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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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 in marine environment - acquiring, processing, and interpreting GLORIA sidescan sonor images of deep sea floor

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

O'Leary, D.W.

1989-03-01

The US Geological Survey's remote sensing instrument for regional imaging of the deep sea floor (> 400 m water depth) is the GLORIA (Geologic Long-Range Inclined Asdic) sidescan sonar system, designed and operated by the British Institute of Oceanographic Sciences. A 30-sec sweep rate provides for a swath width of approximately 45 km, depending on water depth. The return signal is digitally recorded as 8 bit data to provide a cross-range pixel dimension of 50 m. Postcruise image processing is carried out by using USGS software. Processing includes precision water-column removal, geometric and radiometric corrections, and contrast enhancement. Mosaicking includesmore » map grid fitting, concatenation, and tone matching. Seismic reflection profiles, acquired along track during the survey, are image correlative and provide a subsurface dimension unique to marine remote sensing. Generally GLORIA image interpretation is based on brightness variations which are largely a function of (1) surface roughness at a scale of approximately 1 m and (2) slope changes of more than about 4/degrees/ over distances of at least 50 m. Broader, low-frequency changes in slope that cannot be detected from the Gloria data can be determined from seismic profiles. Digital files of bathymetry derived from echo-sounder data can be merged with GLORIA image data to create relief models of the sea floor for geomorphic interpretation of regional slope effects.« less

Ontology-based classification of remote sensing images using spectral rules

NASA Astrophysics Data System (ADS)

Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

2017-05-01

Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

Conference of Remote Sensing Educators (CORSE-78)

NASA Technical Reports Server (NTRS)

1978-01-01

Ways of improving the teaching of remote sensing students at colleges and universities are discussed. Formal papers and workshops on various Earth resources disciplines, image interpretation, and data processing concepts are presented. An inventory of existing remote sensing and related subject courses being given in western regional universities is included.

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

PubMed

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

2018-01-01

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

A modified approach combining FNEA and watershed algorithms for segmenting remotely-sensed optical images

NASA Astrophysics Data System (ADS)

Liu, Likun

2018-01-01

In the field of remote sensing image processing, remote sensing image segmentation is a preliminary step for later analysis of remote sensing image processing and semi-auto human interpretation, fully-automatic machine recognition and learning. Since 2000, a technique of object-oriented remote sensing image processing method and its basic thought prevails. The core of the approach is Fractal Net Evolution Approach (FNEA) multi-scale segmentation algorithm. The paper is intent on the research and improvement of the algorithm, which analyzes present segmentation algorithms and selects optimum watershed algorithm as an initialization. Meanwhile, the algorithm is modified by modifying an area parameter, and then combining area parameter with a heterogeneous parameter further. After that, several experiments is carried on to prove the modified FNEA algorithm, compared with traditional pixel-based method (FCM algorithm based on neighborhood information) and combination of FNEA and watershed, has a better segmentation result.

Geomorphology, tectonics, and exploration

NASA Technical Reports Server (NTRS)

Sabins, F. F., Jr.

1985-01-01

Explorationists interpret satellite images for tectonic features and patterns that may be clues to mineral and energy deposits. The tectonic features of interest range in scale from regional (sedimentary basins, fold belts) to local (faults, fractures) and are generally expressed as geomorphic features in remote sensing images. Explorationists typically employ classic concepts of geomorphology and landform analysis for their interpretations, which leads to the question - Are there new and evolving concepts in geomorphology that may be applicable to tectonic analyses of images?

Remote sensing: a tool for park planning and management

USGS Publications Warehouse

Draeger, William C.; Pettinger, Lawrence R.

1981-01-01

Remote sensing may be defined as the science of imaging or measuring objects from a distance. More commonly, however, the term is used in reference to the acquisition and use of photographs, photo-like images, and other data acquired from aircraft and satellites. Thus, remote sensing includes the use of such diverse materials as photographs taken by hand from a light aircraft, conventional aerial photographs obtained with a precision mapping camera, satellite images acquired with sophisticated scanning devices, radar images, and magnetic and gravimetric data that may not even be in image form. Remotely sensed images may be color or black and white, can vary in scale from those that cover only a few hectares of the earth's surface to those that cover tens of thousands of square kilometers, and they may be interpreted visually or with the assistance of computer systems. This article attempts to describe several of the commonly available types of remotely sensed data, to discuss approaches to data analysis, and to demonstrate (with image examples) typical applications that might interest managers of parks and natural areas.

Looking back to inform the future: The role of cognition in forest disturbance characterization from remote sensing imagery

NASA Astrophysics Data System (ADS)

Bianchetti, Raechel Anne

Remotely sensed images have become a ubiquitous part of our daily lives. From novice users, aiding in search and rescue missions using tools such as TomNod, to trained analysts, synthesizing disparate data to address complex problems like climate change, imagery has become central to geospatial problem solving. Expert image analysts are continually faced with rapidly developing sensor technologies and software systems. In response to these cognitively demanding environments, expert analysts develop specialized knowledge and analytic skills to address increasingly complex problems. This study identifies the knowledge, skills, and analytic goals of expert image analysts tasked with identification of land cover and land use change. Analysts participating in this research are currently working as part of a national level analysis of land use change, and are well versed with the use of TimeSync, forest science, and image analysis. The results of this study benefit current analysts as it improves their awareness of their mental processes used during the image interpretation process. The study also can be generalized to understand the types of knowledge and visual cues that analysts use when reasoning with imagery for purposes beyond land use change studies. Here a Cognitive Task Analysis framework is used to organize evidence from qualitative knowledge elicitation methods for characterizing the cognitive aspects of the TimeSync image analysis process. Using a combination of content analysis, diagramming, semi-structured interviews, and observation, the study highlights the perceptual and cognitive elements of expert remote sensing interpretation. Results show that image analysts perform several standard cognitive processes, but flexibly employ these processes in response to various contextual cues. Expert image analysts' ability to think flexibly during their analysis process was directly related to their amount of image analysis experience. Additionally, results show that the basic Image Interpretation Elements continue to be important despite technological augmentation of the interpretation process. These results are used to derive a set of design guidelines for developing geovisual analytic tools and training to support image analysis.

Accurate estimation of motion blur parameters in noisy remote sensing image

NASA Astrophysics Data System (ADS)

Shi, Xueyan; Wang, Lin; Shao, Xiaopeng; Wang, Huilin; Tao, Zhong

2015-05-01

The relative motion between remote sensing satellite sensor and objects is one of the most common reasons for remote sensing image degradation. It seriously weakens image data interpretation and information extraction. In practice, point spread function (PSF) should be estimated firstly for image restoration. Identifying motion blur direction and length accurately is very crucial for PSF and restoring image with precision. In general, the regular light-and-dark stripes in the spectrum can be employed to obtain the parameters by using Radon transform. However, serious noise existing in actual remote sensing images often causes the stripes unobvious. The parameters would be difficult to calculate and the error of the result relatively big. In this paper, an improved motion blur parameter identification method to noisy remote sensing image is proposed to solve this problem. The spectrum characteristic of noisy remote sensing image is analyzed firstly. An interactive image segmentation method based on graph theory called GrabCut is adopted to effectively extract the edge of the light center in the spectrum. Motion blur direction is estimated by applying Radon transform on the segmentation result. In order to reduce random error, a method based on whole column statistics is used during calculating blur length. Finally, Lucy-Richardson algorithm is applied to restore the remote sensing images of the moon after estimating blur parameters. The experimental results verify the effectiveness and robustness of our algorithm.

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, Jin AU; Shin, Robert T.; Nghiem, Son V.; Yueh, Herng-Aung; Han, Hsiu C.; Lim, Harold H.; Arnold, David V.

1990-01-01

Remote sensing of earth terrain is examined. The layered random medium model is used to investigate the fully polarimetric scattering of electromagnetic waves from vegetation. The model is used to interpret the measured data for vegetation fields such as rice, wheat, or soybean over water or soil. Accurate calibration of polarimetric radar systems is essential for the polarimetric remote sensing of earth terrain. A polarimetric calibration algorithm using three arbitrary in-scene reflectors is developed. In the interpretation of active and passive microwave remote sensing data from the earth terrain, the random medium model was shown to be quite successful. A multivariate K-distribution is proposed to model the statistics of fully polarimetric radar returns from earth terrain. In the terrain cover classification using the synthetic aperture radar (SAR) images, the applications of the K-distribution model will provide better performance than the conventional Gaussian classifiers. The layered random medium model is used to study the polarimetric response of sea ice. Supervised and unsupervised classification procedures are also developed and applied to synthetic aperture radar polarimetric images in order to identify their various earth terrain components for more than two classes. These classification procedures were applied to San Francisco Bay and Traverse City SAR images.

CORSE-81: The 1981 Conference on Remote Sensing Education

NASA Technical Reports Server (NTRS)

Davis, S. M. (Compiler)

1981-01-01

Summaries of the presentations and tutorial workshops addressing various strategies in remote sensing education are presented. Course design from different discipline perspectives, equipment requirements for image interpretation and processing, and the role of universities, private industry, and government agencies in the education process are covered.

Possibility of Cloudless Optical Remote Sensing Images Acquisition Study by Using Meteorological Satellite Observations

NASA Astrophysics Data System (ADS)

Zhang, T.; Lei, B.; Hu, Y.; Liu, K.; Gan, Y.

2018-04-01

Optical remote sensing images have been widely used in feature interpretation and geo-information extraction. All the fundamental applications of optical remote sensing, are greatly influenced by cloud coverage. Generally, the availability of cloudless images depends on the meteorological conditions for a given area. In this study, the cloud total amount (CTA) products of the Fengyun (FY) satellite were introduced to explore the meteorological changes in a year over China. The cloud information of CTA products were tested by using ZY-3 satellite images firstly. CTA products from 2006 to 2017 were used to get relatively reliable results. The window period of cloudless images acquisition for different areas in China was then determined. This research provides a feasible way to get the cloudless images acquisition window by using meteorological observations.

Frequency analysis of gaze points with CT colonography interpretation using eye gaze tracking system

NASA Astrophysics Data System (ADS)

Tsutsumi, Shoko; Tamashiro, Wataru; Sato, Mitsuru; Okajima, Mika; Ogura, Toshihiro; Doi, Kunio

2017-03-01

It is important to investigate eye tracking gaze points of experts, in order to assist trainees in understanding of image interpretation process. We investigated gaze points of CT colonography (CTC) interpretation process, and analyzed the difference in gaze points between experts and trainees. In this study, we attempted to understand how trainees can be improved to a level achieved by experts in viewing of CTC. We used an eye gaze point sensing system, Gazefineder (JVCKENWOOD Corporation, Tokyo, Japan), which can detect pupil point and corneal reflection point by the dark pupil eye tracking. This system can provide gaze points images and excel file data. The subjects are radiological technologists who are experienced, and inexperienced in reading CTC. We performed observer studies in reading virtual pathology images and examined observer's image interpretation process using gaze points data. Furthermore, we examined eye tracking frequency analysis by using the Fast Fourier Transform (FFT). We were able to understand the difference in gaze points between experts and trainees by use of the frequency analysis. The result of the trainee had a large amount of both high-frequency components and low-frequency components. In contrast, both components by the expert were relatively low. Regarding the amount of eye movement in every 0.02 second we found that the expert tended to interpret images slowly and calmly. On the other hand, the trainee was moving eyes quickly and also looking for wide areas. We can assess the difference in the gaze points on CTC between experts and trainees by use of the eye gaze point sensing system and based on the frequency analysis. The potential improvements in CTC interpretation for trainees can be evaluated by using gaze points data.

The University of Kansas Applied Sensing Program: An operational perspective

NASA Technical Reports Server (NTRS)

Martinko, E. A.

1981-01-01

The Kansas applied remote sensing (KARS) program conducts demonstration projects and applied research on remote sensing techniques which enable local, regional, state and federal agency personnel to better utilize available satellite and airborne remote sensing systems. As liason with Kansas agencies for the Earth Resources Laboratory (ERL), Kansas demonstration project, KARS coordinated interagency communication, field data collection, hands-on training, and follow-on technical assistance and worked with Kansas agency personnel in evaluating land cover maps provided by ERL. Short courses are being conducted to provide training in state-of-the-art remote sensing technology for university faculty, state personnel, and persons from private industry and federal government. Topics are listed which were considered in intensive five-day courses covering the acquisition, interpretation, and application of information derived through remote sensing with specific training and hands-on experience in image interpretation and the analysis of LANDSAT data are listed.

Optical vs. electronic enhancement of remote sensing imagery

NASA Technical Reports Server (NTRS)

Colwell, R. N.; Katibah, E. F.

1976-01-01

Basic aspects of remote sensing are considered and a description is provided of the methods which are employed in connection with the optical or electronic enhancement of remote sensing imagery. The advantages and limitations of various image enhancement methods and techniques are evaluated. It is pointed out that optical enhancement methods and techniques are currently superior to electronic ones with respect to spatial resolution and equipment cost considerations. Advantages of electronic procedures, on the other hand, are related to a greater flexibility regarding the presentation of the information as an aid for the interpretation by the image analyst.

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.

Development and implementation of software systems for imaging spectroscopy

USGS Publications Warehouse

Boardman, J.W.; Clark, R.N.; Mazer, A.S.; Biehl, L.L.; Kruse, F.A.; Torson, J.; Staenz, K.

2006-01-01

Specialized software systems have played a crucial role throughout the twenty-five year course of the development of the new technology of imaging spectroscopy, or hyperspectral remote sensing. By their very nature, hyperspectral data place unique and demanding requirements on the computer software used to visualize, analyze, process and interpret them. Often described as a marriage of the two technologies of reflectance spectroscopy and airborne/spaceborne remote sensing, imaging spectroscopy, in fact, produces data sets with unique qualities, unlike previous remote sensing or spectrometer data. Because of these unique spatial and spectral properties hyperspectral data are not readily processed or exploited with legacy software systems inherited from either of the two parent fields of study. This paper provides brief reviews of seven important software systems developed specifically for imaging spectroscopy.

Visual Image Sensor Organ Replacement

NASA Technical Reports Server (NTRS)

Maluf, David A.

2014-01-01

This innovation is a system that augments human vision through a technique called "Sensing Super-position" using a Visual Instrument Sensory Organ Replacement (VISOR) device. The VISOR device translates visual and other sensors (i.e., thermal) into sounds to enable very difficult sensing tasks. Three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. Because the human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns, the translation of images into sounds reduces the risk of accidentally filtering out important clues. The VISOR device was developed to augment the current state-of-the-art head-mounted (helmet) display systems. It provides the ability to sense beyond the human visible light range, to increase human sensing resolution, to use wider angle visual perception, and to improve the ability to sense distances. It also allows compensation for movement by the human or changes in the scene being viewed.

Fuzzy ontologies for semantic interpretation of remotely sensed images

NASA Astrophysics Data System (ADS)

Djerriri, Khelifa; Malki, Mimoun

2015-10-01

Object-based image classification consists in the assignment of object that share similar attributes to object categories. To perform such a task the remote sensing expert uses its personal knowledge, which is rarely formalized. Ontologies have been proposed as solution to represent domain knowledge agreed by domain experts in a formal and machine readable language. Classical ontology languages are not appropriate to deal with imprecision or vagueness in knowledge. Fortunately, Description Logics for the semantic web has been enhanced by various approaches to handle such knowledge. This paper presents the extension of the traditional ontology-based interpretation with fuzzy ontology of main land-cover classes in Landsat8-OLI scenes (vegetation, built-up areas, water bodies, shadow, clouds, forests) objects. A good classification of image objects was obtained and the results highlight the potential of the method to be replicated over time and space in the perspective of transferability of the procedure.

Development and testing of a rural credit supervision system at the level of counties and rural properties utilizing remote sensing techniqes

NASA Technical Reports Server (NTRS)

Batista, G. T. (Principal Investigator); Delima, A. M.; Tardin, A. T.; Rudorff, B. F. T.; Mendonca, F. J.; Dosanjosferreirapinto, S.; Chen, S. C.; Duarte, V.

1984-01-01

Remote sensing techniques for supporting the rural credit supervision system were developed and tested. The test area comprised the counties of Aracatuba and Guararapes, located in the State of Sao Paulo. Aerial photography, LANDSAT images and topographic charts were used. Aerial photographs were extremely useful for the out lining of properties boundaries with financing of sugarcane plantations by the Banco do Brasil S.A.. The percentage of correctly interpreted sugarcane on LANDSAT images, considering the 85 analyzed properties, was of 63.12%. The occurrence of atypical conditions such as excessive raining, sugarcane in bloom, and wind damaged sugarcane and sugarcane not harvested due to planning failures verified during the period the images were obtained, were some of the contributing factors associated with a low interpretation performance. An alternative approach was developed using several LANDSAT overpasses and auxiliary field data, which resulted in 91.77 percent correct.

eeDAP: An Evaluation Environment for Digital and Analog Pathology.

PubMed

Gallas, Brandon D; Cheng, Wei-Chung; Gavrielides, Marios A; Ivansky, Adam; Keay, Tyler; Wunderlich, Adam; Hipp, Jason; Hewitt, Stephen M

2014-01-01

The purpose of this work is to present a platform for designing and executing studies that compare pathologists interpreting histopathology of whole slide images (WSI) on a computer display to pathologists interpreting glass slides on an optical microscope. Here we present eeDAP, an evaluation environment for digital and analog pathology. The key element in eeDAP is the registration of the WSI to the glass slide. Registration is accomplished through computer control of the microscope stage and a camera mounted on the microscope that acquires images of the real time microscope view. Registration allows for the evaluation of the same regions of interest (ROIs) in both domains. This can reduce or eliminate disagreements that arise from pathologists interpreting different areas and focuses the comparison on image quality. We reduced the pathologist interpretation area from an entire glass slide (≈10-30 mm) 2 to small ROIs <(50 um) 2 . We also made possible the evaluation of individual cells. We summarize eeDAP's software and hardware and provide calculations and corresponding images of the microscope field of view and the ROIs extracted from the WSIs. These calculations help provide a sense of eeDAP's functionality and operating principles, while the images provide a sense of the look and feel of studies that can be conducted in the digital and analog domains. The eeDAP software can be downloaded from code.google.com (project: eeDAP) as Matlab source or as a precompiled stand-alone license-free application.

Methodology of remote sensing data interpretation and geological applications. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Veneziani, P.; Dosanjos, C. E.

1982-01-01

Elements of photointerpretation discussed include the analysis of photographic texture and structure as well as film tonality. The method used is based on conventional techniques developed for interpreting aerial black and white photographs. By defining the properties which characterize the form and individuality of dual images, homologous zones can be identified. Guy's logic method (1966) was adapted and used on functions of resolution, scale, and spectral characteristics of remotely sensed products. Applications of LANDSAT imagery are discussed for regional geological mapping, mineral exploration, hydrogeology, and geotechnical engineering in Brazil.

Irrigated rice area estimation using remote sensing techniques: Project's proposal and preliminary results. [Rio Grande do Sul, Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Deassuncao, G. V.; Moreira, M. A.; Novaes, R. A.

1984-01-01

The development of a methodology for annual estimates of irrigated rice crop in the State of Rio Grande do Sul, Brazil, using remote sensing techniques is proposed. The project involves interpretation, digital analysis, and sampling techniques of LANDSAT imagery. Results are discussed from a preliminary phase for identifying and evaluating irrigated rice crop areas in four counties of the State, for the crop year 1982/1983. This first phase involved just visual interpretation techniques of MSS/LANDSAT images.

Study on identifying deciduous forest by the method of feature space transformation

NASA Astrophysics Data System (ADS)

Zhang, Xuexia; Wu, Pengfei

2009-10-01

The thematic remotely sensed information extraction is always one of puzzling nuts which the remote sensing science faces, so many remote sensing scientists devotes diligently to this domain research. The methods of thematic information extraction include two kinds of the visual interpretation and the computer interpretation, the developing direction of which is intellectualization and comprehensive modularization. The paper tries to develop the intelligent extraction method of feature space transformation for the deciduous forest thematic information extraction in Changping district of Beijing city. The whole Chinese-Brazil resources satellite images received in 2005 are used to extract the deciduous forest coverage area by feature space transformation method and linear spectral decomposing method, and the result from remote sensing is similar to woodland resource census data by Chinese forestry bureau in 2004.

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.

An infrared/video fusion system for military robotics

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

Davis, A.W.; Roberts, R.S.

1997-08-05

Sensory information is critical to the telerobotic operation of mobile robots. In particular, visual sensors are a key component of the sensor package on a robot engaged in urban military operations. Visual sensors provide the robot operator with a wealth of information including robot navigation and threat assessment. However, simple countermeasures such as darkness, smoke, or blinding by a laser, can easily neutralize visual sensors. In order to provide a robust visual sensing system, an infrared sensor is required to augment the primary visual sensor. An infrared sensor can acquire useful imagery in conditions that incapacitate a visual sensor. Amore » simple approach to incorporating an infrared sensor into the visual sensing system is to display two images to the operator: side-by-side visual and infrared images. However, dual images might overwhelm the operator with information, and result in degraded robot performance. A better solution is to combine the visual and infrared images into a single image that maximizes scene information. Fusing visual and infrared images into a single image demands balancing the mixture of visual and infrared information. Humans are accustom to viewing and interpreting visual images. They are not accustom to viewing or interpreting infrared images. Hence, the infrared image must be used to enhance the visual image, not obfuscate it.« less

Earth remote sensing - 1970-1995

NASA Technical Reports Server (NTRS)

Thome, P. G.

1984-01-01

The past-achievements, current status, and future prospects of the Landsat terrestrial-remote-sensing satellite program are surveyed. Topics examined include the early history of space flight; the development of analysis techniques to interpret the multispectral images obtained by Landsats 1, 2, and 3; the characteristics of the advanced Landsat-4 Thematic Mapper; microwave scanning by Seasat and the Shuttle Imaging Radar; the usefulness of low-resolution AVHRR data from the NOAA satellites; improvements in Landsats 4 and 5 to permit tailoring of information to user needs; expansion and internationalization of the remote-sensing market in the late 1980s; and technological advances in both instrumentation and data-processing predicted by the 1990s.

The potential of expert systems for remote sensing application

NASA Technical Reports Server (NTRS)

Mooneyhan, D. W.

1983-01-01

An overview of the status and potential of artificial intelligence-driven expert systems in the role of image data analysis is presented. An expert system is defined and its structure is summarized. Three such systems designed for image interpretation are outlined. The use of an expert system to detect changes on the earth's surface is discussed, and the components of a knowledge-based image interpretation system and their make-up are outlined. An example of how such a system should work for an area in the tropics where deforestation has occurred is presented as a sequence of situation/action decisions.

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.

eeDAP: An Evaluation Environment for Digital and Analog Pathology

PubMed Central

Gallas, Brandon D.; Cheng, Wei-Chung; Gavrielides, Marios A.; Ivansky, Adam; Keay, Tyler; Wunderlich, Adam; Hipp, Jason; Hewitt, Stephen M.

2017-01-01

Purpose The purpose of this work is to present a platform for designing and executing studies that compare pathologists interpreting histopathology of whole slide images (WSI) on a computer display to pathologists interpreting glass slides on an optical microscope. Methods Here we present eeDAP, an evaluation environment for digital and analog pathology. The key element in eeDAP is the registration of the WSI to the glass slide. Registration is accomplished through computer control of the microscope stage and a camera mounted on the microscope that acquires images of the real time microscope view. Registration allows for the evaluation of the same regions of interest (ROIs) in both domains. This can reduce or eliminate disagreements that arise from pathologists interpreting different areas and focuses the comparison on image quality. Results We reduced the pathologist interpretation area from an entire glass slide (≈10–30 mm)2 to small ROIs <(50 um)2. We also made possible the evaluation of individual cells. Conclusions We summarize eeDAP’s software and hardware and provide calculations and corresponding images of the microscope field of view and the ROIs extracted from the WSIs. These calculations help provide a sense of eeDAP’s functionality and operating principles, while the images provide a sense of the look and feel of studies that can be conducted in the digital and analog domains. The eeDAP software can be downloaded from code.google.com (project: eeDAP) as Matlab source or as a precompiled stand-alone license-free application. PMID:28845079

Tectonics and volcanism on Mars: a compared remote sensing analysis with earthly geostructures

NASA Astrophysics Data System (ADS)

Baggio, Paolo; Ancona, M. A.; Callegari, I.; Pinori, S.; Vercellone, S.

1999-12-01

The recent knowledge on Mars' lithosphere evolution does not find yet sufficient analogies with the Earth's tectonic models. The Viking image analysis seems to be even now frequently, rather fragmentary, and do not permits to express any coherent relationships among the different detected phenomena. Therefore, today it is impossible to support any reliable kinematic hypothesis. The Remote-Sensing interpretation is addressed to a Viking image mosaic of the known Tharsis Montes region and particularly focused on the Arsia Mons volcano. Several previously unknown lineaments, not directly linked to volcano-tectonics, were detected. Their mutual relationships recall transcurrent kinematics that could be related to similar geostructural models known in the Earth plate tectonic dynamics. Several concordant relationships between the Arsia Mons volcano and the brittle extensive tectonic features of earthly Etnean district (Sicily, South Italy), interpreted on Landsat TM images, were pointed out. These analogies coupled with the recently confirmed strato- volcano topology of Tharsis Montes (Head and Wilson), the layout distribution of the effusive centers (Arsia, Pavonis and Ascraeus Montes), the new tectonic lineaments and the morphological features, suggest the hypothesis of a plate tectonic volcanic region. The frame could be an example in agreement with the most recent interpretation of Mars (Sleep). A buried circular body, previously incorrectly interpreted as a great landslide event from the western slope of Arsia Mons volcano, seems really to be a more ancient volcanic structure (Arsia Mons Senilis), which location is in evident relation with the interpreted new transcurrent tectonic system.

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

NASA Astrophysics Data System (ADS)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

Application of AIS Technology to Forest Mapping

NASA Technical Reports Server (NTRS)

Yool, S. R.; Star, J. L.

1985-01-01

Concerns about environmental effects of large scale deforestation have prompted efforts to map forests over large areas using various remote sensing data and image processing techniques. Basic research on the spectral characteristics of forest vegetation are required to form a basis for development of new techniques, and for image interpretation. Examination of LANDSAT data and image processing algorithms over a portion of boreal forest have demonstrated the complexity of relations between the various expressions of forest canopies, environmental variability, and the relative capacities of different image processing algorithms to achieve high classification accuracies under these conditions. Airborne Imaging Spectrometer (AIS) data may in part provide the means to interpret the responses of standard data and techniques to the vegetation based on its relatively high spectral resolution.

Introduction to the GEOBIA 2010 special issue: From pixels to geographic objects in remote sensing image analysis

NASA Astrophysics Data System (ADS)

Addink, Elisabeth A.; Van Coillie, Frieke M. B.; De Jong, Steven M.

2012-04-01

Traditional image analysis methods are mostly pixel-based and use the spectral differences of landscape elements at the Earth surface to classify these elements or to extract element properties from the Earth Observation image. Geographic object-based image analysis (GEOBIA) has received considerable attention over the past 15 years for analyzing and interpreting remote sensing imagery. In contrast to traditional image analysis, GEOBIA works more like the human eye-brain combination does. The latter uses the object's color (spectral information), size, texture, shape and occurrence to other image objects to interpret and analyze what we see. GEOBIA starts by segmenting the image grouping together pixels into objects and next uses a wide range of object properties to classify the objects or to extract object's properties from the image. Significant advances and improvements in image analysis and interpretation are made thanks to GEOBIA. In June 2010 the third conference on GEOBIA took place at the Ghent University after successful previous meetings in Calgary (2008) and Salzburg (2006). This special issue presents a selection of the 2010 conference papers that are worked out as full research papers for JAG. The papers cover GEOBIA applications as well as innovative methods and techniques. The topics range from vegetation mapping, forest parameter estimation, tree crown identification, urban mapping, land cover change, feature selection methods and the effects of image compression on segmentation. From the original 94 conference papers, 26 full research manuscripts were submitted; nine papers were selected and are presented in this special issue. Selection was done on the basis of quality and topic of the studies. The next GEOBIA conference will take place in Rio de Janeiro from 7 to 9 May 2012 where we hope to welcome even more scientists working in the field of GEOBIA.

Racial Inequality and Self-Image: Identity Maintenance as Identity Diffusion

ERIC Educational Resources Information Center

Hunt, Janet G.; Hunt, Larry L.

1977-01-01

Exploring "interpersonal mediation" interpretations of self-image maintenance in low-status circumstances, this analysis indicates black boys hold higher levels of self-regard in terms of esteem and sex-role identification than their white counterparts but have lower senses of personal efficacy in the early (but not later) school years. (Author/JC)

Mapping ecological states in a complex environment

NASA Astrophysics Data System (ADS)

Steele, C. M.; Bestelmeyer, B.; Burkett, L. M.; Ayers, E.; Romig, K.; Slaughter, A.

2013-12-01

The vegetation of northern Chihuahuan Desert rangelands is sparse, heterogeneous and for most of the year, consists of a large proportion of non-photosynthetic material. The soils in this area are spectrally bright and variable in their reflectance properties. Both factors provide challenges to the application of remote sensing for estimating canopy variables (e.g., leaf area index, biomass, percentage canopy cover, primary production). Additionally, with reference to current paradigms of rangeland health assessment, remotely-sensed estimates of canopy variables have limited practical use to the rangeland manager if they are not placed in the context of ecological site and ecological state. To address these challenges, we created a multifactor classification system based on the USDA-NRCS ecological site schema and associated state-and-transition models to map ecological states on desert rangelands in southern New Mexico. Applying this system using per-pixel image processing techniques and multispectral, remotely sensed imagery raised other challenges. Per-pixel image classification relies upon the spectral information in each pixel alone, there is no reference to the spatial context of the pixel and its relationship with its neighbors. Ecological state classes may have direct relevance to managers but the non-unique spectral properties of different ecological state classes in our study area means that per-pixel classification of multispectral data performs poorly in discriminating between different ecological states. We found that image interpreters who are familiar with the landscape and its associated ecological site descriptions perform better than per-pixel classification techniques in assigning ecological states. However, two important issues affect manual classification methods: subjectivity of interpretation and reproducibility of results. An alternative to per-pixel classification and manual interpretation is object-based image analysis. Object-based image analysis provides a platform for classification that more closely resembles human recognition of objects within a remotely sensed image. The analysis presented here compares multiple thematic maps created for test locations on the USDA-ARS Jornada Experimental Range ranch. Three study sites in different pastures, each 300 ha in size, were selected for comparison on the basis of their ecological site type (';Clayey', ';Sandy' and a combination of both) and the degree of complexity of vegetation cover. Thematic maps were produced for each study site using (i) manual interpretation of digital aerial photography (by five independent interpreters); (ii) object-oriented, decision-tree classification of fine and moderate spatial resolution imagery (Quickbird; Landsat Thematic Mapper) and (iii) ground survey. To identify areas of uncertainty, we compared agreement in location, areal extent and class assignation between 5 independently produced, manually-digitized ecological state maps and with the map created from ground survey. Location, areal extent and class assignation of the map produced by object-oriented classification was also assessed with reference to the ground survey map.

Model for the Interpretation of Hyperspectral Remote-Sensing Reflectance

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

Combining remote sensing image with DEM to identify ancient Minqin Oasis, northwest of China

NASA Astrophysics Data System (ADS)

Xie, Yaowen

2008-10-01

The developing and desertification process of Minqin oasis is representative in the whole arid area of northwest China. Combining Remote Sensing image with Digital Elevation Model (DEM) can produce the three-dimensional image of the research area which can give prominence to the spatial background of historical geography phenomenon's distribution, providing the conditions for extracting and analyzing historical geographical information thoroughly. This research rebuilds the ancient artificial Oasis based on the three-dimensional images produced by the TM digital Remote Sensing image and DEM created using 1:100000 topographic maps. The result indicates that the whole area of the ancient artificial oasis in Minqin Basin over the whole historical period reaches 321km2, in the form of discontinuous sheet, separated on the two banks of ancient Shiyang River and its branches, namely, Xishawo area, west to modern Minqin Basin and Zhongshawo area, in the center of the oasis. Except for a little of the ancient oasis unceasingly used by later people, most of it became desert. The combination of digital Remote Sensing image and DEM can integrate the advantages of both in identifying ancient oasis and improve the interpreting accuracy greatly.

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.

Geologist's Field Assistant: Developing Image and Spectral Analyses Algorithms for Remote Science Exploration

NASA Technical Reports Server (NTRS)

Gulick, V. C.; Morris, R. L.; Bishop, J.; Gazis, P.; Alena, R.; Sierhuis, M.

2002-01-01

We are developing science analyses algorithms to interface with a Geologist's Field Assistant device to allow robotic or human remote explorers to better sense their surroundings during limited surface excursions. Our algorithms will interpret spectral and imaging data obtained by various sensors. Additional information is contained in the original extended abstract.

Introduction and Testing of a Monitoring and Colony-Mapping Method for Waterbird Populations That Uses High-Speed and Ultra-Detailed Aerial Remote Sensing

PubMed Central

Bakó, Gábor; Tolnai, Márton; Takács, Ádám

2014-01-01

Remote sensing is a method that collects data of the Earth's surface without causing disturbances. Thus, it is worthwhile to use remote sensing methods to survey endangered ecosystems, as the studied species will behave naturally while undisturbed. The latest passive optical remote sensing solutions permit surveys from long distances. State-of-the-art highly sensitive sensor systems allow high spatial resolution image acquisition at high altitudes and at high flying speeds, even in low-visibility conditions. As the aerial imagery captured by an airplane covers the entire study area, all the animals present in that area can be recorded. A population assessment is conducted by visual interpretations of an ortho image map. The basic objective of this study is to determine whether small- and medium-sized bird species are recognizable in the ortho images by using high spatial resolution aerial cameras. The spatial resolution needed for identifying the bird species in the ortho image map was studied. The survey was adjusted to determine the number of birds in a colony at a given time. PMID:25046012

Colorizing SENTINEL-1 SAR Images Using a Variational Autoencoder Conditioned on SENTINEL-2 Imagery

NASA Astrophysics Data System (ADS)

Schmitt, M.; Hughes, L. H.; Körner, M.; Zhu, X. X.

2018-05-01

In this paper, we have shown an approach for the automatic colorization of SAR backscatter images, which are usually provided in the form of single-channel gray-scale imagery. Using a deep generative model proposed for the purpose of photograph colorization and a Lab-space-based SAR-optical image fusion formulation, we are able to predict artificial color SAR images, which disclose much more information to the human interpreter than the original SAR data. Future work will aim at further adaption of the employed procedure to our special case of multi-sensor remote sensing imagery. Furthermore, we will investigate if the low-level representations learned intrinsically by the deep network can be used for SAR image interpretation in an end-to-end manner.

Mimicking human expert interpretation of remotely sensed raster imagery by using a novel segmentation analysis within ArcGIS

NASA Astrophysics Data System (ADS)

Le Bas, Tim; Scarth, Anthony; Bunting, Peter

2015-04-01

Traditional computer based methods for the interpretation of remotely sensed imagery use each pixel individually or the average of a small window of pixels to calculate a class or thematic value, which provides an interpretation. However when a human expert interprets imagery, the human eye is excellent at finding coherent and homogenous areas and edge features. It may therefore be advantageous for computer analysis to mimic human interpretation. A new toolbox for ArcGIS 10.x will be presented that segments the data layers into a set of polygons. Each polygon is defined by a K-means clustering and region growing algorithm, thus finding areas, their edges and any lineations in the imagery. Attached to each polygon are the characteristics of the imagery such as mean and standard deviation of the pixel values, within the polygon. The segmentation of imagery into a jigsaw of polygons also has the advantage that the human interpreter does not need to spend hours digitising the boundaries. The segmentation process has been taken from the RSGIS library of analysis and classification routines (Bunting et al., 2014). These routines are freeware and have been modified to be available in the ArcToolbox under the Windows (v7) operating system. Input to the segmentation process is a multi-layered raster image, for example; a Landsat image, or a set of raster datasets made up from derivatives of topography. The size and number of polygons are set by the user and are dependent on the imagery used. Examples will be presented of data from the marine environment utilising bathymetric depth, slope, rugosity and backscatter from a multibeam system. Meaningful classification of the polygons using their numerical characteristics is the next goal. Object based image analysis (OBIA) should help this workflow. Fully calibrated imagery systems will allow numerical classification to be translated into more readily understandable terms. Peter Bunting, Daniel Clewley, Richard M. Lucas and Sam Gillingham. 2014. The Remote Sensing and GIS Software Library (RSGISLib), Computers & Geosciences. Volume 62, Pages 216-226 http://dx.doi.org/10.1016/j.cageo.2013.08.007.

Standardizing Quality Assessment of Fused Remotely Sensed Images

NASA Astrophysics Data System (ADS)

Pohl, C.; Moellmann, J.; Fries, K.

2017-09-01

The multitude of available operational remote sensing satellites led to the development of many image fusion techniques to provide high spatial, spectral and temporal resolution images. The comparison of different techniques is necessary to obtain an optimized image for the different applications of remote sensing. There are two approaches in assessing image quality: 1. Quantitatively by visual interpretation and 2. Quantitatively using image quality indices. However an objective comparison is difficult due to the fact that a visual assessment is always subject and a quantitative assessment is done by different criteria. Depending on the criteria and indices the result varies. Therefore it is necessary to standardize both processes (qualitative and quantitative assessment) in order to allow an objective image fusion quality evaluation. Various studies have been conducted at the University of Osnabrueck (UOS) to establish a standardized process to objectively compare fused image quality. First established image fusion quality assessment protocols, i.e. Quality with No Reference (QNR) and Khan's protocol, were compared on varies fusion experiments. Second the process of visual quality assessment was structured and standardized with the aim to provide an evaluation protocol. This manuscript reports on the results of the comparison and provides recommendations for future research.

The use of multisensor images for Earth Science applications

NASA Technical Reports Server (NTRS)

Evans, D.; Stromberg, B.

1983-01-01

The use of more than one remote sensing technique is particularly important for Earth Science applications because of the compositional and textural information derivable from the images. The ability to simultaneously analyze images acquired by different sensors requires coregistration of the multisensor image data sets. In order to insure pixel to pixel registration in areas of high relief, images must be rectified to eliminate topographic distortions. Coregistered images can be analyzed using a variety of multidimensional techniques and the acquired knowledge of topographic effects in the images can be used in photogeologic interpretations.

Interactive object recognition assistance: an approach to recognition starting from target objects

NASA Astrophysics Data System (ADS)

Geisler, Juergen; Littfass, Michael

1999-07-01

Recognition of target objects in remotely sensed imagery required detailed knowledge about the target object domain as well as about mapping properties of the sensing system. The art of object recognition is to combine both worlds appropriately and to provide models of target appearance with respect to sensor characteristics. Common approaches to support interactive object recognition are either driven from the sensor point of view and address the problem of displaying images in a manner adequate to the sensing system. Or they focus on target objects and provide exhaustive encyclopedic information about this domain. Our paper discusses an approach to assist interactive object recognition based on knowledge about target objects and taking into account the significance of object features with respect to characteristics of the sensed imagery, e.g. spatial and spectral resolution. An `interactive recognition assistant' takes the image analyst through the interpretation process by indicating step-by-step the respectively most significant features of objects in an actual set of candidates. The significance of object features is expressed by pregenerated trees of significance, and by the dynamic computation of decision relevance for every feature at each step of the recognition process. In the context of this approach we discuss the question of modeling and storing the multisensorial/multispectral appearances of target objects and object classes as well as the problem of an adequate dynamic human-machine-interface that takes into account various mental models of human image interpretation.

Appendix C. LANDSAT: A worldwide perspective

NASA Technical Reports Server (NTRS)

1982-01-01

Images characteristics of geographic regions other than the northeastern part of the United States are presented for interpretation. Pre- and post-eruption imagery of Mt. St. Helens volcano serves to demonstrate the advantages of thermal infrared sensing, and the potential for developing a timely, decision oriented thematic map to be used in solving drought-related problems in Upper Volta is examined to show the applicability of satellite remote sensing in all geographic areas.

Sensing Super-position: Visual Instrument Sensor Replacement

NASA Technical Reports Server (NTRS)

Maluf, David A.; Schipper, John F.

2006-01-01

The coming decade of fast, cheap and miniaturized electronics and sensory devices opens new pathways for the development of sophisticated equipment to overcome limitations of the human senses. This project addresses the technical feasibility of augmenting human vision through Sensing Super-position using a Visual Instrument Sensory Organ Replacement (VISOR). The current implementation of the VISOR device translates visual and other passive or active sensory instruments into sounds, which become relevant when the visual resolution is insufficient for very difficult and particular sensing tasks. A successful Sensing Super-position meets many human and pilot vehicle system requirements. The system can be further developed into cheap, portable, and low power taking into account the limited capabilities of the human user as well as the typical characteristics of his dynamic environment. The system operates in real time, giving the desired information for the particular augmented sensing tasks. The Sensing Super-position device increases the image resolution perception and is obtained via an auditory representation as well as the visual representation. Auditory mapping is performed to distribute an image in time. The three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. This paper details the approach of developing Sensing Super-position systems as a way to augment the human vision system by exploiting the capabilities of the human hearing system as an additional neural input. The human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns. The known capabilities of the human hearing system to learn and understand complicated auditory patterns provided the basic motivation for developing an image-to-sound mapping system.

PI2GIS: processing image to geographical information systems, a learning tool for QGIS

NASA Astrophysics Data System (ADS)

Correia, R.; Teodoro, A.; Duarte, L.

2017-10-01

To perform an accurate interpretation of remote sensing images, it is necessary to extract information using different image processing techniques. Nowadays, it became usual to use image processing plugins to add new capabilities/functionalities integrated in Geographical Information System (GIS) software. The aim of this work was to develop an open source application to automatically process and classify remote sensing images from a set of satellite input data. The application was integrated in a GIS software (QGIS), automating several image processing steps. The use of QGIS for this purpose is justified since it is easy and quick to develop new plugins, using Python language. This plugin is inspired in the Semi-Automatic Classification Plugin (SCP) developed by Luca Congedo. SCP allows the supervised classification of remote sensing images, the calculation of vegetation indices such as NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) and other image processing operations. When analysing SCP, it was realized that a set of operations, that are very useful in teaching classes of remote sensing and image processing tasks, were lacking, such as the visualization of histograms, the application of filters, different image corrections, unsupervised classification and several environmental indices computation. The new set of operations included in the PI2GIS plugin can be divided into three groups: pre-processing, processing, and classification procedures. The application was tested consider an image from Landsat 8 OLI from a North area of Portugal.

A framework for farmland parcels extraction based on image classification

NASA Astrophysics Data System (ADS)

Liu, Guoying; Ge, Wenying; Song, Xu; Zhao, Hongdan

2018-03-01

It is very important for the government to build an accurate national basic cultivated land database. In this work, farmland parcels extraction is one of the basic steps. However, during the past years, people had to spend much time on determining an area is a farmland parcel or not, since they were bounded to understand remote sensing images only from the mere visual interpretation. In order to overcome this problem, in this study, a method was proposed to extract farmland parcels by means of image classification. In the proposed method, farmland areas and ridge areas of the classification map are semantically processed independently and the results are fused together to form the final results of farmland parcels. Experiments on high spatial remote sensing images have shown the effectiveness of the proposed method.

Image Processing

NASA Technical Reports Server (NTRS)

1991-01-01

The Computer Graphics Center of North Carolina State University uses LAS, a COSMIC program, to analyze and manipulate data from Landsat and SPOT providing information for government and commercial land resource application projects. LAS is used to interpret aircraft/satellite data and enables researchers to improve image-based classification accuracies. The system is easy to use and has proven to be a valuable remote sensing training tool.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Integrating ambient noise with GIS for a new perspective on volcano imaging and monitoring: The case study of Mt. Etna

NASA Astrophysics Data System (ADS)

Guardo, R.; De Siena, L.

2017-11-01

The timely estimation of short- and long-term volcanic hazard relies on the availability of detailed 3D geophysical images of volcanic structures. High-resolution seismic models of the absorbing uppermost conduit systems and highly-heterogeneous shallowest volcanic layers, while particularly challenging to obtain, provide important data to locate feasible eruptive centres and forecast flank collapses and lava ascending paths. Here, we model the volcanic structures of Mt. Etna (Sicily, Italy) and its outskirts using the Horizontal to Vertical Spectral Ratio method, generally applied to industrial and engineering settings. The integration of this technique with Web-based Geographic Information System improves precision during the acquisition phase. It also integrates geological and geophysical visualization of 3D surface and subsurface structures in a queryable environment representing their exact three-dimensional geographic position, enhancing interpretation. The results show high-resolution 3D images of the shallowest volcanic and feeding systems, which complement (1) deeper seismic tomography imaging and (2) the results of recent remote sensing imaging. The study recovers a vertical structure that divides the pre-existing volcanic complexes of Ellittico and Cuvigghiuni. This could be interpreted as a transitional phase between the two systems. A comparison with recent remote sensing and geological results, however, shows that anomalies are generally related to volcano-tectonic structures active during the last 17 years. We infer that seismic noise measurements from miniaturized instruments, when combined with remote sensing techniques, represent an important resource to monitor volcanoes in unrest, reducing the risk of loss of human lives and instrumentation.

Inventory and monitoring of natural vegetation and related resources in an arid environment: A comprehensive evaluation of ERTS-1 imagery. [Arizona

NASA Technical Reports Server (NTRS)

Schrumpf, B. J. (Principal Investigator); Johnson, J. R.; Mouat, D. A.; Pyott, W. T.

1974-01-01

The author has identified the following significant results. A vegetation classification, with 31 types and compatible with remote sensing applications, was developed for the test site. Terrain features can be used to discriminate vegetation types. Elevation and macrorelief interpretations were successful on ERTS photos, although for macrorelief, high sun angle stereoscopic interpretations were better than low sun angle monoscopic interpretations. Using spectral reflectivity, several vegetation types were characterized in terms of patterns of signature change. ERTS MSS digital data were used to discriminate vegetation classes at the association level and at the alliance level when image contrasts were high or low, respectively. An imagery comparison technique was developed to test image complexity and image groupability. In two stage sampling of vegetation types, ERTS plus high altitude photos were highly satisfactory for estimating kind and extent of types present, and for providing a mapping base.

The Role of Remote Sensing Displays in Earth Climate and Planetary Atmospheric Research

NASA Technical Reports Server (NTRS)

DelGenio, Anthony D.; Hansen, James E. (Technical Monitor)

2001-01-01

The communities of scientists who study the Earth's climate and the atmospheres of the other planets barely overlap, but the types of questions they pose and the resulting implications for the use and interpretation of remote sensing data sets have much in common. Both seek to determine the characteristic behavior of three-dimensional fluids that also evolve in time. Climate researchers want to know how and why the general patterns that define our climate today might be different in the next century. Planetary scientists try to understand why circulation patterns and clouds on Mars, Venus, or Jupiter are different from those on Earth. Both disciplines must aggregate large amounts of data covering long time periods and several altitudes to have a representative picture of the rapidly changing atmosphere they are studying. This emphasis separates climate scientists from weather forecasters, who focus at any one time on a limited number of images. Likewise, it separates planetary atmosphere researchers from planetary geologists, who rely primarily on single images (or mosaics of images covering the globe) to study two-dimensional planetary surfaces that are mostly static over the duration of a spacecraft mission yet reveal dynamic processes acting over thousands to millions of years. Remote sensing displays are usually two-dimensional projections that capture an atmosphere at an instant in time. How scientists manipulate and display such data, how they interpret what they see, and how they thereby understand the physical processes that cause what they see, are the challenges I discuss in this chapter. I begin by discussing differences in how novices and experts in the field relate displays of data to the real world. This leads to a discussion of the use and abuse of image enhancement and color in remote sensing displays. I then show some examples of techniques used by scientists in climate and planetary research to both convey information and design research strategies using remote sensing displays.

Visualizing Airborne and Satellite Imagery

NASA Technical Reports Server (NTRS)

Bierwirth, Victoria A.

2011-01-01

Remote sensing is a process able to provide information about Earth to better understand Earth's processes and assist in monitoring Earth's resources. The Cloud Absorption Radiometer (CAR) is one remote sensing instrument dedicated to the cause of collecting data on anthropogenic influences on Earth as well as assisting scientists in understanding land-surface and atmospheric interactions. Landsat is a satellite program dedicated to collecting repetitive coverage of the continental Earth surfaces in seven regions of the electromagnetic spectrum. Combining these two aircraft and satellite remote sensing instruments will provide a detailed and comprehensive data collection able to provide influential information and improve predictions of changes in the future. This project acquired, interpreted, and created composite images from satellite data acquired from Landsat 4-5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper plus (ETM+). Landsat images were processed for areas covered by CAR during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCT AS), Cloud and Land Surface Interaction Campaign (CLASIC), Intercontinental Chemical Transport Experiment-Phase B (INTEXB), and Southern African Regional Science Initiative (SAFARI) 2000 missions. The acquisition of Landsat data will provide supplemental information to assist in visualizing and interpreting airborne and satellite imagery.

Automated extraction of metadata from remotely sensed satellite imagery

NASA Technical Reports Server (NTRS)

Cromp, Robert F.

1991-01-01

The paper discusses research in the Intelligent Data Management project at the NASA/Goddard Space Flight Center, with emphasis on recent improvements in low-level feature detection algorithms for performing real-time characterization of images. Images, including MSS and TM data, are characterized using neural networks and the interpretation of the neural network output by an expert system for subsequent archiving in an object-oriented data base. The data show the applicability of this approach to different arrangements of low-level remote sensing channels. The technique works well when the neural network is trained on data similar to the data used for testing.

A Classification of Remote Sensing Image Based on Improved Compound Kernels of Svm

NASA Astrophysics Data System (ADS)

Zhao, Jianing; Gao, Wanlin; Liu, Zili; Mou, Guifen; Lu, Lin; Yu, Lina

The accuracy of RS classification based on SVM which is developed from statistical learning theory is high under small number of train samples, which results in satisfaction of classification on RS using SVM methods. The traditional RS classification method combines visual interpretation with computer classification. The accuracy of the RS classification, however, is improved a lot based on SVM method, because it saves much labor and time which is used to interpret images and collect training samples. Kernel functions play an important part in the SVM algorithm. It uses improved compound kernel function and therefore has a higher accuracy of classification on RS images. Moreover, compound kernel improves the generalization and learning ability of the kernel.

Ocean experiments and remotely sensed images of chemically dispersed oil spills

NASA Technical Reports Server (NTRS)

Croswell, W. F.; Fedors, J. C.; Hoge, F. E.; Swift, R. N.; Johnson, J. C.

1983-01-01

A series of experiments was performed at sea where the effectiveness of dispersants applied from a helicopter was tested on fresh and weathered crude oils released from a surface research vessel. In conjunction with these experiments, remote sensing measurements using an array of airborne optical and microwave sensors were performed in order to aid in the interpretation of the dispersant effectiveness and to obtain quantitative images of oil on the sea under controlled conditions. Surface oil thickness and volume are inferred from airborne measurements using a dual-channel microwave imaging radiometer, aerial color photography, and an airborne oceanographic lidar. The remotely sensed measurements are compared with point sampled data obtained using a research vessel. The mass balance computations of surface versus subsurface oil volume using remotely sensed and point sampled data are consistent with each other and with the volumes of oil released. Data collected by the several techniques concur in indicating that, for the oils used and under the sea conditions encountered, the dispersant and application method are primarily useful when applied to fresh oil.

Combining Landform Thematic Layer and Object-Oriented Image Analysis to Map the Surface Features of Mountainous Flood Plain Areas

NASA Astrophysics Data System (ADS)

Chuang, H.-K.; Lin, M.-L.; Huang, W.-C.

2012-04-01

The Typhoon Morakot on August 2009 brought more than 2,000 mm of cumulative rainfall in southern Taiwan, the extreme rainfall event caused serious damage to the Kaoping River basin. The losses were mostly blamed on the landslides along sides of the river, and shifting of the watercourse even led to the failure of roads and bridges, as well as flooding and levees damage happened around the villages on flood bank and terraces. Alluvial fans resulted from debris flow of stream feeders blocked the main watercourse and debris dam was even formed and collapsed. These disasters have highlighted the importance of identification and map the watercourse alteration, surface features of flood plain area and artificial structures soon after the catastrophic typhoon event for natural hazard mitigation. Interpretation of remote sensing images is an efficient approach to acquire spatial information for vast areas, therefore making it suitable for the differentiation of terrain and objects near the vast flood plain areas in a short term. The object-oriented image analysis program (Definiens Developer 7.0) and multi-band high resolution satellite images (QuickBird, DigitalGlobe) was utilized to interpret the flood plain features from Liouguei to Baolai of the the Kaoping River basin after Typhoon Morakot. Object-oriented image interpretation is the process of using homogenized image blocks as elements instead of pixels for different shapes, textures and the mutual relationships of adjacent elements, as well as categorized conditions and rules for semi-artificial interpretation of surface features. Digital terrain models (DTM) are also employed along with the above process to produce layers with specific "landform thematic layers". These layers are especially helpful in differentiating some confusing categories in the spectrum analysis with improved accuracy, such as landslides and riverbeds, as well as terraces, riverbanks, which are of significant engineering importance in disaster mitigation. In this study, an automatic and fast image interpretation process for eight surface features including main channel, secondary channel, sandbar, flood plain, river terrace, alluvial fan, landslide, and the nearby artificial structures in the mountainous flood plain is proposed. Images along timelines can even be compared in order to differentiate historical events such as village inundations, failure of roads, bridges and levees, as well as alternation of watercourse, and therefore can be used as references for safety evaluation of engineering structures near rivers, disaster prevention and mitigation, and even future land-use planning. Keywords: Flood plain area, Remote sensing, Object-oriented, Surface feature interpretation, Terrain analysis, Thematic layer, Typhoon Morakot

Autonomous navigation and control of a Mars rover

NASA Technical Reports Server (NTRS)

Miller, D. P.; Atkinson, D. J.; Wilcox, B. H.; Mishkin, A. H.

1990-01-01

A Mars rover will need to be able to navigate autonomously kilometers at a time. This paper outlines the sensing, perception, planning, and execution monitoring systems that are currently being designed for the rover. The sensing is based around stereo vision. The interpretation of the images use a registration of the depth map with a global height map provided by an orbiting spacecraft. Safe, low energy paths are then planned through the map, and expectations of what the rover's articulation sensors should sense are generated. These expectations are then used to ensure that the planned path is correctly being executed.

3D sensitivity encoded ellipsoidal MR spectroscopic imaging of gliomas at 3T☆

PubMed Central

Ozturk-Isik, Esin; Chen, Albert P.; Crane, Jason C.; Bian, Wei; Xu, Duan; Han, Eric T.; Chang, Susan M.; Vigneron, Daniel B.; Nelson, Sarah J.

2010-01-01

Purpose The goal of this study was to implement time efficient data acquisition and reconstruction methods for 3D magnetic resonance spectroscopic imaging (MRSI) of gliomas at a field strength of 3T using parallel imaging techniques. Methods The point spread functions, signal to noise ratio (SNR), spatial resolution, metabolite intensity distributions and Cho:NAA ratio of 3D ellipsoidal, 3D sensitivity encoding (SENSE) and 3D combined ellipsoidal and SENSE (e-SENSE) k-space sampling schemes were compared with conventional k-space data acquisition methods. Results The 3D SENSE and e-SENSE methods resulted in similar spectral patterns as the conventional MRSI methods. The Cho:NAA ratios were highly correlated (P<.05 for SENSE and P<.001 for e-SENSE) with the ellipsoidal method and all methods exhibited significantly different spectral patterns in tumor regions compared to normal appearing white matter. The geometry factors ranged between 1.2 and 1.3 for both the SENSE and e-SENSE spectra. When corrected for these factors and for differences in data acquisition times, the empirical SNRs were similar to values expected based upon theoretical grounds. The effective spatial resolution of the SENSE spectra was estimated to be same as the corresponding fully sampled k-space data, while the spectra acquired with ellipsoidal and e-SENSE k-space samplings were estimated to have a 2.36–2.47-fold loss in spatial resolution due to the differences in their point spread functions. Conclusion The 3D SENSE method retained the same spatial resolution as full k-space sampling but with a 4-fold reduction in scan time and an acquisition time of 9.28 min. The 3D e-SENSE method had a similar spatial resolution as the corresponding ellipsoidal sampling with a scan time of 4:36 min. Both parallel imaging methods provided clinically interpretable spectra with volumetric coverage and adequate SNR for evaluating Cho, Cr and NAA. PMID:19766422

Integrating passive seismicity with Web-Based GIS for a new perspective on volcano imaging and monitoring: the case study of Mt. Etna

NASA Astrophysics Data System (ADS)

Guardo, Roberto; De Siena, Luca

2017-04-01

The timely estimation of short- and long-term volcanic hazard relies on the existence of detailed 3D geophysical images of volcanic structures. High-resolution seismic models of the absorbing uppermost conduit systems and highly-heterogeneous shallowest volcanic layers, while particularly challenging to obtain, provide important data to locate feasible eruptive centers and forecast flank collapses and lava ascending paths. Here, we model the volcanic structures of Mt. Etna (Sicily, Italy) and its outskirts using the Horizontal to Vertical Spectral Ratio method, generally applied to industrial and engineering settings. The integration of this technique with Web-based Geographic Information System improves precision during the acquisition phase. It also integrates geological and geophysical visualization of 3D surface and subsurface structures in a queryable environment representing their exact three-dimensional geographic position, enhancing interpretation. The results show high-resolution 3D images of the shallowest volcanic and feeding systems, which complement (1) deeper seismic tomography imaging and (2) the results of recent remote sensing imaging. The main novelty with respect to previous model is the presence of a vertical structure that divides the pre-existing volcanic complexes of Ellittico and Cuvigghiuni. This could be interpreted as a transitional phase between the two systems. A comparison with recent remote sensing and geological results, however, shows clear connections between the anomaly and dynamic active during the last 15 years. We infer that seismic noise measurements from miniaturized instruments, when combined with remote sensing techniques, represent an important resource when monitoring volcanic media and eruptions, reducing the risk of loss of human lives and instrumentation.

Study of the wide area of a lake with remote sensing

NASA Astrophysics Data System (ADS)

Lazaridou, Maria A.; Karagianni, Aikaterini C.

2016-08-01

Water bodies are particularly important for environment and development issues. Their study requires multiple information. Remote sensing has been proven useful in the above study. This paper concerns the wide area of Lake Orestiada in the region of Western Macedonia in Greece. The area is of particular interest because Lake Orestiada is included in the Natura 2000 network and is surrounded by diverse landcovers as built up areas and agricultural land. Multispectral and thermal Landsat 5 satellite images of two time periods are being used. Their processing is being done by Erdas Imagine software. The general physiognomy of the area and the lake shore are examined after image enhancement techniques and image interpretation. Directions of the study concern geomorphological aspects, land covers, estimation of surface temperature as well as changes through time.

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.

Assessment of Sampling Approaches for Remote Sensing Image Classification in the Iranian Playa Margins

NASA Astrophysics Data System (ADS)

Kazem Alavipanah, Seyed

There are some problems in soil salinity studies based upon remotely sensed data: 1-spectral world is full of ambiguity and therefore soil reflectance can not be attributed to a single soil property such as salinity, 2) soil surface conditions as a function of time and space is a complex phenomena, 3) vegetation with a dynamic biological nature may create some problems in the study of soil salinity. Due to these problems the first question which may arise is how to overcome or minimise these problems. In this study we hypothesised that different sources of data, well established sampling plan and optimum approach could be useful. In order to choose representative training sites in the Iranian playa margins, to define the spectral and informational classes and to overcome some problems encountered in the variation within the field, the following attempts were made: 1) Principal Component Analysis (PCA) in order: a) to determine the most important variables, b) to understand the Landsat satellite images and the most informative components, 2) the photomorphic unit (PMU) consideration and interpretation; 3) study of salt accumulation and salt distribution in the soil profile, 4) use of several forms of field data, such as geologic, geomorphologic and soil information; 6) confirmation of field data and land cover types with farmers and the members of the team. The results led us to find at suitable approaches with a high and acceptable image classification accuracy and image interpretation. KEY WORDS; Photo Morphic Unit, Pprincipal Ccomponent Analysis, Soil Salinity, Field Work, Remote Sensing

Random Access Memories: A New Paradigm for Target Detection in High Resolution Aerial Remote Sensing Images.

PubMed

Zou, Zhengxia; Shi, Zhenwei

2018-03-01

We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.

Radar image enhancement and simulation as an aid to interpretation and training

NASA Technical Reports Server (NTRS)

Frost, V. S.; Stiles, J. A.; Holtzman, J. C.; Dellwig, L. F.; Held, D. N.

1980-01-01

Greatly increased activity in the field of radar image applications in the coming years demands that techniques of radar image analysis, enhancement, and simulation be developed now. Since the statistical nature of radar imagery differs from that of photographic imagery, one finds that the required digital image processing algorithms (e.g., for improved viewing and feature extraction) differ from those currently existing. This paper addresses these problems and discusses work at the Remote Sensing Laboratory in image simulation and processing, especially for systems comparable to the formerly operational SEASAT synthetic aperture radar.

a Cognitive Approach to Teaching a Graduate-Level Geobia Course

NASA Astrophysics Data System (ADS)

Bianchetti, Raechel A.

2016-06-01

Remote sensing image analysis training occurs both in the classroom and the research lab. Education in the classroom for traditional pixel-based image analysis has been standardized across college curriculums. However, with the increasing interest in Geographic Object-Based Image Analysis (GEOBIA), there is a need to develop classroom instruction for this method of image analysis. While traditional remote sensing courses emphasize the expansion of skills and knowledge related to the use of computer-based analysis, GEOBIA courses should examine the cognitive factors underlying visual interpretation. This current paper provides an initial analysis of the development, implementation, and outcomes of a GEOBIA course that considers not only the computational methods of GEOBIA, but also the cognitive factors of expertise, that such software attempts to replicate. Finally, a reflection on the first instantiation of this course is presented, in addition to plans for development of an open-source repository for course materials.

Interpreting intracorporeal landscapes: how patients visualize pathophysiology and utilize medical images in their understanding of chronic musculoskeletal illness.

PubMed

Moore, Andrew J; Richardson, Jane C; Bernard, Miriam; Sim, Julius

2018-02-26

Medical science and other sources, such as the media, increasingly inform the general public's understanding of disease. There is often discordance between this understanding and the diagnostic interpretations of health care practitioners (HCPs). In this paper - based on a supra-analysis of qualitative interview data from two studies of joint pain, including osteoarthritis - we investigate how people imagine and make sense of the pathophysiology of their illness, and how these understandings may affect self-management behavior. We then explore how HCPs' use of medical images and models can inform patients' understanding. In conceptualizing their illness to make sense of their experience of the disease, individuals often used visualizations of their inner body; these images may arise from their own lay understanding, or may be based on images provided by HCPs. When HCPs used anatomical models or medical images judiciously, patients' orientation to their illness changed. Including patients in a more collaborative diagnostic event that uses medical images and visual models to support explanations about their condition may help them to achieve a more meaningful understanding of their illness and to manage their condition more effectively. Implications for Rehabilitation Chronic musculoskeletal pain is a leading cause of pain and years lived with disability, and despite its being common, patients and healthcare professionals often have a different understanding of the underlying disease. An individual's understanding of his or her pathophysiology plays an important role in making sense of painful joint conditions and in decision-making about self-management and care. Including patients in a more collaborative diagnostic event using medical images and anatomical models to support explanations about their symptoms may help them to better understand their condition and manage it more effectively. Using visually informed explanations and anatomical models may also help to reassure patients about the safety and effectiveness of core treatments such as physical exercise and thereby help restore or improve patients' activity levels and return to social participation.

Applied geointegration to hydrocarbon exploration in the San Pedro-Machango Area, Maracaibo Basin, Venezuela

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

Fonseca, A.; Navarro, A.; Osorio, R.

1996-08-01

Hydrocarbon exploration has nowadays a diversity of technological resources to capture, merge and interpret information from diverse sources. To accomplish this, the integration of geodata for modeling was done through the use of new technologies like Remote Sensing and Geographical Systems of Information and applied to the San Pedro-Machango area, located in the Serrania de Trujillo, west of Costa Bolivar (onshore), eastern Maracaibo Basin, Venezuela. The main purpose of this work was to optimize the design of an exploration program in harmony with environmental conservation procedures. Starting with satellital and radar images that incorporated geophysical, geological and environmental information, theymore » then were analyzed and merged to improve the lithological, structural and tectonic interpretation, generating an integrated model that allowed better project design. The use of a system that combines information of geographical, geodetical, geophysical and geological origins with satellital and radar images produced up to date cartography and refined results of image interpretation.« less

A comparative interregional analysis of selected data from LANDSAT-1 and EREP for the inventory and monitoring of natural ecosystems

NASA Technical Reports Server (NTRS)

Poulton, C. E.

1975-01-01

Comparative statistics were presented on the capability of LANDSAT-1 and three of the Skylab remote sensing systems (S-190A, S-190B, S-192) for the recognition and inventory of analogous natural vegetations and landscape features important in resource allocation and management. Two analogous regions presenting vegetational zonation from salt desert to alpine conditions above the timberline were observed, emphasizing the visual interpretation mode in the investigation. An hierarchical legend system was used as the basic classification of all land surface features. Comparative tests were run on image identifiability with the different sensor systems, and mapping and interpretation tests were made both in monocular and stereo interpretation with all systems except the S-192. Significant advantage was found in the use of stereo from space when image analysis is by visual or visual-machine-aided interactive systems. Some cost factors in mapping from space are identified. The various image types are compared and an operational system is postulated.

Growth pattern research on the modern deposition of Ganjiang delta in Poyang lake basin by spatio-temporal remote sensing images

NASA Astrophysics Data System (ADS)

Zhou, Hongying; Yuan, Xuanjun; Zhang, Youyan; Dong, Wentong; Liu, Song

2016-11-01

It is of great importance for petroleum exploration to study the sedimentary features and the growth pattern of shoal water deltas in lake basins. Taking spatio-temporal remote sensing images as the principal data source, combined with field sedimentation survey, a quantitative research on the modern deposition of Ganjiang delta in the Poyang Lake Basin is described in this paper. Using 76 multi-temporal and multi-type remote sensing images acquired from 1973 to 2015, combined with field sedimentation survey, remote sensing interpretation analysis was conducted on the sedimentary facies of the Ganjiang delta. It is found that that the current Poyang Lake mainly consists of three types of sand body deposits including deltaic deposit, overflow channel deposit, and aeolian deposit, and the distribution of sand bodies was affected by the above three types of depositions jointly. The mid-branch channels of the Ganjiang delta increased on an exponential growth rhythm. The main growth pattern of the Ganjiang delta is dendritic and reticular, and the distributary channel mostly arborizes at lake inlet and was reworked to be reticulatus at late stage.

Edge Response and NIIRS Estimates for Commercial Remote Sensing Satellites

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Ryan, Robert E.; Pagnutti, mary; Stanley, Thomas

2006-01-01

Spatial resolution of panchromatic imagery from commercial remote sensing satellites was characterized based on edge response measurements using edge targets and the tilted-edge technique. Relative Edge Response (RER) was estimated as a geometric mean of normalized edge response differences measured in two directions of image pixels at points distanced from the edge by -0.5 and 0.5 of ground sample distance. RER is one of the engineering parameters used in the General Image Quality Equation to provide predictions of imaging system performance expressed in terms of the National Imagery Interpretability Rating Scale (NIIRS). By assuming a plausible range of signal-to-noise ratio and assessing the effects of Modulation Transfer Function compensation, the NIIRS estimates were made and then compared with vendor-provided values and evaluations conducted by the National Geospatial-Intelligence Agency.

Wetland resources investigation based on 3S technology

NASA Astrophysics Data System (ADS)

Lin, Hui; Jing, Haitao; Zhang, Lianpeng

2008-10-01

Wetland is a special ecosystem between land and water . It can provide massive foods, raw material, water resources and habitat for human being, animals and plants, Wetlands are so important that wetlands' development, management and protection have become the focus of public attention ."3S" integration technology was applied to investigate wetland resources in Shandong Province ,the investigation is based on remote sensing(RS) information, combining wetlandrelated geographic information system(GIS) data concerning existing geology, hydrology, land, lakes, rivers, oceans and environmental protection, using the Global Positioning System (GPS) to determine location accurately and conveniently , as well as multi-source information to demonstrate each other based on "3S" integration technology. In addition, the remote sensing(RS) interpretation shall be perfected by combining house interpretation with field survey and combining interpretation results with known data.By contrasting various types of wetland resources with the TM, ETM, SPOT image and combining with the various types of information, remote sensing interpretation symbols of various types of wetland resources are established respectively. According to the interpretation symbols, we systematically interpret the wetland resources of Shandong Province. In accordance with the purpose of different work, we interpret the image of 1987, 1996 and 2000. Finally, various interpretation results are processed by computer scanning, Vectored, projection transformation and image mosaic, wetland resources distribution map is worked out and wetland resources database of Shandong Province is established in succession. Through the investigation, wetland resource in Shandong province can be divided into 4 major categories and 17 sub-categories. we have ascertained the range and area of each category as well as their present utilization status.. By investigating and calculating, the total area of wetland in Shandong Province is 1,712,200 hm2,which accounts for 7.58% of the total area of land in Shandong Province (not including the wetland in the shallow waters along the coast). Among them, area of river wetland is 286,746 hm2, area of lakes wetland is143,490 hm2, area of reservoir and pond wetland is 118,693 hm2, area of offshore and coastal wetland is 994,100 hm2, and area of other wetland is 169,171 hm2. On the basis of this, we can analyze the dynamic changes trend and the reasons: steady degenerating for natural wetlands, increasing year by year for artificial wetland, and the distribution pattern takes shape that the existing natural wetlands are being protected and the increase of new artificial wetlands is in conformity with the social development, so the situation of the wetland resources is developing towards a virtuous circle direction.

Improved reconstruction and sensing techniques for personnel screening in three-dimensional cylindrical millimeter-wave portal scanning

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

Fernandes, Justin L.; Rappaport, Carey M.; Sheen, David M.

2011-05-01

The cylindrical millimeter-wave imaging technique, developed at Pacific Northwest National Laboratory (PNNL) and commercialized by L-3 Communications/Safeview in the ProVision system, is currently being deployed in airports and other high security locations to meet person-borne weapon and explosive detection requirements. While this system is efficient and effective in its current form, there are a number of areas in which the detection performance may be improved through using different reconstruction algorithms and sensing configurations. PNNL and Northeastern University have teamed together to investigate higher-order imaging artifacts produced by the current cylindrical millimeter-wave imaging technique using full-wave forward modeling and laboratory experimentation.more » Based on imaging results and scattered field visualizations using the full-wave forward model, a new imaging system is proposed. The new system combines a multistatic sensor configuration with the generalized synthetic aperture focusing technique (GSAFT). Initial results show an improved ability to image in areas of the body where target shading, specular and higher-order reflections cause images produced by the monostatic system difficult to interpret.« less

Sea Ice Drift Monitoring in the Bohai Sea Based on GF4 Satellite

NASA Astrophysics Data System (ADS)

Zhao, Y.; Wei, P.; Zhu, H.; Xing, B.

2018-04-01

The Bohai Sea is the inland sea with the highest latitude in China. In winter, the phenomenon of freezing occurs in the Bohai Sea due to frequent cold wave influx. According to historical records, there have been three serious ice packs in the Bohai Sea in the past 50 years which caused heavy losses to our economy. Therefore, it is of great significance to monitor the drift of sea ice and sea ice in the Bohai Sea. The GF4 image has the advantages of short imaging time and high spatial resolution. Based on the GF4 satellite images, the three methods of SIFT (Scale invariant feature - the transform and Scale invariant feature transform), MCC (maximum cross-correlation method) and sift combined with MCC are used to monitor sea ice drift and calculate the speed and direction of sea ice drift, the three calculation results are compared and analyzed by using expert interpretation and historical statistical data to carry out remote sensing monitoring of sea ice drift results. The experimental results show that the experimental results of the three methods are in accordance with expert interpretation and historical statistics. Therefore, the GF4 remote sensing satellite images have the ability to monitor sea ice drift and can be used for drift monitoring of sea ice in the Bohai Sea.

Study on Remote Sensing Image Characteristics of Ecological Land: Case Study of Original Ecological Land in the Yellow River Delta

NASA Astrophysics Data System (ADS)

An, G. Q.

2018-04-01

Takes the Yellow River Delta as an example, this paper studies the characteristics of remote sensing imagery with dominant ecological functional land use types, compares the advantages and disadvantages of different image in interpreting ecological land use, and uses research results to analyse the changing trend of ecological land in the study area in the past 30 years. The main methods include multi-period, different sensor images and different seasonal spectral curves, vegetation index, GIS and data analysis methods. The results show that the main ecological land in the Yellow River Delta included coastal beaches, saline-alkaline lands, and water bodies. These lands have relatively distinct spectral and texture features. The spectral features along the beach show characteristics of absorption in the green band and reflection in the red band. This feature is less affected by the acquisition year, season, and sensor type. Saline-alkali land due to the influence of some saline-alkaline-tolerant plants such as alkali tent, Tamarix and other vegetation, the spectral characteristics have a certain seasonal changes, winter and spring NDVI index is less than the summer and autumn vegetation index. The spectral characteristics of a water body generally decrease rapidly with increasing wavelength, and the reflectance in the red band increases with increasing sediment concentration. In conclusion, according to the spectral characteristics and image texture features of the ecological land in the Yellow River Delta, the accuracy of image interpretation of such ecological land can be improved.

The SENSE-Isomorphism Theoretical Image Voxel Estimation (SENSE-ITIVE) Model for Reconstruction and Observing Statistical Properties of Reconstruction Operators

PubMed Central

Bruce, Iain P.; Karaman, M. Muge; Rowe, Daniel B.

2012-01-01

The acquisition of sub-sampled data from an array of receiver coils has become a common means of reducing data acquisition time in MRI. Of the various techniques used in parallel MRI, SENSitivity Encoding (SENSE) is one of the most common, making use of a complex-valued weighted least squares estimation to unfold the aliased images. It was recently shown in Bruce et al. [Magn. Reson. Imag. 29(2011):1267–1287] that when the SENSE model is represented in terms of a real-valued isomorphism, it assumes a skew-symmetric covariance between receiver coils, as well as an identity covariance structure between voxels. In this manuscript, we show that not only is the skew-symmetric coil covariance unlike that of real data, but the estimated covariance structure between voxels over a time series of experimental data is not an identity matrix. As such, a new model, entitled SENSE-ITIVE, is described with both revised coil and voxel covariance structures. Both the SENSE and SENSE-ITIVE models are represented in terms of real-valued isomorphisms, allowing for a statistical analysis of reconstructed voxel means, variances, and correlations resulting from the use of different coil and voxel covariance structures used in the reconstruction processes to be conducted. It is shown through both theoretical and experimental illustrations that the miss-specification of the coil and voxel covariance structures in the SENSE model results in a lower standard deviation in each voxel of the reconstructed images, and thus an artificial increase in SNR, compared to the standard deviation and SNR of the SENSE-ITIVE model where both the coil and voxel covariances are appropriately accounted for. It is also shown that there are differences in the correlations induced by the reconstruction operations of both models, and consequently there are differences in the correlations estimated throughout the course of reconstructed time series. These differences in correlations could result in meaningful differences in interpretation of results. PMID:22617147

The ORSER System for the Analysis of Remotely Sensed Digital Data

NASA Technical Reports Server (NTRS)

Myers, W. L.; Turner, B. J.

1981-01-01

The main effort of the University of Pennsylvania's Office for Remote Sensing of Earth Resources (ORSER) is the processing, analysis, and interpretation of multispectral data, most often supplied by NASA in the form of imagery and digital data. The facilities used for data reduction and image enhancement are described as well as the development of algorithms for producing a computer map showing various environmental and land use characteristics of data points in the analyzed scenes. The application of an (ORSER) capability for statewide monitoring of gypsy moth defoliation is discussed.

Remote Sensing of Landuse Changes and Implications for Landuse Policy

NASA Technical Reports Server (NTRS)

Kennedy, Ken

1996-01-01

This final report describes grant activities under which students were to study landuse changes by comparing planning and zoning documents using remote sensed data data analyzed and interpreted in the laboratory. Students were recruited through mathematics, political science and engineering classes an clubs. Work protocols were then organized for research on the county's growth patterns over the last three decades. Students and investigators made planes to identify specific scenes in Landsat and other data which would satisfy the research parameters. Finally, statistical and imaging software was identified and some was acquired.

Generalized interpretation scheme for arbitrary HR InSAR image pairs

NASA Astrophysics Data System (ADS)

Boldt, Markus; Thiele, Antje; Schulz, Karsten

2013-10-01

Land cover classification of remote sensing imagery is an important topic of research. For example, different applications require precise and fast information about the land cover of the imaged scenery (e.g., disaster management and change detection). Focusing on high resolution (HR) spaceborne remote sensing imagery, the user has the choice between passive and active sensor systems. Passive systems, such as multispectral sensors, have the disadvantage of being dependent from weather influences (fog, dust, clouds, etc.) and time of day, since they work in the visible part of the electromagnetic spectrum. Here, active systems like Synthetic Aperture Radar (SAR) provide improved capabilities. As an interactive method analyzing HR InSAR image pairs, the CovAmCohTM method was introduced in former studies. CovAmCoh represents the joint analysis of locality (coefficient of variation - Cov), backscatter (amplitude - Am) and temporal stability (coherence - Coh). It delivers information on physical backscatter characteristics of imaged scene objects or structures and provides the opportunity to detect different classes of land cover (e.g., urban, rural, infrastructure and activity areas). As example, railway tracks are easily distinguishable from other infrastructure due to their characteristic bluish coloring caused by the gravel between the sleepers. In consequence, imaged objects or structures have a characteristic appearance in CovAmCoh images which allows the development of classification rules. In this paper, a generalized interpretation scheme for arbitrary InSAR image pairs using the CovAmCoh method is proposed. This scheme bases on analyzing the information content of typical CovAmCoh imagery using the semisupervised k-means clustering. It is shown that eight classes model the main local information content of CovAmCoh images sufficiently and can be used as basis for a classification scheme.

Geology

NASA Technical Reports Server (NTRS)

Stewart, R. K.; Sabins, F. F., Jr.; Rowan, L. C.; Short, N. M.

1975-01-01

Papers from private industry reporting applications of remote sensing to oil and gas exploration were presented. Digitally processed LANDSAT images were successfully employed in several geologic interpretations. A growing interest in digital image processing among the geologic user community was shown. The papers covered a wide geographic range and a wide technical and application range. Topics included: (1) oil and gas exploration, by use of radar and multisensor studies as well as by use of LANDSAT imagery or LANDSAT digital data, (2) mineral exploration, by mapping from LANDSAT and Skylab imagery and by LANDSAT digital processing, (3) geothermal energy studies with Skylab imagery, (4) environmental and engineering geology, by use of radar or LANDSAT and Skylab imagery, (5) regional mapping and interpretation, and digital and spectral methods.

Efficiency analysis for 3D filtering of multichannel images

NASA Astrophysics Data System (ADS)

Kozhemiakin, Ruslan A.; Rubel, Oleksii; Abramov, Sergey K.; Lukin, Vladimir V.; Vozel, Benoit; Chehdi, Kacem

2016-10-01

Modern remote sensing systems basically acquire images that are multichannel (dual- or multi-polarization, multi- and hyperspectral) where noise, usually with different characteristics, is present in all components. If noise is intensive, it is desirable to remove (suppress) it before applying methods of image classification, interpreting, and information extraction. This can be done using one of two approaches - by component-wise or by vectorial (3D) filtering. The second approach has shown itself to have higher efficiency if there is essential correlation between multichannel image components as this often happens for multichannel remote sensing data of different origin. Within the class of 3D filtering techniques, there are many possibilities and variations. In this paper, we consider filtering based on discrete cosine transform (DCT) and pay attention to two aspects of processing. First, we study in detail what changes in DCT coefficient statistics take place for 3D denoising compared to component-wise processing. Second, we analyze how selection of component images united into 3D data array influences efficiency of filtering and can the observed tendencies be exploited in processing of images with rather large number of channels.

Semiconductor Laser Multi-Spectral Sensing and Imaging

PubMed Central

Le, Han Q.; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers. PMID:22315555

Semiconductor laser multi-spectral sensing and imaging.

PubMed

Le, Han Q; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

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

PubMed

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

2012-09-01

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

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

PubMed Central

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

2013-01-01

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

Visualizing time: how linguistic metaphors are incorporated into displaying instruments in the process of interpreting time-varying signals

NASA Astrophysics Data System (ADS)

Garcia-Belmonte, Germà

2017-06-01

Spatial visualization is a well-established topic of education research that has allowed improving science and engineering students' skills on spatial relations. Connections have been established between visualization as a comprehension tool and instruction in several scientific fields. Learning about dynamic processes mainly relies upon static spatial representations or images. Visualization of time is inherently problematic because time can be conceptualized in terms of two opposite conceptual metaphors based on spatial relations as inferred from conventional linguistic patterns. The situation is particularly demanding when time-varying signals are recorded using displaying electronic instruments, and the image should be properly interpreted. This work deals with the interplay between linguistic metaphors, visual thinking and scientific instrument mediation in the process of interpreting time-varying signals displayed by electronic instruments. The analysis draws on a simplified version of a communication system as example of practical signal recording and image visualization in a physics and engineering laboratory experience. Instrumentation delivers meaningful signal representations because it is designed to incorporate a specific and culturally favored time view. It is suggested that difficulties in interpreting time-varying signals are linked with the existing dual perception of conflicting time metaphors. The activation of specific space-time conceptual mapping might allow for a proper signal interpretation. Instruments play then a central role as visualization mediators by yielding an image that matches specific perception abilities and practical purposes. Here I have identified two ways of understanding time as used in different trajectories through which students are located. Interestingly specific displaying instruments belonging to different cultural traditions incorporate contrasting time views. One of them sees time in terms of a dynamic metaphor consisting of a static observer looking at passing events. This is a general and widespread practice common in the contemporary mass culture, which lies behind the process of making sense to moving images usually visualized by means of movie shots. In contrast scientific culture favored another way of time conceptualization (static time metaphor) that historically fostered the construction of graphs and the incorporation of time-dependent functions, as represented on the Cartesian plane, into displaying instruments. Both types of cultures, scientific and mass, are considered highly technological in the sense that complex instruments, apparatus or machines participate in their visual practices.

STRUCTURAL AND HYDROGEOLOGIC APPLICATIONS OF REMOTE SENSING DATA, EASTERN YUCATAN PENINSULA, MEXICO.

USGS Publications Warehouse

Southworth, C. Scott; ,

1984-01-01

Landsat and Seasat satellite images and aerial photographs of eastern Yucatan Peninsula, Mexico, were analyzed to delineate geologic controls of ground water. Significant interpretation results include the delineation of linear topographic swales, interpreted as fractures, extending more than 50 km along strike from the previously known limit of the Holbox fracture system; the alignment of sink holes (cenotes) and inlets (caletas) on strike with existing faults and fracture systems; and the identification of tonal anomalies in Ingles Lagoon suggesting fresh-water discharge from a submarine spring.

Image processing developments and applications for water quality monitoring and trophic state determination

NASA Technical Reports Server (NTRS)

Blackwell, R. J.

1982-01-01

Remote sensing data analysis of water quality monitoring is evaluated. Data anaysis and image processing techniques are applied to LANDSAT remote sensing data to produce an effective operational tool for lake water quality surveying and monitoring. Digital image processing and analysis techniques were designed, developed, tested, and applied to LANDSAT multispectral scanner (MSS) data and conventional surface acquired data. Utilization of these techniques facilitates the surveying and monitoring of large numbers of lakes in an operational manner. Supervised multispectral classification, when used in conjunction with surface acquired water quality indicators, is used to characterize water body trophic status. Unsupervised multispectral classification, when interpreted by lake scientists familiar with a specific water body, yields classifications of equal validity with supervised methods and in a more cost effective manner. Image data base technology is used to great advantage in characterizing other contributing effects to water quality. These effects include drainage basin configuration, terrain slope, soil, precipitation and land cover characteristics.

Searching for patterns in remote sensing image databases using neural networks

NASA Technical Reports Server (NTRS)

Paola, Justin D.; Schowengerdt, Robert A.

1995-01-01

We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.

A rapid extraction of landslide disaster information research based on GF-1 image

NASA Astrophysics Data System (ADS)

Wang, Sai; Xu, Suning; Peng, Ling; Wang, Zhiyi; Wang, Na

2015-08-01

In recent years, the landslide disasters occurred frequently because of the seismic activity. It brings great harm to people's life. It has caused high attention of the state and the extensive concern of society. In the field of geological disaster, landslide information extraction based on remote sensing has been controversial, but high resolution remote sensing image can improve the accuracy of information extraction effectively with its rich texture and geometry information. Therefore, it is feasible to extract the information of earthquake- triggered landslides with serious surface damage and large scale. Taking the Wenchuan county as the study area, this paper uses multi-scale segmentation method to extract the landslide image object through domestic GF-1 images and DEM data, which uses the estimation of scale parameter tool to determine the optimal segmentation scale; After analyzing the characteristics of landslide high-resolution image comprehensively and selecting spectrum feature, texture feature, geometric features and landform characteristics of the image, we can establish the extracting rules to extract landslide disaster information. The extraction results show that there are 20 landslide whose total area is 521279.31 .Compared with visual interpretation results, the extraction accuracy is 72.22%. This study indicates its efficient and feasible to extract earthquake landslide disaster information based on high resolution remote sensing and it provides important technical support for post-disaster emergency investigation and disaster assessment.

Moccasin on One Foot, High Heel on the Other: Life Story Reflections of Coreen Gladue

ERIC Educational Resources Information Center

Vannini, April; Gladue, Coreen

2009-01-01

Drawing from life history interviews with Coreen Gladue--a Cree/Metis woman resident of British Columbia, Canada--this article uses poetic representation and visual images to tell stories about Coreen's sense of self and identity, family relations, education, and interpretation of the meanings of Canada's "Indian Act". Poems and…

A feed-forward Hopfield neural network algorithm (FHNNA) with a colour satellite image for water quality mapping

NASA Astrophysics Data System (ADS)

Asal Kzar, Ahmed; Mat Jafri, M. Z.; Hwee San, Lim; Al-Zuky, Ali A.; Mutter, Kussay N.; Hassan Al-Saleh, Anwar

2016-06-01

There are many techniques that have been given for water quality problem, but the remote sensing techniques have proven their success, especially when the artificial neural networks are used as mathematical models with these techniques. Hopfield neural network is one type of artificial neural networks which is common, fast, simple, and efficient, but it when it deals with images that have more than two colours such as remote sensing images. This work has attempted to solve this problem via modifying the network that deals with colour remote sensing images for water quality mapping. A Feed-forward Hopfield Neural Network Algorithm (FHNNA) was modified and used with a satellite colour image from type of Thailand earth observation system (THEOS) for TSS mapping in the Penang strait, Malaysia, through the classification of TSS concentrations. The new algorithm is based essentially on three modifications: using HNN as feed-forward network, considering the weights of bitplanes, and non-self-architecture or zero diagonal of weight matrix, in addition, it depends on a validation data. The achieved map was colour-coded for visual interpretation. The efficiency of the new algorithm has found out by the higher correlation coefficient (R=0.979) and the lower root mean square error (RMSE=4.301) between the validation data that were divided into two groups. One used for the algorithm and the other used for validating the results. The comparison was with the minimum distance classifier. Therefore, TSS mapping of polluted water in Penang strait, Malaysia, can be performed using FHNNA with remote sensing technique (THEOS). It is a new and useful application of HNN, so it is a new model with remote sensing techniques for water quality mapping which is considered important environmental problem.

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

Ellis, J.M.

Remote sensing allows the petroleum industry to make better and quicker interpretations of geological and environmental conditions in areas of present and future operations. Often remote sensing (including aerial photographs) is required because existing maps are out-of-date, too small of scale, or provide only limited information. Implementing remote sensing can lead to lower project costs and reduced risk. The same satellite and airborne data can be used effectively for both geological and environmental applications. For example, earth scientists can interpret new lithologic, structural, and geomorphic information from near-infrared and radar imagery in terrains as diverse as barren desert and tropicalmore » jungle. Environmental applications with these and other imagery include establishing baselines, assessing impact by documenting changes through time, and mapping land-use, habitat, and vegetation. Higher resolution sensors provide an up-to-date overview of onshore and offshore petroleum facilities, whereas sensors capable of oblique viewing can be used to generate topographic maps. Geological application in Yemen involved merging Landsat TM and SPOT imagery to obtain exceptional lithologic discrimination. In the Congo, a topographic map to plan field operations was interpreted from the overlapping radar strips. Landsat MSS and TM, SPOT, and Russian satellite images with new aerial photographs are being used in the Tengiz supergiant oil field of Kazakhstan to help establish an environmental baseline, generate a base map, locate wells, plan facilities, and support a geographical information system (GIS). In the Niger delta, Landsat TM and SPOT are being used to plan pipeline routes and seismic lines, and to monitor rapid shoreline changes and population growth. Accurate coastlines, facility locations, and shoreline types are being extracted from satellite images for use in oil spill models.« less

Sensing Super-Position: Human Sensing Beyond the Visual Spectrum

NASA Technical Reports Server (NTRS)

Maluf, David A.; Schipper, John F.

2007-01-01

The coming decade of fast, cheap and miniaturized electronics and sensory devices opens new pathways for the development of sophisticated equipment to overcome limitations of the human senses. This paper addresses the technical feasibility of augmenting human vision through Sensing Super-position by mixing natural Human sensing. The current implementation of the device translates visual and other passive or active sensory instruments into sounds, which become relevant when the visual resolution is insufficient for very difficult and particular sensing tasks. A successful Sensing Super-position meets many human and pilot vehicle system requirements. The system can be further developed into cheap, portable, and low power taking into account the limited capabilities of the human user as well as the typical characteristics of his dynamic environment. The system operates in real time, giving the desired information for the particular augmented sensing tasks. The Sensing Super-position device increases the image resolution perception and is obtained via an auditory representation as well as the visual representation. Auditory mapping is performed to distribute an image in time. The three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. This paper details the approach of developing Sensing Super-position systems as a way to augment the human vision system by exploiting the capabilities of Lie human hearing system as an additional neural input. The human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns. The known capabilities of the human hearing system to learn and understand complicated auditory patterns provided the basic motivation for developing an image-to-sound mapping system. The human brain is superior to most existing computer systems in rapidly extracting relevant information from blurred, noisy, and redundant images. From a theoretical viewpoint, this means that the available bandwidth is not exploited in an optimal way. While image-processing techniques can manipulate, condense and focus the information (e.g., Fourier Transforms), keeping the mapping as direct and simple as possible might also reduce the risk of accidentally filtering out important clues. After all, especially a perfect non-redundant sound representation is prone to loss of relevant information in the non-perfect human hearing system. Also, a complicated non-redundant image-to-sound mapping may well be far more difficult to learn and comprehend than a straightforward mapping, while the mapping system would increase in complexity and cost. This work will demonstrate some basic information processing for optimal information capture for headmounted systems.

Old Fire/Grand Prix Fire, California

NASA Image and Video Library

2003-11-19

On November 18, 2003, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA's Terra satellite acquired this image of the Old Fire/Grand Prix fire east of Los Angeles. The image is being processed by NASA's Wildfire Response Team and will be sent to the United States Department of Agriculture's Forest Service Remote Sensing Applications Center (RSAC) which provides interpretation services to Burned Area Emergency Response (BAER) teams to assist in mapping the severity of the burned areas. The image combines data from the visible and infrared wavelength regions to highlight the burned areas. http://photojournal.jpl.nasa.gov/catalog/PIA04879

FEX: A Knowledge-Based System For Planimetric Feature Extraction

NASA Astrophysics Data System (ADS)

Zelek, John S.

1988-10-01

Topographical planimetric features include natural surfaces (rivers, lakes) and man-made surfaces (roads, railways, bridges). In conventional planimetric feature extraction, a photointerpreter manually interprets and extracts features from imagery on a stereoplotter. Visual planimetric feature extraction is a very labour intensive operation. The advantages of automating feature extraction include: time and labour savings; accuracy improvements; and planimetric data consistency. FEX (Feature EXtraction) combines techniques from image processing, remote sensing and artificial intelligence for automatic feature extraction. The feature extraction process co-ordinates the information and knowledge in a hierarchical data structure. The system simulates the reasoning of a photointerpreter in determining the planimetric features. Present efforts have concentrated on the extraction of road-like features in SPOT imagery. Keywords: Remote Sensing, Artificial Intelligence (AI), SPOT, image understanding, knowledge base, apars.

Looking beyond disfigurement: the experience of patients with head and neck cancer.

PubMed

Henry, Melissa; Ho, Angela; Lambert, Sylvie D; Carnevale, Franco A; Greenfield, Brian; MacDonald, Christina; Mlynarek, Alex; Zeitouni, Anthony; Rosberger, Zeev; Hier, Michael; Black, Martin; Kost, Karen; Frenkiel, Saul

2014-01-01

Despite the frequent occurrence of head and neck cancer (HNC) disfigurement, little is known about its psychosocial impact on patients. This study aimed to understand the lived experience of disfigurement in HNC and explore what patients considered to be its influences. Fourteen disfigured HNC patients participated in a 45-to-120-minute in-depth, semistructured interview, which was analyzed qualitatively using interpretive phenomenology. A majority of participants (64 percent) were considered to be at an advanced cancer stage (stage III or stage IV). Patients' experiences revolved around the concept of a ruptured self-image (a discontinuity in sense of self). Forces triggering this ruptured self-image created a sense of "embodied angst", in which disfigurement served as a constant reminder of the patient's cancer and associated foundational malaise. Other influences fostered a sense of normalcy, balance, and acceptance. Participants oscillated between these two states as they grew to accept their disfigurement. This study's findings could guide supportive interventions aimed at helping patients face head and neck surgery.

Utility of shallow-water ATRIS images in defining biogeologic processes and self-similarity in skeletal scleractinia, Florida reefs

USGS Publications Warehouse

Lidz, B.H.; Brock, J.C.; Nagle, D.B.

2008-01-01

A recently developed remote-sensing instrument acquires high-quality digital photographs in shallow-marine settings within water depths of 15 m. The technology, known as the Along-Track Reef-Imaging System, provides remarkably clear, georeferenced imagery that allows visual interpretation of benthic class (substrates, organisms) for mapping coral reef habitats, as intended. Unforeseen, however, are functions new to the initial technologic purpose: interpr??table evidence for real-time biogeologic processes and for perception of scaled-up skeletal self-similarity of scleractinian microstructure. Florida reef sea trials lacked the grid structure required to map contiguous habitat and submarine topography. Thus, only general observations could be made relative to times and sites of imagery. Degradation of corals was nearly universal; absence of reef fish was profound. However, ???1% of more than 23,600 sea-trial images examined provided visual evidence for local environs and processes. Clarity in many images was so exceptional that small tracks left by organisms traversing fine-grained carbonate sand were visible. Other images revealed a compelling sense, not yet fully understood, of the microscopic wall structure characteristic of scleractinian corals. Conclusions drawn from classifiable images are that demersal marine animals, where imaged, are oblivious to the equipment and that the technology has strong capabilities beyond mapping habitat. Imagery acquired along predetermined transects that cross a variety of geomorphic features within depth limits will ( 1) facilitate construction of accurate contour maps of habitat and bathymetry without need for ground-truthing, (2) contain a strong geologic component of interpreted real-time processes as they relate to imaged topography and regional geomorphology, and (3) allow cost-effective monitoring of regional- and local-scale changes in an ecosystem by use of existing-image global-positioning system coordinates to re-image areas. Details revealed in the modern setting have taphonomic implications for what is often found in the geologic record.

Soldier, Sailor, Rebel, Rule-Breaker: Masculinity and the Body in the German Far Right

ERIC Educational Resources Information Center

Miller-Idriss, Cynthia

2017-01-01

Drawing on a unique digital archive of thousands of images of far right symbols and commercial products in Germany, combined with 62 interviews conducted with German youth and their teachers in 2013-2014, this article examines young Germans' sense of style and their interpretation of far right-wing symbols and codes in commercial products,…

The Influence of Visual and Spatial Reasoning in Interpreting Simulated 3D Worlds.

ERIC Educational Resources Information Center

Lowrie, Tom

2002-01-01

Explores ways in which 6-year-old children make sense of screen-based images on the computer. Uses both static and relatively dynamic software programs in the investigation. Suggests that young children should be exposed to activities that establish explicit links between 2D and 3D objects away from the computer before attempting difficult links…

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.

The sky is the limit: reconstructing physical geography fieldwork from an aerial perspective

NASA Astrophysics Data System (ADS)

Williams, R.; Tooth, S.; Gibson, M.; Barrett, B.

2017-12-01

In an era of rapid geographical data acquisition, interpretations of remote sensing products (e.g. aerial photographs, satellite images, digital elevation models) are an integral part of many undergraduate geography degree schemes but there are fewer opportunities for collection and processing of primary remote sensing data. Unmanned aerial vehicles (UAVs) provide a relatively cheap opportunity to introduce the principles and practice of airborne remote sensing into fieldcourses, enabling students to learn about image acquisition, data processing and interpretation of derived products. Three case studies illustrate how a low cost DJI Phantom UAV can be used by students to acquire images that can be processed using off the shelf Structure-from-Motion photogrammetry software. Two case studies are drawn from an international fieldcourse that takes students to field sites that are the focus of current funded research whilst a third case study is from a course in topographic mapping. Results from a student questionnaire and analysis of assessed student reports showed that using UAVs in fieldwork enhanced student engagement with themes on their fieldcourse and equipped them with data processing skills. The derivation of bespoke orthophotos and Digital Elevation Models also provided students with opportunities to gain insight into the various data quality issues that are associated with aerial imagery acquisition and topographic reconstruction, although additional training is required to maximise this potential. Recognition of the successes and limitations of this teaching intervention provides scope for improving exercises that use UAVs and other technologies in future fieldcourses. UAVs are enabling both a reconstruction of how we measure the Earth's surface and a reconstruction of how students do fieldwork.

Landsat and SPOT data for oil exploration in North-Western China

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

Nishidai, Takashi

1996-07-01

Satellite remote sensing technology has been employed by Japex to provide information related to oil exploration programs for many years. Since the beginning of the 1980`s, regional geological interpretation through to advanced studies using satellite imagery with high spectral and spatial resolutions (such as Landsat TM and SPOT HRV), have been carried out, for both exploration programs and for scientific research. Advanced techniques (including analysis of airborne hyper-multispectral imaging sensor data) as well as conventional photogeological techniques were used throughout these programs. The first program using remote sensing technology in China focused on the Tarim Basin, Xinjiang Uygur Autonomous Region,more » and was carried out using Landsat MSS data. Landsat MSS imagery allows us to gain useful preliminary geological information about an area of interest, prior to field studies. About 90 Landsat scenes cover the entire Xinjiang Uygru Autonomous Region, this allowed us to give comprehensive overviews of 3 hydrocarbon-bearing basins (Tarim, Junggar, and Turpan-Hami) in NW China. The overviews were based on the interpretations and assessments of the satellite imagery and on a synthesis of the most up-to-date accessible geological and geophysical data as well as some field works. Pairs of stereoscopic SPOT HRV images were used to generate digital elevation data with a 40 in grid cover for part of the Tarim Basin. Topographic contour maps, created from this digital elevation data, at scales of 1:250,000 and 1:100,000 with contour intervals of 100 m and 50 m, allowed us to make precise geological interpretation, and to carry out swift and efficient geological field work. Satellite imagery was also utilized to make medium scale to large scale image maps, not only to interpret geological features but also to support field workers and seismic survey field operations.« less

Translation-aware semantic segmentation via conditional least-square generative adversarial networks

NASA Astrophysics Data System (ADS)

Zhang, Mi; Hu, Xiangyun; Zhao, Like; Pang, Shiyan; Gong, Jinqi; Luo, Min

2017-10-01

Semantic segmentation has recently made rapid progress in the field of remote sensing and computer vision. However, many leading approaches cannot simultaneously translate label maps to possible source images with a limited number of training images. The core issue is insufficient adversarial information to interpret the inverse process and proper objective loss function to overcome the vanishing gradient problem. We propose the use of conditional least squares generative adversarial networks (CLS-GAN) to delineate visual objects and solve these problems. We trained the CLS-GAN network for semantic segmentation to discriminate dense prediction information either from training images or generative networks. We show that the optimal objective function of CLS-GAN is a special class of f-divergence and yields a generator that lies on the decision boundary of discriminator that reduces possible vanished gradient. We also demonstrate the effectiveness of the proposed architecture at translating images from label maps in the learning process. Experiments on a limited number of high resolution images, including close-range and remote sensing datasets, indicate that the proposed method leads to the improved semantic segmentation accuracy and can simultaneously generate high quality images from label maps.

Application of LANDSAT satellite imagery for iron ore prospecting in the Western Desert of Egypt

NASA Technical Reports Server (NTRS)

Elshazly, E. M.; Abdelhady, M. A.; Elghawaby, M. A.; Khawasik, S. M.

1977-01-01

Prospecting for iron ore occurrences was conducted by the Remote Sensing Center in Bahariya Oasis-El Faiyum area covering some 100,000 km squared in the Western Desert of Egypt. LANDSAT-1 satellite images were utilized as the main tool in the regional prospecting of the iron ores. The delineation of the geological units and geological structure through the interpretation of the images corroborated by field observations and structural analysis led to the discovery of new iron ore occurrences in the area of investigation.

Biochemical Imaging of Gliomas Using MR Spectroscopic Imaging for Radiotherapy Treatment Planning

NASA Astrophysics Data System (ADS)

Heikal, Amr Ahmed

This thesis discusses the main obstacles facing wide clinical implementation of magnetic resonance spectroscopic imaging (MRSI) as a tumor delineation tool for radiotherapy treatment planning, particularly for gliomas. These main obstacles are identified as 1. observer bias and poor interpretational reproducibility of the results of MRSI scans, and 2. the long scan times required to conduct MRSI scans. An examination of an existing user-independent MRSI tumor delineation technique known as the choline-to-NAA index (CNI) is conducted to assess its utility in providing a tool for reproducible interpretation of MRSI results. While working with spatial resolutions typically twice those on which the CNI model was originally designed, a region of statistical uncertainty was discovered between the tumor and normal tissue populations and as such a modification to the CNI model was introduced to clearly identify that region. To address the issue of long scan times, a series of studies were conducted to adapt a scan acceleration technique, compressed sensing (CS), to work with MRSI and to quantify the effects of such a novel technique on the modulation transfer function (MTF), an important quantitative imaging metric. The studies included the development of the first phantom based method of measuring the MTF for MRSI data, a study of the correlation between the k-space sampling patterns used for compressed sensing and the resulting MTFs, and the introduction of a technique circumventing some of side-effects of compressed sensing by exploiting the conjugate symmetry property of k-space. The work in this thesis provides two essential steps towards wide clinical implementation of MRSI-based tumor delineation. The proposed modifications to the CNI method coupled with the application of CS to MRSI address the two main obstacles outlined. However, there continues to be room for improvement and questions that need to be answered by future research.

Structural interpretation of seismic data and inherent uncertainties

NASA Astrophysics Data System (ADS)

Bond, Clare

2013-04-01

Geoscience is perhaps unique in its reliance on incomplete datasets and building knowledge from their interpretation. This interpretation basis for the science is fundamental at all levels; from creation of a geological map to interpretation of remotely sensed data. To teach and understand better the uncertainties in dealing with incomplete data we need to understand the strategies individual practitioners deploy that make them effective interpreters. The nature of interpretation is such that the interpreter needs to use their cognitive ability in the analysis of the data to propose a sensible solution in their final output that is both consistent not only with the original data but also with other knowledge and understanding. In a series of experiments Bond et al. (2007, 2008, 2011, 2012) investigated the strategies and pitfalls of expert and non-expert interpretation of seismic images. These studies focused on large numbers of participants to provide a statistically sound basis for analysis of the results. The outcome of these experiments showed that a wide variety of conceptual models were applied to single seismic datasets. Highlighting not only spatial variations in fault placements, but whether interpreters thought they existed at all, or had the same sense of movement. Further, statistical analysis suggests that the strategies an interpreter employs are more important than expert knowledge per se in developing successful interpretations. Experts are successful because of their application of these techniques. In a new set of experiments a small number of experts are focused on to determine how they use their cognitive and reasoning skills, in the interpretation of 2D seismic profiles. Live video and practitioner commentary were used to track the evolving interpretation and to gain insight on their decision processes. The outputs of the study allow us to create an educational resource of expert interpretation through online video footage and commentary with associated further interpretation and analysis of the techniques and strategies employed. This resource will be of use to undergraduate, post-graduate, industry and academic professionals seeking to improve their seismic interpretation skills, develop reasoning strategies for dealing with incomplete datasets, and for assessing the uncertainty in these interpretations. Bond, C.E. et al. (2012). 'What makes an expert effective at interpreting seismic images?' Geology, 40, 75-78. Bond, C. E. et al. (2011). 'When there isn't a right answer: interpretation and reasoning, key skills for 21st century geoscience'. International Journal of Science Education, 33, 629-652. Bond, C. E. et al. (2008). 'Structural models: Optimizing risk analysis by understanding conceptual uncertainty'. First Break, 26, 65-71. Bond, C. E. et al., (2007). 'What do you think this is?: "Conceptual uncertainty" In geoscience interpretation'. GSA Today, 17, 4-10.

"Proximal Sensing" capabilities for snow cover monitoring

NASA Astrophysics Data System (ADS)

Valt, Mauro; Salvatori, Rosamaria; Plini, Paolo; Salzano, Roberto; Giusti, Marco; Montagnoli, Mauro; Sigismondi, Daniele; Cagnati, Anselmo

2013-04-01

The seasonal snow cover represents one of the most important land cover class in relation to environmental studies in mountain areas, especially considering its variation during time. Snow cover and its extension play a relevant role for the studies on the atmospheric dynamics and the evolution of climate. It is also important for the analysis and management of water resources and for the management of touristic activities in mountain areas. Recently, webcam images collected at daily or even hourly intervals are being used as tools to observe the snow covered areas; those images, properly processed, can be considered a very important environmental data source. Images captured by digital cameras become a useful tool at local scale providing images even when the cloud coverage makes impossible the observation by satellite sensors. When suitably processed these images can be used for scientific purposes, having a good resolution (at least 800x600x16 million colours) and a very good sampling frequency (hourly images taken through the whole year). Once stored in databases, those images represent therefore an important source of information for the study of recent climatic changes, to evaluate the available water resources and to analyse the daily surface evolution of the snow cover. The Snow-noSnow software has been specifically designed to automatically detect the extension of snow cover collected from webcam images with a very limited human intervention. The software was tested on images collected on Alps (ARPAV webcam network) and on Apennine in a pilot station properly equipped for this project by CNR-IIA. The results obtained through the use of Snow-noSnow are comparable to the one achieved by photo-interpretation and could be considered as better as the ones obtained using the image segmentation routine implemented into image processing commercial softwares. Additionally, Snow-noSnow operates in a semi-automatic way and has a reduced processing time. The analysis of this kind of images could represent an useful element to support the interpretation of remote sensing images, especially those provided by high spatial resolution sensors. Keywords: snow cover monitoring, digital images, software, Alps, Apennines.

USGS remote sensing coordination for the 2010 Haiti earthquake

USGS Publications Warehouse

Duda, Kenneth A.; Jones, Brenda

2011-01-01

In response to the devastating 12 January 2010, earthquake in Haiti, the US Geological Survey (USGS) provided essential coordinating services for remote sensing activities. Communication was rapidly established between the widely distributed response teams and data providers to define imaging requirements and sensor tasking opportunities. Data acquired from a variety of sources were received and archived by the USGS, and these products were subsequently distributed using the Hazards Data Distribution System (HDDS) and other mechanisms. Within six weeks after the earthquake, over 600,000 files representing 54 terabytes of data were provided to the response community. The USGS directly supported a wide variety of groups in their use of these data to characterize post-earthquake conditions and to make comparisons with pre-event imagery. The rapid and continuing response achieved was enabled by existing imaging and ground systems, and skilled personnel adept in all aspects of satellite data acquisition, processing, distribution and analysis. The information derived from image interpretation assisted senior planners and on-site teams to direct assistance where it was most needed.

Mapping and monitoring changes in vegetation communities of Jasper Ridge, CA, using spectral fractions derived from AVIRIS images

NASA Technical Reports Server (NTRS)

Sabol, Donald E., Jr.; Roberts, Dar A.; Adams, John B.; Smith, Milton O.

1993-01-01

An important application of remote sensing is to map and monitor changes over large areas of the land surface. This is particularly significant with the current interest in monitoring vegetation communities. Most of traditional methods for mapping different types of plant communities are based upon statistical classification techniques (i.e., parallel piped, nearest-neighbor, etc.) applied to uncalibrated multispectral data. Classes from these techniques are typically difficult to interpret (particularly to a field ecologist/botanist). Also, classes derived for one image can be very different from those derived from another image of the same area, making interpretation of observed temporal changes nearly impossible. More recently, neural networks have been applied to classification. Neural network classification, based upon spectral matching, is weak in dealing with spectral mixtures (a condition prevalent in images of natural surfaces). Another approach to mapping vegetation communities is based on spectral mixture analysis, which can provide a consistent framework for image interpretation. Roberts et al. (1990) mapped vegetation using the band residuals from a simple mixing model (the same spectral endmembers applied to all image pixels). Sabol et al. (1992b) and Roberts et al. (1992) used different methods to apply the most appropriate spectral endmembers to each image pixel, thereby allowing mapping of vegetation based upon the the different endmember spectra. In this paper, we describe a new approach to classification of vegetation communities based upon the spectra fractions derived from spectral mixture analysis. This approach was applied to three 1992 AVIRIS images of Jasper Ridge, California to observe seasonal changes in surface composition.

Recent advances in remote sensing; Proceedings of the First International Geoscience and Remote Sensing Symposium, Washington, DC, June 8-10, 1981

NASA Technical Reports Server (NTRS)

Mcintosh, R.

1982-01-01

The state of the art in remote sensing of the earth and the planets was discussed in terms of sensor performance, signal processing, and data interpretation. Particular attention was given to lidar for characterizing atmospheric particulates, the modulation of short waves by long ocean gravity waves, and runoff modeling for snow-covered areas. The use of NOAA-6 spacecraft AVHRR data to explore hydrologic land surface features, the effects of soil moisture and vegetation canopies on microwave and thermal microwave emissions, and regional scale evapotranspiration rate determination through satellite IR data are examined. A Shuttle experiment to demonstrate high accuracy global time and frequency transfer is described, along with features of the proposed Gravsat, radar image processing for rock-type discrimination, and passive microwave sensing of temperature and salinity in coastal zones.

Imaging and Analytics: The changing face of Medical Imaging

NASA Astrophysics Data System (ADS)

Foo, Thomas

There have been significant technological advances in imaging capability over the past 40 years. Medical imaging capabilities have developed rapidly, along with technology development in computational processing speed and miniaturization. Moving to all-digital, the number of images that are acquired in a routine clinical examination has increased dramatically from under 50 images in the early days of CT and MRI to more than 500-1000 images today. The staggering number of images that are routinely acquired poses significant challenges for clinicians to interpret the data and to correctly identify the clinical problem. Although the time provided to render a clinical finding has not substantially changed, the amount of data available for interpretation has grown exponentially. In addition, the image quality (spatial resolution) and information content (physiologically-dependent image contrast) has also increased significantly with advances in medical imaging technology. On its current trajectory, medical imaging in the traditional sense is unsustainable. To assist in filtering and extracting the most relevant data elements from medical imaging, image analytics will have a much larger role. Automated image segmentation, generation of parametric image maps, and clinical decision support tools will be needed and developed apace to allow the clinician to manage, extract and utilize only the information that will help improve diagnostic accuracy and sensitivity. As medical imaging devices continue to improve in spatial resolution, functional and anatomical information content, image/data analytics will be more ubiquitous and integral to medical imaging capability.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Remotely sensed geology from lander-based to orbital perspectives: Results of FIDO rover May 2000 field tests

USGS Publications Warehouse

Jolliff, B.; Knoll, A.; Morris, R.V.; Moersch, J.; McSween, H.; Gilmore, M.; Arvidson, R.; Greeley, R.; Herkenhoff, K.; Squyres, S.

2002-01-01

Blind field tests of the Field Integration Design and Operations (FIDO) prototype Mars rover were carried out 7-16 May 2000. A Core Operations Team (COT), sequestered at the Jet Propulsion Laboratory without knowledge of test site location, prepared command sequences and interpreted data acquired by the rover. Instrument sensors included a stereo panoramic camera, navigational and hazard-avoidance cameras, a color microscopic imager, an infrared point spectrometer, and a rock coring drill. The COT designed command sequences, which were relayed by satellite uplink to the rover, and evaluated instrument data. Using aerial photos and Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data, and information from the rover sensors, the COT inferred the geology of the landing site during the 18 sol mission, including lithologic diversity, stratigraphic relationships, environments of deposition, and weathering characteristics. Prominent lithologic units were interpreted to be dolomite-bearing rocks, kaolinite-bearing altered felsic volcanic materials, and basalt. The color panoramic camera revealed sedimentary layering and rock textures, and geologic relationships seen in rock exposures. The infrared point spectrometer permitted identification of prominent carbonate and kaolinite spectral features and permitted correlations to outcrops that could not be reached by the rover. The color microscopic imager revealed fine-scale rock textures, soil components, and results of coring experiments. Test results show that close-up interrogation of rocks is essential to investigations of geologic environments and that observations must include scales ranging from individual boulders and outcrops (microscopic, macroscopic) to orbital remote sensing, with sufficient intermediate steps (descent images) to connect in situ and remote observations.

Interpretation of laser/multi-sensor data for short range terrain modeling and hazard detection

NASA Technical Reports Server (NTRS)

Messing, B. S.

1980-01-01

A terrain modeling algorithm that would reconstruct the sensed ground images formed by the triangulation scheme, and classify as unsafe any terrain feature that would pose a hazard to a roving vehicle is described. This modeler greatly reduces quantization errors inherent in a laser/sensing system through the use of a thinning algorithm. Dual filters are employed to separate terrain steps from the general landscape, simplifying the analysis of terrain features. A crosspath analysis is utilized to detect and avoid obstacles that would adversely affect the roll of the vehicle. Computer simulations of the rover on various terrains examine the performance of the modeler.

Geological terrain models

NASA Technical Reports Server (NTRS)

Kaupp, V. H.; Macdonald, H. C.; Waite, W. P.

1981-01-01

The initial phase of a program to determine the best interpretation strategy and sensor configuration for a radar remote sensing system for geologic applications is discussed. In this phase, terrain modeling and radar image simulation were used to perform parametric sensitivity studies. A relatively simple computer-generated terrain model is presented, and the data base, backscatter file, and transfer function for digital image simulation are described. Sets of images are presented that simulate the results obtained with an X-band radar from an altitude of 800 km and at three different terrain-illumination angles. The simulations include power maps, slant-range images, ground-range images, and ground-range images with statistical noise incorporated. It is concluded that digital image simulation and computer modeling provide cost-effective methods for evaluating terrain variations and sensor parameter changes, for predicting results, and for defining optimum sensor parameters.

International Symposium on Remote Sensing of Environment, Third Thematic Conference: Remote Sensing for Exploration Geology, Colorado Springs, CO, April 16-19, 1984, Proceedings. Volumes 1 & 2

NASA Technical Reports Server (NTRS)

1985-01-01

A photogeologic and remote sensing model of porphyry type mineral sytems is considered along with a Landsat application to development of a tectonic model for hydrocarbon exploration of Devonian shales in west-central Virginia, remote sensing and the funnel philosophy, Landsat-based tectonic and metallogenic synthesis of the southwest United States, and an evolving paradigm for computer vision. Attention is given to the neotectonics of the Tibetan plateau deduced from Landsat MSS image interpretation, remote sensing in northern Arizona, the use of an airborne laser system for vegetation inventories and geobotanical prospecting, an evaluation of Thematic Mapper data for hydrocarbon exploration in low-relief basins, and an evaluation of the information content of high spectral resolution imagery. Other topics explored are related to a major source of new radar data for exploration research, the accuracy of geologic maps produced from Landsat data, and an approach for the geometric rectification of radar imagery.

Long-Term Monitoring of Desert Land and Natural Resources and Application of Remote Sensing Technologies

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

Hamada, Yuki; Rollins, Katherine E.

2016-11-01

Monitoring environmental impacts over large, remote desert regions for long periods of time can be very costly. Remote sensing technologies present a promising monitoring tool because they entail the collection of spatially contiguous data, automated processing, and streamlined data analysis. This report provides a summary of remote sensing products and refinement of remote sensing data interpretation methodologies that were generated as part of the U.S. Department of the Interior Bureau of Land Management Solar Energy Program. In March 2015, a team of researchers from Argonne National Laboratory (Argonne) collected field data of vegetation and surface types from more than 5,000more » survey points within the eastern part of the Riverside East Solar Energy Zone (SEZ). Using the field data, remote sensing products that were generated in 2014 using very high spatial resolution (VHSR; 15 cm) multispectral aerial images were validated in order to evaluate potential refinements to the previous methodologies to improve the information extraction accuracy.« less

Application of Machine Learning in Urban Greenery Land Cover Extraction

NASA Astrophysics Data System (ADS)

Qiao, X.; Li, L. L.; Li, D.; Gan, Y. L.; Hou, A. Y.

2018-04-01

Urban greenery is a critical part of the modern city and the greenery coverage information is essential for land resource management, environmental monitoring and urban planning. It is a challenging work to extract the urban greenery information from remote sensing image as the trees and grassland are mixed with city built-ups. In this paper, we propose a new automatic pixel-based greenery extraction method using multispectral remote sensing images. The method includes three main steps. First, a small part of the images is manually interpreted to provide prior knowledge. Secondly, a five-layer neural network is trained and optimised with the manual extraction results, which are divided to serve as training samples, verification samples and testing samples. Lastly, the well-trained neural network will be applied to the unlabelled data to perform the greenery extraction. The GF-2 and GJ-1 high resolution multispectral remote sensing images were used to extract greenery coverage information in the built-up areas of city X. It shows a favourable performance in the 619 square kilometers areas. Also, when comparing with the traditional NDVI method, the proposed method gives a more accurate delineation of the greenery region. Due to the advantage of low computational load and high accuracy, it has a great potential for large area greenery auto extraction, which saves a lot of manpower and resources.

Subatomic Features on the Silicon (111)-(7x7) Surface Observed by Atomic Force Microscopy.

PubMed

Giessibl; Hembacher; Bielefeldt; Mannhart

2000-07-21

The atomic force microscope images surfaces by sensing the forces between a sharp tip and a sample. If the tip-sample interaction is dominated by short-range forces due to the formation of covalent bonds, the image of an individual atom should reflect the angular symmetry of the interaction. Here, we report on a distinct substructure in the images of individual adatoms on silicon (111)-(7x7), two crescents with a spherical envelope. The crescents are interpreted as images of two atomic orbitals of the front atom of the tip. Key for the observation of these subatomic features is a force-detection scheme with superior noise performance and enhanced sensitivity to short-range forces.

PROCEDURES FOR ACCURATE PRODUCTION OF COLOR IMAGES FROM SATELLITE OR AIRCRAFT MULTISPECTRAL DIGITAL DATA.

USGS Publications Warehouse

Duval, Joseph S.

1985-01-01

Because the display and interpretation of satellite and aircraft remote-sensing data make extensive use of color film products, accurate reproduction of the color images is important. To achieve accurate color reproduction, the exposure and chemical processing of the film must be monitored and controlled. By using a combination of sensitometry, densitometry, and transfer functions that control film response curves, all of the different steps in the making of film images can be monitored and controlled. Because a sensitometer produces a calibrated exposure, the resulting step wedge can be used to monitor the chemical processing of the film. Step wedges put on film by image recording machines provide a means of monitoring the film exposure and color balance of the machines.

Sizing up human health through remote sensing: uses and misuses.

PubMed

Herbreteau, V; Salem, G; Souris, M; Hugot, J P; Gonzalez, J P

2005-03-01

Following the launch of new satellites, remote sensing (RS) has been increasingly implicated in human health research for thirty years, providing a growing availability of images with higher resolution and spectral ranges. However, the scope of applications, beyond theoretical large potentialities, appears limited both by their technical nature and the models developed. An exhaustive review of RS applications in human health highlights the real implication thus far regarding the diversity and range of health issues, remotely sensed data, processes and interpretations. The place of RS is far under its expected potential, revealing fundamental barriers in its implementation for health applications. The selection of images is done by practical considerations as trivial as price and availability, which are often not relevant to addressing health questions requiring suitable resolutions and spatio-temporal range. The relationships of environmental variables from RS, geospatial data from other sources for health investigations are poorly addressed and usually simplified. A discussion covering the potential of RS for human health is developed here to assist health scientists deal with spatial and temporal dynamics of health, by finding the most relevant data and analysis procedures.

Geologic Studies of Planetary Surfaces Using Radar Polarimetric Imaging

NASA Technical Reports Server (NTRS)

Carter, Lynn M.; Campbell, Donald B.; Campbell, Bruce A.

2010-01-01

Radar is a useful remote sensing tool for studying planetary geology because it is sensitive to the composition, structure, and roughness of the surface and can penetrate some materials to reveal buried terrain. The Arecibo Observatory radar system transmits a single sense of circular polarization, and both senses of circular polarization are received, which allows for the construction of the Stokes polarization vector. From the Stokes vector, daughter products such as the circular polarization ratio, the degree of linear polarization, and linear polarization angle are obtained. Recent polarimetric imaging using Arecibo has included Venus and the Moon. These observations can be compared to radar data for terrestrial surfaces to better understand surface physical properties and regional geologic evolution. For example, polarimetric radar studies of volcanic settings on Venus, the Moon and Earth display some similarities, but also illustrate a variety of different emplacement and erosion mechanisms. Polarimetric radar data provides important information about surface properties beyond what can be obtained from single-polarization radar. Future observations using polarimetric synthetic aperture radar will provide information on roughness, composition and stratigraphy that will support a broader interpretation of surface evolution.

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

PubMed

Hay, S I

2000-01-01

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

An Overview of Remote Sensing and Geodesy for Epidemiology and Public Health Application

PubMed Central

Hay, S.I.

2011-01-01

The techniques of remote sensing (RS) and geodesy have the potential to revolutionize the discipline of epidemiology and its application in human health. As a new departure from conventional epidemiological methods, these techniques require some detailed explanation. This review provides the theoretical background to RS including (i) its physical basis, (ii) an explanation of the orbital characteristics and specifications of common satellite sensor systems, (iii) details of image acquisition and procedures adopted to overcome inherent sources of data degradation, and (iv) a background to geophysical data preparation. This information allows RS applications in epidemiology to be readily interpreted. Some of the techniques used in geodesy, to locate features precisely on Earth so that they can be registered to satellite sensor-derived images, are also included. While the basic principles relevant to public health are presented here, inevitably many of the details must be left to specialist texts. PMID:10997203

Remote Sensing Tropical Coral Reefs: The View from Above

NASA Astrophysics Data System (ADS)

Purkis, Sam J.

2018-01-01

Carbonate precipitation has been a common life strategy for marine organisms for 3.7 billion years, as, therefore, has their construction of reefs. As favored by modern corals, reef-forming organisms have typically adopted a niche in warm, shallow, well-lit, tropical marine waters, where they are capable of building vast carbonate edifices. Because fossil reefs form water aquifers and hydrocarbon reservoirs, considerable effort has been dedicated to understanding their anatomy and morphology. Remote sensing has a particular role to play here. Interpretation of satellite images has done much to reveal the grand spatial and temporal tapestry of tropical reefs. Comparative sedimentology, whereby modern environments are contrasted with the rock record to improve interpretation, has been particularly transformed by observations made from orbit. Satellite mapping has also become a keystone technology to quantify the coral reef crisis—it can be deployed not only directly to quantify the distribution of coral communities, but also indirectly to establish a climatology for their physical environment. This article reviews the application of remote sensing to tropical coralgal reefs in order to communicate how this fast-growing technology might be central to addressing the coral reef crisis and to look ahead at future developments in the science.

Remote Sensing Tropical Coral Reefs: The View from Above.

PubMed

Purkis, Sam J

2018-01-03

Carbonate precipitation has been a common life strategy for marine organisms for 3.7 billion years, as, therefore, has their construction of reefs. As favored by modern corals, reef-forming organisms have typically adopted a niche in warm, shallow, well-lit, tropical marine waters, where they are capable of building vast carbonate edifices. Because fossil reefs form water aquifers and hydrocarbon reservoirs, considerable effort has been dedicated to understanding their anatomy and morphology. Remote sensing has a particular role to play here. Interpretation of satellite images has done much to reveal the grand spatial and temporal tapestry of tropical reefs. Comparative sedimentology, whereby modern environments are contrasted with the rock record to improve interpretation, has been particularly transformed by observations made from orbit. Satellite mapping has also become a keystone technology to quantify the coral reef crisis-it can be deployed not only directly to quantify the distribution of coral communities, but also indirectly to establish a climatology for their physical environment. This article reviews the application of remote sensing to tropical coralgal reefs in order to communicate how this fast-growing technology might be central to addressing the coral reef crisis and to look ahead at future developments in the science.

Investigation of the Degradation Mechanisms of a Variety of Organic Photovoltaic Devices by Combination of Imaging Techniques - The ISOS-3 Inter-Laboratory Collaboration

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

Rosch, R.; Tanenbaum, D. M.; Jrgensen, M.

2012-04-01

The investigation of degradation of seven distinct sets (with a number of individual cells of n {>=} 12) of state of the art organic photovoltaic devices prepared by leading research laboratories with a combination of imaging methods is reported. All devices have been shipped to and degraded at Riso DTU up to 1830 hours in accordance with established ISOS-3 protocols under defined illumination conditions. Imaging of device function at different stages of degradation was performed by laser-beam induced current (LBIC) scanning; luminescence imaging, specifically photoluminescence (PLI) and electroluminescence (ELI); as well as by lock-in thermography (LIT). Each of the imagingmore » techniques exhibits its specific advantages with respect to sensing certain degradation features, which will be compared and discussed here in detail. As a consequence, a combination of several imaging techniques yields very conclusive information about the degradation processes controlling device function. The large variety of device architectures in turn enables valuable progress in the proper interpretation of imaging results -- hence revealing the benefits of this large scale cooperation in making a step forward in the understanding of organic solar cell aging and its interpretation by state-of-the-art imaging methods.« less

Investigation of the Degradation Mechanisms of a Variety of Organic Photovoltaic Devices by Combination of Imaging Techniques—the ISOS-3Inter-laboratory Collaboration

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

Germack D.; Rosch, R.; Tanenbaum, D.M.

2012-04-01

The investigation of degradation of seven distinct sets (with a number of individual cells of n {ge} 12) of state of the art organic photovoltaic devices prepared by leading research laboratories with a combination of imaging methods is reported. All devices have been shipped to and degraded at Risoe DTU up to 1830 hours in accordance with established ISOS-3 protocols under defined illumination conditions. Imaging of device function at different stages of degradation was performed by laser-beam induced current (LBIC) scanning; luminescence imaging, specifically photoluminescence (PLI) and electroluminescence (ELI); as well as by lock-in thermography (LIT). Each of the imagingmore » techniques exhibits its specific advantages with respect to sensing certain degradation features, which will be compared and discussed here in detail. As a consequence, a combination of several imaging techniques yields very conclusive information about the degradation processes controlling device function. The large variety of device architectures in turn enables valuable progress in the proper interpretation of imaging results - hence revealing the benefits of this large scale cooperation in making a step forward in the understanding of organic solar cell aging and its interpretation by state-of-the-art imaging methods.« less

Progress in remote sensing as it applies to missions of Committee for Coordination of Joint Prospecting for Mineral Resources in Asian Offshore Areas

USGS Publications Warehouse

Fischer, William A.

1979-01-01

An exception to this focus of investigation was the launch of Seasat, a satellite dedicated to marine investigations. Seasat was short lived but the data produced strongly supported the use of imaging radar for land investigation, and, although studies are incomplete, suggest eventual benefits for the navigator, searchers for marine resources, and mariners--provided that the data and/or interpretations can be available to the marine users shortly after collection. In this regard, the positive steps now being taken in Southeast Asia to establish reception, processing, and interpretation centers are a major development.

Computer Vision Research and Its Applications to Automated Cartography

DTIC Science & Technology

1984-09-01

reflecting from scene surfaces, and the film and digitization processes that result in the computer representation of the image. These models, when...alone. Specifically, intepretations that are in some sense "orthogonal" are preferred. A method for finding such interpretations for right-angle...saturated colors are not precisely representable and the colors recorded with different films or cameras may differ, but the tricomponent representation is t

Interpretive Sourcebook, 1996. A Sense of Place, A Sense of Space: Interpretation under the Big Sky. Proceedings of the National Interpreters Workshop (Billings, Montana, October 22-26, 1996).

ERIC Educational Resources Information Center

Koopmann, Richard W., Ed.

This sourcebook is a compilation of presentations from the National Interpreters Workshop held in Billings, Montana, in 1996. In this book, interpreters share stories of American battlefields, driving tours, wetlands, clovis points, floating classrooms, perfect signs, art collaboration, and wild animals in interpretive programming. Sections…

A Integrated Service Platform for Remote Sensing Image 3D Interpretation and Draughting based on HTML5

NASA Astrophysics Data System (ADS)

LIU, Yiping; XU, Qing; ZhANG, Heng; LV, Liang; LU, Wanjie; WANG, Dandi

2016-11-01

The purpose of this paper is to solve the problems of the traditional single system for interpretation and draughting such as inconsistent standards, single function, dependence on plug-ins, closed system and low integration level. On the basis of the comprehensive analysis of the target elements composition, map representation and similar system features, a 3D interpretation and draughting integrated service platform for multi-source, multi-scale and multi-resolution geospatial objects is established based on HTML5 and WebGL, which not only integrates object recognition, access, retrieval, three-dimensional display and test evaluation but also achieves collection, transfer, storage, refreshing and maintenance of data about Geospatial Objects and shows value in certain prospects and potential for growth.

Study of the urban evolution of Brasilia with the use of LANDSAT data

NASA Technical Reports Server (NTRS)

Deoliveira, M. D. N. (Principal Investigator); Foresti, C.; Niero, M.; Parreiras, E. M. D. F.

1984-01-01

The urban growth of Brasilia within the last ten years is analyzed with special emphasis on the utilization of remote sensing orbital data and automatic image processing. The urban spatial structure and the monitoring of its temporal changes were focused in a whole and dynamic way by the utilization of MSS-LANDSAT images for June 1973, 1978 and 1983. In order to aid data interpretation, a registration algorithm implemented at the Interactive Multispectral Image Analysis System (IMAGE-100) was utilized aiming at the overlap of multitemporal images. The utilization of suitable digital filters, combined with the images overlap, allowed a rapid identification of areas of possible urban growth and oriented the field work. The results obtained permitted an evaluation of the urban growth of Brasilia, taking as reference the proposed stated for the construction of the city.

The coastline remote sensing survey for Zhao Shu Island in Xisha Islands based on WorldView-2

NASA Astrophysics Data System (ADS)

Li, Li; Zhong, Chang; Kong, Fanping

2014-11-01

Due to diastrophism, tide action and human activities, the coastline is always in flux. There are lots of coral islands in the south sea of China. Remote sensing survey for the coastline not only can reassert the necessity and importance of coral protection, but also can provide basic data and scientific basis for island ecologic protection, reasonable utilization of land resources. The study area named Zhao Shu Island lies in Jintong Islands of Xisha. It is a coral island which has people inhabited. Using WorldView-2 satellite remote sensing images as data sources we carry out three phases of coastline investigation and monitoring. The satellite data phases are 2002, 2010 and 2013. Firstly, affirm the bands valuable for color composition on the basis of spectral and correlation analysis. Then extract the coastline by a series of image process, such as image correction, fusion, waterline extraction and coastline revision. Finally determine the coastline types and length by artificial interpretation. The results show that the island length is gradually smaller, which means the island area is reducing. The beach bedrock coast in northern island was eroded seriously especially during the period between 2010 and 2013. In addition, the shoal head shape in the western island changed a lot.

Phenological dynamics of arctic tundra vegetation and its implications on satellite imagery interpretation

NASA Astrophysics Data System (ADS)

Juutinen, Sari; Aurela, Mika; Mikola, Juha; Räsänen, Aleksi; Virtanen, Tarmo

2016-04-01

Remote sensing is a key methodology when monitoring the responses of arctic ecosystems to climatic warming. The short growing season and rapid vegetation development, however, set demands to the timing of image acquisition in the arctic. We used multispectral very high spatial resolution satellite images to study the effect of vegetation phenology on the spectral reflectance and image interpretation in the low arctic tundra in coastal Siberia (Tiksi, 71°35'39"N, 128°53'17"E). The study site mainly consists of peatlands, tussock, dwarf shrub, and grass tundra, and stony areas with some lichen and shrub patches. We tested the hypotheses that (1) plant phenology is responsive to the interannual weather variation and (2) the phenological state of vegetation has an impact on satellite image interpretation and the ability to distinguish between the plant communities. We used an empirical transfer function with temperature sums as drivers to reconstruct daily leaf area index (LAI) for the different plant communities for years 2005, and 2010-2014 based on measured LAI development in summer 2014. Satellite images, taken during growing seasons, were acquired for two years having late and early spring, and short and long growing season, respectively. LAI dynamics showed considerable interannual variation due to weather variation, and particularly the relative contribution of graminoid dominated communities was sensitive to these phenology shifts. We have also analyzed the differences in the reflectance values between the two satellite images taking account the LAI dynamics. These results will increase our understanding of the pitfalls that may arise from the timing of image acquisition when interpreting the vegetation structure in a heterogeneous tundra landscape. Very high spatial resolution multispectral images are available at reasonable cost, but not in high temporal resolution, which may lead to compromises when matching ground truth and the imagery. On the other hand, to identify existing plant communities, high resolution images are needed due fragmented nature of tundra vegetation communities. Temporal differences in the phenology among different plant functional types may also obscure the image interpretations when using spatially low resolution images in heterogeneous landscapes. Phenological features of plant communities should be acknowledged, when plant functional or community type based classifications are used in models to estimate global greenhouse gas emissions and when monitoring changes in vegetation are monitored, for example to indicate permafrost thawing or changes in growing season lengths.

Automatic archaeological feature extraction from satellite VHR images

NASA Astrophysics Data System (ADS)

Jahjah, Munzer; Ulivieri, Carlo

2010-05-01

Archaeological applications need a methodological approach on a variable scale able to satisfy the intra-site (excavation) and the inter-site (survey, environmental research). The increased availability of high resolution and micro-scale data has substantially favoured archaeological applications and the consequent use of GIS platforms for reconstruction of archaeological landscapes based on remotely sensed data. Feature extraction of multispectral remotely sensing image is an important task before any further processing. High resolution remote sensing data, especially panchromatic, is an important input for the analysis of various types of image characteristics; it plays an important role in the visual systems for recognition and interpretation of given data. The methods proposed rely on an object-oriented approach based on a theory for the analysis of spatial structures called mathematical morphology. The term "morphology" stems from the fact that it aims at analysing object shapes and forms. It is mathematical in the sense that the analysis is based on the set theory, integral geometry, and lattice algebra. Mathematical morphology has proven to be a powerful image analysis technique; two-dimensional grey tone images are seen as three-dimensional sets by associating each image pixel with an elevation proportional to its intensity level. An object of known shape and size, called the structuring element, is then used to investigate the morphology of the input set. This is achieved by positioning the origin of the structuring element to every possible position of the space and testing, for each position, whether the structuring element either is included or has a nonempty intersection with the studied set. The shape and size of the structuring element must be selected according to the morphology of the searched image structures. Other two feature extraction techniques were used, eCognition and ENVI module SW, in order to compare the results. These techniques were applied to different archaeological sites in Turkmenistan (Nisa) and in Iraq (Babylon); a further change detection analysis was applied to the Babylon site using two HR images as a pre-post second gulf war. We had different results or outputs, taking into consideration the fact that the operative scale of sensed data determines the final result of the elaboration and the output of the information quality, because each of them was sensitive to specific shapes in each input image, we had mapped linear and nonlinear objects, updating archaeological cartography, automatic change detection analysis for the Babylon site. The discussion of these techniques has the objective to provide the archaeological team with new instruments for the orientation and the planning of a remote sensing application.

Identifying structural styles in Colombia

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

Wilson, W.P.; Van Nieuwenhuise, R.E.; Steuer, M.R.

1996-08-01

Much of our understanding of the Earth is from the study of surface geology and seismic, but many surface structures are responses to deformation which occurred below sedimentary layers. The practice within the petroleum industry is to use top-down processes of analyzing the surface to understand the subsurface, and observed surface structural styles tend to influence seismic interpretations. Yet many conditions which influenced the structural styles seen at the surface are different at depth. Since seismic is a time representation of the Earth, many interpretation pitfalls may exist within areas of complex geology. Also, its reliability decreases with depth andmore » with increasing geologic complexity. Forward modeling and pre-stack depth migration technologies are used to provide true depth images of the seismic data. Even with these advances in seismic imaging technology, the interpreter needs to incorporate additional data into the interpretation. Accurate structural identification requires the interpreter to integrate seismic with surface geology, remote sensing, gravity, magnetic data, geochemistry, fault-plane solutions from earthquakes, and regional tectonic studies. Incorporating these types of data into the interpretation will help us learn how basement is involved in the deformation of overlying sediments. A study of the Eastern Cordillera of Colombia shows the deformation to be dominantly transpressional in style. Euler deconvolution of the areomagnetic data shows a highly fractured basement, steep fault lineaments, en echelon structures, and complex fault patterns, all of which would be typical of wrench-type deformation. Available surface geology, regional studies, earthquake data, and forward modeling support this interpretation.« less

Radar imagery interpretation to provide information about several geothermal sites in the Philippines

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

Not Available

1988-11-17

The Republic of the Philippines is intensely interested in the identification, development, and conservation of natural resources. In keeping with this, the Government of the Philippines has recently completed a nation-wide sedimentary basin evaluation program to assess hydrocarbon potential and assist in future exploration activities. This program of collection and interpretation of the radar imagery was designed to augment and complement the existing data base. The primary objective of the project was to further the goals of international energy development by aiding the Republic of the Philippines in the assessment of potential geothermal and petroleum prospects within the areas imaged.more » Secondary goals were to assist the Republic of the Philippines in utilizing state-of-the-art radar remote sensing technology for resource exploration, and to train key Philippines scientists in the use of imaging radar data. 7 refs., 20 figs., 2 tabs.« less

Radar imagery interpretation to assess the hydrocarbon potential of four sites in the Philippines

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

Not Available

1988-11-17

The Republic of the Philippines is intensely interested in the identification, development, and conservation of natural resources. In keeping with this, the Government of the Philippines has recently completed a nationwide sedimentary basin evaluation program to assess hydrocarbon potential and assist in future exploration activities. This program of collection and interpretation of the radar imagery was designed to augment and complement the existing data base. The primary objective of the project was to further the goals of international energy development by aiding the Republic of the Philippines in the assessment of potential petroleum and geothermal prospects within the areas imaged.more » Secondary goals were to assist the Republic of the Philippines in utilizing state-of-the-art radar remote sensing technology for resource exploration, and to train key Philippines scientists in the use of imaging radar data. 29 refs., 30 figs., 14 tabs.« less

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Quattrochi, Dale A.

2000-01-01

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Study on Karst Information Identification of Qiandongnan Prefecture Based on RS and GIS Technology

NASA Astrophysics Data System (ADS)

Yao, M.; Zhou, G.; Wang, W.; Wu, Z.; Huang, Y.; Huang, X.

2018-04-01

Karst area is a pure natural resource base, at the same time, due to the special geological environment; there are droughts and floods alternating with frequent karst collapse, rocky desertification and other resource and environment problems, which seriously restrict the sustainable economic and social development in karst areas. Therefore, this paper identifies and studies the karst, and clarifies the distribution of karst. Provide basic data for the rational development of resources in the karst region and the governance of desertification. Due to the uniqueness of the karst landscape, it can't be directly recognized and extracted by computer in remote sensing images. Therefore, this paper uses the idea of "RS + DEM" to solve the above problems. this article is based on Landsat-5 TM imagery in 2010 and DEM data, proposes the methods to identify karst information research what is use of slope vector diagram, vegetation distribution map, distribution map of karst rocky desertification and other auxiliary data in combination with the signs for human-computer interaction interpretation, identification and extraction of peak forest, peaks cluster and isolated peaks, and further extraction of karst depression. Experiments show that this method achieves the "RS + DEM" mode through the reasonable combination of remote sensing images and DEM data. It not only effectively extracts karst areas covered with vegetation, but also quickly and accurately locks down the karst area and greatly improves the efficiency and precision of visual interpretation. The accurate interpretation rate of karst information in study area in this paper is 86.73 %.

Remote sensing for rural development planning in Africa

NASA Technical Reports Server (NTRS)

Dunford, C.; Mouat, D. A.; Norton-Griffiths, M.; Slaymaker, D. M.

1983-01-01

Multilevel remote-sensing techniques were combined to provide land resource and land-use information for rural development planning in Arusha Region, Tanzania. Enhanced Landsat imagery, supplemented by low-level aerial survey data, slope angle data from topographic sheets, and existing reports on vegetation and soil conditions, was used jointly by image analysts and district-level land-management officials to divide the region's six districts into land-planning units. District-planning officials selected a number of these land-planning units for priority planning and development activities. For the priority areas, natural color aerial photographs provided detailed information for land-use planning discussions between district officials and villagers. Consideration of the efficiency of this remote sensing approach leads to general recommendations for similar applications. The technology and timing of data collection and interpretation activities should allow maximum participation by intended users of the information.

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.

Geological-structural interpretation using products of remote sensing in the region of Carrancas, Minas Gerais, Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Dossantos, A. R.; Dosanjos, C. E.; Barbosa, M. P.; Veneziani, P.

1982-01-01

The efficiency of some criteria developed for the utilization of small scale and low resolution remote sensing products to map geological and structural features was demonstrated. Those criteria were adapted from the Logical Method of Photointerpretation which consists of textural qualitative analysis of landforms and drainage net patterns. LANDSAT images of channel 5 and 7, 4 LANDSAT-RBV scenes, and 1 radar mosiac were utilized. The region of study is characterized by supracrustal metassediments (quartzites and micaschist) folded according to a "zig-zag" pattern and gnaissic basement. Lithological-structural definition was considered outstanding when compared to data acquired during field work, bibliographic data and geologic maps acquired in larger scales.

Improved image classification with neural networks by fusing multispectral signatures with topological data

NASA Technical Reports Server (NTRS)

Harston, Craig; Schumacher, Chris

1992-01-01

Automated schemes are needed to classify multispectral remotely sensed data. Human intelligence is often required to correctly interpret images from satellites and aircraft. Humans suceed because they use various types of cues about a scene to accurately define the contents of the image. Consequently, it follows that computer techniques that integrate and use different types of information would perform better than single source approaches. This research illustrated that multispectral signatures and topographical information could be used in concert. Significantly, this dual source tactic classified a remotely sensed image better than the multispectral classification alone. These classifications were accomplished by fusing spectral signatures with topographical information using neural network technology. A neural network was trained to classify Landsat mulitspectral signatures. A file of georeferenced ground truth classifications were used as the training criterion. The network was trained to classify urban, agriculture, range, and forest with an accuracy of 65.7 percent. Another neural network was programmed and trained to fuse these multispectral signature results with a file of georeferenced altitude data. This topological file contained 10 levels of elevations. When this nonspectral elevation information was fused with the spectral signatures, the classifications were improved to 73.7 and 75.7 percent.

Hyperspectral imaging applied to forensic medicine

NASA Astrophysics Data System (ADS)

Malkoff, Donald B.; Oliver, William R.

2000-03-01

Remote sensing techniques now include the use of hyperspectral infrared imaging sensors covering the mid-and- long wave regions of the spectrum. They have found use in military surveillance applications due to their capability for detection and classification of a large variety of both naturally occurring and man-made substances. The images they produce reveal the spatial distributions of spectral patterns that reflect differences in material temperature, texture, and composition. A program is proposed for demonstrating proof-of-concept in using a portable sensor of this type for crime scene investigations. It is anticipated to be useful in discovering and documenting the affects of trauma and/or naturally occurring illnesses, as well as detecting blood spills, tire patterns, toxic chemicals, skin injection sites, blunt traumas to the body, fluid accumulations, congenital biochemical defects, and a host of other conditions and diseases. This approach can significantly enhance capabilities for determining the circumstances of death. Potential users include law enforcement organizations (police, FBI, CIA), medical examiners, hospitals/emergency rooms, and medical laboratories. Many of the image analysis algorithms already in place for hyperspectral remote sensing and crime scene investigations can be applied to the interpretation of data obtained in this program.

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

DTIC Science & Technology

2002-09-01

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

Data management and digital delivery of analog data

USGS Publications Warehouse

Miller, W.A.; Longhenry, Ryan; Smith, T.

2008-01-01

The U.S. Geological Survey's (USGS) data archive at the Earth Resources Observation and Science (EROS) Center is a comprehensive and impartial record of the Earth's changing land surface. USGS/EROS has been archiving and preserving land remote sensing data for over 35 years. This remote sensing archive continues to grow as aircraft and satellites acquire more imagery. As a world leader in preserving data, USGS/EROS has a reputation as a technological innovator in solving challenges and ensuring that access to these collections is available. Other agencies also call on the USGS to consider their collections for long-term archive support. To improve access to the USGS film archive, each frame on every roll of film is being digitized by automated high performance digital camera systems. The system robotically captures a digital image from each film frame for the creation of browse and medium resolution image files. Single frame metadata records are also created to improve access that otherwise involves interpreting flight indexes. USGS/EROS is responsible for over 8.6 million frames of aerial photographs and 27.7 million satellite images.

Fusion of shallow and deep features for classification of high-resolution remote sensing images

NASA Astrophysics Data System (ADS)

Gao, Lang; Tian, Tian; Sun, Xiao; Li, Hang

2018-02-01

Effective spectral and spatial pixel description plays a significant role for the classification of high resolution remote sensing images. Current approaches of pixel-based feature extraction are of two main kinds: one includes the widelyused principal component analysis (PCA) and gray level co-occurrence matrix (GLCM) as the representative of the shallow spectral and shape features, and the other refers to the deep learning-based methods which employ deep neural networks and have made great promotion on classification accuracy. However, the former traditional features are insufficient to depict complex distribution of high resolution images, while the deep features demand plenty of samples to train the network otherwise over fitting easily occurs if only limited samples are involved in the training. In view of the above, we propose a GLCM-based convolution neural network (CNN) approach to extract features and implement classification for high resolution remote sensing images. The employment of GLCM is able to represent the original images and eliminate redundant information and undesired noises. Meanwhile, taking shallow features as the input of deep network will contribute to a better guidance and interpretability. In consideration of the amount of samples, some strategies such as L2 regularization and dropout methods are used to prevent over-fitting. The fine-tuning strategy is also used in our study to reduce training time and further enhance the generalization performance of the network. Experiments with popular data sets such as PaviaU data validate that our proposed method leads to a performance improvement compared to individual involved approaches.

Application of LANDSAT data to the study of urban development in Brasilia

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Deoliveira, M. D. L. N.; Foresti, C.; Niero, M.; Parreira, E. M. D. M. F.

1984-01-01

The urban growth of Brasilia within the last ten years is analyzed with special emphasis on the utilization of remote sensing orbital data and automatic image processing. The urban spatial structure and the monitoring of its temporal changes were examined in a whole and dynamic way by the utilization of MSS-LANDSAT images for June (1973, 1978 and 1983). In order to aid data interpretation, a registration algorithm implemented in the Interactive Multispectral Image Analysis System (IMAGE-100) was utilized aiming at the overlap of multitemporal images. The utilization of suitable digital filters, combined with the images overlap, allowed a rapid identification of areas of possible urban growth and oriented the field work. The results obtained in this work permitted an evaluation of the urban growth of Brasilia, taking as reference the proposal stated for the construction of the city in the Pilot Plan elaborated by Lucio Costa.

High resolution remote sensing information identification for characterizing uranium mineralization setting in Namibia

NASA Astrophysics Data System (ADS)

Zhang, Jie-Lin; Wang, Jun-hu; Zhou, Mi; Huang, Yan-ju; Xuan, Yan-xiu; Wu, Ding

2011-11-01

The modern Earth Observation System (EOS) technology takes important role in the uranium geological exploration, and high resolution remote sensing as one of key parts of EOS is vital to characterize spectral and spatial information of uranium mineralization factors. Utilizing satellite high spatial resolution and hyperspectral remote sensing data (QuickBird, Radarsat2, ASTER), field spectral measurement (ASD data) and geological survey, this paper established the spectral identification characteristics of uranium mineralization factors including six different types of alaskite, lower and upper marble of Rössing formation, dolerite, alkali metasomatism, hematization and chloritization in the central zone of Damara Orogen, Namibia. Moreover, adopted the texture information identification technology, the geographical distribution zones of ore-controlling faults and boundaries between the different strata were delineated. Based on above approaches, the remote sensing geological anomaly information and image interpretation signs of uranium mineralization factors were extracted, the metallogenic conditions were evaluated, and the prospective areas have been predicted.

A laboratory verification sensor

NASA Technical Reports Server (NTRS)

Vaughan, Arthur H.

1988-01-01

The use of a variant of the Hartmann test is described to sense the coalignment of the 36 primary mirror segments of the Keck 10-meter Telescope. The Shack-Hartmann alignment camera is a surface-tilt-error-sensing device, operable with high sensitivity over a wide range of tilt errors. An interferometer, on the other hand, is a surface-height-error-sensing device. In general, if the surface height error exceeds a few wavelengths of the incident illumination, an interferogram is difficult to interpret and loses utility. The Shack-Hartmann aligment camera is, therefore, likely to be attractive as a development tool for segmented mirror telescopes, particularly at early stages of development in which the surface quality of developmental segments may be too poor to justify interferometric testing. The constraints are examined which would define the first-order properties of a Shack-Hartmann alignment camera and the precision and range of measurement one could expect to achieve with it are investigated. Fundamental constraints do arise, however, from consideration of geometrical imaging, diffraction, and the density of sampling of images at the detector array. Geometrical imagining determines the linear size of the image, and depends on the primary mirror diameter and the f-number of a lenslet. Diffraction is another constraint; it depends on the lenslet aperture. Finally, the sampling density at the detector array is important since the number of pixels in the image determines how accurately the centroid of the image can be measured. When these factors are considered under realistic assumptions it is apparent that the first order design of a Shack-Hartmann alignment camera is completely determined by the first-order constraints considered, and that in the case of a 20-meter telescope with seeing-limited imaging, such a camera, used with a suitable detector array, will achieve useful precision.

Application of remote sensing data to structural analysis of the East Kalimantan, Indonesia

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

Moriya, Shunji; Nishidai, Takashi

1996-07-01

JERS-1 SAR and LANDSAT TM images of the northern Kutei Basin, East Kalimantan, Indonesia were geologically interpreted. The focus of the study is on the structural analysis of the Samarinda Anticlinorium located in the onshore area of the Kutei Basin. In the Samarinda Anticlinorium, N-S folds and thrusts are well developed in the Tertiary sediments. They are believed to have been formed during the Middle Miocene or later. In addition to the N-S structure, an extensive NW-SE lineament traversing the central part of the study area can be identified on the images. Image interpretation reveals that this lineament is amore » major fault formed before the Oligocene. Noticeable differences in the N-S structure are recognized at the north and south of this NW-SE fault, Lithology and thickness of the sediments overlying the basement are remarkably different at the north and south of the fault. These may be responsible for the differences in the N-S structure of the northern and southern Anticlinorium.« less

Dynamic calibration and analysis of crack tip propagation in energetic materials using real-time radiography

NASA Astrophysics Data System (ADS)

Butt, Ali

Crack propagation in a solid rocket motor environment is difficult to measure directly. This experimental and analytical study evaluated the viability of real-time radiography for detecting bore regression and propellant crack propagation speed. The scope included the quantitative interpretation of crack tip velocity from simulated radiographic images of a burning, center-perforated grain and actual real-time radiographs taken on a rapid-prototyped model that dynamically produced the surface movements modeled in the simulation. The simplified motor simulation portrayed a bore crack that propagated radially at a speed that was 10 times the burning rate of the bore. Comparing the experimental image interpretation with the calibrated surface inputs, measurement accuracies were quantified. The average measurements of the bore radius were within 3% of the calibrated values with a maximum error of 7%. The crack tip speed could be characterized with image processing algorithms, but not with the dynamic calibration data. The laboratory data revealed that noise in the transmitted X-Ray intensity makes sensing the crack tip propagation using changes in the centerline transmitted intensity level impractical using the algorithms employed.

Use of remote sensing technology for inventorying and planning utilization of land resources in South Dakota

NASA Technical Reports Server (NTRS)

1974-01-01

A comprehensive land use planning process model is being developed in Meade County, South Dakota, using remote sensing technology. The proper role of remote sensing in the land use planning process is being determined by interaction of remote sensing specialists with local land use planners. The data that were collected by remote sensing techniques are as follows: (1) level I land use data interpreted at a scale of 1:250,000 from false color enlargement prints of ERTS-1 color composite transparencies; (2) detailed land use data interpreted at a scale of 1:24,000 from enlargement color prints of high altitude RB-57 photography; and (3) general soils map interpreted at a scale of 1:250,000 from false color enlargement prints of ERTS-1 color composite transparencies. In addition to use of imagery as an interpretation aid, the utility of using photographs as base maps was demonstrated.

Preliminary investigation of Large Format Camera photography utility in soil mapping and related agricultural applications

NASA Technical Reports Server (NTRS)

Pelletier, R. E.; Hudnall, W. H.

1987-01-01

The use of Space Shuttle Large Format Camera (LFC) color, IR/color, and B&W images in large-scale soil mapping is discussed and illustrated with sample photographs from STS 41-6 (October 1984). Consideration is given to the characteristics of the film types used; the photographic scales available; geometric and stereoscopic factors; and image interpretation and classification for soil-type mapping (detecting both sharp and gradual boundaries), soil parent material topographic and hydrologic assessment, natural-resources inventory, crop-type identification, and stress analysis. It is suggested that LFC photography can play an important role, filling the gap between aerial and satellite remote sensing.

Multiscale morphological filtering for analysis of noisy and complex images

NASA Astrophysics Data System (ADS)

Kher, A.; Mitra, S.

Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in extracting information from a wide variety of images obtained with active and passive sensing techniques is discussed. Such techniques are particularly useful in obtaining more information from fusion of complex images by different sensors such as SAR, visible, and infrared.

Multiscale Morphological Filtering for Analysis of Noisy and Complex Images

NASA Technical Reports Server (NTRS)

Kher, A.; Mitra, S.

1993-01-01

Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in extracting information from a wide variety of images obtained with active and passive sensing techniques is discussed. Such techniques are particularly useful in obtaining more information from fusion of complex images by different sensors such as SAR, visible, and infrared.

Intelligent services for discovery of complex geospatial features from remote sensing imagery

NASA Astrophysics Data System (ADS)

Yue, Peng; Di, Liping; Wei, Yaxing; Han, Weiguo

2013-09-01

Remote sensing imagery has been commonly used by intelligence analysts to discover geospatial features, including complex ones. The overwhelming volume of routine image acquisition requires automated methods or systems for feature discovery instead of manual image interpretation. The methods of extraction of elementary ground features such as buildings and roads from remote sensing imagery have been studied extensively. The discovery of complex geospatial features, however, is still rather understudied. A complex feature, such as a Weapon of Mass Destruction (WMD) proliferation facility, is spatially composed of elementary features (e.g., buildings for hosting fuel concentration machines, cooling towers, transportation roads, and fences). Such spatial semantics, together with thematic semantics of feature types, can be used to discover complex geospatial features. This paper proposes a workflow-based approach for discovery of complex geospatial features that uses geospatial semantics and services. The elementary features extracted from imagery are archived in distributed Web Feature Services (WFSs) and discoverable from a catalogue service. Using spatial semantics among elementary features and thematic semantics among feature types, workflow-based service chains can be constructed to locate semantically-related complex features in imagery. The workflows are reusable and can provide on-demand discovery of complex features in a distributed environment.

Structural Investigations of Afghanistan Deduced from Remote Sensing and Potential Field Data

NASA Astrophysics Data System (ADS)

Saibi, Hakim; Azizi, Masood; Mogren, Saad

2016-08-01

This study integrates potential gravity and magnetic field data with remotely sensed images and geological data in an effort to understand the subsurface major geological structures in Afghanistan. Integrated analysis of Landsat SRTM data was applied for extraction of geological lineaments. The potential field data were analyzed using gradient interpretation techniques, such as analytic signal (AS), tilt derivative (TDR), horizontal gradient of the tilt derivative (HG-TDR), Euler Deconvolution (ED) and power spectrum methods, and results were correlated with known geological structures. The analysis of remote sensing data and potential field data reveals the regional geological structural characteristics of Afghanistan. The power spectrum analysis of magnetic and gravity data suggests shallow basement rocks at around 1 to 1.5 km depth. The results of TDR of potential field data are in agreement with the location of the major regional fault structures and also the location of the basins and swells, except in the Helmand region (SW Afghanistan) where many high potential field anomalies are observed and attributed to batholiths and near-surface volcanic rocks intrusions. A high-resolution airborne geophysical survey in the data sparse region of eastern Afghanistan is recommended in order to have a complete image of the potential field anomalies.

Thermal anomaly before earthquake and damage assessment using remote sensing data for 2014 Yutian earthquake

NASA Astrophysics Data System (ADS)

Zhang, Yanmei; Huang, Haiying; Jiang, Zaisen; Fang, Ying; Cheng, Xiao

2014-12-01

Thermal anomaly appears to be a significant precursor of some strong earthquakes. In this study, time series of MODIS Land Surface Temperature (LST) products from 2001 to 2014 are processed and analyzed to locate possible anomalies prior to the Yutian earthquake (12 February 2014, Xinjiang, CHINA). In order to reduce the seasonal or annual effects from the LST variations, also to avoid the rainy and cloudy weather in this area, a background mean of ten-day nighttime LST are derived using averaged MOD11A2 products from 2001 to 2012. Then the ten-day LST data from Jan 2014 to FebJanuary 2014 were differenced using the above background. Abnormal LST increase before the earthquake is quite obvious from the differential images, indicating that this method is useful in such area with high mountains and wide-area deserts. Also, in order to assess the damage to infrastructure, China's latest civilian high-resolution remote sensing satellite - GF-1 remote sensed data are applied to the affected counties in this area. The damaged infrastructures and ground surface could be easily interpreted in the fused pan-chromatic and multi-spectral images integrating both texture and spectral information.

Seasonality of a boreal forest: a remote sensing perspective

NASA Astrophysics Data System (ADS)

Rautiainen, Miina; Heiskanen, Janne; Lukes, Petr; Majasalmi, Titta; Mottus, Matti; Pisek, Jan

2016-04-01

Understanding the seasonal dynamics of boreal ecosystems through interpretation of satellite reflectance data is needed for efficient large-scale monitoring of northern vegetation dynamics and productivity trends. Satellite remote sensing enables continuous global monitoring of vegetation status and is not limited to single-date phenological metrics. Using remote sensing also enables gaining a wider perspective to the seasonality of vegetation dynamics. The seasonal reflectance cycles of boreal forests observed in optical satellite images are explained by changes in biochemical properties and geometrical structure of vegetation as well as seasonal variation in solar illumination. This poster provides a synthesis of a research project (2010-2015) dedicated to monitoring the seasonal cycle of boreal forests. It is based on satellite and field data collected from the Hyytiälä Forestry Field Station in Finland. The results highlight the role understory vegetation has in forming the forest reflectance measured by satellite instruments.

Other remote sensing systems: Retrospect and outlook

NASA Technical Reports Server (NTRS)

1982-01-01

The history of remote sensing is reviewed and the scope and versatility of the several remote sensing systems already in orbit are discussed, especially those with sensors operating in other EM spectral modes. The multisensor approach is examined by interrelating LANDSAT observations with data from other satellite systems. The basic principles and practices underlying the use of thermal infrared and radar sensors are explored and the types of observations and interpretations emanating from the Nimbus, Heat Capacity Mapping Mission, and SEASAT programs are examined. Approved or proposed Earth resources oriented missions for the 1980's previewed include LANDSAT D, Stereosat, Gravsat, the French satellite SPOT-1, and multimission modular spacecraft launched from space shuttle. The pushbroom imager, the linear array pushbroom radiometer, the multispectral linear array, and the operational LANDSAT observing system, to be designed the LANDSAT-E series are also envisioned for this decade.

REKRIATE: A Knowledge Representation System for Object Recognition and Scene Interpretation

NASA Astrophysics Data System (ADS)

Meystel, Alexander M.; Bhasin, Sanjay; Chen, X.

1990-02-01

What humans actually observe and how they comprehend this information is complex due to Gestalt processes and interaction of context in predicting the course of thinking and enforcing one idea while repressing another. How we extract the knowledge from the scene, what we get from the scene indeed and what we bring from our mechanisms of perception are areas separated by a thin, ill-defined line. The purpose of this paper is to present a system for Representing Knowledge and Recognizing and Interpreting Attention Trailed Entities dubbed as REKRIATE. It will be used as a tool for discovering the underlying principles involved in knowledge representation required for conceptual learning. REKRIATE has some inherited knowledge and is given a vocabulary which is used to form rules for identification of the object. It has various modalities of sensing and has the ability to measure the distance between the objects in the image as well as the similarity between different images of presumably the same object. All sensations received from matrix of different sensors put into an adequate form. The methodology proposed is applicable to not only the pictorial or visual world representation, but to any sensing modality. It is based upon the two premises: a) inseparability of all domains of the world representation including linguistic, as well as those formed by various sensor modalities. and b) representativity of the object at several levels of resolution simultaneously.

The application of the unmanned aerial vehicle remote sensing technology in the FAST project construction

NASA Astrophysics Data System (ADS)

Zhu, Boqin

2015-08-01

The purpose of using unmanned aerial vehicle (UAV) remote sensing application in Five-hundred-meter aperture spherical telescope (FAST) project is to dynamically record the construction process with high resolution image, monitor the environmental impact, and provide services for local environmental protection and the reserve immigrants. This paper introduces the use of UAV remote sensing system and the course design and implementation for the FAST site. Through the analysis of the time series data, we found that: (1) since the year 2012, the project has been widely carried out; (2) till 2013, the internal project begun to take shape;(3) engineering excavation scope was kept stable in 2014, and the initial scale of the FAST engineering construction has emerged as in the meantime, the vegetation recovery went well on the bare soil area; (4) in 2015, none environmental problems caused by engineering construction and other engineering geological disaster were found in the work area through the image interpretation of UAV images. This paper also suggested that the UAV technology need some improvements to fulfill the requirements of surveying and mapping specification., including a new data acquisition and processing measures assigned with the background of highly diverse elevation, usage of telephoto camera, hierarchical photography with different flying height, and adjustment with terrain using the joint empty three settlement method.

What we see when we digitize pain: The risk of valorizing image-based representations of fibromyalgia over body and bodily experience

PubMed Central

Manivannan, Vyshali

2017-01-01

Fibromyalgia is chronic pain of unknown etiology, attended by fatigue and affective dysfunction. Unapparent to the unpracticed eye or diagnostic image, it is denied the status of “real” suffering given to visually confirmable disorders. It is my customary mode of existence: a contingent landscape of swinging bridges that may or may not give way, everything a potential threat or deprivation. I don’t express it within the framework of acute pain, but I am evaluated by traditional biomedical standards anyway. Ultimately, the diagnostic image of pain, and the medical and academic discourse used to interpret it, determines my functionality. Such a stance dismisses bodily senses and alternate ways of knowing in pursuit of the ocularcentric objectivity promised by digital health technologies, whose vision remains chained to the interpretive, discursive strategies of human operators and interpreters. A new poetics of pain is critical not only for rewriting the dominant metaphors that construct and delimit our imaginings of pain but also for rewiring the use and reading of digital technologies, wherein the digital image becomes the new site of the hermeneutic exercise, even when the suffering body lies in plain view. This facilitates a failure to listen and touch in patient care, and the imposition of a narrative based on visual evidence, translated into sanitized language, at the cost of intercorporeality. If pain strips sufferers of a voice, my body and its affects should be allowed to speak. PMID:29942598

Delineation of fault zones using imaging radar

NASA Technical Reports Server (NTRS)

Toksoz, M. N.; Gulen, L.; Prange, M.; Matarese, J.; Pettengill, G. H.; Ford, P. G.

1986-01-01

The assessment of earthquake hazards and mineral and oil potential of a given region requires a detailed knowledge of geological structure, including the configuration of faults. Delineation of faults is traditionally based on three types of data: (1) seismicity data, which shows the location and magnitude of earthquake activity; (2) field mapping, which in remote areas is typically incomplete and of insufficient accuracy; and (3) remote sensing, including LANDSAT images and high altitude photography. Recently, high resolution radar images of tectonically active regions have been obtained by SEASAT and Shuttle Imaging Radar (SIR-A and SIR-B) systems. These radar images are sensitive to terrain slope variations and emphasize the topographic signatures of fault zones. Techniques were developed for using the radar data in conjunction with the traditional types of data to delineate major faults in well-known test sites, and to extend interpretation techniques to remote areas.

Object localization in handheld thermal images for fireground understanding

NASA Astrophysics Data System (ADS)

Vandecasteele, Florian; Merci, Bart; Jalalvand, Azarakhsh; Verstockt, Steven

2017-05-01

Despite the broad application of the handheld thermal imaging cameras in firefighting, its usage is mostly limited to subjective interpretation by the person carrying the device. As remedies to overcome this limitation, object localization and classification mechanisms could assist the fireground understanding and help with the automated localization, characterization and spatio-temporal (spreading) analysis of the fire. An automated understanding of thermal images can enrich the conventional knowledge-based firefighting techniques by providing the information from the data and sensing-driven approaches. In this work, transfer learning is applied on multi-labeling convolutional neural network architectures for object localization and recognition in monocular visual, infrared and multispectral dynamic images. Furthermore, the possibility of analyzing fire scene images is studied and their current limitations are discussed. Finally, the understanding of the room configuration (i.e., objects location) for indoor localization in reduced visibility environments and the linking with Building Information Models (BIM) are investigated.

Remote Sensing as a First Step in Geothermal Exploration in the Xilingol Volcanic Field in NE China

NASA Astrophysics Data System (ADS)

Peng, F.; Huang, S.; Xiong, Y.

2013-12-01

Geothermal energy is a renewable and low-carbon energy source independent of climate change. It is most abundant in Cenozoic volcanic areas where high temperature can be obtained within a relatively shallow depth. Geological structures play an important role in the transfer and storage of geothermal energy. Like other geological resources, geothermal resource prospecting and exploration require a good understanding of the host media. Remote sensing (RS) has the advantages of high spatial and temporal resolution and broad spatial coverage over the conventional geological and geophysical prospecting techniques, while geographical information system (GIS) has intuitive, flexible, and convenient characteristics. In this study, RS and GIS techniques are utilized to prospect the geothermal energy potential in Xilingol, a Cenozoic volcanic area in the eastern Inner Mongolia, NE China. Landsat TM/ETM+ multi-temporal images taken under clear-sky conditions, digital elevation model (DEM) data, and other auxiliary data including geological maps of 1:2,500,000 and 1:200,000 scales are used in this study. The land surface temperature (LST) of the study area is retrieved from the Landsat images with a single-channel algorithm. Prior to the LST retrieval, the imagery data are preprocessed to eliminate abnormal values by reference to the normalized difference vegetation index (NDVI) and the improved normalized water index (MNDWI) on the ENVI platform developed by ITT Visual Information Solutions. Linear and circular geological structures are then inferred through visual interpretation of the LST maps with references to the existing geological maps in conjunction with the computer automatic interpretation features such as lineament frequency, lineament density, and lineament intersection. Several useful techniques such as principal component analysis (PCA), image classification, vegetation suppression, multi-temporal comparative analysis, and 3D Surface View based on DEM data are used to further enable a better visual geologic interpretation with the Landsat imagery of Xilingol. Several major volcanism controlling faults and Cenozoic volcanic eruption centers have been recognized from the linear and circular structures in the remote sensing images. The result shows that the major faults in the study area are mainly NEE oriented. Hidden faults and deep structures are inferred from the analysis of distribution regularities of linear and circular structures. Especially, the swarms of craters northwest to the Dalinuoer Lake appear to be controlled by some NEE trending hidden basement fractures. The intersecting areas of the NEE linear structures with NW trending structures overlapped by the circular structures are the favorable regions for geothermal resources. Seven areas have been preliminarily identified as the targets for further prospecting geothermal energy based on the visual interpretation of the geological structures. The study shows that RS and GIS have great application potential in the geothermal exploration in volcanic areas and will promote the exploration of renewable energy resources of great potential.

Making the invisible body visible. Bone scans, osteoporosis and women's bodily experiences.

PubMed

Reventlow, Susanne Dalsgaard; Hvas, Lotte; Malterud, Kirsti

2006-06-01

The imaging technology of bone scans allows visualization of the bone structure, and determination of a numerical value. Both these are subjected to professional interpretation according to medical (epidemiological) evidence to estimate the individual's risk of fractures. But when bodily experience is challenged by a visual diagnosis, what effect does this have on an individual? The aim of this study was to explore women's bodily experiences after a bone scan and to analyse how the scan affects women's self-awareness, sense of bodily identity and integrity. We interviewed 16 Danish women (aged 61-63) who had had a bone scan for osteoporosis. The analysis was based on Merleau-Ponty's perspective of perception as an embodied experience in which bodily experience is understood to be the existential ground of culture and self. Women appeared to take the scan literally and planned their lives accordingly. They appeared to believe that the 'pictures' revealed some truth in themselves. The information supplied by the scan fostered a new body image. The women interpreted the scan result (a mark on a curve) to mean bodily fragility which they incorporated into their bodily perception. The embodiment of this new body image produced new symptom interpretations and preventive actions, including caution. The result of the bone scan and its cultural interpretation triggered a reconstruction of the body self as weak with reduced capacity. Women's interpretation of the bone scan reorganized their lived space and time, and their relations with others and themselves. Technological information about osteoporosis appeared to leave most affected women more uncertain and restricted rather than empowered. The findings raise some fundamental questions concerning the use of medical technology for the prevention of asymptomatic disorders.

Interpretation of digital chest radiographs: comparison of light emitting diode versus cold cathode fluorescent lamp backlit monitors.

PubMed

Lim, Hyun-ju; Chung, Myung Jin; Lee, Geewon; Yie, Miyeon; Shin, Kyung Eun; Moon, Jung Won; Lee, Kyung Soo

2013-01-01

To compare the diagnostic performance of light emitting diode (LED) backlight monitors and cold cathode fluorescent lamp (CCFL) monitors for the interpretation of digital chest radiographs. We selected 130 chest radiographs from health screening patients. The soft copy image data were randomly sorted and displayed on a 3.5 M LED (2560 × 1440 pixels) monitor and a 3 M CCFL (2048 × 1536 pixels) monitor. Eight radiologists rated their confidence in detecting nodules and abnormal interstitial lung markings (ILD). Low dose chest CT images were used as a reference standard. The performance of the monitor systems was assessed by analyzing 2080 observations and comparing them by multi-reader, multi-case receiver operating characteristic analysis. The observers reported visual fatigue and a sense of heat. Radiant heat and brightness of the monitors were measured. Measured brightness was 291 cd/m(2) for the LED and 354 cd/m(2) for the CCFL monitor. Area under curves for nodule detection were 0.721 ± 0.072 and 0.764 ± 0.098 for LED and CCFL (p = 0.173), whereas those for ILD were 0.871 ± 0.073 and 0.844 ± 0.068 (p = 0.145), respectively. There were no significant differences in interpretation time (p = 0.446) or fatigue score (p = 0.102) between the two monitors. Sense of heat was lower for the LED monitor (p = 0.024). The temperature elevation was 6.7℃ for LED and 12.4℃ for the CCFL monitor. Although the LED monitor had lower maximum brightness compared with the CCFL monitor, soft copy reading of the digital chest radiographs on LED and CCFL showed no difference in terms of diagnostic performance. In addition, LED emitted less heat.

Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Fuell, Kevin; Knaff, John; Lee, Thomas

2012-01-01

What is an RGB Composite Image? (1) Current and future satellite instruments provide remote sensing at a variety of wavelengths. (2) RGB composite imagery assign individual wavelengths or channel differences to the intensities of the red, green, and blue components of a pixel color. (3) Each red, green, and blue color intensity is related to physical properties within the final composite image. (4) Final color assignments are therefore related to the characteristics of image pixels. (5) Products may simplify the interpretation of data from multiple bands by displaying information in a single image. Current Products and Usage: Collaborations between SPoRT, CIRA, and NRL have facilitated the use and evaluation of RGB products at a variety of NWS forecast offices and National Centers. These products are listed in table.

Less is More: Bigger Data from Compressive Measurements

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

Stevens, Andrew; Browning, Nigel D.

Compressive sensing approaches are beginning to take hold in (scanning) transmission electron microscopy (S/TEM) [1,2,3]. Compressive sensing is a mathematical theory about acquiring signals in a compressed form (measurements) and the probability of recovering the original signal by solving an inverse problem [4]. The inverse problem is underdetermined (more unknowns than measurements), so it is not obvious that recovery is possible. Compression is achieved by taking inner products of the signal with measurement weight vectors. Both Gaussian random weights and Bernoulli (0,1) random weights form a large class of measurement vectors for which recovery is possible. The measurements can alsomore » be designed through an optimization process. The key insight for electron microscopists is that compressive sensing can be used to increase acquisition speed and reduce dose. Building on work initially developed for optical cameras, this new paradigm will allow electron microscopists to solve more problems in the engineering and life sciences. We will be collecting orders of magnitude more data than previously possible. The reason that we will have more data is because we will have increased temporal/spatial/spectral sampling rates, and we will be able ability to interrogate larger classes of samples that were previously too beam sensitive to survive the experiment. For example consider an in-situ experiment that takes 1 minute. With traditional sensing, we might collect 5 images per second for a total of 300 images. With compressive sensing, each of those 300 images can be expanded into 10 more images, making the collection rate 50 images per second, and the decompressed data a total of 3000 images [3]. But, what are the implications, in terms of data, for this new methodology? Acquisition of compressed data will require downstream reconstruction to be useful. The reconstructed data will be much larger than traditional data, we will need space to store the reconstructions during analysis, and the computational demands for analysis will be higher. Moreover, there will be time costs associated with reconstruction. Deep learning [5] is an approach to address these problems. Deep learning is a hierarchical approach to find useful (for a particular task) representations of data. Each layer of the hierarchy is intended to represent higher levels of abstraction. For example, a deep model of faces might have sinusoids, edges and gradients in the first layer; eyes, noses, and mouths in the second layer, and faces in the third layer. There has been significant effort recently in deep learning algorithms for tasks beyond image classification such as compressive reconstruction [6] and image segmentation [7]. A drawback of deep learning, however, is that training the model requires large datasets and dedicated computational resources (to reduce training time to a few days). A second issue is that deep learning is not user-friendly and the meaning behind the results is usually not interpretable. We have shown it is possible to reduce the data set size while maintaining model quality [8] and developed interpretable models for image classification [9], but the demands are still significant. The key to addressing these problems is to NOT reconstruct the data. Instead, we should design computational sensors that give answers to specific problems. A simple version of this idea is compressive classification [10], where the goal is to classify signal type from a small number of compressed measurements. Classification is a much simpler problem than reconstruction, so 1) much fewer measurements will be necessary, and 2) these measurements will probably not be useful for reconstruction. Other simple examples of computational sensing include determining object volume or the number of objects present in the field of view [11].« less

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

Borot de Battisti, Maxence, E-mail: M.E.P.Borot@um

Purpose: The development of MR-guided high dose rate (HDR) brachytherapy is under investigation due to the excellent tumor and organs at risk visualization of MRI. However, MR-based localization of needles (including catheters or tubes) has inherently a low update rate and the required image interpretation can be hampered by signal voids arising from blood vessels or calcifications limiting the precision of the needle guidance and reconstruction. In this paper, a new needle tracking prototype is investigated using fiber Bragg gratings (FBG)-based sensing: this prototype involves a MR-compatible stylet composed of three optic fibers with nine sets of embedded FBG sensorsmore » each. This stylet can be inserted into brachytherapy needles and allows a fast measurement of the needle deflection. This study aims to assess the potential of FBG-based sensing for real-time needle (including catheter or tube) tracking during MR-guided intervention. Methods: First, the MR compatibility of FBG-based sensing and its accuracy was evaluated. Different known needle deflections were measured using FBG-based sensing during simultaneous MR-imaging. Then, a needle tracking procedure using FBG-based sensing was proposed. This procedure involved a MR-based calibration of the FBG-based system performed prior to the interventional procedure. The needle tracking system was assessed in an experiment with a moving phantom during MR imaging. The FBG-based system was quantified by comparing the gold-standard shapes, the shape manually segmented on MRI and the FBG-based measurements. Results: The evaluation of the MR compatibility of FBG-based sensing and its accuracy shows that the needle deflection could be measured with an accuracy of 0.27 mm on average. Besides, the FBG-based measurements were comparable to the uncertainty of MR-based measurements estimated at half the voxel size in the MR image. Finally, the mean(standard deviation) Euclidean distance between MR- and FBG-based needle position measurements was equal to 0.79 mm(0.37 mm). The update rate and latency of the FBG-based needle position measurement were 100 and 300 ms, respectively. Conclusions: The FBG-based needle tracking procedure proposed in this paper is able to determine the position of the complete needle, under MR-imaging, with better accuracy and precision, higher update rate, and lower latency compared to current MR-based needle localization methods. This system would be eligible for MR-guided brachytherapy, in particular, for an improved needle guidance and reconstruction.« less

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.

Characterizing the size and shape of sea ice floes

PubMed Central

Gherardi, Marco; Lagomarsino, Marco Cosentino

2015-01-01

Monitoring drift ice in the Arctic and Antarctic regions directly and by remote sensing is important for the study of climate, but a unified modeling framework is lacking. Hence, interpretation of the data, as well as the decision of what to measure, represent a challenge for different fields of science. To address this point, we analyzed, using statistical physics tools, satellite images of sea ice from four different locations in both the northern and southern hemispheres, and measured the size and the elongation of ice floes (floating pieces of ice). We find that (i) floe size follows a distribution that can be characterized with good approximation by a single length scale , which we discuss in the framework of stochastic fragmentation models, and (ii) the deviation of their shape from circularity is reproduced with remarkable precision by a geometric model of coalescence by freezing, based on random Voronoi tessellations, with a single free parameter expressing the shape disorder. Although the physical interpretations remain open, this advocates the parameters and as two independent indicators of the environment in the polar regions, which are easily accessible by remote sensing. PMID:26014797

Techniques for automatic large scale change analysis of temporal multispectral imagery

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

Change detection in remotely sensed imagery is a multi-faceted problem with a wide variety of desired solutions. Automatic change detection and analysis to assist in the coverage of large areas at high resolution is a popular area of research in the remote sensing community. Beyond basic change detection, the analysis of change is essential to provide results that positively impact an image analyst's job when examining potentially changed areas. Present change detection algorithms are geared toward low resolution imagery, and require analyst input to provide anything more than a simple pixel level map of the magnitude of change that has occurred. One major problem with this approach is that change occurs in such large volume at small spatial scales that a simple change map is no longer useful. This research strives to create an algorithm based on a set of metrics that performs a large area search for change in high resolution multispectral image sequences and utilizes a variety of methods to identify different types of change. Rather than simply mapping the magnitude of any change in the scene, the goal of this research is to create a useful display of the different types of change in the image. The techniques presented in this dissertation are used to interpret large area images and provide useful information to an analyst about small regions that have undergone specific types of change while retaining image context to make further manual interpretation easier. This analyst cueing to reduce information overload in a large area search environment will have an impact in the areas of disaster recovery, search and rescue situations, and land use surveys among others. By utilizing a feature based approach founded on applying existing statistical methods and new and existing topological methods to high resolution temporal multispectral imagery, a novel change detection methodology is produced that can automatically provide useful information about the change occurring in large area and high resolution image sequences. The change detection and analysis algorithm developed could be adapted to many potential image change scenarios to perform automatic large scale analysis of change.

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.

A method based on IHS cylindrical transform model for quality assessment of image fusion

NASA Astrophysics Data System (ADS)

Zhu, Xiaokun; Jia, Yonghong

2005-10-01

Image fusion technique has been widely applied to remote sensing image analysis and processing, and methods for quality assessment of image fusion in remote sensing have also become the research issues at home and abroad. Traditional assessment methods combine calculation of quantitative indexes and visual interpretation to compare fused images quantificationally and qualitatively. However, in the existing assessment methods, there are two defects: on one hand, most imdexes lack the theoretic support to compare different fusion methods. On the hand, there is not a uniform preference for most of the quantitative assessment indexes when they are applied to estimate the fusion effects. That is, the spatial resolution and spectral feature could not be analyzed synchronously by these indexes and there is not a general method to unify the spatial and spectral feature assessment. So in this paper, on the basis of the approximate general model of four traditional fusion methods, including Intensity Hue Saturation(IHS) triangle transform fusion, High Pass Filter(HPF) fusion, Principal Component Analysis(PCA) fusion, Wavelet Transform(WT) fusion, a correlation coefficient assessment method based on IHS cylindrical transform is proposed. By experiments, this method can not only get the evaluation results of spatial and spectral features on the basis of uniform preference, but also can acquire the comparison between fusion image sources and fused images, and acquire differences among fusion methods. Compared with the traditional assessment methods, the new methods is more intuitionistic, and in accord with subjective estimation.

Anisotropic Scattering Shadow Compensation Method for Remote Sensing Image with Consideration of Terrain

NASA Astrophysics Data System (ADS)

Wang, Qiongjie; Yan, Li

2016-06-01

With the rapid development of sensor networks and earth observation technology, a large quantity of high resolution remote sensing data is available. However, the influence of shadow has become increasingly greater due to the higher resolution shows more complex and detailed land cover, especially under the shadow. Shadow areas usually have lower intensity and fuzzy boundary, which make the images hard to interpret automatically. In this paper, a simple and effective shadow (including soft shadow) detection and compensation method is proposed based on normal data, Digital Elevation Model (DEM) and sun position. First, we use high accuracy DEM and sun position to rebuild the geometric relationship between surface and sun at the time the image shoot and get the hard shadow boundary and sky view factor (SVF) of each pixel. Anisotropic scattering assumption is accepted to determine the soft shadow factor mainly affected by diffuse radiation. Finally, an easy radiation transmission model is used to compensate the shadow area. Compared with the spectral detection method, our detection method has strict theoretical basis, reliable compensation result and minor affected by the image quality. The compensation strategy can effectively improve the radiation intensity of shadow area, reduce the information loss brought by shadow and improve the robustness and efficiency of the classification algorithms.

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

An Evaluation of Fractal Surface Measurement Methods for Characterizing Landscape Complexity from Remote-Sensing Imagery

NASA Technical Reports Server (NTRS)

Lam, Nina Siu-Ngan; Qiu, Hong-Lie; Quattrochi, Dale A.; Emerson, Charles W.; Arnold, James E. (Technical Monitor)

2001-01-01

The rapid increase in digital data volumes from new and existing sensors necessitates the need for efficient analytical tools for extracting information. We developed an integrated software package called ICAMS (Image Characterization and Modeling System) to provide specialized spatial analytical functions for interpreting remote sensing data. This paper evaluates the three fractal dimension measurement methods: isarithm, variogram, and triangular prism, along with the spatial autocorrelation measurement methods Moran's I and Geary's C, that have been implemented in ICAMS. A modified triangular prism method was proposed and implemented. Results from analyzing 25 simulated surfaces having known fractal dimensions show that both the isarithm and triangular prism methods can accurately measure a range of fractal surfaces. The triangular prism method is most accurate at estimating the fractal dimension of higher spatial complexity, but it is sensitive to contrast stretching. The variogram method is a comparatively poor estimator for all of the surfaces, particularly those with higher fractal dimensions. Similar to the fractal techniques, the spatial autocorrelation techniques are found to be useful to measure complex images but not images with low dimensionality. These fractal measurement methods can be applied directly to unclassified images and could serve as a tool for change detection and data mining.

Exploring Models and Data for Remote Sensing Image Caption Generation

NASA Astrophysics Data System (ADS)

Lu, Xiaoqiang; Wang, Binqiang; Zheng, Xiangtao; Li, Xuelong

2018-04-01

Inspired by recent development of artificial satellite, remote sensing images have attracted extensive attention. Recently, noticeable progress has been made in scene classification and target detection.However, it is still not clear how to describe the remote sensing image content with accurate and concise sentences. In this paper, we investigate to describe the remote sensing images with accurate and flexible sentences. First, some annotated instructions are presented to better describe the remote sensing images considering the special characteristics of remote sensing images. Second, in order to exhaustively exploit the contents of remote sensing images, a large-scale aerial image data set is constructed for remote sensing image caption. Finally, a comprehensive review is presented on the proposed data set to fully advance the task of remote sensing caption. Extensive experiments on the proposed data set demonstrate that the content of the remote sensing image can be completely described by generating language descriptions. The data set is available at https://github.com/201528014227051/RSICD_optimal

Thermophysical properties of the MER and Beagle II landing site regions on Mars

NASA Astrophysics Data System (ADS)

Jakosky, Bruce M.; Hynek, Brian M.; Pelkey, Shannon M.; Mellon, Michael T.; Martínez-Alonso, Sara; Putzig, Nathaniel E.; Murphy, Nate; Christensen, Philip R.

2006-08-01

We analyzed remote-sensing observations of the Isidis Basin, Gusev Crater, and Meridiani Planum landing sites for Beagle II, MER-A Spirit, and MER-B Opportunity spacecraft, respectively. We emphasized the thermophysical properties using daytime and nighttime radiance measurements from the Mars Global Surveyor (MGS) Thermal Emission Spectrometer and Mars Odyssey Thermal Emission Imaging System (THEMIS) and thermal inertias derived from nighttime data sets. THEMIS visible images, MGS Mars Orbiter Camera (MOC) narrow-angle images, and MGS Mars Orbiter Laser Altimeter (MOLA) data are incorporated as well. Additionally, the remote-sensing data were compared with ground-truth at the MER sites. The Isidis Basin surface layer has been shaped by aeolian processes and erosion by slope winds coming off of the southern highlands and funneling through notches between massifs. In the Gusev region, surface materials of contrasting thermophysical properties have been interpreted as rocks or bedrock, duricrust, and dust deposits; these are consistent with a complex geological history dominated by volcanic and aeolian processes. At Meridiani Planum the many layers having different thermophysical and erosional properties suggest periodic deposition of differing sedimentological facies possibly related to clast size, grain orientation and packing, or mineralogy.

Analysis of Benefits and Pitfalls of Satellite SAR for Coastal Area Monitoring

NASA Astrophysics Data System (ADS)

Nunziata, F.; Buono, A.; Mgliaccio, M.; Li, X.; Wei, Y.

2016-08-01

This study aims at describing the outcomes of the Dragon-3 project no. 10689. The undertaken activities deal with coastal area monitoring and they include sea pollution and coastline extraction. The key remote sensing tool is the Synthetic Aperture Radar (SAR) that provides fine resolution images of the microwave reflectivity of the observed scene. However, the interpretation of SAR images is not at all straightforward and all the above-mentioned coastal area applications cannot be easily addressed using single-polarization SAR. Hence, the main outcome of this project is investigating the capability of multi-polarization SAR measurements to generate added-vale product in the frame of coastal area management.

Image analysis by integration of disparate information

NASA Technical Reports Server (NTRS)

Lemoigne, Jacqueline

1993-01-01

Image analysis often starts with some preliminary segmentation which provides a representation of the scene needed for further interpretation. Segmentation can be performed in several ways, which are categorized as pixel based, edge-based, and region-based. Each of these approaches are affected differently by various factors, and the final result may be improved by integrating several or all of these methods, thus taking advantage of their complementary nature. In this paper, we propose an approach that integrates pixel-based and edge-based results by utilizing an iterative relaxation technique. This approach has been implemented on a massively parallel computer and tested on some remotely sensed imagery from the Landsat-Thematic Mapper (TM) sensor.

An evaluation of acquired data as a tool for management of wildlife habitat in Alaska

NASA Technical Reports Server (NTRS)

Vantries, B. J. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Density sliced and digitized imagery of the Kuskokwin/Yukon Delta were analyzed. Color coded images of the isodensity displays were compared with existing vegetation maps of the ERTS-1 frames for the Yukon/Kuskokwin area. A high degree of positive correlation was found to exist between the ERTS-1 image and the conventionally prepared maps. Hydrologic phenomena were also analyzed. Digitization on South Dakota State Remote Sensing Center's SADE system provide some discrimination among several large lakes in the subject area. However, interpretation must await ground observations and depth measurements. An attempt will be made to classify large water bodies by depth classes.

Assessment of the dynamics of urbanized areas by remote sensing

NASA Astrophysics Data System (ADS)

Yeprintsev, S. A.; Klevtsova, M. A.; Lepeshkina, L. A.; Shekoyan, S. V.; Voronin, A. A.

2018-01-01

This research looks at the results of a study of spatial ecological zoning of urban territories using the NDVI-analysis of actual multi-channel satellite images from Landsat-7 and Landsat-8 in the Voronezh region for the period 2001 to 2016. The results obtained in the course of interpretation of space images and processing of statistical information compiled in the GIS environment “Ecology of cities Voronezh region” on the basis of which carried out a comprehensive ecological zoning of the studied urbanized areas. The obtained data on the spatial classification of urban and suburban areas, the peculiarities of the dynamics of weakly and strongly anthropogenically territories, hydrological features and vegetation.

A possible new approach to understanding mental disorder.

PubMed

Sharples, P J

2012-09-01

The aetiology of mental disorders is not fully understood. This paper presents an analysis of the conceptual control process exploring the tools of conceptual application and the phases and the mechanism of the control process and seeks to show how the illness states of mental disorder naturally come to occur. Living occurs in a world of change. For living to occur some control is required and to exert control, to provide direction for the conceptual process, some interpretation of significance, some definition of need is also required. Such interpretation, monitoring significance in relation to the many aspects of change, forms the base on which living occurs. Change in human terms is intrinsically insecure and interpretation of significance is an interpretation of security, an interpretation of control in living. Conceptual control is a process applied to maintain security, to maintain a secure base for the interpretation of significance, it is a process applied to produce and hold a sense of control. Powering a process, producing and holding a sense of control, is an active process and so requires some form of energy. Human beings have a sense of that energy, something exhibited in terms such as full of energy, tired, exhausted. As energy is required to power the control process, accompanying the sense of energy is a sense of the ability to provide power, is a sense of the ability to hold and maintain control, is a sense of security. As available energy reduces there is difficulty holding the same sense of control, a person in the same setting comes to feel more insecure. This can result in a person experiencing mental disorder from mild to severe degree. Mild where conceptual process is applied to manage just one or a very few particular needs, severe and more general where the insecurity affects the base of interpretation. In this later case seeking to protect security can lead to mania, mood-incongruent delusions, schizophrenia. Failing ability to protect can lead to generalized anxiety disorder, mood-congruent delusions, different presentations and degrees of depression. Copyright © 2012 Elsevier Ltd. All rights reserved.

Using Google Earth To Interpret The Southern Taiwan Hsiaolin Village Catastrophe

NASA Astrophysics Data System (ADS)

Lin, Y. H.; Huang, C. M.; Keck, J.; Wei, L. W.; Pan, K. L.

2012-04-01

The August, 2009 Typhoon Morakot resulted in accumulated rainfalls exceeding 2000 mm and the triggering of a massive debris flow that buried Hsiaolin village. Hundreds of people were killed and both domestic and international natural disaster prevention agencies took note of this large scale disaster that was not prevented. Interpretation of Google Earth satellite images reveals that the Hsiaolin debris flow originated in a single location and then split into two parts. The northern debris flow, the smaller of the two parts, flowed within a ravine. The southern part of the debris flow, much larger than the northern part, was responsible for the burial of Hsiaolin village. The movement of the debris flow can be divided into three processes. First a slope failure and subsequent debris flow occurred within a curved ravine. Second, the debris flow eroded the bank of the ravine laterally, causing translational failure of the ravine walls. A massive debris flow, made up of a combination of materials from both the original debris flow and the ravine walls, jammed within the ravine. Finally, as a result of the jam, the debris flow was redirected towards Hsiaolin village. Overlaying locations of the post-Hsiaolin debris flow landforms on top of pre-failure satellite images reveals that characteristics of the post failure landforms match perfectly with characteristics observed in the pre-failure satellite images. This finding supports the thought that large scale geologic disasters are reoccurring. This finding also suggests that areas near villages can use simple satellite image analysis to rapidly identify ancient landslides and that such information may help early evacuation planning. With such planning, property and life losses due to natural disasters can be reduced. Key word: Hsiaolin Village, Debris Flow, Remote Sensing, Image Interpretation, Cause of Disaster, Disaster Recovery, Deep-Seated Landslide, Ancient Debris Flow

Multi- and hyperspectral geologic remote sensing: A review

NASA Astrophysics Data System (ADS)

van der Meer, Freek D.; van der Werff, Harald M. A.; van Ruitenbeek, Frank J. A.; Hecker, Chris A.; Bakker, Wim H.; Noomen, Marleen F.; van der Meijde, Mark; Carranza, E. John M.; Smeth, J. Boudewijn de; Woldai, Tsehaie

2012-02-01

Geologists have used remote sensing data since the advent of the technology for regional mapping, structural interpretation and to aid in prospecting for ores and hydrocarbons. This paper provides a review of multispectral and hyperspectral remote sensing data, products and applications in geology. During the early days of Landsat Multispectral scanner and Thematic Mapper, geologists developed band ratio techniques and selective principal component analysis to produce iron oxide and hydroxyl images that could be related to hydrothermal alteration. The advent of the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) with six channels in the shortwave infrared and five channels in the thermal region allowed to produce qualitative surface mineral maps of clay minerals (kaolinite, illite), sulfate minerals (alunite), carbonate minerals (calcite, dolomite), iron oxides (hematite, goethite), and silica (quartz) which allowed to map alteration facies (propylitic, argillic etc.). The step toward quantitative and validated (subpixel) surface mineralogic mapping was made with the advent of high spectral resolution hyperspectral remote sensing. This led to a wealth of techniques to match image pixel spectra to library and field spectra and to unravel mixed pixel spectra to pure endmember spectra to derive subpixel surface compositional information. These products have found their way to the mining industry and are to a lesser extent taken up by the oil and gas sector. The main threat for geologic remote sensing lies in the lack of (satellite) data continuity. There is however a unique opportunity to develop standardized protocols leading to validated and reproducible products from satellite remote sensing for the geology community. By focusing on geologic mapping products such as mineral and lithologic maps, geochemistry, P-T paths, fluid pathways etc. the geologic remote sensing community can bridge the gap with the geosciences community. Increasingly workflows should be multidisciplinary and remote sensing data should be integrated with field observations and subsurface geophysical data to monitor and understand geologic processes.

Improved spatial mapping of rainfall events with spaceborne SAR imagery

NASA Technical Reports Server (NTRS)

Ulaby, F. T.; Brisco, B.; Dobson, C.

1983-01-01

The Seasat satellite acquired the first spaceborne synthetic-aperture radar (SAR) images of the earth's surface, in 1978, at a frequency of 1.275 GHz (L-band) in a like-polarization mode at incidence angles of 23 + or - 3 deg. Although this may not be the optimum system configuration for radar remote sensing of soil moisture, interpretation of two Seasat images of Iowa demonstrates the sensitivity of microwave backscatter to soil moisture content. In both scenes, increased image brightness, which represents more radar backscatter, can be related to previous rainfall activity in the two areas. Comparison of these images with ground-based rainfall observations illustrates the increased spatial coverage of the rainfall event that can be obtained from the satellite SAR data. These data can then be color-enhanced by a digital computer to produce aesthetically pleasing output products for the user community.

Research on assessment and improvement method of remote sensing image reconstruction

NASA Astrophysics Data System (ADS)

Sun, Li; Hua, Nian; Yu, Yanbo; Zhao, Zhanping

2018-01-01

Remote sensing image quality assessment and improvement is an important part of image processing. Generally, the use of compressive sampling theory in remote sensing imaging system can compress images while sampling which can improve efficiency. A method of two-dimensional principal component analysis (2DPCA) is proposed to reconstruct the remote sensing image to improve the quality of the compressed image in this paper, which contain the useful information of image and can restrain the noise. Then, remote sensing image quality influence factors are analyzed, and the evaluation parameters for quantitative evaluation are introduced. On this basis, the quality of the reconstructed images is evaluated and the different factors influence on the reconstruction is analyzed, providing meaningful referential data for enhancing the quality of remote sensing images. The experiment results show that evaluation results fit human visual feature, and the method proposed have good application value in the field of remote sensing image processing.

Object-Based Random Forest Classification of Land Cover from Remotely Sensed Imagery for Industrial and Mining Reclamation

NASA Astrophysics Data System (ADS)

Chen, Y.; Luo, M.; Xu, L.; Zhou, X.; Ren, J.; Zhou, J.

2018-04-01

The RF method based on grid-search parameter optimization could achieve a classification accuracy of 88.16 % in the classification of images with multiple feature variables. This classification accuracy was higher than that of SVM and ANN under the same feature variables. In terms of efficiency, the RF classification method performs better than SVM and ANN, it is more capable of handling multidimensional feature variables. The RF method combined with object-based analysis approach could highlight the classification accuracy further. The multiresolution segmentation approach on the basis of ESP scale parameter optimization was used for obtaining six scales to execute image segmentation, when the segmentation scale was 49, the classification accuracy reached the highest value of 89.58 %. The classification accuracy of object-based RF classification was 1.42 % higher than that of pixel-based classification (88.16 %), and the classification accuracy was further improved. Therefore, the RF classification method combined with object-based analysis approach could achieve relatively high accuracy in the classification and extraction of land use information for industrial and mining reclamation areas. Moreover, the interpretation of remotely sensed imagery using the proposed method could provide technical support and theoretical reference for remotely sensed monitoring land reclamation.

A learning tool for optical and microwave satellite image processing and analysis

NASA Astrophysics Data System (ADS)

Dashondhi, Gaurav K.; Mohanty, Jyotirmoy; Eeti, Laxmi N.; Bhattacharya, Avik; De, Shaunak; Buddhiraju, Krishna M.

2016-04-01

This paper presents a self-learning tool, which contains a number of virtual experiments for processing and analysis of Optical/Infrared and Synthetic Aperture Radar (SAR) images. The tool is named Virtual Satellite Image Processing and Analysis Lab (v-SIPLAB) Experiments that are included in Learning Tool are related to: Optical/Infrared - Image and Edge enhancement, smoothing, PCT, vegetation indices, Mathematical Morphology, Accuracy Assessment, Supervised/Unsupervised classification etc.; Basic SAR - Parameter extraction and range spectrum estimation, Range compression, Doppler centroid estimation, Azimuth reference function generation and compression, Multilooking, image enhancement, texture analysis, edge and detection. etc.; SAR Interferometry - BaseLine Calculation, Extraction of single look SAR images, Registration, Resampling, and Interferogram generation; SAR Polarimetry - Conversion of AirSAR or Radarsat data to S2/C3/T3 matrix, Speckle Filtering, Power/Intensity image generation, Decomposition of S2/C3/T3, Classification of S2/C3/T3 using Wishart Classifier [3]. A professional quality polarimetric SAR software can be found at [8], a part of whose functionality can be found in our system. The learning tool also contains other modules, besides executable software experiments, such as aim, theory, procedure, interpretation, quizzes, link to additional reading material and user feedback. Students can have understanding of Optical and SAR remotely sensed images through discussion of basic principles and supported by structured procedure for running and interpreting the experiments. Quizzes for self-assessment and a provision for online feedback are also being provided to make this Learning tool self-contained. One can download results after performing experiments.

On the use of Multisensor and multitemporal data for monitoring risk degradation and looting in archaeological site

NASA Astrophysics Data System (ADS)

Masini, Nicola; Lasaponara, Rosa

2015-04-01

Illegal excavations represent one of the main risks which affect the archaeological heritage all over the world. They cause a massive loss of artefacts but also, and above all, a loss of the cultural context, which makes the subsequent interpretation of archaeological remains very difficult. Remote sensing offers a suitable chance to quantify and analyse this phenomenon, especially in those countries, from Southern America to Middle East, where the surveillance on site is not much effective and time consuming or non practicable due to military or political restrictions. In this paper we focus on the use of GeoEye and Google Earth imagery to quantitatively assess looting in Ventarron (Lambayeque, Peru) that is one of most important archaeological sites in Southern America. Multitemporal satellite images acquired for the study area have been processed by using both autocorrelation statistics and unsupervised classification to highlight and extract looting patterns. The mapping of areas affected by looting offered the opportunity to investigate such areas not previously systematically documented. Reference Lasaponara R.; Giovanni Leucci; Nicola Masini; Raffaele Persico 2014 ": Investigating archaeological looting using very high resolution satellite images and georadar: the experience in Lambayeque in North Peru JASC13-61R1 Cigna Francesca, Deodato Tapete, Rosa Lasaponara and Nicola Masini, 2013 Amplitude Change Detection with ENVISAT ASAR to Image the Cultural Landscape of the Nasca Region, Peru (pages 117-131). Archeological Prospection Article first published online: 21 MAY 2013 | DOI: 10.1002/arp.1451 Tapete Deodato, Francesca Cigna, Nicola Masini and Rosa Lasaponara 2013. Prospection and Monitoring of the Archaeological Heritage of Nasca, Peru, with ENVISAT ASAR Archeological Prospection (pages 133-147) Article first published online: 21 MAY 2013 | DOI: 10.1002/arp.1449 Lasaponara Rosa 2013: Geospatial analysis from space: Advanced approaches for data processing, information extraction and interpretation. Int. J. Applied Earth Observation and Geoinformation 20 Lasaponara . R &N. Masini "Satellite Remote Sensing: A NewTool for Archaeology" Springer February 2012 (http://www.amazon.com/Satellite-Remote-Sensing-Archaeology-Processing/dp/9048188008) Lasaponara, R., Lanorte, A., 2012. Satellite time-series analysis. Int. J. Remote Sens.33 (15), 4649-4652, http://dx.doi.org/10.1080/01431161.2011.638342.

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.

Research on remote sensing image pixel attribute data acquisition method in AutoCAD

NASA Astrophysics Data System (ADS)

Liu, Xiaoyang; Sun, Guangtong; Liu, Jun; Liu, Hui

2013-07-01

The remote sensing image has been widely used in AutoCAD, but AutoCAD lack of the function of remote sensing image processing. In the paper, ObjectARX was used for the secondary development tool, combined with the Image Engine SDK to realize remote sensing image pixel attribute data acquisition in AutoCAD, which provides critical technical support for AutoCAD environment remote sensing image processing algorithms.

Digital data from shuttle photography: The effects of platform variables

NASA Technical Reports Server (NTRS)

Davis, Bruce E.

1987-01-01

Two major criticisms of using Shuttle hand held photography as an Earth science sensor are that it is nondigital, nonquantitative and that it has inconsistent platform characteristics, e.g., variable look angles, especially as compared to remote sensing satellites such as LANDSAT and SPOT. However, these criticisms are assumptions and have not been systematically investigated. The spectral effects of off-nadir views of hand held photography from the Shuttle and their role in interpretation of lava flow morphology on the island of Hawaii are studied. Digitization of photography at JSC and use of LIPS image analysis software in obtaining data is discussed. Preliminary interpretative results of one flow are given. Most of the time was spent in developing procedures and overcoming equipment problems. Preliminary data are satisfactory for detailed analysis.

Distinguishing major lithologic types in rocks of precambrian age in central Wyoming using multilevel sensing, with a chapter on possible economic significance of iron formation discovered by use of aircraft images in the Granite Mountains of Wyoming

NASA Technical Reports Server (NTRS)

Houston, R. S. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Information obtained by remote sensing from three altitude levels: ERTS-1 (565 miles), U-2 (60,000 feet), and C-130 aircraft (15,000 feet) illustrates the possible application of multilevel sensing in mineral exploration. Distinction can be made between rocks of greenstone belts and rocks of granite-granite gneiss areas by using ERTS-1 imagery in portions of the Precambrian of central Wyoming. Study of low altitude color and color infrared photographs of the mafic terrain revealed the presence of metasedimentary rocks with distinct layers that were interpreted as amphibolite by photogeologic techniques. Some of the amphibolite layers were found to be iron formation when examined in the field. To our knowledge this occurrence of iron formation has not been previously reported in the literature.

The interaction of light with phytoplankton in the marine environment

NASA Technical Reports Server (NTRS)

Carder, Kendall L.; Collins, Donald J.; Perry, Mary Jane; Clark, H. Lawrence; Mesias, Jorge M.

1986-01-01

In many regions of the ocean, the phytoplankton population dominates both the attenuation and scattering of light. In other regions, non-phytoplankton contributions to the absorption and scattering may change the remote sensing reflectance and thus affect the ability to interpret remotely sensed ocean color. Hence, variations in the composition of both the phytoplankton population and of the non-phytoplankton material in the water can affect the optical properties of the sea. The effects of these contributions to the remote sensing reflectance and the submarine light field are modeled using scattering and absorption measurements of phytoplankton cultures obtained at the Friday Harbor Laboratory of the University of Washington. These measurements are used to develop regional chlorophyll algorithms specific to the summer waters of Puget Sound for the Coastal Zone Color Scanner, Thematic Mapper and future Ocean Color Imager, and their accuracies are compared for high chlorophyll waters with little or no Gelbstoff, but with variable detrital and suspended material.

The Application of Chinese High-Spatial Remote Sensing Satellite Image in Land Law Enforcement Information Extraction

NASA Astrophysics Data System (ADS)

Wang, N.; Yang, R.

2018-04-01

Chinese high -resolution (HR) remote sensing satellites have made huge leap in the past decade. Commercial satellite datasets, such as GF-1, GF-2 and ZY-3 images, the panchromatic images (PAN) resolution of them are 2 m, 1 m and 2.1 m and the multispectral images (MS) resolution are 8 m, 4 m, 5.8 m respectively have been emerged in recent years. Chinese HR satellite imagery has been free downloaded for public welfare purposes using. Local government began to employ more professional technician to improve traditional land management technology. This paper focused on analysing the actual requirements of the applications in government land law enforcement in Guangxi Autonomous Region. 66 counties in Guangxi Autonomous Region were selected for illegal land utilization spot extraction with fusion Chinese HR images. The procedure contains: A. Defines illegal land utilization spot type. B. Data collection, GF-1, GF-2, and ZY-3 datasets were acquired in the first half year of 2016 and other auxiliary data were collected in 2015. C. Batch process, HR images were collected for batch preprocessing through ENVI/IDL tool. D. Illegal land utilization spot extraction by visual interpretation. E. Obtaining attribute data with ArcGIS Geoprocessor (GP) model. F. Thematic mapping and surveying. Through analysing 42 counties results, law enforcement officials found 1092 illegal land using spots and 16 suspicious illegal mining spots. The results show that Chinese HR satellite images have great potential for feature information extraction and the processing procedure appears robust.

A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping

PubMed Central

Kzar, Ahmed Asal; Mat Jafri, Mohd Zubir; Mutter, Kussay N.; Syahreza, Saumi

2015-01-01

Decreasing water pollution is a big problem in coastal waters. Coastal health of ecosystems can be affected by high concentrations of suspended sediment. In this work, a Modified Hopfield Neural Network Algorithm (MHNNA) was used with remote sensing imagery to classify the total suspended solids (TSS) concentrations in the waters of coastal Langkawi Island, Malaysia. The adopted remote sensing image is the Advanced Land Observation Satellite (ALOS) image acquired on 18 January 2010. Our modification allows the Hopfield neural network to convert and classify color satellite images. The samples were collected from the study area simultaneously with the acquiring of satellite imagery. The sample locations were determined using a handheld global positioning system (GPS). The TSS concentration measurements were conducted in a lab and used for validation (real data), classification, and accuracy assessments. Mapping was achieved by using the MHNNA to classify the concentrations according to their reflectance values in band 1, band 2, and band 3. The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. The first group was used as source samples for supervisor classification via the MHNNA. The second group was used to test the MHNNA efficiency. After mapping, the locations of the second group in the produced classes were detected. Next, the correlation coefficient (R) and root mean square error (RMSE) were calculated between the two groups, according to their corresponding locations in the classes. The MHNNA exhibited a higher R (0.977) and lower RMSE (2.887). In addition, we test the MHNNA with noise, where it proves its accuracy with noisy images over a range of noise levels. All results have been compared with a minimum distance classifier (Min-Dis). Therefore, TSS mapping of polluted water in the coastal Langkawi Island, Malaysia can be performed using the adopted MHNNA with remote sensing techniques (as based on ALOS images). PMID:26729148

Recent Growth of Aerial Photographic Interpretation/Remote Sensing in Geography in the United States

ERIC Educational Resources Information Center

Estes, John E.; Thaman, Konai

1974-01-01

This paper traces the history and growth of air photo interpretation and remote sensing within the field of geography. Courses offered in these fields, factors influencing growth, research findings, and professional geographic interest are discussed. (JH)

Making Sense of the ECG - Cases for Self-Assessment Houghton Andrew R Gray David Making Sense of the ECG - Cases for Self-Assessment 290pp Hodder Education 9780340946893 034094689X [Formula: see text].

PubMed

2010-10-27

This practical, pocket-book approach to ECG interpretation accompanies the well-known text Making Sense of the ECG, by the same authors. It is also designed to be used alone to test knowledge of ECG interpretation and to make clinical decisions based on presented scenarios.

Making sense of the ECG: cases for self-assessment Making Sense of the ECG: Cases for Self-Assessment Houghton Andrew and Gray David Hodder Education £18.99 290pp 9780340946893 034094689X [Formula: see text].

PubMed

2011-02-10

This practical pocket-book approach to electrocardiogram (ECG) interpretation accompanies Making sense of the eCg by the same authors. it is also designed to be used alone to test knowledge of ECG interpretation and to make clinical decisions based on presented scenarios.

Development and application of a new comprehensive image-based classification scheme for coastal and benthic environments along the southeast Florida continental shelf

NASA Astrophysics Data System (ADS)

Makowski, Christopher

The coastal (terrestrial) and benthic environments along the southeast Florida continental shelf show a unique biophysical succession of marine features from a highly urbanized, developed coastal region in the north (i.e. northern Miami-Dade County) to a protective marine sanctuary in the southeast (i.e. Florida Keys National Marine Sanctuary). However, the establishment of a standard bio-geomorphological classification scheme for this area of coastal and benthic environments is lacking. The purpose of this study was to test the hypothesis and answer the research question of whether new parameters of integrating geomorphological components with dominant biological covers could be developed and applied across multiple remote sensing platforms for an innovative way to identify, interpret, and classify diverse coastal and benthic environments along the southeast Florida continental shelf. An ordered manageable hierarchical classification scheme was developed to incorporate the categories of Physiographic Realm, Morphodynamic Zone, Geoform, Landform, Dominant Surface Sediment, and Dominant Biological Cover. Six different remote sensing platforms (i.e. five multi-spectral satellite image sensors and one high-resolution aerial orthoimagery) were acquired, delineated according to the new classification scheme, and compared to determine optimal formats for classifying the study area. Cognitive digital classification at a nominal scale of 1:6000 proved to be more accurate than autoclassification programs and therefore used to differentiate coastal marine environments based on spectral reflectance characteristics, such as color, tone, saturation, pattern, and texture of the seafloor topology. In addition, attribute tables were created in conjugation with interpretations to quantify and compare the spatial relationships between classificatory units. IKONOS-2 satellite imagery was determined to be the optimal platform for applying the hierarchical classification scheme. However, each remote sensing platform had beneficial properties depending on research goals, logistical restrictions, and financial support. This study concluded that a new hierarchical comprehensive classification scheme for identifying coastal marine environments along the southeast Florida continental shelf could be achieved by integrating geomorphological features with biological coverages. This newly developed scheme, which can be applied across multiple remote sensing platforms with GIS software, establishes an innovative classification protocol to be used in future research studies.

A neuromorphic approach to satellite image understanding

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Perakakis, Manolis

2014-05-01

Remote sensing satellite imagery provides high altitude, top viewing aspects of large geographic regions and as such the depicted features are not always easily recognizable. Nevertheless, geoscientists familiar to remote sensing data, gradually gain experience and enhance their satellite image interpretation skills. The aim of this study is to devise a novel computational neuro-centered classification approach for feature extraction and image understanding. Object recognition through image processing practices is related to a series of known image/feature based attributes including size, shape, association, texture, etc. The objective of the study is to weight these attribute values towards the enhancement of feature recognition. The key cognitive experimentation concern is to define the point when a user recognizes a feature as it varies in terms of the above mentioned attributes and relate it with their corresponding values. Towards this end, we have set up an experimentation methodology that utilizes cognitive data from brain signals (EEG) and eye gaze data (eye tracking) of subjects watching satellite images of varying attributes; this allows the collection of rich real-time data that will be used for designing the image classifier. Since the data are already labeled by users (using an input device) a first step is to compare the performance of various machine-learning algorithms on the collected data. On the long-run, the aim of this work would be to investigate the automatic classification of unlabeled images (unsupervised learning) based purely on image attributes. The outcome of this innovative process is twofold: First, in an abundance of remote sensing image datasets we may define the essential image specifications in order to collect the appropriate data for each application and improve processing and resource efficiency. E.g. for a fault extraction application in a given scale a medium resolution 4-band image, may be more effective than costly, multispectral, very high resolution imagery. Second, we attempt to relate the experienced against the non-experienced user understanding in order to indirectly assess the possible limits of purely computational systems. In other words, obtain the conceptual limits of computation vs human cognition concerning feature recognition from satellite imagery. Preliminary results of this pilot study show relations between collected data and differentiation of the image attributes which indicates that our methodology can lead to important results.

Development of multiple source data processing for structural analysis at a regional scale. [digital remote sensing in geology

NASA Technical Reports Server (NTRS)

Carrere, Veronique

1990-01-01

Various image processing techniques developed for enhancement and extraction of linear features, of interest to the structural geologist, from digital remote sensing, geologic, and gravity data, are presented. These techniques include: (1) automatic detection of linear features and construction of rose diagrams from Landsat MSS data; (2) enhancement of principal structural directions using selective filters on Landsat MSS, Spacelab panchromatic, and HCMM NIR data; (3) directional filtering of Spacelab panchromatic data using Fast Fourier Transform; (4) detection of linear/elongated zones of high thermal gradient from thermal infrared data; and (5) extraction of strong gravimetric gradients from digitized Bouguer anomaly maps. Processing results can be compared to each other through the use of a geocoded database to evaluate the structural importance of each lineament according to its depth: superficial structures in the sedimentary cover, or deeper ones affecting the basement. These image processing techniques were successfully applied to achieve a better understanding of the transition between Provence and the Pyrenees structural blocks, in southeastern France, for an improved structural interpretation of the Mediterranean region.

Utility of high-altitude infrared spectral data in mineral exploration: Application to Northern Patagonia Mountains, Arizona

USGS Publications Warehouse

Berger, B.R.; King, T.V.V.; Morath, L.C.; Phillips, J.D.

2003-01-01

Synoptic views of hydrothermal alteration assemblages are of considerable utility in regional-scale minerals exploration. Recent advances in data acquisition and analysis technologies have greatly enhanced the usefulness of remotely sensed imaging spectroscopy for reliable alteration mineral assemblages mapping. Using NASA's Airborne Visible Infrared Imaging Spectrometer (AVIRIS) sensor, this study mapped large areas of advanced argillic and phyllic-argillic alteration assemblages in the southeastern Santa Rita and northern Patagonia mountains, Arizona. Two concealed porphyry copper deposits have been identified during past exploration, the Red Mountain and Sunnyside deposits, and related published hydrothermal alteration zoning studies allow the comparison of the results obtained from AVIRIS data to the more traditional field mapping approaches. The AVIRIS mapping compares favorably with field-based studies. An analysis of iron-bearing oxide minerals above a concealed supergene chalcocite deposit at Red Mountain also indicates that remotely sensed data can be of value in the interpretation of leached caps above porphyry copper deposits. In conjunction with other types of geophysical data, AVIRIS mineral maps can be used to discriminate different exploration targets within a region.

Error analysis for creating 3D face templates based on cylindrical quad-tree structure

NASA Astrophysics Data System (ADS)

Gutfeter, Weronika

2015-09-01

Development of new biometric algorithms is parallel to advances in technology of sensing devices. Some of the limitations of the current face recognition systems may be eliminated by integrating 3D sensors into these systems. Depth sensing devices can capture a spatial structure of the face in addition to the texture and color. This kind of data is yet usually very voluminous and requires large amount of computer resources for being processed (face scans obtained with typical depth cameras contain more than 150 000 points per face). That is why defining efficient data structures for processing spatial images is crucial for further development of 3D face recognition methods. The concept described in this work fulfills the aforementioned demands. Modification of the quad-tree structure was chosen because it can be easily transformed into less dimensional data structures and maintains spatial relations between data points. We are able to interpret data stored in the tree as a pyramid of features which allow us to analyze face images using coarse-to-fine strategy, often exploited in biometric recognition systems.

DDx: diagnostic assistance for the radiologist using PACS

NASA Astrophysics Data System (ADS)

Haynor, David R.

1993-09-01

A potentially valuable tool in medical imaging is the development, and integration with PACS, of systems which enhance the interpretive accuracy of the user -- his ability, given a set of findings (in the broad sense, including clinical information about the patient as well as characteristics of the lesion being analyzed), to assign the proper disease label, or diagnosis, to them. Such systems, which we call here interpretive tools (IT), contain a variety of types of information about diseases and their radiologic diagnosis. They can contain information about large numbers of diseases, including statistical information (incidence, characteristic anatomical locations, association with age and gender or with other diseases, probabilities of various findings given a disease), textual information (description of diseases, treatment, literature references, lists of other entities that might be confused with the disease of interest, additional diagnostic points that may not be represented, or even representable, within IT), and image-based information (typical and atypical examples for each entity and radiographic finding, examples of normal anatomy). These databases can be used both for teaching purposes and as a tool for improving interpretive accuracy [Swett, 1987]. This paper describes some of the requirements for these databases and then discusses early work on the implementation of DDx, an IT whose domain is neuroradiology.

Integration of Satellite Tracking Data and Satellite Images for Detailed Characteristics of Wildlife Habitats

NASA Astrophysics Data System (ADS)

Dobrynin, D. V.; Rozhnov, V. V.; Saveliev, A. A.; Sukhova, O. V.; Yachmennikova, A. A.

2017-12-01

Methods of analysis of the results got from satellite tracking of large terrestrial mammals differ in the level of their integration with additional geographic data. The reliable fine-scale cartographic basis for assessing specific wildlife habitats can be developed through the interpretation of multispectral remote sensing data and extrapolation of the results to the entire estimated species range. Topographic maps were ordinated according to classified features using self-organizing maps (Kohonen's SOM). The satellite image of the Ussuriiskyi Nature Reserve area was interpreted for the analysis of movement conditions for seven wild Amur tigers ( Panthera tigris altaica) equipped with GPS collars. 225 SOM classes for cartographic visualization are sufficient for the detailed mapping of all natural complexes that were identified as a result of interpretation. During snow-free periods, tigers preferred deciduous and shrub associations at lower elevations, as well as mixed forests in the valleys of streams that are adjacent to sparse forests and shrub watershed in the mountain ranges; during heavy snow periods, the animals preferred the entire range of plant communities in different relief types, except for open sites in meadows and abandoned fields at foothills. The border zones of different biotopes were typically used by the tigers during all seasons. Amur tigers preferred coniferous forests for long-term movements.

Remote sensing of wildland resources: A state-of-the-art review

Treesearch

Robert C. Aldrich

1979-01-01

A review, with literature citations, of current remote sensing technology, applications, and costs for wildland resource management, including collection, interpretation, and processing of data gathered through photographic and nonphotographic techniques for classification and mapping, interpretive information for specific applications, measurement of resource...

Interpretation of the Seattle uplift, Washington, as a passive-roof duplex

USGS Publications Warehouse

Brocher, T.M.; Blakely, R.J.; Wells, R.E.

2004-01-01

We interpret seismic lines and a wide variety of other geological and geophysical data to suggest that the Seattle uplift is a passive-roof duplex. A passive-roof duplex is bounded top and bottom by thrust faults with opposite senses of vergence that form a triangle zone at the leading edge of the advancing thrust sheet. In passive-roof duplexes the roof thrust slips only when the floor thrust ruptures. The Seattle fault is a south-dipping reverse fault forming the leading edge of the Seattle uplift, a 40-km-wide fold-and-thrust belt. The recently discovered, north-dipping Tacoma reverse fault is interpreted as a back thrust on the trailing edge of the belt, making the belt doubly vergent. Floor thrusts in the Seattle and Tacoma fault zones, imaged as discontinuous reflections, are interpreted as blind faults that flatten updip into bedding plane thrusts. Shallow monoclines in both the Seattle and Tacoma basins are interpreted to overlie the leading edges of thrust-bounded wedge tips advancing into the basins. Across the Seattle uplift, seismic lines image several shallow, short-wavelength folds exhibiting Quaternary or late Quaternary growth. From reflector truncation, several north-dipping thrust faults (splay thrusts) are inferred to core these shallow folds and to splay upward from a shallow roof thrust. Some of these shallow splay thrusts ruptured to the surface in the late Holocene. Ages from offset soils in trenches across the fault scarps and from abruptly raised shorelines indicate that the splay, roof, and floor thrusts of the Seattle and Tacoma faults ruptured about 1100 years ago.

Classification of volcanoes of the Kane Patera Quadrangle of Io: Proportions of lava flows and pyroclastic flows

NASA Technical Reports Server (NTRS)

Elston, W. E.

1984-01-01

Voyager 1 images show 14 volcanic centers wholly or partly within the Kane Patera quadrangle of Io, which are divided into four major classes: (1) shield with parallel flows; (2) shield with early radial fan shapd flows; (3) shield with radial fan shaped flows, surfaces of flows textured with longitudinal ridges; and (4) depression surrounded by plateau-forming scarp-bounded, untextured deposits. The interpretation attempted here hinges largely on the ability to distinguish lava flows from pyroclastic flows by remote sensing.

Remote sensing of Myriophyllum spicatum L. in a shallow, eutrophic lake

NASA Technical Reports Server (NTRS)

Gustafson, T. D.; Adams, M. S.

1973-01-01

An aerial 35 mm system was used for the acquisition of vertical color and color infrared imagery of the submergent aquatic macrophytes of Lake Wingra, Wisconsin. A method of photographic interpretation of stem density classes is tested for its ability to make standing crop biomass estimates of Myriophyllum spicatum. The results of film image density analysis are significantly correlated with stem densities and standing crop biomass of Myriophyllum and with the biomass of Oedogonium mats. Photographic methods are contrasted with conventional harvest procedures for efficiency and accuracy.

Envisioning disaster in the 1910 Paris flood.

PubMed

Jackson, Jeffrey H

2011-01-01

This article uncovers the visual narratives embedded within the photography of the 1910 Paris flood. Images offered Parisians multiple ways to understand and construe the significance of the flood and provided interpretive frameworks to decide the meaning of this event. Investigating three interlocking narratives of ruin, beauty, and fraternité, the article shows how photographs of Paris under water allowed residents to make sense of the destruction but also to imagine the city’s reconstruction. The article concludes with a discussion of the role of visual culture in recovering from urban disasters.

Structure of the knowledge base for an expert labeling system

NASA Technical Reports Server (NTRS)

Rajaram, N. S.

1981-01-01

One of the principal objectives of the NASA AgRISTARS program is the inventory of global crop resources using remotely sensed data gathered by Land Satellites (LANDSAT). A central problem in any such crop inventory procedure is the interpretation of LANDSAT images and identification of parts of each image which are covered by a particular crop of interest. This task of labeling is largely a manual one done by trained human analysts and consequently presents obstacles to the development of totally automated crop inventory systems. However, development in knowledge engineering as well as widespread availability of inexpensive hardware and software for artificial intelligence work offers possibilities for developing expert systems for labeling of crops. Such a knowledge based approach to labeling is presented.

Airborne remote sensing for geology and the environment; present and future

USGS Publications Warehouse

Watson, Ken; Knepper, Daniel H.

1994-01-01

In 1988, a group of leading experts from government, academia, and industry attended a workshop on airborne remote sensing sponsored by the U.S. Geological Survey (USGS) and hosted by the Branch of Geophysics. The purpose of the workshop was to examine the scientific rationale for airborne remote sensing in support of government earth science in the next decade. This report has arranged the six resulting working-group reports under two main headings: (1) Geologic Remote Sensing, for the reports on geologic mapping, mineral resources, and fossil fuels and geothermal resources; and (2) Environmental Remote Sensing, for the reports on environmental geology, geologic hazards, and water resources. The intent of the workshop was to provide an evaluation of demonstrated capabilities, their direct extensions, and possible future applications, and this was the organizational format used for the geologic remote sensing reports. The working groups in environmental remote sensing chose to present their reports in a somewhat modified version of this format. A final section examines future advances and limitations in the field. There is a large, complex, and often bewildering array of remote sensing data available. Early remote sensing studies were based on data collected from airborne platforms. Much of that technology was later extended to satellites. The original 80-m-resolution Landsat Multispectral Scanner System (MSS) has now been largely superseded by the 30-m-resolution Thematic Mapper (TM) system that has additional spectral channels. The French satellite SPOT provides higher spatial resolution for channels equivalent to MSS. Low-resolution (1 km) data are available from the National Oceanographic and Atmospheric Administration's AVHRR system, which acquires reflectance and day and night thermal data daily. Several experimental satellites have acquired limited data, and there are extensive plans for future satellites including those of Japan (JERS), Europe (ESA), Canada (Radarsat), and the United States (EOS). There are currently two national airborne remote sensing programs (photography, radar) with data archived at the USGS' EROS Data Center. Airborne broadband multispectral data (comparable to Landsat MSS and TM but involving several more channels) for limited geographic areas also are available for digital processing and analysis. Narrow-band imaging spectrometer data are available for some NASA experiment sites and can be acquired for other locations commercially. Remote sensing data and derivative images, because of the uniform spatial coverage, availability at different resolutions, and digital format, are becoming important data sets for geographic information system (GIS) analyses. Examples range from overlaying digitized geologic maps on remote sensing images and draping these over topography, to maps of mineral distribution and inferred abundance. A large variety of remote sensing data sets are available, with costs ranging from a few dollars per square mile for satellite digital data to a few hundred dollars per square mile for airborne imaging spectrometry. Computer processing and analysis costs routinely surpass these expenses because of the equipment and expertise necessary for information extraction and interpretation. Effective use requires both an understanding of the current methodology and an appreciation of the most cost-effective solution.

Flight Calibration of the LROC Narrow Angle Camera

NASA Astrophysics Data System (ADS)

Humm, D. C.; Tschimmel, M.; Brylow, S. M.; Mahanti, P.; Tran, T. N.; Braden, S. E.; Wiseman, S.; Danton, J.; Eliason, E. M.; Robinson, M. S.

2016-04-01

Characterization and calibration are vital for instrument commanding and image interpretation in remote sensing. The Lunar Reconnaissance Orbiter Camera Narrow Angle Camera (LROC NAC) takes 500 Mpixel greyscale images of lunar scenes at 0.5 meters/pixel. It uses two nominally identical line scan cameras for a larger crosstrack field of view. Stray light, spatial crosstalk, and nonlinearity were characterized using flight images of the Earth and the lunar limb. These are important for imaging shadowed craters, studying ˜1 meter size objects, and photometry respectively. Background, nonlinearity, and flatfield corrections have been implemented in the calibration pipeline. An eight-column pattern in the background is corrected. The detector is linear for DN = 600--2000 but a signal-dependent additive correction is required and applied for DN<600. A predictive model of detector temperature and dark level was developed to command dark level offset. This avoids images with a cutoff at DN=0 and minimizes quantization error in companding. Absolute radiometric calibration is derived from comparison of NAC images with ground-based images taken with the Robotic Lunar Observatory (ROLO) at much lower spatial resolution but with the same photometric angles.

Saliency-Guided Change Detection of Remotely Sensed Images Using Random Forest

NASA Astrophysics Data System (ADS)

Feng, W.; Sui, H.; Chen, X.

2018-04-01

Studies based on object-based image analysis (OBIA) representing the paradigm shift in change detection (CD) have achieved remarkable progress in the last decade. Their aim has been developing more intelligent interpretation analysis methods in the future. The prediction effect and performance stability of random forest (RF), as a new kind of machine learning algorithm, are better than many single predictors and integrated forecasting method. In this paper, we present a novel CD approach for high-resolution remote sensing images, which incorporates visual saliency and RF. First, highly homogeneous and compact image super-pixels are generated using super-pixel segmentation, and the optimal segmentation result is obtained through image superimposition and principal component analysis (PCA). Second, saliency detection is used to guide the search of interest regions in the initial difference image obtained via the improved robust change vector analysis (RCVA) algorithm. The salient regions within the difference image that correspond to the binarized saliency map are extracted, and the regions are subject to the fuzzy c-means (FCM) clustering to obtain the pixel-level pre-classification result, which can be used as a prerequisite for superpixel-based analysis. Third, on the basis of the optimal segmentation and pixel-level pre-classification results, different super-pixel change possibilities are calculated. Furthermore, the changed and unchanged super-pixels that serve as the training samples are automatically selected. The spectral features and Gabor features of each super-pixel are extracted. Finally, superpixel-based CD is implemented by applying RF based on these samples. Experimental results on Ziyuan 3 (ZY3) multi-spectral images show that the proposed method outperforms the compared methods in the accuracy of CD, and also confirm the feasibility and effectiveness of the proposed approach.

ERS-2 SAR and IRS-1C LISS III data fusion: A PCA approach to improve remote sensing based geological interpretation

NASA Astrophysics Data System (ADS)

Pal, S. K.; Majumdar, T. J.; Bhattacharya, Amit K.

Fusion of optical and synthetic aperture radar data has been attempted in the present study for mapping of various lithologic units over a part of the Singhbhum Shear Zone (SSZ) and its surroundings. ERS-2 SAR data over the study area has been enhanced using Fast Fourier Transformation (FFT) based filtering approach, and also using Frost filtering technique. Both the enhanced SAR imagery have been then separately fused with histogram equalized IRS-1C LISS III image using Principal Component Analysis (PCA) technique. Later, Feature-oriented Principal Components Selection (FPCS) technique has been applied to generate False Color Composite (FCC) images, from which corresponding geological maps have been prepared. Finally, GIS techniques have been successfully used for change detection analysis in the lithological interpretation between the published geological map and the fusion based geological maps. In general, there is good agreement between these maps over a large portion of the study area. Based on the change detection studies, few areas could be identified which need attention for further detailed ground-based geological studies.

Microwave backscattering theory and active remote sensing of the ocean surface

NASA Technical Reports Server (NTRS)

Brown, G. S.; Miller, L. S.

1977-01-01

The status is reviewed of electromagnetic scattering theory relative to the interpretation of microwave remote sensing data acquired from spaceborne platforms over the ocean surface. Particular emphasis is given to the assumptions which are either implicit or explicit in the theory. The multiple scale scattering theory developed during this investigation is extended to non-Gaussian surface statistics. It is shown that the important statistic for the case is the probability density function of the small scale heights conditioned on the large scale slopes; this dependence may explain the anisotropic scattering measurements recently obtained with the AAFE Radscat. It is noted that present surface measurements are inadequate to verify or reject the existing scattering theories. Surface measurements are recommended for qualifying sensor data from radar altimeters and scatterometers. Additional scattering investigations are suggested for imaging type radars employing synthetically generated apertures.

Differentiating aquatic plant communities in a eutrophic river using hyperspectral and multispectral remote sensing

USGS Publications Warehouse

Tian, Y.Q.; Yu, Q.; Zimmerman, M.J.; Flint, S.; Waldron, M.C.

2010-01-01

This study evaluates the efficacy of remote sensing technology to monitor species composition, areal extent and density of aquatic plants (macrophytes and filamentous algae) in impoundments where their presence may violate water-quality standards. Multispectral satellite (IKONOS) images and more than 500 in situ hyperspectral samples were acquired to map aquatic plant distributions. By analyzing field measurements, we created a library of hyperspectral signatures for a variety of aquatic plant species, associations and densities. We also used three vegetation indices. Normalized Difference Vegetation Index (NDVI), near-infrared (NIR)-Green Angle Index (NGAI) and normalized water absorption depth (DH), at wavelengths 554, 680, 820 and 977 nm to differentiate among aquatic plant species composition, areal density and thickness in cases where hyperspectral analysis yielded potentially ambiguous interpretations. We compared the NDVI derived from IKONOS imagery with the in situ, hyperspectral-derived NDVI. The IKONOS-based images were also compared to data obtained through routine visual observations. Our results confirmed that aquatic species composition alters spectral signatures and affects the accuracy of remote sensing of aquatic plant density. The results also demonstrated that the NGAI has apparent advantages in estimating density over the NDVI and the DH. In the feature space of the three indices, 3D scatter plot analysis revealed that hyperspectral data can differentiate several aquatic plant associations. High-resolution multispectral imagery provided useful information to distinguish among biophysical aquatic plant characteristics. Classification analysis indicated that using satellite imagery to assess Lemna coverage yielded an overall agreement of 79% with visual observations and >90% agreement for the densest aquatic plant coverages. Interpretation of biophysical parameters derived from high-resolution satellite or airborne imagery should prove to be a valuable approach for assessing the effectiveness of management practices for controlling aquatic plant growth in inland waters, as well as for routine monitoring of aquatic plants in lakes and suitable lentic environments. ?? 2010 Blackwell Publishing Ltd.

Evidence for Crater Ejecta on Venus Tessera Terrain from Earth-Based Radar Images

NASA Technical Reports Server (NTRS)

Campbell, Bruce A.; Campbell, Donald B.; Morgan, Gareth A.; Carter, Lynn M.; Nolan, Michael C.; Chandler, John F.

2014-01-01

We combine Earth-based radar maps of Venus from the 1988 and 2012 inferior conjunctions, which had similar viewing geometries. Processing of both datasets with better image focusing and co-registration techniques, and summing over multiple looks, yields maps with 1-2 km spatial resolution and improved signal to noise ratio, especially in the weaker same-sense circular (SC) polarization. The SC maps are unique to Earth-based observations, and offer a different view of surface properties from orbital mapping using same-sense linear (HH or VV) polarization. Highland or tessera terrains on Venus, which may retain a record of crustal differentiation and processes occurring prior to the loss of water, are of great interest for future spacecraft landings. The Earth-based radar images reveal multiple examples of tessera mantling by impact ''parabolas'' or ''haloes'', and can extend mapping of locally thick material from Magellan data by revealing thinner deposits over much larger areas. Of particular interest is an ejecta deposit from Stuart crater that we infer to mantle much of eastern Alpha Regio. Some radar-dark tessera occurrences may indicate sediments that are trapped for longer periods than in the plains. We suggest that such radar information is important for interpretation of orbital infrared data and selection of future tessera landing sites.

An Interpretative Phenomenological Analysis of Sense-Making by Department of Defense Employees

ERIC Educational Resources Information Center

Harrison, John L., Sr.

2011-01-01

The purpose of this qualitative, phenomenological study was to explore the perceptions and lived experiences of Department of Defense (DOD) civilian employees to identify how their personal sense-making affects their coaching of adult students. The author used an interpretative phenomenological analysis (IPA) method involving personal interviews…

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Rocky 7 prototype Mars rover field geology experiments 1. Lavic Lake and sunshine volcanic field, California

USGS Publications Warehouse

Arvidson, R. E.; Acton, C.; Blaney, D.; Bowman, J.; Kim, S.; Klingelhofer, G.; Marshall, J.; Niebur, C.; Plescia, J.; Saunders, R.S.; Ulmer, C.T.

1998-01-01

Experiments with the Rocky 7 rover were performed in the Mojave Desert to better understand how to conduct rover-based, long-distance (kilometers) geological traverses on Mars. The rover was equipped with stereo imaging systems for remote sensing science and hazard avoidance and 57Fe Mo??ssbauer and nuclear magnetic resonance spectrometers for in situ determination of mineralogy of unprepared rock and soil surfaces. Laboratory data were also obtained using the spectrometers and an X ray diffraction (XRD)/XRF instrument for unprepared samples collected from the rover sites. Simulated orbital and descent image data assembled for the test sites were found to be critical for assessing the geologic setting, formulating hypotheses to be tested with rover observations, planning traverses, locating the rover, and providing a regional context for interpretation of rover-based observations. Analyses of remote sensing and in situ observations acquired by the rover confirmed inferences made from orbital and simulated descent images that the Sunshine Volcanic Field is composed of basalt flows. Rover data confirmed the idea that Lavic Lake is a recharge playa and that an alluvial fan composed of sediments with felsic compositions has prograded onto the playa. Rover-based discoveries include the inference that the basalt flows are mantled with aeolian sediment and covered with a dense pavement of varnished basalt cobbles. Results demonstrate that the combination of rover remote sensing and in situ analytical observations will significantly increase our understanding of Mars and provide key connecting links between orbital and descent data and analyses of returned samples. Copyright 1998 by the American Geophysical Union.

Digitise This! A Quick and Easy Remote Sensing Method to Monitor the Daily Extent of Dredge Plumes

PubMed Central

Evans, Richard D.; Murray, Kathy L.; Field, Stuart N.; Moore, James A. Y.; Shedrawi, George; Huntley, Barton G.; Fearns, Peter; Broomhall, Mark; McKinna, Lachlan I. W.; Marrable, Daniel

2012-01-01

Technological advancements in remote sensing and GIS have improved natural resource managers’ abilities to monitor large-scale disturbances. In a time where many processes are heading towards automation, this study has regressed to simple techniques to bridge a gap found in the advancement of technology. The near-daily monitoring of dredge plume extent is common practice using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and associated algorithms to predict the total suspended solids (TSS) concentration in the surface waters originating from floods and dredge plumes. Unfortunately, these methods cannot determine the difference between dredge plume and benthic features in shallow, clear water. This case study at Barrow Island, Western Australia, uses hand digitising to demonstrate the ability of human interpretation to determine this difference with a level of confidence and compares the method to contemporary TSS methods. Hand digitising was quick, cheap and required very little training of staff to complete. Results of ANOSIM R statistics show remote sensing derived TSS provided similar spatial results if they were thresholded to at least 3 mg L−1. However, remote sensing derived TSS consistently provided false-positive readings of shallow benthic features as Plume with a threshold up to TSS of 6 mg L−1, and began providing false-negatives (excluding actual plume) at a threshold as low as 4 mg L−1. Semi-automated processes that estimate plume concentration and distinguish between plumes and shallow benthic features without the arbitrary nature of human interpretation would be preferred as a plume monitoring method. However, at this stage, the hand digitising method is very useful and is more accurate at determining plume boundaries over shallow benthic features and is accessible to all levels of management with basic training. PMID:23240055

Spatial assessment of Geo-environmental data by the integration of Remote Sensing and GIS techniques for Sitakund Region, Eastern foldbelt, Bangladesh.

NASA Astrophysics Data System (ADS)

Gazi, M. Y.; Rahman, M.; Islam, M. A.; Kabir, S. M. M.

2016-12-01

Techniques of remote sensing and geographic information systems (GIS) have been applied for the analysis and interpretation of the Geo-environmental assessment to Sitakund area, located within the administrative boundaries of the Chittagong district, Bangladesh. Landsat ETM+ image with a ground resolution of 30-meter and Digital Elevation Model (DEM) has been adopted in this study in order to produce a set of thematic maps. The diversity of the terrain characteristics had a major role in the diversity of recipes and types of soils that are based on the geological structure, also helped to diversity in land cover and use in the region. The geological situation has affected on the general landscape of the study area. The problem of research lies in the possibility of the estimating the techniques of remote sensing and geographic information systems in the evaluation of the natural data for the study area spatially as well as determine the appropriate in grades for the appearance of the ground and in line with the reality of the region. Software for remote sensing and geographic information systems were adopted in the analysis, classification and interpretation of the prepared thematic maps in order to get to the building of the Geo-environmental assessment map of the study area. Low risk geo-environmental land mostly covered area of Quaternary deposits especially with area of slope wash deposits carried by streams. Medium and high risk geo-environmental land distributed with area of other formation with the study area, mostly the high risk shows area of folds and faults. The study has assessed the suitability of lands for agricultural purpose and settlements in less vulnerable areas within this region.

What defines an Expert? - Uncertainty in the interpretation of seismic data

NASA Astrophysics Data System (ADS)

Bond, C. E.

2008-12-01

Studies focusing on the elicitation of information from experts are concentrated primarily in economics and world markets, medical practice and expert witness testimonies. Expert elicitation theory has been applied in the natural sciences, most notably in the prediction of fluid flow in hydrological studies. In the geological sciences expert elicitation has been limited to theoretical analysis with studies focusing on the elicitation element, gaining expert opinion rather than necessarily understanding the basis behind the expert view. In these cases experts are defined in a traditional sense, based for example on: standing in the field, no. of years of experience, no. of peer reviewed publications, the experts position in a company hierarchy or academia. Here traditional indicators of expertise have been compared for significance on affective seismic interpretation. Polytomous regression analysis has been used to assess the relative significance of length and type of experience on the outcome of a seismic interpretation exercise. Following the initial analysis the techniques used by participants to interpret the seismic image were added as additional variables to the analysis. Specific technical skills and techniques were found to be more important for the affective geological interpretation of seismic data than the traditional indicators of expertise. The results of a seismic interpretation exercise, the techniques used to interpret the seismic and the participant's prior experience have been combined and analysed to answer the question - who is and what defines an expert?

Simple models for complex natural surfaces - A strategy for the hyperspectral era of remote sensing

NASA Technical Reports Server (NTRS)

Adams, John B.; Smith, Milton O.; Gillespie, Alan R.

1989-01-01

A two-step strategy for analyzing multispectral images is described. In the first step, the analyst decomposes the signal from each pixel (as expressed by the radiance or reflectance values in each channel) into components that are contributed by spectrally distinct materials on the ground, and those that are due to atmospheric effects, instrumental effects, and other factors, such as illumination. In the second step, the isolated signals from the materials on the ground are selectively edited, and recombined to form various unit maps that are interpretable within the framework of field units. The approach has been tested on multispectral images of a variety of natural land surfaces ranging from hyperarid deserts to tropical rain forests. Data were analyzed from Landsat MSS (multispectral scanner) and TM (Thematic Mapper), the airborne NS001 TM simulator, Viking Lander and Orbiter, AIS, and AVRIS (Airborne Visible and Infrared Imaging Spectrometer).

Interpretation of HCMM images: A regional study

NASA Technical Reports Server (NTRS)

1982-01-01

Potential users of HCMM data, especially those with only a cursory background in thermal remote sensing are familiarized with the kinds of information contained in the images that can be extracted with some reliability solely from inspection of such standard products as those generated at NASA/GSFC and now achieved in the National Space Science Data Center. Visual analysis of photoimagery is prone to various misimpressions and outright errors brought on by unawareness of the influence of physical factors as well as by sometimes misleading tonal patterns introduced during photoprocessing. The quantitative approach, which relies on computer processing of digital HCMM data, field measurements, and integration of rigorous mathematical models, can usually be used to identify, compensate for, or correct the contributions from at least some of the natural factors and those associated with photoprocessing. Color composite, day-IR, night-IR and visible images of California and Nevada are examined.

Preliminary study of near surface detections at geothermal field using optic and SAR imageries

NASA Astrophysics Data System (ADS)

Kurniawahidayati, Beta; Agoes Nugroho, Indra; Syahputra Mulyana, Reza; Saepuloh, Asep

2017-12-01

Current remote sensing technologies shows that surface manifestation of geothermal system could be detected with optical and SAR remote sensing, but to assess target beneath near the surface layer with the surficial method needs a further study. This study conducts a preliminary result using Optic and SAR remote sensing imagery to detect near surface geothermal manifestation at and around Mt. Papandayan, West Java, Indonesia. The data used in this study were Landsat-8 OLI/TIRS for delineating geothermal manifestation prospect area and an Advanced Land Observing Satellite(ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) level 1.1 for extracting lineaments and their density. An assumption was raised that the lineaments correlated with near surface structures due to long L-band wavelength about 23.6 cm. Near surface manifestation prospect area are delineated using visual comparison between Landsat 8 RGB True Colour Composite band 4,3,2 (TCC), False Colour Composite band 5,6,7 (FCC), and lineament density map of ALOS PALSAR. Visual properties of ground object were distinguished from interaction of the electromagnetic radiation and object whether it reflect, scatter, absorb, or and emit electromagnetic radiation based on characteristic of their molecular composition and their macroscopic scale and geometry. TCC and FCC composite bands produced 6 and 7 surface manifestation zones according to its visual classification, respectively. Classified images were then compared to a Normalized Different Vegetation Index (NDVI) to obtain the influence of vegetation at the ground surface to the image. Geothermal area were classified based on vegetation index from NDVI. TCC image is more sensitive to the vegetation than FCC image. The later composite produced a better result for identifying visually geothermal manifestation showed by detail-detected zones. According to lineament density analysis high density area located on the peak of Papandayan overlaid with zone 1 and 2 of FCC. Comparing to the extracted lineament density, we interpreted that the near surface manifestation is located at zone 1 and 2 of FCC image.

Geologic analyses of LANDSAT-1 multispectral imagery of a possible power plant site employing digital and analog image processing. [in Pennsylvania

NASA Technical Reports Server (NTRS)

Lovegreen, J. R.; Prosser, W. J.; Millet, R. A.

1975-01-01

A site in the Great Valley subsection of the Valley and Ridge physiographic province in eastern Pennsylvania was studied to evaluate the use of digital and analog image processing for geologic investigations. Ground truth at the site was obtained by a field mapping program, a subsurface exploration investigation and a review of available published and unpublished literature. Remote sensing data were analyzed using standard manual techniques. LANDSAT-1 imagery was analyzed using digital image processing employing the multispectral Image 100 system and using analog color processing employing the VP-8 image analyzer. This study deals primarily with linears identified employing image processing and correlation of these linears with known structural features and with linears identified manual interpretation; and the identification of rock outcrops in areas of extensive vegetative cover employing image processing. The results of this study indicate that image processing can be a cost-effective tool for evaluating geologic and linear features for regional studies encompassing large areas such as for power plant siting. Digital image processing can be an effective tool for identifying rock outcrops in areas of heavy vegetative cover.

Compressive hyperspectral and multispectral imaging fusion

NASA Astrophysics Data System (ADS)

Espitia, Óscar; Castillo, Sergio; Arguello, Henry

2016-05-01

Image fusion is a valuable framework which combines two or more images of the same scene from one or multiple sensors, allowing to improve the resolution of the images and increase the interpretable content. In remote sensing a common fusion problem consists of merging hyperspectral (HS) and multispectral (MS) images that involve large amount of redundant data, which ignores the highly correlated structure of the datacube along the spatial and spectral dimensions. Compressive HS and MS systems compress the spectral data in the acquisition step allowing to reduce the data redundancy by using different sampling patterns. This work presents a compressed HS and MS image fusion approach, which uses a high dimensional joint sparse model. The joint sparse model is formulated by combining HS and MS compressive acquisition models. The high spectral and spatial resolution image is reconstructed by using sparse optimization algorithms. Different fusion spectral image scenarios are used to explore the performance of the proposed scheme. Several simulations with synthetic and real datacubes show promising results as the reliable reconstruction of a high spectral and spatial resolution image can be achieved by using as few as just the 50% of the datacube.

Evaluation of C-band SAR data from SAREX 1992: Tapajos study site

NASA Technical Reports Server (NTRS)

Shimabukuro, Yosio Edemir; Filho, Pedro Hernandez; Lee, David Chung Liang; Ahern, F. J.; Paivadossantosfilho, Celio; Rolodealmeida, Rionaldo

1993-01-01

As part of the SAREX'92 (South American Radar Experiment), the Tapajos study site, located in Para State, Brazil was imaged by the Canada Center for Remote Sensing (CCRS) Convair 580 SAR system using a C-band frequency in HH and VV polarization and 3 different imaging modes (nadir, narrow, and wide swath). A preliminary analysis of this dataset is presented. The wide swath C-band HH polarized image was enlarged to 1:100,000 in a photographic form for manual interpretation. This was compared with a vegetation map produced primarily from Landsat Thematic Mapper (TM) data and with single-band and color composite images derived from a decomposition analysis of TM data. The Synthetic Aperture Radar (SAR) image shows well the topography and drainage network defining the different geomorphological units, and canopy texture differences which appear to be related to the size and maturity of the forest canopy. Areas of recent clearing of the primary forest can also be identified on the SAR image. The SAR system appears to be a source of information for monitoring tropical forest which is complementary to the Landsat Thematic Mapper.

Automated Rock Identification for Future Mars Exploration Missions

NASA Technical Reports Server (NTRS)

Gulick, V. C.; Morris, R. L.; Gazis, P.; Bishop, J. L.; Alena, R.; Hart, S. D.; Horton, A.

2003-01-01

A key task for human or robotic explorers on the surface of Mars is choosing which particular rock or mineral samples should be selected for more intensive study. The usual challenges of such a task are compounded by the lack of sensory input available to a suited astronaut or the limited downlink bandwidth available to a rover. Additional challenges facing a human mission include limited surface time and the similarities in appearance of important minerals (e.g. carbonates, silicates, salts). Yet the choice of which sample to collect is critical. To address this challenge we are developing science analysis algorithms to interface with a Geologist's Field Assistant (GFA) device that will allow robotic or human remote explorers to better sense and explore their surroundings during limited surface excursions. We aim for our algorithms to interpret spectral and imaging data obtained by various sensors. The algorithms, for example, will identify key minerals, rocks, and sediments from mid-IR, Raman, and visible/near-IR spectra as well as from high resolution and microscopic images to help interpret data and to provide high-level advice to the remote explorer. A top-level system will consider multiple inputs from raw sensor data output by imagers and spectrometers (visible/near-IR, mid-IR, and Raman) as well as human opinion to identify rock and mineral samples.

Sea Ice Thickness Measurement by Ground Penetrating Radar for Ground Truth of Microwave Remote Sensing Data

NASA Astrophysics Data System (ADS)

Matsumoto, M.; Yoshimura, M.; Naoki, K.; Cho, K.; Wakabayashi, H.

2018-04-01

Observation of sea ice thickness is one of key issues to understand regional effect of global warming. One of approaches to monitor sea ice in large area is microwave remote sensing data analysis. However, ground truth must be necessary to discuss the effectivity of this kind of approach. The conventional method to acquire ground truth of ice thickness is drilling ice layer and directly measuring the thickness by a ruler. However, this method is destructive, time-consuming and limited spatial resolution. Although there are several methods to acquire ice thickness in non-destructive way, ground penetrating radar (GPR) can be effective solution because it can discriminate snow-ice and ice-sea water interface. In this paper, we carried out GPR measurement in Lake Saroma for relatively large area (200 m by 300 m, approximately) aiming to obtain grand truth for remote sensing data. GPR survey was conducted at 5 locations in the area. The direct measurement was also conducted simultaneously in order to calibrate GPR data for thickness estimation and to validate the result. Although GPR Bscan image obtained from 600MHz contains the reflection which may come from a structure under snow, the origin of the reflection is not obvious. Therefore, further analysis and interpretation of the GPR image, such as numerical simulation, additional signal processing and use of 200 MHz antenna, are required to move on thickness estimation.

Delineating Floodplain in North Korea using Remote Sensing and Geographic Information System

NASA Astrophysics Data System (ADS)

Lim, J.; Lee, K. S.

2015-12-01

Korea has been divided into two countries after World War II. So environmental studies about North Korean are not easy and very limited. There were several flood damages every summer in North Korea since 1995, which induces lots of economic loss and agricultural production decrease. Delineating floodplain is indispensable to estimate the magnitude of flood damage and restore the flooded paddy field after unification. Remote Sensing (RS) can provide opportunity to study inaccessible area. In addition, flooding detection is possible. Several research groups study about flooding disaster using RS. Optical images and microwave images have been used in that field. Also, Digital topographic data have been used for flooding detection. Therefore, the purpose of this study is to investigate the land characteristics of floodplain by delineating floodplain in inaccessible North Korea using Landsat and digital topographic data. Landsat TM 5 images were used in this study. North Korea had severe flooding disaster since 1995. Among them 1995, 2007 and 2012 flooding are known for serious damages. Two Landsat images before and after flooding of each year were used to delineate floodplain. Study areas are Pyongyang City, Nampo City, North and South Hwanghae Province and South Pyongan Province. Floodplain are derived from overlaid classification image and flood-depth map. 1:25,000 scale digital topographic data were used to make flood-depth map. For land cover classification image enhancement and supervised classification with maximum likelihood classifier were used. Training areas were selected by visual interpretation using Daum-map which provides high resolution image of whole North Korea. The spatial characteristics of the floodplain were discussed based on floodplain map delineated in this study.

Remote sensing of land degradation: experiences from Latin America and the Caribbean.

PubMed

Metternicht, G; Zinck, J A; Blanco, P D; del Valle, H F

2010-01-01

Land degradation caused by deforestation, overgrazing, and inappropriate irrigation practices affects about 16% of Latin America and the Caribbean (LAC). This paper addresses issues related to the application of remote sensing technologies for the identification and mapping of land degradation features, with special attention to the LAC region. The contribution of remote sensing to mapping land degradation is analyzed from the compilation of a large set of research papers published between the 1980s and 2009, dealing with water and wind erosion, salinization, and changes of vegetation cover. The analysis undertaken found that Landsat series (MSS, TM, ETM+) are the most commonly used data source (49% of the papers report their use), followed by aerial photographs (39%), and microwave sensing (ERS, JERS-1, Radarsat) (27%). About 43% of the works analyzed use multi-scale, multi-sensor, multi-spectral approaches for mapping degraded areas, with a combination of visual interpretation and advanced image processing techniques. The use of more expensive hyperspectral and/or very high spatial resolution sensors like AVIRIS, Hyperion, SPOT-5, and IKONOS tends to be limited to small surface areas. The key issue of indicators that can directly or indirectly help recognize land degradation features in the visible, infrared, and microwave regions of the electromagnetic spectrum are discussed. Factors considered when selecting indicators for establishing land degradation baselines include, among others, the mapping scale, the spectral characteristics of the sensors, and the time of image acquisition. The validation methods used to assess the accuracy of maps produced with satellite data are discussed as well.

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.

Analysis of amyloplast dynamics involved in gravity sensing using a novel centrifuge microscope

NASA Astrophysics Data System (ADS)

Toyota, Masatsugu; Tasaka, Masao; Morita, Miyo T.

Plants sense gravity and change their growth orientation, a phenomenon known as gravitropism. According to the starch-statolith hypothesis, sedimentation of high-density starch-filled plastids (amyloplasts) within endodermal cells appears to be involved in gravity sensing of Arabidop-sis shoots. Recent studies suggest, however, that amyloplasts are never static but continu-ously show dynamic and complicated movements due to interaction with vacuole/cytoskeleton. Therefore, it remains unclear what movement/state of amyloplasts is required for gravity sens-ing. To address this critical issue, we analyzed gravitropism and amyloplast dynamics under hypergravity condition where sedimentation by gravity is more dominant than other movements. Segments of Arabidopsis inflorescence stem showed a gravitropism in response to hypergrav-ity (10g) that had been applied perpendicularly to the growth axis for 30 s in a conventional centrifuge, suggesting that amyloplast dynamics during this short time period is involved in gravity sensing. Real-time imaging of amyloplasts during the 10g stimulation was performed using a novel centrifuge microscope (NSK Ltd, Japan): all optical devices including objective lens, light source (LED) and CCD camera are mounted on an AC motor, enabling bright-field imaging with a temporal resolution of 30 frames/sec during rotation. Almost all amyloplasts started to move toward 10g and some reached the one side of endodermal cell within 30 s. These results clearly support the starch-statolith hypothesis that redistribution of amyloplasts to gravity is important for gravity sensing. Furthermore, we analyzed the shoot gravitropic mutant, sgr2, that has non-sedimentable amyloplasts and shows little gravitropism at 1g. An obvious gravitropism was induced by 30g for 5 min where amyloplasts were moved to the hyper-gravity but not by 10g where amyloplasts were not moved. These results not only suggest that gravity sensing of Arabidopsis inflorescence stems is triggered by the amyloplast redistribution resulting from the directional movement to gravity, but also provide a new interpretation of sgr2 that sgr2 has a gravity-sensing mechanism, which is inactivated at 1g probably due to non-sedimentable amyloplasts.

Compressive sensing in medical imaging

PubMed Central

Graff, Christian G.; Sidky, Emil Y.

2015-01-01

The promise of compressive sensing, exploitation of compressibility to achieve high quality image reconstructions with less data, has attracted a great deal of attention in the medical imaging community. At the Compressed Sensing Incubator meeting held in April 2014 at OSA Headquarters in Washington, DC, presentations were given summarizing some of the research efforts ongoing in compressive sensing for x-ray computed tomography and magnetic resonance imaging systems. This article provides an expanded version of these presentations. Sparsity-exploiting reconstruction algorithms that have gained popularity in the medical imaging community are studied, and examples of clinical applications that could benefit from compressive sensing ideas are provided. The current and potential future impact of compressive sensing on the medical imaging field is discussed. PMID:25968400

Workflow Dynamics and the Imaging Value Chain: Quantifying the Effect of Designating a Nonimage-Interpretive Task Workflow.

PubMed

Lee, Matthew H; Schemmel, Andrew J; Pooler, B Dustin; Hanley, Taylor; Kennedy, Tabassum A; Field, Aaron S; Wiegmann, Douglas; Yu, John-Paul J

To assess the impact of separate non-image interpretive task and image-interpretive task workflows in an academic neuroradiology practice. A prospective, randomized, observational investigation of a centralized academic neuroradiology reading room was performed. The primary reading room fellow was observed over a one-month period using a time-and-motion methodology, recording frequency and duration of tasks performed. Tasks were categorized into separate image interpretive and non-image interpretive workflows. Post-intervention observation of the primary fellow was repeated following the implementation of a consult assistant responsible for non-image interpretive tasks. Pre- and post-intervention data were compared. Following separation of image-interpretive and non-image interpretive workflows, time spent on image-interpretive tasks by the primary fellow increased from 53.8% to 73.2% while non-image interpretive tasks decreased from 20.4% to 4.4%. Mean time duration of image interpretation nearly doubled, from 05:44 to 11:01 (p = 0.002). Decreases in specific non-image interpretive tasks, including phone calls/paging (2.86/hr versus 0.80/hr), in-room consultations (1.36/hr versus 0.80/hr), and protocoling (0.99/hr versus 0.10/hr), were observed. The consult assistant experienced 29.4 task switching events per hour. Rates of specific non-image interpretive tasks for the CA were 6.41/hr for phone calls/paging, 3.60/hr for in-room consultations, and 3.83/hr for protocoling. Separating responsibilities into NIT and IIT workflows substantially increased image interpretation time and decreased TSEs for the primary fellow. Consolidation of NITs into a separate workflow may allow for more efficient task completion. Copyright © 2017 Elsevier Inc. All rights reserved.

Geologic map of Mars

USGS Publications Warehouse

Tanaka, Kenneth L.; Skinner, James A.; Dohm, James M.; Irwin, Rossman P.; Kolb, Eric J.; Fortezzo, Corey M.; Platz, Thomas; Michael, Gregory G.; Hare, Trent M.

2014-01-01

This global geologic map of Mars, which records the distribution of geologic units and landforms on the planet's surface through time, is based on unprecedented variety, quality, and quantity of remotely sensed data acquired since the Viking Orbiters. These data have provided morphologic, topographic, spectral, thermophysical, radar sounding, and other observations for integration, analysis, and interpretation in support of geologic mapping. In particular, the precise topographic mapping now available has enabled consistent morphologic portrayal of the surface for global mapping (whereas previously used visual-range image bases were less effective, because they combined morphologic and albedo information and, locally, atmospheric haze). Also, thermal infrared image bases used for this map tended to be less affected by atmospheric haze and thus are reliable for analysis of surface morphology and texture at even higher resolution than the topographic products.

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 bird's eye view: the cognitive strategies of experts interpreting seismic profiles

NASA Astrophysics Data System (ADS)

Bond, C. E.; Butler, R.

2012-12-01

Geoscience is perhaps unique in its reliance on incomplete datasets and building knowledge from their interpretation. This interpretation basis for the science is fundamental at all levels; from creation of a geological map to interpretation of remotely sensed data. To teach and understand better the uncertainties in dealing with incomplete data we need to understand the strategies individual practitioners deploy that make them effective interpreters. The nature of interpretation is such that the interpreter needs to use their cognitive ability in the analysis of the data to propose a sensible solution in their final output that is both consistent not only with the original data but also with other knowledge and understanding. In a series of experiments Bond et al. (2007, 2008, 2011, 2012) investigated the strategies and pitfalls of expert and non-expert interpretation of seismic images. These studies focused on large numbers of participants to provide a statistically sound basis for analysis of the results. The outcome of these experiments showed that techniques and strategies are more important than expert knowledge per se in developing successful interpretations. Experts are successful because of their application of these techniques. In a new set of experiments we have focused on a small number of experts to determine how they use their cognitive and reasoning skills, in the interpretation of 2D seismic profiles. Live video and practitioner commentary were used to track the evolving interpretation and to gain insight on their decision processes. The outputs of the study allow us to create an educational resource of expert interpretation through online video footage and commentary with associated further interpretation and analysis of the techniques and strategies employed. This resource will be of use to undergraduate, post-graduate, industry and academic professionals seeking to improve their seismic interpretation skills, develop reasoning strategies for dealing with incomplete datasets, and for assessing the uncertainty in these interpretations. Bond, C.E. et al. (2012). 'What makes an expert effective at interpreting seismic images?' Geology, 40, 75-78. Bond, C. E. et al. (2011). 'When there isn't a right answer: interpretation and reasoning, key skills for 21st century geoscience'. International Journal of Science Education, 33, 629-652. Bond, C. E. et al. (2008). 'Structural models: Optimizing risk analysis by understanding conceptual uncertainty'. First Break, 26, 65-71. Bond, C. E. et al., (2007). 'What do you think this is?: "Conceptual uncertainty" In geoscience interpretation'. GSA Today, 17, 4-10.

An Approach of Registration between Remote Sensing Image and Electronic Chart Based on Coastal Line

NASA Astrophysics Data System (ADS)

Li, Ying; Yu, Shuiming; Li, Chuanlong

Remote sensing plays an important role marine oil spill emergency. In order to implement a timely and effective countermeasure, it is important to provide exact position of oil spills. Therefore it is necessary to match remote sensing image and electronic chart properly. Variance ordinarily exists between oil spill image and electronic chart, although geometric correction is applied to remote sensing image. It is difficult to find the steady control points on sea to make exact rectification of remote sensing image. An improved relaxation algorithm was developed for finding the control points along the coastline since oil spills occurs generally near the coast. A conversion function is created with the least square, and remote sensing image can be registered with the vector map based on this function. SAR image was used as the remote sensing data and shape format map as the electronic chart data. The results show that this approach can guarantee the precision of the registration, which is essential for oil spill monitoring.

Robotic situational awareness of actions in human teaming

NASA Astrophysics Data System (ADS)

Tahmoush, Dave

2015-06-01

When robots can sense and interpret the activities of the people they are working with, they become more of a team member and less of just a piece of equipment. This has motivated work on recognizing human actions using existing robotic sensors like short-range ladar imagers. These produce three-dimensional point cloud movies which can be analyzed for structure and motion information. We skeletonize the human point cloud and apply a physics-based velocity correlation scheme to the resulting joint motions. The twenty actions are then recognized using a nearest-neighbors classifier that achieves good accuracy.

Remote sensing of snow and ice

NASA Technical Reports Server (NTRS)

Rango, A.

1979-01-01

This paper reviews remote sensing of snow and ice, techniques for improved monitoring, and incorporation of the new data into forecasting and management systems. The snowcover interpretation of visible and infrared data from satellites, automated digital methods, radiative transfer modeling to calculate the solar reflectance of snow, and models using snowcover input data and elevation zones for calculating snowmelt are discussed. The use of visible and near infrared techniques for inferring snow properties, microwave monitoring of snowpack characteristics, use of Landsat images for collecting glacier data, monitoring of river ice with visible imagery from NOAA satellites, use of sequential imagery for tracking ice flow movement, and microwave studies of sea ice are described. Applications of snow and ice research to commercial use are examined, and it is concluded that a major problem to be solved is characterization of snow and ice in nature, since assigning of the correct properties to a real system to be modeled has been difficult.

Satellite Remote Sensing of Cirrus: An Overview

NASA Technical Reports Server (NTRS)

Minnis, Patrick

1998-01-01

The determination of cirrus properties over relatively large spatial and temporal scales will, in most instances, require the use of satellite data. Global coverage, at resolutions as high as several meters are attainable with Landsat, while temporal coverage at 1-min intervals is now available with the latest Geostationary Operational Environmental Satellite (GOES) imagers. Cirrus can be analyzed via interpretation of the radiation that they reflect or emit over a wide range of the electromagnetic spectrum. Many of these spectra and high-resolution satellite data can be used to understand certain aspects of cirrus clouds in particular situations. Production of a global climatology of cirrus clouds, however, requires compromises in spatial, temporal, and spectral coverage. This paper summarizes the state of the art and the potential for future passive remote sensing systems for both understanding cirrus formation and acquiring sufficient statistics to constrain and refine weather and climate models.

Mechanical Sensing with Flexible Metallic Nanowires

NASA Astrophysics Data System (ADS)

Dobrokhotov, Vladimir; Yazdanpanah, Mehdi; Pabba, Santosh; Safir, Abdelilah; Cohn, Robert

2008-03-01

A calibrated method of force sensing is demonstrated in which the buckled shape of a long flexible metallic nanowire is interpreted to determine the applied force. Using a nanomanipulator the nanowire is buckled in the chamber of a scanning electron microscope (SEM) and the buckled shapes are recorded in SEM images. Force is determined as a function of deflection for an assumed elastic modulus by fitting the shapes using the generalized elastica model. In this calibration the elastic modulus was determined using an auxiliary AFM measurement, with the needle in the same orientation as in the SEM. Following this calibration the needle was used as a sensor in a different orientation than the AFM coordinates to deflect a suspended PLLA polymer fiber from which the elastic modulus (2.96 GPa) was determined. In this study the same needle remained rigidly secured to the AFM cantilever throughout the entire SEM/AFM calibration procedure and the characterization of the nanofiber.

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.

Progress in remote sensing (1972-1976)

USGS Publications Warehouse

Fischer, W. A.; Hemphill, W.R.; Kover, Allan

1976-01-01

This report concerns the progress in remote sensing during the period 1972–1976. Remote sensing has been variously defined but is basically the art or science of telling something about an object without touching it. During the past four years, the major research thrusts have been in three areas: (1) computer-assisted enhancement and interpretation systems; (2) earth science applications of Landsat data; (3) and investigations of the usefulness of observations of luminescence, thermal infrared, and microwave energies. Based on the data sales at the EROS Data Center, the largest users of the Landsat data are industrial companies, followed by government agencies (both national and foreign), and academic institutions. Thermal surveys from aircraft have become largely operational, however, significant research is being undertaken in the field of thermal modeling and analysis of high altitude images. Microwave research is increasing rapidly and programs are being developed for satellite observations. Microwave research is concentrating on oil spill detection, soil moisture measurement, and observations of ice distributions. Luminescence investigations offer promise for becoming a quantitative method of assessing vegetation stress and pollutant concentrations.

Geological remote sensing

NASA Astrophysics Data System (ADS)

Bishop, Charlotte; Rivard, Benoit; de Souza Filho, Carlos; van der Meer, Freek

2018-02-01

Geology is defined as the 'study of the planet Earth - the materials of which it is made, the processes that act on these materials, the products formed, and the history of the planet and its life forms since its origin' (Bates and Jackson, 1976). Remote sensing has seen a number of variable definitions such as those by Sabins and Lillesand and Kiefer in their respective textbooks (Sabins, 1996; Lillesand and Kiefer, 2000). Floyd Sabins (Sabins, 1996) defined it as 'the science of acquiring, processing and interpreting images that record the interaction between electromagnetic energy and matter' while Lillesand and Kiefer (Lillesand and Kiefer, 2000) defined it as 'the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation'. Thus Geological Remote Sensing can be considered the study of, not just Earth given the breadth of work undertaken in planetary science, geological features and surfaces and their interaction with the electromagnetic spectrum using technology that is not in direct contact with the features of interest.

Coupling Analysis of Heat Island Effects, Vegetation Coverage and Urban Flood in Wuhan

NASA Astrophysics Data System (ADS)

Liu, Y.; Liu, Q.; Fan, W.; Wang, G.

2018-04-01

In this paper, satellite image, remote sensing technique and geographic information system technique are main technical bases. Spectral and other factors comprehensive analysis and visual interpretation are main methods. We use GF-1 and Landsat8 remote sensing satellite image of Wuhan as data source, and from which we extract vegetation distribution, urban heat island relative intensity distribution map and urban flood submergence range. Based on the extracted information, through spatial analysis and regression analysis, we find correlations among heat island effect, vegetation coverage and urban flood. The results show that there is a high degree of overlap between of urban heat island and urban flood. The area of urban heat island has buildings with little vegetation cover, which may be one of the reasons for the local heavy rainstorms. Furthermore, the urban heat island has a negative correlation with vegetation coverage, and the heat island effect can be alleviated by the vegetation to a certain extent. So it is easy to understand that the new industrial zones and commercial areas which under constructions distribute in the city, these land surfaces becoming bare or have low vegetation coverage, can form new heat islands easily.

The Extraction of Terrace in the Loess Plateau Based on radial method

NASA Astrophysics Data System (ADS)

Liu, W.; Li, F.

2016-12-01

The terrace of Loess Plateau, as a typical kind of artificial landform and an important measure of soil and water conservation, its positioning and automatic extraction will simplify the work of land use investigation. The existing methods of terrace extraction mainly include visual interpretation and automatic extraction. The manual method is used in land use investigation, but it is time-consuming and laborious. Researchers put forward some automatic extraction methods. For example, Fourier transform method can recognize terrace and find accurate position from frequency domain image, but it is more affected by the linear objects in the same direction of terrace; Texture analysis method is simple and have a wide range application of image processing. The disadvantage of texture analysis method is unable to recognize terraces' edge; Object-oriented is a new method of image classification, but when introduce it to terrace extracting, fracture polygons will be the most serious problem and it is difficult to explain its geological meaning. In order to positioning the terraces, we use high- resolution remote sensing image to extract and analyze the gray value of the pixels which the radial went through. During the recognition process, we firstly use the DEM data analysis or by manual selecting, to roughly confirm the position of peak points; secondly, take each of the peak points as the center to make radials in all directions; finally, extracting the gray values of the pixels which the radials went through, and analyzing its changing characteristics to confirm whether the terrace exists. For the purpose of getting accurate position of terrace, terraces' discontinuity, extension direction, ridge width, image processing algorithm, remote sensing image illumination and other influence factors were fully considered when designing the algorithms.

Digital reconstruction on geographical environment of Neolithic human activities in the Lingjiatan site of Chaohu City, East China

NASA Astrophysics Data System (ADS)

Wang, Xinyuan; Zhang, Jie; Wu, Li; Zhou, Kunshu; Mo, Duowen

2010-11-01

The Chaohu Lake Basin is an important area for ancient human activities in East China. The Lingjiatan site, which is located at the southeast of Chaohu City, Anhui Province, and 35 km north to the Yangtze River and 5 km south to the Taihu Mountain, is the most representative Neolithic Age site with advanced jade-carving techniques in this area. The 14C date of Lingjiatan Site is about 5600~5300aBP, the same time as the Hongshan culture and earlier than the Liangzhu culture, which falls into the Mid-Holocene epoch. Based on mid-high resolution remote sensing images and former archaeological materials, combined with field investigations and sampling analysis of the archaeological site profile of Lingjiatan Site as well as core drillings in the Chaohu Lake, the paper reconstructs the climate environment of the Lingjiatan site and the environmental background of ancient human activities during Mid-Holocene. The research results show that: (1) The ancients in Lingjiatan lived in the Holocene Optimum, its culture development was during the interim phase when the climate transformed from warm and wet to cool and dry. (2) The ground surface deposited in the last phase of late Pleistocene epoch (OSL dating is 11.6 +/-1.0 ka BP) was the living ground for Lingjiatan ancient humans. The sedimentary discontinuous surface may be caused by strong fluvial erosion under the warm and humid climatic conditions of the Mid-Holocene. (3) Originally, paleo-geomorphic surface was a level shallow mesa foreside southern part of Taihu Mountain, but was cut by fluvial waters and the geomorphologic configuration formed "finger-like" features alternately with strip hillocks and rivers. These features can be seen on the Landsat ETM+ remote sensing image, especially the depression area. This depression is now cropland, and was interpreted as the palaeochannels. (4) Based on the remote sensing image interpretation, the site was in a "peninsula shape" environment which had rivers flowing around the east, west and south sides of the Changgang terrain and that was good for rice planting, hunting, fishing and water transportation. (5) The most particular characteristic of the Lingjiatan site is the advanced jade production, those maybe have some relationship with the convenient shipping, trade exchanges and optimal environmental conditions, which was also conducive to rice cultivation.

Interpretive repertoires as mirrors on society and as tools for action: reflections on Zeyer and Roth's A mirror of society

NASA Astrophysics Data System (ADS)

Milne, Catherine

2009-12-01

I respond to Zeyer and Roth's (Cultural Studies of Science Education, 2009) paper on their use of interpretive repertoire analysis to explicate Swiss middle school students' dialogic responses to environmental issues. I focus on the strategy of interpretive repertoire analysis, making sense of the stance Zeyer and Roth take with this analysis by synthesizing their argument and comparing their analysis with other researchers that have also used this analytic tool. Interpretive repertoires are discourse resources, including mores, tropes, and metaphors that can be evoked by speakers in support of a tenuous claim. So interpretive repertoires have rhetorical character and function. Interpretive repertoire analysis requires looking for patterns in the contradictions in the speech of a collective of participants that can be codified as interpretive repertoires. Interpretive repertoires provide insight into macro-structures that frame, and are used to justify participants' behavior. My response to Zeyer and Roth's argument might also be thought to be contradictory but I think defensible. In this paper, I outline why I am excited by the possibilities I can image for this type of analysis in areas of science education research. However, I also felt the need to identify possible limitations of Zeyer and Roth's exclusive focus on environmental issues to the neglect of other issues, such as those associated with gender, embedded in participants' discourse. I argue that a critical and historical focus, in conjunction with interpretive repertoire analysis, offer a rich strategy for analysis in science education research, especially in the study of macrostructures, such as gender, race, identity and power.

Target detection method by airborne and spaceborne images fusion based on past images

NASA Astrophysics Data System (ADS)

Chen, Shanjing; Kang, Qing; Wang, Zhenggang; Shen, ZhiQiang; Pu, Huan; Han, Hao; Gu, Zhongzheng

2017-11-01

To solve the problem that remote sensing target detection method has low utilization rate of past remote sensing data on target area, and can not recognize camouflage target accurately, a target detection method by airborne and spaceborne images fusion based on past images is proposed in this paper. The target area's past of space remote sensing image is taken as background. The airborne and spaceborne remote sensing data is fused and target feature is extracted by the means of airborne and spaceborne images registration, target change feature extraction, background noise suppression and artificial target feature extraction based on real-time aerial optical remote sensing image. Finally, the support vector machine is used to detect and recognize the target on feature fusion data. The experimental results have established that the proposed method combines the target area change feature of airborne and spaceborne remote sensing images with target detection algorithm, and obtains fine detection and recognition effect on camouflage and non-camouflage targets.

Blind compressed sensing image reconstruction based on alternating direction method

NASA Astrophysics Data System (ADS)

Liu, Qinan; Guo, Shuxu

2018-04-01

In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

Image quality enhancement in low-light-level ghost imaging using modified compressive sensing method

NASA Astrophysics Data System (ADS)

Shi, Xiaohui; Huang, Xianwei; Nan, Suqin; Li, Hengxing; Bai, Yanfeng; Fu, Xiquan

2018-04-01

Detector noise has a significantly negative impact on ghost imaging at low light levels, especially for existing recovery algorithm. Based on the characteristics of the additive detector noise, a method named modified compressive sensing ghost imaging is proposed to reduce the background imposed by the randomly distributed detector noise at signal path. Experimental results show that, with an appropriate choice of threshold value, modified compressive sensing ghost imaging algorithm can dramatically enhance the contrast-to-noise ratio of the object reconstruction significantly compared with traditional ghost imaging and compressive sensing ghost imaging methods. The relationship between the contrast-to-noise ratio of the reconstruction image and the intensity ratio (namely, the average signal intensity to average noise intensity ratio) for the three reconstruction algorithms are also discussed. This noise suppression imaging technique will have great applications in remote-sensing and security areas.

Wakes from submerged obstacles in an open channel flow

NASA Astrophysics Data System (ADS)

Smith, Geoffrey B.; Marmorino, George; Dong, Charles; Miller, W. D.; Mied, Richard

2015-11-01

Wakes from several submerged obstacles are examined via airborne remote sensing. The primary focus will be bathymetric features in the tidal Potomac river south of Washington, DC, but others may be included as well. In the Potomac the water depth is nominally 10 m with an obstacle height of 8 m, or 80% of the depth. Infrared imagery of the water surface reveals thermal structure suitable both for interpretation of the coherent structures and for estimating surface currents. A novel image processing technique is used to generate two independent scenes with a known time offset from a single overpass from the infrared imagery, suitable for velocity estimation. Color imagery of the suspended sediment also shows suitable texture. Both the `mountain wave' regime and a traditional turbulent wake are observed, depending on flow conditions. Results are validated with in-situ ADCP transects. A computational model is used to further interpret the results.

A Subpixel Classification of Multispectral Satellite Imagery for Interpetation of Tundra-Taiga Ecotone Vegetation (Case Study on Tuliok River Valley, Khibiny, Russia)

NASA Astrophysics Data System (ADS)

Mikheeva, A. I.; Tutubalina, O. V.; Zimin, M. V.; Golubeva, E. I.

2017-12-01

The tundra-taiga ecotone plays significant role in northern ecosystems. Due to global climatic changes, the vegetation of the ecotone is the key object of many remote-sensing studies. The interpretation of vegetation and nonvegetation objects of the tundra-taiga ecotone on satellite imageries of a moderate resolution is complicated by the difficulty of extracting these objects from the spectral and spatial mixtures within a pixel. This article describes a method for the subpixel classification of Terra ASTER satellite image for vegetation mapping of the tundra-taiga ecotone in the Tuliok River, Khibiny Mountains, Russia. It was demonstrated that this method allows to determine the position of the boundaries of ecotone objects and their abundance on the basis of quantitative criteria, which provides a more accurate characteristic of ecotone vegetation when compared to the per-pixel approach of automatic imagery interpretation.

Application of selected methods of remote sensing for detecting carbonaceous water pollution

NASA Technical Reports Server (NTRS)

Davis, E. M.; Fosbury, W. J.

1973-01-01

A reach of the Houston Ship Channel was investigated during three separate overflights correlated with ground truth sampling on the Channel. Samples were analyzed for such conventional parameters as biochemical oxygen demand, chemical oxygen demand, total organic carbon, total inorganic carbon, turbidity, chlorophyll, pH, temperature, dissolved oxygen, and light penetration. Infrared analyses conducted on each sample included reflectance ATR analysis, carbon tetrachloride extraction of organics and subsequent scanning, and KBr evaporate analysis of CCl4 extract concentrate. Imagery which was correlated with field and laboratory data developed from ground truth sampling included that obtained from aerial KA62 hardware, RC-8 metric camera systems, and the RS-14 infrared scanner. The images were subjected to analysis by three film density gradient interpretation units. Data were then analyzed for correlations between imagery interpretation as derived from the three instruments and laboratory infrared signatures and other pertinent field and laboratory analyses.

Aerolian erosion, transport, and deposition of volcaniclastic sands among the shifting sand dunes, Christmas Lake Valley, Oregon: TIMS image analysis

NASA Technical Reports Server (NTRS)

Edgett, Kenneth S.; Ramsey, Michael S.; Christensen, Philip R.

1995-01-01

Remote sensing is a tool that, in the context of aeolian studies, offers a synoptic view of a dune field, sand sea, or entire desert region. Blount et al. (1990) presented one of the first studies demonstrating the power of multispectral images for interpreting the dynamic history of an aeolian sand sea. Blount's work on the Gran Desierto of Mexico used a Landsat TM scene and a linear spectral mixing model to show where different sand populations occur and along what paths these sands may have traveled before becoming incorporated into dunes. Interpretation of sand transport paths and sources in the Gran Desierto led to an improved understanding of the origin and Holocene history of the dunes. With the anticipated advent of the EOS-A platform and ASTER thermal infrared capability in 1998, it will become possible to look at continental sand seas and map sand transport paths using 8-12 mu m bands that are well-suited to tracking silicate sediments. A logical extension of Blount's work is to attempt a similar study using thermal infrared images. One such study has already begun by looking at feldspar, quartz, magnetite, and clay distributions in the Kelso Dunes of southern California. This paper describes the geology and application of TIMS image analysis of a less-well known Holocene dune field in south central Oregon using TIMS data obtained in 1991.

A New Joint-Blade SENSE Reconstruction for Accelerated PROPELLER MRI

PubMed Central

Lyu, Mengye; Liu, Yilong; Xie, Victor B.; Feng, Yanqiu; Guo, Hua; Wu, Ed X.

2017-01-01

PROPELLER technique is widely used in MRI examinations for being motion insensitive, but it prolongs scan time and is restricted mainly to T2 contrast. Parallel imaging can accelerate PROPELLER and enable more flexible contrasts. Here, we propose a multi-step joint-blade (MJB) SENSE reconstruction to reduce the noise amplification in parallel imaging accelerated PROPELLER. MJB SENSE utilizes the fact that PROPELLER blades contain sharable information and blade-combined images can serve as regularization references. It consists of three steps. First, conventional blade-combined images are obtained using the conventional simple single-blade (SSB) SENSE, which reconstructs each blade separately. Second, the blade-combined images are employed as regularization for blade-wise noise reduction. Last, with virtual high-frequency data resampled from the previous step, all blades are jointly reconstructed to form the final images. Simulations were performed to evaluate the proposed MJB SENSE for noise reduction and motion correction. MJB SENSE was also applied to both T2-weighted and T1-weighted in vivo brain data. Compared to SSB SENSE, MJB SENSE greatly reduced the noise amplification at various acceleration factors, leading to increased image SNR in all simulation and in vivo experiments, including T1-weighted imaging with short echo trains. Furthermore, it preserved motion correction capability and was computationally efficient. PMID:28205602

A New Joint-Blade SENSE Reconstruction for Accelerated PROPELLER MRI.

PubMed

Lyu, Mengye; Liu, Yilong; Xie, Victor B; Feng, Yanqiu; Guo, Hua; Wu, Ed X

2017-02-16

PROPELLER technique is widely used in MRI examinations for being motion insensitive, but it prolongs scan time and is restricted mainly to T2 contrast. Parallel imaging can accelerate PROPELLER and enable more flexible contrasts. Here, we propose a multi-step joint-blade (MJB) SENSE reconstruction to reduce the noise amplification in parallel imaging accelerated PROPELLER. MJB SENSE utilizes the fact that PROPELLER blades contain sharable information and blade-combined images can serve as regularization references. It consists of three steps. First, conventional blade-combined images are obtained using the conventional simple single-blade (SSB) SENSE, which reconstructs each blade separately. Second, the blade-combined images are employed as regularization for blade-wise noise reduction. Last, with virtual high-frequency data resampled from the previous step, all blades are jointly reconstructed to form the final images. Simulations were performed to evaluate the proposed MJB SENSE for noise reduction and motion correction. MJB SENSE was also applied to both T2-weighted and T1-weighted in vivo brain data. Compared to SSB SENSE, MJB SENSE greatly reduced the noise amplification at various acceleration factors, leading to increased image SNR in all simulation and in vivo experiments, including T1-weighted imaging with short echo trains. Furthermore, it preserved motion correction capability and was computationally efficient.

Tools and Methods for the Registration and Fusion of Remotely Sensed Data

NASA Technical Reports Server (NTRS)

Goshtasby, Arthur Ardeshir; LeMoigne, Jacqueline

2010-01-01

Tools and methods for image registration were reviewed. Methods for the registration of remotely sensed data at NASA were discussed. Image fusion techniques were reviewed. Challenges in registration of remotely sensed data were discussed. Examples of image registration and image fusion were given.

Advanced geophysical underground coal gasification monitoring

DOE PAGES

Mellors, Robert; Yang, X.; White, J. A.; ...

2014-07-01

Underground Coal Gasification (UCG) produces less surface impact, atmospheric pollutants and greenhouse gas than traditional surface mining and combustion. Therefore, it may be useful in mitigating global change caused by anthropogenic activities. Careful monitoring of the UCG process is essential in minimizing environmental impact. Here we first summarize monitoring methods that have been used in previous UCG field trials. We then discuss in more detail a number of promising advanced geophysical techniques. These methods – seismic, electromagnetic, and remote sensing techniques – may provide improved and cost-effective ways to image both the subsurface cavity growth and surface subsidence effects. Activemore » and passive seismic data have the promise to monitor the burn front, cavity growth, and observe cavity collapse events. Electrical resistance tomography (ERT) produces near real time tomographic images autonomously, monitors the burn front and images the cavity using low-cost sensors, typically running within boreholes. Interferometric synthetic aperture radar (InSAR) is a remote sensing technique that has the capability to monitor surface subsidence over the wide area of a commercial-scale UCG operation at a low cost. It may be possible to infer cavity geometry from InSAR (or other surface topography) data using geomechanical modeling. The expected signals from these monitoring methods are described along with interpretive modeling for typical UCG cavities. They are illustrated using field results from UCG trials and other relevant subsurface operations.« less

Original Size of the Sudbury Structure: Evidence from Field Investigations and Imaging Radar

NASA Technical Reports Server (NTRS)

Lowmman, Paul D., Jr.

1999-01-01

This paper summarizes results of continuing studies of the original size of the Sudbury impact structure, including imaging radar and field investigations of supposed "Sudbury breccia" north of the Sudbury Igneous Comples (SIC). Imaging radar acquired from Canada Centre for Remote Sensing (CCRS) aircraft, European Space Agency Remote Sensing Satellite (ERS-1), and RADARSAT shows no evidence of outer rings concentric with the North Range. Illumination directions are such that these rings, presumably extension fractures, would be conspicuous by look azimuth highlighting if they existed. Field mapping supports this interpretation, showing that supposed ring fractures occupied by Huronian sediments are essentially synclines older than the 1850 Ma impact and are not related to the impact. Field investigations of "Sudbury breccia" north of the SIC shows that most if not all of it is inside or along contacts with diabase dykes of the Sudbury Swarm (ca. 1238 Ma), and hence is far too young to be related to the impact. A recently-discovered occurrence of "Sudbury breccia" south of the SIC, near Creighton, is similarly associated with a NW-trending diabase dyke cutting the SIC, supporting the post-impact age of the breccia. It is concluded that the original north rim of the Sudbury crater was not more than 5 to 10 km north of the present North Range SIC contact, and that published estimates of the crater size (ca 200 km diameter) are incorrect.

Understanding heterogeneity in metropolitan India: The added value of remote sensing data for analyzing sub-standard residential areas

NASA Astrophysics Data System (ADS)

Baud, Isa; Kuffer, Monika; Pfeffer, Karin; Sliuzas, Richard; Karuppannan, Sadasivam

2010-10-01

Analyzing the heterogeneity in metropolitan areas of India utilizing remote sensing data can help to identify more precise patterns of sub-standard residential areas. Earlier work analyzing inequalities in Indian cities employed a constructed index of multiple deprivations (IMDs) utilizing data from the Census of India 2001 ( http://censusindia.gov.in). While that index, described in an earlier paper, provided a first approach to identify heterogeneity at the citywide scale, it neither provided information on spatial variations within the geographical boundaries of the Census database, nor about physical characteristics, such as green spaces and the variation in housing density and quality. In this article, we analyze whether different types of sub-standard residential areas can be identified through remote sensing data, combined, where relevant, with ground-truthing and local knowledge. The specific questions address: (1) the extent to which types of residential sub-standard areas can be drawn from remote sensing data, based on patterns of green space, structure of layout, density of built-up areas, size of buildings and other site characteristics; (2) the spatial diversity of these residential types for selected electoral wards; and (3) the correlation between different types of sub-standard residential areas and the results of the index of multiple deprivations utilized at electoral ward level found previously. The results of a limited number of test wards in Delhi showed that it was possible to extract different residential types matching existing settlement categories using the physical indicators structure of layout, built-up density, building size and other site characteristics. However, the indicator 'amount of green spaces' was not useful to identify informal areas. The analysis of heterogeneity showed that wards with higher IMD scores displayed more or less the full range of residential types, implying that visual image interpretation is able to zoom in on clusters of deprivation of varying size. Finally, the visual interpretation of the diversity of residential types matched the results of the IMD analysis quite well, although the limited number of test wards would need to be expanded to strengthen this statement. Visual image analysis strengthens the robustness of the IMD, and in addition, gives a better idea of the degree of heterogeneity in deprivations within a ward.

Air pollution linked to Remote Sensing tools - Science training using a Master's Level e-Learning Tool

NASA Astrophysics Data System (ADS)

Ladstaetter-Weissenmayer, A.; Kanakidou, M.; Richter, A.; Wagner, T.; Borrell, P.; Law, R. J.; Burrows, J. P.

2009-09-01

As we know it today air pollution is a release into the atmosphere of any substances, chemicals or particles, which are harmful both to the human and animal health as well as the health of the wider environment. The use of satellite based instruments is a young and developing research field and excellent for studying air pollution events over large areas at high spatial-temporal resolutions, especially when ground measurements, which are limited in spatial-temporal coverage, are not available. Students on postgraduate level should be trained in using, and analysing remote sensing data from both ground and satellite based or in interpreting the high variety in remote sensing e.g satellite images or maps. As follows an e-learning online module has been devised and constructed to facilitate the teaching of Remote Sensing of Troposphere from Space to research students at a Master's level. The module, which is essentially an interactive on-line text book, is stand alone, although it could be encompassed within a standard course management system. The scientific content is presented as study pages under three headings: remote sensing from space, the basics of radiation transfer, and retrieval procedures for tropospheric satellite data.The student is encouraged to test his or her comprehension of the material through exercises on the scientific topics.

Air pollution linked to Remote Sensing tools - Science training using a Master's Level e-Learning Tool

NASA Astrophysics Data System (ADS)

Ladstätter-Weißenmayer, A.; Kanakidou, M.; Richter, A.; Wagner, T.; Borrell, P.; Law, R. J.; Burrows, J. P.

2009-04-01

As we know it today air pollution is a release into the atmosphere of any substances, chemicals or particles, which are harmful both to the human and animal health as well as the health of the wider environment. The use of satellite based instruments is a young and developing research field and excellent for studying air pollution events over large areas at high spatial-temporal resolutions, especially when ground measurements, which are limited in spatial-temporal coverage, are not available. Students on postgraduate level should be trained in using, and analysing remote sensing data from both ground and satellite based or in interpreting the high variety in remote sensing e.g satellite images or maps. As follows an e-learning online module has been devised and constructed to facilitate the teaching of Remote Sensing of Troposphere from Space to research students at a Master's level. The module, which is essentially an interactive on-line text book, is stand alone, although it could be encompassed within a standard course management system. The scientific content is presented as study pages under three headings: remote sensing from space, the basics of radiation transfer, and retrieval procedures for tropospheric satellite data.The student is encouraged to test his or her comprehension of the material through exercises on the scientific topics.

Quantitative interpretation of Great Lakes remote sensing data

NASA Technical Reports Server (NTRS)

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

1980-01-01

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

1985 ACSM-ASPRS Fall Convention, Indianapolis, IN, September 8-13, 1985, Technical Papers

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

Not Available

1985-01-01

Papers are presented on Landsat image data quality analysis, primary data acquisition, cartography, geodesy, land surveying, and the applications of satellite remote sensing data. Topics discussed include optical scanning and interactive color graphics; the determination of astrolatitudes and astrolongitudes using x, y, z-coordinates on the celestial sphere; raster-based contour plotting from digital elevation models using minicomputers or microcomputers; the operational techniques of the GPS when utilized as a survey instrument; public land surveying and high technology; the use of multitemporal Landsat MSS data for studying forest cover types; interpretation of satellite and aircraft L-band synthetic aperture radar imagery; geological analysismore » of Landsat MSS data; and an interactive real time digital image processing system. Consideration is given to a large format reconnaissance camera; creating an optimized color balance for TM and MSS imagery; band combination selection for visual interpretation of thematic mapper data for resource management; the effect of spatial filtering on scene noise and boundary detail in thematic mapper imagery; the evaluation of the geometric quality of thematic mapper photographic data; and the analysis and correction of Landsat 4 and 5 thematic mapper sensor data.« less

Remote sensing data applied to the evaluation of soil erosion caused by land-use. Ribeirao Anhumas Basin Area: A case study. [Brazil

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Dosanjosferreirapinto, S.; Kux, H. J. H.

1980-01-01

Formerly covered by a tropical forest, the study area was deforested in the early 40's for coffee plantation and cattle raising, which caused intense gully erosion problems. To develop a method to analyze the relationship between land use and soil erosion, visual interpretations of aerial photographs (scale 1:25.000), MSS-LANDSAT imagery (scale 1:250,000), as well as automatic interpretation of computer compatible tapes by IMAGE-100 system were carried out. From visual interpretation the following data were obtained: land use and cover tapes, slope classes, ravine frequency, and a texture sketch map. During field work, soil samples were collected for texture and X-ray analysis. The texture sketch map indicate that the areas with higher slope angles have a higher susceptibilty to the development of gullies. Also, the over carriage of pastureland, together with very friable lithologies (mainly sandstone) occuring in that area, seem to be the main factors influencing the catastrophic extension of ravines in the study site.

Remote sensing image segmentation based on Hadoop cloud platform

NASA Astrophysics Data System (ADS)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

Efficient Imaging and Real-Time Display of Scanning Ion Conductance Microscopy Based on Block Compressive Sensing

NASA Astrophysics Data System (ADS)

Li, Gongxin; Li, Peng; Wang, Yuechao; Wang, Wenxue; Xi, Ning; Liu, Lianqing

2014-07-01

Scanning Ion Conductance Microscopy (SICM) is one kind of Scanning Probe Microscopies (SPMs), and it is widely used in imaging soft samples for many distinctive advantages. However, the scanning speed of SICM is much slower than other SPMs. Compressive sensing (CS) could improve scanning speed tremendously by breaking through the Shannon sampling theorem, but it still requires too much time in image reconstruction. Block compressive sensing can be applied to SICM imaging to further reduce the reconstruction time of sparse signals, and it has another unique application that it can achieve the function of image real-time display in SICM imaging. In this article, a new method of dividing blocks and a new matrix arithmetic operation were proposed to build the block compressive sensing model, and several experiments were carried out to verify the superiority of block compressive sensing in reducing imaging time and real-time display in SICM imaging.

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

A NDVI assisted remote sensing image adaptive scale segmentation method

NASA Astrophysics Data System (ADS)

Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

2018-03-01

Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

Remote Sensing: Analyzing Satellite Images to Create Higher Order Thinking Skills.

ERIC Educational Resources Information Center

Marks, Steven K.; And Others

1996-01-01

Presents a unit that uses remote-sensing images from satellites and other spacecraft to provide new perspectives of the earth and generate greater global awareness. Relates the levels of Bloom's hierarchy to different aspects of the remote sensing unit to confirm that the concepts and principles of remote sensing and related images belong in…

Superresolution parallel magnetic resonance imaging: Application to functional and spectroscopic imaging

PubMed Central

Otazo, Ricardo; Lin, Fa-Hsuan; Wiggins, Graham; Jordan, Ramiro; Sodickson, Daniel; Posse, Stefan

2009-01-01

Standard parallel magnetic resonance imaging (MRI) techniques suffer from residual aliasing artifacts when the coil sensitivities vary within the image voxel. In this work, a parallel MRI approach known as Superresolution SENSE (SURE-SENSE) is presented in which acceleration is performed by acquiring only the central region of k-space instead of increasing the sampling distance over the complete k-space matrix and reconstruction is explicitly based on intra-voxel coil sensitivity variation. In SURE-SENSE, parallel MRI reconstruction is formulated as a superresolution imaging problem where a collection of low resolution images acquired with multiple receiver coils are combined into a single image with higher spatial resolution using coil sensitivities acquired with high spatial resolution. The effective acceleration of conventional gradient encoding is given by the gain in spatial resolution, which is dictated by the degree of variation of the different coil sensitivity profiles within the low resolution image voxel. Since SURE-SENSE is an ill-posed inverse problem, Tikhonov regularization is employed to control noise amplification. Unlike standard SENSE, for which acceleration is constrained to the phase-encoding dimension/s, SURE-SENSE allows acceleration along all encoding directions — for example, two-dimensional acceleration of a 2D echo-planar acquisition. SURE-SENSE is particularly suitable for low spatial resolution imaging modalities such as spectroscopic imaging and functional imaging with high temporal resolution. Application to echo-planar functional and spectroscopic imaging in human brain is presented using two-dimensional acceleration with a 32-channel receiver coil. PMID:19341804

Remote Sensing Applications with High Reliability in Changjiang Water Resource Management

NASA Astrophysics Data System (ADS)

Ma, L.; Gao, S.; Yang, A.

2018-04-01

Remote sensing technology has been widely used in many fields. But most of the applications cannot get the information with high reliability and high accuracy in large scale, especially for the applications using automatic interpretation methods. We have designed an application-oriented technology system (PIR) composed of a series of accurate interpretation techniques,which can get over 85 % correctness in Water Resource Management from the view of photogrammetry and expert knowledge. The techniques compose of the spatial positioning techniques from the view of photogrammetry, the feature interpretation techniques from the view of expert knowledge, and the rationality analysis techniques from the view of data mining. Each interpreted polygon is accurate enough to be applied to the accuracy sensitive projects, such as the Three Gorge Project and the South - to - North Water Diversion Project. In this paper, we present several remote sensing applications with high reliability in Changjiang Water Resource Management,including water pollution investigation, illegal construction inspection, and water conservation monitoring, etc.

Airborne lidar sensing of massive stony coral colonies on patch reefs in the northern Florida reef tract

USGS Publications Warehouse

Brock, J.C.; Wright, C.W.; Kuffner, I.B.; Hernandez, R.; Thompson, P.

2006-01-01

In this study we examined the ability of the NASA Experimental Advanced Airborne Research Lidar (EAARL) to discriminate cluster zones of massive stony coral colonies on northern Florida reef tract (NFRT) patch reefs based on their topographic complexity (rugosity). Spatially dense EAARL laser submarine topographic soundings acquired in August 2002 were used to create a 1-m resolution digital rugosity map for adjacent NFRT study areas characterized by patch reefs (Region A) and diverse substratums (Region B). In both regions, sites with lidar-sensed rugosities above 1.2 were imaged by an along-track underwater videography system that incorporated the acquisition of instantaneous GPS positions. Subsequent manual interpretation of videotape segments was performed to identify substratum types that caused elevated lidar-sensed rugosity. Our study determined that massive coral colony formation, modified by subsequent physical and biological processes that breakdown patch reef framework, was the primary source of topographic complexity sensed by the EAARL in the NFRT. Sites recognized by lidar scanning to be topographically complex preferentially occurred around the margins of patch reefs, constituted a minor fraction of the reef system, and usually reflected the presence of massive coral colonies in cluster zones, or their derivatives created by mortality, bioerosion, and physical breakdown.

Determining biosonar images using sparse representations.

PubMed

Fontaine, Bertrand; Peremans, Herbert

2009-05-01

Echolocating bats are thought to be able to create an image of their environment by emitting pulses and analyzing the reflected echoes. In this paper, the theory of sparse representations and its more recent further development into compressed sensing are applied to this biosonar image formation task. Considering the target image representation as sparse allows formulation of this inverse problem as a convex optimization problem for which well defined and efficient solution methods have been established. The resulting technique, referred to as L1-minimization, is applied to simulated data to analyze its performance relative to delay accuracy and delay resolution experiments. This method performs comparably to the coherent receiver for the delay accuracy experiments, is quite robust to noise, and can reconstruct complex target impulse responses as generated by many closely spaced reflectors with different reflection strengths. This same technique, in addition to reconstructing biosonar target images, can be used to simultaneously localize these complex targets by interpreting location cues induced by the bat's head related transfer function. Finally, a tentative explanation is proposed for specific bat behavioral experiments in terms of the properties of target images as reconstructed by the L1-minimization method.

Local spatial frequency analysis for computer vision

NASA Technical Reports Server (NTRS)

Krumm, John; Shafer, Steven A.

1990-01-01

A sense of vision is a prerequisite for a robot to function in an unstructured environment. However, real-world scenes contain many interacting phenomena that lead to complex images which are difficult to interpret automatically. Typical computer vision research proceeds by analyzing various effects in isolation (e.g., shading, texture, stereo, defocus), usually on images devoid of realistic complicating factors. This leads to specialized algorithms which fail on real-world images. Part of this failure is due to the dichotomy of useful representations for these phenomena. Some effects are best described in the spatial domain, while others are more naturally expressed in frequency. In order to resolve this dichotomy, we present the combined space/frequency representation which, for each point in an image, shows the spatial frequencies at that point. Within this common representation, we develop a set of simple, natural theories describing phenomena such as texture, shape, aliasing and lens parameters. We show these theories lead to algorithms for shape from texture and for dealiasing image data. The space/frequency representation should be a key aid in untangling the complex interaction of phenomena in images, allowing automatic understanding of real-world scenes.

Restoration of color in a remote sensing image and its quality evaluation

NASA Astrophysics Data System (ADS)

Zhang, Zuxun; Li, Zhijiang; Zhang, Jianqing; Wang, Zhihe

2003-09-01

This paper is focused on the restoration of color remote sensing (including airborne photo). A complete approach is recommended. It propose that two main aspects should be concerned in restoring a remote sensing image, that are restoration of space information, restoration of photometric information. In this proposal, the restoration of space information can be performed by making the modulation transfer function (MTF) as degradation function, in which the MTF is obtained by measuring the edge curve of origin image. The restoration of photometric information can be performed by improved local maximum entropy algorithm. What's more, a valid approach in processing color remote sensing image is recommended. That is splits the color remote sensing image into three monochromatic images which corresponding three visible light bands and synthesizes the three images after being processed separately with psychological color vision restriction. Finally, three novel evaluation variables are obtained based on image restoration to evaluate the image restoration quality in space restoration quality and photometric restoration quality. An evaluation is provided at last.

International Models and Methods of Remote Sensing Education and Training.

ERIC Educational Resources Information Center

Anderson, Paul S.

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

Patient movement characteristics and the impact on CBCT image quality and interpretability.

PubMed

Spin-Neto, Rubens; Costa, Cláudio; Salgado, Daniela Mra; Zambrana, Nataly Rm; Gotfredsen, Erik; Wenzel, Ann

2018-01-01

To assess the impact of patient movement characteristics and metal/radiopaque materials in the field-of-view (FOV) on CBCT image quality and interpretability. 162 CBCT examinations were performed in 134 consecutive (i.e. prospective data collection) patients (age average: 27.2 years; range: 9-73). An accelerometer-gyroscope system registered patient's head position during examination. The threshold for movement definition was set at ≥0.5-mm movement distance based on accelerometer-gyroscope recording. Movement complexity was defined as uniplanar/multiplanar. Three observers scored independently: presence of stripe (i.e. streak) artefacts (absent/"enamel stripes"/"metal stripes"/"movement stripes"), overall unsharpness (absent/present) and image interpretability (interpretable/not interpretable). Kappa statistics assessed interobserver agreement. χ 2 tests analysed whether movement distance, movement complexity and metal/radiopaque material in the FOV affected image quality and image interpretability. Relevant risk factors (p ≤ 0.20) were entered into a multivariate logistic regression analysis with "not interpretable" as the outcome. Interobserver agreement for image interpretability was good (average = 0.65). Movement distance and presence of metal/radiopaque materials significantly affected image quality and interpretability. There were 22-28 cases, in which the observers stated the image was not interpretable. Small movements (i.e. <3 mm) did not significantly affect image interpretability. For movements ≥ 3 mm, the risk that a case was scored as "not interpretable" was significantly (p ≤ 0.05) increased [OR 3.2-11.3; 95% CI (0.70-65.47)]. Metal/radiopaque material was also a significant (p ≤ 0.05) risk factor (OR 3.61-5.05). Patient movement ≥3 mm and metal/radiopaque material in the FOV significantly affected CBCT image quality and interpretability.

Integrating dynamic and distributed compressive sensing techniques to enhance image quality of the compressive line sensing system for unmanned aerial vehicles application

NASA Astrophysics Data System (ADS)

Ouyang, Bing; Hou, Weilin; Caimi, Frank M.; Dalgleish, Fraser R.; Vuorenkoski, Anni K.; Gong, Cuiling

2017-07-01

The compressive line sensing imaging system adopts distributed compressive sensing (CS) to acquire data and reconstruct images. Dynamic CS uses Bayesian inference to capture the correlated nature of the adjacent lines. An image reconstruction technique that incorporates dynamic CS in the distributed CS framework was developed to improve the quality of reconstructed images. The effectiveness of the technique was validated using experimental data acquired in an underwater imaging test facility. Results that demonstrate contrast and resolution improvements will be presented. The improved efficiency is desirable for unmanned aerial vehicles conducting long-duration missions.

An object-based storage model for distributed remote sensing images

NASA Astrophysics Data System (ADS)

Yu, Zhanwu; Li, Zhongmin; Zheng, Sheng

2006-10-01

It is very difficult to design an integrated storage solution for distributed remote sensing images to offer high performance network storage services and secure data sharing across platforms using current network storage models such as direct attached storage, network attached storage and storage area network. Object-based storage, as new generation network storage technology emerged recently, separates the data path, the control path and the management path, which solves the bottleneck problem of metadata existed in traditional storage models, and has the characteristics of parallel data access, data sharing across platforms, intelligence of storage devices and security of data access. We use the object-based storage in the storage management of remote sensing images to construct an object-based storage model for distributed remote sensing images. In the storage model, remote sensing images are organized as remote sensing objects stored in the object-based storage devices. According to the storage model, we present the architecture of a distributed remote sensing images application system based on object-based storage, and give some test results about the write performance comparison of traditional network storage model and object-based storage model.

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

PubMed

Li, Linyi; Xu, Tingbao; Chen, Yun

2017-01-01

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

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

PubMed Central

Xu, Tingbao; Chen, Yun

2017-01-01

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

Research on Method of Interactive Segmentation Based on Remote Sensing Images

NASA Astrophysics Data System (ADS)

Yang, Y.; Li, H.; Han, Y.; Yu, F.

2017-09-01

In this paper, we aim to solve the object extraction problem in remote sensing images using interactive segmentation tools. Firstly, an overview of the interactive segmentation algorithm is proposed. Then, our detailed implementation of intelligent scissors and GrabCut for remote sensing images is described. Finally, several experiments on different typical features (water area, vegetation) in remote sensing images are performed respectively. Compared with the manual result, it indicates that our tools maintain good feature boundaries and show good performance.

A scale-based connected coherence tree algorithm for image segmentation.

PubMed

Ding, Jundi; Ma, Runing; Chen, Songcan

2008-02-01

This paper presents a connected coherence tree algorithm (CCTA) for image segmentation with no prior knowledge. It aims to find regions of semantic coherence based on the proposed epsilon-neighbor coherence segmentation criterion. More specifically, with an adaptive spatial scale and an appropriate intensity-difference scale, CCTA often achieves several sets of coherent neighboring pixels which maximize the probability of being a single image content (including kinds of complex backgrounds). In practice, each set of coherent neighboring pixels corresponds to a coherence class (CC). The fact that each CC just contains a single equivalence class (EC) ensures the separability of an arbitrary image theoretically. In addition, the resultant CCs are represented by tree-based data structures, named connected coherence tree (CCT)s. In this sense, CCTA is a graph-based image analysis algorithm, which expresses three advantages: 1) its fundamental idea, epsilon-neighbor coherence segmentation criterion, is easy to interpret and comprehend; 2) it is efficient due to a linear computational complexity in the number of image pixels; 3) both subjective comparisons and objective evaluation have shown that it is effective for the tasks of semantic object segmentation and figure-ground separation in a wide variety of images. Those images either contain tiny, long and thin objects or are severely degraded by noise, uneven lighting, occlusion, poor illumination, and shadow.

Model-based image analysis of a tethered Brownian fibre for shear stress sensing

PubMed Central

2017-01-01

The measurement of fluid dynamic shear stress acting on a biologically relevant surface is a challenging problem, particularly in the complex environment of, for example, the vasculature. While an experimental method for the direct detection of wall shear stress via the imaging of a synthetic biology nanorod has recently been developed, the data interpretation so far has been limited to phenomenological random walk modelling, small-angle approximation, and image analysis techniques which do not take into account the production of an image from a three-dimensional subject. In this report, we develop a mathematical and statistical framework to estimate shear stress from rapid imaging sequences based firstly on stochastic modelling of the dynamics of a tethered Brownian fibre in shear flow, and secondly on a novel model-based image analysis, which reconstructs fibre positions by solving the inverse problem of image formation. This framework is tested on experimental data, providing the first mechanistically rational analysis of the novel assay. What follows further develops the established theory for an untethered particle in a semi-dilute suspension, which is of relevance to, for example, the study of Brownian nanowires without flow, and presents new ideas in the field of multi-disciplinary image analysis. PMID:29212755

A Low-Power High-Speed Smart Sensor Design for Space Exploration Missions

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi

1997-01-01

A low-power high-speed smart sensor system based on a large format active pixel sensor (APS) integrated with a programmable neural processor for space exploration missions is presented. The concept of building an advanced smart sensing system is demonstrated by a system-level microchip design that is composed with an APS sensor, a programmable neural processor, and an embedded microprocessor in a SOI CMOS technology. This ultra-fast smart sensor system-on-a-chip design mimics what is inherent in biological vision systems. Moreover, it is programmable and capable of performing ultra-fast machine vision processing in all levels such as image acquisition, image fusion, image analysis, scene interpretation, and control functions. The system provides about one tera-operation-per-second computing power which is a two order-of-magnitude increase over that of state-of-the-art microcomputers. Its high performance is due to massively parallel computing structures, high data throughput rates, fast learning capabilities, and advanced VLSI system-on-a-chip implementation.

The spatial resolving power of earth resources satellites: A review

NASA Technical Reports Server (NTRS)

Townshend, J. R. G.

1980-01-01

The significance of spatial resolving power on the utility of current and future Earth resources satellites is critically discussed and the relative merits of different approaches in defining and estimating spatial resolution are outlined. It is shown that choice of a particular measure of spatial resolution depends strongly on the particular needs of the user. Several experiments have simulated the capabilities of future satellite systems by degradation of aircraft images. Surprisingly, many of these indicated that improvements in resolution may lead to a reduction in the classification accuracy of land cover types using computer assisted methods. However, where the frequency of boundary pixels is high, the converse relationship is found. Use of imagery dependent upon visual interpretation is likely to benefit more consistently from higher resolutions. Extraction of information from images will depend upon several other factors apart from spatial resolving power: these include characteristics of the terrain being sensed, the image processing methods that are applied as well as certain sensor characteristics.

Geometric correction of synchronous scanned Operational Modular Imaging Spectrometer II hyperspectral remote sensing images using spatial positioning data of an inertial navigation system

NASA Astrophysics Data System (ADS)

Zhou, Xiaohu; Neubauer, Franz; Zhao, Dong; Xu, Shichao

2015-01-01

The high-precision geometric correction of airborne hyperspectral remote sensing image processing was a hard nut to crack, and conventional methods of remote sensing image processing by selecting ground control points to correct the images are not suitable in the correction process of airborne hyperspectral image. The optical scanning system of an inertial measurement unit combined with differential global positioning system (IMU/DGPS) is introduced to correct the synchronous scanned Operational Modular Imaging Spectrometer II (OMIS II) hyperspectral remote sensing images. Posture parameters, which were synchronized with the OMIS II, were first obtained from the IMU/DGPS. Second, coordinate conversion and flight attitude parameters' calculations were conducted. Third, according to the imaging principle of OMIS II, mathematical correction was applied and the corrected image pixels were resampled. Then, better image processing results were achieved.

Geology of the Shakespeare quadrangle (H03), Mercury

NASA Astrophysics Data System (ADS)

Guzzetta, L.; Galluzzi, V.; Ferranti, L.; Palumbo, P.

2017-09-01

A 1:3M geological map of the H03 Shakespeare quadrangle of Mercury has been compiled through photointerpretation of the remotely sensed images of the NASA MESSENGER mission. This quadrangle is characterized by the occurrence of three main types of plains materials and four basin materials, pertaining to the Caloris basin, the largest impact crater on Mercury's surface. The geologic boundaries have been redefined compared to the previous 1:5M map of the quadrangle and the craters have been classified privileging their stratigraphic order rather than morphological appearance. The abundant tectonic landforms have been interpreted and mapped as thrusts or wrinkle ridges.

When the Eyes Are Shut: The Strange Case of Girolamo Cardano's Idolum in Somniorum Synesiorum Libri IIII (1562).

PubMed

Corrias, Anna

2018-01-01

In his treatise on dreams Somniorum Synesiorum Libri IIII, published in 1562, the Italian Renaissance philosopher and physician Girolamo Cardano distinguishes between idola and visiones (or visa). Historians have discussed the reasons for such a distinction without taking into account Cardano's original theory of sense-perception. In this article I shall argue that, in order to interpret the meaning of idola and visiones in Cardano's theory of dreams, one should bear in mind his view that hearing is superior to sight and that while idola are essentially based on sound, visiones depend on images.

Remote Sensing Image Fusion Method Based on Nonsubsampled Shearlet Transform and Sparse Representation

NASA Astrophysics Data System (ADS)

Moonon, Altan-Ulzii; Hu, Jianwen; Li, Shutao

2015-12-01

The remote sensing image fusion is an important preprocessing technique in remote sensing image processing. In this paper, a remote sensing image fusion method based on the nonsubsampled shearlet transform (NSST) with sparse representation (SR) is proposed. Firstly, the low resolution multispectral (MS) image is upsampled and color space is transformed from Red-Green-Blue (RGB) to Intensity-Hue-Saturation (IHS). Then, the high resolution panchromatic (PAN) image and intensity component of MS image are decomposed by NSST to high and low frequency coefficients. The low frequency coefficients of PAN and the intensity component are fused by the SR with the learned dictionary. The high frequency coefficients of intensity component and PAN image are fused by local energy based fusion rule. Finally, the fused result is obtained by performing inverse NSST and inverse IHS transform. The experimental results on IKONOS and QuickBird satellites demonstrate that the proposed method provides better spectral quality and superior spatial information in the fused image than other remote sensing image fusion methods both in visual effect and object evaluation.

The Joint Agency Commercial Imagery Evaluation (JACIE) Team: Overview and IKONOS Joint Characterization Approach

NASA Technical Reports Server (NTRS)

Zanoni, Vicki; Ryan, Robert; Pagnutti, Mary; Baldridge, Braxton; Roylance, Spencer; Snyder, Greg; Lee, George; Stanley, Tom

2002-01-01

An overview of the Joint Agency Commercial Imagery Evalation (JACIE) team is presented. JACIE, composed of the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA), and the U.S. Geological Survey (USGS), was formed to leverage government agencies' capabilities for the characterization of commercial remote sensing data. Each JACIE agency purchases, or plans to purchase, commercial imagery to support its research and applications. It is critical that the data be assessed for its accuracy and utility. Through JACIE, NASA, NIMA, and USGS jointly characterized image products from Space Imaging's IKONOS satellite. Each JACIE agency performed an aspect of the characterization based on its expertise. NASA and its university partners performed a system characterization focusing on radiometric calibration, geopositional accuracy, and spatial resolution assessment; NIMA performed image interpretability and feature extraction evaluations; and USGS assessed geopositional accuracy of several IKONOS products. The JACIE team purchased IKONOS imagery of several study sites to perform the assessments and presented results at an industry-government workshop. Future plans for JACIE include the characterization of DigitalGlobe's QuickBird-2 image products.

Body Image and Body Experience Disturbances in Schizophrenia: an Attempt to Introduce the Concept of Body Self as a Conceptual Framework.

PubMed

Sakson-Obada, Olga; Chudzikiewicz, Paulina; Pankowski, Daniel; Jarema, Marek

2018-01-01

Disturbances in body experience are described as key schizophrenia symptoms and early disease predictors. In case studies, different disorders relating to body experience are presented, but only a few empirical studies have aimed to distinguish the characteristics of body experience in schizophrenia, and these have been selected arbitrarily and without reference to cohesive theoretical model. To integrate this fragmentary approach, we propose a body self (BS) model, composed of: functions; representations (e.g., body image); and sense of body identity. The aim of the study was to determine whether the BS differentiates schizophrenic patients from healthy controls, and to investigate the relations between aspects of BS and a history of illness and clinical characteristics. The Body Self Questionnaire and the Positive and Negative Syndrome Scale were administered to 63 schizophrenic patients and 63 healthy subjects. The difference was found in the functions of the body-self (perceiving, interpreting, and regulating body experience), in the sense of body identity, and in one of three aspects of body image explored (e.g., acceptance of biological sex). Disturbances in BS were related to positive symptoms and to the number of hospitalizations for other diseases. Together, the results demonstrate that schizophrenia is more body experience than body image disorder, since the negative emotional attitude towards the body and acceptance of fitness were not distinctive for schizophrenia. The link between the disturbances in BS and the number of nonpsychiatric hospitalizations suggests that misinterpretation of body experiences in schizophrenia can promote a search for medical attention.

A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

NASA Astrophysics Data System (ADS)

Shuxin, Li; Zhilong, Zhang; Biao, Li

2018-01-01

Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

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

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

Large Oil Spill Classification Using SAR Images Based on Spatial Histogram

NASA Astrophysics Data System (ADS)

Schvartzman, I.; Havivi, S.; Maman, S.; Rotman, S. R.; Blumberg, D. G.

2016-06-01

Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.

The study of fresh-water lake ice using multiplexed imaging radar

USGS Publications Warehouse

Leonard, Bryan M.; Larson, R.W.

1975-01-01

The study of ice in the upper Great Lakes, both from the operational and the scientific points of view, is receiving continued attention. Quantitative and qualitative field work is being conducted to provide the needed background for accurate interpretation of remotely sensed data. The data under discussion in this paper were obtained by a side-looking multiplexed airborne radar (SLAR) supplemented with ground-truth data.Because of its ability to penetrate adverse weather, radar is an especially important instrument for monitoring ice in the upper Great Lakes. It has previously been shown that imaging radars can provide maps of ice cover in these areas. However, questions concerning both the nature of the surfaces reflecting radar energy and the interpretation of the radar imagery continually arise.Our analysis of ice in Whitefish Bay (Lake Superior) indicates that the combination of the ice/water interlace and the ice/air interface is the major contributor to the radar backscatter as seen on the imagery At these frequencies the ice has a very low relative dielectric permittivity (< 3.0) and a low loss tangent Thus, this ice is somewhat transparent to the energy used by the imaging SLAR system. The ice types studied include newly formed black ice, pancake ice, and frozen and consolidated pack and brash ice.Although ice thickness cannot be measured directly from the received signals, it is suspected that by combining the information pertaining to radar backscatter with data on the meteorological and sea-state history of the area, together with some basic ground truth, better estimates of the ice thickness may be provided. In addition, certain ice features (e.g. ridges, ice-foot formation, areas of brash ice) may be identified with reasonable confidence. There is a continued need for additional ground work to verify the validity of imaging radars for these types of interpretations.

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.

'A real man smells of tobacco smoke'--Chinese youth's interpretation of smoking imagery in film.

PubMed

Davey, Gareth; Zhao, Xiang

2012-05-01

Previous studies have associated youth's exposure to filmic images of smoking with real-life smoking acquisition; initial research in low- and middle-income countries confirms this relationship. The present study in Yunnan, southwest China sought answers to the following questions: How do young people in China make sense of smoking imagery they have seen in film? How are these perceptions shaped by the cultural and social context of images? How do these understandings relate to real-life tobacco use? A study with focus groups and grounded theory was conducted in 2010 and 2011 (Sept-Jan) with middle-school students ages 12 and 13 (n=68, focus groups=12, schools=6). Films and media literacy were important means through which knowledge about smoking was constructed and communicated. Film representations of smoking concurred with Chinese social behaviour (Confucian social networks, face-making, and the notion of society as a harmonious social unit), and were interpreted as congruent with real-life smoking. This pattern, in turn, was intertwined with perceived gender identities of smokers, gender-specific social behaviour, and willingness of girls to explore issues of gender equity. These findings lend new insights into interaction between smoking imagery in film and Chinese youth's smoking beliefs. Tobacco control programs in China should consider young people's interpretations of smoking and the ways they are nested in cultural and social milieu. Copyright © 2012 Elsevier Ltd. All rights reserved.

DOMstudio: an integrated workflow for Digital Outcrop Model reconstruction and interpretation

NASA Astrophysics Data System (ADS)

Bistacchi, Andrea

2015-04-01

Different Remote Sensing technologies, including photogrammetry and LIDAR, allow collecting 3D dataset that can be used to create 3D digital representations of outcrop surfaces, called Digital Outcrop Models (DOM), or sometimes Virtual Outcrop Models (VOM). Irrespective of the Remote Sensing technique used, DOMs can be represented either by photorealistic point clouds (PC-DOM) or textured surfaces (TS-DOM). The first are datasets composed of millions of points with XYZ coordinates and RGB colour, whilst the latter are triangulated surfaces onto which images of the outcrop have been mapped or "textured" (applying a tech-nology originally developed for movies and videogames). Here we present a workflow that allows exploiting in an integrated and efficient, yet flexible way, both kinds of dataset: PC-DOMs and TS-DOMs. The workflow is composed of three main steps: (1) data collection and processing, (2) interpretation, and (3) modelling. Data collection can be performed with photogrammetry, LIDAR, or other techniques. The quality of photogrammetric datasets obtained with Structure From Motion (SFM) techniques has shown a tremendous improvement over the past few years, and this is becoming the more effective way to collect DOM datasets. The main advantages of photogrammetry over LIDAR are represented by the very simple and lightweight field equipment (a digital camera), and by the arbitrary spatial resolution, that can be increased simply getting closer to the out-crop or by using a different lens. It must be noted that concerns about the precision of close-range photogrammetric surveys, that were justified in the past, are no more a problem if modern software and acquisition schemas are applied. In any case, LIDAR is a well-tested technology and it is still very common. Irrespective of the data collection technology, the output will be a photorealistic point cloud and a collection of oriented photos, plus additional imagery in special projects (e.g. infrared images). This dataset can be used as-is (PC-DOM), or a 3D triangulated surface can be interpolated from the point cloud, and images can be used to associate a texture to this surface (TS-DOM). In the DOMstudio workflow we use both PC-DOMs and TS-DOMs. Particularly, the latter are obtained projecting the original images onto the triangulated surface, without any downsampling, thus retaining the original resolution and quality of images collected in the field. In the DOMstudio interpretation step, PC-DOM is considered the best option for fracture analysis in outcrops where facets corresponding to fractures are present. This allows obtaining orientation statistics (e.g. stereoplots, Fisher statistics, etc.) directly from a point cloud where, for each point, the unit vector normal to the outcrop surface has been calculated. A recent development in this kind of processing is represented by the possibility to automatically select (segment) subset point clouds representing single fracture surfaces, which can be used for studies on fracture length, spacing, etc., allowing to obtain parameters like the frequency-length distribution, P21, etc. PC-DOM interpretation can be combined or complemented, depending on the outcrop morphology, with an interpretation carried out on a TS-DOM in terms of traces, which are the linear intersection of "geological" surfaces (fractures, faults, bedding, etc.) with the outcrop surface. This kind of interpretation is very well suited for outcrops with smooth surfaces, and can be performed either by manual picking, or by applying image analysis techniques on the images associated with the DOM. In this case, a huge mass of data, with very high resolution, can be collected very effectively. If we consider applications like lithological or mineral map-ping, TS-DOM datasets are the only suitable support. Finally, the DOMstudio workflow produces output in formats that are compatible with all common geomodelling packages (e.g. Gocad/Skua, Petrel, Move), allowing to directly use the quantitative data collected on DOMs to generate and calibrate geological, structural, or geostatistical models. I will present examples of applications including hydrocarbon reservoir analogue studies, studies on fault zone architecture, lithological mapping on sedimentary and metamorphic rocks, and studies on the surface of planets and small bodies in the Solar System.

The effects of SENSE on PROPELLER imaging.

PubMed

Chang, Yuchou; Pipe, James G; Karis, John P; Gibbs, Wende N; Zwart, Nicholas R; Schär, Michael

2015-12-01

To study how sensitivity encoding (SENSE) impacts periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) image quality, including signal-to-noise ratio (SNR), robustness to motion, precision of motion estimation, and image quality. Five volunteers were imaged by three sets of scans. A rapid method for generating the g-factor map was proposed and validated via Monte Carlo simulations. Sensitivity maps were extrapolated to increase the area over which SENSE can be performed and therefore enhance the robustness to head motion. The precision of motion estimation of PROPELLER blades that are unfolded with these sensitivity maps was investigated. An interleaved R-factor PROPELLER sequence was used to acquire data with similar amounts of motion with and without SENSE acceleration. Two neuroradiologists independently and blindly compared 214 image pairs. The proposed method of g-factor calculation was similar to that provided by the Monte Carlo methods. Extrapolation and rotation of the sensitivity maps allowed for continued robustness of SENSE unfolding in the presence of motion. SENSE-widened blades improved the precision of rotation and translation estimation. PROPELLER images with a SENSE factor of 3 outperformed the traditional PROPELLER images when reconstructing the same number of blades. SENSE not only accelerates PROPELLER but can also improve robustness and precision of head motion correction, which improves overall image quality even when SNR is lost due to acceleration. The reduction of SNR, as a penalty of acceleration, is characterized by the proposed g-factor method. © 2014 Wiley Periodicals, Inc.

Some Defence Applications of Civilian Remote Sensing Satellite Images

DTIC Science & Technology

1993-11-01

This report is on a pilot study to demonstrate some of the capabilities of remote sensing in intelligence gathering. A wide variety of issues, both...colour images. The procedure will be presented in a companion report. Remote sensing , Satellite imagery, Image analysis, Military applications, Military intelligence.

NDSI products system based on Hadoop platform

NASA Astrophysics Data System (ADS)

Zhou, Yan; Jiang, He; Yang, Xiaoxia; Geng, Erhui

2015-12-01

Snow is solid state of water resources on earth, and plays an important role in human life. Satellite remote sensing is significant in snow extraction with the advantages of cyclical, macro, comprehensiveness, objectivity, timeliness. With the continuous development of remote sensing technology, remote sensing data access to the trend of multiple platforms, multiple sensors and multiple perspectives. At the same time, in view of the remote sensing data of compute-intensive applications demand increase gradually. However, current the producing system of remote sensing products is in a serial mode, and this kind of production system is used for professional remote sensing researchers mostly, and production systems achieving automatic or semi-automatic production are relatively less. Facing massive remote sensing data, the traditional serial mode producing system with its low efficiency has been difficult to meet the requirements of mass data timely and efficient processing. In order to effectively improve the production efficiency of NDSI products, meet the demand of large-scale remote sensing data processed timely and efficiently, this paper build NDSI products production system based on Hadoop platform, and the system mainly includes the remote sensing image management module, NDSI production module, and system service module. Main research contents and results including: (1)The remote sensing image management module: includes image import and image metadata management two parts. Import mass basis IRS images and NDSI product images (the system performing the production task output) into HDFS file system; At the same time, read the corresponding orbit ranks number, maximum/minimum longitude and latitude, product date, HDFS storage path, Hadoop task ID (NDSI products), and other metadata information, and then create thumbnails, and unique ID number for each record distribution, import it into base/product image metadata database. (2)NDSI production module: includes the index calculation, production tasks submission and monitoring two parts. Read HDF images related to production task in the form of a byte stream, and use Beam library to parse image byte stream to the form of Product; Use MapReduce distributed framework to perform production tasks, at the same time monitoring task status; When the production task complete, calls remote sensing image management module to store NDSI products. (3)System service module: includes both image search and DNSI products download. To image metadata attributes described in JSON format, return to the image sequence ID existing in the HDFS file system; For the given MapReduce task ID, package several task output NDSI products into ZIP format file, and return to the download link (4)System evaluation: download massive remote sensing data and use the system to process it to get the NDSI products testing the performance, and the result shows that the system has high extendibility, strong fault tolerance, fast production speed, and the image processing results with high accuracy.

Vertical or horizontal orientation of foot radiographs does not affect image interpretation

PubMed Central

Ferran, Nicholas Antonio; Ball, Luke; Maffulli, Nicola

2012-01-01

Summary This study determined whether the orientation of dorsoplantar and oblique foot radiographs has an effect on radiograph interpretation. A test set of 50 consecutive foot radiographs were selected (25 with fractures, and 25 normal), and duplicated in the horizontal orientation. The images were randomly arranged, numbered 1 through 100, and analysed by six image interpreters. Vertical and horizontal area under the ROC curve, accuracy, sensitivity and specificity were calculated for each image interpreter. There was no significant difference in the area under the ROC curve, accuracy, sensitivity or specificity of image interpretation between images viewed in the vertical or horizontal orientation. While conventions for display of radiographs may help to improve the development of an efficient visual search strategy in trainees, and allow for standardisation of publication of radiographic images, variation from the convention in clinical practice does not appear to affect the sensitivity or specificity of image interpretation. PMID:23738310

Compressed Sensing for Body MRI

PubMed Central

Feng, Li; Benkert, Thomas; Block, Kai Tobias; Sodickson, Daniel K; Otazo, Ricardo; Chandarana, Hersh

2016-01-01

The introduction of compressed sensing for increasing imaging speed in MRI has raised significant interest among researchers and clinicians, and has initiated a large body of research across multiple clinical applications over the last decade. Compressed sensing aims to reconstruct unaliased images from fewer measurements than that are traditionally required in MRI by exploiting image compressibility or sparsity. Moreover, appropriate combinations of compressed sensing with previously introduced fast imaging approaches, such as parallel imaging, have demonstrated further improved performance. The advent of compressed sensing marks the prelude to a new era of rapid MRI, where the focus of data acquisition has changed from sampling based on the nominal number of voxels and/or frames to sampling based on the desired information content. This paper presents a brief overview of the application of compressed sensing techniques in body MRI, where imaging speed is crucial due to the presence of respiratory motion along with stringent constraints on spatial and temporal resolution. The first section provides an overview of the basic compressed sensing methodology, including the notion of sparsity, incoherence, and non-linear reconstruction. The second section reviews state-of-the-art compressed sensing techniques that have been demonstrated for various clinical body MRI applications. In the final section, the paper discusses current challenges and future opportunities. PMID:27981664

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.

Global Learning Spectral Archive- A new Way to deal with Unknown Urban Spectra -

NASA Astrophysics Data System (ADS)

Jilge, M.; Heiden, U.; Habermeyer, M.; Jürgens, C.

2015-12-01

Rapid urbanization processes and the need of identifying urban materials demand urban planners and the remote sensing community since years. Urban planners cannot overcome the issue of up-to-date information of urban materials due to time-intensive fieldwork. Hyperspectral remote sensing can facilitate this issue by interpreting spectral signals to provide information of occurring materials. However, the complexity of urban areas and the occurrence of diverse urban materials vary due to regional and cultural aspects as well as the size of a city, which makes identification of surface materials a challenging analysis task. For the various surface material identification approaches, spectral libraries containing pure material spectra are commonly used, which are derived from field, laboratory or the hyperspectral image itself. One of the requirements for successful image analysis is that all spectrally different surface materials are represented by the library. Currently, a universal library, applicable in every urban area worldwide and taking each spectral variability into account, is and will not be existent. In this study, the issue of unknown surface material spectra and the demand of an urban site-specific spectral library is tackled by the development of a learning spectral archive tool. Starting with an incomplete library of labelled image spectra from several German cities, surface materials of pure image pixels will be identified in a hyperspectral image based on a similarity measure (e.g. SID-SAM). Additionally, unknown image spectra of urban objects are identified based on an object- and spectral-based-rule set. The detected unknown surface material spectra are entered with additional metadata, such as regional occurrence into the existing spectral library and thus, are reusable for further studies. Our approach is suitable for pure surface material detection of urban hyperspectral images that is globally applicable by taking incompleteness into account. The generically development enables the implementation of different hyperspectral sensors.

A case of recurrent depressive disorder presenting with Alice in Wonderland syndrome: psychopathology and pre- and post-treatment FDG-PET findings.

PubMed

Yokoyama, Tatsushi; Okamura, Tsuyoshi; Takahashi, Miwako; Momose, Toshimitsu; Kondo, Shinsuke

2017-04-27

Alice in Wonderland syndrome (AIWS) is a rare neuropsychiatric syndrome that typically manifests in distortion of extrapersonal visual image, altered perception of one's body image, and a disturbed sense of the passage of distance and time. Several conditions have been reported to contribute to AIWS, although its biological basis is still unknown. Here, we present the first case demonstrating a clear concurrence of recurrent depressive disorder and AIWS. The clinical manifestations and pre- and post-treatment fluorodeoxyglucose positron-emission tomographic (FDG-PET) images provide insights into the psychopathological and biological basis of AIWS. We describe a 63-year-old Japanese male who developed two distinct episodes of major depression concurrent with AIWS. In addition to typical AIWS perceptual symptoms, he complained of losing the ability to intuitively grasp the seriousness of news and the value of money, which implies disturbance of high-order cognition related to estimating magnitude and worth. Both depression and AIWS remitted after treatment in each episode. Pre-treatment FDG-PET images showed significant hypometabolism in the frontal cortex and hypermetabolism in the occipital and parietal cortex. Post-treatment images showed improvement of these abnormalities. The clinical co-occurrence of depressive episodes and presentation of AIWS can be interpreted to mean that they have certain functional disturbances in common. In view of incapacity, indifference, devitalization, altered perception of one's body image, and disturbed sense of time and space, the features of AIWS analogous to those of psychotic depression imply a common psychopathological basis. These high-order brain dysfunctions are possibly associated with the metabolic abnormalities in visual and parietotemporal association cortices that we observed on the pre- and post-treatment FDG-PET images in this case, while the hypometabolism in the frontal cortex is probably associated with depressive symptoms.

Oleoresin, Chemistry and Spectral Reflectance in "Stressed" Lodgepole and White Bark Pine, Mammoth Mountain, California

NASA Technical Reports Server (NTRS)

Hickey, James C.; Birnie, Richard W.; Zhao, Mei-Xun

2001-01-01

Development of methods to identify the physical and chemical character of materials on the earth's surface is one of the foci of hyperspectral remote sensing activities. Enhancing the ability to elucidate changes in foliar chemistry that relate to the health of a plant is a benefit to plant physiologists, foresters, and plant ecologists, as well as geologist and environmental scientists. Vegetation covers the landscape throughout the temperate and tropical regions of the earth. The existence of vegetation in these areas presents special problems to remote sensing systems since geologic bedrock and alteration zones are masked. At times, however, alterations in the soil/sediment geochemical environment result in foliar chemical changes that are detectable via remote sensing. Examples include monitoring of chlorophyll reflectance/fluorescence and equivalent water thickness indices as indicators of drought-induced plant stress. Another processing and interpretation approach used with hyperspectral data has been principal components analysis (PCA). Rowan et al. used PCA to identify absorption feature patterns obtained from vegetated areas with discrete bedrock geology or mineralization as the substrate. Many researchers highlight the need to advance our ability for hyperspectral imaging in vegetated areas as a near-term priority.

A layered abduction model of perception: Integrating bottom-up and top-down processing in a multi-sense agent

NASA Technical Reports Server (NTRS)

Josephson, John R.

1989-01-01

A layered-abduction model of perception is presented which unifies bottom-up and top-down processing in a single logical and information-processing framework. The process of interpreting the input from each sense is broken down into discrete layers of interpretation, where at each layer a best explanation hypothesis is formed of the data presented by the layer or layers below, with the help of information available laterally and from above. The formation of this hypothesis is treated as a problem of abductive inference, similar to diagnosis and theory formation. Thus this model brings a knowledge-based problem-solving approach to the analysis of perception, treating perception as a kind of compiled cognition. The bottom-up passing of information from layer to layer defines channels of information flow, which separate and converge in a specific way for any specific sense modality. Multi-modal perception occurs where channels converge from more than one sense. This model has not yet been implemented, though it is based on systems which have been successful in medical and mechanical diagnosis and medical test interpretation.

Prevalence of and Risk Factors for Secondary Traumatization in Interpreters for Refugees: A Cross-Sectional Study.

PubMed

Kindermann, David; Schmid, Carolin; Derreza-Greeven, Cassandra; Huhn, Daniel; Kohl, Rupert Maria; Junne, Florian; Schleyer, Maritta; Daniels, Judith K; Ditzen, Beate; Herzog, Wolfgang; Nikendei, Christoph

2017-01-01

A substantial proportion of refugees, fleeing persecution, torture, and war, are estimated to suffer from psychological traumatization. After being sheltered in reception centers, the refugees come in close contact with different occupational groups, e.g., physicians, social workers, and interpreters. Previous studies ascertained that such interpreters themselves often suffer from primary psychological traumatization. Moreover, through translating refugees' potentially traumatic depictions, the interpreters are in danger of developing a so-called secondary traumatization. The present study aimed (1) to analyze the prevalence rates of primary traumatization in interpreters, (2) to assess the prevalence of secondary traumatization, depression, anxiety, and stress symptoms, (3) to examine the association between secondary traumatization symptoms and resilience factors in terms of sense of coherence, social support, and attachment style, and (4) to test whether these resilience factors mediate the relationship between primary and secondary traumatization. Participating interpreters (n = 64) were assessed for past exposure to potentially traumatic events as well as symptoms of posttraumatic stress disorder (PTSD), secondary traumatization, depressive symptoms, anxiety, and subjective stress levels. Furthermore, we conducted psychometric surveys to measure interpreters' sense of coherence, degree of social support, and attachment style as potential predictors. (1) 9% of the interpreters fulfilled all criteria for PTSD and a further 33% had subclinical PTSD; (2) a secondary traumatization was present in 21% of the examined interpreters - of these, 6% showed very high total scores indicating a severe secondary traumatization; furthermore, we found higher scores for depression, anxiety, and stress as compared to representative population samples, especially for females; (3) a present sense of coherence, an existing social support network, and a secure or preoccupied attachment style correlated significantly with low scores for secondary traumatization; and (4) a significant correlation emerged between primary and secondary traumatization (r = 0.595, p < 0.001); a mediation analysis revealed that this effect is partially mediated by secure attachment. A substantial proportion of interpreters working with refugees suffer from primary as well as secondary traumatization. However, high scores for sense of coherence and social support, male gender, and especially a secure attachment style were identified as resilience factors for secondary traumatization. The results may have implications for the selection, training, and supervision of interpreters. © 2017 S. Karger AG, Basel.

The Earth Resources Observation Systems data center's training technical assistance, and applications research activities

USGS Publications Warehouse

Sturdevant, J.A.

1981-01-01

The Earth Resources Observation Systems (EROS) Data Center (EDO, administered by the U.S. Geological Survey, U.S. Department of the Interior, provides remotely sensed data to the user community and offers a variety of professional services to further the understanding and use of remote sensing technology. EDC reproduces and sells photographic and electronic copies of satellite images of areas throughout the world. Other products include aerial photographs collected by 16 organizations, including the U.S. Geological Survey and the National Aeronautics and Space Administration. Primary users of the remotely sensed data are Federal, State, and municipal government agencies, universities, foreign nations, and private industries. The professional services available at EDC are primarily directed at integrating satellite and aircraft remote sensing technology into the programs of the Department of the Interior and its cooperators. This is accomplished through formal training workshops, user assistance, cooperative demonstration projects, and access to equipment and capabilities in an advanced data analysis laboratory. In addition, other Federal agencies, State and local governments, universities, and the general public can get assistance from the EDC Staff. Since 1973, EDC has contributed to the accelerating growth in development and operational use of remotely sensed data for land resource problems through its role as educator and by conducting basic and applied remote sensing applications research. As remote sensing technology continues to evolve, EDC will continue to respond to the increasing demand for timely information on remote sensing applications. Questions most often asked about EDC's research and training programs include: Who may attend an EDC remote sensing training course? Specifically, what is taught? Who may cooperate with EDC on remote sensing projects? Are interpretation services provided on a service basis? This report attempts to define the goals and objectives of and policies on the following EDC services: Training Program.User Assistance.Data Analysis Laboratory.Cooperative Demonstration Projects.Research Projects.

Agile beam laser radar using computational imaging for robotic perception

NASA Astrophysics Data System (ADS)

Powers, Michael A.; Stann, Barry L.; Giza, Mark M.

2015-05-01

This paper introduces a new concept that applies computational imaging techniques to laser radar for robotic perception. We observe that nearly all contemporary laser radars for robotic (i.e., autonomous) applications use pixel basis scanning where there is a one-to-one correspondence between world coordinates and the measurements directly produced by the instrument. In such systems this is accomplished through beam scanning and/or the imaging properties of focal-plane optics. While these pixel-basis measurements yield point clouds suitable for straightforward human interpretation, the purpose of robotic perception is the extraction of meaningful features from a scene, making human interpretability and its attendant constraints mostly unnecessary. The imposing size, weight, power and cost of contemporary systems is problematic, and relief from factors that increase these metrics is important to the practicality of robotic systems. We present a system concept free from pixel basis sampling constraints that promotes efficient and adaptable sensing modes. The cornerstone of our approach is agile and arbitrary beam formation that, when combined with a generalized mathematical framework for imaging, is suited to the particular challenges and opportunities of robotic perception systems. Our hardware concept looks toward future systems with optical device technology closely resembling modern electronically-scanned-array radar that may be years away from practicality. We present the design concept and results from a prototype system constructed and tested in a laboratory environment using a combination of developed hardware and surrogate devices for beam formation. The technological status and prognosis for key components in the system is discussed.

AERIAL PHOTO INTERPRETATION FOR SITE CHARACTERIZATION, ENVIRONMENTAL PHOTOGRAPHIC INTERPRETATION CENTER (EPIC)

EPA Science Inventory

The Environmental Photographic Interpretation Center (EPIC) is a field station of the Landscape Ecology Branch (LEB), Environmental Sciences Division - Las Vegas, Office of Research and Development EPIC provides remote sensing technical support to help the Agency achieve its mult...

THE APPLICATION OF PHOTOGRAPHIC INTERPRETATION AND RELATED TECHNOLOGIES IN MODERN ENVIRONMENTAL PROTECTION

EPA Science Inventory

Imagery Interpretation is a timed-tested technique for extracting landscape-level information from aerial photographs and other types of remotely sensed data. The U.S. Environmental Protection Agency's Environmental Photographic Interpretation Center (EPIC) has a 25+ year history...

Broadband Phase Retrieval for Image-Based Wavefront Sensing

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2007-01-01

A focus-diverse phase-retrieval algorithm has been shown to perform adequately for the purpose of image-based wavefront sensing when (1) broadband light (typically spanning the visible spectrum) is used in forming the images by use of an optical system under test and (2) the assumption of monochromaticity is applied to the broadband image data. Heretofore, it had been assumed that in order to obtain adequate performance, it is necessary to use narrowband or monochromatic light. Some background information, including definitions of terms and a brief description of pertinent aspects of image-based phase retrieval, is prerequisite to a meaningful summary of the present development. Phase retrieval is a general term used in optics to denote estimation of optical imperfections or aberrations of an optical system under test. The term image-based wavefront sensing refers to a general class of algorithms that recover optical phase information, and phase-retrieval algorithms constitute a subset of this class. In phase retrieval, one utilizes the measured response of the optical system under test to produce a phase estimate. The optical response of the system is defined as the image of a point-source object, which could be a star or a laboratory point source. The phase-retrieval problem is characterized as image-based in the sense that a charge-coupled-device camera, preferably of scientific imaging quality, is used to collect image data where the optical system would normally form an image. In a variant of phase retrieval, denoted phase-diverse phase retrieval [which can include focus-diverse phase retrieval (in which various defocus planes are used)], an additional known aberration (or an equivalent diversity function) is superimposed as an aid in estimating unknown aberrations by use of an image-based wavefront-sensing algorithm. Image-based phase-retrieval differs from such other wavefront-sensing methods, such as interferometry, shearing interferometry, curvature wavefront sensing, and Shack-Hartmann sensing, all of which entail disadvantages in comparison with image-based methods. The main disadvantages of these non-image based methods are complexity of test equipment and the need for a wavefront reference.

Remote sensing image ship target detection method based on visual attention model

NASA Astrophysics Data System (ADS)

Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

2017-11-01

The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

The Sensed Presence Questionnaire (SenPQ): initial psychometric validation of a measure of the “Sensed Presence” experience

PubMed Central

Bell, Vaughan

2017-01-01

Background The experience of ‘sensed presence’—a feeling or sense that another entity, individual or being is present despite no clear sensory or perceptual evidence—is known to occur in the general population, appears more frequently in religious or spiritual contexts, and seems to be prominent in certain psychiatric or neurological conditions and may reflect specific functions of social cognition or body-image representation systems in the brain. Previous research has relied on ad-hoc measures of the experience and no specific psychometric scale to measure the experience exists to date. Methods Based on phenomenological description in the literature, we created the 16-item Sensed Presence Questionnaire (SenPQ). We recruited participants from (i) a general population sample, and; (ii) a sample including specific selection for religious affiliation, to complete the SenPQ and additional measures of well-being, schizotypy, social anxiety, social imagery, and spiritual experience. We completed an analysis to test internal reliability, the ability of the SenPQ to distinguish between religious and non-religious participants, and whether the SenPQ was specifically related to positive schizotypical experiences and social imagery. A factor analysis was also conducted to examine underlying latent variables. Results The SenPQ was found to be reliable and valid, with religious participants significantly endorsing more items than non-religious participants, and the scale showing a selective relationship with construct relevant measures. Principal components analysis indicates two potential underlying factors interpreted as reflecting ‘benign’ and ‘malign’ sensed presence experiences. Discussion The SenPQ appears to be a reliable and valid measure of sensed presence experience although further validation in neurological and psychiatric conditions is warranted. PMID:28367379

Biomedical imaging and sensing using flatbed scanners.

PubMed

Göröcs, Zoltán; Ozcan, Aydogan

2014-09-07

In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g., ~600-700 cm(2)) of these devices coupled with their cost-effectiveness provide unique opportunities for digital imaging of samples that are too large for regular optical microscopes, and for collection of large amounts of statistical data in various automated imaging or sensing tasks. Here we give a short introduction to the basic features of flatbed scanners also highlighting the key parameters for designing scientific experiments using these devices, followed by a discussion of some of the significant examples, where scanner-based systems were constructed to conduct various biomedical imaging and/or sensing experiments. Along with mobile phones and other emerging consumer electronics devices, flatbed scanners and their use in advanced imaging and sensing experiments might help us transform current practices of medicine, engineering and sciences through democratization of measurement science and empowerment of citizen scientists, science educators and researchers in resource limited settings.

Biomedical Imaging and Sensing using Flatbed Scanners

PubMed Central

Göröcs, Zoltán; Ozcan, Aydogan

2014-01-01

In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g., ~600–700 cm2) of these devices coupled with their cost-effectiveness provide unique opportunities for digital imaging of samples that are too large for regular optical microscopes, and for collection of large amounts of statistical data in various automated imaging or sensing tasks. Here we give a short introduction to the basic features of flatbed scanners also highlighting the key parameters for designing scientific experiments using these devices, followed by a discussion of some of the significant examples, where scanner-based systems were constructed to conduct various biomedical imaging and/or sensing experiments. Along with mobile phones and other emerging consumer electronics devices, flatbed scanners and their use in advanced imaging and sensing experiments might help us transform current practices of medicine, engineering and sciences through democratization of measurement science and empowerment of citizen scientists, science educators and researchers in resource limited settings. PMID:24965011

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Remote sensing and GIS technology in the Global Land Ice Measurements from Space (GLIMS) Project

USGS Publications Warehouse

Raup, B.; Kääb, Andreas; Kargel, J.S.; Bishop, M.P.; Hamilton, G.; Lee, E.; Paul, F.; Rau, F.; Soltesz, D.; Khalsa, S.J.S.; Beedle, M.; Helm, C.

2007-01-01

Global Land Ice Measurements from Space (GLIMS) is an international consortium established to acquire satellite images of the world's glaciers, analyze them for glacier extent and changes, and to assess these change data in terms of forcings. The consortium is organized into a system of Regional Centers, each of which is responsible for glaciers in their region of expertise. Specialized needs for mapping glaciers in a distributed analysis environment require considerable work developing software tools: terrain classification emphasizing snow, ice, water, and admixtures of ice with rock debris; change detection and analysis; visualization of images and derived data; interpretation and archival of derived data; and analysis to ensure consistency of results from different Regional Centers. A global glacier database has been designed and implemented at the National Snow and Ice Data Center (Boulder, CO); parameters have been expanded from those of the World Glacier Inventory (WGI), and the database has been structured to be compatible with (and to incorporate) WGI data. The project as a whole was originated, and has been coordinated by, the US Geological Survey (Flagstaff, AZ), which has also led the development of an interactive tool for automated analysis and manual editing of glacier images and derived data (GLIMSView). This article addresses remote sensing and Geographic Information Science techniques developed within the framework of GLIMS in order to fulfill the goals of this distributed project. Sample applications illustrating the developed techniques are also shown. ?? 2006 Elsevier Ltd. All rights reserved.

Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.

PubMed

Zhang, Lefei; Zhang, Qian; Du, Bo; Huang, Xin; Tang, Yuan Yan; Tao, Dacheng

2018-01-01

In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier. However, multiple features from various domains definitely have different physical meanings and statistical properties, and thus such concatenation has not efficiently explore the complementary properties among different features, which should benefit for boost the feature discriminability. Furthermore, it is also difficult to interpret the transformed results of the concatenated vector. Consequently, finding a physically meaningful consensus low dimensional feature representation of original multiple features is still a challenging task. In order to address these issues, we propose a novel feature learning framework, i.e., the simultaneous spectral-spatial feature selection and extraction algorithm, for hyperspectral images spectral-spatial feature representation and classification. Specifically, the proposed method learns a latent low dimensional subspace by projecting the spectral-spatial feature into a common feature space, where the complementary information has been effectively exploited, and simultaneously, only the most significant original features have been transformed. Encouraging experimental results on three public available hyperspectral remote sensing datasets confirm that our proposed method is effective and efficient.

In with the new, out with the old? Auto-extraction for remote sensing archaeology

NASA Astrophysics Data System (ADS)

Cowley, David C.

2012-09-01

This paper explores aspects of the inter-relationships between traditional archaeological interpretation of remote sensed data (principally visual examination of aerial photographs/satellite) and those drawing on automated feature extraction and processing. Established approaches to archaeological interpretation of aerial photographs are heavily reliant on individual observation (eye/brain) in an experience and knowledge-based process. Increasingly, however, much more complex and extensive datasets are becoming available to archaeology and these require critical reflection on analytical and interpretative processes. Archaeological applications of Airborne Laser Scanning (ALS) are becoming increasingly routine, and as the spatial resolution of hyper-spectral data improves, its potentially massive implications for archaeological site detection may prove to be a sea-change. These complex datasets demand new approaches, as traditional methods based on direct observation by an archaeological interpreter will never do more than scratch the surface, and will fail to fully extend the boundaries of knowledge. Inevitably, changing analytical and interpretative processes can create tensions, especially, as has been the case in archaeology, when the innovations in data and analysis come from outside the discipline. These tensions often centre on the character of the information produced, and a lack of clarity on the place of archaeological interpretation in the workflow. This is especially true for ALS data and autoextraction techniques, and carries implications for all forms of remote sensed archaeological datasets, including hyperspectral data and aerial photographs.

Passive microwave remote sensing for sea ice research

NASA Technical Reports Server (NTRS)

1984-01-01

Techniques for gathering data by remote sensors on satellites utilized for sea ice research are summarized. Measurement of brightness temperatures by a passive microwave imager converted to maps of total sea ice concentration and to the areal fractions covered by first year and multiyear ice are described. Several ancillary observations, especially by means of automatic data buoys and submarines equipped with upward looking sonars, are needed to improve the validation and interpretation of satellite data. The design and performance characteristics of the Navy's Special Sensor Microwave Imager, expected to be in orbit in late 1985, are described. It is recommended that data from that instrument be processed to a form suitable for research applications and archived in a readily accessible form. The sea ice data products required for research purposes are described and recommendations for their archival and distribution to the scientific community are presented.

Nature and origin of mineral coatings on volcanic rocks of the Black Mountain, Stonewall Mountain and Kane Springs Wash volcanic centers, southern Nevada

NASA Technical Reports Server (NTRS)

Taranik, J. V.; Noble, D. C.; Hsu, L. C.; Hutsinpiller, A.; Spatz, D.

1986-01-01

Surface coatings on volcanic rock assemblages that occur at select tertiary volcanic centers in southern Nevada were investigated using LANDSAT 5 Thematic Mapper imagery. Three project sites comprise the subject of this study: the Kane Springs Wash, Black Mountain, and Stonewall Mountain volcanic centers. LANDSAT 5 TM work scenes selected for each area are outlined along with local area geology. The nature and composition of surface coatings on the rock types within the subproject areas are determined, along with the origin of the coatings and their genetic link to host rocks, geologic interpretations are related to remote sensing units discriminated on TM imagery. Image processing was done using an ESL VAX/IDIMS image processing system, field sampling, and observation. Aerial photographs were acquired to facilitate location on the ground and to aid stratigraphic differentiation.

Regional agriculture surveys using ERTS-1 data

NASA Technical Reports Server (NTRS)

Draeger, W. C.; Nichols, J. D.; Benson, A. S.; Larrabee, D. G.; Jenkus, W. M.; Hay, C. M.

1974-01-01

The Center for Remote Sensing Research has conducted studies designed to evaluate the potential application of ERTS data in performing agricultural inventories, and to develop efficient methods of data handling and analysis useful in the operational context for performing large area surveys. This work has resulted in the development of an integrated system utilizing both human and computer analysis of ground, aerial, and space imagery, which has been shown to be very efficient for regional crop acreage inventories. The technique involves: (1) the delineation of ERTS images into relatively homogeneous strata by human interpreters, (2) the point-by-point classification of the area within each strata on the basis of crop type using a human/machine interactive digital image processing system; and (3) a multistage sampling procedure for the collection of supporting aerial and ground data used in the adjustment and verification of the classification results.

Calibration of AIS Data Using Ground-based Spectral Reflectance Measurements

NASA Technical Reports Server (NTRS)

Conel, J. E.

1985-01-01

Present methods of correcting airborne imaging spectrometer (AIS) data for instrumental and atmospheric effects include the flat- or curved-field correction and a deviation-from-the-average adjustment performed on a line-by-line basis throughout the image. Both methods eliminate the atmospheric absorptions, but remove the possibility of studying the atmosphere for its own sake, or of using the atmospheric information present as a possible basis for theoretical modeling. The method discussed here relies on use of ground-based measurements of the surface spectral reflectance in comparison with scanner data to fix in a least-squares sense parameters in a simplified model of the atmosphere on a wavelength-by-wavelength basis. The model parameters (for optically thin conditions) are interpretable in terms of optical depth and scattering phase function, and thus, in principle, provide an approximate description of the atmosphere as a homogeneous body intervening between the sensor and the ground.

Challenges in rendering Coral Triangle habitat richness in remotely sensed habitat maps: The case of Bunaken Island (Indonesia).

PubMed

Ampou, Eghbert Elvan; Ouillon, Sylvain; Andréfouët, Serge

2018-06-01

The Coral Triangle is the epicenter of marine biodiversity, yet the numbers of habitats that can be found on coral reefs remain poorly described. First surveys for habitat mapping in Indonesia revealed a high number of habitats (>150) even for structurally simple reefs. To be able to represent all these habitats, typical habitat mapping procedures and performances are poorly effective even using very high resolution satellite images. Using Bunaken Island (North Sulawesi, Indonesia) as a case study, we devised a way to maintain all the in situ habitat information in remote sensing habitat map products without loss and with mapping procedures based on photo-interpretation. The result is a product which is consistent with a per-polygon fuzzy classification. As such, it is a complex product that meets our habitat representation goal, but its complexity can also limit its immediate use by managers and conservation planners when analyses per habitat are needed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimized computational imaging methods for small-target sensing in lens-free holographic microscopy

NASA Astrophysics Data System (ADS)

Xiong, Zhen; Engle, Isaiah; Garan, Jacob; Melzer, Jeffrey E.; McLeod, Euan

2018-02-01

Lens-free holographic microscopy is a promising diagnostic approach because it is cost-effective, compact, and suitable for point-of-care applications, while providing high resolution together with an ultra-large field-of-view. It has been applied to biomedical sensing, where larger targets like eukaryotic cells, bacteria, or viruses can be directly imaged without labels, and smaller targets like proteins or DNA strands can be detected via scattering labels like micro- or nano-spheres. Automated image processing routines can count objects and infer target concentrations. In these sensing applications, sensitivity and specificity are critically affected by image resolution and signal-to-noise ratio (SNR). Pixel super-resolution approaches have been shown to boost resolution and SNR by synthesizing a high-resolution image from multiple, partially redundant, low-resolution images. However, there are several computational methods that can be used to synthesize the high-resolution image, and previously, it has been unclear which methods work best for the particular case of small-particle sensing. Here, we quantify the SNR achieved in small-particle sensing using regularized gradient-descent optimization method, where the regularization is based on cardinal-neighbor differences, Bayer-pattern noise reduction, or sparsity in the image. In particular, we find that gradient-descent with sparsity-based regularization works best for small-particle sensing. These computational approaches were evaluated on images acquired using a lens-free microscope that we assembled from an off-the-shelf LED array and color image sensor. Compared to other lens-free imaging systems, our hardware integration, calibration, and sample preparation are particularly simple. We believe our results will help to enable the best performance in lens-free holographic sensing.

Images of a Loving God and Sense of Meaning in Life

ERIC Educational Resources Information Center

Stroope, Samuel; Draper, Scott; Whitehead, Andrew L.

2013-01-01

Although prior studies have documented a positive association between religiosity and sense of meaning in life, the role of specific religious beliefs is currently unclear. Past research on images of God suggests that loving images of God will positively correlate with a sense of meaning and purpose. Mechanisms for this hypothesized relationship…

Polarimetric and Indoor Imaging Fusion Based on Compressive Sensing

DTIC Science & Technology

2013-04-01

Signal Process., vol. 57, no. 6, pp. 2275-2284, 2009. [20] A. Gurbuz, J. McClellan, and W. Scott, Jr., "Compressive sensing for subsurface imaging using...SciTech Publishing, 2010, pp. 922- 938. [45] A. C. Gurbuz, J. H. McClellan, and W. R. Scott, Jr., "Compressive sensing for subsurface imaging using

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

NASA Astrophysics Data System (ADS)

Hong, Liang

2013-10-01

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

Specific coil design for SENSE: a six-element cardiac array.

PubMed

Weiger, M; Pruessmann, K P; Leussler, C; Röschmann, P; Boesiger, P

2001-03-01

In sensitivity encoding (SENSE), the effects of inhomogeneous spatial sensitivity of surface coils are utilized for signal localization in addition to common Fourier encoding using magnetic field gradients. Unlike standard Fourier MRI, SENSE images exhibit an inhomogeneous noise distribution, which crucially depends on the geometrical sensitivity relations of the coils used. Thus, for optimum signal-to-noise-ratio (SNR) and noise homogeneity, specialized coil configurations are called for. In this article we study the implications of SENSE imaging for coil layout by means of simulations and imaging experiments in a phantom and in vivo. New, specific design principles are identified. For SENSE imaging, the elements of a coil array should be smaller than for common phased-array imaging. Furthermore, adjacent coil elements should not overlap. Based on the findings of initial investigations, a configuration of six coils was designed and built specifically for cardiac applications. The in vivo evaluation of this array showed a considerable SNR increase in SENSE images, as compared with a conventional array. Magn Reson Med 45:495-504, 2001. Copyright 2001 Wiley-Liss, Inc.

Secure distribution for high resolution remote sensing images

NASA Astrophysics Data System (ADS)

Liu, Jin; Sun, Jing; Xu, Zheng Q.

2010-09-01

The use of remote sensing images collected by space platforms is becoming more and more widespread. The increasing value of space data and its use in critical scenarios call for adoption of proper security measures to protect these data against unauthorized access and fraudulent use. In this paper, based on the characteristics of remote sensing image data and application requirements on secure distribution, a secure distribution method is proposed, including users and regions classification, hierarchical control and keys generation, and multi-level encryption based on regions. The combination of the three parts can make that the same remote sensing images after multi-level encryption processing are distributed to different permission users through multicast, but different permission users can obtain different degree information after decryption through their own decryption keys. It well meets user access control and security needs in the process of high resolution remote sensing image distribution. The experimental results prove the effectiveness of the proposed method which is suitable for practical use in the secure transmission of remote sensing images including confidential information over internet.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

NASA Astrophysics Data System (ADS)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

Feasibility of 4D flow MR imaging of the brain with either Cartesian y-z radial sampling or k-t SENSE: comparison with 4D Flow MR imaging using SENSE.

PubMed

Sekine, Tetsuro; Amano, Yasuo; Takagi, Ryo; Matsumura, Yoshio; Murai, Yasuo; Kumita, Shinichiro

2014-01-01

A drawback of time-resolved 3-dimensional phase contrast magnetic resonance (4D Flow MR) imaging is its lengthy scan time for clinical application in the brain. We assessed the feasibility for flow measurement and visualization of 4D Flow MR imaging using Cartesian y-z radial sampling and that using k-t sensitivity encoding (k-t SENSE) by comparison with the standard scan using SENSE. Sixteen volunteers underwent 3 types of 4D Flow MR imaging of the brain using a 3.0-tesla scanner. As the standard scan, 4D Flow MR imaging with SENSE was performed first and then followed by 2 types of acceleration scan-with Cartesian y-z radial sampling and with k-t SENSE. We measured peak systolic velocity (PSV) and blood flow volume (BFV) in 9 arteries, and the percentage of particles arriving from the emitter plane at the target plane in 3 arteries, visually graded image quality in 9 arteries, and compared these quantitative and visual data between the standard scan and each acceleration scan. 4D Flow MR imaging examinations were completed in all but one volunteer, who did not undergo the last examination because of headache. Each acceleration scan reduced scan time by 50% compared with the standard scan. The k-t SENSE imaging underestimated PSV and BFV (P < 0.05). There were significant correlations for PSV and BFV between the standard scan and each acceleration scan (P < 0.01). The percentage of particles reaching the target plane did not differ between the standard scan and each acceleration scan. For visual assessment, y-z radial sampling deteriorated the image quality of the 3 arteries. Cartesian y-z radial sampling is feasible for measuring flow, and k-t SENSE offers sufficient flow visualization; both allow acquisition of 4D Flow MR imaging with shorter scan time.

Determination of Movement Sense in Mylonites.

ERIC Educational Resources Information Center

Simpson, Carol

1986-01-01

Describes how mylonite samples can be used to determine the sense of shear. Several sample collection techniques are presented. Criteria for shear sense determination are outlined and discussed so that they can be recognized and interpreted by students familiar with the use of a compass and a petrographic microscope. (TW)

Leadership Metaphors: School Principals' Sense-Making of a National Reform

ERIC Educational Resources Information Center

Schechter, Chen; Shaked, Haim; Ganon-Shilon, Sherry; Goldratt, Miri

2018-01-01

During reforms, principals often experience ambiguity, contradicting demands, and lack of information. As critical change agents and system players, principals interpret reform demands and translate them into school practices through a process of sense-making. The current qualitative research explored 59 elementary school principals' sense-making…

Fully Engaging Students in the Remote Sensing Process through Field Experience

ERIC Educational Resources Information Center

Rundquist, Bradley C.; Vandeberg, Gregory S.

2013-01-01

Field data collection is often crucial to the success of investigations based upon remotely sensed data. Students of environmental remote sensing typically learn about the discipline through classroom lectures, a textbook, and computer laboratory sessions focused on the interpretation and processing of aircraft and satellite data. The importance…

Active and Passive Remote Sensing of Ice.

DTIC Science & Technology

1984-09-01

This is a report on the progress that has been made in the study of active and passive remote sensing of ice during the period of February 1, 1984...the emissivities as functions of viewing angles and polarizations. They are used to interpret the passive microwave remote sensing data from

Science & the Senses: Perceptions & Deceptions

ERIC Educational Resources Information Center

Stansfield, William D.

2012-01-01

Science requires the acquisition and analysis of empirical (sense-derived) data. Given the same physical objects or phenomena, the sense organs of all people do not respond equally to these stimuli, nor do their minds interpret sensory signals identically. Therefore, teachers should develop lectures on human sensory systems that include some…

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%.

Automatically assisting human memory: a SenseCam browser.

PubMed

Doherty, Aiden R; Moulin, Chris J A; Smeaton, Alan F

2011-10-01

SenseCams have many potential applications as tools for lifelogging, including the possibility of use as a memory rehabilitation tool. Given that a SenseCam can log hundreds of thousands of images per year, it is critical that these be presented to the viewer in a manner that supports the aims of memory rehabilitation. In this article we report a software browser constructed with the aim of using the characteristics of memory to organise SenseCam images into a form that makes the wealth of information stored on SenseCam more accessible. To enable a large amount of visual information to be easily and quickly assimilated by a user, we apply a series of automatic content analysis techniques to structure the images into "events", suggest their relative importance, and select representative images for each. This minimises effort when browsing and searching. We provide anecdotes on use of such a system and emphasise the need for SenseCam images to be meaningfully sorted using such a browser.

a Hadoop-Based Distributed Framework for Efficient Managing and Processing Big Remote Sensing Images

NASA Astrophysics Data System (ADS)

Wang, C.; Hu, F.; Hu, X.; Zhao, S.; Wen, W.; Yang, C.

2015-07-01

Various sensors from airborne and satellite platforms are producing large volumes of remote sensing images for mapping, environmental monitoring, disaster management, military intelligence, and others. However, it is challenging to efficiently storage, query and process such big data due to the data- and computing- intensive issues. In this paper, a Hadoop-based framework is proposed to manage and process the big remote sensing data in a distributed and parallel manner. Especially, remote sensing data can be directly fetched from other data platforms into the Hadoop Distributed File System (HDFS). The Orfeo toolbox, a ready-to-use tool for large image processing, is integrated into MapReduce to provide affluent image processing operations. With the integration of HDFS, Orfeo toolbox and MapReduce, these remote sensing images can be directly processed in parallel in a scalable computing environment. The experiment results show that the proposed framework can efficiently manage and process such big remote sensing data.

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.

Remote sensing applied to land-use studies in Wyoming

NASA Technical Reports Server (NTRS)

Breckenridge, R. M.; Marrs, R. W.; Murphy, D. J.

1973-01-01

Impending development of Wyoming's vast fuel resources requires a quick and efficient method of land use inventory and evaluation. Preliminary evaluations of ERTS-1 imagery have shown that physiographic and land use inventory maps can be compiled by using a combination of visual and automated interpretation techniques. Test studies in the Powder River Basin showed that ERTS image interpretations can provide much of the needed physiographic and land use information. Water impoundments as small as one acre were detected and water bodies larger than five acres could be mapped and their acreage estimated. Flood plains and irrigated lands were successfully mapped, and some individual crops were identified and mapped. Coniferous and deciduous trees were mapped separately using color additive analysis on the ERTS multispectral imagery. Gross soil distinctions were made with the ERTS imagery, and were found to be closely related to the bedrock geology. Several broad unstable areas were identified. These were related to specific geologic and slope conditions and generally extended through large regions. Some new oil fields and all large open-cut coal mines were mapped. The most difficult task accomplished was that of mapping urban areas. Work in the urban areas provides a striking example of snow enhancement and the detail available from a snow enhanced image.

POX 4 and Tol 35: Two Peculiar Wolf-Rayet Dwarf Galaxies

NASA Astrophysics Data System (ADS)

Méndez, David I.; Esteban, César

1999-12-01

We present results of narrowband (Hα and adjacent continuum) and broadband (U, B, and V) optical CCD imaging together with high-resolution Hα spectroscopy of the blue compact Wolf-Rayet dwarf galaxies POX 4 and Tol 35. POX 4 has a fainter, irregular, and diffuse companion located 20.5" (4.7 kpc) along the minor axis of the galaxy, which is visible also in the Hα emission. The difference in recession velocity between the galaxy and the companion is about 130 km s-1. The observational results lead us to propose that POX 4 could be interpreted as a low-mass ring galaxy, produced by a head-on intrusion of the fainter companion. Regarding the other object, a spectrum taken along the major axis of Tol 35 shows the coexistence of systems of motion with a velocity difference of about 50 km s-1. Moreover, the deep continuum-subtracted Hα image of the galaxy shows very faint features that resemble the beginning of crossed tidal tails or gaseous filaments powered by the mechanical action of the young stellar population. In this sense, Tol 35 could be interpreted either as an object in an intermediate-stage merging process between two gas-rich dwarf galaxies or as an object suffering the effect of a galactic wind.

LACO-Wiki: A land cover validation tool and a new, innovative teaching resource for remote sensing and the geosciences

NASA Astrophysics Data System (ADS)

See, Linda; Perger, Christoph; Dresel, Christopher; Hofer, Martin; Weichselbaum, Juergen; Mondel, Thomas; Steffen, Fritz

2016-04-01

The validation of land cover products is an important step in the workflow of generating a land cover map from remotely-sensed imagery. Many students of remote sensing will be given exercises on classifying a land cover map followed by the validation process. Many algorithms exist for classification, embedded within proprietary image processing software or increasingly as open source tools. However, there is little standardization for land cover validation, nor a set of open tools available for implementing this process. The LACO-Wiki tool was developed as a way of filling this gap, bringing together standardized land cover validation methods and workflows into a single portal. This includes the storage and management of land cover maps and validation data; step-by-step instructions to guide users through the validation process; sound sampling designs; an easy-to-use environment for validation sample interpretation; and the generation of accuracy reports based on the validation process. The tool was developed for a range of users including producers of land cover maps, researchers, teachers and students. The use of such a tool could be embedded within the curriculum of remote sensing courses at a university level but is simple enough for use by students aged 13-18. A beta version of the tool is available for testing at: http://www.laco-wiki.net.

A new hyperspectral image compression paradigm based on fusion

NASA Astrophysics Data System (ADS)

Guerra, Raúl; Melián, José; López, Sebastián.; Sarmiento, Roberto

2016-10-01

The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.

Investigations of remote sensing techniques for early detection of Dutch elm disease

NASA Technical Reports Server (NTRS)

Hammerschlag, R. S.; Sopstyle, W. J.

1975-01-01

Several forms of aerial photography were pursued in quest of a technique which could provide early detection of Dutch elm disease. The two most promising techniques tested were multispectral photography with object enhancement and biband ratioing coupled with scanning microdensitometry. For practical purposes the multispectral system has the advantage of providing a readily interpretable image in a relatively short time. Laboratory studies indicated that less emphasis should be placed on the use of a red filter or the near infrared beyond 750 mm for early detection of stress within a single plant species. Color infrared film would be optimal when used for a long term detection of loss of plant vigor which results in a physical change in a plant canopy, but should find minimal practicality for early detection of specific sources of plant stress such as Dutch elm disease. Considerable discretion should be used when interpreting imagery on copy film because of loss of resolution and color definition.

LORAKS Makes Better SENSE: Phase-Constrained Partial Fourier SENSE Reconstruction without Phase Calibration

PubMed Central

Kim, Tae Hyung; Setsompop, Kawin; Haldar, Justin P.

2016-01-01

Purpose Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. Theory and Methods The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly-accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely-used calibrationless uniformly-undersampled trajectories. Results Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. Conclusion The SENSE-LORAKS framework provides promising new opportunities for highly-accelerated MRI. PMID:27037836

Coding Strategies and Implementations of Compressive Sensing

NASA Astrophysics Data System (ADS)

Tsai, Tsung-Han

This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others. This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system. Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity. Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-05-25

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-11-23

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Geothermal Prospecting with Remote Sensing and Geographical Information System Technologies in Xilingol Volcanic Field in the Eastern Inner Mongolia, NE China

NASA Astrophysics Data System (ADS)

Peng, F.; Huang, S.; Xiong, Y.; Zhao, Y.; Cheng, Y.

2013-05-01

Geothermal energy is a renewable and low-carbon energy source independent of climate change. It is most abundant in Cenozoic volcanic areas where high temperature can be obtained within a relatively shallow depth. Like other geological resources, geothermal resource prospecting and exploration require a good understanding of the host media. Remote sensing (RS) has the advantages of high spatial and temporal resolution and broad spatial coverage over the conventional geological and geophysical prospecting, while geographical information system (GIS) has intuitive, flexible, and convenient characteristics. In this study, we apply RS and GIS technics in prospecting the geothermal energy potential in Xilingol, a Cenozoic volcanic field in the eastern Inner Mongolia, NE China. Landsat TM/ETM+ multi-temporal images taken under clear-sky conditions, digital elevation model (DEM) data, and other auxiliary data including geological maps of 1:2,500,000 and 1:200,000 scales are used in this study. The land surface temperature (LST) of the study area is retrieved from the Landsat images with the single-channel algorithm on the platform of ENVI developed by ITT Visual Information Solutions. Information of linear and circular geological structure is then extracted from the LST maps and compared to the existing geological data. Several useful technologies such as principal component analysis (PCA), vegetation suppression technique, multi-temporal comparative analysis, and 3D Surface View based on DEM data are used to further enable a better visual geologic interpretation with the Landsat imagery of Xilingol. The Preliminary results show that major faults in the study area are mainly NE and NNE oriented. Several major volcanism controlling faults and Cenozoic volcanic eruption centers have been recognized from the linear and circular structures in the remote images. Seven areas have been identified as potential targets for further prospecting geothermal energy based on the visual interpretation of the geological structures. The study shows that GIS and RS have great application potential in the geothermal exploration in volcanic areas and will promote the exploration of renewable energy resources of great potential.

Searches over graphs representing geospatial-temporal remote sensing data

DOEpatents

Brost, Randolph; Perkins, David Nikolaus

2018-03-06

Various technologies pertaining to identifying objects of interest in remote sensing images by searching over geospatial-temporal graph representations are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Geospatial-temporal graph searches are made computationally efficient by taking advantage of characteristics of geospatial-temporal data in remote sensing images through the application of various graph search techniques.

A parallel method of atmospheric correction for multispectral high spatial resolution remote sensing images

NASA Astrophysics Data System (ADS)

Zhao, Shaoshuai; Ni, Chen; Cao, Jing; Li, Zhengqiang; Chen, Xingfeng; Ma, Yan; Yang, Leiku; Hou, Weizhen; Qie, Lili; Ge, Bangyu; Liu, Li; Xing, Jin

2018-03-01

The remote sensing image is usually polluted by atmosphere components especially like aerosol particles. For the quantitative remote sensing applications, the radiative transfer model based atmospheric correction is used to get the reflectance with decoupling the atmosphere and surface by consuming a long computational time. The parallel computing is a solution method for the temporal acceleration. The parallel strategy which uses multi-CPU to work simultaneously is designed to do atmospheric correction for a multispectral remote sensing image. The parallel framework's flow and the main parallel body of atmospheric correction are described. Then, the multispectral remote sensing image of the Chinese Gaofen-2 satellite is used to test the acceleration efficiency. When the CPU number is increasing from 1 to 8, the computational speed is also increasing. The biggest acceleration rate is 6.5. Under the 8 CPU working mode, the whole image atmospheric correction costs 4 minutes.

Investigating biomass burning aerosol morphology using a laser imaging nephelometer

NASA Astrophysics Data System (ADS)

Manfred, Katherine M.; Washenfelder, Rebecca A.; Wagner, Nicholas L.; Adler, Gabriela; Erdesz, Frank; Womack, Caroline C.; Lamb, Kara D.; Schwarz, Joshua P.; Franchin, Alessandro; Selimovic, Vanessa; Yokelson, Robert J.; Murphy, Daniel M.

2018-02-01

Particle morphology is an important parameter affecting aerosol optical properties that are relevant to climate and air quality, yet it is poorly constrained due to sparse in situ measurements. Biomass burning is a large source of aerosol that generates particles with different morphologies. Quantifying the optical contributions of non-spherical aerosol populations is critical for accurate radiative transfer models, and for correctly interpreting remote sensing data. We deployed a laser imaging nephelometer at the Missoula Fire Sciences Laboratory to sample biomass burning aerosol from controlled fires during the FIREX intensive laboratory study. The laser imaging nephelometer measures the unpolarized scattering phase function of an aerosol ensemble using diode lasers at 375 and 405 nm. Scattered light from the bulk aerosol in the instrument is imaged onto a charge-coupled device (CCD) using a wide-angle field-of-view lens, which allows for measurements at 4-175° scattering angle with ˜ 0.5° angular resolution. Along with a suite of other instruments, the laser imaging nephelometer sampled fresh smoke emissions both directly and after removal of volatile components with a thermodenuder at 250 °C. The total integrated aerosol scattering signal agreed with both a cavity ring-down photoacoustic spectrometer system and a traditional integrating nephelometer within instrumental uncertainties. We compare the measured scattering phase functions at 405 nm to theoretical models for spherical (Mie) and fractal (Rayleigh-Debye-Gans) particle morphologies based on the size distribution reported by an optical particle counter. Results from representative fires demonstrate that particle morphology can vary dramatically for different fuel types. In some cases, the measured phase function cannot be described using Mie theory. This study demonstrates the capabilities of the laser imaging nephelometer instrument to provide realtime, in situ information about dominant particle morphology, which is vital for understanding remote sensing data and accurately describing the aerosol population in radiative transfer calculations.

Wide-Field Imaging Using Nitrogen Vacancies

NASA Technical Reports Server (NTRS)

Englund, Dirk Robert (Inventor); Trusheim, Matthew Edwin (Inventor)

2017-01-01

Nitrogen vacancies in bulk diamonds and nanodiamonds can be used to sense temperature, pressure, electromagnetic fields, and pH. Unfortunately, conventional sensing techniques use gated detection and confocal imaging, limiting the measurement sensitivity and precluding wide-field imaging. Conversely, the present sensing techniques do not require gated detection or confocal imaging and can therefore be used to image temperature, pressure, electromagnetic fields, and pH over wide fields of view. In some cases, wide-field imaging supports spatial localization of the NVs to precisions at or below the diffraction limit. Moreover, the measurement range can extend over extremely wide dynamic range at very high sensitivity.

Geostatistics, remote sensing and precision farming.

PubMed

Mulla, D J

1997-01-01

Precision farming is possible today because of advances in farming technology, procedures for mapping and interpolating spatial patterns, and geographic information systems for overlaying and interpreting several soil, landscape and crop attributes. The key component of precision farming is the map showing spatial patterns in field characteristics. Obtaining information for this map is often achieved by soil sampling. This approach, however, can be cost-prohibitive for grain crops. Soil sampling strategies can be simplified by use of auxiliary data provided by satellite or aerial photo imagery. This paper describes geostatistical methods for estimating spatial patterns in soil organic matter, soil test phosphorus and wheat grain yield from a combination of Thematic Mapper imaging and soil sampling.

Natural Resource Information System. Remote Sensing Studies.

ERIC Educational Resources Information Center

Leachtenauer, J.; And Others

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

Feasibility study ASCS remote sensing/compliance determination system

NASA Technical Reports Server (NTRS)

Duggan, I. E.; Minter, T. C., Jr.; Moore, B. H.; Nosworthy, C. T.

1973-01-01

A short-term technical study was performed by the MSC Earth Observations Division to determine the feasibility of the proposed Agricultural Stabilization and Conservation Service Automatic Remote Sensing/Compliance Determination System. For the study, the term automatic was interpreted as applying to an automated remote-sensing system that includes data acquisition, processing, and management.

Remote-sensing image encryption in hybrid domains

NASA Astrophysics Data System (ADS)

Zhang, Xiaoqiang; Zhu, Guiliang; Ma, Shilong

2012-04-01

Remote-sensing technology plays an important role in military and industrial fields. Remote-sensing image is the main means of acquiring information from satellites, which always contain some confidential information. To securely transmit and store remote-sensing images, we propose a new image encryption algorithm in hybrid domains. This algorithm makes full use of the advantages of image encryption in both spatial domain and transform domain. First, the low-pass subband coefficients of image DWT (discrete wavelet transform) decomposition are sorted by a PWLCM system in transform domain. Second, the image after IDWT (inverse discrete wavelet transform) reconstruction is diffused with 2D (two-dimensional) Logistic map and XOR operation in spatial domain. The experiment results and algorithm analyses show that the new algorithm possesses a large key space and can resist brute-force, statistical and differential attacks. Meanwhile, the proposed algorithm has the desirable encryption efficiency to satisfy requirements in practice.

Improving Landslide Susceptibility Modeling Using an Empirical Threshold Scheme for Excluding Landslide Deposition

NASA Astrophysics Data System (ADS)

Tsai, F.; Lai, J. S.; Chiang, S. H.

2015-12-01

Landslides are frequently triggered by typhoons and earthquakes in Taiwan, causing serious economic losses and human casualties. Remotely sensed images and geo-spatial data consisting of land-cover and environmental information have been widely used for producing landslide inventories and causative factors for slope stability analysis. Landslide susceptibility, on the other hand, can represent the spatial likelihood of landslide occurrence and is an important basis for landslide risk assessment. As multi-temporal satellite images become popular and affordable, they are commonly used to generate landslide inventories for subsequent analysis. However, it is usually difficult to distinguish different landslide sub-regions (scarp, debris flow, deposition etc.) directly from remote sensing imagery. Consequently, the extracted landslide extents using image-based visual interpretation and automatic detections may contain many depositions that may reduce the fidelity of the landslide susceptibility model. This study developed an empirical thresholding scheme based on terrain characteristics for eliminating depositions from detected landslide areas to improve landslide susceptibility modeling. In this study, Bayesian network classifier is utilized to build a landslide susceptibility model and to predict sequent rainfall-induced shallow landslides in the Shimen reservoir watershed located in northern Taiwan. Eleven causative factors are considered, including terrain slope, aspect, curvature, elevation, geology, land-use, NDVI, soil, distance to fault, river and road. Landslide areas detected using satellite images acquired before and after eight typhoons between 2004 to 2008 are collected as the main inventory for training and verification. In the analysis, previous landslide events are used as training data to predict the samples of the next event. The results are then compared with recorded landslide areas in the inventory to evaluate the accuracy. Experimental results demonstrate that the accuracies of landslide susceptibility analysis in all sequential predictions have been improved significantly after eliminating landslide depositions.

An L1-norm phase constraint for half-Fourier compressed sensing in 3D MR imaging.

PubMed

Li, Guobin; Hennig, Jürgen; Raithel, Esther; Büchert, Martin; Paul, Dominik; Korvink, Jan G; Zaitsev, Maxim

2015-10-01

In most half-Fourier imaging methods, explicit phase replacement is used. In combination with parallel imaging, or compressed sensing, half-Fourier reconstruction is usually performed in a separate step. The purpose of this paper is to report that integration of half-Fourier reconstruction into iterative reconstruction minimizes reconstruction errors. The L1-norm phase constraint for half-Fourier imaging proposed in this work is compared with the L2-norm variant of the same algorithm, with several typical half-Fourier reconstruction methods. Half-Fourier imaging with the proposed phase constraint can be seamlessly combined with parallel imaging and compressed sensing to achieve high acceleration factors. In simulations and in in-vivo experiments half-Fourier imaging with the proposed L1-norm phase constraint enables superior performance both reconstruction of image details and with regard to robustness against phase estimation errors. The performance and feasibility of half-Fourier imaging with the proposed L1-norm phase constraint is reported. Its seamless combination with parallel imaging and compressed sensing enables use of greater acceleration in 3D MR imaging.

Design of Restoration Method Based on Compressed Sensing and TwIST Algorithm

NASA Astrophysics Data System (ADS)

Zhang, Fei; Piao, Yan

2018-04-01

In order to improve the subjective and objective quality of degraded images at low sampling rates effectively,save storage space and reduce computational complexity at the same time, this paper proposes a joint restoration algorithm of compressed sensing and two step iterative threshold shrinkage (TwIST). The algorithm applies the TwIST algorithm which used in image restoration to the compressed sensing theory. Then, a small amount of sparse high-frequency information is obtained in frequency domain. The TwIST algorithm based on compressed sensing theory is used to accurately reconstruct the high frequency image. The experimental results show that the proposed algorithm achieves better subjective visual effects and objective quality of degraded images while accurately restoring degraded images.

Active machine learning for rapid landslide inventory mapping with VHR satellite images (Invited)

NASA Astrophysics Data System (ADS)

Stumpf, A.; Lachiche, N.; Malet, J.; Kerle, N.; Puissant, A.

2013-12-01

VHR satellite images have become a primary source for landslide inventory mapping after major triggering events such as earthquakes and heavy rainfalls. Visual image interpretation is still the prevailing standard method for operational purposes but is time-consuming and not well suited to fully exploit the increasingly better supply of remote sensing data. Recent studies have addressed the development of more automated image analysis workflows for landslide inventory mapping. In particular object-oriented approaches that account for spatial and textural image information have been demonstrated to be more adequate than pixel-based classification but manually elaborated rule-based classifiers are difficult to adapt under changing scene characteristics. Machine learning algorithm allow learning classification rules for complex image patterns from labelled examples and can be adapted straightforwardly with available training data. In order to reduce the amount of costly training data active learning (AL) has evolved as a key concept to guide the sampling for many applications. The underlying idea of AL is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and data structure to iteratively select the most valuable samples that should be labelled by the user. With relatively few queries and labelled samples, an AL strategy yields higher accuracies than an equivalent classifier trained with many randomly selected samples. This study addressed the development of an AL method for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. Our approach [1] is based on the Random Forest algorithm and considers the classifier uncertainty as well as the variance of potential sampling regions to guide the user towards the most valuable sampling areas. The algorithm explicitly searches for compact regions and thereby avoids a spatially disperse sampling pattern inherent to most other AL methods. The accuracy, the sampling time and the computational runtime of the algorithm were evaluated on multiple satellite images capturing recent large scale landslide events. Sampling between 1-4% of the study areas the accuracies between 74% and 80% were achieved, whereas standard sampling schemes yielded only accuracies between 28% and 50% with equal sampling costs. Compared to commonly used point-wise AL algorithm the proposed approach significantly reduces the number of iterations and hence the computational runtime. Since the user can focus on relatively few compact areas (rather than on hundreds of distributed points) the overall labeling time is reduced by more than 50% compared to point-wise queries. An experimental evaluation of multiple expert mappings demonstrated strong relationships between the uncertainties of the experts and the machine learning model. It revealed that the achieved accuracies are within the range of the inter-expert disagreement and that it will be indispensable to consider ground truth uncertainties to truly achieve further enhancements in the future. The proposed method is generally applicable to a wide range of optical satellite images and landslide types. [1] A. Stumpf, N. Lachiche, J.-P. Malet, N. Kerle, and A. Puissant, Active learning in the spatial domain for remote sensing image classification, IEEE Transactions on Geosciece and Remote Sensing. 2013, DOI 10.1109/TGRS.2013.2262052.

Development of a fusion approach selection tool

NASA Astrophysics Data System (ADS)

Pohl, C.; Zeng, Y.

2015-06-01

During the last decades number and quality of available remote sensing satellite sensors for Earth observation has grown significantly. The amount of available multi-sensor images along with their increased spatial and spectral resolution provides new challenges to Earth scientists. With a Fusion Approach Selection Tool (FAST) the remote sensing community would obtain access to an optimized and improved image processing technology. Remote sensing image fusion is a mean to produce images containing information that is not inherent in the single image alone. In the meantime the user has access to sophisticated commercialized image fusion techniques plus the option to tune the parameters of each individual technique to match the anticipated application. This leaves the operator with an uncountable number of options to combine remote sensing images, not talking about the selection of the appropriate images, resolution and bands. Image fusion can be a machine and time-consuming endeavour. In addition it requires knowledge about remote sensing, image fusion, digital image processing and the application. FAST shall provide the user with a quick overview of processing flows to choose from to reach the target. FAST will ask for available images, application parameters and desired information to process this input to come out with a workflow to quickly obtain the best results. It will optimize data and image fusion techniques. It provides an overview on the possible results from which the user can choose the best. FAST will enable even inexperienced users to use advanced processing methods to maximize the benefit of multi-sensor image exploitation.

Remote sensing, imaging, and signal engineering

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

Brase, J.M.

1993-03-01

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

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

DTIC Science & Technology

2016-10-22

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

First results of ground-based LWIR hyperspectral imaging remote gas detection

NASA Astrophysics Data System (ADS)

Zheng, Wei-jian; Lei, Zheng-gang; Yu, Chun-chao; Wang, Hai-yang; Fu, Yan-peng; Liao, Ning-fang; Su, Jun-hong

2014-11-01

The new progress of ground-based long-wave infrared remote sensing is presented. The LWIR hyperspectral imaging by using the windowing spatial and temporal modulation Fourier spectroscopy, and the results of outdoor ether gas detection, verify the features of LWIR hyperspectral imaging remote sensing and technical approach. It provides a new technical means for ground-based gas remote sensing.

Tradeoff between picture element dimensions and noncoherent averaging in side-looking airborne radar

NASA Technical Reports Server (NTRS)

Moore, R. K.

1979-01-01

An experiment was performed in which three synthetic-aperture images and one real-aperture image were successively degraded in spatial resolution, both retaining the same number of independent samples per pixel and using the spatial degradation to allow averaging of different numbers of independent samples within each pixel. The original and degraded images were provided to three interpreters familiar with both aerial photographs and radar images. The interpreters were asked to grade each image in terms of their ability to interpret various specified features on the image. The numerical interpretability grades were then used as a quantitative measure of the utility of the different kinds of image processing and different resolutions. The experiment demonstrated empirically that the interpretability is related exponentially to the SGL volume which is the product of azimuth, range, and gray-level resolution.

Mapping three-dimensional geological features from remotely-sensed images and digital elevation models

NASA Astrophysics Data System (ADS)

Morris, Kevin Peter

Accurate mapping of geological structures is important in numerous applications, ranging from mineral exploration through to hydrogeological modelling. Remotely sensed data can provide synoptic views of study areas enabling mapping of geological units within the area. Structural information may be derived from such data using standard manual photo-geologic interpretation techniques, although these are often inaccurate and incomplete. The aim of this thesis is, therefore, to compile a suite of automated and interactive computer-based analysis routines, designed to help a the user map geological structure. These are examined and integrated in the context of an expert system. The data used in this study include Digital Elevation Model (DEM) and Airborne Thematic Mapper images, both with a spatial resolution of 5m, for a 5 x 5 km area surrounding Llyn Cow lyd, Snowdonia, North Wales. The geology of this area comprises folded and faulted Ordo vician sediments intruded throughout by dolerite sills, providing a stringent test for the automated and semi-automated procedures. The DEM is used to highlight geomorphological features which may represent surface expressions of the sub-surface geology. The DEM is created from digitized contours, for which kriging is found to provide the best interpolation routine, based on a number of quantitative measures. Lambertian shading and the creation of slope and change of slope datasets are shown to provide the most successful enhancement of DEMs, in terms of highlighting a range of key geomorphological features. The digital image data are used to identify rock outcrops as well as lithologically controlled features in the land cover. To this end, a series of standard spectral enhancements of the images is examined. In this respect, the least correlated 3 band composite and a principal component composite are shown to give the best visual discrimination of geological and vegetation cover types. Automatic edge detection (followed by line thinning and extraction) and manual interpretation techniques are used to identify a set of 'geological primitives' (linear or arc features representing lithological boundaries) within these data. Inclusion of the DEM data provides the three-dimensional co-ordinates of these primitives enabling a least-squares fit to be employed to calculate dip and strike values, based, initially, on the assumption of a simple, linearly dipping structural model. A very large number of scene 'primitives' is identified using these procedures, only some of which have geological significance. Knowledge-based rules are therefore used to identify the relevant. For example, rules are developed to identify lake edges, forest boundaries, forest tracks, rock-vegetation boundaries, and areas of geomorphological interest. Confidence in the geological significance of some of the geological primitives is increased where they are found independently in both the DEM and remotely sensed data. The dip and strike values derived in this way are compared to information taken from the published geological map for this area, as well as measurements taken in the field. Many results are shown to correspond closely to those taken from the map and in the field, with an error of < 1°. These data and rules are incorporated into an expert system which, initially, produces a simple model of the geological structure. The system also provides a graphical user interface for manual control and interpretation, where necessary. Although the system currently only allows a relatively simple structural model (linearly dipping with faulting), in the future it will be possible to extend the system to model more complex features, such as anticlines, synclines, thrusts, nappes, and igneous intrusions.

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.

Fast imaging of laboratory core floods using 3D compressed sensing RARE MRI.

PubMed

Ramskill, N P; Bush, I; Sederman, A J; Mantle, M D; Benning, M; Anger, B C; Appel, M; Gladden, L F

2016-09-01

Three-dimensional (3D) imaging of the fluid distributions within the rock is essential to enable the unambiguous interpretation of core flooding data. Magnetic resonance imaging (MRI) has been widely used to image fluid saturation in rock cores; however, conventional acquisition strategies are typically too slow to capture the dynamic nature of the displacement processes that are of interest. Using Compressed Sensing (CS), it is possible to reconstruct a near-perfect image from significantly fewer measurements than was previously thought necessary, and this can result in a significant reduction in the image acquisition times. In the present study, a method using the Rapid Acquisition with Relaxation Enhancement (RARE) pulse sequence with CS to provide 3D images of the fluid saturation in rock core samples during laboratory core floods is demonstrated. An objective method using image quality metrics for the determination of the most suitable regularisation functional to be used in the CS reconstructions is reported. It is shown that for the present application, Total Variation outperforms the Haar and Daubechies3 wavelet families in terms of the agreement of their respective CS reconstructions with a fully-sampled reference image. Using the CS-RARE approach, 3D images of the fluid saturation in the rock core have been acquired in 16min. The CS-RARE technique has been applied to image the residual water saturation in the rock during a water-water displacement core flood. With a flow rate corresponding to an interstitial velocity of vi=1.89±0.03ftday(-1), 0.1 pore volumes were injected over the course of each image acquisition, a four-fold reduction when compared to a fully-sampled RARE acquisition. Finally, the 3D CS-RARE technique has been used to image the drainage of dodecane into the water-saturated rock in which the dynamics of the coalescence of discrete clusters of the non-wetting phase are clearly observed. The enhancement in the temporal resolution that has been achieved using the CS-RARE approach enables dynamic transport processes pertinent to laboratory core floods to be investigated in 3D on a time-scale and with a spatial resolution that, until now, has not been possible. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Interpretation of Radiological Images: Towards a Framework of Knowledge and Skills

ERIC Educational Resources Information Center

van der Gijp, A.; van der Schaaf, M. F.; van der Schaaf, I. C.; Huige, J. C. B. M.; Ravesloot, C. J.; van Schaik, J. P. J.; ten Cate, Th. J.

2014-01-01

The knowledge and skills that are required for radiological image interpretation are not well documented, even though medical imaging is gaining importance. This study aims to develop a comprehensive framework of knowledge and skills, required for two-dimensional and multiplanar image interpretation in radiology. A mixed-method study approach was…

Experimental Sea Slicks in the Marsen (Maritime Remote Sensing) Exercise.

DTIC Science & Technology

1980-10-30

Experimental slicks with various surface properties were generated in the North Sea as part of the MARSEN (Maritime Remote Sensing ) exercise. The one...with remote sensing instrumentation. Because of the numerous effects of surface films on air-sea interfacial processes, these experiments were designed...information was obtained on the influence of sea surface films on the interpretation of signals received by remote sensing systems. Criteria for the

A fully automatic tool to perform accurate flood mapping by merging remote sensing imagery and ancillary data

NASA Astrophysics Data System (ADS)

D'Addabbo, Annarita; Refice, Alberto; Lovergine, Francesco; Pasquariello, Guido

2016-04-01

Flooding is one of the most frequent and expansive natural hazard. High-resolution flood mapping is an essential step in the monitoring and prevention of inundation hazard, both to gain insight into the processes involved in the generation of flooding events, and from the practical point of view of the precise assessment of inundated areas. Remote sensing data are recognized to be useful in this respect, thanks to the high resolution and regular revisit schedules of state-of-the-art satellites, moreover offering a synoptic overview of the extent of flooding. In particular, Synthetic Aperture Radar (SAR) data present several favorable characteristics for flood mapping, such as their relative insensitivity to the meteorological conditions during acquisitions, as well as the possibility of acquiring independently of solar illumination, thanks to the active nature of the radar sensors [1]. However, flood scenarios are typical examples of complex situations in which different factors have to be considered to provide accurate and robust interpretation of the situation on the ground: the presence of many land cover types, each one with a particular signature in presence of flood, requires modelling the behavior of different objects in the scene in order to associate them to flood or no flood conditions [2]. Generally, the fusion of multi-temporal, multi-sensor, multi-resolution and/or multi-platform Earth observation image data, together with other ancillary information, seems to have a key role in the pursuit of a consistent interpretation of complex scenes. In the case of flooding, distance from the river, terrain elevation, hydrologic information or some combination thereof can add useful information to remote sensing data. Suitable methods, able to manage and merge different kind of data, are so particularly needed. In this work, a fully automatic tool, based on Bayesian Networks (BNs) [3] and able to perform data fusion, is presented. It supplies flood maps describing the dynamics of each analysed event, combining time series of images, acquired by different sensors, with ancillary information. Some experiments have been performed by combining multi-temporal SAR intensity images, InSAR coherence and optical data, with geomorphic and other ground information. The tool has been tested on different flood events occurred in the Basilicata region (Italy) during the last years, showing good capabilities of identification of a large area interested by the flood phenomenon, partially overcoming the obstacle constituted by the presence of scattering/coherence classes corresponding to different land cover types, which respond differently to the presence of water and to inundation evolution [1] A. Refice et al, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 7, pp. 2711-2722, 2014. [2] L. Pulvirenti et al., IEEE Trans. Geosci. Rem. Sens., Vol. PP, pp. 1- 13, 2015. [3] A. D'Addabbo et al., "A Bayesian Network for Flood Detection combining SAR Imagery and Ancillary Data," IEEE Trans. Geosci. Rem. Sens., in press.

Oblique synoptic images, produced from digital data, display strong evidence of a "new" caldera in southwestern Guatemala

USGS Publications Warehouse

Duffield, W.; Heiken, G.; Foley, D.; McEwen, A.

1993-01-01

The synoptic view of broad regions of the Earth's surface as displayed in Landsat and other satellite images has greatly aided in the recognition of calderas, ignimbrite plateaus and other geologic landforms. Remote-sensing images that include visual representation of depth are an even more powerful tool for geologic interpretation of landscapes, but their use has been largely restricted to the exploration of planets other than Earth. By combining Landsat images with digitized topography, we have generated regional oblique views that display compelling evidence for a previously undocumented late-Cenozoic caldera within the active volcanic zone of southwestern Guatemala. This "new" caldera, herein called Xela, is a depression about 30 km wide and 400-600 m deep, which includes the Quezaltenango basin. The caldera depression is breached only by a single river canyon. The caldera outline is broadly circular, but a locally scalloped form suggests the occurrence of multiple caldera-collapse events, or local slumping of steep caldera walls, or both. Within its northern part, Xela caldera contains a toreva block, about 500 m high and 2 km long, that may be incompletely foundered pre-caldera bedrock. Xela contains several post-caldera volcanoes, some of which are active. A Bouguer gravity low, tens of milligals in amplitude, is approximately co-located with the proposed caldera. The oblique images also display an extensive plateau that dips about 2?? away from the north margin of Xela caldera. We interpret this landform to be underlain by pyroclastic outflow from Xela and nearby Atitla??n calderas. Field mapping by others has documented a voluminous rhyolitic pumiceous fallout deposit immediately east of Xela caldera. We speculate that Xela caldera was the source of this deposit. If so, the age of at least part of the caldera is between about 84 ka and 126 ka, the ages of deposits that stratigraphically bracket this fallout. Most of the floor of Xela caldera is covered with Los Chocoyos pyroclastics, 84-ka deposits erupted from Atitla??n caldera. Oblique images produced from digital data are unique tools that can greatly facilitate initial geologic interpretation of morphologically young volcanic (and other) terrains where field access is limited, especially because conventional visual representations commonly lack depth perspective and may cover only part of the region of interest. ?? 1993.

Common-Path Wavefront Sensing for Advanced Coronagraphs

NASA Technical Reports Server (NTRS)

Wallace, J. Kent; Serabyn, Eugene; Mawet, Dimitri

2012-01-01

Imaging of faint companions around nearby stars is not limited by either intrinsic resolution of a coronagraph/telescope system, nor is it strictly photon limited. Typically, it is both the magnitude and temporal variation of small phase and amplitude errors imparted to the electric field by elements in the optical system which will limit ultimate performance. Adaptive optics systems, particularly those with multiple deformable mirrors, can remove these errors, but they need to be sensed in the final image plane. If the sensing system is before the final image plane, which is typical for most systems, then the non-common path optics between the wavefront sensor and science image plane will lead to un-sensed errors. However, a new generation of high-performance coronagraphs naturally lend themselves to wavefront sensing in the final image plane. These coronagraphs and the wavefront sensing will be discussed, as well as plans for demonstrating this with a high-contrast system on the ground. Such a system will be a key system-level proof for a future space-based coronagraph mission, which will also be discussed.

LORAKS makes better SENSE: Phase-constrained partial fourier SENSE reconstruction without phase calibration.

PubMed

Kim, Tae Hyung; Setsompop, Kawin; Haldar, Justin P

2017-03-01

Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely used calibrationless uniformly undersampled trajectories. Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. The SENSE-LORAKS framework provides promising new opportunities for highly accelerated MRI. Magn Reson Med 77:1021-1035, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Oil Spill AISA+ Hyperspectral Data Detection Based on Different Sea Surface Glint Suppression Methods

NASA Astrophysics Data System (ADS)

Yang, J.; Ren, G.; Ma, Y.; Dong, L.; Wan, J.

2018-04-01

The marine oil spill is a sudden event, and the airborne hyperspectral means to detect the oil spill is an important part of the rapid response. Sun glint, the specular reflection of sun light from water surface to sensor, is inevitable due to the limitation of observation geometry, which makes so much bright glint in image that it is difficult to extract oil spill feature information from the remote sensing data. This paper takes AISA+ airborne hyperspectral oil spill image as data source, using multi-scale wavelet transform, enhanced Lee filter, enhanced Frost filter and mean filter method for sea surface glint suppression of images. And then the classical SVM method is used for the oil spill information detection, and oil spill information distribution map obtained by human-computer interactive interpretation is used to verify the accuracy of oil spill detection. The results show that the above methods can effectively suppress the sea surface glints and improve the accuracy of oil spill detection. The enhanced Lee filter method has the highest detection accuracy of 88.28 %, which is 12.2 % higher than that of the original image.

A case study of comparing radiometrically calibrated reflectance of an image mosaic from unmanned aerial system with that of a single image from manned aircraft over a same area

USDA-ARS?s Scientific Manuscript database

Although conventional high-altitude airborne remote sensing and low-altitude unmanned aerial system (UAS) based remote sensing share many commonalities, one of the major differences between the two remote sensing platforms is that the latter has much smaller image footprint. To cover the same area o...

ERTS data user investigation to develop a multistage forest sampling inventory system

NASA Technical Reports Server (NTRS)

Langley, P. G.; Vanroessel, J. W. (Principal Investigator); Wert, S. L.

1973-01-01

The author has identified the following significant results. A system to provide precision annotation of predetermined forest inventory sampling units on the ERTS-1 MSS images was developed. In addition, an annotation system for high altitude U2 photographs was completed. MSS bulk image accuracy is good enough to allow the use of one square mile sampling units. IMANCO image analyzer interpretation work for small scale images demonstrated the need for much additional analyses. Continuing image interpretation work for the next reporting period is concentrated on manual image interpretation work as well as digital interpretation system development using the computer compatible tapes.

The mass remote sensing image data management based on Oracle InterMedia

NASA Astrophysics Data System (ADS)

Zhao, Xi'an; Shi, Shaowei

2013-07-01

With the development of remote sensing technology, getting the image data more and more, how to apply and manage the mass image data safely and efficiently has become an urgent problem to be solved. According to the methods and characteristics of the mass remote sensing image data management and application, this paper puts forward to a new method that takes Oracle Call Interface and Oracle InterMedia to store the image data, and then takes this component to realize the system function modules. Finally, it successfully takes the VC and Oracle InterMedia component to realize the image data storage and management.

ENVIRONMENTAL PHOTOGRAPHIC INTERPRETATION CENTER (EPIC)

EPA Science Inventory

The Environmental Sciences Division (ESD) in the National Exposure Research Laboratory (NERL) of the Office of Research and Development provides remote sensing technical support including aerial photograph acquisition and interpretation to the EPA Program Offices, ORD Laboratorie...

Photography and imagery: a clarification of terms

USGS Publications Warehouse

Robinove, Charles J.

1963-01-01

The increased use of pictorial displays of data in the fields of photogrammetry and photo interpretation has led to some confusion of terms, not so much b photogrammetrists as bu users and interpreters of pictorial data. The terms "remote sensing" and "remote sensing of environment" are being used as general terms to describe "the measurement of some property of an object without having the measuring device physically in contact with the object" (Parker, 1962).Measurements of size and shape by photogrammetric and optical means are common examples of remote sensing and therefore require no elaboration. Other techniques of remote sensing of electromagnetic radiation in and beyond the limits of the visible spectrum require some explanation and differentiation from the techniques used in the visible spectrum.The following definitions of "photography" and "imagery" are proposed to clarify these two terms in hope that this will lead to more precise understanding and explanation of the processes.

Visible and infrared remote imaging of hazardous waste: A review

USGS Publications Warehouse

Slonecker, Terrence; Fisher, Gary B.; Aiello, Danielle P.; Haack, Barry

2010-01-01

One of the critical global environmental problems is human and ecological exposure to hazardous wastes from agricultural, industrial, military and mining activities. These wastes often include heavy metals, hydrocarbons and other organic chemicals. Traditional field and laboratory detection and monitoring of these wastes are generally expensive and time consuming. The synoptic perspective of overhead remote imaging can be very useful for the detection and remediation of hazardous wastes. Aerial photography has a long and effective record in waste site evaluations. Aerial photographic archives allow temporal evaluation and change detection by visual interpretation. Multispectral aircraft and satellite systems have been successfully employed in both spectral and morphological analysis of hazardous wastes on the landscape and emerging hyperspectral sensors have permitted determination of the specific contaminants by processing strategies using the tens or hundreds of acquired wavelengths in the solar reflected and/or thermal infrared parts of the electromagnetic spectrum. This paper reviews the literature of remote sensing and overhead imaging in the context of hazardous waste and discusses future monitoring needs and emerging scientific research areas.

Preliminary evaluation of the airborne imaging spectrometer for vegetation analysis in the Klamath National Forest of northeastern California

NASA Technical Reports Server (NTRS)

Strahler, A. H.; Woodcock, C. E.; Avila, F. X.

1985-01-01

The experiences and results associated with a project entitled Preliminary Evaluation of the Airborne Imaging Spectrometer for Vegetation Analysis is documented. The primary goal of the project was to provide ground truth, manual interpretation, and computer processing of data from an experimental flight of the Airborne Infrared Spectrometer (AIS) to determine the extent to which high spectral resolution remote sensing could differentiate among plant species, and especially species of conifers, for a naturally vegetated test site. Through the course of the research, JPL acquired AIS imagery of the test areas in the Klamath National Forest, northeastern California, on two overflights of both the Dock Well and Grass Lake transects. Over the next year or so, three generations of data was also received: first overflight, second overflight, and reprocessed second overflight. Two field visits were made: one trip immediately following the first overflight to note snow conditions and temporally-related vegetation states at the time of the sensor overpass; and a second trip about six weeks later, following acquisition of prints of the images from the first AIS overpass.

Ocean-ice interaction in the marginal ice zone using synthetic aperture radar imagery

NASA Technical Reports Server (NTRS)

Liu, Antony K.; Peng, Chich Y.; Weingartner, Thomas J.

1994-01-01

Ocean-ice interaction processes in the marginal ice zone (MIZ) by wind, waves, and mesoscale features, such as up/downwelling and eddies are studied using Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) images and an ocean-ice interaction model. A sequence of seven SAR images of the MIZ in the Chukchi Sea with 3 or 6 days interval are investigated for ice edge advance/retreat. Simultaneous current measurements from the northeast Chukchi Sea, as well as the Barrow wind record, are used to interpret the MIZ dynamics. SAR spectra of waves in ice and ocean waves in the Bering and Chukchi Sea are compared for the study of wave propagation and dominant SAR imaging mechanism. By using the SAR-observed ice edge configuration and wind and wave field in the Chukchi Sea as inputs, a numerical simulation has been performed with the ocean-ice interaction model. After 3 days of wind and wave forcing the resulting ice edge configuration, eddy formation, and flow velocity field are shown to be consistent with SAR observations.

Remote Sensing Information Science Research

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

An integrated approach for updating cadastral maps in Pakistan using satellite remote sensing data

NASA Astrophysics Data System (ADS)

Ali, Zahir; Tuladhar, Arbind; Zevenbergen, Jaap

2012-08-01

Updating cadastral information is crucial for recording land ownership and property division changes in a timely fashioned manner. In most cases, the existing cadastral maps do not provide up-to-date information on land parcel boundaries. Such a situation demands that all the cadastral data and parcel boundaries information in these maps to be updated in a timely fashion. The existing techniques for acquiring cadastral information are discipline-oriented based on different disciplines such as geodesy, surveying, and photogrammetry. All these techniques require a large number of manpower, time, and cost when they are carried out separately. There is a need to integrate these techniques for acquiring cadastral information to update the existing cadastral data and (re)produce cadastral maps in an efficient manner. To reduce the time and cost involved in cadastral data acquisition, this study develops an integrated approach by integrating global position system (GPS) data, remote sensing (RS) imagery, and existing cadastral maps. For this purpose, the panchromatic image with 0.6 m spatial resolution and the corresponding multi-spectral image with 2.4 m spatial resolution and 3 spectral bands from QuickBird satellite were used. A digital elevation model (DEM) was extracted from SPOT-5 stereopairs and some ground control points (GCPs) were also used for ortho-rectifying the QuickBird images. After ortho-rectifying these images and registering the multi-spectral image to the panchromatic image, fusion between them was attained to get good quality multi-spectral images of these two study areas with 0.6 m spatial resolution. Cadastral parcel boundaries were then identified on QuickBird images of the two study areas via visual interpretation using participatory-GIS (PGIS) technique. The regions of study are the urban and rural areas of Peshawar and Swabi districts in the Khyber Pakhtunkhwa province of Pakistan. The results are the creation of updated cadastral maps with a lot of cadastral information which can be used in updating the existing cadastral data with less time and cost.

Disparities in Sense of Community: True Race Differences or Differential Item Functioning?

ERIC Educational Resources Information Center

Coffman, Donna L.; BeLue, Rhonda

2009-01-01

The sense of community index (SCI) has been widely used to measure psychological sense of community (SOC). Furthermore, SOC has been found to differ among racial groups. Because different ethnic groups have different cultural and historical experiences that may lead to different interpretations of measurement items, it is important to know whether…

Half-quadratic variational regularization methods for speckle-suppression and edge-enhancement in SAR complex image

NASA Astrophysics Data System (ADS)

Zhao, Xia; Wang, Guang-xin

2008-12-01

Synthetic aperture radar (SAR) is an active remote sensing sensor. It is a coherent imaging system, the speckle is its inherent default, which affects badly the interpretation and recognition of the SAR targets. Conventional methods of removing the speckle is studied usually in real SAR image, which reduce the edges of the images at the same time as depressing the speckle. Morever, Conventional methods lost the information about images phase. Removing the speckle and enhancing the target and edge simultaneously are still a puzzle. To suppress the spckle and enhance the targets and the edges simultaneously, a half-quadratic variational regularization method in complex SAR image is presented, which is based on the prior knowledge of the targets and the edge. Due to the non-quadratic and non- convex quality and the complexity of the cost function, a half-quadratic variational regularization variation is used to construct a new cost function,which is solved by alternate optimization. In the proposed scheme, the construction of the model, the solution of the model and the selection of the model peremeters are studied carefully. In the end, we validate the method using the real SAR data.Theoretic analysis and the experimental results illustrate the the feasibility of the proposed method. Further more, the proposed method can preserve the information about images phase.

Role of remote sensing in the evaluation of anthropogenic activity and its effect on environment and human econonomic development: an Indian example

NASA Astrophysics Data System (ADS)

Perni, Venkateswarlu

In the scenario of a exponential growth of world population, changes in land use and evaluating the domestication and rearing of aquatic animals and plants; Remote Sensing has the role of an emerging discipline and provides essential tools of trade to the environmental scientist. Ecologically sustainable development of the aqua resources requires that management and use as compatible with the attributes of exploited resources. Aquaculture plays a crucial role in the development of fishing industry and contributes in rural development, increased foreign reserves besides replenishment of important aquatic species. The synoptivity, repititivity and multi spectral vision are the significant edges of Remote Sensing over conventional practices in the application domain. The present study aimed at mapping and monitoring of damages to the ecologically sensitive land farms like mangroves, sand deserts, wetlands, marshy areas etc., due to the development of aquaculture ponds and to analyze and understand the impact of pond aquaculture on water course, ground water quality, drinking water source etc. Indian Remote Sensing satellite:1D - Liss-III + PAN sensors merged data of two seasons is used to carry out change detection studies of mangroves, lakes/lagoons and coastal wetlands. To generate microscopic information of Machilipatnam and to monitor the water circulation in creeks the very high resolution IKONOS Panchromatic data is used. Geometrically rectified digital base map covering the study area is prepared on 1:63,630 scale. Satellite data of Land Sat TM, IRS Liss - II, Liss - III and PAN were used. Satellite data geometrically rectified with reference to base map using standard image-to-image tie up procedure besides necessary enhancement techniques for better interpretation. The economic impact of aquaculture is critically analyzed considering certain statistics and the resultant affects are presented. Tropical brackish water and saltwater aquaculture have contributed to the destruction of Mangrove Forests, Wetlands and Salt Marshes, because they have been cleared for use as ponds. It is observed that around 60

SenseCam improves memory for recent events and quality of life in a patient with memory retrieval difficulties.

PubMed

Browne, Georgina; Berry, Emma; Kapur, Narinder; Hodges, Steve; Smyth, Gavin; Watson, Peter; Wood, Ken

2011-10-01

A wearable camera that takes pictures automatically, SenseCam, was used to generate images for rehearsal, promoting consolidation and retrieval of memories for significant events in a patient with memory retrieval deficits. SenseCam images of recent events were systematically reviewed over a 2-week period. Memory for these events was assessed throughout and longer-term recall was tested up to 6 months later. A written diary control condition followed the same procedure. The SenseCam review procedure resulted in significantly more details of an event being recalled, with twice as many details recalled at 6 months follow up compared to the written diary method. Self-report measures suggested autobiographical recollection was triggered by the SenseCam condition but not by reviewing the written diary. Emotional and social wellbeing questionnaires indicated improved confidence and decreased anxiety as a result of memory rehearsal using SenseCam images. We propose that SenseCam images provide a powerful boost to autobiographical recall, with secondary benefits for quality of life.

Aerial Vehicle Surveys of other Planetary Atmospheres and Surfaces: Imaging, Remote-sensing, and Autonomy Technology Requirements

NASA Technical Reports Server (NTRS)

Young, Larry A.; Pisanich, Gregory; Ippolito, Corey; Alena, Rick

2005-01-01

The objective of this paper is to review the anticipated imaging and remote-sensing technology requirements for aerial vehicle survey missions to other planetary bodies in our Solar system that can support in-atmosphere flight. In the not too distant future such planetary aerial vehicle (a.k.a. aerial explorers) exploration missions will become feasible. Imaging and remote-sensing observations will be a key objective for these missions. Accordingly, it is imperative that optimal solutions in terms of imaging acquisition and real-time autonomous analysis of image data sets be developed for such vehicles.

HPT: A High Spatial Resolution Multispectral Sensor for Microsatellite Remote Sensing

PubMed Central

Takahashi, Yukihiro; Sakamoto, Yuji; Kuwahara, Toshinori

2018-01-01

Although nano/microsatellites have great potential as remote sensing platforms, the spatial and spectral resolutions of an optical payload instrument are limited. In this study, a high spatial resolution multispectral sensor, the High-Precision Telescope (HPT), was developed for the RISING-2 microsatellite. The HPT has four image sensors: three in the visible region of the spectrum used for the composition of true color images, and a fourth in the near-infrared region, which employs liquid crystal tunable filter (LCTF) technology for wavelength scanning. Band-to-band image registration methods have also been developed for the HPT and implemented in the image processing procedure. The processed images were compared with other satellite images, and proven to be useful in various remote sensing applications. Thus, LCTF technology can be considered an innovative tool that is suitable for future multi/hyperspectral remote sensing by nano/microsatellites. PMID:29463022

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.

Research on fast Fourier transforms algorithm of huge remote sensing image technology with GPU and partitioning technology.

PubMed

Yang, Xue; Li, Xue-You; Li, Jia-Guo; Ma, Jun; Zhang, Li; Yang, Jan; Du, Quan-Ye

2014-02-01

Fast Fourier transforms (FFT) is a basic approach to remote sensing image processing. With the improvement of capacity of remote sensing image capture with the features of hyperspectrum, high spatial resolution and high temporal resolution, how to use FFT technology to efficiently process huge remote sensing image becomes the critical step and research hot spot of current image processing technology. FFT algorithm, one of the basic algorithms of image processing, can be used for stripe noise removal, image compression, image registration, etc. in processing remote sensing image. CUFFT function library is the FFT algorithm library based on CPU and FFTW. FFTW is a FFT algorithm developed based on CPU in PC platform, and is currently the fastest CPU based FFT algorithm function library. However there is a common problem that once the available memory or memory is less than the capacity of image, there will be out of memory or memory overflow when using the above two methods to realize image FFT arithmetic. To address this problem, a CPU and partitioning technology based Huge Remote Fast Fourier Transform (HRFFT) algorithm is proposed in this paper. By improving the FFT algorithm in CUFFT function library, the problem of out of memory and memory overflow is solved. Moreover, this method is proved rational by experiment combined with the CCD image of HJ-1A satellite. When applied to practical image processing, it improves effect of the image processing, speeds up the processing, which saves the time of computation and achieves sound result.

Landslide inventory maps: New tools for an old problem

NASA Astrophysics Data System (ADS)

Guzzetti, Fausto; Mondini, Alessandro Cesare; Cardinali, Mauro; Fiorucci, Federica; Santangelo, Michele; Chang, Kang-Tsung

2012-04-01

Landslides are present in all continents, and play an important role in the evolution of landscapes. They also represent a serious hazard in many areas of the world. Despite their importance, we estimate that landslide maps cover less than 1% of the slopes in the landmasses, and systematic information on the type, abundance, and distribution of landslides is lacking. Preparing landslide maps is important to document the extent of landslide phenomena in a region, to investigate the distribution, types, pattern, recurrence and statistics of slope failures, to determine landslide susceptibility, hazard, vulnerability and risk, and to study the evolution of landscapes dominated by mass-wasting processes. Conventional methods for the production of landslide maps rely chiefly on the visual interpretation of stereoscopic aerial photography, aided by field surveys. These methods are time consuming and resource intensive. New and emerging techniques based on satellite, airborne, and terrestrial remote sensing technologies, promise to facilitate the production of landslide maps, reducing the time and resources required for their compilation and systematic update. In this work, we first outline the principles for landslide mapping, and we review the conventional methods for the preparation of landslide maps, including geomorphological, event, seasonal, and multi-temporal inventories. Next, we examine recent and new technologies for landslide mapping, considering (i) the exploitation of very-high resolution digital elevation models to analyze surface morphology, (ii) the visual interpretation and semi-automatic analysis of different types of satellite images, including panchromatic, multispectral, and synthetic aperture radar images, and (iii) tools that facilitate landslide field mapping. Next, we discuss the advantages and the limitations of the new remote sensing data and technology for the production of geomorphological, event, seasonal, and multi-temporal inventory maps. We conclude by arguing that the new tools will help to improve the quality of landslide maps, with positive effects on all derivative products and analyses, including erosion studies and landscape modeling, susceptibility and hazard assessments, and risk evaluations.

Atmospheric Radiative Transfer for Satellite Remote Sensing

NASA Technical Reports Server (NTRS)

Marshak, Alexander

2008-01-01

I will discuss the science of satellite remote sensing which involves the interpretation and inversion of radiometric measurements made from space. The goal of remote sensing is to retrieve some physical aspects of the medium which are sensitive to the radiation at specific wavelengths. This requires the use of fundamentals of atmospheric radiative transfer. I will talk about atmospheric radiation or, more specifically, about the interactions of solar radiation with aerosols and cloud particles. The focus will be more on cloudy atmospheres. I will also show how a standard one-dimensional approach, that is traced back at least 100 years, can fail to interpret the complexity of real clouds. I n these cases, three-dimensional radiative transfer should be used. Examples of satellite retrievals will illustrate the cases.

Development of data processing, interpretation and analysis system for the remote sensing of trace atmospheric gas species

NASA Technical Reports Server (NTRS)

Casas, Joseph C.; Saylor, Mary S.; Kindle, Earl C.

1987-01-01

The major emphasis is on the advancement of remote sensing technology. In particular, the gas filter correlation radiometer (GFCR) technique was applied to the measurement of trace gas species, such as carbon monoxide (CO), from airborne and Earth orbiting platforms. Through a series of low altitude aircraft flights, high altitude aircraft flights, and orbiting space platform flights, data were collected and analyzed, culminating in the first global map of carbon monoxide concentration in the middle troposphere and stratosphere. The four major areas of this remote sensing program, known as the Measurement of Air Pollution from Satellites (MAPS) experiment, are: (1) data acquisition, (2) data processing, analysis, and interpretation algorithms, (3) data display techniques, and (4) information processing.

The integrated design and archive of space-borne signal processing and compression coding

NASA Astrophysics Data System (ADS)

He, Qiang-min; Su, Hao-hang; Wu, Wen-bo

2017-10-01

With the increasing demand of users for the extraction of remote sensing image information, it is very urgent to significantly enhance the whole system's imaging quality and imaging ability by using the integrated design to achieve its compact structure, light quality and higher attitude maneuver ability. At this present stage, the remote sensing camera's video signal processing unit and image compression and coding unit are distributed in different devices. The volume, weight and consumption of these two units is relatively large, which unable to meet the requirements of the high mobility remote sensing camera. This paper according to the high mobility remote sensing camera's technical requirements, designs a kind of space-borne integrated signal processing and compression circuit by researching a variety of technologies, such as the high speed and high density analog-digital mixed PCB design, the embedded DSP technology and the image compression technology based on the special-purpose chips. This circuit lays a solid foundation for the research of the high mobility remote sensing camera.

MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification

NASA Astrophysics Data System (ADS)

Lin, Daoyu; Fu, Kun; Wang, Yang; Xu, Guangluan; Sun, Xian

2017-11-01

With the development of deep learning, supervised learning has frequently been adopted to classify remotely sensed images using convolutional networks (CNNs). However, due to the limited amount of labeled data available, supervised learning is often difficult to carry out. Therefore, we proposed an unsupervised model called multiple-layer feature-matching generative adversarial networks (MARTA GANs) to learn a representation using only unlabeled data. MARTA GANs consists of both a generative model $G$ and a discriminative model $D$. We treat $D$ as a feature extractor. To fit the complex properties of remote sensing data, we use a fusion layer to merge the mid-level and global features. $G$ can produce numerous images that are similar to the training data; therefore, $D$ can learn better representations of remotely sensed images using the training data provided by $G$. The classification results on two widely used remote sensing image databases show that the proposed method significantly improves the classification performance compared with other state-of-the-art methods.

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 Distributed Compressive Sensing Scheme for Event Capture in Wireless Visual Sensor Networks

NASA Astrophysics Data System (ADS)

Hou, Meng; Xu, Sen; Wu, Weiling; Lin, Fei

2018-01-01

Image signals which acquired by wireless visual sensor network can be used for specific event capture. This event capture is realized by image processing at the sink node. A distributed compressive sensing scheme is used for the transmission of these image signals from the camera nodes to the sink node. A measurement and joint reconstruction algorithm for these image signals are proposed in this paper. Make advantage of spatial correlation between images within a sensing area, the cluster head node which as the image decoder can accurately co-reconstruct these image signals. The subjective visual quality and the reconstruction error rate are used for the evaluation of reconstructed image quality. Simulation results show that the joint reconstruction algorithm achieves higher image quality at the same image compressive rate than the independent reconstruction algorithm.

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications

PubMed Central

Moussa, Adel; El-Sheimy, Naser; Habib, Ayman

2017-01-01

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research. PMID:29057847

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications.

PubMed

Al-Rawabdeh, Abdulla; Moussa, Adel; Foroutan, Marzieh; El-Sheimy, Naser; Habib, Ayman

2017-10-18

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research.

Horizontal-to-Vertical Spectral Ratio for Estimating Thickness of Sedimentary Deposits across the PoroTomo site in Brady Hot Springs, Nevada (USA)

NASA Astrophysics Data System (ADS)

Parker, L.; Fratta, D.; Zeng, X.; Lord, N. E.; Wang, H. F.; Thurber, C. H.; Lin, F. C.; Feigl, K. L.; Team, P.

2016-12-01

During March 2016, the PoroTomo research team deployed more than 8700 m of DAS and DTS cable in horizontal and vertical sensing arrays, 244 three-component surface geophones, inSAR images, pressure transducers, and a vibroseis truck to actively and passively image the response of a geothermal field in Brady Hot Springs, Nevada. During the imaging period the geothermal field was manipulated to change the pore pressure in the formation. The objective of the study is to invert for poroelastic parameters within a 1500 m by 500 m by 400 m volume using tomographic techniques. Among the different imaging techniques, the research team is using passive horizontal-to-vertical spectral ratio data captured with the three-component geophones to estimate the thickness of the sedimentary deposits across the PoroTomo site. The interpretation of the inverted data is complicated due the heterogeneity in the near surface deposits at the site. These deposits include diatomaceous earth, sandy/silty layers, and hardened silica associated with the presence of fumaroles. In spite of the challenges associated with deposits of very different stiffness, the mapping of sediment thickness across the Natural Laboratory helps constrain the inversion of Multiple Channel Analysis of Surface Waves to improve the quality of the solution images.

Wavelet-based multicomponent denoising on GPU to improve the classification of hyperspectral images

NASA Astrophysics Data System (ADS)

Quesada-Barriuso, Pablo; Heras, Dora B.; Argüello, Francisco; Mouriño, J. C.

2017-10-01

Supervised classification allows handling a wide range of remote sensing hyperspectral applications. Enhancing the spatial organization of the pixels over the image has proven to be beneficial for the interpretation of the image content, thus increasing the classification accuracy. Denoising in the spatial domain of the image has been shown as a technique that enhances the structures in the image. This paper proposes a multi-component denoising approach in order to increase the classification accuracy when a classification method is applied. It is computed on multicore CPUs and NVIDIA GPUs. The method combines feature extraction based on a 1Ddiscrete wavelet transform (DWT) applied in the spectral dimension followed by an Extended Morphological Profile (EMP) and a classifier (SVM or ELM). The multi-component noise reduction is applied to the EMP just before the classification. The denoising recursively applies a separable 2D DWT after which the number of wavelet coefficients is reduced by using a threshold. Finally, inverse 2D-DWT filters are applied to reconstruct the noise free original component. The computational cost of the classifiers as well as the cost of the whole classification chain is high but it is reduced achieving real-time behavior for some applications through their computation on NVIDIA multi-GPU platforms.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Direct Satellite Data Acquisition and its Application for Large -scale Monitoring Projects in Russia

NASA Astrophysics Data System (ADS)

Gershenzon, O.

2011-12-01

ScanEx RDC created an infrastructure (ground stations network) to acquire and process remote sensing data from different satellites: Terra, Aqua, Landsat, IRS-P5/P6, SPOT 4/5, FORMOSAT-2, EROS A/B, RADARSAT-1/2, ENVISAT-1. It owns image archives from these satellites as well as from SPOT-2 and CARTOSAT-2. ScanEx RDC builds and delivers remote sensing ground stations (working with up to 15 satellites); and owns the ground stations network to acquire data for Russia and surrounding territory. ScanEx stations are the basic component in departmental networks of remote sensing data acquisition for different state authorities (Roshydromet, Ministry of Natural Recourses, Emercom) and University- based remote sensing data acquisition and processing centers in Russia and abroad. ScanEx performs large-scale projects in collaboration with government agencies to monitor forests, floods, fires, sea surface pollution, and ice situation in Northern Russia. During 2010-2011 ScanEx conducted daily monitoring of wild fires in Russia detecting and registering thermal anomalies using data from Terra, Aqua, Landsat and SPOT satellites. Detailed SPOT 4/5 data is used to analyze burnt areas and to assess damage caused by fire. Satellite data along with other information about fire situation in Russia was daily updated and published via free-access Internet geoportal. A few projects ScanEx conducted together with environmental NGO. Project "Satellite monitoring of Especially Protected Natural Areas of Russia and its results visualization on geoportal was conducted in cooperation with NGO "Transparent World". The project's goal was to observe natural phenomena and economical activity, including illegal, by means of Earth remote sensing data. Monitoring is based on multi-temporal optical space imagery of different spatial resolution. Project results include detection of anthropogenic objects that appeared in the vicinity or even within the border of natural territories, that have never been touched by civilization before. "Satellite based technology for monitoring ship ice navigation and its influence on seal population in the White Sea" project was conducted in cooperation with IFAW. Results of the near real-time satellite monitoring were published on specially designed open web source. This allows project team to put image interpretation results in near real-time mode for on-line access to all interesting external stakeholders. During project realization Envisat, Radarsat, SPOT, EROS space images were used. In addition the methodology to locate seal population using EROS space images was developed. This methodology is based on detection of vital functions and displacement traces. Environmental satellite monitoring of Northern Russian territory and Arctic seas projects where the results are published via free-access Internet geoportal has a significant social importance.

a New Graduation Algorithm for Color Balance of Remote Sensing Image

NASA Astrophysics Data System (ADS)

Zhou, G.; Liu, X.; Yue, T.; Wang, Q.; Sha, H.; Huang, S.; Pan, Q.

2018-05-01

In order to expand the field of view to obtain more data and information when doing research on remote sensing image, workers always need to mosaicking images together. However, the image after mosaic always has the large color differences and produces the gap line. This paper based on the graduation algorithm of tarigonometric function proposed a new algorithm of Two Quarter-rounds Curves (TQC). The paper uses the Gaussian filter to solve the program about the image color noise and the gap line. The paper used one of Greenland compiled data acquired in 1963 from Declassified Intelligence Photography Project (DISP) by ARGON KH-5 satellite, and used the photography of North Gulf, China, by Landsat satellite to experiment. The experimental results show that the proposed method has improved the accuracy of the results in two parts: on the one hand, for the large color differences remote sensing image will become more balanced. On the other hands, the remote sensing image will achieve more smooth transition.

Enhancing the Teaching of Digital Processing of Remote Sensing Image Course through Geospatial Web Processing Services

NASA Astrophysics Data System (ADS)

di, L.; Deng, M.

2010-12-01

Remote sensing (RS) is an essential method to collect data for Earth science research. Huge amount of remote sensing data, most of them in the image form, have been acquired. Almost all geography departments in the world offer courses in digital processing of remote sensing images. Such courses place emphasis on how to digitally process large amount of multi-source images for solving real world problems. However, due to the diversity and complexity of RS images and the shortcomings of current data and processing infrastructure, obstacles for effectively teaching such courses still remain. The major obstacles include 1) difficulties in finding, accessing, integrating and using massive RS images by students and educators, and 2) inadequate processing functions and computing facilities for students to freely explore the massive data. Recent development in geospatial Web processing service systems, which make massive data, computing powers, and processing capabilities to average Internet users anywhere in the world, promises the removal of the obstacles. The GeoBrain system developed by CSISS is an example of such systems. All functions available in GRASS Open Source GIS have been implemented as Web services in GeoBrain. Petabytes of remote sensing images in NASA data centers, the USGS Landsat data archive, and NOAA CLASS are accessible transparently and processable through GeoBrain. The GeoBrain system is operated on a high performance cluster server with large disk storage and fast Internet connection. All GeoBrain capabilities can be accessed by any Internet-connected Web browser. Dozens of universities have used GeoBrain as an ideal platform to support data-intensive remote sensing education. This presentation gives a specific example of using GeoBrain geoprocessing services to enhance the teaching of GGS 588, Digital Remote Sensing taught at the Department of Geography and Geoinformation Science, George Mason University. The course uses the textbook "Introductory Digital Image Processing, A Remote Sensing Perspective" authored by John Jensen. The textbook is widely adopted in the geography departments around the world for training students on digital processing of remote sensing images. In the traditional teaching setting for the course, the instructor prepares a set of sample remote sensing images to be used for the course. Commercial desktop remote sensing software, such as ERDAS, is used for students to do the lab exercises. The students have to do the excurses in the lab and can only use the simple images. For this specific course at GMU, we developed GeoBrain-based lab excurses for the course. With GeoBrain, students now can explore petabytes of remote sensing images in the NASA, NOAA, and USGS data archives instead of dealing only with sample images. Students have a much more powerful computing facility available for their lab excurses. They can explore the data and do the excurses any time at any place they want as long as they can access the Internet through the Web Browser. The feedbacks from students are all very positive about the learning experience on the digital image processing with the help of GeoBrain web processing services. The teaching/lab materials and GeoBrain services are freely available to anyone at http://www.laits.gmu.edu.

HyFlux - Part I: Regional Modeling of Methane Flux From Near-Seafloor Gas Hydrate Deposits on Continental Margins

NASA Astrophysics Data System (ADS)

MacDonald, I. R.; Asper, V.; Garcia, O. P.; Kastner, M.; Leifer, I.; Naehr, T.; Solomon, E.; Yvon-Lewis, S.; Zimmer, B.

2008-12-01

HyFlux - Part I: Regional modeling of methane flux from near-seafloor gas hydrate deposits on continental margins MacDonald, I.R., Asper, V., Garcia, O., Kastner, M., Leifer, I., Naehr, T.H., Solomon, E., Yvon-Lewis, S., and Zimmer, B. The Dept. of Energy National Energy Technology Laboratory (DOE/NETL) has recently awarded a project entitled HyFlux: "Remote sensing and sea-truth measurements of methane flux to the atmosphere." The project will address this problem with a combined effort of satellite remote sensing and data collection at proven sites in the Gulf of Mexico where gas hydrate releases gas to the water column. Submarine gas hydrate is a large pool of greenhouse gas that may interact with the atmosphere over geologic time to affect climate cycles. In the near term, the magnitude of methane reaching the atmosphere from gas hydrate on continental margins is poorly known because 1) gas hydrate is exposed to metastable oceanic conditions in shallow, dispersed deposits that are poorly imaged by standard geophysical techniques and 2) the consumption of methane in marine sediments and in the water column is subject to uncertainty. The northern GOM is a prolific hydrocarbon province where rapid migration of oil, gases, and brines from deep subsurface petroleum reservoirs occurs through faults generated by salt tectonics. Focused expulsion of hydrocarbons is manifested at the seafloor by gas vents, gas hydrates, oil seeps, chemosynthetic biological communities, and mud volcanoes. Where hydrocarbon seeps occur in depths below the hydrate stability zone (~500m), rapid flux of gas will feed shallow deposits of gas hydrate that potentially interact with water column temperature changes; oil released from seeps forms sea-surface features that can be detected in remote-sensing images. The regional phase of the project will quantify verifiable sources of methane (and oil) the Gulf of Mexico continental margin and selected margins (e.g. Pakistan Margin, South China Sea, and West Africa Margin) world-wide by using the substantial archive of satellite synthetic aperture radar (SAR) images. An automated system for satellite image interpretation will make it possible to process hundreds of SAR images to increase the geographic and temporal coverage. Field programs will quantify the flux and fate of hydrate methane in sediments and the water column.

Consistency of response and image recognition, pulmonary nodules

PubMed Central

Liu, M A Q; Galvan, E; Bassett, R; Murphy, W A; Matamoros, A; Marom, E M

2014-01-01

Objective: To investigate the effect of recognition of a previously encountered radiograph on consistency of response in localized pulmonary nodules. Methods: 13 radiologists interpreted 40 radiographs each to locate pulmonary nodules. A few days later, they again interpreted 40 radiographs. Half of the images in the second set were new. We asked the radiologists whether each image had been in the first set. We used Fisher's exact test and Kruskal–Wallis test to evaluate the correlation between recognition of an image and consistency in its interpretation. We evaluated the data using all possible recognition levels—definitely, probably or possibly included vs definitely, probably or possibly not included by collapsing the recognition levels into two and by eliminating the “possibly included” and “possibly not included” scores. Results: With all but one of six methods of looking at the data, there was no significant correlation between consistency in interpretation and recognition of the image. When the possibly included and possibly not included scores were eliminated, there was a borderline statistical significance (p = 0.04) with slightly greater consistency in interpretation of recognized than that of non-recognized images. Conclusion: We found no convincing evidence that radiologists' recognition of images in an observer performance study affects their interpretation on a second encounter. Advances in knowledge: Conscious recognition of chest radiographs did not result in a greater degree of consistency in the tested interpretation than that in the interpretation of images that were not recognized. PMID:24697724

Thermal Infrared Airborne Field Studies: Applications to the Mars Global Surveyor Thermal Emission Spectrometer

NASA Astrophysics Data System (ADS)

Herr, K.; Kirkland, L.; Keim, E.; Hackwell, J.

2002-12-01

A primary goal of the Mars exploration program is to reconnoiter the planet from orbit using infrared remote sensing. Currently the Global Surveyor Thermal Emission Spectrometer (TES) and the 2001 Mars Odyssey 9-band radiometer THEMIS provide this capability. Landing site selection and modeling of the geologic and climate history depend on accurate interpretations of these data sets. Interpretations use terrestrial analog remote sensing and laboratory studies. Until recently, there have been no airborne thermal infrared spectrometer ("hyspectral") data sets available to NASA researchers that are comparable to TES. As a result, studies relied on airborne multi-channel radiometer ("multispectral") measurements (e.g. TIMS, MASTER). A radiometer has the advantage that measurement of broad bands makes it easier to measure with higher sensitivity. However, radiometers lack the spectral resolution to investigate details of spectral signatures. This gap may be partially addressed using field samples collected and measured in the laboratory. However, that leaves questions unanswered about the field environment and potentially leaves important complicating issues undiscovered. Two questions that haunt thermal infrared remote sensing investigations of Mars are: (1) If a mineral is not detected in a given data set, how definitively should we state that it is not there? (2) When does the method provide quantitative mineral mapping? In order to address these questions, we began collaborating with Department of Defense (DoD) oriented researchers and drawing on the unique instrumentation they developed. Both Mars and DoD researchers have a common need to identify materials without benefit of ground truth. Such collaborations provide a fresh perspective as well as unique data. Our work addresses uncertainties in stand-off identification of solid phase surface materials when the identification must proceed without benefit of ground truth. We will report on the results applied to TES, with a focus on the two primary questions above. We use images recorded by a unique airborne imaging spectrometer, the Spatially Enhanced Broadband Array Spectrograph System. SEBASS uses cooled prisms to measure 2.4-5.3 and 7.6-13.5 microns. Each range is measured in 128 channels, with a spectral resolution of 7 wavenumbers at 890 wavenumbers, and a one milliradian field of view per pixel. SEBASS operates as a pushbroom instrument, using two 128 x 128 detector arrays, and the entire optical bench is cooled to 4K using liquid helium. It is operated by The Aerospace Corporation, which is a non-profit Federally Funded Research and Development Center. Images are typically 128 pixels wide and 2000 pixels long, measured with a surface spatial resolution of ~1 or 2 square meters. TES measures ~6.5-50 microns in 143 channels, with a spectral resolution of 10 or 20 wavenumbers. Issues that affect the spectral signature include surface roughness, particle size, coatings, reflected downwelling radiance, atmospheric transmission, and atmospheric reemission. A full understanding of these effects is required in order to determine the uncertainties in field interpretations, whether terrestrially or on Mars. SEBASS data fill this need by measuring with a sensitivity comparable to laboratory data, and sufficient spectral resolution to examine subtle spectral effects that are not resolvable in multi-channel radiometer data.

Research on Remote Sensing recognition features of Yuan Yang Terraces in Yunnan Province (China)

NASA Astrophysics Data System (ADS)

Xiang, Jie; Chen, Jianping; Lai, ZiLi; Yang, Wei

2016-04-01

Yuan Yang terraces is one of the most famous terraces in China, and it was successfully listed in the world heritage list at the 37th world heritage convention. On the one hand, Yuan Yang terraces retain more soil and water, to reduce both hydrological connectivity and erosion, and to support irrigation. On the other hand, It has the important tourism value, bring the huge revenue to local residents. In order to protect and make use of Yuan Yang terraces better, This study analyzed the spatial distribution and spectral characteristics of terraces:(1) Through visual interpretation, the study recognized the terraces based on the spatial adjusted remote sensing image (2010 Geoeye-1 with resolution of 1m/pix), and extracted topographic feature (elevation, slope, aspect, etc.) based on the digital elevation model with resolution of 20m/pix. The terraces cover a total area of about 11.58Km2, accounted for 24.4% of the whole study area. The terraces appear at range from 1400m to 1800m in elevation, 10°to 20°in slope, northwest to northeast in aspect; (2) Using the method of weight of evidence, this study assessed the importance of different topographic feature. The results show that the sort of importance: elevation>slope>aspect; (3) The study counted the Normalized Difference Vegetation Index (NDVI) changes of terraces throughout the year, based on the landsat-5 image with resolution of 30m/pix. The results show that the changes of terraces' NDVI are bigger than other stuff (e.g. forest, road, house, etc.). Those work made a good preparations for establishing the dynamic remote sensing monitoring system of Yuan Yang terraces.

Multidata remote sensing approach to regional geologic mapping in Venezuela

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

Baker, R.N.

1996-08-01

Remote Sensing played an important role in evaluating the exploration potential of selected lease blocks in Venezuela. Data sets used ranged from regional Landsat and airborne radar (SLAR) surveys to high-quality cloud-free air photos for local but largely inaccessible terrains. The resulting data base provided a framework for the conventional analyses of surface and subsurface information available to the project team. (1) Regional surface geology and major structural elements were interpreted from Landsat MSS imagery supplemented by TM and a regional 1:250,000 airborne radar (SLAR) survey. Evidence of dextral offset, en echelon folds and major thoroughgoing faults suggest a regionalmore » transpressional system modified by local extension and readjustment between small-scale crustal blocks. Surface expression of the major structural elements diminishes to the east, but can often be extended beneath the coastal plain by drainage anomalies and subtle geomorphic trends. (2) Environmental conditions were mapped using the high resolution airborne radar images which were used to relate vegetation types to surface texture and elevation; wetlands, outcrop and cultural features to image brightness. Additional work using multispectral TM or SPOT imagery is planned to more accurately define environmental conditions and provide a baseline for monitoring future trends. (3) Offshore oil seeps were detected using ERS-1 satellite radar (SAR) and known seeps in the Gulf of Paria as analogs. While partially successful, natural surfactants, wind shadow and a surprising variety of other phenomena created {open_quotes}false alarms{close_quotes} which required other supporting data and field sampling to verify the results. Key elements of the remote sensing analyses will be incorporated into a comprehensive geographic information (GIS) which will eventually include all of Venezuela.« less

Immune systems are not just for making you feel better: they are for controlling autonomous robots

NASA Astrophysics Data System (ADS)

Rosenblum, Mark

2005-05-01

The typical algorithm for robot autonomous navigation in off-road complex environments involves building a 3D map of the robot's surrounding environment using a 3D sensing modality such as stereo vision or active laser scanning, and generating an instantaneous plan to navigate around hazards. Although there has been steady progress using these methods, these systems suffer from several limitations that cannot be overcome with 3D sensing and planning alone. Geometric sensing alone has no ability to distinguish between compressible and non-compressible materials. As a result, these systems have difficulty in heavily vegetated environments and require sensitivity adjustments across different terrain types. On the planning side, these systems have no ability to learn from their mistakes and avoid problematic environmental situations on subsequent encounters. We have implemented an adaptive terrain classification system based on the Artificial Immune System (AIS) computational model, which is loosely based on the biological immune system, that combines various forms of imaging sensor inputs to produce a "feature labeled" image of the scene categorizing areas as benign or detrimental for autonomous robot navigation. Because of the qualities of the AIS computation model, the resulting system will be able to learn and adapt on its own through interaction with the environment by modifying its interpretation of the sensor data. The feature labeled results from the AIS analysis are inserted into a map and can then be used by a planner to generate a safe route to a goal point. The coupling of diverse visual cues with the malleable AIS computational model will lead to autonomous robotic ground vehicles that require less human intervention for deployment in novel environments and more robust operation as a result of the system's ability to improve its performance through interaction with the environment.

Validation of Satellite Derived Cloud Properties Over the Southeastern Pacific

NASA Astrophysics Data System (ADS)

Ayers, J.; Minnis, P.; Zuidema, P.; Sun-Mack, S.; Palikonda, R.; Nguyen, L.; Fairall, C.

2005-12-01

Satellite measurements of cloud properties and the radiation budget are essential for understanding meso- and large-scale processes that determine the variability in climate over the southeastern Pacific. Of particular interest in this region is the prevalent stratocumulus cloud deck. The stratocumulus albedos are directly related to cloud microphysical properties that need to be accurately characterized in Global Climate Models (GCMs) to properly estimate the Earth's radiation budget. Meteorological observations in this region are sparse causing large uncertainties in initialized model fields. Remote sensing from satellites can provide a wealth of information about the clouds in this region, but it is vital to validate the remotely sensed parameters and to understand their relationship to other parameters that are not directly observed by the satellites. The variety of measurements from the R/V Roger Revelle during the 2003 STRATUS cruise and from the R/V Ron Brown during EPIC 2001 and the 2004 STRATUS cruises are suitable for validating and improving the interpretation of the satellite derived cloud properties. In this study, satellite-derived cloud properties including coverage, height, optical depth, and liquid water path are compared with in situ measurements taken during the EPIC and STRATUS cruises. The remotely sensed values are derived from Geostationary Operational Environmental Satellite (GOES) imager data, Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellites, and from the Visible and Infrared Scanner (VIRS) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The products from this study will include regional monthly cloud climatologies derived from the GOES data for the 2003 and 2004 cruises as well as micro and macro physical cloud property retrievals centered over the ship tracks from MODIS and VIRS.

Compressive Sensing Image Sensors-Hardware Implementation

PubMed Central

Dadkhah, Mohammadreza; Deen, M. Jamal; Shirani, Shahram

2013-01-01

The compressive sensing (CS) paradigm uses simultaneous sensing and compression to provide an efficient image acquisition technique. The main advantages of the CS method include high resolution imaging using low resolution sensor arrays and faster image acquisition. Since the imaging philosophy in CS imagers is different from conventional imaging systems, new physical structures have been developed for cameras that use the CS technique. In this paper, a review of different hardware implementations of CS encoding in optical and electrical domains is presented. Considering the recent advances in CMOS (complementary metal–oxide–semiconductor) technologies and the feasibility of performing on-chip signal processing, important practical issues in the implementation of CS in CMOS sensors are emphasized. In addition, the CS coding for video capture is discussed. PMID:23584123

Verification technology of remote sensing camera satellite imaging simulation based on ray tracing

NASA Astrophysics Data System (ADS)

Gu, Qiongqiong; Chen, Xiaomei; Yang, Deyun

2017-08-01

Remote sensing satellite camera imaging simulation technology is broadly used to evaluate the satellite imaging quality and to test the data application system. But the simulation precision is hard to examine. In this paper, we propose an experimental simulation verification method, which is based on the test parameter variation comparison. According to the simulation model based on ray-tracing, the experiment is to verify the model precision by changing the types of devices, which are corresponding the parameters of the model. The experimental results show that the similarity between the imaging model based on ray tracing and the experimental image is 91.4%, which can simulate the remote sensing satellite imaging system very well.

Contrast-based sensorless adaptive optics for retinal imaging.

PubMed

Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T O; He, Zheng; Metha, Andrew

2015-09-01

Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes.

Compressive sensing method for recognizing cat-eye effect targets.

PubMed

Li, Li; Li, Hui; Dang, Ersheng; Liu, Bo

2013-10-01

This paper proposes a cat-eye effect target recognition method with compressive sensing (CS) and presents a recognition method (sample processing before reconstruction based on compressed sensing, or SPCS) for image processing. In this method, the linear projections of original image sequences are applied to remove dynamic background distractions and extract cat-eye effect targets. Furthermore, the corresponding imaging mechanism for acquiring active and passive image sequences is put forward. This method uses fewer images to recognize cat-eye effect targets, reduces data storage, and translates the traditional target identification, based on original image processing, into measurement vectors processing. The experimental results show that the SPCS method is feasible and superior to the shape-frequency dual criteria method.

Optical and Electric Multifunctional CMOS Image Sensors for On-Chip Biosensing Applications.

PubMed

Tokuda, Takashi; Noda, Toshihiko; Sasagawa, Kiyotaka; Ohta, Jun

2010-12-29

In this review, the concept, design, performance, and a functional demonstration of multifunctional complementary metal-oxide-semiconductor (CMOS) image sensors dedicated to on-chip biosensing applications are described. We developed a sensor architecture that allows flexible configuration of a sensing pixel array consisting of optical and electric sensing pixels, and designed multifunctional CMOS image sensors that can sense light intensity and electric potential or apply a voltage to an on-chip measurement target. We describe the sensors' architecture on the basis of the type of electric measurement or imaging functionalities.

Environmental Remote Sensing for Natural Resources Management: A Workshop in Collaboration with Faculdade de Agronomia e Engenharia Florestal, Universidade Eduardo Mondlane

NASA Astrophysics Data System (ADS)

Washington-Allen, R. A.; Fatoyinbo, T. E.; Ribeiro, N. S.; Shugart, H. H.; Therrell, M. D.; Vaz, K. T.; von Schill, L.

2006-12-01

A workshop titled: Environmental Remote Sensing for Natural Resources Management was held from June 12 23, 2006 at Eduardo Mondlane University in Maputo Mozambique. The workshop was initiated through an invitation and pre-course evaluation form to interested NGOs, universities, and government organizations. The purpose of the workshop was to provide training to interested professionals, graduate students, faculty and researchers at Mozambican institutions on the research and practical uses of remote sensing for natural resource management. The course had 24 participants who were predominantly professionals in remote sensing and GIS from various NGOs, governmental and academic institutions in Mozambique. The course taught remote sensing from an ecological perspective, specifically the course focused on the application of new remote sensing technology [the Shuttle Radar Topography Mission (SRTM) C-band radar data] to carbon accounting research in Miombo woodlands and Mangrove forests. The 2-week course was free to participants and consisted of lectures, laboratories, and a field trip to the mangrove forests of Inhaca Island, Maputo. The field trip consisted of training in the use of forest inventory techniques in support of remote sensing studies. Specifically, the field workshop centered on use of Global Positioning Systems (GPS) and collection of forest inventory data on tree height, structure [leaf area index (LAI)], and productivity. Productivity studies were enhanced with the teaching of introductory dendrochronology including sample collection of tree rings from four different mangrove species. Students were provided with all course materials including a DVD that contained satellite data (e.g., Landsat and SRTM imagery), ancillary data, lectures, exercises, and remote sensing publications used in the course including a CD from the Environmental Protection Agency's Environmental Photographic Interpretation Center's (EPA-EPIC) program to teach remote sensing and data CDs from NASA's SAFARI 2000 field campaign. Nineteen participants evaluated the effectiveness of the course in regards to the course lectures, instructors, and the field trip. Future workshops should focus more on the individual projects that students are engaged with in their jobs, replace the laboratories computers with workstations geared towards computer intensive image processing software, and the purchase of field remote sensing instrumentation for practical exercises.

Hyperspectral remote sensing for terrestrial applications

USGS Publications Warehouse

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

2015-01-01

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

In Defense of Dirty Words: The Case against Judicial Censorship in Oral Interpretation Events.

ERIC Educational Resources Information Center

Kugler, Drew B.

Within the realm of forensic oral interpretation, concern over the use of profanity in presentations has aroused repressive criticism from some judges, who then express their offense by ranking the performance negatively. This judicial opposition is deleterious not only to the precepts of oral interpretation, but also--in a larger sense--to the…

Method of determining forest production from remotely sensed forest parameters

DOEpatents

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

1987-08-31

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

Apply an Augmented Reality in a Mobile Guidance to Increase Sense of Place for Heritage Places

ERIC Educational Resources Information Center

Chang, Yu-Lien; Hou, Huei-Tse; Pan, Chao-Yang; Sung, Yao-Ting; Chang, Kuo-En

2015-01-01

Based on the sense of place theory and the design principles of guidance and interpretation, this study developed an augmented reality mobile guidance system that used a historical geo-context-embedded visiting strategy. This tool for heritage guidance and educational activities enhanced visitor sense of place. This study consisted of 3 visitor…

Biomedical imaging with THz waves

NASA Astrophysics Data System (ADS)

Nguyen, Andrew

2010-03-01

We discuss biomedical imaging using radio waves operating in the terahertz (THz) range between 300 GHz to 3 THz. Particularly, we present the concept for two THz imaging systems. One system employs single antenna, transmitter and receiver operating over multi-THz-frequency simultaneously for sensing and imaging small areas of the human body or biological samples. Another system consists of multiple antennas, a transmitter, and multiple receivers operating over multi-THz-frequency capable of sensing and imaging simultaneously the whole body or large biological samples. Using THz waves for biomedical imaging promises unique and substantial medical benefits including extremely small medical devices, extraordinarily fine spatial resolution, and excellent contrast between images of diseased and healthy tissues. THz imaging is extremely attractive for detection of cancer in the early stages, sensing and imaging of tissues near the skin, and study of disease and its growth versus time.

EPIC'S NEW REMOTE SENSING DATA AND INFORMATION TOOLS AVAILABLE FOR EPA CUSTOMERS

EPA Science Inventory

EPIC's New Remote Sensing Data and Information Tools Available for EPA Customers Donald Garofalo Environmental Photographic Interpretation Center (EPIC) Landscape Ecology Branch Environmental Sciences Division National Exposure Research Laboratory

Several new too...

God image and happiness in chronic pain patients: the mediating role of disease interpretation.

PubMed

Dezutter, Jessie; Luyckx, Koen; Schaap-Jonker, Hanneke; Büssing, Arndt; Corveleyn, Jozef; Hutsebaut, Dirk

2010-05-01

The present study explored the role of the emotional experience of God (i.e., positive and negative God images) in the happiness of chronic pain (CP) patients. Framed in the transactional model of stress, we tested a model in which God images would influence happiness partially through its influence on disease interpretation as a mediating mechanism. We expected God images to have both a direct and an indirect (through the interpretation of disease) effect on happiness. A cross-sectional questionnaire design was adopted in order to measure demographics, pain condition, God images, disease interpretation, and happiness. One hundred thirty-six CP patients, all members of a national patients' association, completed the questionnaires. Correlational analyses showed meaningful associations among God images, disease interpretation, and happiness. Path analyses from a structural equation modeling approach indicated that positive God images seemed to influence happiness, both directly and indirectly through the pathway of positive interpretation of the disease. Ancillary analyses showed that the negative influence of angry God images on happiness disappeared after controlling for pain severity. The results indicated that one's emotional experience of God has an influence on happiness in CP patients, both directly and indirectly through the pathway of positive disease interpretation. These findings can be framed within the transactional theory of stress and can stimulate further pain research investigating the possible effects of religion in the adaptation to CP.

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

NASA Astrophysics Data System (ADS)

Niethammer, U.; Joswig, M.

2009-04-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Satellites, Remote Sensing, and Classroom Geography for Canadian Teachers.

ERIC Educational Resources Information Center

Kirman, Joseph M.

1998-01-01

Argues that remote sensing images are a powerful tool for teaching geography. Discusses the use of remote sensing images in the classroom and provides a number of sources for them, some free, many on the World Wide Web. Reviews each source's usefulness for different grade levels and geographic topics. (DSK)

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.

Photogrammetric Processing of Planetary Linear Pushbroom Images Based on Approximate Orthophotos

NASA Astrophysics Data System (ADS)

Geng, X.; Xu, Q.; Xing, S.; Hou, Y. F.; Lan, C. Z.; Zhang, J. J.

2018-04-01

It is still a great challenging task to efficiently produce planetary mapping products from orbital remote sensing images. There are many disadvantages in photogrammetric processing of planetary stereo images, such as lacking ground control information and informative features. Among which, image matching is the most difficult job in planetary photogrammetry. This paper designs a photogrammetric processing framework for planetary remote sensing images based on approximate orthophotos. Both tie points extraction for bundle adjustment and dense image matching for generating digital terrain model (DTM) are performed on approximate orthophotos. Since most of planetary remote sensing images are acquired by linear scanner cameras, we mainly deal with linear pushbroom images. In order to improve the computational efficiency of orthophotos generation and coordinates transformation, a fast back-projection algorithm of linear pushbroom images is introduced. Moreover, an iteratively refined DTM and orthophotos scheme was adopted in the DTM generation process, which is helpful to reduce search space of image matching and improve matching accuracy of conjugate points. With the advantages of approximate orthophotos, the matching results of planetary remote sensing images can be greatly improved. We tested the proposed approach with Mars Express (MEX) High Resolution Stereo Camera (HRSC) and Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) images. The preliminary experimental results demonstrate the feasibility of the proposed approach.

Geoheritage, geotourism and cultural landscapes in Scotland

NASA Astrophysics Data System (ADS)

Gordon, John E.

2015-04-01

Geoheritage is closely linked with many aspects of cultural heritage and the development of tourism in Scotland. Historically, aesthetic appreciation of the physical landscape and links with literature and art formed the foundation for tourism during the 18th and 19th centuries. Today, exploration of the cultural links between geodiversity and landscape is providing new opportunities for raising awareness of geoheritage through literature, poetry, art and the built heritage. Interpreting the cultural dimension of geodiversity can enable people to connect with geodiversity through different experiences and a renewed sense of wonder about the physical landscape and the creative inspiration provided by geodiversity. It can also link geodiversity to cultural roots and sense of place, allowing exploration of different connections between people and the natural world. Such experiential engagement is promoted through the development of Geoparks. It requires thinking about how interpretation can add value to people's experiences and provide involvement that evokes a sense of wonder about the physical landscape. This means encouraging new and memorable experiential ways of interpreting the landscape and communicating its geological stories, not simply presenting information. Rediscovering a sense of wonder about the physical landscape through cultural links can enable wider public appreciation of geoheritage and help to develop greater support for geoconservation.

Research Issues in Image Registration for Remote Sensing

NASA Technical Reports Server (NTRS)

Eastman, Roger D.; LeMoigne, Jacqueline; Netanyahu, Nathan S.

2007-01-01

Image registration is an important element in data processing for remote sensing with many applications and a wide range of solutions. Despite considerable investigation the field has not settled on a definitive solution for most applications and a number of questions remain open. This article looks at selected research issues by surveying the experience of operational satellite teams, application-specific requirements for Earth science, and our experiments in the evaluation of image registration algorithms with emphasis on the comparison of algorithms for subpixel accuracy. We conclude that remote sensing applications put particular demands on image registration algorithms to take into account domain-specific knowledge of geometric transformations and image content.

Effectiveness of an e-Learning Platform for Image Interpretation Education of Medical Staff and Students.

PubMed

Ogura, Akio; Hayashi, Norio; Negishi, Tohru; Watanabe, Haruyuki

2018-05-09

Medical staff must be able to perform accurate initial interpretations of radiography to prevent diagnostic errors. Education in medical image interpretation is an ongoing need that is addressed by text-based and e-learning platforms. The effectiveness of these methods has been previously reported. Here, we describe the effectiveness of an e-learning platform used for medical image interpretation education. Ten third-year medical students without previous experience in chest radiography interpretation were provided with e-learning instructions. Accuracy of diagnosis using chest radiography was provided before and after e-learning education. We measured detection accuracy for two image groups: nodular shadow and ground-glass shadow. We also distributed the e-learning system to the two groups and analyzed the effectiveness of education for both types of image shadow. The mean correct answer rate after the 2-week e-learning period increased from 34.5 to 72.7%. Diagnosis of the ground glass shadow improved significantly more than that of the mass shadow. Education using the e-leaning platform is effective for interpretation of chest radiography results. E-learning is particularly effective for the interpretation of chest radiography images containing ground glass shadow.

Quantification of fatigue cracking in CT specimens with passive and active piezoelectric sensing

NASA Astrophysics Data System (ADS)

Yu, Jianguo; Ziehl, Paul; Zarate, Boris; Caicedo, Juan; Yu, Lingyu; Giurgiutiu, Victor; Metrovich, Brian; Matta, Fabio

2010-04-01

Monitoring of fatigue cracks in steel bridges is of interest to bridge owners and agencies. Monitoring of fatigue cracks has been attempted with acoustic emission using either resonant or broadband sensors. One drawback of passive sensing is that the data is limited to that caused by growing cracks. In this work, passive emission was complemented with active sensing (piezoelectric wafer active sensors) for enhanced detection capabilities. Passive and active sensing methods were described for fatigue crack monitoring on specialized compact tension specimens. The characteristics of acoustic emission were obtained to understand the correlation of acoustic emission behavior and crack growth. Crack and noise induced signals were interpreted through Swansong II Filter and waveform-based approaches, which are appropriate for data interpretation of field tests. Upon detection of crack extension, active sensing was activated to measure the crack size. Model updating techniques were employed to minimize the difference between the numerical results and experimental data. The long term objective of this research is to develop an in-service prognostic system to monitor structural health and to assess the remaining fatigue life.

New Tools for Viewing Spectrally and Temporally-Rich Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Bradley, E. S.; Toomey, M. P.; Roberts, D. A.; Still, C. J.

2010-12-01

High frequency, temporally extensive remote sensing datasets (GOES: 30 minutes, Santa Cruz Island webcam: nearly 5 years at every 10 min.) and airborne imaging spectrometry (AVIRIS with 224 spectral bands), present exciting opportunities for education, synthesis, and analysis. However, the large file volume / size can make holistic review and exploration difficult. In this research, we explore two options for visualization (1) a web-based portal for time-series analysis, PanOpt, and (2) Google Earth-based timestamped image overlays. PanOpt is an interactive website (http://zulu.geog.ucsb.edu/panopt/), which integrates high frequency (GOES) and multispectral (MODIS) satellite imagery with webcam ground-based repeat photography. Side-by-side comparison of satellite imagery with webcam images supports analysis of atmospheric and environmental phenomena. In this proof of concept, we have integrated four years of imagery for a multi-view FogCam on Santa Cruz Island off the coast of Southern California with two years of GOES-11 and four years of MODIS Aqua imagery subsets for the area (14,000 km2). From the PHP-based website, users can search the data (date, time of day, etc.) and specify timestep and display size; and then view the image stack as animations or in a matrix form. Extracted metrics for regions of interest (ROIs) can be viewed in different formats, including time-series and scatter plots. Through click and mouseover actions over the hyperlink-enabled data points, users can view the corresponding images. This directly melds the quantitative and qualitative aspects and could be particularly effective for both education as well as anomaly interpretation. We have also extended this project to Google Earth with timestamped GOES and MODIS image overlays, which can be controlled using the temporal slider and linked to a screen chart of ancillary meteorological data. The automated ENVI/IDL script for generating KMZ overlays was also applied for generating same-day visualization of AVIRIS acquisitions as part of the Gulf of Mexico oil spill response. This supports location-focused imagery review and synthesis, which is critical for successfully imaging moving targets, such as oil slicks.

The effect of a chest imaging lecture on emergency department doctors' ability to interpret chest CT images: a randomized study.

PubMed

Keijzers, Gerben; Sithirasenan, Vasugi

2012-02-01

To assess the chest computed tomography (CT) imaging interpreting skills of emergency department (ED) doctors and to study the effect of a CT chest imaging interpretation lecture on these skills. Sixty doctors in two EDs were randomized, using computerized randomization, to either attend a chest CT interpretation lecture or not to attend this lecture. Within 2 weeks of the lecture, the participants completed a questionnaire on demographic variables, anatomical knowledge, and diagnostic interpretation of 10 chest CT studies. Outcome measures included anatomical knowledge score, diagnosis score, and the combined overall score, all expressed as a percentage of correctly answered questions (0-100). Data on 58 doctors were analyzed, of which 27 were randomized to attend the lecture. The CT interpretation lecture did not have an effect on anatomy knowledge scores (72.9 vs. 70.2%), diagnosis scores (71.2 vs. 69.2%), or overall scores (71.4 vs. 69.5%). Twenty-nine percent of doctors stated that they had a systematic approach to chest CT interpretation. Overall self-perceived competency for interpreting CT imaging (brain, chest, abdomen) was low (between 3.2 and 5.2 on a 10-point Visual Analogue Scale). A single chest CT interpretation lecture did not improve chest CT interpretation by ED doctors. Less than one-third of doctors had a systematic approach to chest CT interpretation. A standardized systematic approach may improve interpretation skills.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1983-01-01

Multispectral scanning, infrared imagery, thematic mapping, and spectroradiometry from LANDSAT, GOES, and ground based instruments are being used to determine conifer distribution, maximum and minimum temperatures, topography, and crop diseases in Michigan's lower Peninsula. Image interpretation and automatic digital processing information from LANDSAT data are employed to classify and map the coniferous forests. Radiant temperature data from GOES were compared to temperature readings from the climatological station network. Digital data from LANDSAT is being used to develop techniques for detecting, monitoring, and modeling land surface change. Improved reflectance signatures through spectroradiometry aided in the detection of viral diseases in blueberry fields and vineyards. Soil survey maps from aerial reconnaissance are included as well as information on education, conferences, and awards.

Left-right asymmetry of the gnathostome skull: its evolutionary, developmental, and functional aspects.

PubMed

Compagnucci, Claudia; Fish, Jennifer; Depew, Michael J

2014-06-01

Much of the gnathostome (jawed vertebrate) evolutionary radiation was dependent on the ability to sense and interpret the environment and subsequently act upon this information through utilization of a specialized mode of feeding involving the jaws. While the gnathostome skull, reflective of the vertebrate baüplan, typically is bilaterally symmetric with right (dextral) and left (sinistral) halves essentially representing mirror images along the midline, both adaptive and abnormal asymmetries have appeared. Herein we provide a basic primer on studies of the asymmetric development of the gnathostome skull, touching briefly on asymmetry as a field of study, then describing the nature of cranial development and finally underscoring evolutionary and functional aspects of left-right asymmetric cephalic development. © 2014 Wiley Periodicals, Inc.

Landsat maps (phase V, deliverable 60), ASTER maps (phase V, deliverable 62), ASTER_DEM maps (phase V, deliverable 63), and spectral remote sensing in support of PRISM-II mineral resource assessment project, Islamic Republic of Mauritania (phase V, deliverables 61 and 64): Chapter E in Second projet de renforcement institutionnel du secteur minier de la République Islamique de Mauritanie (PRISM-II)

USGS Publications Warehouse

Rockwell, Barnaby W.; Knepper, Daniel H.; Horton, John D.

2015-01-01

The image products derived from Landsat TM and ASTER data enable the delineation of mineral groups across wide areas based on color response. Guides are provided that allow users to interpret these colors as to mineral group occurrence over lithologic units and known deposits. This information can be extrapolated to other geologically permissive tracts for various deposit types in the search for similar mineralogic responses that may be indicative of concealed deposits.

Tree-ring width reveals the preparation of the 1974 Mt. Etna eruption

PubMed Central

Seiler, Ruedi; Houlié, Nicolas; Cherubini, Paolo

2017-01-01

Reduced near-infrared reflectance observed in September 1973 in Skylab images of the western flank of Mt. Etna has been interpreted as an eruption precursor of the January 1974 eruption. Until now, it has been unclear when this signal started, whether it was sustained and which process(es) could have caused it. By analyzing tree-ring width time-series, we show that the reduced near-infrared precursory signal cannot be linked to a reduction in annual tree growth in the area. However, comparing the tree-ring width time-series with both remote sensing observations and volcano-seismic activity enables us to discuss the starting date of the pre-eruptive period of the 1974 eruption. PMID:28266610

High resolution seismic-reflection imaging of shallow deformation beneath the northeast margin of the Manila high at Big Lake, Arkansas

USGS Publications Warehouse

Odum, J.K.; Stephenson, W.J.; Williams, R.A.; Worley, D.M.; Guccione, M.J.; Van Arsdale, R.B.

2001-01-01

The Manila high, an elliptical area 19 km long (N-S) by 6 km wide (E-W) located west-southwest of Big Lake. Arkansas, has less than 3 m of topographic relief. Geomorphic, stratigraphic and chronology data indicate that Big Lake formed during at least two periods of Holocene uplift and subsequent damming of the south-flowing Little River. Age data of an organic mat located at the base of an upper lacustrine deposit indicates an abrupt, possibly tectonic, formation of the present Big Lake between AD 1640 and 1950. We acquired 7 km of high-resolution seismic-reflection data across the northeastern margin of the Manila high to examine its near-surface bedrock structure and possible association with underlying structures such as the Blytheville arch. Sense of displacement and character of imaged faults support interpretations for either a northwest trending, 1.5 km-wide, block of uplifted strata or a series of parallel northeast-trending faults that bound horst and graben structures. We interpret deformation of the Manila high to result from faulting generated by the reactivation of right-lateral strike-slip fault motion along this portion of the Blytheville arch. The most recent uplift of the Manila high may have occurred during the December 16, 1811, New Madrid earthquake. Published by Elsevier Science B.V.

A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape.

PubMed

Lausch, Angela; Pause, Marion; Merbach, Ines; Zacharias, Steffen; Doktor, Daniel; Volk, Martin; Seppelt, Ralf

2013-02-01

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the "One Sensor at Different Scales" (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R (2) of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.

Wind Streaks on Earth; Exploration and Interpretation

NASA Astrophysics Data System (ADS)

Cohen-Zada, Aviv Lee; Blumberg, Dan G.; Maman, Shimrit

2015-04-01

Wind streaks, one of the most common aeolian features on planetary surfaces, are observable on the surface of the planets Earth, Mars and Venus. Due to their reflectance properties, wind streaks are distinguishable from their surroundings, and they have thus been widely studied by remote sensing since the early 1970s, particularly on Mars. In imagery, these streaks are interpreted as the presence - or lack thereof - of small loose particles on the surface deposited or eroded by wind. The existence of wind streaks serves as evidence for past or present active aeolian processes. Therefore, wind streaks are thought to represent integrative climate processes. As opposed to the comprehensive and global studies of wind streaks on Mars and Venus, wind streaks on Earth are understudied and poorly investigated, both geomorphologically and by remote sensing. The aim of this study is, thus, to fill the knowledge gap about the wind streaks on Earth by: generating a global map of Earth wind streaks from modern high-resolution remotely sensed imagery; incorporating the streaks in a geographic information system (GIS); and overlaying the GIS layers with boundary layer wind data from general circulation models (GCMs) and data from the ECMWF Reanalysis Interim project. The study defines wind streaks (and thereby distinguishes them from other aeolian features) based not only on their appearance in imagery but more importantly on their surface appearance. This effort is complemented by a focused field investigation to study wind streaks on the ground and from a variety of remotely sensed images (both optical and radar). In this way, we provide a better definition of the physical and geomorphic characteristics of wind streaks and acquire a deeper knowledge of terrestrial wind streaks as a means to better understand global and planetary climate and climate change. In a preliminary study, we detected and mapped over 2,900 wind streaks in the desert regions of Earth distributed in approximately 500 sites. Most terrestrial wind streaks are formed on a relatively young geological surface and are concentrated along the equator (± 30°). They are categorized by the combination of their planform and reflectance; with linear-bright and dark are the most common. A site-specific examination of remote-sensing effects on wind streaks identification has been conducted. The results thus far, indicate that in images with varying spatial and spectral specifications some wind streaks are actually composed of other aeolian bedforms, especially dunes. Specific regions of the Earth were then compared qualitatively to surface wind data extracted from a general circulation model. Understanding the mechanism and spatial and temporal distribution of wind streak formation is important not only for understanding surface modifications in the geomorphological context but also for shedding light on past and present climatic processes and atmospheric circulation on Earth. This study yields an explanation for wind streaks as a geomorphological feature. Moreover, it is in this planet-wide geomorphological research ability to lay down the foundations for comparative planetary research.

Fuzzy intelligent quality monitoring model for X-ray image processing.

PubMed

Khalatbari, Azadeh; Jenab, Kouroush

2009-01-01

Today's imaging diagnosis needs to adapt modern techniques of quality engineering to maintain and improve its accuracy and reliability in health care system. One of the main factors that influences diagnostic accuracy of plain film X-ray on detecting pathology is the level of film exposure. If the level of film exposure is not adequate, a normal body structure may be interpretated as pathology and vice versa. This not only influences the patient management but also has an impact on health care cost and patient's quality of life. Therefore, providing an accurate and high quality image is the first step toward an excellent patient management in any health care system. In this paper, we study these techniques and also present a fuzzy intelligent quality monitoring model, which can be used to keep variables from degrading the image quality. The variables derived from chemical activity, cleaning procedures, maintenance, and monitoring may not be sensed, measured, or calculated precisely due to uncertain situations. Therefore, the gamma-level fuzzy Bayesian model for quality monitoring of an image processing is proposed. In order to apply the Bayesian concept, the fuzzy quality characteristics are assumed as fuzzy random variables. Using the fuzzy quality characteristics, the newly developed model calculates the degradation risk for image processing. A numerical example is also presented to demonstrate the application of the model.

First Atomic Force Microscope Image from Mars

NASA Technical Reports Server (NTRS)

2008-01-01

This calibration image presents three-dimensional data from the atomic force microscope on NASA's Phoenix Mars Lander, showing surface details of a substrate on the microscope station's sample wheel. It will be used as an aid for interpreting later images that will show shapes of minuscule Martian soil particles.

The area imaged by the microscope is 40 microns by 40 microns, small enough to fit on an eyelash. The grooves in this substrate are 14 microns (0.00055 inch) apart, from center to center. The vertical dimension is exaggerated in the image to make surface details more visible. The grooves are 300 nanometers (0.00001 inch) deep.

This is the first atomic force microscope image recorded on another planet. It was taken on July 9, 2008, during the 44th Martian day, or sol, of the Phoenix mission since landing.

Phoenix's Swiss-made atomic force microscope builds an image of the surface shape of a particle by sensing it with a sharp tip at the end of a spring, all microfabricated out of a silicon wafer. A strain gauge records how far the spring flexes to follow the contour of the surface. It can provide details of soil-particle shapes smaller than one-hundredth the width of a human hair. This is about 20 times smaller than what can be resolved with Phoenix's optical microscope, which has provided much higher-magnification imaging than anything seen on Mars previously. Both microscopes are part of Phoenix's Microscopy, Electrochemistry and Conductivity Analyzer.