REVIEW OF METHODS FOR REMOTE SENSING OF ATMOSPHERIC EMISSIONS FROM STATIONARY SOURCES

EPA Science Inventory

The report reviews the commercially available and developing technologies for the application of remote sensing to the measurement of source emissions. The term 'remote sensing technology', as applied in the report, means the detection or concentration measurement of trace atmosp...

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

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

Crosscutting Airborne Remote Sensing Technologies for Oil and Gas and Earth Science Applications

NASA Technical Reports Server (NTRS)

Aubrey, A. D.; Frankenberg, C.; Green, R. O.; Eastwood, M. L.; Thompson, D. R.; Thorpe, A. K.

2015-01-01

Airborne imaging spectroscopy has evolved dramatically since the 1980s as a robust remote sensing technique used to generate 2-dimensional maps of surface properties over large spatial areas. Traditional applications for passive airborne imaging spectroscopy include interrogation of surface composition, such as mapping of vegetation diversity and surface geological composition. Two recent applications are particularly relevant to the needs of both the oil and gas as well as government sectors: quantification of surficial hydrocarbon thickness in aquatic environments and mapping atmospheric greenhouse gas components. These techniques provide valuable capabilities for petroleum seepage in addition to detection and quantification of fugitive emissions. New empirical data that provides insight into the source strength of anthropogenic methane will be reviewed, with particular emphasis on the evolving constraints enabled by new methane remote sensing techniques. Contemporary studies attribute high-strength point sources as significantly contributing to the national methane inventory and underscore the need for high performance remote sensing technologies that provide quantitative leak detection. Imaging sensors that map spatial distributions of methane anomalies provide effective techniques to detect, localize, and quantify fugitive leaks. Airborne remote sensing instruments provide the unique combination of high spatial resolution (<1 m) and large coverage required to directly attribute methane emissions to individual emission sources. This capability cannot currently be achieved using spaceborne sensors. In this study, results from recent NASA remote sensing field experiments focused on point-source leak detection, will be highlighted. This includes existing quantitative capabilities for oil and methane using state-of-the-art airborne remote sensing instruments. While these capabilities are of interest to NASA for assessment of environmental impact and global climate change, industry similarly seeks to detect and localize leaks of both oil and methane across operating fields. In some cases, higher sensitivities desired for upstream and downstream applications can only be provided by new airborne remote sensing instruments tailored specifically for a given application. There exists a unique opportunity for alignment of efforts between commercial and government sectors to advance the next generation of instruments to provide more sensitive leak detection capabilities, including those for quantitative source strength determination.

Airplane detection in remote sensing images using convolutional neural networks

NASA Astrophysics Data System (ADS)

Ouyang, Chao; Chen, Zhong; Zhang, Feng; Zhang, Yifei

2018-03-01

Airplane detection in remote sensing images remains a challenging problem and has also been taking a great interest to researchers. In this paper we propose an effective method to detect airplanes in remote sensing images using convolutional neural networks. Deep learning methods show greater advantages than the traditional methods with the rise of deep neural networks in target detection, and we give an explanation why this happens. To improve the performance on detection of airplane, we combine a region proposal algorithm with convolutional neural networks. And in the training phase, we divide the background into multi classes rather than one class, which can reduce false alarms. Our experimental results show that the proposed method is effective and robust in detecting airplane.

Remote Sensing Plant Stress Using Combined Fluorescence and Reflectance Measurements for Early Detection of Defoliants within the Battlefield Environment

DTIC Science & Technology

2012-10-02

Sensing Imagery, Instituto de Agricultura Sostenible, Córdoba, Spain Young, D.R. 2007. Leaf to landscape in a barrier island environment.” Workshop...on Vegetation Stress Detection with Remote Sensing Imagery, Instituto de Agricultura Sostenible, Córdoba, Spain Young, D.R. and J.C. Naumann. 2007

A change detection method for remote sensing image based on LBP and SURF feature

NASA Astrophysics Data System (ADS)

Hu, Lei; Yang, Hao; Li, Jin; Zhang, Yun

2018-04-01

Finding the change in multi-temporal remote sensing image is important in many the image application. Because of the infection of climate and illumination, the texture of the ground object is more stable relative to the gray in high-resolution remote sensing image. And the texture features of Local Binary Patterns (LBP) and Speeded Up Robust Features (SURF) are outstanding in extracting speed and illumination invariance. A method of change detection for matched remote sensing image pair is present, which compares the similarity by LBP and SURF to detect the change and unchanged of the block after blocking the image. And region growing is adopted to process the block edge zone. The experiment results show that the method can endure some illumination change and slight texture change of the ground object.

Some fundamental concepts in remote sensing

NASA Technical Reports Server (NTRS)

1982-01-01

The term remote sensing is defined as well as ideas such as class, pattern, feature, pattern recognition, feature extraction, and theme. The electromagnetic spectrum is examined especially those wavelength regions available to remote sensing. Relevant energy and wave propagation laws are discussed and the characteristics of emitted and reflected radiation and their detection are investigated. The identification of classes by their spectral signatures, the multispectral approach, and the principal types of sensors and platforms used in remote sensing are also considered.

NASA Remote Sensing Research as Applied to Archaeology

NASA Technical Reports Server (NTRS)

Giardino, Marco J.; Thomas, Michael R.

2002-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Feasibility of remote sensing for detecting thermal pollution. Part 1: Feasibility study. Part 2: Implementation plan. [coastal ecology

NASA Technical Reports Server (NTRS)

Veziroglu, T. N.; Lee, S. S.

1973-01-01

A feasibility study for the development of a three-dimensional generalized, predictive, analytical model involving remote sensing, in-situ measurements, and an active system to remotely measure turbidity is presented. An implementation plan for the development of the three-dimensional model and for the application of remote sensing of temperature and turbidity measurements is outlined.

Educational activities of remote sensing archaeology (Conference Presentation)

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

People, Places and Pixels: Remote Sensing in the Service of Society

NASA Technical Reports Server (NTRS)

Lulla, Kamlesh

2003-01-01

What is the role of Earth remote sensing and other geospatial technologies in our society? Recent global events have brought into focus the role of geospatial science and technology such as remote sensing, GIS, GPS in assisting the professionals who are responsible for operations such as rescue and recovery of sites after a disaster or a terrorist act. This paper reviews the use of recent remote sensing products from satellites such as IKONOS in these efforts. Aerial and satellite imagery used in land mine detection has been evaluated and the results of this evaluation will be discussed. Synopsis of current and future ISS Earth Remote Sensing capabilities will be provided. The role of future missions in humanitarian use of remote sensing will be explored.

Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application.

PubMed

Chen, Pengyun; Zhang, Yichen; Jia, Zhenhong; Yang, Jie; Kasabov, Nikola

2017-06-06

Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information's relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Markov Tree model (NSCT-HMT) for change detection of remote sensing images. First, the ENVI software is used to calibrate the original remote sensing images. After that, the mean-ratio operation is adopted to obtain the difference image that will be denoised by the NSCT-HMT model. Then, using the Fuzzy Local Information C-means (FLICM) algorithm, the difference image is divided into the change area and unchanged area. The proposed algorithm is applied to a real remote sensing data set. The application results show that the proposed algorithm can effectively suppress clutter noise, and retain more detailed information from the original images. The proposed algorithm has higher detection accuracy than the Markov Random Field-Fuzzy C-means (MRF-FCM), the non-subsampled contourlet transform-Fuzzy C-means clustering (NSCT-FCM), the pointwise approach and graph theory (PA-GT), and the Principal Component Analysis-Nonlocal Means (PCA-NLM) denosing algorithm. Finally, the five algorithms are used to detect the southern boundary of the Gurbantunggut Desert in Xinjiang Uygur Autonomous Region of China, and the results show that the proposed algorithm has the best effect on real remote sensing image change detection.

Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application

PubMed Central

Chen, Pengyun; Zhang, Yichen; Jia, Zhenhong; Yang, Jie; Kasabov, Nikola

2017-01-01

Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information’s relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Markov Tree model (NSCT-HMT) for change detection of remote sensing images. First, the ENVI software is used to calibrate the original remote sensing images. After that, the mean-ratio operation is adopted to obtain the difference image that will be denoised by the NSCT-HMT model. Then, using the Fuzzy Local Information C-means (FLICM) algorithm, the difference image is divided into the change area and unchanged area. The proposed algorithm is applied to a real remote sensing data set. The application results show that the proposed algorithm can effectively suppress clutter noise, and retain more detailed information from the original images. The proposed algorithm has higher detection accuracy than the Markov Random Field-Fuzzy C-means (MRF-FCM), the non-subsampled contourlet transform-Fuzzy C-means clustering (NSCT-FCM), the pointwise approach and graph theory (PA-GT), and the Principal Component Analysis-Nonlocal Means (PCA-NLM) denosing algorithm. Finally, the five algorithms are used to detect the southern boundary of the Gurbantunggut Desert in Xinjiang Uygur Autonomous Region of China, and the results show that the proposed algorithm has the best effect on real remote sensing image change detection. PMID:28587299

Airborne remote sensing to detect greenbug stress to wheat

USDA-ARS?s Scientific Manuscript database

Vegetation indices calculated from the quantity of reflected electromagnetic radiation have been used to quantify levels of stress to plants. Greenbugs cause stress to wheat plants and therefore multi-spectral remote sensing may be useful for detecting greenbug infested wheat fields. The objective...

Ship detection using STFT sea background statistical modeling for large-scale oceansat remote sensing image

NASA Astrophysics Data System (ADS)

Wang, Lixia; Pei, Jihong; Xie, Weixin; Liu, Jinyuan

2018-03-01

Large-scale oceansat remote sensing images cover a big area sea surface, which fluctuation can be considered as a non-stationary process. Short-Time Fourier Transform (STFT) is a suitable analysis tool for the time varying nonstationary signal. In this paper, a novel ship detection method using 2-D STFT sea background statistical modeling for large-scale oceansat remote sensing images is proposed. First, the paper divides the large-scale oceansat remote sensing image into small sub-blocks, and 2-D STFT is applied to each sub-block individually. Second, the 2-D STFT spectrum of sub-blocks is studied and the obvious different characteristic between sea background and non-sea background is found. Finally, the statistical model for all valid frequency points in the STFT spectrum of sea background is given, and the ship detection method based on the 2-D STFT spectrum modeling is proposed. The experimental result shows that the proposed algorithm can detect ship targets with high recall rate and low missing rate.

Remote Sensing Wind and Wind Shear System.

DTIC Science & Technology

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

Analysis of the moderate resolution imaging spectroradiometer contextual algorithm for small fire detection, Journal of Applied Remote Sensing Vol.3

Treesearch

W. Wang; J.J. Qu; X. Hao; Y. Liu

2009-01-01

In the southeastern United States, most wildland fires are of low intensity. A substantial number of these fires cannot be detected by the MODIS contextual algorithm. To improve the accuracy of fire detection for this region, the remote-sensed characteristics of these fires have to be...

Why Infrared?

ERIC Educational Resources Information Center

Harris, J. R.

1973-01-01

Discusses applications of techniques developed for the remote sensing of infrared radiation. In addition to military applications, remote sensing has become important in collecting environmental data and detecting ecological problems. (JR)

Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

NASA Technical Reports Server (NTRS)

Pelletier, R. E.; Griffin, R. H.

1985-01-01

The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

76 FR 66018 - Endangered and Threatened Wildlife and Plants; Delisting of the Plant Frankenia johnstonii

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-25

... johnstonii will be implemented for 9 years, and will include habitat evaluation using remote sensing of 20 populations and on-site monitoring of 10 populations. Habitat assessments with remote sensing will occur about... site visit will be triggered from remote sensing analysis when a 30 percent loss of habitat is detected...

Remote sensing of wet lands in irrigated areas

NASA Technical Reports Server (NTRS)

Ham, H. H.

1972-01-01

The use of airborne remote sensing techniques to: (1) detect drainage problem areas, (2) delineate the problem in terms of areal extent, depth to the water table, and presence of excessive salinity, and (3) evaluate the effectiveness of existing subsurface drainage facilities, is discussed. Experimental results show that remote sensing, as demonstrated in this study and as presently constituted and priced, does not represent a practical alternative as a management tool to presently used visual and conventional photographic methods in the systematic and repetitive detection and delineation of wetlands.

Detecting Landscape Change: The View from Above

ERIC Educational Resources Information Center

Porter, Jess

2008-01-01

This article will demonstrate an approach for discovering and assessing local landscape change through the use of remotely sensed images. A brief introduction to remotely sensed imagery is followed by a discussion of relevant ways to introduce this technology into the college science classroom. The Map Detective activity demonstrates the…

Progress in the Development of Practical Remote Detection of Icing Conditions

NASA Technical Reports Server (NTRS)

Reehorst, Andrew; Politovich, Marcia K.; Zednik, Stephan; Isaac, George A.; Cober, Stewart

2006-01-01

The NASA Icing Remote Sensing System (NIRSS) has been under definition and development at NASA Glenn Research Center since 1997. The goal of this development activity is to produce and demonstrate the required sensing and data processing technologies required to accurately remotely detect and measure icing conditions aloft. As part of that effort NASA has teamed with NCAR to develop software to fuse data from multiple instruments into a single detected icing condition product. The multiple instrument approach utilizes a X-band vertical staring radar, a multifrequency microwave, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data is post-processed with a LabVIEW program with a resultant supercooled liquid water profile and aircraft hazard depiction. Ground-based, remotely-sensed measurements and in-situ measurements from research aircraft were gathered during the international 2003-2004 Alliance Icing Research Study (AIRS II). Comparisons between the remote sensing system s fused icing product and the aircraft measurements are reviewed here. While there are areas where improvement can be made, the cases examined suggest that the fused sensor remote sensing technique appears to be a valid approach.

Applications of Sentinel-2 data for agriculture and forest monitoring using the absolute difference (ZABUD) index derived from the AgroEye software (ESA)

NASA Astrophysics Data System (ADS)

de Kok, R.; WeŻyk, P.; PapieŻ, M.; Migo, L.

2017-10-01

To convince new users of the advantages of the Sentinel_2 sensor, a simplification of classic remote sensing tools allows to create a platform of communication among domain specialists of agricultural analysis, visual image interpreters and remote sensing programmers. An index value, known in the remote sensing user domain as "Zabud" was selected to represent, in color, the essentials of a time series analysis. The color index used in a color atlas offers a working platform for an agricultural field control. This creates a database of test and training areas that enables rapid anomaly detection in the agricultural domain. The use cases and simplifications now function as an introduction to Sentinel_2 based remote sensing, in an area that before relies on VHR imagery and aerial data, to serve mainly the visual interpretation. The database extension with detected anomalies allows developers of open source software to design solutions for further agricultural control with remote sensing.

Applications of Remote Sensing to Alien Invasive Plant Studies

PubMed Central

Huang, Cho-ying; Asner, Gregory P.

2009-01-01

Biological invasions can affect ecosystems across a wide spectrum of bioclimatic conditions. Therefore, it is often important to systematically monitor the spread of species over a broad region. Remote sensing has been an important tool for large-scale ecological studies in the past three decades, but it was not commonly used to study alien invasive plants until the mid 1990s. We synthesize previous research efforts on remote sensing of invasive plants from spatial, temporal and spectral perspectives. We also highlight a recently developed state-of-the-art image fusion technique that integrates passive and active energies concurrently collected by an imaging spectrometer and a scanning-waveform light detection and ranging (LiDAR) system, respectively. This approach provides a means to detect the structure and functional properties of invasive plants of different canopy levels. Finally, we summarize regional studies of biological invasions using remote sensing, discuss the limitations of remote sensing approaches, and highlight current research needs and future directions. PMID:22408558

Remote sensing techniques for conservation and management of natural vegetation ecosystems

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Verdesio, J. J.; Dossantos, J. R.

1981-01-01

The importance of using remote sensing techniques, in the visible and near-infrared ranges, for mapping, inventory, conservation and management of natural ecosystems is discussed. Some examples realized in Brazil or other countries are given to evaluate the products from orbital platform (MSS and RBV imagery of LANDSAT) and aerial level (photography) for ecosystems study. The maximum quantitative and qualitative information which can be obtained from each sensor, at different level, are discussed. Based on the developed experiments it is concluded that the remote sensing technique is a useful tool in mapping vegetation units, estimating biomass, forecasting and evaluation of fire damage, disease detection, deforestation mapping and change detection in land-use. In addition, remote sensing techniques can be used in controling implantation and planning natural/artificial regeneration.

Application of Earth Sciencés Technology in Mapping the of Brazilian Coast: Localization, Analysis & Monitoring of the Archaeological Sites with Remote Sensing & LiDAR

NASA Astrophysics Data System (ADS)

Thompson Alves de Souza, Carlos Eduardo

Application of Earth Sciencés Technology in Mapping the of Brazilian Coast: Localization, Analysis & Monitoring of the Archaeological Sites with Remote Sensing & LiDAR Carlos Eduardo Thompson Alves de Souza cethompsoniii@hotmail.com Archaeologist Member of the European Association of Archaeologists B.A.Archaeology MA.Remote Sensing Abstract The Archaeological Research in Urban Environment with the Air Light Detection and Ranging is problematic for the Overlay Layers mixed with contexts concerning the Interpretation of Archaeological Data. However, in the Underwater Archaeology the results are excellent. This paper considers the application of Remote Sensing and Air Light Detection and Ranging (LIDAR) as separate things as well as Land Archaeology and the Underwater Archaeology. European Archaeologists know very little about Brazil and the article presents an Overview of Research in Brazil with Remote Sensing in Archaeology and Light Detection and Ranging in Land Archaeology and Underwater Archaeology, because Brazil has Continental Dimensions. Braziliańs Methodology for Location, Analysis and Monitoring of Archaeological Sites is necessarily more Complex and Innovative and therefore can serve as a New Paradigm for other archaeologists involved in the Advanced Management Heritage.

Applications of remote sensing in resource management in Nebraska

NASA Technical Reports Server (NTRS)

Drew, J. V.

1974-01-01

The project is reported for studying the application of remote sensing in land use classification and delineation of major tectonic lineaments in Nebraska. Other research reported include the use of aircraft and ERTS-1 satellite imagery in detecting and estimating the acreage of irrigated land, and the application of remote sensing in estimating evapotranspiration in the Platte River Basin.

Temporal Forest Change Detection and Forest Health Assessment using Remote Sensing

NASA Astrophysics Data System (ADS)

Ya'acob, Norsuzila; Mohd Azize, Aziean Binti; Anis Mahmon, Nur; Laily Yusof, Azita; Farhana Azmi, Nor; Mustafa, Norfazira

2014-03-01

This paper presents the detection of Angsi and Berembun Reserve Forest change for years 1996 and 2013. Forest is an important part of our ecosystem. The main function is to absorb carbon oxide and produce oxygen in their cycle of photosynthesis to maintain a balance and healthy atmosphere. However, forest changes as time changes. Some changes are necessary as to give way for economic growth. Nevertheless, it is important to monitor forest change so that deforestation and development can be planned and the balance of ecosystem is still preserved. It is important because there are number of unfavorable effects of deforestation that include environmental and economic such as erosion of soil, loss of biodiversity and climate change. The forest change detection can be studied with reference of several satellite images using remote sensing application. Forest change detection is best done with remote sensing due to large and remote study area. The objective of this project is to detect forest change over time and to compare forest health indicated by Normalized Difference Vegetation Index (NDVI) using remote sensing and image processing. The forest under study shows depletion of forest area by 12% and 100% increment of deforestation activities. The NDVI value which is associated with the forest health also shows 13% of reduction.

Object-oriented recognition of high-resolution remote sensing image

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

A hyper-temporal remote sensing protocol for detecting ecosystem disturbance, classifying ecological state, and assessing soil resilience

USDA-ARS?s Scientific Manuscript database

Hyper-temporal remote sensing is capable of detecting detailed information on vegetation dynamics relating to plant functional types (PFT), a useful proxy for estimating soil physical and chemical properties. A central concept of PFT is that plant morphological and physiological adaptations are link...

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Borehole sounding device with sealed depth and water level sensors

DOEpatents

Skalski, Joseph C.; Henke, Michael D.

2005-08-02

A borehole device having proximal and distal ends comprises an enclosure at the proximal end for accepting an aircraft cable containing a plurality of insulated conductors from a remote position. A water sensing enclosure is sealingly attached to the enclosure and contains means for detecting water, and sending a signal on the cable to the remote position indicating water has been detected. A bottom sensing enclosure is sealingly attached to the water sensing enclosure for determining when the borehole device encounters borehole bottom and sends a signal on the cable to the remote position indicating that borehole bottom has been encountered.

Remote Sensing Monitoring Methods for Detecting Invasive Weed Coverage in Delta Waterways and Bay Marshlands

NASA Technical Reports Server (NTRS)

Potter, Christopher

2018-01-01

This presentation is part of the Independent Science Board of the State of California Delta Stewardship Council brown bag seminar series on the "How the Delta is Monitored", followed with a panel discussion. Various remote sensing approaches for aquatic vegetation will be reviewed. Key research and application issues with remote sensing monitoring in the Delta will be addressed.

Background and principle applications of remote sensing in Mexico

NASA Technical Reports Server (NTRS)

Perez, J. A. D.

1978-01-01

Remote sensing, or the collection of information from objectives at a distance, crystallizes the interest in implementing techniques which assist in the search for solutions to the problems raised by the detection, exploitation, and conservation of the natural resources of the earth. An attempt is made to present an overview of the studies and achievements which have been obtained with remote sensing in Mexico.

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

NASA Astrophysics Data System (ADS)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

Rapid Target Detection in High Resolution Remote Sensing Images Using Yolo Model

NASA Astrophysics Data System (ADS)

Wu, Z.; Chen, X.; Gao, Y.; Li, Y.

2018-04-01

Object detection in high resolution remote sensing images is a fundamental and challenging problem in the field of remote sensing imagery analysis for civil and military application due to the complex neighboring environments, which can cause the recognition algorithms to mistake irrelevant ground objects for target objects. Deep Convolution Neural Network(DCNN) is the hotspot in object detection for its powerful ability of feature extraction and has achieved state-of-the-art results in Computer Vision. Common pipeline of object detection based on DCNN consists of region proposal, CNN feature extraction, region classification and post processing. YOLO model frames object detection as a regression problem, using a single CNN predicts bounding boxes and class probabilities in an end-to-end way and make the predict faster. In this paper, a YOLO based model is used for object detection in high resolution sensing images. The experiments on NWPU VHR-10 dataset and our airport/airplane dataset gain from GoogleEarth show that, compare with the common pipeline, the proposed model speeds up the detection process and have good accuracy.

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

USGS Publications Warehouse

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.

Applications of remote sensor data to geologic and economic analysis on the Bonanza Test Site, Colorado

NASA Technical Reports Server (NTRS)

Reeves, R. G. (Compiler)

1972-01-01

Recent studies conducted in the Bonanza Test Site, Colorado, area indicated that: (1) more geologic structural information is available from remote sensing data than from conventional techniques; (2) greater accuracy results from using remote sensing data; (3) all major structural features were detected; (4) of all structural interpretations, about 75% were correct; and (5) interpretation of remote sensing data will not supplant field work, but it enables field work to be done much more efficiently.

Design and Performance of a Multiwavelength Airborne Polarimetric Lidar for Vegetation Remote Sensing

NASA Astrophysics Data System (ADS)

Tan, Songxin; Narayanan, Ram M.

2004-04-01

The University of Nebraska has developed a multiwavelength airborne polarimetric lidar (MAPL) system to support its Airborne Remote Sensing Program for vegetation remote sensing. The MAPL design and instrumentation are described in detail. Characteristics of the MAPL system include lidar waveform capture and polarimetric measurement capabilities, which provide enhanced opportunities for vegetation remote sensing compared with current sensors. Field tests were conducted to calibrate the range measurement. Polarimetric calibration of the system is also discussed. Backscattered polarimetric returns, as well as the cross-polarization ratios, were obtained from a small forested area to validate the system's ability for vegetation canopy detection. The system has been packaged to fly abroad a Piper Saratoga aircraft for airborne vegetation remote sensing applications.

The application of remote sensing techniques to inter and intra urban analysis

NASA Technical Reports Server (NTRS)

Horton, F. E.

1972-01-01

This is an effort to assess the applicability of air and spaceborne photography toward providing data inputs to urban and regional planning, management, and research. Through evaluation of remote sensing inputs to urban change detection systems, analyzing an effort to replicate an existing urban land use data file using remotely sensed data, estimating population and dwelling units from imagery, and by identifying and evaluating a system of urban places ultilizing space photography, it was determined that remote sensing can provide data concerning land use, changes in commercial structure, data for transportation planning, housing quality, residential dynamics, and population density.

Satellite detection of land-use change and effects on regional forest aboveground biomass estimates

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey

2008-01-01

We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg·ha−1, dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data...

Urban Methane Point Sources Detected by Tiered System of Remote-sensing Observations

NASA Image and Video Library

2015-07-10

This image captured by a prototype NASA satellite instrument at NASA California Laboratory for Atmospheric Remote Sensing CLARS shows a persistent methane hotspot central red area over Los Angeles basin.

Levee Monitoring with Radar Remote Sensing

NASA Technical Reports Server (NTRS)

Jones, Cathleen E.

2012-01-01

Topics in this presentation are: 1. Overview of radar remote sensing 2. Surface change detection with Differential Interferometric Radar Processing 3. Study of the Sacramento - San Joaquin levees 4. Mississippi River Levees during the Spring 2011 floods.

Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects

Treesearch

Robert E. Kennedy; Philip A. Townsend; John E. Gross; Warren B. Cohen; Paul Bolstad; Wang Y. Q.; Phyllis Adams

2009-01-01

Remote sensing provides a broad view of landscapes and can be consistent through time, making it an important tool for monitoring and managing protected areas. An impediment to broader use of remote sensing science for monitoring has been the need for resource managers to understand the specialized capabilities of an ever-expanding array of image sources and analysis...

Active and Passive Remote Sensing of Ice

DTIC Science & Technology

1991-11-15

To demonstrate the use of polarimetry in passive remote sensing of azimuthally asymmetric features on a terrain surface, an experiment was designed...azimuthal asymmetry on the remotely sensed soil surface. It is also observed from the experiment that the brightness temperatures for all three Stokes...significant implication of this experiment is that the surface asymmetry can be detected with a measurement of U at a single azimuthal angle. -8

Satellite Remote Sensing of Harmful Algal Blooms (HABs) and a Potential Synthesized Framework

PubMed Central

Shen, Li; Xu, Huiping; Guo, Xulin

2012-01-01

Harmful algal blooms (HABs) are severe ecological disasters threatening aquatic systems throughout the World, which necessitate scientific efforts in detecting and monitoring them. Compared with traditional in situ point observations, satellite remote sensing is considered as a promising technique for studying HABs due to its advantages of large-scale, real-time, and long-term monitoring. The present review summarizes the suitability of current satellite data sources and different algorithms for detecting HABs. It also discusses the spatial scale issue of HABs. Based on the major problems identified from previous literature, including the unsystematic understanding of HABs, the insufficient incorporation of satellite remote sensing, and a lack of multiple oceanographic explanations of the mechanisms causing HABs, this review also attempts to provide a comprehensive understanding of the complicated mechanism of HABs impacted by multiple oceanographic factors. A potential synthesized framework can be established by combining multiple accessible satellite remote sensing approaches including visual interpretation, spectra analysis, parameters retrieval and spatial-temporal pattern analysis. This framework aims to lead to a systematic and comprehensive monitoring of HABs based on satellite remote sensing from multiple oceanographic perspectives. PMID:22969372

Distributed solar photovoltaic array location and extent dataset for remote sensing object identification

PubMed Central

Bradbury, Kyle; Saboo, Raghav; L. Johnson, Timothy; Malof, Jordan M.; Devarajan, Arjun; Zhang, Wuming; M. Collins, Leslie; G. Newell, Richard

2016-01-01

Earth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment. PMID:27922592

Distributed solar photovoltaic array location and extent dataset for remote sensing object identification

NASA Astrophysics Data System (ADS)

Bradbury, Kyle; Saboo, Raghav; L. Johnson, Timothy; Malof, Jordan M.; Devarajan, Arjun; Zhang, Wuming; M. Collins, Leslie; G. Newell, Richard

2016-12-01

Earth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment.

Distributed solar photovoltaic array location and extent dataset for remote sensing object identification.

PubMed

Bradbury, Kyle; Saboo, Raghav; L Johnson, Timothy; Malof, Jordan M; Devarajan, Arjun; Zhang, Wuming; M Collins, Leslie; G Newell, Richard

2016-12-06

Earth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment.

Research on airborne infrared leakage detection of natural gas pipeline

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Detecting submerged features in water: modeling, sensors, and measurements

NASA Astrophysics Data System (ADS)

Bostater, Charles R., Jr.; Bassetti, Luce

2004-11-01

It is becoming more important to understand the remote sensing systems and associated autonomous or semi-autonomous methodologies (robotic & mechatronics) that may be utilized in freshwater and marine aquatic environments. This need comes from several issues related not only to advances in our scientific understanding and technological capabilities, but also from the desire to insure that the risk associated with UXO (unexploded ordnance), related submerged mines, as well as submerged targets (such as submerged aquatic vegetation) and debris left from previous human activities are remotely sensed and identified followed by reduced risks through detection and removal. This paper will describe (a) remote sensing systems, (b) platforms (fixed and mobile, as well as to demonstrate (c) the value of thinking in terms of scalability as well as modularity in the design and application of new systems now being constructed within our laboratory and other laboratories, as well as future systems. New remote sensing systems - moving or fixed sensing systems, as well as autonomous or semi-autonomous robotic and mechatronic systems will be essential to secure domestic preparedness for humanitarian reasons. These remote sensing systems hold tremendous value, if thoughtfully designed for other applications which include environmental monitoring in ambient environments.

Autonomous Exploration for Gathering Increased Science

NASA Technical Reports Server (NTRS)

Bornstein, Benjamin J.; Castano, Rebecca; Estlin, Tara A.; Gaines, Daniel M.; Anderson, Robert C.; Thompson, David R.; DeGranville, Charles K.; Chien, Steve A.; Tang, Benyang; Burl, Michael C.;

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

NASA Astrophysics Data System (ADS)

Sofina, N.; Ehlers, M.

2012-08-01

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

Photographic Remote Sensing of Sick Citrus Trees

NASA Technical Reports Server (NTRS)

Gausman, H. W.

1971-01-01

Remote sensing with infrared color aerial photography (Kodak Ektachrome Infrared Aero 8443 film) for detecting citrus tree anomalies is described. Illustrations and discussions are given for detecting nutrient toxicity symptoms, for detecting foot rot and sooty mold fungal diseases, and for distinguishing among citrus species. Also, the influence of internal leaf structure on light reflectance, transmittance, and absorptance are considered; and physiological and environmental factors that affect citrus leaf light reflectance are reviewed briefly and illustrated.

Application research on land use remote sensing dynamic monitoring: A case study of Anning district, Lanzhou

NASA Astrophysics Data System (ADS)

Zhu, Yunqiang; Zhu, Huazhong; Lu, Heli; Ni, Jianguang; Zhu, Shaoxia

2005-10-01

Remote sensing dynamic monitoring of land use can detect the change information of land use and update the current land use map, which is important for rational utilization and scientific management of land resources. This paper discusses the technological procedure of remote sensing dynamic monitoring of land use including the process of remote sensing images, the extraction of annual change information of land use, field survey, indoor post processing and accuracy assessment. Especially, we emphasize on comparative research on the choice of remote sensing rectifying models, image fusion algorithms and accuracy assessment methods. Taking Anning district in Lanzhou as an example, we extract the land use change information of the district during 2002-2003, access monitoring accuracy and analyze the reason of land use change.

National Satellite Land Remote Sensing Data Archive

USGS Publications Warehouse

Faundeen, John L.; Kelly, Francis P.; Holm, Thomas M.; Nolt, Jenna E.

2013-01-01

The National Satellite Land Remote Sensing Data Archive (NSLRSDA) resides at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center. Through the Land Remote Sensing Policy Act of 1992, the U.S. Congress directed the Department of the Interior (DOI) to establish a permanent Government archive containing satellite remote sensing data of the Earth's land surface and to make this data easily accessible and readily available. This unique DOI/USGS archive provides a comprehensive, permanent, and impartial observational record of the planet's land surface obtained throughout more than five decades of satellite remote sensing. Satellite-derived data and information products are primary sources used to detect and understand changes such as deforestation, desertification, agricultural crop vigor, water quality, invasive plant species, and certain natural hazards such as flood extent and wildfire scars.

[Application of hyperspectral remote sensing in research on ecological boundary in north farming-pasturing transition in China].

PubMed

Wang, Hong-Mei; Wang, Kun; Xie, Ying-Zhong

2009-06-01

Studies of ecological boundaries are important and have become a rapidly evolving part of contemporary ecology. The ecotones are dynamic and play several functional roles in ecosystem dynamics, and the changes in their locations can be used as an indicator of environment changes, and for these reasons, ecotones have recently become a focus of investigation of landscape ecology and global climate change. As the interest in ecotone increases, there is an increased need for formal techniques to detect it. Hence, to better study and understand the functional roles and dynamics of ecotones in ecosystem, we need quantitative methods to characterize them. In the semi-arid region of northern China, there exists a farming-pasturing transition resulting from grassland reclamation and deforestation. With the fragmentation of grassland landscape, the structure and function of the grassland ecosystem are changing. Given this perspective; new-image processing approaches are needed to focus on transition themselves. Hyperspectral remote sensing data, compared with wide-band remote sensing data, has the advantage of high spectral resolution. Hyperspectral remote sensing can be used to visualize transitional zones and to detect ecotone based on surface properties (e. g. vegetation, soil type, and soil moisture etc). In this paper, the methods of hyperspectral remote sensing information processing, spectral analysis and its application in detecting the vegetation classifications, vegetation growth state, estimating the canopy biochemical characteristics, soil moisture, soil organic matter etc are reviewed in detail. Finally the paper involves further application of hyperspectral remote sensing information in research on local climate in ecological boundary in north farming-pasturing transition in China.

Remote Sensing Monitoring of Changes in Soil Salinity: A Case Study in Inner Mongolia, China.

PubMed

Wu, Jingwei; Vincent, Bernard; Yang, Jinzhong; Bouarfa, Sami; Vidal, Alain

2008-11-07

This study used archived remote sensing images to depict the history of changes in soil salinity in the Hetao Irrigation District in Inner Mongolia, China, with the purpose of linking these changes with land and water management practices and to draw lessons for salinity control. Most data came from LANDSAT satellite images taken in 1973, 1977, 1988, 1991, 1996, 2001, and 2006. In these years salt-affected areas were detected using a normal supervised classification method. Corresponding cropped areas were detected from NVDI (Normalized Difference Vegetation Index) values using an unsupervised method. Field samples and agricultural statistics were used to estimate the accuracy of the classification. Historical data concerning irrigation/drainage and the groundwater table were used to analyze the relation between changes in soil salinity and land and water management practices. Results showed that: (1) the overall accuracy of remote sensing in detecting soil salinity was 90.2%, and in detecting cropped area, 98%; (2) the installation/innovation of the drainage system did help to control salinity; and (3) a low ratio of cropped land helped control salinity in the Hetao Irrigation District. These findings suggest that remote sensing is a useful tool to detect soil salinity and has potential in evaluating and improving land and water management practices.

Energy and remote sensing. [satellite exploration, monitoring, siting

NASA Technical Reports Server (NTRS)

Summers, R. A.; Smith, W. L.; Short, N. M.

1977-01-01

Exploration for uranium, thorium, oil, gas and geothermal activity through remote sensing techniques is considered; satellite monitoring of coal-derived CO2 in the atmosphere, and the remote assessment of strip mining and land restoration are also mentioned. Reference is made to color ratio composites based on Landsat data, which may aid in the detection of uranium deposits, and to computer-enhanced black and white airborne scanning imagery, which may locate geothermal anomalies. Other applications of remote sensing to energy resources management, including mapping of transportation networks and power plant siting, are discussed.

Detection of geothermal anomalies in Tengchong, Yunnan Province, China from MODIS multi-temporal night LST imagery

NASA Astrophysics Data System (ADS)

Li, H.; Kusky, T. M.; Peng, S.; Zhu, M.

2012-12-01

Thermal infrared (TIR) remote sensing is an important technique in the exploration of geothermal resources. In this study, a geothermal survey is conducted in Tengchong area of Yunnan province in China using multi-temporal MODIS LST (Land Surface Temperature). The monthly night MODIS LST data from Mar. 2000 to Mar. 2011 of the study area were collected and analyzed. The 132 month average LST map was derived and three geothermal anomalies were identified. The findings of this study agree well with the results from relative geothermal gradient measurements. Finally, we conclude that TIR remote sensing is a cost-effective technique to detect geothermal anomalies. Combining TIR remote sensing with geological analysis and the understanding of geothermal mechanism is an accurate and efficient approach to geothermal area detection.

Remote sensing of on-road vehicle emissions: Mechanism, applications and a case study from Hong Kong

NASA Astrophysics Data System (ADS)

Huang, Yuhan; Organ, Bruce; Zhou, John L.; Surawski, Nic C.; Hong, Guang; Chan, Edward F. C.; Yam, Yat Shing

2018-06-01

Vehicle emissions are a major contributor to air pollution in cities and have serious health impacts to their inhabitants. On-road remote sensing is an effective and economic tool to monitor and control vehicle emissions. In this review, the mechanism, accuracy, advantages and limitations of remote sensing were introduced. Then the applications and major findings of remote sensing were critically reviewed. It was revealed that the emission distribution of on-road vehicles was highly skewed so that the dirtiest 10% vehicles accounted for over half of the total fleet emissions. Such findings highlighted the importance and effectiveness of using remote sensing for in situ identification of high-emitting vehicles for further inspection and maintenance programs. However, the accuracy and number of vehicles affected by screening programs were greatly dependent on the screening criteria. Remote sensing studies showed that the emissions of gasoline and diesel vehicles were significantly reduced in recent years, with the exception of NOx emissions of diesel vehicles in spite of greatly tightened automotive emission regulations. Thirdly, the experience and issues of using remote sensing for identifying high-emitting vehicles in Hong Kong (where remote sensing is a legislative instrument for enforcement purposes) were reported. That was followed by the first time ever identification and discussion of the issue of frequent false detection of diesel high-emitters using remote sensing. Finally, the challenges and future research directions of on-road remote sensing were elaborated.

Chirped Laser Dispersion Spectroscopy for Remote Open-Path Trace-Gas Sensing

PubMed Central

Nikodem, Michal; Wysocki, Gerard

2012-01-01

In this paper we present a prototype instrument for remote open-path detection of nitrous oxide. The sensor is based on a 4.53 μm quantum cascade laser and uses the chirped laser dispersion spectroscopy (CLaDS) technique for molecular concentration measurements. To the best of our knowledge this is the first demonstration of open-path laser-based trace-gas detection using a molecular dispersion measurement. The prototype sensor achieves a detection limit down to the single-ppbv level and exhibits excellent stability and robustness. The instrument characterization, field deployment performance, and the advantages of applying dispersion sensing to sensitive trace-gas detection in a remote open-path configuration are presented. PMID:23443389

Chirped laser dispersion spectroscopy for remote open-path trace-gas sensing.

PubMed

Nikodem, Michal; Wysocki, Gerard

2012-11-28

In this paper we present a prototype instrument for remote open-path detection of nitrous oxide. The sensor is based on a 4.53 μm quantum cascade laser and uses the chirped laser dispersion spectroscopy (CLaDS) technique for molecular concentration measurements. To the best of our knowledge this is the first demonstration of open-path laser-based trace-gas detection using a molecular dispersion measurement. The prototype sensor achieves a detection limit down to the single-ppbv level and exhibits excellent stability and robustness. The instrument characterization, field deployment performance, and the advantages of applying dispersion sensing to sensitive trace-gas detection in a remote open-path configuration are presented.

Remote sensing of rangeland biodiversity

USDA-ARS?s Scientific Manuscript database

Rangelands are managed based on state and transition models for an ecological site. Transitions to alternative ecological states are indicative of degrading rangelands. Three key variables may be remotely sensed to detect transitions between alternative states: amount of bare soil, presence of inva...

Integrating multiple satellite data for crop monitoring

USDA-ARS?s Scientific Manuscript database

Remote sensing provides a valuable data source for detecting crop types, monitoring crop condition and predicting crop yields from space. Routine and continuous remote sensing data are critical for agricultural research and operational applications. Since crop field dimensions tend to be relatively ...

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1981-01-01

Progress in studies for using remotely sensed data for assessing crop stress and in crop estimation is reported. The estimation of acreage of small forested areas in the southern lower peninsula of Michigan using LANDSAT data is evaluated. Damage to small grains caused by the cereal leaf beetle was assessed through remote sensing. The remote detection of X-disease of peach and cherry trees and of fire blight of pear and apple trees was investigated. The reliability of improving on standard methods of crop production estimation was demonstrated. Areas of virus infestation in vineyards and blueberry fields in western and southwestern Michigan were identified. The installation and systems integration of a microcomputer system for processing and making available remotely sensed data are described.

Remote sensing of water and nitrogen stress in broccoli

NASA Astrophysics Data System (ADS)

Elsheikha, Diael-Deen Mohamed

Remote sensing is being used in agriculture for crop management. Ground based remote sensing data acquisition system was used for collection of high spatial and temporal resolution data for irrigated broccoli crop. The system was composed of a small cart that ran back and forth on a rail system that was mounted on a linear move irrigation system. The cart was equipped with a sensor that had 4 discrete wavelengths; 550 nm, 660 nm, 720 nm, and 810 nm, and an infrared thermometer, all had 10 nm bandwidth. A global positioning system was used to indicate the cart position. The study consisted of two parts; the first was to evaluate remotely sensed reflectance and indices in broccoli during the growing season, and determine whether remotely sensed indices or standard deviation of indices can distinguish between nitrogen and water stress in broccoli, and the second part of the study was to evaluate remotely sensed indices and standard deviation of remotely sensed indices in broccoli during daily changes in solar zenith angle. Results indicated that nitrogen was detected using Ratio Vegetation index, RVI, Normalized Difference Vegetation Index, NDVI, Canopy Chlorophyll Concentration Index, CCCI, and also using the reflectance in the Near-Infrared, NIR, bands. The Red reflectance band capability of showing stress was not as clear as the previous indices and bands reflectance. The Canopy Chlorophyll Concentration Index, CCCI, was the most successful index. The Crop Water Stress Index was able to detect water stress but it was highly affected by the solar zenith angle change along the day.

International Symposium on Remote Sensing of Environment, 9th, University of Michigan, Ann Arbor, Mich., April 15-19, 1974, Proceedings. Volumes 1, 2 & 3

NASA Technical Reports Server (NTRS)

1974-01-01

The present work gathers together numerous papers describing the use of remote sensing technology for mapping, monitoring, and management of earth resources and man's environment. Studies using various types of sensing equipment are described, including multispectral scanners, radar imagery, spectrometers, lidar, and aerial photography, and both manual and computer-aided data processing techniques are described. Some of the topics covered include: estimation of population density in Tokyo districts from ERTS-1 data, a clustering algorithm for unsupervised crop classification, passive microwave sensing of moist soils, interactive computer processing for land use planning, the use of remote sensing to delineate floodplains, moisture detection from Skylab, scanning thermal plumes, electrically scanning microwave radiometers, oil slick detection by X-band synthetic aperture radar, and the use of space photos for search of oil and gas fields. Individual items are announced in this issue.

A REMOTE SENSING AND GIS-ENABLED HIGHWAY ASSET MANAGEMENT SYSTEM PHASE 2

DOT National Transportation Integrated Search

2018-02-02

The objective of this project is to validate the use of commercial remote sensing and spatial information (CRS&SI) technologies, including emerging 3D line laser imaging technology, mobile light detection and ranging (LiDAR), image processing algorit...

Detection of TNT using a sensitive two-photon organic dendrimer for remote sensing

NASA Astrophysics Data System (ADS)

Narayanan, Aditya; Varnavski, Oleg; Mongin, Oliver; Majoral, Jean-Pierre; Blanchard-Desce, Mireille; Goodson, Theodore, III

2008-03-01

There is currently a need for superior stand-off detection schemes for protection against explosive weapons of mass destruction. Fluorescence detection at small distances from the target has proven to be attractive. A novel unexplored route in fluorescence chemical sensing that utilizes the exceptional spectroscopic capabilities of nonlinear optical methods is two-photon excited fluorescence. This approach utilizes infra-red light for excitation of remote sensors. Infra-red light suffers less scattering in porous materials which is beneficial for vapor sensing and has greater depth of penetration through the atmosphere, and there are fewer concerns regarding eye safety in remote detection schemes. We demonstrate this method using a novel dendritic system which possesses both excellent fluorescence sensitivity to the presence of TNT with infra-red pulses of light and high two-photon absorption (TPA) response. This illustrates the use of TPA for potential stand-off detection of energetic materials in the infra-red spectral regions in a highly two-photon responsive dendrimer.

Upgraded airborne scanner for commercial remote sensing

NASA Astrophysics Data System (ADS)

Chang, Sheng-Huei; Rubin, Tod D.

1994-06-01

Traditional commercial remote sensing has focused on the geologic market, with primary focus on mineral identification and mapping in the visible through short-wave infrared spectral regions (0.4 to 2.4 microns). Commercial remote sensing users now demand airborne scanning capabilities spanning the entire wavelength range from ultraviolet through thermal infrared (0.3 to 12 microns). This spectral range enables detection, identification, and mapping of objects and liquids on the earth's surface and gases in the air. Applications requiring this range of wavelengths include detection and mapping of oil spills, soil and water contamination, stressed vegetation, and renewable and non-renewable natural resources, and also change detection, natural hazard mitigation, emergency response, agricultural management, and urban planning. GER has designed and built a configurable scanner that acquires high resolution images in 63 selected wave bands in this broad wavelength range.

a Coarse-To Model for Airplane Detection from Large Remote Sensing Images Using Saliency Modle and Deep Learning

NASA Astrophysics Data System (ADS)

Song, Z. N.; Sui, H. G.

2018-04-01

High resolution remote sensing images are bearing the important strategic information, especially finding some time-sensitive-targets quickly, like airplanes, ships, and cars. Most of time the problem firstly we face is how to rapidly judge whether a particular target is included in a large random remote sensing image, instead of detecting them on a given image. The problem of time-sensitive-targets target finding in a huge image is a great challenge: 1) Complex background leads to high loss and false alarms in tiny object detection in a large-scale images. 2) Unlike traditional image retrieval, what we need to do is not just compare the similarity of image blocks, but quickly find specific targets in a huge image. In this paper, taking the target of airplane as an example, presents an effective method for searching aircraft targets in large scale optical remote sensing images. Firstly, we used an improved visual attention model utilizes salience detection and line segment detector to quickly locate suspected regions in a large and complicated remote sensing image. Then for each region, without region proposal method, a single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation is adopted to search small airplane objects. Unlike sliding window and region proposal-based techniques, we can do entire image (region) during training and test time so it implicitly encodes contextual information about classes as well as their appearance. Experimental results show the proposed method is quickly identify airplanes in large-scale images.

Interfacing geographic information systems and remote sensing for rural land-use analysis

NASA Technical Reports Server (NTRS)

Nellis, M. Duane; Lulla, Kamlesh; Jensen, John

1990-01-01

Recent advances in computer-based geographic information systems (GISs) are briefly reviewed, with an emphasis on the incorporation of remote-sensing data in GISs for rural applications. Topics addressed include sampling procedures for rural land-use analyses; GIS-based mapping of agricultural land use and productivity; remote sensing of land use and agricultural, forest, rangeland, and water resources; monitoring the dynamics of irrigation agriculture; GIS methods for detecting changes in land use over time; and the development of land-use modeling strategies.

The Maximum Cross-Correlation approach to detecting translational motions from sequential remote-sensing images

NASA Astrophysics Data System (ADS)

Gao, J.; Lythe, M. B.

1996-06-01

This paper presents the principle of the Maximum Cross-Correlation (MCC) approach in detecting translational motions within dynamic fields from time-sequential remotely sensed images. A C program implementing the approach is presented and illustrated in a flowchart. The program is tested with a pair of sea-surface temperature images derived from Advanced Very High Resolution Radiometer (AVHRR) images near East Cape, New Zealand. Results show that the mean currents in the region have been detected satisfactorily with the approach.

The application of remote sensing techniques to selected inter and intra urban data acquisition problems

NASA Technical Reports Server (NTRS)

Horton, F. E.

1970-01-01

The utility of remote sensing techniques to urban data acquisition problems in several distinct areas was identified. This endeavor included a comparison of remote sensing systems for urban data collection, the extraction of housing quality data from aerial photography, utilization of photographic sensors in urban transportation studies, urban change detection, space photography utilization, and an application of remote sensing techniques to the acquisition of data concerning intra-urban commercial centers. The systematic evaluation of variable extraction for urban modeling and planning at several different scales, and the model derivation for identifying and predicting economic growth and change within a regional system of cities are also studied.

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

PubMed

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

2014-11-01

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

What is a picture worth? A history of remote sensing

USGS Publications Warehouse

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.

Experimental evidence for spring and autumn windows for the detection of geobotanical anomalies through the remote sensing of overlying vegetation

NASA Technical Reports Server (NTRS)

Labovitz, M. L.; Masuoka, E. J.; Bell, R.; Nelson, R. F.; Larsen, C. A.; Hooker, L. K.; Troensegaard, K. W.

1985-01-01

It is pointed out that in many regions of the world, vegetation is the predominant factor influencing variation in reflected energy in the 0.4-2.5 micron region of the spectrum. Studies have, therefore, been conducted regarding the utility of remote sensing for detecting changes in vegetation which could be related to the presence of mineralization. The present paper provides primarily a report on the results of the second year of a multiyear study of geobotanical-remote-sensing relationships as developed over areas of sulfide mineralization. The field study has a strong experimental design basis. It is proceeded by first delineating the boundaries of a large geographic region which satisfied a set of previously enumerated field-site criteria. Within this region, carefully selected pairs of mineralized and nonmineralized test sites were examined over the growing season. The experiment is to provide information about the spectral and temporal resolutions required for remote-sensing-geobotanical exploration. The obtained results are evaluated.

Remote sensing applications in agriculture and forestry. Applications of aerial photography and ERTS data to agricultural, forest and water resources management

NASA Technical Reports Server (NTRS)

1973-01-01

Remote sensing techniques are being used in Minnesota to study: (1) forest disease detection and control; (2) water quality indicators; (3) forest vegetation classification and management; (4) detection of saline soils in the Red River Valley; (5) corn defoliation; and (6) alfalfa crop productivity. Results of progress, and plans for future work in these areas, are discussed.

The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

NASA Technical Reports Server (NTRS)

Hogan, Christine A.

1996-01-01

A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation composition was noted in the change detection image.

Assessing the Rayleigh Intensity Remote Leak Detection Technique

NASA Technical Reports Server (NTRS)

Clements, Sandra

2001-01-01

Remote sensing technologies are being considered for efficient, low cost gas leak detection. An exploratory project to identify and evaluate remote sensing technologies for application to gas leak detection is underway. During Phase 1 of the project, completed last year, eleven specific techniques were identified for further study. One of these, the Rayleigh Intensity technique, would make use of changes in the light scattered off of gas molecules to detect and locate a leak. During the 10-week Summer Faculty Fellowship Program, the scatter of light off of gas molecules was investigated. The influence of light scattered off of aerosols suspended in the atmosphere was also examined to determine if this would adversely affect leak detection. Results of this study indicate that in unconditioned air, it will be difficult, though perhaps not impossible, to distinguish between a gas leak and natural variations in the aerosol content of the air. Because information about the particle size distribution in clean room environments is incomplete, the applicability in clean rooms is uncertain though more promising than in unconditioned environments. It is suggested that problems caused by aerosols may be overcome by using the Rayleigh Intensity technique in combination with another remote sensing technique, the Rayleigh Doppler technique.

Using GPS Reflections for Satellite Remote Sensing

NASA Technical Reports Server (NTRS)

Mickler, David

2000-01-01

GPS signals that have reflected off of the ocean's surface have shown potential for use in oceanographic and atmospheric studies. The research described here investigates the possible deployment of a GPS reflection receiver onboard a remote sensing satellite in low Earth orbit (LEO). The coverage and resolution characteristics of this receiver are calculated and estimated. This mission analysis examines using reflected GPS signals for several remote sensing missions. These include measurement of the total electron content in the ionosphere, sea surface height, and ocean wind speed and direction. Also discussed is the potential test deployment of such a GPS receiver on the space shuttle. Constellations of satellites are proposed to provide adequate spatial and temporal resolution for the aforementioned remote sensing missions. These results provide a starting point for research into the feasibility of augmenting or replacing existing remote sensing satellites with spaceborne GPS reflection-detecting receivers.

Graphic products used in the evaluation of traditional and emerging remote sensing technologies for the detection of fugitive contamination at selected superfund hazardous waste sites

USGS Publications Warehouse

Slonecker, E. Terrence; Fisher, Gary B.

2011-01-01

This report presents the overhead imagery and field sampling results used to prepare U.S. Geological Survey Open-File Report 2011-1050, 'Evaluation of Traditional and Emerging Remote Sensing Technologies for the Detection of Fugitive Contamination at Selected Superfund Hazardous Waste Sites'. These graphic products were used in the evaluation of remote sensing technology in postclosure monitoring of hazardous waste sites and represent an ongoing research effort. Soil sampling results presented here were accomplished with field portable x-ray fluoresence (XRF) technology and are used as screening tools only representing the current conditions of metals and other contaminants at selected Superfund hazardous waste sites.

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images

PubMed Central

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-01-01

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency. PMID:28640236

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

PubMed

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-06-22

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

Detection of potato beetle damage using remote sensing from small unmanned aircraft systems

USDA-ARS?s Scientific Manuscript database

Remote sensing with small unmanned aircraft systems (sUAS) has potential applications in agriculture because low flight altitudes allow image acquisition at very high spatial resolution. We set up experiments at the Oregon State University Hermiston Agricultural Research and Extension Center (HAREC...

Development of a remote sensing network for time-sensitive detection of fine scale damage to transportation infrastructure : [final report].

DOT National Transportation Integrated Search

2015-09-23

This research project aimed to develop a remote sensing system capable of rapidly identifying fine-scale damage to critical transportation infrastructure following hazard events. Such a system must be pre-planned for rapid deployment, automate proces...

[Analysis of related factors of slope plant hyperspectral remote sensing].

PubMed

Sun, Wei-Qi; Zhao, Yun-Sheng; Tu, Lin-Ling

2014-09-01

In the present paper, the slope gradient, aspect, detection zenith angle and plant types were analyzed. In order to strengthen the theoretical discussion, the research was under laboratory condition, and modeled uniform slope for slope plant. Through experiments we found that these factors indeed have influence on plant hyperspectral remote sensing. When choosing slope gradient as the variate, the blade reflection first increases and then decreases as the slope gradient changes from 0° to 36°; When keeping other factors constant, and only detection zenith angle increasing from 0° to 60°, the spectral characteristic of slope plants do not change significantly in visible light band, but decreases gradually in near infrared band; With only slope aspect changing, when the dome meets the light direction, the blade reflectance gets maximum, and when the dome meets the backlit direction, the blade reflectance gets minimum, furthermore, setting the line of vertical intersection of incidence plane and the dome as an axis, the reflectance on the axis's both sides shows symmetric distribution; In addition, spectral curves of different plant types have a lot differences between each other, which means that the plant types also affect hyperspectral remote sensing results of slope plants. This research breaks through the limitations of the traditional vertical remote sensing data collection and uses the multi-angle and hyperspectral information to analyze spectral characteristics of slope plants. So this research has theoretical significance to the development of quantitative remote sensing, and has application value to the plant remote sensing monitoring.

The application analysis of the multi-angle polarization technique for ocean color remote sensing

NASA Astrophysics Data System (ADS)

Zhang, Yongchao; Zhu, Jun; Yin, Huan; Zhang, Keli

2017-02-01

The multi-angle polarization technique, which uses the intensity of polarized radiation as the observed quantity, is a new remote sensing means for earth observation. With this method, not only can the multi-angle light intensity data be provided, but also the multi-angle information of polarized radiation can be obtained. So, the technique may solve the problems, those could not be solved with the traditional remote sensing methods. Nowadays, the multi-angle polarization technique has become one of the hot topics in the field of the international quantitative research on remote sensing. In this paper, we firstly introduce the principles of the multi-angle polarization technique, then the situations of basic research and engineering applications are particularly summarized and analysed in 1) the peeled-off method of sun glitter based on polarization, 2) the ocean color remote sensing based on polarization, 3) oil spill detection using polarization technique, 4) the ocean aerosol monitoring based on polarization. Finally, based on the previous work, we briefly present the problems and prospects of the multi-angle polarization technique used in China's ocean color remote sensing.

Public health applications of remote sensing of the environment, an evaluation

NASA Technical Reports Server (NTRS)

1972-01-01

The available techniques were examined in the field of remote sensing (including aerial photography, infrared detection, radar, etc.) and applications to a number of problems in the wide field of public health determined. The specific areas of public health examined included: air pollution, water pollution, communicable disease, and the combined problems of urban growth and the effect of disasters on human communities. The assessment of the possible applications of remote sensing to these problems was made primarily by examination of the available literature in each field, and by interviews with health authorities, physicists, biologists, and other interested workers. Three types of programs employing remote sensors were outlined in the air pollution field: (1) proving ability of sensors to monitor pollutants at three levels of interest - point source, ambient levels in cities, and global patterns; (2) detection of effects of pollutants on the environment at local and global levels; and (3) routine monitoring.

Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

NASA Technical Reports Server (NTRS)

Engman, Edwin T.

1997-01-01

Many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of soils and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric soil moisture measurements in the top few cm. These signatures should provide information on how and where to apply soil physical parameters in distributed and lumped parameter models and how to subdivide drainage basins into hydrologically similar sub-basins.

Insect detection and nitrogen management for irrigated potatoes using remote sensing from small unmanned aircraft systems

USDA-ARS?s Scientific Manuscript database

Remote sensing with small unmanned aircraft systems (sUAS) has potential applications in agriculture because low flight altitudes allow image acquisition at very high spatial resolution. We set up experiments at the Oregon State University Hermiston Agricultural Research and Extension Center with d...

Remote Sensing of Earth--A New Perspective

ERIC Educational Resources Information Center

Boyer, Robert E.

1973-01-01

Photographs of the earth taken from space are used to illustrate the advantages and application of remote sensing. This technique may be used in such areas as the immediate appraisal of disasters, surveillance of the oceans, monitoring of land, food and water resources, detection of natural resources, and identification of pollution. (JR)

Linear- and Repetitive Feature Detection Within Remotely Sensed Imagery

DTIC Science & Technology

2017-04-01

applicable to Python or other pro- gramming languages with image- processing capabilities. 4.1 Classification machine learning The first methodology uses...remotely sensed images that are in panchromatic or true-color formats. Image- processing techniques, in- cluding Hough transforms, machine learning, and...data fusion .................................................................................................... 44 6.3 Context-based processing

Current and emerging operational uses of remote sensing in Swedish forestry

Treesearch

Hakan Olsson; Mikael Egberth; Jonas Engberg; Johan E.S. Fransson; Tina Granqvist Pahlen; < i> et al< /i>

2007-01-01

Satellite remote sensing is being used operationally by Swedish authorities in applications involving, for example, change detection of clear felled areas, use of k-Nearest Neighbour estimates of forest parameters, and post-stratification (in combination with National Forest Inventory plots). For forest management planning of estates, aerial...

The Feasibility Evaluation of Land Use Change Detection Using GAOFEN-3 Data

NASA Astrophysics Data System (ADS)

Huang, G.; Sun, Y.; Zhao, Z.

2018-04-01

GaoFen-3 (GF-3) satellite, is the first C band and multi-polarimetric Synthetic Aperture Radar (SAR) satellite in China. In order to explore the feasibility of GF-3 satellite in remote sensing interpretation and land-use remote sensing change detection, taking Guangzhou, China as a study area, the full polarimetric image of GF-3 satellite with 8 m resolution of two temporal as the data source. Firstly, the image is pre-processed by orthorectification, image registration and mosaic, and the land-use remote sensing digital orthophoto map (DOM) in 2017 is made according to the each county. Then the classification analysis and judgment of ground objects on the image are carried out by means of ArcGIS combining with the auxiliary data and using artificial visual interpretation, to determine the area of changes and the category of change objects. According to the unified change information extraction principle to extract change areas. Finally, the change detection results are compared with 3 m resolution TerraSAR-X data and 2 m resolution multi-spectral image, and the accuracy is evaluated. Experimental results show that the accuracy of the GF-3 data is over 75 % in detecting the change of ground objects, and the detection capability of new filling soil is better than that of TerraSAR-X data, verify the detection and monitoring capability of GF-3 data to the change information extraction, also, it shows that GF-3 can provide effective data support for the remote sensing detection of land resources.

Remote sensing of land surface phenology

USGS Publications Warehouse

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

2014-01-01

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

Remote Sensing Technologies and Geospatial Modelling Hierarchy for Smart City Support

NASA Astrophysics Data System (ADS)

Popov, M.; Fedorovsky, O.; Stankevich, S.; Filipovich, V.; Khyzhniak, A.; Piestova, I.; Lubskyi, M.; Svideniuk, M.

2017-12-01

The approach to implementing the remote sensing technologies and geospatial modelling for smart city support is presented. The hierarchical structure and basic components of the smart city information support subsystem are considered. Some of the already available useful practical developments are described. These include city land use planning, urban vegetation analysis, thermal condition forecasting, geohazard detection, flooding risk assessment. Remote sensing data fusion approach for comprehensive geospatial analysis is discussed. Long-term city development forecasting by Forrester - Graham system dynamics model is provided over Kiev urban area.

Methods and potentials for using satellite image classification in school lessons

NASA Astrophysics Data System (ADS)

Voss, Kerstin; Goetzke, Roland; Hodam, Henryk

2011-11-01

The FIS project - FIS stands for Fernerkundung in Schulen (Remote Sensing in Schools) - aims at a better integration of the topic "satellite remote sensing" in school lessons. According to this, the overarching objective is to teach pupils basic knowledge and fields of application of remote sensing. Despite the growing significance of digital geomedia, the topic "remote sensing" is not broadly supported in schools. Often, the topic is reduced to a short reflection on satellite images and used only for additional illustration of issues relevant for the curriculum. Without addressing the issue of image data, this can hardly contribute to the improvement of the pupils' methodical competences. Because remote sensing covers more than simple, visual interpretation of satellite images, it is necessary to integrate remote sensing methods like preprocessing, classification and change detection. Dealing with these topics often fails because of confusing background information and the lack of easy-to-use software. Based on these insights, the FIS project created different simple analysis tools for remote sensing in school lessons, which enable teachers as well as pupils to be introduced to the topic in a structured way. This functionality as well as the fields of application of these analysis tools will be presented in detail with the help of three different classification tools for satellite image classification.

Ship detection in panchromatic images: a new method and its DSP implementation

NASA Astrophysics Data System (ADS)

Yao, Yuan; Jiang, Zhiguo; Zhang, Haopeng; Wang, Mengfei; Meng, Gang

2016-03-01

In this paper, a new ship detection method is proposed after analyzing the characteristics of panchromatic remote sensing images and ship targets. Firstly, AdaBoost(Adaptive Boosting) classifiers trained by Haar features are utilized to make coarse detection of ship targets. Then LSD (Line Segment Detector) is adopted to extract the line features in target slices to make fine detection. Experimental results on a dataset of panchromatic remote sensing images with a spatial resolution of 2m show that the proposed algorithm can achieve high detection rate and low false alarm rate. Meanwhile, the algorithm can meet the needs of practical applications on DSP (Digital Signal Processor).

Fiber-optic Fourier transform infrared spectroscopy for remote label-free sensing of medical device surface contamination.

PubMed

Hassan, Moinuddin; Tan, Xin; Welle, Elissa; Ilev, Ilko

2013-05-01

As a potential major source of biochemical contamination, medical device surfaces are of critical safety concerns in the clinical practice and public health. The development of innovative sensing methods for accurate and real-time detection of medical device surface contamination is essential to protect patients from high risk infection. In this paper, we demonstrate an alternative fiber-optic Fourier Transform Infrared (FTIR) spectroscopy based sensing approach for remote, non-contact, and label-free detection of biochemical contaminants in the mid-infrared (mid-IR) region. The sensing probe is designed using mid-IR hollow fibers and FTIR measurements are carried out in reflection mode. Bovine Serum Albumin (BSA) and bacterial endotoxin of different concentrations under thoroughly dry condition are used to evaluate the detection sensitivity. The devised system can identify ≤0.0025% (≤4 × 10(11) molecules) BSA and 0.5% (0.5 EU/ml) endotoxin concentration. The developed sensing approach may be applied to detect various pathogens that pose public health threats.

Fiber-optic Fourier transform infrared spectroscopy for remote label-free sensing of medical device surface contamination

NASA Astrophysics Data System (ADS)

Hassan, Moinuddin; Tan, Xin; Welle, Elissa; Ilev, Ilko

2013-05-01

As a potential major source of biochemical contamination, medical device surfaces are of critical safety concerns in the clinical practice and public health. The development of innovative sensing methods for accurate and real-time detection of medical device surface contamination is essential to protect patients from high risk infection. In this paper, we demonstrate an alternative fiber-optic Fourier Transform Infrared (FTIR) spectroscopy based sensing approach for remote, non-contact, and label-free detection of biochemical contaminants in the mid-infrared (mid-IR) region. The sensing probe is designed using mid-IR hollow fibers and FTIR measurements are carried out in reflection mode. Bovine Serum Albumin (BSA) and bacterial endotoxin of different concentrations under thoroughly dry condition are used to evaluate the detection sensitivity. The devised system can identify ≤0.0025% (≤4 × 1011 molecules) BSA and 0.5% (0.5 EU/ml) endotoxin concentration. The developed sensing approach may be applied to detect various pathogens that pose public health threats.

The Integration of Remote-Sensing Detection Techniques into the Operational Decision-Making of Marine Oil Spills

NASA Astrophysics Data System (ADS)

Garron, J.; Trainor, S.

2017-12-01

Remotely-sensed data collected from satellites, airplanes and unmanned aerial systems can be used in marine oil spills to identify the overall footprint, estimate fate and transport, and to identify resources at risk. Mandates for the use of best available technology exists for addressing marine oil spills under the jurisdiction of the USCG (33 CFR 155.1050), though clear pathways to familiarization of these technologies during a marine oil spill, or more importantly, between marine oil spills, does not. Similarly, remote-sensing scientists continue to experiment with highly tuned oil detection, fate and transport techniques that can benefit decision-making during a marine oil spill response, but the process of translating these prototypical tools to operational information remains undefined, leading most researchers to describe the "potential" of these new tools in an operational setting rather than their actual use, and decision-makers relying on traditional field observational methods. Arctic marine oil spills are no different in their mandates and the remote-sensing research undertaken, but are unique via the dark, cold, remote, infrastructure-free environment in which they can occur. These conditions increase the reliance of decision-makers in an Arctic oil spill on remotely-sensed data and tools for their manipulation. In the absence of another large-scale oil spill in the US, and limited literature on the subject, this study was undertaken to understand how remotely-sensed data and tools are being used in the Incident Command System of a marine oil spill now, with an emphasis on Arctic implementation. Interviews, oil spill scenario/drill observations and marine oil spill after action reports were collected and analyzed to determine the current state of remote-sensing data use for decision-making during a marine oil spill, and to define a set of recommendations for the process of integrating new remote-sensing tools and information in future oil spill responses. Using automated synthetic aperture radar analyses of oil spills in a common operational picture as a scientific case study, this presentation is a demonstration of how landscape-level scientific data can be integrated into Arctic planning and operational decision-making.

A Saliency Guided Semi-Supervised Building Change Detection Method for High Resolution Remote Sensing Images

PubMed Central

Hou, Bin; Wang, Yunhong; Liu, Qingjie

2016-01-01

Characterizations of up to date information of the Earth’s surface are an important application providing insights to urban planning, resources monitoring and environmental studies. A large number of change detection (CD) methods have been developed to solve them by utilizing remote sensing (RS) images. The advent of high resolution (HR) remote sensing images further provides challenges to traditional CD methods and opportunities to object-based CD methods. While several kinds of geospatial objects are recognized, this manuscript mainly focuses on buildings. Specifically, we propose a novel automatic approach combining pixel-based strategies with object-based ones for detecting building changes with HR remote sensing images. A multiresolution contextual morphological transformation called extended morphological attribute profiles (EMAPs) allows the extraction of geometrical features related to the structures within the scene at different scales. Pixel-based post-classification is executed on EMAPs using hierarchical fuzzy clustering. Subsequently, the hierarchical fuzzy frequency vector histograms are formed based on the image-objects acquired by simple linear iterative clustering (SLIC) segmentation. Then, saliency and morphological building index (MBI) extracted on difference images are used to generate a pseudo training set. Ultimately, object-based semi-supervised classification is implemented on this training set by applying random forest (RF). Most of the important changes are detected by the proposed method in our experiments. This study was checked for effectiveness using visual evaluation and numerical evaluation. PMID:27618903

A Saliency Guided Semi-Supervised Building Change Detection Method for High Resolution Remote Sensing Images.

PubMed

Hou, Bin; Wang, Yunhong; Liu, Qingjie

2016-08-27

Characterizations of up to date information of the Earth's surface are an important application providing insights to urban planning, resources monitoring and environmental studies. A large number of change detection (CD) methods have been developed to solve them by utilizing remote sensing (RS) images. The advent of high resolution (HR) remote sensing images further provides challenges to traditional CD methods and opportunities to object-based CD methods. While several kinds of geospatial objects are recognized, this manuscript mainly focuses on buildings. Specifically, we propose a novel automatic approach combining pixel-based strategies with object-based ones for detecting building changes with HR remote sensing images. A multiresolution contextual morphological transformation called extended morphological attribute profiles (EMAPs) allows the extraction of geometrical features related to the structures within the scene at different scales. Pixel-based post-classification is executed on EMAPs using hierarchical fuzzy clustering. Subsequently, the hierarchical fuzzy frequency vector histograms are formed based on the image-objects acquired by simple linear iterative clustering (SLIC) segmentation. Then, saliency and morphological building index (MBI) extracted on difference images are used to generate a pseudo training set. Ultimately, object-based semi-supervised classification is implemented on this training set by applying random forest (RF). Most of the important changes are detected by the proposed method in our experiments. This study was checked for effectiveness using visual evaluation and numerical evaluation.

A Robust False Matching Points Detection Method for Remote Sensing Image Registration

NASA Astrophysics Data System (ADS)

Shan, X. J.; Tang, P.

2015-04-01

Given the influences of illumination, imaging angle, and geometric distortion, among others, false matching points still occur in all image registration algorithms. Therefore, false matching points detection is an important step in remote sensing image registration. Random Sample Consensus (RANSAC) is typically used to detect false matching points. However, RANSAC method cannot detect all false matching points in some remote sensing images. Therefore, a robust false matching points detection method based on Knearest- neighbour (K-NN) graph (KGD) is proposed in this method to obtain robust and high accuracy result. The KGD method starts with the construction of the K-NN graph in one image. K-NN graph can be first generated for each matching points and its K nearest matching points. Local transformation model for each matching point is then obtained by using its K nearest matching points. The error of each matching point is computed by using its transformation model. Last, L matching points with largest error are identified false matching points and removed. This process is iterative until all errors are smaller than the given threshold. In addition, KGD method can be used in combination with other methods, such as RANSAC. Several remote sensing images with different resolutions and terrains are used in the experiment. We evaluate the performance of KGD method, RANSAC + KGD method, RANSAC, and Graph Transformation Matching (GTM). The experimental results demonstrate the superior performance of the KGD and RANSAC + KGD methods.

Automatic Building Damage Detection Method Using High-Resolution Remote Sensing Images and 3d GIS Model

NASA Astrophysics Data System (ADS)

Tu, Jihui; Sui, Haigang; Feng, Wenqing; Song, Zhina

2016-06-01

In this paper, a novel approach of building damaged detection is proposed using high resolution remote sensing images and 3D GIS-Model data. Traditional building damage detection method considers to detect damaged building due to earthquake, but little attention has been paid to analyze various building damaged types(e.g., trivial damaged, severely damaged and totally collapsed.) Therefore, we want to detect the different building damaged type using 2D and 3D feature of scenes because the real world we live in is a 3D space. The proposed method generalizes that the image geometric correction method firstly corrects the post-disasters remote sensing image using the 3D GIS model or RPC parameters, then detects the different building damaged types using the change of the height and area between the pre- and post-disasters and the texture feature of post-disasters. The results, evaluated on a selected study site of the Beichuan earthquake ruins, Sichuan, show that this method is feasible and effective in building damage detection. It has also shown that the proposed method is easily applicable and well suited for rapid damage assessment after natural disasters.

Evidential analysis of difference images for change detection of multitemporal remote sensing images

NASA Astrophysics Data System (ADS)

Chen, Yin; Peng, Lijuan; Cremers, Armin B.

2018-03-01

In this article, we develop two methods for unsupervised change detection in multitemporal remote sensing images based on Dempster-Shafer's theory of evidence (DST). In most unsupervised change detection methods, the probability of difference image is assumed to be characterized by mixture models, whose parameters are estimated by the expectation maximization (EM) method. However, the main drawback of the EM method is that it does not consider spatial contextual information, which may entail rather noisy detection results with numerous spurious alarms. To remedy this, we firstly develop an evidence theory based EM method (EEM) which incorporates spatial contextual information in EM by iteratively fusing the belief assignments of neighboring pixels to the central pixel. Secondly, an evidential labeling method in the sense of maximizing a posteriori probability (MAP) is proposed in order to further enhance the detection result. It first uses the parameters estimated by EEM to initialize the class labels of a difference image. Then it iteratively fuses class conditional information and spatial contextual information, and updates labels and class parameters. Finally it converges to a fixed state which gives the detection result. A simulated image set and two real remote sensing data sets are used to evaluate the two evidential change detection methods. Experimental results show that the new evidential methods are comparable to other prevalent methods in terms of total error rate.

Remote Sensing of Plastic Debris

NASA Astrophysics Data System (ADS)

Garaba, S. P.; Dierssen, H. M.

2016-02-01

Plastic debris is becoming a nuisance in the environment and as a result there has been a dire need to synoptically detect and quantify them in the ocean and on land. We investigate the possible utility of spectral information determined from hand held, airborne and satellite remote sensing tools in the detection and identification polymer source of plastic debris. Sampled debris will be compared to our derived spectral library of typical raw polymer sources found at sea and in household waste. Additional work will be to determine ways to estimate the abundance of plastic debris in target areas. Implications of successful remote detection, tracking and quantification of plastic debris will be towards validating field observations over large areas and at repeated time intervals both on land and at sea.

Book Review: Book review

NASA Astrophysics Data System (ADS)

van der Linden, Sebastian

2016-05-01

Compiling a good book on urban remote sensing is probably as hard as the research in this disciplinary field itself. Urban areas comprise various environments and show high heterogeneity in many respects, they are highly dynamic in time and space and at the same time of greatest influence on connected and even tele-connected regions due to their great economic importance. Urban remote sensing is therefore of great importance, yet as manifold as its study area: mapping urban areas (or sub-categories thereof) plays an important (and challenging) role in land use and land cover (change) monitoring; the analysis of urban green and forests is by itself a specialization of ecological remote sensing; urban climatology asks for spatially and temporally highly resolved remote sensing products; the detection of artificial objects is not only a common and important remote sensing application but also a typical benchmark for image analysis techniques, etc. Urban analyses are performed with all available spaceborne sensor types and at the same time they are one of the most relevant fields for airborne remote sensing. Several books on urban remote sensing have been published during the past 10 years, each taking a different perspective. The book Global Urban Monitoring and Assessment through Earth Observation is motivated by the objectives of the Global Urban Observation and Information Task (SB-04) in the GEOSS (Global Earth Observation System of Systems) 2012-2015 workplan (compare Chapter 2) and wants to highlight the global aspects of state-of-the-art urban remote sensing.

Intelligent Detection of Structure from Remote Sensing Images Based on Deep Learning Method

NASA Astrophysics Data System (ADS)

Xin, L.

2018-04-01

Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.

Remote sensing and human health: new sensors and new opportunities.

PubMed

Beck, L R; Lobitz, B M; Wood, B L

2000-01-01

Since the launch of Landsat-1 28 years ago, remotely sensed data have been used to map features on the earth's surface. An increasing number of health studies have used remotely sensed data for monitoring, surveillance, or risk mapping, particularly of vector-borne diseases. Nearly all studies used data from Landsat, the French Système Pour l'Observation de la Terre, and the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer. New sensor systems are in orbit, or soon to be launched, whose data may prove useful for characterizing and monitoring the spatial and temporal patterns of infectious diseases. Increased computing power and spatial modeling capabilities of geographic information systems could extend the use of remote sensing beyond the research community into operational disease surveillance and control. This article illustrates how remotely sensed data have been used in health applications and assesses earth-observing satellites that could detect and map environmental variables related to the distribution of vector-borne and other diseases.

Automated railroad reconstruction from remote sensing image based on texture filter

NASA Astrophysics Data System (ADS)

Xiao, Jie; Lu, Kaixia

2018-03-01

Techniques of remote sensing have been improved incredibly in recent years and very accurate results and high resolution images can be acquired. There exist possible ways to use such data to reconstruct railroads. In this paper, an automated railroad reconstruction method from remote sensing images based on Gabor filter was proposed. The method is divided in three steps. Firstly, the edge-oriented railroad characteristics (such as line features) in a remote sensing image are detected using Gabor filter. Secondly, two response images with the filtering orientations perpendicular to each other are fused to suppress the noise and acquire a long stripe smooth region of railroads. Thirdly, a set of smooth regions can be extracted by firstly computing global threshold for the previous result image using Otsu's method and then converting it to a binary image based on the previous threshold. This workflow is tested on a set of remote sensing images and was found to deliver very accurate results in a quickly and highly automated manner.

Remote sensing and human health: new sensors and new opportunities

NASA Technical Reports Server (NTRS)

Beck, L. R.; Lobitz, B. M.; Wood, B. L.

2000-01-01

Since the launch of Landsat-1 28 years ago, remotely sensed data have been used to map features on the earth's surface. An increasing number of health studies have used remotely sensed data for monitoring, surveillance, or risk mapping, particularly of vector-borne diseases. Nearly all studies used data from Landsat, the French Systeme Pour l'Observation de la Terre, and the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer. New sensor systems are in orbit, or soon to be launched, whose data may prove useful for characterizing and monitoring the spatial and temporal patterns of infectious diseases. Increased computing power and spatial modeling capabilities of geographic information systems could extend the use of remote sensing beyond the research community into operational disease surveillance and control. This article illustrates how remotely sensed data have been used in health applications and assesses earth-observing satellites that could detect and map environmental variables related to the distribution of vector-borne and other diseases.

Remote Sensing of Environmental Pollution

NASA Technical Reports Server (NTRS)

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.

Remote sensing and implications for variable-rate application using agricultural aircraft

NASA Astrophysics Data System (ADS)

Thomson, Steven J.; Smith, Lowrey A.; Ray, Jeffrey D.; Zimba, Paul V.

2004-01-01

Aircraft routinely used for agricultural spray application are finding utility for remote sensing. Data obtained from remote sensing can be used for prescription application of pesticides, fertilizers, cotton growth regulators, and water (the latter with the assistance of hyperspectral indices and thermal imaging). Digital video was used to detect weeds in early cotton, and preliminary data were obtained to see if nitrogen status could be detected in early soybeans. Weeds were differentiable from early cotton at very low altitudes (65-m), with the aid of supervised classification algorithms in the ENVI image analysis software. The camera was flown at very low altitude for acceptable pixel resolution. Nitrogen status was not detectable by statistical analysis of digital numbers (DNs) obtained from images, but soybean cultivar differences were statistically discernable (F=26, p=0.01). Spectroradiometer data are being analyzed to identify narrow spectral bands that might aid in selecting camera filters for determination of plant nitrogen status. Multiple camera configurations are proposed to allow vegetative indices to be developed more readily. Both remotely sensed field images and ground data are to be used for decision-making in a proposed variable-rate application system for agricultural aircraft. For this system, prescriptions generated from digital imagery and data will be coupled with GPS-based swath guidance and programmable flow control.

Remote sensing detection of atmospheric pollutants using lidar, sodar and correlation with air quality data in an industrial area

NASA Astrophysics Data System (ADS)

Steffens, Juliana; da Costa, Renata F.; Landulfo, Eduardo; Guardani, Roberto; Moreira, Paulo F., Jr.; Held, Gerhard

2011-11-01

Optical remote sensing techniques have obvious advantages for monitoring gas and aerosol emissions, since they enable the operation over large distances, far from hostile environments, and fast processing of the measured signal. In this study two remote sensing devices, namely a Lidar (Light Detection and Ranging) for monitoring the vertical profile of backscattered light intensity, and a Sodar (Acoustic Radar, Sound Detection and Ranging) for monitoring the vertical profile of the wind vector were operated during specific periods. The acquired data were processed and compared with data of air quality obtained from ground level monitoring stations, in order to verify the possibility of using the remote sensing techniques to monitor industrial emissions. The campaigns were carried out in the area of the Environmental Research Center (Cepema) of the University of Sao Paulo, in the city of Cubatao, Brazil, a large industrial site, where numerous different industries are located, including an oil refinery, a steel plant, as well as fertilizer, cement and chemical/petrochemical plants. The local environmental problems caused by the industrial activities are aggravated by the climate and topography of the site, unfavorable to pollutant dispersion. Results of a campaign are presented for a 24- hour period, showing data of a Lidar, an air quality monitoring station and a Sodar.

Performance of One-Class Classifiers for Invasive Species Mapping using Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Skowronek, S.; Asner, G. P.; Feilhauer, H.

2016-12-01

Reliable distribution maps are crucial for the monitoring and management of invasive plant species. Remote sensing can provide such maps for larger areas. However, most remote sensing approaches focus on species in a prominent phenological stage, and a systematic assessment of the performance of different one-class classifiers for mapping species in a more inconspicuous phenological stage is missing so far. In this study, we used hyperspectral remote sensing data to detect the invasive grass Phalaris aquatica and the invasive herb Centaurea solstitialisin a pre-flowering stage in the Jasper Ridge Biological Preserve in California. We collected presence-only data, 66 plots for C. solstitialis and 30 plots for P. aquatica, to calibrate a distribution model and additional presence-absence data (166 / 173 plots) to validate model performance. All plots have a size of 3 m x 3 m. The hyperspectral remote sensing imagery was acquired using the Carnegie Airborne Observatory (CAO) visible to shortwave infrared (VSWIR) imaging spectrometer (400-2500 nm range) in May 2015 with a ground sampling distance (pixel size) of 1 m x 1 m. To find the best approach for mapping these species, we compared the performance of three different state-of-the-art classifiers working with presence-only data: Maxent, biased support vector machines and boosted regression trees. The resulting overall accuracies were 72 - 74% for C. solstitialis, and 83 - 88% for P. aquatica. For both species the overall performance was slightly better for Maxent and BRT than for biased SVM. The detection rates for low cover plots were considerably higher for C. solstitialis than for P. aquatica. For C. solstitalis, they ranged between 71 and 75% for plots with less than 15% cover, highlighting the potential of remote sensing to contribute to an early detection. The models relied on different areas of the spectrum, but still produced the same general pattern, which implies that more than one property of a species or a mixed plot can be used to create a viable model. We conclude that the different one-class classifiers we tested do allow detecting the target species in a more inconspicuous phenological stage, with similar success rates.

Monitoring Crop Phenology and Growth Stages from Space: Opportunities and Challenges

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.; Mladenova, I. E.; Kustas, W. P.; Alfieri, J. G.

2014-12-01

Crop growth stages in concert with weather and soil moisture conditions can have a significant impact on crop yields. In the U.S., crop growth stages and conditions are reported by farmers at the county level. These reports are somewhat subjective and fluctuate between different reporters, locations and times. Remote sensing data provide an alternative approach to monitoring crop growth over large areas in a more consistent and quantitative way. In the recent years, remote sensing data have been used to detect vegetation phenology at 1-km spatial resolution globally. However, agricultural applications at field scale require finer spatial resolution remote sensing data. Landsat (30-m) data have been successfully used for agricultural applications. There are many medium resolution sensors available today or in near future. These include Landsat, SPOT, RapidEye, ASTER and future Sentinel-2 etc. Approaches have been developed in the past several years to integrate remote sensing data from different sensors which may have different sensor characteristics, and spatial and temporal resolutions. This allows us opportunities today to map crop growth stages and conditions using dense time-series remote sensing at field scales. However, remotely sensed phenology (or phenological metrics) is normally derived based on the mathematical functions of the time-series data. The phenological metrics are determined by either identifying inflection (curvature) points or some pre-defined thresholds in the remote sensing phenology algorithms. Furthermore, physiological crop growth stages may not be directly correlated to the remotely sensed phenology. The relationship between remotely sensed phenology and crop growth stages is likely to vary for specific crop types and varieties, growing stages, conditions and even locations. In this presentation, we will examine the relationship between remotely sensed phenology and crop growth stages using in-situ measurements from Fluxnet sites and crop progress reports from USDA NASS. We will present remote sensing approaches and focus on: 1) integrating multiple sources of remote sensing data; and 2) extracting crop phenology at field scales. An example in the U.S. Corn Belt area will be presented and analyzed. Future directions for mapping crop growth stages will be discussed.

Remote sensing strategic exploration of large or superlarge gold ore deposits

NASA Astrophysics Data System (ADS)

Yan, Shouxun; Liu, Qingsheng; Wang, Hongmei; Wang, Zhigang; Liu, Suhong

1998-08-01

To prospect large or superlarge gold ore deposits, blending of remote sensing techniques and modern metallogenitic theories is one of the effective measures. The theory of metallogeny plays a director role before and during remote sensing technique applications. The remote sensing data with different platforms and different resolutions can be respectively applied to detect direct or indirect metallogenic information, and to identify the ore-controlling structure, especially, the ore-controlling structural assemblage, which, conversely, usually are the new conditions to study and to modify the metallogenic model, and to further develop the exploration model of large or superlarge ore deposits. Guidance by an academic idea of 'adjustment structure' which is the conceptual model of transverse structure, an obscured ore- controlling transverse structure has been identified on the refined TM imagery in the Hadamengou gold ore deposit, Setai Hyperspectral Geological Remote Sensing Testing Site (SHGRSTS), Wulashan mountains, Inner Mongolia, China. Meanwhile, The MAIS data has been applied to quickly identify the auriferous alteration rocks with Correspondence Analysis method and Spectral Angle Mapping (SAM) technique. The theoretical system and technical method of remote sensing strategic exploration of large or superlarge gold ore deposits have been demonstrated by the practices in the SHGRSTS.

Water Column Correction for Coral Reef Studies by Remote Sensing

PubMed Central

Zoffoli, Maria Laura; Frouin, Robert; Kampel, Milton

2014-01-01

Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application. PMID:25215941

Water column correction for coral reef studies by remote sensing.

PubMed

Zoffoli, Maria Laura; Frouin, Robert; Kampel, Milton

2014-09-11

Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application.

Magnetic Anomaly Detection by Remote Means

DTIC Science & Technology

2016-09-21

REFERENCES 1. W. Happer, "Laser Remote Sensing of Magnetic Fields in the Atmosphere by Two-Photon Optical Pumping of Xe 129,” , NADC Report N62269-78-M...by Remote Means 5b. GRANT NUMBER NOOO 14-13-1-0282 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Miles , Richard and Dogariu...unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Research on the possibility of detecting magnetic anomalies remotely using laser excitation of a

The U.S. Geological Survey Land Remote Sensing Program

USGS Publications Warehouse

,

2003-01-01

In 2002, the U. S. Geological Survey (USGS) launched a program to enhance the acquisition, preservation, and use of remotely sensed data for USGS science programs, as well as for those of cooperators and customers. Remotely sensed data are fundamental tools for studying the Earth's land surface, including coastal and near-shore environments. For many decades, the USGS has been a leader in providing remotely sensed data to the national and international communities. Acting on its historical topographic mapping mission, the USGS has archived and distributed aerial photographs of the United States for more than half a century. Since 1972, the USGS has acquired, processed, archived, and distributed Landsat and other satellite and airborne remotely sensed data products to users worldwide. Today, the USGS operates and manages the Landsats 5 and 7 missions and cooperates with the National Aeronautics and Space Administration (NASA) to define and implement future satellite missions that will continue and expand the collection of moderate-resolution remotely sensed data. In addition to being a provider of remotely sensed data, the USGS is a user of these data and related remote sensing technology. These data are used in natural resource evaluations for energy and minerals, coastal environmental surveys, assessments of natural hazards (earthquakes, volcanoes, and landslides), biological surveys and investigations, water resources status and trends analyses and studies, and geographic and cartographic applications, such as wildfire detection and tracking and as a source of information for The National Map. The program furthers these distinct but related roles by leading the USGS activities in providing remotely sensed data while advancing applications of such data for USGS programs and a wider user community.

Evaluation of spatial, radiometric and spectral Thematic Mapper performance for coastal studies

NASA Technical Reports Server (NTRS)

Klemas, V.; Ackleson, S. G.; Hardisky, M. A.

1985-01-01

On 31 March 1983, the University of Delaware's Center for Remote Sensing initiated a study to evaluate the spatial, radiometric and spectral performance of the LANDSAT Thematic Mapper for coastal and estuarine studies. The investigation was supported by Contract NAS5-27580 from the NASA Goddard Space Flight Center. The research was divided into three major subprojects: (1) a comparison of LANDSAT TM to MSS imagery for detecting submerged aquatic vegetation in Chesapeake Bay; (2) remote sensing of submerged aquatic vegetation - a radiative transfer approach; and (3) remote sensing of coastal wetland biomass using Thematic Mapper wavebands.

Public health applications of remote sensing of vector borne and parasitic diseases

NASA Technical Reports Server (NTRS)

1976-01-01

Results of an investigation of the potential application of remote sensing to various fields of public health are presented. Specific topics discussed include: detection of snail habitats in connection with the epidemiology of schistosomiasis; the detection of certain Anopheles breeding sites, and location of transient human populations, both in connection with malaria eradication programs; and detection of overwintering population sites for the primary screwworm (Cochliomyia americana). Emphasis was placed on the determination of ground truth data on the biological, chemical, and physical characteristics of ground waters which would or would not support the growth of significant populations of mosquitoes.

Can Hyperspectral Remote Sensing Detect Species Specific Biochemicals ?

NASA Astrophysics Data System (ADS)

Vanderbilt, V. C.; Daughtry, C. S.

2011-12-01

Discrimination of a few plants scattered among many plants is a goal common to detection of agricultural weeds, invasive plant species and illegal Cannabis clandestinely grown outdoors, the subject of this research. Remote sensing technology provides an automated, computer based, land cover classification capability that holds promise for improving upon the existing approaches to Cannabis detection. In this research, we investigated whether hyperspectral reflectance of recently harvested, fully turgid Cannabis leaves and buds depends upon the concentration of the psychoactive ingredient Tetrahydrocannabinol (THC) that, if present at sufficient concentration, presumably would allow species-specific identification of Cannabis.

An evaluation of remote sensing technologies for the detection of fugitive contamination at selected Superfund hazardous waste sites in Pennsylvania

USGS Publications Warehouse

Slonecker, E. Terrence; Fisher, Gary B.

2014-01-01

This evaluation was conducted to assess the potential for using both traditional remote sensing, such as aerial imagery, and emerging remote sensing technology, such as hyperspectral imaging, as tools for postclosure monitoring of selected hazardous waste sites. Sixteen deleted Superfund (SF) National Priorities List (NPL) sites in Pennsylvania were imaged with a Civil Air Patrol (CAP) Airborne Real-Time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) sensor between 2009 and 2012. Deleted sites are those sites that have been remediated and removed from the NPL. The imagery was processed to radiance and atmospherically corrected to relative reflectance with standard software routines using the Environment for Visualizing Imagery (ENVI, ITT–VIS, Boulder, Colorado) software. Standard routines for anomaly detection, endmember collection, vegetation stress, and spectral analysis were applied.

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

NASA Astrophysics Data System (ADS)

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 and cooperation and communication to the larger end-user community on remote sensing and its best use.

A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers

Treesearch

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

2016-01-01

In evergreen conifers, where the foliage amount changes little with season, accurate detection of the underlying “photosynthetic phenology” from satellite remote sensing has been difficult, presenting challenges for global models of ecosystem carbon uptake. Here, we report a close correspondence between seasonally changing foliar pigment levels, expressed as...

Lidar remote sensing of above-ground biomass in three biomes.

Treesearch

Michael A. Lefsky; Warren B. Cohen; David J. Harding; Geoffrey G. Parkers; Steven A. Acker; S. Thomas Gower

2002-01-01

Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, estimation of carbon storage in moderate to high biomass forests is difficult for conventional optical and radar sensors. Lidar (light detection and ranging) instruments measure the vertical...

Remote Sensing of Water Pollution

NASA Technical Reports Server (NTRS)

White, P. G.

1971-01-01

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

At-sea detection of marine debris: overview of technologies, processes, issues, and options.

PubMed

Mace, Thomas H

2012-01-01

At-sea detection of marine debris presents a difficult problem, as the debris items are often relatively small and partially submerged. However, they may accumulate in water parcel boundaries or eddy lines. The application of models, satellite radar and multispectral data, and airborne remote sensing (particularly radar) to focus the search on eddies and convergence zones in the open ocean appear to be a productive avenue of investigation. A multistage modeling and remote sensing approach is proposed for the identification of areas of the open ocean where debris items are more likely to congregate. A path forward may best be achieved through the refinement of the Ghost Net procedures with the addition of a final search stage using airborne radar from an UAS simulator aircraft to detect zones of potential accumulation for direct search. Sampling strategies, direct versus indirect measurements, remote sensing resolution, sensor/platform considerations, and future state are addressed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Spatial-Spectral Approaches to Edge Detection in Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Cox, Cary M.

This dissertation advances geoinformation science at the intersection of hyperspectral remote sensing and edge detection methods. A relatively new phenomenology among its remote sensing peers, hyperspectral imagery (HSI) comprises only about 7% of all remote sensing research - there are five times as many radar-focused peer reviewed journal articles than hyperspectral-focused peer reviewed journal articles. Similarly, edge detection studies comprise only about 8% of image processing research, most of which is dedicated to image processing techniques most closely associated with end results, such as image classification and feature extraction. Given the centrality of edge detection to mapping, that most important of geographic functions, improving the collective understanding of hyperspectral imagery edge detection methods constitutes a research objective aligned to the heart of geoinformation sciences. Consequently, this dissertation endeavors to narrow the HSI edge detection research gap by advancing three HSI edge detection methods designed to leverage HSI's unique chemical identification capabilities in pursuit of generating accurate, high-quality edge planes. The Di Zenzo-based gradient edge detection algorithm, an innovative version of the Resmini HySPADE edge detection algorithm and a level set-based edge detection algorithm are tested against 15 traditional and non-traditional HSI datasets spanning a range of HSI data configurations, spectral resolutions, spatial resolutions, bandpasses and applications. This study empirically measures algorithm performance against Dr. John Canny's six criteria for a good edge operator: false positives, false negatives, localization, single-point response, robustness to noise and unbroken edges. The end state is a suite of spatial-spectral edge detection algorithms that produce satisfactory edge results against a range of hyperspectral data types applicable to a diverse set of earth remote sensing applications. This work also explores the concept of an edge within hyperspectral space, the relative importance of spatial and spectral resolutions as they pertain to HSI edge detection and how effectively compressed HSI data improves edge detection results. The HSI edge detection experiments yielded valuable insights into the algorithms' strengths, weaknesses and optimal alignment to remote sensing applications. The gradient-based edge operator produced strong edge planes across a range of evaluation measures and applications, particularly with respect to false negatives, unbroken edges, urban mapping, vegetation mapping and oil spill mapping applications. False positives and uncompressed HSI data presented occasional challenges to the algorithm. The HySPADE edge operator produced satisfactory results with respect to localization, single-point response, oil spill mapping and trace chemical detection, and was challenged by false positives, declining spectral resolution and vegetation mapping applications. The level set edge detector produced high-quality edge planes for most tests and demonstrated strong performance with respect to false positives, single-point response, oil spill mapping and mineral mapping. False negatives were a regular challenge for the level set edge detection algorithm. Finally, HSI data optimized for spectral information compression and noise was shown to improve edge detection performance across all three algorithms, while the gradient-based algorithm and HySPADE demonstrated significant robustness to declining spectral and spatial resolutions.

Knowledge-guided golf course detection using a convolutional neural network fine-tuned on temporally augmented data

NASA Astrophysics Data System (ADS)

Chen, Jingbo; Wang, Chengyi; Yue, Anzhi; Chen, Jiansheng; He, Dongxu; Zhang, Xiuyan

2017-10-01

The tremendous success of deep learning models such as convolutional neural networks (CNNs) in computer vision provides a method for similar problems in the field of remote sensing. Although research on repurposing pretrained CNN to remote sensing tasks is emerging, the scarcity of labeled samples and the complexity of remote sensing imagery still pose challenges. We developed a knowledge-guided golf course detection approach using a CNN fine-tuned on temporally augmented data. The proposed approach is a combination of knowledge-driven region proposal, data-driven detection based on CNN, and knowledge-driven postprocessing. To confront data complexity, knowledge-derived cooccurrence, composition, and area-based rules are applied sequentially to propose candidate golf regions. To confront sample scarcity, we employed data augmentation in the temporal domain, which extracts samples from multitemporal images. The augmented samples were then used to fine-tune a pretrained CNN for golf detection. Finally, commission error was further suppressed by postprocessing. Experiments conducted on GF-1 imagery prove the effectiveness of the proposed approach.

Rapid Change Detection Algorithm for Disaster Management

NASA Astrophysics Data System (ADS)

Michel, U.; Thunig, H.; Ehlers, M.; Reinartz, P.

2012-07-01

This paper focuses on change detection applications in areas where catastrophic events took place which resulted in rapid destruction especially of manmade objects. Standard methods for automated change detection prove not to be sufficient; therefore a new method was developed and tested. The presented method allows a fast detection and visualization of change in areas of crisis or catastrophes. While often new methods of remote sensing are developed without user oriented aspects, organizations and authorities are not able to use these methods because of absence of remote sensing know how. Therefore a semi-automated procedure was developed. Within a transferable framework, the developed algorithm can be implemented for a set of remote sensing data among different investigation areas. Several case studies are the base for the retrieved results. Within a coarse dividing into statistical parts and the segmentation in meaningful objects, the framework is able to deal with different types of change. By means of an elaborated Temporal Change Index (TCI) only panchromatic datasets are used to extract areas which are destroyed, areas which were not affected and in addition areas where rebuilding has already started.

a Hyperspectral Based Method to Detect Cannabis Plantation in Inaccessible Areas

NASA Astrophysics Data System (ADS)

Houmi, M.; Mohamadi, B.; Balz, T.

2018-04-01

The increase in drug use worldwide has led to sophisticated illegal planting methods. Most countries depend on helicopters, and local knowledge to identify such illegal plantations. However, remote sensing techniques can provide special advantages for monitoring the extent of illegal drug production. This paper sought to assess the ability of the Satellite remote sensing to detect Cannabis plantations. This was achieved in two stages: 1- Preprocessing of Hyperspectral data EO-1, and testing the capability to collect the spectral signature of Cannabis in different sites of the study area (Morocco) from well-known Cannabis plantation fields. 2- Applying the method of Spectral Angle Mapper (SAM) based on a specific angle threshold on Hyperion data EO-1 in well-known Cannabis plantation sites, and other sites with negative Cannabis plantation in another study area (Algeria), to avoid any false Cannabis detection using these spectra. This study emphasizes the benefits of using hyperspectral remote sensing data as an effective detection tool for illegal Cannabis plantation in inaccessible areas based on SAM classification method with a maximum angle (radians) less than 0.03.

Role of remote sensing in desert locust early warning

NASA Astrophysics Data System (ADS)

Cressman, Keith

2013-01-01

Desert locust (Schistocerca gregaria, Forskål) plagues have historically had devastating consequences on food security in Africa and Asia. The current strategy to reduce the frequency of plagues and manage desert locust infestations is early warning and preventive control. To achieve this, the Food and Agriculture Organization of the United Nations operates one of the oldest, largest, and best-known migratory pest monitoring systems in the world. Within this system, remote sensing plays an important role in detecting rainfall and green vegetation. Despite recent technological advances in data management and analysis, communications, and remote sensing, monitoring desert locusts and preventing plagues in the years ahead will continue to be a challenge from a geopolitical and financial standpoint for affected countries and the international donor community. We present an overview of the use of remote sensing in desert locust early warning.

Dejection and/or prevention of human diseases through remote sensing

NASA Technical Reports Server (NTRS)

Edmisten, J. A.

1976-01-01

The use of remote sensors for the detection of probable areas of disease infestation, and possibly as a tool in the control of these diseases, is discussed. Particular attention is given to malaria, encephalitis, and Rocky Mountain Spotted Fever. The vector ecology, epidemiology, and pathogenesis of these diseases are examined. The use of remote sensors to detect the presence of Red Tide is also discussed.

Remote sensing of impervious surface growth: A framework for quantifying urban expansion and re-densification mechanisms

NASA Astrophysics Data System (ADS)

Shahtahmassebi, Amir Reza; Song, Jie; Zheng, Qing; Blackburn, George Alan; Wang, Ke; Huang, Ling Yan; Pan, Yi; Moore, Nathan; Shahtahmassebi, Golnaz; Sadrabadi Haghighi, Reza; Deng, Jing Song

2016-04-01

A substantial body of literature has accumulated on the topic of using remotely sensed data to map impervious surfaces which are widely recognized as an important indicator of urbanization. However, the remote sensing of impervious surface growth has not been successfully addressed. This study proposes a new framework for deriving and summarizing urban expansion and re-densification using time series of impervious surface fractions (ISFs) derived from remotely sensed imagery. This approach integrates multiple endmember spectral mixture analysis (MESMA), analysis of regression residuals, spatial statistics (Getis_Ord) and urban growth theories; hence, the framework is abbreviated as MRGU. The performance of MRGU was compared with commonly used change detection techniques in order to evaluate the effectiveness of the approach. The results suggested that the ISF regression residuals were optimal for detecting impervious surface changes while Getis_Ord was effective for mapping hotspot regions in the regression residuals image. Moreover, the MRGU outputs agreed with the mechanisms proposed in several existing urban growth theories, but importantly the outputs enable the refinement of such models by explicitly accounting for the spatial distribution of both expansion and re-densification mechanisms. Based on Landsat data, the MRGU is somewhat restricted in its ability to measure re-densification in the urban core but this may be improved through the use of higher spatial resolution satellite imagery. The paper ends with an assessment of the present gaps in remote sensing of impervious surface growth and suggests some solutions. The application of impervious surface fractions in urban change detection is a stimulating new research idea which is driving future research with new models and algorithms.

Optimalisation of remote sensing algorithm in mapping of chlorophyl-a concentration at Pasuruan coastal based on surface reflectance images of Aqua Modis

NASA Astrophysics Data System (ADS)

Wibisana, H.; Zainab, S.; Dara K., A.

2018-01-01

Chlorophyll-a is one of the parameters used to detect the presence of fish populations, as well as one of the parameters to state the quality of a water. Research on chlorophyll concentrations has been extensively investigated as well as with chlorophyll-a mapping using remote sensing satellites. Mapping of chlorophyll concentration is used to obtain an optimal picture of the condition of waters that is often used as a fishing area by the fishermen. The role of remote sensing is a technological breakthrough in broadly monitoring the condition of waters. And in the process to get a complete picture of the aquatic conditions it would be used an algorithm that can provide an image of the concentration of chlorophyll at certain points scattered in the research area of capture fisheries. Remote sensing algorithms have been widely used by researchers to detect the presence of chlorophyll content, where the channels corresponding to the mapping of chlorophyll -concentrations from Landsat 8 images are canals 4, 3 and 2. With multiple channels from Landsat-8 satellite imagery used for chlorophyll detection, optimum algorithmic search can be formulated to obtain maximum results of chlorophyll-a concentration in the research area. From the calculation of remote sensing algorithm hence can be known the suitable algorithm for condition at coast of Pasuruan, where green channel give good enough correlation equal to R2 = 0,853 with algorithm for Chlorophyll-a (mg / m3) = 0,093 (R (-0) Red - 3,7049, from this result it can be concluded that there is a good correlation of the green channel that can illustrate the concentration of chlorophyll scattered along the coast of Pasuruan

Airborne and Ground-Based Optical Characterization of Legacy Underground Nuclear Test Sites

NASA Astrophysics Data System (ADS)

Vigil, S.; Craven, J.; Anderson, D.; Dzur, R.; Schultz-Fellenz, E. S.; Sussman, A. J.

2015-12-01

Detecting, locating, and characterizing suspected underground nuclear test sites is a U.S. security priority. Currently, global underground nuclear explosion monitoring relies on seismic and infrasound sensor networks to provide rapid initial detection of potential underground nuclear tests. While seismic and infrasound might be able to generally locate potential underground nuclear tests, additional sensing methods might be required to further pinpoint test site locations. Optical remote sensing is a robust approach for site location and characterization due to the ability it provides to search large areas relatively quickly, resolve surface features in fine detail, and perform these tasks non-intrusively. Optical remote sensing provides both cultural and surface geological information about a site, for example, operational infrastructure, surface fractures. Surface geological information, when combined with known or estimated subsurface geologic information, could provide clues concerning test parameters. We have characterized two legacy nuclear test sites on the Nevada National Security Site (NNSS), U20ak and U20az using helicopter-, ground- and unmanned aerial system-based RGB imagery and light detection and ranging (lidar) systems. The multi-faceted information garnered from these different sensing modalities has allowed us to build a knowledge base of how a nuclear test site might look when sensed remotely, and the standoff distances required to resolve important site characteristics.

[Remote sensing of atmospheric trace gas by airborne passive FTIR].

PubMed

Gao, Min-quang; Liu, Wen-qing; Zhang, Tian-shu; Liu, Jian-guo; Lu, Yi-huai; Wang, Ya-ping; Xu, Liang; Zhu, Jun; Chen, Jun

2006-12-01

The present article describes the details of aviatic measurement for remote sensing trace gases in atmosphere under various surface backgrounds with airborne passive FTIR. The passive down viewing and remote sensing technique used in the experiment is discussed. The method of acquiring atmospheric trace gases infrared characteristic spectra in complicated background and the algorithm of concentration retrieval are discussed. The concentrations of CO and N2O of boundary-layer atmosphere in experimental region below 1000 m are analyzed quantitatively. This measurement technique and the data analysis method, which does not require a previously measured background spectrum, allow fast and mobile remote detection and identification of atmosphere trace gas in large area, and also can be used for urgent monitoring of pollution accidental breakout.

Remote sensing to detect the movement of wheat curl mites through the spatial spread of virus symptoms, and identification of thrips as predators of wheat curl mites

NASA Astrophysics Data System (ADS)

Stilwell, Abby R.

The wheat curl mite (WCM), Aceria tosichella Keifer, transmits three viruses to winter wheat: wheat streak mosaic virus, High Plains virus, and Triticum mosaic virus. This virus complex causes yellowing of the foliage and stunting of plants. WCMs disperse by wind, and an increased understanding of mite movement and subsequent virus spread is necessary in determining the risk of serious virus infections in winter wheat. These risk parameters will help growers make better decisions regarding WCM management. The objectives of this study were to evaluate the capabilities of remote sensing to identify virus infected plants and to establish the potential of using remote sensing to track virus spread and consequently, mite movement. Although the WCM is small and very hard to track, the viruses it vectors produce symptoms that can be detected with remote sensing. Field plots of simulated volunteer wheat were established between 2006 and 2009, infested with WCMs, and spread mites and virus into adjacent winter wheat. The virus gradients created by WCM movement allowed for the measurement of mite movement potential with both proximal and aerial remote sensing instruments. The ability to detect WCM-vectored viruses with remote sensing was investigated by comparing vegetation indices calculated from proximal remote sensing data to ground truth data obtained in the field. Of the ten vegetation indices tested, the red edge position (REP) index had the best relationship with ground truth data. The spatial spread of virus from WCM source plots was modeled with cokriging. Virus symptoms predicted by cokriging occurred in an oval pattern displaced to the southeast. Data from the spatial spread in small plots of this study were used to estimate the potential sphere of influence for volunteer wheat fields. The impact of thrips on WCM populations was investigated by a series of greenhouse, field, and observational studies. WCM populations in winter wheat increased more slowly when thrips populations were higher, both in the field and in the greenhouse. Two species of thrips, Thrips tabaci Lindeman and Frankliniella occidentalis (Pergande) were observed to feed directly on WCMs. The collective results from this study identify thrips as a regulating factor for WCM populations.

Development of a Spectropolarimetric Remote Sensing Capability

DTIC Science & Technology

2013-03-01

34Review of passive imaging polarimetry for remote sensing applications," Appl. Opt. 45, 5453-5469 (2006). [8] D. B. Chenault, "Infrared...Annen, “Hyperspectral IR polarimetry with application in demining and unexploded ordnance detection,” SPIE Vol. 3534 (1998). [30] Pesses, M... Polarimetry , Fourier Transform Spectrometer, DOLP, Spectropolarimetry, Stokes 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18

The practical utility of hyperspectral remote sensing for early detection of emerald ash borer

Treesearch

Richard Hallett; Jennifer Pontius; Mary Martin; Lucie Plourde

2008-01-01

Hyperspectral remote sensing technology has been used in forest ecology research for the last decade to examine landscape scale patterns of foliar chemistry (nitrogen, cellulose, and lignin) (Martin and Aber 1997), stand productivity (Smith et al. 2002), and soil nitrogen dynamics (Ollinger et al. 2002). More recently, techniques have been developed to map the location...

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1985-01-01

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Thermal remote sensing of active vegetation fires and biomass burning events [Chapter 18

Treesearch

Martin J. Wooster; Gareth Roberts; Alistair M.S. Smith; Joshua Johnston; Patrick Freeborn; Stefania Amici; Andrew T. Hudak

2013-01-01

Thermal remote sensing is widely used in the detection, study, and management of biomass burning occurring in open vegetation fires. Such fires may be planned for land management purposes, may occur as a result of a malicious or accidental ignition by humans, or may result from lightning or other natural phenomena. Under suitable conditions, fires may spread rapidly...

Status and prospects for LiDAR remote sensing of forested ecosystems

Treesearch

M. A. Wulder; N. C. Coops; A. T. Hudak; F. Morsdorf; R. Nelson; G. Newnham; M. Vastaranta

2013-01-01

The science associated with the use of airborne and satellite Light Detection and Ranging (LiDAR) to remotely sense forest structure has rapidly progressed over the past decade. LiDAR has evolved from being a poorly understood, potentially useful tool to an operational technology in a little over a decade, and these instruments have become a major success story in...

ASTER VNIR 15 years growth to the standard imaging radiometer in remote sensing

NASA Astrophysics Data System (ADS)

Hiramatsu, Masaru; Inada, Hitomi; Kikuchi, Masakuni; Sakuma, Fumihiro

2015-10-01

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Visible and Near Infrared Radiometer (VNIR) is the remote sensing equipment which has 3 spectral bands and one along-track stereoscopic band radiometer. ASTER VNIR's planned long life design (more than 5 years) is successfully achieved. ASTER VNIR has been imaging the World-wide Earth surface multiband images and the Global Digital Elevation Model (GDEM). VNIR data create detailed world-wide maps and change-detection of the earth surface as utilization transitions and topographical changes. ASTER VNIR's geometric resolution is 15 meters; it is the highest spatial resolution instrument on NASA's Terra spacecraft. Then, ASTER VNIR was planned for the geometrical basis map makers in Terra instruments. After 15-years VNIR growth to the standard map-maker for space remote-sensing. This paper presents VNIR's feature items during 15-year operation as change-detection images , DEM and calibration result. VNIR observed the World-wide Earth images for biological, climatological, geological, and hydrological study, those successful work shows a way on space remote sensing instruments. Still more, VNIR 15 years observation data trend and onboard calibration trend data show several guide or support to follow-on instruments.

Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria

USGS Publications Warehouse

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

2016-01-01

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

Irrigated lands: Monitoring by remote sensing

NASA Technical Reports Server (NTRS)

Epiphanio, J. C. N.; Vitorelli, I.

1983-01-01

The use of remote sensing for irrigated areas, especially in the region of Guaira, Brazil (state of Sao Paulo), is examined. Major principles of utilizing LANDSAT data for the detection and mapping of irrigated lands are discussed. In addition, initial results obtained by computer processing of digital data, use of MSS (Multispectral Scanner System)/LANDSAT products, and the availability of new remote sensing products are highlighted. Future activities include the launching of the TM (Thematic Mapper)/LANDSAT 4 with 30 meters of resolution and SPOT (Systeme Probatorie d'Observation de la Terre) with 10 to 20 meters of resolution, to be operational in 1984 and 1986 respectively.

Review of oil spill remote sensing.

PubMed

Fingas, Merv; Brown, Carl

2014-06-15

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

First observations of tropospheric δD data observed by ground- and space-based remote sensing and surface in-situ measurement techniques at MUSICA's principle reference station (Izaña Observatory, Spain)

NASA Astrophysics Data System (ADS)

González, Yenny; Schneider, Matthias; Christner, Emanuel; Rodríguez, Omaira E.; Sepúlveda, Eliezer; Dyroff, Christoph; Wiegele, Andreas

2013-04-01

The main goal of the project MUSICA (Multiplatform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) is the generation of a quasi global tropospheric water vapor isototopologue dataset of a good and well-documented quality. Therefore, new ground- and space-based remote sensing observations (NDACC-FTIR and IASI/METOP) are combined with in-situ measurements. This work presents the first comparison between in-situ and remote sensing observations made at the Izaña Atmospheric Research Centre (Tenerife, Canary Islands, Spain). The in-situ measurements are made by a Picarro L2120-i water vapor isotopologue analyzer. At Izaña the in-situ data are affected by local small-scale mixing processes: during daylight, the thermally buoyant upslope flow prompts the mixing between the Marine Boundary Layer (MBL) and the low Free Troposphere (FT). However, the remote sensors detect δD values averaged over altitudes that are more representative for the free troposphere. This difference has to be considered for the comparison. In general, a good agreement between the MUSICA remote sensing and the in situ H2O-versus-δD plots is found, which demonstrates that the MUSICA δD remote sensing products add scientifically valuable information to the H2O data.

Oil pollution signatures by remote sensing.

NASA Technical Reports Server (NTRS)

Catoe, C. E.; Mclean, J. T.

1972-01-01

Study of the possibility of developing an effective remote sensing system for oil pollution monitoring which would be capable of detecting oil films on water, mapping the areal extent of oil slicks, measuring slick thickness, and identifying the oil types. In the spectral regions considered (ultraviolet, visible, infrared, microwave, and radar), the signatures were sufficiently unique when compared to the background so that it was possible to detect and map oil slicks. Both microwave and radar techniques are capable of operating in adverse weather. Fluorescence techniques show promise in identifying oil types. A multispectral system will be required to detect oil, map its distribution, estimate film thickness, and characterize the oil pollutant.

Practical Approach To Building A Mid-Wave Remote Sensing System

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

Pyke, Benjamin J.

The purpose of this project, Laser Active Transmitter & Receiver (LATR), was to build a mobile ground based remote sensing system that can detect, identify and quantify a specific gaseous species using Differential Absorption LIDAR (DIAL). This thesis project is concerned with the development and field testing of a mid-wave infrared active remote sensing system, capable of identifying and quantifying emissions in the 3.2 – 3.5 micron range. The goal is to give a brief description of what remote sensing is about and the specific technique used to analyze the collected data. The thesis will discuss the transmitter and themore » associated subsystems used to create the required wavelength, and the receiver used to collect the returns. And finally, the thesis will discuss the process of collecting the data and some of the results from field and lab collections.« less

Building change detection via a combination of CNNs using only RGB aerial imageries

NASA Astrophysics Data System (ADS)

Nemoto, Keisuke; Hamaguchi, Ryuhei; Sato, Masakazu; Fujita, Aito; Imaizumi, Tomoyuki; Hikosaka, Shuhei

2017-10-01

Building change information extracted from remote sensing imageries is important for various applications such as urban management and marketing planning. The goal of this work is to develop a methodology for automatically capturing building changes from remote sensing imageries. Recent studies have addressed this goal by exploiting 3-D information as a proxy for building height. In contrast, because in practice it is expensive or impossible to prepare 3-D information, we do not rely on 3-D data but focus on using only RGB aerial imageries. Instead, we employ deep convolutional neural networks (CNNs) to extract effective features, and improve change detection accuracy in RGB remote sensing imageries. We consider two aspects of building change detection, building detection and subsequent change detection. Our proposed methodology was tested on several areas, which has some differences such as dominant building characteristics and varying brightness values. On all over the tested areas, the proposed method provides good results for changed objects, with recall values over 75 % with a strict overlap requirement of over 50% in intersection-over-union (IoU). When the IoU threshold was relaxed to over 10%, resulting recall values were over 81%. We conclude that use of CNNs enables accurate detection of building changes without employing 3-D information.

Detection, identification, and quantification techniques for spills of hazardous chemicals

NASA Technical Reports Server (NTRS)

Washburn, J. F.; Sandness, G. A.

1977-01-01

The first 400 chemicals listed in the Coast Guard's Chemical Hazards Response Information System were evaluated with respect to their detectability, identifiability, and quantifiability by 12 generalized remote and in situ sensing techniques. Identification was also attempted for some key areas in water pollution sensing technology.

GIS Integration for Quantitatively Determining the Capabilities of Five Remote Sensors for Resource Exploration

NASA Technical Reports Server (NTRS)

Pascucci, R. F.; Smith, A.

1982-01-01

To assist the U.S. Geological Survey in carrying out a Congressional mandate to investigate the use of side-looking airborne radar (SLAR) for resources exploration, a research program was conducted to define the contribution of SLAR imagery to structural geologic mapping and to compare this with contributions from other remote sensing systems. Imagery from two SLAR systems and from three other remote sensing systems was interpreted, and the resulting information was digitized, quantified and intercompared using a computer-assisted geographic information system (GIS). The study area covers approximately 10,000 square miles within the Naval Petroleum Reserve, Alaska, and is situated between the foothills of the Brooks Range and the North Slope. The principal objectives were: (1) to establish quantitatively, the total information contribution of each of the five remote sensing systems to the mapping of structural geology; (2) to determine the amount of information detected in common when the sensors are used in combination; and (3) to determine the amount of unique, incremental information detected by each sensor when used in combination with others. The remote sensor imagery that was investigated included real-aperture and synthetic-aperture radar imagery, standard and digitally enhanced LANDSAT MSS imagery, and aerial photos.

Remote sensing for detection of termite infestations—Proof of Concept

Treesearch

Frederick Green III; Rachel A. Arango; Charles R. Boardman; Keith J. Bourne; John C. Hermanson; Robert A. Munson

2015-01-01

This paper reports the results of a search to discover the most cost effective and robust method of detecting Reticulitermes flavipes infestations in structural members of remote bridges, homes and other wooden structures and transmitting these results to internet cloud storage thus obviating routine travel to these structures for periodic visual...

Remote sensing of chemical warfare agent by CO2 -lidar

NASA Astrophysics Data System (ADS)

Geiko, Pavel P.; Smirnov, Sergey S.

2014-11-01

The possibilities of remote sensing of chemical warfare agent by differential absorption method were analyzed. The CO2 - laser emission lines suitable for sounding of chemical warfare agent with provision for disturbing absorptions by water vapor were choose. The detection range of chemical warfare agents was estimated for a lidar based on CO2 - laser The other factors influencing upon echolocation range were analyzed.

Detection, identification, and classification of mosquito larval habitats using remote sensing scanners in earth-orbiting satellites.

PubMed

Hayes, R O; Maxwell, E L; Mitchell, C J; Woodzick, T L

1985-01-01

A method of identifying mosquito larval habitats associated with fresh-water plant communities, wetlands, and other aquatic locations at Lewis and Clark Lake in the states of Nebraska and South Dakota, USA, using remote sensing imagery obtained by multispectral scanners aboard earth-orbiting satellites (Landsat 1 and 2) is described. The advantages and limitations of this method are discussed.

Multi-Source Image Analysis.

DTIC Science & Technology

1979-12-01

vegetation shows on the imagery but emphasis has been placed on the detection of wooded and scrub areas and the differentiation between deciduous and...S. A., 1974b, Phenology and remote sensing, phenology and seasonality modeling: in Helmut Lieth, H. (ed.), Ecological Studies-Analysis and Synthesis...Remote Sensing of Ecology , University of d-eorgia Press, Athens, Georgia, p. 63-94. Phillipson, W. R. and T. Liang, 1975, Airphoto analysis in the

The use of satellite data for monitoring temporal and spatial patterns of fire: a comprehensive review

NASA Astrophysics Data System (ADS)

Lasaponara, R.

2009-04-01

Remotely sensed (RS) data can fruitfully support both research activities and operative monitoring of fire at different temporal and spatial scales with a synoptic view and cost effective technologies. "The contribution of remote sensing (RS) to forest fires may be grouped in three categories, according to the three phases of fire management: (i) risk estimation (before fire), (ii) detection (during fire) and (iii) assessment (after fire)" Chuvieco (2006). Relating each phase, wide research activities have been conducted over the years. (i) Risk estimation (before fire) has been mainly based on the use of RS data for (i) monitoring vegetation stress and assessing variations in vegetation moisture content, (ii) fuel type mapping, at different temporal and spatial scales from global, regional down to a local scale (using AVHRR, MODIS, TM, ASTER, Quickbird images and airborne hyperspectral and LIDAR data). Danger estimation has been mainly based on the use of AVHRR (onborad NOAA), MODIS (onboard TERRA and AQUA), VEGETATION (onboard SPOT) due to the technical characteristics (i.e. spectral, spatial and temporal resolution). Nevertheless microwave data have been also used for vegetation monitoring. (ii) Detection: identification of active fires, estimation of fire radiative energy and fire emission. AVHRR was one of the first satellite sensors used for setting up fire detection algorithms. The availbility of MODIS allowed us to obtain global fire products free downloaded from NASA web site. Sensors onboard geostationary satellite platforms, such as GOES, SEVIRI, have been used for fire detection, to obtain a high temporal resolution (at around 15 minutes) monitoring of active fires. (iii) Post fire damage assessment includes: burnt area mapping, fire emission, fire severity, vegetation recovery, fire resilience estimation, and, more recently, fire regime characterization. Chuvieco E. L. Giglio, C. Justice, 2008 Global charactrerization of fire activity: toward defining fire regimes from Earth observation data Global Change Biology vo. 14. doi: 10.1111/j.1365-2486.2008.01585.x 1-15, Chuvieco E., P. Englefield, Alexander P. Trishchenko, Yi Luo Generation of long time series of burn area maps of the boreal forest from NOAA-AVHRR composite data. Remote Sensing of Environment, Volume 112, Issue 5, 15 May 2008, Pages 2381-2396 Chuvieco Emilio 2006, Remote Sensing of Forest Fires: Current limitations and future prospects in Observing Land from Space: Science, Customers and Technology, Advances in Global Change Research Vol. 4 pp 47-51 De Santis A., E. Chuvieco Burn severity estimation from remotely sensed data: Performance of simulation versus empirical models, Remote Sensing of Environment, Volume 108, Issue 4, 29 June 2007, Pages 422-435. De Santis A., E. Chuvieco, Patrick J. Vaughan, Short-term assessment of burn severity using the inversion of PROSPECT and GeoSail models, Remote Sensing of Environment, Volume 113, Issue 1, 15 January 2009, Pages 126-136 García M., E. Chuvieco, H. Nieto, I. Aguado Combining AVHRR and meteorological data for estimating live fuel moisture content Remote Sensing of Environment, Volume 112, Issue 9, 15 September 2008, Pages 3618-3627 Ichoku C., L. Giglio, M. J. Wooster, L. A. Remer Global characterization of biomass-burning patterns using satellite measurements of fire radiative energy. Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 2950-2962. Lasaponara R. and Lanorte, On the capability of satellite VHR QuickBird data for fuel type characterization in fragmented landscape Ecological Modelling Volume 204, Issues 1-2, 24 May 2007, Pages 79-84 Lasaponara R., A. Lanorte, S. Pignatti,2006 Multiscale fuel type mapping in fragmented ecosystems: preliminary results from Hyperspectral MIVIS and Multispectral Landsat TM data, Int. J. Remote Sens., vol. 27 (3) pp. 587-593. Lasaponara R., V. Cuomo, M. F. Macchiato, and T. Simoniello, 2003 .A self-adaptive algorithm based on AVHRR multitemporal data analysis for small active fire detection.n International Journal of Remote Sensing, vol. 24, No 8, 1723-1749. Minchella A., F. Del Frate, F. Capogna, S. Anselmi, F. Manes Use of multitemporal SAR data for monitoring vegetation recovery of Mediterranean burned areas Remote Sensing of Environment, In Press Næsset E., T. Gobakken Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 3079-3090 Peterson S. H, Dar A. Roberts, Philip E. Dennison Mapping live fuel moisture with MODIS data: A multiple regression approach, Remote Sensing of Environment, Volume 112, Issue 12, 15 December 2008, Pages 4272-4284. Schroeder Wilfrid, Elaine Prins, Louis Giglio, Ivan Csiszar, Christopher Schmidt, Jeffrey Morisette, Douglas Morton Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data Remote Sensing of Environment, Volume 112, Issue 5, 15 May 2008, Pages 2711-2726 Shi J., T. Jackson, J. Tao, J. Du, R. Bindlish, L. Lu, K.S. Chen Microwave vegetation indices for short vegetation covers from satellite passive microwave sensor AMSR-E Remote Sensing of Environment, Volume 112, Issue 12, 15 December 2008, Pages 4285-4300 Tansey, K., Grégoire, J-M., Defourny, P., Leigh, R., Pekel, J-F., van Bogaert, E. and Bartholomé, E., 2008 A New, Global, Multi-Annual (2000-2007) Burnt Area Product at 1 km Resolution and Daily Intervals Geophysical Research Letters, VOL. 35, L01401, doi:10.1029/2007GL031567, 2008. Telesca L. and Lasaponara R., 2006; "Pre-and Post- fire Behaviural trends revealed in satellite NDVI time series" Geophysical Research Letters,., 33, L14401, doi:10.1029/2006GL026630 Telesca L. and Lasaponara R 2005 Discriminating Dynamical Patterns in Burned and Unburned Vegetational Covers by Using SPOT-VGT NDVI Data. Geophysical Research Letters,, 32, L21401, doi:10.1029/2005GL024391. Telesca L. and Lasaponara R. Investigating fire-induced behavioural trends in vegetation covers , Communications in Nonlinear Science and Numerical Simulation, 13, 2018-2023, 2008 Telesca L., A. Lanorte and R. Lasaponara, 2007. Investigating dynamical trends in burned and unburned vegetation covers by using SPOT-VGT NDVI data. Journal of Geophysics and Engineering, Vol. 4, pp. 128-138, 2007 Telesca L., R. Lasaponara, and A. Lanorte, Intra-annual dynamical persistent mechanisms in Mediterranean ecosystems revealed SPOT-VEGETATION Time Series, Ecological Complexity, 5, 151-156, 2008 Verbesselt, J., Somers, B., Lhermitte, S., Jonckheere, I., van Aardt, J., and Coppin, P. (2007) Monitoring herbaceous fuel moisture content with SPOT VEGETATION time-series for fire risk prediction in savanna ecosystems. Remote Sensing of Environment 108: 357-368. Zhang X., S. Kondragunta Temporal and spatial variability in biomass burned areas across the USA derived from the GOES fire product Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 2886-2897 Zhang X., Shobha Kondragunta Temporal and spatial variability in biomass burned areas across the USA derived from the GOES fire product Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 2886-2897

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques

NASA Astrophysics Data System (ADS)

Kumar, Lalit; Ghosh, Manoj Kumer

2012-01-01

Land cover change is a significant issue for environmental managers for sustainable management. Remote sensing techniques have been shown to have a high probability of recognizing land cover patterns and change detection due to periodic coverage, data integrity, and provision of data in a broad range of the electromagnetic spectrum. We evaluate the applicability of remote sensing techniques for land cover pattern recognition, as well as land cover change detection of the Hatiya Island, Bangladesh, and quantify land cover changes from 1977 to 1999. A supervised classification approach was used to classify Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM), and Multispectral Scanner (MSS) images into eight major land cover categories. We detected major land cover changes over the 22-year study period. During this period, marshy land, mud, mud with small grass, and bare soil had decreased by 85%, 46%, 44%, and 24%, respectively, while agricultural land, medium forest, forest, and settlement had positive changes of 26%, 45%, 363%, and 59%, respectively. The primary drivers of such landscape change were erosion and accretion processes, human pressure, and the reforestation and land reclamation programs of the Bangladesh Government.

Lunar Prospector: a Preliminary Surface Remote Sensing Resource Assessment for the Moon

NASA Technical Reports Server (NTRS)

Mardon, A. A.

1992-01-01

The potential existence of lunar volatiles is a scientific discovery that could distinctly change the direction of pathways of inner solar system human expansion. With a dedicated germanium gamma ray spectrometer launched in the early 1990's, surface water concentrations of 0.7 percent could be detected immediately upon full lunar polar orbit operations. The expense of lunar base construction and operation would be dramatically reduced over a scenario with no lunar volatile resources. Global surface mineral distribution could be mapped out and integrated into a GIS database for lunar base site selection. Extensive surface lunar mapping would also result in the utilization of archived Apollo images. A variety of remote sensing systems and their parameters have been proposed for use in the detection of these lunar ice masses. The detection or nondetection of subsurface and surface ice masses in lunar polar crater floors could dramatically direct the development pathways that the human race might follow in its radiation from the Earth to habitable locales in the inner terran solar system. Potential sources of lunar volatiles are described. The use of remote sensing to detect lunar volatiles is addressed.

Wearable system-on-a-chip radiometer for remote temperature sensing and its application to the safeguard of emergency operators.

PubMed

Fonte, A; Alimenti, F; Zito, D; Neri, B; De Rossi, D; Lanatà, A; Tognetti, A

2007-01-01

The remote sensing and the detection of events that may represent a danger for human beings have become more and more important thanks to the latest advances of the technology. A microwave radiometer is a sensor capable to detect a fire or an abnormal increase of the internal temperature of the human body (hyperthermia), or an onset of a cancer, or even meteorological phenomena (forest fires, pollution release, ice formation on road pavement). In this paper, the overview of a wearable low-cost low-power system-on-a-chip (SoaC) 13 GHz passive microwave radiometer in CMOS 90 nm technology is presented. In particular, we focused on its application to the fire detection for civil safeguard. In detail, this sensor has been thought to be inserted into the fireman jacket in order to help the fireman in the detection of a hidden fire behind a door or a wall. The simulation results obtained by Ptolemy system simulation have confirmed the feasibility of such a SoaC microwave radiometer in a low-cost standard silicon technology for temperature remote sensing and, in particular, for its application to the safeguard of emergency operators.

a model based on crowsourcing for detecting natural hazards

NASA Astrophysics Data System (ADS)

Duan, J.; Ma, C.; Zhang, J.; Liu, S.; Liu, J.

2015-12-01

Remote Sensing Technology provides a new method for the detecting,early warning,mitigation and relief of natural hazards. Given the suddenness and the unpredictability of the location of natural hazards as well as the actual demands for hazards work, this article proposes an evaluation model for remote sensing detecting of natural hazards based on crowdsourcing. Firstly, using crowdsourcing model and with the help of the Internet and the power of hundreds of millions of Internet users, this evaluation model provides visual interpretation of high-resolution remote sensing images of hazards area and collects massive valuable disaster data; secondly, this evaluation model adopts the strategy of dynamic voting consistency to evaluate the disaster data provided by the crowdsourcing workers; thirdly, this evaluation model pre-estimates the disaster severity with the disaster pre-evaluation model based on regional buffers; lastly, the evaluation model actuates the corresponding expert system work according to the forecast results. The idea of this model breaks the boundaries between geographic information professionals and the public, makes the public participation and the citizen science eventually be realized, and improves the accuracy and timeliness of hazards assessment results.

Grapevine Remote Sensing Analysis of Phylloxera Early Stress (GRAPES): Remote Sensing Analysis Summary

NASA Technical Reports Server (NTRS)

Lobitz, Brad; Johnson, Lee; Hlavka, Chris; Armstrong, Roy; Bell, Cindy

1997-01-01

High spatial resolution airborne imagery was acquired in California's Napa Valley in 1993 and 1994 as part of the Grapevine Remote sensing Analysis of Phylloxera Early Stress (GRAPES) project. Investigators from NASA, the University of California, the California State University, and Robert Mondavi Winery examined the application of airborne digital imaging technology to vineyard management, with emphasis on detecting the phylloxera infestation in California vineyards. Because the root louse causes vine stress that leads to grapevine death in three to five years, the infested areas must be replanted with resistant rootstock. Early detection of infestation and changing cultural practices can compensate for vine damage. Vineyard managers need improved information to decide where and when to replant fields or sections of fields to minimize crop financial losses. Annual relative changes in leaf area due to phylloxera infestation were determined by using information obtained from computing Normalized Difference Vegetation Index (NDVI) images. Two other methods of monitoring vineyards through imagery were also investigated: optical sensing of the Red Edge Inflection Point (REIP), and thermal sensing. These did not convey the stress patterns as well as the NDVI imagery and require specialized sensor configurations. NDVI-derived products are recommended for monitoring phylloxera infestations.

Dual-use applications of laser remote sensing to the military battlefield and environmental monitoring

NASA Astrophysics Data System (ADS)

Leonelli, Joseph

1994-06-01

For the past 20 years, the Department of Defense has sponsored investigations and studies on the use of laser remote sensing techniques and light detection and ranging (lidar) methods for the detection, identification, and tracking of toxic and hazardous battlefield materials. The same lidar methods used by NASA, EPA, and several industry research groups to detect and measure the movement and concentration of air pollution near urban centers have been applied to the national security problem of detecting chemical and biological warfare agents that might be used on the modern battlefield. Significant government investment in the technology base and laser technology has resulted in advanced hardware configurations that are now available for demonstration and evaluation for industrial and environmental monitoring.

Measuring and Monitoring Long Term Disaster Recovery Using Remote Sensing: A Case Study of Post Katrina New Orleans

NASA Astrophysics Data System (ADS)

Archer, Reginald S.

This research focuses on measuring and monitoring long term recovery progress from the impacts of Hurricane Katrina on New Orleans, LA. Remote sensing has frequently been used for emergency response and damage assessment after natural disasters. However, techniques for analysis of long term disaster recovery using remote sensing have not been widely explored. With increased availability and lower costs, remote sensing offers an objective perspective, systematic and repeatable analysis, and provides a substitute to multiple site visits. In addition, remote sensing allows access to large geographical areas and areas where ground access may be disrupted, restricted or denied. This dissertation addressed the primary difficulties involved in the development of change detection methods capable of detecting changes experienced by disaster recovery indicators. Maximum likelihood classification and post-classification change detection were applied to multi-temporal high resolution aerial images to quantitatively measure the progress of recovery. Images were classified to automatically identify disaster recovery indicators and exploit the indicators that are visible within each image. The spectral analysis demonstrated that employing maximum likelihood classification to high resolution true color aerial images performed adequately and provided a good indication of spectral pattern recognition, despite the limited spectral information. Applying the change detection to the classified images was effective for determining the temporal trajectory of indicators categorized as blue tarps, FEMA trailers, houses, vegetation, bare earth and pavement. The results of the post classification change detection revealed a dominant change trajectory from bluetarp to house, as damaged houses became permanently repaired. Specifically, the level of activity of blue tarps, housing, vegetation, FEMA trailers (temporary housing) pavement and bare earth were derived from aerial image processing to measure and monitor the progress of recovery. Trajectories of recovery for each individual indicator were examined to provide a better understanding of activity during reconstruction. A collection of spatial metrics was explored in order to identify spatial patterns and characterize classes in terms of patches of pixels. One of the key findings of the spatial analysis is that patch shapes were more complex in the presence of debris and damaged or destroyed buildings. The combination of spectral, temporal, and spatial analysis provided a satisfactory, though limited, solution to the question of whether remote sensing alone, can be used to quantitatively assess and monitor the progress of long term recovery following a major disaster. The research described in this dissertation provided a detailed illustration of the level of activity experienced by different recovery indicators during the long term recovery process. It also addressed the primary difficulties involved in the development of change detection methods capable of detecting changes experienced by disaster recovery indicators identified from classified high resolution true color aerial imagery. The results produced in this research demonstrate that the observed trajectories for actual indicators of recovery indicate different levels of recovery activity even within the same community. The level of activity of the long term reconstruction phase observed in the Kates model is not consistent with the level of activity of key recovery indicators in the Lower 9th Ward during the same period. Used in the proper context, these methods and results provide decision making information for determining resources. KEYWORDS: Change detection, classification, Katrina, New Orleans, remote sensing, disaster recovery, spatial metrics

The emerging role of lidar remote sensing in coastal research and resource management

USGS Publications Warehouse

Brock, J.C.; Purkis, S.J.

2009-01-01

Knowledge of coastal elevation is an essential requirement for resource management and scientific research. Recognizing the vast potential of lidar remote sensing in coastal studies, this Special Issue includes a collection of articles intended to represent the state-of-the-art for lidar investigations of nearshore submerged and emergent ecosystems, coastal morphodynamics, and hazards due to sea-level rise and severe storms. Some current applications for lidar remote sensing described in this Special Issue include bluegreen wavelength lidar used for submarine coastal benthic environments such as coral reef ecosystems, airborne lidar used for shoreline mapping and coastal change detection, and temporal waveform-resolving lidar used for vegetation mapping. ?? 2009 Coastal Education and Research Foundation.

The emerging role of lidar remote sensing in coastal research and resource management

USGS Publications Warehouse

Brock, John C.; Purkis, Samuel J.

2009-01-01

Knowledge of coastal elevation is an essential requirement for resource management and scientific research. Recognizing the vast potential of lidar remote sensing in coastal studies, this Special Issue includes a collection of articles intended to represent the state-of-the-art for lidar investigations of nearshore submerged and emergent ecosystems, coastal morphodynamics, and hazards due to sea-level rise and severe storms. Some current applications for lidar remote sensing described in this Special Issue include bluegreen wavelength lidar used for submarine coastal benthic environments such as coral reef ecosystems, airborne lidar used for shoreline mapping and coastal change detection, and temporal waveform-resolving lidar used for vegetation mapping.

Detecting bugweed (Solanum mauritianum) abundance in plantation forestry using multisource remote sensing

NASA Astrophysics Data System (ADS)

Peerbhay, Kabir; Mutanga, Onisimo; Lottering, Romano; Bangamwabo, Victor; Ismail, Riyad

2016-11-01

The invasive weed Solanum mauritianum (bugweed) has infested large areas of plantation forests in KwaZulu-Natal, South Africa. Bugweed often forms dense infestations and rapidly capitalises on available natural resources hindering the production of forest resources. Precise assessment of bugweed canopy cover, especially at low abundance cover, is essential to an effective weed management strategy. In this study, the utility of AISA Eagle airborne hyperspectral data (393-994 nm) with the new generation Worldview-2 multispectral sensor (427-908 nm) was compared to detect the abundance of bugweed cover within the Hodgsons Sappi forest plantation. Using sparse partial least squares discriminant analysis (SPLS-DA), the best detection results were obtained when performing discrimination using the remotely sensing images combined with LiDAR. Overall classification accuracies subsequently improved by 10% and 11.67% for AISA and Worldview-2 respectively, with improved detection accuracies for bugweed cover densities as low as 5%. The incorporation of LiDAR worked well within the SPLS-DA framework for detecting the abundance of bugweed cover using remotely sensed data. In addition, the algorithm performed simultaneous dimension reduction and variable selection successfully whereby wavelengths in the visible (393-670 nm) and red-edge regions (725-734 nm) of the spectrum were the most effective.

Multi-class geospatial object detection and geographic image classification based on collection of part detectors

NASA Astrophysics Data System (ADS)

Cheng, Gong; Han, Junwei; Zhou, Peicheng; Guo, Lei

2014-12-01

The rapid development of remote sensing technology has facilitated us the acquisition of remote sensing images with higher and higher spatial resolution, but how to automatically understand the image contents is still a big challenge. In this paper, we develop a practical and rotation-invariant framework for multi-class geospatial object detection and geographic image classification based on collection of part detectors (COPD). The COPD is composed of a set of representative and discriminative part detectors, where each part detector is a linear support vector machine (SVM) classifier used for the detection of objects or recurring spatial patterns within a certain range of orientation. Specifically, when performing multi-class geospatial object detection, we learn a set of seed-based part detectors where each part detector corresponds to a particular viewpoint of an object class, so the collection of them provides a solution for rotation-invariant detection of multi-class objects. When performing geographic image classification, we utilize a large number of pre-trained part detectors to discovery distinctive visual parts from images and use them as attributes to represent the images. Comprehensive evaluations on two remote sensing image databases and comparisons with some state-of-the-art approaches demonstrate the effectiveness and superiority of the developed framework.

Developing a novel UAV (Unmanned Aerial Vehicle) helicopter platform for very high resolution environmental monitoring of catchment processes

NASA Astrophysics Data System (ADS)

Freer, J. E.; Richardson, T.; Yang, Z.

2012-12-01

Recent advances in remote sensing and geographic information has led the way for the development of hyperspectral sensors and cloud scanning LIDAR (Light Detection And Ranging). Both these technologies can be used to sense environmental processes and capture detailed spatial information, they are often deployed in ground, aircraft and satellite based systems. Hyperspectral remote sensing, also known as imaging spectroscopy, is a relatively new technology that is currently being investigated by researchers and scientists with regard to the detection and identification of landscapes, terrestrial vegetation, and manmade materials and backgrounds. There are many applications that could take advantages of hyperspectral remote sensing coupled to detailed surface feature mapping using LIDAR. This embryonic project involves developing the engineering solutions and post processing techniques needed to realise an ultra high resolution helicopter based environmental sensing platform which can fly at lower altitudes than aircraft systems and can be deployed more frequently. We aim to present this new technology platform in this special session (the only one of it's kind in the UK). Initial applications are planned on a range of environmental sensing problems that would benefit from such complex and detailed data.We look forward to being able to display and discuss this initiative with colleagues and any potential interest in future collaborative projects.

Developing a novel UAV (Unmanned Aerial Vehicle) helicopter platform for very high resolution environmental monitoring of catchment processes

NASA Astrophysics Data System (ADS)

Freer, J.; Richardson, T. S.

2012-04-01

Recent advances in remote sensing and geographic information has led the way for the development of hyperspectral sensors and cloud scanning LIDAR (Light Detection And Ranging). Both these technologies can be used to sense environmental processes and capture detailed spatial information, they are often deployed in ground, aircraft and satellite based systems. Hyperspectral remote sensing, also known as imaging spectroscopy, is a relatively new technology that is currently being investigated by researchers and scientists with regard to the detection and identification of landscapes, terrestrial vegetation, and manmade materials and backgrounds. There are many applications that could take advantages of hyperspectral remote sensing coupled to detailed surface feature mapping using LIDAR. This embryonic project involves developing the engineering solutions and post processing techniques needed to realise an ultra high resolution helicopter based environmental sensing platform which can fly at lower altitudes than aircraft systems and can be deployed more frequently. We aim to display this new technology platform in this special session (the only one of it's kind in the UK). Initial applications are planned on a range of environmental sensing problems that would benefit from such complex and detailed data. We look forward to being able to display and discuss this initiative with colleagues and any potential interest in future collaborative projects.

A fast and fully automatic registration approach based on point features for multi-source remote-sensing images

NASA Astrophysics Data System (ADS)

Yu, Le; Zhang, Dengrong; Holden, Eun-Jung

2008-07-01

Automatic registration of multi-source remote-sensing images is a difficult task as it must deal with the varying illuminations and resolutions of the images, different perspectives and the local deformations within the images. This paper proposes a fully automatic and fast non-rigid image registration technique that addresses those issues. The proposed technique performs a pre-registration process that coarsely aligns the input image to the reference image by automatically detecting their matching points by using the scale invariant feature transform (SIFT) method and an affine transformation model. Once the coarse registration is completed, it performs a fine-scale registration process based on a piecewise linear transformation technique using feature points that are detected by the Harris corner detector. The registration process firstly finds in succession, tie point pairs between the input and the reference image by detecting Harris corners and applying a cross-matching strategy based on a wavelet pyramid for a fast search speed. Tie point pairs with large errors are pruned by an error-checking step. The input image is then rectified by using triangulated irregular networks (TINs) to deal with irregular local deformations caused by the fluctuation of the terrain. For each triangular facet of the TIN, affine transformations are estimated and applied for rectification. Experiments with Quickbird, SPOT5, SPOT4, TM remote-sensing images of the Hangzhou area in China demonstrate the efficiency and the accuracy of the proposed technique for multi-source remote-sensing image registration.

A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data.

PubMed

Vanegas, Fernando; Bratanov, Dmitry; Powell, Kevin; Weiss, John; Gonzalez, Felipe

2018-01-17

Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used-the sensors, the UAV, and the flight operations-the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analising and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications.

Remote sensing in agriculture. [using Earth Resources Technology Satellite photography

NASA Technical Reports Server (NTRS)

Downs, S. W., Jr.

1974-01-01

Some examples are presented of the use of remote sensing in cultivated crops, forestry, and range management. Areas of concern include: the determination of crop areas and types, prediction of yield, and detection of disease; the determination of forest areas and types, timber volume estimation, detection of insect and disease attack, and forest fires; and the determination of range conditions and inventory, and livestock inventory. Articles in the literature are summarized and specific examples of work being performed at the Marshall Space Flight Center are given. Primarily, aerial photographs and photo-like ERTS images are considered.

Radio Frequency Interference Detection for Passive Remote Sensing Using Eigenvalue Analysis

NASA Technical Reports Server (NTRS)

Schoenwald, Adam; Kim, Seung-Jun; Mohammed-Tano, Priscilla

2017-01-01

Radio frequency interference (RFI) can corrupt passive remote sensing measurements taken with microwave radiometers. With the increasingly utilized spectrum and the push for larger bandwidth radiometers, the likelihood of RFI contamination has grown significantly. In this work, an eigenvalue-based algorithm is developed to detect the presence of RFI and provide estimates of RFI-free radiation levels. Simulated tests show that the proposed detector outperforms conventional kurtosis-based RFI detectors in the low-to-medium interferece-to-noise-power-ratio (INR) regime under continuous wave (CW) and quadrature phase shift keying (QPSK) RFIs.

Radio Frequency Interference Detection for Passive Remote Sensing Using Eigenvalue Analysis

NASA Technical Reports Server (NTRS)

Schoenwald, Adam J.; Kim, Seung-Jun; Mohammed, Priscilla N.

2017-01-01

Radio frequency interference (RFI) can corrupt passive remote sensing measurements taken with microwave radiometers. With the increasingly utilized spectrum and the push for larger bandwidth radiometers, the likelihood of RFI contamination has grown significantly. In this work, an eigenvalue-based algorithm is developed to detect the presence of RFI and provide estimates of RFI-free radiation levels. Simulated tests show that the proposed detector outperforms conventional kurtosis-based RFI detectors in the low-to-medium interference-to-noise-power-ratio (INR) regime under continuous wave (CW) and quadrature phase shift keying (QPSK) RFIs.

Raman spectroscopy measurement of CH4 gas and CH4 dissolved in water for laser remote sensing in water

NASA Astrophysics Data System (ADS)

Somekawa, Toshihiro; Fujita, Masayuki

2018-04-01

We examined the applicability of Raman spectroscopy as a laser remote sensing tool for monitoring CH4 in water. The Raman technique has already been used successfully for measurements of CO2 gas in water. In this paper, considering the spectral transmittance of water, third harmonics of Q-switched Nd:YAG laser at 355 nm (UV region) was used for detection of CH4 Raman signals. The Raman signal at 2892 cm-1 from CH4 dissolved in water was detected at a tail of water Raman signal.

Combining hyperspectral imaging and Raman spectroscopy for remote chemical sensing

NASA Astrophysics Data System (ADS)

Ingram, John M.; Lo, Edsanter

2008-04-01

The Photonics Research Center at the United States Military Academy is conducting research to demonstrate the feasibility of combining hyperspectral imaging and Raman spectroscopy for remote chemical detection over a broad area of interest. One limitation of future trace detection systems is their ability to analyze large areas of view. Hyperspectral imaging provides a balance between fast spectral analysis and scanning area. Integration of a hyperspectral system capable of remote chemical detection will greatly enhance our soldiers' ability to see the battlefield to make threat related decisions. It can also queue the trace detection systems onto the correct interrogation area saving time and reconnaissance/surveillance resources. This research develops both the sensor design and the detection/discrimination algorithms. The one meter remote detection without background radiation is a simple proof of concept.

Using Landsat digital data to detect moisture stress in corn-soybean growing regions

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Wehmanen, O. A.

1980-01-01

As a part of a follow-on study to the moisture stress detection effort conducted in the Large Area Crop Inventory Experiment (LACIE), a technique utilizing transformed Landsat digital data was evaluated for detecting moisture stress in humid growing regions using sample segments from Iowa, Illinois, and Indiana. At known growth stages of corn and soybeans, segments were classified as undergoing moisture stress or not undergoing stress. The remote-sensing-based information was compared to a weekly ground-based index (Crop Moisture Index). This comparison demonstrated that the remote sensing technique could be used to monitor the growing conditions within a region where corn and soybeans are the major crop.

Theory on data processing and instrumentation. [remote sensing

NASA Technical Reports Server (NTRS)

Billingsley, F. C.

1978-01-01

A selection of NASA Earth observations programs are reviewed, emphasizing hardware capabilities. Sampling theory, noise and detection considerations, and image evaluation are discussed for remote sensor imagery. Vision and perception are considered, leading to numerical image processing. The use of multispectral scanners and of multispectral data processing systems, including digital image processing, is depicted. Multispectral sensing and analysis in application with land use and geographical data systems are also covered.

[Algorithms of multiband remote sensing for coastal red tide waters].

PubMed

Mao, Xianmou; Huang, Weigen

2003-07-01

The spectral characteristics of the coastal waters in East China Sea was studied using in situ measurements, and the multiband algorithms of remote sensing for bloom waters was discussed and developed. Examples of red tide detection using the algorithms in the East China Sea were presented. The results showed that the algorithms could provide information about the location and the area coverage of the red tide events.

Land use planning

NASA Technical Reports Server (NTRS)

1975-01-01

The organization, objectives, and accomplishments of the panel on Land Use Planning are reported. Technology developments, and projected developments are discussed along with anticipated information requirements. The issues for users, recommended remote sensing programs, and space systems are presented. It was found that remote sensing systems are useful in future land use planning. It is recommended that a change detection system for monitoring land use and critical environmental areas be developed by 1979.

Mini-lidar sensor for the remote stand-off sensing of chemical/biological substances and method for sensing same

DOEpatents

Ray, Mark D.; Sedlacek, Arthur J.

2003-08-19

A method and apparatus for remote, stand-off, and high efficiency spectroscopic detection of biological and chemical substances. The apparatus including an optical beam transmitter which transmits a beam having an axis of transmission to a target, the beam comprising at least a laser emission. An optical detector having an optical detection path to the target is provided for gathering optical information. The optical detection path has an axis of optical detection. A beam alignment device fixes the transmitter proximal to the detector and directs the beam to the target along the optical detection path such that the axis of transmission is within the optical detection path. Optical information gathered by the optical detector is analyzed by an analyzer which is operatively connected to the detector.

Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks

NASA Astrophysics Data System (ADS)

Yang, Xue; Sun, Hao; Fu, Kun; Yang, Jirui; Sun, Xian; Yan, Menglong; Guo, Zhi

2018-01-01

Ship detection has been playing a significant role in the field of remote sensing for a long time but it is still full of challenges. The main limitations of traditional ship detection methods usually lie in the complexity of application scenarios, the difficulty of intensive object detection and the redundancy of detection region. In order to solve such problems above, we propose a framework called Rotation Dense Feature Pyramid Networks (R-DFPN) which can effectively detect ship in different scenes including ocean and port. Specifically, we put forward the Dense Feature Pyramid Network (DFPN), which is aimed at solving the problem resulted from the narrow width of the ship. Compared with previous multi-scale detectors such as Feature Pyramid Network (FPN), DFPN builds the high-level semantic feature-maps for all scales by means of dense connections, through which enhances the feature propagation and encourages the feature reuse. Additionally, in the case of ship rotation and dense arrangement, we design a rotation anchor strategy to predict the minimum circumscribed rectangle of the object so as to reduce the redundant detection region and improve the recall. Furthermore, we also propose multi-scale ROI Align for the purpose of maintaining the completeness of semantic and spatial information. Experiments based on remote sensing images from Google Earth for ship detection show that our detection method based on R-DFPN representation has a state-of-the-art performance.

COSMO-SkyMed and GIS applications

NASA Astrophysics Data System (ADS)

Milillo, Pietro; Sole, Aurelia; Serio, Carmine

2013-04-01

Geographic Information Systems (GIS) and Remote Sensing have become key technology tools for the collection, storage and analysis of spatially referenced data. Industries that utilise these spatial technologies include agriculture, forestry, mining, market research as well as the environmental analysis . Synthetic Aperture Radar (SAR) is a coherent active sensor operating in the microwave band which exploits relative motion between antenna and target in order to obtain a finer spatial resolution in the flight direction exploiting the Doppler effect. SAR have wide applications in Remote Sensing such as cartography, surface deformation detection, forest cover mapping, urban planning, disasters monitoring , surveillance etc… The utilization of satellite remote sensing and GIS technology for this applications has proven to be a powerful and effective tool for environmental monitoring. Remote sensing techniques are often less costly and time-consuming for large geographic areas compared to conventional methods, moreover GIS technology provides a flexible environment for, analyzing and displaying digital data from various sources necessary for classification, change detection and database development. The aim of this work si to illustrate the potential of COSMO-SkyMed data and SAR applications in a GIS environment, in particular a demostration of the operational use of COSMO-SkyMed SAR data and GIS in real cases will be provided for what concern DEM validation, river basin estimation, flood mapping and landslide monitoring.

A review of ultra-short pulse lasers for military remote sensing and rangefinding

NASA Astrophysics Data System (ADS)

Lamb, Robert A.

2009-09-01

Advances in ultra-short pulse laser technology have resulted in commercially available laser systems capable of generating high peak powers >1GW in tabletop systems. This opens the prospect of generating very wide spectral emissions with a combination of non-linear optical effects in photonic crystal fibres to produce supercontinuua in systems that are readily accessible to military applications. However, military remote sensing rarely requires bandwidths spanning two octaves and it is clear that efficient systems require controlled spectral emission in relevant bands. Furthermore, the limited spectral responsivity of focal plane arrays may impose further restriction on the usable spectrum. A recent innovation which temporally encodes a spectrum using group velocity dispersion allows detection with a photodiode, opening the prospect for high speed hyperspectral sensing and imaging. At the opposite end of the power spectrum, ultra-low power remote sensing using time-correlated single photon counting (SPC) has reduced the laser power requirement and demonstrated remote sensing over 5km during daylight with repetition rates of ~10MHz with ps pulses. Recent research has addressed uncorrelated SPC and waveform transmission to increase data rates for absolute rangefinding whilst avoiding range aliasing. This achievement opens the prospect of combining SPC with high repetition rate temporal encoding of supercontinuua to realise practical hyperspectral remote sensing lidar. The talk will present an overview of these technologies and present a concept which combines them into a single system for high-speed hyperspectral imaging and remote sensing.

Can we infer plant facilitation from remote sensing? A test across global drylands

PubMed Central

Xu, Chi; Holmgren, Milena; Van Nes, Egbert H.; Maestre, Fernando T.; Soliveres, Santiago; Berdugo, Miguel; Kéfi, Sonia; Marquet, Pablo A.; Abades, Sebastian; Scheffer, Marten

2016-01-01

Facilitation is a major force shaping the structure and diversity of plant communities in terrestrial ecosystems. Detecting positive plant-plant interactions relies on the combination of field experimentation and the demonstration of spatial association between neighboring plants. This has often restricted the study of facilitation to particular sites, limiting the development of systematic assessments of facilitation over regional and global scales. Here we explore whether the frequency of plant spatial associations detected from high-resolution remotely-sensed images can be used to infer plant facilitation at the community level in drylands around the globe. We correlated the information from remotely-sensed images freely available through Google Earth™ with detailed field assessments, and used a simple individual-based model to generate patch-size distributions using different assumptions about the type and strength of plant-plant interactions. Most of the patterns found from the remotely-sensed images were more right-skewed than the patterns from the null model simulating a random distribution. This suggests that the plants in the studied drylands show stronger spatial clustering than expected by chance. We found that positive plant co-occurrence, as measured in the field, was significantly related to the skewness of vegetation patch-size distribution measured using Google Earth™ images. Our findings suggest that the relative frequency of facilitation may be inferred from spatial pattern signals measured from remotely-sensed images, since facilitation often determines positive co-occurrence among neighboring plants. They pave the road for a systematic global assessment of the role of facilitation in terrestrial ecosystems. PMID:26552256

LIFES: Laser Induced Fluorescence and Environmental Sensing. [remote sensing technique for marine environment

NASA Technical Reports Server (NTRS)

Houston, W. R.; Stephenson, D. G.; Measures, R. M.

1975-01-01

A laboratory investigation has been conducted to evaluate the detection and identification capabilities of laser induced fluorescence as a remote sensing technique for the marine environment. The relative merits of fluorescence parameters including emission and excitation profiles, intensity and lifetime measurements are discussed in relation to the identification of specific targets of the marine environment including crude oils, refined petroleum products, fish oils and algae. Temporal profiles displaying the variation of lifetime with emission wavelength have proven to add a new dimension of specificity and simplicity to the technique.

Utilization of combined remote sensing techniques to detect environmental variables influencing malaria vector densities in rural West Africa

PubMed Central

2012-01-01

Introduction The use of remote sensing has found its way into the field of epidemiology within the last decades. With the increased sensor resolution of recent and future satellites new possibilities emerge for high resolution risk modeling and risk mapping. Methods A SPOT 5 satellite image, taken during the rainy season 2009 was used for calculating indices by combining the image's spectral bands. Besides the widely used Normalized Difference Vegetation Index (NDVI) other indices were tested for significant correlation against field observations. Multiple steps, including the detection of surface water, its breeding appropriateness for Anopheles and modeling of vector imagines abundance, were performed. Data collection on larvae, adult vectors and geographic parameters in the field, was amended by using remote sensing techniques to gather data on altitude (Digital Elevation Model = DEM), precipitation (Tropical Rainfall Measurement Mission = TRMM), land surface temperatures (LST). Results The DEM derived altitude as well as indices calculations combining the satellite's spectral bands (NDTI = Normalized Difference Turbidity Index, NDWI Mac Feeters = Normalized Difference Water Index) turned out to be reliable indicators for surface water in the local geographic setting. While Anopheles larvae abundance in habitats is driven by multiple, interconnected factors - amongst which the NDVI - and precipitation events, the presence of vector imagines was found to be correlated negatively to remotely sensed LST and positively to the cumulated amount of rainfall in the preceding 15 days and to the Normalized Difference Pond Index (NDPI) within the 500 m buffer zone around capture points. Conclusions Remotely sensed geographical and meteorological factors, including precipitations, temperature, as well as vegetation, humidity and land cover indicators could be used as explanatory variables for surface water presence, larval development and imagines densities. This modeling approach based on remotely sensed information is potentially useful for counter measures that are putting on at the environmental side, namely vector larvae control via larviciding and water body reforming. PMID:22443452

Utilization of combined remote sensing techniques to detect environmental variables influencing malaria vector densities in rural West Africa.

PubMed

Dambach, Peter; Machault, Vanessa; Lacaux, Jean-Pierre; Vignolles, Cécile; Sié, Ali; Sauerborn, Rainer

2012-03-23

The use of remote sensing has found its way into the field of epidemiology within the last decades. With the increased sensor resolution of recent and future satellites new possibilities emerge for high resolution risk modeling and risk mapping. A SPOT 5 satellite image, taken during the rainy season 2009 was used for calculating indices by combining the image's spectral bands. Besides the widely used Normalized Difference Vegetation Index (NDVI) other indices were tested for significant correlation against field observations. Multiple steps, including the detection of surface water, its breeding appropriateness for Anopheles and modeling of vector imagines abundance, were performed. Data collection on larvae, adult vectors and geographic parameters in the field, was amended by using remote sensing techniques to gather data on altitude (Digital Elevation Model = DEM), precipitation (Tropical Rainfall Measurement Mission = TRMM), land surface temperatures (LST). The DEM derived altitude as well as indices calculations combining the satellite's spectral bands (NDTI = Normalized Difference Turbidity Index, NDWI Mac Feeters = Normalized Difference Water Index) turned out to be reliable indicators for surface water in the local geographic setting. While Anopheles larvae abundance in habitats is driven by multiple, interconnected factors - amongst which the NDVI - and precipitation events, the presence of vector imagines was found to be correlated negatively to remotely sensed LST and positively to the cumulated amount of rainfall in the preceding 15 days and to the Normalized Difference Pond Index (NDPI) within the 500 m buffer zone around capture points. Remotely sensed geographical and meteorological factors, including precipitations, temperature, as well as vegetation, humidity and land cover indicators could be used as explanatory variables for surface water presence, larval development and imagines densities. This modeling approach based on remotely sensed information is potentially useful for counter measures that are putting on at the environmental side, namely vector larvae control via larviciding and water body reforming. © 2012 Dambach et al; licensee BioMed Central Ltd.

Environmental mapping and monitoring of Iceland by remote sensing (EMMIRS)

NASA Astrophysics Data System (ADS)

Pedersen, Gro B. M.; Vilmundardóttir, Olga K.; Falco, Nicola; Sigurmundsson, Friðþór S.; Rustowicz, Rose; Belart, Joaquin M.-C.; Gísladóttir, Gudrun; Benediktsson, Jón A.

2016-04-01

Iceland is exposed to rapid and dynamic landscape changes caused by natural processes and man-made activities, which impact and challenge the country. Fast and reliable mapping and monitoring techniques are needed on a big spatial scale. However, currently there is lack of operational advanced information processing techniques, which are needed for end-users to incorporate remote sensing (RS) data from multiple data sources. Hence, the full potential of the recent RS data explosion is not being fully exploited. The project Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS) bridges the gap between advanced information processing capabilities and end-user mapping of the Icelandic environment. This is done by a multidisciplinary assessment of two selected remote sensing super sites, Hekla and Öræfajökull, which encompass many of the rapid natural and man-made landscape changes that Iceland is exposed to. An open-access benchmark repository of the two remote sensing supersites is under construction, providing high-resolution LIDAR topography and hyperspectral data for land-cover and landform classification. Furthermore, a multi-temporal and multi-source archive stretching back to 1945 allows a decadal evaluation of landscape and ecological changes for the two remote sensing super sites by the development of automated change detection techniques. The development of innovative pattern recognition and machine learning-based approaches to image classification and change detection is one of the main tasks of the EMMIRS project, aiming to extract and compute earth observation variables as automatically as possible. Ground reference data collected through a field campaign will be used to validate the implemented methods, which outputs are then inferred with geological and vegetation models. Here, preliminary results of an automatic land-cover classification based on hyperspectral image analysis are reported. Furthermore, the EMMIRS project investigates the complex landscape dynamics between geological and ecological processes. This is done through cross-correlation of mapping results and implementation of modelling techniques that simulate geological and ecological processes in order to extrapolate the landscape evolution

Results from the National Aeronautics and Space Administration remote sensing experiments in the New York Bight, 7-17 April 1975

NASA Technical Reports Server (NTRS)

Hall, J. B., Jr. (Compiler); Pearson, A. O. (Compiler)

1977-01-01

A cooperative operation was conducted in the New York Bight to evaluate the role of remote sensing technology to monitor ocean dumping. Six NASA remote sensing experiments were flown on the C-54, U-2, and C-130 NASA aircraft, while NOAA obtained concurrent sea truth information using helicopters and surface platforms. The experiments included: (1) a Radiometer/Scatterometer (RADSCAT), (2) an Ocean Color Scanner (OCS), (3) a Multichannel Ocean Color Sensor (MOCS), (4) four Hasselblad cameras, (5) an Ebert spectrometer; and (6) a Reconafax IV infrared scanner and a Precision Radiation Thermometer (PRT-5). The results of these experiments relative to the use of remote sensors to detect, quantify, and determine the dispersion of pollutants dumped into the New York Bight are presented.

Remote distinction of a noxious weed (musk thistle: Carduus nutans) using airborne hyperspectral imagery and the support vector machine classifier

USDA-ARS?s Scientific Manuscript database

Remote detection of invasive plant species using geospatial imagery may significantly improve monitoring, planning, and management practices by eliminating shortfalls such as observer bias and accessibility involved in ground-based surveys. The use of remote sensing for accurate mapping invasion ex...

Specific sensors for special roles in oil spill remote sensing

NASA Astrophysics Data System (ADS)

Brown, Carl E.; Fingas, Mervin F.

1997-01-01

Remote sensing is becoming an increasingly important tool for the effective direction of oil spill countermeasures. Cleanup personnel have recognized that remote sensing can increase spill cleanup efficiency. The general public expects that the government and/or the spiller know the location and the extent of the contamination. The Emergencies Science Division (ESD) of Environment Canada, is responsible for remote sensing during oil spill emergencies along Canada's three coastlines, extensive inland waterways, as well as over the entire land mass. In addition to providing operational remote sensing, ESD conducts research into the development of airborne oil spill remote sensors, including the Scanning Laser Environmental Airborne Fluorosensor (SLEAF) and the Laser Ultrasonic Remote SEnsing of Oil Thickness (LURSOT) sensor. It has long been recognized that there is not one sensor or 'magic bullet' which is capable of detecting oil and related petroleum products in all environments and spill scenarios. There are sensors which possess a wide filed-of-view and can therefore be used to map the overall extent of the spill. These sensors, however lack the specificity required to positively identify oil and related products. This is even more of a problem along complicated beach and shoreline environments where several substrates are present. The specific laser- based sensors under development by Environment Canada are designed to respond to special roles in oil spill response. In particular, the SLEAF is being developed to unambiguously detect and map oil and related petroleum products in complicated marine and shoreline environments where other non-specific sensors experience difficulty. The role of the SLEAF would be to confirm or reject suspected oil contamination sites that have been targeted by the non- specific sensors. This confirmation will release response crews from the time consuming task of physically inspecting each site, and direct crews to sites that require remediation. The LURSOT sensor will provide an absolute measurement of oil thickness form an airborne platform. There are presently no sensors available, either airborne or in the laboratory which can provide an absolute measurement of oil thickness. This information is necessary for the effective direction of spill countermeasures such as dispersant application and in-situ burning. This paper will describe the development of laser-based airborne oil spill remote sensing instrumentation at Environment Canada and identify the anticipated benefits of the use of this technology to the oil spill response community.

Analysis of Unmanned Aerial Vehicle (UAV) hyperspectral remote sensing monitoring key technology in coastal wetland

NASA Astrophysics Data System (ADS)

Ma, Yi; Zhang, Jie; Zhang, Jingyu

2016-01-01

The coastal wetland, a transitional zone between terrestrial ecosystems and marine ecosystems, is the type of great value to ecosystem services. For the recent 3 decades, area of the coastal wetland is decreasing and the ecological function is gradually degraded with the rapid development of economy, which restricts the sustainable development of economy and society in the coastal areas of China in turn. It is a major demand of the national reality to carry out the monitoring of coastal wetlands, to master the distribution and dynamic change. UAV, namely unmanned aerial vehicle, is a new platform for remote sensing. Compared with the traditional satellite and manned aerial remote sensing, it has the advantage of flexible implementation, no cloud cover, strong initiative and low cost. Image-spectrum merging is one character of high spectral remote sensing. At the same time of imaging, the spectral curve of each pixel is obtained, which is suitable for quantitative remote sensing, fine classification and target detection. Aimed at the frontier and hotspot of remote sensing monitoring technology, and faced the demand of the coastal wetland monitoring, this paper used UAV and the new remote sensor of high spectral imaging instrument to carry out the analysis of the key technologies of monitoring coastal wetlands by UAV on the basis of the current situation in overseas and domestic and the analysis of developing trend. According to the characteristic of airborne hyperspectral data on UAV, that is "three high and one many", the key technology research that should develop are promoted as follows: 1) the atmosphere correction of the UAV hyperspectral in coastal wetlands under the circumstance of complex underlying surface and variable geometry, 2) the best observation scale and scale transformation method of the UAV platform while monitoring the coastal wetland features, 3) the classification and detection method of typical features with high precision from multi scale hyperspectral images based on time sequence. The research results of this paper will help to break the traditional concept of remote sensing monitoring coastal wetlands by satellite and manned aerial vehicle, lead the trend of this monitoring technology, and put forward a new technical proposal for grasping the distribution of the coastal wetland and the changing trend and carrying out the protection and management of the coastal wetland.

Ship detection in optical remote sensing images based on deep convolutional neural networks

NASA Astrophysics Data System (ADS)

Yao, Yuan; Jiang, Zhiguo; Zhang, Haopeng; Zhao, Danpei; Cai, Bowen

2017-10-01

Automatic ship detection in optical remote sensing images has attracted wide attention for its broad applications. Major challenges for this task include the interference of cloud, wave, wake, and the high computational expenses. We propose a fast and robust ship detection algorithm to solve these issues. The framework for ship detection is designed based on deep convolutional neural networks (CNNs), which provide the accurate locations of ship targets in an efficient way. First, the deep CNN is designed to extract features. Then, a region proposal network (RPN) is applied to discriminate ship targets and regress the detection bounding boxes, in which the anchors are designed by intrinsic shape of ship targets. Experimental results on numerous panchromatic images demonstrate that, in comparison with other state-of-the-art ship detection methods, our method is more efficient and achieves higher detection accuracy and more precise bounding boxes in different complex backgrounds.

Estimation of the distribution of Tabebuia guayacan (Bignoniaceae) using high-resolution remote sensing imagery.

PubMed

Sánchez-Azofeifa, Arturo; Rivard, Benoit; Wright, Joseph; Feng, Ji-Lu; Li, Peijun; Chong, Mei Mei; Bohlman, Stephanie A

2011-01-01

Species identification and characterization in tropical environments is an emerging field in tropical remote sensing. Significant efforts are currently aimed at the detection of tree species, of levels of forest successional stages, and the extent of liana occurrence at the top of canopies. In this paper we describe our use of high resolution imagery from the Quickbird Satellite to estimate the flowering population of Tabebuia guayacan trees at Barro Colorado Island (BCI), in Panama. The imagery was acquired on 29 April 2002 and 21 March 2004. Spectral Angle Mapping via a One-Class Support Vector machine was used to detect the presence of 422 and 557 flowering tress in the April 2002 and March 2004 imagery. Of these, 273 flowering trees are common to both dates. This study presents a new perspective on the effectiveness of high resolution remote sensing for monitoring a phenological response and its use as a tool for potential conservation and management of natural resources in tropical environments.

Estimation of the Distribution of Tabebuia guayacan (Bignoniaceae) Using High-Resolution Remote Sensing Imagery

PubMed Central

Sánchez-Azofeifa, Arturo; Rivard, Benoit; Wright, Joseph; Feng, Ji-Lu; Li, Peijun; Chong, Mei Mei; Bohlman, Stephanie A.

2011-01-01

Species identification and characterization in tropical environments is an emerging field in tropical remote sensing. Significant efforts are currently aimed at the detection of tree species, of levels of forest successional stages, and the extent of liana occurrence at the top of canopies. In this paper we describe our use of high resolution imagery from the Quickbird Satellite to estimate the flowering population of Tabebuia guayacan trees at Barro Colorado Island (BCI), in Panama. The imagery was acquired on 29 April 2002 and 21 March 2004. Spectral Angle Mapping via a One-Class Support Vector machine was used to detect the presence of 422 and 557 flowering tress in the April 2002 and March 2004 imagery. Of these, 273 flowering trees are common to both dates. This study presents a new perspective on the effectiveness of high resolution remote sensing for monitoring a phenological response and its use as a tool for potential conservation and management of natural resources in tropical environments. PMID:22163825

Forest Disturbance Analysis with LANDSAT-8 Oli Data Related to a Parametric Wind Field: a Case Study for Typhoon Rammasun (201409)

NASA Astrophysics Data System (ADS)

Tan, C.; Fang, W.

2018-04-01

Forest disturbance induced by tropical cyclone often has significant and profound effects on the structure and function of forest ecosystem. Detection and analysis of post-disaster forest disturbance based on remote sensing technology has been widely applied. At present, it is necessary to conduct further quantitative analysis of the magnitude of forest disturbance with the intensity of typhoon. In this study, taking the case of super typhoon Rammasun (201409), we analysed the sensitivity of four common used remote sensing indices and explored the relationship between remote sensing index and corresponding wind speeds based on pre-and post- Landsat-8 OLI (Operational Land Imager) images and a parameterized wind field model. The results proved that NBR is the most sensitive index for the detection of forest disturbance induced by Typhoon Rammasun and the variation of NBR has a significant linear dependence relation with the simulated 3-second gust wind speed.

Determination of Winter Wheat Phenology in Bavaria- A Contribution to Regional Crop Health Monitoring from Space

NASA Astrophysics Data System (ADS)

Bruggemann, Lena; Bach, Heike; Ruf, Tobias; Appel, Florian; Migdall, Silke; Hank, Tobias; Mauser, Wolfram; Eiblmeier, Peter

2016-08-01

The central topic of this study is the monitoring of winter wheat phenology and the detection of anthesis (flowering) using remotely sensed data as well as crop growth modeling. It is not possible to directly observe the flowering of wheat with optical satellite sensors. Thus, an approach that combines crop growth modeling with remote sensing data covering optical and microwave spectral ranges was developed. This was done in three steps: The hydro-agroecological land surface model PROMET was first run in a stand-alone version for selected sites distributed throughout Bavaria using only static input parameters (e.g. soil map) and current meteorological data as driving factors. Thus, multitemporal information from optical remote sensing data was assimilated into the model runs in a second step to improve the accuracy of the results. Finally, the use of radar data for anthesis detection in winter wheat was tested using Sentinel-1 data of 2015 in dual polarization mode (VV+VH).

Forest Attributes from Radar Interferometric Structure and its Fusion with Optical Remote Sensing

NASA Technical Reports Server (NTRS)

Treuhaft, Robert N.; Law, Beverly E.; Asner, Gregory P.

2004-01-01

The possibility of global, three-dimensional remote sensing of forest structure with interferometric synthetic aperture radar (InSAR) bears on important forest ecological processes, particularly the carbon cycle. InSAR supplements two-dimensional remote sensing with information in the vertical dimension. Its strengths in potential for global coverage complement those of lidar (light detecting and ranging), which has the potential for high-accuracy vertical profiles over small areas. InSAR derives its sensitivity to forest vertical structure from the differences in signals received by two, spatially separate radar receivers. Estimation of parameters describing vertical structure requires multiple-polarization, multiple-frequency, or multiple-baseline InSAR. Combining InSAR with complementary remote sensing techniques, such as hyperspectral optical imaging and lidar, can enhance vertical-structure estimates and consequent biophysical quantities of importance to ecologists, such as biomass. Future InSAR experiments will supplement recent airborne and spaceborne demonstrations, and together with inputs from ecologists regarding structure, they will suggest designs for future spaceborne strategies for measuring global vegetation structure.

Demonstration of versatile whispering-gallery micro-lasers for remote refractive index sensing.

PubMed

Wan, Lei; Chandrahalim, Hengky; Zhou, Jian; Li, Zhaohui; Chen, Cong; Cho, Sangha; Zhang, Hui; Mei, Ting; Tian, Huiping; Oki, Yuji; Nishimura, Naoya; Fan, Xudong; Guo, L Jay

2018-03-05

We developed chip-scale remote refractive index sensors based on Rhodamine 6G (R6G)-doped polymer micro-ring lasers. The chemical, temperature, and mechanical sturdiness of the fused-silica host guaranteed a flexible deployment of dye-doped polymers for refractive index sensing. The introduction of the dye as gain medium demonstrated the feasibility of remote sensing based on the free-space optics measurement setup. Compared to the R6G-doped TZ-001, the lasing behavior of R6G-doped SU-8 polymer micro-ring laser under an aqueous environment had a narrower spectrum linewidth, producing the minimum detectable refractive index change of 4 × 10 -4 RIU. The maximum bulk refractive index sensitivity (BRIS) of 75 nm/RIU was obtained for SU-8 laser-based refractive index sensors. The economical, rapid, and simple realization of polymeric micro-scale whispering-gallery-mode (WGM) laser-based refractive index sensors will further expand pathways of static and dynamic remote environmental, chemical, biological, and bio-chemical sensing.

Unmanned Aerial Systems and Spectroscopy for Remote Sensing Applications in Archaeology

NASA Astrophysics Data System (ADS)

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.

Implication of relationship between natural impacts and land use/land cover (LULC) changes of urban area in Mongolia

NASA Astrophysics Data System (ADS)

Gantumur, Byambakhuu; Wu, Falin; Zhao, Yan; Vandansambuu, Battsengel; Dalaibaatar, Enkhjargal; Itiritiphan, Fareda; Shaimurat, Dauryenbyek

2017-10-01

Urban growth can profoundly alter the urban landscape structure, ecosystem processes, and local climates. Timely and accurate information on the status and trends of urban ecosystems is critical to develop strategies for sustainable development and to improve the urban residential environment and living quality. Ulaanbaatar city was urbanized very rapidly caused by herders and farmers, many of them migrating from rural places, have played a big role in this urban expansion (sprawl). Today, 1.3 million residents for about 40% of total population are living in the Ulaanbaatar region. Those human activities influenced stronger to green environments. Therefore, the aim of this study is determined to change detection of land use/land cover (LULC) and estimating their areas for the trend of future by remote sensing and statistical methods. The implications of analysis were provided by change detection methods of LULC, remote sensing spectral indices including normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and normalized difference built-up index (NDBI). In addition, it can relate to urban heat island (UHI) provided by Land surface temperature (LST) with local climate issues. Statistical methods for image processing used to define relations between those spectral indices and change detection images and regression analysis for time series trend in future. Remote sensing data are used by Landsat (TM/ETM+/OLI) satellite images over the period between 1990 and 2016 by 5 years. The advantages of this study are very useful remote sensing approaches with statistical analysis and important to detecting changes of LULC. The experimental results show that the LULC changes can image on the present and after few years and determined relations between impacts of environmental conditions.

Sensing our Environment: Remote sensing in a physics classroom

NASA Astrophysics Data System (ADS)

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. The teams then processed their data and presented it to their foreign partners for evaluation in a video conference call. Alongside exciting insights about their respective environments and living conditions, the young scientists had daily access to live satellite sensors and remote sensing through the DLR_School_Lab in Germany and the Earth and Planetary Image Facility in Israel. This paper provides an overview regarding the project, the techniques used and the evaluation results following a pre-past-questionnaire design, and above all demonstrates the use of remote sensing as an application for physics teaching in a significant learning environment.

Plant trait detection with multi-scale spectrometry

NASA Astrophysics Data System (ADS)

Gamon, J. A.; Wang, R.

2017-12-01

Proximal and remote sensing using imaging spectrometry offers new opportunities for detecting plant traits, with benefits for phenotyping, productivity estimation, stress detection, and biodiversity studies. Using proximal and airborne spectrometry, we evaluated variation in plant optical properties at various spatial and spectral scales with the goal of identifying optimal scales for distinguishing plant traits related to photosynthetic function. Using directed approaches based on physiological vegetation indices, and statistical approaches based on spectral information content, we explored alternate ways of distinguishing plant traits with imaging spectrometry. With both leaf traits and canopy structure contributing to the signals, results exhibit a strong scale dependence. Our results demonstrate the benefits of multi-scale experimental approaches within a clear conceptual framework when applying remote sensing methods to plant trait detection for phenotyping, productivity, and biodiversity studies.

Quantitative Infrared Spectroscopy in Challenging Environments: Applications to Passive Remote Sensing and Process Monitoring

DTIC Science & Technology

2012-12-01

IR remote sensing o ers a measurement method to detect gaseous species in the outdoor environment. Two major obstacles limit the application of this... method in quantitative analysis : (1) the e ect of both temperature and concentration on the measured spectral intensities and (2) the di culty and...crucial. In this research, particle swarm optimization, a population- based optimization method was applied. Digital ltering and wavelet processing methods

Difet: Distributed Feature Extraction Tool for High Spatial Resolution Remote Sensing Images

NASA Astrophysics Data System (ADS)

Eken, S.; Aydın, E.; Sayar, A.

2017-11-01

In this paper, we propose distributed feature extraction tool from high spatial resolution remote sensing images. Tool is based on Apache Hadoop framework and Hadoop Image Processing Interface. Two corner detection (Harris and Shi-Tomasi) algorithms and five feature descriptors (SIFT, SURF, FAST, BRIEF, and ORB) are considered. Robustness of the tool in the task of feature extraction from LandSat-8 imageries are evaluated in terms of horizontal scalability.

Space-Based Remote Sensing of Atmospheric Aerosols: The Multi-Angle Spectro-Polarimetric Frontier

NASA Technical Reports Server (NTRS)

Kokhanovsky, A. A.; Davis, A. B.; Cairns, B.; Dubovik, O.; Hasekamp, O. P.; Sano, I.; Mukai, S.; Rozanov, V. V.; Litvinov, P.; Lapyonok, T.;

Remote sensing applications to resource problems in South Dakota

NASA Technical Reports Server (NTRS)

Myers, V. I. (Principal Investigator)

1981-01-01

The procedures used as well as the results obtained and conclusions derived are described for the following applications of remote sensing in South Dakota: (1) sage grouse management; (2) censusing Canada geese; (3) monitoring grasshopper infestation in rangeland; (4) detecting Dutch elm disease in an urban environment; (5) determining water usage from the Belle Fourche River; (6) resource management of the Lower James River; and (7) the National Model Implantation Program: Lake Herman watershed.

Eighth year projects and activities of the Environmental Remote Sensing Applications Laboratory (ERSAL). [Oregon

NASA Technical Reports Server (NTRS)

Lewis, A. J.; Isaacson, D. L.; Schrumpf, B. J. (Principal Investigator)

1980-01-01

Projects completed for the NASA Office of University Affairs include the application of remote sensing data in support of rehabilitation of wild fire damaged areas and the use of LANDSAT 3 return beam vidicon in forestry mapping applications. Continuing projects for that office include monitoring western Oregon timber clearcut; detecting and monitoring wheat disease; land use monitoring for tax assessment in Umatilla, Lake, and Morrow Counties; and the use of Oregon Air National Guard thermal infrared scanning data. Projects funded through other agencies include the remote sensing inventory of elk in the Blue Mountains; the estimation of burned agricultural acreage in the Willamette Valley; a resource inventory of Deschutes County; and hosting a LANDSAT digital workshop.

Using Remotely Sensed Data to Map Urban Vulnerability to Heat

NASA Technical Reports Server (NTRS)

Stefanov, William L.

2010-01-01

This slide presentation defines remote sensing, and presents examples of remote sensing and astronaut photography, which has been a part of many space missions. The presentation then reviews the project aimed at analyzing urban vulnerability to climate change, which is to test the hypotheses that Exposure to excessively warm weather threatens human health in all types of climate regimes; Heat kills and sickens multitudes of people around the globe every year -- directly and indirectly, and Climate change, coupled with urban development, will impact human health. Using Multiple Endmember Spectral Mixing Analysis (MESMA), and the Phoenix urban area as the example, the Normalized Difference Vegetation Index (NDVI) is calculated, a change detection analysis is shown, and surface temperature is shown.

EROS: A space program for Earth resources

USGS Publications Warehouse

Metz, G.G.; Wiepking, P.J.

1980-01-01

Within the technology of the space age lies a key to increased knowledge about the resources and environment of the Earth. This key is remote sensing detecting the nature of an object without actually touching it. Although the photographic camera is the most familiar remote-sensing device, other instrument systems, such as scanning radiometers and radar, also can produce photographs and images. On the basis of the potential of this technology, and in response to the critical need for greater knowledge of the Earth and its resources, the Department of the Interior established the Earth Resources Observation Systems (EROS) Program to gather and use remotely sensed data collected by satellite and aircraft of natural and manmade features on the Earth's surface.

Urban Spatial Pattern and Interaction based on Analysis of Nighttime Remote Sensing Data and Geo-social Media Information

NASA Astrophysics Data System (ADS)

Ratnasari, Nila; Dwi Candra, Erika; Herdianta Saputra, Defa; Putra Perdana, Aji

2016-11-01

Urban development in Indonesia significantly incerasing in line with rapid development of infrastructure, utility, and transportation network. Recently, people live depend on lights at night and social media and these two aspects can depicted urban spatial pattern and interaction. This research used nighttime remote sensing data with the VIIRS (Visible Infrared Imaging Radiometer Suite) day-night band detects lights, gas flares, auroras, and wildfires. Geo-social media information derived from twitter data gave big picture on spatial interaction from the geospatial footprint. Combined both data produced comprehensive urban spatial pattern and interaction in general for Indonesian territory. The result is shown as a preliminary study of integrating nighttime remote sensing data and geospatial footprint from twitter data.

Hi-Tech for Archeology

NASA Technical Reports Server (NTRS)

1987-01-01

Remote sensing is the process of acquiring physical information from a distance, obtaining data on Earth features from a satellite or an airplane. Advanced remote sensing instruments detect radiations not visible to the ordinary camera or the human eye in several bands of the spectrum. These data are computer processed to produce multispectral images that can provide enormous amounts of information about Earth objects or phenomena. Since every object on Earth emits or reflects radiation in its own unique signature, remote sensing data can be interpreted to tell the difference between one type of vegetation and another, between densely populated urban areas and lightly populated farmland, between clear and polluted water or in the archeological application between rain forest and hidden man made structures.

Adult mortality in a low-density tree population using high-resolution remote sensing.

PubMed

Kellner, James R; Hubbell, Stephen P

2017-06-01

We developed a statistical framework to quantify mortality rates in canopy trees observed using time series from high-resolution remote sensing. By timing the acquisition of remote sensing data with synchronous annual flowering in the canopy tree species Handroanthus guayacan, we made 2,596 unique detections of 1,006 individual adult trees within 18,883 observation attempts on Barro Colorado Island, Panama (BCI) during an 11-yr period. There were 1,057 observation attempts that resulted in missing data due to cloud cover or incomplete spatial coverage. Using the fraction of 123 individuals from an independent field sample that were detected by satellite data (109 individuals, 88.6%), we estimate that the adult population for this species on BCI was 1,135 individuals. We used a Bayesian state-space model that explicitly accounted for the probability of tree detection and missing observations to compute an annual adult mortality rate of 0.2%·yr -1 (SE = 0.1, 95% CI = 0.06-0.45). An independent estimate of the adult mortality rate from 260 field-checked trees closely matched the landscape-scale estimate (0.33%·yr -1 , SE = 0.16, 95% CI = 0.12-0.74). Our proof-of-concept study shows that one can remotely estimate adult mortality rates for canopy tree species precisely in the presence of variable detection and missing observations. © 2017 by the Ecological Society of America.

Concept, Simulation, and Instrumentation for Radiometric Inflight Icing Detection

NASA Technical Reports Server (NTRS)

Ryerson, Charles; Koenig, George G.; Reehorst, Andrew L.; Scott, Forrest R.

2009-01-01

The multi-agency Flight in Icing Remote Sensing Team (FIRST), a consortium of the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), the National Center for Atmospheric Research (NCAR), the National Oceanographic and Atmospheric Administration (NOAA), and the Army Corps of Engineers (USACE), has developed technologies for remotely detecting hazardous inflight icing conditions. The USACE Cold Regions Research and Engineering Laboratory (CRREL) assessed the potential of onboard passive microwave radiometers for remotely detecting icing conditions ahead of aircraft. The dual wavelength system differences the brightness temperature of Space and clouds, with greater differences potentially indicating closer and higher magnitude cloud liquid water content (LWC). The Air Force RADiative TRANsfer model (RADTRAN) was enhanced to assess the flight track sensing concept, and a 'flying' RADTRAN was developed to simulate a radiometer system flying through simulated clouds. Neural network techniques were developed to invert brightness temperatures and obtain integrated cloud liquid water. In addition, a dual wavelength Direct-Detection Polarimeter Radiometer (DDPR) system was built for detecting hazardous drizzle drops. This paper reviews technology development to date and addresses initial polarimeter performance.

Laser-Based Remote Sensing of Explosives by a Differential Absorption and Scattering Method

NASA Astrophysics Data System (ADS)

Ayrapetyan, V. S.

2018-01-01

A multifunctional IR parametric laser system is developed and tested for remote detection and identification of atmospheric gases, including explosive and chemically aggressive substances. Calculations and experimental studies of remote determination of the spectroscopic parameters of the best known explosive substances TNT, RDX, and PETN are carried out. The feasibility of high sensitivity detection ( 1 ppm) of these substances with the aid of a multifunctional IR parametric light source by differential absorption and scattering is demonstrated.

Possibilities for the detection of microbial life on extrasolar planets.

PubMed

Knacke, Roger F

2003-01-01

We consider possibilities for the remote detection of microbial life on extrasolar planets. The Darwin/Terrestrial Planet Finder (TPF) telescope concepts for observations of terrestrial planets focus on indirect searches for life through the detection of atmospheric gases related to life processes. Direct detection of extraterrestrial life may also be possible through well-designed searches for microbial life forms. Satellites in Earth orbit routinely monitor colonies of terrestrial algae in oceans and lakes by analysis of reflected ocean light in the visible region of the spectrum. These remote sensing techniques suggest strategies for extrasolar searches for signatures of chlorophylls and related photosynthetic compounds associated with life. However, identification of such life-related compounds on extrasolar planets would require observations through strong, interfering absorptions and scattering radiances from the remote atmospheres and landmasses. Techniques for removal of interfering radiances have been extensively developed for remote sensing from Earth orbit. Comparable techniques would have to be developed for extrasolar planet observations also, but doing so would be challenging for a remote planet. Darwin/TPF coronagraph concepts operating in the visible seem to be best suited for searches for extrasolar microbial life forms with instruments that can be projected for the 2010-2020 decades, although resolution and signal-to-noise ratio constraints severely limit detection possibilities on terrestrial-type planets. The generation of telescopes with large apertures and extremely high spatial resolutions that will follow Darwin/TPF could offer striking possibilities for the direct detection of extrasolar microbial life.

Measuring short-term post-fire forest recovery across a burn severity gradient in a mixed pine-oak forest using multi-sensor remote sensing techniques

DOE PAGES

Meng, Ran; Wu, Jin; Zhao, Feng; ...

2018-06-01

Understanding post-fire forest recovery is pivotal to the study of forest dynamics and global carbon cycle. Field-based studies indicated a convex response of forest recovery rate to burn severity at the individual tree level, related with fire-induced tree mortality; however, these findings were constrained in spatial/temporal extents, while not detectable by traditional optical remote sensing studies, largely attributing to the contaminated effect from understory recovery. For this work, we examined whether the combined use of multi-sensor remote sensing techniques (i.e., 1m simultaneous airborne imaging spectroscopy and LiDAR and 2m satellite multi-spectral imagery) to separate canopy recovery from understory recovery wouldmore » enable to quantify post-fire forest recovery rate spanning a large gradient in burn severity over large-scales. Our study was conducted in a mixed pine-oak forest in Long Island, NY, three years after a top-killing fire. Our studies remotely detected an initial increase and then decline of forest recovery rate to burn severity across the burned area, with a maximum canopy area-based recovery rate of 10% per year at moderate forest burn severity class. More intriguingly, such remotely detected convex relationships also held at species level, with pine trees being more resilient to high burn severity and having a higher maximum recovery rate (12% per year) than oak trees (4% per year). These results are one of the first quantitative evidences showing the effects of fire adaptive strategies on post-fire forest recovery, derived from relatively large spatial-temporal domains. Our study thus provides the methodological advance to link multi-sensor remote sensing techniques to monitor forest dynamics in a spatially explicit manner over large-scales, with important implications for fire-related forest management, and for constraining/benchmarking fire effect schemes in ecological process models.« less

Measuring short-term post-fire forest recovery across a burn severity gradient in a mixed pine-oak forest using multi-sensor remote sensing techniques

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

Meng, Ran; Wu, Jin; Zhao, Feng

Understanding post-fire forest recovery is pivotal to the study of forest dynamics and global carbon cycle. Field-based studies indicated a convex response of forest recovery rate to burn severity at the individual tree level, related with fire-induced tree mortality; however, these findings were constrained in spatial/temporal extents, while not detectable by traditional optical remote sensing studies, largely attributing to the contaminated effect from understory recovery. For this work, we examined whether the combined use of multi-sensor remote sensing techniques (i.e., 1m simultaneous airborne imaging spectroscopy and LiDAR and 2m satellite multi-spectral imagery) to separate canopy recovery from understory recovery wouldmore » enable to quantify post-fire forest recovery rate spanning a large gradient in burn severity over large-scales. Our study was conducted in a mixed pine-oak forest in Long Island, NY, three years after a top-killing fire. Our studies remotely detected an initial increase and then decline of forest recovery rate to burn severity across the burned area, with a maximum canopy area-based recovery rate of 10% per year at moderate forest burn severity class. More intriguingly, such remotely detected convex relationships also held at species level, with pine trees being more resilient to high burn severity and having a higher maximum recovery rate (12% per year) than oak trees (4% per year). These results are one of the first quantitative evidences showing the effects of fire adaptive strategies on post-fire forest recovery, derived from relatively large spatial-temporal domains. Our study thus provides the methodological advance to link multi-sensor remote sensing techniques to monitor forest dynamics in a spatially explicit manner over large-scales, with important implications for fire-related forest management, and for constraining/benchmarking fire effect schemes in ecological process models.« less

Remote Sensing of Water Quality in Multipurpose Reservoirs: Case Study Applications in Indonesia, Mexico, and Uruguay

NASA Astrophysics Data System (ADS)

Miralles-Wilhelm, F.; Serrat-Capdevila, A.; Rodriguez, D.

2017-12-01

This research is focused on development of remote sensing methods to assess surface water pollution issues, particularly in multipurpose reservoirs. Three case study applications are presented to comparatively analyze remote sensing techniquesforo detection of nutrient related pollution, i.e., Nitrogen, Phosphorus, Chlorophyll, as this is a major water quality issue that has been identified in terms of pollution of major water sources around the country. This assessment will contribute to a better understanding of options for nutrient remote sensing capabilities and needs and assist water agencies in identifying the appropriate remote sensing tools and devise an application strategy to provide information needed to support decision-making regarding the targeting and monitoring of nutrient pollution prevention and mitigation measures. A detailed review of the water quality data available from ground based measurements was conducted in order to determine their suitability for a case study application of remote sensing. In the first case study, the Valle de Bravo reservoir in Mexico City reservoir offers a larger database of water quality which may be used to better calibrate and validate the algorithms required to obtain water quality data from remote sensing raw data. In the second case study application, the relatively data scarce Lake Toba in Indonesia can be useful to illustrate the value added of remote sensing data in locations where water quality data is deficient or inexistent. The third case study in the Paso Severino reservoir in Uruguay offers a combination of data scarcity and persistent development of harmful algae blooms. Landsat-TM data was obteined for the 3 study sites and algorithms for three key water quality parameters that are related to nutrient pollution: Chlorophyll-a, Total Nitrogen, and Total Phosphorus were calibrated and validated at the study sites. The three case study applications were developed into capacity building/training workshops for water resources students, applied scientists, practitioners, reservoir and water quality managers, and other interested stakeholders.

Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

2018-04-01

In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

Fast Detection of Airports on Remote Sensing Images with Single Shot MultiBox Detector

NASA Astrophysics Data System (ADS)

Xia, Fei; Li, HuiZhou

2018-01-01

This paper introduces a method for fast airport detection on remote sensing images (RSIs) using Single Shot MultiBox Detector (SSD). To our knowledge, this could be the first study which introduces an end-to-end detection model into airport detection on RSIs. Based on the common low-level features between natural images and RSIs, a convolution neural network trained on large amounts of natural images was transferred to tackle the airport detection problem with limited annotated data. To deal with the specific characteristics of RSIs, some related parameters in the SSD, such as the scales and layers, were modified for more accurate and rapider detection. The experiments show that the proposed method could achieve 83.5% Average Recall at 8 FPS on RSIs with the size of 1024*1024. In contrast to Faster R-CNN, an improvement on AP and speed could be obtained.

Detection of potato beetle damage using remote sensing from small unmanned aircraft systems

NASA Astrophysics Data System (ADS)

Hunt, E. Raymond; Rondon, Silvia I.

2017-04-01

Colorado potato beetle (CPB) adults and larvae devour leaves of potato and other solanaceous crops and weeds, and may quickly develop resistance to pesticides. With early detection of CPB damage, more options are available for precision integrated pest management, which reduces the amount of pesticides applied in a field. Remote sensing with small unmanned aircraft systems (sUAS) has potential for CPB detection because low flight altitudes allow image acquisition at very high spatial resolution. A five-band multispectral sensor and up-looking incident light sensor were mounted on a six-rotor sUAS, which was flown at altitudes of 60 and 30 m in June 2014. Plants went from visibly undamaged to having some damage in just 1 day. Whole-plot normalized difference vegetation index (NDVI) and the number of pixels classified as damaged (0.70≤NDVI≤0.80) were not correlated with visible CPB damage ranked from least to most. Area of CPB damage estimated using object-based image analysis was highly correlated to the visual ranking of damage. Furthermore, plant height calculated using structure-from-motion point clouds was related to CPB damage, but this method required extensive operator intervention for success. Object-based image analysis has potential for early detection based on high spatial resolution sUAS remote sensing.

Chemical-biological defense remote sensing: what's happening

NASA Astrophysics Data System (ADS)

Carrico, John P.

1998-08-01

The proliferation of weapons of mass destruction (WMD) continues to be a serious threat to the security of the US. Proliferation of chemical and biological (CB) weapons is particularly disturbing, and the threats posed can be devastating. Critical elements of the US efforts to reduce and counter WMD proliferation include: (1) the location and characterization of WMD facilities and capabilities worldwide; (2) the ability to rapidly detect and identify the use of CB weapons for expeditious warning and reporting on the battlefield; and (3) the capability to mitigate deleterious consequences of a CB incident through effective protective and medical treatment measures. Remote sensing has been touted as a key technology in these efforts. Historically, the role of remote sensing in CB defense has been to provide early warning of an attack from an extended distance. However, additional roles for remote sensing in CB defense, as well as applications in related missions, are possible and should be pursued. This paper examines what has been happening in remote sensing over the past decade to address needs in this area. Accomplishments, emerging technologies, programmatic issues, and opportunities for the future are covered. The Department of Defence chemical- biological, the Department of Energy's Chemical Analysis by Laser Interrogation of Proliferation Effluents, and other agency related programs are examined. Also, the status of remote sensing in the commercial market arena for environmental monitoring, its relevance to the WMD counterproliferation program, and opportunities for technology transfer are discussed. A course of action for the future is recommended.

Development of Laser Based Remote Sensing System for Inner-Concrete Defects

NASA Astrophysics Data System (ADS)

Shimada, Yoshinori; Kotyaev, Oleg

Laser-based remote sensing using a vibration detection system has been developed using a photorefractive crystal to reduce the effect of concrete surface-roughness. An electric field was applied to the crystal and the reference beam was phase shifted to increase the detection efficiency (DE). The DE increased by factor of 8.5 times compared to that when no voltage and no phase shifting were applied. Vibration from concrete defects can be detected at a distance of 5 m from the system. A vibration-canceling system has also developed that appears to be promising for canceling vibrations between the laser system and the concrete. Finally, we have constructed a prototype system that can be transported in a small truck.

Mineralogy and Astrobiology Detection Using Laser Remote Sensing Instrument

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Impact Crater Hydrothermal Niches for Life on Mars: Question of Scale

NASA Technical Reports Server (NTRS)

Pope, K. O.; Ames, D. E.; Kieffer, S. W.; Ocampo, A. C.

2000-01-01

A major focus in the search for fossil life on Mars is on ancient hydrothermal deposits. Nevertheless, remote sensing efforts have not found mineral assemblages characteristic of hydrothermal activity. Future remote sensing work, including missions with higher spatial resolution, may detect localized hydrothermal deposits, but it is possible that dust mantles will prohibit detection from orbit and lander missions will be required. In anticipation of such missions, it is critical to develop a strategy for selecting potential hydrothermal sites on Mars. Such a strategy is being developed for volcanogenic hydrothermal systems, and a similar strategy is needed for impact hydrothermal systems.

A study of Minnesota forests and lakes using data from Earth Resources Technology Satellites

NASA Technical Reports Server (NTRS)

1974-01-01

Highlights of research and practical benefits are discussed for the following projects which utilized ERTS 1 data to provide municipal, state, federal, and industrial users with environmental resource information for the state of Minnesota: (1) forest disease detection and control; (2) evaluation of water quality by remote sensing techniques; (3) forest vegetation classification and management; (4) detection of saline soils in the Red River Valley; (5) snowmelt flood prediction; (6) remote sensing applications to hydrology; (7) Rice Creek watershed project; (8) water quality in Lake Superior and the Duluth Superior Harbor; and (9) determination of Lake Superior currents from turbidity patterns.

Emerging solid-state laser technology by lidar/DIAL remote sensing

NASA Technical Reports Server (NTRS)

Killinger, Dennis

1992-01-01

Significant progress has been made in recent years in the development of new, solid-state laser sources. This talk will present an overview of some of the new developments in solid-state lasers, and their application toward lidar/DIAL measurements of the atmosphere. Newly emerging lasers such as Ho:YAG, Tm:YAG, OPO, and Ti:Sapphire will be covered, along with the spectroscopic parameters required for differential operational modes of atmospheric remote sensing including Doppler-Windshear lidar, Tunable laser detection of water/CO2, and broad linewidth OPO's for open path detection of pollutant hydrocarbon gases. Additional considerations of emerging laser technology for lidar/DIAL will also be covered.

Remote sensing applications to resource problems in South Dakota

NASA Technical Reports Server (NTRS)

Myers, V. I. (Principal Investigator); Best, R. G.; Dalsted, K. J.; Devries, M. E.; Eidenshink, J. C.; Fowler, R.; Heilman, J.; Schmer, F. A.

1980-01-01

Cooperative projects between RSI and numerous South Dakota agencies have provided a means of incorporating remote sensing techniques into operational programs. Eight projects discussed in detail are: (1) detection of high moisture zones near interstate 90; (2) thermal infrared census of Canada geese in South Dakota; (3) dutch elm disease detection in urban environment; (4) a feasibility study for monitoring effective precipitation in South Dakota using TIROS-N; (5) open and abandoned dump sites in Spink county; (6) the influence of soil reflectance on LANDSAT signatures of crops; (7) A model implementation program for Lake Herman watershed; and (8) the Six-Mile Creek investigation follow-on.

Optical researches for cyanobacteria bloom monitoring in Curonian Lagoon

NASA Astrophysics Data System (ADS)

Shirshin, Evgeny A.; Budylin, Gleb B.; Yakimov, Boris P.; Voloshina, Olga V.; Karabashev, Genrik S.; Evdoshenko, Marina A.; Fadeev, Victor V.

2016-04-01

Cyanobacteria bloom is a great ecological problem of Curonian Lagoon and Baltic Sea. The development of novel methods for the on-line control of cyanobacteria concentration and, moreover, for prediction of bloom spreading is of interest for monitoring the state of ecosystem. Here, we report the results of the joint application of hyperspectral measurements and remote sensing of Curonian Lagoon in July 2015 aimed at the assessment of cyanobacteria communities. We show that hyperspectral data allow on-line detection and qualitative estimation of cyanobacteria concentration, while the remote sensing data indicate the possibility of cyanobacteria bloom detection using the spectral features of upwelling irradiation.

Automated seamline detection along skeleton for remote sensing image mosaicking

NASA Astrophysics Data System (ADS)

Zhang, Hansong; Chen, Jianyu; Liu, Xin

2015-08-01

The automatic generation of seamline along the overlap region skeleton is a concerning problem for the mosaicking of Remote Sensing(RS) images. Along with the improvement of RS image resolution, it is necessary to ensure rapid and accurate processing under complex conditions. So an automated seamline detection method for RS image mosaicking based on image object and overlap region contour contraction is introduced. By this means we can ensure universality and efficiency of mosaicking. The experiments also show that this method can select seamline of RS images with great speed and high accuracy over arbitrary overlap regions, and realize RS image rapid mosaicking in surveying and mapping production.

Mountain pine beetle detection and monitoring: evaluation of airborne imagery

NASA Astrophysics Data System (ADS)

Roberts, A.; Bone, C.; Dragicevic, S.; Ettya, A.; Northrup, J.; Reich, R.

2007-10-01

The processing and evaluation of digital airborne imagery for detection, monitoring and modeling of mountain pine beetle (MPB) infestations is evaluated. The most efficient and reliable remote sensing strategy for identification and mapping of infestation stages ("current" to "red" to "grey" attack) of MPB in lodgepole pine forests is determined for the most practical and cost effective procedures. This research was planned to specifically enhance knowledge by determining the remote sensing imaging systems and analytical procedures that optimize resource management for this critical forest health problem. Within the context of this study, airborne remote sensing of forest environments for forest health determinations (MPB) is most suitably undertaken using multispectral digitally converted imagery (aerial photography) at scales of 1:8000 for early detection of current MPB attack and 1:16000 for mapping and sequential monitoring of red and grey attack. Digital conversion should be undertaken at 10 to 16 microns for B&W multispectral imagery and 16 to 24 microns for colour and colour infrared imagery. From an "operational" perspective, the use of twin mapping-cameras with colour and B&W or colour infrared film will provide the best approximation of multispectral digital imagery with near comparable performance in a competitive private sector context (open bidding).

Geothermal area detection using Landsat ETM+ thermal infrared data and its mechanistic analysis—A case study in Tengchong, China

NASA Astrophysics Data System (ADS)

Qin, Qiming; Zhang, Ning; Nan, Peng; Chai, Leilei

2011-08-01

Thermal infrared (TIR) remote sensing is an important technique in the exploration of geothermal resources. In this study, a geothermal survey is conducted in Tengchong area of Yunnan province in China using TIR data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. Based on radiometric calibration, atmospheric correction and emissivity calculation, a simple but efficient single channel algorithm with acceptable precision is applied to retrieve the land surface temperature (LST) of study area. The LST anomalous areas with temperature about 4-10 K higher than background area are discovered. Four geothermal areas are identified with the discussion of geothermal mechanism and the further analysis of regional geologic structure. The research reveals that the distribution of geothermal areas is consistent with the fault development in study area. Magmatism contributes abundant thermal source to study area and the faults provide thermal channels for heat transfer from interior earth to land surface and facilitate the present of geothermal anomalies. Finally, we conclude that TIR remote sensing is a cost-effective technique to detect LST anomalies. Combining TIR remote sensing with geological analysis and the understanding of geothermal mechanism is an accurate and efficient approach to geothermal area detection.

The predictability of reported drought events and impacts in the Ebro Basin using six different remote sensing data sets

NASA Astrophysics Data System (ADS)

Linés, Clara; Werner, Micha; Bastiaanssen, Wim

2017-09-01

The implementation of drought management plans contributes to reduce the wide range of adverse impacts caused by water shortage. A crucial element of the development of drought management plans is the selection of appropriate indicators and their associated thresholds to detect drought events and monitor the evolution. Drought indicators should be able to detect emerging drought processes that will lead to impacts with sufficient anticipation to allow measures to be undertaken effectively. However, in the selection of appropriate drought indicators, the connection to the final impacts is often disregarded. This paper explores the utility of remotely sensed data sets to detect early stages of drought at the river basin scale and determine how much time can be gained to inform operational land and water management practices. Six different remote sensing data sets with different spectral origins and measurement frequencies are considered, complemented by a group of classical in situ hydrologic indicators. Their predictive power to detect past drought events is tested in the Ebro Basin. Qualitative (binary information based on media records) and quantitative (crop yields) data of drought events and impacts spanning a period of 12 years are used as a benchmark in the analysis. Results show that early signs of drought impacts can be detected up to 6 months before impacts are reported in newspapers, with the best correlation-anticipation relationships for the standard precipitation index (SPI), the normalised difference vegetation index (NDVI) and evapotranspiration (ET). Soil moisture (SM) and land surface temperature (LST) offer also good anticipation but with weaker correlations, while gross primary production (GPP) presents moderate positive correlations only for some of the rain-fed areas. Although classical hydrological information from water levels and water flows provided better anticipation than remote sensing indicators in most of the areas, correlations were found to be weaker. The indicators show a consistent behaviour with respect to the different levels of crop yield in rain-fed areas among the analysed years, with SPI, NDVI and ET providing again the stronger correlations. Overall, the results confirm remote sensing products' ability to anticipate reported drought impacts and therefore appear as a useful source of information to support drought management decisions.

[Investigation on remote measurement of air pollution by a method of infrared passive scanning imaging].

PubMed

Jiao, Yang; Xu, Liang; Gao, Min-Guang; Feng, Ming-Chun; Jin, Ling; Tong, Jing-Jing; Li, Sheng

2012-07-01

Passive remote sensing by Fourier-transform infrared (FTIR) spectrometry allows detection of air pollution. However, for the localization of a leak and a complete assessment of the situation in the case of the release of a hazardous cloud, information about the position and the distribution of a cloud is essential. Therefore, an imaging passive remote sensing system comprising an interferometer, a data acquisition and processing software, scan system, a video system, and a personal computer has been developed. The remote sensing of SF6 was done. The column densities of all directions in which a target compound has been identified may be retrieved by a nonlinear least squares fitting algorithm and algorithm of radiation transfer, and a false color image is displayed. The results were visualized by a video image, overlaid by false color concentration distribution image. The system has a high selectivity, and allows visualization and quantification of pollutant clouds.

Remote optical stethoscope and optomyography sensing device

NASA Astrophysics Data System (ADS)

Golberg, Mark; Polani, Sagi; Ozana, Nisan; Beiderman, Yevgeny; Garcia, Javier; Ruiz-Rivas Onses, Joaquin; Sanz Sabater, Martin; Shatsky, Max; Zalevsky, Zeev

2017-02-01

In this paper we present the usage of photonic remote laser based device for sensing nano-vibrations for detection of muscle contraction and fatigue, eye movements and in-vivo estimation of glucose concentration. The same concept is also used to realize a remote optical stethoscope. The advantage of doing the measurements from a distance is in preventing passage of infections as in the case of optical stethoscope or in the capability to monitor e.g. sleep quality without disturbing the patient. The remote monitoring of glucose concentration in the blood stream and the capability to perform opto-myography for the Messer muscles (chewing) is very useful for nutrition and weight control. The optical configuration for sensing the nano-vibrations is based upon analyzing the statistics of the secondary speckle patterns reflected from various tissues along the body of the subjects. Experimental results present the preliminary capability of the proposed configuration for the above mentioned applications.

A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data

PubMed Central

Vanegas, Fernando; Weiss, John; Gonzalez, Felipe

2018-01-01

Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used—the sensors, the UAV, and the flight operations—the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analysing and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications. PMID:29342101

Laser-based sensors for oil spill remote sensing

NASA Astrophysics Data System (ADS)

Brown, Carl E.; Fingas, Mervin F.; Mullin, Joseph V.

1997-07-01

Remote sensing is becoming an increasingly important tool for the effective direction of oil spill countermeasures. Cleanup personnel have recognized that remote sensing can increase spill cleanup efficiency. It has long been recognized that there is no one sensor which is capable of detecting oil and related petroleum products in all environments and spill scenarios. There are sensors which possess a wide field-of- view and can therefore be used to map the overall extent of the spill. These sensors, however lack the capability to positively identify oil and related products, especially along complicated beach and shoreline environments where several substrates are present. The laser-based sensors under development by the Emergencies Science Division of Environment Canada are designed to fill specific roles in oil spill response. The scanning laser environmental airborne fluorosensor (SLEAF) is being developed to detect and map oil and related petroleum products in complex marine and shoreline environments where other non-specific sensors experience difficulty. The role of the SLEAF would be to confirm or reject suspected oil contamination sites that have been targeted by the non-specific sensors. This confirmation will release response crews from the time-consuming task of physically inspecting each site, and direct crews to sites that require remediation. The laser ultrasonic remote sensing of oil thickness (LURSOT) sensor will provide an absolute measurement of oil thickness from an airborne platform. There are presently no sensors available, either airborne or in the laboratory which can provide an absolute measurement of oil thickness. This information is necessary for the effective direction of spill countermeasures such as dispersant application and in-situ burning. This paper describes the development of laser-based airborne oil spill remote sensing instrumentation at Environment Canada and identifies the anticipated benefits of the use of this technology to the oil spill response community.

Ground-based remote sensing of volcanic CO2 and correlated SO2, HF, HCl, and BrO, in safe-distance from the crater

NASA Astrophysics Data System (ADS)

Butz, Andre; Solvejg Dinger, Anna; Bobrowski, Nicole; Kostinek, Julian; Fieber, Lukas; Fischerkeller, Constanze; Giuffrida, Giovanni Bruno; Hase, Frank; Klappenbach, Friedrich; Kuhn, Jonas; Lübcke, Peter; Tirpitz, Lukas; Tu, Qiansi

2017-04-01

Remote sensing of CO2 enhancements in volcanic plumes can be a tool to estimate volcanic CO2 emissions and thereby, to gain insight into the geological carbon cycle and into volcano interior processes. However, remote sensing of the volcanic CO2 is challenged by the large atmospheric background concentrations masking the minute volcanic signal. Here, we report on a demonstrator study conducted in September 2015 at Mt. Etna on Sicily, where we deployed an EM27/SUN Fourier Transform Spectrometer together with a UV spectrometer on a mobile remote sensing platform. The spectrometers were operated in direct-sun viewing geometry collecting cross-sectional scans of solar absorption spectra through the volcanic plume by operating the platform in stop-and-go patterns in 5 to 10 kilometers distance from the crater region. We successfully detected correlated intra-plume enhancements of CO2 and volcanic SO2, HF, HCl, and BrO. The path-integrated volcanic CO2 enhancements amounted to about 0.5 ppm (on top of the ˜400 ppm background). Key to successful detection of volcanic CO2 was A) the simultaneous observation of the O2 total column which allowed for correcting changes in the CO2 column caused by changes in observer altitude and B) the simultaneous measurement of volcanic species co-emitted with CO2 which allowed for discriminating intra-plume and extra-plume observations. The latter were used for subtracting the atmospheric CO2 background. The field study suggests that our remote sensing observatory is a candidate technique for volcano monitoring in safe distance from the crater region.

Remote identification of individual volunteer cotton plants

USDA-ARS?s Scientific Manuscript database

Although airborne multispectral remote sensing can identify fields of small cotton plants, improvements to detection sensitivity are needed to identify individual or small clusters of plants that can similarly provide habitat for boll weevils. However, when consumer-grade cameras are used, each pix...

Remote sensing in Virginia agriculture

NASA Technical Reports Server (NTRS)

Pettry, D. E.; Newhouse, M. E.; Dunton, E. M., Jr.; Scott, J. H., Jr.

1972-01-01

An experimental investigation, designed to develop and evaluate multispectral sensing techniques used in sensing agricultural crops, is described. Initial studies were designed to detect plant species and associated diseases, soil variations, and cultural practices under natural environment conditions. In addition, crop varieties, age, spacing, plant height, percentage of ground cover, and plant vigor are determined.

Propagation Limitations in Remote Sensing.

DTIC Science & Technology

Contents: Multi-sensors and systems in remote sensing ; Radar sensing systems over land; Remote sensing techniques in oceanography; Influence of...propagation media and background; Infrared techniques in remote sensing ; Photography in remote sensing ; Analytical studies in remote sensing .

NONDESTRUCTIVE TESTING (NDT) TECHNIQUES TO DETECT CONTAINED SUBSURFACE HAZARDOUS WASTE

EPA Science Inventory

The project involves the detection of buried containers with NDT (remote-sensing) techniques. Seventeen techniques were considered and four were ultimately decided upon. They were: electromagnetic induction (EMI); metal detection (MD); magnetometer (MAG); and ground penetrating r...

Application of remote sensing for prediction and detection of thermal pollution

NASA Technical Reports Server (NTRS)

Veziroglu, T. N.; Lee, S. S.

1974-01-01

The first phase is described of a three year project for the development of a mathematical model for predicting thermal pollution by use of remote sensing measurements. A rigid-lid model was developed, and results were obtained for different wind conditions at Biscayne Bay in South Florida. The design of the measurement system was completed, and instruments needed for the first stage of experiment were acquired, tested, and calibrated. A preliminary research flight was conducted.

Remote Sensing Systems to Detect and Analyze Oil Spills on the U.S. Outer Continental Shelf - A State of the Art Assessment

DTIC Science & Technology

2016-08-18

multi- sensor remote sensing approach to describe the distribution of oil from the DWH spill. They used airborne and satellite , multi- and hyperspectral...Experimental Sensors e.g., Acoustic and Nuclear Magnetic Resonance (NMR) (Fingas and Brown, 2012; Puestow et al., 2013). These are further...ship, aerial - aircraft, aerostat or UAV, or satellite ), among other classification criteria. A comprehensive review of sensor categories employed

Research on visible and near infrared spectral-polarimetric properties of soil polluted by crude oil

NASA Astrophysics Data System (ADS)

Shen, Hui-yan; Zhou, Pu-cheng; Pan, Bang-long

2017-10-01

Hydrocarbon contaminated soil can impose detrimental effects on forest health and quality of agricultural products. To manage such consequences, oil leak indicators should be detected quickly by monitoring systems. Remote sensing is one of the most suitable techniques for monitoring systems, especially for areas which are uninhabitable and difficulty to access. The most available physical quantities in optical remote sensing domain are the intensity and spectral information obtained by visible or infrared sensors. However, besides the intensity and wavelength, polarization is another primary physical quantity associated with an optical field. During the course of reflecting light-wave, the surface of soil polluted by crude oil will cause polarimetric properties which are related to the nature of itself. Thus, detection of the spectralpolarimetric properties for soil polluted by crude oil has become a new remote sensing monitoring method. In this paper, the multi-angle spectral-polarimetric instrument was used to obtain multi-angle visible and near infrared spectralpolarimetric characteristic data of soil polluted by crude oil. And then, the change rule between polarimetric properties with different affecting factors, such as viewing zenith angle, incidence zenith angle of the light source, relative azimuth angle, waveband of the detector as well as different grain size of soil were discussed, so as to provide a scientific basis for the research on polarization remote sensing for soil polluted by crude oil.

NASA Icing Remote Sensing System Comparisons From AIRS II

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Brinker, David J.; Ratvasky, Thomas P.

2005-01-01

NASA has an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. A multiple instrument approach is the current emphasis of this activity. Utilizing radar, radiometry, and lidar, a region of supercooled liquid is identified. If the liquid water content (LWC) is sufficiently high, then the region of supercooled liquid cloud is flagged as being an aviation hazard. The instruments utilized for the current effort are an X-band vertical staring radar, a radiometer that measures twelve frequencies between 22 and 59 GHz, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data is post-processed with a LabVIEW program with a resultant supercooled LWC profile and aircraft hazard identification. Individual remotely sensed measurements gathered during the 2003-2004 Alliance Icing Research Study (AIRS II) were compared to aircraft in-situ measurements. Comparisons between the remote sensing system s fused icing product and in-situ measurements from the research aircraft are reviewed here. While there are areas where improvement can be made, the cases examined indicate that the fused sensor remote sensing technique appears to be a valid approach.

Science, technology, and application of THz air photonics

NASA Astrophysics Data System (ADS)

Lu, X. F.; Clough, B.; Ho, I.-C.; Kaur, G.; Liu, J.; Karpowicz, N.; Dai, J. M.; Zhang, X.-C.

2010-11-01

The significant scientific and technological potential of terahertz (THz) wave sensing and imaging has been attracted considerable attention within many fields of research. However, the development of remote, broadband THz wave sensing technology is lagging behind the compelling needs that exist in the areas of astronomy, global environmental monitoring, and homeland security. This is due to the challenge posed by high absorption of ambient moisture in the THz range. Although various time-domain THz detection techniques have recently been demonstrated, the requirement for an on-site bias or forward collection of the optical signal inevitably prohibits their applications for remote sensing. The objective of this paper is to report updated THz air-plasma technology to meet this great challenge of remote sensing. A focused optical pulse (mJ pulse energy and femtosecond pulse duration) in gas creates a plasma, which can serve to generate intense, broadband, and directional THz waves in the far field.

The use of remote sensors to relate biological and physical indicators to environmental and public health problems

NASA Technical Reports Server (NTRS)

1972-01-01

Relationships between biological, ecological and botanical structures, and disease organisms and their vectors which might be detected and measured by remote sensing are determined. In addition to the use of trees as indicators of disease or potential disease, an attempt is made to identify environmental factors such as soil moisture and soil and water temperatures as they relate to disease or health problems and may be detected by remote sensing. The following three diseases and one major health problem are examined: Malaria, Rocky Mountain spotted fever, Encephalitis and Red Tide. It is shown that no single species of vascular plant nor any one environmental factor can be used as the indicator of disease or health problems. Entire vegetation types, successional stages and combinations of factors must be used.

2005 AG20/20 Annual Review

NASA Technical Reports Server (NTRS)

Ross, Kenton W.; McKellip, Rodney D.

2005-01-01

Topics covered include: Implementation and Validation of Sensor-Based Site-Specific Crop Management; Enhanced Management of Agricultural Perennial Systems (EMAPS) Using GIS and Remote Sensing; Validation and Application of Geospatial Information for Early Identification of Stress in Wheat; Adapting and Validating Precision Technologies for Cotton Production in the Mid-Southern United States - 2004 Progress Report; Development of a System to Automatically Geo-Rectify Images; Economics of Precision Agriculture Technologies in Cotton Production-AG 2020 Prescription Farming Automation Algorithms; Field Testing a Sensor-Based Applicator for Nitrogen and Phosphorus Application; Early Detection of Citrus Diseases Using Machine Vision and DGPS; Remote Sensing of Citrus Tree Stress Levels and Factors; Spectral-based Nitrogen Sensing for Citrus; Characterization of Tree Canopies; In-field Sensing of Shallow Water Tables and Hydromorphic Soils with an Electromagnetic Induction Profiler; Maintaining the Competitiveness of Tree Fruit Production Through Precision Agriculture; Modeling and Visualizing Terrain and Remote Sensing Data for Research and Education in Precision Agriculture; Thematic Soil Mapping and Crop-Based Strategies for Site-Specific Management; and Crop-Based Strategies for Site-Specific Management.

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

PubMed

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.

Study on multispectral imaging detection and recognition

NASA Astrophysics Data System (ADS)

Jun, Wang; Na, Ding; Gao, Jiaobo; Yu, Hu; Jun, Wu; Li, Junna; Zheng, Yawei; Fei, Gao; Sun, Kefeng

2009-07-01

Multispectral imaging detecting technology use target radiation character in spectral spatial distribution and relation between spectral and image to detect target and remote sensing measure. Its speciality is multi channel, narrow bandwidth, large amount of information, high accuracy. The ability of detecting target in environment of clutter, camouflage, concealment and beguilement is improved. At present, spectral imaging technology in the range of multispectral and hyperspectral develop greatly. The multispectral imaging equipment of unmanned aerial vehicle can be used in mine detection, information, surveillance and reconnaissance. Spectral imaging spectrometer operating in MWIR and LWIR has already been applied in the field of remote sensing and military in the advanced country. The paper presents the technology of multispectral imaging. It can enhance the reflectance, scatter and radiation character of the artificial targets among nature background. The targets among complex background and camouflage/stealth targets can be effectively identified. The experiment results and the data of spectral imaging is obtained.

Integrating Remote and Social Sensing Data for a Scenario on Secure Societies in Big Data Platform

NASA Astrophysics Data System (ADS)

Albani, Sergio; Lazzarini, Michele; Koubarakis, Manolis; Taniskidou, Efi Karra; Papadakis, George; Karkaletsis, Vangelis; Giannakopoulos, George

2016-08-01

In the framework of the Horizon 2020 project BigDataEurope (Integrating Big Data, Software & Communities for Addressing Europe's Societal Challenges), a pilot for the Secure Societies Societal Challenge was designed considering the requirements coming from relevant stakeholders. The pilot is focusing on the integration in a Big Data platform of data coming from remote and social sensing.The information on land changes coming from the Copernicus Sentinel 1A sensor (Change Detection workflow) is integrated with information coming from selected Twitter and news agencies accounts (Event Detection workflow) in order to provide the user with multiple sources of information.The Change Detection workflow implements a processing chain in a distributed parallel manner, exploiting the Big Data capabilities in place; the Event Detection workflow implements parallel and distributed social media and news agencies monitoring as well as suitable mechanisms to detect and geo-annotate the related events.

Geospatial Image Mining For Nuclear Proliferation Detection: Challenges and New Opportunities

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

Vatsavai, Raju; Bhaduri, Budhendra L; Cheriyadat, Anil M

2010-01-01

With increasing understanding and availability of nuclear technologies, and increasing persuasion of nuclear technologies by several new countries, it is increasingly becoming important to monitor the nuclear proliferation activities. There is a great need for developing technologies to automatically or semi-automatically detect nuclear proliferation activities using remote sensing. Images acquired from earth observation satellites is an important source of information in detecting proliferation activities. High-resolution remote sensing images are highly useful in verifying the correctness, as well as completeness of any nuclear program. DOE national laboratories are interested in detecting nuclear proliferation by developing advanced geospatial image mining algorithms. Inmore » this paper we describe the current understanding of geospatial image mining techniques and enumerate key gaps and identify future research needs in the context of nuclear proliferation.« less

Remote sensing with laser spectrum radar

NASA Astrophysics Data System (ADS)

Wang, Tianhe; Zhou, Tao; Jia, Xiaodong

2016-10-01

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

Detection of ocean waste in the New York Bight

NASA Technical Reports Server (NTRS)

Philpot, W.; Klemas, V.

1979-01-01

The application of remote sensing to detection and monitoring of ocean waste disposal in the New York Bight is discussed. Attention is focused on the two major pollutants in this area--sewage sludge and iron-acid waste--and on detecting and identifying these pollutants. The emphasis is on the use of LANDSAT multispectral data in identifying these pollutants and distinguishing them from other substances. The analysis technique applied to the LANDSAT data is the eigenvector. This approach proved to be quite successful in detecting iron-acid waste of the coast of Delaware and is applied here with relatively minor modifications. The results of the New York Bight work are compared to the Delaware results. Finally, other remote sensing systems (Nimbus G, aircraft photography and multispectral scanner systems) are discussed as possible complements of or replacements for the Landsat observations.

A strategy for detecting derelict fishing gear at sea.

PubMed

McElwee, Kris; Donohue, Mary J; Courtney, Catherine A; Morishige, Carey; Rivera-Vicente, Ariel

2012-01-01

Derelict fishing gear (DFG) is a highly persistent form of marine pollution known to cause environmental and economic damage. At-sea detection of DFG would support pelagic removal of this gear to prevent and minimize impacts on marine environments and species. In 2008, experts in marine debris, oceanography, remote sensing, and marine policy outlined a strategy to develop the capability to detect and ultimately remove DFG from the open ocean. The strategy includes three interrelated components: understanding the characteristics of the targeted DFG, indirectly detecting DFG by modeling likely locations, and directly detecting pelagic DFG using remote sensing. Together, these components aim to refine the search area, increase the likelihood of detection, and decrease mitigation response time, thereby providing guidance for removal operations. Here, we present this at-sea detection strategy, relate it to relevant extant research and technology, and identify gaps that currently prevent successful at-sea detection and removal of DFG. Copyright © 2011 Elsevier Ltd. All rights reserved.

Using leaf optical properties to detect ozone effects on foliar biochemistry

USDA-ARS?s Scientific Manuscript database

Efficient methods for accurate and meaningful high-throughput plant phenotyping are limiting the development and breeding of stress-tolerant crops. A number of emerging techniques, specifically remote sensing methods, have been identified as promising tools for plant phenotyping. These remote-sensin...

Intercomparison of in-situ and remote sensing δD signals in tropospheric water vapour

NASA Astrophysics Data System (ADS)

Schneider, Matthias; González, Yenny; Dyroff, Christoph; Christner, Emanuel; García, Omaira; Wiegele, Andreas; Andrey, Javier; Barthlott, Sabine; Blumenstock, Thomas; Guirado, Carmen; Hase, Frank; Ramos, Ramon; Rodríguez, Sergio; Sepúveda, Eliezer

2014-05-01

The main mission of the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) is the generation of a quasi-global tropospheric water vapour isototopologue dataset of a good and well-documented quality. We present a first empirical validation of MUSICA's remote sensing δD products (ground-based FTIR within NDACC, Network for the Detection of Atmospheric Composition Change, and space-based with IASI, Infrared Atmospheric Sounding Interferometer, flown on METOP). As reference we use in-situ measurements made on the island of Tenerife at two different altitudes (2370 and 3550 m a.s.l., using two Picarro L2120-i water isotopologue analyzers) and aboard an aircraft (between 200 and 6800 m a.s.l., using the homemade ISOWAT instrument).

Flux Calculation Using CARIBIC DOAS Aircraft Measurements: SO2 Emission of Norilsk

NASA Technical Reports Server (NTRS)

Walter, D.; Heue, K.-P.; Rauthe-Schoech, A.; Brenninkmeijer, C. A. M.; Lamsal, L. N.; Krotkov, N. A.; Platt, U.

2012-01-01

Based on a case-study of the nickel smelter in Norilsk (Siberia), the retrieval of trace gas fluxes using airborne remote sensing is discussed. A DOAS system onboard an Airbus 340 detected large amounts of SO2 and NO2 near Norilsk during a regular passenger flight within the CARIBIC project. The remote sensing data were combined with ECMWF wind data to estimate the SO2 output of the Norilsk industrial complex to be around 1 Mt per year, which is in agreement with independent estimates. This value is compared to results using data from satellite remote sensing (GOME, OMI). The validity of the assumptions underlying our estimate is discussed, including the adaptation of this method to other gases and sources like the NO2 emissions of large industries or cities.

Structural and spectroscopic changes to natural nontronite induced by experimental impacts between 10 and 40 GPa

NASA Astrophysics Data System (ADS)

Friedlander, Lonia R.; Glotch, Timothy D.; Bish, David L.; Dyar, M. Darby; Sharp, Thomas G.; Sklute, Elizabeth C.; Michalski, Joseph R.

2015-05-01

Many phyllosilicate deposits remotely detected on Mars occur within bombarded terrains. Shock metamorphism from meteor impacts alters mineral structures, producing changed mineral spectra. Thus, impacts have likely affected the spectra of remotely sensed Martian phyllosilicates. We present spectral analysis results for a natural nontronite sample before and after laboratory-generated impacts over five peak pressures between 10 and 40 GPa. We conducted a suite of spectroscopic analyses to characterize the sample's impact-induced structural and spectral changes. Nontronite becomes increasingly disordered with increasing peak impact pressure. Every infrared spectroscopic technique used showed evidence of structural changes at shock pressures above ~25 GPa. Reflectance spectroscopy in the visible near-infrared region is primarily sensitive to the vibrations of metal-OH and interlayer H2O groups in the nontronite octahedral sheet. Midinfrared (MIR) spectroscopic techniques are sensitive to the vibrations of silicon and oxygen in the nontronite tetrahedral sheet. Because the tetrahedral and octahedral sheets of nontronite deform differently, impact-driven structural deformation may contribute to differences in phyllosilicate detection between remote sensing techniques sensitive to different parts of the nontronite structure. Observed spectroscopic changes also indicated that the sample's octahedral and tetrahedral sheets were structurally deformed but not completely dehydroxylated. This finding is an important distinction from previous studies of thermally altered phyllosilicates in which dehydroxylation follows dehydration in a stepwise progression preceding structural deformation. Impact alteration may thus complicate mineral-specific identifications based on the location of OH-group bands in remotely detected spectra. This is a key implication for Martian remote sensing arising from our results.

From Pixels to Population Stress: Global Multispectral Remote Sensing for Vulnerable Communities

NASA Astrophysics Data System (ADS)

Prashad, L.; Kaplan, E.; Letouze, E.; Kirkpatrick, R.; Luengo-Oroz, M.; Christensen, P. R.

2011-12-01

The Arizona State University (ASU) School of Earth and Space Exploration's Mars Space Flight Facility (MSFF) and 100 Cities Project, in collaboration with the United Nations Global Pulse initiative are utilizing NASA multispectral satellite data to visualize and analyze socioeconomic characteristics and human activity in Uganda. The Global Pulse initiative is exploring how new kinds of real-time data and innovative technologies can be leveraged to detect early social impacts of slow-onset crisis and global shocks. Global Pulse is developing a framework for real-time monitoring, assembling an open-source toolkit for analyzing new kinds of data and establishing a global network of country-level "Pulse Labs" where governments, UN agencies, academia and the private sector learn together how to harness the new world of "big data" to protect the vulnerable with targeted and agile policy responses. The ASU MSFF and 100 Cities Project are coordinating with the Global Pulse team to utilize NASA remote sensing data in this effort. Human behavior and socioeconomic parameters have been successfully studied via proxy through remote sensing of the physical environment by measuring the growth of city boundaries and transportation networks, crop health, soil moisture, and slum development from visible and infrared imagery. The NASA/ NOAA image of Earth's "Lights at Night" is routinely used to estimate economic development and population density. There are many examples of the conventional uses of remote sensing in humanitarian-related projects including the Famine Early Warning System Network (FEWS NET) and the UN's operational satellite applications programme (UNOSAT), which provides remote sensing for humanitarian and disaster relief. Since the Global Pulse project is focusing on new, innovative uses of technology for early crisis detection, we are focusing on three non-conventional uses of satellite remote sensing to understand what role NASA multispectral satellites can play in monitoring underlying socioeconomic and human parameters. These are: 1) measuring and visualizing changes in agriculture and fertilizer use in Ugandan villages in order to assist policymakers in designing land use policies and evaluating the impact of fertilizer use on smallholder farmers in developing countries; 2) monitoring the size and composition of large scale rubbish dumps to determine correlation with changes in policy and economic growth; 3) measuring the size and shape of open air markets, or proxies related to the markets, to determine if changes can be detected that correspond to fluctuations in economic activity. The ASU MSFF open source geographical information systems (GIS) platform, J-Earth, will be used to provide easy access to and analytical tools for the data and imagery resulting from this project. J-Earth is a part of the Java Mission-planning and Analysis for Remote Sensing (JMARS) suite of software first developed for targeting NASA instruments on planetary missions.

Remote Sensing of In-Flight Icing Conditions: Operational, Meteorological, and Technological Considerations

NASA Technical Reports Server (NTRS)

Ryerson, Charles C.

2000-01-01

Remote-sensing systems that map aircraft icing conditions in the flight path from airports or aircraft would allow icing to be avoided and exited. Icing remote-sensing system development requires consideration of the operational environment, the meteorological environment, and the technology available. Operationally, pilots need unambiguous cockpit icing displays for risk management decision-making. Human factors, aircraft integration, integration of remotely sensed icing information into the weather system infrastructures, and avoid-and-exit issues need resolution. Cost, maintenance, power, weight, and space concern manufacturers, operators, and regulators. An icing remote-sensing system detects cloud and precipitation liquid water, drop size, and temperature. An algorithm is needed to convert these conditions into icing potential estimates for cockpit display. Specification development requires that magnitudes of cloud microphysical conditions and their spatial and temporal variability be understood at multiple scales. The core of an icing remote-sensing system is the technology that senses icing microphysical conditions. Radar and microwave radiometers penetrate clouds and can estimate liquid water and drop size. Retrieval development is needed; differential attenuation and neural network assessment of multiple-band radar returns are most promising to date. Airport-based radar or radiometers are the most viable near-term technologies. A radiometer that profiles cloud liquid water, and experimental techniques to use radiometers horizontally, are promising. The most critical operational research needs are to assess cockpit and aircraft system integration, develop avoid-and-exit protocols, assess human factors, and integrate remote-sensing information into weather and air traffic control infrastructures. Improved spatial characterization of cloud and precipitation liquid-water content, drop-size spectra, and temperature are needed, as well as an algorithm to convert sensed conditions into a measure of icing potential. Technology development also requires refinement of inversion techniques. These goals can be accomplished with collaboration among federal agencies including NASA, the FAA, the National Center for Atmospheric Research, NOAA, and the Department of Defense. This report reviews operational, meteorological, and technological considerations in developing the capability to remotely map in-flight icing conditions from the ground and from the air.

Overview of the NASA tropospheric environmental quality remote sensing program

NASA Technical Reports Server (NTRS)

Allario, F.; Ayers, W. G.; Hoell, J. M.

1979-01-01

This paper will summarize the current NASA Tropospheric Environmental Quality Remote Sensing Program for studying the global and regional troposphere from space, airborne and ground-based platforms. As part of the program to develop remote sensors for utilization from space, NASA has developed a series of passive and active remote sensors which have undergone field test measurements from airborne and ground platforms. Recent measurements with active lidar and passive gas filter correlation and infrared heterodyne techniques will be summarized for measurements of atmospheric aerosols, CO, SO2, O3, and NH3. These measurements provide the data base required to assess the sensitivity of remote sensors for applications to urban and regional field measurement programs. Studies of Earth Observation Satellite Systems are currently being performed by the scientific community to assess the capability of satellite imagery to detect regions of elevated pollution in the troposphere. The status of NASA sponsored research efforts in interpreting satellite imagery for determining aerosol loadings over land and inland bodies of water will be presented, and comments on the potential of these measurements to supplement in situ and airborne remote sensors in detecting regional haze will be made.

A low-cost, portable optical sensing system with wireless communication compatible of real-time and remote detection of dissolved ammonia

NASA Astrophysics Data System (ADS)

Deng, Shijie; Doherty, William; McAuliffe, Michael AP; Salaj-Kosla, Urszula; Lewis, Liam; Huyet, Guillaume

2016-06-01

A low-cost and portable optical chemical sensor based ammonia sensing system that is capable of detecting dissolved ammonia up to 5 ppm is presented. In the system, an optical chemical sensor is designed and fabricated for sensing dissolved ammonia concentrations. The sensor uses eosin as the fluorescence dye which is immobilized on the glass substrate by a gas-permeable protection layer. A compact module is developed to hold the optical components, and a battery powered micro-controller system is designed to read out and process the data measured. The system operates without the requirement of laboratory instruments that makes it cost effective and highly portable. Moreover, the calculated results in the system can be transmitted to a PC wirelessly, which allows the remote and real-time monitoring of dissolved ammonia.

Earth view: A business guide to orbital remote sensing

NASA Technical Reports Server (NTRS)

Bishop, Peter C.

1990-01-01

The following subject areas are covered: Earth view - a guide to orbital remote sensing; current orbital remote sensing systems (LANDSAT, SPOT image, MOS-1, Soviet remote sensing systems); remote sensing satellite; and remote sensing organizations.

Horizon sensors attitude errors simulation for the Brazilian Remote Sensing Satellite

NASA Astrophysics Data System (ADS)

Vicente de Brum, Antonio Gil; Ricci, Mario Cesar

Remote sensing, meteorological and other types of satellites require an increasingly better Earth related positioning. From the past experience it is well known that the thermal horizon in the 15 micrometer band provides conditions of determining the local vertical at any time. This detection is done by horizon sensors which are accurate instruments for Earth referred attitude sensing and control whose performance is limited by systematic and random errors amounting about 0.5 deg. Using the computer programs OBLATE, SEASON, ELECTRO and MISALIGN, developed at INPE to simulate four distinct facets of conical scanning horizon sensors, attitude errors are obtained for the Brazilian Remote Sensing Satellite (the first one, SSR-1, is scheduled to fly in 1996). These errors are due to the oblate shape of the Earth, seasonal and latitudinal variations of the 15 micrometer infrared radiation, electronic processing time delay and misalignment of sensor axis. The sensor related attitude errors are thus properly quantified in this work and will, together with other systematic errors (for instance, ambient temperature variation) take part in the pre-launch analysis of the Brazilian Remote Sensing Satellite, with respect to the horizon sensor performance.

Fiber-Optic Sensor-Based Remote Acoustic Emission Measurement in a 1000 °C Environment.

PubMed

Yu, Fengming; Okabe, Yoji

2017-12-14

Recently, the authors have proposed a remote acoustic emission (AE) measurement configuration using a sensitive fiber-optic Bragg grating (FBG) sensor. In the configuration, the FBG sensor was remotely bonded on a plate, and an optical fiber was used as the waveguide to propagate AE waves from the adhesive point to the sensor. The previous work (Yu et al., Smart Materials and Structures 25 (10), 105,033 (2016)) has clarified the sensing principle behind the special remote measurement system that enables accurate remote sensing of AE signals. Since the silica-glass optical fibers have a high heat-resistance exceeding 1000 °C, this work presents a preliminary high-temperature AE detection method by using the optical fiber-based ultrasonic waveguide to propagate the AE from a high-temperature environment to a room-temperature environment, in which the FBG sensor could function as the receiver of the guided wave. As a result, the novel measurement configuration successfully achieved highly sensitive and stable AE detection in an alumina plate at elevated temperatures in the 100 °C to 1000 °C range. Due to its good performance, this detection method will be potentially useful for the non-destructive testing that can be performed in high-temperature environments to evaluate the microscopic damage in heat-resistant materials.

Possible methods for distinguishing icebergs from ships by aerial remote sensing

NASA Technical Reports Server (NTRS)

Howes, W. L.

1979-01-01

The simplest methods for aerial remote sensing which are least affected by atmospheric opacities are summarized. Radar is preferred for targets off the flight path, and microwave radiometry for targets along the flight path. Radar methods are classified by ability to resolve targets. Techniques which do not require target resolution are preferred. Among these techniques, polarization methods appear most promising, specifically those which differentiate the expected relatively greater depolarization by icebergs from that by ships or which detect doubly-reversed circular polarization.

Global geomorphology: Report of Working Group Number 1

NASA Technical Reports Server (NTRS)

Douglas, I.

1985-01-01

Remote sensing was considered invaluable for seeing landforms in their regional context and in relationship to each other. Sequential images, such as those available from LANDSAT orbits provide a means of detecting landform change and the operation of large scale processes, such as major floods in semiarid regions. The use of remote sensing falls into two broad stages: (1) the characterization or accurate description of the features of the Earth's surface; and (2) the study of landform evolution. Recommendations for future research are made.

Studying turbulence by remote sensing systems during slope-2016 campaign

NASA Astrophysics Data System (ADS)

Moreira, Gregori de A.; Guerrero-Rascado, Juan L.; Benavent-Oltra, Jose A.; Ortiz-Amezcua, Pablo; Róman, Roberto; Landulfo, Eduardo; Alados-Arboledas, Lucas

2018-04-01

The Planetary Boundary Layer (PBL) is the lowermost part of the troposphere. In this work, we analysed some high order moments and PBL height detected continuously by three remote sensing systems: an elastic lidar, a Doppler lidar and a passive Microwave Radiometer, during the SLOPE-2016 campaign, which was held in Granada from May to August 2016. This study confirms the feasibility of these systems for the characterization of the PBL, helping us to justify and understand its behaviour along the day.

Remote sensing applied to agriculture: Basic principles, methodology, and applications

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Mendonca, F. J.

1981-01-01

The general principles of remote sensing techniques as applied to agriculture and the methods of data analysis are described. the theoretical spectral responses of crops; reflectance, transmittance, and absorbtance of plants; interactions of plants and soils with reflectance energy; leaf morphology; and factors which affect the reflectance of vegetation cover are dicussed. The methodologies of visual and computer-aided analyses of LANDSAT data are presented. Finally, a case study wherein infrared film was used to detect crop anomalies and other data applications are described.

A Low Cost Remote Sensing System Using PC and Stereo Equipment

NASA Technical Reports Server (NTRS)

Campbell, Joel F.; Flood, Michael A.; Prasad, Narasimha S.; Hodson, Wade D.

2011-01-01

A system using a personal computer, speaker, and a microphone is used to detect objects, and make crude measurements using a carrier modulated by a pseudorandom noise (PN) code. This system can be constructed using a personal computer and audio equipment commonly found in the laboratory or at home, or more sophisticated equipment that can be purchased at reasonable cost. We demonstrate its value as an instructional tool for teaching concepts of remote sensing and digital signal processing.

Application of remote thermal scanning to the NASA energy conservation program

NASA Technical Reports Server (NTRS)

Bowman, R. L.; Jack, J. R.

1977-01-01

Airborne thermal scans of all NASA centers were made during 1975 and 1976. The remotely sensed data were used to identify a variety of heat losses, including those from building roofs and central heating system distribution lines. Thermal imagery from several NASA centers is presented to demonstrate the capability of detecting these heat losses remotely. Many heat loss areas located by the scan data were verified by ground surveys. At this point, at least for such energy-intensive areas, thermal scanning is an excellent means of detecting many possible energy losses.

Multitask SVM learning for remote sensing data classification

NASA Astrophysics Data System (ADS)

Leiva-Murillo, Jose M.; Gómez-Chova, Luis; Camps-Valls, Gustavo

2010-10-01

Many remote sensing data processing problems are inherently constituted by several tasks that can be solved either individually or jointly. For instance, each image in a multitemporal classification setting could be taken as an individual task but relation to previous acquisitions should be properly considered. In such problems, different modalities of the data (temporal, spatial, angular) gives rise to changes between the training and test distributions, which constitutes a difficult learning problem known as covariate shift. Multitask learning methods aim at jointly solving a set of prediction problems in an efficient way by sharing information across tasks. This paper presents a novel kernel method for multitask learning in remote sensing data classification. The proposed method alleviates the dataset shift problem by imposing cross-information in the classifiers through matrix regularization. We consider the support vector machine (SVM) as core learner and two regularization schemes are introduced: 1) the Euclidean distance of the predictors in the Hilbert space; and 2) the inclusion of relational operators between tasks. Experiments are conducted in the challenging remote sensing problems of cloud screening from multispectral MERIS images and for landmine detection.

Information recovery through image sequence fusion under wavelet transformation

NASA Astrophysics Data System (ADS)

He, Qiang

2010-04-01

Remote sensing is widely applied to provide information of areas with limited ground access with applications such as to assess the destruction from natural disasters and to plan relief and recovery operations. However, the data collection of aerial digital images is constrained by bad weather, atmospheric conditions, and unstable camera or camcorder. Therefore, how to recover the information from the low-quality remote sensing images and how to enhance the image quality becomes very important for many visual understanding tasks, such like feature detection, object segmentation, and object recognition. The quality of remote sensing imagery can be improved through meaningful combination of the employed images captured from different sensors or from different conditions through information fusion. Here we particularly address information fusion to remote sensing images under multi-resolution analysis in the employed image sequences. The image fusion is to recover complete information by integrating multiple images captured from the same scene. Through image fusion, a new image with high-resolution or more perceptive for human and machine is created from a time series of low-quality images based on image registration between different video frames.

Two candidate systems for unmanned fog bank detection

DOT National Transportation Integrated Search

1971-06-01

The detection of coastal fog banks by remote sensing methods is discussed. The feasibility of laser backscattering (LIDAR) and infrared radiometry is explored in detail. These techniques are analyzed theoretically and experimental data are presented ...

Remote Sensing Application in Oil and Gas Industry

NASA Astrophysics Data System (ADS)

Sizov, Oleg; Aloltsov, Alexander; Rubtsova, Natalia

2014-05-01

The main environmental problems of the Khanty-Mansi Autonomous Okrug (a federal subject of Russia) related to the activities of oil and gas industry (82 active companies which hold 77,000 oil wells). As on the 1st of January 2013 the subject produces more than 50% of all oil in Russia. The principle of environmental responsibility makes it necessary to minimize human impact and ecological impact. One of the most effective tools for environmental monitoring is remote sensing. The main advantages of such approach are: wide coverage of areas of interest, high temporal resolution, precise location, automatic processing, large set of extracted parameters, etc. Authorities of KhMAO are interested in regular detection of the impact on the environment by processing satellite data and plan to increase the coverage from 434.9 to 659.9 square kilometers with resolution not less than 10 m/pixel. Years of experience of our company shows the significant potential to expand the use of such remote sensing data in the solution of environmental problems. The main directions are: monitoring of rational use of associated petroleum gas (detection of all gas flares and volumes of burned gas), monitoring of soil pollution (detection of areas of oil pollution, assess of the extent of pollution, planning of reclamation activities and assessment of their efficiency, detection of potential areas of pipelines corrosion), monitoring of status of sludge pits (inventory of all sludge pits, assessment of their liquidation), monitoring of technogenic impact (detection of changes), upgrading of a geospatial database (topographic map of not less than 1:50000 scale). Implementation of modeling, extrapolation and remote analysis techniques based on satellite images will help to reduce unnecessary costs for instrumental methods. Thus, the introduction of effective remote monitoring technology to the activity of oil and gas companies promotes environmental responsibility of these companies.

a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.

2018-04-01

Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

The ship edge feature detection based on high and low threshold for remote sensing image

NASA Astrophysics Data System (ADS)

Li, Xuan; Li, Shengyang

2018-05-01

In this paper, a method based on high and low threshold is proposed to detect the ship edge feature due to the low accuracy rate caused by the noise. Analyze the relationship between human vision system and the target features, and to determine the ship target by detecting the edge feature. Firstly, using the second-order differential method to enhance the quality of image; Secondly, to improvement the edge operator, we introduction of high and low threshold contrast to enhancement image edge and non-edge points, and the edge as the foreground image, non-edge as a background image using image segmentation to achieve edge detection, and remove the false edges; Finally, the edge features are described based on the result of edge features detection, and determine the ship target. The experimental results show that the proposed method can effectively reduce the number of false edges in edge detection, and has the high accuracy of remote sensing ship edge detection.

Distribution of chlorophyll and harmful algal blooms (HABs): A review on space based studies in the coastal environments of Chinese marginal seas

NASA Astrophysics Data System (ADS)

Wei, Guifeng; Tang, Danling; Wang, Sufen

Monitoring of spatial and temporal distribution of chlorophyll (Chl-a) concentrations in the aquatic milieu is always challenging and often interesting. However, the recent advancements in satellite digital data play a significant role in providing outstanding results for the marine environmental investigations. The present paper is aimed to review ‘remote sensing research in Chinese seas’ within the period of 24 years from 1978 to 2002. Owing to generalized distributional pattern, the Chl-a concentrations are recognized high towards northern Chinese seas than the southern. Moreover, the coastal waters, estuaries, and upwelling zones always exhibit relatively high Chl-a concentrations compared with offshore waters. On the basis of marine Chl-a estimates obtained from satellite and other field measured environmental parameters, we have further discussed on the applications of satellite remote sensing in the fields of harmful algal blooms (HABs), primary production and physical oceanographic currents of the regional seas. Concerned with studies of HABs, satellite remote sensing proved more advantageous than any other conventional methods for large-scale applications. Probably, it may be the only source of authentic information responsible for the evaluation of new research methodologies to detect HABs. At present, studies using remote sensing methods are mostly confined to observe algal bloom occurrences, hence, it is essential to coordinate the mechanism of marine ecological and oceanographic dynamic processes of HABs using satellite remote sensing data with in situ measurements of marine environmental parameters. The satellite remote sensing on marine environment and HABs is believed to have a great improvement with popular application of technology.

Multispectral, hyperspectral, and LiDAR remote sensing and geographic information fusion for improved earthquake response

NASA Astrophysics Data System (ADS)

Kruse, F. A.; Kim, A. M.; Runyon, S. C.; Carlisle, Sarah C.; Clasen, C. C.; Esterline, C. H.; Jalobeanu, A.; Metcalf, J. P.; Basgall, P. L.; Trask, D. M.; Olsen, R. C.

2014-06-01

The Naval Postgraduate School (NPS) Remote Sensing Center (RSC) and research partners have completed a remote sensing pilot project in support of California post-earthquake-event emergency response. The project goals were to dovetail emergency management requirements with remote sensing capabilities to develop prototype map products for improved earthquake response. NPS coordinated with emergency management services and first responders to compile information about essential elements of information (EEI) requirements. A wide variety of remote sensing datasets including multispectral imagery (MSI), hyperspectral imagery (HSI), and LiDAR were assembled by NPS for the purpose of building imagery baseline data; and to demonstrate the use of remote sensing to derive ground surface information for use in planning, conducting, and monitoring post-earthquake emergency response. Worldview-2 data were converted to reflectance, orthorectified, and mosaicked for most of Monterey County; CA. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data acquired at two spatial resolutions were atmospherically corrected and analyzed in conjunction with the MSI data. LiDAR data at point densities from 1.4 pts/m2 to over 40 points/ m2 were analyzed to determine digital surface models. The multimodal data were then used to develop change detection approaches and products and other supporting information. Analysis results from these data along with other geographic information were used to identify and generate multi-tiered products tied to the level of post-event communications infrastructure (internet access + cell, cell only, no internet/cell). Technology transfer of these capabilities to local and state emergency response organizations gives emergency responders new tools in support of post-disaster operational scenarios.

Research on Horizontal Accuracy Method of High Spatial Resolution Remotely Sensed Orthophoto Image

NASA Astrophysics Data System (ADS)

Xu, Y. M.; Zhang, J. X.; Yu, F.; Dong, S.

2018-04-01

At present, in the inspection and acceptance of high spatial resolution remotly sensed orthophoto image, the horizontal accuracy detection is testing and evaluating the accuracy of images, which mostly based on a set of testing points with the same accuracy and reliability. However, it is difficult to get a set of testing points with the same accuracy and reliability in the areas where the field measurement is difficult and the reference data with high accuracy is not enough. So it is difficult to test and evaluate the horizontal accuracy of the orthophoto image. The uncertainty of the horizontal accuracy has become a bottleneck for the application of satellite borne high-resolution remote sensing image and the scope of service expansion. Therefore, this paper proposes a new method to test the horizontal accuracy of orthophoto image. This method using the testing points with different accuracy and reliability. These points' source is high accuracy reference data and field measurement. The new method solves the horizontal accuracy detection of the orthophoto image in the difficult areas and provides the basis for providing reliable orthophoto images to the users.

Land cover mapping after the tsunami event over Nanggroe Aceh Darussalam (NAD) province, Indonesia

NASA Astrophysics Data System (ADS)

Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Alias, A. N.; Mohd. Saleh, N.; Wong, C. J.; Surbakti, M. S.

2008-03-01

Remote sensing offers an important means of detecting and analyzing temporal changes occurring in our landscape. This research used remote sensing to quantify land use/land cover changes at the Nanggroe Aceh Darussalam (Nad) province, Indonesia on a regional scale. The objective of this paper is to assess the changed produced from the analysis of Landsat TM data. A Landsat TM image was used to develop land cover classification map for the 27 March 2005. Four supervised classifications techniques (Maximum Likelihood, Minimum Distance-to- Mean, Parallelepiped and Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier) were performed to the satellite image. Training sites and accuracy assessment were needed for supervised classification techniques. The training sites were established using polygons based on the colour image. High detection accuracy (>80%) and overall Kappa (>0.80) were achieved by the Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier in this study. This preliminary study has produced a promising result. This indicates that land cover mapping can be carried out using remote sensing classification method of the satellite digital imagery.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

The potential of volunteered geographic information to investigate peri-urbanization in the conservation zone of Mexico City.

PubMed

Heider, Katharina; Lopez, Juan Miguel Rodriguez; Scheffran, Jürgen

2018-03-14

Due to the availability of Web 2.0 technologies, volunteered geographic information (VGI) is on the rise. This new type of data is available on many topics and on different scales. Thus, it has become interesting for research. This article deals with the collective potential of VGI and remote sensing to detect peri-urbanization in the conservation zone of Mexico City. On the one hand, remote sensing identifies horizontal urban expansion, and on the other hand, VGI of ecological complaints provides data about informal settlements. This enables the combination of top-down approaches (remote sensing) and bottom-up approaches (ecological complaints). Within the analysis, we identify areas of high urbanization as well as complaint densities and bring them together in a multi-scale analysis using Geographic Information Systems (GIS). Furthermore, we investigate the influence of settlement patterns and main roads on the peri-urbanization process in Mexico City using OpenStreetMap. Peri-urbanization is detected especially in the transition zone between the urban and rural (conservation) area and near main roads as well as settlements.

Detection of the power lines in UAV remote sensed images using spectral-spatial methods.

PubMed

Bhola, Rishav; Krishna, Nandigam Hari; Ramesh, K N; Senthilnath, J; Anand, Gautham

2018-01-15

In this paper, detection of the power lines on images acquired by Unmanned Aerial Vehicle (UAV) based remote sensing is carried out using spectral-spatial methods. Spectral clustering was performed using Kmeans and Expectation Maximization (EM) algorithm to classify the pixels into the power lines and non-power lines. The spectral clustering methods used in this study are parametric in nature, to automate the number of clusters Davies-Bouldin index (DBI) is used. The UAV remote sensed image is clustered into the number of clusters determined by DBI. The k clustered image is merged into 2 clusters (power lines and non-power lines). Further, spatial segmentation was performed using morphological and geometric operations, to eliminate the non-power line regions. In this study, UAV images acquired at different altitudes and angles were analyzed to validate the robustness of the proposed method. It was observed that the EM with spatial segmentation (EM-Seg) performed better than the Kmeans with spatial segmentation (Kmeans-Seg) on most of the UAV images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of remotely sensed land-use information to improve estimates of streamflow characteristics, volume 8. [Maryland, Virginia, and Delaware

NASA Technical Reports Server (NTRS)

Pluhowski, E. J. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Land use data derived from high altitude photography and satellite imagery were studied for 49 basins in Delaware, and eastern Maryland and Virginia. Applying multiple regression techniques to a network of gaging stations monitoring runoff from 39 of the basins, demonstrated that land use data from high altitude photography provided an effective means of significantly improving estimates of stream flow. Forty stream flow characteristic equations for incorporating remotely sensed land use information, were compared with a control set of equations using map derived land cover. Significant improvement was detected in six equations where level 1 data was added and in five equations where level 2 information was utilized. Only four equations were improved significantly using land use data derived from LANDSAT imagery. Significant losses in accuracy due to the use of remotely sensed land use information were detected only in estimates of flood peaks. Losses in accuracy for flood peaks were probably due to land cover changes associated with temporal differences among the primary land use data sources.

Clever eye algorithm for target detection of remote sensing imagery

NASA Astrophysics Data System (ADS)

Geng, Xiurui; Ji, Luyan; Sun, Kang

2016-04-01

Target detection algorithms for hyperspectral remote sensing imagery, such as the two most commonly used remote sensing detection algorithms, the constrained energy minimization (CEM) and matched filter (MF), can usually be attributed to the inner product between a weight filter (or detector) and a pixel vector. CEM and MF have the same expression except that MF requires data centralization first. However, this difference leads to a difference in the target detection results. That is to say, the selection of the data origin could directly affect the performance of the detector. Therefore, does there exist another data origin other than the zero and mean-vector points for a better target detection performance? This is a very meaningful issue in the field of target detection, but it has not been paid enough attention yet. In this study, we propose a novel objective function by introducing the data origin as another variable, and the solution of the function is corresponding to the data origin with the minimal output energy. The process of finding the optimal solution can be vividly regarded as a clever eye automatically searching the best observing position and direction in the feature space, which corresponds to the largest separation between the target and background. Therefore, this new algorithm is referred to as the clever eye algorithm (CE). Based on the Sherman-Morrison formula and the gradient ascent method, CE could derive the optimal target detection result in terms of energy. Experiments with both synthetic and real hyperspectral data have verified the effectiveness of our method.

Technology study of quantum remote sensing imaging

NASA Astrophysics Data System (ADS)

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

2016-02-01

According to remote sensing science and technology development and application requirements, quantum remote sensing is proposed. First on the background of quantum remote sensing, quantum remote sensing theory, information mechanism, imaging experiments and prototype principle prototype research situation, related research at home and abroad are briefly introduced. Then we expounds compress operator of the quantum remote sensing radiation field and the basic principles of single-mode compression operator, quantum quantum light field of remote sensing image compression experiment preparation and optical imaging, the quantum remote sensing imaging principle prototype, Quantum remote sensing spaceborne active imaging technology is brought forward, mainly including quantum remote sensing spaceborne active imaging system composition and working principle, preparation and injection compression light active imaging device and quantum noise amplification device. Finally, the summary of quantum remote sensing research in the past 15 years work and future development are introduced.

Use of change detection in assessing development plans - A Philippine example. [aircraft/Landsat remote sensing information system for regional planning

NASA Technical Reports Server (NTRS)

Coiner, J. C.; Bruce, R. C.

1978-01-01

An aircraft/Landsat change-detection study conducted 1948-1972 on Marinduque Province, Republic of the Philippines, is discussed, and a procedure using both remote sensing and information systems for collection, spatial analysis, and display of periodic data is described. Each of the 4,008 25-hectare cells representing Marinduque were observed, and changes in and between variables were measured and tested using nonparametric statistics to determine the effect of specific land cover changes. Procedures using Landsat data to obtain a more continuous updating of the data base are considered. The system permits storage and comparison of historical and current data.

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

NASA Astrophysics Data System (ADS)

Walther, Christian; Frei, Michaela

2017-04-01

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

Factors affecting the identification of phytoplankton groups by means of remote sensing

NASA Technical Reports Server (NTRS)

Weaver, Ellen C.; Wrigley, Robert

1994-01-01

A literature review was conducted on the state of the art as to whether or not information about communities and populations of phytoplankton in aquatic environments can be derived by remote sensing. In order to arrive at this goal, the spectral characteristics of various types of phytoplankton were compared to determine first, whether there are characteristic differences in pigmentation among the types and second, whether such differences can be detected remotely. In addition to the literature review, an extensive, but not exhaustive, annotated bibliography of the literature that bears on these questions is included as an appendix, since it constitutes a convenient resource for anyone wishing an overview of the field of ocean color. The review found some progress has already been made in remote sensing of assemblages such as coccolithophorid blooms, mats of cyanobacteria, and red tides. Much more information about the composition of algal groups is potentially available by remote sensing particularly in water bodies having higher phytoplankton concentrations, but it will be necessary to develop the remote sensing techniques required for working in so-called Case 2 waters. It is also clear that none of the satellite sensors presently available or soon to be launched is ideal from the point of view of what we might wish to know; it would seem wise to pursue instruments with the planned characteristics of the Moderate Resolution Imaging Spectrometer-Tilt (MODIS-T) or Medium Resolution Imaging Spectrometer (MERIS).

Buildings Change Detection Based on Shape Matching for Multi-Resolution Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Abdessetar, M.; Zhong, Y.

2017-09-01

Buildings change detection has the ability to quantify the temporal effect, on urban area, for urban evolution study or damage assessment in disaster cases. In this context, changes analysis might involve the utilization of the available satellite images with different resolutions for quick responses. In this paper, to avoid using traditional method with image resampling outcomes and salt-pepper effect, building change detection based on shape matching is proposed for multi-resolution remote sensing images. Since the object's shape can be extracted from remote sensing imagery and the shapes of corresponding objects in multi-scale images are similar, it is practical for detecting buildings changes in multi-scale imagery using shape analysis. Therefore, the proposed methodology can deal with different pixel size for identifying new and demolished buildings in urban area using geometric properties of objects of interest. After rectifying the desired multi-dates and multi-resolutions images, by image to image registration with optimal RMS value, objects based image classification is performed to extract buildings shape from the images. Next, Centroid-Coincident Matching is conducted, on the extracted building shapes, based on the Euclidean distance measurement between shapes centroid (from shape T0 to shape T1 and vice versa), in order to define corresponding building objects. Then, New and Demolished buildings are identified based on the obtained distances those are greater than RMS value (No match in the same location).

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

A survey of natural aggregate properties and characteristics important in remote sensing and airborne geophysics

USGS Publications Warehouse

Knepper, D.H.; Langer, W.H.; Miller, S.

1995-01-01

Natural aggregate is vital to the construction industry. Although natural aggregate is a high volume/low value commodity that is abundant, new sources are becoming increasingly difficult to find and develop because of rigid industry specifications, political considerations, development and transportation costs, and environmental concerns. There are two primary sources of natural aggregate: (1) exposed or near-surface bedrock that can be crushed, and (2) deposits of sand and gravel. Remote sensing and airborne geophysics detect surface and near-surface phenomena, and may be useful for detecting and mapping potential aggregate sources; however, before a methodology for applying these techniques can be developed, it is necessary to understand the type, distribution, physical properties, and characteristics of natural aggregate deposits. The distribution of potential aggregate sources is closely tied to local geologic history. Conventional exploration for natural aggregate deposits has been largely a ground-based operation, although aerial photographs and topographic maps have been extensively used to target possible deposits. Today, the exploration process also considers factors such as the availability of the land, space and water supply for processing, political and environmental factors, and distance from the market; exploration and planning cannot be separated. There are many physical properties and characteristics by which to judge aggregate material for specific applications; most of these properties and characteristics pertain only to individual aggregate particles. The application of remote sensing and airborne geophysical measurements to detecting and mapping potential aggregate sources, however, is based on intrinsic bulk physical properties and extrinsic characteristics of the deposits that can be directly measured, mathematically derived from measurement, or interpreted with remote sensing and geophysical data. ?? 1995 Oxford UniversityPress.

Petroleum exploration in Africa from space

NASA Astrophysics Data System (ADS)

Gianinetto, Marco; Frassy, Federico; Aiello, Martina; Rota Nodari, Francesco

2017-10-01

Hydrocarbons are nonrenewable resources but today they are the cheaper and easier energy we have access and will remain the main source of energy for this century. Nevertheless, their exploration is extremely high-risk, very expensive and time consuming. In this context, satellite technologies for Earth observation can play a fundamental role by making hydrocarbon exploration more efficient, economical and much more eco-friendly. Complementary to traditional geophysical methods such as gravity and magnetic (gravmag) surveys, satellite remote sensing can be used to detect onshore long-term biochemical and geochemical alterations on the environment produced by invisible small fluxes of light hydrocarbons migrating from the underground deposits to the surface, known as microseepage effect. This paper describes two case studies: one in South Sudan and another in Mozambique. Results show how remote sensing is a powerful technology for detecting active petroleum systems, thus supporting hydrocarbon exploration in remote or hardly accessible areas and without the need of any exploration license.

DETECTION AND IDENTIFICATION OF TOXIC AIR POLLUTANTS USING FIELD PORTABLE AND AIRBORNE REMOTE IMAGING SYSTEMS

EPA Science Inventory

Remote sensing technologies are a class of instrument and sensor systems that include laser imageries, imaging spectrometers, and visible to thermal infrared cameras. These systems have been successfully used for gas phase chemical compound identification in a variety of field e...

Recent Progress in the Remote Detection of Vapours and Gaseous Pollutants.

ERIC Educational Resources Information Center

Moffat, A. J.; And Others

Work has been continuing on the correlation spectrometry techniques described at previous remote sensing symposiums. Advances in the techniques are described which enable accurate quantitative measurements of diffused atmospheric gases to be made using controlled light sources, accurate quantitative measurements of gas clouds relative to…

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

NASA Astrophysics Data System (ADS)

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 obtained to determine SST anomalies associated with surfaced wastewater at a higher resolution than MODIS. SAR data from ALOS-2, and Sentinel-1 were used to identify surfaced wastewater plumes. In situ drifter, chl-a, SST, and hyperspectral water quality measurements from the diversion were also compared with those obtained by satellite sensors.

Laser Induced Fluorescence (LIF) as a Remote Sensing Tool: A Review

NASA Technical Reports Server (NTRS)

Chappelle, E. W.; Kim, M. S.; Mulchi, C. L.; Daughtry, C. S. T.; McMurtrey, J.; Corp, L.

1998-01-01

Vegetational changes are primary indicators of the present and future ecological status of the globe. These are changes which not only impact upon the primary productivity, but the total of the biogeochemical processes occurring on the planet. The impacts of global climatic and other environmental changes on vegetation must be monitored by some means in order to develop models which will allow us to predict long term effects. Large scale monitoring is now possible only with remote sensing systems, primarily passive reflectance, obtained by the use of satellite and aircraft platforms. However, passive reflectance techniques at this time are limited in their ability to detect subtle changes in the concentration and oxidation states of the many compounds involved in the light reactions of photosynthesis. Knowledge of these changes we consider to be fundamental in the remote assessment of both the rate and efficiency of photosynthesis and also the early detection of stress damage. The above factors pointed to the desirability of a sensing technique with the sensitivity and specificity necessary for detecting and quantifying those biological entities involved in photosynthesis. Another optical technique for vegetation monitoring is fluorescence. Previously, the lack of adequate excitation light sources and detector technologies have limited the use of fluorescence on intact plant leaves in the field. It is only recently with the advent of lasers with short pulse duration and advanced detector technologies that fluorescence measurements in the remote mode have become possible in the presence of ambient light.

Assessment of landscape change associated with tropical cyclone phenomena in Baja California Sur, Mexico, using satellite remote sensing

NASA Astrophysics Data System (ADS)

Martinez-Gutierrez, Genaro

Baja California Sur (Mexico), as well as mainland Mexico, is affected by tropical cyclone storms, which originate in the eastern north Pacific. Historical records show that Baja has been damaged by intense summer storms. An arid to semiarid climate characterizes the study area, where precipitation mainly occurs during the summer and winter seasons. Natural and anthropogenic changes have impacted the landscape of southern Baja. The present research documents the effects of tropical storms over the southern region of Baja California for a period of approximately twenty-six years. The goal of the research is to demonstrate how remote sensing can be used to detect the important effects of tropical storms including: (a) evaluation of change detection algorithms, and (b) delineating changes to the landscape including coastal modification, fluvial erosion and deposition, vegetation change, river avulsion using change detection algorithms. Digital image processing methods with temporal Landsat satellite remotely sensed data from the North America Landscape Characterization archive (NALC), Thematic Mapper (TM), and Enhanced Thematic Mapper (ETM) images were used to document the landscape change. Two image processing methods were tested including Image differencing (ID), and Principal Component Analysis (PCA). Landscape changes identified with the NALC archive and TM images showed that the major changes included a rapid change of land use in the towns of San Jose del Cabo and Cabo San Lucas between 1973 and 1986. The features detected using the algorithms included flood deposits within the channels of active streams, erosion banks, and new channels caused by channel avulsion. Despite the 19 year period covered by the NALC data and approximately 10 year intervals between acquisition dates, there were changed features that could be identified in the images. The TM images showed that flooding from Hurricane Isis (1998) produced new large deposits within the stream channels. This research has shown that remote sensing based change detection can delineate the effects of flooding on the landscape at scales down to the nominal resolution of the sensor. These findings indicate that many other applications for change detection are both viable and important. These include disaster response, flood hazard planning, geomorphic studies, water supply management in deserts.

NASA/GSFC Research Activities for the Global Ocean Carbon Cycle: A Prospectus for the 21st Century

NASA Technical Reports Server (NTRS)

Gregg, W. W.; Behrenfield, M. J.; Hoge, F. E.; Esaias, W. E.; Huang, N. E.; Long, S. R.; McClain, C. R.

2000-01-01

There are increasing concerns that anthropogenic inputs of carbon dioxide into the Earth system have the potential for climate change. In response to these concerns, the GSFC Laboratory for Hydrospheric Processes has formed the Ocean Carbon Science Team (OCST) to contribute to greater understanding of the global ocean carbon cycle. The overall goals of the OCST are to: 1) detect changes in biological components of the ocean carbon cycle through remote sensing of biooptical properties, 2) refine understanding of ocean carbon uptake and sequestration through application of basic research results, new satellite algorithms, and improved model parameterizations, 3) develop and implement new sensors providing critical missing environmental information related to the oceanic carbon cycle and the flux of CO2 across the air-sea interface. The specific objectives of the OCST are to: 1) establish a 20-year time series of ocean color, 2) develop new remote sensing technologies, 3) validate ocean remote sensing observations, 4) conduct ocean carbon cycle scientific investigations directly related to remote sensing data, emphasizing physiological, empirical and coupled physical/biological models, satellite algorithm development and improvement, and analysis of satellite data sets. These research and mission objectives are intended to improve our understanding of global ocean carbon cycling and contribute to national goals by maximizing the use of remote sensing data.

Food, water, and fault lines: Remote sensing opportunities for earthquake-response management of agricultural water.

PubMed

Rodriguez, Jenna; Ustin, Susan; Sandoval-Solis, Samuel; O'Geen, Anthony Toby

2016-09-15

Earthquakes often cause destructive and unpredictable changes that can affect local hydrology (e.g. groundwater elevation or reduction) and thus disrupt land uses and human activities. Prolific agricultural regions overlie seismically active areas, emphasizing the importance to improve our understanding and monitoring of hydrologic and agricultural systems following a seismic event. A thorough data collection is necessary for adequate post-earthquake crop management response; however, the large spatial extent of earthquake's impact makes challenging the collection of robust data sets for identifying locations and magnitude of these impacts. Observing hydrologic responses to earthquakes is not a novel concept, yet there is a lack of methods and tools for assessing earthquake's impacts upon the regional hydrology and agricultural systems. The objective of this paper is to describe how remote sensing imagery, methods and tools allow detecting crop responses and damage incurred after earthquakes because a change in the regional hydrology. Many remote sensing datasets are long archived with extensive coverage and with well-documented methods to assess plant-water relations. We thus connect remote sensing of plant water relations to its utility in agriculture using a post-earthquake agrohydrologic remote sensing (PEARS) framework; specifically in agro-hydrologic relationships associated with recent earthquake events that will lead to improved water management. Copyright © 2016 Elsevier B.V. All rights reserved.

Remote sensing techniques in monitoring areas affected by forest fire

NASA Astrophysics Data System (ADS)

Karagianni, Aikaterini Ch.; Lazaridou, Maria A.

2017-09-01

Forest fire is a part of nature playing a key role in shaping ecosystems. However, fire's environmental impacts can be significant, affecting wildlife habitat and timber, human settlements, man-made technical constructions and various networks (road, power networks) and polluting the air with emissions harmful to human health. Furthermore, fire's effect on the landscape may be long-lasting. Monitoring the development of a fire occurs as an important aspect at the management of natural hazards in general. Among the used methods for monitoring, satellite data and remote sensing techniques can be proven of particular importance. Satellite remote sensing offers a useful tool for forest fire detection, monitoring, management and damage assessment. Especially for fire scars detection and monitoring, satellite data derived from Landsat 8 can be a useful research tool. This paper includes critical considerations of the above and concerns in particular an example of the Greek area (Thasos Island). This specific area was hit by fires several times in the past and recently as well (September 2016). Landsat 8 satellite data are being used (pre and post fire imagery) and digital image processing techniques are applied (enhancement techniques, calculation of various indices) for fire scars detection. Visual interpretation of the example area affected by the fires is also being done, contributing to the overall study.

A high throughput geocomputing system for remote sensing quantitative retrieval and a case study

NASA Astrophysics Data System (ADS)

Xue, Yong; Chen, Ziqiang; Xu, Hui; Ai, Jianwen; Jiang, Shuzheng; Li, Yingjie; Wang, Ying; Guang, Jie; Mei, Linlu; Jiao, Xijuan; He, Xingwei; Hou, Tingting

2011-12-01

The quality and accuracy of remote sensing instruments have been improved significantly, however, rapid processing of large-scale remote sensing data becomes the bottleneck for remote sensing quantitative retrieval applications. The remote sensing quantitative retrieval is a data-intensive computation application, which is one of the research issues of high throughput computation. The remote sensing quantitative retrieval Grid workflow is a high-level core component of remote sensing Grid, which is used to support the modeling, reconstruction and implementation of large-scale complex applications of remote sensing science. In this paper, we intend to study middleware components of the remote sensing Grid - the dynamic Grid workflow based on the remote sensing quantitative retrieval application on Grid platform. We designed a novel architecture for the remote sensing Grid workflow. According to this architecture, we constructed the Remote Sensing Information Service Grid Node (RSSN) with Condor. We developed a graphic user interface (GUI) tools to compose remote sensing processing Grid workflows, and took the aerosol optical depth (AOD) retrieval as an example. The case study showed that significant improvement in the system performance could be achieved with this implementation. The results also give a perspective on the potential of applying Grid workflow practices to remote sensing quantitative retrieval problems using commodity class PCs.

Trace gas detection in hyperspectral imagery using the wavelet packet subspace

NASA Astrophysics Data System (ADS)

Salvador, Mark A. Z.

This dissertation describes research into a new remote sensing method to detect trace gases in hyperspectral and ultra-spectral data. This new method is based on the wavelet packet transform. It attempts to improve both the computational tractability and the detection of trace gases in airborne and spaceborne spectral imagery. Atmospheric trace gas research supports various Earth science disciplines to include climatology, vulcanology, pollution monitoring, natural disasters, and intelligence and military applications. Hyperspectral and ultra-spectral data significantly increases the data glut of existing Earth science data sets. Spaceborne spectral data in particular significantly increases spectral resolution while performing daily global collections of the earth. Application of the wavelet packet transform to the spectral space of hyperspectral and ultra-spectral imagery data potentially improves remote sensing detection algorithms. It also facilities the parallelization of these methods for high performance computing. This research seeks two science goals, (1) developing a new spectral imagery detection algorithm, and (2) facilitating the parallelization of trace gas detection in spectral imagery data.

Extracting Forest Canopy Characteristics from Remote Sensing Imagery: Implications for Sentinel-2 Mission

NASA Astrophysics Data System (ADS)

Gholizadeh, Asa; Kopaekova, Veronika; Rogass, Christian; Mielke, Christian; Misurec, Jan

2016-08-01

Systematic quantification and monitoring of forest biophysical and biochemical variables is required to assess the response of ecosystems to climate change. Remote sensing has been introduced as a time and cost- efficient way to carry out large scale monitoring of vegetation parameters. Red-Edge Position (REP) is a hyperspectrally detectable parameter which is sensitive to vegetation Chl. In the current study, REP was modelled for the Norway spruce forest canopy resampled to HyMap and Sentinel-2 spectral resolution as well as calculated from the real HyMap and Sentinel-2 simulated data. Different REP extraction methods (4PLI, PF, LE, 4PLIH and 4PLIS) were assessed. The study showed the way for effective utilization of the forthcoming hyper and superspectral remote sensing sensors from orbit to monitor vegetation attributes.

The promise of remote sensing in the atmospheric sciences

NASA Technical Reports Server (NTRS)

Atlas, D.

1981-01-01

The applications and advances in remote sensing technology for weather prediction, mesoscale meteorology, severe storms, and climate studies are discussed. Doppler radar permits tracking of the three-dimensional field of motion within storms, thereby increasing the accuracy of convective storm modeling. Single Doppler units are also employed for detecting mesoscale storm vortices and tornado vortex signatures with lead times of 30 min. Clear air radar in pulsed and high resolution FM-CW forms reveals boundary layer convection, Kelvin-Helmoltz waves, shear layer turbulence, and wave motions. Lidar is successfully employed for stratospheric aerosol measurements, while Doppler lidar provides data on winds from the ground and can be based in space. Sodar is useful for determining the structure of the PBL. Details and techniques of satellite-based remote sensing are presented, and results from the GWE and FGGE experiments are discussed.

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

NASA Technical Reports Server (NTRS)

King, Michael; Reehorst, Andrew; Serke, Dave

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Research of building information extraction and evaluation based on high-resolution remote-sensing imagery

NASA Astrophysics Data System (ADS)

Cao, Qiong; Gu, Lingjia; Ren, Ruizhi; Wang, Lang

2016-09-01

Building extraction currently is important in the application of high-resolution remote sensing imagery. At present, quite a few algorithms are available for detecting building information, however, most of them still have some obvious disadvantages, such as the ignorance of spectral information, the contradiction between extraction rate and extraction accuracy. The purpose of this research is to develop an effective method to detect building information for Chinese GF-1 data. Firstly, the image preprocessing technique is used to normalize the image and image enhancement is used to highlight the useful information in the image. Secondly, multi-spectral information is analyzed. Subsequently, an improved morphological building index (IMBI) based on remote sensing imagery is proposed to get the candidate building objects. Furthermore, in order to refine building objects and further remove false objects, the post-processing (e.g., the shape features, the vegetation index and the water index) is employed. To validate the effectiveness of the proposed algorithm, the omission errors (OE), commission errors (CE), the overall accuracy (OA) and Kappa are used at final. The proposed method can not only effectively use spectral information and other basic features, but also avoid extracting excessive interference details from high-resolution remote sensing images. Compared to the original MBI algorithm, the proposed method reduces the OE by 33.14% .At the same time, the Kappa increase by 16.09%. In experiments, IMBI achieved satisfactory results and outperformed other algorithms in terms of both accuracies and visual inspection

Robust feature matching via support-line voting and affine-invariant ratios

NASA Astrophysics Data System (ADS)

Li, Jiayuan; Hu, Qingwu; Ai, Mingyao; Zhong, Ruofei

2017-10-01

Robust image matching is crucial for many applications of remote sensing and photogrammetry, such as image fusion, image registration, and change detection. In this paper, we propose a robust feature matching method based on support-line voting and affine-invariant ratios. We first use popular feature matching algorithms, such as SIFT, to obtain a set of initial matches. A support-line descriptor based on multiple adaptive binning gradient histograms is subsequently applied in the support-line voting stage to filter outliers. In addition, we use affine-invariant ratios computed by a two-line structure to refine the matching results and estimate the local affine transformation. The local affine model is more robust to distortions caused by elevation differences than the global affine transformation, especially for high-resolution remote sensing images and UAV images. Thus, the proposed method is suitable for both rigid and non-rigid image matching problems. Finally, we extract as many high-precision correspondences as possible based on the local affine extension and build a grid-wise affine model for remote sensing image registration. We compare the proposed method with six state-of-the-art algorithms on several data sets and show that our method significantly outperforms the other methods. The proposed method achieves 94.46% average precision on 15 challenging remote sensing image pairs, while the second-best method, RANSAC, only achieves 70.3%. In addition, the number of detected correct matches of the proposed method is approximately four times the number of initial SIFT matches.

Passive remote sensing of large-scale methane emissions from Oil Fields in California's San Joaquin Valley and validation by airborne in-situ measurements - Results from COMEX

NASA Astrophysics Data System (ADS)

Gerilowski, Konstantin; Krautwurst, Sven; Thompson, David R.; Thorpe, Andrew K.; Kolyer, Richard W.; Jonsson, Haflidi; Krings, Thomas; Frankenberg, Christian; Horstjann, Markus; Leifer, Ira; Eastwood, Michael; Green, Robert O.; Vigil, Sam; Fladeland, Matthew; Schüttemeyer, Dirk; Burrows, John P.; Bovensmann, Heinrich

2016-04-01

The CO2 and MEthane EXperiment (COMEX) was a NASA and ESA funded campaign in support of the HyspIRI and CarbonSat mission definition activities. As a part of this effort, seven flights were performed between June 3 and September 4, 2014 with the Methane Airborne MAPper (MAMAP) remote sensing instrument (operated by the University of Bremen in cooperation with the German Research Centre for Geosciences - GFZ) over the Kern River, Kern Front, and Poso Creek Oil Fields located in California's San Joaquin Valley. MAMAP was installed for the flights aboard the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft, together with: a Picarro fast in-situ greenhouse gas (GHG) analyzer operated by the NASA Ames Research Center, ARC; a 5-hole turbulence probe; and an atmospheric measurement package operated by CIRPAS measuring aerosols, temperature, dew-point, and other atmospheric parameters. Three of the flights were accompanied by the Next Generation Airborne Visual InfraRed Imaging Spectrometer (AVIRIS-NG), operated by the Jet Propulsion Laboratory (JPL), California Institute of Technology, installed aboard a second Twin Otter aircraft. Large-scale, high-concentration CH4 plumes were detected by the MAMAP instrument over the fields and tracked over several kilometers. The spatial distribution of the MAMAP observed plumes was compared to high spatial resolution CH4 anomaly maps derived by AVIRIS-NG imaging spectroscopy data. Remote sensing data collected by MAMAP was used to infer CH4 emission rates and their distributions over the three fields. Aggregated emission estimates for the three fields were compared to aggregated emissions inferred by subsequent airborne in-situ validation measurements collected by the Picarro instrument. Comparison of remote sensing and in-situ flux estimates will be presented, demonstrating the ability of airborne remote sensing data to provide accurate emission estimates for concentrations above the detection limit. This opens new applications of airborne atmospheric remote sensing in the area of anthropogenic top-down emission monitoring as well as for atmospheric CH4 leakage monitoring during accidents like the Elgin blow-out (March 2012) in the North Sea or the recent Aliso Canyon gas leak incident (2015/2016) in California.

Change detection in a time series of polarimetric SAR data by an omnibus test statistic and its factorization (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nielsen, Allan A.; Conradsen, Knut; Skriver, Henning

2016-10-01

Test statistics for comparison of real (as opposed to complex) variance-covariance matrices exist in the statistics literature [1]. In earlier publications we have described a test statistic for the equality of two variance-covariance matrices following the complex Wishart distribution with an associated p-value [2]. We showed their application to bitemporal change detection and to edge detection [3] in multilook, polarimetric synthetic aperture radar (SAR) data in the covariance matrix representation [4]. The test statistic and the associated p-value is described in [5] also. In [6] we focussed on the block-diagonal case, we elaborated on some computer implementation issues, and we gave examples on the application to change detection in both full and dual polarization bitemporal, bifrequency, multilook SAR data. In [7] we described an omnibus test statistic Q for the equality of k variance-covariance matrices following the complex Wishart distribution. We also described a factorization of Q = R2 R3 … Rk where Q and Rj determine if and when a difference occurs. Additionally, we gave p-values for Q and Rj. Finally, we demonstrated the use of Q and Rj and the p-values to change detection in truly multitemporal, full polarization SAR data. Here we illustrate the methods by means of airborne L-band SAR data (EMISAR) [8,9]. The methods may be applied to other polarimetric SAR data also such as data from Sentinel-1, COSMO-SkyMed, TerraSAR-X, ALOS, and RadarSat-2 and also to single-pol data. The account given here closely follows that given our recent IEEE TGRS paper [7]. Selected References [1] Anderson, T. W., An Introduction to Multivariate Statistical Analysis, John Wiley, New York, third ed. (2003). [2] Conradsen, K., Nielsen, A. A., Schou, J., and Skriver, H., "A test statistic in the complex Wishart distribution and its application to change detection in polarimetric SAR data," IEEE Transactions on Geoscience and Remote Sensing 41(1): 4-19, 2003. [3] Schou, J., Skriver, H., Nielsen, A. A., and Conradsen, K., "CFAR edge detector for polarimetric SAR images," IEEE Transactions on Geoscience and Remote Sensing 41(1): 20-32, 2003. [4] van Zyl, J. J. and Ulaby, F. T., "Scattering matrix representation for simple targets," in Radar Polarimetry for Geoscience Applications, Ulaby, F. T. and Elachi, C., eds., Artech, Norwood, MA (1990). [5] Canty, M. J., Image Analysis, Classification and Change Detection in Remote Sensing,with Algorithms for ENVI/IDL and Python, Taylor & Francis, CRC Press, third revised ed. (2014). [6] Nielsen, A. A., Conradsen, K., and Skriver, H., "Change detection in full and dual polarization, single- and multi-frequency SAR data," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8(8): 4041-4048, 2015. [7] Conradsen, K., Nielsen, A. A., and Skriver, H., "Determining the points of change in time series of polarimetric SAR data," IEEE Transactions on Geoscience and Remote Sensing 54(5), 3007-3024, 2016. [9] Christensen, E. L., Skou, N., Dall, J., Woelders, K., rgensen, J. H. J., Granholm, J., and Madsen, S. N., "EMISAR: An absolutely calibrated polarimetric L- and C-band SAR," IEEE Transactions on Geoscience and Remote Sensing 36: 1852-1865 (1998).

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

NASA Technical Reports Server (NTRS)

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 unknown features. All of these applications are pertinent to the goals of site discovery and assessment in cultural resource management.

Effects of Regolith Properties on UV/VIS Spectra and Implications for Lunar Remote Sensing

NASA Astrophysics Data System (ADS)

Coman, Ecaterina Oana

Lunar regolith chemistry, mineralogy, various maturation factors, and grain size dominate the reflectance of the lunar surface at ultraviolet (UV) to visible (VIS) wavelengths. These regolith properties leave unique fingerprints on reflectance spectra in the form of varied spectral shapes, reflectance intensity values, and absorption bands. With the addition of returned lunar soils from the Apollo and Luna missions as ground truth, these spectral fingerprints can be used to derive maps of global lunar chemistry or mineralogy to analyze the range of basalt types on the Moon, their spatial distribution, and source regions for clues to lunar formation history and evolution. The Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) is the first lunar imager to detect bands at UV wavelengths (321 and 360 nm) in addition to visible bands (415, 566, 604, 643, and 689 nm). This dissertation uses a combination of laboratory and remote sensing studies to examine the relation between TiO2 concentration and WAC UV/VIS spectral ratios and to test the effects of variations in lunar chemistry, mineralogy, and soil maturity on ultraviolet and visible wavelength reflectance. Chapter 1 presents an introduction to the dissertation that includes some background in lunar mineralogy and remote sensing. Chapter 2 covers coordinated analyses of returned lunar soils using UV-VIS spectroscopy, X-ray diffraction, and micro X-ray fluorescence. Chapter 3 contains comparisons of local and global remote sensing observations of the Moon using LROC WAC and Clementine UVVIS TiO2 detection algorithms and Lunar Prospector (LP) Gamma Ray Spectrometer (GRS)-derived FeO and TiO2 concentrations. While the data shows effects from maturity and FeO on the UV/VIS detection algorithm, a UV/VIS relationship remains a simple yet accurate method for TiO2 detection on the Moon.

Applications of Remote Sensing to Emergency Management.

DTIC Science & Technology

1980-02-15

Contents: Foundations of Remote Sensing : Data Acquisition and Interpretation; Availability of Remote Sensing Technology for Disaster Response...Imaging Systems, Current and Near Future Satellite and Aircraft Remote Sensing Systems; Utilization of Remote Sensing in Disaster Response: Categories of...Disasters, Phases of Monitoring Activities; Recommendations for Utilization of Remote Sensing Technology in Disaster Response; Selected Reading List.

Evaluation of harmonic direction-finding systems for detecting locomotor activity

USGS Publications Warehouse

Boyarski, V.L.; Rodda, G.H.; Savidge, J.A.

2007-01-01

We conducted a physical simulation experiment to test the efficacy of harmonic direction finding for remotely detecting locomotor activity in animals. The ability to remotely detect movement helps to avoid disturbing natural movement behavior. Remote detection implies that the observer can sense only a change in signal bearing. In our simulated movements, small changes in bearing (<5.7??) were routinely undetectable. Detectability improved progressively with the size of the simulated animal movement. The average (??SD) of reflector tag movements correctly detected for 5 observers was 93.9 ?? 12.8% when the tag was moved ???11.5??; most observers correctly detected tag movements ???20.1??. Given our data, one can assess whether the technique will be effective for detecting movements at an observation distance appropriate for the study organism. We recommend that both habitat and behavior of the organism be taken into consideration when contemplating use of this technique for detecting locomotion.

An AdaBoost Based Approach to Automatic Classification and Detection of Buildings Footprints, Vegetation Areas and Roads from Satellite Images

NASA Astrophysics Data System (ADS)

Gonulalan, Cansu

In recent years, there has been an increasing demand for applications to monitor the targets related to land-use, using remote sensing images. Advances in remote sensing satellites give rise to the research in this area. Many applications ranging from urban growth planning to homeland security have already used the algorithms for automated object recognition from remote sensing imagery. However, they have still problems such as low accuracy on detection of targets, specific algorithms for a specific area etc. In this thesis, we focus on an automatic approach to classify and detect building foot-prints, road networks and vegetation areas. The automatic interpretation of visual data is a comprehensive task in computer vision field. The machine learning approaches improve the capability of classification in an intelligent way. We propose a method, which has high accuracy on detection and classification. The multi class classification is developed for detecting multiple objects. We present an AdaBoost-based approach along with the supervised learning algorithm. The combi- nation of AdaBoost with "Attentional Cascade" is adopted from Viola and Jones [1]. This combination decreases the computation time and gives opportunity to real time applications. For the feature extraction step, our contribution is to combine Haar-like features that include corner, rectangle and Gabor. Among all features, AdaBoost selects only critical features and generates in extremely efficient cascade structured classifier. Finally, we present and evaluate our experimental results. The overall system is tested and high performance of detection is achieved. The precision rate of the final multi-class classifier is over 98%.

Vasu Kilaru

EPA Pesticide Factsheets

Vasu Kilaru's expertise is in Geographic Information Systems, Spatial Analysis, and satellite remote sensing particularly with respect to trying to detect ground-level fine particles using space borne instruments.

Land use mapping and change detection using ERTS imagery in Montgomery County, Alabama

NASA Technical Reports Server (NTRS)

Wilms, R. P.

1973-01-01

The feasibility of using remotely sensed data from ERTS-1 for mapping land use and detecting land use change was investigated. Land use information was gathered from 1964 air photo mosaics and from 1972 ERTS data. The 1964 data provided the basis for comparison with ERTS-1 imagery. From this comparison, urban sprawl was quite evident for the city of Montgomery. A significant trend from forestland to agricultural was also discovered. The development of main traffic arteries between 1964 and 1972 was a vital factor in the development of some of the urban centers. Even though certain problems in interpreting and correlating land use data from ERTS imagery were encountered, it has been demonstrated that remotely sensed data from ERTS is useful for inventorying land use and detecting land use change.

Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid

PubMed Central

Byambasuren, Bat-erdene; Kim, Donghan; Oyun-Erdene, Mandakh; Bold, Chinguun; Yura, Jargalbaatar

2016-01-01

Smart sensing and power line tracking is very important in a smart grid system. Illegal electricity usage can be detected by remote current measurement on overhead power lines using an inspection robot. There is a need for accurate detection methods of illegal electricity usage. Stable and correct power line tracking is a very prominent issue. In order to correctly track and make accurate measurements, the swing path of a power line should be previously fitted and predicted by a mathematical function using an inspection robot. After this, the remote inspection robot can follow the power line and measure the current. This paper presents a new power line tracking method using parabolic and circle fitting algorithms for illegal electricity detection. We demonstrate the effectiveness of the proposed tracking method by simulation and experimental results. PMID:26907274

Inspection Robot Based Mobile Sensing and Power Line Tracking for Smart Grid.

PubMed

Byambasuren, Bat-Erdene; Kim, Donghan; Oyun-Erdene, Mandakh; Bold, Chinguun; Yura, Jargalbaatar

2016-02-19

Smart sensing and power line tracking is very important in a smart grid system. Illegal electricity usage can be detected by remote current measurement on overhead power lines using an inspection robot. There is a need for accurate detection methods of illegal electricity usage. Stable and correct power line tracking is a very prominent issue. In order to correctly track and make accurate measurements, the swing path of a power line should be previously fitted and predicted by a mathematical function using an inspection robot. After this, the remote inspection robot can follow the power line and measure the current. This paper presents a new power line tracking method using parabolic and circle fitting algorithms for illegal electricity detection. We demonstrate the effectiveness of the proposed tracking method by simulation and experimental results.

Detection of reflecting surfaces by a statistical model

NASA Astrophysics Data System (ADS)

He, Qiang; Chu, Chee-Hung H.

2009-02-01

Remote sensing is widely used assess the destruction from natural disasters and to plan relief and recovery operations. How to automatically extract useful features and segment interesting objects from digital images, including remote sensing imagery, becomes a critical task for image understanding. Unfortunately, current research on automated feature extraction is ignorant of contextual information. As a result, the fidelity of populating attributes corresponding to interesting features and objects cannot be satisfied. In this paper, we present an exploration on meaningful object extraction integrating reflecting surfaces. Detection of specular reflecting surfaces can be useful in target identification and then can be applied to environmental monitoring, disaster prediction and analysis, military, and counter-terrorism. Our method is based on a statistical model to capture the statistical properties of specular reflecting surfaces. And then the reflecting surfaces are detected through cluster analysis.

Estimation of Regional Evapotranspiration Using Remotely Sensed Land Surface Temperature. Part 1: Measurement of Evapotranspiration at the Environmental Research Center and Determination of Priestley-taylor Parameter

NASA Technical Reports Server (NTRS)

Kotada, K.; Nakagawa, S.; Kai, K.; Yoshino, M. M.; Takeda, K.; Seki, K.

1985-01-01

In order to study the distribution of evapotranspiration in the humid region using remote sensing technology, the parameter (alpha) in the Priestley-Taylor model was determined. The daily means of the parameter alpha = 1.14 can be available from summer to autumn and alpha = to approximately 2.0 in winter. The results of the satellite and the airborne sensing done on 21st and 22nd January, 1983, are described. Using the vegetation distribution in the Tsukuba Academic New Town, as well as the radiation temperature obtained by remote sensing and the radiation data observed at the ground surface, the evapotranspiration was calculated for each vegetation type by the Priestley-Taylor method. The daily mean evapotranspiration on 22nd January, 1983, was approximately 0.4 mm/day. The differences in evapotranspiration between the vegetation types were not detectable, because the magnitude of evapotranspiration is very little in winter.

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

NASA Astrophysics Data System (ADS)

Chen, Xi; Zhou, Liqing

2015-12-01

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

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1987-01-01

The overall objectives and strategies of the Center for Remote Sensing remain to provide a center for excellence for multidisciplinary scientific expertise to address land-related global habitability and earth observing systems scientific issues. Specific research projects that were underway during the final contract period include: digital classification of coniferous forest types in Michigan's northern lower peninsula; a physiographic ecosystem approach to remote classification and mapping; land surface change detection and inventory; analysis of radiant temperature data; and development of methodologies to assess possible impacts of man's changes of land surface on meteorological parameters. Significant progress in each of the five project areas has occurred. Summaries on each of the projects are provided.

Supercooled Liquid Water Content Instrument Analysis and Winter 2014 Data with Comparisons to the NASA Icing Remote Sensing System and Pilot Reports

NASA Technical Reports Server (NTRS)

King, Michael C.

2016-01-01

The National Aeronautics and Space Administration (NASA) has developed a system for remotely detecting the hazardous conditions leading to aircraft icing in flight, the NASA Icing Remote Sensing System (NIRSS). Newly developed, weather balloon-borne instruments have been used to obtain in-situ measurements of supercooled liquid water during March 2014 to validate the algorithms used in the NIRSS. A mathematical model and a processing method were developed to analyze the data obtained from the weather balloon soundings. The data from soundings obtained in March 2014 were analyzed and compared to the output from the NIRSS and pilot reports.

Ground-based remote sensing of tropospheric water vapour isotopologues within the project MUSICA

NASA Astrophysics Data System (ADS)

Schneider, M.; Barthlott, S.; Hase, F.; González, Y.; Yoshimura, K.; García, O. E.; Sepúlveda, E.; Gomez-Pelaez, A.; Gisi, M.; Kohlhepp, R.; Dohe, S.; Blumenstock, T.; Wiegele, A.; Christner, E.; Strong, K.; Weaver, D.; Palm, M.; Deutscher, N. M.; Warneke, T.; Notholt, J.; Lejeune, B.; Demoulin, P.; Jones, N.; Griffith, D. W. T.; Smale, D.; Robinson, J.

2012-12-01

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water), long-term tropospheric water vapour isotopologue data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change). We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere) to 8 km (in the upper troposphere) and with an estimated precision of better than 10%. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30‰ for the ratio between the two isotopologues HD16O and H216O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and the cross-dependence on humidity are the leading error sources. We introduce an a posteriori correction method of the cross-dependence on humidity, and we recommend applying it to isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO2 retrievals and use them for demonstrating the MUSICA network-wide data consistency. In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model). We identify differences in the multi-year mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.

Ground-based remote sensing of tropospheric water vapour isotopologues within the project MUSICA

NASA Astrophysics Data System (ADS)

Schneider, M.; Barthlott, S.; Hase, F.; González, Y.; Yoshimura, K.; García, O. E.; Sepúlveda, E.; Gomez-Pelaez, A.; Gisi, M.; Kohlhepp, R.; Dohe, S.; Blumenstock, T.; Strong, K.; Weaver, D.; Palm, M.; Deutscher, N. M.; Warneke, T.; Notholt, J.; Lejeune, B.; Demoulin, P.; Jones, N.; Griffith, D. W. T.; Smale, D.; Robinson, J.

2012-08-01

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water), long-term tropospheric water vapour isotopologues data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change). We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere) to 8 km (in the upper troposphere) and with an estimated precision of better than 10%. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30‰ for the ratio between the two isotopologues HD16O and H216O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and interferences from humidity are the leading error sources. We introduce an a posteriori correction method of the humidity interference error and we recommend applying it for isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO2 retrievals and use them for demonstrating the MUSICA network-wide data consistency. In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model). We identify differences in the multi-year mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

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

PubMed

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

2018-01-01

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

REMOTE SENSING TECHNOLOGIES APPLICATIONS RESEARCH

EPA Science Inventory

Remote sensing technologies applications research supports the ORD Landscape Sciences Program (LSP) in two separate areas: operational remote sensing, and remote sensing research and development. Operational remote sensing is provided to the LSP through the use of current and t...

Commercial Earth Observation

NASA Technical Reports Server (NTRS)

1995-01-01

Through the Earth Observation Commercial Applications Program (EOCAP) at Stennis Space Center, Applied Analysis, Inc. developed a new tool for analyzing remotely sensed data. The Applied Analysis Spectral Analytical Process (AASAP) detects or classifies objects smaller than a pixel and removes the background. This significantly enhances the discrimination among surface features in imagery. ERDAS, Inc. offers the system as a modular addition to its ERDAS IMAGINE software package for remote sensing applications. EOCAP is a government/industry cooperative program designed to encourage commercial applications of remote sensing. Projects can run three years or more and funding is shared by NASA and the private sector participant. Through the Earth Observation Commercial Applications Program (EOCAP), Ocean and Coastal Environmental Sensing (OCENS) developed SeaStation for marine users. SeaStation is a low-cost, portable, shipboard satellite groundstation integrated with vessel catch and product monitoring software. Linked to the Global Positioning System, SeaStation provides real time relationships between vessel position and data such as sea surface temperature, weather conditions and ice edge location. This allows the user to increase fishing productivity and improve vessel safety. EOCAP is a government/industry cooperative program designed to encourage commercial applications of remote sensing. Projects can run three years or more and funding is shared by NASA and the private sector participant.

Detect, map, and preserve Bronze & Iron Age monuments along the pre-historic Silk Road

NASA Astrophysics Data System (ADS)

Balz, Timo; Caspari, Gino; Fu, Bihong

2017-02-01

Central Asia is rich in cultural heritage generated by thousands of years of human occupation. Aiming for a better understanding of Central Asia’s archaeology and how this unique heritage can be protected, the region should be studied as a whole with regard to its cultural ties with China and combined efforts should be undertaken in shielding the archaeological monuments from destruction. So far, international research campaigns have focused predominantly on single-sites or small-scale surveys, mainly due to the bureaucratic and security related issues involved in cross-border research. This is why we created the Dzungaria Landscape Project. Since 2013, we have worked on collecting remote sensing data of Xinjiang including IKONOS, WorldView-2, and TerraSAR-X data. We have developed a method for the automatic detection of larger grave mound structures in optical and SAR data. Gravemounds are typically spatially clustered and the detection of larger mound structures is a sufficient hint towards areas of high archaeological interest in a region. A meticulous remote sensing survey is the best planning tool for subsequent ground surveys and excavation. In summer 2015, we undertook a survey in the Chinese Altai in order to establish ground-truth in the Hailiutan valley. We categorized over 1000 monuments in just three weeks thanks to the previous detection and classification work using remote sensing data. Creating accurate maps of the cemeteries in northern Xinjiang is a crucial step to preserving the cultural heritage of the region since graves in remote areas are especially prone to looting. We will continue our efforts with the ultimate aim to map and monitor all large gravemounds in Dzungaria and potentially neighbouring eastern Kazakhstan.

Hyperspectral surface reflectance data detect low moisture status of pecan orchards during flood irrigation

USDA-ARS?s Scientific Manuscript database

For large fields, remote sensing might permit plant low moisture status to be detected early, and this may improve drought detection and monitoring. The objective of this study was to determine whether canopy and soil surface reflectance data derived from a handheld spectroradiometer can detect mois...

Constellation analysis of an integrated AIS/remote sensing spaceborne system for ship detection

NASA Astrophysics Data System (ADS)

Graziano, Maria Daniela; D'Errico, Marco; Razzano, Elena

2012-08-01

A future system integrating data from remote sensing and upcoming AIS satellites is analyzed through the development of a novel design method for global, discontinuous coverage constellations. It is shown that 8 AIS satellites suffice to guarantee global coverage and a ship location update of 50 min if the spaceborne AIS receiver has a swath of 2800 nm. Furthermore, synergic utilization of COSMO/SkyMed and Radarsat-C data would provide a mean revisit time of 7 h, with AIS information available within 25 min from SAR data acquisition.

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

NASA Technical Reports Server (NTRS)

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.

Model for mapping settlements

DOEpatents

Vatsavai, Ranga Raju; Graesser, Jordan B.; Bhaduri, Budhendra L.

2016-07-05

A programmable media includes a graphical processing unit in communication with a memory element. The graphical processing unit is configured to detect one or more settlement regions from a high resolution remote sensed image based on the execution of programming code. The graphical processing unit identifies one or more settlements through the execution of the programming code that executes a multi-instance learning algorithm that models portions of the high resolution remote sensed image. The identification is based on spectral bands transmitted by a satellite and on selected designations of the image patches.

Hyperspectral remote sensing of postfire soil properties

Treesearch

Sarah A. Lewis; Peter R. Robichaud; William J. Elliot; Bruce E. Frazier; Joan Q. Wu

2004-01-01

Forest fires may induce changes in soil organic properties that often lead to water repellent conditions within the soil profile that decrease soil infiltration capacity. The remote detection of water repellent soils after forest fires would lead to quicker and more accurate assessment of erosion potential. An airborne hyperspectral image was acquired over the Hayman...

Targets Mask U-Net for Wind Turbines Detection in Remote Sensing Images

NASA Astrophysics Data System (ADS)

Han, M.; Wang, H.; Wang, G.; Liu, Y.

2018-04-01

To detect wind turbines precisely and quickly in very high resolution remote sensing images (VHRRSI) we propose target mask U-Net. This convolution neural network (CNN), which is carefully designed to be a wide-field detector, models the pixel class assignment to wind turbines and their context information. The shadow, which is the context information of the target in this study, has been regarded as part of a wind turbine instance. We have trained the target mask U-Net on training dataset, which is composed of down sampled image blocks and instance mask blocks. Some post-processes have been integrated to eliminate wrong spots and produce bounding boxes of wind turbine instances. The evaluation metrics prove the reliability and effectiveness of our method for the average F1-score of our detection method is up to 0.97. The comparison of detection accuracy and time consuming with the weakly supervised targets detection method based on CNN illustrates the superiority of our method.

Plant-Stress Measurements Using Laser-Induced Fluorescence Excitation: Poland Experiment

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

Gene Capelle; Steve Jones

1999-05-01

Bechtel Nevada's Special Technologies Laboratory (STL) has been involved in remote sensing for many years, and in April 1995 STL began to study the use of active remote sensing for detecting plant stress. This work was motivated by the need to detect subsurface contamination, with the supposition that this could be accomplished by remote measurement of optical signatures from the overgrowing vegetation. The project has been a cooperative DOE/Disney effort, in which basic optical signature measurements (primarily fluorescence) were done at the Disney greenhouse facilities at Epcot Center in Florida, using instrumentation developed by STL on DOE funding. The primarymore » instrument is a LIFI system, which had originally been developed for detection of surface uranium contamination at DOE sites. To deal specifically with the plant stress measurements, a LIFS system was built that utilizes the same laser, but captures the complete fluorescence spectrum from blue to red wavelengths. This system had continued to evolve, and the version in existence in September 1997 was sent to Poland, accompanied by two people from STL, for the purpose of making the measurements described in this report.« less

Analysis of the moderate resolution imaging spectroradiometer contextual algorithm for small fire detection

Treesearch

W. Wang; J.J. Qu; X. Hao; Y. Liu

2009-01-01

In the southeastern United States, most wildland fires are of low intensity. Asubstantial number of these fires cannot be detected by the MODIS contextual algorithm. Toimprove the accuracy of fire detection for this region, the remote-sensed characteristics ofthese fires have to be systematically...

Detecting Change in Landscape Greenness over Large Areas: An Example for New Mexico, USA

EPA Science Inventory

Monitoring and quantifying changes in vegetation cover over large areas using remote sensing can potentially detect large-scale, slow changes (e.g., climate change), as well as more local and rapid changes (e.g., fire, land development). A useful indicator for detecting change i...

A sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image

NASA Astrophysics Data System (ADS)

Li, Jing; Xie, Weixin; Pei, Jihong

2018-03-01

Sea-land segmentation is one of the key technologies of sea target detection in remote sensing images. At present, the existing algorithms have the problems of low accuracy, low universality and poor automatic performance. This paper puts forward a sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image removing island. Firstly, the coastline data is extracted and all of land area is labeled by using the geographic information in large-field remote sensing image. Secondly, three features (local entropy, local texture and local gradient mean) is extracted in the sea-land border area, and the three features combine a 3D feature vector. And then the MultiGaussian model is adopted to describe 3D feature vectors of sea background in the edge of the coastline. Based on this multi-gaussian sea background model, the sea pixels and land pixels near coastline are classified more precise. Finally, the coarse segmentation result and the fine segmentation result are fused to obtain the accurate sea-land segmentation. Comparing and analyzing the experimental results by subjective vision, it shows that the proposed method has high segmentation accuracy, wide applicability and strong anti-disturbance ability.

The NASA Icing Remote Sensing System

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Brinker, David J.; Ratvasky, Thomas P.; Ryerson, Charles C.; Koenig, George G.

2005-01-01

NASA and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) have an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. A multiple instrument approach is the current emphasis of this activity. Utilizing radar, radiometry, and lidar, a region of supercooled liquid is identified. If the liquid water content (LWC) is sufficiently high, then the region of supercooled liquid cloud is flagged as being an aviation hazard. The instruments utilized for the current effort are an X-band vertical staring radar, a radiometer that measures twelve frequencies between 22 and 59 GHz, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data are post-processed with a LabVIEW program with a resultant supercooled LWC profile and aircraft hazard identification. Remotely sensed measurements gathered during the 2003-2004 Alliance Icing Research Study (AIRS II) were compared to aircraft in-situ measurements. Although the comparison data set is quite small, the cases examined indicate that the remote sensing technique appears to be an acceptable approach.

An overview of remote sensing of chlorophyll fluorescence

NASA Astrophysics Data System (ADS)

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

2007-03-01

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

A Review of Wetland Remote Sensing.

PubMed

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

2017-04-05

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

A Review of Wetland Remote Sensing

PubMed Central

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

2017-01-01

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

The Use of Remote Sensing to Resolve the Aerosol Radiative Forcing

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Tanre, D.; Remer, Lorraine

1999-01-01

Satellites are used for remote sensing of aerosol optical thickness and optical properties in order to derive the aerosol direct and indirect radiative forcing of climate. Accuracy of the derived aerosol optical thickness is used as a measure of the accuracy in deriving the aerosol radiative forcing. Several questions can be asked to challenge this concept. Is the accuracy of the satellite-derived aerosol direct forcing limited to the accuracy of the measured optical thickness? What are the spectral bands needed to derive the total aerosol forcing? Does most of the direct or indirect aerosol forcing of climate originate from regions with aerosol concentrations that are high enough to be detected from space? What should be the synergism ground-based and space-borne remote sensing to solve the problem? We shall try to answer some of these questions, using AVIRIS airborne measurements and simulations.

Use of remote sensing in agriculture

NASA Technical Reports Server (NTRS)

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

1975-01-01

The remote sensing studies of (a) cultivated peanut areas in Southeastern Virginia; (b) studies at the Virginia Truck and Ornamentals Research Station near Painter, Virginia, the Eastern Virginia Research Station near Warsaw, Virginia, the Tidewater Research and Continuing Education Center near Suffolk, Virginia, and the Southern Piedmont Research and Continuing Education Center Blackstone, Virginia; and (c) land use classification studies at Virginia Beach, Virginia are presented. The practical feasibility of using false color infrared imagery to detect and determine the areal extent of peanut disease infestation of Cylindrocladium black rot and Sclerotinia blight is demonstrated. These diseases pose a severe hazard to this major agricultural food commodity. The value of remote sensing technology in terrain analyses and land use classification of diverse land areas is also investigated. Continued refinement of spectral signatures of major agronomic crops and documentation of pertinent environmental variables have provided a data base for the generation of an agricultural-environmental prediction model.

A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers

PubMed Central

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

2016-01-01

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

Improving tsunami warning systems with remote sensing and geographical information system input.

PubMed

Wang, Jin-Feng; Li, Lian-Fa

2008-12-01

An optimal and integrative tsunami warning system is introduced that takes full advantage of remote sensing and geographical information systems (GIS) in monitoring, forecasting, detection, loss evaluation, and relief management for tsunamis. Using the primary impact zone in Banda Aceh, Indonesia as the pilot area, we conducted three simulations that showed that while the December 26, 2004 Indian Ocean tsunami claimed about 300,000 lives because there was no tsunami warning system at all, it is possible that only about 15,000 lives could have been lost if the area had used a tsunami warning system like that currently in use in the Pacific Ocean. The simulations further calculated that the death toll could have been about 3,000 deaths if there had been a disaster system further optimized with full use of remote sensing and GIS, although the number of badly damaged or destroyed houses (29,545) could have likely remained unchanged.

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

PubMed

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

2016-11-15

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

Remote Sensing Laboratory - RSL

ScienceCinema

None

2018-01-16

One of the primary resources supporting homeland security is the Remote Sensing Laboratory, or RSL. The Laboratory creates advanced technologies for emergency response operations, radiological incident response, and other remote sensing activities. RSL emergency response teams are on call 24-hours a day, and maintain the capability to deploy domestically and internationally in response to threats involving the loss, theft, or release of nuclear or radioactive material. Such incidents might include Nuclear Power Plant accidents, terrorist incidents involving nuclear or radiological materials, NASA launches, and transportation accidents involving nuclear materials. Working with the US Department of Homeland Security, RSL personnel equip, maintain, and conduct training on the mobile detection deployment unit, to provide nuclear radiological security at major national events such as the super bowl, the Indianapolis 500, New Year's Eve celebrations, presidential inaugurations, international meetings and conferences, just about any event where large numbers of people will gather.

An evaluation of traditional and emerging remote sensing technologies for the detection of fugitive contamination at selected Superfund hazardous waste sites

USGS Publications Warehouse

Slonecker, E. Terrence; Fisher, Gary B.

2011-01-01

This report represents a remote sensing research effort conducted by the U.S. Geological Survey in cooperation with the U.S. Environmental Protection Agency (EPA) for the EPA Office of Inspector General. The objective of this investigation was to explore the efficacy of remote sensing as a technology for postclosure monitoring of hazardous waste sites as defined under the Comprehensive Environmental Response Compensation and Liability Act of 1980 (Public Law 96-510, 42 U.S.C. §9601 et seq.), also known as \\"Superfund.\\" Five delisted Superfund sites in Maryland and Virginia were imaged with a hyperspectral sensor and visited for collection of soil, water, and spectral samples and inspection of general site conditions. This report evaluates traditional and hyperspectral imagery and field spectroscopic measurement techniques in the characterization and analysis of fugitive (anthropogenic, uncontrolled) contamination at previously remediated hazardous waste disposal sites.

Remote Sensing Laboratory - RSL

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

None

2014-11-06

One of the primary resources supporting homeland security is the Remote Sensing Laboratory, or RSL. The Laboratory creates advanced technologies for emergency response operations, radiological incident response, and other remote sensing activities. RSL emergency response teams are on call 24-hours a day, and maintain the capability to deploy domestically and internationally in response to threats involving the loss, theft, or release of nuclear or radioactive material. Such incidents might include Nuclear Power Plant accidents, terrorist incidents involving nuclear or radiological materials, NASA launches, and transportation accidents involving nuclear materials. Working with the US Department of Homeland Security, RSL personnel equip,more » maintain, and conduct training on the mobile detection deployment unit, to provide nuclear radiological security at major national events such as the super bowl, the Indianapolis 500, New Year's Eve celebrations, presidential inaugurations, international meetings and conferences, just about any event where large numbers of people will gather.« less

Tunnel-Site Selection by Remote Sensing Techniques

DTIC Science & Technology

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

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

DOEpatents

Schroeder, John; Hirth, Brian; Guynes, Jerry

2016-12-13

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

Concept of an advanced hyperspectral remote sensing system for pipeline monitoring

NASA Astrophysics Data System (ADS)

Keskin, Göksu; Teutsch, Caroline D.; Lenz, Andreas; Middelmann, Wolfgang

2015-10-01

Areas occupied by oil pipelines and storage facilities are prone to severe contamination due to leaks caused by natural forces, poor maintenance or third parties. These threats have to be detected as quickly as possible in order to prevent serious environmental damage. Periodical and emergency monitoring activities need to be carried out for successful disaster management and pollution minimization. Airborne remote sensing stands out as an appropriate choice to operate either in an emergency or periodically. Hydrocarbon Index (HI) and Hydrocarbon Detection Index (HDI) utilize the unique absorption features of hydrocarbon based materials at SWIR spectral region. These band ratio based methods require no a priori knowledge of the reference spectrum and can be calculated in real time. This work introduces a flexible airborne pipeline monitoring system based on the online quasi-operational hyperspectral remote sensing system developed at Fraunhofer IOSB, utilizing HI and HDI for oil leak detection on the data acquired by an SWIR imaging sensor. Robustness of HI and HDI compared to state of the art detection algorithms is evaluated in an experimental setup using a synthetic dataset, which was prepared in a systematic way to simulate linear mixtures of selected background and oil spectra consisting of gradually decreasing percentages of oil content. Real airborne measurements in Ettlingen, Germany are used to gather background data while the crude oil spectrum was measured with a field spectrometer. The results indicate that the system can be utilized for online and offline monitoring activities.

Effects of artificial lighting on the detection of plant stress with spectral reflectance remote sensing in bioregenerative life support systems

NASA Astrophysics Data System (ADS)

Schuerger, Andrew C.; Richards, Jeffrey T.

2006-09-01

Plant-based life support systems that utilize bioregenerative technologies have been proposed for long-term human missions to both the Moon and Mars. Bioregenerative life support systems will utilize higher plants to regenerate oxygen, water, and edible biomass for crews, and are likely to significantly lower the ‘equivalent system mass’ of crewed vehicles. As part of an ongoing effort to begin the development of an automatic remote sensing system to monitor plant health in bioregenerative life support modules, we tested the efficacy of seven artificial illumination sources on the remote detection of plant stresses. A cohort of pepper plants (Capsicum annuum L.) were grown 42 days at 25 °C, 70% relative humidity, and 300 μmol m-2 s-1 of photosynthetically active radiation (PAR; from 400 to 700 nm). Plants were grown under nutritional stresses induced by irrigating subsets of the plants with 100, 50, 25, or 10% of a standard nutrient solution. Reflectance spectra of the healthy and stressed plants were collected under seven artificial lamps including two tungsten halogen lamps, plus high pressure sodium, metal halide, fluorescent, microwave, and red/blue light emitting diode (LED) sources. Results indicated that several common algorithms used to estimate biomass and leaf chlorophyll content were effective in predicting plant stress under all seven illumination sources. However, the two types of tungsten halogen lamps and the microwave illumination source yielded linear models with the highest residuals and thus the highest predictive capabilities of all lamps tested. The illumination sources with the least predictive capabilities were the red/blue LEDs and fluorescent lamps. Although the red/blue LEDs yielded the lowest residuals for linear models derived from the remote sensing data, the LED arrays used in these experiments were optimized for plant productivity and not the collection of remote sensing data. Thus, we propose that if adjusted to optimize the collectio n of remote sensing information from plants, LEDs remain the best candidates for illumination sources for monitoring plant stresses in bioregenerative life support systems.

Early Forest Fire Detection Using Radio-Acoustic Sounding System

PubMed Central

Sahin, Yasar Guneri; Ince, Turker

2009-01-01

Automated early fire detection systems have recently received a significant amount of attention due to their importance in protecting the global environment. Some emergent technologies such as ground-based, satellite-based remote sensing and distributed sensor networks systems have been used to detect forest fires in the early stages. In this study, a radio-acoustic sounding system with fine space and time resolution capabilities for continuous monitoring and early detection of forest fires is proposed. Simulations show that remote thermal mapping of a particular forest region by the proposed system could be a potential solution to the problem of early detection of forest fires. PMID:22573967

Software for a GPS-Reflection Remote-Sensing System

NASA Technical Reports Server (NTRS)

Lowe, Stephen

2003-01-01

A special-purpose software Global Positioning System (GPS) receiver designed for remote sensing with reflected GPS signals is described in Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System (NPO-30385), which appears elsewhere in this issue of NASA Tech Briefs. The input accepted by this program comprises raw (open-loop) digitized GPS signals sampled at a rate of about 20 MHz. The program processes the data samples to perform the following functions: detection of signals; tracking of phases and delays; mapping of delay, Doppler, and delay/Doppler waveforms; dual-frequency processing; coherent integrations as short as 125 s; decoding of navigation messages; and precise time tagging of observable quantities. The software can perform these functions on all detectable satellite signals without dead time. Open-loop data collected over water, land, or ice and processed by this software can be further processed to extract geophysical information. Possible examples include mean sea height, wind speed and direction, and significant wave height (for observations over the ocean); bistatic-radar terrain images and measures of soil moisture and biomass (for observations over land); and estimates of ice age, thickness, and surface density (for observations over ice).

Relative radiometric calibration for multispectral remote sensing imagery

NASA Astrophysics Data System (ADS)

Ren, Hsuan

2006-10-01

Our environment has been changed continuously by nature causes or human activities. In order to identify what has been changed during certain time period, we need to spend enormous resources to collect all kinds of data and analyze them. With remote sensing images, change detection has become one efficient and inexpensive technique. It has wide applications including disaster management, agriculture analysis, environmental monitoring and military reconnaissance. To detect the changes between two remote sensing images collected at different time, radiometric calibration is one of the most important processes. Under the different weather and atmosphere conditions, even the same material might be resulting distinct radiance spectrum in two images. In this case, they will be misclassified as changes and false alarm rate will also increase. To achieve absolute calibration, i.e., to convert the radiance to reflectance spectrum, the information about the atmosphere condition or ground reference materials with known reflectance spectrum is needed but rarely available. In this paper, we present relative radiometric calibration methods which transform image pair into similar atmospheric effect instead of remove it in absolutely calibration, so that the information of atmosphere condition is not required. A SPOT image pair will be used for experiment to demonstrate the performance.

Fusing chlorophyll fluorescence and plant canopy reflectance to detect TNT contamination in soils

NASA Astrophysics Data System (ADS)

Naumann, Julie C.; Rubis, Kathryn; Young, Donald R.

2010-04-01

TNT is released into the soil from many different sources, especially from military and mining activities, including buried land mines. Vegetation may absorb explosive residuals, causing stress and by understanding how plants respond to energetic compounds, we may be able to develop non-invasive techniques to detect soil contamination. The objectives of our study were to examine the physiological response of plants grown in TNT contaminated soils and to use remote sensing methods to detect uptake in plant leaves and canopies in both laboratory and field studies. Differences in physiology and light-adapted fluorescence were apparent in laboratory plants grown in N enriched soils and when compared with plants grown in TNT contaminated soils. Several reflectance indices were able to detect TNT contamination prior to visible signs of stress, including the fluorescence-derived indices, R740/R850 and R735/R850, which may be attributed to transformation and conjugation of TNT metabolites with other compounds. Field studies at the Duck, NC Field Research Facility revealed differences in physiological stress measures, and leaf and canopy reflectance when plants growing over suspected buried UXOs were compared with reference plants. Multiple reflectance indices indicated stress at the suspected contaminated sites, including R740/R850 and R735/R850. Under natural conditions of constant leaching of TNT into the soil, TNT uptake would be continuous in plants, potentially creating a distinct signature from remotely sensed vegetation. We may be able to use remote sensing of plant canopies to detect TNT soil contamination prior to visible signs.

Spectroscopic remote sensing of plant stress at leaf and canopy levels using the chlorophyll 680 nm absorption feature with continuum removal

USGS Publications Warehouse

Sanches, Ieda Del´Arco; Souza Filho, Carlos Roberto de; Kokaly, Raymond F.

2014-01-01

This paper explores the use of spectral feature analysis to detect plant stress in visible/near infrared wavelengths. A time series of close range leaf and canopy reflectance data of two plant species grown in hydrocarbon-contaminated soil was acquired with a portable spectrometer. The ProSpecTIR-VS airborne imaging spectrometer was used to obtain far range hyperspectral remote sensing data over the field experiment. Parameters describing the chlorophyll 680 nm absorption feature (depth, width, and area) were derived using continuum removal applied to the spectra. A new index, the Plant Stress Detection Index (PSDI), was calculated using continuum-removed values near the chlorophyll feature centre (680 nm) and on the green-edge (560 and 575 nm). Chlorophyll feature’s depth, width and area, the PSDI and a narrow-band normalised difference vegetation index were evaluated for their ability to detect stressed plants. The objective was to analyse how the parameters/indices were affected by increasing degrees of plant stress and to examine their utility as plant stress indicators at the remote sensing level (e.g. airborne sensor). For leaf data, PSDI and the chlorophyll feature area revealed the highest percentage (67–70%) of stressed plants. The PSDI also proved to be the best constraint for detecting the stress in hydrocarbon-impacted plants with field canopy spectra and airborne imaging spectroscopy data. This was particularly true using thresholds based on the ASD canopy data and considering the combination of higher percentage of stressed plants detected (across the thresholds) and fewer false-positives.

The MUSICA MetOp/IASI H2O and δD products: characterisation and long-term comparison to NDACC/FTIR data

NASA Astrophysics Data System (ADS)

Wiegele, A.; Schneider, M.; Hase, F.; Barthlott, S.; García, O. E.; Sepúlveda, E.; González, Y.; Blumenstock, T.; Raffalski, U.; Gisi, M.; Kohlhepp, R.

2014-04-01

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) ground- and space-based remote sensing as well as in-situ datasets of tropospheric water vapour isotopologues are provided. The space-based remote-sensing dataset is produced from spectra measured by the IASI (Infrared Atmospheric Sounding Interferometer) sensor and is potentially available on a global scale. Here, we present the MUSICA IASI data for three different geophysical locations (subtropics, mid-latitudes, and arctic) and we provide a comprehensive characterisation of the complex nature of such space-based isotopologue remote sensing products. The quality assessment study is complemented by a comparison to MUSICA's ground-based FTIR (Fourier-Transform InfraRed) remote sensing data retrieved from the spectra recorded at three different locations within the framework of NDACC (Network for the Detection of Atmospheric Composition Change). We confirm that IASI is able to measure tropospheric H2O profiles with a vertical resolution of about 4 km and a random error of about 10%. In addition IASI can observe middle tropospheric δD that adds complementary value to IASI's middle tropospheric H2O observations. Our study is both, a theoretical and an empirical proof that IASI has the capability for a global observation of middle tropospheric water vapour isotopologues on a daily timescale and at a quality that is sufficiently high for water cycle research purposes.

The MUSICA MetOp/IASI H2O and δD products: characterisation and long-term comparison to NDACC/FTIR data

NASA Astrophysics Data System (ADS)

Wiegele, A.; Schneider, M.; Hase, F.; Barthlott, S.; García, O. E.; Sepúlveda, E.; González, Y.; Blumenstock, T.; Raffalski, U.; Gisi, M.; Kohlhepp, R.

2014-08-01

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) ground- and space-based remote sensing as well as in situ data sets of tropospheric water vapour isotopologues are provided. The space-based remote-sensing data set is produced from spectra measured by the IASI (Infrared Atmospheric Sounding Interferometer) sensor and is potentially available on a global scale. Here, we present the MUSICA IASI data for three different geophysical locations (subtropics, midlatitudes, and Arctic), and we provide a comprehensive characterisation of the complex nature of such space-based isotopologue remote-sensing products. The quality assessment study is complemented by a comparison to MUSICA's ground-based FTIR (Fourier Transform InfraRed) remote-sensing data retrieved from the spectra recorded at three different locations within the framework of NDACC (Network for the Detection of Atmospheric Composition Change). We confirm that IASI is able to measure tropospheric H2O profiles with a vertical resolution of about 4 km and a random error of about 10%. In addition IASI can observe middle tropospheric δD that adds complementary value to IASI's middle tropospheric H2O observations. Our study presents theoretical and empirical proof that IASI has the capability for a global observation of middle tropospheric water vapour isotopologues on a daily timescale and at a quality that is sufficiently high for water cycle research purposes.

What Models and Satellites Tell Us (and Don't Tell Us) About Arctic Sea Ice Melt Season Length

NASA Astrophysics Data System (ADS)

Ahlert, A.; Jahn, A.

2017-12-01

Melt season length—the difference between the sea ice melt onset date and the sea ice freeze onset date—plays an important role in the radiation balance of the Arctic and the predictability of the sea ice cover. However, there are multiple possible definitions for sea ice melt and freeze onset in climate models, and none of them exactly correspond to the remote sensing definition. Using the CESM Large Ensemble model simulations, we show how this mismatch between model and remote sensing definitions of melt and freeze onset limits the utility of melt season remote sensing data for bias detection in models. It also opens up new questions about the precise physical meaning of the melt season remote sensing data. Despite these challenges, we find that the increase in melt season length in the CESM is not as large as that derived from remote sensing data, even when we account for internal variability and different definitions. At the same time, we find that the CESM ensemble members that have the largest trend in sea ice extent over the period 1979-2014 also have the largest melt season trend, driven primarily by the trend towards later freeze onsets. This might be an indication that an underestimation of the melt season length trend is one factor contributing to the generally underestimated sea ice loss within the CESM, and potentially climate models in general.

Introduction to the physics and techniques of remote sensing

NASA Technical Reports Server (NTRS)

Elachi, Charles

1987-01-01

This book presents a comprehensive overview of the basics behind remote-sensing physics, techniques, and technology. The physics of wave/matter interactions, techniques of remote sensing across the electromagnetic spectrum, and the concepts behind remote sensing techniques now established and future ones under development are discussed. Applications of remote sensing are described for a wide variety of earth and planetary atmosphere and surface sciences. Solid surface sensing across the electromagnetic spectrum, ocean surface sensing, basic principles of atmospheric sensing and radiative transfer, and atmospheric remote sensing in the microwave, millimeter, submillimeter, and infrared regions are examined.

Rotation and scale invariant shape context registration for remote sensing images with background variations

NASA Astrophysics Data System (ADS)

Jiang, Jie; Zhang, Shumei; Cao, Shixiang

2015-01-01

Multitemporal remote sensing images generally suffer from background variations, which significantly disrupt traditional region feature and descriptor abstracts, especially between pre and postdisasters, making registration by local features unreliable. Because shapes hold relatively stable information, a rotation and scale invariant shape context based on multiscale edge features is proposed. A multiscale morphological operator is adapted to detect edges of shapes, and an equivalent difference of Gaussian scale space is built to detect local scale invariant feature points along the detected edges. Then, a rotation invariant shape context with improved distance discrimination serves as a feature descriptor. For a distance shape context, a self-adaptive threshold (SAT) distance division coordinate system is proposed, which improves the discriminative property of the feature descriptor in mid-long pixel distances from the central point while maintaining it in shorter ones. To achieve rotation invariance, the magnitude of Fourier transform in one-dimension is applied to calculate angle shape context. Finally, the residual error is evaluated after obtaining thin-plate spline transformation between reference and sensed images. Experimental results demonstrate the robustness, efficiency, and accuracy of this automatic algorithm.

High resolution remote sensing for reducing uncertainties in urban forest carbon offset life cycle assessments.

PubMed

Tigges, Jan; Lakes, Tobia

2017-10-04

Urban forests reduce greenhouse gas emissions by storing and sequestering considerable amounts of carbon. However, few studies have considered the local scale of urban forests to effectively evaluate their potential long-term carbon offset. The lack of precise, consistent and up-to-date forest details is challenging for long-term prognoses. Therefore, this review aims to identify uncertainties in urban forest carbon offset assessment and discuss the extent to which such uncertainties can be reduced by recent progress in high resolution remote sensing. We do this by performing an extensive literature review and a case study combining remote sensing and life cycle assessment of urban forest carbon offset in Berlin, Germany. Recent progress in high resolution remote sensing and methods is adequate for delivering more precise details on the urban tree canopy, individual tree metrics, species, and age structures compared to conventional land use/cover class approaches. These area-wide consistent details can update life cycle inventories for more precise future prognoses. Additional improvements in classification accuracy can be achieved by a higher number of features derived from remote sensing data of increasing resolution, but first studies on this subject indicated that a smart selection of features already provides sufficient data that avoids redundancies and enables more efficient data processing. Our case study from Berlin could use remotely sensed individual tree species as consistent inventory of a life cycle assessment. However, a lack of growth, mortality and planting data forced us to make assumptions, therefore creating uncertainty in the long-term prognoses. Regarding temporal changes and reliable long-term estimates, more attention is required to detect changes of gradual growth, pruning and abrupt changes in tree planting and mortality. As such, precise long-term urban ecological monitoring using high resolution remote sensing should be intensified, especially due to increasing climate change effects. This is important for calibrating and validating recent prognoses of urban forest carbon offset, which have so far scarcely addressed longer timeframes. Additionally, higher resolution remote sensing of urban forest carbon estimates can improve upscaling approaches, which should be extended to reach a more precise global estimate for the first time. Urban forest carbon offset can be made more relevant by making more standardized assessments available for science and professional practitioners, and the increasing availability of high resolution remote sensing data and the progress in data processing allows for precisely that.

NASA Remote Sensing Applications for Archaeology and Cultural Resources Management

NASA Technical Reports Server (NTRS)

Giardino, Marco J.

2008-01-01

NASA's Earth Science Mission Directorate recently completed the deployment of the Earth Observation System (EOS) which is a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans. One of the many applications derived from EOS is the advancement of archaeological research and applications. Using satellites, manned and unmanned airborne platform, NASA scientists and their partners have conducted archaeological research using both active and passive sensors. The NASA Stennis Space Center (SSC) located in south Mississippi, near New Orleans, has been a leader in space archaeology since the mid-1970s. Remote sensing is useful in a wide range of archaeological research applications from landscape classification and predictive modeling to site discovery and mapping. Remote sensing technology and image analysis are currently undergoing a profound shift in emphasis from broad classification to detection, identification and condition of specific materials, both organic and inorganic. In the last few years, remote sensing platforms have grown increasingly capable and sophisticated. Sensors currently in use, including commercial instruments, offer significantly improved spatial and spectral resolutions. Paired with new techniques of image analysis, this technology provides for the direct detection of archaeological sites. As in all archaeological research, the application of remote sensing to archaeology requires a priori development of specific research designs and objectives. Initially targeted at broad archaeological issues, NASA space archaeology has progressed toward developing practical applications for cultural resources management (CRM). These efforts culminated with the Biloxi Workshop held by NASA and the University of Mississippi in 2002. The workshop and resulting publication specifically address the requirements of cultural resource managers through the use of remote sensing. In 2007, NASA awarded six competitively chosen projects in Space Archaeology through an open solicitation whose purpose, among several, was to addresses the potential benefits to modern society that can be derived through a better understanding of how past cultures succeeded or failed to adapt to local, regional, and global change. A further objective of NASA's space archaeology is the protection and preservation of cultural heritage sites while planning for the sustainable development of cultural resources. NASA s archaeological approach through remote sensing builds on traditional methods of aerial archaeology (i.e. crop marks) and utilizes advanced technologies for collecting and analyzing archaeological data from digital imagery. NASA s archaeological research and application projects using remote sensing have been conducted throughout the world. In North America, NASA has imaged prehistoric mound sites in Mississippi; prehistoric shell middens in Louisiana, Puebloan sites in New Mexico and more recently the sites associated with the Lewis and Clark Corps of Discovery Expedition (1804-1806). In Central America, NASA archaeologists have researched Mayan sites throughout the region, including the Yucatan and Costa Rica, as well as Olmec localities in Veracruz. Other data has been collected over Angkor, Cambodia, Giza in Egypt, the lost city of Ubar on the Arabian Peninsula.

A Remotely Sensed Global Terrestrial Drought Severity Index

NASA Astrophysics Data System (ADS)

Mu, Q.; Zhao, M.; Kimball, J. S.; McDowell, N. G.; Running, S. W.

2012-12-01

Regional drought and flooding from extreme climatic events are increasing in frequency and severity, with significant adverse eco-social impacts. Detecting and monitoring drought at regional to global scales remains challenging, despite the availability of various drought indices and widespread availability of potentially synergistic global satellite observational records. We developed a method to generate a near-real-time remotely sensed Drought Severity Index (DSI) to monitor and detect drought globally at 1-km spatial resolution and regular 8-day, monthly and annual frequencies. The new DSI integrates and exploits information from current operational satellite based terrestrial evapotranspiration (ET) and Vegetation greenness Index (NDVI) products, which are sensitive to vegetation water stress. Specifically, our approach determines the annual DSI departure from its normal (2000-2011) using the remotely sensed ratio of ET to potential ET (PET) and NDVI. The DSI results were derived globally and captured documented major regional droughts over the last decade, including severe events in Europe (2003), the Amazon (2005 and 2010), and Russia (2010). The DSI corresponded favorably (r=0.43) with the precipitation based Palmer Drought Severity Index (PDSI), while both indices captured similar wetting and drying patterns. The DSI was also correlated with satellite based vegetation net primary production (NPP) records, indicating that the combined use of these products may be useful for assessing water supply and ecosystem interactions, including drought impacts on crop yields and forest productivity. The remotely-sensed global terrestrial DSI enhances capabilities for near-real-time drought monitoring to assist decision makers in regional drought assessment and mitigation efforts, and without many of the constraints of more traditional drought monitoring methods.

Support vector machine as a binary classifier for automated object detection in remotely sensed data

NASA Astrophysics Data System (ADS)

Wardaya, P. D.

2014-02-01

In the present paper, author proposes the application of Support Vector Machine (SVM) for the analysis of satellite imagery. One of the advantages of SVM is that, with limited training data, it may generate comparable or even better results than the other methods. The SVM algorithm is used for automated object detection and characterization. Specifically, the SVM is applied in its basic nature as a binary classifier where it classifies two classes namely, object and background. The algorithm aims at effectively detecting an object from its background with the minimum training data. The synthetic image containing noises is used for algorithm testing. Furthermore, it is implemented to perform remote sensing image analysis such as identification of Island vegetation, water body, and oil spill from the satellite imagery. It is indicated that SVM provides the fast and accurate analysis with the acceptable result.

Atmospheric boundary layer CO2 remote sensing with a direct detection LIDAR instrument based on a widely tunable optical parametric source.

PubMed

Cadiou, Erwan; Mammez, Dominique; Dherbecourt, Jean-Baptiste; Gorju, Guillaume; Pelon, Jacques; Melkonian, Jean-Michel; Godard, Antoine; Raybaut, Myriam

2017-10-15

We report on the capability of a direct detection differential absorption lidar (DIAL) for range resolved and integrated path (IPDIAL) remote sensing of CO 2 in the atmospheric boundary layer (ABL). The laser source is an amplified nested cavity optical parametric oscillator (NesCOPO) emitting approximately 8 mJ at the two measurement wavelengths selected near 2050 nm. Direct detection atmospheric measurements are taken from the ground using a 30 Hz frequency switching between emitted wavelengths. Results show that comparable precision measurements are achieved in DIAL and IPDIAL modes (not better than a few ppm) on high SNR targets such as near range ABL aerosol and clouds, respectively. Instrumental limitations are analyzed and degradation due to cloud scattering variability is discussed to explain observed DIAL and IPDIAL limitations.

Building Shadow Detection from Ghost Imagery

NASA Astrophysics Data System (ADS)

Zhou, G.; Sha, J.; Yue, T.; Wang, Q.; Liu, X.; Huang, S.; Pan, Q.; Wei, J.

2018-05-01

Shadow is one of the basic features of remote sensing image, it expresses a lot of information of the object which is loss or interference, and the removal of shadow is always a difficult problem to remote sensing image processing. In this paper, it is mainly analyzes the characteristics and properties of shadows from the ghost image (traditional orthorectification). The DBM and the interior and exterior orientation elements of the image are used to calculate the zenith angle of sun. Then this paper combines the scope of the architectural shadows which has be determined by the zenith angle of sun with the region growing method to make the detection of architectural shadow areas. This method lays a solid foundation for the shadow of the repair from the ghost image later. It will greatly improve the accuracy of shadow detection from buildings and make it more conducive to solve the problem of urban large-scale aerial imagines.

Spectral Detection of Soybean Aphid (Hemiptera: Aphididae) and Confounding Insecticide Effects in Soybean

NASA Astrophysics Data System (ADS)

Alves, Tavvs Micael

Soybean aphid, Aphis glycines (Hemiptera: Aphididae) is the primary insect pest of soybean in the northcentral United States. Soybean aphid may cause stunted plants, leaf discoloration, plant death, and decrease soybean yield by 40%. Sampling plans have been developed for supporting soybean aphid management. However, growers' perception about time involved in direct insect counts has been contributing to a lower adoption of traditional pest scouting methods and may be associated with the use of prophylactic insecticide applications in soybean. Remote sensing of plant spectral (light-derived) responses to soybean aphid feeding is a promising alternative to estimate injury without direct insect counts and, thus, increase adoption and efficiency of scouting programs. This research explored the use of remote sensing of soybean reflectance for detection of soybean aphids and showed that foliar insecticides may have implications for subsequent use of soybean spectral reflectance for pest detection. (Abstract shortened by ProQuest.).

[Thematic Issue: Remote Sensing.

ERIC Educational Resources Information Center

Howkins, John, Ed.

1978-01-01

Four of the articles in this publication discuss the remote sensing of the Earth and its resources by satellites. Among the topics dealt with are the development and management of remote sensing systems, types of satellites used for remote sensing, the uses of remote sensing, and issues involved in using information obtained through remote…

75 FR 65304 - Advisory Committee on Commercial Remote Sensing (ACCRES); Request for Nominations

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-22

... Commercial Remote Sensing (ACCRES); Request for Nominations AGENCY: National Oceanic and Atmospheric... Commercial Remote Sensing (ACCRES). SUMMARY: The Advisory Committee on Commercial Remote Sensing (ACCRES) was... Atmosphere, on matters relating to the U.S. commercial remote sensing industry and NOAA's activities to carry...

Using SPOT-5 images in rice farming for detecting BPH (Brown Plant Hopper)

NASA Astrophysics Data System (ADS)

Ghobadifar, F.; Wayayok, A.; Shattri, M.; Shafri, H.

2014-06-01

Infestation of rice plant-hopper such as Brown Plant Hopper (BPH) (Nilaparvata lugens) is one of the most notable risk in rice yield in tropical areas especially in Asia. In order to use visible and infrared images to detect stress in rice production caused by BPH infestation, several remote sensing techniques have been developed. Initial recognition of pest infestation by means of remote sensing will spreads, for precision farming practice. To address this issue, detection of sheath blight in rice farming was examined by using SPOT-5 images. Specific image indices such as Normalized decrease food production costs, limit environmental hazards, and enhance natural pest control before the problem Normalized Difference Vegetation Index (NDVI), Standard difference indices (SDI) and Ratio Vegetation Index (RVI) were used for analyses using ENVI 4.8 and SPSS software. Results showed that all the indices to recognize infected plants are significant at α = 0.01. Examination of the association between the disease indices indicated that band 3 (near infrared) and band 4 (mid infrared) have a relatively high correlation. The selected indices declared better association for detecting healthy plants from diseased ones. Consequently, these sorts of indices especially NDVI could be valued as indicators for developing techniques for detecting the sheath blight of rice by using remote sensing. This infers that they are useful for crop disease detection but the spectral resolution is probably not sufficient to distinguish plants with light infections (low severity level). Using the index as an indicator can clarify the threshold for zoning the outbreaks. Quick assessment information is very useful in precision farming to practice site specific management such as pesticide application.

Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

NASA Astrophysics Data System (ADS)

Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

2017-09-01

With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

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

NASA Astrophysics Data System (ADS)

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.

Remote sensing with intense filaments enhanced by adaptive optics

NASA Astrophysics Data System (ADS)

Daigle, J.-F.; Kamali, Y.; Châteauneuf, M.; Tremblay, G.; Théberge, F.; Dubois, J.; Roy, G.; Chin, S. L.

2009-11-01

A method involving a closed loop adaptive optic system is investigated as a tool to significantly enhance the collected optical emissions, for remote sensing applications involving ultrafast laser filamentation. The technique combines beam expansion and geometrical focusing, assisted by an adaptive optics system to correct the wavefront aberrations. Targets, such as a gaseous mixture of air and hydrocarbons, solid lead and airborne clouds of contaminated aqueous aerosols, were remotely probed with filaments generated at distances up to 118 m after the focusing beam expander. The integrated backscattered signals collected by the detection system (15-28 m from the filaments) were increased up to a factor of 7, for atmospheric N2 and solid lead, when the wavefronts were corrected by the adaptive optic system. Moreover, an extrapolation based on a simplified version of the LIDAR equation showed that the adaptive optic system improved the detection distance for N2 molecular fluorescence, from 45 m for uncorrected wavefronts to 125 m for corrected.

Detection of Endolithes Using Infrared Spectroscopy

NASA Astrophysics Data System (ADS)

Dumas, S.; Dutil, Y.; Joncas, G.

2009-12-01

On Earth, the Dry Valleys of Antarctica provide the closest martian-like environment for the study of extremophiles. Colonies of bacterias are protected from the freezing temperatures, the drought and UV light. They represent almost half of the biomass of those regions. Due to their resilience, endolithes are one possible model of martian biota. We propose to use infrared spectroscopy to remotely detect those colonies even if there is no obvious sign of their presence. This remote sensing approach reduces the risk of contamination or damage to the samples.

Literature relevant to remote sensing of water quality

NASA Technical Reports Server (NTRS)

Middleton, E. M.; Marcell, R. F.

1983-01-01

References relevant to remote sensing of water quality were compiled, organized, and cross-referenced. The following general categories were included: (1) optical properties and measurement of water characteristics; (2) interpretation of water characteristics by remote sensing, including color, transparency, suspended or dissolved inorganic matter, biological materials, and temperature; (3) application of remote sensing for water quality monitoring; (4) application of remote sensing according to water body type; and (5) manipulation, processing and interpretation of remote sensing digital water data.

Learning Methods of Remote Sensing In the 2013 Curriculum of Secondary School

NASA Astrophysics Data System (ADS)

Lili Somantri, Nandi

2016-11-01

The new remote sensing material included in the subjects of geography in the curriculum of 1994. For geography teachers generation of 90s and over who in college do not get the material remote sensing, for teaching is a tough matter. Most teachers only give a theoretical matter, and do not carry out practical reasons in the lack of facilities and infrastructure of computer laboratories. Therefore, in this paper studies the importance about the method or manner of teaching remote sensing material in schools. The purpose of this paper is 1) to explain the position of remote sensing material in the study of geography, 2) analyze the Geography Curriculum 2013 Subjects related to remote sensing material, 3) describes a method of teaching remote sensing material in schools. The method used in this paper is a descriptive analytical study supported by the literature. The conclusion of this paper that the position of remote sensing in the study of geography is a method or a way to obtain spatial data earth's surface. In the 2013 curriculum remote sensing material has been applied to the study of land use and transportation. Remote sensing methods of teaching must go through a practicum, which starts from the introduction of the theory of remote sensing, data extraction phase of remote sensing imagery to produce maps, both visually and digitally, field surveys, interpretation of test accuracy, and improved maps.

VERIFICATION OF PORTABLE OPTICAL AND THERMAL IMAGING DEVICES FOR LEAK DETECTION AT PETROLEUM REFINERIES AND CHEMICAL PLANTS

EPA Science Inventory

Optical and thermal imaging devices are remote sensing systems that can be used to detect leaking gas compounds such as methane and benzene. Use of these systems can reduce fugitive emission losses through early detection and repair at industrial facilities by providing an effici...

JPRS Report, Science & Technology, China, Remote Sensing Systems, Applications.

DTIC Science & Technology

1991-01-17

Partial Contents: Short Introduction to Nation’s Remote Sensing Units, Domestic Airborne Remote - Sensing System, Applications in Monitoring Natural...Disasters, Applications of Imagery From Experimental Satellites Launched in 1985, 1986, Current Status, Future Prospects for Domestic Remote - Sensing -Satellite...Ground Station, and Radar Remote - Sensing Technology Used to Monitor Yellow River Delta,

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Development of an Algorithm for Satellite Remote Sensing of Sea and Lake Ice

NASA Astrophysics Data System (ADS)

Dorofy, Peter T.

Satellite remote sensing of snow and ice has a long history. The traditional method for many snow and ice detection algorithms has been the use of the Normalized Difference Snow Index (NDSI). This manuscript is composed of two parts. Chapter 1, Development of a Mid-Infrared Sea and Lake Ice Index (MISI) using the GOES Imager, discusses the desirability, development, and implementation of alternative index for an ice detection algorithm, application of the algorithm to the detection of lake ice, and qualitative validation against other ice mapping products; such as, the Ice Mapping System (IMS). Chapter 2, Application of Dynamic Threshold in a Lake Ice Detection Algorithm, continues with a discussion of the development of a method that considers the variable viewing and illumination geometry of observations throughout the day. The method is an alternative to Bidirectional Reflectance Distribution Function (BRDF) models. Evaluation of the performance of the algorithm is introduced by aggregating classified pixels within geometrical boundaries designated by IMS and obtaining sensitivity and specificity statistical measures.

Urban Area Detection in Very High Resolution Remote Sensing Images Using Deep Convolutional Neural Networks.

PubMed

Tian, Tian; Li, Chang; Xu, Jinkang; Ma, Jiayi

2018-03-18

Detecting urban areas from very high resolution (VHR) remote sensing images plays an important role in the field of Earth observation. The recently-developed deep convolutional neural networks (DCNNs), which can extract rich features from training data automatically, have achieved outstanding performance on many image classification databases. Motivated by this fact, we propose a new urban area detection method based on DCNNs in this paper. The proposed method mainly includes three steps: (i) a visual dictionary is obtained based on the deep features extracted by pre-trained DCNNs; (ii) urban words are learned from labeled images; (iii) the urban regions are detected in a new image based on the nearest dictionary word criterion. The qualitative and quantitative experiments on different datasets demonstrate that the proposed method can obtain a remarkable overall accuracy (OA) and kappa coefficient. Moreover, it can also strike a good balance between the true positive rate (TPR) and false positive rate (FPR).

Extraction of Greenhouse Areas with Image Processing Methods in Karabuk Province

NASA Astrophysics Data System (ADS)

Yildirima, M. Z.; Ozcan, C.

2017-11-01

Greenhouses provide the environmental conditions to be controlled and regulated as desired while allowing agricultural products to be produced without being affected by external environmental conditions. High quality and a wide variety of agricultural products can be produced throughout the year. In addition, mapping and detection of these areas has great importance in terms of factors such as yield analysis, natural resource management and environmental impact. Various remote sensing techniques are currently available for extraction of greenhouse areas. These techniques are based on the automatic detection and interpretation of objects on remotely sensed images. In this study, greenhouse areas were determined from optical images obtained from Landsat. The study was carried out in the greenhouse areas in Karabuk province. The obtained results are presented with figures and tables.

BP fusion model for the detection of oil spills on the sea by remote sensing

NASA Astrophysics Data System (ADS)

Chen, Weiwei; An, Jubai; Zhang, Hande; Lin, Bin

2003-06-01

Oil spills are very serious marine pollution in many countries. In order to detect and identify the oil-spilled on the sea by remote sensor, scientists have to conduct a research work on the remote sensing image. As to the detection of oil spills on the sea, edge detection is an important technology in image processing. There are many algorithms of edge detection developed for image processing. These edge detection algorithms always have their own advantages and disadvantages in the image processing. Based on the primary requirements of edge detection of the oil spills" image on the sea, computation time and detection accuracy, we developed a fusion model. The model employed a BP neural net to fuse the detection results of simple operators. The reason we selected BP neural net as the fusion technology is that the relation between simple operators" result of edge gray level and the image"s true edge gray level is nonlinear, while BP neural net is good at solving the nonlinear identification problem. Therefore in this paper we trained a BP neural net by some oil spill images, then applied the BP fusion model on the edge detection of other oil spill images and obtained a good result. In this paper the detection result of some gradient operators and Laplacian operator are also compared with the result of BP fusion model to analysis the fusion effect. At last the paper pointed out that the fusion model has higher accuracy and higher speed in the processing oil spill image"s edge detection.

Laser applications in meteorology and earth and atmospheric remote sensing; Proceedings of the Meeting, Los Angeles, CA, Jan. 16-18, 1989

NASA Technical Reports Server (NTRS)

Sokoloski, Martin M. (Editor)

1989-01-01

Various papers on laser applications in meteorology and earth and atmospheric remote sensing are presented. The individual topics addressed include: solid state lasers for the mid-IR region, tunable chromium lasers, GaInAsSb/AlGaAsSb injection lasers for remote sensing applications, development and design of an airborne autonomous wavemeter for laser tuning, fabrication of lightweight Si/SiC lidar mirrors, low-cost double heterostructure and quantum-well laser array development, nonlinear optical processes for the mid-IR region, simulated space-based Doppler lidar performance in regions of backscatter inhomogeneities, design of CO2 recombination catalysts for closed-cycle CO2 lasers, density measurements with combined Raman-Rayleigh lidar, geodynamics applications of spaceborne laser ranging, use of aircraft laser ranging data for forest mensuration, remote active spectrometer, multiwavelngth and triple CO2 lidars for trace gas detection, analysis of laser diagnostics in plumes, laser atmospheric wind sounder, compact Doppler lidar system using commercial off-the-shelf components, and preliminary design for a laser atmospheric wind sounder.

A Search-and-Rescue Robot System for Remotely Sensing the Underground Coal Mine Environment

PubMed Central

Gao, Junyao; Zhao, Fangzhou; Liu, Yi

2017-01-01

This paper introduces a search-and-rescue robot system used for remote sensing of the underground coal mine environment, which is composed of an operating control unit and two mobile robots with explosion-proof and waterproof function. This robot system is designed to observe and collect information of the coal mine environment through remote control. Thus, this system can be regarded as a multifunction sensor, which realizes remote sensing. When the robot system detects danger, it will send out signals to warn rescuers to keep away. The robot consists of two gas sensors, two cameras, a two-way audio, a 1 km-long fiber-optic cable for communication and a mechanical explosion-proof manipulator. Especially, the manipulator is a novel explosion-proof manipulator for cleaning obstacles, which has 3-degree-of-freedom, but is driven by two motors. Furthermore, the two robots can communicate in series for 2 km with the operating control unit. The development of the robot system may provide a reference for developing future search-and-rescue systems. PMID:29065560

Very-to-barely remote sensing of prehistoric features under tephra in Central America

NASA Technical Reports Server (NTRS)

Sheets, Payson D.

1991-01-01

A wide variety of remote sensing instruments have been utilized to attempt to detect archaeological features under volcanic ash in Central America. Some techniques have not been successful, such as seismic refraction, for reasons that are not difficult to understand. Others have been very successful and provide optimism for archaeologists witnessing the destruction of unburied sites throughout Central America. The sudden burial of buildings, gardens, and footpaths by volcanic ash can preserve them extremely well providing a rich data base for understanding human life and culture at certain points in time.

An Improved Unsupervised Image Segmentation Evaluation Approach Based on - and Over-Segmentation Aware

NASA Astrophysics Data System (ADS)

Su, Tengfei

2018-04-01

In this paper, an unsupervised evaluation scheme for remote sensing image segmentation is developed. Based on a method called under- and over-segmentation aware (UOA), the new approach is improved by overcoming the defect in the part of estimating over-segmentation error. Two cases of such error-prone defect are listed, and edge strength is employed to devise a solution to this issue. Two subsets of high resolution remote sensing images were used to test the proposed algorithm, and the experimental results indicate its superior performance, which is attributed to its improved OSE detection model.

Research Implementation and Quality Assurance Project Plan: An Evaluation of Hyperspectral Remote Sensing Technologies for the Detection of Fugitive Contamination at Selected Superfund Hazardous Waste Sites

USGS Publications Warehouse

Slonecker, E. Terrence; Fisher, Gary B.

2009-01-01

This project is a research collaboration between the U.S. Environmental Protection Agency (EPA) Office of Inspector General (OIG) and the U.S. Geological Survey (USGS) Eastern Geographic Science Center (EGSC), for the purpose of evaluating the utility of hyperspectral remote sensing technology for post-closure monitoring of residual contamination at delisted and closed hazardous waste sites as defined under the Comprehensive Environmental Response Compensation and Liability Act [CERCLA (also known as 'Superfund')] of 1980 and the Superfund Amendments and Reauthorization Act (SARA) of 1986.

Remote Sensing for Farmers and Flood Watching

NASA Technical Reports Server (NTRS)

2005-01-01

The Applied Sciences Directorate, part of NASA s Science Mission Directorate, makes use of the Agency s remote-sensing capabilities to acquire detailed information about our home planet. It uses this information for a variety of purposes, ranging from increasing agricultural efficiency to protecting homeland security. Sensors fly over areas of interest to detect and record information that sometimes is not even visible from the ground with the human eye. Scientists analyze these data for a variety of purposes and make maps of the areas. These maps are often used to answer questions about the environment, weather, natural resources, community growth, and natural disasters.

Fast, cheap and in control: spectral imaging with handheld devices

NASA Astrophysics Data System (ADS)

Gooding, Edward A.; Deutsch, Erik R.; Huehnerhoff, Joseph; Hajian, Arsen R.

2017-05-01

Remote sensing has moved out of the laboratory and into the real world. Instruments using reflection or Raman imaging modalities become faster, cheaper and more powerful annually. Enabling technologies include virtual slit spectrometer design, high power multimode diode lasers, fast open-loop scanning systems, low-noise IR-sensitive array detectors and low-cost computers with touchscreen interfaces. High-volume manufacturing assembles these components into inexpensive portable or handheld devices that make possible sophisticated decision-making based on robust data analytics. Examples include threat, hazmat and narcotics detection; remote gas sensing; biophotonic screening; environmental remediation and a host of other applications.

Effect of metal stress on the thermal infrared emission of soybeans: A greenhouse experiment - Possible utility in remote sensing

NASA Technical Reports Server (NTRS)

Suresh, R.; Schwaller, M. R.; Foy, C. D.; Weidner, J. R.; Schnetzler, C. S.

1989-01-01

Manganese-sensitive forest and manganese-tolerant lee soybean cultivars were subjected to differential manganese stress in loring soil in a greenhouse experiment. Leaf temperature measurements were made using thermistors for forest and lee. Manganese-stressed plants had higher leaf temperatures than control plants in both forest and lee. Results of this experiment have potential applications in metal stress detection using remote sensing thermal infrared data over large areas of vegetation. This technique can be useful in reconnaissance mineral exploration in densely-vegetated regions where conventional ground-based methods are of little help.

Feasibility Study of Space-based CO2 Remote Sensing Using Pulsed 2-micron Integrated Path Differential Absorption Lidar

NASA Astrophysics Data System (ADS)

Singh, U. N.; Refaat, T. F.; Ismail, S.; Davis, K. J.; Kawa, S. R.; Menzies, R. T.; Petros, M.; Yu, J.

2016-12-01

Carbon dioxide (CO2) is recognized as the most important anthropogenic greenhouse gas. While CO2 concentration is rapidly increasing, understanding of the global carbon cycle remains a primary scientific challenge. This is mainly due to the lack of full characterization of CO2 sources and sinks. Quantifying the current global distribution of CO2 sources and sinks with sufficient accuracy and spatial resolution is a critical requirement for improving models of carbon-climate interactions and for attributing them to specific biogeochemical processes. This requires sustained atmospheric CO2 observations with high precision, and low bias for high accuracy, and spatial and temporal dense representation that cannot be fully realized with current CO2 observing systems, including existing satellite CO2 passive remote sensors. Progress in 2-micron instrument technologies, airborne testing, and system performance simulations indicates that the necessary lower tropospheric weighted CO2 measurements can be achieved from space using new high pulse energy 2-micron direct detection active remote sensing. Advantages of the CO2 active remote sensing include low bias measurements that are independent of sun light or Earth's radiation and day/night coverage over all latitudes and seasons. In addition, the direct detection system provides precise ranging with simultaneous measurement of aerosol and cloud distributions. The 2-micron active remote sensing offers strong CO2 absorption lines with optimum low tropospheric and near surface weighting. A feasibility study, including system optimization and sensitivity analysis of a space-based 2-micron pulsed IPDA lidar for CO2 measurement, is presented. This is based on the successful demonstration of the CO2 double-pulse IPDA lidar and the technology maturation of the triple-pulse IPDA lidar, currently under development at NASA Langley Research Center. Preliminary simulations indicate CO2 random measurement errors of 0.71, 0.35 and 0.13 ppm for snow, ocean surface, and desert surface reflectivity, respectively. These simulations assume a 400 km altitude polar orbit, 100 mJ pulse energy, a 1.5 m telescope, a 6.2 MHz detection bandwidth, 0.05 aerosol optical depth and 7 second data average.

Feasibility study of the application of existing techniques to remotely monitor hydrochloric acid in the atmosphere

NASA Technical Reports Server (NTRS)

Zwick, H.; Ward, V.; Beaudette, L.

1973-01-01

A critical evaluation of existing optical remote sensors for HCl vapor detection in solid propellant rocket plumes is presented. The P branch of the fundamental vibration-rotation band was selected as the most promising spectral feature to sense. A computation of transmittance for HCl vapor, an estimation of interferent spectra, the application of these spectra to computer modelled remote sensors, and a trade-off study for instrument recommendation are also included.

Cybernetic Basis and System Practice of Remote Sensing and Spatial Information Science

NASA Astrophysics Data System (ADS)

Tan, X.; Jing, X.; Chen, R.; Ming, Z.; He, L.; Sun, Y.; Sun, X.; Yan, L.

2017-09-01

Cybernetics provides a new set of ideas and methods for the study of modern science, and it has been fully applied in many areas. However, few people have introduced cybernetics into the field of remote sensing. The paper is based on the imaging process of remote sensing system, introducing cybernetics into the field of remote sensing, establishing a space-time closed-loop control theory for the actual operation of remote sensing. The paper made the process of spatial information coherently, and improved the comprehensive efficiency of the space information from acquisition, procession, transformation to application. We not only describes the application of cybernetics in remote sensing platform control, sensor control, data processing control, but also in whole system of remote sensing imaging process control. We achieve the information of output back to the input to control the efficient operation of the entire system. This breakthrough combination of cybernetics science and remote sensing science will improve remote sensing science to a higher level.

Mobile multiwave lidar

NASA Astrophysics Data System (ADS)

Gritsuta, A. N.; Klimkin, A. V.; Kokhanenko, G. P.; Kuryak, A. N.; Osipov, K. Y.; Ponomarev, Yu. N.; Simonova, G. V.

2018-04-01

The task that faced the authors was construction of a mobile lidar complex for detection and investigation of aerosol-gas formations in the atmosphere. The complex must be constructed of commercial industrially produced components as much as possible. Many of engineering solutions had been previously worked out by the authors when the first lidar of such type was developed. The complex is designed for study of capabilities of lidar sensing for remote investigation of aerosol-gas formations by their fluorescence and Raman scattering spectra, as well as topographyc objects by fluorescence spectra of their surfaces. The complex has been tested in 2016, and may be applied for atmospheric sensing, for detection of potentially hazardous and dangerous admixtures above the cities, industrial and agricultural emissions, including emissions after disclosures of agricultural animal burial sites. The complex is mounted on a motor vehicle chassis and is energy-independent, and that allow using it for remote sensing of different objects in different natural conditions. Probing distance: 30 000 meters in elastic scattering channel and 5 000 meters in fluorescence channel.

Settlement patterns and communication routes of the western Maya wetlands: An archaeological and remote-sensing survey, Chunchucmil, Yucatan, Mexico

NASA Astrophysics Data System (ADS)

Hixson, David R.

This dissertation investigates the role of the seasonal wetlands in the political economy and subsistence strategies of the ancient Maya of Chunchucmil, Yucatan, Mexico. A combination of pedestrian surveys and remote-sensing tasks were performed in order to better understand the settlement patterns and potential communication routes in and through the wetlands between Chunchucmil and the Gulf of Mexico. These western wetlands had been proposed as the principal avenue for interregional trade between coastal merchants and inland consumers, yet were thought to be uninhabited and uncultivable. Following the survey tasks outlined in this dissertation, these wetlands were found to contain an abundance of archaeological settlements and features indicating habitation, utilization, and trade throughout this diverse ecological zone. The remote-sensing platforms utilized in this study include both multispectral (Landsat) and synthetic aperture radar (AirSAR), combined with additional remotely sensed resources. One of the goals of this survey was to test the capabilities of these two sensors for the direct detection of archaeological features from air and space. The results indicate that Landsat can be highly successful at detecting site location and measuring site size under certain environmental conditions. The Airborne Synthetic Aperture Radar proved to be adept at detecting large mounded architecture within the Yucatecan karstic plain, but its further utility is hampered by limitations of resolution, scale, and land cover. One of the salient features of the landscape west of Chunchucmil is a network of stone pathways called andadores. These avenues through the wetlands outline a dendritic network of communication, trade, and extraction routes. The following dissertation places this network and its associated settlements (from suburban centers to diminutive camps) within their regional context, examining the roles they may have played in supporting a large mercantile economy centered at the site of Chunchucmil.

Geophysics, Remote Sensing, and the Comprehensive Nuclear-Test-Ban Treaty (CTBT) Integrated Field Exercise 2014

NASA Astrophysics Data System (ADS)

Sussman, A. J.; Macleod, G.; Labak, P.; Malich, G.; Rowlands, A. P.; Craven, J.; Sweeney, J. J.; Chiappini, M.; Tuckwell, G.; Sankey, P.

2015-12-01

The Integrated Field Exercise of 2014 (IFE14) was an event held in the Hashemite Kingdom of Jordan (with concurrent activities in Austria) that tested the operational and technical capabilities of an on-site inspection (OSI) within the CTBT verification regime. During an OSI, up to 40 international inspectors will search an area for evidence of a nuclear explosion. Over 250 experts from ~50 countries were involved in IFE14 (the largest simulation of a real OSI to date) and worked from a number of different directions, such as the Exercise Management and Control Teams (which executed the scenario in which the exercise was played) and those participants performing as members of the Inspection Team (IT). One of the main objectives of IFE14 was to test and integrate Treaty allowed inspection techniques, including a number of geophysical and remote sensing methods. In order to develop a scenario in which the simulated exercise could be carried out, suites of physical features in the IFE14 inspection area were designed and engineered by the Scenario Task Force (STF) that the IT could detect by applying the geophysical and remote sensing inspection technologies, in addition to other techniques allowed by the CTBT. For example, in preparation for IFE14, the STF modeled a seismic triggering event that was provided to the IT to prompt them to detect and localize aftershocks in the vicinity of a possible explosion. Similarly, the STF planted shallow targets such as borehole casings and pipes for detection using other geophysical methods. In addition, airborne technologies, which included multi-spectral imaging, were deployed such that the IT could identify freshly exposed surfaces, imported materials, and other areas that had been subject to modification. This presentation will introduce the CTBT and OSI, explain the IFE14 in terms of the goals specific to geophysical and remote sensing methods, and show how both the preparation for and execution of IFE14 meet those goals.

Use of Geophysical and Remote Sensing Techniques During the Comprehensive Test Ban Treaty Organization's Integrated Field Exercise 2014

NASA Astrophysics Data System (ADS)

Labak, Peter; Sussman, Aviva; Rowlands, Aled; Chiappini, Massimo; Malich, Gregor; MacLeod, Gordon; Sankey, Peter; Sweeney, Jerry; Tuckwell, George

2016-04-01

The Integrated Field Exercise of 2014 (IFE14) was a field event held in the Hashemite Kingdom of Jordan (with concurrent activities in Austria) that tested the operational and technical capabilities of a Comprehensive Test Ban Treaty's (CTBT) on-site inspection (OSI). During an OSI, up to 40 inspectors search a 1000km2 inspection area for evidence of a nuclear explosion. Over 250 experts from ~50 countries were involved in IFE14 (the largest simulation of an OSI to date) and worked from a number of different directions, such as the Exercise Management and Control Teams to execute the scenario in which the exercise was played, to those participants performing as members of the Inspection Team (IT). One of the main objectives of IFE14 was to test Treaty allowed inspection techniques, including a number of geophysical and remote sensing methods. In order to develop a scenario in which the simulated exercise could be carried out, a number of physical features in the IFE14 inspection area were designed and engineered by the Scenario Task Force Group (STF) that the IT could detect by applying the geophysical and remote sensing inspection technologies, as well as other techniques allowed by the CTBT. For example, in preparation for IFE14, the STF modeled a seismic triggering event that was provided to the IT to prompt them to detect and localize aftershocks in the vicinity of a possible explosion. Similarly, the STF planted shallow targets such as borehole casings and pipes for detection by other geophysical methods. In addition, airborne technologies, which included multi-spectral imaging, were deployed such that the IT could identify freshly exposed surfaces, imported materials and other areas that had been subject to modification. This presentation will introduce the CTBT and OSI, explain the IFE14 in terms of goals specific to geophysical and remote sensing methods, and show how both the preparation for and execution of IFE14 meet those goals.

Detecting neighborhood vacancy level in Detroit city using remote sensing

NASA Astrophysics Data System (ADS)

Li, X.; Wang, R.; Yang, A.; Vojnovic, I.

2015-12-01

With the decline of manufacturing industries, many Rust Belt cities, which enjoyed prosperity in the past, are now suffering from financial stress, population decrease and urban poverty. As a consequence, urban neighborhoods deteriorate. Houses are abandoned and left to decay. Neighborhood vacancy brings on many problems. Governments and agencies try to survey the vacancy level by going through neighborhoods and record the condition of each structure, or by buying information of active mailing addresses to get approximate neighborhood vacancy rate. But these methods are expensive and time consuming. Remote sensing provides a quick and comparatively cost-efficient way to access spatial information on social and demographical attributes of urban area. In our study, we use remote sensing to detect a major aspect of neighborhood deterioration, the vacancy levels of neighborhoods in Detroit city. We compared different neighborhoods using Landsat 8 images in 2013. We calculated NDVI that indicates the greenness of neighborhoods with the image in July 2013. Then we used thermal infrared information from image in February to detect human activities. In winter, abandoned houses will not consume so much energy and therefore neighborhoods with more abandoned houses will have smaller urban heat island effect. Controlling for the differences in terms of the greenness obtained from summer time image, we used thermal infrared from winter image to determine the temperatures of urban surface. We find that hotter areas are better maintained and have lower house vacancy rates. We also compared the changes over time for neighborhoods using Landsat 7 images from 2003 to 2013. The results show that deteriorated neighborhoods have increased NDVI in summer and get colder in winter due to abandonment of houses. Our results show the potential application of remote sensing as an easily accessed and efficient way to obtain data about social conditions in cities. We used the neighborhood vacancy survey data for Detroit data (2013-2014) to validate the results of vacancy levels of local neighborhood.

Detecting moisture status of pecan orchards and the potential of remotely-sensed surface reflectance data

NASA Astrophysics Data System (ADS)

Othman, Yahia Abdelrahman

Demand for New Mexico's limited water resources coupled with periodic drought has increased the need to schedule irrigation of pecan orchards based on tree water status. The overall goal of this research was to develop advanced tree water status sensing techniques to optimize irrigation scheduling of pecan orchards. To achieve this goal, I conducted three studies in the La Mancha and Leyendecker orchards, both mature pecan orchards located in the Mesilla Valley, New Mexico. In the first study, I screened leaf-level physiological changes that occurred during cyclic irrigation to determine parameters that best represented changes in plant moisture status. Then, I linked plant physiological changes to remotely-sensed surface reflectance data derived from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+). In the second study, I assessed the impact of water deficits that developed during the flood irrigation dry-down cycles on photosynthesis (A) and gas exchange and established preliminary water deficit thresholds of midday stem water potential (Psi smd) critical to A and gas exchange of pecans. In a third study, I investigated whether hyperspectral data obtained from a handheld spectroradiometer and multispectral remotely-sensed data derived from Landsat 7 ETM+ and Landsat 8 Operational Land Imager (OLI) could detect moisture status in pecans during cyclic flood irrigations. I conducted the first study simultaneously in both orchards. Leaf-level physiological responses and remotely-sensed surface reflectance data were collected from trees that were either well watered or in water deficit. Midday stem water potential was the best leaf-level physiological response to detect moisture status in pecans. Multiple linear regression between Psismd and vegetation indices revealed a significant relationship (R 2 = 0.54) in both orchards. Accordingly, I concluded that remotely-sensed multispectral data form Landsat TMETM+ holds promise for detecting the moisture status of pecans. I conducted the second study simultaneously on the same mature pecan orchards that were used in the first study. Photosynthesis and gas exchange were assessed at Psismd of -0.4 to -2.0 MPa. This study established preliminary values of Psismd that significantly impacted A and gas exchange of field-grown pecans. I recommended that pecan orchards be maintained at Psismd that ranged between -0.80 to -0.90 MPa to prevent significant reductions in A and gas exchange. Broken-line analysis revealed that A remained relatively constant when Psismd was above -0.65 MPa. Conversely, there was linear positive relationship between Psi smd and A when Psismd was less than -0.65 MPa. In the third study, again conducted on both orchards, leaf-level physiological measurements and remotely-sensed data were taken at Psismd levels of -0.40 to -0.85 MPa, -0.95 to -1.45 MPa , and -1.5 to -2.0 MPa. Hyperspectral reflectance indices (from handheld spectroradiometer) detected moisture status in pecan trees better than multispectral reflectance indices (from Landsat ETM+OLI). Vegetation moisture index-I (VMI-I) and vegetation moisture index-II (VMI-II) significantly correlated with Psismd (VMI-I, 0.88 > r > 0.87; VMI-II, -0.68 > r > -0.65). Vegetation moisture index-I Boxplot analysis did not clearly separate moderate water status (-0.95 to -1.45 MPa) at La Mancha, but did so at Leyendecker. However, multispectral reflectance indices had a limited capacity to precisely detect the moderate water status at both orchards (the time when A declined by 15 - 40 %). Given that Psi smd of-0.90 to -1.45 MPa is a critical range for irrigating pecans, I concluded that vegetation indices derived only from hyperspectral reflectance data could be used to detect plant physiological responses that are related to plant water status.

Grazing incidence angle based sensing approach integrated with fiber-optic Fourier transform infrared (FO-FTIR) spectroscopy for remote and label-free detection of medical device contaminations.

PubMed

Hassan, Moinuddin; Ilev, Ilko

2014-10-01

Contamination of medical devices has become a critical and prevalent public health safety concern since medical devices are being increasingly used in clinical practices for diagnostics, therapeutics and medical implants. The development of effective sensing methods for real-time detection of pathogenic contamination is needed to prevent and reduce the spread of infections to patients and the healthcare community. In this study, a hollow-core fiber-optic Fourier transform infrared spectroscopy methodology employing a grazing incidence angle based sensing approach (FO-FTIR-GIA) was developed for detection of various biochemical contaminants on medical device surfaces. We demonstrated the sensitivity of FO-FTIR-GIA sensing approach for non-contact and label-free detection of contaminants such as lipopolysaccharide from various surface materials relevant to medical device. The proposed sensing system can detect at a minimum loading concentration of approximately 0.7 μg/cm(2). The FO-FTIR-GIA has the potential for the detection of unwanted pathogen in real time.

Grazing incidence angle based sensing approach integrated with fiber-optic Fourier transform infrared (FO-FTIR) spectroscopy for remote and label-free detection of medical device contaminations

NASA Astrophysics Data System (ADS)

Hassan, Moinuddin; Ilev, Ilko

2014-10-01

Contamination of medical devices has become a critical and prevalent public health safety concern since medical devices are being increasingly used in clinical practices for diagnostics, therapeutics and medical implants. The development of effective sensing methods for real-time detection of pathogenic contamination is needed to prevent and reduce the spread of infections to patients and the healthcare community. In this study, a hollow-core fiber-optic Fourier transform infrared spectroscopy methodology employing a grazing incidence angle based sensing approach (FO-FTIR-GIA) was developed for detection of various biochemical contaminants on medical device surfaces. We demonstrated the sensitivity of FO-FTIR-GIA sensing approach for non-contact and label-free detection of contaminants such as lipopolysaccharide from various surface materials relevant to medical device. The proposed sensing system can detect at a minimum loading concentration of approximately 0.7 μg/cm2. The FO-FTIR-GIA has the potential for the detection of unwanted pathogen in real time.

Grazing incidence angle based sensing approach integrated with fiber-optic Fourier transform infrared (FO-FTIR) spectroscopy for remote and label-free detection of medical device contaminations

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

Hassan, Moinuddin, E-mail: moinuddin.hassan@fda.hhs.gov; Ilev, Ilko

2014-10-15

Contamination of medical devices has become a critical and prevalent public health safety concern since medical devices are being increasingly used in clinical practices for diagnostics, therapeutics and medical implants. The development of effective sensing methods for real-time detection of pathogenic contamination is needed to prevent and reduce the spread of infections to patients and the healthcare community. In this study, a hollow-core fiber-optic Fourier transform infrared spectroscopy methodology employing a grazing incidence angle based sensing approach (FO-FTIR-GIA) was developed for detection of various biochemical contaminants on medical device surfaces. We demonstrated the sensitivity of FO-FTIR-GIA sensing approach for non-contactmore » and label-free detection of contaminants such as lipopolysaccharide from various surface materials relevant to medical device. The proposed sensing system can detect at a minimum loading concentration of approximately 0.7 μg/cm{sup 2}. The FO-FTIR-GIA has the potential for the detection of unwanted pathogen in real time.« less

Approach for removing ghost-images in remote field eddy current testing of ferromagnetic pipes

NASA Astrophysics Data System (ADS)

Luo, Q. W.; Shi, Y. B.; Wang, Z. G.; Zhang, W.; Zhang, Y.

2016-10-01

In the non-destructive testing of ferromagnetic pipes based on remote field eddy currents, an array of sensing coils is often used to detect local defects. While testing, the image that is obtained by sensing coils exhibits a ghost-image, which originates from both the transmitter and sensing coils passing over the same defects in pipes. Ghost-images are caused by transmitters and lead to undesirable assessments of defects. In order to remove ghost-images, two pickup coils are coaxially set to each other in remote field. Due to the time delay between differential signals tested by the two pickup coils, a Wiener deconvolution filter is used to identify the artificial peaks that lead to ghost-images. Because the sensing coils and two pickup coils all receive the same signal from one transmitter, they all contain the same artificial peaks. By subtracting the artificial peak values obtained by the two pickup coils from the imaging data, the ghost-image caused by the transmitter is eliminated. Finally, a relatively highly accurate image of local defects is obtained by these sensing coils. With proposed method, there is no need to subtract the average value of the sensing coils, and it is sensitive to ringed defects.

Approach for removing ghost-images in remote field eddy current testing of ferromagnetic pipes.

PubMed

Luo, Q W; Shi, Y B; Wang, Z G; Zhang, W; Zhang, Y

2016-10-01

In the non-destructive testing of ferromagnetic pipes based on remote field eddy currents, an array of sensing coils is often used to detect local defects. While testing, the image that is obtained by sensing coils exhibits a ghost-image, which originates from both the transmitter and sensing coils passing over the same defects in pipes. Ghost-images are caused by transmitters and lead to undesirable assessments of defects. In order to remove ghost-images, two pickup coils are coaxially set to each other in remote field. Due to the time delay between differential signals tested by the two pickup coils, a Wiener deconvolution filter is used to identify the artificial peaks that lead to ghost-images. Because the sensing coils and two pickup coils all receive the same signal from one transmitter, they all contain the same artificial peaks. By subtracting the artificial peak values obtained by the two pickup coils from the imaging data, the ghost-image caused by the transmitter is eliminated. Finally, a relatively highly accurate image of local defects is obtained by these sensing coils. With proposed method, there is no need to subtract the average value of the sensing coils, and it is sensitive to ringed defects.

Sensitive Infrared Signal Detection by Upconversion Technique

NASA Technical Reports Server (NTRS)

Wong, Teh-Hwa; Yu, Jirong; Bai, Yingxin; Johnson, William; Chen, Songsheng; Petros, Mulugeta; Singh, Upendra N.

2014-01-01

We demonstrated upconversion assisted detection of a 2.05-micron signal by sum frequency generation to generate a 700-nm light using a bulk periodically poled lithium niobate crystal. The achieved 94% intrinsic upconversion efficiency and 22.58% overall detection efficiency at a pW level of 2.05 micron pave the path to detect extremely weak infrared (IR) signals for remote sensing applications.

Assessing the capabilities of hyperspectral remote sensing to map oil films on waters

NASA Astrophysics Data System (ADS)

Liu, Bingxin; Li, Ying; Zhu, Xueyuan

2014-11-01

The harm of oil spills has caused extensive public concern. Remote sensing technology has become one of the most effective means of monitoring oil spill. However, how to evaluate the information extraction capabilities of various sensors and choose the most effective one has become an important issue. The current evaluation of sensors to detect oil films was mainly using in-situ measured spectra as a reference to determine the favorable band, but ignoring the effects of environmental noise and spectral response function. To understand the precision and accuracy of environment variables acquired from remote sensing, it is important to evaluate the target detection sensitivity of the entire sensor-air-target system corresponding to the change of reflectivity. The measurement data associated with the evaluation is environmental noise equivalent reflectance difference (NEΔRE ), which depends on the instrument signal to noise ratio(SNR) and other image data noise (such as atmospheric variables, scattered sky light scattering and direct sunlight, etc.). Hyperion remote sensing data is taken as an example for evaluation of its oil spill detection capabilities with the prerequisite that the impact of the spatial resolution is ignored. In order to evaluate the sensor's sensitivity of the film of water, the reflectance spectral data of light diesel and crude oil film were used. To obtain Hyperion reflectance data, we used FLAASH to do the atmospheric correction. The spectral response functions of Hyperion sensor was used for filtering the measured reflectance of the oil films to the theoretic spectral response. Then, these spectral response spectra were normalized to NEΔRE, according to which, the sensitivity of the sensor in oil film detecting could be evaluated. For crude oil, the range for Hyperion sensor to identify the film is within the wavelength from 518nm to 610nm (Band 17 to Band 26 of Hyperion sensors), within which the thin film and thick film can also be distinguished. For light diesel oil film, the range for Hyperion sensor to identify the film is within the wavelength from 468nm to 752nm (Band 12 to Band 40 of Hyperion sensors).

Unsupervised Change Detection for Geological and Ecological Monitoring via Remote Sensing: Application on a Volcanic Area

NASA Astrophysics Data System (ADS)

Falco, N.; Pedersen, G. B. M.; Vilmunandardóttir, O. K.; Belart, J. M. M. C.; Sigurmundsson, F. S.; Benediktsson, J. A.

2016-12-01

The project "Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS)" aims at providing fast and reliable mapping and monitoring techniques on a big spatial scale with a high temporal resolution of the Icelandic landscape. Such mapping and monitoring will be crucial to both mitigate and understand the scale of processes and their often complex interlinked feedback mechanisms.In the EMMIRS project, the Hekla volcano area is one of the main sites under study, where the volcanic eruptions, extreme weather and human activities had an extensive impact on the landscape degradation. The development of innovative remote sensing approaches to compute earth observation variables as automatically as possible is one of the main tasks of the EMMIRS project. Furthermore, a temporal remote sensing archive is created and composed by images acquired by different sensors (Landsat, RapidEye, ASTER and SPOT5). Moreover, historical aerial stereo photos allowed decadal reconstruction of the landscape by reconstruction of digital elevation models. Here, we propose a novel architecture for automatic unsupervised change detection analysis able to ingest multi-source data in order to detect landscape changes in the Hekla area. The change detection analysis is based on multi-scale analysis, which allows the identification of changes at different level of abstraction, from pixel-level to region-level. For this purpose, operators defined in mathematical morphology framework are implemented to model the contextual information, represented by the neighbour system of a pixel, allowing the identification of changes related to both geometrical and spectral domains. Automatic radiometric normalization strategy is also implemented as pre-processing step, aiming at minimizing the effect of different acquisition conditions. The proposed architecture is tested on multi-temporal data sets acquired over different time periods coinciding with the last three eruptions (1980-1981, 1991, 2000) occurred on Hekla volcano. The results reveal emplacement of new lava flows and the initial vegetation succession, providing insightful information on the evolving of vegetation in such environment. Shadow and snow patch changes are resolved in post-processing by exploiting the available spectral information.

Remote sensing program

NASA Technical Reports Server (NTRS)

Liang, T.

1973-01-01

Research projects concerning the development and application of remote sensors are discussed. Some of the research projects conducted are as follows: (1) aerial photographic inventory of natural resources, (2) detection of buried river channels, (3) delineation of interconnected waterways, (4) plant indicators of atmospheric pollution, and (5) techniques for data transfer from photographs to base maps. On-going projects involving earth resources analyses are described.

Advancing Partnerships Towards an Integrated Approach to Oil Spill Response

NASA Astrophysics Data System (ADS)

Green, D. S.; Stough, T.; Gallegos, S. C.; Leifer, I.; Murray, J. J.; Streett, D.

2015-12-01

Oil spills can cause enormous ecological and economic devastation, necessitating application of the best science and technology available, and remote sensing is playing a growing critical role in the detection and monitoring of oil spills, as well as facilitating validation of remote sensing oil spill products. The FOSTERRS (Federal Oil Science Team for Emergency Response Remote Sensing) interagency working group seeks to ensure that during an oil spill, remote sensing assets (satellite/aircraft/instruments) and analysis techniques are quickly, effectively, appropriately, and seamlessly available to oil spills responders. Yet significant challenges remain for addressing oils spanning a vast range of chemical properties that may be spilled from the Tropics to the Arctic, with algorithms and scientific understanding needing advances to keep up with technology. Thus, FOSTERRS promotes enabling scientific discovery to ensure robust utilization of available technology as well as identifying technologies moving up the TRL (Technology Readiness Level). A recent FOSTERRS facilitated support activity involved deployment of the AVIRIS NG (Airborne Visual Infrared Imaging Spectrometer- Next Generation) during the Santa Barbara Oil Spill to validate the potential of airborne hyperspectral imaging to real-time map beach tar coverage including surface validation data. Many developing airborne technologies have potential to transition to space-based platforms providing global readiness.

High Data Rate Satellite Communications for Environmental Remote Sensing

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Method for Identifying Probable Archaeological Sites from Remotely Sensed Data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Comer, Douglas C.; Priebe, Carey E.; Sussman, Daniel

2011-01-01

Archaeological sites are being compromised or destroyed at a catastrophic rate in most regions of the world. The best solution to this problem is for archaeologists to find and study these sites before they are compromised or destroyed. One way to facilitate the necessary rapid, wide area surveys needed to find these archaeological sites is through the generation of maps of probable archaeological sites from remotely sensed data. We describe an approach for identifying probable locations of archaeological sites over a wide area based on detecting subtle anomalies in vegetative cover through a statistically based analysis of remotely sensed data from multiple sources. We further developed this approach under a recent NASA ROSES Space Archaeology Program project. Under this project we refined and elaborated this statistical analysis to compensate for potential slight miss-registrations between the remote sensing data sources and the archaeological site location data. We also explored data quantization approaches (required by the statistical analysis approach), and we identified a superior data quantization approached based on a unique image segmentation approach. In our presentation we will summarize our refined approach and demonstrate the effectiveness of the overall approach with test data from Santa Catalina Island off the southern California coast. Finally, we discuss our future plans for further improving our approach.

Research on the remote sensing methods of drought monitoring in Chongqing

NASA Astrophysics Data System (ADS)

Yang, Shiqi; Tang, Yunhui; Gao, Yanghua; Xu, Yongjin

2011-12-01

There are regional and periodic droughts in Chongqing, which impacted seriously on agricultural production and people's lives. This study attempted to monitor the drought in Chongqing with complex terrain using MODIS data. First, we analyzed and compared three remote sensing methods for drought monitoring (time series of vegetation index, temperature vegetation dryness index (TVDI), and vegetation supply water index (VSWI)) for the severe drought in 2006. Then we developed a remote sensing based drought monitoring model for Chongqing by combining soil moisture data and meteorological data. The results showed that the three remote sensing based drought monitoring models performed well in detecting the occurrence of drought in Chongqing on a certain extent. However, Time Series of Vegetation Index has stronger sensitivity in time pattern but weaker in spatial pattern; although TVDI and VSWI can reflect inverse the whole process of severe drought in 2006 summer from drought occurred - increased - relieved - increased again - complete remission in spatial domain, but TVDI requires the situation of extreme drought and extreme moist both exist in study area which it is more difficult in Chongqing; VSWI is simple and practicable, which the correlation coefficient between VSWI and soil moisture data reaches significant levels. In summary, VSWI is the best model for summer drought monitoring in Chongqing.

Scaling from instantaneous remote-sensing-based latent heat flux to daytime integrated value with the help of SiB2

NASA Astrophysics Data System (ADS)

Song, Yi; Ma, Mingguo; Li, Xin; Wang, Xufeng

2011-11-01

This research dealt with a daytime integration method with the help of Simple Biosphere Model, Version 2 (SiB2). The field observations employed in this study were obtained at the Yingke (YK) oasis super-station, which includes an Automatic Meteorological Station (AMS), an eddy covariance (EC) system and a Soil Moisture and Temperature Measuring System (SMTMS). This station is located in the Heihe River Basin, the second largest inland river basin in China. The remotely sensed data and field observations employed in this study were derived from Watershed Allied Telemetry Experimental Research (WATER). Daily variations of EF in temporal and spatial scale would be detected by using SiB2. An instantaneous midday EF was calculated based on a remote-sensing-based estimation of surface energy budget. The invariance of daytime EF was examined using the instantaneous midday EF calculated from a remote-sensing-based estimation. The integration was carried out using the constant EF method in the intervals with a steady EF. Intervals with an inconsistent EF were picked up and ET in these intervals was integrated separately. The truth validation of land Surface ET at satellite pixel scale was carried out using the measurement of eddy covariance (EC) system.

IR lasers in a struggle against dangerous cosmic objects

NASA Astrophysics Data System (ADS)

Kuzyakov, Boris A.

2001-03-01

Humanity can struggle with the small dangerous cosmic objects in our time and its parameter knowledge are needed. A present paper deals with prospects for the perspective of the laser methods applications for a dangerous asteroids discovering and a remote sensing and for the course correction systems of the influence expedients. The cosmic IR lasers will be used for remote sensing measurement of the various cosmic objects parameters: dimensions are more than 50 m, velocity is more than 10 km/s. The laser methods have the good perspectives among a large fleet of diagnostics technical means. The more effective CO2-laser parameters were defined for the solar systems smaller bodies velocity analysis. The laser is supplied with modulated laser radiation and an automatic tuning optical system. The CO2-lidars are needed for the asteroids detections and remote sensing at the distances of 30,000 km to 1 Mkm. A laser Doppler anemometer method with adaptive selection is used. The power calculations were made for the various asteroids in a cosmic space. The possibilities are estimated for remote sensing and for the course correction systems of the influence expedients also. The such system must be good for the distances nearby 12600 km, as the asteroids velocity can be more than 70 km/s.

Mapping Migratory Bird Prevalence Using Remote Sensing Data Fusion

PubMed Central

Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G.; Sun, Mindy; Simard, Marc; Holmes, Richard

2012-01-01

Background Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. Methodology and Principal Findings A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy (“fusion”) models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Conclusion and Significance Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level. PMID:22235254

Reliable clarity automatic-evaluation method for optical remote sensing images

NASA Astrophysics Data System (ADS)

Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen

2015-10-01

Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.

Mapping migratory bird prevalence using remote sensing data fusion.

PubMed

Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G; Sun, Mindy; Simard, Marc; Holmes, Richard

2012-01-01

Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level.

Advanced Doppler radar physiological sensing technique for drone detection

NASA Astrophysics Data System (ADS)

Yoon, Ji Hwan; Xu, Hao; Garcia Carrillo, Luis R.

2017-05-01

A 24 GHz medium-range human detecting sensor, using the Doppler Radar Physiological Sensing (DRPS) technique, which can also detect unmanned aerial vehicles (UAVs or drones), is currently under development for potential rescue and anti-drone applications. DRPS systems are specifically designed to remotely monitor small movements of non-metallic human tissues such as cardiopulmonary activity and respiration. Once optimized, the unique capabilities of DRPS could be used to detect UAVs. Initial measurements have shown that DRPS technology is able to detect moving and stationary humans, as well as largely non-metallic multi-rotor drone helicopters. Further data processing will incorporate pattern recognition to detect multiple signatures (motor vibration and hovering patterns) of UAVs.

Near-earth orbital guidance and remote sensing

NASA Technical Reports Server (NTRS)

Powers, W. F.

1972-01-01

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

Modular separation-based fiber-optic sensors for remote in situ monitoring.

PubMed

Dickens, J; Sepaniak, M

2000-02-01

A modular separation-based fiber-optic sensor (SBFOS) with an integrated electronically controlled injection device is described for potential use in remote environmental monitoring. An SBFOS is a chemical monitor that integrates the separation selectivity and versatility afforded by capillary electrophoresis with the remote and high sensitivity capabilities of fiber-optic-based laser-induced fluorescence sensing. The detection module of the SBFOS accommodates all essential sensing components for dual-optical fiber, on-capillary fluorescence detection. An injection module, similar to injection platforms on micro-analysis chips, is also integrated to the SBFOS. The injection module allows for electronically controlled injection of the sample onto the separation capillary. The design and operational characteristics of the modular SBFOS are discussed in this paper. A micellar electrokinetic capillary chromatography mode of separation is employed to evaluate the potential of the sensor for in situ monitoring of neutral toxins (aflatoxins). The analytical figures of merit for the modular SBFOS include analysis times of between 5 and 10 min, separation efficiencies of approximately 10(4) theoretical plates, detection limits for aflatoxins in the mid-to-low nanomolar range, and controllable operation that results in sensor performance that is largely immune to sample matrix effects.

Operational programs in forest management and priority in the utilization of remote sensing

NASA Technical Reports Server (NTRS)

Douglass, R. W.

1978-01-01

A speech is given on operational remote sensing programs in forest management and the importance of remote sensing in forestry is emphasized. Forest service priorities in using remote sensing are outlined.

Remote sensing, land use, and demography - A look at people through their effects on the land

NASA Technical Reports Server (NTRS)

Paul, C. K.; Landini, A. J.

1976-01-01

Relevant causes of failure by the remote sensing community in the urban scene are analyzed. The reasons for the insignificant role of remote sensing in urban land use data collection are called the law of realism, the incompatibility of remote sensing and urban management system data formats is termed the law of nominal/ordinal systems compatibility, and the land use/population correlation dilemma is referred to as the law of missing persons. The study summarizes the three laws of urban land use information for which violations, avoidance, or ignorance have caused the decline of present remote sensing research. Particular attention is given to the rationale for urban land use information and for remote sensing. It is shown that remote sensing of urban land uses compatible with the three laws can be effectively developed by realizing the 10 percent contribution of remote sensing to urban land use planning data collection.

Thematic Conference on Geologic Remote Sensing, 8th, Denver, CO, Apr. 29-May 2, 1991, Proceedings. Vols. 1 & 2

NASA Technical Reports Server (NTRS)

1991-01-01

The proceedings contain papers discussing the state-of-the-art exploration, engineering, and environmental applications of geologic remote sensing, along with the research and development activities aimed at increasing the future capabilities of this technology. The following topics are addressed: spectral geology, U.S. and international hydrocarbon exporation, radar and thermal infrared remote sensing, engineering geology and hydrogeology, mineral exploration, remote sensing for marine and environmental applications, image processing and analysis, geobotanical remote sensing, and data integration and geographic information systems. Particular attention is given to spectral alteration mapping with imaging spectrometers, mapping the coastal plain of the Congo with airborne digital radar, applications of remote sensing techniques to the assessment of dam safety, remote sensing of ferric iron minerals as guides for gold exploration, principal component analysis for alteration mappping, and the application of remote sensing techniques for gold prospecting in the north Fujian province.

Methods of training the graduate level and professional geologist in remote sensing technology

NASA Technical Reports Server (NTRS)

Kolm, K. E.

1981-01-01

Requirements for a basic course in remote sensing to accommodate the needs of the graduate level and professional geologist are described. The course should stress the general topics of basic remote sensing theory, the theory and data types relating to different remote sensing systems, an introduction to the basic concepts of computer image processing and analysis, the characteristics of different data types, the development of methods for geological interpretations, the integration of all scales and data types of remote sensing in a given study, the integration of other data bases (geophysical and geochemical) into a remote sensing study, and geological remote sensing applications. The laboratories should stress hands on experience to reinforce the concepts and procedures presented in the lecture. The geologist should then be encouraged to pursue a second course in computer image processing and analysis of remotely sensed data.

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, J. A.

1993-01-01

Progress report on remote sensing of Earth terrain covering the period from Jan. to June 1993 is presented. Areas of research include: radiative transfer model for active and passive remote sensing of vegetation canopy; polarimetric thermal emission from rough ocean surfaces; polarimetric passive remote sensing of ocean wind vectors; polarimetric thermal emission from periodic water surfaces; layer model with tandom spheriodal scatterers for remote sensing of vegetation canopy; application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated mie scatterers with size distributions and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

Flat Surface Damage Detection System (FSDDS)

NASA Technical Reports Server (NTRS)

Williams, Martha; Lewis, Mark; Gibson, Tracy; Lane, John; Medelius, Pedro; Snyder, Sarah; Ciarlariello, Dan; Parks, Steve; Carrejo, Danny; Rojdev, Kristina

2013-01-01

The Flat Surface Damage Detection system (FSDDS} is a sensory system that is capable of detecting impact damages to surfaces utilizing a novel sensor system. This system will provide the ability to monitor the integrity of an inflatable habitat during in situ system health monitoring. The system consists of three main custom designed subsystems: the multi-layer sensing panel, the embedded monitoring system, and the graphical user interface (GUI). The GUI LABVIEW software uses a custom developed damage detection algorithm to determine the damage location based on the sequence of broken sensing lines. It estimates the damage size, the maximum depth, and plots the damage location on a graph. Successfully demonstrated as a stand alone technology during 2011 D-RATS. Software modification also allowed for communication with HDU avionics crew display which was demonstrated remotely (KSC to JSC} during 2012 integration testing. Integrated FSDDS system and stand alone multi-panel systems were demonstrated remotely and at JSC, Mission Operations Test using Space Network Research Federation (SNRF} network in 2012. FY13, FSDDS multi-panel integration with JSC and SNRF network Technology can allow for integration with other complementary damage detection systems.

Electromagnetic Remote Sensing. Low Frequency Electromagnetics

DTIC Science & Technology

1989-01-01

biased superconducting point - contact quantum devices", J.Appl.Phys. 41, p.1572, 1970. [40] A.Yariv and H.Winsor, "Proposal for detection of magnetic ... magnetics , electromagnetic induc- tion, electrostatics) 2. Nondestructive testing (electromagnetic induction, neutron tomography, x-ray imaging) 3...Detection of submarines from aircraft or ships ( magnetics , electromagnetic induction) 4. Detection of land vehicles using buried sensors ( magnetics

Optical detection of oil on water

NASA Technical Reports Server (NTRS)

Millard, J. P.; Arvesen, J. C.

1973-01-01

Three radiometric techniques utilizing sunlight reflected and backscattered from water bodies have potential application for remote sensing of oil spills. Oil on water can be detected by viewing perpendicular polarization component of reflected light or difference between polarization components. Best detection is performed in ultraviolet or far-red portions of spectrum and in azimuth directions toward or opposite sun.

Remote sensing by satellite - Technical and operational implications for international cooperation

NASA Technical Reports Server (NTRS)

Doyle, S. E.

1976-01-01

International cooperation in the U.S. Space Program is discussed and related to the NASA program for remote sensing of the earth. Satellite remote sensing techniques are considered along with the selection of the best sensors and wavelength bands. The technology of remote sensing satellites is considered with emphasis on the Landsat system configuration. Future aspects of remote sensing satellites are considered.

Assessing the performance of remotely-sensed flooding indicators and their potential contribution to early warning for leptospirosis in Cambodia

PubMed Central

Ledien, Julia; Sorn, Sopheak; Hem, Sopheak; Huy, Rekol; Buchy, Philippe

2017-01-01

Remote sensing can contribute to early warning for diseases with environmental drivers, such as flooding for leptospirosis. In this study we assessed whether and which remotely-sensed flooding indicator could be used in Cambodia to study any disease for which flooding has already been identified as an important driver, using leptospirosis as a case study. The performance of six potential flooding indicators was assessed by ground truthing. The Modified Normalized Difference Water Index (MNDWI) was used to estimate the Risk Ratio (RR) of being infected by leptospirosis when exposed to floods it detected, in particular during the rainy season. Chi-square tests were also calculated. Another variable—the time elapsed since the first flooding of the year—was created using MNDWI values and was also included as explanatory variable in a generalized linear model (GLM) and in a boosted regression tree model (BRT) of leptospirosis infections, along with other explanatory variables. Interestingly, MNDWI thresholds for both detecting water and predicting the risk of leptospirosis seroconversion were independently evaluated at -0.3. Value of MNDWI greater than -0.3 was significantly related to leptospirosis infection (RR = 1.61 [1.10–1.52]; χ2 = 5.64, p-value = 0.02, especially during the rainy season (RR = 2.03 [1.25–3.28]; χ2 = 8.15, p-value = 0.004). Time since the first flooding of the year was a significant risk factor in our GLM model (p-value = 0.042). These results suggest that MNDWI may be useful as a risk indicator in an early warning remote sensing tool for flood-driven diseases like leptospirosis in South East Asia. PMID:28704461

Assessing the performance of remotely-sensed flooding indicators and their potential contribution to early warning for leptospirosis in Cambodia.

PubMed

Ledien, Julia; Sorn, Sopheak; Hem, Sopheak; Huy, Rekol; Buchy, Philippe; Tarantola, Arnaud; Cappelle, Julien

2017-01-01

Remote sensing can contribute to early warning for diseases with environmental drivers, such as flooding for leptospirosis. In this study we assessed whether and which remotely-sensed flooding indicator could be used in Cambodia to study any disease for which flooding has already been identified as an important driver, using leptospirosis as a case study. The performance of six potential flooding indicators was assessed by ground truthing. The Modified Normalized Difference Water Index (MNDWI) was used to estimate the Risk Ratio (RR) of being infected by leptospirosis when exposed to floods it detected, in particular during the rainy season. Chi-square tests were also calculated. Another variable-the time elapsed since the first flooding of the year-was created using MNDWI values and was also included as explanatory variable in a generalized linear model (GLM) and in a boosted regression tree model (BRT) of leptospirosis infections, along with other explanatory variables. Interestingly, MNDWI thresholds for both detecting water and predicting the risk of leptospirosis seroconversion were independently evaluated at -0.3. Value of MNDWI greater than -0.3 was significantly related to leptospirosis infection (RR = 1.61 [1.10-1.52]; χ2 = 5.64, p-value = 0.02, especially during the rainy season (RR = 2.03 [1.25-3.28]; χ2 = 8.15, p-value = 0.004). Time since the first flooding of the year was a significant risk factor in our GLM model (p-value = 0.042). These results suggest that MNDWI may be useful as a risk indicator in an early warning remote sensing tool for flood-driven diseases like leptospirosis in South East Asia.

Integrating remote sensing with species distribution models; Mapping tamarisk invasions using the Software for Assisted Habitat Modeling (SAHM)

USGS Publications Warehouse

West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Young, Nicholas E.; Stohlgren, Thomas J.; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan

2016-01-01

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

An Experimental Global Monitoring System for Rainfall-triggered Landslides using Satellite Remote Sensing Information

NASA Technical Reports Server (NTRS)

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

2006-01-01

Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of extensive ground-based observing network in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing an experimental real-time monitoring system to detect rainfall-triggered landslides is proposed by combining two necessary components: surface landslide susceptibility and a real-time space-based rainfall analysis system (http://trmm.gsfc.nasa.aov). First, a global landslide susceptibility map is derived from a combination of semi-static global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a GIs weighted linear combination approach. Second, an adjusted empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess landslide risks at areas with high susceptibility. A major outcome of this work is the availability of a first-time global assessment of landslide risk, which is only possible because of the utilization of global satellite remote sensing products. This experimental system can be updated continuously due to the availability of new satellite remote sensing products. This proposed system, if pursued through wide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and risk mitigation activities across the world.

Utility of BRDF Models for Estimating Optimal View Angles in Classification of Remotely Sensed Images

NASA Technical Reports Server (NTRS)

Valdez, P. F.; Donohoe, G. W.

1997-01-01

Statistical classification of remotely sensed images attempts to discriminate between surface cover types on the basis of the spectral response recorded by a sensor. It is well known that surfaces reflect incident radiation as a function of wavelength producing a spectral signature specific to the material under investigation. Multispectral and hyperspectral sensors sample the spectral response over tens and even hundreds of wavelength bands to capture the variation of spectral response with wavelength. Classification algorithms then exploit these differences in spectral response to distinguish between materials of interest. Sensors of this type, however, collect detailed spectral information from one direction (usually nadir); consequently, do not consider the directional nature of reflectance potentially detectable at different sensor view angles. Improvements in sensor technology have resulted in remote sensing platforms capable of detecting reflected energy across wavelengths (spectral signatures) and from multiple view angles (angular signatures) in the fore and aft directions. Sensors of this type include: the moderate resolution imaging spectroradiometer (MODIS), the multiangle imaging spectroradiometer (MISR), and the airborne solid-state array spectroradiometer (ASAS). A goal of this paper, then, is to explore the utility of Bidirectional Reflectance Distribution Function (BRDF) models in the selection of optimal view angles for the classification of remotely sensed images by employing a strategy of searching for the maximum difference between surface BRDFs. After a brief discussion of directional reflect ante in Section 2, attention is directed to the Beard-Maxwell BRDF model and its use in predicting the bidirectional reflectance of a surface. The selection of optimal viewing angles is addressed in Section 3, followed by conclusions and future work in Section 4.

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM).

PubMed

West, Amanda M; Evangelista, Paul H; Jarnevich, Catherine S; Young, Nicholas E; Stohlgren, Thomas J; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan

2016-10-11

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

Hyperspectral remote sensing tools for quantifying plant litter and invasive species in arid ecosystems

USGS Publications Warehouse

Nagler, Pamela L.; Sridhar, B.B. Maruthi; Olsson, Aaryn Dyami; Glenn, Edward P.; van Leeuwen, Willem J.D.; Thenkabail, Prasad S.; Huete, Alfredo; Lyon, John G.

2012-01-01

Green vegetation can be distinguished using visible and infrared multi-band and hyperspectral remote sensing methods. The problem has been in identifying and distinguishing the non-photosynthetically active radiation (PAR) landscape components, such as litter and soils, and from green vegetation. Additionally, distinguishing different species of green vegetation is challenging using the relatively few bands available on most satellite sensors. This chapter focuses on hyperspectral remote sensing characteristics that aim to distinguish between green vegetation, soil, and litter (or senescent vegetation). Quantifying litter by remote sensing methods is important in constructing carbon budgets of natural and agricultural ecosystems. Distinguishing between plant types is important in tracking the spread of invasive species. Green leaves of different species usually have similar spectra, making it difficult to distinguish between species. However, in this chapter we show that phenological differences between species can be used to detect some invasive species by their distinct patterns of greening and dormancy over an annual cycle based on hyperspectral data. Both applications require methods to quantify the non-green cellulosic fractions of plant tissues by remote sensing even in the presence of soil and green plant cover. We explore these methods and offer three case studies. The first concerns distinguishing surface litter from soil using the Cellulose Absorption Index (CAI), as applied to no-till farming practices where plant litter is left on the soil after harvest. The second involves using different band combinations to distinguish invasive saltcedar from agricultural and native riparian plants on the Lower Colorado River. The third illustrates the use of the CAI and NDVI in time-series analyses to distinguish between invasive buffelgrass and native plants in a desert environment in Arizona. Together the results show how hyperspectral imagery can be applied to solve problems that are not amendable to solution by the simple band combinations normally used in remote sensing.

Intercomparison of Remotely Sensed Vegetation Indices, Ground Spectroscopy, and Foliar Chemistry Data from NEON

NASA Astrophysics Data System (ADS)

Hulslander, D.; Warren, J. N.; Weintraub, S. R.

2017-12-01

Hyperspectral imaging systems can be used to produce spectral reflectance curves giving rich information about composition, relative abundances of materials, mixes and combinations. Indices based on just a few spectral bands have been used for over 40 years to study vegetation health, mineral abundance, and more. These indices are much simpler to visualize and use than a full hyperspectral data set which may contain over 400 bands. Yet historically, it has been difficult to directly relate remotely sensed spectral indices to quantitative biophysical properties significant to forest ecology such as canopy nitrogen, lignin, and chlorophyll. This linkage is a critical piece in enabling the detection of high value ecological information, usually only available from labor-intensive canopy foliar chemistry sampling, to the geographic and temporal coverage available via remote sensing. Previous studies have shown some promising results linking ground-based data and remotely sensed indices, but are consistently limited in time, geographic extent, and land cover type. Moreover, previous studies are often focused on tuning linkage algorithms for the purpose of achieving good results for only one study site or one type of vegetation, precluding development of more generalized algorithms. The National Ecological Observatory Network (NEON) is a unique system of 47 terrestrial sites covering all of the major eco-climatic domains of the US, including AK, HI, and Puerto Rico. These sites are regularly monitored and sampled using uniform instrumentation and protocols, including both foliar chemistry sampling and remote sensing flights for high resolution hyperspectral, LiDAR, and digital camera data acquisition. In this study we compare the results of foliar chemistry analysis to the remote sensing vegetation indices and investigate possible sources for variance and difference through the use of the larger hyperspectral dataset as well as ground based spectrometer measurements of samples subsequently analyzed for foliar chemistry.

Remote sensing in operational range management programs in Western Canada

NASA Technical Reports Server (NTRS)

Thompson, M. D.

1977-01-01

A pilot program carried out in Western Canada to test remote sensing under semi-operational conditions and display its applicability to operational range management programs was described. Four agencies were involved in the program, two in Alberta and two in Manitoba. Each had different objectives and needs for remote sensing within its range management programs, and each was generally unfamiliar with remote sensing techniques and their applications. Personnel with experience and expertise in the remote sensing and range management fields worked with the agency personnel through every phase of the pilot program. Results indicate that these agencies have found remote sensing to be a cost effective tool and will begin to utilize remote sensing in their operational work during ensuing seasons.

Effects of image spatial and radiometric resolutions on the detection of cotton plants

USDA-ARS?s Scientific Manuscript database

Accurate and timely detection of volunteer and regrowth cotton plants is important for the eradication of boll weevils in south Texas. Airborne remote sensing imagery has the potential to identify volunteer and regrowth cotton plants over large geographic regions. The objective of this study was to ...

Effect of spatial image support in detecting long-term vegetation change from satellite time-series

USDA-ARS?s Scientific Manuscript database

Context Arid rangelands have been severely degraded over the past century. Multi-temporal remote sensing techniques are ideally suited to detect significant changes in ecosystem state; however, considerable uncertainty exists regarding the effects of changing image resolution on their ability to de...

Remote Sensing of Aerosol and their Radiative Forcing of Climate

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Tanre, Didier; Remer, Lorraine A.

1999-01-01

Remote sensing of aerosol and aerosol radiative forcing of climate is going through a major transformation. The launch in next few years of new satellites designed specifically for remote sensing of aerosol is expected to further revolutionized aerosol measurements: until five years ago satellites were not designed for remote sensing of aerosol. Aerosol optical thickness was derived as a by product, only over the oceans using one AVHRR channel with errors of approx. 50%. However it already revealed a very important first global picture of the distribution and sources of aerosol. In the last 5 years we saw the introduction of polarization and multi-view observations (POLDER and ATSR) for satellite remote sensing of aerosol over land and ocean. Better products are derived from AVHRR using its two channels. The new TOMS aerosol index shows the location and transport of aerosol over land and ocean. Now we anticipate the launch of EOS-Terra with MODIS, MISR and CERES on board for multi-view, multi-spectral remote sensing of aerosol and its radiative forcing. This will allow application of new techniques, e.g. using a wide spectral range (0.55-2.2 microns) to derive precise optical thickness, particle size and mass loading. Aerosol is transparent in the 2.2 microns channel, therefore this channel can be used to detect surface features that in turn are used to derive the aerosol optical thickness in the visible part of the spectrum. New techniques are developed to derive the aerosol single scattering albedo, a measure of absorption of sunlight, and techniques to derive directly the aerosol forcing at the top of the atmosphere. In the last 5 years a global network of sun/sky radiometers was formed, designed to communicate in real time the spectral optical thickness from 50-80 locations every day, every 15 minutes. The sky angular and spectral information is also measured and used to retrieve the aerosol size distribution, refractive index, single scattering albedo and the spectral flux reaching the surface. Effort to introduce remote sensing from lidars will literally additional dimension to aerosol remote sensing. The vertical dimension is a critical link between the global satellite observations and modeling of aerosol transport. Lidars are also critical to study aerosol impact on cloud microphysics and reflectance. Both lidar ground networks and satellite systems are in development. This new capability is expected to put remote sensing in the forefront of aerosol and climate studies. Together with field experiments, chemical analysis and chemical transport models we anticipate, in the next decade, to be able to resolve some of the outstanding questions regarding the role of aerosol in climate, in atmospheric chemistry and its influence on human health and life on this planet.

Study on environment detection and appraisement of mining area with RS

NASA Astrophysics Data System (ADS)

Yang, Fengjie; Hou, Peng; Zhou, Guangzhu; Li, Qingting; Wang, Jie; Cheng, Jianguang

2006-12-01

In this paper, the big coal mining area Yanzhou is selected as the typical research area. According to the special dynamic change characteristic of the environment in the mining area, the environmental dynamic changes are timely monitored with the remote sensing detection technology. Environmental special factors, such as vegetation, water, air, land-over, are extracted by the professional remote sensing image processing software, then the spatial information is managed and analyzed in the geographical information system (GIS) software. As the result, the dynamic monitor and query for change information is achieved, and the special environmental factor dynamic change maps are protracted. On the base of the data coming from the remote sensing image, GIS and the traditional environment monitoring, the environmental quality is appraised with the method of indistinct matrix analysis, the multi-index and the analytical hierarchy process. At last, those provide the credible science foundation for the local environment appraised and the sustained development. In addition, this paper apply the hyper spectrum graphs by the FieldSpec Pro spectroradiometer, together with the analytical data from environmental chemical, to study the growth of vegetation which were seed in the land-over consisting of gangue, which is a new method to study the impact to vegetation that are growing in the soil.

Remote sensing of atmospheric NO2 by employing the continuous-wave differential absorption lidar technique.

PubMed

Mei, Liang; Guan, Peng; Kong, Zheng

2017-10-02

Differential absorption lidar (DIAL) technique employed for remote sensing has been so far based on the sophisticated narrow-band pulsed laser sources, which require intensive maintenance during operation. In this work, a continuous-wave (CW) NO 2 DIAL system based on the Scheimpflug principle has been developed by employing a compact high-power CW multimode 450 nm laser diode as the light source. Laser emissions at the on-line and off-line wavelengths of the NO 2 absorption spectrum are implemented by tuning the injection current of the laser diode. Lidar signals are detected by a 45° tilted area CCD image sensor satisfying the Scheimpflug principle. Range-resolved NO 2 concentrations on a near-horizontal path are obtained by the NO 2 DIAL system in the range of 0.3-3 km and show good agreement with those measured by a conventional air pollution monitoring station. A detection sensitivity of ± 0.9 ppbv at 95% confidence level in the region of 0.3-1 km is achieved with 15-minute averaging and 700 m range resolution during hours of darkness, which allows accurate concentration measurement of ambient NO 2 . The low-cost and robust DIAL system demonstrated in this work opens up many possibilities for field NO 2 remote sensing applications.

Remote sensing in precision farming: real-time monitoring of water and fertilizer requirements of agricultural crops

NASA Astrophysics Data System (ADS)

Zilberman, Arkadi; Ben Asher, Jiftah; Kopeika, Norman S.

2016-10-01

The advancements in remote sensing in combination with sensor technology (both passive and active) enable growers to analyze an entire crop field as well as its local features. In particular, changes of actual evapo-transpiration (ET) as a function of water availability can be measured remotely with infrared radiometers. Detection of crop water stress and ET and combining it with the soil water flow model enable rational irrigation timing and application amounts. Nutrient deficiency, and in particular nitrogen deficiency, causes substantial crop losses. This deficiency needs to be identified immediately. A faster the detection and correction, a lesser the damage to the crop yield. In the present work, to retrieve ET a novel deterministic approach was used which is based on the remote sensing data. The algorithm can automatically provide timely valuable information on plant and soil water status, which can improve the management of irrigated crops. The solution is capable of bridging between Penman-Monteith ET model and Richards soil water flow model. This bridging can serve as a preliminary tool for expert irrigation system. To support decisions regarding fertilizers the greenness of plant canopies is assessed and quantified by using the spectral reflectance sensors and digital color imaging. Fertilization management can be provided on the basis of sampling and monitoring of crop nitrogen conditions using RS technique and translating measured N concentration in crop to kg/ha N application in the field.

Thin Cloud Detection Method by Linear Combination Model of Cloud Image

NASA Astrophysics Data System (ADS)

Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.

2018-04-01

The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.

[Detection of oil spills on water by differential polarization FTIR spectrometry].

PubMed

Yuan, Yue-ming; Xiong, Wei; Fang, Yong-hua; Lan, Tian-ge; Li, Da-cheng

2010-08-01

Detection of oil spills on water, by traditional thermal remote sensing, is based on the radiance contrast between the large area of clean water and the polluted area of water. And the categories of oil spills can not be identified by analysing the thermal infrared image. In order to find out the extent of pollution and identify the oil contaminants, an approach to the passive detection of oil spills on water by differential polarization FTIR spectrometry is proposed. This approach can detect the contaminants by obtaining and analysing the subtracted spectrum of horizontal and vertical polarization intensity spectrum. In the present article, the radiance model of differential polarization FTIR spectrometry is analysed, and an experiment about detection of No. O diesel and SF96 film on water by this method is presented. The results of this experiment indicate that this method can detect the oil contaminants on water without radiance contrast with clean water, and it also can identify oil spills by analysing the spectral characteristic of differential polarization FTIR spectrum. So it well makes up for the shortage of traditional thermal remote sensing on detecting oil spills on water.

Remote sensing in Michigan for land resource management

NASA Technical Reports Server (NTRS)

Lowe, D. S.; Istvan, L. B.; Roller, N. E. G.; Prentice, V. L.

1976-01-01

The Environmental Research Institute of Michigan is conducting a program whose goal is the large-scale adoption, by both public agencies and private interests in Michigan, of NASA earth-resource survey technology as an important aid in the solution of current problems in resource management and environmental protection. During the period from June 1975 to June 1976, remote sensing techniques to aid Michigan government agencies were used to achieve the following major results: (1) supply justification for public acquisition of land to establish the St. John's Marshland Recreation Area; (2) recommend economical and effective methods for performing a statewide wetlands survey; (3) assist in the enforcement of state laws relating to sand and gravel mining, soil erosion and sedimentation, and shorelands protection; (4) accomplish a variety of regional resource management actions in the East Central Michigan Planning and Development Region. Other tasks on which remote sensing technology was used include industrial and school site selection, ice detachment in the Soo Harbor, grave detection, and data presentation for wastewater management programs.

Remote sensing the plasmasphere, plasmapause, plumes and other features using ground-based magnetometers

NASA Astrophysics Data System (ADS)

Menk, Frederick; Kale, Zoë; Sciffer, Murray; Robinson, Peter; Waters, Colin; Grew, Russell; Clilverd, Mark; Mann, Ian

2014-11-01

The plasmapause is a highly dynamic boundary between different magnetospheric particle populations and convection regimes. Some of the most important space weather processes involve wave-particle interactions in this region, but wave properties may also be used to remote sense the plasmasphere and plasmapause, contributing to plasmasphere models. This paper discusses the use of existing ground magnetometer arrays for such remote sensing. Using case studies we illustrate measurement of plasmapause location, shape and movement during storms; refilling of flux tubes within and outside the plasmasphere; storm-time increase in heavy ion concentration near the plasmapause; and detection and mapping of density irregularities near the plasmapause, including drainage plumes, biteouts and bulges. We also use a 2D MHD model of wave propagation through the magnetosphere, incorporating a realistic ionosphere boundary and Alfvén speed profile, to simulate ground array observations of power and cross-phase spectra, hence confirming the signatures of plumes and other density structures.

A Terminal Area Icing Remote Sensing System

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Serke, David J.

2014-01-01

NASA and the National Center for Atmospheric Research (NCAR) have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology is now being extended to provide volumetric coverage surrounding an airport. With volumetric airport terminal area coverage, the resulting icing hazard information will be usable by aircrews, traffic control, and airline dispatch to make strategic and tactical decisions regarding routing when conditions are conducive to airframe icing. Building on the existing vertical pointing system, the new method for providing volumetric coverage will utilize cloud radar, microwave radiometry, and NEXRAD radar. This terminal area icing remote sensing system will use the data streams from these instruments to provide icing hazard classification along the defined approach paths into an airport. Strategies for comparison to in-situ instruments on aircraft and weather balloons for a planned NASA field test are discussed, as are possible future applications into the NextGen airspace system.

a Novel Framework for Remote Sensing Image Scene Classification

NASA Astrophysics Data System (ADS)

Jiang, S.; Zhao, H.; Wu, W.; Tan, Q.

2018-04-01

High resolution remote sensing (HRRS) images scene classification aims to label an image with a specific semantic category. HRRS images contain more details of the ground objects and their spatial distribution patterns than low spatial resolution images. Scene classification can bridge the gap between low-level features and high-level semantics. It can be applied in urban planning, target detection and other fields. This paper proposes a novel framework for HRRS images scene classification. This framework combines the convolutional neural network (CNN) and XGBoost, which utilizes CNN as feature extractor and XGBoost as a classifier. Then, this framework is evaluated on two different HRRS images datasets: UC-Merced dataset and NWPU-RESISC45 dataset. Our framework achieved satisfying accuracies on two datasets, which is 95.57 % and 83.35 % respectively. From the experiments result, our framework has been proven to be effective for remote sensing images classification. Furthermore, we believe this framework will be more practical for further HRRS scene classification, since it costs less time on training stage.

Remote sensing inputs to water demand modeling

NASA Technical Reports Server (NTRS)

Estes, J. E.; Jensen, J. R.; Tinney, L. R.; Rector, M.

1975-01-01

In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.

Remote sensing captures varying temporal patterns of vegetation between human-altered and natural landscapes.

PubMed

Leong, Misha; Roderick, George K

2015-01-01

Global change has led to shifts in phenology, potentially disrupting species interactions such as plant-pollinator relationships. Advances in remote sensing techniques allow one to detect vegetation phenological diversity between different land use types, but it is not clear how this translates to other communities in the ecosystem. Here, we investigated the phenological diversity of the vegetation across a human-altered landscape including urban, agricultural, and natural land use types. We found that the patterns of change in the vegetation indices (EVI and NDVI) of human-altered landscapes are out of synchronization with the phenology in neighboring natural California grassland habitat. Comparing these findings to a spatio-temporal pollinator distribution dataset, EVI and NDVI were significant predictors of total bee abundance, a relationship that improved with time lags. This evidence supports the importance of differences in temporal dynamics between land use types. These findings also highlight the potential to utilize remote sensing data to make predictions for components of biodiversity that have tight vegetation associations, such as pollinators.

Arc Fault Detection & Localization by Electromagnetic-Acoustic Remote Sensing

NASA Astrophysics Data System (ADS)

Vasile, C.; Ioana, C.

2017-05-01

Electrical arc faults that occur in photovoltaic systems represent a danger due to their economic impact on production and distribution. In this paper we propose a complete system, with focus on the methodology, that enables the detection and localization of the arc fault, by the use of an electromagnetic-acoustic sensing system. By exploiting the multiple emissions of the arc fault, in conjunction with a real-time detection signal processing method, we ensure accurate detection and localization. In its final form, this present work will present in greater detail the complete system, the methods employed, results and performance, alongside further works that will be carried on.

Recent Advances in Remote Sensing of Natural Hazards-Induced Atmospheric and Ionospheric Perturbations

NASA Astrophysics Data System (ADS)

Yang, Y. M.; Komjathy, A.; Meng, X.; Verkhoglyadova, O. P.; Langley, R. B.; Mannucci, A. J.

2015-12-01

Traveling ionospheric disturbances (TIDs) induced by acoustic-gravity waves in the neutral atmosphere have significant impact on trans-ionospheric radio waves such as Global Navigation Satellite System (GNSS, including Global Position System (GPS)) measurements. Natural hazards and solid Earth events, such as earthquakes, tsunamis and volcanic eruptions are actual sources that may trigger acoustic and gravity waves resulting in traveling ionospheric disturbances (TIDs) in the upper atmosphere. Trans-ionospheric radio wave measurements sense the total electron content (TEC) along the signal propagation path. In this research, we introduce a novel GPS-based detection and estimation technique for remote sensing of atmospheric wave-induced TIDs including space weather phenomena induced by major natural hazard events, using TEC time series collected from worldwide ground-based dual-frequency GNSS (including GPS) receiver networks. We demonstrate the ability of using ground- and space-based dual-frequency GPS measurements to detect and monitor tsunami wave propagation from the 2011 Tohoku-Oki earthquake and tsunami. Major wave trains with different propagation speeds and wavelengths were identified through analysis of the GPS remote sensing observations. Dominant physical characteristics of atmospheric wave-induced TIDs are found to be associated with specific tsunami propagations and oceanic Rayleigh waves. In this research, we compared GPS-based observations, corresponding model simulations and tsunami wave propagation. Results are shown to lead to a better understanding of the tsunami-induced ionosphere responses. Based on current distribution of Plate Boundary Observatory GPS stations, the results indicate that tsunami-induced TIDs may be detected about 60 minutes prior to tsunamis arriving at the U.S. west coast. It is expected that this GNSS-based technology will become an integral part of future early-warning systems.

PROCEEDINGS OF THE FOURTH SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT; 12, 13, 14 APRIL 1966.

DTIC Science & Technology

The symposium was conducted as part of a continuing program investigating the field of remote sensing , its potential in scientific research and...information on all aspects of remote sensing , with special emphasis on such topics as needs for remotely sensed data, data management, and the special... remote sensing programs, data acquisition, data analysis and application, and equipment design, were presented. (Author)