not always apparent in measurements of related parameters in blocks. Here, we evaluate the effectiveness of decisions and assumptions we made in applying the remotely sensed data for the assessment and the value of integrating observations across scales, sensors, and disciplines.

Remote sensing strategies for global resource exploration and environmental management

Science.gov (United States)

Henderson, Frederick B.

Since 1972, satellite remote sensing, when integrated with other exploration techniques, has demonstrated operational exploration and engineering cost savings and reduced exploration risks through improved geological mapping. Land and ocean remote sensing satellite systems under development for the 1990's by the United States, France, Japan, Canada, ESA, Russia, China, and others, will significantly increase our ability to explore for, develop, and manage energy and mineral resources worldwide. A major difference between these systems is the "Open Skies" and "Non-Discriminatory Access to Data" policies as have been practiced by the U.S. and France and the restrictive nationalistic data policies as have been practiced by Russia and India. Global exploration will use satellite remote sensing to better map regional structural and basin-like features that control the distribution of energy and mineral resources. Improved sensors will better map lithologic and stratigraphic units and identify alteration effects in rocks, soils, and vegetation cover indicative of undiscovered subsurface resources. These same sensors will also map and monitor resource development. The use of satellite remote sensing data will grow substantially through increasing integration with other geophysical, geochemical, and geologic data using improved geographic information systems (GIS). International exploration will focus on underdeveloped countries rather than on mature exploration areas such as the United States, Europe, and Japan. Energy and mineral companies and government agencies in these countries and others will utilize available remote sensing data to acquire economic intelligence on global resources. If the "Non-Discriminatory Access to Data" principle is observed by satellite producing countries, exploration will remain competitive "on the ground". In this manner, remote sensing technology will continue to be developed to better explore for and manage the world's needed resources

Spectral interdependence of remote-sensing reflectance and its implications on the design of ocean color satellite sensors.

Science.gov (United States)

Lee, Zhongping; Shang, Shaoling; Hu, Chuanmin; Zibordi, Giuseppe

2014-05-20

Using 901 remote-sensing reflectance spectra (R(rs)(λ), sr⁻¹, λ from 400 to 700 nm with a 5 nm resolution), we evaluated the correlations of R(rs)(λ) between neighboring spectral bands in order to characterize (1) the spectral interdependence of R(rs)(λ) at different bands and (2) to what extent hyperspectral R(rs)(λ) can be reconstructed from multiband measurements. The 901 R(rs) spectra were measured over a wide variety of aquatic environments in which water color varied from oceanic blue to coastal green or brown, with chlorophyll-a concentrations ranging from ~0.02 to >100  mg  m⁻³, bottom depths from ~1  m to >1000  m, and bottom substrates including sand, coral reef, and seagrass. The correlation coefficient of R(rs)(λ) between neighboring bands at center wavelengths λ(k) and λ(l), r(Δλ)(λ(k), λ(l)), was evaluated systematically, with the spectral gap (Δλ=λ(l)-λ(k)) changing between 5, 10, 15, 20, 25, and 30 nm, respectively. It was found that r(Δλ) decreased with increasing Δλ, but remained >0.97 for Δλ≤20  nm for all spectral bands. Further, using 15 spectral bands between 400 and 710 nm, we reconstructed, via multivariant linear regression, hyperspectral R(rs)(λ) (from 400 to 700 nm with a 5 nm resolution). The percentage difference between measured and reconstructed R(rs) for each band in the 400-700 nm range was generally less than 1%, with a correlation coefficient close to 1.0. The mean absolute error between measured and reconstructed R(rs) was about 0.00002  sr⁻¹ for each band, which is significantly smaller than the R(rs) uncertainties from all past and current ocean color satellite radiometric products. These results echo findings of earlier studies that R(rs) measurements at ~15 spectral bands in the visible domain can provide nearly identical spectral information as with hyperspectral (contiguous bands at 5 nm spectral resolution) measurements. Such results provide insights for data

Using infrared spectroscopy and satellite data to accurately monitor remote volcanoes and map their eruptive products

Science.gov (United States)

Ramsey, M. S.

2011-12-01

The ability to detect the onset of new activity at a remote volcano commonly relies on high temporal resolution thermal infrared (TIR) satellite-based observations. These observations from sensors such as AVHRR and MODIS are being used in innovative ways to produce trends of activity, which are critical for hazard response planning and scientific modeling. Such data are excellent for detection of new thermal features, volcanic plumes, and tracking changes over the hour time scale, for example. For some remote volcanoes, the lack of ground-based monitoring typically means that these sensors provide the first and only confirmation of renewed activity. However, what is lacking is the context of the higher spatial scale, which provides the volcanologist with meter-scale information on specific temperatures and changes in the composition and texture of the eruptive products. For the past eleven years, the joint US-Japanese ASTER instrument has been acquiring image-based data of volcanic eruptions around the world, including in the remote northern Pacific region. There have been more ASTER observations of Kamchatka volcanoes than any other location on the globe due mainly to an operational program put into place in 2004. Automated hot spot alarms from AVHRR data trigger ASTER acquisitions using the instrument's "rapid response" mode. Specifically for Kamchatka, this program has resulted in more than 700 additional ASTER images of the most thermally-active volcanoes (e.g., Shiveluch, Kliuchevskoi, Karymsky, Bezymianny). The scientific results from this program at these volcanoes will be highlighted. These results were strengthened by several field seasons used to map new products, collect samples for laboratory-based spectroscopy, and acquire TIR camera data. The fusion of ground, laboratory and space-based spectroscopy provided the most accurate interpretation of the eruptions and laid the ground work for future VSWIR/TIR sensors such as HyspIRI, which are a critically

Advanced Remote Sensing Research

Science.gov (United States)

Slonecker, Terrence; Jones, John W.; Price, Susan D.; Hogan, Dianna

2008-01-01

'Remote sensing' is a generic term for monitoring techniques that collect information without being in physical contact with the object of study. Overhead imagery from aircraft and satellite sensors provides the most common form of remotely sensed data and records the interaction of electromagnetic energy (usually visible light) with matter, such as the Earth's surface. Remotely sensed data are fundamental to geographic science. The Eastern Geographic Science Center (EGSC) of the U.S. Geological Survey (USGS) is currently conducting and promoting the research and development of three different aspects of remote sensing science: spectral analysis, automated orthorectification of historical imagery, and long wave infrared (LWIR) polarimetric imagery (PI).

Advancing the capabilities of reservoir remote sensing by leveraging multi-source satellite data

Science.gov (United States)

Gao, H.; Zhang, S.; Zhao, G.; Li, Y.

2017-12-01

With a total global capacity of more than 6000 km3, reservoirs play a key role in the hydrological cycle and in water resources management. However, essential reservoir data (e.g., elevation, storage, and evaporation loss) are usually not shared at a large scale. While satellite remote sensing offers a unique opportunity for monitoring large reservoirs from space, the commonly used radar altimeters can only detect storage variations of about 15% of global lakes at a repeat period of 10 days or longer. To advance the capabilities of reservoir sensing, we developed a series of algorithms geared towards generating long term reservoir records at improved spatial coverage, and at improved temporal resolution. To this goal, observations are leveraged from multiple satellite sensors, which include radar/laser altimeters, imagers, and passive microwave radiometers. In South Asia, we demonstrate that reservoir storage can be estimated under all-weather conditions at a 4 day time step, with the total capacity of monitored reservoirs increased to 45%. Within the Continuous United States, a first Landsat based evaporation loss dataset was developed (containing 204 reservoirs) from 1984 to 2011. The evaporation trends of these reservoirs are identified and the causes are analyzed. All of these algorithms and products were validated with gauge observations. Future satellite missions, which will make significant contributions to monitoring global reservoirs, are also discussed.

Satellite Data for All? Review of Google Earth Engine for Archaeological Remote Sensing

Directory of Open Access Journals (Sweden)

Omar A. Alcover Firpi

2016-11-01

Full Text Available A review of Google Earth Engine for archaeological remote sensing using satellite data. GEE is a freely accessible software option for processing remotely sensed data, part of the larger Google suite of products.

A remote assessment system with a vision robot and wearable sensors.

Science.gov (United States)

Zhang, Tong; Wang, Jue; Ren, Yumiao; Li, Jianjun

2004-01-01

This paper describes an ongoing researched remote rehabilitation assessment system that has a 6-freedom double-eyes vision robot to catch vision information, and a group of wearable sensors to acquire biomechanical signals. A server computer is fixed on the robot, to provide services to the robot's controller and all the sensors. The robot is connected to Internet by wireless channel, and so do the sensors to the robot. Rehabilitation professionals can semi-automatically practise an assessment program via Internet. The preliminary results show that the smart device, including the robot and the sensors, can improve the quality of remote assessment, and reduce the complexity of operation at a distance.

Calibration Uncertainty in Ocean Color Satellite Sensors and Trends in Long-term Environmental Records

Science.gov (United States)

Turpie, Kevin R.; Eplee, Robert E., Jr.; Franz, Bryan A.; Del Castillo, Carlos

2014-01-01

Launched in late 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft is being evaluated by NASA to determine whether this sensor can continue the ocean color data record established through the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and the MODerate resolution Imaging Spectroradiometer (MODIS). To this end, Goddard Space Flight Center generated evaluation ocean color data products using calibration techniques and algorithms established by NASA during the SeaWiFS and MODIS missions. The calibration trending was subjected to some initial sensitivity and uncertainty analyses. Here we present an introductory assessment of how the NASA-produced time series of ocean color is influenced by uncertainty in trending instrument response over time. The results help quantify the uncertainty in measuring regional and global biospheric trends in the ocean using satellite remote sensing, which better define the roles of such records in climate research.

In situ Volcanic Plume Monitoring with small Unmanned Aerial Systems for Cal/Val of Satellite Remote Sensing Data: CARTA-UAV 2013 Mission (Invited)

Science.gov (United States)

Diaz, J. A.; Pieri, D. C.; Bland, G.; Fladeland, M. M.

2013-12-01

The development of small unmanned aerial systems (sUAS) with a variety of sensor packages, enables in situ and proximal remote sensing measurements of volcanic plumes. Using Costa Rican volcanoes as a Natural Laboratory, the University of Costa Rica as host institution, in collaboration with four NASA centers, have started an initiative to develop low-cost, field-deployable airborne platforms to perform volcanic gas & ash plume research, and in-situ volcanic monitoring in general, in conjunction with orbital assets and state-of-the-art models of plume transport and composition. Several gas sensors have been deployed into the active plume of Turrialba Volcano including a miniature mass spectrometer, and an electrochemical SO2 sensor system with temperature, pressure, relative humidity, and GPS sensors. Several different airborne platforms such as manned research aircraft, unmanned aerial vehicles, tethered balloons, as well as man-portable in-situ ground truth systems are being used for this research. Remote sensing data is also collected from the ASTER and OMI spaceborne instruments and compared with in situ data. The CARTA-UAV 2013 Mission deployment and follow up measurements successfully demonstrated a path to study and visualize gaseous volcanic emissions using mass spectrometer and gas sensor based instrumentation in harsh environment conditions to correlate in situ ground/airborne data with remote sensing satellite data for calibration and validation purposes. The deployment of such technology improves on our current capabilities to detect, analyze, monitor, model, and predict hazards presented to aircraft by volcanogenic ash clouds from active and impending volcanic eruptions.

SENSOR: a tool for the simulation of hyperspectral remote sensing systems

Science.gov (United States)

Börner, Anko; Wiest, Lorenz; Keller, Peter; Reulke, Ralf; Richter, Rolf; Schaepman, Michael; Schläpfer, Daniel

The consistent end-to-end simulation of airborne and spaceborne earth remote sensing systems is an important task, and sometimes the only way for the adaptation and optimisation of a sensor and its observation conditions, the choice and test of algorithms for data processing, error estimation and the evaluation of the capabilities of the whole sensor system. The presented software simulator SENSOR (Software Environment for the Simulation of Optical Remote sensing systems) includes a full model of the sensor hardware, the observed scene, and the atmosphere in between. The simulator consists of three parts. The first part describes the geometrical relations between scene, sun, and the remote sensing system using a ray-tracing algorithm. The second part of the simulation environment considers the radiometry. It calculates the at-sensor radiance using a pre-calculated multidimensional lookup-table taking the atmospheric influence on the radiation into account. The third part consists of an optical and an electronic sensor model for the generation of digital images. Using SENSOR for an optimisation requires the additional application of task-specific data processing algorithms. The principle of the end-to-end-simulation approach is explained, all relevant concepts of SENSOR are discussed, and first examples of its use are given. The verification of SENSOR is demonstrated. This work is closely related to the Airborne PRISM Experiment (APEX), an airborne imaging spectrometer funded by the European Space Agency.

Remote Laser Evaporative Molecular Absorption Spectroscopy Sensor System

Data.gov (United States)

National Aeronautics and Space Administration — We propose a sensor system capable of remotely probing the molecular composition of cold solar system targets (asteroids, comets, planets, moons), such as from a...

Using Satellite Remote Sensing and Modelling for Insights into N02 Air Pollution and NO2 Emissions

Science.gov (United States)

Lamsal, L. N.; Martin, R. V.; Krotkov, N. A.; Bucsela, E. J.; Celarier, E. A.; vanDonkelaar, A.; Parrish, D.

2012-01-01

Nitrogen oxides (NO(x)) are key actors in air quality and climate change. Satellite remote sensing of tropospheric NO2 has developed rapidly with enhanced spatial and temporal resolution since initial observations in 1995. We have developed an improved algorithm and retrieved tropospheric NO2 columns from Ozone Monitoring Instrument. Column observations of tropospheric NO2 from the nadir-viewing satellite sensors contain large contributions from the boundary layer due to strong enhancement of NO2 in the boundary layer. We infer ground-level NO2 concentrations from the OMI satellite instrument which demonstrate significant agreement with in-situ surface measurements. We examine how NO2 columns measured by satellite, ground-level NO2 derived from satellite, and NO(x) emissions obtained from bottom-up inventories relate to world's urban population. We perform inverse modeling analysis of NO2 measurements from OMI to estimate "top-down" surface NO(x) emissions, which are used to evaluate and improve "bottom-up" emission inventories. We use NO2 column observations from OMI and the relationship between NO2 columns and NO(x) emissions from a GEOS-Chem model simulation to estimate the annual change in bottom-up NO(x) emissions. The emission updates offer an improved estimate of NO(x) that are critical to our understanding of air quality, acid deposition, and climate change.

Towards automated statewide land cover mapping in Wisconsin using satellite remote sensing and GIS techniques

International Nuclear Information System (INIS)

Cosentino, B.L.; Lillesand, T.M.

1991-01-01

Attention is given to an initial research project being performed by the University of Wisconsin-Madison, Environmental Remote Sensing Center in conjunction with seven local, state, and federal agencies to implement automated statewide land cover mapping using satellite remote sensing and geographical information system (GIS) techniques. The basis, progress, and future research needs for this mapping program are presented. The research efforts are directed toward strategies that integrate satellite remote sensing and GIS techniques in the generation of land cover data for multiple users of land cover information. The project objectives are to investigate methodologies that integrate satellite data with other imagery and spatial data resident in emerging GISs in the state for particular program needs, and to develop techniques that can improve automated land cover mapping efficiency and accuracy. 10 refs

Sensor fault detection and recovery in satellite attitude control

Science.gov (United States)

Nasrolahi, Seiied Saeed; Abdollahi, Farzaneh

2018-04-01

This paper proposes an integrated sensor fault detection and recovery for the satellite attitude control system. By introducing a nonlinear observer, the healthy sensor measurements are provided. Considering attitude dynamics and kinematic, a novel observer is developed to detect the fault in angular rate as well as attitude sensors individually or simultaneously. There is no limit on type and configuration of attitude sensors. By designing a state feedback based control signal and Lyapunov stability criterion, the uniformly ultimately boundedness of tracking errors in the presence of sensor faults is guaranteed. Finally, simulation results are presented to illustrate the performance of the integrated scheme.

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

The use of the Space Shuttle for land remote sensing

Science.gov (United States)

Thome, P. G.

1982-01-01

The use of the Space Shuttle for land remote sensing will grow significantly during the 1980's. The main use will be for general land cover and geological mapping purposes by worldwide users employing specialized sensors such as: high resolution film systems, synthetic aperture radars, and multispectral visible/IR electronic linear array scanners. Because these type sensors have low Space Shuttle load factors, the user's preference will be for shared flights. With this strong preference and given the present prognosis for Space Shuttle flight frequency as a function of orbit inclination, the strongest demand will be for 57 deg orbits. However, significant use will be made of lower inclination orbits. Compared with freeflying satellites, Space Shuttle mission investment requirements will be significantly lower. The use of the Space Shuttle for testing R and D land remote sensors will replace the free-flying satellites for most test programs.

Impact of Missing Passive Microwave Sensors on Multi-Satellite Precipitation Retrieval Algorithm

Directory of Open Access Journals (Sweden)

Bin Yong

2015-01-01

Full Text Available The impact of one or two missing passive microwave (PMW input sensors on the end product of multi-satellite precipitation products is an interesting but obscure issue for both algorithm developers and data users. On 28 January 2013, the Version-7 TRMM Multi-satellite Precipitation Analysis (TMPA products were reproduced and re-released by National Aeronautics and Space Administration (NASA Goddard Space Flight Center because the Advanced Microwave Sounding Unit-B (AMSU-B and the Special Sensor Microwave Imager-Sounder-F16 (SSMIS-F16 input data were unintentionally disregarded in the prior retrieval. Thus, this study investigates the sensitivity of TMPA algorithm results to missing PMW sensors by intercomparing the “early” and “late” Version-7 TMPA real-time (TMPA-RT precipitation estimates (i.e., without and with AMSU-B, SSMIS-F16 sensors with an independent high-density gauge network of 200 tipping-bucket rain gauges over the Chinese Jinghe river basin (45,421 km2. The retrieval counts and retrieval frequency of various PMW and Infrared (IR sensors incorporated into the TMPA system were also analyzed to identify and diagnose the impacts of sensor availability on the TMPA-RT retrieval accuracy. Results show that the incorporation of AMSU-B and SSMIS-F16 has substantially reduced systematic errors. The improvement exhibits rather strong seasonal and topographic dependencies. Our analyses suggest that one or two single PMW sensors might play a key role in affecting the end product of current combined microwave-infrared precipitation estimates. This finding supports algorithm developers’ current endeavor in spatiotemporally incorporating as many PMW sensors as possible in the multi-satellite precipitation retrieval system called Integrated Multi-satellitE Retrievals for Global Precipitation Measurement mission (IMERG. This study also recommends users of satellite precipitation products to switch to the newest Version-7 TMPA datasets and

Remote diagnosis via a telecommunication satellite--ultrasonic tomographic image transmission experiments.

Science.gov (United States)

Nakajima, I; Inokuchi, S; Tajima, T; Takahashi, T

1985-04-01

An experiment to transmit ultrasonic tomographic section images required for remote medical diagnosis and care was conducted using the mobile telecommunication satellite OSCAR-10. The images received showed the intestinal condition of a patient incapable of verbal communication, however the image screen had a fairly coarse particle structure. On the basis of these experiments, were considered as the transmission of ultrasonic tomographic images extremely effective in remote diagnosis.

Minimizing Gaps of Daily Ndvi Map with Geostationary Satellite Remote Sensing Data

Science.gov (United States)

Lee, S.; Ryu, Y.; Jiang, C.

2015-12-01

Satellite based remote sensing has been used to monitor plant phenology. Numerous studies have generally utilized normalized difference vegetation index (NDVI) to quantify phenological patterns and changes in regional to the global scales. Obtaining the NDVI values during summer in East Asian Monsoon regions is important because most plants grow vigorously in this season. However, satellite derived NDVI data are error prone to clouds during most of the period. Various methods have attempted to reduce the effect of cloud in temporal and spatial NDVI monitoring; the fundamental solution is to have a large data pool that includes multiple images in short period and supplements NDVI values in same period. Multiple images of geostationary satellite in a day can be a method to expand the pool. In this study, we suggest an approach that minimizes data gaps in NDVI of the day through geostationary satellite derived NDVI composition. We acquired data from Geostationary Ocean Color Imager (GOCI) which is a satellite that was launched to monitor ocean around the Korean peninsula, China, Japan and Russia. The satellite observes eight times per day (09:00 - 16:00, every hour) at 500 x 500 m resolution from 2011 to 2015. GOCI red- and near infrared radiance was converted into surface reflectance by using 6S Radiative Transfer Model (6S). We calculated NDVI tiles for each of observed eight tiles per day and made one day NDVI through maximum-value composite method. We evaluated the composite GOCI derived NDVI by comparing with daily MODIS-derived NDVI (composited from MOD09GA and MYD09GA), 16-day Landsat 8-derived NDVI, and in-situ light emitting diode (LED) NDVI measurements at a homogeneous deciduous forest and rice paddy sites. We found that GOCI-derived NDVI maps revealed little data gaps compared to MODIS and Landsat, and GOCI derived NDVI time series were smoother than MODIS derived NDVI time series in summer. GOCI-derived NDVI agreed well with in-situ observations of NDVI

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

Orbital resonances of Taiwan's FORMOSAT-2 remote sensing satellite

Science.gov (United States)

Lin, Shin-Fa; Hwang, Cheinway

2018-06-01

Unlike a typical remote sensing satellite that has a global coverage and non-integral orbital revolutions per day, Taiwan's FORMOSAT-2 (FS-2) satellite has a non-global coverage due to the mission requirements of one-day repeat cycle and daily visit around Taiwan. These orbital characteristics result in an integer number of revolutions a day and orbital resonances caused by certain components of the Earth's gravity field. Orbital flight data indicated amplified variations in the amplitudes of FS-2's Keplerian elements. We use twelve years of orbital observations and maneuver data to analyze the cause of the resonances and explain the differences between the simulated (at the pre-launch stage) and real orbits of FS-2. The differences are quantified using orbital perturbation theories that describe secular and long-period orbital evolutions caused by resonances. The resonance-induced orbital rising rate of FS-2 reaches +1.425 m/day, due to the combined (modeled) effect of resonances and atmospheric drags (the relative modeling errors remote sensing mission similar to FS-2, especially in the early mission design and planning phase.

Satellite Remote Sensing For Aluminum And Nickel Laterites

Science.gov (United States)

Henderson, Frederick B.; Penfield, Glen T.; Grubbs, Donald K.

1984-08-01

The new LANDSAT-4,-5/Thematic Mapper (TM) land observational satellite remote sensing systems are providing dramatically new and important short wave infrared (SWIR) data, which combined with Landsat's Multi-Spectral Scanner (MSS) visible (VIS), very near infrared (VNIR), and thermal infrared (TI) data greatly improves regional geological mapping on a global scale. The TM will significantly improve clay, iron oxide, aluminum, and nickel laterite mapping capabilities over large areas of the world. It will also improve the ability to discriminate vegetation stress and species distribution associated with lateritic environments. Nickel laterites on Gag Island, Indonesia are defined by MSS imagery. Satellite imagery of the Cape Bougainville and the Darling Range, Australia bauxite deposits show the potential use of MSS data for exploration and mining applications. Examples of satellite syn-thetic aperture radar (SAR) for Jamaica document the use of this method for bauxite exploration. Thematic Mapper data will be combined with the French SPOT satellite's high spatial resolution and stereoscopic digital data, and U.S., Japanese, European, and Canadian Synthetic Aperture Radar (SAR) data to assist with logistics, mine development, and environ-mental concerns associated with aluminum and nickel lateritic deposits worldwide.

Micro-satellite for space debris observation by optical sensors

Science.gov (United States)

Thillot, Marc; Brenière, Xavier; Midavaine, Thierry

2017-11-01

The purpose of this theoretical study carried out under CNES contract is to analyze the feasibility of small space debris detection and classification with an optical sensor on-board micro-satellite. Technical solutions based on active and passive sensors are analyzed and compared. For the most appropriated concept an optimization was made and theoretical performances in terms of number of detection versus class of diameter were calculated. Finally we give some preliminary physical sensor features to illustrate the concept (weight, volume, consumption,…).

Famine Early Warning Systems and Their Use of Satellite Remote Sensing Data

Science.gov (United States)

Brown, Molly E.; Essam, Timothy; Leonard, Kenneth

2011-01-01

Famine early warning organizations have experience that has much to contribute to efforts to incorporate climate and weather information into economic and political systems. Food security crises are now caused almost exclusively by problems of food access, not absolute food availability, but the role of monitoring agricultural production both locally and globally remains central. The price of food important to the understanding of food security in any region, but it needs to be understood in the context of local production. Thus remote sensing is still at the center of much food security analysis, along with an examination of markets, trade and economic policies during food security analyses. Technology including satellite remote sensing, earth science models, databases of food production and yield, and modem telecommunication systems contributed to improved food production information. Here we present an econometric approach focused on bringing together satellite remote sensing and market analysis into food security assessment in the context of early warning.

User requirements and user acceptance of current and next-generation satellite mission and sensor complement, oriented toward the monitoring of water resources

Science.gov (United States)

Castruccio, P. A.; Loats, H. L., Jr.; Fowler, T. R.; Robinson, P.

1975-01-01

Principal water resources users were surveyed to determine the applicability of remotely sensed data to their present and future requirements. Analysis of responses was used to assess the levels of adequacy of LANDSAT 1 and 2 in fulfilling hydrological functions, and to derive systems specifications for future water resources-oriented remote sensing satellite systems. The analysis indicates that water resources applications for all but the very large users require: (1) resolutions on the order of 15 meters, (2) a number of radiometric levels of the same order as currently used in LANDSAT 1 (64), (3) a number of spectral bands not in excess of those used in LANDSAT 1, and (4) a repetition frequency on the order of 2 weeks. The users had little feel for the value of new sensors (thermal IR, passive and active microwaves). What is needed in this area is to achieve specific demonstrations of the utility of these sensors and submit the results to the users to evince their judgement.

Method and apparatus for positioning a satellite antenna from a remote well logging location

International Nuclear Information System (INIS)

Toellner, R.L.; Copland, G.V.

1987-01-01

An automatic system for positioning a Ku band microwave antenna accurately to within approximately 0.1 degrees to point at a particular satellite located among others having as close as 2 degree angular spacing in geosynchronous earth orbit from a remote location for establishing a Ku band microwave communication link from the remote location via the satellite is described comprising: a Ku band microwave antenna having a gimbal mount adapted to move in at least azimuth and elevation; means for driving the gimbal mount in azimuth and means for driving the gimbal mount in elevation; means for sensing a satellite signal detected by the antenna and for producing an output signal representative of the strength of the satellite signal and a separate output signal indicative of a satellite code or signature; inclinometer means for measuring the actual elevation angle of the elevation gimbal with respect to vertical and for generating an output signal representative thereof; means for measuring the azimuth angle of the azimuth gimbal relative to a fixed reference and for generating an output signal representative thereof; computer means capable of receiving input data comprising the earth latitude and longitude of a remote location and a satellite position and capable of receiving as inputs the strength representative signal; means for pointing the elevation gimbal to a fixed direction and for scanning the azimuth gimbal to a computed direction based on the earth latitude and longitude and the satellite position signals; and wherein the computer means further includes means capable of receiving the input signal indicative of a satellite code or signature and means for comparing the code or signature input signal with a predetermined reference code or signature signal in the memory of the computer means

Fixed-focus camera objective for small remote sensing satellites

Science.gov (United States)

Topaz, Jeremy M.; Braun, Ofer; Freiman, Dov

1993-09-01

An athermalized objective has been designed for a compact, lightweight push-broom camera which is under development at El-Op Ltd. for use in small remote-sensing satellites. The high performance objective has a fixed focus setting, but maintains focus passively over the full range of temperatures encountered in small satellites. The lens is an F/5.0, 320 mm focal length Tessar type, operating over the range 0.5 - 0.9 micrometers . It has a 16 degree(s) field of view and accommodates various state-of-the-art silicon detector arrays. The design and performance of the objective is described in this paper.

SENSOR++: Simulation of Remote Sensing Systems from Visible to Thermal Infrared

Science.gov (United States)

Paproth, C.; Schlüßler, E.; Scherbaum, P.; Börner, A.

2012-07-01

During the development process of a remote sensing system, the optimization and the verification of the sensor system are important tasks. To support these tasks, the simulation of the sensor and its output is valuable. This enables the developers to test algorithms, estimate errors, and evaluate the capabilities of the whole sensor system before the final remote sensing system is available and produces real data. The presented simulation concept, SENSOR++, consists of three parts. The first part is the geometric simulation which calculates where the sensor looks at by using a ray tracing algorithm. This also determines whether the observed part of the scene is shadowed or not. The second part describes the radiometry and results in the spectral at-sensor radiance from the visible spectrum to the thermal infrared according to the simulated sensor type. In the case of earth remote sensing, it also includes a model of the radiative transfer through the atmosphere. The final part uses the at-sensor radiance to generate digital images by using an optical and an electronic sensor model. Using SENSOR++ for an optimization requires the additional application of task-specific data processing algorithms. The principle of the simulation approach is explained, all relevant concepts of SENSOR++ are discussed, and first examples of its use are given, for example a camera simulation for a moon lander. Finally, the verification of SENSOR++ is demonstrated.

The Department of Energy Nevada Test Site Remote Area Monitoring System

International Nuclear Information System (INIS)

Sanders, L.D.; Hart, O.F.

1993-01-01

The Remote Area Monitoring System was developed by Los Alamos National Laboratory (LANL) for DOE test directors at the Nevada Test Site (NTS) to verify radiological conditions are safe after a nuclear test. In the unlikely event of a venting as a result of a nuclear test, this system provides radiological and meteorological data to Weather Service Nuclear Support Office (WSNSO) computers where mesoscale models are used to predict downwind exposure rates. The system uses a combination of hardwired radiation sensors and satellite based data acquisition units with their own radiation sensors to measure exposure rates in remote areas of the NTS. The satellite based data acquisition units are available as small, Portable Remote Area Monitors (RAMs) for rapid deployment, and larger, Semipermanent RAMs that can have meteorological towers. The satellite based stations measure exposure rates and transmit measurements to the GOES (Geostationary Operational Environmental Satellite) where they are relayed to Direct Readout Ground Stations (DRGS) at the NTS and Los Alamos. Computers process the data and display results in the NTS Operations Coordination Center. Los Alamos computers and NTS computers are linked together through a wide area network, providing remote redundant system capability. Recently, LANL, expanded the system to take radiological and meteorological measurements in communities in the western United States. The system was also expanded to acquire data from Remote Automatic Weather Stations (RAWS) that transmit through GOES. The addition of Portable and Semipermanent RAMs to the system has vastly expanded monitoring capabilities at NTS and can be used to take measurements anywhere in this hemisphere

Comparability of red/near-infrared reflectance and NDVI based on the spectral response function between MODIS and 30 other satellite sensors using rice canopy spectra.

Science.gov (United States)

Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing

2013-11-26

Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The reflectance and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR reflectances and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy reflectances were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra MODIS, the mean relative percentage difference (RPD) ranged from -12.67% to 36.30% for the red reflectance, -8.52% to -0.23% for the NIR reflectance, and -9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra MODIS ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between MODIS and the other 30 satellite sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between MODIS and the other 30 satellite sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed

Satellite microwave remote sensing of North Eurasian inundation dynamics: development of coarse-resolution products and comparison with high-resolution synthetic aperture radar data

International Nuclear Information System (INIS)

Schroeder, R; Rawlins, M A; McDonald, K C; Podest, E; Zimmermann, R; Kueppers, M

2010-01-01

Wetlands are not only primary producers of atmospheric greenhouse gases but also possess unique features that are favourable for application of satellite microwave remote sensing to monitoring their status and trend. In this study we apply combined passive and active microwave remote sensing data sets from the NASA sensors AMSR-E and QuikSCAT to map surface water dynamics over Northern Eurasia. We demonstrate our method on the evolution of large wetland complexes for two consecutive years from January 2006 to December 2007. We apply river discharge measurements from the Ob River along with land surface runoff simulations derived from the Pan-Arctic Water Balance Model during and after snowmelt in 2006 and 2007 to interpret the abundance of widespread flooding along the River Ob in early summer of 2007 observed in the remote sensing products. The coarse-resolution, 25 km, surface water product is compared to a high-resolution, 30 m, inundation map derived from ALOS PALSAR (Advanced Land Observation Satellite phased array L-band synthetic aperture radar) imagery acquired for 11 July 2006, and extending along a transect in the central Western Siberian Plain. We found that the surface water fraction derived from the combined AMSR-E/QuikSCAT data sets closely tracks the inundation mapped using higher-resolution ALOS PALSAR data.

Preliminary data for the 20 May 1974, simultaneous evaluation of remote sensors experiment. [water pollution monitoring

Science.gov (United States)

Johnson, R. W.; Batten, C. E.; Bowker, D. E.; Bressette, W. E.; Grew, G. W.

1975-01-01

Several remote sensors were simultaneously used to collect data over the tidal James River from Hopewell to Norfolk, Virginia. Sensors evaluated included the Multichannel-Ocean Color Sensor, multispectral scanners, and multispectral photography. Ground truth measurements and remotely sensed data are given. Preliminary analysis indicates that suspended sediment and concentrated industrial effluent are observable from all sensors.

Dynamic sensor tasking and IMM EKF estimation for tracking impulsively maneuvering satellites

Science.gov (United States)

Lace, Arthur A.

In order to efficiently maintain space situational awareness, care must be taken to optimally allocate expensive observation resources. In most situations the available sensors capable of tracking spacecraft have their time split between many different monitoring responsibilities. Tracking maneuvering spacecraft can be especially difficult as the schedule of maneuvers may not be known and will often throw off previous orbital models. Effectively solving this tasking problem is an ongoing focus of research in the area of space situational awareness. Most methods of automated tasking do not make use of interacting multiple model extended Kalman filter techniques to better track satellites during maneuvers. This paper proposes a modification to a Fisher information gain and estimated state covariance based sensor tasking method to take maneuver probability and multiple model dynamics into account. By incorporating the probabilistic maneuvering model, sensor tasking can be improved during satellite maneuvers using constrained resources. The proposed methods are verified through the use of numerical simulations with multiple maneuvering satellites and both orbital and ground-based sensors.

An Autonomous Satellite Time Synchronization System Using Remotely Disciplined VC-OCXOs

Directory of Open Access Journals (Sweden)

Xiaobo Gu

2015-07-01

Full Text Available An autonomous remote clock control system is proposed to provide time synchronization and frequency syntonization for satellite to satellite or ground to satellite time transfer, with the system comprising on-board voltage controlled oven controlled crystal oscillators (VC-OCXOs that are disciplined to a remote master atomic clock or oscillator. The synchronization loop aims to provide autonomous operation over extended periods, be widely applicable to a variety of scenarios and robust. A new architecture comprising the use of frequency division duplex (FDD, synchronous time division (STDD duplex and code division multiple access (CDMA with a centralized topology is employed. This new design utilizes dual one-way ranging methods to precisely measure the clock error, adopts least square (LS methods to predict the clock error and employs a third-order phase lock loop (PLL to generate the voltage control signal. A general functional model for this system is proposed and the error sources and delays that affect the time synchronization are discussed. Related algorithms for estimating and correcting these errors are also proposed. The performance of the proposed system is simulated and guidance for selecting the clock is provided.

Integrated fiber optic sensors for hot spot detection and temperature field reconstruction in satellites

International Nuclear Information System (INIS)

Rapp, S; Baier, H

2010-01-01

Large satellites are often equipped with more than 1000 temperature sensors during the test campaign. Hundreds of them are still used for monitoring during launch and operation in space. This means an additional mass and especially high effort in assembly, integration and verification on a system level. So the use of fiber Bragg grating temperature sensors is investigated as they offer several advantages. They are lightweight, small in size and electromagnetically immune, which fits well in space applications. Their multiplexing capability offers the possibility to build extensive sensor networks including dozens of sensors of different types, such as strain sensors, accelerometers and temperature sensors. The latter allow the detection of hot spots and the reconstruction of temperature fields via proper algorithms, which is shown in this paper. A temperature sensor transducer was developed, which can be integrated into satellite sandwich panels with negligible mechanical influence. Mechanical and thermal vacuum tests were performed to verify the space compatibility of the developed sensor system. Proper reconstruction algorithms were developed to estimate the temperature field and detect thermal hot spots on the panel surface. A representative hardware demonstrator has been built and tested, which shows the capability of using an integrated fiber Bragg grating temperature sensor network for temperature field reconstruction and hot spot detection in satellite structures

Advanced and applied remote sensing of environmental conditions

Science.gov (United States)

Slonecker, E. Terrence; Fisher, Gary B.; Marr, David A.; Milheim, Lesley E.; Roig-Silva, Coral M.

2013-01-01

"Remote sensing” is a general term for monitoring techniques that collect information without being in physical contact with the object of study. Overhead imagery from aircraft and satellite sensors provides the most common form of remotely sensed data and records the interaction of electromagnetic energy (usually visible light) with matter, such as the Earth’s surface. Remotely sensed data are fundamental to geographic science. The U.S. Geological Survey’s (USGS) Eastern Geographic Science Center (EGSC) is currently conducting and promoting the research and development of several different aspects of remote sensing science in both the laboratory and from overhead instruments. Spectroscopy is the science of recording interactions of energy and matter and is the bench science for all remote sensing. Visible and infrared analysis in the laboratory with special instruments called spectrometers enables the transfer of this research from the laboratory to multispectral (5–15 broad bands) and hyperspectral (50–300 narrow contiguous bands) analyses from aircraft and satellite sensors. In addition, mid-wave (3–5 micrometers, µm) and long-wave (8–14 µm) infrared data analysis, such as attenuated total reflectance (ATR) spectral analysis, are also conducted. ATR is a special form of vibrational infrared spectroscopy that has many applications in chemistry and biology but has recently been shown to be especially diagnostic for vegetation analysis.

GEO Satellites as Space Weather Sensors

Science.gov (United States)

2016-04-26

AFRL-AFOSR-VA-TR-2016-0161 GEO Satellites as Space Weather Sensors Kerri Cahoy MASSACHUSETTS INSTITUTE OF TECHNOLOGY 77 MASSACHUSETTS AVE CAMBRIDGE ... Cambridge , MA 02139 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) AF Office of Scientific...Lohmeyer  and  Cahoy,  2013;   Lohmeyer,  et  al.,  2015].  From  the   statistical  analysis,  we  identified  that

Leds used as spectral selective light detectors in remote sensing techniques

International Nuclear Information System (INIS)

Weber, C; Tocho, J O; Rodriguez, E J; Acciaresi, H A

2011-01-01

Remote sensing has been commonly considered as an effective technique in developing precision agriculture tools. Ground based and satellite spectral sensors have wide uses to retrieve remotely quantitative biophysical and biochemical characteristics of vegetation canopies as well as vegetation ground cover. Usually in-field remote sensing technologies use either a combination of interferential filters and photodiodes or different compact spectrometers to separate the spectral regions of interest. In this paper we present a new development of a sensor with LEDs used as spectrally selective photodetectors. Its performance was compared with a photodiode-filter sensor used in agronomic applications. Subsequent measurements of weed cover degree were performed and compared with other methodologies. Results show that the new LEDs based sensor has similar features that conventional ones to determining the weed soil cover degree; while LEDs based sensor has comparative advantages related its very low manufacturing cost and its robustness compatible with agricultural field applications.

Linear wide angle sun sensor for spinning satellites

Science.gov (United States)

Philip, M. P.; Kalakrishnan, B.; Jain, Y. K.

1983-08-01

A concept is developed which overcomes the defects of the nonlinearity of response and limitation in range exhibited by the V-slit, N-slit, and crossed slit sun sensors normally used for sun elevation angle measurements on spinning spacecraft. Two versions of sensors based on this concept which give a linear output and have a range of nearly + or - 90 deg of elevation angle are examined. Results are presented for the application of the twin slit version of the sun sensor in the three Indian satellites, Rohini, Apple, and Bhaskara II, which was successfully used for spin rate control and spin axis orientation control corrections as well as for sun elevation angle and spin period measurements.

Quantifying Freshwater Mass Balance in the Central Tibetan Plateau by Integrating Satellite Remote Sensing, Altimetry, and Gravimetry

Directory of Open Access Journals (Sweden)

Kuo-Hsin Tseng

2016-05-01

Full Text Available The Tibetan Plateau (TP has been observed by satellite optical remote sensing, altimetry, and gravimetry for a variety of geophysical parameters, including water storage change. However, each of these sensors has its respective limitation in the parameters observed, accuracy and spatial-temporal resolution. Here, we utilized an integrated approach to combine remote sensing imagery, digital elevation model, and satellite radar and laser altimetry data, to quantify freshwater storage change in a twin lake system named Chibuzhang Co and Dorsoidong Co in the central TP, and compared that with independent observations including mass changes from the Gravity Recovery and Climate Experiment (GRACE data. Our results show that this twin lake, located within the Tanggula glacier system, remained almost steady during 1973–2000. However, Dorsoidong Co has experienced a significant lake level rise since 2000, especially during 2000–2005, that resulted in the plausible connection between the two lakes. The contemporary increasing lake level signal at a rate of 0.89 ± 0.05 cm·yr−1, in a 2° by 2° grid equivalent water height since 2002, is higher than the GRACE observed trend at 0.41 ± 0.17 cm·yr−1 during the same time span. Finally, a down-turning trend or inter-annual variability shown in the GRACE signal is observed after 2012, while the lake level is still rising at a consistent rate.

Possibility of continuous monitoring of environment around the nuclear plant using satellite remote sensing

International Nuclear Information System (INIS)

Sasaki, Takanori; Tanabu, Yoshimine; Fujita, Shigetaka; Zhao Wenhui

2008-01-01

Interest in nuclear power generation is increasing by rising of power demand and environmental concern. It is important more and more to confirm and show the safety operation of nuclear plants, which is useful to remove anxiety of residents. Satellite remote sensing is one of the way of it. Large observation width and long and continuous observation period are advantage of satellite remote sensing. In addition, it is very important to be able to monitor without visitation on the site. We have continued local area environmental analysis using various satellites. MODIS on Terra and Aqua which are NASA satellites received by Hachinohe Institute of Technology is mainly used. According to these results, we have shown that combined analysis of various information parameters such as land surface temperature, geographical changes, vegetation, etc. is very effective to monitor environmental changes. In these analyses, error detection is very important. Therefore, enough storage data with continuously monitoring in usual state is necessary. Moreover, it is thought that the confirmation of stable operation of plants by means of continuous monitoring can contribute to reduce residents' anxiety of nuclear power plant. Additionally, in the case that the change of influence on surroundings is detected, it is possible to grasp the situation and take measure in early stage by error detection. In this paper, as an possible example of continuous monitoring using satellite remote sensing, we introduce the result of analysis and investigation of which changes of sea surface temperature and chlorophyll concentration on the sea around power plant. (author)

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.

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).

THERMAL AND VISIBLE SATELLITE IMAGE FUSION USING WAVELET IN REMOTE SENSING AND SATELLITE IMAGE PROCESSING

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A. H. Ahrari

2017-09-01

Full Text Available Multimodal remote sensing approach is based on merging different data in different portions of electromagnetic radiation that improves the accuracy in satellite image processing and interpretations. Remote Sensing Visible and thermal infrared bands independently contain valuable spatial and spectral information. Visible bands make enough information spatially and thermal makes more different radiometric and spectral information than visible. However low spatial resolution is the most important limitation in thermal infrared bands. Using satellite image fusion, it is possible to merge them as a single thermal image that contains high spectral and spatial information at the same time. The aim of this study is a performance assessment of thermal and visible image fusion quantitatively and qualitatively with wavelet transform and different filters. In this research, wavelet algorithm (Haar and different decomposition filters (mean.linear,ma,min and rand for thermal and panchromatic bands of Landast8 Satellite were applied as shortwave and longwave fusion method . Finally, quality assessment has been done with quantitative and qualitative approaches. Quantitative parameters such as Entropy, Standard Deviation, Cross Correlation, Q Factor and Mutual Information were used. For thermal and visible image fusion accuracy assessment, all parameters (quantitative and qualitative must be analysed with respect to each other. Among all relevant statistical factors, correlation has the most meaningful result and similarity to the qualitative assessment. Results showed that mean and linear filters make better fused images against the other filters in Haar algorithm. Linear and mean filters have same performance and there is not any difference between their qualitative and quantitative results.

Development of a computationally efficient algorithm for attitude estimation of a remote sensing satellite

Science.gov (United States)

Labibian, Amir; Bahrami, Amir Hossein; Haghshenas, Javad

2017-09-01

This paper presents a computationally efficient algorithm for attitude estimation of remote a sensing satellite. In this study, gyro, magnetometer, sun sensor and star tracker are used in Extended Kalman Filter (EKF) structure for the purpose of Attitude Determination (AD). However, utilizing all of the measurement data simultaneously in EKF structure increases computational burden. Specifically, assuming n observation vectors, an inverse of a 3n×3n matrix is required for gain calculation. In order to solve this problem, an efficient version of EKF, namely Murrell's version, is employed. This method utilizes measurements separately at each sampling time for gain computation. Therefore, an inverse of a 3n×3n matrix is replaced by an inverse of a 3×3 matrix for each measurement vector. Moreover, gyro drifts during the time can reduce the pointing accuracy. Therefore, a calibration algorithm is utilized for estimation of the main gyro parameters.

Wearable Sensors for Remote Health Monitoring.

Science.gov (United States)

Majumder, Sumit; Mondal, Tapas; Deen, M Jamal

2017-01-12

Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a large aging demographic in the near future that would impose significant  burdens on the socio-economic structure of these countries. Therefore, it is essential to develop cost-effective, easy-to-use systems for the sake of elderly healthcare and well-being. Remote health monitoring, based on non-invasive and wearable sensors, actuators and modern communication and information technologies offers an efficient and cost-effective solution that allows the elderly to continue to live in their comfortable home environment instead of expensive healthcare facilities. These systems will also allow healthcare personnel to monitor important physiological signs of their patients in real time, assess health conditions and provide feedback from distant facilities. In this paper, we have presented and compared several low-cost and non-invasive health and activity monitoring systems that were reported in recent years. A survey on textile-based sensors that can potentially be used in wearable systems is also presented. Finally, compatibility of several communication technologies as well as future perspectives and research challenges in remote monitoring systems will be discussed.

Wearable Sensors for Remote Health Monitoring

Directory of Open Access Journals (Sweden)

Sumit Majumder

2017-01-01

Full Text Available Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a large aging demographic in the near future that would impose significant  burdens on the socio-economic structure of these countries. Therefore, it is essential to develop cost-effective, easy-to-use systems for the sake of elderly healthcare and well-being. Remote health monitoring, based on non-invasive and wearable sensors, actuators and modern communication and information technologies offers an efficient and cost-effective solution that allows the elderly to continue to live in their comfortable home environment instead of expensive healthcare facilities. These systems will also allow healthcare personnel to monitor important physiological signs of their patients in real time, assess health conditions and provide feedback from distant facilities. In this paper, we have presented and compared several low-cost and non-invasive health and activity monitoring systems that were reported in recent years. A survey on textile-based sensors that can potentially be used in wearable systems is also presented. Finally, compatibility of several communication technologies as well as future perspectives and research challenges in remote monitoring systems will be discussed.

SENSOR CORRECTION AND RADIOMETRIC CALIBRATION OF A 6-BAND MULTISPECTRAL IMAGING SENSOR FOR UAV REMOTE SENSING

Directory of Open Access Journals (Sweden)

J. Kelcey

2012-07-01

Full Text Available The increased availability of unmanned aerial vehicles (UAVs has resulted in their frequent adoption for a growing range of remote sensing tasks which include precision agriculture, vegetation surveying and fine-scale topographic mapping. The development and utilisation of UAV platforms requires broad technical skills covering the three major facets of remote sensing: data acquisition, data post-processing, and image analysis. In this study, UAV image data acquired by a miniature 6-band multispectral imaging sensor was corrected and calibrated using practical image-based data post-processing techniques. Data correction techniques included dark offset subtraction to reduce sensor noise, flat-field derived per-pixel look-up-tables to correct vignetting, and implementation of the Brown- Conrady model to correct lens distortion. Radiometric calibration was conducted with an image-based empirical line model using pseudo-invariant features (PIFs. Sensor corrections and radiometric calibration improve the quality of the data, aiding quantitative analysis and generating consistency with other calibrated datasets.

High efficient optical remote sensing images acquisition for nano-satellite: reconstruction algorithms

Science.gov (United States)

Liu, Yang; Li, Feng; Xin, Lei; Fu, Jie; Huang, Puming

2017-10-01

Large amount of data is one of the most obvious features in satellite based remote sensing systems, which is also a burden for data processing and transmission. The theory of compressive sensing(CS) has been proposed for almost a decade, and massive experiments show that CS has favorable performance in data compression and recovery, so we apply CS theory to remote sensing images acquisition. In CS, the construction of classical sensing matrix for all sparse signals has to satisfy the Restricted Isometry Property (RIP) strictly, which limits applying CS in practical in image compression. While for remote sensing images, we know some inherent characteristics such as non-negative, smoothness and etc.. Therefore, the goal of this paper is to present a novel measurement matrix that breaks RIP. The new sensing matrix consists of two parts: the standard Nyquist sampling matrix for thumbnails and the conventional CS sampling matrix. Since most of sun-synchronous based satellites fly around the earth 90 minutes and the revisit cycle is also short, lots of previously captured remote sensing images of the same place are available in advance. This drives us to reconstruct remote sensing images through a deep learning approach with those measurements from the new framework. Therefore, we propose a novel deep convolutional neural network (CNN) architecture which takes in undersampsing measurements as input and outputs an intermediate reconstruction image. It is well known that the training procedure to the network costs long time, luckily, the training step can be done only once, which makes the approach attractive for a host of sparse recovery problems.

Normalization of time-series satellite reflectance data to a standard sun-target-sensor geometry using a semi-empirical model

Science.gov (United States)

Zhao, Yongguang; Li, Chuanrong; Ma, Lingling; Tang, Lingli; Wang, Ning; Zhou, Chuncheng; Qian, Yonggang

2017-10-01

Time series of satellite reflectance data have been widely used to characterize environmental phenomena, describe trends in vegetation dynamics and study climate change. However, several sensors with wide spatial coverage and high observation frequency are usually designed to have large field of view (FOV), which cause variations in the sun-targetsensor geometry in time-series reflectance data. In this study, on the basis of semiempirical kernel-driven BRDF model, a new semi-empirical model was proposed to normalize the sun-target-sensor geometry of remote sensing image. To evaluate the proposed model, bidirectional reflectance under different canopy growth conditions simulated by Discrete Anisotropic Radiative Transfer (DART) model were used. The semi-empirical model was first fitted by using all simulated bidirectional reflectance. Experimental result showed a good fit between the bidirectional reflectance estimated by the proposed model and the simulated value. Then, MODIS time-series reflectance data was normalized to a common sun-target-sensor geometry by the proposed model. The experimental results showed the proposed model yielded good fits between the observed and estimated values. The noise-like fluctuations in time-series reflectance data was also reduced after the sun-target-sensor normalization process.

A wireless acoustic emission sensor remotely powered by light

International Nuclear Information System (INIS)

Zahedi, F; Huang, H

2014-01-01

In this paper, wireless sensing of acoustic emission (AE) signals using a battery-free sensor node remotely powered by light is presented. The wireless sensor consists of a piezoelectric wafer active sensor (PWAS) for AE signal acquisition and a wireless transponder that performs signal conditioning, frequency conversion, and wireless transmission. For signal conditioning, a voltage follower that consumes less than 2 mW was introduced to buffer the high impedance of the PWAS from the low impedance of the wireless transponder. A photocell-based energy harvester with a stable voltage output was developed to power the voltage follower so that the wireless AE sensor can operate without an external power source. The principle of operation of the battery-free wireless AE sensor node and the sensor interrogation system is described, followed by a detailed description of the hardware implementation. The voltage follower and the wireless channel were characterized by ultrasound pitch–catch and pencil lead break experiments. (paper)

A design of an on-orbit radiometric calibration device for high dynamic range infrared remote sensors

Science.gov (United States)

Sheng, Yicheng; Jin, Weiqi; Dun, Xiong; Zhou, Feng; Xiao, Si

2017-10-01

With the demand of quantitative remote sensing technology growing, high reliability as well as high accuracy radiometric calibration technology, especially the on-orbit radiometric calibration device has become an essential orientation in term of quantitative remote sensing technology. In recent years, global launches of remote sensing satellites are equipped with innovative on-orbit radiometric calibration devices. In order to meet the requirements of covering a very wide dynamic range and no-shielding radiometric calibration system, we designed a projection-type radiometric calibration device for high dynamic range sensors based on the Schmidt telescope system. In this internal radiometric calibration device, we select the EF-8530 light source as the calibration blackbody. EF-8530 is a high emittance Nichrome (Ni-Cr) reference source. It can operate in steady or pulsed state mode at a peak temperature of 973K. The irradiance from the source was projected to the IRFPA. The irradiance needs to ensure that the IRFPA can obtain different amplitude of the uniform irradiance through the narrow IR passbands and cover the very wide dynamic range. Combining the internal on-orbit radiometric calibration device with the specially designed adaptive radiometric calibration algorithms, an on-orbit dynamic non-uniformity correction can be accomplished without blocking the optical beam from outside the telescope. The design optimizes optics, source design, and power supply electronics for irradiance accuracy and uniformity. The internal on-orbit radiometric calibration device not only satisfies a series of indexes such as stability, accuracy, large dynamic range and uniformity of irradiance, but also has the advantages of short heating and cooling time, small volume, lightweight, low power consumption and many other features. It can realize the fast and efficient relative radiometric calibration without shielding the field of view. The device can applied to the design and

REMOTE, a Wireless Sensor Network Based System to Monitor Rowing Performance

Science.gov (United States)

Llosa, Jordi; Vilajosana, Ignasi; Vilajosana, Xavier; Navarro, Nacho; Suriñach, Emma; Marquès, Joan Manuel

2009-01-01

In this paper, we take a hard look at the performance of REMOTE, a sensor network based application that provides a detailed picture of a boat movement, individual rower performance, or his/her performance compared with other crew members. The application analyzes data gathered with a WSN strategically deployed over a boat to obtain information on the boat and oar movements. Functionalities of REMOTE are compared to those of RowX [1] outdoor instrument, a commercial wired sensor instrument designed for similar purposes. This study demonstrates that with smart geometrical configuration of the sensors, rotation and translation of the oars and boat can be obtained. Three different tests are performed: laboratory calibration allows us to become familiar with the accelerometer readings and validate the theory, ergometer tests which help us to set the acquisition parameters, and on boat tests shows the application potential of this technologies in sports. PMID:22423204

REMOTE, a Wireless Sensor Network Based System to Monitor Rowing Performance

Directory of Open Access Journals (Sweden)

Jordi Llosa

2009-09-01

Full Text Available In this paper, we take a hard look at the performance of REMOTE, a sensor network based application that provides a detailed picture of a boat movement, individual rower performance, or his/her performance compared with other crew members. The application analyzes data gathered with a WSN strategically deployed over a boat to obtain information on the boat and oar movements. Functionalities of REMOTE are compared to those of RowX [1] outdoor instrument, a commercial wired sensor instrument designed for similar purposes. This study demonstrates that with smart geometrical configuration of the sensors, rotation and translation of the oars and boat can be obtained. Three different tests are performed: laboratory calibration allows us to become familiar with the accelerometer readings and validate the theory, ergometer tests which help us to set the acquisition parameters, and on boat tests shows the application potential of this technologies in sports.

Detection, emission estimation and risk prediction of forest fires in China using satellite sensors and simulation models in the past three decades--an overview.

Science.gov (United States)

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K

2011-08-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status.

Use of Satellite Remote Sensing Data in the Mapping of Global Landslide Susceptibility

Science.gov (United States)

Hong, Yang; Adler, Robert F.; Huffman, George J.

2007-01-01

Satellite remote sensing data has significant potential use in analysis of natural hazards such as landslides. Relying on the recent advances in satellite remote sensing and geographic information system (GIS) techniques, this paper aims to map landslide susceptibility over most of the globe using a GIs-based weighted linear combination method. First , six relevant landslide-controlling factors are derived from geospatial remote sensing data and coded into a GIS system. Next, continuous susceptibility values from low to high are assigned to each of the six factors. Second, a continuous scale of a global landslide susceptibility index is derived using GIS weighted linear combination based on each factor's relative significance to the process of landslide occurrence (e.g., slope is the most important factor, soil types and soil texture are also primary-level parameters, while elevation, land cover types, and drainage density are secondary in importance). Finally, the continuous index map is further classified into six susceptibility categories. Results show the hot spots of landslide-prone regions include the Pacific Rim, the Himalayas and South Asia, Rocky Mountains, Appalachian Mountains, Alps, and parts of the Middle East and Africa. India, China, Nepal, Japan, the USA, and Peru are shown to have landslide-prone areas. This first-cut global landslide susceptibility map forms a starting point to provide a global view of landslide risks and may be used in conjunction with satellite-based precipitation information to potentially detect areas with significant landslide potential due to heavy rainfall. 1

New optical sensor systems for high-resolution satellite, airborne and terrestrial imaging systems

Science.gov (United States)

Eckardt, Andreas; Börner, Anko; Lehmann, Frank

2007-10-01

The department of Optical Information Systems (OS) at the Institute of Robotics and Mechatronics of the German Aerospace Center (DLR) has more than 25 years experience with high-resolution imaging technology. The technology changes in the development of detectors, as well as the significant change of the manufacturing accuracy in combination with the engineering research define the next generation of spaceborne sensor systems focusing on Earth observation and remote sensing. The combination of large TDI lines, intelligent synchronization control, fast-readable sensors and new focal-plane concepts open the door to new remote-sensing instruments. This class of instruments is feasible for high-resolution sensor systems regarding geometry and radiometry and their data products like 3D virtual reality. Systemic approaches are essential for such designs of complex sensor systems for dedicated tasks. The system theory of the instrument inside a simulated environment is the beginning of the optimization process for the optical, mechanical and electrical designs. Single modules and the entire system have to be calibrated and verified. Suitable procedures must be defined on component, module and system level for the assembly test and verification process. This kind of development strategy allows the hardware-in-the-loop design. The paper gives an overview about the current activities at DLR in the field of innovative sensor systems for photogrammetric and remote sensing purposes.

The Design and Implementation of a Remote Fault Reasoning Diagnosis System for Meteorological Satellites Data Acquisition

Directory of Open Access Journals (Sweden)

Zhu Jie

2017-01-01

Full Text Available Under the background of the trouble shooting requirements of FENGYUN-3 (FY-3 meteorological satellites data acquisition in domestic and oversea ground stations, a remote fault reasoning diagnosis system is developed by Java 1.6 in eclipse 3.6 platform. The general framework is analyzed, the workflow is introduced. Based on the system, it can realize the remote and centralized monitoring of equipment running status in ground stations，triggering automatic fault diagnosis and rule based fault reasoning by parsing the equipment quality logs, generating trouble tickets and importing expert experience database, providing text and graphics query methods. Through the practical verification, the system can assist knowledge engineers in remote precise and rapid fault location with friendly graphical user interface, boost the fault diagnosis efficiency, enhance the remote monitoring ability of integrity operating control system. The system has a certain practical significance to improve reliability of FY-3 meteorological satellites data acquisition.

BIOME: An Ecosystem Remote Sensor Based on Imaging Interferometry

Science.gov (United States)

Peterson, David L.; Hammer, Philip; Smith, William H.; Lawless, James G. (Technical Monitor)

1994-01-01

Until recent times, optical remote sensing of ecosystem properties from space has been limited to broad band multispectral scanners such as Landsat and AVHRR. While these sensor data can be used to derive important information about ecosystem parameters, they are very limited for measuring key biogeochemical cycling parameters such as the chemical content of plant canopies. Such parameters, for example the lignin and nitrogen contents, are potentially amenable to measurements by very high spectral resolution instruments using a spectroscopic approach. Airborne sensors based on grating imaging spectrometers gave the first promise of such potential but the recent decision not to deploy the space version has left the community without many alternatives. In the past few years, advancements in high performance deep well digital sensor arrays coupled with a patented design for a two-beam interferometer has produced an entirely new design for acquiring imaging spectroscopic data at the signal to noise levels necessary for quantitatively estimating chemical composition (1000:1 at 2 microns). This design has been assembled as a laboratory instrument and the principles demonstrated for acquiring remote scenes. An airborne instrument is in production and spaceborne sensors being proposed. The instrument is extremely promising because of its low cost, lower power requirements, very low weight, simplicity (no moving parts), and high performance. For these reasons, we have called it the first instrument optimized for ecosystem studies as part of a Biological Imaging and Observation Mission to Earth (BIOME).

Il telerilevamento per la qualità dell'aria L'esperienza SENSORER

Directory of Open Access Journals (Sweden)

Marco Folegani

2012-04-01

Full Text Available Il monitoraggio della qualità dell'aria con tecniche di telerilevamento è noto da tempo negli ambienti scientifici ma considerato ancora con prudenza e perplessità dalle strutture istituzionali sia per il livello "accademico" delle applicazioni sia per la mancanza di una forte motivazione normativa nell'adottare nuovi metodi di monitoraggio. L'esperienza SENSORER ha l'ambizione di mostrare come si possono superare entrambe queste barriere. The remote sensing for air quality monitoring The SENSORER project.The satellite observations have proven their capabilities for re-mote sensing of atmospheric pollutants such as the Particulate Matter. But the advantage of global coverage, homogeneous quality and a relative good spatial resolution are counterbalanced by the limited temporal resolution and the cloud cover-age. The SENSORER project is just the last example of a web platform that thanks to a combination of satellite data with information from ground based sensors and models overcomes the limitations of each single observation method to provide better pollution maps to make better decisions.

Validation of Remote Sensing Retrieval Products using Data from a Wireless Sensor-Based Online Monitoring in Antarctica

Science.gov (United States)

Li, Xiuhong; Cheng, Xiao; Yang, Rongjin; Liu, Qiang; Qiu, Yubao; Zhang, Jialin; Cai, Erli; Zhao, Long

2016-01-01

Of the modern technologies in polar-region monitoring, the remote sensing technology that can instantaneously form large-scale images has become much more important in helping acquire parameters such as the freezing and melting of ice as well as the surface temperature, which can be used in the research of global climate change, Antarctic ice sheet responses, and cap formation and evolution. However, the acquirement of those parameters is impacted remarkably by the climate and satellite transit time which makes it almost impossible to have timely and continuous observation data. In this research, a wireless sensor-based online monitoring platform (WSOOP) for the extreme polar environment is applied to obtain a long-term series of data which is site-specific and continuous in time. Those data are compared and validated with the data from a weather station at Zhongshan Station Antarctica and the result shows an obvious correlation. Then those data are used to validate the remote sensing products of the freezing and melting of ice and the surface temperature and the result also indicated a similar correlation. The experiment in Antarctica has proven that WSOOP is an effective system to validate remotely sensed data in the polar region. PMID:27869668

Wireless Networked Sensors for Remote Monitoring in Propulsion Systems, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — This NASA Phase I SBIR program would fabricate wireless networked nanomembrane (NM) based surface pressure sensors for remote monitoring in propulsion systems, using...

1999 IEEE international geoscience and remote sensing symposium

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-07-01

The theme of IGARSS'99, ``Remote Sensing of the System Earth--A Challenge for the 21st Century,'' shows how earth observation based on satellite remote sensing can significantly contribute to the future study of the environment and the changes it is undergoing, whether from natural causes or human activities. The wide range of topics offers an interdisciplinary approach and suggests integrated techniques and theory in remote sensing are essential for modeling and understanding the environment. Topics covered include: new instrumentation and future systems; high resolution SAR/InSAR; earth system science educational initiative; data fusion; radar sensing of ice sheets; image processing techniques; clouds and ice particles; internal waves; natural hazards and disaster monitoring; advanced passive and active sensors and sensor calibration; radar assessment of rain, oil spills and natural slicks; data standards and distribution; and vegetation monitoring using BRDF approaches.

Evaluating Terra MODIS Satellite Sensor Data Products for Maize ...

African Journals Online (AJOL)

Evaluating Terra MODIS Satellite Sensor Data Products for Maize Yield Estimation in South Africa. C Frost, N Thiebaut, T Newby. Abstract. The Free State Province of the Republic of South Africa contains some of the most important maize-producing areas in South Africa. For this reason this province has also been selected ...

Satellite Imagery and In-situ Data Overlay Approach for Fishery Zonation

Directory of Open Access Journals (Sweden)

Fardhi Adria

2010-12-01

Full Text Available Remote sensing technology can be used to better understand the earth’s characteristics. SeaWiFS (sea-viewing wide field-of-view sensor is one of remote sensors used to observe global ocean phenomena. Previous studies showed that the distribution of chlorophyll-a in the ocean indicates the presence of fish. However, only a few studies tried to directly relate the chlorophyll-a distribution obtained through interpretation of satellite imagery to in-situ data of fish distribution. This paper investigates the relation between chlorophyll-a distribution and fish-capturing points in Aceh Province sea waters using overlay image analysis. The results are then used to identify the potential fishing ground in Aceh. The profile of chlorophyll-a concentration is derived from SeaWIFS satellite imagery. Fish-capturing points data is obtained from the fisherman communities of Banda Aceh, starting from June to November 2008. The results showed that the chlorophyll-a profile derived from satellite imagery has a positive relationship to fish-capturing point data. The most potential fish-capturing zone in Aceh sea waters is identified at 5-8º north latitude (N and 96-99º east longitude (E.

Robust satellite techniques for remote sensing of seismically active areas

Energy Technology Data Exchange (ETDEWEB)

Tramutoli, V; Di Bello, G [Potenza Univ., Potenza (Italy). Dipt. di Ingegneria e Fisica dell' Ambiente; Pergola, N; Piscitelli, S [Consiglio Nazionale delle Ricerche, Istituto di Metodologie Avanzate di Analisi Ambientale, Potenza (Italy)

2001-04-01

Several satellite techniques have been recently proposed to remotely map seismically active zones and to monitor geophysical phenomena possibly associated with earthquakes. Even if questionable in terms of their effective applicability, all these techniques highlight as the major problem, still to be overcome, the high number of natural factors (independent of any seismic activity) whose variable contributions to the investigated signal can be so high as to completely mask (or simulate) the space-time anomaly possibly associated to the seismic event under study. A robust approach (RAT) has recently been proposed (and successfully applied in the field of the monitoring of the major environmental risks) which, better than other methods, seems suitable for recognising space-time anomalies in the satellite observation field also in the presence of highly variable contributions from atmospheric (transmittance), surface (emissivity and morphology) and observational (time/season, but also solar and satellite zenithal angles) conditions. This work presents the first preliminary results, based on several years of NOA A/AVHRR observations, regarding its extension to satellite monitoring of thermal anomalies possibly associated to seismically active areas of Southern Italy. The main merits of this approach are its robustness against the possibility of false events detection (specially important for this kind of applications) as well as its intrinsic exportability not only to different geographic areas but also to different satellite instrumental packages.

Robust satellite techniques for remote sensing of seismically active areas

Directory of Open Access Journals (Sweden)

S. Piscitelli

2001-06-01

Full Text Available Several satellite techniques have been recently proposed to remotely map seismically active zones and to monitor geophysical phenomena possibly associated with earthquakes. Even if questionable in terms of their effective applicability, all these techniques highlight as the major problem, still to be overcome, the high number of natural factors (independent of any seismic activity whose variable contributions to the investigated signal can be so high as to completely mask (or simulate the space-time anomaly possibly associated to the seismic event under study. A robust approach (RAT has recently been proposed (and successfully applied in the field of the monitoring of the major environmental risks which, better than other methods, seems suitable for recognising space-time anomalies in the satellite observational field also in the presence of highly variable contributions from atmospheric (transmittance, surface (emissivity and morphology and observational (time/season, but also solar and satellite zenithal angles conditions.This work presents the first preliminary results, based on several years of NOAA/AVHRR observations, regarding its extension to satellite monitoring of thermal anomalies possibly associated to seismically active areas of Southern Italy. The main merits of this approach are its robustness against the possibility of false events detection (specially important for this kind of applications as well as its intrinsic exportability not only to different geographic areas but also to different satellite instrumental packages.

A remote characterization system for subsurface mapping of buried waste sites

International Nuclear Information System (INIS)

Sandness, G.A.; Bennett, D.W.

1992-10-01

Mapping of buried objects and regions of chemical and radiological contamination is required at US Department of Energy (DOE) buried waste sites. The DOE Office of Technology Development Robotics Integrated Program has initiated a project to develop and demonstrate a remotely controlled subsurface sensing system, called the Remote Characterization System (RCS). This project, a collaborative effort by five of the National Laboratories, involves the development of a unique low-signature survey vehicle, a base station, radio telemetry data links, satellite-based vehicle tracking, stereo vision, and sensors for non-invasive inspection of the surface and subsurface. To minimize interference with on-board sensors, the survey vehicle has been constructed predominatantly of non-metallic materials. The vehicle is self-propelled and will be guided by an operator located at a remote base station. The RCS sensors will be environmentally sealed and internally cooled to preclude contamination during use. Ground-penetrating radar, magnetometers, and conductivity devices are planned for geophysical surveys. Chemical and radiological sensors will be provided to locate hot spots and to provide isotopic concentration data

A review of hyperspectral remote sensing and its application in ...

African Journals Online (AJOL)

Multispectral imagery has been used as the data source for water and land observational remote sensing from airborne and satellite systems since the early 1960s. Over the past two decades, advances in sensor technology have made it possible for the collection of several hundred spectral bands. This is commonly ...

Feasibility Study on Fiber-optic Radiation Sensor for Remote Gamma-ray Spectroscopy

International Nuclear Information System (INIS)

Jeon, Hyesu; Jang, Kyoung Won; Shin, Sang Hun and others

2014-01-01

In this study, we fabricated a fiber-optic radiation sensor using an optical fiber and various scintillators. To select an adequate inorganic scintillator for the sensing probe of fiber-optic radiation sensor, 5 types of scintillators were evaluated. The spectra of gamma-rays emitted from a Na-22 radiation source were measured by using the manufactured sensors. As a result, the BGO was suitable for the sensing probe of fiber-optic radiation sensor due to its high scintillation output and exact photoelectric peak for the gamma-ray energy. The basic principle of radiation detection is to detect the signals caused by interactions between radiations and materials. There are various types of radiation detectors depending on types of radiation to be detected and physical quantities to be measured. As one of the radiation detectors, a fiber-optic radiation sensor using a scintillator and an optical fiber has two advantages such as no space restraint and remote sensing. Moreover, in nuclear environments, this kind of sensor has immunities for electromagnetic field, temperature, and pressure. Thus, the fiber-optic radiation sensor can be used in various fields including nondestructive inspection, radioactive waste management, nuclear safety, radiodiagnosis and radiation therapy. As a fundamental study of the fiber-optic radiation sensor for remote gamma-ray spectroscopy, in this study, we fabricated a fiber-optic radiation sensor using an optical fiber and various scintillators. To select an adequate inorganic scintillator for the sensing probe of fiber-optic radiation sensor, 5 types of scintillators were evaluated. The spectra of gamma-rays emitted from a Na-22 radiation source were measured by using the manufactured sensors

Remote query measurement of pressure, fluid-flow velocity, and humidity using magnetoelastic thick-film sensors

Science.gov (United States)

Grimes, C. A.; Kouzoudis, D.

2000-01-01

Free-standing magnetoelastic thick-film sensors have a characteristic resonant frequency that can be determined by monitoring the magnetic flux emitted from the sensor in response to a time varying magnetic field. This property allows the sensors to be monitored remotely without the use of direct physical connections, such as wires, enabling measurement of environmental parameters from within sealed, opaque containers. In this work, we report on application of magnetoelastic sensors to measurement of atmospheric pressure, fluid-flow velocity, temperature, and mass load. Mass loading effects are demonstrated by fabrication of a remote query humidity sensor, made by coating the magnetoelastic thick film with a thin layer of solgel deposited Al2O3 that reversibly changes mass in response to humidity. c2000 Elsevier Science S.A. All rights reserved.

Space-Based Remote Sensing of the Earth: A Report to the Congress

Science.gov (United States)

1987-01-01

The commercialization of the LANDSAT Satellites, remote sensing research and development as applied to the Earth and its atmosphere as studied by NASA and NOAA is presented. Major gaps in the knowledge of the Earth and its atmosphere are identified and a series of space based measurement objectives are derived. The near-term space observations programs of the United States and other countries are detailed. The start is presented of the planning process to develop an integrated national program for research and development in Earth remote sensing for the remainder of this century and the many existing and proposed satellite and sensor systems that the program may include are described.

Tracking big and small agriculture with new satellite sensors

Science.gov (United States)

Lobell, D. B.; Azzari, G.; Jin, Z.

2017-12-01

New sensors from both the public and private sector are opening up exciting possibilities for monitoring agriculture and its use of water. This talk will present selected examples from recent work using data from Planet's Planetscope and Skysat sensors as well as Sentinel-1 and Sentinel-2 missions that are part of Europe's Copernicus program. Among other things, these satellites are now helping to track crop types and productivity for fields in rainfed cropping systems of East Africa and irrigated systems in South Asia. This information should contribute to understanding land and water use decisions throughout the world.

Remote sensing models and methods for image processing

CERN Document Server

Schowengerdt, Robert A

2007-01-01

Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. This book, in its 3rd edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standa

Fluxgate sensor for the vector magnetometer onboard the ’Astrid-2’ satellite

DEFF Research Database (Denmark)

Brauer, Peter; Risbo, T.; Merayo, José M.G.

2000-01-01

satellite called 'Orsted'. To obtain good axial stability special attention is drawn to the mechanical construction of the tri-axial sensor configuration. Almost all parts of the sensor are machined from the glassy material MACOR(R) that has approximately the same thermal expansion coefficient as the core...... ribbon. The single axis compensated ringcore sensors are known to have some linearity problems with large uncompensated fields perpendicular to the measuring axis, This phenomenon is also seen for the Astrid-2 sensor, and from a coil-calibration of the flight-spare sensor we observe: non-linearities...

Remote, mobile telemedicine: the satellite transmission of medical data from Mount Logan.

Science.gov (United States)

Otto, C; Pipe, A

1997-01-01

The purpose of this investigation was to demonstrate the potential of remote, mobile telemedicine during a four-week, high-altitude mountaineering expedition to Mount Logan, Canada's highest summit. Using a mobile satellite terminal and a laptop computer (both powered by a photovoltaic solar panel), ECG tracings and blood pressure measurements, in addition to colour images, short-segment video and audio clips were transmitted during the course of the ascent. The data were transmitted via a mobile communications satellite to a ground station in Ottawa, a distance of over 4000 km. The data were then transferred to the public switched data network and delivered to the University of Ottawa Heart Institute for analysis. Similarly, data were transmitted from the ground station to the expedition team on Mount Logan throughout the ascent. Using this technique, medical diagnosis and emergency care can be facilitated in extreme and isolated locations lacking a telecommunications infrastructure. Such technology has applications in developing countries, disaster response efforts, remote civilian and military operations, and in space operations.

Ocean Remote Sensing from Chinese Spaceborne Microwave Sensors

Science.gov (United States)

Yang, J.

2017-12-01

GF-3 (GF stands for GaoFen, which means High Resolution in Chinese) is the China's first C band multi-polarization high resolution microwave remote sensing satellite. It was successfully launched on Aug. 10, 2016 in Taiyuan satellite launch center. The synthetic aperture radar (SAR) on board GF-3 works at incidence angles ranging from 20 to 50 degree with several polarization modes including single-polarization, dual-polarization and quad-polarization. GF-3 SAR is also the world's most imaging modes SAR satellite, with 12 imaging modes consisting of some traditional ones like stripmap and scanSAR modes and some new ones like spotlight, wave and global modes. GF-3 SAR is thus a multi-functional satellite for both land and ocean observation by switching the different imaging modes. TG-2 (TG stands for TianGong, which means Heavenly Palace in Chinese) is a Chinese space laboratory which was launched on 15 Sep. 2016 from Jiuquan Satellite Launch Centre aboard a Long March 2F rocket. The onboard Interferometric Imaging Radar Altimeter (InIRA) is a new generation radar altimeter developed by China and also the first on orbit wide swath imaging radar altimeter, which integrates interferometry, synthetic aperture, and height tracking techniques at small incidence angles and a swath of 30 km. The InIRA was switch on to acquire data during this mission on 22 September. This paper gives some preliminary results for the quantitative remote sensing of ocean winds and waves from the GF-3 SAR and the TG-2 InIRA. The quantitative analysis and ocean wave spectra retrieval have been given from the SAR imagery. The image spectra which contain ocean wave information are first estimated from image's modulation using fast Fourier transform. Then, the wave spectra are retrieved from image spectra based on Hasselmann's classical quasi-linear SAR-ocean wave mapping model and the estimation of three modulation transfer functions (MTFs) including tilt, hydrodynamic and velocity bunching

Subsurface remote sensing

International Nuclear Information System (INIS)

Schweitzer, Jeffrey S.; Groves, Joel L.

2002-01-01

Subsurface remote sensing measurements are widely used for oil and gas exploration, for oil and gas production monitoring, and for basic studies in the earth sciences. Radiation sensors, often including small accelerator sources, are used to obtain bulk properties of the surrounding strata as well as to provide detailed elemental analyses of the rocks and fluids in rock pores. Typically, instrument packages are lowered into a borehole at the end of a long cable, that may be as long as 10 km, and two-way data and instruction telemetry allows a single radiation instrument to operate in different modes and to send the data to a surface computer. Because these boreholes are often in remote locations throughout the world, the data are frequently transmitted by satellite to various locations around the world for almost real-time analysis and incorporation with other data. The complete system approach that permits rapid and reliable data acquisition, remote analysis and transmission to those making decisions is described

Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

Directory of Open Access Journals (Sweden)

Cheng Liu

2011-07-01

Full Text Available Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction，have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR and near infrared (NIR channels of satellite sensors have been employed for detecting live fuel moisture content (FMC, and the Normalized Difference Water Index (NDWI was used for evaluating the forest vegetation condition and its moisture status.

Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

Science.gov (United States)

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K.

2011-01-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status. PMID:21909297

Mountainous Ecosystem Sensor Array (MESA): a mesh sensor network for climate change research in remote mountainous environments

Science.gov (United States)

Robinson, P. W.; Neal, D.; Frome, D.; Kavanagh, K.; Davis, A.; Gessler, P. E.; Hess, H.; Holden, Z. A.; Link, T. E.; Newingham, B. A.; Smith, A. M.

2013-12-01

Developing sensor networks robust enough to perform unattended in the world's remote regions is critical since these regions serve as important benchmarks that lack anthropogenic influence. Paradoxically, the factors that make these remote, natural sites challenging for sensor networking are often what make them indispensable for climate change research. The MESA (Mountainous Ecosystem Sensor Array) project has faced these challenges and developed a wireless mesh sensor network across a 660 m topoclimatic gradient in a wilderness area in central Idaho. This sensor array uses advances in sensing, networking, and power supply technologies to provide near real-time synchronized data covering a suite of biophysical parameters used in ecosystem process models. The 76 sensors in the network monitor atmospheric carbon dioxide concentration, humidity, air and soil temperature, soil water content, precipitation, incoming and outgoing shortwave and longwave radiation, snow depth, wind speed and direction, and leaf wetness at synchronized time intervals ranging from two minutes to two hours and spatial scales from a few meters to two kilometers. We present our novel methods of placing sensors and network nodes above, below, and throughout the forest canopy without using meteorological towers. In addition, we explain our decision to use different forms of power (wind and solar) and the equipment we use to control and integrate power harvesting. Further, we describe our use of the network to sense and quantify its own power use. Using examples of environmental data from the project, we discuss how these data may be used to increase our understanding of the effects of climate change on ecosystem processes in mountainous environments. MESA sensor locations across a 700 m topoclimatic gradient at the University of Idaho Taylor Wilderness Research Station.

Remote support services using condition monitoring and online sensor data for offshore oilfield

OpenAIRE

Du, Baoli

2013-01-01

Master's thesis in Offshore technology Based on advanced technology in condition monitoring and online sensor data, a new style of operation and maintenance management called remote operation and maintenance support services has been created to improve oil and gas E&P performance. This master thesis will look into how the remote support service is conducted including the concept, design, technology and management philosophies; the current implementation of remote support services in China,...

A Remote Characterization System for subsurface mapping of buried waste sites

International Nuclear Information System (INIS)

Sandness, G.A.; Bennett, D.W.; Martinson, L.

1992-06-01

This paper describes a development project that will provide new technology for characterizing hazardous waste burial sites. The project is a collaborative effort by five of the national laboratories, involving the development and demonstration of a remotely controlled site characterization system. The Remote Characterization System (RCS) includes a unique low-signature survey vehicle, a base station, radio telemetry data links, satellite-based vehicle tracking, stereo vision, and sensors for non-invasive inspection of the surface and subsurface

Research of remote control for Chinese Antarctica Telescope based on iridium satellite communication

Science.gov (United States)

Xu, Lingzhe; Yang, Shihai

2010-07-01

Astronomers are ever dreaming of sites with best seeing on the Earth surface for celestial observation, and the Antarctica is one of a few such sites only left owing to the global air pollution. However, Antarctica region is largely unaccessible for human being due to lacking of fundamental living conditions, travel facilities and effective ways of communication. Worst of all, the popular internet source as a general way of communication scarcely exists there. Facing such a dilemma and as a solution remote control and data transmission for telescopes through iridium satellite communication has been put forward for the Chinese network Antarctic Schmidt Telescopes 3 (AST3), which is currently under all round research and development. This paper presents iridium satellite-based remote control application adapted to telescope control. The pioneer work in China involves hardware and software configuration utilizing techniques for reliable and secure communication, which is outlined in the paper too.

Satellite-based Tropical Cyclone Monitoring Capabilities

Science.gov (United States)

Hawkins, J.; Richardson, K.; Surratt, M.; Yang, S.; Lee, T. F.; Sampson, C. R.; Solbrig, J.; Kuciauskas, A. P.; Miller, S. D.; Kent, J.

2012-12-01

Satellite remote sensing capabilities to monitor tropical cyclone (TC) location, structure, and intensity have evolved by utilizing a combination of operational and research and development (R&D) sensors. The microwave imagers from the operational Defense Meteorological Satellite Program [Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS)] form the "base" for structure observations due to their ability to view through upper-level clouds, modest size swaths and ability to capture most storm structure features. The NASA TRMM microwave imager and precipitation radar continue their 15+ yearlong missions in serving the TC warning and research communities. The cessation of NASA's QuikSCAT satellite after more than a decade of service is sorely missed, but India's OceanSat-2 scatterometer is now providing crucial ocean surface wind vectors in addition to the Navy's WindSat ocean surface wind vector retrievals. Another Advanced Scatterometer (ASCAT) onboard EUMETSAT's MetOp-2 satellite is slated for launch soon. Passive microwave imagery has received a much needed boost with the launch of the French/Indian Megha Tropiques imager in September 2011, basically greatly supplementing the very successful NASA TRMM pathfinder with a larger swath and more frequent temporal sampling. While initial data issues have delayed data utilization, current news indicates this data will be available in 2013. Future NASA Global Precipitation Mission (GPM) sensors starting in 2014 will provide enhanced capabilities. Also, the inclusion of the new microwave sounder data from the NPP ATMS (Oct 2011) will assist in mapping TC convective structures. The National Polar orbiting Partnership (NPP) program's VIIRS sensor includes a day night band (DNB) with the capability to view TC cloud structure at night when sufficient lunar illumination exits. Examples highlighting this new capability will be discussed in concert with additional data fusion efforts.

Stream Tracker: Crowd sourcing and remote sensing to monitor stream flow intermittence

Science.gov (United States)

Puntenney, K.; Kampf, S. K.; Newman, G.; Lefsky, M. A.; Weber, R.; Gerlich, J.

2017-12-01

Streams that do not flow continuously in time and space support diverse aquatic life and can be critical contributors to downstream water supply. However, these intermittent streams are rarely monitored and poorly mapped. Stream Tracker is a community powered stream monitoring project that pairs citizen contributed observations of streamflow presence or absence with a network of streamflow sensors and remotely sensed data from satellites to track when and where water is flowing in intermittent stream channels. Citizens can visit sites on roads and trails to track flow and contribute their observations to the project site hosted by CitSci.org. Data can be entered using either a mobile application with offline capabilities or an online data entry portal. The sensor network provides a consistent record of streamflow and flow presence/absence across a range of elevations and drainage areas. Capacitance, resistance, and laser sensors have been deployed to determine the most reliable, low cost sensor that could be mass distributed to track streamflow intermittence over a larger number of sites. Streamflow presence or absence observations from the citizen and sensor networks are then compared to satellite imagery to improve flow detection algorithms using remotely sensed data from Landsat. In the first two months of this project, 1,287 observations have been made at 241 sites by 24 project members across northern and western Colorado.

Assimilation of Real-Time Satellite And Human Sensor Networks for Modeling Natural Disasters

Science.gov (United States)

Aulov, O.; Halem, M.; Lary, D. J.

2011-12-01

We describe the development of underlying technologies needed to address the merging of a web of real time satellite sensor Web (SSW) and Human Sensor Web (HSW) needed to augment the US response to extreme events. As an initial prototyping step and use case scenario, we consider the development of two major system tools that can be transitioned from research to the responding operational agency for mitigating coastal oil spills. These tools consist of the capture of Situation Aware (SA) Social Media (SM) Data, and assimilation of the processed information into forecasting models to provide incident decision managers with interactive virtual spatial temporal animations superimposed with probabilistic data estimates. The system methodologies are equally applicable to the wider class of extreme events such as plume dispersions from volcanoes or massive fires, major floods, hurricane impacts, radioactive isotope dispersions from nuclear accidents, etc. A successful feasibility demonstration of this technology has been shown in the case of the Deepwater Horizon Oil Spill where Human Sensor Networks have been combined with a geophysical model to perform parameter assessments. Flickr images of beached oil were mined from the spill area, geolocated and timestamped and converted into geophysical data. This data was incorporated into General NOAA Operational Modeling Environment (GNOME), a Lagrangian forecast model that uses near real-time surface winds, ocean currents, and satellite shape profiles of oil to generate a forecast of plume movement. As a result, improved estimates of diffusive coefficients and rates of oil spill were determined. Current approaches for providing satellite derived oil distributions are collected from a satellite sensor web of operational and research sensors from many countries, and a manual analysis is performed by NESDIS. A real time SA HSW processing system based on geolocated SM data from sources such as Twitter, Flickr, YouTube etc., greatly

Remote sensing sensors and applications in environmental resources mapping and modeling

Science.gov (United States)

Melesse, Assefa M.; Weng, Qihao; Thenkabail, Prasad S.; Senay, Gabriel B.

2007-01-01

The history of remote sensing and development of different sensors for environmental and natural resources mapping and data acquisition is reviewed and reported. Application examples in urban studies, hydrological modeling such as land-cover and floodplain mapping, fractional vegetation cover and impervious surface area mapping, surface energy flux and micro-topography correlation studies is discussed. The review also discusses the use of remotely sensed-based rainfall and potential evapotranspiration for estimating crop water requirement satisfaction index and hence provides early warning information for growers. The review is not an exhaustive application of the remote sensing techniques rather a summary of some important applications in environmental studies and modeling.

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

Global, Persistent, Real-time Multi-sensor Automated Satellite Image Analysis and Crop Forecasting in Commercial Cloud

Science.gov (United States)

Brumby, S. P.; Warren, M. S.; Keisler, R.; Chartrand, R.; Skillman, S.; Franco, E.; Kontgis, C.; Moody, D.; Kelton, T.; Mathis, M.

2016-12-01

Cloud computing, combined with recent advances in machine learning for computer vision, is enabling understanding of the world at a scale and at a level of space and time granularity never before feasible. Multi-decadal Earth remote sensing datasets at the petabyte scale (8×10^15 bits) are now available in commercial cloud, and new satellite constellations will generate daily global coverage at a few meters per pixel. Public and commercial satellite observations now provide a wide range of sensor modalities, from traditional visible/infrared to dual-polarity synthetic aperture radar (SAR). This provides the opportunity to build a continuously updated map of the world supporting the academic community and decision-makers in government, finanace and industry. We report on work demonstrating country-scale agricultural forecasting, and global-scale land cover/land, use mapping using a range of public and commercial satellite imagery. We describe processing over a petabyte of compressed raw data from 2.8 quadrillion pixels (2.8 petapixels) acquired by the US Landsat and MODIS programs over the past 40 years. Using commodity cloud computing resources, we convert the imagery to a calibrated, georeferenced, multiresolution tiled format suited for machine-learning analysis. We believe ours is the first application to process, in less than a day, on generally available resources, over a petabyte of scientific image data. We report on work combining this imagery with time-series SAR collected by ESA Sentinel 1. We report on work using this reprocessed dataset for experiments demonstrating country-scale food production monitoring, an indicator for famine early warning. We apply remote sensing science and machine learning algorithms to detect and classify agricultural crops and then estimate crop yields and detect threats to food security (e.g., flooding, drought). The software platform and analysis methodology also support monitoring water resources, forests and other general

Remote Inspection Techniques for Reactor Internals of Liquid Metal Reactor by using Ultrasonic Waveguide Sensor

International Nuclear Information System (INIS)

Joo, Young Sang; Kim, Seok Hun; Lee, Jae Han

2006-02-01

The primary components such as a reactor core, heat exchangers, pumps and internal structures of a liquid metal reactor (LMR) are submerged in hot sodium of reactor vessel. The division 3 of ASME code section XI specifies the visual inspection and continuous monitoring as major in-service inspection (ISI) methods of reactor internal structures. Reactor core and internal structures of LMR can not be visually examined due to an opaque liquid sodium. The under-sodium viewing and remote inspection techniques by using an ultrasonic wave should be applied for the in-service inspection of reactor internals. The remote inspection techniques using ultrasonic wave have been developed and applied for the visualization and ISI of reactor internals. The under sodium viewing technique has a limitation for the application of LMR due to the high temperature and irradiation environment. In this study, an ultrasonic waveguide sensor with a strip plate has been developed for an application to the under-sodium viewing and remote inspection. The Lamb wave propagation of a waveguide sensor has been analyzed and the zero-order antisymmetric A 0 plate wave was selected as the application mode of the sensor. The A 0 plate wave can be propagated in the dispersive low frequency range by using a liquid wedge clamped to the waveguide. A new technique is presented which is capable of steering the radiation beam angle of a waveguide sensor without a mechanical movement of the sensor assembly. The steering function of the ultrasonic radiation beam can be achieved by a frequency tuning method of the excitation pulse in the dispersive range of the A 0 mode. The technique provides an opportunity to overcome the scanning limitation of a waveguide sensor. The beam steering function has been evaluated by an experimental verification. The ultrasonic C-scanning experiments are performed in water and the feasibility of the ultrasonic waveguide sensor has been verified. The various remote inspection

Satellite Imagery Analysis for Automated Global Food Security Forecasting

Science.gov (United States)

Moody, D.; Brumby, S. P.; Chartrand, R.; Keisler, R.; Mathis, M.; Beneke, C. M.; Nicholaeff, D.; Skillman, S.; Warren, M. S.; Poehnelt, J.

2017-12-01

The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. Cloud computing and storage, combined with recent advances in machine learning, are enabling understanding of the world at a scale and at a level of detail never before feasible. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and that can scale with the high-rate and dimensionality of imagery being collected. We focus on the problem of monitoring food crop productivity across the Middle East and North Africa, and show how an analysis-ready, multi-sensor data platform enables quick prototyping of satellite imagery analysis algorithms, from land use/land cover classification and natural resource mapping, to yearly and monthly vegetative health change trends at the structural field level.

Test-bed for the remote health monitoring system for bridge structures using FBG sensors

Science.gov (United States)

Lee, Chin-Hyung; Park, Ki-Tae; Joo, Bong-Chul; Hwang, Yoon-Koog

2009-05-01

This paper reports on test-bed for the long-term health monitoring system for bridge structures employing fiber Bragg grating (FBG) sensors, which is remotely accessible via the web, to provide real-time quantitative information on a bridge's response to live loading and environmental changes, and fast prediction of the structure's integrity. The sensors are attached on several locations of the structure and connected to a data acquisition system permanently installed onsite. The system can be accessed through remote communication using an optical cable network, through which the evaluation of the bridge behavior under live loading can be allowed at place far away from the field. Live structural data are transmitted continuously to the server computer at the central office. The server computer is connected securely to the internet, where data can be retrieved, processed and stored for the remote web-based health monitoring. Test-bed revealed that the remote health monitoring technology will enable practical, cost-effective, and reliable condition assessment and maintenance of bridge structures.

Cloud detection method for Chinese moderate high resolution satellite imagery (Conference Presentation)

Science.gov (United States)

Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo

2016-10-01

Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.

A comprehensive remote automated mobile robot framework for deployment of compact radiation sensors and campaign management

International Nuclear Information System (INIS)

Mukherjee, J.K.

2005-01-01

Remote controlled on-line sensing with compact radiation sensors for interactive, fast contamination mapping and source localization needs integrated command control and machine intelligence supported operation. The combination of remote operation capability and automation of sensing needs a comprehensive framework encompassing precision real-time remote controlled agent, reliable remote communication techniques for unified command and sensory data exchange with optimized bandwidth allocation between the real time low volume as well as moderate speed bulk data transfer and data abstraction for seamless multi-domain abstraction in single environment. The paper describes an indigenously developed comprehensive framework that achieves vertical integration of layered services complex functions, explains its implementation and details its operation with examples of on-line application sessions. Several important features like precise remote control of sensor trajectory generation in real time by digital signal processing, prediction and visualization of remote agent locus and attitude, spatial modeling of fixed features of the monitored region and localization of activity source over mapped region have been dealt with. (author)

High resolution color imagery for orthomaps and remote sensing

Energy Technology Data Exchange (ETDEWEB)

Fricker, Peter [Leica Geosystems GIS and Mapping, LLC (Switzerland); Gallo, M. Guillermo [Leica Geosystems GIS and Mapping, LLC (United States)

2005-07-01

The ADS40 Airborne Digital Pushbroom Sensor is currently the only commercial sensor capable of acquiring color and false color strip images in the low decimeter range at the same high resolution as the black and white stereo images. This high resolution of 12,000 pixels across the entire swath and 100% forward overlap in the image strips result in high quality DSM's, True Ortho's and at the same time allow unbiased remote sensing applications due to color strip images unchanged by pan-sharpening. The paper gives details on how the pushbroom sensor achieves these seemingly difficult technical challenges. It describes how a variety of mapping applications benefit from this sensor, a sensor which acts as a satellite pushbroom sensor within the airborne environment. (author)

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Volume 2; Revised

Science.gov (United States)

Mueller, James L. (Editor); Fargion, Giulietta S. (Editor); Trees, C.; Austin, R. W.; Pietras, C. (Editor); Hooker, S.; Holben, B.; McClain, Charles R.; Clark, D. K.; Yuen, M.

2002-01-01

This document stipulates protocols for measuring bio-optical and radiometric data for the SIMBIOS Project. It supersedes the earlier version, and is organized into four parts: Introductory Background, Instrument Characteristics, Field Measurements and Data Analysis, Data Reporting and Archival. Changes in this revision include the addition of three new chapters: (1) Fundamental Definitions, Relationships and Conventions; (2) MOBY, A Radiometric Buoy for Performance Monitoring and Vicarious Calibration of Satellite Ocean Color Sensors: Measurement and Data Analysis Protocols; and (3) Normalized Water-Leaving Radiance and Remote Sensing Reflectance: Bidirectional Reflectance and Other Factors. Although the present document represents another significant, incremental improvement in the ocean optics protocols, there are several protocols that have either been overtaken by recent technological progress, or have been otherwise identified as inadequate. Revision 4 is scheduled for completion sometime in 2003. This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational Project. The contributions are published as submitted, after only minor editing to correct obvious grammatical or clerical errors.

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Volume 1; Revised

Science.gov (United States)

Mueller, James L. (Editor); Fargion, Giulietta (Editor); Mueller, J. L.; Trees, C.; Austin, R. W.; Pietras, C.; Hooker, S.; Holben, B.; McClain, Charles R.; Clark, D. K.;

Development of a remote vital signs sensor

International Nuclear Information System (INIS)

Ladd, M.D.; Pacheco, M.S.; Rivas, R.R.

1997-01-01

This paper describes the work at Sandia National Laboratories to develop sensors that remotely detect unique life-form characteristics, such as breathing patterns or heartbeat patterns. This paper will address the Technical Support Working Group's (TSWG) objective: to develop a remote vital signs detector which can be used to assess someone's malevolent intent. The basic concept of operations for the projects, system development issues, and the preliminary results for a radar device currently in-house and the implications for implementation are described. A survey that identified the in-house technology currently being evaluated is reviewed, as well as ideas for other potential technologies to explore. A radar unit for breathing and heartbeat detection is being tested, and the applicability of infrared technology is being explored. The desire for rapid prototyping is driving the need for off-the-shelf technology. As a conclusion, current status and future directions of the effort are reviewed

Development of a remote vital signs sensor

Energy Technology Data Exchange (ETDEWEB)

Ladd, M.D.; Pacheco, M.S.; Rivas, R.R.

1997-06-01

This paper describes the work at Sandia National Laboratories to develop sensors that remotely detect unique life-form characteristics, such as breathing patterns or heartbeat patterns. This paper will address the Technical Support Working Group`s (TSWG) objective: to develop a remote vital signs detector which can be used to assess someone`s malevolent intent. The basic concept of operations for the projects, system development issues, and the preliminary results for a radar device currently in-house and the implications for implementation are described. A survey that identified the in-house technology currently being evaluated is reviewed, as well as ideas for other potential technologies to explore. A radar unit for breathing and heartbeat detection is being tested, and the applicability of infrared technology is being explored. The desire for rapid prototyping is driving the need for off-the-shelf technology. As a conclusion, current status and future directions of the effort are reviewed.

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

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...... 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...

MODELING AND SIMULATION OF HIGH RESOLUTION OPTICAL REMOTE SENSING SATELLITE GEOMETRIC CHAIN

Directory of Open Access Journals (Sweden)

Z. Xia

2018-04-01

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

Turbidity retrieval and monitoring of Danube Delta waters using multi-sensor optical remote sensing data: An integrated view from the delta plain lakes to the western-northwestern Black Sea coastal zone

OpenAIRE

Guttler, Fabio; Niculescu, Simona; Gohin, Francis

2013-01-01

Based on multi-sensor optical remote sensing techniques, more than 80 medium and high spatial resolution satellite images were used for studying the turbidity patterns of Danube Delta waters. During a selected 4-year temporal coverage (2006 to 2009), the turbidity gradients were simultaneously analyzed in the delta plain lakes and in the Black Sea western-northwestern coastal zone. Two distinct, but complementary, methodologies for retrieving turbidity were employed, one for the lakes and the...

[A mobile sensor for remote detection of natural gas leakage].

Science.gov (United States)

Zhang, Shuai; Liu, Wen-qing; Zhang, Yu-jun; Kan, Rui-feng; Ruan, Jun; Wang, Li-ming; Yu, Dian-qiang; Dong, Jin-ting; Han, Xiao-lei; Cui, Yi-ben; Liu, Jian-guo

2012-02-01

The detection of natural gas pipeline leak becomes a significant issue for body security, environmental protection and security of state property. However, the leak detection is difficult, because of the pipeline's covering many areas, operating conditions and complicated environment. A mobile sensor for remote detection of natural gas leakage based on scanning wavelength differential absorption spectroscopy (SWDAS) is introduced. The improved soft threshold wavelet denoising was proposed by analyzing the characteristics of reflection spectrum. And the results showed that the signal to noise ratio (SNR) was increased three times. When light intensity is 530 nA, the minimum remote sensitivity will be 80 ppm x m. A widely used SWDAS can make quantitative remote sensing of natural gas leak and locate the leak source precisely in a faster, safer and more intelligent way.

Research on Coal Exploration Technology Based on Satellite Remote Sensing

Directory of Open Access Journals (Sweden)

Dong Xiao

2016-01-01

Full Text Available Coal is the main source of energy. In China and Vietnam, coal resources are very rich, but the exploration level is relatively low. This is mainly caused by the complicated geological structure, the low efficiency, the related damage, and other bad situations. To this end, we need to make use of some advanced technologies to guarantee the resource exploration is implemented smoothly and orderly. Numerous studies show that remote sensing technology is an effective way in coal exploration and measurement. In this paper, we try to measure the distribution and reserves of open-air coal area through satellite imagery. The satellite picture of open-air coal mining region in Quang Ninh Province of Vietnam was collected as the experimental data. Firstly, the ENVI software is used to eliminate satellite imagery spectral interference. Then, the image classification model is established by the improved ELM algorithm. Finally, the effectiveness of the improved ELM algorithm is verified by using MATLAB simulations. The results show that the accuracies of the testing set reach 96.5%. And it reaches 83% of the image discernment precision compared with the same image from Google.

A droplet-based passive force sensor for remote tactile sensing applications

Science.gov (United States)

Nie, Baoqing; Yao, Ting; Zhang, Yiqiu; Liu, Jian; Chen, Xinjian

2018-01-01

A droplet-based flexible wireless force sensor has been developed for remote tactile-sensing applications. By integration of a droplet-based capacitive sensing unit and two circular planar coils, this inductor-capacitor (LC) passive sensor offers a platform for the mechanical force detection in a wireless transmitting mode. Under external loads, the membrane surface of the sensor deforms the underlying elastic droplet uniformly, introducing a capacitance response in tens of picofarads. The LC circuit transduces the applied force into corresponding variations of its resonance frequency, which is detected by an external electromagnetic coupling coil. Specifically, the liquid droplet features a mechanosensitive plasticity, which results in an increased device sensitivity as high as 2.72 MHz N-1. The high dielectric property of the droplet endows our sensor with high tolerance for noise and large capacitance values (20-40 pF), the highest value in the literature for the LC passive devices in comparable dimensions. It achieves excellent reproducibility under periodical loads ranging from 0 to 1.56 N and temperature fluctuations ranging from 10 °C to 55 °C. As an interesting conceptual demonstration, the flexible device has been configured into a fingertip-amounted setting in a highly compact package (of 11 mm × 11 mm × 0.25 mm) for remote contact force sensing in the table tennis game.

Absolute Radiometric Calibration of the GÖKTÜRK-2 Satellite Sensor Using Tuz GÖLÜ (landnet Site) from Ndvi Perspective

Science.gov (United States)

Sakarya, Ufuk; Hakkı Demirhan, İsmail; Seda Deveci, Hüsne; Teke, Mustafa; Demirkesen, Can; Küpçü, Ramazan; Feray Öztoprak, A.; Efendioğlu, Mehmet; Fehmi Şimşek, F.; Berke, Erdinç; Zübeyde Gürbüz, Sevgi

2016-06-01

TÜBİTAK UZAY has conducted a research study on the use of space-based satellite resources for several aspects of agriculture. Especially, there are two precision agriculture related projects: HASSAS (Widespread application of sustainable precision agriculture practices in Southeastern Anatolia Project Region (GAP) Project) and AKTAR (Smart Agriculture Feasibility Project). The HASSAS project aims to study development of precision agriculture practice in GAP region. Multi-spectral satellite imagery and aerial hyperspectral data along with ground measurements was collected to analyze data in an information system. AKTAR aims to develop models for irrigation, fertilization and spectral signatures of crops in Inner Anatolia. By the end of the project precision agriculture practices to control irrigation, fertilization, pesticide and estimation of crop yield will be developed. Analyzing the phenology of crops using NDVI is critical for the projects. For this reason, absolute radiometric calibration of the Red and NIR bands in space-based satellite sensors is an important issue. The Göktürk-2 satellite is an earth observation satellite which was designed and built in Turkey and was launched in 2012. The Göktürk-2 satellite sensor has a resolution 2.5 meters in panchromatic and 5 meters in R/G/B/NIR bands. The absolute radiometric calibration of the Göktürk-2 satellite sensor was performed via the ground-based measurements - spectra-radiometer, sun photometer, and meteorological station- in Tuz Gölü cal/val site in 2015. In this paper, the first ground-based absolute radiometric calibration results of the Göktürk-2 satellite sensor using Tuz Gölü is demonstrated. The absolute radiometric calibration results of this paper are compared with the published cross-calibration results of the Göktürk-2 satellite sensor utilizing Landsat 8 imagery. According to the experimental comparison results, the Göktürk-2 satellite sensor coefficients for red and NIR bands

ABSOLUTE RADIOMETRIC CALIBRATION OF THE GÖKTÜRK-2 SATELLITE SENSOR USING TUZ GÖLÜ (LANDNET SITE FROM NDVI PERSPECTIVE

Directory of Open Access Journals (Sweden)

U. Sakarya

2016-06-01

Full Text Available TÜBİTAK UZAY has conducted a research study on the use of space-based satellite resources for several aspects of agriculture. Especially, there are two precision agriculture related projects: HASSAS (Widespread application of sustainable precision agriculture practices in Southeastern Anatolia Project Region (GAP Project and AKTAR (Smart Agriculture Feasibility Project. The HASSAS project aims to study development of precision agriculture practice in GAP region. Multi-spectral satellite imagery and aerial hyperspectral data along with ground measurements was collected to analyze data in an information system. AKTAR aims to develop models for irrigation, fertilization and spectral signatures of crops in Inner Anatolia. By the end of the project precision agriculture practices to control irrigation, fertilization, pesticide and estimation of crop yield will be developed. Analyzing the phenology of crops using NDVI is critical for the projects. For this reason, absolute radiometric calibration of the Red and NIR bands in space-based satellite sensors is an important issue. The Göktürk-2 satellite is an earth observation satellite which was designed and built in Turkey and was launched in 2012. The Göktürk-2 satellite sensor has a resolution 2.5 meters in panchromatic and 5 meters in R/G/B/NIR bands. The absolute radiometric calibration of the Göktürk-2 satellite sensor was performed via the ground-based measurements - spectra-radiometer, sun photometer, and meteorological station- in Tuz Gölü cal/val site in 2015. In this paper, the first ground-based absolute radiometric calibration results of the Göktürk-2 satellite sensor using Tuz Gölü is demonstrated. The absolute radiometric calibration results of this paper are compared with the published cross-calibration results of the Göktürk-2 satellite sensor utilizing Landsat 8 imagery. According to the experimental comparison results, the Göktürk-2 satellite sensor coefficients for

Sensors and sensor systems for guidance and navigation; Proceedings of the Meeting, Orlando, FL, Apr. 2, 3, 1991

Science.gov (United States)

Wade, Jack; Tuchman, Avi

1991-07-01

The present conference discusses wide field-of-view star-tracker cameras, discrete frequency vs radius reticle trackers, a sensor system for comet approach and landing, a static horizon sensor for a remote-sensing satellite, an improved ring laser gyro navigator, FM reticle trackers in the pupil plane, and the 2D encoding of images via discrete reticles. Also discussed are reduced-cost coil windings for interferometric fiber-optic gyro sensors, the ASTRO 1M space attitude-determination system, passive range-sensor refinement via texture and segmentation, a coherent launch-site atmospheric wind sounder, and a radar-optronic tracking experiment for short and medium range aerial combat. (For individual items see A93-27044 to A93-27046)

Coalfire related CO2 emissions and remote sensing

Energy Technology Data Exchange (ETDEWEB)

Gangopadhyay, P.K.

2008-06-11

Subsurface and surface coalfires are a serious problem in many coal-producing countries. Combustion can occur within the coal seams (underground or surface), in piles of stored coal, or in spoil dumps at the surface. While consuming a non renewable energy source, coalfires promote several environmental problems. Among all GHGs that are emitted from coalfires, CO2 is the most significant because of its high quantity. In connection to this environmental problem, the core aim of the present research is to develop a hyperspectral remote sensing and radiative transfer based model that is able to estimate CO2 concentration (ppmv) from coalfires. Since 1960s remote sensing is being used as a tool to detect and monitoring coalfires. With time, remote sensing has proven a reliable tool to identify and monitor coalfires. In the present study multi-temporal, multi-sensor and multi-spectral thermal remote sensing data are being used to detect and monitor coalfires. Unlike the earlier studies, the present study explores the possibilities of satellite derived emissivity to detect and monitor coalfires. Two methods of emissivity extraction from satellite data were tested, namely NDVI (Normalized Difference Vegetation Index) derived and TES (Temperature emissivity separation) in two study areas situated in India and China and it was observed that the satellite derived emissivity offers a better kinetic surface temperature of the surface to understand the spread and extent of the coalfires more effectively. In order to reduce coalfire related GHG emissions and to achieve more effective fire fighting plans it is crucial to understand the dynamics of coalfire. Multitemporal spaceborne remote sensing data can be used to study the migration and expresses the results as vectors, indicating direction and speed of migration. The present study proposes a 2D model that recognizes an initiation point of coalfire from thermal remote sensing data and considers local geological settings to

Coalfires related CO2 emissions and remote sensing

Energy Technology Data Exchange (ETDEWEB)

Gangopadhyay, P.K.

2008-06-11

Subsurface and surface coalfires are a serious problem in many coal-producing countries. Combustion can occur within the coal seams (underground or surface), in piles of stored coal, or in spoil dumps at the surface. While consuming a non renewable energy source, coalfires promote several environmental problems. Among all GHGs that are emitted from coalfires, CO2 is the most significant because of its high quantity. In connection to this environmental problem, the core aim of the present research is to develop a hyperspectral remote sensing and radiative transfer based model that is able to estimate CO2 concentration (ppmv) from coalfires. Since 1960s remote sensing is being used as a tool to detect and monitoring coalfires. With time, remote sensing has proven a reliable tool to identify and monitor coalfires. In the present study multi-temporal, multi-sensor and multi-spectral thermal remote sensing data are being used to detect and monitor coalfires. Unlike the earlier studies, the present study explores the possibilities of satellite derived emissivity to detect and monitor coalfires. Two methods of emissivity extraction from satellite data were tested, namely NDVI (Normalized Difference Vegetation Index) derived and TES (Temperature emissivity separation) in two study areas situated in India and China and it was observed that the satellite derived emissivity offers a better kinetic surface temperature of the surface to understand the spread and extent of the coalfires more effectively. In order to reduce coalfire related GHG emissions and to achieve more effective fire fighting plans it is crucial to understand the dynamics of coalfire. Multitemporal spaceborne remote sensing data can be used to study the migration and expresses the results as vectors, indicating direction and speed of migration. The present study proposes a 2D model that recognizes an initiation point of coalfire from thermal remote sensing data and considers local geological settings to

Coalfire related CO2 emissions and remote sensing

International Nuclear Information System (INIS)

Gangopadhyay, P.K.

2008-01-01

Subsurface and surface coalfires are a serious problem in many coal-producing countries. Combustion can occur within the coal seams (underground or surface), in piles of stored coal, or in spoil dumps at the surface. While consuming a non renewable energy source, coalfires promote several environmental problems. Among all GHGs that are emitted from coalfires, CO2 is the most significant because of its high quantity. In connection to this environmental problem, the core aim of the present research is to develop a hyperspectral remote sensing and radiative transfer based model that is able to estimate CO2 concentration (ppmv) from coalfires. Since 1960s remote sensing is being used as a tool to detect and monitoring coalfires. With time, remote sensing has proven a reliable tool to identify and monitor coalfires. In the present study multi-temporal, multi-sensor and multi-spectral thermal remote sensing data are being used to detect and monitor coalfires. Unlike the earlier studies, the present study explores the possibilities of satellite derived emissivity to detect and monitor coalfires. Two methods of emissivity extraction from satellite data were tested, namely NDVI (Normalized Difference Vegetation Index) derived and TES (Temperature emissivity separation) in two study areas situated in India and China and it was observed that the satellite derived emissivity offers a better kinetic surface temperature of the surface to understand the spread and extent of the coalfires more effectively. In order to reduce coalfire related GHG emissions and to achieve more effective fire fighting plans it is crucial to understand the dynamics of coalfire. Multitemporal spaceborne remote sensing data can be used to study the migration and expresses the results as vectors, indicating direction and speed of migration. The present study proposes a 2D model that recognizes an initiation point of coalfire from thermal remote sensing data and considers local geological settings to

Development of satellite remote sensing techniques as an economic tool for forestry industry

Science.gov (United States)

Sader, Steven A.; Jadkowski, Mark A.

1989-01-01

A cooperative commercial development project designed to focus on cost-effective and practical applications of satellite remote sensing in forest management is discussed. The project, initiated in September, 1988 is being executed in three phases: (1) development of a forest resource inventory and geographic information system (GIS) updating systems; (2) testing and evaluation of remote-sensing products against forest industry specifications; and (3) integration of remote-sensing services and products in an operational setting. An advisory group represented by eleven major forest-product companies will provide direct involvement of the target market. The advisory group will focus on the following questions: Does the technology work for them? How can it be packaged to provide the needed forest-management information? Can the products and information be provided in a cost-effective manner?

Mapping Palm Swamp Wetland Ecosystems in the Peruvian Amazon: a Multi-Sensor Remote Sensing Approach

Science.gov (United States)

Podest, E.; McDonald, K. C.; Schroeder, R.; Pinto, N.; Zimmerman, R.; Horna, V.

2012-12-01

Wetland ecosystems are prevalent in the Amazon basin, especially in northern Peru. Of specific interest are palm swamp wetlands because they are characterized by constant surface inundation and moderate seasonal water level variation. This combination of constantly saturated soils and warm temperatures year-round can lead to considerable methane release to the atmosphere. Because of the widespread occurrence and expected sensitivity of these ecosystems to climate change, it is critical to develop methods to quantify their spatial extent and inundation state in order to assess their carbon dynamics. Spatio-temporal information on palm swamps is difficult to gather because of their remoteness and difficult accessibility. Spaceborne microwave remote sensing is an effective tool for characterizing these ecosystems since it is sensitive to surface water and vegetation structure and allows monitoring large inaccessible areas on a temporal basis regardless of atmospheric conditions or solar illumination. We developed a remote sensing methodology using multi-sensor remote sensing data from the Advanced Land Observing Satellite (ALOS) Phased Array L-Band Synthetic Aperture Radar (PALSAR), Shuttle Radar Topography Mission (SRTM) DEM, and Landsat to derive maps at 100 meter resolution of palm swamp extent and inundation based on ground data collections; and combined active and passive microwave data from AMSR-E and QuikSCAT to derive inundation extent at 25 kilometer resolution on a weekly basis. We then compared information content and accuracy of the coarse resolution products relative to the high-resolution datasets. The synergistic combination of high and low resolution datasets allowed for characterization of palm swamps and assessment of their flooding status. This work has been undertaken partly within the framework of the JAXA ALOS Kyoto & Carbon Initiative. PALSAR data have been provided by JAXA. Portions of this work were carried out at the Jet Propulsion Laboratory

Summary of breakout Session A1: A1, surveillance and remote sensing - sensor technology

International Nuclear Information System (INIS)

Anon.

1992-01-01

The breakout session was well attended and prompted a very informative discussion on the different types of sensor technology. Remote sensing was identified as an important part of oil spill response. The session was divided into four parts and focused on characteristics unique to each of these technologies, the major research and development (R ampersand D) issues, and innovative ideas associated with each sensor technology. The following technologies were discussed: 1. Tactical All Weather Sensor Technology; 2. Strategic All Weather Sensor Technology; 3. Oil on Shoreline; and 4. Miscellaneous Sensor Technology

Development of a multi-sensor based urban discharge forecasting system using remotely sensed data: A case study of extreme rainfall in South Korea

Science.gov (United States)

Yoon, Sunkwon; Jang, Sangmin; Park, Kyungwon

2017-04-01

Extreme weather due to changing climate is a main source of water-related disasters such as flooding and inundation and its damage will be accelerated somewhere in world wide. To prevent the water-related disasters and mitigate their damage in urban areas in future, we developed a multi-sensor based real-time discharge forecasting system using remotely sensed data such as radar and satellite. We used Communication, Ocean and Meteorological Satellite (COMS) and Korea Meteorological Agency (KMA) weather radar for quantitative precipitation estimation. The Automatic Weather System (AWS) and McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) were used for verification of rainfall accuracy. The optimal Z-R relation was applied the Tropical Z-R relationship (Z=32R1.65), it has been confirmed that the accuracy is improved in the extreme rainfall events. In addition, the performance of blended multi-sensor combining rainfall was improved in 60mm/h rainfall and more strong heavy rainfall events. Moreover, we adjusted to forecast the urban discharge using Storm Water Management Model (SWMM). Several statistical methods have been used for assessment of model simulation between observed and simulated discharge. In terms of the correlation coefficient and r-squared discharge between observed and forecasted were highly correlated. Based on this study, we captured a possibility of real-time urban discharge forecasting system using remotely sensed data and its utilization for real-time flood warning. Acknowledgement This research was supported by a grant (13AWMP-B066744-01) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korean government.

Monitoring drought using multi-sensor remote sensing data in cropland of Gansu Province

International Nuclear Information System (INIS)

Zeng, Linglin; Shan, Jie; Xiang, Daxiang

2014-01-01

Various drought monitoring models have been developed from different perspectives, as drought is impacted by various factors (precipitation, evaporation, runoff) and usually reflected in various aspects (vegetation condition, temperature). Cloud not only plays an important role in the earth's energy balance and climate change, but also directly impacts the regional precipitation and evaporation. As a result, the change of cloud cover and cloud type can be used to monitor drought. This paper proposes a new drought composite index, the Drought Composite Index (DCI), for drought monitoring based on multi-sensor remote sensing data in cropland of Gansu Province. This index combines the cloud classification data (CLS) from FY satellite and Vegetation Condition Index (VCI) which was calculated using the maximum and minimum NDVI values for the same time period from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson correlation was performed to correlate NDVI, VCI, CLS and DCI values to precipitation data and soil moisture (SM) data collected from 20 meteorological stations during the growing season of 2011 and 2012. Better agreement was observed between DCI and precipitation as compared with that between NDVI/VCI and precipitation, especially the one-month precipitation, and there is an obvious time lag in the response of vegetation to precipitation. In addition, the results indicated that DCI well reflected precipitation fluctuations in the study area promising a possibility for early drought awareness necessary and near real-time drought monitoring

Remote Driven and Read MEMS Sensors for Harsh Environments

Directory of Open Access Journals (Sweden)

David W. Vernooy

2013-10-01

Full Text Available The utilization of high accuracy sensors in harsh environments has been limited by the temperature constraints of the control electronics that must be co-located with the sensor. Several methods of remote interrogation for resonant sensors are presented in this paper which would allow these sensors to be extended to harsh environments. This work in particular demonstrates for the first time the ability to acoustically drive a silicon comb drive resonator into resonance and electromagnetically couple to the resonator to read its frequency. The performance of this system was studied as a function of standoff distance demonstrating the ability to excite and read the device from 22 cm when limited to drive powers of 30 mW. A feedback architecture was implemented that allowed the resonator to be driven into resonance from broadband noise and a standoff distance of 15 cm was demonstrated. It is emphasized that no junction-based electronic device was required to be co-located with the resonator, opening the door for the use of silicon-based, high accuracy MEMS devices in high temperature wireless applications.

Quantifying the Terrestrial Surface Energy Fluxes Using Remotely-Sensed Satellite Data

Science.gov (United States)

Siemann, Amanda Lynn

The dynamics of the energy fluxes between the land surface and the atmosphere drive local and regional climate and are paramount to understand the past, present, and future changes in climate. Although global reanalysis datasets, land surface models (LSMs), and climate models estimate these fluxes by simulating the physical processes involved, they merely simulate our current understanding of these processes. Global estimates of the terrestrial, surface energy fluxes based on observations allow us to capture the dynamics of the full climate system. Remotely-sensed satellite data is the source of observations of the land surface which provide the widest spatial coverage. Although net radiation and latent heat flux global, terrestrial, surface estimates based on remotely-sensed satellite data have progressed, comparable sensible heat data products and ground heat flux products have not progressed at this scale. Our primary objective is quantifying and understanding the terrestrial energy fluxes at the Earth's surface using remotely-sensed satellite data with consistent development among all energy budget components [through the land surface temperature (LST) and input meteorology], including validation of these products against in-situ data, uncertainty assessments, and long-term trend analysis. The turbulent fluxes are constrained by the available energy using the Bowen ratio of the un-constrained products to ensure energy budget closure. All final products are within uncertainty ranges of literature values, globally. When validated against the in-situ estimates, the sensible heat flux estimates using the CFSR air temperature and constrained with the products using the MODIS albedo produce estimates closest to the FLUXNET in-situ observations. Poor performance over South America is consistent with the largest uncertainties in the energy budget. From 1984-2007, the longwave upward flux increase due to the LST increase drives the net radiation decrease, and the

Coherent Uncertainty Analysis of Aerosol Measurements from Multiple Satellite Sensors

Science.gov (United States)

Petrenko, M.; Ichoku, C.

2013-01-01

Aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS altogether, a total of 11 different aerosol products were comparatively analyzed using data collocated with ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations within the Multi-sensor Aerosol Products Sampling System (MAPSS, http://giovanni.gsfc.nasa.gov/mapss/ and http://giovanni.gsfc.nasa.gov/aerostat/). The analysis was performed by comparing quality-screened satellite aerosol optical depth or thickness (AOD or AOT) retrievals during 2006-2010 to available collocated AERONET measurements globally, regionally, and seasonally, and deriving a number of statistical measures of accuracy. We used a robust statistical approach to detect and remove possible outliers in the collocated data that can bias the results of the analysis. Overall, the proportion of outliers in each of the quality-screened AOD products was within 12%. Squared correlation coefficient (R2) values of the satellite AOD retrievals relative to AERONET exceeded 0.6, with R2 for most of the products exceeding 0.7 over land and 0.8 over ocean. Root mean square error (RMSE) values for most of the AOD products were within 0.15 over land and 0.09 over ocean. We have been able to generate global maps showing regions where the different products present advantages over the others, as well as the relative performance of each product over different landcover types. It was observed that while MODIS, MISR, and SeaWiFS provide accurate retrievals over most of the landcover types, multi-angle capabilities make MISR the only sensor to retrieve reliable AOD over barren and snow / ice surfaces. Likewise, active sensing enables CALIOP to retrieve aerosol properties over bright-surface shrublands more accurately than the other sensors, while POLDER, which is the only one of the sensors capable of measuring polarized aerosols, outperforms other sensors in

A SERS-active sensor based on heterogeneous gold nanostar core-silver nanoparticle satellite assemblies for ultrasensitive detection of aflatoxinB1.

Science.gov (United States)

Li, Aike; Tang, Lijuan; Song, Dan; Song, Shanshan; Ma, Wei; Xu, Liguang; Kuang, Hua; Wu, Xiaoling; Liu, Liqiang; Chen, Xin; Xu, Chuanlai

2016-01-28

A surface-enhanced Raman scattering (SERS) sensor based on gold nanostar (Au NS) core-silver nanoparticle (Ag NP) satellites was fabricated for the first time to detect aflatoxinB1 (AFB1). We constructed the SERS sensor using AFB1 aptamer (DNA1)-modified Ag satellites and a complementary sequence (DNA2)-modified Au NS core. The Raman label (ATP) was modified on the surface of Ag satellites. The SERS signal was enhanced when the satellite NP was attached to the Au core NS. The AFB1 aptamer on the surface of Ag satellites would bind to the targets when AFB1 was present in the system, Ag satellites were then removed and the SERS signal decreased. This SERS sensor showed superior specificity for AFB1 and the linear detection range was from 1 to 1000 pg mL(-1) with the limit of detection (LOD) of 0.48 pg mL(-1). The excellent recovery experiment using peanut milk demonstrated that the sensor could be applied in food and environmental detection.

What is a picture worth? A history of remote sensing

Science.gov (United States)

Moore, Gerald K.

1979-01-01

Remote sensing is the use of electromagnetic energy to measure the physical properties of distant objects. It includes photography and geophysical surveying as well as newer techniques that use other parts of the electromagnetic spectrum. The history of remote sensing begins with photography. The origin of other types of remote sensing can be traced to World War II, with the development of radar, sonar, and thermal infrared detection systems. Since the 1960s, sensors have been designed to operate in virtually all of the electromagnetic spectrum. Today a wide variety of remote sensing instruments are available for use in hydrological studies; satellite data, such as Skylab photographs and Landsat images are particularly suitable for regional problems and studies. Planned future satellites will provide a ground resolution of 10–80 m. Remote sensing is currently used for hydrological applications in most countries of the world. The range of applications includes groundwater exploration determination of physical water quality, snowfield mapping, flood-inundation delineation, and making inventories of irrigated land. The use of remote sensing commonly results in considerable hydrological information at minimal cost. This information can be used to speed-up the development of water resources, to improve management practices, and to monitor environmental problems.

Combined Geometric and Neural Network Approach to Generic Fault Diagnosis in Satellite Actuators and Sensors

DEFF Research Database (Denmark)

Baldi, P.; Blanke, Mogens; Castaldi, P.

2016-01-01

This paper presents a novel scheme for diagnosis of faults affecting the sensors measuring the satellite attitude, body angular velocity and flywheel spin rates as well as defects related to the control torques provided by satellite reaction wheels. A nonlinear geometric design is used to avoid t...

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.

Validation of satellite data through the remote sensing techniques and the inclusion of them into agricultural education pilot programs

Science.gov (United States)

Papadavid, Georgios; Kountios, Georgios; Bournaris, T.; Michailidis, Anastasios; Hadjimitsis, Diofantos G.

2016-08-01

Nowadays, the remote sensing techniques have a significant role in all the fields of agricultural extensions as well as agricultural economics and education but they are used more specifically in hydrology. The aim of this paper is to demonstrate the use of field spectroscopy for validation of the satellite data and how combination of remote sensing techniques and field spectroscopy can have more accurate results for irrigation purposes. For this reason vegetation indices are used which are mostly empirical equations describing vegetation parameters during the lifecycle of the crops. These numbers are generated by some combination of remote sensing bands and may have some relationship to the amount of vegetation in a given image pixel. Due to the fact that most of the commonly used vegetation indices are only concerned with red-near-infrared spectrum and can be divided to perpendicular and ratio based indices the specific goal of the research is to illustrate the effect of the atmosphere to those indices, in both categories. In this frame field spectroscopy is employed in order to derive the spectral signatures of different crops in red and infrared spectrum after a campaign of ground measurements. The main indices have been calculated using satellite images taken at interval dates during the whole lifecycle of the crops by using a GER 1500 spectro-radiomete. These indices was compared to those extracted from satellite images after applying an atmospheric correction algorithm -darkest pixel- to the satellite images at a pre-processing level so as the indices would be in comparable form to those of the ground measurements. Furthermore, there has been a research made concerning the perspectives of the inclusion of the above mentioned remote satellite techniques to agricultural education pilot programs.

Signal Conditioning for the Kalman Filter: Application to Satellite Attitude Estimation with Magnetometer and Sun Sensors.

Science.gov (United States)

Esteban, Segundo; Girón-Sierra, Jose M; Polo, Óscar R; Angulo, Manuel

2016-10-31

Most satellites use an on-board attitude estimation system, based on available sensors. In the case of low-cost satellites, which are of increasing interest, it is usual to use magnetometers and Sun sensors. A Kalman filter is commonly recommended for the estimation, to simultaneously exploit the information from sensors and from a mathematical model of the satellite motion. It would be also convenient to adhere to a quaternion representation. This article focuses on some problems linked to this context. The state of the system should be represented in observable form. Singularities due to alignment of measured vectors cause estimation problems. Accommodation of the Kalman filter originates convergence difficulties. The article includes a new proposal that solves these problems, not needing changes in the Kalman filter algorithm. In addition, the article includes assessment of different errors, initialization values for the Kalman filter; and considers the influence of the magnetic dipole moment perturbation, showing how to handle it as part of the Kalman filter framework.

Signal Conditioning for the Kalman Filter: Application to Satellite Attitude Estimation with Magnetometer and Sun Sensors

Directory of Open Access Journals (Sweden)

Segundo Esteban

2016-10-01

Full Text Available Most satellites use an on-board attitude estimation system, based on available sensors. In the case of low-cost satellites, which are of increasing interest, it is usual to use magnetometers and Sun sensors. A Kalman filter is commonly recommended for the estimation, to simultaneously exploit the information from sensors and from a mathematical model of the satellite motion. It would be also convenient to adhere to a quaternion representation. This article focuses on some problems linked to this context. The state of the system should be represented in observable form. Singularities due to alignment of measured vectors cause estimation problems. Accommodation of the Kalman filter originates convergence difficulties. The article includes a new proposal that solves these problems, not needing changes in the Kalman filter algorithm. In addition, the article includes assessment of different errors, initialization values for the Kalman filter; and considers the influence of the magnetic dipole moment perturbation, showing how to handle it as part of the Kalman filter framework.

Combining airborne and satellite remote sensing programs to repress illegal oil discharges in restricted sea areas

International Nuclear Information System (INIS)

Price, M.

2005-01-01

An airborne surveillance program has been conducted over the Belgian part of the North Sea since 1991. The role of the program is to detect infringements on the Marpol Convention via remote sensing, and to take legal action against polluters through the use of recorded observations. Although Belgium has a restricted sea area of about 3,500 km with no fixed offshore oil installations, a pollution risk is constantly present due to 2 dense traffic separation schemes close to the shoreline. The Belgian marine areas and adjacent waters are regularly scanned with a Side Looking Airborne Radar (SLAR) on board a remote sensing aircraft. This paper describes an evaluation trial that the Belgian Management Unit of the North Sea Mathematical Models (MUMM) joined in 2004, together with various agencies from the United Kingdom, Germany and the Netherlands. The trial consists of a cost-sharing satellite service for oil detection with ENVISAT ASAR data. The trial was co-funded by the European Space Agency (ESA) and run by Kongsberg Satellite Services. MUMM's objective was to evaluate the effectiveness and operational character of satellite services for detecting oil spills at sea. The results of the 3 month trial have indicated that aerial remote sensing for the detection of illegal oil discharges at sea increases the chances of catching polluters more efficiently, with improved chances of evidence collecting. It was concluded that when various services are integrated and strict operational conditions are met, satellite services may prove to be valuable in restricted, very densely navigated national waters that are easily reached by airborne means. 12 refs., 8 tabs., 3 figs

Satellite remote sensing of river inundation area, stage, and discharge: a review

Science.gov (United States)

Smith, Laurence C.

1997-08-01

The growing availability of multi-temporal satellite data has increased opportunities for monitoring large rivers from space. A variety of passive and active sensors operating in the visible and microwave range are currently operating, or planned, which can estimate inundation area and delineate flood boundaries. Radar altimeters show great promise for directly measuring stage variation in large rivers. It also appears to be possible to obtain estimates of river discharge from space, using ground measurements and satellite data to construct empirical curves that relate water surface area to discharge. Extrapolation of these curves to ungauged sites may be possible for the special case of braided rivers.Where clouds, trees and floating vegetation do not obscure the water surface, high-resolution visible/infrared sensors provide good delineation of inundated areas. Synthetic aperture radar (SAR) sensors can penetrate clouds and can also detect standing water through emergent aquatic plants and forest canopies. However, multiple frequencies and polarizations are required for optimal discrimination of various inundated vegetation cover types. Existing single-polarization, fixed-frequency SARs are not sufficient for mapping inundation area in all riverine environments. In the absence of a space-borne multi-parameter SAR, a synergistic approach using single-frequency, fixed-polarization SAR and visible/infrared data will provide the best results over densely vegetated river floodplains.

Fiber optical sensing on-board communication satellites

Science.gov (United States)

Hurni, A.; Lemke, N. M. K.; Roner, M.; Obermaier, J.; Putzer, P.; Kuhenuri Chami, N.

2017-11-01

Striving constantly to reduce mass, AIT effort and overall cost of the classical point-to-point wired temperature sensor harness on-board telecommunication satellites, OHB System (formerly Kayser-Threde) has introduced the Hybrid Sensor Bus (HSB) system. As a future spacecraft platform element, HSB relies on electrical remote sensor units as well as fiber-optical sensors, both of which can serially be connected in a bus architecture. HSB is a modular measurement system with many applications, also thanks to the opportunities posed by the digital I²C bus. The emphasis, however, is on the introduction of fiber optics and especially fiber-Bragg grating (FBG) temperature sensors as disruptive innovation for the company's satellite platforms. The light weight FBG sensors are directly inscribed in mechanically robust and radiation tolerant fibers, reducing the need for optical fiber connectors and splices to a minimum. Wherever an FBG sensor shall be used, the fiber is glued together with a corresponding temperature transducer to the satellites structure or to a subsystem. The transducer is necessary to provide decoupling of mechanical stress, but simultaneously ensure a high thermal conductivity. HSB has been developed in the frame of an ESA-ARTES program with European and German co-funding and will be verified as flight demonstrator on-board the German Heinrich Hertz satellite (H2Sat). In this paper the Engineering Model development of HSB is presented and a Fiber-optical Sensor Multiplexer for a more flexible sensor bus architecture is introduced. The HSB system aims at telecommunication satellite platforms with an operational life time beyond 15 years in geostationary orbit. It claims a high compatibility in terms of performance and interfaces with existing platforms while it was designed with future applications with increased radiation exposure already in mind. In its basic configuration HSB consists of four modules which are the Power Supply Unit, the HSB

New and Emerging Satellite Imaging Capabilities in Support of Safeguards

International Nuclear Information System (INIS)

Johnson, M.; Paquette, J.P.; Spyropoulos, N.; Rainville, L.; Schichor, P.; Hong, M.

2015-01-01

This abstract is focused on new and emerging commercial satellite imagery (CSI) capabilities. For more than a decade, experienced imagery analysts have been exploiting and analyzing CSI in support of the Department of Safeguards. As the remote sensing industry continues to evolve, additional CSI imagery types are becoming available that could enhance our ability to evaluate and verify States' declarations and to investigate the possible presence of undeclared activities. A newly available and promising CSI capability that may have a Safeguards application is Full Motion Video (FMV) imagery collection from satellites. For quite some time, FMV imagery has been collected from airborne platforms, but now FMV sensors are being deployed into space. Like its airborne counterpart, satellite FMV imagery could provide analysts with a great deal of information, including insight into the operational status of facilities and patterns of activity. From a Safeguards perspective, FMV imagery could help the Agency in the evaluation and verification of States' declared facilities and activities. There are advantages of FMV imaging capabilities that cannot be duplicated with other CSI capabilities, including the ability to loiter over areas of interest and the potential to revisit sites multiple times per day. Additional sensor capabilities applicable to the Safeguards mission include, but are not limited to, the following sensors: · Thermal Infrared imaging sensors will be launched in late 2014 to monitor operational status, e.g., heat from a transformer. · High resolution ShortWave Infrared sensors able to characterize materials that could support verification of Additional Protocol declarations under Article 2.a(v). · Unmanned Aerial Vehicles with individual sensors or specific sensor combinations. The Safeguards Symposium provides a forum to showcase and demonstrate safeguards applications for these emerging satellite imaging capabilities. (author)

Remotely Sensed Data for High Resolution Agro-Environmental Policy Analysis

Science.gov (United States)

Welle, Paul

Policy analyses of agricultural and environmental systems are often limited due to data constraints. Measurement campaigns can be costly, especially when the area of interest includes oceans, forests, agricultural regions or other dispersed spatial domains. Satellite based remote sensing offers a way to increase the spatial and temporal resolution of policy analysis concerning these systems. However, there are key limitations to the implementation of satellite data. Uncertainty in data derived from remote-sensing can be significant, and traditional methods of policy analysis for managing uncertainty on large datasets can be computationally expensive. Moreover, while satellite data can increasingly offer estimates of some parameters such as weather or crop use, other information regarding demographic or economic data is unlikely to be estimated using these techniques. Managing these challenges in practical policy analysis remains a challenge. In this dissertation, I conduct five case studies which rely heavily on data sourced from orbital sensors. First, I assess the magnitude of climate and anthropogenic stress on coral reef ecosystems. Second, I conduct an impact assessment of soil salinity on California agriculture. Third, I measure the propensity of growers to adapt their cropping practices to soil salinization in agriculture. Fourth, I analyze whether small-scale desalination units could be applied on farms in California in order mitigate the effects of drought and salinization as well as prevent agricultural drainage from entering vulnerable ecosystems. And fifth, I assess the feasibility of satellite-based remote sensing for salinity measurement at global scale. Through these case studies, I confront both the challenges and benefits associated with implementing satellite based-remote sensing for improved policy analysis.

On the use of Satellite Remote Sensing and GIS to detect NO2 in the Troposphere

DEFF Research Database (Denmark)

Nielsen, Søren Zebitz

2012-01-01

This thesis studies the spatio-temporal patterns and trends in NO2 air pollution over Denmark using the satellite remote sensing product OMNO2e retrieved from the OMI instrument on the NASA AURA satellite. These data are related to in situ measurements of NO2 made at four rural and four urban...... measured in Denmark. Trends in the data are assessed and declining trends are seen over several European cities, whereas no significant trends are found in the Danish area. The mean distribution of NO2 from the satellite data is also used to evaluate the NOx emission inventory....

Remote Power Systems for Sensors on the Northern Border

Energy Technology Data Exchange (ETDEWEB)

Simpson, Lin J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kandt, Alicen J [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-06-08

The National Renewable Energy Laboratory (NREL) is working with the Department of Homeland Security (DHS) [1] to field sensors that accurately track different types of transportation across the northern border of the U.S.. To do this, the sensors require remote power so that they can be placed in the most advantageous geographical locations, often where no grid power is available. This enables the sensors to detect and track aircraft/vehicles despite natural features (e.g., mountains, ridges, valleys, trees) that often prevent standard methods (e.g., monostatic radar or visual observers) from detecting them. Without grid power, portable power systems were used to provide between 80 and 300 W continuously, even in bitter cold and when buried under feet of snow/ice. NREL provides details about the design, installation, and lessons learned from long-term deployment of a second-generation of novel power systems that used adjustable-angle photovoltaics (PV), lithium ion batteries, and fuel cells that provide power to achieve 100% up-time.

Open Access Data in Polar and Cryospheric Remote Sensing

Directory of Open Access Journals (Sweden)

Allen Pope

2014-07-01

Full Text Available This paper aims to introduce the main types and sources of remotely sensed data that are freely available and have cryospheric applications. We describe aerial and satellite photography, satellite-borne visible, near-infrared and thermal infrared sensors, synthetic aperture radar, passive microwave imagers and active microwave scatterometers. We consider the availability and practical utility of archival data, dating back in some cases to the 1920s for aerial photography and the 1960s for satellite imagery, the data that are being collected today and the prospects for future data collection; in all cases, with a focus on data that are openly accessible. Derived data products are increasingly available, and we give examples of such products of particular value in polar and cryospheric research. We also discuss the availability and applicability of free and, where possible, open-source software tools for reading and processing remotely sensed data. The paper concludes with a discussion of open data access within polar and cryospheric sciences, considering trends in data discoverability, access, sharing and use.

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

Science.gov (United States)

Zheng, Guang; Moskal, L Monika

2009-01-01

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

Satellite Image Classification of Building Damages Using Airborne and Satellite Image Samples in a Deep Learning Approach

Science.gov (United States)

Duarte, D.; Nex, F.; Kerle, N.; Vosselman, G.

2018-05-01

The localization and detailed assessment of damaged buildings after a disastrous event is of utmost importance to guide response operations, recovery tasks or for insurance purposes. Several remote sensing platforms and sensors are currently used for the manual detection of building damages. However, there is an overall interest in the use of automated methods to perform this task, regardless of the used platform. Owing to its synoptic coverage and predictable availability, satellite imagery is currently used as input for the identification of building damages by the International Charter, as well as the Copernicus Emergency Management Service for the production of damage grading and reference maps. Recently proposed methods to perform image classification of building damages rely on convolutional neural networks (CNN). These are usually trained with only satellite image samples in a binary classification problem, however the number of samples derived from these images is often limited, affecting the quality of the classification results. The use of up/down-sampling image samples during the training of a CNN, has demonstrated to improve several image recognition tasks in remote sensing. However, it is currently unclear if this multi resolution information can also be captured from images with different spatial resolutions like satellite and airborne imagery (from both manned and unmanned platforms). In this paper, a CNN framework using residual connections and dilated convolutions is used considering both manned and unmanned aerial image samples to perform the satellite image classification of building damages. Three network configurations, trained with multi-resolution image samples are compared against two benchmark networks where only satellite image samples are used. Combining feature maps generated from airborne and satellite image samples, and refining these using only the satellite image samples, improved nearly 4 % the overall satellite image

In situ ozone data for comparison with laser absorption remote sensor: 1980 pepe/neros program

International Nuclear Information System (INIS)

Mcdougal, D.S.; Lee, R.B. III; Bendura, R.J.

1982-05-01

Several sets of in situ ozone (O 3 ) measurements were made by a NASA aircraft in support of the laser absorption spectrometer (LAS) remote sensor. These measurements were designed to provide comparative O 3 data for the LAS sensor. The LAS, which was flown on a second aircraft, remotely measured the vertical burden of O 3 from the aircraft to the surface. In situ results of the air quality (O 3 and B sub scat) and meteorological (temperature and dewpoint) parameters for three correlative missions are presented. The aircraft flight plans, in situ concentration profiles and vertical burdens, and measurement errors are summarized

Remote Sensing Applications to Water Quality Management in Florida

Science.gov (United States)

Lehrter, J. C.; Schaeffer, B. A.; Hagy, J.; Spiering, B.; Barnes, B.; Hu, C.; Le, C.; McEachron, L.; Underwood, L. W.; Ellis, C.; Fisher, B.

2013-12-01

Optical datasets from estuarine and coastal systems are increasingly available for remote sensing algorithm development, validation, and application. With validated algorithms, the data streams from satellite sensors can provide unprecedented spatial and temporal data for local and regional coastal water quality management. Our presentation will highlight two recent applications of optical data and remote sensing to water quality decision-making in coastal regions of the state of Florida; (1) informing the development of estuarine and coastal nutrient criteria for the state of Florida and (2) informing the rezoning of the Florida Keys National Marine Sanctuary. These efforts involved building up the underlying science to demonstrate the applicability of satellite data as well as an outreach component to educate decision-makers about the use, utility, and uncertainties of remote sensing data products. Scientific developments included testing existing algorithms and generating new algorithms for water clarity and chlorophylla in case II (CDOM or turbidity dominated) estuarine and coastal waters and demonstrating the accuracy of remote sensing data products in comparison to traditional field based measurements. Including members from decision-making organizations on the research team and interacting with decision-makers early and often in the process were key factors for the success of the outreach efforts and the eventual adoption of satellite data into the data records and analyses used in decision-making. Florida coastal water bodies (black boxes) for which remote sensing imagery were applied to derive numeric nutrient criteria and in situ observations (black dots) used to validate imagery. Florida ocean color applied to development of numeric nutrient criteria

Development of a Three Dimensional Wireless Sensor Network for Terrain-Climate Research in Remote Mountainous Environments

Science.gov (United States)

Kavanagh, K.; Davis, A.; Gessler, P.; Hess, H.; Holden, Z.; Link, T. E.; Newingham, B. A.; Smith, A. M.; Robinson, P.

2011-12-01

Developing sensor networks that are robust enough to perform in the world's remote regions is critical since these regions serve as important benchmarks compared to human-dominated areas. Paradoxically, the factors that make these remote, natural sites challenging for sensor networking are often what make them indispensable for climate change research. We aim to overcome these challenges by developing a three-dimensional sensor network arrayed across a topoclimatic gradient (1100-1800 meters) in a wilderness area in central Idaho. Development of this sensor array builds upon advances in sensing, networking, and power supply technologies coupled with experiences of the multidisciplinary investigators in conducting research in remote mountainous locations. The proposed gradient monitoring network will provide near real-time data from a three-dimensional (3-D) array of sensors measuring biophysical parameters used in ecosystem process models. The network will monitor atmospheric carbon dioxide concentration, humidity, air and soil temperature, soil water content, precipitation, incoming and outgoing shortwave and longwave radiation, snow depth, wind speed and direction, tree stem growth and leaf wetness at time intervals ranging from seconds to days. The long-term goal of this project is to realize a transformative integration of smart sensor networks adaptively communicating data in real-time to ultimately achieve a 3-D visualization of ecosystem processes within remote mountainous regions. Process models will be the interface between the visualization platforms and the sensor network. This will allow us to better predict how non-human dominated terrestrial and aquatic ecosystems function and respond to climate dynamics. Access to the data will be ensured as part of the Northwest Knowledge Network being developed at the University of Idaho, through ongoing Idaho NSF-funded cyber infrastructure initiatives, and existing data management systems funded by NSF, such as

Potential for boom-mounted remote sensing applications in seedling quality monitoring

Science.gov (United States)

Robert F. Keefe; Jan U. H. Eitel; Daniel S. Long; Anthony S. Davis; Paul Gessler; Alistair M. S. Smith

2009-01-01

Remotely sensed aerial and satellite sensor imagery is widely used for classification of vegetation structure and health on industrial and public lands. More intensively than at any other time in the life of a planted tree, its health and status will be maintained and monitored while under culture in a bareroot or container nursery. As a case in point, inventories to...

Remote sensing data in Rangeland assessment and monitoring

International Nuclear Information System (INIS)

Hamid, Amna Ahmed; Ali, Mohamed M.

1999-01-01

The main objective of the paper is to illustrate the potential of remote sensing data in the study and monitoring of environmental changes in western Sudan where considerable part of the area is under rangeland use. Data from NOAA satellite AVHRR sensor as well as thematic mapper Tm was used to assess the environment of the area during 1982-1997. The AVHRR data was processed into vegetation index (NDVI) images. Image analysis and classification was done using image display and analysis (IDA) GIS method to study vegetation condition in time series. The obtained information from field observations. The result showed high correlation between the information the work concluded the followings: NDVI images and thematic mapper data proved to be efficient in environment change analysis. NOAA AVHRR satellite data can provide an early-warning indicator of an approaching disaster. Remote sensing integrated into a GIS can contribute effectively to improve land management through better understanding of environment variability.(Author)

Reconciled freshwater flux into the Godthåbsfjord system from satellite and airborne remote sensing

DEFF Research Database (Denmark)

Simonsen, Sebastian Bjerregaard; Barletta, Valentina Roberta; Forsberg, René

2015-01-01

IS hamper in situ observations. Here, we evaluate available data from remote sensing and find a drainage basin in rapid change. An analysis of data from the Gravity Recovery and Climate Experiment (GRACE) satellites shows a mean seasonal freshwater flux into Godthåbsfjord of 18.2 ± 1.2 Gt, in addition......, from various remote-sensing data sets, estimate the freshwater flux from the GrIS into a specific fjord system, the Godthåbsfjord, in southwest Greenland. The area of the GrIS draining into Godthåbsfjord covers approximately 36,700 km2. The large areal extent and the multiple outlets from the Gr...... to an imbalance in the mass balance of the drainage basin from 2003 to 2013 of 14.4 ± 0.2 Gt year−1. Altimetry data from air and spaceborne missions also suggest rapid changes in the outlet glacier dynamics. We find that only applying data from the Ice, Cloud, and land Elevation Satellite (ICESat) mission...

Distributed Multi-Sensor Real-Time Building Environmental Parameters Monitoring System with Remote Data Access

Directory of Open Access Journals (Sweden)

Beinarts Ivars

2014-12-01

Full Text Available In this paper the advanced monitoring system of multiple environmental parameters is presented. The purpose of the system is a long-term estimation of energy efficiency and sustainability for the research test stands which are made of different building materials. Construction of test stands, and placement of main sensors are presented in the first chapter. The structure of data acquisition system includes a real-time interface with sensors and a data logger that allows to acquire and log data from all sensors with fixed rate. The data logging system provides a remote access to the processing of the acquired data and carries out periodical saving at a remote FTP server using an Internet connection. The system architecture and the usage of sensors are explained in the second chapter. In the third chapter implementation of the system, different interfaces of sensors and energy measuring devices are discussed and several examples of data logger program are presented. Each data logger is reading data from analog and digital channels. Measurements can be displayed directly on a screen using WEB access or using data from FTP server. Measurements and acquired data graphical results are presented in the fourth chapter in the selected diagrams. The benefits of the developed system are presented in the conclusion.

Polarimetric Remote Sensing of Atmospheric Particulate Pollutants

Science.gov (United States)

Li, Z.; Zhang, Y.; Hong, J.

2018-04-01

Atmospheric particulate pollutants not only reduce atmospheric visibility, change the energy balance of the troposphere, but also affect human and vegetation health. For monitoring the particulate pollutants, we establish and develop a series of inversion algorithms based on polarimetric remote sensing technology which has unique advantages in dealing with atmospheric particulates. A solution is pointed out to estimate the near surface PM2.5 mass concentrations from full remote sensing measurements including polarimetric, active and infrared remote sensing technologies. It is found that the mean relative error of PM2.5 retrieved by full remote sensing measurements is 35.5 % in the case of October 5th 2013, improved to a certain degree compared to previous studies. A systematic comparison with the ground-based observations further indicates the effectiveness of the inversion algorithm and reliability of results. A new generation of polarized sensors (DPC and PCF), whose observation can support these algorithms, will be onboard GF series satellites and launched by China in the near future.

A MGy radiation-hardened sensor instrumentation link for nuclear reactor monitoring and remote handling

Energy Technology Data Exchange (ETDEWEB)

Verbeeck, Jens; Cao, Ying [KU Leuven - KUL, Div. LRD-MAGyICS, Kasteelpark Arenberg 10, 3001 Heverlee (Belgium); Van Uffelen, Marco; Mont Casellas, Laura; Damiani, Carlo; Morales, Emilio Ruiz; Santana, Roberto Ranz [Fusion for Energy - F4E, c/Josep,n deg. 2, Torres Diagonal Litoral, Ed. B3, 08019 Barcelona (Spain); Meek, Richard; Haist, Bernhard [Oxford Technologies Ltd. OTL, 7 Nuffield Way, Abingdon OX14 1RL (United Kingdom); De Cock, Wouter; Vermeeren, Ludo [SCK-CEN, Boeretang 200, 2400 Mol (Belgium); Steyaert, Michiel [KU Leuven, ESAT-MICAS, KasteelparkArenberg 10, 3001 Heverlee (Belgium); Leroux, Paul [KU Leuven, ESAT-MICAS, KasteelparkArenberg 10, 3001 Heverlee (Belgium)

2015-07-01

Decommissioning, dismantling and remote handling applications in nuclear facilities all require robotic solutions that are able to survive in radiation environments. Recently raised safety, radiation hardness and cost efficiency demands from both the nuclear regulatory and the society impose severe challenges in traditional methods. For example, in case of the dismantling of the Fukushima sites, solutions that survive accumulated doses higher than 1 MGy are mandatory. To allow remote operation of these tools in nuclear environments, electronics were used to be shielded with several centimeters of lead or even completely banned in these solutions. However, shielding electronics always leads to bulky and heavy solutions, which reduces the flexibility of robotic tools. It also requires longer repair time and produces extra waste further in a dismantling or decommissioning cycle. In addition, often in current reactor designs, due to size restrictions and the need to inspect very tight areas there are limitations to the use of shielding. A MGy radiation-hardened sensor instrumentation link developed by MAGyICS provides a solution to build a flexible, easy removable and small I and C module with MGy radiation tolerance without any shielding. Hereby it removes all these pains to implement electronics in robotic tools. The demonstrated solution in this poster is developed for ITER Remote Handling equipments operating in high radiation environments (>1 MGy) in and around the Tokamak. In order to obtain adequately accurate instrumentation and control information, as well as to ease the umbilical management, there is a need of front-end electronics that will have to be located close to those actuators and sensors on the remote handling tool. In particular, for diverter remote handling, it is estimated that these components will face gamma radiation up to 300 Gy/h (in-vessel) and a total dose of 1 MGy. The radiation-hardened sensor instrumentation link presented here, consists

New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

Science.gov (United States)

Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

2016-12-01

Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and

Design and Implementation of a Wireless Sensor Network-Based Remote Water-Level Monitoring System

Science.gov (United States)

Li, Xiuhong; Cheng, Xiao; Gong, Peng; Yan, Ke

2011-01-01

The proposed remote water-level monitoring system (RWMS) consists of a field sensor module, a base station module, adata center module and aWEB releasing module. It has advantages in real time and synchronized remote control, expandability, and anti-jamming capabilities. The RWMS can realize real-time remote monitoring, providing early warning of events and protection of the safety of monitoring personnel under certain dangerous circumstances. This system has been successfully applied in Poyanghu Lake. The cost of the whole system is approximately 1,500 yuan (RMB). PMID:22319377

Design and implementation of a wireless sensor network-based remote water-level monitoring system.

Science.gov (United States)

Li, Xiuhong; Cheng, Xiao; Gong, Peng; Yan, Ke

2011-01-01

The proposed remote water-level monitoring system (RWMS) consists of a field sensor module, a base station module, a data center module and a WEB releasing module. It has advantages in real time and synchronized remote control, expandability, and anti-jamming capabilities. The RWMS can realize real-time remote monitoring, providing early warning of events and protection of the safety of monitoring personnel under certain dangerous circumstances. This system has been successfully applied in Poyanghu Lake. The cost of the whole system is approximately 1,500 yuan (RMB).

Satellite imagery in safeguards: progress and prospects

International Nuclear Information System (INIS)

Niemeyer, I.; Listner, C.

2013-01-01

The use of satellite imagery has become very important for the verification of the safeguards implementation under the Nuclear Non-Proliferation Treaty (NPT). The main applications of satellite imagery are to verify the correctness and completeness of the member states' declarations, and to provide preparatory information for inspections, complimentary access and other technical visits. If the area of interest is not accessible, remote sensing sensors provide one of the few opportunities of gathering data for nuclear monitoring, as for example in Iraq between 1998 and 2002 or currently in North Korea. Satellite data of all available sensor types contains a considerable amount of safeguard-relevant information. Very high-resolution optical satellite imagery provides the most detailed spatial information on nuclear sites and activities up to 0.41 m resolution, together with up to 8 spectral bands from the visible light and near infrared. Thermal infrared (TIR) images can indicate the operational status of nuclear facilities and help to identify undeclared activities. Hyper-spectral imagery allows a quantitative estimation of geophysical, geochemical and biochemical characteristics of the earth's surface and is therefore useful for assessing, for example, surface cover changes due to drilling, mining and milling activities. Synthetic Aperture Radar (SAR) image data up to 1 m spatial resolution provides an all-weather, day and night monitoring capability. However, the absence (or existence) of nuclear activities can never be confirmed completely based on satellite imagery. (A.C.)

Mapping and Visualization of The Deepwater Horizon Oil Spill Using Satellite Imagery

Science.gov (United States)

Ferreira Pichardo, E.

2017-12-01

Satellites are man-made objects hovering around the Earth's orbit and are essential for Earth observation, i.e. the monitoring and gathering of data about the Earth's vital systems. Environmental Satellites are used for atmospheric research, weather forecasting, and warning as well as monitoring extreme weather events. These satellites are categorized into Geosynchronous and Low Earth (Polar) orbiting satellites. Visualizing satellite data is critical to understand the Earth's systems and changes to our environment. The objective of this research is to examine satellite-based remotely sensed data that needs to be processed and rendered in the form of maps or other forms of visualization to understand and interpret the satellites' observations to monitor the status, changes and evolution of the mega-disaster Deepwater Horizon Spill that occurred on April 20, 2010 in the Gulf of Mexico. In this project, we will use an array of tools and programs such as Python, CSPP and Linux. Also, we will use data from the National Oceanic and Atmospheric Administration (NOAA): Polar-Orbiting Satellites Terra Earth Observing System AM-1 (EOS AM-1), and Aqua EOS PM-1 to investigate the mega-disaster. Each of these satellites carry a variety of instruments, and we will use the data obtained from the remote sensor Moderate-Resolution Imaging Spectroradiometer (MODIS). Ultimately, this study shows the importance of mapping and visualizing data such as satellite data (MODIS) to understand the extents of environmental impacts disasters such as the Deepwater Horizon Oil spill.

Remote Autonomous Sensor Networks: A Study in Redundancy and Life Cycle Costs

Science.gov (United States)

Ahlrichs, M.; Dotson, A.; Cenek, M.

2017-12-01

The remote nature of the United States and Canada border and their extreme seasonal shifts has made monitoring much of the area impossible using conventional monitoring techniques. Currently, the United States has large gaps in its ability to detect movement on an as-needed-basis in remote areas. The proposed autonomous sensor network aims to meet that need by developing a product that is low cost, robust, and can be deployed on an as-needed-basis for short term monitoring events. This is accomplished by identifying radio frequency disturbance and acoustic disturbance. This project aims to validate the proposed design and offer optimization strategies by conducting a redundancy model as well as performing a Life Cycle Assessment (LCA). The model will incorporate topological, meteorological, and land cover datasets to estimate sensor loss over a three-month period, ensuring that the remaining network does not have significant gaps in coverage which preclude being able to receive and transmit data. The LCA will investigate the materials used to create the sensor to generate an estimate of the total environmental energy that is utilized to create the network and offer alternative materials and distribution methods that can lower this cost. This platform can function as a stand-alone monitoring network or provide additional spatial and temporal resolution to existing monitoring networks. This study aims to create the framework to determine if a sensor's design and distribution is appropriate for the target environment. The incorporation of a LCA will seek to answer if the data a proposed sensor network will collect outweighs the environmental damage that will result from its deployment. Furthermore, as the arctic continues to thaw and economic development grows, the methodology described in paper will function as a guidance document to ensure that future sensor networks have a minimal impact on these pristine areas.

Web of Things-Based Remote Monitoring System for Coal Mine Safety Using Wireless Sensor Network

OpenAIRE

Bo, Cheng; Xin, Cheng; Zhongyi, Zhai; Chengwen, Zhang; Junliang, Chen

2014-01-01

Frequent accidents have occurred in coal mine enterprises; therefore, raising the technological level of coal mine safety monitoring systems is an urgent problem. Wireless sensor networks (WSN), as a new field of research, have broad application prospects. This paper proposes a Web of Things- (WoT-) based remote monitoring system that takes full advantage of wireless sensor networks in combination with the CAN bus communication technique that abstracts the underground sensor data and capabili...

A comparision between satellite based and drone based remote sensing technology to achieve sustainable development: a review

Directory of Open Access Journals (Sweden)

Babankumar Bansod

2017-12-01

Full Text Available Precision agriculture is a way to manage the crop yield resources like water, fertilizers, soil, seeds in order to increase production, quality, gain and reduce squander products so that the existing system become eco-friendly. The main target of precision agriculture is to match resources and execution according to the crop and climate to ameliorate the effects of Praxis. Global Positioning System, Geographic Information System, Remote sensing technologies and various sensors are used in Precision farming for identifying the variability in field and using different methods to deal with them. Satellite based remote sensing is used to study the variability in crop and ground but suffer from various disadvantageous such as prohibited use, high price, less revisiting them, poor resolution due to great height, Unmanned Aerial Vehicle (UAV is other alternative option for application in precision farming. UAV overcomes the drawback of the ground based system, i.e. inaccessibility to muddy and very dense regions. Hovering at a peak of 500 meter - 1000 meter is good enough to offer various advantageous in image acquisition such as high spatial and temporal resolution, full flexibility, low cost. Recent studies of application of UAV in precision farming indicate advanced designing of UAV, enhancement in georeferencing and the mosaicking of image, analysis and extraction of information required for supplying a true end product to farmers. This paper also discusses the various platforms of UAV used in farming applications, its technical constraints, seclusion rites, reliability and safety.

A manual for inexpensive methods of analyzing and utilizing remote sensor data

Science.gov (United States)

Elifrits, C. D.; Barr, D. J.

1978-01-01

Instructions are provided for inexpensive methods of using remote sensor data to assist in the completion of the need to observe the earth's surface. When possible, relative costs were included. Equipment need for analysis of remote sensor data is described, and methods of use of these equipment items are included, as well as advantages and disadvantages of the use of individual items. Interpretation and analysis of stereo photos and the interpretation of typical patterns such as tone and texture, landcover, drainage, and erosional form are described. Similar treatment is given to monoscopic image interpretation, including LANDSAT MSS data. Enhancement techniques are detailed with respect to their application and simple techniques of creating an enhanced data item. Techniques described include additive and subtractive (Diazo processes) color techniques and enlargement of photos or images. Applications of these processes, including mappings of land resources, engineering soils, geology, water resources, environmental conditions, and crops and/or vegetation, are outlined.

Estimating stream discharge from a Himalayan Glacier using coupled satellite sensor data

Science.gov (United States)

Child, S. F.; Stearns, L. A.; van der Veen, C. J.; Haritashya, U. K.; Tarpanelli, A.

2015-12-01

The 4th IPCC report highlighted our limited understanding of Himalayan glacier behavior and contribution to the region's hydrology. Seasonal snow and glacier melt in the Himalayas are important sources of water, but estimates greatly differ about the actual contribution of melted glacier ice to stream discharge. A more comprehensive understanding of the contribution of glaciers to stream discharge is needed because streams being fed by glaciers affect the livelihoods of a large part of the world's population. Most of the streams in the Himalayas are unmonitored because in situ measurements are logistically difficult and costly. This necessitates the use of remote sensing platforms to obtain estimates of river discharge for validating hydrological models. In this study, we estimate stream discharge using cost-effective methods via repeat satellite imagery from Landsat-8 and SENTINEL-1A sensors. The methodology is based on previous studies, which show that ratio values from optical satellite bands correlate well with measured stream discharge. While similar, our methodology relies on significantly higher resolution imagery (30 m) and utilizes bands that are in the blue and near-infrared spectrum as opposed to previous studies using 250 m resolution imagery and spectral bands only in the near-infrared. Higher resolution imagery is necessary for streams where the source is a glacier's terminus because the width of the stream is often only 10s of meters. We validate our methodology using two rivers in the state of Kansas, where stream gauges are plentiful. We then apply our method to the Bhagirathi River, in the North-Central Himalayas, which is fed by the Gangotri Glacier and has a well monitored stream gauge. The analysis will later be used to couple river discharge and glacier flow and mass balance through an integrated hydrologic model in the Bhagirathi Basin.

Offshore Wind Energy: Wind and Sea Surface Temperature from Satellite Observations

DEFF Research Database (Denmark)

Karagali, Ioanna

as the entire atmosphere above. Under conditions of light winds and strong solar insolation, warming of the upper oceanic layer may occur. In this PhD study, remote sensing from satellites is used to obtain information for the near-surface ocean wind and the sea surface temperature over the North Sea......, demonstrate that wind information from SAR is more appropriate when small scale local features are of interest, not resolved by scatterometers. Hourly satellite observations of the sea surface temperature, from a thermal infra-red sensor, are used to identify and quantify the daily variability of the sea...

Online Resource for Earth-Observing Satellite Sensor Calibration

Science.gov (United States)

McCorkel, J.; Czapla-Myers, J.; Thome, K.; Wenny, B.

2015-01-01

The Radiometric Calibration Test Site (RadCaTS) at Railroad Valley Playa, Nevada is being developed by the University of Arizona to enable improved accuracy and consistency for airborne and satellite sensor calibration. Primary instrumentation at the site consists of ground-viewing radiometers, a sun photometer, and a meteorological station. Measurements made by these instruments are used to calculate surface reflectance, atmospheric properties and a prediction for top-of-atmosphere reflectance and radiance. This work will leverage research for RadCaTS, and describe the requirements for an online database, associated data formats and quality control, and processing levels.

Remote Sensing and Quantization of Analog Sensors

Science.gov (United States)

Strauss, Karl F.

2011-01-01

This method enables sensing and quantization of analog strain gauges. By manufacturing a piezoelectric sensor stack in parallel (physical) with a piezoelectric actuator stack, the capacitance of the sensor stack varies in exact proportion to the exertion applied by the actuator stack. This, in turn, varies the output frequency of the local sensor oscillator. The output, F(sub out), is fed to a phase detector, which is driven by a stable reference, F(sub ref). The output of the phase detector is a square waveform, D(sub out), whose duty cycle, t(sub W), varies in exact proportion according to whether F(sub out) is higher or lower than F(sub ref). In this design, should F(sub out) be precisely equal to F(sub ref), then the waveform has an exact 50/50 duty cycle. The waveform, D(sub out), is of generally very low frequency suitable for safe transmission over long distances without corruption. The active portion of the waveform, t(sub W), gates a remotely located counter, which is driven by a stable oscillator (source) of such frequency as to give sufficient digitization of t(sub W) to the resolution required by the application. The advantage to this scheme is that it negates the most-common, present method of sending either very low level signals (viz. direct output from the sensors) across great distances (anything over one-half meter) or the need to transmit widely varying higher frequencies over significant distances thereby eliminating interference [both in terms of beat frequency generation and in-situ EMI (electromagnetic interference)] caused by ineffective shielding. It also results in a significant reduction in shielding mass.

Toward daily monitoring of vegetation conditions at field scale through fusing data from multiple sensors

Science.gov (United States)

Vegetation monitoring requires remote sensing data at fine spatial and temporal resolution. While imagery from coarse resolution sensors such as MODIS/VIIRS can provide daily observations, they lack spatial detail to capture surface features for crop and rangeland monitoring. The Landsat satellite s...

Remote sensing for non-renewable resources - Satellite and airborne multiband scanners for mineral exploration

Science.gov (United States)

Goetz, Alexander F. H.

1986-01-01

The application of remote sensing techniques to mineral exploration involves the use of both spatial (morphological) as well as spectral information. This paper is directed toward a discussion of the uses of spectral image information and emphasizes the newest airborne and spaceborne sensor developments involving imaging spectrometers.

Development of Remote-Type Haptic Catheter Sensor System using Piezoelectric Transducer

Science.gov (United States)

Haruta, Mineyuki; Murayama, Yoshinobu; Omata, Sadao

This study describes the development of Remote-Type Haptic Catheter Sensor System which enables the mechanical property evaluation of a blood vessel. This system consists of a feedback circuit and a piezoelectric ultrasound transducer, and is operated based on a phase shift method so that the entire system oscillates at its inherent resonance frequency. Ultrasound reflected by the blood vessel makes a phase shift of the resonance system depending on the acoustic impedance of the reflector. The phase shift is then measured as a change in resonance frequency of the system; therefore, the detection resolution is highly improved. The correlation between the acoustic impedance and the resonance frequency change of the sensor system was demonstrated using silicone rubbers, metals and actual blood vessels from a pig. The performance of the sensor was also examined using vessel shaped phantom model. Finally, the discussion surveys a possibility of the novel sensor system in an application for intra vascular diagnosis.

Satellite Sensor Requirements for Monitoring Essential Biodiversity Variables of Coastal Ecosystems

Science.gov (United States)

Muller-Karger, Frank E.; Hestir, Erin; Ade, Christiana; Turpie, Kevin; Roberts, Dar A.; Siegel, David; Miller, Robert J.; Humm, David; Izenberg, Noam; Keller, Mary;

The fusion of satellite and UAV data: simulation of high spatial resolution band

Science.gov (United States)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

Directory of Open Access Journals (Sweden)

Mohammad Haji Gholizadeh

2016-08-01

Full Text Available Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM, chlorophyll-a, and pollutants. A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water’s surface. In this review paper, various properties (spectral, spatial and temporal, etc. of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a, colored dissolved organic matters (CDOM, Secchi disk depth (SDD, turbidity, total suspended sediments (TSS, water temperature (WT, total phosphorus (TP, sea surface salinity (SSS, dissolved oxygen (DO, biochemical oxygen demand (BOD and chemical oxygen demand (COD.

Remote sensing of forest degradation in Southeast Asia—Aiming for a regional view through 5–30 m satellite data

Directory of Open Access Journals (Sweden)

Jukka Miettinen

2014-12-01

Full Text Available In this review paper we present geographical, ecological and historical aspects of Southeast Asia from the perspective of forest degradation monitoring and critically discuss available approaches for large area forest degradation monitoring with satellite remote sensing data at high to medium spatial resolution (5–30 m. Several authors have achieved promising results in geographically limited areas within Southeast Asia using automated detection algorithms. However, the application of automated methods to large area assessments remains a major challenge. To-date, nearly all large area assessments of forest degradation in the region have included a strong visual interpretation component. We conclude that due to the variety of forest types and forest disturbance levels, as well as the variable image acquisition conditions in Southeast Asia, it is unlikely that forest degradation monitoring can be conducted throughout the region using a single automated approach with currently available remote sensing data. The provision of regionally consistent information on forest degradation from satellite remote sensing data remains therefore challenging. However, the expected increase in observation frequency in the near future (due to Landsat 8 and Sentinel-2 satellites may lead to the desired improvement in data availability and enable consistent and robust regional forest degradation monitoring in Southeast Asia. Keywords: Tropical forest disturbance, Selective logging, Shifting cultivation, Satellite data, Indochina peninsula, Maritime continent

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.

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.

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

Science.gov (United States)

Li, Zhaoqin; Xu, Dandan; Guo, Xulin

2014-01-01

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. PMID:25386759

Use of the Earth Observing One (EO-1) Satellite for the Namibia SensorWeb Flood Early Warning Pilot

Science.gov (United States)

Mandl, Daniel; Frye, Stuart; Cappelaere, Pat; Handy, Matthew; Policelli, Fritz; Katjizeu, McCloud; Van Langenhove, Guido; Aube, Guy; Saulnier, Jean-Francois; Sohlberg, Rob;

Meteorological satellite systems

CERN Document Server

Tan, Su-Yin

2014-01-01

“Meteorological Satellite Systems” is a primer on weather satellites and their Earth applications. This book reviews historic developments and recent technological advancements in GEO and polar orbiting meteorological satellites. It explores the evolution of these remote sensing technologies and their capabilities to monitor short- and long-term changes in weather patterns in response to climate change. Satellites developed by various countries, such as U.S. meteorological satellites, EUMETSAT, and Russian, Chinese, Japanese and Indian satellite platforms are reviewed. This book also discusses international efforts to coordinate meteorological remote sensing data collection and sharing. This title provides a ready and quick reference for information about meteorological satellites. It serves as a useful tool for a broad audience that includes students, academics, private consultants, engineers, scientists, and teachers.

Regional water resources management in the Andean region with numerical models and satellite remote sensing

NARCIS (Netherlands)

Menenti, M.; Mulders, C.W.B.

1999-01-01

This report describes the development and adaptation of distributed numerical simulation models of hydrological processes in complex watersheds typical of the Andean region. These distributed models take advantage of the synoptic capabilities of sensors on-board satellites and GIS procedures have

Forecasting Global Horizontal Irradiance Using the LETKF and a Combination of Advected Satellite Images and Sparse Ground Sensors

Science.gov (United States)

Harty, T. M.; Lorenzo, A.; Holmgren, W.; Morzfeld, M.

2017-12-01

The irradiance incident on a solar panel is the main factor in determining the power output of that panel. For this reason, accurate global horizontal irradiance (GHI) estimates and forecasts are critical when determining the optimal location for a solar power plant, forecasting utility scale solar power production, or forecasting distributed, behind the meter rooftop solar power production. Satellite images provide a basis for producing the GHI estimates needed to undertake these objectives. The focus of this work is to combine satellite derived GHI estimates with ground sensor measurements and an advection model. The idea is to use accurate but sparsely distributed ground sensors to improve satellite derived GHI estimates which can cover large areas (the size of a city or a region of the United States). We use a Bayesian framework to perform the data assimilation, which enables us to produce irradiance forecasts and associated uncertainties which incorporate both satellite and ground sensor data. Within this framework, we utilize satellite images taken from the GOES-15 geostationary satellite (available every 15-30 minutes) as well as ground data taken from irradiance sensors and rooftop solar arrays (available every 5 minutes). The advection model, driven by wind forecasts from a numerical weather model, simulates cloud motion between measurements. We use the Local Ensemble Transform Kalman Filter (LETKF) to perform the data assimilation. We present preliminary results towards making such a system useful in an operational context. We explain how localization and inflation in the LETKF, perturbations of wind-fields, and random perturbations of the advection model, affect the accuracy of our estimates and forecasts. We present experiments showing the accuracy of our forecasted GHI over forecast-horizons of 15 mins to 1 hr. The limitations of our approach and future improvements are also discussed.

Secure Authentication for Remote Patient Monitoring with Wireless Medical Sensor Networks.

Science.gov (United States)

Hayajneh, Thaier; Mohd, Bassam J; Imran, Muhammad; Almashaqbeh, Ghada; Vasilakos, Athanasios V

2016-03-24

There is broad consensus that remote health monitoring will benefit all stakeholders in the healthcare system and that it has the potential to save billions of dollars. Among the major concerns that are preventing the patients from widely adopting this technology are data privacy and security. Wireless Medical Sensor Networks (MSNs) are the building blocks for remote health monitoring systems. This paper helps to identify the most challenging security issues in the existing authentication protocols for remote patient monitoring and presents a lightweight public-key-based authentication protocol for MSNs. In MSNs, the nodes are classified into sensors that report measurements about the human body and actuators that receive commands from the medical staff and perform actions. Authenticating these commands is a critical security issue, as any alteration may lead to serious consequences. The proposed protocol is based on the Rabin authentication algorithm, which is modified in this paper to improve its signature signing process, making it suitable for delay-sensitive MSN applications. To prove the efficiency of the Rabin algorithm, we implemented the algorithm with different hardware settings using Tmote Sky motes and also programmed the algorithm on an FPGA to evaluate its design and performance. Furthermore, the proposed protocol is implemented and tested using the MIRACL (Multiprecision Integer and Rational Arithmetic C/C++) library. The results show that secure, direct, instant and authenticated commands can be delivered from the medical staff to the MSN nodes.

CBERS-2B Brazilian remote sensing satellite to help to monitor the Bolivia-Brazil gas pipeline

Energy Technology Data Exchange (ETDEWEB)

Hernandes, Gilberto Luis Sanches [TBG Transportadora Brasileira Gasoduto Bolivia-Brasil, Rio de Janeiro, RJ (Brazil)

2009-07-01

This paper presents the results of CBERS-2B' Brazilian Remote Sensing Satellite to help to monitor the Bolivia-Brazil Gas Pipeline. The CBERS-2B is the third satellite launched in 2007 by the CBERS Program (China-Brazil Earth Resources Satellite) and the innovation was the HRC camera that produces high resolution images. It will be possible to obtain one complete coverage of the country every 130 days. In this study, 2 images from different parts of the Bolivia- Brazil Gas Pipeline were selected. Image processing involved the geometric registration of CBERS-2B satellite images with airborne images, contrast stretch transform and pseudo color. The analysis of satellite and airborne images in a GIS software to detect third party encroachment was effective to detect native vegetation removal, street construction, growth of urban areas, farming and residential/industrial land development. Very young, the CBERS-2B is a good promise to help to inspect the areas along the pipelines. (author)

The Use Of Satellite Remote Sensing And Helicopter Tem Data For The Identification And Characterization Of Contaminated Landfill Sites

DEFF Research Database (Denmark)

Viezzoli, Andrea; Edsen, Anders; Auken, Esben

, satellite remote sensing has been successfully used to identify numerous candidate sites that are most likely to host waste materials. This result was the basis for further monitoring activities based on the use of an helicopter transient electromagnetic (TEM) system, to be carried out at end of April 2009...... and remote sensing methods represents a useful instrument for environmental management....

A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing..

Science.gov (United States)

Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying...

Using Open Access Satellite Data Alongside Ground Based Remote Sensing: An Assessment, with Case Studies from Egypt’s Delta

Directory of Open Access Journals (Sweden)

Sarah Parcak

2017-09-01

Full Text Available This paper will assess the most recently available open access high-resolution optical satellite data (0.3 m–0.6 m and its detection of buried ancient features versus ground based remote sensing tools. It also discusses the importance of CORONA satellite data to evaluate landscape changes over the past 50 years surrounding sites. The study concentrates on Egypt’s Nile Delta, which is threatened by rising sea and water tables and urbanization. Many ancient coastal sites will be lost in the next few decades, thus this paper emphasizes the need to map them before they disappear. It shows that high resolution satellites can sometimes provide the same general picture on ancient sites in the Egyptian Nile Delta as ground based remote sensing, with relatively sandier sedimentary and degrading tell environments, during periods of rainfall, and higher groundwater conditions. Research results also suggest potential solutions for rapid mapping of threatened Delta sites, and urge a collaborative global effort to maps them before they disappear.

An Optical Fibre Depth (Pressure) Sensor for Remote Operated Vehicles in Underwater Applications

Science.gov (United States)

Duraibabu, Dinesh Babu; Poeggel, Sven; Omerdic, Edin; Capocci, Romano; Lewis, Elfed; Newe, Thomas; Leen, Gabriel; Toal, Daniel; Dooly, Gerard

2017-01-01

A miniature sensor for accurate measurement of pressure (depth) with temperature compensation in the ocean environment is described. The sensor is based on an optical fibre Extrinsic Fabry-Perot interferometer (EFPI) combined with a Fibre Bragg Grating (FBG). The EFPI provides pressure measurements while the Fibre Bragg Grating (FBG) provides temperature measurements. The sensor is mechanically robust, corrosion-resistant and suitable for use in underwater applications. The combined pressure and temperature sensor system was mounted on-board a mini remotely operated underwater vehicle (ROV) in order to monitor the pressure changes at various depths. The reflected optical spectrum from the sensor was monitored online and a pressure or temperature change caused a corresponding observable shift in the received optical spectrum. The sensor exhibited excellent stability when measured over a 2 h period underwater and its performance is compared with a commercially available reference sensor also mounted on the ROV. The measurements illustrates that the EFPI/FBG sensor is more accurate for depth measurements (depth of ~0.020 m). PMID:28218727

A Review of Ocean/Sea Subsurface Water Temperature Studies from Remote Sensing and Non-Remote Sensing Methods

Directory of Open Access Journals (Sweden)

Elahe Akbari

2017-12-01

Full Text Available Oceans/Seas are important components of Earth that are affected by global warming and climate change. Recent studies have indicated that the deeper oceans are responsible for climate variability by changing the Earth’s ecosystem; therefore, assessing them has become more important. Remote sensing can provide sea surface data at high spatial/temporal resolution and with large spatial coverage, which allows for remarkable discoveries in the ocean sciences. The deep layers of the ocean/sea, however, cannot be directly detected by satellite remote sensors. Therefore, researchers have examined the relationships between salinity, height, and temperature of the oceans/Seas to estimate their subsurface water temperature using dynamical models and model-based data assimilation (numerical based and statistical approaches, which simulate these parameters by employing remotely sensed data and in situ measurements. Due to the requirements of comprehensive perception and the importance of global warming in decision making and scientific studies, this review provides comprehensive information on the methods that are used to estimate ocean/sea subsurface water temperature from remotely and non-remotely sensed data. To clarify the subsurface processes, the challenges, limitations, and perspectives of the existing methods are also investigated.

Distributed Sensor Particles for Remote Fluorescence Detection of Trace Analytes: UXO/CW; TOPICAL

International Nuclear Information System (INIS)

SINGH, ANUP K.; GUPTA, ALOK; MULCHANDANI, ASHOK; CHEN, WILFRED; BHATIA, RIMPLE B.; SCHOENIGER, JOSEPH S.; ASHLEY, CAROL S.; BRINKER, C. JEFFREY; HANCE, BRADLEY G.; SCHMITT, RANDAL L.; JOHNSON, MARK S.; HARGIS JR. PHILIP J.; SIMONSON, ROBERT J.

2001-01-01

This report summarizes the development of sensor particles for remote detection of trace chemical analytes over broad areas, e.g residual trinitrotoluene from buried landmines or other unexploded ordnance (UXO). We also describe the potential of the sensor particle approach for the detection of chemical warfare (CW) agents. The primary goal of this work has been the development of sensor particles that incorporate sample preconcentration, analyte molecular recognition, chemical signal amplification, and fluorescence signal transduction within a ''grain of sand''. Two approaches for particle-based chemical-to-fluorescence signal transduction are described: (1) enzyme-amplified immunoassays using biocompatible inorganic encapsulants, and (2) oxidative quenching of a unique fluorescent polymer by TNT

Advances in Small Remotely Piloted Aircraft Communications and Remote Sensing in Maritime Environments including the Arctic

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McGillivary, P. A.; Borges de Sousa, J.; Wackowski, S.; Walker, G.

2011-12-01

Small remotely piloted aircraft have recently been used for maritime remote sensing, including launch and retrieval operations from land, ships and sea ice. Such aircraft can also function to collect and communicate data from other ocean observing system platforms including moorings, tagged animals, drifters, autonomous surface vessels (ASVs), and autonomous underwater vessels (AUVs). The use of small remotely piloted aircraft (or UASs, unmanned aerial systems) with a combination of these capabilities will be required to monitor the vast areas of the open ocean, as well as in harsh high-latitude ecosystems. Indeed, these aircraft are a key component of planned high latitude maritime domain awareness environmental data collection capabilities, including use of visible, IR and hyperspectral sensors, as well as lidar, meteorological sensors, and interferometric synthetic aperture radars (ISARs). We here first describe at-sea demonstrations of improved reliability and bandwidth of communications from ocean sensors on autonomous underwater vehicles to autonomous surface vessels, and then via remotely piloted aircraft to shore, ships and manned aircraft using Delay and Disruption Tolerant (DTN) communication protocols. DTN enables data exchange in communications-challenged environments, such as remote regions of the ocean including high latitudes where low satellite angles and auroral disturbances can be problematic. DTN provides a network architecture and application interface structured around optionally-reliable asynchronous message forwarding, with limited expectations of end-to-end connectivity and node resources. This communications method enables aircraft and surface vessels to function as data mules to move data between physically disparate nodes. We provide examples of the uses of this communication protocol for environmental data collection and data distribution with a variety of different remotely piloted aircraft in a coastal ocean environment. Next, we

Feasibility of Using Remotely Sensed Data to Aid in Long-Term Monitoring of Biodiversity

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Carroll, Mark L.; Brown, Molly E.; Elders, Akiko; Johnson, Kiersten

2014-01-01

Remote sensing is defined as making observations of an event or phenomena without physically sampling it. Typically this is done with instruments and sensors mounted on anything from poles extended over a cornfield,to airplanes,to satellites orbiting the Earth The sensors have characteristics that allow them to detect and record information regarding the emission and reflectance of electromagnetic energy from a surface or object. That information can then be represented visually on a screen or paper map or used in data analysis to inform decision-making.

Satellite Based Education and Training in Remote Sensing and Geo-Information AN E-Learning Approach to Meet the Growing Demands in India

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Raju, P. L. N.; Gupta, P. K.

2012-07-01

One of the prime activities of Indian Space Research Organisation's (ISRO) Space Program is providing satellite communication services, viz., television broadcasting, mobile communication, cyclone disaster warning and rescue operations etc. so as to improve their economic conditions, disseminate technical / scientific knowledge to improve the agriculture production and education for rural people of India. ISRO, along with National Aeronautical and Space Administration (NASA) conducted experimental satellite communication project i.e. Satellite Instructional Television Experiment (SITE) using NASA's Advanced Telecommunication Satellite (i.e. ATS 6) with an objective to educate poor people of India via satellite broadcasting in 1975 and 1976, covering more than 2600 villages in six states of India and territories. Over the years India built communication satellites indigenously to meet the communication requirements of India. This has further lead to launch of an exclusive satellite from ISRO for educational purposes i.e. EDUSAT in 2004 through which rich audio-video content is transmitted / received, recreating virtual classes through interactivity. Indian Institute of Remote Sensing (IIRS) established in 1966, a premier institute in south East Asia in disseminating Remote Sensing (RS) and Geographical Information System (GIS), mainly focusing on contact based programs. But expanded the scope with satellite based Distance Learning Programs for Universities, utilizing the dedicated communication satellite i.e. EDUSAT in 2007. IIRS conducted successfully eight Distance Learning Programs in the last five years and training more than 6000 students mainly at postgraduate level from more than 60 universities /Institutions spread across India. IIRS obtained feedback and improved the programs on the continuous basis. Expanded the scope of IIRS outreach program to train user departments tailor made in any of the applications of Remote Sensing and Geoinformation, capacity

SATELLITE BASED EDUCATION AND TRAINING IN REMOTE SENSING AND GEO-INFORMATION: AN E-LEARNING APPROACH TO MEET THE GROWING DEMANDS IN INDIA

Directory of Open Access Journals (Sweden)

P. L. N. Raju

2012-07-01

Full Text Available One of the prime activities of Indian Space Research Organisation's (ISRO Space Program is providing satellite communication services, viz., television broadcasting, mobile communication, cyclone disaster warning and rescue operations etc. so as to improve their economic conditions, disseminate technical / scientific knowledge to improve the agriculture production and education for rural people of India. ISRO, along with National Aeronautical and Space Administration (NASA conducted experimental satellite communication project i.e. Satellite Instructional Television Experiment (SITE using NASA’s Advanced Telecommunication Satellite (i.e. ATS 6 with an objective to educate poor people of India via satellite broadcasting in 1975 and 1976, covering more than 2600 villages in six states of India and territories. Over the years India built communication satellites indigenously to meet the communication requirements of India. This has further lead to launch of an exclusive satellite from ISRO for educational purposes i.e. EDUSAT in 2004 through which rich audio-video content is transmitted / received, recreating virtual classes through interactivity. Indian Institute of Remote Sensing (IIRS established in 1966, a premier institute in south East Asia in disseminating Remote Sensing (RS and Geographical Information System (GIS, mainly focusing on contact based programs. But expanded the scope with satellite based Distance Learning Programs for Universities, utilizing the dedicated communication satellite i.e. EDUSAT in 2007. IIRS conducted successfully eight Distance Learning Programs in the last five years and training more than 6000 students mainly at postgraduate level from more than 60 universities /Institutions spread across India. IIRS obtained feedback and improved the programs on the continuous basis. Expanded the scope of IIRS outreach program to train user departments tailor made in any of the applications of Remote Sensing and

Site-characterization information using LANDSAT satellite and other remote-sensing data: integration of remote-sensing data with geographic information systems. A case study in Pennsylvania

International Nuclear Information System (INIS)

Campbell, W.J.; Imhoff, M.L.; Robinson, J.; Gunther, F.; Boyd, R.; Anuta, M.

1983-06-01

The utility and cost effectiveness of incorporating digitized aircraft and satellite remote sensing data into a geographic information system for facility siting and environmental impact assessments was evaluated. This research focused on the evaluation of several types of multisource remotely sensed data representing a variety of spectral band widths and spatial resolution. High resolution aircraft photography, Landsat MSS, and 7 band Thematic Mapper Simulator (TMS) data were acquired, analyzed, and evaluated for their suitability as input to an operational geographic information system (GIS). 78 references, 59 figures, 74 tables

Characterization of precipitation features over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

Science.gov (United States)

Prat, O. P.; Nelson, B. R.

2013-12-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, surface observations, and models to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets of TMPA 3B42, CMORPH, and PERSIANN. The satellite based QPEs are compared over the concurrent period with the NCEP Stage IV product, which is a near real time product providing precipitation data at the hourly temporal scale gridded at a nominal 4-km spatial resolution. In addition, remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model), which provides gridded precipitation estimates that are used as a baseline for multi-sensor QPE products comparison. The comparisons are performed at the annual, seasonal, monthly, and daily scales with focus on selected river basins (Southeastern US, Pacific Northwest, Great Plains). While, unconditional annual rain rates present a satisfying agreement between all products, results suggest that satellite QPE datasets exhibit important biases in particular at higher rain rates (≥4 mm/day). Conversely, on seasonal scales differences between remotely sensed data and ground surface observations can be greater than 50% and up to 90% for low daily accumulation (≤1 mm/day) such as in the Western US (summer) and Central US (winter). The conditional analysis performed using different daily rainfall accumulation thresholds (from low rainfall intensity to intense precipitation) shows that while intense events measured at the ground are infrequent (around 2% for daily accumulation above 2 inches/day), remotely sensed products displayed differences from 20-50% and up to 90-100%. A discussion on the impact of differing spatial and temporal resolutions with respect to the datasets ability to capture extreme

Project MEDSAT: The design of a remote sensing platform for malaria research and control

Science.gov (United States)

1991-04-01

Project MEDSAT was proposed with the specific goal of designing a satellite to remotely sense pertinent information useful in establishing strategies to control malaria. The 340 kg MEDSAT satellite is to be inserted into circular earth orbit aboard the Pegasus Air-Launched Space Booster at an inclination of 21 degrees and an altitude of 473 km. It is equipped with a synthetic aperture radar and a visible thermal/infrared sensor to remotely sense conditions at the target area of Chiapas, Mexico. The orbit is designed so that MEDSAT will pass over the target site twice each day. The data from each scan will be downlinked to Hawaii for processing, resulting in maps indicating areas of high malaria risk. These will be distributed to health officials at the target site. A relatively inexpensive launch by Pegasus and a design using mainly proven, off-the-shelf technology permit a low mission cost, while innovations in the satellite controls and the scientific instruments allow a fairly complex mission.

Satellite remote sensing of limnological indicators of global change

International Nuclear Information System (INIS)

Wynne, R.H.; Lillesand, T.M.

1991-01-01

The paper examines the general hypothesis that large-scale and long-term trends in lake ice formation and breakup, along with changes in the optical properties of lakes, can serve as robust integrated measures of regional and global climate change. Recent variation in the periodicity of lake ice formation and breakup is investigated using the AVHRR aboard the NOAA/TIROS series of polar orbiting satellites. The study area consists of 44 lakes and reservoirs with a surface area of greater than 1000 hectares in Wisconsin. The utility of AVHRR for lake ice detection with high temporal resolution is demonstrated, the relationship between ice phenology and periodicity with lake morphometry for the lakes in the study is elucidated, and remotely sensed measures of ice periodicity are correlated with local and regional temperature trends. 31 refs

Experimental design for the evaluation of high-T(sub c) superconductive thermal bridges in a sensor satellite

Science.gov (United States)

Scott, Elaine P.; Lee, Kasey M.

1994-01-01

Infrared sensor satellites, which consist of cryogenic infrared sensor detectors, electrical instrumentation, and data acquisition systems, are used to monitor the conditions of the earth's upper atmosphere in order to evaluate its present and future changes. Currently, the electrical connections (instrumentation), which act as thermal bridges between the cryogenic infrared sensor and the significantly warmer data acquisition unit of the sensor satellite system, constitute a significant portion of the heat load on the cryogen. As a part of extending the mission life of the sensor satellite system, the researchers at the National Aeronautics and Space Administration's Langley Research Center (NASA-LaRC) are evaluating the effectiveness of replacing the currently used manganin wires with high-temperature superconductive (HTS) materials as the electrical connections (thermal bridges). In conjunction with the study being conducted at NASA-LaRC, the proposed research is to design a space experiment to determine the thermal savings on a cryogenic subsystem when manganin leads are replaced by HTS leads printed onto a substrate with a low thermal conductivity, and to determine the thermal conductivities of HTS materials. The experiment is designed to compare manganin wires with two different types of superconductors on substrates by determining the heat loss by the thermal bridges and providing temperature measurements for the estimation of thermal conductivity. A conductive mathematical model has been developed and used as a key tool in the design process and subsequent analysis.

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

Science.gov (United States)

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

2016-11-15

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

Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research

Science.gov (United States)

Maxwell, S.K.; Meliker, J.R.; Goovaerts, P.

2010-01-01

In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.

The Sensor Management for Applied Research Technologies (SMART) Project

Science.gov (United States)

Goodman, Michael; Jedlovec, Gary; Conover, Helen; Botts, Mike; Robin, Alex; Blakeslee, Richard; Hood, Robbie; Ingenthron, Susan; Li, Xiang; Maskey, Manil;

Two fast temperature sensors for probing of the atmospheric boundary layer using small remotely piloted aircraft (RPA)

Science.gov (United States)

Wildmann, N.; Mauz, M.; Bange, J.

2013-08-01

Two types of temperature sensors are designed and tested: a thermocouple and a fine wire resistance thermometer. The intention of this study is to figure out which kind of measurement principle is in general more suited for atmospheric boundary layer meteorology with small remotely piloted aircraft (RPA). The sensors are calibrated in a NIST traceable climate chamber and validated in flight against tower measurements, radiosondes and remote sensing. The sensors have a measurement range of at least -10-50 °C, an absolute RMS error of less than ±0.2 K which is stable over the lifetime of the sensors, and a resolution of about 0.01 K. Both devices are tested for typical errors like radiation error and adiabatic heating, as well as for their dynamic response. Spectral resolutions of up to approximately 10 Hz can be obtained with both sensors, which makes them suitable for turbulence measurement. Their low cost of less than 100 EUR in pure hardware is a major advantage for research with small RPA.

Two fast temperature sensors for probing of the atmospheric boundary layer using small remotely piloted aircraft (RPA

Directory of Open Access Journals (Sweden)

N. Wildmann

2013-08-01

Full Text Available Two types of temperature sensors are designed and tested: a thermocouple and a fine wire resistance thermometer. The intention of this study is to figure out which kind of measurement principle is in general more suited for atmospheric boundary layer meteorology with small remotely piloted aircraft (RPA. The sensors are calibrated in a NIST traceable climate chamber and validated in flight against tower measurements, radiosondes and remote sensing. The sensors have a measurement range of at least −10–50 °C, an absolute RMS error of less than ±0.2 K which is stable over the lifetime of the sensors, and a resolution of about 0.01 K. Both devices are tested for typical errors like radiation error and adiabatic heating, as well as for their dynamic response. Spectral resolutions of up to approximately 10 Hz can be obtained with both sensors, which makes them suitable for turbulence measurement. Their low cost of less than 100 EUR in pure hardware is a major advantage for research with small RPA.

Observational Constraints on Cloud Feedbacks: The Role of Active Satellite Sensors

Science.gov (United States)

Winker, David; Chepfer, Helene; Noel, Vincent; Cai, Xia

2017-11-01

Cloud profiling from active lidar and radar in the A-train satellite constellation has significantly advanced our understanding of clouds and their role in the climate system. Nevertheless, the response of clouds to a warming climate remains one of the largest uncertainties in predicting climate change and for the development of adaptions to change. Both observation of long-term changes and observational constraints on the processes responsible for those changes are necessary. We review recent progress in our understanding of the cloud feedback problem. Capabilities and advantages of active sensors for observing clouds are discussed, along with the importance of active sensors for deriving constraints on cloud feedbacks as an essential component of a global climate observing system.

Relation of NDVI obtained from different remote sensing at different space and resolutions sensors in Spanish Dehesas

Science.gov (United States)

Escribano Rodríguez, Juan; Tarquis, Ana M.; Saa-Requejo, Antonio; Díaz-Ambrona, Carlos G. H.

2015-04-01

Satellite data are an important source of information and serve as monitoring crops on large scales. There are several indexes, but the most used for monitoring vegetation is NDVI (Normalized Difference Vegetation Index), calculated from the spectral bands of red (RED) and near infrared (NIR), obtaining the value according to relationship: [(NIR - RED) / (NIR + RED)]. During the years 2010-2013 monthly monitoring was conducted in three areas of Spain (Salamanca, Caceres and Cordoba). Pasture plots were selected and satellite images of two different sensors, DEIMOS-1 and MODIS were obtained. DEIMOS-1 is based on the concept Microsat-100 from Surrey. It is designed for imaging the Earth with a resolution good enough to study terrestrial vegetation cover (20x20 m), although with a wide range of visual field (600 km) to get those images with high temporal resolution. By contrast, MODIS images present a much lower spatial resolution (500x500 m). Indices obtained from both sensors to the same area and date are compared and the results show r2 = 0.56; r2 = 0.65 and r2 = 0.90 for the areas of Salamanca, Cáceres and Cordoba respectively. According to the results obtained show that the NDVI obtained by MODIS is slightly larger than that obtained by the sensor for DEIMOS for same time and area. References J.A. Escribano, C.G.H. Diaz-Ambrona, L. Recuero, M. Huesca, V. Cicuendez, A. Palacios-Orueta y A.M. Tarquis. Aplicacion de Indices de Vegetacion para evaluar la falta de produccion de pastos y montaneras en dehesas. I Congreso Iberico de la Dehesa y el Montado. 6-7 Noviembre, 2013, Badajoz. J.A. Escribano Rodriguez, A.M. Tarquis, C.G. Hernandez Diaz-Ambrona. Pasture Drought Insurance Based on NDVI and SAVI. Geophysical Research Abstracts, 14, EGU2012-13945, 2012. EGU General Assembly 2012. Juan Escribano Rodriguez, Carmelo Alonso, Ana Maria Tarquis, Rosa Maria Benito, Carlos Hernandez Diaz-Ambrona. Comparison of NDVI fields obtained from different remote sensors

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 1: A cloud ensemble/radiative parameterization for sensor response (report version)

Science.gov (United States)

Olson, William S.; Raymond, William H.

1990-01-01

The physical retrieval of geophysical parameters based upon remotely sensed data requires a sensor response model which relates the upwelling radiances that the sensor observes to the parameters to be retrieved. In the retrieval of precipitation water contents from satellite passive microwave observations, the sensor response model has two basic components. First, a description of the radiative transfer of microwaves through a precipitating atmosphere must be considered, because it is necessary to establish the physical relationship between precipitation water content and upwelling microwave brightness temperature. Also the spatial response of the satellite microwave sensor (or antenna pattern) must be included in the description of sensor response, since precipitation and the associated brightness temperature field can vary over a typical microwave sensor resolution footprint. A 'population' of convective cells, as well as stratiform clouds, are simulated using a computationally-efficient multi-cylinder cloud model. Ensembles of clouds selected at random from the population, distributed over a 25 km x 25 km model domain, serve as the basis for radiative transfer calculations of upwelling brightness temperatures at the SSM/I frequencies. Sensor spatial response is treated explicitly by convolving the upwelling brightness temperature by the domain-integrated SSM/I antenna patterns. The sensor response model is utilized in precipitation water content retrievals.

Regional geology mapping using satellite-based remote sensing approach in Northern Victoria Land, Antarctica

Science.gov (United States)

Pour, Amin Beiranvand; Park, Yongcheol; Park, Tae-Yoon S.; Hong, Jong Kuk; Hashim, Mazlan; Woo, Jusun; Ayoobi, Iman

2018-06-01

Satellite remote sensing imagery is especially useful for geological investigations in Antarctica because of its remoteness and extreme environmental conditions that constrain direct geological survey. The highest percentage of exposed rocks and soils in Antarctica occurs in Northern Victoria Land (NVL). Exposed Rocks in NVL were part of the paleo-Pacific margin of East Gondwana during the Paleozoic time. This investigation provides a satellite-based remote sensing approach for regional geological mapping in the NVL, Antarctica. Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) datasets were used to extract lithological-structural and mineralogical information. Several spectral-band ratio indices were developed using Landsat-8 and ASTER bands and proposed for Antarctic environments to map spectral signatures of snow/ice, iron oxide/hydroxide minerals, Al-OH-bearing and Fe, Mg-OH and CO3 mineral zones, and quartz-rich felsic and mafic-to-ultramafic lithological units. The spectral-band ratio indices were tested and implemented to Level 1 terrain-corrected (L1T) products of Landsat-8 and ASTER datasets covering the NVL. The surface distribution of the mineral assemblages was mapped using the spectral-band ratio indices and verified by geological expeditions and laboratory analysis. Resultant image maps derived from spectral-band ratio indices that developed in this study are fairly accurate and correspond well with existing geological maps of the NVL. The spectral-band ratio indices developed in this study are especially useful for geological investigations in inaccessible locations and poorly exposed lithological units in Antarctica environments.

Unmanned Aerial Systems and Spectroscopy for Remote Sensing Applications in Archaeology

Science.gov (United States)

Themistocleous, K.; Agapiou, A.; Cuca, B.; Hadjimitsis, D. G.

2015-04-01

Remote sensing has open up new dimensions in archaeological research. Although there has been significant progress in increasing the resolution of space/aerial sensors and image processing, the detection of the crop (and soil marks) formations, which relate to buried archaeological remains, are difficult to detect since these marks may not be visible in the images if observed over different period or at different spatial/spectral resolution. In order to support the improvement of earth observation remote sensing technologies specifically targeting archaeological research, a better understanding of the crop/soil marks formation needs to be studied in detail. In this paper the contribution of both Unmanned Aerial Systems as well ground spectroradiometers is discussed in a variety of examples applied in the eastern Mediterranean region (Cyprus and Greece) as well in Central Europe (Hungary). In- situ spectroradiometric campaigns can be applied for the removal of atmospheric impact to simultaneous satellite overpass images. In addition, as shown in this paper, the systematic collection of ground truth data prior to the satellite/aerial acquisition can be used to detect the optimum temporal and spectral resolution for the detection of stress vegetation related to buried archaeological remains. Moreover, phenological studies of the crops from the area of interest can be simulated to the potential sensors based on their Relative Response Filters and therefore prepare better the satellite-aerial campaigns. Ground data and the use of Unmanned Aerial Systems (UAS) can provide an increased insight for studying the formation of crop and soil marks. New algorithms such as vegetation indices and linear orthogonal equations for the enhancement of crop marks can be developed based on the specific spectral characteristics of the area. As well, UAS can be used for remote sensing applications in order to document, survey and model cultural heritage and archaeological sites.

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

Science.gov (United States)

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

2016-07-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a "simulated radiance" product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land-ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers.This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled.In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model subgrid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to

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

Science.gov (United States)

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

2016-01-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to

POLARIMETRIC REMOTE SENSING OF ATMOSPHERIC PARTICULATE POLLUTANTS

Directory of Open Access Journals (Sweden)

Z. Li

2018-04-01

Full Text Available Atmospheric particulate pollutants not only reduce atmospheric visibility, change the energy balance of the troposphere, but also affect human and vegetation health. For monitoring the particulate pollutants, we establish and develop a series of inversion algorithms based on polarimetric remote sensing technology which has unique advantages in dealing with atmospheric particulates. A solution is pointed out to estimate the near surface PM2.5 mass concentrations from full remote sensing measurements including polarimetric, active and infrared remote sensing technologies. It is found that the mean relative error of PM2.5 retrieved by full remote sensing measurements is 35.5 % in the case of October 5th 2013, improved to a certain degree compared to previous studies. A systematic comparison with the ground-based observations further indicates the effectiveness of the inversion algorithm and reliability of results. A new generation of polarized sensors (DPC and PCF, whose observation can support these algorithms, will be onboard GF series satellites and launched by China in the near future.

Remote Sensing by Satellite for Environmental Education: A Survey and a Proposal for Teaching at Upper Secondary and University Level.

Science.gov (United States)

Bosler, Ulrich

Knowledge of the environment has grown to such an extent that information technology (IT) is essential to make sense of the available data. An example of this is remote sensing by satellite. In recent years this field has grown in importance and remote sensing is used for a range of uses including the automatic survey of wheat yields in North…

Remote Sensing of Suspended Sediment Dynamics in the Mississippi Sound

Science.gov (United States)

Merritt, D. N.; Skarke, A. D.; Silwal, S.; Dash, P.

2016-02-01

The Mississippi Sound is a semi-enclosed estuary between the coast of Mississippi and a chain of offshore barrier islands with relatively shallow water depths and high marine biodiversity that is wildly utilized for commercial fishing and public recreation. The discharge of sediment-laden rivers into the Mississippi Sound and the adjacent Northern Gulf of Mexico creates turbid plumes that can extend hundreds of square kilometers along the coast and persist for multiple days. The concentration of suspended sediment in these coastal waters is an important parameter in the calculation of regional sediment budgets as well as analysis of water-quality factors such as primary productivity, nutrient dynamics, and the transport of pollutants as well as pathogens. The spectral resolution, sampling frequency, and regional scale spatial domain associated with satellite based sensors makes remote sensing an ideal tool to monitor suspended sediment dynamics in the Northern Gulf of Mexico. Accordingly, the presented research evaluates the validity of published models that relate remote sensing reflectance with suspended sediment concentrations (SSC), for similar environmental settings, with 51 in situ observations of SSC from the Mississippi Sound. Additionally, regression analysis is used to correlate additional in situ observations of SSC in Mississippi Sound with coincident observations of visible and near-infrared band reflectance collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Aqua satellite, in order to develop a site-specific empirical predictive model for SSC. Finally, specific parameters of the sampled suspended sediment such as grain size and mineralogy are analyzed in order to quantify their respective contributions to total remotely sensed reflectance.

Observability of satellite launcher navigation with INS, GPS, attitude sensors and reference trajectory

Science.gov (United States)

Beaudoin, Yanick; Desbiens, André; Gagnon, Eric; Landry, René

2018-01-01

The navigation system of a satellite launcher is of paramount importance. In order to correct the trajectory of the launcher, the position, velocity and attitude must be known with the best possible precision. In this paper, the observability of four navigation solutions is investigated. The first one is the INS/GPS couple. Then, attitude reference sensors, such as magnetometers, are added to the INS/GPS solution. The authors have already demonstrated that the reference trajectory could be used to improve the navigation performance. This approach is added to the two previously mentioned navigation systems. For each navigation solution, the observability is analyzed with different sensor error models. First, sensor biases are neglected. Then, sensor biases are modelled as random walks and as first order Markov processes. The observability is tested with the rank and condition number of the observability matrix, the time evolution of the covariance matrix and sensitivity to measurement outlier tests. The covariance matrix is exploited to evaluate the correlation between states in order to detect structural unobservability problems. Finally, when an unobservable subspace is detected, the result is verified with theoretical analysis of the navigation equations. The results show that evaluating only the observability of a model does not guarantee the ability of the aiding sensors to correct the INS estimates within the mission time. The analysis of the covariance matrix time evolution could be a powerful tool to detect this situation, however in some cases, the problem is only revealed with a sensitivity to measurement outlier test. None of the tested solutions provide GPS position bias observability. For the considered mission, the modelling of the sensor biases as random walks or Markov processes gives equivalent results. Relying on the reference trajectory can improve the precision of the roll estimates. But, in the context of a satellite launcher, the roll

Fault Diagnosis for Satellite Sensors and Actuators using Nonlinear Geometric Approach and Adaptive Observers

DEFF Research Database (Denmark)

Baldi, P.; Blanke, Mogens; Castaldi, P.

2018-01-01

This paper presents a novel scheme for diagnosis of faults affecting sensors that measure the satellite attitude, body angular velocity, flywheel spin rates, and defects in control torques from reaction wheel motors. The proposed methodology uses adaptive observers to provide fault estimates that...

Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

International Nuclear Information System (INIS)

Boresjoe Bronge, Laine

2004-03-01

Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given

Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

Energy Technology Data Exchange (ETDEWEB)

Boresjoe Bronge, Laine [SwedPower AB, Stockholm (Sweden)

2004-03-01

Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given.

Satellite imagery and the Department of Safeguards

International Nuclear Information System (INIS)

Chitumbo, K.; Bunney, J.; Leve, G.; Robb, S.

2001-01-01

Full text: The presentation examines some of the challenges the Satellite Imagery and Analysis Laboratory (SIAL) is facing in supporting Strengthened Safeguards. It focuses on the analytical process, starting with specifying initial tasking and continuing through to end products that are a direct result of in-house analysis. In addition it also evaluates the advantages and disadvantages of SIAL's mission and introduces external forces that the agency must consider, but cannot itself, predict or control. Although SIAL's contribution to tasks relating to Article 2a(iii) of the Additional Protocol are known and are presently of great benefit to operations areas, this is only one aspect of its work. SIAL's ability to identify and analyze historical satellite imagery data has the advantage of permitting operations to take a more in depth view of a particular area of interest's (AOI) development, and thus may permit operations to confirm or refute specific assertions relating to the AOI's function or abilities. These assertions may originate in-house or may be open source reports the agency feels it is obligated to explore. SIAL's mission is unique in the world of imagery analysis. Its aim is to support all operations areas equally and in doing so it must maintain global focus. The task is tremendous, but the resultant coverage and concentration of unique expertise will allow SIAL to develop and provide operations with datasets that can be exploited in standalone mode or be incorporated into new cutting edge tools to be developed in SGIT. At present SIAL relies on two remote sensors, IKONOS-2 and EROS-AI, for present high- resolution imagery data and is using numerous sources for historical, pre 1999, data. A multiplicity of sources for high-resolution data is very important to SIAL, but is something that it cannot influence. It is hoped that the planned launch of two new sensors by Summer 2002 will be successful and will offer greater flexibility for image collection

The Federal Oil Spill Team for Emergency Response Remote Sensing (FOSTERRS)

Science.gov (United States)

Stough, T.; Jones, C. E.; Leifer, I.; Lindsay, F. E.; Murray, J. J.; Ramirez, E. M.; Salemi, A.; Streett, D.

2014-12-01

Oil spills can cause enormous ecological and economic devastation, necessitating application of the best science and technology available, for which remote sensing plays a critical role in detection and monitoring of oil spills. The FOSTERRS interagency working group seeks to ensure that during an oil spill, remote sensing assets (satellite/aircraft) and analysis techniques are quickly, effectively and seamlessly available to oil spills responders. FOSTERRS enables cooperation between agencies with core environmental remote sensing assets and capabilities and academic and industry experts to act as an oil spill remote sensing information clearinghouse. The US government and its collaborators have a broad variety of aircraft and satellite sensors, imagery interrogation techniques and other technology that can provide indispensable remote sensing information to agencies, emergency responders and the public during an oil spill. Specifically, FOSTERRS will work to ensure that (1) suitable aircraft and satellite imagery and radar observations are quickly made available in a manner that can be integrated into oil spill detection and mitigation efforts, (2) existing imagery interrogation techniques are in the hands of those who will provide the 24 x 7 operational support and (3) efforts are made to develop new technology where the existing techniques do not provide oil spills responders with important information they need. The FOSTERRS mission goal places it in an ideal place for identification of critical technological needs, and identifying bottlenecks in technology acceptance. The core FOSTERRS team incorporates representation for operations and science for agencies with relevant instrumental and platform assets (NASA, NOAA, USGS, NRL). FOSTERRS membership will open to a wide range of end-user agencies and planned observer status from industry and academic experts, and eventually international partners. Through these collaborations, FOSTERRS facilitates interagency

Space-Derived Imagery and a Commercial Remote Sensing Industry: Impossible Dream or Inevitable Reality?

Science.gov (United States)

Murray, Felsher

Landsat-1 was launched in 1972 as a research satellite. Many of us viewed this satellite as a precursor to remote sensing "commercialization." Indeed since that time, the birth, growth and maturation of a remote sensing "industry" has been an ongoing objective for much of the U.S. private sector engaged in space and ground-segment activities related to the acquisition, analysis, and dissemination of imagery. In September 1999 a U.S. commercial entity, Space Imaging, Inc. launched its 1-meter pan/4-meter multispectral IKONOS sensor. DigitalGlobe, Inc. (nee EarthWatch, Inc.) matched this feat in October 2001. Thus, a full 30 years later, we are finally on the brink of building a true remote sensing information industry based on the global availability of competitively-priced space- derived imagery of the Earth. The upcoming availability of similar imagery from non-U.S. sources as ImageSat and U.S. sources as ORBIMAGE will only strengthen that reality. However, a remote sensing industry can only grow by allowing these entities (in times of peace) unencumbered access to a world market. And that market continues to expand -- up 11% in 2001, with gross revenues of U.S. commercial remote sensing firms alone reaching 2.44 billion, according to a joint NASA/ASPRS industry survey. However, the 30-year gap between the research-labeled Landsat-1 and our current commercial successes was not technology-driven. That lacuna was purely political -- driven by valid concerns related to national security. Although the world's governments have cooperated thoroughly and completely in areas related to satellite telecommunications, cooperation in space-derived image information is still today done cautiously and on a case-by-case basis -- and then only for science- based undertakings. It is still a fact that, except for the United States, all other Earth-imaging satellites/sensors flying today are owned, operated, and their products disseminated, by national governments -- and not private

High-frequency remote monitoring of large lakes with MODIS 500 m imagery

Science.gov (United States)

McCullough, Ian M.; Loftin, Cynthia S.; Sader, Steven A.

2012-01-01

Satellite-based remote monitoring programs of regional lake water quality largely have relied on Landsat Thematic Mapper (TM) owing to its long image archive, moderate spatial resolution (30 m), and wide sensitivity in the visible portion of the electromagnetic spectrum, despite some notable limitations such as temporal resolution (i.e., 16 days), data pre-processing requirements to improve data quality, and aging satellites. Moderate-Resolution Imaging Spectroradiometer (MODIS) sensors on Aqua/Terra platforms compensate for these shortcomings, although at the expense of spatial resolution. We developed and evaluated a remote monitoring protocol for water clarity of large lakes using MODIS 500 m data and compared MODIS utility to Landsat-based methods. MODIS images captured during May–September 2001, 2004 and 2010 were analyzed with linear regression to identify the relationship between lake water clarity and satellite-measured surface reflectance. Correlations were strong (R² = 0.72–0.94) throughout the study period; however, they were the most consistent in August, reflecting seasonally unstable lake conditions and inter-annual differences in algal productivity during the other months. The utility of MODIS data in remote water quality estimation lies in intra-annual monitoring of lake water clarity in inaccessible, large lakes, whereas Landsat is more appropriate for inter-annual, regional trend analyses of lakes ≥ 8 ha. Model accuracy is improved when ancillary variables are included to reflect seasonal lake dynamics and weather patterns that influence lake clarity. The identification of landscape-scale drivers of regional water quality is a useful way to supplement satellite-based remote monitoring programs relying on spectral data alone.

Remotely Piloted Aircraft Systems and a Wireless Sensors Network for Radiological Accidents

Directory of Open Access Journals (Sweden)

A. Reyes-Muñoz

2016-01-01

Full Text Available In critical radiological situations, the real time information that we could get from the disaster area becomes of great importance. However, communication systems could be affected after a radiological accident. The proposed network in this research consists of distributed sensors in charge of collecting radiological data and ground vehicles that are sent to the nuclear plant at the moment of the accident to sense environmental and radiological information. Afterwards, data would be analyzed in the control center. Collected data by sensors and ground vehicles would be delivered to a control center using Remotely Piloted Aircraft Systems (RPAS as a message carrier. We analyze the pairwise contacts, as well as visiting times, data collection, capacity of the links, size of the transmission window of the sensors, and so forth. All this calculus was made analytically and compared via network simulations.

Non supervised classification of vegetable covers on digital images of remote sensors: Landsat - ETM+

International Nuclear Information System (INIS)

Arango Gutierrez, Mauricio; Branch Bedoya, John William; Botero Fernandez, Veronica

2005-01-01

The plant species diversity in Colombia and the lack of inventory of them suggests the need for a process that facilitates the work of investigators in these disciplines. Remote satellite sensors such as landsat ETM+ and non-supervised artificial intelligence techniques, such as self-organizing maps - SOM, could provide viable alternatives for advancing in the rapid obtaining of information related to zones with different vegetative covers in the national geography. The zone proposed for the study case was classified in a supervised form by the method of maximum likelihood by another investigation in forest sciences and eight types of vegetative covers were discriminated. This information served as a base line to evaluate the performance of the non-supervised sort keys isodata and SOM. However, the information that the images provided had to first be purified according to the criteria of use and data quality, so that adequate information for these non-supervised methods were used. For this, several concepts were used; such as, image statistics, spectral behavior of the vegetative communities, sensor characteristics and the average divergence that allowed to define the best bands and their combinations. Principal component analysis was applied to these to reduce to the number of data while conserving a large percentage of the information. The non-supervised techniques were applied to these purified data, modifying some parameters that could yield a better convergence of the methods. The results obtained were compared with the supervised classification via confusion matrices and it was concluded that there was not a good convergence of non-supervised classification methods with this process for the case of vegetative covers

Radar Remote Sensing

Science.gov (United States)

Rosen, Paul A.

2012-01-01

This lecture was just a taste of radar remote sensing techniques and applications. Other important areas include Stereo radar grammetry. PolInSAR for volumetric structure mapping. Agricultural monitoring, soil moisture, ice-mapping, etc. The broad range of sensor types, frequencies of observation and availability of sensors have enabled radar sensors to make significant contributions in a wide area of earth and planetary remote sensing sciences. The range of applications, both qualitative and quantitative, continue to expand with each new generation of sensors.

Human-factors-based implementation of the remote characterization system high-level control station

International Nuclear Information System (INIS)

Noakes, M.W.; Richardson, B.S.; Rowe, J.C.; Draper, J.V.; Sandness, G.R.

1993-01-01

The detection and characterization of buried objects and materials is an important first step in the restoration of the numerous US Department of Energy (DOE) and US Department of Defense waste disposal sites. DOE, through its Environmental Restoration and Waste Management Robotics and Technology Development Program, has developed the Remote Characterization System (RCS) to address the needs of remote subsurfacecharacterization. The RCS consists of a low-metal-content (low-metallic-signature) remotely piloted vehicle, a high-level control station (HLCS) where operators can remotely control the vehicle and analyze real-time data from sensors, and an array of sensors that can be chosen to meet the survey task at hand. Communication between the vehicle and the base station is handled by a radio link. Site mapping is made possible through the use of geopositioning satellite data. The primary mode of vehicle operation is teleoperation, but provision has been made for semiautonomous or supervisory control that allows for automated sitesurvey on simple sites. Data analysis and display is supported for both real-time observation and postprocessing of data. The particular emphasis of this paper documents the human-factors-based design influences on the HLCS and describes the design in detail

Generating Land Surface Reflectance for the New Generation of Geostationary Satellite Sensors with the MAIAC Algorithm

Science.gov (United States)

Wang, W.; Wang, Y.; Hashimoto, H.; Li, S.; Takenaka, H.; Higuchi, A.; Lyapustin, A.; Nemani, R. R.

2017-12-01

The latest generation of geostationary satellite sensors, including the GOES-16/ABI and the Himawari 8/AHI, provide exciting capability to monitor land surface at very high temporal resolutions (5-15 minute intervals) and with spatial and spectral characteristics that mimic the Earth Observing System flagship MODIS. However, geostationary data feature changing sun angles at constant view geometry, which is almost reciprocal to sun-synchronous observations. Such a challenge needs to be carefully addressed before one can exploit the full potential of the new sources of data. Here we take on this challenge with Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, recently developed for accurate and globally robust applications like the MODIS Collection 6 re-processing. MAIAC first grids the top-of-atmosphere measurements to a fixed grid so that the spectral and physical signatures of each grid cell are stacked ("remembered") over time and used to dramatically improve cloud/shadow/snow detection, which is by far the dominant error source in the remote sensing. It also exploits the changing sun-view geometry of the geostationary sensor to characterize surface BRDF with augmented angular resolution for accurate aerosol retrievals and atmospheric correction. The high temporal resolutions of the geostationary data indeed make the BRDF retrieval much simpler and more robust as compared with sun-synchronous sensors such as MODIS. As a prototype test for the geostationary-data processing pipeline on NASA Earth Exchange (GEONEX), we apply MAIAC to process 18 months of data from Himawari 8/AHI over Australia. We generate a suite of test results, including the input TOA reflectance and the output cloud mask, aerosol optical depth (AOD), and the atmospherically-corrected surface reflectance for a variety of geographic locations, terrain, and land cover types. Comparison with MODIS data indicates a general agreement between the retrieved surface reflectance

Real-Time and Seamless Monitoring of Ground-Level PM2.5 Using Satellite Remote Sensing

Science.gov (United States)

Li, Tongwen; Zhang, Chengyue; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Liangpei

2018-04-01

Satellite remote sensing has been reported to be a promising approach for the monitoring of atmospheric PM2.5. However, the satellite-based monitoring of ground-level PM2.5 is still challenging. First, the previously used polar-orbiting satellite observations, which can be usually acquired only once per day, are hard to monitor PM2.5 in real time. Second, many data gaps exist in satellitederived PM2.5 due to the cloud contamination. In this paper, the hourly geostationary satellite (i.e., Harawari-8) observations were adopted for the real-time monitoring of PM2.5 in a deep learning architecture. On this basis, the satellite-derived PM2.5 in conjunction with ground PM2.5 measurements are incorporated into a spatio-temporal fusion model to fill the data gaps. Using Wuhan Urban Agglomeration as an example, we have successfully derived the real-time and seamless PM2.5 distributions. The results demonstrate that Harawari-8 satellite-based deep learning model achieves a satisfactory performance (out-of-sample cross-validation R2 = 0.80, RMSE = 17.49 μg/m3) for the estimation of PM2.5. The missing data in satellite-derive PM2.5 are accurately recovered, with R2 between recoveries and ground measurements of 0.75. Overall, this study has inherently provided an effective strategy for the realtime and seamless monitoring of ground-level PM2.5.

Assessment of space sensors for ocean pollution monitoring

Science.gov (United States)

Alvarado, U. R.; Tomiyasu, K.; Gulatsi, R. L.

1980-01-01

Several passive and active microwave, as well as passive optical remote sensors, applicable to the monitoring of oil spills and waste discharges at sea, are considered. The discussed types of measurements relate to: (1) spatial distribution and properties of the pollutant, and (2) oceanic parameters needed to predict the movement of the pollutants and their impact upon land. The sensors, operating from satellite platforms at 700-900 km altitudes, are found to be useful in mapping the spread of oil in major oil spills and in addition, can be effective in producing wind and ocean parameters as inputs to oil trajectory and dispersion models. These capabilities can be used in countermeasures.

Spectral slopes of the absorption coefficient of colored dissolved and detrital material inverted from UV-visible remote sensing reflectance.

Science.gov (United States)

Wei, Jianwei; Lee, Zhongping; Ondrusek, Michael; Mannino, Antonio; Tzortziou, Maria; Armstrong, Roy

2016-03-01

The spectral slope of the absorption coefficient of colored dissolved and detrital material (CDM), S cdm (units: nm -1 ), is an important optical parameter for characterizing the absorption spectral shape of CDM. Although highly variable in natural waters, in most remote sensing algorithms, this slope is either kept as a constant or empirically modeled with multiband ocean color in the visible domain. In this study, we explore the potential of semianalytically retrieving S cdm with added ocean color information in the ultraviolet (UV) range between 360 and 400 nm. Unique features of hyperspectral remote sensing reflectance in the UV-visible wavelengths (360-500 nm) have been observed in various waters across a range of coastal and open ocean environments. Our data and analyses indicate that ocean color in the UV domain is particularly sensitive to the variation of the CDM spectral slope. Here, we used a synthesized data set to show that adding UV wavelengths to the ocean color measurements will improve the retrieval of S cdm from remote sensing reflectance considerably, while the spectral band settings of past and current satellite ocean color sensors cannot fully account for the spectral variation of remote sensing reflectance. Results of this effort support the concept to include UV wavelengths in the next generation of satellite ocean color sensors.

Remote sensing as a preliminary analysis for the detection of active tectonic structures: an application to the Albanian orogenic system

Directory of Open Access Journals (Sweden)

Andrea Favretto

2013-12-01

Full Text Available As is well known, both the traditional direct geological and geophysical survey methods used to identify geologic features are very expensive and time-consuming procedures. In this regard, remote sensing methods applied to multispectral and medium spatial resolution satellite images allow a more focused approach with respect to the more specific geologic methods. This is achieved by a preliminary land inspection carried out by the semi-automated analysis of satellite imagery. This avoids wasting resources as the geological/geophysical survey methods can be later applied only to those zones suspected of having certain tectonic activity (derived by the remotely sensed imagery. This paper will evaluate an ASTER sensor satellite image (and its derived Digital Elevation Model or DEM, in order to point out the suspected presence of active geologic structures (faults. The area in question is west – central Albania. The results of the remote sensing procedures are later compared with the established data for the same area taken by satellite images, in order to verify the reliability of the adopted method. The source of the established data has been from the bibliography.

Cross-comparison of the IRS-P6 AWiFS sensor with the L5 TM, L7 ETM+, & Terra MODIS sensors

Science.gov (United States)

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

2009-01-01

As scientists and decision makers increasingly rely on multiple Earth-observing satellites to address urgent global issues, it is imperative that they can rely on the accuracy of Earth-observing data products. This paper focuses on the crosscomparison of the Indian Remote Sensing (IRS-P6) Advanced Wide Field Sensor (AWiFS) with the Landsat 5 (L5) Thematic Mapper (TM), Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+), and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The cross-comparison was performed using image statistics based on large common areas observed by the sensors within 30 minutes. Because of the limited availability of simultaneous observations between the AWiFS and the Landsat and MODIS sensors, only a few images were analyzed. These initial results are presented. Regression curves and coefficients of determination for the top-of-atmosphere (TOA) trends from these sensors were generated to quantify the uncertainty in these relationships and to provide an assessment of the calibration differences between these sensors. ?? 2009 SPIE.

INTEGRATION OF SPATIAL INFORMATION WITH COLOR FOR CONTENT RETRIEVAL OF REMOTE SENSING IMAGES

Directory of Open Access Journals (Sweden)

Bikesh Kumar Singh

2010-08-01

Full Text Available There is rapid increase in image databases of remote sensing images due to image satellites with high resolution, commercial applications of remote sensing & high available bandwidth in last few years. The problem of content-based image retrieval (CBIR of remotely sensed images presents a major challenge not only because of the surprisingly increasing volume of images acquired from a wide range of sensors but also because of the complexity of images themselves. In this paper, a software system for content-based retrieval of remote sensing images using RGB and HSV color spaces is presented. Further, we also compare our results with spatiogram based content retrieval which integrates spatial information along with color histogram. Experimental results show that the integration of spatial information in color improves the image analysis of remote sensing data. In general, retrievals in HSV color space showed better performance than in RGB color space.

Remote Sensing Analysis Techniques and Sensor Requirements to Support the Mapping of Illegal Domestic Waste Disposal Sites in Queensland, Australia

Directory of Open Access Journals (Sweden)

Katharine Glanville

2015-10-01

Full Text Available Illegal disposal of waste is a significant management issue for contemporary governments with waste posing an economic, social, and environmental risk. An improved understanding of the distribution of illegal waste disposal sites is critical to enhance the cost-effectiveness and efficiency of waste management efforts. Remotely sensed data has the potential to address this knowledge gap. However, the literature regarding the use of remote sensing to map illegal waste disposal sites is incomplete. This paper aims to analyze existing remote sensing methods and sensors used to monitor and map illegal waste disposal sites. The purpose of this paper is to support the evaluation of existing remote sensing methods for mapping illegal domestic waste sites in Queensland, Australia. Recent advances in technology and the acquisition of very high-resolution remote sensing imagery provide an important opportunity to (1 revisit established analysis techniques for identifying illegal waste disposal sites, (2 examine the applicability of different remote sensors for illegal waste disposal detection, and (3 identify opportunities for future research to increase the accuracy of any illegal waste disposal mapping products.

Hydrological storage variations in a lake water balance, observed from multi-sensor satellite data and hydrological models.

Science.gov (United States)

Singh, Alka; Seitz, Florian; Schwatke, Christian; Guentner, Andreas

2013-04-01

Freshwater lakes and reservoirs account for 74.5% of continental water storage in surface water bodies and only 1.8% resides in rivers. Lakes and reservoirs are a key component of the continental hydrological cycle but in-situ monitoring networks are very limited either because of sparse spatial distribution of gauges or national data policy. Monitoring and predicting extreme events is very challenging in that case. In this study we demonstrate the use of optical remote sensing, satellite altimetry and the GRACE gravity field mission to monitor the lake water storage variations in the Aral Sea. Aral Sea is one of the most unfortunate examples of a large anthropogenic catastrophe. The 4th largest lake of 1960s has been decertified for more than 75% of its area due to the diversion of its primary rivers for irrigation purposes. Our study is focused on the time frame of the GRACE mission; therefore we consider changes from 2002 onwards. Continuous monthly time series of water masks from Landsat satellite data and water level from altimetry missions were derived. Monthly volumetric variations of the lake water storage were computed by intersecting a digital elevation model of the lake with respective water mask and altimetry water level. With this approach we obtained volume from two independent remote sensing methods to reduce the error in the estimated volume through least square adjustment. The resultant variations were then compared with mass variability observed by GRACE. In addition, GARCE estimates of water storage variations were compared with simulation results of the Water Gap Hydrology Model (WGHM). The different observations from all missions agree that the lake reached an absolute minimum in autumn 2009. A marked reversal of the negative trend occured in 2010 but water storage in the lake decreased again afterwards. The results reveal that water storage variations in the Aral Sea are indeed the principal, but not the only contributor to the GRACE signal of

An assessment of aerosol optical properties from remote-sensing observations and regional chemistry-climate coupled models over Europe

Science.gov (United States)

Palacios-Peña, Laura; Baró, Rocío; Baklanov, Alexander; Balzarini, Alessandra; Brunner, Dominik; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; María López-Romero, José; Montávez, Juan Pedro; Pérez, Juan Luis; Pirovano, Guido; San José, Roberto; Schröder, Wolfram; Werhahn, Johannes; Wolke, Ralf; Žabkar, Rahela; Jiménez-Guerrero, Pedro

2018-04-01

Atmospheric aerosols modify the radiative budget of the Earth due to their optical, microphysical and chemical properties, and are considered one of the most uncertain climate forcing agents. In order to characterise the uncertainties associated with satellite and modelling approaches to represent aerosol optical properties, mainly aerosol optical depth (AOD) and Ångström exponent (AE), their representation by different remote-sensing sensors and regional online coupled chemistry-climate models over Europe are evaluated. This work also characterises whether the inclusion of aerosol-radiation (ARI) or/and aerosol-cloud interactions (ACI) help improve the skills of modelling outputs.Two case studies were selected within the EuMetChem COST Action ES1004 framework when important aerosol episodes in 2010 all over Europe took place: a Russian wildfire episode and a Saharan desert dust outbreak that covered most of the Mediterranean Sea. The model data came from different regional air-quality-climate simulations performed by working group 2 of EuMetChem, which differed according to whether ARI or ACI was included or not. The remote-sensing data came from three different sensors: MODIS, OMI and SeaWIFS. The evaluation used classical statistical metrics to first compare satellite data versus the ground-based instrument network (AERONET) and then to evaluate model versus the observational data (both satellite and ground-based data).Regarding the uncertainty in the satellite representation of AOD, MODIS presented the best agreement with the AERONET observations compared to other satellite AOD observations. The differences found between remote-sensing sensors highlighted the uncertainty in the observations, which have to be taken into account when evaluating models. When modelling results were considered, a common trend for underestimating high AOD levels was observed. For the AE, models tended to underestimate its variability, except when considering a sectional approach in

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

a Semi-Empirical Topographic Correction Model for Multi-Source Satellite Images

Science.gov (United States)

Xiao, Sa; Tian, Xinpeng; Liu, Qiang; Wen, Jianguang; Ma, Yushuang; Song, Zhenwei

2018-04-01

Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.

The Short Wave Aerostat-Mounted Imager (SWAMI): A novel platform for acquiring remotely sensed data from a tethered balloon

Science.gov (United States)

Vierling, L.A.; Fersdahl, M.; Chen, X.; Li, Z.; Zimmerman, P.

2006-01-01

We describe a new remote sensing system called the Short Wave Aerostat-Mounted Imager (SWAMI). The SWAMI is designed to acquire co-located video imagery and hyperspectral data to study basic remote sensing questions and to link landscape level trace gas fluxes with spatially and temporally appropriate spectral observations. The SWAMI can fly at altitudes up to 2 km above ground level to bridge the spatial gap between radiometric measurements collected near the surface and those acquired by other aircraft or satellites. The SWAMI platform consists of a dual channel hyperspectral spectroradiometer, video camera, GPS, thermal infrared sensor, and several meteorological and control sensors. All SWAMI functions (e.g. data acquisition and sensor pointing) can be controlled from the ground via wireless transmission. Sample data from the sampling platform are presented, along with several potential scientific applications of SWAMI data.

Development of a remote spectroelectrochemical sensor for technetium as pertechnetate

Science.gov (United States)

Monk, David James

Subsurface contamination by technetium (Tc) is of particular concern in the monitoring, characterization, and remediation of underground nuclear waste storage tanks, processing areas, and associated surroundings at the Hanford Site and other U.S. DOE sites nationwide. The concern over this radioactive element arises for two reasons. First, its most common isotope, 99Tc, has an extremely long lifetime of 2.15 x 105 years. Second, it's most common chemical form in environmental conditions, pertechnetate (TcO4-), exhibits very fast migration through soils and readily presents itself to any nearby aquifer. Standard procedures of sampling and analysis in a laboratory prove to be slow and costly in the case of subsurface contamination by radioactive materials. It is highly desirable to develop sensors for these materials that possess the capability of either in-situ or on-site placement for continuous monitoring or immediate analysis of collected samples. These sensors need to possess adequate detection limit and selectivity, rapid response, reversibility (many measurements with one sensor), the ability to perform remotely, and ruggedness. This dissertation describes several areas of the continued work toward a sensor for 99Tc as TcO4-. Research initially focused on developing spectroelectrochemical instrumentation and a disposable sensing element, engineered to address the need to perform remote measurements. The instrument was then tested using samples containing 99Tc, resulting in the development of ancillary equipment and techniques to address concerns associated with performing experiments on radioactive materials. In these tests, the electrochemistry of TcO4 - was demonstrated to be irreversible. Electrochemical reduction of TcO4- on a bare or polymer modified electrode resulted in the continuous build up of technetium oxide (TcO2) on the electrode surface. This TcO2 formed in visual quantities in these films during electrochemistry, and proved to be non-ideal for

Application of Remote Sensing in Building Damages Assessment after Moderate and Strong Earthquake

Science.gov (United States)

Tian, Y.; Zhang, J.; Dou, A.

2003-04-01

- Earthquake is a main natural disaster in modern society. However, we still cannot predict the time and place of its occurrence accurately. Then it is of much importance to survey the damages information when an earthquake occurs, which can help us to mitigate losses and implement fast damage evaluation. In this paper, we use remote sensing techniques for our purposes. Remotely sensed satellite images often view a large scale of land at a time. There are several kinds of satellite images, which of different spatial and spectral resolutions. Landsat-4/5 TM sensor can view ground at 30m resolution, while Landsat-7 ETM Plus has a resolution of 15m in panchromatic waveband. SPOT satellite can provide images with higher resolutions. Those images obtained pre- and post-earthquake can help us greatly in identifying damages of moderate and large-size buildings. In this paper, we bring forward a method to implement quick damages assessment by analyzing both pre- and post-earthquake satellite images. First, those images are geographically registered together with low RMS (Root Mean Square) error. Then, we clip out residential areas by overlaying images with existing vector layers through Geographic Information System (GIS) software. We present a new change detection algorithm to quantitatively identify damages degree. An empirical or semi-empirical model is then established by analyzing the real damage degree and changes of pixel values of the same ground objects. Experimental result shows that there is a good linear relationship between changes of pixel values and ground damages, which proves the potentials of remote sensing in post-quake fast damage assessment. Keywords: Damages Assessment, Earthquake Hazard, Remote Sensing

Wireless Sensor Network Handles Image Data

Science.gov (United States)

2008-01-01

To relay data from remote locations for NASA s Earth sciences research, Goddard Space Flight Center contributed to the development of "microservers" (wireless sensor network nodes), which are now used commercially as a quick and affordable means to capture and distribute geographical information, including rich sets of aerial and street-level imagery. NASA began this work out of a necessity for real-time recovery of remote sensor data. These microservers work much like a wireless office network, relaying information between devices. The key difference, however, is that instead of linking workstations within one office, the interconnected microservers operate miles away from one another. This attribute traces back to the technology s original use: The microservers were originally designed for seismology on remote glaciers and ice streams in Alaska, Greenland, and Antarctica-acquiring, storing, and relaying data wirelessly between ground sensors. The microservers boast three key attributes. First, a researcher in the field can establish a "managed network" of microservers and rapidly see the data streams (recovered wirelessly) on a field computer. This rapid feedback permits the researcher to reconfigure the network for different purposes over the course of a field campaign. Second, through careful power management, the microservers can dwell unsupervised in the field for up to 2 years, collecting tremendous amounts of data at a research location. The third attribute is the exciting potential to deploy a microserver network that works in synchrony with robotic explorers (e.g., providing ground truth validation for satellites, supporting rovers as they traverse the local environment). Managed networks of remote microservers that relay data unsupervised for up to 2 years can drastically reduce the costs of field instrumentation and data rec

Aircraft and satellite remote sensing of desert soils and landscapes

Science.gov (United States)

Petersen, G. W.; Connors, K. F.; Miller, D. A.; Day, R. L.; Gardner, T. W.

1987-01-01

Remote sensing data on desert soils and landscapes, obtained by the Landsat TM, Heat Capacity Mapping Mission (HCMM), Simulated SPOT, and Thermal IR Multispectral Scanner (TIMS) aboard an aircraft, are discussed together with the analytical techniques used in the studies. The TM data for southwestern Nevada were used to discriminate among the alluvial fan deposits with different degrees of desert pavement and varnish, and different vegetation cover. Thermal-IR data acquired from the HCMM satellite were used to map the spatial distribution of diurnal surface temperatures and to estimate mean annual soil temperatures in central Utah. Simulated SPOT data for northwestern New Mexico identified geomorphic features, such as differences in eolian sand cover and fluvial incision, while the TIMS data depicted surface geologic features of the Saline Valley in California.

Technical implementation in support of the IAEA's remote monitoring field trial at the Oak Ridge Y-12 Plant

International Nuclear Information System (INIS)

Corbell, B.H.; Moran, B.W.; Pickett, C.A.; Whitaker, J.M.; Resnik, W.; Landreth, D.

1996-01-01

A remote monitoring system (RMS) field trial will be conducted for the International Atomic Energy Agency (IAEA) on highly enriched uranium materials in a vault at the Oak Ridge Y-12 Plant. Remote monitoring technologies are being evaluated to verify their capability to enhance the effectiveness and timeliness of IAEA safeguards in storage facilities while reducing the costs of inspections and burdens on the operator. Phase one of the field trial, which involved proving the satellite transmission of sensor data and safeguards images from a video camera activated by seals and motion sensors installed in the vault, was completed in September 1995. Phase two involves formal testing of the RMS as a tool for use by the IAEA during their tasks of monitoring the storage of nuclear material. The field trial to be completed during early 1997 includes access and item monitoring of nuclear materials in two storage trays. The RMS includes a variety of Sandia, Oak Ridge, and Aquila sensor technologies that provide video monitoring, radiation attribute measurements, and container identification to the on-site data acquisition system (DAS) by way of radio-frequency and Echelon LONWorks networks. The accumulated safeguards information will be transmitted to the IAEA via satellite (COMSAT/RSI) and international telephone lines

Study of Remote Globular Cluster Satellites of M87

Science.gov (United States)

Sahai, Arushi; Shao, Andrew; Toloba, Elisa; Guhathakurta, Puragra; Peng, Eric W.; Zhang, Hao

2017-01-01

We present a sample of “orphan” globular clusters (GCs) with previously unknown parent galaxies, which we determine to be remote satellites of M87, a massive elliptical galaxy at the center of the Virgo Cluster of Galaxies. Because GCs were formed in the early universe along with their original parent galaxies, which were cannibalized by massive galaxies such as M87, they share similar age and chemical properties. In this study, we first confirm that M87 is the adoptive parent galaxy of our orphan GCs using photometric and spectroscopic data to analyze spatial and velocity distributions. Next, we increase the signal-to-noise ratio of our samples’ spectra through a process known as coaddition. We utilize spectroscopic absorption lines to determine the age and metallicity of our orphan GCs through comparison to stellar population synthesis models, which we then relate to the GCs’ original parent galaxies using a mass-metallicity relation. Our finding that remote GCs of M87 likely developed in galaxies with ~1010 solar masses implies that M87’s outer halo is formed of relatively massive galaxies, serving as important parameters for developing theories about the formation and evolution of massive galaxies.This research was funded in part by NASA/STScI and the National Science Foundation. Most of this work was carried out by high school students working under the auspices of the Science Internship Program at UC Santa Cruz.

Atmospheric Corrections and Multi-Conditional Algorithm for Multi-Sensor Remote Sensing of Suspended Particulate Matter in Low-to-High Turbidity Levels Coastal Waters

Directory of Open Access Journals (Sweden)

Stéfani Novoa

2017-01-01

Full Text Available The accurate measurement of suspended particulate matter (SPM concentrations in coastal waters is of crucial importance for ecosystem studies, sediment transport monitoring, and assessment of anthropogenic impacts in the coastal ocean. Ocean color remote sensing is an efficient tool to monitor SPM spatio-temporal variability in coastal waters. However, near-shore satellite images are complex to correct for atmospheric effects due to the proximity of land and to the high level of reflectance caused by high SPM concentrations in the visible and near-infrared spectral regions. The water reflectance signal (ρw tends to saturate at short visible wavelengths when the SPM concentration increases. Using a comprehensive dataset of high-resolution satellite imagery and in situ SPM and water reflectance data, this study presents (i an assessment of existing atmospheric correction (AC algorithms developed for turbid coastal waters; and (ii a switching method that automatically selects the most sensitive SPM vs. ρw relationship, to avoid saturation effects when computing the SPM concentration. The approach is applied to satellite data acquired by three medium-high spatial resolution sensors (Landsat-8/Operational Land Imager, National Polar-Orbiting Partnership/Visible Infrared Imaging Radiometer Suite and Aqua/Moderate Resolution Imaging Spectrometer to map the SPM concentration in some of the most turbid areas of the European coastal ocean, namely the Gironde and Loire estuaries as well as Bourgneuf Bay on the French Atlantic coast. For all three sensors, AC methods based on the use of short-wave infrared (SWIR spectral bands were tested, and the consistency of the retrieved water reflectance was examined along transects from low- to high-turbidity waters. For OLI data, we also compared a SWIR-based AC (ACOLITE with a method based on multi-temporal analyses of atmospheric constituents (MACCS. For the selected scenes, the ACOLITE-MACCS difference was

Satellite and airborne oil spill remote sensing: state of the art and application to the BP Deepwater Horizon oil spill

Energy Technology Data Exchange (ETDEWEB)

Leifer, Ira [University of California (United States); Clark, Roger; Swayze, Gregg [US Geology Survey (United States); Jones, Cathleen [California Institute of Technology (United States); Svejkovsky, Jan [Ocean Imaging Corporation (United States)

2011-07-01

This study stresses the value of using satellite technology in quantifying oil seepage impact, and how it can be applied to the case of Horizon oil spill. The purpose of the study is to clarify the remote sensing process as it applies to oil spills, and how testing resources should be properly allocated so as to come up with the optimal response strategy. Many parameters were involved in this research, of which the most important were the environmental factors, the active and passive remote sensing measures, satellite imagery and imaging spectroscopy, and oil thickness measurements using thermal infrared and laser-induced fluorescence. These parameters were later used to quantify the spills in the impacted regions. Results showed that remote sensing would always be accompanied by certain errors, however, in the case of the Horizon spill, the infrared approach proved to be a convenient and a reliable approach for impact analysis process. The study also put emphasis on the importance of oil spatial patterns in validating the reliability of a test procedure.

Satellite and airborne oil spill remote sensing: state of the art and application to the BP Deepwater Horizon oil spill

International Nuclear Information System (INIS)

Leifer, Ira; Clark, Roger; Swayze, Gregg; Jones, Cathleen; Svejkovsky, Jan

2011-01-01

This study stresses the value of using satellite technology in quantifying oil seepage impact, and how it can be applied to the case of Horizon oil spill. The purpose of the study is to clarify the remote sensing process as it applies to oil spills, and how testing resources should be properly allocated so as to come up with the optimal response strategy. Many parameters were involved in this research, of which the most important were the environmental factors, the active and passive remote sensing measures, satellite imagery and imaging spectroscopy, and oil thickness measurements using thermal infrared and laser-induced fluorescence. These parameters were later used to quantify the spills in the impacted regions. Results showed that remote sensing would always be accompanied by certain errors, however, in the case of the Horizon spill, the infrared approach proved to be a convenient and a reliable approach for impact analysis process. The study also put emphasis on the importance of oil spatial patterns in validating the reliability of a test procedure.

Remote sensing for oil spill detection and response

International Nuclear Information System (INIS)

Engelhardt, F.R.

1999-01-01

This paper focuses on the use of remote sensing for marine oil spill detection and response. The surveillance and monitoring of discharges, and the main elements of effective surveillance are discussed. Tactical emergency response and the requirements for selecting a suitable remote sensing approach, airborne remote sensing systems, and the integration of satellite and airborne imaging are examined. Specifications of satellite surveillance systems potentially usable for oil spill detection, and specifications of airborne remote sensing systems suitable for oil spill detection, monitoring and supplemental actions are tabulated, and a schema of integrated satellite-airborne remote sensing (ISARS) is presented. (UK)

Bluetooth-based sensor networks for remotely monitoring the physiological signals of a patient.

Science.gov (United States)

Zhang, Ying; Xiao, Hannan

2009-11-01

Integrating intelligent medical microsensors into a wireless communication network makes it possible to remotely collect physiological signals of a patient, release the patient from being tethered to monitoring medical instrumentations, and facilitate the patient's early hospital discharge. This can further improve life quality by providing continuous observation without the need of disrupting the patient's normal life, thus reducing the risk of infection significantly, and decreasing the cost of the hospital and the patient. This paper discusses the implementation issues, and describes the overall system architecture of our developed Bluetooth sensor network for patient monitoring and the corresponding heart activity sensors. It also presents our approach to developing the intelligent physiological sensor nodes involving integration of Bluetooth radio technology, hardware and software organization, and our solutions for onboard signal processing.

Gesture recognition based on computer vision and glove sensor for remote working environments

Energy Technology Data Exchange (ETDEWEB)

Chien, Sung Il; Kim, In Chul; Baek, Yung Mok; Kim, Dong Su; Jeong, Jee Won; Shin, Kug [Kyungpook National University, Taegu (Korea)

1998-04-01

In this research, we defined a gesture set needed for remote monitoring and control of a manless system in atomic power station environments. Here, we define a command as the loci of a gesture. We aim at the development of an algorithm using a vision sensor and glove sensors in order to implement the gesture recognition system. The gesture recognition system based on computer vision tracks a hand by using cross correlation of PDOE image. To recognize the gesture word, the 8 direction code is employed as the input symbol for discrete HMM. Another gesture recognition based on sensor has introduced Pinch glove and Polhemus sensor as an input device. The extracted feature through preprocessing now acts as an input signal of the recognizer. For recognition 3D loci of Polhemus sensor, discrete HMM is also adopted. The alternative approach of two foregoing recognition systems uses the vision and and glove sensors together. The extracted mesh feature and 8 direction code from the locus tracking are introduced for further enhancing recognition performance. MLP trained by backpropagation is introduced here and its performance is compared to that of discrete HMM. (author). 32 refs., 44 figs., 21 tabs.

Remote Sensing of Black Lakes and Using 810 nm Reflectance Peak for Retrieving Water Quality Parameters of Optically Complex Waters

Directory of Open Access Journals (Sweden)

Tiit Kutser

2016-06-01

Full Text Available Many lakes in boreal and arctic regions have high concentrations of CDOM (coloured dissolved organic matter. Remote sensing of such lakes is complicated due to very low water leaving signals. There are extreme (black lakes where the water reflectance values are negligible in almost entire visible part of spectrum (400–700 nm due to the absorption by CDOM. In these lakes, the only water-leaving signal detectable by remote sensing sensors occurs as two peaks—near 710 nm and 810 nm. The first peak has been widely used in remote sensing of eutrophic waters for more than two decades. We show on the example of field radiometry data collected in Estonian and Swedish lakes that the height of the 810 nm peak can also be used in retrieving water constituents from remote sensing data. This is important especially in black lakes where the height of the 710 nm peak is still affected by CDOM. We have shown that the 810 nm peak can be used also in remote sensing of a wide variety of lakes. The 810 nm peak is caused by combined effect of slight decrease in absorption by water molecules and backscattering from particulate material in the water. Phytoplankton was the dominant particulate material in most of the studied lakes. Therefore, the height of the 810 peak was in good correlation with all proxies of phytoplankton biomass—chlorophyll-a (R2 = 0.77, total suspended matter (R2 = 0.70, and suspended particulate organic matter (R2 = 0.68. There was no correlation between the peak height and the suspended particulate inorganic matter. Satellite sensors with sufficient spatial and radiometric resolution for mapping lake water quality (Landsat 8 OLI and Sentinel-2 MSI were launched recently. In order to test whether these satellites can capture the 810 nm peak we simulated the spectral performance of these two satellites from field radiometry data. Actual satellite imagery from a black lake was also used to study whether these sensors can detect the peak

Remote and unattended monitoring techniques

International Nuclear Information System (INIS)

Abedin-Zadeh, R.; Whichello, J.

1998-01-01

In the last years, there has been a tremendous growth in the number of unattended assay and monitoring systems in the field. These systems have enabled reduced presence of inspectors while increasing the verification coverage. As part of the Strengthened safeguards System and in particular as part of the measures to improve the cost-effectiveness of safeguards, the possibility of remote transfer of authenticated and encrypted video surveillance, seals and radiation sensor data via telephone or special satellite links have been demonstrated and the necessary arrangements and infrastructure have been prepared. The evaluation of field trials of the remote monitoring systems have shown that the systems are effective in monitoring events of safeguards relevance in near real times. The systems are competitive from a cost standpoint when compared to current methods. The reduction of inspection efforts can be realized by application of remote monitoring technique with scheduled inspections and more effectively with the short notice or unannounced random inspections. It is expected that, upon completion of the necessary arrangements with the Member States authorities, the safeguards department will implement the technique widely before the year 2000

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

An overview of remote sensing and geodesy for epidemiology and public health application.

Science.gov (United States)

Hay, S I

2000-01-01

The techniques of remote sensing (RS) and geodesy have the potential to revolutionize the discipline of epidemiology and its application in human health. As a new departure from conventional epidemiological methods, these techniques require some detailed explanation. This review provides the theoretical background to RS including (i) its physical basis, (ii) an explanation of the orbital characteristics and specifications of common satellite sensor systems, (iii) details of image acquisition and procedures adopted to overcome inherent sources of data degradation, and (iv) a background to geophysical data preparation. This information allows RS applications in epidemiology to be readily interpreted. Some of the techniques used in geodesy, to locate features precisely on Earth so that they can be registered to satellite sensor-derived images, are also included. While the basic principles relevant to public health are presented here, inevitably many of the details must be left to specialist texts.

Remote sensing of high-latitude ionization profiles by ground-based and spaceborne instrumentation

International Nuclear Information System (INIS)

Vondrak, R.R.

1981-01-01

Ionospheric specification and modeling are now largely based on data provided by active remote sensing with radiowave techniques (ionosondes, incoherent-scatter radars, and satellite beacons). More recently, passive remote sensing techniques have been developed that can be used to monitor quantitatively the spatial distribution of high-latitude E-region ionization. These passive methods depend on the measurement, or inference, of the energy distribution of precipitating kilovolt electrons, the principal source of the nighttime E-region at high latitudes. To validate these techniques, coordinated measurements of the auroral ionosphere have been made with the Chatanika incoherent-scatter radar and a variety of ground-based and spaceborne sensors

Assessing soil carbon stocks under pastures through orbital remote sensing

Directory of Open Access Journals (Sweden)

Gabor Gyula Julius Szakács

2011-10-01

Full Text Available The growing demand of world food and energy supply increases the threat of global warming due to higher greenhouse gas emissions by agricultural activity. Therefore, it is widely admitted that agriculture must establish a new paradigm in terms of environmental sustainability that incorporate techniques for mitigation of greenhouse gas emissions. This article addresses to the scientific demand to estimate in a fast and inexpensive manner current and potential soil organic carbon (SOC stocks in degraded pastures, using remote sensing techniques. Four pastures on sandy soils under Brazilian Cerrado vegetation in São Paulo state were chosen due to their SOC sequestration potential, which was characterized for the soil depth 0-50 cm. Subsequently, a linear regression analysis was performed between SOC and Leaf Area Index (LAI measured in the field (LAIfield and derived by satellite (LAIsatellite as well as SOC and pasture reflectance in six spectra from 450 nm - 2350 nm, using the Enhanced Thematic Mapper (ETM+ sensor of satellite Landsat 7. A high correlation between SOC and LAIfield (R² = 0.9804 and LAIsatellite (R² = 0.9812 was verified. The suitability of satellite derived LAI for SOC determination leads to the assumption, that orbital remote sensing is a very promising SOC estimation technique from regional to global scale.

Environmental monitoring of El Hierro Island submarine volcano, by combining low and high resolution satellite imagery

Science.gov (United States)

Eugenio, F.; Martin, J.; Marcello, J.; Fraile-Nuez, E.

2014-06-01

El Hierro Island, located at the Canary Islands Archipelago in the Atlantic coast of North Africa, has been rocked by thousands of tremors and earthquakes since July 2011. Finally, an underwater volcanic eruption started 300 m below sea level on October 10, 2011. Since then, regular multidisciplinary monitoring has been carried out in order to quantify the environmental impacts caused by the submarine eruption. Thanks to this natural tracer release, multisensorial satellite imagery obtained from MODIS and MERIS sensors have been processed to monitor the volcano activity and to provide information on the concentration of biological, chemical and physical marine parameters. Specifically, low resolution satellite estimations of optimal diffuse attenuation coefficient (Kd) and chlorophyll-a (Chl-a) concentration under these abnormal conditions have been assessed. These remote sensing data have played a fundamental role during field campaigns guiding the oceanographic vessel to the appropriate sampling areas. In addition, to analyze El Hierro submarine volcano area, WorldView-2 high resolution satellite spectral bands were atmospherically and deglinted processed prior to obtain a high-resolution optimal diffuse attenuation coefficient model. This novel algorithm was developed using a matchup data set with MERIS and MODIS data, in situ transmittances measurements and a seawater radiative transfer model. Multisensor and multitemporal imagery processed from satellite remote sensing sensors have demonstrated to be a powerful tool for monitoring the submarine volcanic activities, such as discolored seawater, floating material and volcanic plume, having shown the capabilities to improve the understanding of submarine volcanic processes.

Satellite-based remote sensing of running water habitats at large riverscape scales: Tools to analyze habitat heterogeneity for river ecosystem management

Science.gov (United States)

Hugue, F.; Lapointe, M.; Eaton, B. C.; Lepoutre, A.

2016-01-01

We illustrate an approach to quantify patterns in hydraulic habitat composition and local heterogeneity applicable at low cost over very large river extents, with selectable reach window scales. Ongoing developments in remote sensing and geographical information science massively improve efficiencies in analyzing earth surface features. With the development of new satellite sensors and drone platforms and with the lowered cost of high resolution multispectral imagery, fluvial geomorphology is experiencing a revolution in mapping streams at high resolution. Exploiting the power of aerial or satellite imagery is particularly useful in a riverscape research framework (Fausch et al., 2002), where high resolution sampling of fluvial features and very large coverage extents are needed. This study presents a satellite remote sensing method that requires very limited field calibration data to estimate over various scales ranging from 1 m to many tens or river kilometers (i) spatial composition metrics for key hydraulic mesohabitat types and (ii) reach-scale wetted habitat heterogeneity indices such as the hydromorphological index of diversity (HMID). When the purpose is hydraulic habitat characterization applied over long river networks, the proposed method (although less accurate) is much less computationally expensive and less data demanding than two dimensional computational fluid dynamics (CFD). Here, we illustrate the tools based on a Worldview 2 satellite image of the Kiamika River, near Mont Laurier, Quebec, Canada, specifically over a 17-km river reach below the Kiamika dam. In the first step, a high resolution water depth (D) map is produced from a spectral band ratio (calculated from the multispectral image), calibrated with limited field measurements. Next, based only on known river discharge and estimated cross section depths at time of image capture, empirical-based pseudo-2D hydraulic rules are used to rapidly generate a two-dimensional map of flow velocity

Assessment of Lake Water Quality and Quantity Using Satellite Remote Sensing

Science.gov (United States)

Daniel, K. C.; Suresh, A.; Paredes Mesa, S.

2017-12-01

Lakes are one of the few sources of freshwater used throughout the world but due to human activities, its quality and availability has been decreasing. The drying of lakes is a concerning issue in different communities around the world. This problem can affect jobs and the lives of individuals who use lakes as a source of income, consumption and recreation. Another dilemma that has occurred in lakes is eutrophication which is the buildup of excess nutrients in the lakes caused by runoff. This natural process can lead to anoxic conditions that may have a detrimental impact on surrounding ecosystems. Therefore, causing a devastating impact to economies and human livelihood worldwide. To monitor these issues, satellite data can be used to assess the water quality of different lakes throughout the world. Landsat satellite data from the past 10 years was used to conduct this research. By using the IOP (Inherent Optical Properties) of chlorophyll and suspended solids in the visible spectrum, the presence of algal blooms and sediments was determined. ARCGIS was used to outline the areas of the lakes and obtain reflectance values for quantity and quality assessment. Because there is always a certain amount of contamination in the lake, this research is used to evaluate the condition of the lakes throughout the years. Using the data that we have collected, we are able to understand how the issues addressed can harm civilians seasonally. Key Words: Lakes, Water Quality, Algal Blooms, Eutrophication, Remote Sensing, Satellite DataData Source: Landsat 4, Landsat 5, Landsat 7, Landsat 8

Satellite Based Live and Interactive Distance Learning Program in the Field of Geoinformatics - a Perspective of Indian Institute of Remote Sensing, India

Science.gov (United States)

Raju, P. L. N.; Gupta, P. K.; Roy, P. S.

2011-09-01

Geoinformatics is a highly specialized discipline that deals with Remote Sensing, Geographical Information System (GIS), Global Positioning System (GPS) and field surveys for assessing, quantification, development and management of resources, planning and infrastructure development, utility services etc. Indian Institute of Remote Sensing (IIRS), a premier institute and one of its kinds has played a key role for capacity Building in this specialized area since its inception in 1966. Realizing the large demand, IIRS has started outreach program in basics of Remote Sensing, GIS and GPS for universities and institutions. EDUSAT (Educational Satellite) is the communication satellite built and launched by ISRO in 2004 exclusively for serving the educational sector to meet the demand for an interactive satellite based distance education system for the country. IIRS has used EDUSAT (shifted to INSAT 4 CR recently due to termination of services from EDUSAT) for its distance learning program to impart basic training in Remote Sensing, GIS and GPS, catering to the universities spread across India. The EDUSAT based training is following similar to e-learning method but has advantage of live interaction sessions between teacher and the students when the lecture is delivered using EDUSAT satellite communication. Because of its good quality reception the interactions are not constrained due to bandwidth problems of Internet. National Natural Resource Management System, Department of Space, Government of India, under Standing Committee in Training and Technology funded this unique program to conduct the basic training in Geoinformatics. IIRS conducts 6 weeks basic training course on "Remote Sensing, GIS and GPS" regularly since the year 2007. The course duration is spread over the period of 3 months beginning with the start of the academic year (1st semester) i.e., July to December every year, for university students. IIRS has utilized EDUSAT satellite for conducting 4 six weeks

Bridging the Scales from Field to Region with Practical Tools to Couple Time- and Space-Synchronized Data from Flux Towers and Networks with Proximal and Remote Sensing Data

Science.gov (United States)

Burba, G. G.; Avenson, T.; Burkart, A.; Gamon, J. A.; Guan, K.; Julitta, T.; Pastorello, G.; Sakowska, K.

2017-12-01

Many hundreds of flux towers are presently operational as standalone projects and as parts of regional networks. However, the vast majority of these towers do not allow straightforward coupling with remote sensing (drone, aircraft, satellite, etc.) data, and even fewer have optical sensors for validation of remote sensing products, and upscaling from field to regional levels. In 2016-2017, new tools to collect, process, and share time-synchronized flux data from multiple towers were developed and deployed globally. Originally designed to automate site and data management, and to streamline flux data analysis, these tools allow relatively easy matching of tower data with remote sensing data: GPS-driven PTP time protocol synchronizes instrumentation within the station, different stations with each other, and all of these to remote sensing data to precisely align remote sensing and flux data in time Footprint size and coordinates computed and stored with flux data help correctly align tower flux footprints and drone, aircraft or satellite motion to precisely align optical and flux data in space Full snapshot of the remote sensing pixel can then be constructed, including leaf-level, ground optical sensor, and flux tower measurements from the same footprint area, closely coupled with the remote sensing measurements to help interpret remote sensing data, validate models, and improve upscaling Additionally, current flux towers can be augmented with advanced ground optical sensors and can use standard routines to deliver continuous products (e.g. SIF, PRI, NDVI, etc.) based on automated field spectrometers (e.g., FloX and RoX, etc.) and other optical systems. Several dozens of new towers already operational globally can be readily used for the proposed workflow. Over 500 active traditional flux towers can be updated to synchronize their data with remote sensing measurements. This presentation will show how the new tools are used by major networks, and describe how this

Remote Left Ventricular Hemodynamic Monitoring Using a Novel Intracardiac Sensor.

Science.gov (United States)

Mondritzki, Thomas; Boehme, Philip; White, Jason; Park, Jin Woo; Hoffmann, Jessica; Vogel, Julia; Kolkhof, Peter; Walsh, Stuart; Sandner, Peter; Bischoff, Erwin; Dinh, Wilfried; Hüser, Jörg; Truebel, Hubert

2018-05-01

Heart failure (HF) remains the most common reason for hospital admission in patients aged >65 years. Despite modern drug therapy, mortality and readmission rates for patients hospitalized with HF remain high. This necessitates further research to identify early patients at risk for readmission to limit hospitalization by timely adjustment of medical therapy. Implantable devices can monitor left ventricular (LV) hemodynamics and remotely and continuously detect the early signs of decompensation to trigger interventions and reduce the risk of hospitalization for HF. Here, we report the first preclinical study validating a new batteryless and easy to implant LV-microelectromechanical system to assess LV performance. A miniaturized implantable wireless pressure sensor was adapted for implantation in the LV apex. The LV-microelectromechanical system sensor was tested in a canine model of HF. The wireless pressure sensor measurements were compared with invasive left heart catheter-derived measurements at several time points. During different pharmacological challenge studies with dobutamine or vasopressin, the device was equally sensitive compared with invasive standard procedures. No adverse events or any observable reaction related to the implantation and application of the device for a period of 35 days was observed. Our miniaturized wireless pressure sensor placed in the LV (LV-microelectromechanical system) has the potential to become a new telemetric tool to earlier identify patients at risk for HF decompensation and to guide the treatment of patients with HF. © 2018 American Heart Association, Inc.

Remote Sensing products for water quality monitoring and water resources management; Teledeccion para la monitorizacion de vairables de calidad del agua y del recurso hidrologico

Energy Technology Data Exchange (ETDEWEB)

Pi Figueroa, A.; Moreno, L.

2008-07-01

This article addresses the use of remote sensing technology for water quality monitoring and water resources management. Remote sensing is the stand-off collection through the use of a variety of devices aboard on satellites for gathering information on a given object or area. The different kind of sensors used for the different applications are presented, as well as a list of products for a better monitoring and management of these topics. (Author) 3 refs.

Analysis of smear in high-resolution remote sensing satellites

Science.gov (United States)

Wahballah, Walid A.; Bazan, Taher M.; El-Tohamy, Fawzy; Fathy, Mahmoud

2016-10-01

High-resolution remote sensing satellites (HRRSS) that use time delay and integration (TDI) CCDs have the potential to introduce large amounts of image smear. Clocking and velocity mismatch smear are two of the key factors in inducing image smear. Clocking smear is caused by the discrete manner in which the charge is clocked in the TDI-CCDs. The relative motion between the HRRSS and the observed object obliges that the image motion velocity must be strictly synchronized with the velocity of the charge packet transfer (line rate) throughout the integration time. During imaging an object off-nadir, the image motion velocity changes resulting in asynchronization between the image velocity and the CCD's line rate. A Model for estimating the image motion velocity in HRRSS is derived. The influence of this velocity mismatch combined with clocking smear on the modulation transfer function (MTF) is investigated by using Matlab simulation. The analysis is performed for cross-track and along-track imaging with different satellite attitude angles and TDI steps. The results reveal that the velocity mismatch ratio and the number of TDI steps have a serious impact on the smear MTF; a velocity mismatch ratio of 2% degrades the MTFsmear by 32% at Nyquist frequency when the TDI steps change from 32 to 96. In addition, the results show that to achieve the requirement of MTFsmear >= 0.95 , for TDI steps of 16 and 64, the allowable roll angles are 13.7° and 6.85° and the permissible pitch angles are no more than 9.6° and 4.8°, respectively.

Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks.

Science.gov (United States)

Shi, Shengchao; Li, Guangxia; An, Kang; Gao, Bin; Zheng, Gan

2017-09-04

This paper proposes novel satellite-based wireless sensor networks (WSNs), which integrate the WSN with the cognitive satellite terrestrial network. Having the ability to provide seamless network access and alleviate the spectrum scarcity, cognitive satellite terrestrial networks are considered as a promising candidate for future wireless networks with emerging requirements of ubiquitous broadband applications and increasing demand for spectral resources. With the emerging environmental and energy cost concerns in communication systems, explicit concerns on energy efficient resource allocation in satellite networks have also recently received considerable attention. In this regard, this paper proposes energy-efficient optimal power allocation schemes in the cognitive satellite terrestrial networks for non-real-time and real-time applications, respectively, which maximize the energy efficiency (EE) of the cognitive satellite user while guaranteeing the interference at the primary terrestrial user below an acceptable level. Specifically, average interference power (AIP) constraint is employed to protect the communication quality of the primary terrestrial user while average transmit power (ATP) or peak transmit power (PTP) constraint is adopted to regulate the transmit power of the satellite user. Since the energy-efficient power allocation optimization problem belongs to the nonlinear concave fractional programming problem, we solve it by combining Dinkelbach's method with Lagrange duality method. Simulation results demonstrate that the fading severity of the terrestrial interference link is favorable to the satellite user who can achieve EE gain under the ATP constraint comparing to the PTP constraint.

Optimizing cloud removal from satellite remotely sensed data for monitoring vegetation dynamics in humid tropical climate

International Nuclear Information System (INIS)

Hashim, M; Pour, A B; Onn, C H

2014-01-01

Remote sensing technology is an important tool to analyze vegetation dynamics, quantifying vegetation fraction of Earth's agricultural and natural vegetation. In optical remote sensing analysis removing atmospheric interferences, particularly distribution of cloud contaminations, are always a critical task in the tropical climate. This paper suggests a fast and alternative approach to remove cloud and shadow contaminations for Landsat Enhanced Thematic Mapper + (ETM + ) multi temporal datasets. Band 3 and Band 4 from all the Landsat ETM + dataset are two main spectral bands that are very crucial in this study for cloud removal technique. The Normalise difference vegetation index (NDVI) and the normalised difference soil index (NDSI) are two main derivatives derived from the datasets. Change vector analysis is used in this study to seek the vegetation dynamics. The approach developed in this study for cloud optimizing can be broadly applicable for optical remote sensing satellite data, which are seriously obscured with heavy cloud contamination in the tropical climate

A far-field-viewing sensor for making analytical measurements in remote locations.

Science.gov (United States)

Michael, K L; Taylor, L C; Walt, D R

1999-07-15

We demonstrate a far-field-viewing GRINscope sensor for making analytical measurements in remote locations. The GRINscope was fabricated by permanently affixing a micro-Gradient index (GRIN) lens on the distal face of a 350-micron-diameter optical imaging fiber. The GRINscope can obtain both chemical and visual information. In one application, a thin, pH-sensitive polymer layer was immobilized on the distal end of the GRINscope. The ability of the GRINscope to visually image its far-field surroundings and concurrently detect pH changes in a flowing stream was demonstrated. In a different application, the GRINscope was used to image pH- and O2-sensitive particles on a remote substrate and simultaneously measure their fluorescence intensity in response to pH or pO2 changes.

Spatiotemporal Fusion of Multisource Remote Sensing Data: Literature Survey, Taxonomy, Principles, Applications, and Future Directions

Directory of Open Access Journals (Sweden)

Xiaolin Zhu

2018-03-01

Full Text Available Satellite time series with high spatial resolution is critical for monitoring land surface dynamics in heterogeneous landscapes. Although remote sensing technologies have experienced rapid development in recent years, data acquired from a single satellite sensor are often unable to satisfy our demand. As a result, integrated use of data from different sensors has become increasingly popular in the past decade. Many spatiotemporal data fusion methods have been developed to produce synthesized images with both high spatial and temporal resolutions from two types of satellite images, frequent coarse-resolution images, and sparse fine-resolution images. These methods were designed based on different principles and strategies, and therefore show different strengths and limitations. This diversity brings difficulties for users to choose an appropriate method for their specific applications and data sets. To this end, this review paper investigates literature on current spatiotemporal data fusion methods, categorizes existing methods, discusses the principal laws underlying these methods, summarizes their potential applications, and proposes possible directions for future studies in this field.

Developing the remote sensing-based water environmental model for monitoring alpine river water environment over Plateau cold zone

Science.gov (United States)

You, Y.; Wang, S.; Yang, Q.; Shen, M.; Chen, G.

2017-12-01

Alpine river water environment on the Plateau (such as Tibetan Plateau, China) is a key indicator for water security and environmental security in China. Due to the complex terrain and various surface eco-environment, it is a very difficult to monitor the water environment over the complex land surface of the plateau. The increasing availability of remote sensing techniques with appropriate spatiotemporal resolutions, broad coverage and low costs allows for effective monitoring river water environment on the Plateau, particularly in remote and inaccessible areas where are lack of in situ observations. In this study, we propose a remote sense-based monitoring model by using multi-platform remote sensing data for monitoring alpine river environment. In this study some parameterization methodologies based on satellite remote sensing data and field observations have been proposed for monitoring the water environmental parameters (including chlorophyll-a concentration (Chl-a), water turbidity (WT) or water clarity (SD), total nitrogen (TN), total phosphorus (TP), and total organic carbon (TOC)) over the china's southwest highland rivers, such as the Brahmaputra. First, because most sensors do not collect multiple observations of a target in a single pass, data from multiple orbits or acquisition times may be used, and varying atmospheric and irradiance effects must be reconciled. So based on various types of satellite data, at first we developed the techniques of multi-sensor data correction, atmospheric correction. Second, we also built the inversion spectral database derived from long-term remote sensing data and field sampling data. Then we have studied and developed a high-precision inversion model over the southwest highland river backed by inversion spectral database through using the techniques of multi-sensor remote sensing information optimization and collaboration. Third, take the middle reaches of the Brahmaputra river as the study area, we validated the key

SensorWeb Evolution Using the Earth Observing One (EO-1) Satellite as a Test Platform

Science.gov (United States)

Mandl, Daniel; Frye, Stuart; Cappelaere, Pat; Ly, Vuong; Handy, Matthew; Chien, Steve; Grossman, Robert; Tran, Daniel

2012-01-01

The Earth Observing One (EO-1) satellite was launched in November 2000 as a one year technology demonstration mission for a variety of space technologies. After the first year, in addition to collecting science data from its instruments, the EO-1 mission has been used as a testbed for a variety of technologies which provide various automation capabilities and which have been used as a pathfinder for the creation of SensorWebs. A SensorWeb is the integration of variety of space, airborne and ground sensors into a loosely coupled collaborative sensor system that automatically provides useful data products. Typically, a SensorWeb is comprised of heterogeneous sensors tied together with a messaging architecture and web services. This paper provides an overview of the various technologies that were tested and eventually folded into normal operations. As these technologies were folded in, the nature of operations transformed. The SensorWeb software enables easy connectivity for collaboration with sensors, but the side benefit is that it improved the EO-1 operational efficiency. This paper presents the various phases of EO-1 operation over the past 12 years and also presents operational efficiency gains demonstrated by some metrics.

A Novel High Sensitivity Sensor for Remote Field Eddy Current Non-Destructive Testing Based on Orthogonal Magnetic Field

Directory of Open Access Journals (Sweden)

Xiaojie Xu

2014-12-01

Full Text Available Remote field eddy current is an effective non-destructive testing method for ferromagnetic tubular structures. In view of conventional sensors’ disadvantages such as low signal-to-noise ratio and poor sensitivity to axial cracks, a novel high sensitivity sensor based on orthogonal magnetic field excitation is proposed. Firstly, through a three-dimensional finite element simulation, the remote field effect under orthogonal magnetic field excitation is determined, and an appropriate configuration which can generate an orthogonal magnetic field for a tubular structure is developed. Secondly, optimized selection of key parameters such as frequency, exciting currents and shielding modes is analyzed in detail, and different types of pick-up coils, including a new self-differential mode pick-up coil, are designed and analyzed. Lastly, the proposed sensor is verified experimentally by various types of defects manufactured on a section of a ferromagnetic tube. Experimental results show that the proposed novel sensor can largely improve the sensitivity of defect detection, especially for axial crack whose depth is less than 40% wall thickness, which are very difficult to detect and identify by conventional sensors. Another noteworthy advantage of the proposed sensor is that it has almost equal sensitivity to various types of defects, when a self-differential mode pick-up coil is adopted.

An Assessment of the Capabilities of the ERS Satellites' Active Microwave Instruments for Monitoring Soil Moisture Change

Directory of Open Access Journals (Sweden)

K. Blyth

1997-01-01

Full Text Available The launch of the European Remote sensing Satellite (ERS-1 in July 1991 represented an important turning point in the development of Earth observation as it was the first of a series of satellites which would carry high resolution active microwave (radar sensors which could operate through the thickest cloudeover and provide continuity of data for at least a decade. This was of particular relevance to hydrological applications, such as soil moisture monitoring, which generally require frequent satellite observations to monitor changes in state. ERS-1 and its successor ERS-2 carry the active microwave instrument (AMI which operates in 3 modes (synthetic aperture radar, wind scatterometer and wave seatterometer together with the radar altimeter which may all be useful for the observation of soil moisture. This paper assesses the utility of these sensors through a comprehensive review of work in this field. Two approaches to soil moisture retrieval are identified: 1 inversion modelling, where the physical effects of vegetation and soil roughness on radar backscatter are quantified through the use of multi-frequency and/or multi-polarization sensors and 2 change detection where these effects are normalized through frequent satellite observation, the residual effects being attributed to short-term changes in soil moisture. Both approaches will be better supported by the future European Envisat-l satellite which will provide both multi-polarization SAR and low resolution products which should facilitate more frequent temporal observation.

Satellite remote sensing reveals a positive impact of living oyster reefs on microalgal biofilm development

Directory of Open Access Journals (Sweden)

C. Echappé

2018-02-01

Full Text Available Satellite remote sensing (RS is routinely used for the large-scale monitoring of microphytobenthos (MPB biomass in intertidal mudflats and has greatly improved our knowledge of MPB spatio-temporal variability and its potential drivers. Processes operating on smaller scales however, such as the impact of benthic macrofauna on MPB development, to date remain underinvestigated. In this study, we analysed the influence of wild Crassostrea gigas oyster reefs on MPB biofilm development using multispectral RS. A 30-year time series (1985–2015 combining high-resolution (30 m Landsat and SPOT data was built in order to explore the relationship between C. gigas reefs and MPB spatial distribution and seasonal dynamics, using the normalized difference vegetation index (NDVI. Emphasis was placed on the analysis of a before–after control-impact (BACI experiment designed to assess the effect of oyster killing on the surrounding MPB biofilms. Our RS data reveal that the presence of oyster reefs positively affects MPB biofilm development. Analysis of the historical time series first showed the presence of persistent, highly concentrated MPB patches around oyster reefs. This observation was supported by the BACI experiment which showed that killing the oysters (while leaving the physical reef structure, i.e. oyster shells, intact negatively affected both MPB biofilm biomass and spatial stability around the reef. As such, our results are consistent with the hypothesis of nutrient input as an explanation for the MPB growth-promoting effect of oysters, whereby organic and inorganic matter released through oyster excretion and biodeposition stimulates MPB biomass accumulation. MPB also showed marked seasonal variations in biomass and patch shape, size and degree of aggregation around the oyster reefs. Seasonal variations in biomass, with higher NDVI during spring and autumn, were consistent with those observed on broader scales in other European mudflats. Our

Satellite remote sensing reveals a positive impact of living oyster reefs on microalgal biofilm development

Science.gov (United States)

Echappé, Caroline; Gernez, Pierre; Méléder, Vona; Jesus, Bruno; Cognie, Bruno; Decottignies, Priscilla; Sabbe, Koen; Barillé, Laurent

2018-02-01

Satellite remote sensing (RS) is routinely used for the large-scale monitoring of microphytobenthos (MPB) biomass in intertidal mudflats and has greatly improved our knowledge of MPB spatio-temporal variability and its potential drivers. Processes operating on smaller scales however, such as the impact of benthic macrofauna on MPB development, to date remain underinvestigated. In this study, we analysed the influence of wild Crassostrea gigas oyster reefs on MPB biofilm development using multispectral RS. A 30-year time series (1985-2015) combining high-resolution (30 m) Landsat and SPOT data was built in order to explore the relationship between C. gigas reefs and MPB spatial distribution and seasonal dynamics, using the normalized difference vegetation index (NDVI). Emphasis was placed on the analysis of a before-after control-impact (BACI) experiment designed to assess the effect of oyster killing on the surrounding MPB biofilms. Our RS data reveal that the presence of oyster reefs positively affects MPB biofilm development. Analysis of the historical time series first showed the presence of persistent, highly concentrated MPB patches around oyster reefs. This observation was supported by the BACI experiment which showed that killing the oysters (while leaving the physical reef structure, i.e. oyster shells, intact) negatively affected both MPB biofilm biomass and spatial stability around the reef. As such, our results are consistent with the hypothesis of nutrient input as an explanation for the MPB growth-promoting effect of oysters, whereby organic and inorganic matter released through oyster excretion and biodeposition stimulates MPB biomass accumulation. MPB also showed marked seasonal variations in biomass and patch shape, size and degree of aggregation around the oyster reefs. Seasonal variations in biomass, with higher NDVI during spring and autumn, were consistent with those observed on broader scales in other European mudflats. Our study provides the

Comparing land surface phenology derived from satellite and GPS network microwave remote sensing.

Science.gov (United States)

Jones, Matthew O; Kimball, John S; Small, Eric E; Larson, Kristine M

2014-08-01

The land surface phenology (LSP) start of season (SOS) metric signals the seasonal onset of vegetation activity, including canopy growth and associated increases in land-atmosphere water, energy and carbon (CO2) exchanges influencing weather and climate variability. The vegetation optical depth (VOD) parameter determined from satellite passive microwave remote sensing provides for global LSP monitoring that is sensitive to changes in vegetation canopy water content and biomass, and insensitive to atmosphere and solar illumination constraints. Direct field measures of canopy water content and biomass changes desired for LSP validation are generally lacking due to the prohibitive costs of maintaining regional monitoring networks. Alternatively, a normalized microwave reflectance index (NMRI) derived from GPS base station measurements is sensitive to daily vegetation water content changes and may provide for effective microwave LSP validation. We compared multiyear (2007-2011) NMRI and satellite VOD records at over 300 GPS sites in North America, and their derived SOS metrics for a subset of 24 homogenous land cover sites to investigate VOD and NMRI correspondence, and potential NMRI utility for LSP validation. Significant correlations (P<0.05) were found at 276 of 305 sites (90.5 %), with generally favorable correspondence in the resulting SOS metrics (r (2)=0.73, P<0.001, RMSE=36.8 days). This study is the first attempt to compare satellite microwave LSP metrics to a GPS network derived reflectance index and highlights both the utility and limitations of the NMRI data for LSP validation, including spatial scale discrepancies between local NMRI measurements and relatively coarse satellite VOD retrievals.

Will the aerosol derived from the OCM satellite sensor be representative of the aerosol over Goa?

Digital Repository Service at National Institute of Oceanography (India)

Talaulikar, M.; Suresh, T.; Rodrigues, A.; Desa, E.; Chauhan, P.

Most of the ocean color satellite sensors such as IRS-P4 OCM, SeaWiFS and MODIS are sun synchronous and have pass over the regions during noon. From our measurements of aerosol optical properties using five-channel sunphotometer over the coastal...

Backthinned TDI CCD image sensor design and performance for the Pleiades high resolution Earth observation satellites

Science.gov (United States)

Materne, A.; Bardoux, A.; Geoffray, H.; Tournier, T.; Kubik, P.; Morris, D.; Wallace, I.; Renard, C.

2017-11-01

The PLEIADES-HR Earth observing satellites, under CNES development, combine a 0.7m resolution panchromatic channel, and a multispectral channel allowing a 2.8 m resolution, in 4 spectral bands. The 2 satellites will be placed on a sun-synchronous orbit at an altitude of 695 km. The camera operates in push broom mode, providing images across a 20 km swath. This paper focuses on the specifications, design and performance of the TDI detectors developed by e2v technologies under CNES contract for the panchromatic channel. Design drivers, derived from the mission and satellite requirements, architecture of the sensor and measurement results for key performances of the first prototypes are presented.

Miniaturised Gravity Sensors for Remote Gravity Surveys.

Science.gov (United States)

Middlemiss, R. P.; Bramsiepe, S. G.; Hough, J.; Paul, D. J.; Rowan, S.; Samarelli, A.; Hammond, G.

2016-12-01

Gravimetry lets us see the world from a completely different perspective. The ability to measure tiny variations in gravitational acceleration (g), allows one to see not just the Earth's gravitational pull, but the influence of smaller objects. The more accurate the gravimeter, the smaller the objects one can see. Gravimetry has applications in many different fields: from tracking magma moving under volcanoes before eruptions; to locating hidden tunnels. The top commercial gravimeters weigh tens of kg and cost at least $100,000, limiting the situations in which they can be used. By contrast, smart phones use a MEMS (microelectromechanical system) accelerometer that can measure the orientation of the device. These are not nearly sensitive or stable enough to be used for the gravimetry but they are cheap, light-weight and mass-producible. At Glasgow University we have developed a MEMS device with both the stability and sensitivity for useful gravimetric measurements. This was demonstrated by a measurement of the Earth tides - the first time this has been achieved with a MEMS sensor. A gravimeter of this size opens up the possiblility for new gravity imaging modalities. Thousands of gravimeters could be networked over a survey site, storing data on an SD card or communicating wirelessly to a remote location. These devices could also be small enough to be carried by a UAVs: airborne gravity surveys could be carried out at low altitude by mulitple UAVs, or UAVs could be used to deliver ground based gravimeters to remote or inaccessible locations.

Mechanism and look-alikes analysis of oil spill monitoring with optical remote sensing

Science.gov (United States)

Lan, Guoxin; Ma, Long; Li, Ying; Liu, Bingxin

2011-12-01

Remote Sensing surveillance constitutes an important component of oil spill disaster management system, but subject to monitoring accuracy and ability, which suffered from resolution, environmental conditions, and look-alikes. So this article aims to provide information of identification and distinguishing of look-alikes for optical sensors, and then improve the monitoring precision. Although limited by monitoring conditions of the atmosphere and night, optical satellite remote sensing can provide the intrinsic spectral information of the film and the background sea, then affords the potentiality for detailed identification of the film thickness, oil type classification (crude/light oil), trends, and sea surface roughness by multi-type data products. This paper focused on optical sensors and indicated that these false targets of sun glint, bottom feature, cloud shadow, suspend bed sediment and surface bioorganic are the main factors for false alarm in optical images. Based on the detailed description of the theory of oil spill detection in optical images, depending on the preliminary summary of the feature of look-alikes in visible-infrared bands, a discriminate criteria and work-flow for slicks identification are proposed. The results are helpful to improve the remote sensing monitoring ability and the contingency planning.

Integrating TWES and Satellite-based remote sensing: Lessons learned from the Honshu 2011 Tsunami

Science.gov (United States)

Löwe, Peter; Wächter, Joachim

2013-04-01

The Boxing Day Tsunami killed 240,000 people and inundated the affected shorelines with waves reaching heights up to 30m. Tsunami Early Warning Capabilities have improved in the meantime by continuing development of modular Tsunami Early Warning Systems (TEWS). However, recent tsunami events, like the Chile 2010 and the Honshu 2011 tsunami demonstrate that the key challenge for TEWS research still lies in the timely issuing of reliable early warning messages to areas at risk, but also to other stakeholders professionally involved in the unfolding event. Until now remote sensing products for Tsunami events, including crisis maps and change detection products, are exclusively linked to those phases of the disaster life cycle, which follow after the early warning stage: Response, recovery and mitigation. The International Charter for Space and Major Disasters has been initiated by the European Space Agency (ESA) and the Centre National d'Etudes Spatiales (CNES) in 1999. It coordinates a voluntary group of governmental space agencies and industry partners, to provide rapid crisis imaging and mapping to disaster and relief organisations to mitigate the effects of disasters on human life, property and the environment. The efficiency of this approach has been demonstrated in the field of Tsunami early warning by Charter activations following the Boxing Day Tsunami 2004, the Chile Tsunami 2010 and the Honshu Tsunami 2011. Traditional single-satellite operations allow at best bimonthly repeat rates over a given Area of Interest (AOI). This allows a lot of time for image acquisition campaign planning between imaging windows for the same AOI. The advent of constellations of identical remote sensing satellites in the early 21st century resulted both in daily AOI revisit capabilities and drastically reduced time frames for acquisition planning. However, the image acquisition planning for optical remote sensing satellite constellations is constrained by orbital and communication

A New Remotely Operated Sensor Platform for Interdisciplinary Observations under Sea Ice

Directory of Open Access Journals (Sweden)

Christian Katlein

2017-09-01

Full Text Available Observation of the climate and ecosystem of ice covered polar seas is a timely task for the scientific community. The goal is to assess the drastic and imminent changes of the polar sea ice cover induced by climate change. Retreating and thinning sea ice affects the planets energy budget, atmospheric, and oceanic circulation patterns as well as the ecosystem associated with this unique habitat. To increase the observational capabilities of sea ice scientists, we equipped a remotely operated vehicle (ROV as sensor platform for interdisciplinary research at the ice water interface. Here, we present the technical details and operation scheme of the new vehicle and provide data examples from a first campaign in the Arctic in autumn 2016 to demonstrate the vehicle's capabilities. The vehicle is designed for efficient operations in the harsh polar conditions. Redundant modular design allows operation by three scientists simultaneously operating a wide variety of sensors. Sensors from physical, chemical, and biological oceanography are combined with optical and acoustic sea ice sensors to provide a comprehensive picture of the underside of sea ice. The sensor suite provides comprehensive capabilities and can be further extended as additional ports for power and communication are available. The vehicle provides full six degrees of freedom in navigation, enabling intervention, and manipulation skills despite its simple one function manipulator arm.

A numerical testbed for remote sensing of aerosols, and its demonstration for evaluating retrieval synergy from a geostationary satellite constellation of GEO-CAPE and GOES-R

International Nuclear Information System (INIS)

Wang, Jun; Xu, Xiaoguang; Ding, Shouguo; Zeng, Jing; Spurr, Robert; Liu, Xiong; Chance, Kelly; Mishchenko, Michael

2014-01-01

We present a numerical testbed for remote sensing of aerosols, together with a demonstration for evaluating retrieval synergy from a geostationary satellite constellation. The testbed combines inverse (optimal-estimation) software with a forward model containing linearized code for computing particle scattering (for both spherical and non-spherical particles), a kernel-based (land and ocean) surface bi-directional reflectance facility, and a linearized radiative transfer model for polarized radiance. Calculation of gas absorption spectra uses the HITRAN (HIgh-resolution TRANsmission molecular absorption) database of spectroscopic line parameters and other trace species cross-sections. The outputs of the testbed include not only the Stokes 4-vector elements and their sensitivities (Jacobians) with respect to the aerosol single scattering and physical parameters (such as size and shape parameters, refractive index, and plume height), but also DFS (Degree of Freedom for Signal) values for retrieval of these parameters. This testbed can be used as a tool to provide an objective assessment of aerosol information content that can be retrieved for any constellation of (planned or real) satellite sensors and for any combination of algorithm design factors (in terms of wavelengths, viewing angles, radiance and/or polarization to be measured or used). We summarize the components of the testbed, including the derivation and validation of analytical formulae for Jacobian calculations. Benchmark calculations from the forward model are documented. In the context of NASA's Decadal Survey Mission GEO-CAPE (GEOstationary Coastal and Air Pollution Events), we demonstrate the use of the testbed to conduct a feasibility study of using polarization measurements in and around the O 2 A band for the retrieval of aerosol height information from space, as well as an to assess potential improvement in the retrieval of aerosol fine and coarse mode aerosol optical depth (AOD) through the

Radiometric Cross-Calibration of the Chilean Satellite FASat-C Using RapidEye and EO-1 Hyperion Data and a Simultaneous Nadir Overpass Approach

Directory of Open Access Journals (Sweden)

Carolina Barrientos

2016-07-01

Full Text Available The absolute radiometric calibration of a satellite sensor is the critical factor that ensures the usefulness of the acquired data for quantitative applications on remote sensing. This work presents the results of the first cross-calibration of the sensor on board the Sistema Satelital de Observación de la Tierra (SSOT Chilean satellite or Air Force Satellite FASat-C. RapidEye-MSI was chosen as the reference sensor, and a simultaneous Nadir Overpass Approach (SNO was applied. The biases caused by differences in the spectral responses of both instruments were compensated through an adjustment factor derived from EO-1 Hyperion data. Through this method, the variations affecting the radiometric response of New AstroSat Optical Modular Instrument (NAOMI-1, have been corrected based on collections over the Frenchman Flat calibration site. The results of a preliminary evaluation of the pre-flight and updated coefficients have shown a significant improvement in the accuracy of at-sensor radiances and TOA reflectances: an average agreement of 2.63% (RMSE was achieved for the multispectral bands of both instruments. This research will provide a basis for the continuity of calibration and validation tasks of future Chilean space missions.

Coupling Flux Towers and Networks with Proximal and Remote Sensing Data: New Tools to Collect and Share Time-Synchronized Hourly Fluxes

Science.gov (United States)

Burba, George; Avenson, Tom; Burkart, Andreas; Gamon, John; Guan, Kaiyu; Julitta, Tommaso; Pastorello, Gilberto; Sakowska, Karolina

2017-04-01

Multiple hundreds of flux towers are presently operational as standalone projects and as parts of larger networks. However, the vast majority of these towers do not allow straight-forward coupling with satellite data, and even fewer have optical sensors for validation of satellite products and upscaling from field to regional levels. In 2016, new tools to collect, process, and share time-synchronized flux data from multiple towers were developed and deployed globally. Originally designed to automate site and data management, these new tools can also be effective in coupling tower data with satellite data due to the following present capabilities: Fully automated FluxSuite system combines hardware, software and web-services, and does not require an expert to run it It can be incorporated into a new flux station or added to a present station, using weatherized remotely-accessible microcomputer, SmartFlux2 It utilizes EddyPro software to calculate fully-processed fluxes and footprints in near-realtime, alongside radiation, optical, weather and soil data All site data are merged into a single quality-controlled file timed using PTP time protocol Data from optical sensors can be integrated into this complete dataset via compatible dataloggers Multiple stations can be linked into time-synchronized network with automated reports and email alerts visible to PIs in real-time Remote sensing researchers without stations can form "virtual networks" of stations by collaborating with tower PIs from different physical networks The present system can then be utilized to couple ground data with satellite data via the following proposed concept: GPS-driven PTP protocol will synchronize instrumentation within the station, different stations with each other, and all of these to satellite data to precisely align optical and flux data in time Footprint size and coordinates computed and stored with flux data will help correctly align footprints and satellite motion to precisely align

Physics teaching by infrared remote sensing of vegetation

Science.gov (United States)

Schüttler, Tobias; Maman, Shimrit; Girwidz, Raimund

2018-05-01

Context- and project-based teaching has proven to foster different affective and cognitive aspects of learning. As a versatile and multidisciplinary scientific research area with diverse applications for everyday life, satellite remote sensing is an interesting context for physics education. In this paper we give a brief overview of satellite remote sensing of vegetation and how to obtain your own, individual infrared remote sensing data with affordable converted digital cameras. This novel technique provides the opportunity to conduct individual remote sensing measurement projects with students in their respective environment. The data can be compared to real satellite data and is of sufficient accuracy for educational purposes.

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.

Optical Remote Sensing Algorithm Validation using High-Frequency Underway Biogeochemical Measurements in Three Large Global River Systems

Science.gov (United States)

Kuhn, C.; Richey, J. E.; Striegl, R. G.; Ward, N.; Sawakuchi, H. O.; Crawford, J.; Loken, L. C.; Stadler, P.; Dornblaser, M.; Butman, D. E.

2017-12-01

More than 93% of the world's river-water volume occurs in basins impacted by large dams and about 43% of river water discharge is impacted by flow regulation. Human land use also alters nutrient and carbon cycling and the emission of carbon dioxide from inland reservoirs. Increased water residence times and warmer temperatures in reservoirs fundamentally alter the physical settings for biogeochemical processing in large rivers, yet river biogeochemistry for many large systems remains undersampled. Satellite remote sensing holds promise as a methodology for responsive regional and global water resources management. Decades of ocean optics research has laid the foundation for the use of remote sensing reflectance in optical wavelengths (400 - 700 nm) to produce satellite-derived, near-surface estimates of phytoplankton chlorophyll concentration. Significant improvements between successive generations of ocean color sensors have enabled the scientific community to document changes in global ocean productivity (NPP) and estimate ocean biomass with increasing accuracy. Despite large advances in ocean optics, application of optical methods to inland waters has been limited to date due to their optical complexity and small spatial scale. To test this frontier, we present a study evaluating the accuracy and suitability of empirical inversion approaches for estimating chlorophyll-a, turbidity and temperature for the Amazon, Columbia and Mississippi rivers using satellite remote sensing. We demonstrate how riverine biogeochemical measurements collected at high frequencies from underway vessels can be used as in situ matchups to evaluate remotely-sensed, near-surface temperature, turbidity, chlorophyll-a derived from the Landsat 8 (NASA) and Sentinel 2 (ESA) satellites. We investigate the use of remote sensing water reflectance to infer trophic status as well as tributary influences on the optical characteristics of the Amazon, Mississippi and Columbia rivers.

The role of satellite remote sensing in REDD/MRV

Science.gov (United States)

Jonckheere, Inge; Sandoval, Alberto

2010-05-01

REDD, which stands for 'Reducing Emissions from Deforestation and Forest Degradation in Developing Countries' - is an effort to create a financial value for the carbon stored in forests, offering incentives for developing countries to reduce emissions from forested lands and invest in low-carbon paths to sustainable development. The UN-REDD Programme, a collaborative partnership between FAO, UNDP and UNEP launched in September 2008, supports countries to develop capacity to REDD and to implement a future REDD mechanism in a post- 2012 climate regime. The programme works at both the national and global scale, through support mechanisms for country-driven REDD strategies and international consensus-building on REDD processes. The UN-REDD Programme gathers technical teams from around the world to develop common approaches, analyses and guidelines on issues such as measurement, reporting and verification (MRV) of carbon emissions and flows, remote sensing, and greenhouse gas inventories. Within the partnership, FAO supports countries on technical issues related to forestry and the development of cost effective and credible MRV processes for emission reductions. While at the international level, it fosters improved guidance on MRV approaches, including consensus on principles and guidelines for MRV and training programmes.It provides guidance on how best to design and implement REDD, to ensure that forests continue to provide multiple benefits for livelihoods and biodiversity to societies while storing carbon at the same time. Other areas of work include national forest assessments and monitoring of in-country policy and institutional change. The outcomes about the role of satellite remote sensing technologies as a tool for monitoring, assessment, reporting and verification of carbon credits and co-benefits under the REDD mechanism are here presented.

Volumetric Forest Change Detection Through Vhr Satellite Imagery

Science.gov (United States)

Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro

2016-06-01

Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in

GEONEX: Land Monitoring From a New Generation of Geostationary Satellite Sensors

Science.gov (United States)

Nemani, Ramakrishna; Lyapustin, Alexei; Wang, Weile; Wang, Yujie; Hashimoto, Hirofumi; Li, Shuang; Ganguly, Sangram; Michaelis, Andrew; Higuchi, Atsushi; Takaneka, Hideaki;

GEONEX: Land monitoring from a new generation of geostationary satellite sensors

Science.gov (United States)

Nemani, R. R.; Lyapustin, A.; Wang, W.; Ganguly, S.; Wang, Y.; Michaelis, A.; Hashimoto, H.; Li, S.; Higuchi, A.; Huete, A. R.; Yeom, J. M.; camacho De Coca, F.; Lee, T. J.; Takenaka, H.

2017-12-01

The latest generation of geostationary satellites carry sensors such as ABI (Advanced Baseline Imager on GOES-16) and the AHI (Advanced Himawari Imager on Himawari) that closely mimic the spatial and spectral characteristics of Earth Observing System flagship MODIS for monitoring land surface conditions. More importantly they provide observations at 5-15 minute intervals. Such high frequency data offer exciting possibilities for producing robust estimates of land surface conditions by overcoming cloud cover, enabling studies of diurnally varying local-to-regional biosphere-atmosphere interactions, and operational decision-making in agriculture, forestry and disaster management. But the data come with challenges that need special attention. For instance, geostationary data feature changing sun angle at constant view for each pixel, which is reciprocal to sun-synchronous observations, and thus require careful adaptation of EOS algorithms. Our goal is to produce a set of land surface products from geostationary sensors by leveraging NASA's investments in EOS algorithms and in the data/compute facility NEX. The land surface variables of interest include atmospherically corrected surface reflectances, snow cover, vegetation indices and leaf area index (LAI)/fraction of photosynthetically absorbed radiation (FPAR), as well as land surface temperature and fires. In order to get ready to produce operational products over the US from GOES-16 starting 2018, we have utilized 18 months of data from Himawari AHI over Australia to test the production pipeline and the performance of various algorithms for our initial tests. The end-to-end processing pipeline consists of a suite of modules to (a) perform calibration and automatic georeference correction of the AHI L1b data, (b) adopt the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to produce surface spectral reflectances along with compositing schemes and QA, and (c) modify relevant EOS retrieval

Geospatial analysis of creeks evolution in the Indus Delta, Pakistan using multi sensor satellite data

Science.gov (United States)

Ijaz, Muhammad Wajid; Mahar, Rasool Bux; Siyal, Altaf Ali; Anjum, Muhammad Naveed

2018-01-01

Sea level rise (SLR) in response to looming climate change is being considered as a major impediment to coastal areas. Acute wave activities and tidal propagations of semi-diurnal to mixed type are impairing the morphology of the Indus Delta in Pakistan. In this study a synthetic approach has been adopted using multi sensor satellite and ground data in order to integrate the individual effect of topography, oceanic activities and vegetative canopy for deduction of a synergic impact over the morphology of the Indus Delta creeks system from 1972 to 2017. Geomorphologic anomalies in the planform of fourteen major creeks were explored. Spatiotemporal variations suggested that a substantial amount of the delta alluvium had been engulfed by the Arabian Sea. On average, the creeks located on the right side of the Indus River were relatively less wide (3.9 km) than those of on the left side (5.2 km). Zonal statistics calculated with topographic position index (TPI) enabled to understand the tide induced inundation extents. The mangrove canopy on the right side was found greater, which is why tidal basins on that side experienced less erosive activities. Thus, it could be maintained that the coastal sedimentary processes may be monitored effectively with the remotely sensed data and temporal pattern of changes can be quantified for future planning and mitigation of adverse effects.

Mobile satellite service communications tests using a NASA satellite

Science.gov (United States)

Chambers, Katherine H.; Koschmeder, Louis A.; Hollansworth, James E.; ONeill, Jack; Jones, Robert E.; Gibbons, Richard C.

1995-01-01

Emerging applications of commercial mobile satellite communications include satellite delivery of compact disc (CD) quality radio to car drivers who can select their favorite programming as they drive any distance; transmission of current air traffic data to aircraft; and handheld communication of data and images from any remote corner of the world. Experiments with the enabling technologies and tests and demonstrations of these concepts are being conducted before the first satellite is launched by utilizing an existing NASA spacecraft.

California's transition from conventional snowpack measurements to a developing remote sensing capability for water supply forecasting

Science.gov (United States)

Brown, A. J.; Peterson, N.

1980-01-01

California's Snow Survey Program and water supply forecasting procedures are described. A review is made of current activities and program direction on such matters as: the growing statewide network of automatic snow sensors; restrictions on the gathering hydrometeorological data in areas designated as wilderness; the use of satellite communications, which both provides a flexible network without mountaintop repeaters and satisfies the need for unobtrusiveness in wilderness areas; and the increasing operational use of snow covered area (SCA) obtained from satellite imagery, which, combined with water equivalent from snow sensors, provides a high correlation to the volumes and rates of snowmelt runoff. Also examined are the advantages of remote sensing; the anticipated effects of a new input of basin wide index of water equivalent, such as the obtained through microwave techniques, on future forecasting opportunities; and the future direction and goals of the California Snow Surveys Program.

Remote Sensing of shallow sea floor for digital earth environment

International Nuclear Information System (INIS)

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

2014-01-01

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

Biogeography of the Oceans: a Review of Development of Knowledge of Currents, Fronts and Regional Boundaries from Sailing Ships in the Sixteenth Century to Satellite Remote Sensing

Science.gov (United States)

Priede, Imants G.

2014-06-01

The development of knowledge of global biogeography of the oceans from sixteenthcentury European voyages of exploration to present-day use of satellite remote sensing is reviewed in three parts; the pre-satellite era (1513-1977), the satellite era leading to a first global synthesis (1978-1998), and more recent studies since 1998. The Gulf Stream was first identified as a strong open-ocean feature in 1513 and by the eighteenth century, regular transatlantic voyages by sailing ships had established the general patterns of winds and circulation, enabling optimisation of passage times. Differences in water temperature, water colour and species of animals were recognised as important cues for navigation. Systematic collection of information from ships' logs enabled Maury (The Physical Geography of the Sea Harper and Bros. New York 1855) to produce a chart of prevailing winds across the entire world's oceans, and by the early twentieth century the global surface ocean circulation that defines the major biogeographic regions was well-known. This information was further supplemented by data from large-scale plankton surveys. The launch of the Coastal Zone Color Scanner, specifically designed to study living marine resources on board the Nimbus 7 polar orbiting satellite in 1978, marked the advent of the satellite era. Over subsequent decades, correlation of satellite-derived sea surface temperature and chlorophyll data with in situ measurements enabled Longhurst (Ecological Geography of the Sea. Academic Press, New York 1998) to divide the global ocean into 51 ecological provinces with Polar, Westerly Wind, Trade Wind and Coastal Biomes clearly recognisable from earlier subdivisions of the oceans. Satellite imagery with semi-synoptic images of large areas of the oceans greatly aided definition of boundaries between provinces. However, ocean boundaries are dynamic, varying from season to season and year to year. More recent work has focused on the study of variability of

First European Workshop on 'Remote sensing in mineral exploration'

International Nuclear Information System (INIS)

Van Wambeke, L.; Sanderson, D.J.; Dolan, J.M.

1986-01-01

The First European Workshop on 'Remote sensing in mineral exploration' organized by the Commission of the European Communities in February 1985 took stock of the results obtained within the European Community on the application of remote sensing techniques in exploration. The papers presented in this publication are essentially based on data obtained with the first generation of satellites and some airborne experiments. Important progress in data processing and interpretation has been made in the EEC since 1979 and is continuing to be made. The main aim is to provide the EC mining industry with a new tool for exploration. Significant results have already been obtained with the EEC playing an important role in the promotion of this relatively new technique. The main R and D trend is towards an integration of multidata sets (remote sensing, geochemical, geophysical and other data) to improve the methodology for delineating new targets in exploration. Another general trend is the participation of mining companies in remote sensing experiments. Further improvement for exploration is expected in the near future with the thematic mapper and the spot imageries as well as new airborne sensors

Advances in remote sensing of vegetation function and traits

KAUST Repository

Houborg, Rasmus

2015-07-09

Remote sensing of vegetation function and traits has advanced significantly over the past half-century in the capacity to retrieve useful plant biochemical, physiological and structural quantities across a range of spatial and temporal scales. However, the translation of remote sensing signals into meaningful descriptors of vegetation function and traits is still associated with large uncertainties due to complex interactions between leaf, canopy, and atmospheric mediums, and significant challenges in the treatment of confounding factors in spectrum-trait relations. This editorial provides (1) a background on major advances in the remote sensing of vegetation, (2) a detailed timeline and description of relevant historical and planned satellite missions, and (3) an outline of remaining challenges, upcoming opportunities and key research objectives to be tackled. The introduction sets the stage for thirteen Special Issue papers here that focus on novel approaches for exploiting current and future advancements in remote sensor technologies. The described enhancements in spectral, spatial and temporal resolution and radiometric performance provide exciting opportunities to significantly advance the ability to accurately monitor and model the state and function of vegetation canopies at multiple scales on a timely basis.

Technical results of Y-12/IAEA field trial of remote monitoring system

International Nuclear Information System (INIS)

Corbell, B.H.; Whitaker, J.M.; Welch, J.

1997-01-01

A Remote Monitoring System (RMS) field trial has been conducted with the International Atomic Energy Agency (IAEA) on highly enriched uranium materials in a vault at the Oak Ridge Y-12 Plant. The RMS included a variety of Sandia, Oak Ridge, and Aquila sensor technologies which provide containment seals, video monitoring, radiation asset measurements, and container identification data to the on-site DAS (Data Acquisition System) by way of radio-frequency and Echelon LonWorks networks. The accumulated safeguards information was transmitted to the IAEA via satellite (COMSAT/RSI) and international telephone lines. The technologies tested in the remote monitoring environment are the RadCouple, RadSiP, and SmartShelf sensors from the ORSENS (Oak Ridge Sensors for Enhancing Nuclear Safeguards) technologies; the AIMS (Authenticated Item Monitoring System) motion sensor (AMS), AIMS fiber-optic seal (AFOS), ICAM (Image Compression and Authentication Module) video surveillance system, DAS (Data Acquisition System), and DIRS (Data and Image Review Station) from Sandia; and the AssetLAN identification tag, VACOSS-S seal, and Gemini digital surveillance system from Aquila. The field trial was conducted from October 1996 through May 1997. Tests were conducted during the monthly IAEA Interim Inventory Verification (IIV) inspections for evaluation of the equipment. Experience gained through the field trials will allow the technologies to be applied to various monitoring scenarios

Hydroclimatology of Lake Victoria region using hydrologic model and satellite remote sensing data

Directory of Open Access Journals (Sweden)

S. I. Khan

2011-01-01

Full Text Available Study of hydro-climatology at a range of temporal scales is important in understanding and ultimately mitigating the potential severe impacts of hydrological extreme events such as floods and droughts. Using daily in-situ data over the last two decades combined with the recently available multiple-years satellite remote sensing data, we analyzed and simulated, with a distributed hydrologic model, the hydro-climatology in Nzoia, one of the major contributing sub-basins of Lake Victoria in the East African highlands. The basin, with a semi arid climate, has no sustained base flow contribution to Lake Victoria. The short spell of high discharge showed that rain is the prime cause of floods in the basin. There is only a marginal increase in annual mean discharge over the last 21 years. The 2-, 5- and 10- year peak discharges, for the entire study period showed that more years since the mid 1990's have had high peak discharges despite having relatively less annual rain. The study also presents the hydrologic model calibration and validation results over the Nzoia basin. The spatiotemporal variability of the water cycle components were quantified using a hydrologic model, with in-situ and multi-satellite remote sensing datasets. The model is calibrated using daily observed discharge data for the period between 1985 and 1999, for which model performance is estimated with a Nash Sutcliffe Efficiency (NSCE of 0.87 and 0.23% bias. The model validation showed an error metrics with NSCE of 0.65 and 1.04% bias. Moreover, the hydrologic capability of satellite precipitation (TRMM-3B42 V6 is evaluated. In terms of reconstruction of the water cycle components the spatial distribution and time series of modeling results for precipitation and runoff showed considerable agreement with the monthly model runoff estimates and gauge observations. Runoff values responded to precipitation events that occurred across the catchment during the wet season from March to

Quantifying the clear-sky bias of satellite-derived infrared LST

Science.gov (United States)

Ermida, S. L.; Trigo, I. F.; DaCamara, C.

2017-12-01

Land surface temperature (LST) is one of the most relevant parameters when addressing the physical processes that take place at the surface of the Earth. Satellite data are particularly appropriate for measuring LST over the globe with high temporal resolution. Remote-sensed LST estimation from space-borne sensors has been systematically performed over the Globe for nearly 3 decades and geostationary LST climate data records are now available. The retrieval of LST from satellite observations generally relies on measurements in the thermal infrared (IR) window. Although there is a large number of IR sensors on-board geostationary satellites and polar orbiters suitable for LST retrievals with different temporal and spatial resolutions, the use of IR observations limits LST estimates to clear sky conditions. As a consequence, climate studies based on IR LST are likely to be affected by the restriction of LST data to cloudless conditions. However, such "clear sky bias" has never been quantified and, therefore, the actual impact of relying only on clear sky data is still to be determined. On the other hand, an "all-weather" global LST database may be set up based on passive microwave (MW) measurements which are much less affected by clouds. An 8-year record of all-weather MW LST is here used to quantify the clear-sky bias of IR LST at global scale based on MW observations performed by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) onboard NASA's Aqua satellite. Selection of clear-sky and cloudy pixels is based on information derived from measurements performed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the same satellite.

The potential of satellite-observed crop phenology to enhance yield gap assessments in smallholder landscapes

Directory of Open Access Journals (Sweden)

John M A Duncan

2015-08-01

Full Text Available Many of the undernourished people on the planet obtain their entitlements to food via agricultural-based livelihood strategies, often on underperforming croplands and smallholdings. In this context, expanding cropland extent is not a viable strategy for smallholders to meet their food needs. Therefore, attention must shift to increasing productivity on existing plots and ensuring yield gaps do not widen. Thus, supporting smallholder farmers to sustainably increase the productivity of their lands is one part of a complex solution to realising universal food security. However, the information (e.g. location and causes of cropland underperformance required to support measures to close yield gaps in smallholder landscapes are often not available. This paper reviews the potential of crop phenology, observed from satellites carrying remote sensing sensors, to fill this information gap. It is suggested that on a theoretical level phenological approaches can reveal greater intra-cropland thematic detail, and increase the accuracy of crop extent maps and crop yield estimates. However, on a practical level the spatial mismatch between the resolution at which crop phenology can be estimated from satellite remote sensing data and the scale of yield variability in smallholder croplands inhibits its use in this context. Similarly, the spatial coverage of remote sensing-derived phenology offers potential for integration with ancillary spatial datasets to identify causes of yield gaps. To reflect the complexity of smallholder cropping systems requires ancillary datasets at fine spatial resolutions which, often, are not available. This further precludes the use of crop phenology in attempts to unpick the causes of yield gaps. Research agendas should focus on generating fine spatial resolution crop phenology, either via data fusion or through new sensors (e.g. Sentinel-2 in smallholder croplands. This has potential to transform the applied use of remote sensing

Virtual Satellite Construction and Application for Image Classification

International Nuclear Information System (INIS)

Su, W G; Su, F Z; Zhou, C H

2014-01-01

Nowadays, most remote sensing image classification uses single satellite remote sensing data, so the number of bands and band spectral width is consistent. In addition, observed phenomenon such as land cover have the same spectral signature, which causes the classification accuracy to decrease as different data have unique characteristic. Therefore, this paper analyzes different optical remote sensing satellites, comparing the spectral differences and proposes the ideas and methods to build a virtual satellite. This article illustrates the research on the TM, HJ-1 and MODIS data. We obtained the virtual band X 0 through these satellites' bands combined it with the 4 bands of a TM image to build a virtual satellite with five bands. Based on this, we used these data for image classification. The experimental results showed that the virtual satellite classification results of building land and water information were superior to the HJ-1 and TM data respectively

Distributed Remote Vector Gaussian Source Coding for Wireless Acoustic Sensor Networks

DEFF Research Database (Denmark)

Zahedi, Adel; Østergaard, Jan; Jensen, Søren Holdt

2014-01-01

In this paper, we consider the problem of remote vector Gaussian source coding for a wireless acoustic sensor network. Each node receives messages from multiple nodes in the network and decodes these messages using its own measurement of the sound field as side information. The node’s measurement...... and the estimates of the source resulting from decoding the received messages are then jointly encoded and transmitted to a neighboring node in the network. We show that for this distributed source coding scenario, one can encode a so-called conditional sufficient statistic of the sources instead of jointly...

Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Methods and Applications

Science.gov (United States)

Quattrochi, Dale A.; Luvall, Jeffrey C.

1998-01-01

Thermal Infrared (TIR) remote sensing data can provide important measurements of surface energy fluxes and temperatures, which are integral to understanding landscape processes and responses. One example of this is the successful application of TIR remote sensing data to estimate evapotranspiration and soil moisture, where results from a number of studies suggest that satellite-based measurements from TIR remote sensing data can lead to more accurate regional-scale estimates of daily evapotranspiration. With further refinement in analytical techniques and models, the use of TIR data from airborne and satellite sensors could be very useful for parameterizing surface moisture conditions and developing better simulations of landscape energy exchange over a variety of conditions and space and time scales. Thus, TIR remote sensing data can significantly contribute to the observation, measurement, and analysis of energy balance characteristics (i.e., the fluxes and redistribution of thermal energy within and across the land surface) as an implicit and important aspect of landscape dynamics and landscape functioning. The application of TIR remote sensing data in landscape ecological studies has been limited, however, for several fundamental reasons that relate primarily to the perceived difficulty in use and availability of these data by the landscape ecology community, and from the fragmentation of references on TIR remote sensing throughout the scientific literature. It is our purpose here to provide evidence from work that has employed TIR remote sensing for analysis of landscape characteristics to illustrate how these data can provide important data for the improved measurement of landscape energy response and energy flux relationships. We examine the direct or indirect use of TIR remote sensing data to analyze landscape biophysical characteristics, thereby offering some insight on how these data can be used more robustly to further the understanding and modeling of

From silk to satellite: Half a century of ocean colour anomalies in the Northeast Atlantic

KAUST Repository

Raitsos, Dionysios E.

2014-04-23

Changes in phytoplankton dynamics influence marine biogeochemical cycles, climate processes, and food webs, with substantial social and economic consequences. Large-scale estimation of phytoplankton biomass was possible via ocean colour measurements from two remote sensing satellites - the Coastal Zone Colour Scanner (CZCS, 1979-1986) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 1998-2010). Due to the large gap between the two satellite eras and differences in sensor characteristics, comparison of the absolute values retrieved from the two instruments remains challenging. Using a unique in situ ocean colour dataset that spans more than half a century, the two satellite-derived chlorophyll-a (Chl-a) eras are linked to assess concurrent changes in phytoplankton variability and bloom timing over the Northeast Atlantic Ocean and North Sea. Results from this unique re-analysis reflect a clear increasing pattern of Chl-a, a merging of the two seasonal phytoplankton blooms producing a longer growing season and higher seasonal biomass, since the mid-1980s. The broader climate plays a key role in Chl-a variability as the ocean colour anomalies parallel the oscillations of the Northern Hemisphere Temperature (NHT) since 1948. © 2013 John Wiley & Sons Ltd.

From silk to satellite: Half a century of ocean colour anomalies in the Northeast Atlantic

KAUST Repository

Raitsos, Dionysios E.; Pradhan, Yaswant; Lavender, Sam; Hoteit, Ibrahim; McQuatters-Gollop, Abigail L.; Reid, Philip Chris; Richardson, Anthony J.

2014-01-01

Changes in phytoplankton dynamics influence marine biogeochemical cycles, climate processes, and food webs, with substantial social and economic consequences. Large-scale estimation of phytoplankton biomass was possible via ocean colour measurements from two remote sensing satellites - the Coastal Zone Colour Scanner (CZCS, 1979-1986) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 1998-2010). Due to the large gap between the two satellite eras and differences in sensor characteristics, comparison of the absolute values retrieved from the two instruments remains challenging. Using a unique in situ ocean colour dataset that spans more than half a century, the two satellite-derived chlorophyll-a (Chl-a) eras are linked to assess concurrent changes in phytoplankton variability and bloom timing over the Northeast Atlantic Ocean and North Sea. Results from this unique re-analysis reflect a clear increasing pattern of Chl-a, a merging of the two seasonal phytoplankton blooms producing a longer growing season and higher seasonal biomass, since the mid-1980s. The broader climate plays a key role in Chl-a variability as the ocean colour anomalies parallel the oscillations of the Northern Hemisphere Temperature (NHT) since 1948. © 2013 John Wiley & Sons Ltd.

Smart multi-level tool for remote patient monitoring based on a wireless sensor network and mobile augmented reality.

Science.gov (United States)

González, Fernando Cornelio Jiménez; Villegas, Osslan Osiris Vergara; Ramírez, Dulce Esperanza Torres; Sánchez, Vianey Guadalupe Cruz; Domínguez, Humberto Ochoa

2014-09-16

Technological innovations in the field of disease prevention and maintenance of patient health have enabled the evolution of fields such as monitoring systems. One of the main advances is the development of real-time monitors that use intelligent and wireless communication technology. In this paper, a system is presented for the remote monitoring of the body temperature and heart rate of a patient by means of a wireless sensor network (WSN) and mobile augmented reality (MAR). The combination of a WSN and MAR provides a novel alternative to remotely measure body temperature and heart rate in real time during patient care. The system is composed of (1) hardware such as Arduino microcontrollers (in the patient nodes), personal computers (for the nurse server), smartphones (for the mobile nurse monitor and the virtual patient file) and sensors (to measure body temperature and heart rate), (2) a network layer using WiFly technology, and (3) software such as LabView, Android SDK, and DroidAR. The results obtained from tests show that the system can perform effectively within a range of 20 m and requires ten minutes to stabilize the temperature sensor to detect hyperthermia, hypothermia or normal body temperature conditions. Additionally, the heart rate sensor can detect conditions of tachycardia and bradycardia.

Terra and Aqua MODIS Design, Radiometry, and Geometry in Support of Land Remote Sensing

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Xiong, Xiaoxiong; Wolfe, Robert; Barnes, William; Guenther, Bruce; Vermote, Eric; Saleous, Nazmi; Salomonson, Vincent

2011-01-01

The NASA Earth Observing System (EOS) mission includes the construction and launch of two nearly identical Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. The MODIS proto-flight model (PFM) is onboard the EOS Terra satellite (formerly EOS AM-1) launched on December 18, 1999 and hereafter referred to as Terra MODIS. Flight model-1 (FM1) is onboard the EOS Aqua satellite (formerly EOS PM-1) launched on May 04, 2002 and referred to as Aqua MODIS. MODIS was developed based on the science community s desire to collect multiyear continuous datasets for monitoring changes in the Earth s land, oceans and atmosphere, and the human contributions to these changes. It was designed to measure discrete spectral bands, which includes many used by a number of heritage sensors, and thus extends the heritage datasets to better understand both long- and short-term changes in the global environment (Barnes and Salomonson 1993; Salomonson et al. 2002; Barnes et al. 2002). The MODIS development, launch, and operation were managed by NASA/Goddard Space Flight Center (GSFC), Greenbelt, Maryland. The sensors were designed, built, and tested by Raytheon/ Santa Barbara Remote Sensing (SBRS), Goleta, California. Each MODIS instrument offers 36 spectral bands, which span the spectral region from the visible (0.41 m) to long-wave infrared (14.4 m). MODIS collects data at three different nadir spatial resolutions: 0.25, 0.5, and 1 km. Key design specifications, such as spectral bandwidths, typical scene radiances, required signal-to-noise ratios (SNR) or noise equivalent temperature differences (NEDT), and primary applications of each MODIS spectral band are summarized in Table 7.1. These parameters were the basis for the MODIS design. More details on the evolution of the NASA EOS and development of the MODIS instruments are provided in Chap. 1. This chapter focuses on the MODIS sensor design, radiometry, and geometry as they apply to land remote sensing. With near

A Method for Application of Classification Tree Models to Map Aquatic Vegetation Using Remotely Sensed Images from Different Sensors and Dates

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Ying Cai

2012-09-01

Full Text Available In previous attempts to identify aquatic vegetation from remotely-sensed images using classification trees (CT, the images used to apply CT models to different times or locations necessarily originated from the same satellite sensor as that from which the original images used in model development came, greatly limiting the application of CT. We have developed an effective normalization method to improve the robustness of CT models when applied to images originating from different sensors and dates. A total of 965 ground-truth samples of aquatic vegetation types were obtained in 2009 and 2010 in Taihu Lake, China. Using relevant spectral indices (SI as classifiers, we manually developed a stable CT model structure and then applied a standard CT algorithm to obtain quantitative (optimal thresholds from 2009 ground-truth data and images from Landsat7-ETM+, HJ-1B-CCD, Landsat5-TM and ALOS-AVNIR-2 sensors. Optimal CT thresholds produced average classification accuracies of 78.1%, 84.7% and 74.0% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. However, the optimal CT thresholds for different sensor images differed from each other, with an average relative variation (RV of 6.40%. We developed and evaluated three new approaches to normalizing the images. The best-performing method (Method of 0.1% index scaling normalized the SI images using tailored percentages of extreme pixel values. Using the images normalized by Method of 0.1% index scaling, CT models for a particular sensor in which thresholds were replaced by those from the models developed for images originating from other sensors provided average classification accuracies of 76.0%, 82.8% and 68.9% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. Applying the CT models developed for normalized 2009 images to 2010 images resulted in high classification (78.0%–93.3% and overall (92.0%–93.1% accuracies. Our

Comparison of different sensors for river discharge estimation from space

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Tarpanelli, Angelica; Brocca, Luca; Barbetta, Silvia; Moramarco, Tommaso

2013-04-01

River discharge is an important quantity of the hydrologic cycle and it is essential for both scientific and operational applications related to water resources management and flood risk prevention. The absence of flow measurements along the natural channels and, sometimes, the inaccessibility to remote areas contribute to make the discharge estimation difficult. In recent years, the availability of remote sensing data is steadily increasing and the great potential of satellite sensors to be used for discharge estimation has been already demonstrated. In particular, recent advances in radar altimetry technology have improved the accuracy in the monitoring of water height of large rivers and lakes located in ungauged or poorly gauged inland regions. Additionally, although not specifically dedicated sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) have also the potential to provide river discharge estimates. In this context, this study uses data provided by MODIS onboard AQUA satellite and by altimetry onboard ERS-2 and ENVISAT satellites for discharge estimation along Po River (North Italy) where in-situ observations are available from January 2002 to December 2010. The MODIS-derive discharge is obtained exploiting the different behavior of water and land in the Near Infrared (NIR) portion of the electromagnetic spectrum (MODIS channel 2). The ratio of reflectance values between two pixels located within and outside the river increases with the presence of the water and, hence, with discharge (or velocity). In a previous study, a regional relationship between the reflectance ratio and the flow velocity is derived by using MODIS data at four river reaches along the Po River. Altimetry-derived water levels are firstly compared with in-situ observed water levels in order to verify their accuracy. Successively, discharge is estimated from velocity (MODIS) and water level (altimeter) data by using simplified hydraulic relationships that incorporate

Satellite Remote Sensing of Severe Haze Pollution over Eastern China on June, 2012

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Christopher, S. A.; Feng, N.; Guo, Y.; Hong, S.

2012-12-01

Severe yellow haze hit a vast portion of Eastern China during the second week on June, 2012, as large area in Hubei, Henan, Hunan, Jiangsu, Anhui, Jiangxi, Shandong, Zhejiang provinces and Shanghai city were covered by lingering haze. This massive haze conditions caused considerable inconvenience to people's daily lives. Previous global air quality studies have also shown that Eastern China is one of regions with highest fine particulate matter (PM2.5) concentrations around the world. In this study, we estimate spatial and temporal variations of PM2.5 concentrations using satellite observations of this severe haze pollution on June, 2012. Satellite derived Aerosol Optical Thickness (AOT), sites measured hourly PM2.5 and meteorological fields from surface are statistically correlated based on a multiple regression model. We also explore the utility of higher spatial resolution aerosol retrieval from MODIS. Both satellite-derived and in-situ values have peak daily mean concentrations of approximately 400 μg m-3 on June 12th, 2012 in the City of Wuhan, which is nearly 10 times of the primary standard of PM2.5 concentration of China's "Ambient Air Quality Standards" (35 μg m-3). Cities in the Eastern China, e.g. Nanjing, Hangzhou and Nanchang, have also witnessed similar peak values, along with heavy smog during the same period. Satellite observations in this case study demonstrate that the transport of smoke plumes can be one of the main drivers of regional haze pollution over Eastern China. Comparing to the U.S., current limited ground-based stations is one of the biggest problem to develop the PM2.5 monitoring program over China. Our results may suggest the potential of combining satellite remote sensing with atmospheric model to map the PM2.5 spatial concentration over the nationwide level, which can further accelerate the construction of PM2.5 monitoring network over China.

Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

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Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

2013-12-01

Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output

Radiometric, geometric, and image quality assessment of ALOS AVNIR-2 and PRISM sensors

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Saunier, S.; Goryl, P.; Chander, G.; Santer, R.; Bouvet, M.; Collet, B.; Mambimba, A.; Kocaman, Aksakal S.

2010-01-01

The Advanced Land Observing Satellite (ALOS) was launched on January 24, 2006, by a Japan Aerospace Exploration Agency (JAXA) H-IIA launcher. It carries three remote-sensing sensors: 1) the Advanced Visible and Near-Infrared Radiometer type 2 (AVNIR-2); 2) the Panchromatic Remote-Sensing Instrument for Stereo Mapping (PRISM); and 3) the Phased-Array type L-band Synthetic Aperture Radar (PALSAR). Within the framework of ALOS Data European Node, as part of the European Space Agency (ESA), the European Space Research Institute worked alongside JAXA to provide contributions to the ALOS commissioning phase plan. This paper summarizes the strategy that was adopted by ESA to define and implement a data verification plan for missions operated by external agencies; these missions are classified by the ESA as third-party missions. The ESA was supported in the design and execution of this plan by GAEL Consultant. The verification of ALOS optical data from PRISM and AVNIR-2 sensors was initiated 4 months after satellite launch, and a team of principal investigators assembled to provide technical expertise. This paper includes a description of the verification plan and summarizes the methodologies that were used for radiometric, geometric, and image quality assessment. The successful completion of the commissioning phase has led to the sensors being declared fit for operations. The consolidated measurements indicate that the radiometric calibration of the AVNIR-2 sensor is stable and agrees with the Landsat-7 Enhanced Thematic Mapper Plus and the Envisat MEdium-Resolution Imaging Spectrometer calibration. The geometrical accuracy of PRISM and AVNIR-2 products improved significantly and remains under control. The PRISM modulation transfer function is monitored for improved characterization.

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Revised

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Fargion, Giulietta S.; Mueller, James L.

2000-01-01

The document stipulates protocols for measuring bio-optical and radiometric data for the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities and algorithm development. This document supersedes the earlier version (Mueller and Austin 1995) published as Volume 25 in the SeaWiFS Technical Report Series. This document marks a significant departure from, and improvement on, theformat and content of Mueller and Austin (1995). The authorship of the protocols has been greatly broadened to include experts specializing in some key areas. New chapters have been added to provide detailed and comprehensive protocols for stability monitoring of radiometers using portable sources, abovewater measurements of remote-sensing reflectance, spectral absorption measurements for discrete water samples, HPLC pigment analysis and fluorometric pigment analysis. Protocols were included in Mueller and Austin (1995) for each of these areas, but the new treatment makes significant advances in each topic area. There are also new chapters prescribing protocols for calibration of sun photometers and sky radiance sensors, sun photometer and sky radiance measurements and analysis, and data archival. These topic areas were barely mentioned in Mueller and Austin (1995).

Uniform competency-based local feature extraction for remote sensing images

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Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

Remote sensing applications for the dam industry

Energy Technology Data Exchange (ETDEWEB)

Pryse-Phillips, A.; Woolgar, R. [Hatch Ltd., St. John' s, NL (Canada); Puestow, T.; Warren, S. [Memorial Univ. of Newfoundland, St. John' s, NL (Canada). C-Core; Rogers, K. [Nalcor Energy, St. John' s, NL (Canada); Khan, A. [Government of Newfoundland and Labrador, St. Johns, NL (Canada)

2009-07-01

There has been an increase in the earth observation missions providing satellite imagery for operational monitoring applications. This technique has been found to be especially useful for the surveillance of large, remote areas, which is challenging to achieve in a cost-effective manner by conventional field-based or aerial means. This paper discussed the utility of satellite-based monitoring for different applications relevant to hydrology and water resources management. Emphasis was placed on the monitoring of river ice covers in near, real-time and water resources management. The paper first outlined river ice monitoring using remote sensing on the Lower Churchill River. The benefits of remote sensing over traditional survey methods for the dam industry was then outlined. Satellite image acquisition and interpretation for the Churchill River was then presented. Several images were offered. Watershed physiographic characterization using remote sensing was also described. It was concluded that satellite imagery proved to be a useful tool to develop physiographic characteristics when conducting rainfall-runoff modelling. 3 refs., 1 tab., 11 figs.

Remote inspection with multi-copters, radiological sensors and SLAM techniques

Science.gov (United States)

Carvalho, Henrique; Vale, Alberto; Marques, Rúben; Ventura, Rodrigo; Brouwer, Yoeri; Gonçalves, Bruno

2018-01-01

Activated material can be found in different scenarios, such as in nuclear reactor facilities or medical facilities (e.g. in positron emission tomography commonly known as PET scanning). In addition, there are unexpected scenarios resulting from possible accidents, or where dangerous material is hidden for terrorism attacks using nuclear weapons. Thus, a technological solution is important to cope with fast and reliable remote inspection. The multi-copter is a common type of Unmanned Aerial Vehicle (UAV) that provides the ability to perform a first radiological inspection in the described scenarios. The paper proposes a solution with a multi-copter equipped with on-board sensors to perform a 3D reconstruction and a radiological mapping of the scenario. A depth camera and a Geiger-Müler counter are the used sensors. The inspection is performed in two steps: i) a 3D reconstruction of the environment and ii) radiation activity inference to localise and quantify sources of radiation. Experimental results were achieved with real 3D data and simulated radiation activity. Experimental tests with real sources of radiation are planned in the next iteration of the work.

Remote inspection with multi-copters, radiological sensors and SLAM techniques

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Carvalho Henrique

2018-01-01

Full Text Available Activated material can be found in different scenarios, such as in nuclear reactor facilities or medical facilities (e.g. in positron emission tomography commonly known as PET scanning. In addition, there are unexpected scenarios resulting from possible accidents, or where dangerous material is hidden for terrorism attacks using nuclear weapons. Thus, a technological solution is important to cope with fast and reliable remote inspection. The multi-copter is a common type of Unmanned Aerial Vehicle (UAV that provides the ability to perform a first radiological inspection in the described scenarios. The paper proposes a solution with a multi-copter equipped with on-board sensors to perform a 3D reconstruction and a radiological mapping of the scenario. A depth camera and a Geiger-Müler counter are the used sensors. The inspection is performed in two steps: i a 3D reconstruction of the environment and ii radiation activity inference to localise and quantify sources of radiation. Experimental results were achieved with real 3D data and simulated radiation activity. Experimental tests with real sources of radiation are planned in the next iteration of the work.

Australian Soil Moisture Field Experiments in Support of Soil Moisture Satellite Observations

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