A spectrum fractal feature classification algorithm for agriculture crops with hyper spectrum image
NASA Astrophysics Data System (ADS)
Su, Junying
2011-11-01
A fractal dimension feature analysis method in spectrum domain for hyper spectrum image is proposed for agriculture crops classification. Firstly, a fractal dimension calculation algorithm in spectrum domain is presented together with the fast fractal dimension value calculation algorithm using the step measurement method. Secondly, the hyper spectrum image classification algorithm and flowchart is presented based on fractal dimension feature analysis in spectrum domain. Finally, the experiment result of the agricultural crops classification with FCL1 hyper spectrum image set with the proposed method and SAM (spectral angle mapper). The experiment results show it can obtain better classification result than the traditional SAM feature analysis which can fulfill use the spectrum information of hyper spectrum image to realize precision agricultural crops classification.
Thematic mapper design parameter investigation
NASA Technical Reports Server (NTRS)
Colby, C. P., Jr.; Wheeler, S. G.
1978-01-01
This study simulated the multispectral data sets to be expected from three different Thematic Mapper configurations, and the ground processing of these data sets by three different resampling techniques. The simulated data sets were then evaluated by processing them for multispectral classification, and the Thematic Mapper configuration, and resampling technique which provided the best classification accuracy were identified.
NASA Technical Reports Server (NTRS)
Wrigley, R. C.; Acevedo, W.; Alexander, D.; Buis, J.; Card, D.
1984-01-01
An experiment of a factorial design was conducted to test the effects on classification accuracy of land cover types due to the improved spatial, spectral and radiometric characteristics of the Thematic Mapper (TM) in comparison to the Multispectral Scanner (MSS). High altitude aircraft scanner data from the Airborne Thematic Mapper instrument was acquired over central California in August, 1983 and used to simulate Thematic Mapper data as well as all combinations of the three characteristics for eight data sets in all. Results for the training sites (field center pixels) showed better classification accuracies for MSS spatial resolution, TM spectral bands and TM radiometry in order of importance.
MetalMapper: A Multi-Sensor TEM System for UXO Detection and Classification
2011-02-01
accelerometer to measure pitch and roll angles and a 3-axis fluxgate magnetometer that provides reference heading to magnetic...investigations included a magnetometer transect survey and an EMI survey over a larger area to assist in selecting a
NASA Technical Reports Server (NTRS)
Hoffer, R. M. (Principal Investigator); Knowlton, D. J.; Dean, M. E.
1981-01-01
Supervised and cluster block training statistics were used to analyze the thematic mapper simulation MSS data (both 1979 and 1980 data sets). Cover information classes identified on SAR imagery include: hardwood, pine, mixed pine hardwood, clearcut, pasture, crops, emergent crops, bare soil, urban, and water. Preliminary analysis of the HH and HV polarized SAR data indicate a high variance associated with each information class except for water and bare soil. The large variance for most spectral classes suggests that while the means might be statistically separable, an overlap may exist between the classes which could introduce a significant classification error. The quantitative values of many cover types are much larger on the HV polarization than on the HH, thereby indicating the relative nature of the digitized data values. The mean values of the spectral classes in the areas with larger look angles are greater than the means of the same cover type in other areas having steeper look angles. Difficulty in accurately overlaying the dual polarization of the SAR data was resolved.
A classification model of Hyperion image base on SAM combined decision tree
NASA Astrophysics Data System (ADS)
Wang, Zhenghai; Hu, Guangdao; Zhou, YongZhang; Liu, Xin
2009-10-01
Monitoring the Earth using imaging spectrometers has necessitated more accurate analyses and new applications to remote sensing. A very high dimensional input space requires an exponentially large amount of data to adequately and reliably represent the classes in that space. On the other hand, with increase in the input dimensionality the hypothesis space grows exponentially, which makes the classification performance highly unreliable. Traditional classification algorithms Classification of hyperspectral images is challenging. New algorithms have to be developed for hyperspectral data classification. The Spectral Angle Mapper (SAM) is a physically-based spectral classification that uses an ndimensional angle to match pixels to reference spectra. The algorithm determines the spectral similarity between two spectra by calculating the angle between the spectra, treating them as vectors in a space with dimensionality equal to the number of bands. The key and difficulty is that we should artificial defining the threshold of SAM. The classification precision depends on the rationality of the threshold of SAM. In order to resolve this problem, this paper proposes a new automatic classification model of remote sensing image using SAM combined with decision tree. It can automatic choose the appropriate threshold of SAM and improve the classify precision of SAM base on the analyze of field spectrum. The test area located in Heqing Yunnan was imaged by EO_1 Hyperion imaging spectrometer using 224 bands in visual and near infrared. The area included limestone areas, rock fields, soil and forests. The area was classified into four different vegetation and soil types. The results show that this method choose the appropriate threshold of SAM and eliminates the disturbance and influence of unwanted objects effectively, so as to improve the classification precision. Compared with the likelihood classification by field survey data, the classification precision of this model heightens 9.9%.
On-board multispectral classification study
NASA Technical Reports Server (NTRS)
Ewalt, D.
1979-01-01
The factors relating to onboard multispectral classification were investigated. The functions implemented in ground-based processing systems for current Earth observation sensors were reviewed. The Multispectral Scanner, Thematic Mapper, Return Beam Vidicon, and Heat Capacity Mapper were studied. The concept of classification was reviewed and extended from the ground-based image processing functions to an onboard system capable of multispectral classification. Eight different onboard configurations, each with varying amounts of ground-spacecraft interaction, were evaluated. Each configuration was evaluated in terms of turnaround time, onboard processing and storage requirements, geometric and classification accuracy, onboard complexity, and ancillary data required from the ground.
NASA Technical Reports Server (NTRS)
Quattrochi, D. A.
1984-01-01
An initial analysis of LANDSAT 4 Thematic Mapper (TM) data for the discrimination of agricultural, forested wetland, and urban land covers is conducted using a scene of data collected over Arkansas and Tennessee. A classification of agricultural lands derived from multitemporal LANDSAT Multispectral Scanner (MSS) data is compared with a classification of TM data for the same area. Results from this comparative analysis show that the multitemporal MSS classification produced an overall accuracy of 80.91% while the TM classification yields an overall classification accuracy of 97.06% correct.
Unsupervised change detection in a particular vegetation land cover type using spectral angle mapper
NASA Astrophysics Data System (ADS)
Renza, Diego; Martinez, Estibaliz; Molina, Iñigo; Ballesteros L., Dora M.
2017-04-01
This paper presents a new unsupervised change detection methodology for multispectral images applied to specific land covers. The proposed method involves comparing each image against a reference spectrum, where the reference spectrum is obtained from the spectral signature of the type of coverage you want to detect. In this case the method has been tested using multispectral images (SPOT5) of the community of Madrid (Spain), and multispectral images (Quickbird) of an area over Indonesia that was impacted by the December 26, 2004 tsunami; here, the tests have focused on the detection of changes in vegetation. The image comparison is obtained by applying Spectral Angle Mapper between the reference spectrum and each multitemporal image. Then, a threshold to produce a single image of change is applied, which corresponds to the vegetation zones. The results for each multitemporal image are combined through an exclusive or (XOR) operation that selects vegetation zones that have changed over time. Finally, the derived results were compared against a supervised method based on classification with the Support Vector Machine. Furthermore, the NDVI-differencing and the Spectral Angle Mapper techniques were selected as unsupervised methods for comparison purposes. The main novelty of the method consists in the detection of changes in a specific land cover type (vegetation), therefore, for comparison purposes, the best scenario is to compare it with methods that aim to detect changes in a specific land cover type (vegetation). This is the main reason to select NDVI-based method and the post-classification method (SVM implemented in a standard software tool). To evaluate the improvements using a reference spectrum vector, the results are compared with the basic-SAM method. In SPOT5 image, the overall accuracy was 99.36% and the κ index was 90.11%; in Quickbird image, the overall accuracy was 97.5% and the κ index was 82.16%. Finally, the precision results of the method are comparable to those of a supervised method, supported by low detection of false positives and false negatives, along with a high overall accuracy and a high kappa index. On the other hand, the execution times were comparable to those of unsupervised methods of low computational load.
Study of carbonate concretions using imaging spectroscopy in the Frontier Formation, Wyoming
NASA Astrophysics Data System (ADS)
de Linaje, Virginia Alonso; Khan, Shuhab D.; Bhattacharya, Janok
2018-04-01
Imaging spectroscopy is applied to study diagenetic processes of the Wall Creek Member of the Cretaceous Frontier Formation, Wyoming. Visible Near-Infrared and Shortwave-Infrared hyperspectral cameras were used to scan near vertical and well-exposed outcrop walls to analyze lateral and vertical geochemical variations. Reflectance spectra were analyzed and compared with high-resolution laboratory spectral and hyperspectral imaging data. Spectral Angle Mapper (SAM) and Mixture Tuned Matched Filtering (MTMF) classification algorithms were applied to quantify facies and mineral abundances in the Frontier Formation. MTMF is the most effective and reliable technique when studying spectrally similar materials. Classification results show that calcite cement in concretions associated with the channel facies is homogeneously distributed, whereas the bar facies was shown to be interbedded with layers of non-calcite-cemented sandstone.
David L. Evans
1994-01-01
A forest cover classification of the Kisatchie National Forest, Catahoula Ranger district, was performed with Landsat Thematic Mapper data. Data base retrievals and map products from this analysis demonstrated use of Landsat for forest management decisions.
NASA Technical Reports Server (NTRS)
Quattrochi, D. A.; Anderson, J. E.; Brannon, D. P.; Hill, C. L.
1982-01-01
An initial analysis of LANDSAT 4 thematic mapper (TM) data for the delineation and classification of agricultural, forested wetland, and urban land covers was conducted. A study area in Poinsett County, Arkansas was used to evaluate a classification of agricultural lands derived from multitemporal LANDSAT multispectral scanner (MSS) data in comparison with a classification of TM data for the same area. Data over Reelfoot Lake in northwestern Tennessee were utilized to evaluate the TM for delineating forested wetland species. A classification of the study area was assessed for accuracy in discriminating five forested wetland categories. Finally, the TM data were used to identify urban features within a small city. A computer generated classification of Union City, Tennessee was analyzed for accuracy in delineating urban land covers. An evaluation of digitally enhanced TM data using principal components analysis to facilitate photointerpretation of urban features was also performed.
NASA Astrophysics Data System (ADS)
Padma, S.; Sanjeevi, S.
2014-12-01
This paper proposes a novel hyperspectral matching algorithm by integrating the stochastic Jeffries-Matusita measure (JM) and the deterministic Spectral Angle Mapper (SAM), to accurately map the species and the associated landcover types of the mangroves of east coast of India using hyperspectral satellite images. The JM-SAM algorithm signifies the combination of a qualitative distance measure (JM) and a quantitative angle measure (SAM). The spectral capabilities of both the measures are orthogonally projected using the tangent and sine functions to result in the combined algorithm. The developed JM-SAM algorithm is implemented to discriminate the mangrove species and the landcover classes of Pichavaram (Tamil Nadu), Muthupet (Tamil Nadu) and Bhitarkanika (Odisha) mangrove forests along the Eastern Indian coast using the Hyperion image dat asets that contain 242 bands. The developed algorithm is extended in a supervised framework for accurate classification of the Hyperion image. The pixel-level matching performance of the developed algorithm is assessed by the Relative Spectral Discriminatory Probability (RSDPB) and Relative Spectral Discriminatory Entropy (RSDE) measures. From the values of RSDPB and RSDE, it is inferred that hybrid JM-SAM matching measure results in improved discriminability of the mangrove species and the associated landcover types than the individual SAM and JM algorithms. This performance is reflected in the classification accuracies of species and landcover map of Pichavaram mangrove ecosystem. Thus, the JM-SAM (TAN) matching algorithm yielded an accuracy better than SAM and JM measures at an average difference of 13.49 %, 7.21 % respectively, followed by JM-SAM (SIN) at 12.06%, 5.78% respectively. Similarly, in the case of Muthupet, JM-SAM (TAN) yielded an increased accuracy than SAM and JM measures at an average difference of 12.5 %, 9.72 % respectively, followed by JM-SAM (SIN) at 8.34 %, 5.55% respectively. For Bhitarkanika, the combined JM-SAM (TAN) and (SIN) measures improved the performance of individual SAM by (16.1 %, 15%) and of JM by (10.3%, 9.2%) respectively.
Mapping Glauconite Unites with Using Remote Sensing Techniques in North East of Iran
NASA Astrophysics Data System (ADS)
Ahmadirouhani, R.; Samiee, S.
2014-10-01
Glauconite is a greenish ferric-iron silicate mineral with micaceous structure, characteristically formed in shallow marine environments. Glauconite has been used as a pigmentation agent for oil paint, contaminants remover in environmental studies and a source of potassium in plant fertilizers, and other industries. Koppeh-dagh basin is extended in Iran, Afghanistan and Turkmenistan countries and Glauconite units exist in this basin. In this research for enhancing and mapping glauconitic units in Koppeh-dagh structural zone in north east of Iran, remote sensing techniques such as Spectral Angle Mapper classification (SAM), band ratio and band composition methods on SPOT, ASTER and Landsat data in 3 steps were applied.
Development of image mappers for hyperspectral biomedical imaging applications
Kester, Robert T.; Gao, Liang; Tkaczyk, Tomasz S.
2010-01-01
A new design and fabrication method is presented for creating large-format (>100 mirror facets) image mappers for a snapshot hyperspectral biomedical imaging system called an image mapping spectrometer (IMS). To verify this approach a 250 facet image mapper with 25 multiple-tilt angles is designed for a compact IMS that groups the 25 subpupils in a 5 × 5 matrix residing within a single collecting objective's pupil. The image mapper is fabricated by precision diamond raster fly cutting using surface-shaped tools. The individual mirror facets have minimal edge eating, tilt errors of <1 mrad, and an average roughness of 5.4 nm. PMID:20357875
Forest/non-forest stratification in Georgia with Landsat Thematic Mapper data
William H. Cooke
2000-01-01
Geographically accurate Forest Inventory and Analysis (FIA) data may be useful for training, classification, and accuracy assessment of Landsat Thematic Mapper (TM) data. Minimum expectation for maps derived from Landsat data is accurate discrimination of several land cover classes. Landsat TM costs have decreased dramatically, but acquiring cloud-free scenes at...
VEGETATION CLASSIFICATION OF THE SAN PEDRO RIPARIAN CORRIDOR
This data set is a vegetation classification of the San Pedro riparian corridor. The classification was accomplished using a combination of Thematic Mapper Simulator (TMS) imagery from JPL, and high resolution color infrared photography (CIR)from USDA ARS Weslaco Tx, supported by...
NASA Technical Reports Server (NTRS)
Hoffer, R. M.; Dean, M. E.; Knowlton, D. J.; Latty, R. S.
1982-01-01
Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented.
NASA Technical Reports Server (NTRS)
Malila, W. A.; Gleason, J. M.; Cicone, R. C.
1976-01-01
A simulation study was carried out to characterize atmospheric effects in LANDSAT-D Thematic Mapper data. In particular, the objective was to determine if any differences would result from using a linear vs. a conical scanning geometry. Insight also was gained about the overall effect of the atmosphere on Thematic Mapper signals, together with the effects of time of day. An added analysis was made of the geometric potential for direct specular reflections (sun glint). The ERIM multispectral system simulation model was used to compute inband Thematic Mapper radiances, taking into account sensor, atmospheric, and surface characteristics. Separate analyses were carried out for the thermal band and seven bands defined in the reflective spectral region. Reflective-region radiances were computed for 40 deg N, 0 deg, and 40 deg S latitudes; June, Mar., and Dec. days; and 9:30 and 11:00 AM solar times for both linear and conical scan modes. Also, accurate simulations of solar and viewing geometries throughout Thematic Mapper orbits were made. It is shown that the atmosphere plays an important role in determining Thematic Mapper radiances, with atmospheric path radiance being the major component of total radiances for short wavelengths and decreasing in importance as wavelength increases. Path radiance is shown to depend heavily on the direct radiation scattering angle and on haze content. Scan-angle-dependent variations were shown to be substantial, especially for the short-wavelength bands.
Classification of hyperspectral imagery with neural networks: comparison to conventional tools
NASA Astrophysics Data System (ADS)
Merényi, Erzsébet; Farrand, William H.; Taranik, James V.; Minor, Timothy B.
2014-12-01
Efficient exploitation of hyperspectral imagery is of great importance in remote sensing. Artificial intelligence approaches have been receiving favorable reviews for classification of hyperspectral data because the complexity of such data challenges the limitations of many conventional methods. Artificial neural networks (ANNs) were shown to outperform traditional classifiers in many situations. However, studies that use the full spectral dimensionality of hyperspectral images to classify a large number of surface covers are scarce if non-existent. We advocate the need for methods that can handle the full dimensionality and a large number of classes to retain the discovery potential and the ability to discriminate classes with subtle spectral differences. We demonstrate that such a method exists in the family of ANNs. We compare the maximum likelihood, Mahalonobis distance, minimum distance, spectral angle mapper, and a hybrid ANN classifier for real hyperspectral AVIRIS data, using the full spectral resolution to map 23 cover types and using a small training set. Rigorous evaluation of the classification accuracies shows that the ANN outperforms the other methods and achieves ≈90% accuracy on test data.
NASA Technical Reports Server (NTRS)
Hill, C. L.
1984-01-01
A computer-implemented classification has been derived from Landsat-4 Thematic Mapper data acquired over Baldwin County, Alabama on January 15, 1983. One set of spectral signatures was developed from the data by utilizing a 3x3 pixel sliding window approach. An analysis of the classification produced from this technique identified forested areas. Additional information regarding only the forested areas. Additional information regarding only the forested areas was extracted by employing a pixel-by-pixel signature development program which derived spectral statistics only for pixels within the forested land covers. The spectral statistics from both approaches were integrated and the data classified. This classification was evaluated by comparing the spectral classes produced from the data against corresponding ground verification polygons. This iterative data analysis technique resulted in an overall classification accuracy of 88.4 percent correct for slash pine, young pine, loblolly pine, natural pine, and mixed hardwood-pine. An accuracy assessment matrix has been produced for the classification.
a Hyperspectral Based Method to Detect Cannabis Plantation in Inaccessible Areas
NASA Astrophysics Data System (ADS)
Houmi, M.; Mohamadi, B.; Balz, T.
2018-04-01
The increase in drug use worldwide has led to sophisticated illegal planting methods. Most countries depend on helicopters, and local knowledge to identify such illegal plantations. However, remote sensing techniques can provide special advantages for monitoring the extent of illegal drug production. This paper sought to assess the ability of the Satellite remote sensing to detect Cannabis plantations. This was achieved in two stages: 1- Preprocessing of Hyperspectral data EO-1, and testing the capability to collect the spectral signature of Cannabis in different sites of the study area (Morocco) from well-known Cannabis plantation fields. 2- Applying the method of Spectral Angle Mapper (SAM) based on a specific angle threshold on Hyperion data EO-1 in well-known Cannabis plantation sites, and other sites with negative Cannabis plantation in another study area (Algeria), to avoid any false Cannabis detection using these spectra. This study emphasizes the benefits of using hyperspectral remote sensing data as an effective detection tool for illegal Cannabis plantation in inaccessible areas based on SAM classification method with a maximum angle (radians) less than 0.03.
Analysis of thematic mapper simulator data collected over eastern North Dakota
NASA Technical Reports Server (NTRS)
Anderson, J. E. (Principal Investigator)
1982-01-01
The results of the analysis of aircraft-acquired thematic mapper simulator (TMS) data, collected to investigate the utility of thematic mapper data in crop area and land cover estimates, are discussed. Results of the analysis indicate that the seven-channel TMS data are capable of delineating the 13 crop types included in the study to an overall pixel classification accuracy of 80.97% correct, with relative efficiencies for four crop types examined between 1.62 and 26.61. Both supervised and unsupervised spectral signature development techniques were evaluated. The unsupervised methods proved to be inferior (based on analysis of variance) for the majority of crop types considered. Given the ground truth data set used for spectral signature development as well as evaluation of performance, it is possible to demonstrate which signature development technique would produce the highest percent correct classification for each crop type.
Forest tree species discrimination in western Himalaya using EO-1 Hyperion
NASA Astrophysics Data System (ADS)
George, Rajee; Padalia, Hitendra; Kushwaha, S. P. S.
2014-05-01
The information acquired in the narrow bands of hyperspectral remote sensing data has potential to capture plant species spectral variability, thereby improving forest tree species mapping. This study assessed the utility of spaceborne EO-1 Hyperion data in discrimination and classification of broadleaved evergreen and conifer forest tree species in western Himalaya. The pre-processing of 242 bands of Hyperion data resulted into 160 noise-free and vertical stripe corrected reflectance bands. Of these, 29 bands were selected through step-wise exclusion of bands (Wilk's Lambda). Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) algorithms were applied to the selected bands to assess their effectiveness in classification. SVM was also applied to broadband data (Landsat TM) to compare the variation in classification accuracy. All commonly occurring six gregarious tree species, viz., white oak, brown oak, chir pine, blue pine, cedar and fir in western Himalaya could be effectively discriminated. SVM produced a better species classification (overall accuracy 82.27%, kappa statistic 0.79) than SAM (overall accuracy 74.68%, kappa statistic 0.70). It was noticed that classification accuracy achieved with Hyperion bands was significantly higher than Landsat TM bands (overall accuracy 69.62%, kappa statistic 0.65). Study demonstrated the potential utility of narrow spectral bands of Hyperion data in discriminating tree species in a hilly terrain.
Neuro-classification of multi-type Landsat Thematic Mapper data
NASA Technical Reports Server (NTRS)
Zhuang, Xin; Engel, Bernard A.; Fernandez, R. N.; Johannsen, Chris J.
1991-01-01
Neural networks have been successful in image classification and have shown potential for classifying remotely sensed data. This paper presents classifications of multitype Landsat Thematic Mapper (TM) data using neural networks. The Landsat TM Image for March 23, 1987 with accompanying ground observation data for a study area In Miami County, Indiana, U.S.A. was utilized to assess recognition of crop residues. Principal components and spectral ratio transformations were performed on the TM data. In addition, a layer of the geographic information system (GIS) for the study site was incorporated to generate GIS-enhanced TM data. This paper discusses (1) the performance of neuro-classification on each type of data, (2) how neural networks recognized each type of data as a new image and (3) comparisons of the results for each type of data obtained using neural networks, maximum likelihood, and minimum distance classifiers.
NASA Technical Reports Server (NTRS)
Hoffer, R. M. (Principal Investigator); Knowlton, D. J.; Dean, M. E.
1981-01-01
A set of training statistics for the 30 meter resolution simulated thematic mapper MSS data was generated based on land use/land cover classes. In addition to this supervised data set, a nonsupervised multicluster block of training statistics is being defined in order to compare the classification results and evaluate the effect of the different training selection methods on classification performance. Two test data sets, defined using a stratified sampling procedure incorporating a grid system with dimensions of 50 lines by 50 columns, and another set based on an analyst supervised set of test fields were used to evaluate the classifications of the TMS data. The supervised training data set generated training statistics, and a per point Gaussian maximum likelihood classification of the 1979 TMS data was obtained. The August 1980 MSS data was radiometrically adjusted. The SAR data was redigitized and the SAR imagery was qualitatively analyzed.
Classification of corn and soybeans using multitemporal Thematic Mapper data
NASA Technical Reports Server (NTRS)
Badhwar, G. D.
1984-01-01
The multitemporal classification approach based on the greenness profile derived from Landsat Multispectral Scanner (MSS) spectral bands has proved successful in effectively separating and identifying corn, soybean, and other ground cover classes. Features derived from these profiles have been shown to carry virtually all the information contained in the original data and, in addition, have been shown to be stable over a large geographic area of the United States. The objective of this investigation was to determine if the same features derived from multitemporal Thematic Mapper (TM) data would also prove effective in separating these two crop types, and, in fact, if algorithms developed for MSS could be directly applied to TM. It is shown that this is indeed the case. In addition, because of greater spatial and spectral resolution, the accuracy of TM classifications is better than in MSS.
Time Series of Images to Improve Tree Species Classification
NASA Astrophysics Data System (ADS)
Miyoshi, G. T.; Imai, N. N.; de Moraes, M. V. A.; Tommaselli, A. M. G.; Näsi, R.
2017-10-01
Tree species classification provides valuable information to forest monitoring and management. The high floristic variation of the tree species appears as a challenging issue in the tree species classification because the vegetation characteristics changes according to the season. To help to monitor this complex environment, the imaging spectroscopy has been largely applied since the development of miniaturized sensors attached to Unmanned Aerial Vehicles (UAV). Considering the seasonal changes in forests and the higher spectral and spatial resolution acquired with sensors attached to UAV, we present the use of time series of images to classify four tree species. The study area is an Atlantic Forest area located in the western part of São Paulo State. Images were acquired in August 2015 and August 2016, generating three data sets of images: only with the image spectra of 2015; only with the image spectra of 2016; with the layer stacking of images from 2015 and 2016. Four tree species were classified using Spectral angle mapper (SAM), Spectral information divergence (SID) and Random Forest (RF). The results showed that SAM and SID caused an overfitting of the data whereas RF showed better results and the use of the layer stacking improved the classification achieving a kappa coefficient of 18.26 %.
2015-07-01
concentrations. A total of 11.23 acres of dynamic surveys were conducted using MetalMapper advanced electromagnetic induction (EMI) sensor. A total of...centimeter DGM digital geophysical mapping DSB Defense Science Board EE/CA Engineering Evaluation/Cost Analysis EMI electromagnetic induction...performed a live site demonstration project using the Geometrics MetalMapper advanced electromagnetic induction (EMI) sensor at the former
EL68D Wasteway Watershed Land-Cover Generation
Ruhl, Sheila; Usery, E. Lynn; Finn, Michael P.
2007-01-01
Classification of land cover from Landsat Enhanced Thematic Mapper Plus (ETM+) for the EL68D Wasteway Watershed in the State of Washington is documented. The procedures for classification include use of two ETM+ scenes in a simultaneous unsupervised classification process supported by extensive field data collection using Global Positioning System receivers and digital photos. The procedure resulted in a detailed classification at the individual crop species level.
Suzanne M. Joy; R. M. Reich; Richard T. Reynolds
2003-01-01
Traditional land classification techniques for large areas that use Landsat Thematic Mapper (TM) imagery are typically limited to the fixed spatial resolution of the sensors (30m). However, the study of some ecological processes requires land cover classifications at finer spatial resolutions. We model forest vegetation types on the Kaibab National Forest (KNF) in...
Yong Wang; Shanta Parajuli; Callie Schweitzer; Glendon Smalley; Dawn Lemke; Wubishet Tadesse; Xiongwen Chen
2010-01-01
Forest cover classifications focus on the overall growth form (physiognomy) of the community, dominant vegetation, and species composition of the existing forest. Accurately classifying the forest cover type is important for forest inventory and silviculture. We compared classification accuracy based on Landsat Enhanced Thematic Mapper Plus (Landsat ETM+) and Satellite...
Improved classification of small-scale urban watersheds using thematic mapper simulator data
NASA Technical Reports Server (NTRS)
Owe, M.; Ormsby, J. P.
1984-01-01
The utility of Landsat MSS classification methods in the case of small, highly urbanized hydrological basins containing complex land-use patterns is limited, and is plagued by misclassifications due to the spectral response similarity of many dissimilar surfaces. Landsat MSS data for the Conley Creek basin near Atlanta, Georgia, have been compared to thematic mapper simulator (TMS) data obtained on the same day by aircraft. The TMS data were able to alleviate many of the recurring patterns associated with MSS data, through bandwidth optimization, an increase of the number of spectral bands to seven, and an improvement of ground resolution to 30 m. The TMS is thereby able to detect small water bodies, powerline rights-of-way, and even individual buildings.
Mapping benthic macroalgal communities in the coastal zone using CHRIS-PROBA mode 2 images
NASA Astrophysics Data System (ADS)
Casal, G.; Kutser, T.; Domínguez-Gómez, J. A.; Sánchez-Carnero, N.; Freire, J.
2011-09-01
The ecological importance of benthic macroalgal communities in coastal ecosystems has been recognised worldwide and the application of remote sensing to study these communities presents certain advantages respect to in situ methods. The present study used three CHRIS-PROBA images to analyse macroalgal communities distribution in the Seno de Corcubión (NW Spain). The use of this sensor represent a challenge given that its design, build and deployment programme is intended to follow the principles of the "faster, better, cheaper". To assess the application of this sensor to macroalgal mapping, two types of classifications were carried out: Maximum Likelihood and Spectral Angle Mapper (SAM). Maximum Likelihood classifier showed positive results, reaching overall accuracy percentages higher than 90% and kappa coefficients higher than 0.80 for the bottom classes shallow submerged sand, deep submerged sand, macroalgae less than 5 m and macroalgae between 5 and 10 m depth. The differentiation among macroalgal groups using SAM classifications showed positive results for green seaweeds although the differentiation between brown and red algae was not clear in the study area.
Ullah, Saleem; Groen, Thomas A; Schlerf, Martin; Skidmore, Andrew K; Nieuwenhuis, Willem; Vaiphasa, Chaichoke
2012-01-01
Genetic variation between various plant species determines differences in their physio-chemical makeup and ultimately in their hyperspectral emissivity signatures. The hyperspectral emissivity signatures, on the one hand, account for the subtle physio-chemical changes in the vegetation, but on the other hand, highlight the problem of high dimensionality. The aim of this paper is to investigate the performance of genetic algorithms coupled with the spectral angle mapper (SAM) to identify a meaningful subset of wavebands sensitive enough to discriminate thirteen broadleaved vegetation species from the laboratory measured hyperspectral emissivities. The performance was evaluated using an overall classification accuracy and Jeffries Matusita distance. For the multiple plant species, the targeted bands based on genetic algorithms resulted in a high overall classification accuracy (90%). Concentrating on the pairwise comparison results, the selected wavebands based on genetic algorithms resulted in higher Jeffries Matusita (J-M) distances than randomly selected wavebands did. This study concludes that targeted wavebands from leaf emissivity spectra are able to discriminate vegetation species.
2016-09-23
Acquisition and Data Analysis). EMI sensors, MetalMapper, man-portable Time-domain Electromagnetic Multi-sensor Towed Array Detection System (TEMTADS...California Department of Toxic Substances Control EM61 EM61-MK2 EMI electromagnetic induction ESTCP Environmental Security Technology Certification...SOP Standard Operating Procedure v TEMTADS Time-domain Electromagnetic Multi-sensor Towed Array Detection System man-portable 2x2 TOI target(s
NASA Astrophysics Data System (ADS)
Marwaha, Richa; Kumar, Anil; Kumar, Arumugam Senthil
2015-01-01
Our primary objective was to explore a classification algorithm for thermal hyperspectral data. Minimum noise fraction is applied to thermal hyperspectral data and eight pixel-based classifiers, i.e., constrained energy minimization, matched filter, spectral angle mapper (SAM), adaptive coherence estimator, orthogonal subspace projection, mixture-tuned matched filter, target-constrained interference-minimized filter, and mixture-tuned target-constrained interference minimized filter are tested. The long-wave infrared (LWIR) has not yet been exploited for classification purposes. The LWIR data contain emissivity and temperature information about an object. A highest overall accuracy of 90.99% was obtained using the SAM algorithm for the combination of thermal data with a colored digital photograph. Similarly, an object-oriented approach is applied to thermal data. The image is segmented into meaningful objects based on properties such as geometry, length, etc., which are grouped into pixels using a watershed algorithm and an applied supervised classification algorithm, i.e., support vector machine (SVM). The best algorithm in the pixel-based category is the SAM technique. SVM is useful for thermal data, providing a high accuracy of 80.00% at a scale value of 83 and a merge value of 90, whereas for the combination of thermal data with a colored digital photograph, SVM gives the highest accuracy of 85.71% at a scale value of 82 and a merge value of 90.
K-Nearest Neighbor Estimation of Forest Attributes: Improving Mapping Efficiency
Andrew O. Finley; Alan R. Ek; Yun Bai; Marvin E. Bauer
2005-01-01
This paper describes our efforts in refining k-nearest neighbor forest attributes classification using U.S. Department of Agriculture Forest Service Forest Inventory and Analysis plot data and Landsat 7 Enhanced Thematic Mapper Plus imagery. The analysis focuses on FIA-defined forest type classification across St. Louis County in northeastern Minnesota. We outline...
NASA Technical Reports Server (NTRS)
Jackson, M. J.; Baker, J. R.; Townshend, J. R. G.; Gayler, J. E.; Hardy, J. R.
1984-01-01
In assessing the accuracy of classification techniques for Thematic Mapper data the consistency of the detector-to-detector response is critical. Preliminary studies were undertaken, therefore, to assess the significance of this factor for the TM. The overall structure of the band relationships can be examined by principal component analysis. In order to examine the utility of the Thematic Mapper data more carefully, six different land cover classes approximately Anderson level 1 were selected. These included an area of water from the sediment-laden Mississippi, woodland, agricultural land and urban land. A plume class was also selected which includes the plume of smoke emanating from the power station and drifting over the Mississippi river.
Landsat-4 MSS and Thematic Mapper data quality and information content analysis
NASA Technical Reports Server (NTRS)
Anuta, P. E.; Bartolucci, L. A.; Dean, M. E.; Lozano, D. F.; Malaret, E.; Mcgillem, C. D.; Valdes, J. A.; Valenzuela, C. R.
1984-01-01
Landsat-4 Thematic Mapper and Multispectral Scanner data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic Mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and numerous supervised classifiers on data from Iowa and Illinois. A detailed spectral class analysis (multispectral classification) was carried out on data from the Des Moines, IA area to compare the information content of the MSS and TM for a large number of scene classes.
Proposed hybrid-classifier ensemble algorithm to map snow cover area
NASA Astrophysics Data System (ADS)
Nijhawan, Rahul; Raman, Balasubramanian; Das, Josodhir
2018-01-01
Metaclassification ensemble approach is known to improve the prediction performance of snow-covered area. The methodology adopted in this case is based on neural network along with four state-of-art machine learning algorithms: support vector machine, artificial neural networks, spectral angle mapper, K-mean clustering, and a snow index: normalized difference snow index. An AdaBoost ensemble algorithm related to decision tree for snow-cover mapping is also proposed. According to available literature, these methods have been rarely used for snow-cover mapping. Employing the above techniques, a study was conducted for Raktavarn and Chaturangi Bamak glaciers, Uttarakhand, Himalaya using multispectral Landsat 7 ETM+ (enhanced thematic mapper) image. The study also compares the results with those obtained from statistical combination methods (majority rule and belief functions) and accuracies of individual classifiers. Accuracy assessment is performed by computing the quantity and allocation disagreement, analyzing statistic measures (accuracy, precision, specificity, AUC, and sensitivity) and receiver operating characteristic curves. A total of 225 combinations of parameters for individual classifiers were trained and tested on the dataset and results were compared with the proposed approach. It was observed that the proposed methodology produced the highest classification accuracy (95.21%), close to (94.01%) that was produced by the proposed AdaBoost ensemble algorithm. From the sets of observations, it was concluded that the ensemble of classifiers produced better results compared to individual classifiers.
Mark D. Nelson; Ronald E. McRoberts; Greg C. Liknes; Geoffrey R. Holden
2005-01-01
Landsat Thematic Mapper (TM) satellite imagery and Forest Inventory and Analysis (FIA) plot data were used to construct forest/nonforest maps of Mapping Zone 41, National Land Cover Dataset 2000 (NLCD 2000). Stratification approaches resulting from Maximum Likelihood, Fuzzy Convolution, Logistic Regression, and k-Nearest Neighbors classification/prediction methods were...
Landsat TM Classifications For SAFIS Using FIA Field Plots
William H. Cooke; Andrew J. Hartsell
2001-01-01
Wall-to-wall Landsat Thematic Mapper (TM) classification efforts in Georgia require field validation. We developed a new crown modeling procedure based on Forest Health Monitoring (FHM) data to test Forest Inventory and Analysis (FIA) data. These models simulate the proportion of tree crowns that reflect light on a FIA subplot basis. We averaged subplot crown...
Dale D. Gormanson; Mark H. Hansen; Ronald E. McRoberts
2005-01-01
In an extensive forest inventory, stratifications that use dual-date forest/nonforest classifications of Landsat Thematic Mapper data approximately 10 years apart are tested against similar classifications that use data from only one date. Alternative stratifications that further define edge strata as pixels adjacent to a forest/nonforest boundary are included in the...
NASA Technical Reports Server (NTRS)
Heric, Matthew; Cox, William; Gordon, Daniel K.
1987-01-01
In an attempt to improve the land cover/use classification accuracy obtainable from remotely sensed multispectral imagery, Airborne Imaging Spectrometer-1 (AIS-1) images were analyzed in conjunction with Thematic Mapper Simulator (NS001) Large Format Camera color infrared photography and black and white aerial photography. Specific portions of the combined data set were registered and used for classification. Following this procedure, the resulting derived data was tested using an overall accuracy assessment method. Precise photogrammetric 2D-3D-2D geometric modeling techniques is not the basis for this study. Instead, the discussion exposes resultant spectral findings from the image-to-image registrations. Problems associated with the AIS-1 TMS integration are considered, and useful applications of the imagery combination are presented. More advanced methodologies for imagery integration are needed if multisystem data sets are to be utilized fully. Nevertheless, research, described herein, provides a formulation for future Earth Observation Station related multisensor studies.
Kim, Heekang; Kwon, Soon; Kim, Sungho
2016-07-08
This paper proposes a vehicle light detection method using a hyperspectral camera instead of a Charge-Coupled Device (CCD) or Complementary metal-Oxide-Semiconductor (CMOS) camera for adaptive car headlamp control. To apply Intelligent Headlight Control (IHC), the vehicle headlights need to be detected. Headlights are comprised from a variety of lighting sources, such as Light Emitting Diodes (LEDs), High-intensity discharge (HID), and halogen lamps. In addition, rear lamps are made of LED and halogen lamp. This paper refers to the recent research in IHC. Some problems exist in the detection of headlights, such as erroneous detection of street lights or sign lights and the reflection plate of ego-car from CCD or CMOS images. To solve these problems, this study uses hyperspectral images because they have hundreds of bands and provide more information than a CCD or CMOS camera. Recent methods to detect headlights used the Spectral Angle Mapper (SAM), Spectral Correlation Mapper (SCM), and Euclidean Distance Mapper (EDM). The experimental results highlight the feasibility of the proposed method in three types of lights (LED, HID, and halogen).
Analysis methods for Thematic Mapper data of urban regions
NASA Technical Reports Server (NTRS)
Wang, S. C.
1984-01-01
Studies have indicated the difficulty in deriving a detailed land-use/land-cover classification for heterogeneous metropolitan areas with Landsat MSS and TM data. The major methodological issues of digital analysis which possibly have effected the results of classification are examined. In response to these methodological issues, a multichannel hierarchical clustering algorithm has been developed and tested for a more complete analysis of the data for urban areas.
Spectroscopic classification of SN 2018bwp as a type Ia supernova a few weeks after peak brightness
NASA Astrophysics Data System (ADS)
Lopez-Sanchez, Angel R.; Galbany, Lluis; Ascasibar, Yago; Fiegert, Kristin; Barnes, Timothy; Cunningham, Casey; Cristiano, Tony; Dean, Sarah; Edwards, Robert; East, Nicholas; Franks, Karen; Hams, Julie; Higgins, Robert Ian; Hogan, Jennifer; Last, Rusel; Longmuir, Mark; McRae, Andrew; McElhinney, Neil; Miller, Rosie; Murphy, Chris; Quarrell, Christopher Daniel Andrew; O'Donnell, Gianna; Rochler, Michael; Roberts, Hayden; Robinson, Lyn; Soule, Stephan; Spillman, Natalie J.; Shelmerdine, Paul; Vassie, Robert; Vickers, Michael; Westwood, Jennifer A.; Smethurst, Rebecca J.; Lintott, Chris; Moller, Anais; Tucker, Brad; Armstrong, Patrick; Bray, Charles; Chang, Seo-Won; Onken, Chris; Ridden-Harper, Ryan; Taylor, Georgie; Ruiter, Ashley; Cox, Brian; Zemiro, Julia
2018-05-01
We report the spectroscopic classification of SN 2018bwp (RA=13:25:54.77, DEC=-37:14:12.05) in the galaxy 2MASX J13255427-3714139 . The candidate was discovered by the SkyMapper Transient (SMT) survey (Scalzo et al. 2017, PASA, 34:30) on UT 2018-05-04 09:50 UT at 19.1 mag in the r-band.
Spectroscopic classification of SN 2018bwq as a type Ia supernova a few days before maximum light.
NASA Astrophysics Data System (ADS)
Lopez-Sanchez, Angel R.; Galbany, Lluis; Ascasibar, Yago; Fiegert, Kristin; Burchat, Leigh; Long, Barb; Roberts, Hayden; Newling, Pip; Smethurst, Rebecca J.; Lintott, Chris; Moller, Anais; Tucker, Brad; Armstrong, Patrick; Bray, Charles; Chang, Seo-Won; Onken, Chris; Ridden-Harper, Ryan; Taylor, Georgie; Ruiter, Ashley; Cox, Brian; Zemiro, Julia
2018-05-01
We report the spectroscopic classification of SN 2018bwq (RA=21:29:11.76, DEC=-29:09:46.2) in the galaxy 2MASX J21291210-2909468. The candidate was discovered by the SkyMapper Transient (SMT) survey (Scalzo et al. 2017, PASA, 34:30) on UT 2018-05-13 15:34 UT at 19.32 mag in the r-band.
LANDSAT-4 MSS and Thematic Mapper data quality and information content analysis
NASA Technical Reports Server (NTRS)
Anuta, P.; Bartolucci, L.; Dean, E.; Lozano, F.; Malaret, E.; Mcgillem, C. D.; Valdes, J.; Valenzuela, C.
1984-01-01
LANDSAT-4 thematic mapper (TM) and multispectral scanner (MSS) data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and supervised classifiers on test data. A detailed spectral class analysis (multispectral classification) was carried out to compare the information content of the MSS and TM for a large number of scene classes. A temperature-mapping experiment was carried out for a cooling pond to test the quality of thermal-band calibration. Overall TM data quality is very good. The MSS data are noisier than previous LANDSAT results.
Nelson, G.; Ramsey, Elijah W.; Rangoonwala, A.
2005-01-01
Landsat Thematic Mapper images and collateral data sources were used to classify the land cover of the Mermentau River Basin within the chenier coastal plain and the adjacent uplands of Louisiana, USA. Landcover classes followed that of the National Oceanic and Atmospheric Administration's Coastal Change Analysis Program; however, classification methods needed to be developed to meet these national standards. Our first classification was limited to the Mermentau River Basin (MRB) in southcentral Louisiana, and the years of 1990, 1993, and 1996. To overcome problems due to class spectral inseparable, spatial and spectra continuums, mixed landcovers, and abnormal transitions, we separated the coastal area into regions of commonality and applying masks to specific land mixtures. Over the three years and 14 landcover classes (aggregating the cultivated land and grassland, and water and floating vegetation classes), overall accuracies ranged from 82% to 90%. To enhance landcover change interpretation, three indicators were introduced as Location Stability, Residence stability, and Turnover. Implementing methods substantiated in the multiple date MRB classification, we spatially extended the classification to the entire Louisiana coast and temporally extended the original 1990, 1993, 1996 classifications to 1999 (Figure 1). We also advanced the operational functionality of the classification and increased the credibility of change detection results. Increased operational functionality that resulted in diminished user input was for the most part gained by implementing a classification logic based on forbidden transitions. The logic detected and corrected misclassifications and mostly alleviated the necessity of subregion separation prior to the classification. The new methods provided an improved ability for more timely detection and response to landcover impact. ?? 2005 IEEE.
Spectroscopic classification of icy satellites of Saturn II: Identification of terrain units on Rhea
NASA Astrophysics Data System (ADS)
Scipioni, F.; Tosi, F.; Stephan, K.; Filacchione, G.; Ciarniello, M.; Capaccioni, F.; Cerroni, P.
2014-05-01
Rhea is the second largest icy satellites of Saturn and it is mainly composed of water ice. Its surface is characterized by a leading hemisphere slightly brighter than the trailing side. The main goal of this work is to identify homogeneous compositional units on Rhea by applying the Spectral Angle Mapper (SAM) classification technique to Rhea’s hyperspectral images acquired by the Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini Orbiter in the infrared range (0.88-5.12 μm). The first step of the classification is dedicated to the identification of Rhea’s spectral endmembers by applying the k-means unsupervised clustering technique to four hyperspectral images representative of a limited portion of the surface, imaged at relatively high spatial resolution. We then identified eight spectral endmembers, corresponding to as many terrain units, which mostly distinguish for water ice abundance and ice grain size. In the second step, endmembers are used as reference spectra in SAM classification method to achieve a comprehensive classification of the entire surface. From our analysis of the infrared spectra returned by VIMS, it clearly emerges that Rhea’ surface units shows differences in terms of water ice bands depths, average ice grain size, and concentration of contaminants, particularly CO2 and hydrocarbons. The spectral units that classify optically dark terrains are those showing suppressed water ice bands, a finer ice grain size and a higher concentration of carbon dioxide. Conversely, spectral units labeling brighter regions have deeper water ice absorption bands, higher albedo and a smaller concentration of contaminants. All these variations reflect surface’s morphological and geological structures. Finally, we performed a comparison between Rhea and Dione, to highlight different magnitudes of space weathering effects in the icy satellites as a function of the distance from Saturn.
NASA Astrophysics Data System (ADS)
Naidoo, L.; Cho, M. A.; Mathieu, R.; Asner, G.
2012-04-01
The accurate classification and mapping of individual trees at species level in the savanna ecosystem can provide numerous benefits for the managerial authorities. Such benefits include the mapping of economically useful tree species, which are a key source of food production and fuel wood for the local communities, and of problematic alien invasive and bush encroaching species, which can threaten the integrity of the environment and livelihoods of the local communities. Species level mapping is particularly challenging in African savannas which are complex, heterogeneous, and open environments with high intra-species spectral variability due to differences in geology, topography, rainfall, herbivory and human impacts within relatively short distances. Savanna vegetation are also highly irregular in canopy and crown shape, height and other structural dimensions with a combination of open grassland patches and dense woody thicket - a stark contrast to the more homogeneous forest vegetation. This study classified eight common savanna tree species in the Greater Kruger National Park region, South Africa, using a combination of hyperspectral and Light Detection and Ranging (LiDAR)-derived structural parameters, in the form of seven predictor datasets, in an automated Random Forest modelling approach. The most important predictors, which were found to play an important role in the different classification models and contributed to the success of the hybrid dataset model when combined, were species tree height; NDVI; the chlorophyll b wavelength (466 nm) and a selection of raw, continuum removed and Spectral Angle Mapper (SAM) bands. It was also concluded that the hybrid predictor dataset Random Forest model yielded the highest classification accuracy and prediction success for the eight savanna tree species with an overall classification accuracy of 87.68% and KHAT value of 0.843.
Use of field reflectance data for crop mapping using airborne hyperspectral image
NASA Astrophysics Data System (ADS)
Nidamanuri, Rama Rao; Zbell, Bernd
2011-09-01
Recent developments in hyperspectral remote sensing technologies enable acquisition of image with high spectral resolution, which is typical to the laboratory or in situ reflectance measurements. There has been an increasing interest in the utilization of in situ reference reflectance spectra for rapid and repeated mapping of various surface features. Here we examined the prospect of classifying airborne hyperspectral image using field reflectance spectra as the training data for crop mapping. Canopy level field reflectance measurements of some important agricultural crops, i.e. alfalfa, winter barley, winter rape, winter rye, and winter wheat collected during four consecutive growing seasons are used for the classification of a HyMAP image acquired for a separate location by (1) mixture tuned matched filtering (MTMF), (2) spectral feature fitting (SFF), and (3) spectral angle mapper (SAM) methods. In order to answer a general research question "what is the prospect of using independent reference reflectance spectra for image classification", while focussing on the crop classification, the results indicate distinct aspects. On the one hand, field reflectance spectra of winter rape and alfalfa demonstrate excellent crop discrimination and spectral matching with the image across the growing seasons. On the other hand, significant spectral confusion detected among the winter barley, winter rye, and winter wheat rule out the possibility of existence of a meaningful spectral matching between field reflectance spectra and image. While supporting the current notion of "non-existence of characteristic reflectance spectral signatures for vegetation", results indicate that there exist some crops whose spectral signatures are similar to characteristic spectral signatures with possibility of using them in image classification.
NASA Astrophysics Data System (ADS)
Catelli, Emilio; Randeberg, Lise Lyngsnes; Alsberg, Bjørn Kåre; Gebremariam, Kidane Fanta; Bracci, Silvano
2017-04-01
Hyperspectral imaging (HSI) is a fast non-invasive imaging technology recently applied in the field of art conservation. With the help of chemometrics, important information about the spectral properties and spatial distribution of pigments can be extracted from HSI data. With the intent of expanding the applications of chemometrics to the interpretation of hyperspectral images of historical documents, and, at the same time, to study the colorants and their spatial distribution on ancient illuminated manuscripts, an explorative chemometric approach is here presented. The method makes use of chemometric tools for spectral de-noising (minimum noise fraction (MNF)) and image analysis (multivariate image analysis (MIA) and iterative key set factor analysis (IKSFA)/spectral angle mapper (SAM)) which have given an efficient separation, classification and mapping of colorants from visible-near-infrared (VNIR) hyperspectral images of an ancient illuminated fragment. The identification of colorants was achieved by extracting and interpreting the VNIR spectra as well as by using a portable X-ray fluorescence (XRF) spectrometer.
Landsat-7 long-term acquisition plan radiometry - evolution over time
Markham, Brian L; Goward, Samuel; Arvidson, Terry; Barsi, Julia A.; Scaramuzza, Pat
2006-01-01
The Landsat-7 Enhanced Thematic Mapper Plus instrument has two selectable gains for each spectral band. In the acquisition plan, the gains were initially set to maximize the entropy in each scene. One unintended consequence of this strategy was that, at times, dense vegetation saturated band 4 and deserts saturated all bands. A revised strategy, based on a land-cover classification and sun angle thresholds, reduced saturation, but resulted in gain changes occurring within the same scene on multiple overpasses. As the gain changes cause some loss of data and difficulties for some ground processing systems, a procedure was devised to shift the gain changes to the nearest predicted cloudy scenes. The results are still not totally satisfactory as gain changes still impact some scenes and saturation still occurs, particularly in ephemerally snow-covered regions. A primary conclusion of our experience with variable gain on Landsat-7 is that such an approach should not be employed on future global monitoring missions.
Applying six classifiers to airborne hyperspectral imagery for detecting giant reed
USDA-ARS?s Scientific Manuscript database
This study evaluated and compared six different image classifiers, including minimum distance (MD), Mahalanobis distance (MAHD), maximum likelihood (ML), spectral angle mapper (SAM), mixture tuned matched filtering (MTMF) and support vector machine (SVM), for detecting and mapping giant reed (Arundo...
Demonstration of angular anisotropy in the output of Thematic Mapper
NASA Technical Reports Server (NTRS)
Duggin, M. J. (Principal Investigator); Lindsay, J.; Piwinski, D. J.; Schoch, L. B.
1984-01-01
There is a dependence of TM output (proportional to scene radiance in a manner which will be discussed) upon season, upon cover type and upon view angle. The existence of a significant systematic variation across uniform scenes in p-type (radiometrically and geometrically pre-processed) data is demonstrated. Present pre-processing does remove the effects and the problem must be addressed because the effects are large. While this is in no way attributable to any shortcomings in the thematic mapper, it is an effect which is sufficiently important to warrant more study, with a view to developing suitable pre-processing correction algorithms.
Podwysocki, Melvin H.; Power, Marty S.; Salisbury, Jack; Jones, O.D.
1984-01-01
Landsat-4 Thematic Mapper (TM) data of southern Nevada collected under conditions of low-angle solar illumination were digitally processed to identify hydroxyl-bearing minerals commonly associated with hydrothermal alteration in volcanic terrains. Digital masking procedures were used to exclude shadow areas and vegetation and thus to produce a CRC image suitable for testing the new TM bands as a means to map hydrothermally altered rocks. Field examination of a masked CRC image revealed that several different types of altered rocks displayed hues associated with spectral characteristics common to hydroxyl-bearing minerals. Several types of unaltered rocks also displayed similar hues.
Kim, Heekang; Kwon, Soon; Kim, Sungho
2016-01-01
This paper proposes a vehicle light detection method using a hyperspectral camera instead of a Charge-Coupled Device (CCD) or Complementary metal-Oxide-Semiconductor (CMOS) camera for adaptive car headlamp control. To apply Intelligent Headlight Control (IHC), the vehicle headlights need to be detected. Headlights are comprised from a variety of lighting sources, such as Light Emitting Diodes (LEDs), High-intensity discharge (HID), and halogen lamps. In addition, rear lamps are made of LED and halogen lamp. This paper refers to the recent research in IHC. Some problems exist in the detection of headlights, such as erroneous detection of street lights or sign lights and the reflection plate of ego-car from CCD or CMOS images. To solve these problems, this study uses hyperspectral images because they have hundreds of bands and provide more information than a CCD or CMOS camera. Recent methods to detect headlights used the Spectral Angle Mapper (SAM), Spectral Correlation Mapper (SCM), and Euclidean Distance Mapper (EDM). The experimental results highlight the feasibility of the proposed method in three types of lights (LED, HID, and halogen). PMID:27399720
NASA Astrophysics Data System (ADS)
Nikonow, Wilhelm; Rammlmair, Dieter
2017-10-01
Recent developments in the application of micro-energy-dispersive X-ray fluorescence spectrometry mapping (µ-EDXRF) have opened up new opportunities for fast geoscientific analyses. Acquiring spatially resolved spectral and chemical information non-destructively for large samples of up to 20 cm length provides valuable information for geoscientific interpretation. Using supervised classification of the spectral information, mineral distribution maps can be obtained. In this work, thin sections of plutonic rocks are analyzed by µ-EDXRF and classified using the supervised classification algorithm spectral angle mapper (SAM). Based on the mineral distribution maps, it is possible to obtain quantitative mineral information, i.e., to calculate the modal mineralogy, search and locate minerals of interest, and perform image analysis. The results are compared to automated mineralogy obtained from the mineral liberation analyzer (MLA) of a scanning electron microscope (SEM) and show good accordance, revealing variation resulting mostly from the limit of spatial resolution of the µ-EDXRF instrument. Taking into account the little time needed for sample preparation and measurement, this method seems suitable for fast sample overviews with valuable chemical, mineralogical and textural information. Additionally, it enables the researcher to make better and more targeted decisions for subsequent analyses.
Identifying and classifying water hyacinth (Eichhornia crassipes) using the HyMap sensor
NASA Astrophysics Data System (ADS)
Rajapakse, Sepalika S.; Khanna, Shruti; Andrew, Margaret E.; Ustin, Susan L.; Lay, Mui
2006-08-01
In recent years, the impact of aquatic invasive species on biodiversity has become a major global concern. In the Sacramento-San Joaquin Delta region in the Central Valley of California, USA, dense infestations of the invasive aquatic emergent weed, water hyacinth (Eichhornia crassipes) interfere with ecosystem functioning. This silent invader constantly encroaches into waterways, eventually making them unusable by people and uninhabitable to aquatic fauna. Quantifying and mapping invasive plant species in aquatic ecosystems is important for efficient management and implementation of mitigation measures. This paper evaluates the ability of hyperspectral imagery, acquired using the HyMap sensor, for mapping water hyacinth in the Sacramento-San Joaquin Delta region. Classification was performed on sixty-four flightlines acquired over the study site using a decision tree which incorporated Spectral Angle Mapper (SAM) algorithm, absorption feature parameters in the spectral region between 0.4 and 2.5μm, and spectral endmembers. The total image dataset was 130GB. Spectral signatures of other emergent aquatic species like pennywort (Hydrocotyle ranunculoides) and water primrose (Ludwigia peploides) showed close similarity with the water hyacinth spectrum, however, the decision tree successfully discriminated water hyacinth from other emergent aquatic vegetation species. The classification algorithm showed high accuracy (κ value = 0.8) in discriminating water hyacinth.
THEMATIC ACCURACY OF MRLC LAND COVER FOR THE EASTERN UNITED STATES
One objective of the MultiResolution Land Characteristics (MRLC) consortium is to map general land-cover categories for the conterminous United States using Landsat Thematic Mapper (TM) data. Land-cover mapping and classification accuracy assessment are complete for the e...
Classifying multispectral data by neural networks
NASA Technical Reports Server (NTRS)
Telfer, Brian A.; Szu, Harold H.; Kiang, Richard K.
1993-01-01
Several energy functions for synthesizing neural networks are tested on 2-D synthetic data and on Landsat-4 Thematic Mapper data. These new energy functions, designed specifically for minimizing misclassification error, in some cases yield significant improvements in classification accuracy over the standard least mean squares energy function. In addition to operating on networks with one output unit per class, a new energy function is tested for binary encoded outputs, which result in smaller network sizes. The Thematic Mapper data (four bands were used) is classified on a single pixel basis, to provide a starting benchmark against which further improvements will be measured. Improvements are underway to make use of both subpixel and superpixel (i.e. contextual or neighborhood) information in tile processing. For single pixel classification, the best neural network result is 78.7 percent, compared with 71.7 percent for a classical nearest neighbor classifier. The 78.7 percent result also improves on several earlier neural network results on this data.
FIREX mission requirements document for nonrenewable resources
NASA Technical Reports Server (NTRS)
Dixon, T.; Carsey, F.
1982-01-01
The proposed mission requirements and a proposed experimental program for satellite synthetic aperture radar (SAR) system named FIREX (Free-Flying Imaging Radar Experiment) for nonrenewable resources is described. The recommended spacecraft minimum SAR system is a C-band imager operating in four modes: (1) low look angle HH-polarized; (2) intermediate look angle, HH-polarized; (3) intermediate look angle, IIV-polarized; and (4) high look angle HH-polarized. This SAR system is complementary to other future spaceborne imagers such as the Thematic Mapper on LANDSAT-D. A near term aircraft SAR based research program is outlined which addresses specific mission design issues such as preferred incidence angles or polarizations for geologic targets of interest.
NASA Technical Reports Server (NTRS)
Enslin, William R.; Ton, Jezching; Jain, Anil
1987-01-01
Landsat TM data were combined with land cover and planimetric data layers contained in the State of Michigan's geographic information system (GIS) to identify changes in forestlands, specifically new oil/gas wells. A GIS-guided feature-based classification method was developed. The regions extracted by the best image band/operator combination were studied using a set of rules based on the characteristics of the GIS oil/gas pads.
NASA Technical Reports Server (NTRS)
Kiang, Richard K.
1992-01-01
Neural networks have been applied to classifications of remotely sensed data with some success. To improve the performance of this approach, an examination was made of how neural networks are applied to the optical character recognition (OCR) of handwritten digits and letters. A three-layer, feedforward network, along with techniques adopted from OCR, was used to classify Landsat-4 Thematic Mapper data. Good results were obtained. To overcome the difficulties that are characteristic of remote sensing applications and to attain significant improvements in classification accuracy, a special network architecture may be required.
Monitoring Global Precipitation through UCI CHRS's RainMapper App on Mobile Devices
NASA Astrophysics Data System (ADS)
Nguyen, P.; Huynh, P.; Braithwaite, D.; Hsu, K. L.; Sorooshian, S.
2014-12-01
The Water and Development Information for Arid Lands-a Global Network (G-WADI) Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks—Cloud Classification System (PERSIANN-CCS) GeoServer has been developed through a collaboration between the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California, Irvine (UCI) and the UNESCO's International Hydrological Program (IHP). G-WADI PERSIANN-CCS GeoServer provides near real-time high resolution (0.04o, approx 4km) global (60oN - 60oS) satellite precipitation estimated by the PERSIANN-CCS algorithm developed by the scientists at CHRS. The G-WADI PERSIANN-CCS GeoServer utilizes the open-source MapServer software from the University of Minnesota to provide a user-friendly web-based mapping and visualization of satellite precipitation data. Recent efforts have been made by the scientists at CHRS to provide free on-the-go access to the PERSIANN-CCS precipitation data through an application named RainMapper for mobile devices. RainMapper provides visualization of global satellite precipitation of the most recent 3, 6, 12, 24, 48 and 72-hour periods overlaid with various basemaps. RainMapper uses the Google maps application programing interface (API) and embedded global positioning system (GPS) access to better monitor the global precipitation data on mobile devices. Functionalities include using geographical searching with voice recognition technologies make it easy for the user to explore near real-time precipitation in a certain location. RainMapper also allows for conveniently sharing the precipitation information and visualizations with the public through social networks such as Facebook and Twitter. RainMapper is available for iOS and Android devices and can be downloaded (free) from the App Store and Google Play. The usefulness of RainMapper was demonstrated through an application in tracking the evolution of the recent Rammasun Typhoon over the Philippines in mid July 2014.
NASA Astrophysics Data System (ADS)
Laoufi, Fatiha; Belbachir, Ahmed-Hafid; Benabadji, Noureddine; Zanoun, Abdelouahab
2011-10-01
We have mapped the region of Oran, Algeria, using multispectral remote sensing with different resolutions. For the identification of objects on the ground using their spectral signatures, two methods were applied to images from SPOT, LANDSAT, IRS-1 C and ASTER. The first one is called Base Rule method (BR method) and is based on a set of rules that must be met at each pixel in the different bands reflectance calibrated and henceforth it is assigned to a given class. The construction of these rules is based on the spectral profiles of popular classes in the scene studied. The second one is called Spectral Angle Mapper method (SAM method) and is based on the direct calculation of the spectral angle between the target vector representing the spectral profile of the desired class and the pixel vector whose components are numbered accounts in the different bands of the calibrated image reflectance. This new method was performed using PCSATWIN software developed by our own laboratory LAAR. After collecting a library of spectral signatures with multiple libraries, a detailed study of the principles and physical processes that can influence the spectral signature has been conducted. The final goal is to establish the range of variation of a spectral profile of a well-defined class and therefore to get precise bases for spectral rules. From the results we have obtained, we find that the supervised classification of these pixels by BR method derived from spectral signatures reduces the uncertainty associated with identifying objects by enhancing significantly the percentage of correct classification with very distinct classes.
Collection of endmembers and their separability for spectral unmixing in rangeland applications
NASA Astrophysics Data System (ADS)
Rolfson, David
Rangelands are an important resource to Alberta. Due to their size, mapping rangeland features is difficult. However, the use of aerial and satellite data for mapping has increased the area that can be studied at one time. The recent success in applying hyperspectral data to vegetation mapping has shown promise in rangeland classification. However, classification mapping of hyperspectral data requires existing data for input into classification algorithms. The research reported in this thesis focused on acquiring a seasonal inventory of in-situ reflectance spectra of rangeland plant species (endmembers) and comparing them to evaluate their separability as an indicator of their suitability for hyperspectral image classification analysis. The goals of this research also included determining the separability of species endmembers at different times of the growing season. In 2008, reflectance spectra were collected for three shrub species ( Artemisia cana, Symphoricarpos occidentalis, and Rosa acicularis ), five rangeland grass species native to southern Alberta ( Koeleria gracilis, Stipa comata, Bouteloua gracilis, Agropyron smithii, Festuca idahoensis) and one invasive grass species (Agropyron cristatum ). A spectral library, built using the SPECCHIO spectral database software, was populated using these spectroradiometric measurements with a focus on vegetation spectra. Average endmembers of plant spectra acquired during the peak of sample greenness were compared using three separability measures -- normalized Euclidean distance (NED), correlation separability measure (CSM) and Modified Spectral Angle Mapper (MSAM) -- to establish the degree to which the species were separable. Results were normalized to values between 0 and 1 and values above the established thresholds indicate that the species were not separable. The endmembers for Agropyron cristatum, Agropyron smithii, and Rosa acicularis were not separable using CSM (threshold = 0.992) or MSAM (threshold = 0.970). NED (threshold = 0.950) was best able to separate species endmembers. Using reflectance data collected throughout the summer and fall, species endmembers obtained within two-week periods were analyzed using NED to plot their separability. As expected, separability of sample species changed as they progressed through their individual phenological patterns. Spectra collected during different solar zenith angles were compared to see if they affected the separability measures. Sample species endmembers were generally separable using NED during the periods in which they were measured and compared. However, Koeleria gracilis and Festuca idahoensis endmembers were inseparable from June to mid-August when measurements were taken at solar zenith angles between 25° -- 30° and 45° -- 60°. However, between 30° and 45°, Bouteloua gracilis and Festuca idahoensis endmembers, normally separable during other solar zenith angles, became spectrally similar during the same sampling period. Findings suggest that the choice of separability measures is an important factor when analyzing hyperspectral data. The differences observed in the separability results over time also suggest that the consideration of phenological patterns in planning data acquisition for rangeland classification mapping has a high level of importance.
NASA Technical Reports Server (NTRS)
Nalepka, R. F. (Principal Investigator); Sadowski, F. E.; Sarno, J. E.
1976-01-01
The author has identified the following significant results. A supervised classification within two separate ground areas of the Sam Houston National Forest was carried out for two sq meters spatial resolution MSS data. Data were progressively coarsened to simulate five additional cases of spatial resolution ranging up to 64 sq meters. Similar processing and analysis of all spatial resolutions enabled evaluations of the effect of spatial resolution on classification accuracy for various levels of detail and the effects on area proportion estimation for very general forest features. For very coarse resolutions, a subset of spectral channels which simulated the proposed thematic mapper channels was used to study classification accuracy.
Implementing Classification on a Munitions Response Project
2011-12-01
Detection Dig List IVS/Seed Site Planning Decisions Dig All Anomalies Site Characterization Implementing Classification on a Munitions Response...Details ● Seed emplacement ● EM61-MK2 detection survey RTK GPS ● Select anomalies for further investigation ● Collect cued data using MetalMapper...5.2 mV in channel 2 938 anomalies selected ● All QC seeds detected using this threshold Some just inside the 60-cm halo ● IVS reproducibility
EXhype: A tool for mineral classification using hyperspectral data
NASA Astrophysics Data System (ADS)
Adep, Ramesh Nityanand; shetty, Amba; Ramesh, H.
2017-02-01
Various supervised classification algorithms have been developed to classify earth surface features using hyperspectral data. Each algorithm is modelled based on different human expertises. However, the performance of conventional algorithms is not satisfactory to map especially the minerals in view of their typical spectral responses. This study introduces a new expert system named 'EXhype (Expert system for hyperspectral data classification)' to map minerals. The system incorporates human expertise at several stages of it's implementation: (i) to deal with intra-class variation; (ii) to identify absorption features; (iii) to discriminate spectra by considering absorption features, non-absorption features and by full spectra comparison; and (iv) finally takes a decision based on learning and by emphasizing most important features. It is developed using a knowledge base consisting of an Optimal Spectral Library, Segmented Upper Hull method, Spectral Angle Mapper (SAM) and Artificial Neural Network. The performance of the EXhype is compared with a traditional, most commonly used SAM algorithm using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data acquired over Cuprite, Nevada, USA. A virtual verification method is used to collect samples information for accuracy assessment. Further, a modified accuracy assessment method is used to get a real users accuracies in cases where only limited or desired classes are considered for classification. With the modified accuracy assessment method, SAM and EXhype yields an overall accuracy of 60.35% and 90.75% and the kappa coefficient of 0.51 and 0.89 respectively. It was also found that the virtual verification method allows to use most desired stratified random sampling method and eliminates all the difficulties associated with it. The experimental results show that EXhype is not only producing better accuracy compared to traditional SAM but, can also rightly classify the minerals. It is proficient in avoiding misclassification between target classes when applied on minerals.
MetalMapper: A Multi-Sensor TEM System for UXO Detection and Classification
2011-04-01
fluxgate magnetometer that provides reference heading to magnetic north. DeploymentCThe MM can be deployed either as a man-powered cart or as a...is a live site. Preliminary investigations included a magnetometer transect survey and an EMI survey over a larger area to assist in selecting a
ESTCP Pilot Program. Classification Approaches in Munitions Response, San Luis Obispo, California
2010-05-01
geology. Electromagnetic induction sensors detect ferrous and nonferrous metallic objects and can be effective in geology that challenges...34 5.3 Metal Mapper...correspond to munitions, but rather to other harmless metallic objects or geology: field experience indicates that often in excess of 90% of objects
The goal of this project was to determine the utility of subpixel processing of multi-temporal Landsat Enhanced Thematic Mapper Plus (ETM+) data for the detection of isolated wetlands greater than 0.50 acres in Cuyahoga County, located in the Erie Drift Plains ecoregion of northe...
A spectral-knowledge-based approach for urban land-cover discrimination
NASA Technical Reports Server (NTRS)
Wharton, Stephen W.
1987-01-01
A prototype expert system was developed to demonstrate the feasibility of classifying multispectral remotely sensed data on the basis of spectral knowledge. The spectral expert was developed and tested with Thematic Mapper Simulator (TMS) data having eight spectral bands and a spatial resolution of 5 m. A knowledge base was developed that describes the target categories in terms of characteristic spectral relationships. The knowledge base was developed under the following assumptions: the data are calibrated to ground reflectance, the area is well illuminated, the pixels are dominated by a single category, and the target categories can be recognized without the use of spatial knowledge. Classification decisions are made on the basis of convergent evidence as derived from applying the spectral rules to a multiple spatial resolution representation of the image. The spectral expert achieved an accuracy of 80-percent correct or higher in recognizing 11 spectral categories in TMS data for the washington, DC, area. Classification performance can be expected to decrease for data that do not satisfy the above assumptions as illustrated by the 63-percent accuracy for 30-m resolution Thematic Mapper data.
Classification of urban features using airborne hyperspectral data
NASA Astrophysics Data System (ADS)
Ganesh Babu, Bharath
Accurate mapping and modeling of urban environments are critical for their efficient and successful management. Superior understanding of complex urban environments is made possible by using modern geospatial technologies. This research focuses on thematic classification of urban land use and land cover (LULC) using 248 bands of 2.0 meter resolution hyperspectral data acquired from an airborne imaging spectrometer (AISA+) on 24th July 2006 in and near Terre Haute, Indiana. Three distinct study areas including two commercial classes, two residential classes, and two urban parks/recreational classes were selected for classification and analysis. Four commonly used classification methods -- maximum likelihood (ML), extraction and classification of homogeneous objects (ECHO), spectral angle mapper (SAM), and iterative self organizing data analysis (ISODATA) - were applied to each data set. Accuracy assessment was conducted and overall accuracies were compared between the twenty four resulting thematic maps. With the exception of SAM and ISODATA in a complex commercial area, all methods employed classified the designated urban features with more than 80% accuracy. The thematic classification from ECHO showed the best agreement with ground reference samples. The residential area with relatively homogeneous composition was classified consistently with highest accuracy by all four of the classification methods used. The average accuracy amongst the classifiers was 93.60% for this area. When individually observed, the complex recreational area (Deming Park) was classified with the highest accuracy by ECHO, with an accuracy of 96.80% and 96.10% Kappa. The average accuracy amongst all the classifiers was 92.07%. The commercial area with relatively high complexity was classified with the least accuracy by all classifiers. The lowest accuracy was achieved by SAM at 63.90% with 59.20% Kappa. This was also the lowest accuracy in the entire analysis. This study demonstrates the potential for using the visible and near infrared (VNIR) bands from AISA+ hyperspectral data in urban LULC classification. Based on their performance, the need for further research using ECHO and SAM is underscored. The importance incorporating imaging spectrometer data in high resolution urban feature mapping is emphasized.
Singh, Minerva; Evans, Damian; Tan, Boun Suy; Nin, Chan Samean
2015-01-01
At present, there is very limited information on the ecology, distribution, and structure of Cambodia's tree species to warrant suitable conservation measures. The aim of this study was to assess various methods of analysis of aerial imagery for characterization of the forest mensuration variables (i.e., tree height and crown width) of selected tree species found in the forested region around the temples of Angkor Thom, Cambodia. Object-based image analysis (OBIA) was used (using multiresolution segmentation) to delineate individual tree crowns from very-high-resolution (VHR) aerial imagery and light detection and ranging (LiDAR) data. Crown width and tree height values that were extracted using multiresolution segmentation showed a high level of congruence with field-measured values of the trees (Spearman's rho 0.782 and 0.589, respectively). Individual tree crowns that were delineated from aerial imagery using multiresolution segmentation had a high level of segmentation accuracy (69.22%), whereas tree crowns delineated using watershed segmentation underestimated the field-measured tree crown widths. Both spectral angle mapper (SAM) and maximum likelihood (ML) classifications were applied to the aerial imagery for mapping of selected tree species. The latter was found to be more suitable for tree species classification. Individual tree species were identified with high accuracy. Inclusion of textural information further improved species identification, albeit marginally. Our findings suggest that VHR aerial imagery, in conjunction with OBIA-based segmentation methods (such as multiresolution segmentation) and supervised classification techniques are useful for tree species mapping and for studies of the forest mensuration variables.
Singh, Minerva; Evans, Damian; Tan, Boun Suy; Nin, Chan Samean
2015-01-01
At present, there is very limited information on the ecology, distribution, and structure of Cambodia’s tree species to warrant suitable conservation measures. The aim of this study was to assess various methods of analysis of aerial imagery for characterization of the forest mensuration variables (i.e., tree height and crown width) of selected tree species found in the forested region around the temples of Angkor Thom, Cambodia. Object-based image analysis (OBIA) was used (using multiresolution segmentation) to delineate individual tree crowns from very-high-resolution (VHR) aerial imagery and light detection and ranging (LiDAR) data. Crown width and tree height values that were extracted using multiresolution segmentation showed a high level of congruence with field-measured values of the trees (Spearman’s rho 0.782 and 0.589, respectively). Individual tree crowns that were delineated from aerial imagery using multiresolution segmentation had a high level of segmentation accuracy (69.22%), whereas tree crowns delineated using watershed segmentation underestimated the field-measured tree crown widths. Both spectral angle mapper (SAM) and maximum likelihood (ML) classifications were applied to the aerial imagery for mapping of selected tree species. The latter was found to be more suitable for tree species classification. Individual tree species were identified with high accuracy. Inclusion of textural information further improved species identification, albeit marginally. Our findings suggest that VHR aerial imagery, in conjunction with OBIA-based segmentation methods (such as multiresolution segmentation) and supervised classification techniques are useful for tree species mapping and for studies of the forest mensuration variables. PMID:25902148
NASA Astrophysics Data System (ADS)
Amer, Reda; Kusky, Timothy; El Mezayen, Ahmed
2012-01-01
Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Phased Array L-band Synthetic Aperture Radar (PALSAR) images covering the Um Rus area in the Central Eastern Desert of Egypt were evaluated for mapping geologic structure, lithology, and gold-related alteration zones. The study area is covered by Pan-African basement rocks including gabbro and granodiorite intruded into a variable mixture of metavolcanics and metasediments. The first three principal component analyses (PCA1, PCA2, PCA3) in a Red-Green-Blue (RGB) of the visible through shortwave-infrared (VNIR + SWIR) ASTER bands enabled the discrimination between lithological units. The results show that ASTER band ratios ((2 + 4)/3, (5 + 7)/6, (7 + 9)/8) in RGB identifies the lithological units and discriminates the granodiorite very well from the adjacent rock units.The granodiorites are dissected by gold-bearing quartz veins surrounded by alteration zones. The microscopic examination of samples collected from the alteration zones shows sericitic and argillic alteration zones. The Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) supervised classification methods were applied using the reference spectra of the USGS spectral library. The results show that these classification methods are capable of mapping the alteration zones as indicated by field verification work. The PALSAR image was enhanced for fracture mapping using the second moment co-occurrence filter. Overlying extracted faults and alteration zone classification images show that the N30E and N-S fractures represent potential zones for gold exploration. It is concluded that the proposed methods can be used as a powerful tool for ore deposit exploration.
NASA Astrophysics Data System (ADS)
Wakila, M. H.; Saepuloh, A.; Heriawan, M. N.; Susanto, A.
2016-09-01
Geothermal explorations and productions are currently being intensively conducted at certain areas in Indonesia such as Wayang Windu Geothermal Field (WWGF) in West Java, Indonesia. The WWGF is located at wide area covering about 40 km2. An accurate method to map the distribution of heterogeneity minerals is necessary for wide areas such as WWGF. Mineral mapping is an important method in geothermal explorations to determine the distribution of minerals which indicate the surface manifestations of geothermal system. This study is aimed to determine the most precise and accurate methods for minerals mapping at geothermal field. Field measurements were performed to assess the accuracy of three proposed methods: 1) Minimum Noise Fraction (MNF), utilizing the linear transformation method to eliminate the correlation among the spectra bands and to reduce the noise in the data, 2) Pixel Purity Index (PPI), a designed method to find the most extreme spectrum pixels and their characteristics due to end-members mixing, 3) Spectral Angle Mapper (SAM), an image classification technique by measuring the spectral similarity between an unknown object with spectral reference in n- dimension. The output of those methods were mineral distribution occurrence. The performance of each mapping method was analyzed based on the ground truth data. Among the three proposed method, the SAM classification method is the most appropriate and accurate for mineral mapping related to spatial distribution of alteration minerals.
NASA Astrophysics Data System (ADS)
Wicaksono, Pramaditya; Salivian Wisnu Kumara, Ignatius; Kamal, Muhammad; Afif Fauzan, Muhammad; Zhafarina, Zhafirah; Agus Nurswantoro, Dwi; Noviaris Yogyantoro, Rifka
2017-12-01
Although spectrally different, seagrass species may not be able to be mapped from multispectral remote sensing images due to the limitation of their spectral resolution. Therefore, it is important to quantitatively assess the possibility of mapping seagrass species using multispectral images by resampling seagrass species spectra to multispectral bands. Seagrass species spectra were measured on harvested seagrass leaves. Spectral resolution of multispectral images used in this research was adopted from WorldView-2, Quickbird, Sentinel-2A, ASTER VNIR, and Landsat 8 OLI. These images are widely available and can be a good representative and baseline for previous or future remote sensing images. Seagrass species considered in this research are Enhalus acoroides (Ea), Thalassodendron ciliatum (Tc), Thalassia hemprichii (Th), Cymodocea rotundata (Cr), Cymodocea serrulata (Cs), Halodule uninervis (Hu), Halodule pinifolia (Hp), Syringodum isoetifolium (Si), Halophila ovalis (Ho), and Halophila minor (Hm). Multispectral resampling analysis indicate that the resampled spectra exhibit similar shape and pattern with the original spectra but less precise, and they lose the unique absorption feature of seagrass species. Relying on spectral bands alone, multispectral image is not effective in mapping these seagrass species individually, which is shown by the poor and inconsistent result of Spectral Angle Mapper (SAM) classification technique in classifying seagrass species using seagrass species spectra as pure endmember. Only Sentinel-2A produced acceptable classification result using SAM.
Nontronite mineral identification in nilgiri hills of tamil nadu using hyperspectral remote sensing
NASA Astrophysics Data System (ADS)
Vigneshkumar, M.; Yarakkula, Kiran
2017-11-01
Hyperspectral Remote sensing is a tool to identify the minerals along with field investigation. Tamil Nadu has abundant minerals like 30% titanium, 52% molybdenum, 59% garnet, 69% dunite, 75% vermiculite and 81% lignite. To enhance the user and industry requirements, mineral extraction is required. To identify the minerals properly, sophisticated tools are required. Hyperspectral remote sensing provides continuous extraction of earth surface information in an accurate manner. Nontronite is an iron-rich mineral mainly available in Nilgiri hills, Tamil Nadu, India. Due to the large number of bands, hyperspectral data require various preprocessing steps such as bad bands removal, destriping, radiance conversion and atmospheric correction. The atmospheric correction is performed using FLAASH method. The spectral data reduction is carried out with minimum noise fraction (MNF) method. The spatial information is reduced using pixel purity index (PPI) with 10000 iterations. The selected end members are compared with spectral libraries like USGS, JPL, and JHU. In the Nontronite mineral gives the probability of 0.85. Finally the classification is accomplished using spectral angle mapper (SAM) method.
Fluorescence-based classification of Caribbean coral reef organisms and substrates
Zawada, David G.; Mazel, Charles H.
2014-01-01
A diverse group of coral reef organisms, representing several phyla, possess fluorescent pigments. We investigated the potential of using the characteristic fluorescence emission spectra of these pigments to enable unsupervised, optical classification of coral reef habitats. We compiled a library of characteristic fluorescence spectra through in situ and laboratory measurements from a variety of specimens throughout the Caribbean. Because fluorescent pigments are not species-specific, the spectral library is organized in terms of 15 functional groups. We investigated the spectral separability of the functional groups in terms of the number of wavebands required to distinguish between them, using the similarity measures Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), SID-SAM mixed measure, and Mahalanobis distance. This set of measures represents geometric, stochastic, joint geometric-stochastic, and statistical approaches to classifying spectra. Our hyperspectral fluorescence data were used to generate sets of 4-, 6-, and 8-waveband spectra, including random variations in relative signal amplitude, spectral peak shifts, and water-column attenuation. Each set consisted of 2 different band definitions: ‘optimally-picked’ and ‘evenly-spaced.’ The optimally-picked wavebands were chosen to coincide with as many peaks as possible in the functional group spectra. Reference libraries were formed from half of the spectra in each set and used for training purposes. Average classification accuracies ranged from 76.3% for SAM with 4 evenly-spaced wavebands to 93.8% for Mahalanobis distance with 8 evenly-spaced wavebands. The Mahalanobis distance consistently outperformed the other measures. In a second test, empirically-measured spectra were classified using the same reference libraries and the Mahalanobis distance for just the 8 evenly-spaced waveband case. Average classification accuracies were 84% and 87%, corresponding to the extremes in modeled water-column attenuation. The classification results from both tests indicate that a high degree of separability among the 15 fluorescent-spectra functional groups is possible using only a modest number of spectral bands.
Multi-phenology WorldView-2 imagery improves remote sensing of savannah tree species
NASA Astrophysics Data System (ADS)
Madonsela, Sabelo; Cho, Moses Azong; Mathieu, Renaud; Mutanga, Onisimo; Ramoelo, Abel; Kaszta, Żaneta; Kerchove, Ruben Van De; Wolff, Eléonore
2017-06-01
Biodiversity mapping in African savannah is important for monitoring changes and ensuring sustainable use of ecosystem resources. Biodiversity mapping can benefit from multi-spectral instruments such as WorldView-2 with very high spatial resolution and a spectral configuration encompassing important spectral regions not previously available for vegetation mapping. This study investigated i) the benefits of the eight-band WorldView-2 (WV-2) spectral configuration for discriminating tree species in Southern African savannah and ii) if multiple-images acquired at key points of the typical phenological development of savannahs (peak productivity, transition to senescence) improve on tree species classifications. We first assessed the discriminatory power of WV-2 bands using interspecies-Spectral Angle Mapper (SAM) via Band Add-On procedure and tested the spectral capability of WorldView-2 against simulated IKONOS for tree species classification. The results from interspecies-SAM procedure identified the yellow and red bands as the most statistically significant bands (p = 0.000251 and p = 0.000039 respectively) in the discriminatory power of WV-2 during the transition from wet to dry season (April). Using Random Forest classifier, the classification scenarios investigated showed that i) the 8-bands of the WV-2 sensor achieved higher classification accuracy for the April date (transition from wet to dry season, senescence) compared to the March date (peak productivity season) ii) the WV-2 spectral configuration systematically outperformed the IKONOS sensor spectral configuration and iii) the multi-temporal approach (March and April combined) improved the discrimination of tress species and produced the highest overall accuracy results at 80.4%. Consistent with the interspecies-SAM procedure, the yellow (605 nm) band also showed a statistically significant contribution in the improved classification accuracy from WV-2. These results highlight the mapping opportunities presented by WV-2 data for monitoring the distribution status of e.g. species often harvested by local communities (e.g. Sclerocharya birrea), encroaching species, or species-specific tree losses induced by elephants.
Regional land cover characterization using Landsat thematic mapper data and ancillary data sources
Vogelmann, James E.; Sohl, Terry L.; Campbell, P.V.; Shaw, D.M.; ,
1998-01-01
As part of the activities of the Multi-Resolution Land Characteristics (MRLC) Interagency Consortium, an intermediate-scale land cover data set is being generated for the conterminous United States. This effort is being conducted on a region-by-region basis using U.S. Standard Federal Regions. To date, land cover data sets have been generated for Federal Regions 3 (Pennsylvania, West Virginia, Virginia, Maryland, and Delaware) and 2 (New York and New Jersey). Classification work is currently under way in Federal Region 4 (the southeastern United States), and land cover mapping activities have been started in Federal Regions 5 (the Great Lakes region) and 1 (New England). It is anticipated that a land cover data set for the conterminous United States will be completed by the end of 1999. A standard land cover classification legend is used, which is analogous to and compatible with other classification schemes. The primary MRLC regional classification scheme contains 23 land cover classes.The primary source of data for the project is the Landsat thematic mapper (TM) sensor. For each region, TM scenes representing both leaf-on and leaf-off conditions are acquired, preprocessed, and georeferenced to MRLC specifications. Mosaicked data are clustered using unsupervised classification, and individual clusters are labeled using aerial photographs. Individual clusters that represent more than one land cover unit are split using spatial modeling with multiple ancillary spatial data layers (most notably, digital elevation model, population, land use and land cover, and wetlands information). This approach yields regional land cover information suitable for a wide array of applications, including landscape metric analyses, land management, land cover change studies, and nutrient and pesticide runoff modeling.
The National Land Cover Data (NLCD) is a land cover classification derived from Landsat Thematic Mapper satellite data collected in the early to mid-1990s. In this work, land use coverages calculated from the NLCD database are used to assess the impact of non-point sources on the...
Developing New Coastal Forest Restoration Products Based on Landsat, ASTER, and MODIS Data
2010-06-01
hydrology, wildfire, and conversion to non-forest land use. In some cases, such forest disturbance has led to forest loss or loss of regeneration capacity...classification of bald cypress and tupelo gum trees in Thematic Mapper imagery,” Photogrammetric Engineering and Remote Sensing, vol. 63, pp. 717–725, 1997. [14
NASA Astrophysics Data System (ADS)
Buteau, Sylvie; Simard, Jean-Robert; Roy, Gilles; Lahaie, Pierre; Nadeau, Denis; Mathieu, Pierre
2013-10-01
A standoff sensor called BioSense was developed to demonstrate the capacity to map, track and classify bioaerosol clouds from a distant range and over wide area. The concept of the system is based on a two steps dynamic surveillance: 1) cloud detection using an infrared (IR) scanning cloud mapper and 2) cloud classification based on a staring ultraviolet (UV) Laser Induced Fluorescence (LIF) interrogation. The system can be operated either in an automatic surveillance mode or using manual intervention. The automatic surveillance operation includes several steps: mission planning, sensor deployment, background monitoring, surveillance, cloud detection, classification and finally alarm generation based on the classification result. One of the main challenges is the classification step which relies on a spectrally resolved UV LIF signature library. The construction of this library relies currently on in-chamber releases of various materials that are simultaneously characterized with the standoff sensor and referenced with point sensors such as Aerodynamic Particle Sizer® (APS). The system was tested at three different locations in order to evaluate its capacity to operate in diverse types of surroundings and various environmental conditions. The system showed generally good performances even though the troubleshooting of the system was not completed before initiating the Test and Evaluation (T&E) process. The standoff system performances appeared to be highly dependent on the type of challenges, on the climatic conditions and on the period of day. The real-time results combined with the experience acquired during the 2012 T & E allowed to identify future ameliorations and investigation avenues.
NASA Technical Reports Server (NTRS)
Herrmann, Karin; Ammer, Ulrich; Rock, Barrett; Paley, Helen N.
1988-01-01
This study evaluated the utility of data collected by the high-spectral resolution airborne imaging spectrometer (AIS-2, tree mode, spectral range 0.8-2.2 microns) and the broad-band Daedalus airborne thematic mapper (ATM, spectral range 0.42-13.0 micron) in assessing forest decline damage at a predominantly Scotch pine forest in the FRG. Analysis of spectral radiance values from the ATM and raw digital number values from AIS-2 showed that higher reflectance in the near infrared was characteristic of high damage (heavy chlorosis, limited needle loss) in Scotch pine canopies. A classification image of a portion of the AIS-2 flight line agreed very well with a damage assessment map produced by standard aerial photointerpretation techniques.
Remote sensing research for agricultural applications
NASA Technical Reports Server (NTRS)
Colwell, R. N. (Principal Investigator)
1983-01-01
The thematic mapper simulator (TMS) flown by the U-2/ER-2 aircraft is being used as a surrogate for LANDSAT-4TM data. Progress is reported on spectral data acquisition including TMS, color infrared high altitude aerial photography, and LANDSAT 3 MSS and ground data collection to support classification and testing. A test site in San Joaquin County was selected for analysis.
NASA Technical Reports Server (NTRS)
Colwell, R. N. (Principal Investigator)
1984-01-01
The spatial, geometric, and radiometric qualities of LANDSAT 4 thematic mapper (TM) and multispectral scanner (MSS) data were evaluated by interpreting, through visual and computer means, film and digital products for selected agricultural and forest cover types in California. Multispectral analyses employing Bayesian maximum likelihood, discrete relaxation, and unsupervised clustering algorithms were used to compare the usefulness of TM and MSS data for discriminating individual cover types. Some of the significant results are as follows: (1) for maximizing the interpretability of agricultural and forest resources, TM color composites should contain spectral bands in the visible, near-reflectance infrared, and middle-reflectance infrared regions, namely TM 4 and TM % and must contain TM 4 in all cases even at the expense of excluding TM 5; (2) using enlarged TM film products, planimetric accuracy of mapped poins was within 91 meters (RMSE east) and 117 meters (RMSE north); (3) using TM digital products, planimetric accuracy of mapped points was within 12.0 meters (RMSE east) and 13.7 meters (RMSE north); and (4) applying a contextual classification algorithm to TM data provided classification accuracies competitive with Bayesian maximum likelihood.
NASA Astrophysics Data System (ADS)
Pournamdari, M.; Hashim, M.
2014-02-01
Chromite ore deposit occurrence is related to ophiolite complexes as a part of the oceanic crust and provides a good opportunity for lithological mapping using remote sensing data. The main contribution of this paper is a novel approaches to discriminate different rock units associated with ophiolite complex using the Feature Level Fusion technique on ASTER and Landsat TM satellite data at regional scale. In addition this study has applied spectral transform approaches, consisting of Spectral Angle Mapper (SAM) to distinguish the concentration of high-potential areas of chromite and also for determining the boundary between different rock units. Results indicated both approaches show superior outputs compared to other methods and can produce a geological map for ophiolite complex rock units in the arid and the semi-arid region. The novel technique including feature level fusion and Spectral Angle Mapper (SAM) discriminated ophiolitic rock units and produced detailed geological maps of the study area. As a case study, Sikhoran ophiolite complex located in SE, Iran has been selected for image processing techniques. In conclusion, a suitable approach for lithological mapping of ophiolite complexes is demonstrated, this technique contributes meaningfully towards economic geology in terms of identifying new prospects.
Modified Angle's Classification for Primary Dentition.
Chandranee, Kaushik Narendra; Chandranee, Narendra Jayantilal; Nagpal, Devendra; Lamba, Gagandeep; Choudhari, Purva; Hotwani, Kavita
2017-01-01
This study aims to propose a modification of Angle's classification for primary dentition and to assess its applicability in children from Central India, Nagpur. Modification in Angle's classification has been proposed for application in primary dentition. Small roman numbers i/ii/iii are used for primary dentition notation to represent Angle's Class I/II/III molar relationships as in permanent dentition, respectively. To assess applicability of modified Angle's classification a cross-sectional preschool 2000 children population from central India; 3-6 years of age residing in Nagpur metropolitan city of Maharashtra state were selected randomly as per the inclusion and exclusion criteria. Majority 93.35% children were found to have bilateral Class i followed by 2.5% bilateral Class ii and 0.2% bilateral half cusp Class iii molar relationships as per the modified Angle's classification for primary dentition. About 3.75% children had various combinations of Class ii relationships and 0.2% children were having Class iii subdivision relationship. Modification of Angle's classification for application in primary dentition has been proposed. A cross-sectional investigation using new classification revealed various 6.25% Class ii and 0.4% Class iii molar relationships cases in preschool children population in a metropolitan city of Nagpur. Application of the modified Angle's classification to other population groups is warranted to validate its routine application in clinical pediatric dentistry.
Spectroscopic classification of icy satellites of Saturn I: Identification of terrain units on Dione
NASA Astrophysics Data System (ADS)
Scipioni, F.; Tosi, F.; Stephan, K.; Filacchione, G.; Ciarniello, M.; Capaccioni, F.; Cerroni, P.
2013-11-01
Dione is one of the largest and densest icy satellites of Saturn. Its surface shows a marked asymmetry between its leading and trailing hemispheres, the leading side being brighter than the trailing side, which shows regions mantled by a dark veneer whose origin is likely exogenic. In order to identify different terrain units we applied the Spectral Angle Mapper (SAM) classification technique to Dione’s hyperspectral images acquired by the Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini Orbiter in the infrared range (0.88-5.12 μm). On a relatively limited portion of the surface of Dione we first identified nine spectral endmembers, corresponding to as many terrain units, which mostly distinguish for water ice abundance and ice grain size. We then used these endmembers in SAM to achieve a comprehensive classification of the entire surface. The analysis of the infrared spectra returned by VIMS shows that different regions of Dione have variations in water ice bands depths, in average ice grain size, and in the concentration of contaminants, such as CO2 and hydrocarbons, which are clearly connected to morphological and geological structures. Generally, the spectral units that classify optically dark terrains are those showing suppressed water ice bands, a finer ice grain size and a higher concentration of carbon dioxide. Conversely, spectral units labeling brighter regions have deeper water ice absorption bands, higher albedo and a smaller concentration of contaminants. We also considered VIMS cubes of the small satellite Helene (one of the two Dione’s trojan moons) and we compared its infrared spectra to those of the spectral units found on Dione. We observe that the closest match between the spectra of the two satellites occurs for one of the youngest and freshest terrain units on Dione: the Creusa crater region.
Land-cover classification in a moist tropical region of Brazil with Landsat TM imagery.
Li, Guiying; Lu, Dengsheng; Moran, Emilio; Hetrick, Scott
2011-01-01
This research aims to improve land-cover classification accuracy in a moist tropical region in Brazil by examining the use of different remote sensing-derived variables and classification algorithms. Different scenarios based on Landsat Thematic Mapper (TM) spectral data and derived vegetation indices and textural images, and different classification algorithms - maximum likelihood classification (MLC), artificial neural network (ANN), classification tree analysis (CTA), and object-based classification (OBC), were explored. The results indicated that a combination of vegetation indices as extra bands into Landsat TM multispectral bands did not improve the overall classification performance, but the combination of textural images was valuable for improving vegetation classification accuracy. In particular, the combination of both vegetation indices and textural images into TM multispectral bands improved overall classification accuracy by 5.6% and kappa coefficient by 6.25%. Comparison of the different classification algorithms indicated that CTA and ANN have poor classification performance in this research, but OBC improved primary forest and pasture classification accuracies. This research indicates that use of textural images or use of OBC are especially valuable for improving the vegetation classes such as upland and liana forest classes having complex stand structures and having relatively large patch sizes.
Land-cover classification in a moist tropical region of Brazil with Landsat TM imagery
LI, GUIYING; LU, DENGSHENG; MORAN, EMILIO; HETRICK, SCOTT
2011-01-01
This research aims to improve land-cover classification accuracy in a moist tropical region in Brazil by examining the use of different remote sensing-derived variables and classification algorithms. Different scenarios based on Landsat Thematic Mapper (TM) spectral data and derived vegetation indices and textural images, and different classification algorithms – maximum likelihood classification (MLC), artificial neural network (ANN), classification tree analysis (CTA), and object-based classification (OBC), were explored. The results indicated that a combination of vegetation indices as extra bands into Landsat TM multispectral bands did not improve the overall classification performance, but the combination of textural images was valuable for improving vegetation classification accuracy. In particular, the combination of both vegetation indices and textural images into TM multispectral bands improved overall classification accuracy by 5.6% and kappa coefficient by 6.25%. Comparison of the different classification algorithms indicated that CTA and ANN have poor classification performance in this research, but OBC improved primary forest and pasture classification accuracies. This research indicates that use of textural images or use of OBC are especially valuable for improving the vegetation classes such as upland and liana forest classes having complex stand structures and having relatively large patch sizes. PMID:22368311
NASA Astrophysics Data System (ADS)
Lu, Xian; Chen, Cao; Huang, Wentao; Smith, John A.; Chu, Xinzhao; Yuan, Tao; Pautet, Pierre-Dominique; Taylor, Mike J.; Gong, Jie; Cullens, Chihoko Y.
2015-10-01
We present the first coordinated study using two lidars at two separate locations to characterize a 1 h mesoscale gravity wave event in the mesopause region. The simultaneous observations were made with the Student Training and Atmospheric Research (STAR) Na Doppler lidar at Boulder, CO, and the Utah State University Na Doppler lidar and temperature mapper at Logan, UT, on 27 November 2013. The high precision possessed by the STAR lidar enabled these waves to be detected in vertical wind. The mean wave amplitudes are ~0.44 m/s in vertical wind and ~1% in relative temperature at altitudes of 82-107 km. Those in the zonal and meridional winds are 6.1 and 5.2 m/s averaged from 84 to 99 km. The horizontal and vertical wavelengths inferred from the mapper and lidars are ~219 ± 4 and 16.0 ± 0.3 km, respectively. The intrinsic period is ~1.3 h for the airglow layer, Doppler shifted by a mean wind of ~17 m/s. The wave packet propagates from Logan to Boulder with an azimuth angle of ~135° clockwise from north and an elevation angle of ~ 3° from the horizon. The observed phase difference between the two locations can be explained by the traveling time of the 1 h wave from Logan to Boulder, which is about ~2.4 h. The wave polarization relations are examined through the simultaneous quantifications of the three wind components and temperature. This study has developed a systematic methodology for fully characterizing mesoscale gravity waves, inspecting their intrinsic properties and validating the derivation of horizontal wave structures by applying multiple instruments from coordinated stations.
Classifying northern forests using Thematic Mapper Simulator data
NASA Technical Reports Server (NTRS)
Nelson, R. F.; Latty, R. S.; Mott, G.
1984-01-01
Thematic Mapper Simulator data were collected over a 23,200 hectare forested area near Baxter State Park in north-central Maine. Photointerpreted ground reference information was used to drive a stratified random sampling procedure for waveband discriminant analyses and to generate training statistics and test pixel accuracies. Stepwise discriminant analyses indicated that the following bands best differentiated the thirteen level II - III cover types (in order of entry): near infrared (0.77 to 0.90 micron), blue (0.46 0.52 micron), first middle infrared (1.53 to 1.73 microns), second middle infrared (2.06 to 2.33 microsn), red (0.63 to 0.69 micron), thermal (10.32 to 12.33 microns). Classification accuracies peaked at 58 percent for thirteen level II-III land-cover classes and at 65 percent for ten level II classes.
Ground truth management system to support multispectral scanner /MSS/ digital analysis
NASA Technical Reports Server (NTRS)
Coiner, J. C.; Ungar, S. G.
1977-01-01
A computerized geographic information system for management of ground truth has been designed and implemented to relate MSS classification results to in situ observations. The ground truth system transforms, generalizes and rectifies ground observations to conform to the pixel size and shape of high resolution MSS aircraft data. These observations can then be aggregated for comparison to lower resolution sensor data. Construction of a digital ground truth array allows direct pixel by pixel comparison between classification results of MSS data and ground truth. By making comparisons, analysts can identify spatial distribution of error within the MSS data as well as usual figures of merit for the classifications. Use of the ground truth system permits investigators to compare a variety of environmental or anthropogenic data, such as soil color or tillage patterns, with classification results and allows direct inclusion of such data into classification operations. To illustrate the system, examples from classification of simulated Thematic Mapper data for agricultural test sites in North Dakota and Kansas are provided.
NASA Astrophysics Data System (ADS)
Ma, L.; Zhou, M.; Li, C.
2017-09-01
In this study, a Random Forest (RF) based land covers classification method is presented to predict the types of land covers in Miyun area. The returned full-waveforms which were acquired by a LiteMapper 5600 airborne LiDAR system were processed, including waveform filtering, waveform decomposition and features extraction. The commonly used features that were distance, intensity, Full Width at Half Maximum (FWHM), skewness and kurtosis were extracted. These waveform features were used as attributes of training data for generating the RF prediction model. The RF prediction model was applied to predict the types of land covers in Miyun area as trees, buildings, farmland and ground. The classification results of these four types of land covers were obtained according to the ground truth information acquired from CCD image data of the same region. The RF classification results were compared with that of SVM method and show better results. The RF classification accuracy reached 89.73% and the classification Kappa was 0.8631.
Classifying environmentally significant urban land uses with satellite imagery.
Park, Mi-Hyun; Stenstrom, Michael K
2008-01-01
We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.
Angle classification revisited 2: a modified Angle classification.
Katz, M I
1992-09-01
Edward Angle, in his classification of malocclusions, appears to have made Class I a range of abnormality, not a point of ideal occlusion. Current goals of orthodontic treatment, however, strive for the designation "Class I occlusion" to be synonymous with the point of ideal intermeshing and not a broad range. If contemporary orthodontists are to continue to use Class I as a goal, then it is appropriate that Dr. Angle's century-old classification, be modified to be more precise.
Modified Angle's Classification for Primary Dentition
Chandranee, Kaushik Narendra; Chandranee, Narendra Jayantilal; Nagpal, Devendra; Lamba, Gagandeep; Choudhari, Purva; Hotwani, Kavita
2017-01-01
Aim: This study aims to propose a modification of Angle's classification for primary dentition and to assess its applicability in children from Central India, Nagpur. Methods: Modification in Angle's classification has been proposed for application in primary dentition. Small roman numbers i/ii/iii are used for primary dentition notation to represent Angle's Class I/II/III molar relationships as in permanent dentition, respectively. To assess applicability of modified Angle's classification a cross-sectional preschool 2000 children population from central India; 3–6 years of age residing in Nagpur metropolitan city of Maharashtra state were selected randomly as per the inclusion and exclusion criteria. Results: Majority 93.35% children were found to have bilateral Class i followed by 2.5% bilateral Class ii and 0.2% bilateral half cusp Class iii molar relationships as per the modified Angle's classification for primary dentition. About 3.75% children had various combinations of Class ii relationships and 0.2% children were having Class iii subdivision relationship. Conclusions: Modification of Angle's classification for application in primary dentition has been proposed. A cross-sectional investigation using new classification revealed various 6.25% Class ii and 0.4% Class iii molar relationships cases in preschool children population in a metropolitan city of Nagpur. Application of the modified Angle's classification to other population groups is warranted to validate its routine application in clinical pediatric dentistry. PMID:29326514
Hyperspectral and Hypertemporal Longwave Infrared Data Characterization
NASA Astrophysics Data System (ADS)
Jeganathan, Nirmalan
The Army Research Lab conducted a persistent imaging experiment called the Spectral and Polarimetric Imagery Collection Experiment (SPICE) in 2012 and 2013 which focused on collecting and exploiting long wave infrared hyperspectral and polarimetric imagery. A part of this dataset was made for public release for research and development purposes. This thesis investigated the hyperspectral portion of this released dataset through data characterization and scene characterization of man-made and natural objects. First, the data were contrasted with MODerate resolution atmospheric TRANsmission (MODTRAN) results and found to be comparable. Instrument noise was characterized using an in-scene black panel, and was found to be comparable with the sensor manufacturer's specication. The temporal and spatial variation of certain objects in the scene were characterized. Temporal target detection was conducted on man-made objects in the scene using three target detection algorithms: spectral angle mapper (SAM), spectral matched lter (SMF) and adaptive coherence/cosine estimator (ACE). SMF produced the best results for detecting the targets when the training and testing data originated from different time periods, with a time index percentage result of 52.9%. Unsupervised and supervised classification were conducted using spectral and temporal target signatures. Temporal target signatures produced better visual classification than spectral target signature for unsupervised classification. Supervised classification yielded better results using the spectral target signatures, with a highest weighted accuracy of 99% for 7-class reference image. Four emissivity retrieval algorithms were applied on this dataset. However, the retrieved emissivities from all four methods did not represent true material emissivity and could not be used for analysis. This spectrally and temporally rich dataset enabled to conduct analysis that was not possible with other data collections. Regarding future work, applying noise-reduction techniques before applying temperature-emissivity retrieval algorithms may produce more realistic emissivity values, which could be used for target detection and material identification.
Analysis of LANDSAT-4 TM Data for Lithologic and Image Mapping Purpose
NASA Technical Reports Server (NTRS)
Podwysocki, M. H.; Salisbury, J. W.; Bender, L. V.; Jones, O. D.; Mimms, D. L.
1984-01-01
Lithologic mapping techniques using the near infrared bands of the Thematic Mapper onboard the LANDSAT 4 satellite are investigated. These methods are coupled with digital masking to test the capability of mapping geologic materials. Data are examined under medium to low Sun angle illumination conditions to determine the detection limits of materials with absorption features. Several detection anomalies are observed and explained.
Landsat Thematic Mapper studies of land cover spatial variability related to hydrology
NASA Technical Reports Server (NTRS)
Wharton, S.; Ormsby, J.; Salomonson, V.; Mulligan, P.
1984-01-01
Past accomplishments involving remote sensing based land-cover analysis for hydrologic applications are reviewed. Ongoing research in exploiting the increased spatial, radiometric, and spectral capabilities afforded by the TM on Landsats 4 and 5 is considered. Specific studies to compare MSS and TM for urbanizing watersheds, wetlands, and floodplain mapping situations show that only a modest improvement in classification accuracy is achieved via statistical per pixel multispectral classifiers. The limitations of current approaches to multispectral classification are illustrated. The objectives, background, and progress in the development of an alternative analysis approach for defining inputs to urban hydrologic models using TM are discussed.
NASA Technical Reports Server (NTRS)
Boyd, R. K.; Brumfield, J. O.; Campbell, W. J.
1984-01-01
Three feature extraction methods, canonical analysis (CA), principal component analysis (PCA), and band selection, have been applied to Thematic Mapper Simulator (TMS) data in order to evaluate the relative performance of the methods. The results obtained show that CA is capable of providing a transformation of TMS data which leads to better classification results than provided by all seven bands, by PCA, or by band selection. A second conclusion drawn from the study is that TMS bands 2, 3, 4, and 7 (thermal) are most important for landcover classification.
Mapping permafrost in the boreal forest with Thematic Mapper satellite data
NASA Technical Reports Server (NTRS)
Morrissey, L. A.; Strong, L. L.; Card, D. H.
1986-01-01
A geographic data base incorporating Landsat TM data was used to develop and evaluate logistic discriminant functions for predicting the distribution of permafrost in a boreal forest watershed. The data base included both satellite-derived information and ancillary map data. Five permafrost classifications were developed from a stratified random sample of the data base and evaluated by comparison with a photo-interpreted permafrost map using contingency table analysis and soil temperatures recorded at sites within the watershed. A classification using a TM thermal band and a TM-derived vegetation map as independent variables yielded the highest mapping accuracy for all permafrost categories.
Shufen Pan; Guiying Li
2007-01-01
Florida Panhandle region has been experiencing rapid land transformation in the recent decades. To quantify land use and land-cover (LULC) changes and other landscape changes in this area, three counties including Franklin, Liberty and Gulf were taken as a case study and an unsupervised classification approach implemented to Landsat TM images acquired from 1985 to 2005...
MR 201424 Final Report Addendum
2016-09-01
FINAL REPORT ADDENDUM Munitions Classification Library ESTCP Project MR-201424 SEPTEMBER 2016 Mr. Craig Murray Dr. Nagi Khadr Parsons Dr...solver and multi-solver library databases, and only the TEMTADS 2X2 and the MetalMapper advanced TEM systems are supported by UX-Analyze, data on...other steps (section 3.4) before getting into the data collection activities (sections 3.5-3.7). All inversions of library quality data collected over
2016-03-14
DoD Department of Defense EMI electromagnetic induction ESTCP Environmental Security Technology Certification Program ft. foot GPS global...three primary objectives: Test and validate detection and discrimination capabilities of a currently available advanced electromagnetic induction ... induction (EMI) sensors in dynamic and static data acquisition modes and associated analysis software. To achieve these objectives, a controlled test was
Michael Hoppus; Stan Arner; Andrew Lister
2001-01-01
A reduction in variance for estimates of forest area and volume in the state of Connecticut was accomplished by stratifying FIA ground plots using raw, transformed and classified Landsat Thematic Mapper (TM) imagery. A US Geological Survey (USGS) Multi-Resolution Landscape Characterization (MRLC) vegetation cover map for Connecticut was used to produce a forest/non-...
NASA Technical Reports Server (NTRS)
1984-01-01
Rectifications of multispectral scanner and thematic mapper data sets for full and subscene areas, analyses of planimetric errors, assessments of the number and distribution of ground control points required to minimize errors, and factors contributing to error residual are examined. Other investigations include the generation of three dimensional terrain models and the effects of spatial resolution on digital classification accuracies.
Application of thematic mapper-type data over a porphyry-molybdenum deposit in Colorado
NASA Technical Reports Server (NTRS)
Rickman, D. L.; Sadowski, R. M.
1983-01-01
The objective of the study was to evaluate the utility of thematic mapper data as a source of geologically useful information for mountainous areas of varying vegetation density. Much of the processing was done in an a priori manner without prior ground-based information. This approach resulted in a successfull mapping of the alteration associated with the Mt. Emmons molybdenum ore body as well as several other hydrothermal systems. Supervised classification produced a vegetation map at least as accurate as the mapping done for the environmental impact statement. Principal components were used to map zones of general, subtle alteration and to separate hematitically stained rock from staining associated with hydrothermal activity. Decorrelation color composites were found to be useful field mapping aids, easily delineating many lithologies and vegetation classes of interest. The factors restricting the interpretability and computer manipulation of the data are examined.
A Novel Multi-Class Ensemble Model for Classifying Imbalanced Biomedical Datasets
NASA Astrophysics Data System (ADS)
Bikku, Thulasi; Sambasiva Rao, N., Dr; Rao, Akepogu Ananda, Dr
2017-08-01
This paper mainly focuseson developing aHadoop based framework for feature selection and classification models to classify high dimensionality data in heterogeneous biomedical databases. Wide research has been performing in the fields of Machine learning, Big data and Data mining for identifying patterns. The main challenge is extracting useful features generated from diverse biological systems. The proposed model can be used for predicting diseases in various applications and identifying the features relevant to particular diseases. There is an exponential growth of biomedical repositories such as PubMed and Medline, an accurate predictive model is essential for knowledge discovery in Hadoop environment. Extracting key features from unstructured documents often lead to uncertain results due to outliers and missing values. In this paper, we proposed a two phase map-reduce framework with text preprocessor and classification model. In the first phase, mapper based preprocessing method was designed to eliminate irrelevant features, missing values and outliers from the biomedical data. In the second phase, a Map-Reduce based multi-class ensemble decision tree model was designed and implemented in the preprocessed mapper data to improve the true positive rate and computational time. The experimental results on the complex biomedical datasets show that the performance of our proposed Hadoop based multi-class ensemble model significantly outperforms state-of-the-art baselines.
NASA Astrophysics Data System (ADS)
Rokni Deilmai, B.; Ahmad, B. Bin; Zabihi, H.
2014-06-01
Mapping is essential for the analysis of the land use and land cover, which influence many environmental processes and properties. For the purpose of the creation of land cover maps, it is important to minimize error. These errors will propagate into later analyses based on these land cover maps. The reliability of land cover maps derived from remotely sensed data depends on an accurate classification. In this study, we have analyzed multispectral data using two different classifiers including Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM). To pursue this aim, Landsat Thematic Mapper data and identical field-based training sample datasets in Johor Malaysia used for each classification method, which results indicate in five land cover classes forest, oil palm, urban area, water, rubber. Classification results indicate that SVM was more accurate than MLC. With demonstrated capability to produce reliable cover results, the SVM methods should be especially useful for land cover classification.
Maia Mapper: high definition XRF imaging in the lab
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ryan, Chris G.; Kirkham, R.; Moorhead, G. F.
Here, Maia Mapper is a laboratory μXRF mapping system for efficient elemental imaging of drill core sections serving minerals research and industrial applications. It targets intermediate spatial scales, with imaging of up to ~80 M pixels over a 500×150 mm 2 sample area. It brings together (i) the Maia detector and imaging system, with its large solid-angle, event-mode operation, millisecond pixel transit times in fly-scan mode and real-time spectral deconvolution and imaging, (ii) the high brightness MetalJet D2 liquid metal micro-focus X-ray source from Excillum, and (iii) an efficient XOS polycapillary lens with a flux gain ~15,900 at 21 keVmore » into a ~32 μm focus, and (iv) a sample scanning stage engineered for standard drill-core sections. Count-rates up to ~3 M/s are observed on drill core samples with low dead-time up to ~1.5%. Automated scans are executed in sequence with display of deconvoluted element component images accumulated in real-time in the Maia detector. Application images on drill core and polished rock slabs illustrate Maia Mapper capabilities as part of the analytical workflow of the Advanced Resource Characterisation Facility, which spans spatial dimensions from ore deposit to atomic scales.« less
NASA Astrophysics Data System (ADS)
Bharti, Rishikesh; Ramakrishnan, D.; Singh, K. D.
2014-02-01
This study investigated the potential of Moon Mineralogy Mapper (M3) data for studying compositional variation in the near-, far-side transition zone of the lunar surface. For this purpose, the radiance values of the M3 data were corrected for illumination and emission related effects and converted to apparent reflectance. Dimensionality of the calibrated reflectance image cube was reduced using Independent Component Analysis (ICA) and endmembers were extracted by using Pixel Purity Index (PPI) algorithm. The selected endmembers were linearly unmixed and resolved for mineralogy using United States Geological Survey (USGS) library spectra of minerals. These mineralogically resolved endmembers were used to map the compositional variability within, and outside craters using Spectral Angle Mapper (SAM) algorithm. Cross validation for certain litho types was attempted using band ratios like Optical Maturity (OMAT), Color Ratio Composite and Integrated Band Depth ratio (IBD). The identified lithologies for highland and basin areas match well with published works and strongly support depth related magmatic differentiation. Prevalence of pigeonite-basalt, pigeonite-norite and pyroxenite in crater peaks and floors are unique to the investigated area and are attributed to local, lateral compositional variability in magma composition due to pressure, temperature, and rate of cooling.
Maia Mapper: high definition XRF imaging in the lab
Ryan, Chris G.; Kirkham, R.; Moorhead, G. F.; ...
2018-03-13
Here, Maia Mapper is a laboratory μXRF mapping system for efficient elemental imaging of drill core sections serving minerals research and industrial applications. It targets intermediate spatial scales, with imaging of up to ~80 M pixels over a 500×150 mm 2 sample area. It brings together (i) the Maia detector and imaging system, with its large solid-angle, event-mode operation, millisecond pixel transit times in fly-scan mode and real-time spectral deconvolution and imaging, (ii) the high brightness MetalJet D2 liquid metal micro-focus X-ray source from Excillum, and (iii) an efficient XOS polycapillary lens with a flux gain ~15,900 at 21 keVmore » into a ~32 μm focus, and (iv) a sample scanning stage engineered for standard drill-core sections. Count-rates up to ~3 M/s are observed on drill core samples with low dead-time up to ~1.5%. Automated scans are executed in sequence with display of deconvoluted element component images accumulated in real-time in the Maia detector. Application images on drill core and polished rock slabs illustrate Maia Mapper capabilities as part of the analytical workflow of the Advanced Resource Characterisation Facility, which spans spatial dimensions from ore deposit to atomic scales.« less
Maia Mapper: high definition XRF imaging in the lab
NASA Astrophysics Data System (ADS)
Ryan, C. G.; Kirkham, R.; Moorhead, G. F.; Parry, D.; Jensen, M.; Faulks, A.; Hogan, S.; Dunn, P. A.; Dodanwela, R.; Fisher, L. A.; Pearce, M.; Siddons, D. P.; Kuczewski, A.; Lundström, U.; Trolliet, A.; Gao, N.
2018-03-01
Maia Mapper is a laboratory μXRF mapping system for efficient elemental imaging of drill core sections serving minerals research and industrial applications. It targets intermediate spatial scales, with imaging of up to ~80 M pixels over a 500×150 mm2 sample area. It brings together (i) the Maia detector and imaging system, with its large solid-angle, event-mode operation, millisecond pixel transit times in fly-scan mode and real-time spectral deconvolution and imaging, (ii) the high brightness MetalJet D2 liquid metal micro-focus X-ray source from Excillum, and (iii) an efficient XOS polycapillary lens with a flux gain ~15,900 at 21 keV into a ~32 μm focus, and (iv) a sample scanning stage engineered for standard drill-core sections. Count-rates up to ~3 M/s are observed on drill core samples with low dead-time up to ~1.5%. Automated scans are executed in sequence with display of deconvoluted element component images accumulated in real-time in the Maia detector. Application images on drill core and polished rock slabs illustrate Maia Mapper capabilities as part of the analytical workflow of the Advanced Resource Characterisation Facility, which spans spatial dimensions from ore deposit to atomic scales.
Determining successional stage of temperate coniferous forests with Landsat satellite data
NASA Technical Reports Server (NTRS)
Fiorella, Maria; Ripple, William J.
1993-01-01
Thematic Mapper (TM) digital imagery was used to map forest successional stages and to evaluate spectral differences between old-growth and mature forests in the central Cascade Range of Oregon. Relative sun incidence values were incorporated into the successional stage classification to compensate for topographic induced variation. Relative sun incidence improved the classification accuracy of young successional stages, but did not improve the classification accuracy of older, closed canopy forest classes or overall accuracy. TM bands 1, 2, and 4; the normalized difference vegetation index; and TM 4/3, 4/5, and 4/7 band ratio values for o|d-growth forests were found to be significantly lower than the values of mature forests. The Tasseled Cap features of brightness, greenness, and wetness also had significantly lower old-growth values as compared to mature forest values .
Landenburger, L.; Lawrence, R.L.; Podruzny, S.; Schwartz, C.C.
2008-01-01
Moderate resolution satellite imagery traditionally has been thought to be inadequate for mapping vegetation at the species level. This has made comprehensive mapping of regional distributions of sensitive species, such as whitebark pine, either impractical or extremely time consuming. We sought to determine whether using a combination of moderate resolution satellite imagery (Landsat Enhanced Thematic Mapper Plus), extensive stand data collected by land management agencies for other purposes, and modern statistical classification techniques (boosted classification trees) could result in successful mapping of whitebark pine. Overall classification accuracies exceeded 90%, with similar individual class accuracies. Accuracies on a localized basis varied based on elevation. Accuracies also varied among administrative units, although we were not able to determine whether these differences related to inherent spatial variations or differences in the quality of available reference data.
Analysis of multiple incidence angle SIR-B data for determining forest stand characteristics
NASA Technical Reports Server (NTRS)
Hoffer, R. M.; Lozano-Garcia, D. F.; Gillespie, D. D.; Mueller, P. W.; Ruzek, M. J.
1986-01-01
For the first time in the U.S. space program, digital synthetic aperture radar (SR) data were obtained from different incidence angles during Space Shuttle Mission 41-G. Shuttle Imaging Radar-B (SIR-B) data were obtained at incidence angles of 58 deg., 45 deg., and 28 deg., on October 9, 10, and 11, 1984, respectively, for a predominantly forested study area in northern Florida. Cloud-free LANDSAT Thematic Mapper (T.M.) data were obtained over the same area on October 12. The SIR-B data were processed and then digitally registered to the LANDSAT T.M. data by scientists at the Jet Propulsion Laboratory. This is the only known digitally registered SIR-B and T.M. data set for which the data were obtained nearly simultaneously. The data analysis of this information is discussed.
NASA Astrophysics Data System (ADS)
Stock, M.; Lapierre, J. L.; Zhu, Y.
2017-12-01
Recently, the Geostationary Lightning Mapper (GLM) began collecting optical data to locate lightning events and flashes over the North and South American continents. This new instrument promises uniformly high detection efficiency (DE) over its entire field of view, with location accuracy on the order of 10 km. In comparison, Earth Networks Total Lightning Networks (ENTLN) has a less uniform coverage, with higher DE in regions with dense sensor coverage, and lower DE with sparse sensor coverage. ENTLN also offers better location accuracy, lightning classification, and peak current estimation for their lightning locations. It is desirable to produce an integrated dataset, combining the strong points of GLM and ENTLN. The easiest way to achieve this is to simply match located lightning processes from each system using time and distance criteria. This simple method will be limited in scope by the uneven coverage of the ground based network. Instead, we will use GLM group locations to look up the electric field change data recorded by ground sensors near each GLM group, vastly increasing the coverage of the ground network. The ground waveforms can then be used for: improvements to differentiation between glint and lightning for GLM, higher precision lighting location, current estimation, and lightning process classification. Presented is an initial implementation of this type of integration using preliminary GLM data, and waveforms from ENTLN.
NASA Astrophysics Data System (ADS)
Aufaristama, Muhammad; Hölbling, Daniel; Höskuldsson, Ármann; Jónsdóttir, Ingibjörg
2017-04-01
The Krafla volcanic system is part of the Icelandic North Volcanic Zone (NVZ). During Holocene, two eruptive events occurred in Krafla, 1724-1729 and 1975-1984. The last eruptive episode (1975-1984), known as the "Krafla Fires", resulted in nine volcanic eruption episodes. The total area covered by the lavas from this eruptive episode is 36 km2 and the volume is about 0.25-0.3 km3. Lava morphology is related to the characteristics of the surface morphology of a lava flow after solidification. The typical morphology of lava can be used as primary basis for the classification of lava flows when rheological properties cannot be directly observed during emplacement, and also for better understanding the behavior of lava flow models. Although mapping of lava flows in the field is relatively accurate such traditional methods are time consuming, especially when the lava covers large areas such as it is the case in Krafla. Semi-automatic mapping methods that make use of satellite remote sensing data allow for an efficient and fast mapping of lava morphology. In this study, two semi-automatic methods for lava morphology classification are presented and compared using Landsat 8 (30 m spatial resolution) and SPOT-5 (10 m spatial resolution) satellite images. For assessing the classification accuracy, the results from semi-automatic mapping were compared to the respective results from visual interpretation. On the one hand, the Spectral Angle Mapper (SAM) classification method was used. With this method an image is classified according to the spectral similarity between the image reflectance spectrums and the reference reflectance spectra. SAM successfully produced detailed lava surface morphology maps. However, the pixel-based approach partly leads to a salt-and-pepper effect. On the other hand, we applied the Random Forest (RF) classification method within an object-based image analysis (OBIA) framework. This statistical classifier uses a randomly selected subset of training samples to produce multiple decision trees. For final classification of pixels or - in the present case - image objects, the average of the class assignments probability predicted by the different decision trees is used. While the resulting OBIA classification of lava morphology types shows a high coincidence with the reference data, the approach is sensitive to the segmentation-derived image objects that constitute the base units for classification. Both semi-automatic methods produce reasonable results in the Krafla lava field, even if the identification of different pahoehoe and aa types of lava appeared to be difficult. The use of satellite remote sensing data shows a high potential for fast and efficient classification of lava morphology, particularly over large and inaccessible areas.
NASA Technical Reports Server (NTRS)
Nguyen, Andrew; Gole, Alexander; Randall, Jarom; Dlott, Glade; Zhang, Sylvia; Alfaro, Brian; Schmidt, Cindy; Skiles, J. W.
2011-01-01
Mapping and predicting the spatial distribution of invasive plant species is central to habitat management, however difficult to implement at landscape and regional scales. Remote sensing techniques can reduce the impact field campaigns have on these ecologically sensitive areas and can provide a regional and multi-temporal view of invasive species spread. Invasive perennial pepperweed (Lepidium latifolium) is now widespread in fragmented estuaries of the South San Francisco Bay, and is shown to degrade native vegetation in estuaries and adjacent habitats, thereby reducing forage and shelter for wildlife. The purpose of this study is to map the present distribution of pepperweed in estuarine areas of the South San Francisco Bay Salt Pond Restoration Project (Alviso, CA), and create a habitat suitability model to predict future spread. Pepperweed reflectance data were collected in-situ with a GER 1500 spectroradiometer along with 88 corresponding pepperweed presence and absence points used for building the statistical models. The spectral angle mapper (SAM) classification algorithm was used to distinguish the reflectance spectrum of pepperweed and map its distribution using an image from EO-1 Hyperion. To map pepperweed, we performed a supervised classification on an ASTER image with a resulting classification accuracy of 71.8%. We generated a weighted overlay analysis model within a geographic information system (GIS) framework to predict areas in the study site most susceptible to pepperweed colonization. Variables for the model included propensity for disturbance, status of pond restoration, proximity to water channels, and terrain curvature. A Generalized Additive Model (GAM) was also used to generate a probability map and investigate the statistical probability that each variable contributed to predict pepperweed spread. Results from the GAM revealed distance to channels, distance to ponds and curvature were statistically significant (p < 0.01) in determining the locations of suitable pepperweed habitats.
NASA Astrophysics Data System (ADS)
Rose, K.
2012-12-01
Habitat mapping and classification provides essential information for land use planning and ecosystem research, monitoring and management. At the Grand Bay National Estuarine Research Reserve (GRDNERR), Mississippi, habitat characterization of the Grand Bay watershed will also be used to develop a decision-support tool for the NERR's managers and state and local partners. Grand Bay NERR habitat units were identified using a combination of remotely sensed imagery, aerial photography and elevation data. Airborne Imaging Spectrometer for Applications (AISA) hyperspectral data, acquired 5 and 6 May 2010, was analyzed and classified using ENVI v4.8 and v5.0 software. The AISA system was configured to return 63 bands of digital imagery data with a spectral range of 400 to 970 nm (VNIR), spectral resolution (bandwidth) at 8.76 nm, and 1 m spatial resolution. Minimum Noise Fraction (MNF) and Inverse Minimum Noise Fraction were applied to the data prior to using Spectral Angle Mapper ([SAM] supervised) and ISODATA (unsupervised) classification techniques. The resulting class image was exported to ArcGIS 10.0 and visually inspected and compared with the original imagery as well as auxiliary datasets to assist in the attribution of habitat characteristics to the spectral classes, including: National Agricultural Imagery Program (NAIP) aerial photography, Jackson County, MS, 2010; USFWS National Wetlands Inventory, 2007; an existing GRDNERR habitat map (2004), SAV (2009) and salt panne (2002-2003) GIS produced by GRDNERR; and USACE lidar topo-bathymetry, 2005. A field survey to validate the map's accuracy will take place during the 2012 summer season. ENVI's Random Sample generator was used to generate GIS points for a ground-truth survey. The broad range of coastal estuarine habitats and geomorphological features- many of which are transitional and vulnerable to environmental stressors- that have been identified within the GRDNERR point to the value of the Reserve for continued coastal research.
Karstensen, Krista A.; Warner, Kelly L.
2010-01-01
The Land-Cover Trends project is a collaborative effort between the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS), the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA) to understand the rates, trends, causes, and consequences of contemporary land-use and land-cover change in the United States. The data produced from this research can lead to an enriched understanding of the drivers of future landuse change, effects on environmental systems, and any associated feedbacks. USGS scientists are using the EPA Level III ecoregions as the geographic framework to process geospatial data collected between 1973 and 2000 to characterize ecosystem responses to land-use changes. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize and evaluate land-cover change using a modified Anderson Land-Use/Land-Cover Classification System for image interpretation.
Land cover trends dataset, 1973-2000
Soulard, Christopher E.; Acevedo, William; Auch, Roger F.; Sohl, Terry L.; Drummond, Mark A.; Sleeter, Benjamin M.; Sorenson, Daniel G.; Kambly, Steven; Wilson, Tamara S.; Taylor, Janis L.; Sayler, Kristi L.; Stier, Michael P.; Barnes, Christopher A.; Methven, Steven C.; Loveland, Thomas R.; Headley, Rachel; Brooks, Mark S.
2014-01-01
The U.S. Geological Survey Land Cover Trends Project is releasing a 1973–2000 time-series land-use/land-cover dataset for the conterminous United States. The dataset contains 5 dates of land-use/land-cover data for 2,688 sample blocks randomly selected within 84 ecological regions. The nominal dates of the land-use/land-cover maps are 1973, 1980, 1986, 1992, and 2000. The land-use/land-cover maps were classified manually from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery using a modified Anderson Level I classification scheme. The resulting land-use/land-cover data has a 60-meter resolution and the projection is set to Albers Equal-Area Conic, North American Datum of 1983. The files are labeled using a standard file naming convention that contains the number of the ecoregion, sample block, and Landsat year. The downloadable files are organized by ecoregion, and are available in the ERDAS IMAGINETM (.img) raster file format.
Hyperspectral Imaging Sensors and the Marine Coastal Zone
NASA Technical Reports Server (NTRS)
Richardson, Laurie L.
2000-01-01
Hyperspectral imaging sensors greatly expand the potential of remote sensing to assess, map, and monitor marine coastal zones. Each pixel in a hyperspectral image contains an entire spectrum of information. As a result, hyperspectral image data can be processed in two very different ways: by image classification techniques, to produce mapped outputs of features in the image on a regional scale; and by use of spectral analysis of the spectral data embedded within each pixel of the image. The latter is particularly useful in marine coastal zones because of the spectral complexity of suspended as well as benthic features found in these environments. Spectral-based analysis of hyperspectral (AVIRIS) imagery was carried out to investigate a marine coastal zone of South Florida, USA. Florida Bay is a phytoplankton-rich estuary characterized by taxonomically distinct phytoplankton assemblages and extensive seagrass beds. End-member spectra were extracted from AVIRIS image data corresponding to ground-truth sample stations and well-known field sites. Spectral libraries were constructed from the AVIRIS end-member spectra and used to classify images using the Spectral Angle Mapper (SAM) algorithm, a spectral-based approach that compares the spectrum, in each pixel of an image with each spectrum in a spectral library. Using this approach different phytoplankton assemblages containing diatoms, cyanobacteria, and green microalgae, as well as benthic community (seagrasses), were mapped.
Multitemporal WorldView satellites imagery for mapping chestnut trees
NASA Astrophysics Data System (ADS)
Marchetti, F.; Arbelo, M.; Moreno-Ruíz, J. A.; Hernández-Leal, P. A.; Alonso-Benito, A.
2017-10-01
Chestnuts have been part of the landscape and popular culture of the Canary Islands (Spain) since the sixteenth century. Many crops of this species are in state of abandonment and an updated mapping for its study and evaluation is needed. This work proposes the elaboration of this cartography using two satellite images of very high spatial resolution captured on two different dates and representing well-differentiated phenological states of the chestnut: a WorldView-2 image of March 10th, 2015 and a WorldView-3 image of May 12th, 2015 (without and with leaves respectively). Two study areas were selected within the municipality of La Orotava (Tenerife Island). One of the areas contains chestnut trees dispersed in an agricultural and semi-urban environment and in the other one, the specimens are grouped forming a forest merged with Canarian pines and other species of Monteverde. The Maximum Likelihood (ML), the Artificial Neural Networks (ANN) and the Spectral Angle Mapper (SAM) classification algorithms were applied to the multi-temporal image resulting from the combination of both dates. The results show the benefits of using the multi-temporal image for Pinolere with the ANN algorithm and for Chasna area with ML algorithm, in both cases providing an overall accuracy close to 95%.
Anterior Chamber Angle Shape Analysis and Classification of Glaucoma in SS-OCT Images.
Ni Ni, Soe; Tian, J; Marziliano, Pina; Wong, Hong-Tym
2014-01-01
Optical coherence tomography is a high resolution, rapid, and noninvasive diagnostic tool for angle closure glaucoma. In this paper, we present a new strategy for the classification of the angle closure glaucoma using morphological shape analysis of the iridocorneal angle. The angle structure configuration is quantified by the following six features: (1) mean of the continuous measurement of the angle opening distance; (2) area of the trapezoidal profile of the iridocorneal angle centered at Schwalbe's line; (3) mean of the iris curvature from the extracted iris image; (4) complex shape descriptor, fractal dimension, to quantify the complexity, or changes of iridocorneal angle; (5) ellipticity moment shape descriptor; and (6) triangularity moment shape descriptor. Then, the fuzzy k nearest neighbor (fkNN) classifier is utilized for classification of angle closure glaucoma. Two hundred and sixty-four swept source optical coherence tomography (SS-OCT) images from 148 patients were analyzed in this study. From the experimental results, the fkNN reveals the best classification accuracy (99.11 ± 0.76%) and AUC (0.98 ± 0.012) with the combination of fractal dimension and biometric parameters. It showed that the proposed approach has promising potential to become a computer aided diagnostic tool for angle closure glaucoma (ACG) disease.
NASA Astrophysics Data System (ADS)
Becker, Brian L.
Great Lakes wetlands are increasingly being recognized as vital ecosystem components that provide valuable functions such as sediment retention, wildlife habitat, and nutrient removal. Aerial photography has traditionally provided a cost effective means to inventory and monitor coastal wetlands, but is limited by its broad spectral sensitivity and non-digital format. Airborne sensor advancements have now made the acquisition of digital imagery with high spatial and spectral resolution a reality. In this investigation, we selected two Lake Huron coastal wetlands, each from a distinct eco-region, over which, digital, airborne imagery (AISA or CASI-II) was acquired. The 1-meter images contain approximately twenty, 10-nanometer-wide spectral bands strategically located throughout the visible and near-infrared. The 4-meter hyperspectral imagery contains 48 contiguous bands across the visible and short-wavelength near-infrared. Extensive, in-situ, reflectance spectra (SE-590) and sub-meter GPS locations were acquired for the dominant botanical and substrate classes field-delineated at each location. Normalized in-situ spectral signatures were subjected to Principal Components and 2nd Derivative analyses in order to identify the most botanically explanative image bands. Three image-based investigations were implemented in order to evaluate the ability of three classification algorithms (ISODATA, Spectral Angle Mapper and Maximum-Likelihood) to differentiate botanical regions-of-interest. Two additional investigations were completed in order to assess classification changes associated with the independent manipulation of both spatial and spectral resolution. Of the three algorithms tested, the Maximum-Likelihood classifier best differentiated (89%) the regions-of-interest in both study sites. Covariance-based PCA rotation consistently enhanced the performance of the Maximum-Likelihood classifier. Seven non-overlapping bands (425.4, 514.9, 560.1, 685.5, 731.5, 812.3 and 916.7 nanometers) were identified that represented the best performing bands with respect to classification performance. A spatial resolution of 2 meters or less was determined to be the as being most appropriate in Great Lakes coastal wetland environments. This research represents the first step in evaluating the effectiveness of applying high-resolution, narrow-band imagery to the detailed mapping of coastal wetlands in the Great Lakes region.
Leaf water stress detection utilizing thematic mapper bands 3, 4 and 5 in soybean plants
NASA Technical Reports Server (NTRS)
Holben, B. N.; Schutt, J. B.; Mcmurtrey, J., III
1983-01-01
The total and diffuse radiance responses of Thematic Mapper bands 3 (0.63-0.69 microns), 4 (0.76-0.90 microns), and 5 (1.55-1.75 microns) to water stress in a soybean canopy are compared. Polarization measurements were used to separate the total from the diffuse reflectance; the reflectances were compared statistically at a variety of look angles at 15 min intervals from about 09.00 until 14.00 hrs EST. The results suggest that remotely sensed data collected in the photographic infrared region (TM4) are sensitive to leaf water stress in a 100 percent canopy cover of soybeans, and that TM3 is less sensitive than TM4 for detection of reversible foliar water stress. The mean values of TM5 reflectance data show similar trends to TM4. The primary implication of this study is that remote sensing of water stress in green plant canopies is possible in TM4 from ground-based observations primarily through the indirect link of leaf geometry.
Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E; Moran, Emilio
2008-01-01
Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin.
Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E.; Moran, Emilio
2009-01-01
Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin. PMID:19789716
Ramsey, Elijah W.; Nelson, Gene A.; Sapkota, Sijan
1998-01-01
A progressive classification of a marsh and forest system using Landsat Thematic Mapper (TM), color infrared (CIR) photograph, and ERS-1 synthetic aperture radar (SAR) data improved classification accuracy when compared to classification using solely TM reflective band data. The classification resulted in a detailed identification of differences within a nearly monotypic black needlerush marsh. Accuracy percentages of these classes were surprisingly high given the complexities of classification. The detailed classification resulted in a more accurate portrayal of the marsh transgressive sequence than was obtainable with TM data alone. Individual sensor contribution to the improved classification was compared to that using only the six reflective TM bands. Individually, the green reflective CIR and SAR data identified broad categories of water, marsh, and forest. In combination with TM, SAR and the green CIR band each improved overall accuracy by about 3% and 15% respectively. The SAR data improved the TM classification accuracy mostly in the marsh classes. The green CIR data also improved the marsh classification accuracy and accuracies in some water classes. The final combination of all sensor data improved almost all class accuracies from 2% to 70% with an overall improvement of about 20% over TM data alone. Not only was the identification of vegetation types improved, but the spatial detail of the classification approached 10 m in some areas.
Applications of satellite image processing to the analysis of Amazonian cultural ecology
NASA Technical Reports Server (NTRS)
Behrens, Clifford A.
1991-01-01
This paper examines the application of satellite image processing towards identifying and comparing resource exploitation among indigenous Amazonian peoples. The use of statistical and heuristic procedures for developing land cover/land use classifications from Thematic Mapper satellite imagery will be discussed along with actual results from studies of relatively small (100 - 200 people) settlements. Preliminary research indicates that analysis of satellite imagery holds great potential for measuring agricultural intensification, comparing rates of tropical deforestation, and detecting changes in resource utilization patterns over time.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Son, Young-Sun; Yoon, Wang-Jung
The purpose of this study is to map pyprophyllite distribution at surface of the Nohwa deposit, Korea by using Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) data. For this, combined Spectral Angle Mapper (SAM), and Matched Filtering (MF) technique based on mathematical algorithm was applied. The regional distribution of high-grade and low-grade pyrophyllite in the Nohwa deposit area could be differentiated by this method. The results of this study show that ASTER data analysis using combination of SAM and MF techniques will assist in exploration of pyrophyllite at the exposed surface.
Classification of river water pollution using Hyperion data
NASA Astrophysics Data System (ADS)
Kar, Soumyashree; Rathore, V. S.; Champati ray, P. K.; Sharma, Richa; Swain, S. K.
2016-06-01
A novel attempt is made to use hyperspectral remote sensing to identify the spatial variability of metal pollutants present in river water. It was also attempted to classify the hyperspectral image - Earth Observation-1 (EO-1) Hyperion data of an 8 km stretch of the river Yamuna, near Allahabad city in India depending on its chemical composition. For validating image analysis results, a total of 10 water samples were collected and chemically analyzed using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Two different spectral libraries from field and image data were generated for the 10 sample locations. Advanced per-pixel supervised classifications such as Spectral Angle Mapper (SAM), SAM target finder using BandMax and Support Vector Machine (SVM) were carried out along with the unsupervised clustering procedure - Iterative Self-Organizing Data Analysis Technique (ISODATA). The results were compared and assessed with respect to ground data. Analytical Spectral Devices (ASD), Inc. spectroradiometer, FieldSpec 4 was used to generate the spectra of the water samples which were compiled into a spectral library and used for Spectral Absorption Depth (SAD) analysis. The spectral depth pattern of image and field spectral libraries was found to be highly correlated (correlation coefficient, R2 = 0.99) which validated the image analysis results with respect to the ground data. Further, we carried out a multivariate regression analysis to assess the varying concentrations of metal ions present in water based on the spectral depth of the corresponding absorption feature. Spectral Absorption Depth (SAD) analysis along with metal analysis of field data revealed the order in which the metals affected the river pollution, which was in conformity with the findings of Central Pollution Control Board (CPCB). Therefore, it is concluded that hyperspectral imaging provides opportunity that can be used for satellite based remote monitoring of water quality from space.
NASA Astrophysics Data System (ADS)
Hall-Brown, Mary
The heterogeneity of Arctic vegetation can make land cover classification vey difficult when using medium to small resolution imagery (Schneider et al., 2009; Muller et al., 1999). Using high radiometric and spatial resolution imagery, such as the SPOT 5 and IKONOS satellites, have helped arctic land cover classification accuracies rise into the 80 and 90 percentiles (Allard, 2003; Stine et al., 2010; Muller et al., 1999). However, those increases usually come at a high price. High resolution imagery is very expensive and can often add tens of thousands of dollars onto the cost of the research. The EO-1 satellite launched in 2002 carries two sensors that have high specral and/or high spatial resolutions and can be an acceptable compromise between the resolution versus cost issues. The Hyperion is a hyperspectral sensor with the capability of collecting 242 spectral bands of information. The Advanced Land Imager (ALI) is an advanced multispectral sensor whose spatial resolution can be sharpened to 10 meters. This dissertation compares the accuracies of arctic land cover classifications produced by the Hyperion and ALI sensors to the classification accuracies produced by the Systeme Pour l' Observation de le Terre (SPOT), the Landsat Thematic Mapper (TM) and the Landsat Enhanced Thematic Mapper Plus (ETM+) sensors. Hyperion and ALI images from August 2004 were collected over the Upper Kuparuk River Basin, Alaska. Image processing included the stepwise discriminant analysis of pixels that were positively classified from coinciding ground control points, geometric and radiometric correction, and principle component analysis. Finally, stratified random sampling was used to perform accuracy assessments on satellite derived land cover classifications. Accuracy was estimated from an error matrix (confusion matrix) that provided the overall, producer's and user's accuracies. This research found that while the Hyperion sensor produced classfication accuracies that were equivalent to the TM and ETM+ sensor (approximately 78%), the Hyperion could not obtain the accuracy of the SPOT 5 HRV sensor. However, the land cover classifications derived from the ALI sensor exceeded most classification accuracies derived from the TM and ETM+ senors and were even comparable to most SPOT 5 HRV classifications (87%). With the deactivation of the Landsat series satellites, the monitoring of remote locations such as in the Arctic on an uninterupted basis thoughout the world is in jeopardy. The utilization of the Hyperion and ALI sensors are a way to keep that endeavor operational. By keeping the ALI sensor active at all times, uninterupted observation of the entire Earth can be accomplished. Keeping the Hyperion sensor as a "tasked" sensor can provide scientists with additional imagery and options for their studies without overburdening storage issues.
Landsat D Thematic Mapper image dimensionality reduction and geometric correction accuracy
NASA Technical Reports Server (NTRS)
Ford, G. E.
1986-01-01
To characterize and quantify the performance of the Landsat thematic mapper (TM), techniques for dimensionality reduction by linear transformation have been studied and evaluated and the accuracy of the correction of geometric errors in TM images analyzed. Theoretical evaluations and comparisons for existing methods for the design of linear transformation for dimensionality reduction are presented. These methods include the discrete Karhunen Loeve (KL) expansion, Multiple Discriminant Analysis (MDA), Thematic Mapper (TM)-Tasseled Cap Linear Transformation and Singular Value Decomposition (SVD). A unified approach to these design problems is presented in which each method involves optimizing an objective function with respect to the linear transformation matrix. From these studies, four modified methods are proposed. They are referred to as the Space Variant Linear Transformation, the KL Transform-MDA hybrid method, and the First and Second Version of the Weighted MDA method. The modifications involve the assignment of weights to classes to achieve improvements in the class conditional probability of error for classes with high weights. Experimental evaluations of the existing and proposed methods have been performed using the six reflective bands of the TM data. It is shown that in terms of probability of classification error and the percentage of the cumulative eigenvalues, the six reflective bands of the TM data require only a three dimensional feature space. It is shown experimentally as well that for the proposed methods, the classes with high weights have improvements in class conditional probability of error estimates as expected.
NASA Technical Reports Server (NTRS)
Salu, Yehuda; Tilton, James
1993-01-01
The classification of multispectral image data obtained from satellites has become an important tool for generating ground cover maps. This study deals with the application of nonparametric pixel-by-pixel classification methods in the classification of pixels, based on their multispectral data. A new neural network, the Binary Diamond, is introduced, and its performance is compared with a nearest neighbor algorithm and a back-propagation network. The Binary Diamond is a multilayer, feed-forward neural network, which learns from examples in unsupervised, 'one-shot' mode. It recruits its neurons according to the actual training set, as it learns. The comparisons of the algorithms were done by using a realistic data base, consisting of approximately 90,000 Landsat 4 Thematic Mapper pixels. The Binary Diamond and the nearest neighbor performances were close, with some advantages to the Binary Diamond. The performance of the back-propagation network lagged behind. An efficient nearest neighbor algorithm, the binned nearest neighbor, is described. Ways for improving the performances, such as merging categories, and analyzing nonboundary pixels, are addressed and evaluated.
NASA Astrophysics Data System (ADS)
Anker, Y.; Hershkovitz, Y.; Gasith, A.; Ben-Dor, E.
2011-12-01
Although remote sensing of fluvial ecosystems is well developed, the tradeoff between spectral and spatial resolutions prevents its application in small streams (<3m width). In the current study, a remote sensing approach for monitoring and research of small ecosystem was developed. The method is based on differentiation between two indicative vegetation species out of the ecosystem flora. Since when studied, the channel was covered mostly by a filamentous green alga (Cladophora glomerata) and watercress (Nasturtium officinale), these species were chosen as indicative; nonetheless, common reed (Phragmites australis) was also classified in order to exclude it from the stream ROI. The procedure included: A. For both section and habitat scales classifications, acquisition of aerial digital RGB datasets. B. For section scale classification, hyperspectral (HSR) dataset acquisition. C. For calibration, HSR reflectance measurements of specific ground targets, in close proximity to each dataset acquisition swath. D. For habitat scale classification, manual, in-stream flora grid transects classification. The digital RGB datasets were converted to reflectance units by spectral calibration against colored reference plates. These red, green, blue, white, and black EVA foam reference plates were measured by an ASD field spectrometer and each was given a spectral value. Each spectral value was later applied to the spectral calibration and radiometric correction of spectral RGB (SRGB) cube. Spectral calibration of the HSR dataset was done using the empirical line method, based on reference values of progressive grey scale targets. Differentiation between the vegetation species was done by supervised classification both for the HSR and for the SRGB datasets. This procedure was done using the Spectral Angle Mapper function with the spectral pattern of each vegetation species as a spectral end member. Comparison between the two remote sensing techniques and between the SRGB classification and the in-situ transects indicates that: A. Stream vegetation classification resolution is about 4 cm by the SRGB method compared to about 1 m by HSR. Moreover, this resolution is also higher than of the manual grid transect classification. B. The SRGB method is by far the most cost-efficient. The combination of spectral information (rather than the cognitive color) and high spatial resolution of aerial photography provides noise filtration and better sub-water detection capabilities than the HSR technique. C. Only the SRGB method applies for habitat and section scales; hence, its application together with in-situ grid transects for validation, may be optimal for use in similar scenarios.
The HSR dataset was first degraded to 17 bands with the same spectral range as the RGB dataset and also to a dataset with 3 equivalent bands
NASA Technical Reports Server (NTRS)
Hoffer, R. M. (Principal Investigator)
1980-01-01
The column normalizing technique was used to adjust the data for variations in the amplitude of the signal due to look angle effects with respect to solar zenith angle along the scan lines (i.e., across columns). Evaluation of the data set containing the geometric and radiometric adjustments, indicates that the data set should be satisfactory for further processing and analysis. Software was developed for degrading the spatial resolution of the aircraft data to produce a total of four data sets for further analysis. The quality of LANDSAT 2 CCT data for the test site is good for channels four, five, and six. Channel seven was not present on the tape. The data received were reformatted and analysis of the test site area was initiated.
Discrimination of natural and cultivated vegetation using Thematic Mapper spectral data
NASA Technical Reports Server (NTRS)
Degloria, Stephen D.; Bernstein, Ralph; Dizenzo, Silvano
1986-01-01
The availability of high quality spectral data from the current suite of earth observation satellite systems offers significant improvements in the ability to survey and monitor food and fiber production on both a local and global basis. Current research results indicate that Landsat TM data when used in either digital or analog formats achieve higher land-cover classification accuracies than MSS data using either comparable or improved spectral bands and spatial resolution. A review of these quantitative results is presented for both natural and cultivated vegetation.
NASA Technical Reports Server (NTRS)
Jackson, M. J.; Baker, J. R.; Townshend, J. R. G.; Gayler, J. E.; Hardy, J. R.
1983-01-01
The principal objectives of the UK SATMaP program are to determine thematic mapper (TM) performance with particular reference to spatial resolution properties and geometric characteristics of the data. So far, analysis is restricted to images from the U.S. and concentrates on spectra and radiometric properties. The results indicate that the data are inherently three dimensional compared with the two dimensional character of MSS data. Preliminary classification results indicate the importance of the near infrared band (TM 4), at least one middle infrared band (TM 5 or TM 6) and at least one of the visible bands (preferably either TM 3 or TM 1). The thermal infrared also appears to have discriminatory ability despite its coarser spatial resolution. For band 4 the forward and reverse scans show somewhat different spectral responses in one scene but this effect is absent in the other analyzed. From examination of the histograms it would appear that the full 8-bit quantization is not being effectively utilized for all the bands.
NASA Technical Reports Server (NTRS)
Mcbride, J. H.; Fielding, E. J.; Isacks, B. L.
1987-01-01
Landsat Thematic Mapper (TM) images of portions of the Central Andean Puna-Altiplano volcanic belt have been tested for the feasibility of discriminating individual volcanic flows using supervised classifications. This technique distinguishes volcanic rock classes as well as individual phases (i.e., relative age groups) within each class. The spectral signature of a volcanic rock class appears to depend on original texture and composition and on the degree of erosion, weathering, and chemical alteration. Basalts and basaltic andesite stand out as a clearly distinguishable class. The age dependent degree of weathering of these generally dark volcanic rocks can be correlated with reflectance: older rocks have a higher reflectance. On the basis of this relationship, basaltaic lava flows can be separated into several subclasses. These individual subclasses would correspond to mappable geologic units on the ground at a reconnaissance scale. The supervised classification maps are therefore useful for establishing a general stratigraphic framework for later detailed surface mapping of volcanic sequences.
Evolving land cover classification algorithms for multispectral and multitemporal imagery
NASA Astrophysics Data System (ADS)
Brumby, Steven P.; Theiler, James P.; Bloch, Jeffrey J.; Harvey, Neal R.; Perkins, Simon J.; Szymanski, John J.; Young, Aaron C.
2002-01-01
The Cerro Grande/Los Alamos forest fire devastated over 43,000 acres (17,500 ha) of forested land, and destroyed over 200 structures in the town of Los Alamos and the adjoining Los Alamos National Laboratory. The need to measure the continuing impact of the fire on the local environment has led to the application of a number of remote sensing technologies. During and after the fire, remote-sensing data was acquired from a variety of aircraft- and satellite-based sensors, including Landsat 7 Enhanced Thematic Mapper (ETM+). We now report on the application of a machine learning technique to the automated classification of land cover using multi-spectral and multi-temporal imagery. We apply a hybrid genetic programming/supervised classification technique to evolve automatic feature extraction algorithms. We use a software package we have developed at Los Alamos National Laboratory, called GENIE, to carry out this evolution. We use multispectral imagery from the Landsat 7 ETM+ instrument from before, during, and after the wildfire. Using an existing land cover classification based on a 1992 Landsat 5 TM scene for our training data, we evolve algorithms that distinguish a range of land cover categories, and an algorithm to mask out clouds and cloud shadows. We report preliminary results of combining individual classification results using a K-means clustering approach. The details of our evolved classification are compared to the manually produced land-cover classification.
Evaluation of Aster Images for Characterization and Mapping of Amethyst Mining Residues
NASA Astrophysics Data System (ADS)
Markoski, P. R.; Rolim, S. B. A.
2012-07-01
The objective of this work was to evaluate the potential of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), subsystems VNIR (Visible and Near Infrared) and SWIR (Short Wave Infrared) images, for discrimination and mapping of amethyst mining residues (basalt) in the Ametista do Sul Region, Rio Grande do Sul State, Brazil. This region provides the most part of amethyst mining of the World. The basalt is extracted during the mining process and deposited outside the mine. As a result, mounts of residues (basalt) rise up. These mounts are many times smaller than ASTER pixel size (VNIR - 15 meters and SWIR - 30 meters). Thus, the pixel composition becomes a mixing of various materials, hampering its identification and mapping. Trying to solve this problem, multispectral algorithm Maximum Likelihood (MaxVer) and the hyperspectral technique SAM (Spectral Angle Mapper) were used in this work. Images from ASTER subsystems VNIR and SWIR were used to perform the classifications. SAM technique produced better results than MaxVer algorithm. The main error found by the techniques was the mixing between "shadow" and "mining residues/basalt" classes. With the SAM technique the confusion decreased because it employed the basalt spectral curve as a reference, while the multispectral techniques employed pixels groups that could have spectral mixture with other targets. The results showed that in tropical terrains as the study area, ASTER data can be efficacious for the characterization of mining residues.
Lagrangian submanifolds with constant angle functions of the nearly Kähler S3 ×S3
NASA Astrophysics Data System (ADS)
Bektaş, Burcu; Moruz, Marilena; Van der Veken, Joeri; Vrancken, Luc
2018-04-01
We study Lagrangian submanifolds of the nearly Kähler S3 ×S3 with respect to their so called angle functions. We show that if all angle functions are constant, then the submanifold is either totally geodesic or has constant sectional curvature and there is a classification theorem that follows from Dioos et al. (2018). Moreover, we show that if precisely one angle function is constant, then it must be equal to 0 , π/3 or 2π/3. Using then two remarkable constructions together with the classification of Lagrangian submanifolds of which the first component has nowhere maximal rank from, Bektaş et al. (2018), we obtain a classification of such Lagrangian submanifolds.
A long-term perspective on deforestation rates in the Brazilian Amazon
NASA Astrophysics Data System (ADS)
Velasco Gomez, M. D.; Beuchle, R.; Shimabukuro, Y.; Grecchi, R.; Simonetti, D.; Eva, H. D.; Achard, F.
2015-04-01
Monitoring tropical forest cover is central to biodiversity preservation, terrestrial carbon stocks, essential ecosystem and climate functions, and ultimately, sustainable economic development. The Amazon forest is the Earth's largest rainforest, and despite intensive studies on current deforestation rates, relatively little is known as to how these compare to historic (pre 1985) deforestation rates. We quantified land cover change between 1975 and 2014 in the so-called Arc of Deforestation of the Brazilian Amazon, covering the southern stretch of the Amazon forest and part of the Cerrado biome. We applied a consistent method that made use of data from Landsat sensors: Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI). We acquired suitable images from the US Geological Survey (USGS) for five epochs: 1975, 1990, 2000, 2010, and 2014. We then performed land cover analysis for each epoch using a systematic sample of 156 sites, each one covering 10 km x 10 km, located at the confluence point of integer degree latitudes and longitudes. An object-based classification of the images was performed with five land cover classes: tree cover, tree cover mosaic, other wooded land, other land cover, and water. The automatic classification results were corrected by visual interpretation, and, when available, by comparison with higher resolution imagery. Our results show a decrease of forest cover of 24.2% in the last 40 years in the Brazilian Arc of Deforestation, with an average yearly net forest cover change rate of -0.71% for the 39 years considered.
NASA Astrophysics Data System (ADS)
Kriegs, Stefanie; Buddenbaum, Henning; Rogge, Derek; Steffens, Markus
2015-04-01
Laboratory imaging Vis-NIR spectroscopy of soil profiles is a novel technique in soil science that can determine quantity and quality of various chemical soil properties with a hitherto unreached spatial resolution in undisturbed soil profiles. We have applied this technique to soil cores in order to get quantitative proof of redoximorphic processes under two different tree species and to proof tree-soil interactions at microscale. Due to the imaging capabilities of Vis-NIR spectroscopy a spatially explicit understanding of soil processes and properties can be achieved. Spatial heterogeneity of the soil profile can be taken into account. We took six 30 cm long rectangular soil columns of adjacent Luvisols derived from quaternary aeolian sediments (Loess) in a forest soil near Freising/Bavaria using stainless steel boxes (100×100×300 mm). Three profiles were sampled under Norway spruce and three under European beech. A hyperspectral camera (VNIR, 400-1000 nm in 160 spectral bands) with spatial resolution of 63×63 µm² per pixel was used for data acquisition. Reference samples were taken at representative spots and analysed for organic carbon (OC) quantity and quality with a CN elemental analyser and for iron oxides (Fe) content using dithionite extraction followed by ICP-OES measurement. We compared two supervised classification algorithms, Spectral Angle Mapper and Maximum Likelihood, using different sets of training areas and spectral libraries. As established in chemometrics we used multivariate analysis such as partial least-squares regression (PLSR) in addition to multivariate adaptive regression splines (MARS) to correlate chemical data with Vis-NIR spectra. As a result elemental mapping of Fe and OC within the soil core at high spatial resolution has been achieved. The regression model was validated by a new set of reference samples for chemical analysis. Digital soil classification easily visualizes soil properties within the soil profiles. By combining both techniques, detailed soil maps, elemental balances and a deeper understanding of soil forming processes at the microscale become feasible for complete soil profiles.
Ramsey, Elijah W.; Nelson, G.A.; Echols, D.; Sapkota, S.K.
2002-01-01
The National Vegetation Classification Standard (NVCS) was implemented at two US National Park Service (NPS) sites in Texas, the Padre Island National Seashore (PINS) and the Lake Meredith National Recreation Area (LM-NRA), to provide information for NPS oil and gas management plans. Because NVCS landcover classifications did not exist for these two areas prior to this study, we created landcover classes, through intensive ground and aerial reconnaissance, that characterized the general landscape features and at the same time complied with NVCS guidelines. The created landcover classes were useful for the resource management and were conducive to classification with optical remote sensing systems, such as the Landsat Thematic Mapper (TM). In the LMNRA, topographic elevation data were added to the TM data to reduce confusion between cliff, high plains, and forest classes. Classification accuracies (kappa statistics) of 89.9% (0.89) and 88.2% (0.87) in PINS and LMNRA, respectively, verified that the two NPS landholdings were adequately mapped with TM data. Improved sensor systems with higher spectral and spatial resolutions will ultimately refine the broad classes defined in this classification; however, the landcover classifications created in this study have already provided valuable information for the management of both NPS lands. Habitat information provided by the classifications has aided in the placement of inventory and monitoring plots, has assisted oil and gas operators by providing information on sensitive habitats, and has allowed park managers to better use resources when fighting wildland fires and in protecting visitors and the infrastructure of NPS lands.
Ramsey, Elijah W; Nelson, Gene A; Echols, Darrell; Sapkota, Sijan K
2002-05-01
The National Vegetation Classification Standard (NVCS) was implemented at two US National Park Service (NPS) sites in Texas, the Padre Island National Seashore (PINS) and the Lake Meredith National Recreation Area (LMNRA), to provide information for NPS oil and gas management plans. Because NVCS landcover classifications did not exist for these two areas prior to this study, we created landcover classes, through intensive ground and aerial reconnaissance, that characterized the general landscape features and at the same time complied with NVCS guidelines. The created landcover classes were useful for the resource management and were conducive to classification with optical remote sensing systems, such as the Landsat Thematic Mapper (TM). In the LMNRA, topographic elevation data were added to the TM data to reduce confusion between cliff, high plains, and forest classes. Classification accuracies (kappa statistics) of 89.9% (0.89) and 88.2% (0.87) in PINS and LMNRA, respectively, verified that the two NPS landholdings were adequately mapped with TM data. Improved sensor systems with higher spectral and spatial resolutions will ultimately refine the broad classes defined in this classification; however, the landcover classifications created in this study have already provided valuable information for the management of both NPS lands. Habitat information provided by the classifications has aided in the placement of inventory and monitoring plots, has assisted oil and gas operators by providing information on sensitive habitats, and has allowed park managers to better use resources when fighting wildland fires and in protecting visitors and the infrastructure of NPS lands.
Satellite spectral data and archaeological reconnaissance in western Greece
NASA Technical Reports Server (NTRS)
Cooper, Frederick A.; Bauer, M. E.; Cullen, Brenda C.
1991-01-01
A Macro-geographical reconnaissance of the Western Peloponnesos adopts spectral signatures taken by Landsat-5 Thematic Mapper as a new instrument of archaeological survey in Greece. Ancient records indicate that indigenous resources contributed to the prosperity of the region. Natural resources and Ancient, Medieval, and Pre-modern Folklife in the Western Peloponnesos describes the principal lines of research. For a supervised classification of attested ancient resources, a variety of biophysical surface features were pinpointed: stone quarries, coal mines, forests of oak and silver fir, terracotta-producing clay beds, crops, and various wild but exploited shrubs such as flax.
Earth Observatory Satellite system definition study. Report 2: Instrument constraints and interfaces
NASA Technical Reports Server (NTRS)
1974-01-01
The instrument constraints and interface specifications for the Earth Observatory Satellite (EOS) are discussed. The Land Use Classification Mission using a 7 band Thematic Mapper and a 4 band High Resolution Pointable Imager is stressed. The mission and performance of the instruments were reviewed and expanded to reflect the instrument as a part of the total remote sensing system. A preliminary EOS interface handbook is provided to describe the mission and system, to specify the spacecraft interfaces to potential instrument contractors, and to describe the instrument interface data required by the system integration contractor.
Vegetation mapping and stress detection in the Santa Monica Mountains, California
NASA Technical Reports Server (NTRS)
Price, Curtis V.; Westman, Walter E.
1987-01-01
Thematic Mapper (TM) simulator data have been used to map coastal sage scrub in the mountains near Los Angeles by means of supervised classification. Changes in TM band radiances and band ratios are examined along an east-west gradient in ozone pollution loads. While the changes noted are interpretable in terms of ozone- and temperature-induced premature leaf drop, and consequent exposure of a dry, grassy understory, TM band and band ratio reflectances are influenced by a variety of independent factors which require that pollution stress interpretations be conducted in the context of the greatest possible ecological system comprehension.
Development, implementation and evaluation of satellite-aided agricultural monitoring systems
NASA Technical Reports Server (NTRS)
Cicone, R. (Principal Investigator); Crist, E.; Metzler, M.; Parris, T.
1982-01-01
Research supporting the use of remote sensing for inventory and assessment of agricultural commodities is summarized. Three task areas are described: (1) corn and soybean crop spectral/temporal signature characterization; (2) efficient area estimation technology development; and (3) advanced satellite and sensor system definition. Studies include an assessment of alternative green measures from MSS variables; the evaluation of alternative methods for identifying, labeling or classification targets in an automobile procedural context; a comparison of MSS, the advanced very high resolution radiometer and the coastal zone color scanner, as well as a critical assessment of thematic mapper dimensionally and spectral structure.
Wiig, Ola; Terjesen, Terje; Svenningsen, Svein
2002-10-01
We evaluated the inter-observer agreement of radiographic methods when evaluating patients with Perthes' disease. The radiographs were assessed at the time of diagnosis and at the 1-year follow-up by local orthopaedic surgeons (O) and 2 experienced pediatric orthopedic surgeons (TT and SS). The Catterall, Salter-Thompson, and Herring lateral pillar classifications were compared, and the femoral head coverage (FHC), center-edge angle (CE-angle), and articulo-trochanteric distance (ATD) were measured in the affected and normal hips. On the primary evaluation, the lateral pillar and Salter-Thompson classifications had a higher level of agreement among the observers than the Catterall classification, but none of the classifications showed good agreement (weighted kappa values between O and SS 0.56, 0.54, 0.49, respectively). Combining Catterall groups 1 and 2 into one group, and groups 3 and 4 into another resulted in better agreement (kappa 0.55) than with the original 4-group system. The agreement was also better (kappa 0.62-0.70) between experienced than between less experienced examiners for all classifications. The femoral head coverage was a more reliable and accurate measure than the CE-angle for quantifying the acetabular covering of the femoral head, as indicated by higher intraclass correlation coefficients (ICC) and smaller inter-observer differences. The ATD showed good agreement in all comparisons and had low interobserver differences. We conclude that all classifications of femoral head involvement are adequate in clinical work if the radiographic assessment is done by experienced examiners. When they are less experienced examiners, a 2-group classification or the lateral pillar classification is more reliable. For evaluation of containment of the femoral head, FHC is more appropriate than the CE-angle.
Automated quasi-3D spine curvature quantification and classification
NASA Astrophysics Data System (ADS)
Khilari, Rupal; Puchin, Juris; Okada, Kazunori
2018-02-01
Scoliosis is a highly prevalent spine deformity that has traditionally been diagnosed through measurement of the Cobb angle on radiographs. More recent technology such as the commercial EOS imaging system, although more accurate, also require manual intervention for selecting the extremes of the vertebrae forming the Cobb angle. This results in a high degree of inter and intra observer error in determining the extent of spine deformity. Our primary focus is to eliminate the need for manual intervention by robustly quantifying the curvature of the spine in three dimensions, making it consistent across multiple observers. Given the vertebrae centroids, the proposed Vertebrae Sequence Angle (VSA) estimation and segmentation algorithm finds the largest angle between consecutive pairs of centroids within multiple inflection points on the curve. To exploit existing clinical diagnostic standards, the algorithm uses a quasi-3-dimensional approach considering the curvature in the coronal and sagittal projection planes of the spine. Experiments were performed with manuallyannotated ground-truth classification of publicly available, centroid-annotated CT spine datasets. This was compared with the results obtained from manual Cobb and Centroid angle estimation methods. Using the VSA, we then automatically classify the occurrence and the severity of spine curvature based on Lenke's classification for idiopathic scoliosis. We observe that the results appear promising with a scoliotic angle lying within +/- 9° of the Cobb and Centroid angle, and vertebrae positions differing by at the most one position. Our system also resulted in perfect classification of scoliotic from healthy spines with our dataset with six cases.
Rotationally Invariant Image Representation for Viewing Direction Classification in Cryo-EM
Zhao, Zhizhen; Singer, Amit
2014-01-01
We introduce a new rotationally invariant viewing angle classification method for identifying, among a large number of cryo-EM projection images, similar views without prior knowledge of the molecule. Our rotationally invariant features are based on the bispectrum. Each image is denoised and compressed using steerable principal component analysis (PCA) such that rotating an image is equivalent to phase shifting the expansion coefficients. Thus we are able to extend the theory of bispectrum of 1D periodic signals to 2D images. The randomized PCA algorithm is then used to efficiently reduce the dimensionality of the bispectrum coefficients, enabling fast computation of the similarity between any pair of images. The nearest neighbors provide an initial classification of similar viewing angles. In this way, rotational alignment is only performed for images with their nearest neighbors. The initial nearest neighbor classification and alignment are further improved by a new classification method called vector diffusion maps. Our pipeline for viewing angle classification and alignment is experimentally shown to be faster and more accurate than reference-free alignment with rotationally invariant K-means clustering, MSA/MRA 2D classification, and their modern approximations. PMID:24631969
Normalization of satellite imagery
NASA Technical Reports Server (NTRS)
Kim, Hongsuk H.; Elman, Gregory C.
1990-01-01
Sets of Thematic Mapper (TM) imagery taken over the Washington, DC metropolitan area during the months of November, March and May were converted into a form of ground reflectance imagery. This conversion was accomplished by adjusting the incident sunlight and view angles and by applying a pixel-by-pixel correction for atmospheric effects. Seasonal color changes of the area can be better observed when such normalization is applied to space imagery taken in time series. In normalized imagery, the grey scale depicts variations in surface reflectance and tonal signature of multi-band color imagery can be directly interpreted for quantitative information of the target.
NASA Technical Reports Server (NTRS)
Thomas, Randall W.; Ustin, Susan L.
1987-01-01
A preliminary assessment was made of Airborne Imaging Spectrometer (AIS) data for discriminating and characterizing vegetation in a semiarid environment. May and October AIS data sets were acquired over a large alluvial fan in eastern California, on which were found Great Basin desert shrub communities. Maximum likelihood classification of a principal components representation of the May AIS data enabled discrimination of subtle spatial detail in images relating to vegetation and soil characteristics. The spatial patterns in the May AIS classification were, however, too detailed for complete interpretation with existing ground data. A similar analysis of the October AIS data yielded poor results. Comparison of AIS results with a similar analysis of May Landsat Thematic Mapper data showed that the May AIS data contained approximately three to four times as much spectrally coherent information. When only two shortwave infrared TM bands were used, results were similar to those from AIS data acquired in October.
NASA Technical Reports Server (NTRS)
Tendam, I. M. (Editor); Morrison, D. B.
1979-01-01
Papers are presented on techniques and applications for the machine processing of remotely sensed data. Specific topics include the Landsat-D mission and thematic mapper, data preprocessing to account for atmospheric and solar illumination effects, sampling in crop area estimation, the LACIE program, the assessment of revegetation on surface mine land using color infrared aerial photography, the identification of surface-disturbed features through a nonparametric analysis of Landsat MSS data, the extraction of soil data in vegetated areas, and the transfer of remote sensing computer technology to developing nations. Attention is also given to the classification of multispectral remote sensing data using context, the use of guided clustering techniques for Landsat data analysis in forest land cover mapping, crop classification using an interactive color display, and future trends in image processing software and hardware.
Internet protocol network mapper
Youd, David W.; Colon III, Domingo R.; Seidl, Edward T.
2016-02-23
A network mapper for performing tasks on targets is provided. The mapper generates a map of a network that specifies the overall configuration of the network. The mapper inputs a procedure that defines how the network is to be mapped. The procedure specifies what, when, and in what order the tasks are to be performed. Each task specifies processing that is to be performed for a target to produce results. The procedure may also specify input parameters for a task. The mapper inputs initial targets that specify a range of network addresses to be mapped. The mapper maps the network by, for each target, executing the procedure to perform the tasks on the target. The results of the tasks represent the mapping of the network defined by the initial targets.
NASA Technical Reports Server (NTRS)
Tilton, James C.; Ramapriyan, H. K.
1989-01-01
A case study is presented where an image segmentation based compression technique is applied to LANDSAT Thematic Mapper (TM) and Nimbus-7 Coastal Zone Color Scanner (CZCS) data. The compression technique, called Spatially Constrained Clustering (SCC), can be regarded as an adaptive vector quantization approach. The SCC can be applied to either single or multiple spectral bands of image data. The segmented image resulting from SCC is encoded in small rectangular blocks, with the codebook varying from block to block. Lossless compression potential (LDP) of sample TM and CZCS images are evaluated. For the TM test image, the LCP is 2.79. For the CZCS test image the LCP is 1.89, even though when only a cloud-free section of the image is considered the LCP increases to 3.48. Examples of compressed images are shown at several compression ratios ranging from 4 to 15. In the case of TM data, the compressed data are classified using the Bayes' classifier. The results show an improvement in the similarity between the classification results and ground truth when compressed data are used, thus showing that compression is, in fact, a useful first step in the analysis.
Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques
NASA Astrophysics Data System (ADS)
Kumar, Lalit; Ghosh, Manoj Kumer
2012-01-01
Land cover change is a significant issue for environmental managers for sustainable management. Remote sensing techniques have been shown to have a high probability of recognizing land cover patterns and change detection due to periodic coverage, data integrity, and provision of data in a broad range of the electromagnetic spectrum. We evaluate the applicability of remote sensing techniques for land cover pattern recognition, as well as land cover change detection of the Hatiya Island, Bangladesh, and quantify land cover changes from 1977 to 1999. A supervised classification approach was used to classify Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM), and Multispectral Scanner (MSS) images into eight major land cover categories. We detected major land cover changes over the 22-year study period. During this period, marshy land, mud, mud with small grass, and bare soil had decreased by 85%, 46%, 44%, and 24%, respectively, while agricultural land, medium forest, forest, and settlement had positive changes of 26%, 45%, 363%, and 59%, respectively. The primary drivers of such landscape change were erosion and accretion processes, human pressure, and the reforestation and land reclamation programs of the Bangladesh Government.
NASA Astrophysics Data System (ADS)
Morgan, Andy J.
The San Bernardino National Forest (SBNF) has experienced periods of high, concentrated bark beetle epidemics in the late 1990's and into the 2000's. This increased activity has caused huge amounts of forest loss, resulting from disease introduced by bark beetles. Using remote sensing techniques and Landsat Thematic Mapper 5 (TM5) imagery, the spread of bark beetle diseased trees is mapped over a period from 1998 to 2008. Acreage of two attack stages (red and gray) were calculated from a level sliced classification method developed on data training sites. In each image using Normalized Difference Vegetation Index (NDVI) is the driver of forest health classifications. The results of the analysis are classification maps for each year, red acreage estimated for each study year, and gray attack acreage estimated for each study year. Additionally, for the period of 2001-2004, acreage was compared to those reported by the USDA with a thirteen percent lower mortality total in comparison to USDA federal land and a thirty-two percent lower total mortality (federal and non-federal) land in the SBNF.
Determining successional stage of temperate coniferous forests with Landsat satellite data
NASA Technical Reports Server (NTRS)
Fiorella, Maria; Ripple, William J.
1995-01-01
Thematic Mapper (TM) digital imagery was used to map forest successional stages and to evaluate spectral differences between old-growth and mature forests in the central Cascade Range of Oregon. Relative sun incidence values were incorporated into the successional stage classification to compensate for topographic induced variation. Relative sun incidence improved the classification accuracy of young successional stages, but did not improve the classification accuracy of older, closed canopy forest classes or overall accuracy. TM bands 1, 2, and 4; the normalized difference vegetation index (NDVI); and TM 4/3, 4/5, and 4/7 band ratio values for old-growth forests were found to be significantly lower than the values of mature forests (P less than or equal to 0.010). Wetness and the TM 4/5 and 4/7 band ratios all had low correlations to relative sun incidence (r(exp 2) less than or equal to 0.16). The TM 4/5 band ratio was named the 'structural index' (SI) because of its ability to distinguish between mature and old-growth forests and its simplicity.
Shermeyer, Jacob S.; Haack, Barry N.
2015-01-01
Two forestry-change detection methods are described, compared, and contrasted for estimating deforestation and growth in threatened forests in southern Peru from 2000 to 2010. The methods used in this study rely on freely available data, including atmospherically corrected Landsat 5 Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF). The two methods include a conventional supervised signature extraction method and a unique self-calibrating method called MODIS VCF guided forest/nonforest (FNF) masking. The process chain for each of these methods includes a threshold classification of MODIS VCF, training data or signature extraction, signature evaluation, k-nearest neighbor classification, analyst-guided reclassification, and postclassification image differencing to generate forest change maps. Comparisons of all methods were based on an accuracy assessment using 500 validation pixels. Results of this accuracy assessment indicate that FNF masking had a 5% higher overall accuracy and was superior to conventional supervised classification when estimating forest change. Both methods succeeded in classifying persistently forested and nonforested areas, and both had limitations when classifying forest change.
Initial attitude determination for the hipparcos satellite
NASA Astrophysics Data System (ADS)
Van der Ha, Jozef C.
The present paper described the strategy and algorithms used during the initial on-ground three-axes attitude determination of ESA's astrometry satellite HIPPARCOS. The estimation is performed using calculated crossing times of identified stars over the Star Mapper's vertical and inclined slit systems as well as outputs from a set of rate-integrating gyros. Valid star transits in either of the two fields of view are expected to occur in average about every 30 s whereas the gyros are sampled at about 1 Hz. The state vector to be estimated consists of the three angles, three rates and three gyro drift rate components. Simulations have shown that convergence of the estimator is established within about 10 min and that the accuracies achieved are in the order of a few arcsec for the angles and a few milliarcsec per s for the rates. These stringent accuracies are in fact required for initialisation of subsequent autonomous on-board real-time attitude determination.
Landsat Thematic Mapper Image Mosaic of Colorado
Cole, Christopher J.; Noble, Suzanne M.; Blauer, Steven L.; Friesen, Beverly A.; Bauer, Mark A.
2010-01-01
The U.S. Geological Survey (USGS) Rocky Mountain Geographic Science Center (RMGSC) produced a seamless, cloud-minimized remotely-sensed image spanning the State of Colorado. Multiple orthorectified Landsat 5 Thematic Mapper (TM) scenes collected during 2006-2008 were spectrally normalized via reflectance transformation and linear regression based upon pseudo-invariant features (PIFS) following the removal of clouds. Individual Landsat scenes were then mosaicked to form a six-band image composite spanning the visible to shortwave infrared spectrum. This image mosaic, presented here, will also be used to create a conifer health classification for Colorado in Scientific Investigations Map 3103. An archive of past and current Landsat imagery exists and is available to the scientific community (http://glovis.usgs.gov/), but significant pre-processing was required to produce a statewide mosaic from this information. Much of the data contained perennial cloud cover that complicated analysis and classification efforts. Existing Landsat mosaic products, typically three band image composites, did not include the full suite of multispectral information necessary to produce this assessment, and were derived using data collected in 2001 or earlier. A six-band image mosaic covering Colorado was produced. This mosaic includes blue (band 1), green (band 2), red (band 3), near infrared (band 4), and shortwave infrared information (bands 5 and 7). The image composite shown here displays three of the Landsat bands (7, 4, and 2), which are sensitive to the shortwave infrared, near infrared, and green ranges of the electromagnetic spectrum. Vegetation appears green in this image, while water looks black, and unforested areas appear pink. The lines that may be visible in the on-screen version of the PDF are an artifact of the export methods used to create this file. The file should be viewed at 150 percent zoom or greater for optimum viewing.
NASA Astrophysics Data System (ADS)
Amer, R.; Ofterdinger, U.; Ruffell, A.; Donald, A.
2012-04-01
This study presents landuse/landcover (LULC) classifications of Northern Ireland in order to quantify land-use types driving chemical loading in the surface water bodies. The major LULC classes are agricultural land, bare land (mountainous areas), forest, urban areas, and water bodies. Three ENVISAT ASAR multi-look precision images acquired in 2011 and two Enhanced Thematic Mapper Plus (ETM+) acquired in 2003 were used for classification. The ASAR digital numbers were converted to backscattering coefficient (sigma nought) and enhanced using adaptive Gamma filter and Gaussian stretch. Supervised classifications of Maximum Likelihood, Mahalanobils Distance, Minimum Distance, Spectral Angel Mapper, Parallelepiped, and Winner Tercat were applied on ETM+ and ASAR images. A confusion matrix was used to evaluate the classification accuracy; the best results of ETM+ and ASAR were given by the winner classification (82.9 and 73.6 %), and maximum likelihood (81.7 and 72.5 %), respectively. Change detection was applied to identify the areas of significant changes in landuse/landcover over the last eight years. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model was processed to extract the drainage systems and watersheds. Water quality data of the first and second order streams were extracted from 2005 survey by Geological Survey of Northern Ireland. GIS spatially distributed modelling generated maps showing the distribution of phosphorus (P), nitrate (NO3), dissolved organic carbon (DOC), and some of the trace elements including fluoride (F), calcium (Ca), aluminium (Al), iron (Fe), copper (Cu), lead (Pb), zinc (Zn), and arsenic (As) across the watersheds of the Northern Ireland were generated. The distribution of these elements was evaluated against the LULC classes and bed rock geology. Concentration of these elements was classified into normal (safe level), moderate, high, and very high based on the World Health Organization (WHO, 2011) water quality standards. The results show that P concentration is generally high across all the watersheds. NO3 is within normal range in all watersheds. DOC is within normal range in urban areas, moderate to high in agricultural lands, and high in the forest areas and bare lands. F and Fe are within safe level in all watersheds. Al, Cu, and As are high in all watersheds around the bare land LULC class which are underlain by psammite and semipelite metamorphic rocks. Ca is within normal range in most of watersheds but it is high in the south western part of the study area because of the presence of limestone bedrock. Pb and Zn are within normal range in the urban and most of the agricultural land, and high in the mountainous areas underlain by psammite and semipelite metamorphic bed rock.
NASA Technical Reports Server (NTRS)
Hoffer, Roger M.; Hussin, Yousif Ali
1989-01-01
Multipolarized aircraft L-band radar data are classified using two different image classification algorithms: (1) a per-point classifier, and (2) a contextual, or per-field, classifier. Due to the distinct variations in radar backscatter as a function of incidence angle, the data are stratified into three incidence-angle groupings, and training and test data are defined for each stratum. A low-pass digital mean filter with varied window size (i.e., 3x3, 5x5, and 7x7 pixels) is applied to the data prior to the classification. A predominately forested area in northern Florida was the study site. The results obtained by using these image classifiers are then presented and discussed.
NS001MS - Landsat-D thematic mapper band aircraft scanner
NASA Technical Reports Server (NTRS)
Richard, R. R.; Merkel, R. F.; Meeks, G. R.
1978-01-01
The thematic mapper is a multispectral scanner which will be launched aboard Landsat-D in the early 1980s. Compared with previous Landsat scanners, this instrument will have an improved spatial resolution (30 m) and new spectral bands. Designated NS001MS, the scanner is designed to duplicate the thematic mapper spectral bands plus two additional bands (1.0 to 1.3 microns and 2.08 to 2.35 microns) in an aircraft scanner for evaluation and investigation prior to design and launch of the final thematic mapper. Applicable specifications used in defining the thematic mapper were retained in the NS001MS design, primarily with respect to spectral bandwidths, noise equivalent reflectance, and noise equivalent difference temperature. The technical design and operational characteristics of the multispectral scanner (with thematic mapper bands) are discussed.
A comparison of four different lens mappers.
Larrue, Denis; Legeard, Morgane
2014-11-01
Recently, a number of lens mappers have become available for measuring the detailed optical properties of progressive addition lenses (PALs). The goal of this study was to compare the results obtained from several different lens mappers for a range of different lenses. The optical power maps of six lenses-two single-vision lenses, a parallel-sided slide, a flat prism, and two progressive lenses-were measured using four different lens mappers: the Dual Lens Mapper, the Nimo TR4005, the Rotlex Class Plus, and the Visionix VM2500. The repeatability of the instruments was also evaluated. All lens mappers gave very repeatable measurements; however, measurements among the lens mappers varied considerably. Differences appeared to be above the tolerance at the optical center for measurements of single-vision lenses, and these differences increase in the periphery up to 1.00 diopter. Similar differences were observed for the PALs, even increased by prism and base curve effect, with figures greater than 1 diopter in the periphery. The measurements made on the prism and lenses with different base curves suggest that base curve, thickness, and prismatic effect can all contribute to the differences among instruments. Measurements of a given lens taken with different lens mappers can vary substantially. Particular caution should be exercised when interpreting power maps for PALs taken with different instruments.
Mitchell, Michael; Wilson, R. Randy; Twedt, Daniel J.; Mini, Anne E.; James, J. Dale
2016-01-01
The Mississippi Alluvial Valley is a floodplain along the southern extent of the Mississippi River extending from southern Missouri to the Gulf of Mexico. This area once encompassed nearly 10 million ha of floodplain forests, most of which has been converted to agriculture over the past two centuries. Conservation programs in this region revolve around protection of existing forest and reforestation of converted lands. Therefore, an accurate and up to date classification of forest cover is essential for conservation planning, including efforts that prioritize areas for conservation activities. We used object-based image analysis with Random Forest classification to quickly and accurately classify forest cover. We used Landsat band, band ratio, and band index statistics to identify and define similar objects as our training sets instead of selecting individual training points. This provided a single rule-set that was used to classify each of the 11 Landsat 5 Thematic Mapper scenes that encompassed the Mississippi Alluvial Valley. We classified 3,307,910±85,344 ha (32% of this region) as forest. Our overall classification accuracy was 96.9% with Kappa statistic of 0.96. Because this method of forest classification is rapid and accurate, assessment of forest cover can be regularly updated and progress toward forest habitat goals identified in conservation plans can be periodically evaluated.
Enjoyment of Euclidean Planar Triangles
ERIC Educational Resources Information Center
Srinivasan, V. K.
2013-01-01
This article adopts the following classification for a Euclidean planar [triangle]ABC, purely based on angles alone. A Euclidean planar triangle is said to be acute angled if all the three angles of the Euclidean planar [triangle]ABC are acute angles. It is said to be right angled at a specific vertex, say B, if the angle ?ABC is a right angle…
Remote sensing of environmental impact of land use activities
NASA Technical Reports Server (NTRS)
Paul, C. K.
1977-01-01
The capability to monitor land cover, associated in the past with aerial film cameras and radar systems, was discussed in regard to aircraft and spacecraft multispectral scanning sensors. A proposed thematic mapper with greater spectral and spatial resolutions for the fourth LANDSAT is expected to usher in new environmental monitoring capability. In addition, continuing improvements in image classification by supervised and unsupervised computer techniques are being operationally verified for discriminating environmental impacts of human activities on the land. The benefits of employing remote sensing for this discrimination was shown to far outweigh the incremental costs of converting to an aircraft-satellite multistage system.
LAPR: An experimental aircraft pushbroom scanner
NASA Technical Reports Server (NTRS)
Wharton, S. W.; Irons, J. I.; Heugel, F.
1980-01-01
A three band Linear Array Pushbroom Radiometer (LAPR) was built and flown on an experimental basis by NASA at the Goddard Space Flight Center. The functional characteristics of the instrument and the methods used to preprocess the data, including radiometric correction, are described. The radiometric sensitivity of the instrument was tested and compared to that of the Thematic Mapper and the Multispectral Scanner. The radiometric correction procedure was evaluated quantitatively, using laboratory testing, and qualitatively, via visual examination of the LAPR test flight imagery. Although effective radiometric correction could not yet be demonstrated via laboratory testing, radiometric distortion did not preclude the visual interpretation or parallel piped classification of the test imagery.
[Actual relevance of Pauwels' classification of femoral neck fractures--a critical review].
Schwarz, N
2010-03-01
The aim of this study was to evaluate the validity of Pauwels' classification of femoral neck fractures. A study of literature was performed. It has never been proven that the inclination of the fracture plane has a prognostic relevance. A number of papers prove the contrary, there are no publications where Pauwels' classification has been used successfully in selecting treatment modalities. Pauwels' theory of fracture inclination angle has not been transferred into clinical practice. This discrepancy probably goes back to the fact that the angle cannot be determined preoperatively, that in the majority of femoral neck fractures the angle is within the range of 40 to 60 degrees, that the theoretical angle variations do practically not exist, and that the shearing forces are reduced to an unknown amount by friction resistance due to the uneven fracture plane. The mechanical laws of the pseudarthrosis of the femoral neck cannot be extrapolated to acute fractures. The theory of Pauwels has apparently no clinical relevance for the majority of acute fractures, except for the rare transcervical fractures, and should not be considered any longer as a classification of acute femoral neck fractures due to the lack of prognostic and therapeutic relevance.
Cho, Misuk
2015-06-01
[Purpose] This study aimed to identify correlations among pelvic positions and differences in lower extremity joint angles during walking in female university students. [Subjects] Thirty female university students were enrolled and their pelvic positions and differences in lower extremity joint angles were measured. [Methods] Pelvic position, pelvic torsion, and pelvic rotation were assessed using the BackMapper. In addition, motion analysis was performed to derive differences between left and right flexion, abduction, and external rotation ranges of hip joints; flexion, abduction, and external rotation ranges of knee joints; and dorsiflexion, inversion, and abduction ranges of ankle joints, according to X, Y, and Z-axes. [Results] Pelvic position was found to be positively correlated with differences between left and right hip flexion (r=0.51), hip abduction (r=0.62), knee flexion (r=0.45), knee abduction (r=0.42), and ankle inversion (r=0.38). In addition, the difference between left and right hip abduction showed a positive correlation with difference between left and right ankle dorsiflexion (r=0.64). Moreover, differences between left and right knee flexion exhibited positive correlations with differences between left and right knee abduction (r=0.41) and ankle inversion (r=0.45). [Conclusion] Bilateral pelvic tilt angles are important as they lead to bilateral differences in lower extremity joint angles during walking.
Operon-mapper: A Web Server for Precise Operon Identification in Bacterial and Archaeal Genomes.
Taboada, Blanca; Estrada, Karel; Ciria, Ricardo; Merino, Enrique
2018-06-19
Operon-mapper is a web server that accurately, easily, and directly predicts the operons of any bacterial or archaeal genome sequence. The operon predictions are based on the intergenic distance of neighboring genes as well as the functional relationships of their protein-coding products. To this end, Operon-mapper finds all the ORFs within a given nucleotide sequence, along with their genomic coordinates, orthology groups, and functional relationships. We believe that Operon-mapper, due to its accuracy, simplicity and speed, as well as the relevant information that it generates, will be a useful tool for annotating and characterizing genomic sequences. http://biocomputo.ibt.unam.mx/operon_mapper/.
Red Blood Cell Count Automation Using Microscopic Hyperspectral Imaging Technology.
Li, Qingli; Zhou, Mei; Liu, Hongying; Wang, Yiting; Guo, Fangmin
2015-12-01
Red blood cell counts have been proven to be one of the most frequently performed blood tests and are valuable for early diagnosis of some diseases. This paper describes an automated red blood cell counting method based on microscopic hyperspectral imaging technology. Unlike the light microscopy-based red blood count methods, a combined spatial and spectral algorithm is proposed to identify red blood cells by integrating active contour models and automated two-dimensional k-means with spectral angle mapper algorithm. Experimental results show that the proposed algorithm has better performance than spatial based algorithm because the new algorithm can jointly use the spatial and spectral information of blood cells.
Evaluation of corn/soybeans separability using Thematic Mapper and Thematic Mapper Simulator data
NASA Technical Reports Server (NTRS)
Pitts, D. E.; Badhwar, G. D.; Thompson, D. R.; Henderson, K. E.; Shen, S. S.; Sorensen, C. T.; Carnes, J. G.
1984-01-01
Multitemporal Thematic Mapper, Thematic Mapper Simulator, and detailed ground truth data were collected for a 9- by 11-km sample segment in Webster County, IA, in the summer of 1982. Three dates were acquired each with Thematic Mapper Simulator (June 7, June 23, and July 31) and Thematic Mapper (August 2, September 3, and October 21). The Thematic Mapper Simulator data were converted to equivalent TM count values using TM and TMS calibration data and model based estimates of atmospheric effects. The July 31, TMS image was compared to the August 2, TM image to verify the conversion process. A quantitative measure of proportion estimation variance (Fisher information) was used to evaluate the corn/soybeans separability for each TM band as a function of time during the growing season. The additional bands in the middle infrared allowed corn and soybeans to be separated much earlier than was possible with the visible and near-infrared bands alone. Using the TM and TMS data, temporal profiles of the TM principal components were developed. The greenness and brightness exhibited behavior similar to MSS greenness and brightness for corn and soybeans.
Simulation of Thematic Mapper performance as a function of sensor scanning parameters
NASA Technical Reports Server (NTRS)
Johnson, R. H.; Shah, N. J.; Schmidt, N. F.
1975-01-01
The investigation and results of the Thematic Mapper Instrument Performance Study are described. The Thematic Mapper is the advanced multispectral scanner initially planned for the Earth Observation Satellite and now planned for LANDSAT D. The use of existing digital airborne scanner data obtained with the Modular Multispectral Scanner (M2S) at Bendix provided an opportunity to simulate the effects of variation of design parameters of the Thematic Mapper. Analysis and processing of this data on the Bendix Multispectral Data Analysis System were used to empirically determine categorization performance on data generated with variations of the sampling period and scan overlap parameters of the Thematic Mapper. The Bendix M2S data, with a 2.5 milliradian instantaneous field of view and a spatial resolution (pixel size) of 10-m from 13,000 ft altitude, allowed a direct simulation of Thematic Mapper data with a 30-m resolution. The flight data chosen were obtained on 30 June 1973 over agricultural test sites in Indiana.
The use of landsat 7 enhanced thematic mapper plus for mapping leafy spurge
Mladinich, C.S.; Bustos, M.R.; Stitt, S.; Root, R.; Brown, K.; Anderson, G.L.; Hager, S.
2006-01-01
Euphorbia esula L. (leafy spurge) is an invasive weed that is a major problem in much of the Upper Great Plains region, including parts of Montana, South Dakota, North Dakota, Nebraska, and Wyoming. Infestations in North Dakota alone have had a serious economic impact, estimated at $87 million annually in 1991, to the state's wildlife, tourism, and agricultural economy. Leafy spurge degrades prairie and badland ecosystems by displacing native grasses and forbs. It is a major threat to protected ecosystems in many national parks, national wild lands, and state recreational areas in the region. This study explores the use of Landsat 7 Enhanced Thematic Mapper Plus (Landsat) imagery and derived products as a management tool for mapping leafy spurge in Theodore Roosevelt National Park, in southwestern North Dakota. An unsupervised clustering approach was used to map leafy spurge classes and resulted in overall classification accuracies of approximately 63%. The uses of Landsat imagery did not provide the accuracy required for detailed mapping of small patches of the weed. However, it demonstrated the potential for mapping broad-scale (regional) leafy spurge occurrence. This paper offers recommendations on the suitability of Landsat imagery as a tool for use by resource managers to map and monitor leafy spurge populations over large areas.
Completion of the National Land Cover Database (NLCD) 1992–2001 Land Cover Change Retrofit product
Fry, J.A.; Coan, Michael; Homer, Collin G.; Meyer, Debra K.; Wickham, J.D.
2009-01-01
The Multi-Resolution Land Characteristics Consortium has supported the development of two national digital land cover products: the National Land Cover Dataset (NLCD) 1992 and National Land Cover Database (NLCD) 2001. Substantial differences in imagery, legends, and methods between these two land cover products must be overcome in order to support direct comparison. The NLCD 1992-2001 Land Cover Change Retrofit product was developed to provide more accurate and useful land cover change data than would be possible by direct comparison of NLCD 1992 and NLCD 2001. For the change analysis method to be both national in scale and timely, implementation required production across many Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) path/rows simultaneously. To meet these requirements, a hybrid change analysis process was developed to incorporate both post-classification comparison and specialized ratio differencing change analysis techniques. At a resolution of 30 meters, the completed NLCD 1992-2001 Land Cover Change Retrofit product contains unchanged pixels from the NLCD 2001 land cover dataset that have been cross-walked to a modified Anderson Level I class code, and changed pixels labeled with a 'from-to' class code. Analysis of the results for the conterminous United States indicated that about 3 percent of the land cover dataset changed between 1992 and 2001.
Van Wagtendonk, Jan W.; Root, Ralph R.
2003-01-01
The objective of this study was to test the applicability of using Normalized Difference Vegetation Index (NDVI) values derived from a temporal sequence of six Landsat Thematic Mapper (TM) scenes to map fuel models for Yosemite National Park, USA. An unsupervised classification algorithm was used to define 30 unique spectral-temporal classes of NDVI values. A combination of graphical, statistical and visual techniques was used to characterize the 30 classes and identify those that responded similarly and could be combined into fuel models. The final classification of fuel models included six different types: short annual and perennial grasses, tall perennial grasses, medium brush and evergreen hardwoods, short-needled conifers with no heavy fuels, long-needled conifers and deciduous hardwoods, and short-needled conifers with a component of heavy fuels. The NDVI, when analysed over a season of phenologically distinct periods along with ancillary data, can elicit information necessary to distinguish fuel model types. Fuels information derived from remote sensors has proven to be useful for initial classification of fuels and has been applied to fire management situations on the ground.
NASA Technical Reports Server (NTRS)
Zhuang, Xin
1990-01-01
LANDSAT Thematic Mapper (TM) data for March 23, 1987 with accompanying ground truth data for the study area in Miami County, IN were used to determine crop residue type and class. Principle components and spectral ratioing transformations were applied to the LANDSAT TM data. One graphic information system (GIS) layer of land ownership was added to each original image as the eighth band of data in an attempt to improve classification. Maximum likelihood, minimum distance, and neural networks were used to classify the original, transformed, and GIS-enhanced remotely sensed data. Crop residues could be separated from one another and from bare soil and other biomass. Two types of crop residue and four classes were identified from each LANDSAT TM image. The maximum likelihood classifier performed the best classification for each original image without need of any transformation. The neural network classifier was able to improve the classification by incorporating a GIS-layer of land ownership as an eighth band of data. The maximum likelihood classifier was unable to consider this eighth band of data and thus, its results could not be improved by its consideration.
Intelligent image processing for vegetation classification using multispectral LANDSAT data
NASA Astrophysics Data System (ADS)
Santos, Stewart R.; Flores, Jorge L.; Garcia-Torales, G.
2015-09-01
We propose an intelligent computational technique for analysis of vegetation imaging, which are acquired with multispectral scanner (MSS) sensor. This work focuses on intelligent and adaptive artificial neural network (ANN) methodologies that allow segmentation and classification of spectral remote sensing (RS) signatures, in order to obtain a high resolution map, in which we can delimit the wooded areas and quantify the amount of combustible materials present into these areas. This could provide important information to prevent fires and deforestation of wooded areas. The spectral RS input data, acquired by the MSS sensor, are considered in a random propagation remotely sensed scene with unknown statistics for each Thematic Mapper (TM) band. Performing high-resolution reconstruction and adding these spectral values with neighbor pixels information from each TM band, we can include contextual information into an ANN. The biggest challenge in conventional classifiers is how to reduce the number of components in the feature vector, while preserving the major information contained in the data, especially when the dimensionality of the feature space is high. Preliminary results show that the Adaptive Modified Neural Network method is a promising and effective spectral method for segmentation and classification in RS images acquired with MSS sensor.
Vogelmann, James E.; Helder, Dennis; Morfitt, Ron; Choate, Michael J.; Merchant, James W.; Bulley, Henry
2001-01-01
The Thematic Mapper (TM) instruments onboard Landsats 4 and 5 provide high-quality imagery appropriate for many different applications, including land cover mapping, landscape ecology, and change detection. Precise calibration was considered to be critical to the success of the Landsat 7 mission and, thus, issues of calibration were given high priority during the development of the Enhanced Thematic Mapper Plus (ETM+). Data sets from the Landsat 5 TM are not routinely corrected for a number of radiometric and geometric artifacts, including memory effect, gain/bias, and interfocal plane misalignment. In the current investigation, the effects of correcting vs. not correcting these factors were investigated for several applications. Gain/bias calibrations were found to have a greater impact on most applications than did memory effect calibrations. Correcting interfocal plane offsets was found to have a moderate effect on applications. On June 2, 1999, Landsats 5 and 7 data were acquired nearly simultaneously over a study site in the Niobrara, NE area. Field radiometer data acquired at that site were used to facilitate crosscalibrations of Landsats 5 and 7 data. Current findings and results from previous investigations indicate that the internal calibrator of Landsat 5 TM tracked instrument gain well until 1988. After this, the internal calibrator diverged from the data derived from vicarious calibrations. Results from this study also indicate very good agreement between prelaunch measurements and vicarious calibration data for all Landsat 7 reflective bands except Band 4. Values are within about 3.5% of each other, except for Band 4, which differs by 10%. Coefficient of variation (CV) values derived from selected targets in the imagery were also analyzed. The Niobrara Landsat 7 imagery was found to have lower CV values than Landsat 5 data, implying that lower levels of noise characterize Landsat 7 data than current Landsat 5 data. It was also found that following radiometric normalization, the Normalized Difference Vegetation Index (NDVI) imagery and classification products of Landsats 5 and 7 were very similar. This implies that data from the two sensors can be used to measure and monitor the same landscape phenomena and that Landsats 5 and 7 data can be used interchangeably with proper caution. In addition, it was found that difference imagery produced using Landsat 7 ETM+ data are of excellent quality.
NASA Technical Reports Server (NTRS)
Quattrochi, D. A.
1985-01-01
The capabilities of TM data for discriminating land covers within three particular cultural and ecological realms was assessed. The agricultural investigation in Poinsett County, Arkansas illustrates that TM data can successfully be used to discriminate a variety of crop cover types within the study area. The single-date TM classification produced results that were significantly better than those developed from multitemporal MSS data. For the Reelfoot Lake area of Tennessee TM data, processed using unsupervised signature development techniques, produced a detailed classification of forested wetlands with excellent accuracy. Even in a small city of approximately 15,000 people (Union City, Tennessee). TM data can successfully be used to spectrally distinguish specific urban classes. Furthermore, the principal components analysis evaluation of the data shows that through photointerpretation, it is possible to distinguish individual buildings and roof responses with the TM.
Segmentation and classification of road markings using MLS data
NASA Astrophysics Data System (ADS)
Soilán, Mario; Riveiro, Belén; Martínez-Sánchez, Joaquín; Arias, Pedro
2017-01-01
Traffic signs are one of the most important safety elements in a road network. Particularly, road markings provide information about the limits and direction of each road lane, or warn the drivers about potential danger. The optimal condition of road markings contributes to a better road safety. Mobile Laser Scanning technology can be used for infrastructure inspection and specifically for traffic sign detection and inventory. This paper presents a methodology for the detection and semantic characterization of the most common road markings, namely pedestrian crossings and arrows. The 3D point cloud data acquired by a LYNX Mobile Mapper system is filtered in order to isolate reflective points in the road, and each single element is hierarchically classified using Neural Networks. State of the art results are obtained for the extraction and classification of the markings, with F-scores of 94% and 96% respectively. Finally, data from classified markings are exported to a GIS layer and maintenance criteria based on the aforementioned data are proposed.
Jorgenson, Janet C.; Joria, Peter C.; Douglas, David C.; Douglas, David C.; Reynolds, Patricia E.; Rhode, E.B.
2002-01-01
Documenting the distribution of land-cover types on the Arctic National Wildlife Refuge coastal plain is the foundation for impact assessment and mitigation of potential oil exploration and development. Vegetation maps facilitate wildlife studies by allowing biologists to quantify the availability of important wildlife habitats, investigate the relationships between animal locations and the distribution or juxtaposition of habitat types, and assess or extrapolate habitat characteristics across regional areas.To meet the needs of refuge managers and biologists, satellite imagery was chosen as the most cost-effective method for mapping the large, remote landscape of the 1002 Area.Objectives of our study were the following: 1) evaluate a vegetation classification scheme for use in mapping. 2) determine optimal methods for producing a satellite-based vegetation map that adequately met the needs of the wildlife research and management objectives; 3) produce a digital vegetation map for the Arctic Refuge coastal plain using Lands at-Thematic Mapper(TM) satellite imagery, existing geobotanical classifications, ground data, and aerial photographs, and 4) perform an accuracy assessment of the map.
Evaluation of spatial, radiometric and spectral Thematic Mapper performance for coastal studies
NASA Technical Reports Server (NTRS)
Klemas, V. (Principal Investigator)
1983-01-01
A series of experiments were initiated to determine the feasibility of using thematic mapper spectral data to estimate wetlands biomass. The experiments were conducted using hand-held radiometers simulating thematic mapper wavebands 3, 4 and 5. Spectral radiance data were collected from the ground and from a low altitude aircraft in an attempt to gain some insight into the potential utility of actual thematic mapper data for biomass estimation in wetland plant communities. In addition, radiative transfer models describing volume reflectance of eight water column containing submerged aquatic vegetation were refined.
A neural network approach for enhancing information extraction from multispectral image data
Liu, J.; Shao, G.; Zhu, H.; Liu, S.
2005-01-01
A back-propagation artificial neural network (ANN) was applied to classify multispectral remote sensing imagery data. The classification procedure included four steps: (i) noisy training that adds minor random variations to the sampling data to make the data more representative and to reduce the training sample size; (ii) iterative or multi-tier classification that reclassifies the unclassified pixels by making a subset of training samples from the original training set, which means the neural model can focus on fewer classes; (iii) spectral channel selection based on neural network weights that can distinguish the relative importance of each channel in the classification process to simplify the ANN model; and (iv) voting rules that adjust the accuracy of classification and produce outputs of different confidence levels. The Purdue Forest, located west of Purdue University, West Lafayette, Indiana, was chosen as the test site. The 1992 Landsat thematic mapper imagery was used as the input data. High-quality airborne photographs of the same Lime period were used for the ground truth. A total of 11 land use and land cover classes were defined, including water, broadleaved forest, coniferous forest, young forest, urban and road, and six types of cropland-grassland. The experiment, indicated that the back-propagation neural network application was satisfactory in distinguishing different land cover types at US Geological Survey levels II-III. The single-tier classification reached an overall accuracy of 85%. and the multi-tier classification an overall accuracy of 95%. For the whole test, region, the final output of this study reached an overall accuracy of 87%. ?? 2005 CASI.
Landsat-5 bumper-mode geometric correction
Storey, James C.; Choate, Michael J.
2004-01-01
The Landsat-5 Thematic Mapper (TM) scan mirror was switched from its primary operating mode to a backup mode in early 2002 in order to overcome internal synchronization problems arising from long-term wear of the scan mirror mechanism. The backup bumper mode of operation removes the constraints on scan start and stop angles enforced in the primary scan angle monitor operating mode, requiring additional geometric calibration effort to monitor the active scan angles. It also eliminates scan timing telemetry used to correct the TM scan geometry. These differences require changes to the geometric correction algorithms used to process TM data. A mathematical model of the scan mirror's behavior when operating in bumper mode was developed. This model includes a set of key timing parameters that characterize the time-varying behavior of the scan mirror bumpers. To simplify the implementation of the bumper-mode model, the bumper timing parameters were recast in terms of the calibration and telemetry data items used to process normal TM imagery. The resulting geometric performance, evaluated over 18 months of bumper-mode operations, though slightly reduced from that achievable in the primary operating mode, is still within the Landsat specifications when the data are processed with the most up-to-date calibration parameters.
Karan, Shivesh Kishore; Samadder, Sukha Ranjan
2016-08-01
One objective of the present study was to evaluate the performance of support vector machine (SVM)-based image classification technique with the maximum likelihood classification (MLC) technique for a rapidly changing landscape of an open-cast mine. The other objective was to assess the change in land use pattern due to coal mining from 2006 to 2016. Assessing the change in land use pattern accurately is important for the development and monitoring of coalfields in conjunction with sustainable development. For the present study, Landsat 5 Thematic Mapper (TM) data of 2006 and Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) data of 2016 of a part of Jharia Coalfield, Dhanbad, India, were used. The SVM classification technique provided greater overall classification accuracy when compared to the MLC technique in classifying heterogeneous landscape with limited training dataset. SVM exceeded MLC in handling a difficult challenge of classifying features having near similar reflectance on the mean signature plot, an improvement of over 11 % was observed in classification of built-up area, and an improvement of 24 % was observed in classification of surface water using SVM; similarly, the SVM technique improved the overall land use classification accuracy by almost 6 and 3 % for Landsat 5 and Landsat 8 images, respectively. Results indicated that land degradation increased significantly from 2006 to 2016 in the study area. This study will help in quantifying the changes and can also serve as a basis for further decision support system studies aiding a variety of purposes such as planning and management of mines and environmental impact assessment.
An assessment of the effectiveness of a random forest classifier for land-cover classification
NASA Astrophysics Data System (ADS)
Rodriguez-Galiano, V. F.; Ghimire, B.; Rogan, J.; Chica-Olmo, M.; Rigol-Sanchez, J. P.
2012-01-01
Land cover monitoring using remotely sensed data requires robust classification methods which allow for the accurate mapping of complex land cover and land use categories. Random forest (RF) is a powerful machine learning classifier that is relatively unknown in land remote sensing and has not been evaluated thoroughly by the remote sensing community compared to more conventional pattern recognition techniques. Key advantages of RF include: their non-parametric nature; high classification accuracy; and capability to determine variable importance. However, the split rules for classification are unknown, therefore RF can be considered to be black box type classifier. RF provides an algorithm for estimating missing values; and flexibility to perform several types of data analysis, including regression, classification, survival analysis, and unsupervised learning. In this paper, the performance of the RF classifier for land cover classification of a complex area is explored. Evaluation was based on several criteria: mapping accuracy, sensitivity to data set size and noise. Landsat-5 Thematic Mapper data captured in European spring and summer were used with auxiliary variables derived from a digital terrain model to classify 14 different land categories in the south of Spain. Results show that the RF algorithm yields accurate land cover classifications, with 92% overall accuracy and a Kappa index of 0.92. RF is robust to training data reduction and noise because significant differences in kappa values were only observed for data reduction and noise addition values greater than 50 and 20%, respectively. Additionally, variables that RF identified as most important for classifying land cover coincided with expectations. A McNemar test indicates an overall better performance of the random forest model over a single decision tree at the 0.00001 significance level.
NASA Technical Reports Server (NTRS)
Hoffer, R. M. (Principal Investigator)
1979-01-01
The spatial characteristics of the data were evaluated. A program was developed to reduce the spatial distortions resulting from variable viewing distance, and geometrically adjusted data sets were generated. The potential need for some level of radiometric adjustment was evidenced by an along track band of high reflectance across different cover types in the Varian imagery. A multiple regression analysis was employed to explore the viewing angle effect on measured reflectance. Areas in the data set which appeared to have no across track stratification of cover type were identified. A program was developed which computed the average reflectance by column for each channel, over all of the scan lines in the designated areas. A regression analysis was then run using the first, second, and third degree polynomials, for each channel. An atmospheric effect as a component of the viewing angle source of variance is discussed. Cover type maps were completed and training and test field selection was initiated.
Navigation system for autonomous mapper robots
NASA Astrophysics Data System (ADS)
Halbach, Marc; Baudoin, Yvan
1993-05-01
This paper describes the conception and realization of a fast, robust, and general navigation system for a mobile (wheeled or legged) robot. A database, representing a high level map of the environment is generated and continuously updated. The first part describes the legged target vehicle and the hexapod robot being developed. The second section deals with spatial and temporal sensor fusion for dynamic environment modeling within an obstacle/free space probabilistic classification grid. Ultrasonic sensors are used, others are suspected to be integrated, and a-priori knowledge is treated. US sensors are controlled by the path planning module. The third part concerns path planning and a simulation of a wheeled robot is also presented.
Relationship between foot posture and dental malocclusions in children aged 6 to 9 years
Marchena-Rodríguez, Ana; Moreno-Morales, Noelia; Ramírez-Parga, Edith; Labajo-Manzanares, María Teresa; Luque-Suárez, Alejandro; Gijon-Nogueron, Gabriel
2018-01-01
Abstract The aim of this study was to determine the association, if any, between foot posture and dental malocclusions in the anteroposterior plane, in children. The study population consisted of 189 children (95 boys and 94 girls) aged 6 to 9 years. In every case, previous informed consent was requested and obtained from the parent/guardian and the study was approved by the Ethics Committee of the University of Málaga (CEUMA 26/2015H). This observational, descriptive, cross-sectional analysis is based on a study population (STROBE). Qualified personnel conducted a podiatric and dental examination of each child, recording the Clarke angle and the foot posture index (FPI) as an outcomes measure in the feet, and also dental malocclusions, according to Angle classification. A significant correlation was observed for the FPI scores (for right foot) as well as the Clarke angle (for right foot), in relation to dental malocclusions as determined by Angle classification (P < .001). Of all the supinated feet analyzed, 38.46% were Class II according to Angle classification, and none were Class III. Of the pronated feet, 48.57% were Class III, 42.85% were Class I, and 8.57% were Class II. The Clarke angle decreases with the progression from Class I to III, whereas the FPI increases with that from Class I to III. These findings suggest there is a relation between the Clarke angle and FPI, on the one hand, and dental malocclusion on the other. PMID:29742725
Marchena-Rodríguez, Ana; Moreno-Morales, Noelia; Ramírez-Parga, Edith; Labajo-Manzanares, María Teresa; Luque-Suárez, Alejandro; Gijon-Nogueron, Gabriel
2018-05-01
The aim of this study was to determine the association, if any, between foot posture and dental malocclusions in the anteroposterior plane, in children.The study population consisted of 189 children (95 boys and 94 girls) aged 6 to 9 years. In every case, previous informed consent was requested and obtained from the parent/guardian and the study was approved by the Ethics Committee of the University of Málaga (CEUMA 26/2015H).This observational, descriptive, cross-sectional analysis is based on a study population (STROBE). Qualified personnel conducted a podiatric and dental examination of each child, recording the Clarke angle and the foot posture index (FPI) as an outcomes measure in the feet, and also dental malocclusions, according to Angle classification.A significant correlation was observed for the FPI scores (for right foot) as well as the Clarke angle (for right foot), in relation to dental malocclusions as determined by Angle classification (P < .001). Of all the supinated feet analyzed, 38.46% were Class II according to Angle classification, and none were Class III. Of the pronated feet, 48.57% were Class III, 42.85% were Class I, and 8.57% were Class II.The Clarke angle decreases with the progression from Class I to III, whereas the FPI increases with that from Class I to III. These findings suggest there is a relation between the Clarke angle and FPI, on the one hand, and dental malocclusion on the other.
NASA Astrophysics Data System (ADS)
Lang, T. J.; Blakeslee, R. J.; Cecil, D. J.; Christian, H. J.; Gatlin, P. N.; Goodman, S. J.; Koshak, W. J.; Petersen, W. A.; Quick, M.; Schultz, C. J.; Tatum, P. F.
2018-02-01
We propose the Deep Space Gateway Lightning Mapper (DLM) instrument. The primary goal of the DLM is to optically monitor Earth's high-latitude (50° and poleward) total lightning not observed by current and planned spaceborne lightning mappers.
Resource and environmental surveys from space with the thematic mapper in the 1980's
NASA Technical Reports Server (NTRS)
1976-01-01
The selection of observation of vegetation is the primary optimization objective of the thematic mapper. The following are aspects of plans for the thematic mapper: (1) to include an appropriately modified first generation MSS in the thematic mapper mission; (2) to provide assured coverage for a minimum of six years to give agencies and other users an opportunity to justify the necessary commitment of resources for the transition into a completely valid operational phase; (3) to provide for global, direct data read-out, without the necessity for on-board data storage or dependence on foreign receiving stations; (4) to recognize the operational character of the thematic mapper after successful completion of its experimental evaluation; and (5) to combine future experimental packages with compatible orbits as part of the operational LANDSAT follow-on payloads.
A mobile, web-based system can improve positive airway pressure adherence.
Hostler, Jordanna M; Sheikh, Karen L; Andrada, Teotimo F; Khramtsov, Andrei; Holley, Paul R; Holley, Aaron B
2017-04-01
SleepMapper is a mobile, web-based system that allows patients to self-monitor their positive airway pressure therapy, and provides feedback and education in real time. In addition to the usual, comprehensive support provided at our clinic, we gave the SleepMapper to 30 patients initiating positive airway pressure. They were compared with patients initiating positive airway pressure at our clinic without SleepMapper (controls) to determine whether SleepMapper affected adherence. A total of 61 patients had polysomnographic and adherence data analysed, 30 were given SleepMapper and 31 received our standard of care. The two groups were well matched at baseline to include no significant differences in age, apnea-hypopnea index, percentage receiving split-night polysomnographs and starting pressures. Patients in the control group received significantly more non-benzodiazepine sedative hypnotics the night of their polysomnography and during positive airway pressure initiation. At 11 weeks, patients in the SleepMapper group had a greater percentage of nights with any use (78.0 ± 22.0 versus 55.5 ± 24.0%; P < 0.001) and >4 h positive airway pressure use (78.0 ± 22.0 versus 55.5 ± 24.0%; P = 0.02). There was a trend toward more patients in the SleepMapper group achieving >4 h of use for at least 70% of nights [9/30 (30%) versus 3/31 (9.7%); P = 0.06]. In multivariate linear regression, the SleepMapper remained significantly associated with percentage of nights >4 h positive airway pressure use (β coefficient = 0.18; P = 0.02). Added to our usual, comprehensive programme to maximize positive airway pressure adherence in new users, the SleepMapper was independently associated with an 18% increase in nights >4 h of use. © 2016 European Sleep Research Society.
NASA Astrophysics Data System (ADS)
Gallegos, M. I.; Espejel-Garcia, V. V.
2012-12-01
The Camargo volcanic field (CVF) covers ~3000 km2 and is located in the southeast part of the state of Chihuahua, within the Basin and Range province. The CVF represents the largest mafic alkali volcanic field in northern Mexico. Over a 300 cinder cones have been recognized in the Camargo volcanic field. Volcanic activity ranges from 4.7 to 0.09 Ma revealed by 40Ar/39Ar dating methods. Previous studies say that there is a close relationship between the cinder cone slope angle, due to mechanical weathering, and age. This technique is considered a reliable age indicator, especially in arid climates, such as occur in the CVF. Data were acquired with digital topographic maps (DRG) and digital elevation models (DEM) overlapped in the Global Mapper software. For each cone, the average radius (r) was calculated from six measurements, the height (h) is the difference between peak elevation and the altitude of the contour used to close the radius, and the slope angle was calculated using the equation Θ = tan-1(h/r). The slope angles of 30 cinder cones were calculated showing angles ranging from 4 to 15 degrees. A diffusion model, displayed by an exponential relationship between slope angle and age, places the ages of these 30 cones from 215 to 82 ka, within the range marked by radiometric methods. Future work include the analysis of more cinder cones to cover the whole CVF, and contribute to the validation of this technique.
NASA Technical Reports Server (NTRS)
Mehta, N. C.
1984-01-01
The utility of radar scatterometers for discrimination and characterization of natural vegetation was investigated. Backscatter measurements were acquired with airborne multi-frequency, multi-polarization, multi-angle radar scatterometers over a test site in a southern temperate forest. Separability between ground cover classes was studied using a two-class separability measure. Very good separability is achieved between most classes. Longer wavelength is useful in separating trees from non-tree classes, while shorter wavelength and cross polarization are helpful for discrimination among tree classes. Using the maximum likelihood classifier, 50% overall classification accuracy is achieved using a single, short-wavelength scatterometer channel. Addition of multiple incidence angles and another radar band improves classification accuracy by 20% and 50%, respectively, over the single channel accuracy. Incorporation of a third radar band seems redundant for vegetation classification. Vertical transmit polarization is critically important for all classes.
SAR target recognition and posture estimation using spatial pyramid pooling within CNN
NASA Astrophysics Data System (ADS)
Peng, Lijiang; Liu, Xiaohua; Liu, Ming; Dong, Liquan; Hui, Mei; Zhao, Yuejin
2018-01-01
Many convolution neural networks(CNN) architectures have been proposed to strengthen the performance on synthetic aperture radar automatic target recognition (SAR-ATR) and obtained state-of-art results on targets classification on MSTAR database, but few methods concern about the estimation of depression angle and azimuth angle of targets. To get better effect on learning representation of hierarchies of features on both 10-class target classification task and target posture estimation tasks, we propose a new CNN architecture with spatial pyramid pooling(SPP) which can build high hierarchy of features map by dividing the convolved feature maps from finer to coarser levels to aggregate local features of SAR images. Experimental results on MSTAR database show that the proposed architecture can get high recognition accuracy as 99.57% on 10-class target classification task as the most current state-of-art methods, and also get excellent performance on target posture estimation tasks which pays attention to depression angle variety and azimuth angle variety. What's more, the results inspire us the application of deep learning on SAR target posture description.
Delineation of marsh types and marsh-type change in coastal Louisiana for 2007 and 2013
Hartley, Stephen B.; Couvillion, Brady R.; Enwright, Nicholas M.
2017-05-30
The Bureau of Ocean Energy Management researchers often require detailed information regarding emergent marsh vegetation types (such as fresh, intermediate, brackish, and saline) for modeling habitat capacities and mitigation. In response, the U.S. Geological Survey in cooperation with the Bureau of Ocean Energy Management produced a detailed change classification of emergent marsh vegetation types in coastal Louisiana from 2007 and 2013. This study incorporates two existing vegetation surveys and independent variables such as Landsat Thematic Mapper multispectral satellite imagery, high-resolution airborne imagery from 2007 and 2013, bare-earth digital elevation models based on airborne light detection and ranging, alternative contemporary land-cover classifications, and other spatially explicit variables. An image classification based on image objects was created from 2007 and 2013 National Agriculture Imagery Program color-infrared aerial photography. The final products consisted of two 10-meter raster datasets. Each image object from the 2007 and 2013 spatial datasets was assigned a vegetation classification by using a simple majority filter. In addition to those spatial datasets, we also conducted a change analysis between the datasets to produce a 10-meter change raster product. This analysis identified how much change has taken place and where change has occurred. The spatial data products show dynamic areas where marsh loss is occurring or where marsh type is changing. This information can be used to assist and advance conservation efforts for priority natural resources.
Lineage mapper: A versatile cell and particle tracker
NASA Astrophysics Data System (ADS)
Chalfoun, Joe; Majurski, Michael; Dima, Alden; Halter, Michael; Bhadriraju, Kiran; Brady, Mary
2016-11-01
The ability to accurately track cells and particles from images is critical to many biomedical problems. To address this, we developed Lineage Mapper, an open-source tracker for time-lapse images of biological cells, colonies, and particles. Lineage Mapper tracks objects independently of the segmentation method, detects mitosis in confluence, separates cell clumps mistakenly segmented as a single cell, provides accuracy and scalability even on terabyte-sized datasets, and creates division and/or fusion lineages. Lineage Mapper has been tested and validated on multiple biological and simulated problems. The software is available in ImageJ and Matlab at isg.nist.gov.
HGDP and HapMap Analysis by Ancestry Mapper Reveals Local and Global Population Relationships
Magalhães, Tiago R.; Casey, Jillian P.; Conroy, Judith; Regan, Regina; Fitzpatrick, Darren J.; Shah, Naisha; Sobral, João; Ennis, Sean
2012-01-01
Knowledge of human origins, migrations, and expansions is greatly enhanced by the availability of large datasets of genetic information from different populations and by the development of bioinformatic tools used to analyze the data. We present Ancestry Mapper, which we believe improves on existing methods, for the assignment of genetic ancestry to an individual and to study the relationships between local and global populations. The principle function of the method, named Ancestry Mapper, is to give each individual analyzed a genetic identifier, made up of just 51 genetic coordinates, that corresponds to its relationship to the HGDP reference population. As a consequence, the Ancestry Mapper Id (AMid) has intrinsic biological meaning and provides a tool to measure similarity between world populations. We applied Ancestry Mapper to a dataset comprised of the HGDP and HapMap data. The results show distinctions at the continental level, while simultaneously giving details at the population level. We clustered AMids of HGDP/HapMap and observe a recapitulation of human migrations: for a small number of clusters, individuals are grouped according to continental origins; for a larger number of clusters, regional and population distinctions are evident. Calculating distances between AMids allows us to infer ancestry. The number of coordinates is expandable, increasing the power of Ancestry Mapper. An R package called Ancestry Mapper is available to apply this method to any high density genomic data set. PMID:23189146
HGDP and HapMap analysis by Ancestry Mapper reveals local and global population relationships.
Magalhães, Tiago R; Casey, Jillian P; Conroy, Judith; Regan, Regina; Fitzpatrick, Darren J; Shah, Naisha; Sobral, João; Ennis, Sean
2012-01-01
Knowledge of human origins, migrations, and expansions is greatly enhanced by the availability of large datasets of genetic information from different populations and by the development of bioinformatic tools used to analyze the data. We present Ancestry Mapper, which we believe improves on existing methods, for the assignment of genetic ancestry to an individual and to study the relationships between local and global populations. The principle function of the method, named Ancestry Mapper, is to give each individual analyzed a genetic identifier, made up of just 51 genetic coordinates, that corresponds to its relationship to the HGDP reference population. As a consequence, the Ancestry Mapper Id (AMid) has intrinsic biological meaning and provides a tool to measure similarity between world populations. We applied Ancestry Mapper to a dataset comprised of the HGDP and HapMap data. The results show distinctions at the continental level, while simultaneously giving details at the population level. We clustered AMids of HGDP/HapMap and observe a recapitulation of human migrations: for a small number of clusters, individuals are grouped according to continental origins; for a larger number of clusters, regional and population distinctions are evident. Calculating distances between AMids allows us to infer ancestry. The number of coordinates is expandable, increasing the power of Ancestry Mapper. An R package called Ancestry Mapper is available to apply this method to any high density genomic data set.
CheS-Mapper 2.0 for visual validation of (Q)SAR models
2014-01-01
Background Sound statistical validation is important to evaluate and compare the overall performance of (Q)SAR models. However, classical validation does not support the user in better understanding the properties of the model or the underlying data. Even though, a number of visualization tools for analyzing (Q)SAR information in small molecule datasets exist, integrated visualization methods that allow the investigation of model validation results are still lacking. Results We propose visual validation, as an approach for the graphical inspection of (Q)SAR model validation results. The approach applies the 3D viewer CheS-Mapper, an open-source application for the exploration of small molecules in virtual 3D space. The present work describes the new functionalities in CheS-Mapper 2.0, that facilitate the analysis of (Q)SAR information and allows the visual validation of (Q)SAR models. The tool enables the comparison of model predictions to the actual activity in feature space. The approach is generic: It is model-independent and can handle physico-chemical and structural input features as well as quantitative and qualitative endpoints. Conclusions Visual validation with CheS-Mapper enables analyzing (Q)SAR information in the data and indicates how this information is employed by the (Q)SAR model. It reveals, if the endpoint is modeled too specific or too generic and highlights common properties of misclassified compounds. Moreover, the researcher can use CheS-Mapper to inspect how the (Q)SAR model predicts activity cliffs. The CheS-Mapper software is freely available at http://ches-mapper.org. Graphical abstract Comparing actual and predicted activity values with CheS-Mapper.
Gose, Shinichi; Sakai, Takashi; Shibata, Toru; Akiyama, Keisuke; Yoshikawa, Hideki; Sugamoto, Kazuomi
2011-12-01
We evaluated the validity of the Robin and Graham classification system of hip disease in cerebral palsy (CP) using three-dimensional computed tomography in young people with CP. A total of 91 hips in 91 consecutive children with bilateral spastic CP (57 males, 34 females; nine classified at Gross Motor Function Classification System level II, 42 at level III, 32 at level IV, and eight at level V; mean age 5 y 2 mo, SD 11 mo; range 2-6 y) were investigated retrospectively using anteroposterior plain radiographs and three-dimensional computed tomography (3D-CT) of the hip. The migration percentage was calculated on plain radiographs and all participants were classified into four groups according to migration percentage: grade II, migration percentage ≥ 10% but ≤ 15%, (four hips), grade III, migration percentage >15% but ≤ 30%, (20 hips); grade IV, migration percentage >30% but <100%, (63 hips); and grade V, migration percentage ≥ 100%, (four hips). The lateral opening angle and the sagittal inclination angle of the acetabulum, the neck-shaft angle, and the femoral anteversion of the femur were measured on 3D-CT. The three-dimensional quantitative evaluation indicated that there were significant differences in the lateral opening angle and the neck-shaft angle between the four groups (Kruskal-Wallis test, p ≤ 0.001). This three-dimensional evaluation supports the validation of the Robin and Graham classification system for hip disease in 2- to 7-year-olds with CP. © The Authors. Developmental Medicine & Child Neurology © 2011 Mac Keith Press.
NASA Astrophysics Data System (ADS)
Haffner, D. P.; McPeters, R. D.; Bhartia, P. K.; Labow, G. J.
2015-12-01
The TOMS V9 total ozone algorithm will be applied to the OMPS Nadir Mapper instrument to supersede the exisiting V8.6 data product in operational processing and re-processing for public release. Becuase the quality of the V8.6 data is already quite high, enchancements in V9 are mainly with information provided by the retrieval and simplifcations to the algorithm. The design of the V9 algorithm has been influenced by improvements both in our knowledge of atmospheric effects, such as those of clouds made possible by studies with OMI, and also limitations in the V8 algorithms applied to both OMI and OMPS. But the namesake instruments of the TOMS algorithm are substantially more limited in their spectral and noise characterisitics, and a requirement of our algorithm is to also apply the algorithm to these discrete band spectrometers which date back to 1978. To achieve continuity for all these instruments, the TOMS V9 algorithm continues to use radiances in discrete bands, but now uses Rodgers optimal estimation to retrieve a coarse profile and provide uncertainties for each retrieval. The algorithm remains capable of achieving high accuracy results with a small number of discrete wavelengths, and in extreme cases, such as unusual profile shapes and high solar zenith angles, the quality of the retrievals is improved. Despite the intended design to use limited wavlenegths, the algorithm can also utilitze additional wavelengths from hyperspectral sensors like OMPS to augment the retreival's error detection and information content; for example SO2 detection and correction of Ring effect on atmospheric radiances. We discuss these and other aspects of the V9 algorithm as it will be applied to OMPS, and will mention potential improvements which aim to take advantage of a synergy with OMPS Limb Profiler and Nadir Mapper to further improve the quality of total ozone from the OMPS instrument.
Vogelmann, James E.; DeFelice, Thomas P.
2003-01-01
Landsat-7 and Landsat-5 have orbits that are offset from each other by 8 days. During the time that the sensors on both satellites are operational, there is an opportunity for conducting analyses that incorporate multiple intra-annual high spatial resolution data sets for characterizing the Earth's land surface. In the current study, nine Landsat thematic mapper (TM) and enhanced thematic mapper plus (ETM+) data sets, covering the same path and row on different dates, were acquired during a 1-year time interval for a region in southeastern South Dakota and analyzed. Scenes were normalized using pseudoinvariant objects, and digital data from a series of test sites were extracted from the imagery and converted to surface reflectance. Sunphotometer data acquired on site were used to atmospherically correct the data. Ground observations that were made throughout the growing season by a large group of volunteers were used to help interpret spectroradiometric patterns and trends. Normalized images were found to be very effective in portraying the seasonal patterns of reflectance change that occurred throughout the region. Many of the radiometric patterns related to plant growth and development, but some also related to different background properties. The different kinds of land cover in the region were spectrally and radiometrically characterized and were found to have different seasonal patterns of reflectance. The degree to which the land cover classes could be separated spectrally and radiometrically, however, depended on the time of year during which the data sets were acquired, and no single data set appeared to be adequate for separating all types of land cover. This has practical implications for classification studies because known patterns of seasonal reflectance properties for the different types of land cover within a region will facilitate selection of the most appropriate data sets for producing land cover classifications.
Land Cover Change in the Boston Mountains, 1973-2000
Karstensen, Krista A.
2009-01-01
The U.S. Geological Survey (USGS) Land Cover Trends project is focused on understanding the rates, trends, causes, and consequences of contemporary U.S. land-cover change. The objectives of the study are to: (1) to develop a comprehensive methodology for using sampling and change analysis techniques and Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) data to measure regional land-cover change across the United States; (2) to characterize the types, rates, and temporal variability of change for a 30-year period; (3) to document regional driving forces and consequences of change; and (4) to prepare a national synthesis of land-cover change (Loveland and others, 1999). The 1999 Environmental Protection Agency (EPA) Level III ecoregions derived from Omernik (1987) provide the geographic framework for the geospatial data collected between 1973 and 2000. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000, and 1973-2000, and the data are evaluated using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) for image interpretation. The rates of land-cover change are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change for the five time periods previously mentioned. Additionally, historic aerial photographs from similar time frames and other ancillary data, such as census statistics and published literature, are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. Field data of the sample blocks include direct measurements of land cover, particularly ground-survey data collected for training and validation of image classifications (Loveland and others, 2002). The field experience allows for additional observations of the character and condition of the landscape, assistance in sample block interpretation, ground truthing of Landsat imagery, and determination of the driving forces of change identified in an ecoregion.
cMapper: gene-centric connectivity mapper for EBI-RDF platform.
Shoaib, Muhammad; Ansari, Adnan Ahmad; Ahn, Sung-Min
2017-01-15
In this era of biological big data, data integration has become a common task and a challenge for biologists. The Resource Description Framework (RDF) was developed to enable interoperability of heterogeneous datasets. The EBI-RDF platform enables an efficient data integration of six independent biological databases using RDF technologies and shared ontologies. However, to take advantage of this platform, biologists need to be familiar with RDF technologies and SPARQL query language. To overcome this practical limitation of the EBI-RDF platform, we developed cMapper, a web-based tool that enables biologists to search the EBI-RDF databases in a gene-centric manner without a thorough knowledge of RDF and SPARQL. cMapper allows biologists to search data entities in the EBI-RDF platform that are connected to genes or small molecules of interest in multiple biological contexts. The input to cMapper consists of a set of genes or small molecules, and the output are data entities in six independent EBI-RDF databases connected with the given genes or small molecules in the user's query. cMapper provides output to users in the form of a graph in which nodes represent data entities and the edges represent connections between data entities and inputted set of genes or small molecules. Furthermore, users can apply filters based on database, taxonomy, organ and pathways in order to focus on a core connectivity graph of their interest. Data entities from multiple databases are differentiated based on background colors. cMapper also enables users to investigate shared connections between genes or small molecules of interest. Users can view the output graph on a web browser or download it in either GraphML or JSON formats. cMapper is available as a web application with an integrated MySQL database. The web application was developed using Java and deployed on Tomcat server. We developed the user interface using HTML5, JQuery and the Cytoscape Graph API. cMapper can be accessed at http://cmapper.ewostech.net Readers can download the development manual from the website http://cmapper.ewostech.net/docs/cMapperDocumentation.pdf. Source Code is available at https://github.com/muhammadshoaib/cmapperContact:smahn@gachon.ac.krSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
EEG Subspace Analysis and Classification Using Principal Angles for Brain-Computer Interfaces
NASA Astrophysics Data System (ADS)
Ashari, Rehab Bahaaddin
Brain-Computer Interfaces (BCIs) help paralyzed people who have lost some or all of their ability to communicate and control the outside environment from loss of voluntary muscle control. Most BCIs are based on the classification of multichannel electroencephalography (EEG) signals recorded from users as they respond to external stimuli or perform various mental activities. The classification process is fraught with difficulties caused by electrical noise, signal artifacts, and nonstationarity. One approach to reducing the effects of similar difficulties in other domains is the use of principal angles between subspaces, which has been applied mostly to video sequences. This dissertation studies and examines different ideas using principal angles and subspaces concepts. It introduces a novel mathematical approach for comparing sets of EEG signals for use in new BCI technology. The success of the presented results show that principal angles are also a useful approach to the classification of EEG signals that are recorded during a BCI typing application. In this application, the appearance of a subject's desired letter is detected by identifying a P300-wave within a one-second window of EEG following the flash of a letter. Smoothing the signals before using them is the only preprocessing step that was implemented in this study. The smoothing process based on minimizing the second derivative in time is implemented to increase the classification accuracy instead of using the bandpass filter that relies on assumptions on the frequency content of EEG. This study examines four different ways of removing outliers that are based on the principal angles and shows that the outlier removal methods did not help in the presented situations. One of the concepts that this dissertation focused on is the effect of the number of trials on the classification accuracies. The achievement of the good classification results by using a small number of trials starting from two trials only, should make this approach more appropriate for online BCI applications. In order to understand and test how EEG signals are different from one subject to another, different users are tested in this dissertation, some with motor impairments. Furthermore, the concept of transferring information between subjects is examined by training the approach on one subject and testing it on the other subject using the training subject's EEG subspaces to classify the testing subject's trials.
SLO blind data set inversion and classification using physically complete models
NASA Astrophysics Data System (ADS)
Shamatava, I.; Shubitidze, F.; Fernández, J. P.; Barrowes, B. E.; O'Neill, K.; Grzegorczyk, T. M.; Bijamov, A.
2010-04-01
Discrimination studies carried out on TEMTADS and Metal Mapper blind data sets collected at the San Luis Obispo UXO site are presented. The data sets included four types of targets of interest: 2.36" rockets, 60-mm mortar shells, 81-mm projectiles, and 4.2" mortar items. The total parameterized normalized magnetic source (NSMS) amplitudes were used to discriminate TOI from metallic clutter and among the different hazardous UXO. First, in object's frame coordinate, the total NSMS were determined for each TOI along three orthogonal axes from the training data provided by the Strategic Environmental Research and Development Program (SERDP) along with the referred blind data sets. Then the inverted total NSMS were used to extract the time-decay classification features. Once our inversion and classification algorithms were tested on the calibration data sets then we applied the same procedure to all blind data sets. The combined NSMS and differential evolution algorithm is utilized for determine the NSMS strengths for each cell. The obtained total NSMS time-decay curves were used to extract the discrimination features and perform classification using the training data as reference. In addition, for cross validation, the inverted locations and orientations from NSMS-DE algorithm were compared against the inverted data that obtained via the magnetic field, vector and scalar potentials (HAP) method and the combined dipole and Gauss-Newton approach technique. We examined the entire time decay history of the total NSMS case-by-case for classification purposes. Also, we use different multi-class statistical classification algorithms for separating the dangerous objects from non hazardous items. The inverted targets were ranked by target ID and submitted to SERDP for independent scoring. The independent scoring results are presented.
Land-cover trends in the Mojave basin and range ecoregion
Sleeter, Benjamin M.; Raumann, Christian G.
2006-01-01
The U.S. Geological Survey's Land-Cover Trends Project aims to estimate the rates of contemporary land-cover change within the conterminous United States between 1972 and 2000. A random sampling approach was used to select a representative sample of 10-km by 10-km sample blocks and to estimate change within +/- 1 percent at an 85-percent confidence interval. Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus data were used, and each 60-m pixel was assigned to one of 11 distinct land-cover classes based upon a modified Anderson classification system. Upon completion of land-cover change mapping for five dates, land-cover change statistics were generated and analyzed. This paper presents estimates for the Mojave Basin and Range ecoregion located in the southwestern United States. Our research suggests land-cover change within the Mojave to be relatively rare and highly localized. The primary shift in land cover is unidirectional, with natural desert grass/shrubland being converted to development. We estimate that more than 1,300 km2 have been converted since 1973 and that the conversion is being largely driven by economic and recreational opportunities provided by the Mojave ecoregion. The time interval with the highest rate of change was 1986 to 1992, in which the rate was 0.21 percent (321.9 km2) per year total change.
NASA Technical Reports Server (NTRS)
Tucker, C. J.
1978-01-01
The first four Landsat-D thematic mapper sensors were evaluated and compared to the RBV and MSS sensors from Landsats-1, 2, and 3, Colvocoresses' proposed 'operational Landsat' three band system, and the French SPOT three band system using simulation/integration techniques and in situ collected spectral reflectance data. Sensors were evaluated by their ability to discriminate vegetation biomass, chlorophyll concentration, and leaf water content. The thematic mapper and SPOT bands were superior in a spectral resolution context to the other three sensor systems for vegetational applications. Significant improvements are expected for vegetational analyses from Landsat-D thematic mapper and SPOT imagery over MSS and RBV imagery.
Selection of a seventh spectral band for the LANDSAT-D thematic mapper
NASA Technical Reports Server (NTRS)
Holmes, Q. A. (Principal Investigator); Nuesch, D. R.
1978-01-01
The author has identified the following significant results. Each of the candidate bands were examined in terms of the feasibility of gathering high quality imagery from space while taking into account solar illumination, atmospheric attenuation, and the signal/noise ratio achievable within the TM sensor constraints. For the 2.2 micron region and the thermal IR region, inband signal values were calculated from representative spectral reflectance/emittance curves and a linear discriminant analysis was employed to predict classification accuracies. Based upon the substantial improvement (from 78 t0 92%) in discriminating zones of hydrothermally altered rocks from unaltered zones, over a broad range of observation conditions, a 2.08-2.35 micron spectral band having a ground resolution of 30 meters was recommended.
SkyMapper Southern Survey: First Data Release (DR1)
NASA Astrophysics Data System (ADS)
Wolf, Christian; Onken, Christopher A.; Luvaul, Lance C.; Schmidt, Brian P.; Bessell, Michael S.; Chang, Seo-Won; Da Costa, Gary S.; Mackey, Dougal; Martin-Jones, Tony; Murphy, Simon J.; Preston, Tim; Scalzo, Richard A.; Shao, Li; Smillie, Jon; Tisserand, Patrick; White, Marc C.; Yuan, Fang
2018-02-01
We present the first data release of the SkyMapper Southern Survey, a hemispheric survey carried out with the SkyMapper Telescope at Siding Spring Observatory in Australia. Here, we present the survey strategy, data processing, catalogue construction, and database schema. The first data release dataset includes over 66 000 images from the Shallow Survey component, covering an area of 17 200 deg2 in all six SkyMapper passbands uvgriz, while the full area covered by any passband exceeds 20 000 deg2. The catalogues contain over 285 million unique astrophysical objects, complete to roughly 18 mag in all bands. We compare our griz point-source photometry with Pan-STARRS1 first data release and note an RMS scatter of 2%. The internal reproducibility of SkyMapper photometry is on the order of 1%. Astrometric precision is better than 0.2 arcsec based on comparison with Gaia first data release. We describe the end-user database, through which data are presented to the world community, and provide some illustrative science queries.
Software used with the flux mapper at the solar parabolic dish test site
NASA Technical Reports Server (NTRS)
Miyazono, C.
1984-01-01
Software for data archiving and data display was developed for use on a Digital Equipment Corporation (DEC) PDP-11/34A minicomputer for use with the JPL-designed flux mapper. The flux mapper is a two-dimensional, high radiant energy scanning device designed to measure radiant flux energies expected at the focal point of solar parabolic dish concentrators. Interfacing to the DEC equipment was accomplished by standard RS-232C serial lines. The design of the software was dicated by design constraints of the flux-mapper controller. Early attemps at data acquisition from the flux-mapper controller were not without difficulty. Time and personnel limitations result in an alternative method of data recording at the test site with subsequent analysis accomplished at a data evaluation location at some later time. Software for plotting was also written to better visualize the flux patterns. Recommendations for future alternative development are discussed. A listing of the programs used in the anaysis is included in an appendix.
NASA Technical Reports Server (NTRS)
Valdez, P. F.; Donohoe, G. W.
1997-01-01
Statistical classification of remotely sensed images attempts to discriminate between surface cover types on the basis of the spectral response recorded by a sensor. It is well known that surfaces reflect incident radiation as a function of wavelength producing a spectral signature specific to the material under investigation. Multispectral and hyperspectral sensors sample the spectral response over tens and even hundreds of wavelength bands to capture the variation of spectral response with wavelength. Classification algorithms then exploit these differences in spectral response to distinguish between materials of interest. Sensors of this type, however, collect detailed spectral information from one direction (usually nadir); consequently, do not consider the directional nature of reflectance potentially detectable at different sensor view angles. Improvements in sensor technology have resulted in remote sensing platforms capable of detecting reflected energy across wavelengths (spectral signatures) and from multiple view angles (angular signatures) in the fore and aft directions. Sensors of this type include: the moderate resolution imaging spectroradiometer (MODIS), the multiangle imaging spectroradiometer (MISR), and the airborne solid-state array spectroradiometer (ASAS). A goal of this paper, then, is to explore the utility of Bidirectional Reflectance Distribution Function (BRDF) models in the selection of optimal view angles for the classification of remotely sensed images by employing a strategy of searching for the maximum difference between surface BRDFs. After a brief discussion of directional reflect ante in Section 2, attention is directed to the Beard-Maxwell BRDF model and its use in predicting the bidirectional reflectance of a surface. The selection of optimal viewing angles is addressed in Section 3, followed by conclusions and future work in Section 4.
Improved classification of drainage networks using junction angles and secondary tributary lengths
NASA Astrophysics Data System (ADS)
Jung, Kichul; Marpu, Prashanth R.; Ouarda, Taha B. M. J.
2015-06-01
River networks in different regions have distinct characteristics generated by geological processes. These differences enable classification of drainage networks using several measures with many features of the networks. In this study, we propose a new approach that only uses the junction angles with secondary tributary lengths to directly classify different network types. This methodology is based on observations on 50 predefined channel networks. The cumulative distributions of secondary tributary lengths for different ranges of junction angles are used to obtain the descriptive values that are defined using a power-law representation. The averages of the values for the known networks are used to represent the classes, and any unclassified network can be classified based on the similarity of the representative values to those of the known classes. The methodology is applied to 10 networks in the United Arab Emirates and Oman and five networks in the USA, and the results are validated using the classification obtained with other methods.
HomozygosityMapper2012--bridging the gap between homozygosity mapping and deep sequencing.
Seelow, Dominik; Schuelke, Markus
2012-07-01
Homozygosity mapping is a common method to map recessive traits in consanguineous families. To facilitate these analyses, we have developed HomozygosityMapper, a web-based approach to homozygosity mapping. HomozygosityMapper allows researchers to directly upload the genotype files produced by the major genotyping platforms as well as deep sequencing data. It detects stretches of homozygosity shared by the affected individuals and displays them graphically. Users can interactively inspect the underlying genotypes, manually refine these regions and eventually submit them to our candidate gene search engine GeneDistiller to identify the most promising candidate genes. Here, we present the new version of HomozygosityMapper. The most striking new feature is the support of Next Generation Sequencing *.vcf files as input. Upon users' requests, we have implemented the analysis of common experimental rodents as well as of important farm animals. Furthermore, we have extended the options for single families and loss of heterozygosity studies. Another new feature is the export of *.bed files for targeted enrichment of the potential disease regions for deep sequencing strategies. HomozygosityMapper also generates files for conventional linkage analyses which are already restricted to the possible disease regions, hence superseding CPU-intensive genome-wide analyses. HomozygosityMapper is freely available at http://www.homozygositymapper.org/.
Development and initial validation of the Classification of Early-Onset Scoliosis (C-EOS).
Williams, Brendan A; Matsumoto, Hiroko; McCalla, Daren J; Akbarnia, Behrooz A; Blakemore, Laurel C; Betz, Randal R; Flynn, John M; Johnston, Charles E; McCarthy, Richard E; Roye, David P; Skaggs, David L; Smith, John T; Snyder, Brian D; Sponseller, Paul D; Sturm, Peter F; Thompson, George H; Yazici, Muharrem; Vitale, Michael G
2014-08-20
Early-onset scoliosis is a heterogeneous condition, with highly variable manifestations and natural history. No standardized classification system exists to describe and group patients, to guide optimal care, or to prognosticate outcomes within this population. A classification system for early-onset scoliosis is thus a necessary prerequisite to the timely evolution of care of these patients. Fifteen experienced surgeons participated in a nominal group technique designed to achieve a consensus-based classification system for early-onset scoliosis. A comprehensive list of factors important in managing early-onset scoliosis was generated using a standardized literature review, semi-structured interviews, and open forum discussion. Three group meetings and two rounds of surveying guided the selection of classification components, subgroupings, and cut-points. Initial validation of the system was conducted using an interobserver reliability assessment based on the classification of a series of thirty cases. Nominal group technique was used to identify three core variables (major curve angle, etiology, and kyphosis) with high group content validity scores. Age and curve progression ranked slightly lower. Participants evaluated the cases of thirty patients with early-onset scoliosis for reliability testing. The mean kappa value for etiology (0.64) was substantial, while the mean kappa values for major curve angle (0.95) and kyphosis (0.93) indicated almost perfect agreement. The final classification consisted of a continuous age prefix, etiology (congenital or structural, neuromuscular, syndromic, and idiopathic), major curve angle (1, 2, 3, or 4), and kyphosis (-, N, or +) variables, and an optional progression modifier (P0, P1, or P2). Utilizing formal consensus-building methods in a large group of surgeons experienced in treating early-onset scoliosis, a novel classification system for early-onset scoliosis was developed with all core components demonstrating substantial to excellent interobserver reliability. This classification system will serve as a foundation to guide ongoing research efforts and standardize communication in the clinical setting. Copyright © 2014 by The Journal of Bone and Joint Surgery, Incorporated.
NASA Technical Reports Server (NTRS)
Crist, E. P.; Cicone, R. C.; Metzler, M. D.; Parris, T. M.; Rice, D. P.; Sampson, R. E.
1983-01-01
The TM Tasseled Cap transformation, which provides both a 50% reduction in data volume with little or no loss of important information and spectral features with direct physical association, is presented and discussed. Using both simulated and actual TM data, some important characteristics of vegetation and soils in this feature space are described, as are the effects of solar elevation angle and atmospheric haze. A preliminary spectral haze diagnostic feature, based on only simulated data, is also examined. The characteristics of the TM thermal band are discussed, as is a demonstration of the use of TM data in energy balance studies. Some characteristics of AVHRR data are described, as are the sensitivities to scene content of several LANDSAT-MSS preprocessing techniques.
Mineral Mapping Using AVIRIS Data at Ray Mine, AZ
NASA Technical Reports Server (NTRS)
McCubbin, Ian; Lang, Harold; Green, Robert O.; Roberts, Dar
1998-01-01
Imaging Spectroscopy enables the identification and mapping of surface mineralogy over large areas. This study focused on assessing the utility of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data for environmental impact analysis over the Environmental Protection Agency's (EPA) high priority Superfund site Ray Mine, AZ. Using the Spectral Angle Mapper (SAM) algorithm to analyze AVIRIS data makes it possible to map surface materials that are indicative of acid generating minerals. The improved performance of the AVIRIS sensor since 1996 provides data with sufficient signal to noise ratio to characterize up to 8 image endmembers. Specifically we employed SAM to map minerals associated with mine generated acid waste, namely jarositc, goethite, and hematite, in the presence of a complex mineralogical background.
Response of some Thematic Mapper band ratios to variation in soil water content
NASA Technical Reports Server (NTRS)
Musick, H. Brad; Pelletier, Ramona E.
1986-01-01
Bidirectional reflectance to nadir in the reflective TM bands and the 1.15-1.3-micron band was measured in the laboratory as moisture content was varied in ten soils. Stronger absorption by water in TM5 and TM7 was expected to cause ratios of other bands to TM5 and TM7 to increase with water content, but in most cases these ratios were constant or decreased at low to intermediate water content and increased only at high moisture levels. Because these ratios were found to decrease as illumination elevation angle decreased, it was suggested that increased roughness resulting from the methods of moistening and mixing the soil may have tended to counteract the expected ratio increases.
Su, Yanling; Chen, Wei; Zhang, Tao; Wu, Xingwang; Wu, Zhanpo; Zhang, Yingze
2013-09-24
Controversy exits over the role of Böhler's angle in assessing the injury severity of displaced intra-articular calcaneal fractures and predicting the functional outcome following internal fixation. This study aims to investigate whether a correlation exists between Böhler's angle and the injury severity of displaced calcaneal fractures, and between surgical improvement of Böhler's angle and functional outcome. Patients treated operatively for unilateral closed displaced intra-articular calcaneal fractures from January 1, 2004 to March 31, 2008 were identified. The Böhler's angles of both calcaneus were measured, and the measurement of the uninjured foot was used as its normal control. The difference in the value of Böhler's angle measured preoperatively or postoperatively between the angle of the injured foot and that of the contralateral calcaneus were calculated, respectively. The change in Böhler's angle by ratio was calculated by dividing the difference value of Böhler's angle between bilateral calcaneus by its normal control. The injury severity was assessed according to Sanders classification. The functional outcomes were assessed using American Orthopaedic Foot & Ankle Society hindfoot scores. 274 patients were included into the study with a mean follow-up duration of 71 months. According to Sanders classification, the fracture pattern included 105 type II, 121 type III and 48 type IV fractures. According to American Orthopaedic Foot & Ankle Society hindfoot scoring system, the excellent, good, fair and poor results were achieved in 104, 132, 27, and 11 patients, respectively. The preoperative Böhler's angle, difference value of Böhler's angle between bilateral calcaneus, and change in Böhler's angle by ratio each has a significant correlation with Sanders classification (rs=-0.178, P=0.003; rs=-0.174, P=0.004; rs=-0.172, P=0.005, respectively), however, is not correlated with functional outcome individually. The three postoperative measurements were all found to have a significant correlation with American Orthopaedic Foot & Ankle Society hindfoot scores (rs=0.223, P<0.001; rs=0.224, P<0.001; rs=0.220, P<0.001, respectively). However, these correlations were all weak to low. There was a significant correlation between preoperative Böhler's angle and the injury severity of displaced intra-articular calcaneal fractures, but only postoperative Böhler's angle parameters were found to have a significant correlation with the functional recovery.
NASA Astrophysics Data System (ADS)
Lawrence, R.; Landenburger, L.; Jewett, J.
2007-12-01
Whitebark pine seeds have long been identified as the most significant vegetative food source for grizzly bears in the Greater Yellowstone Ecosystem (GYE) and, hence, a crucial element of suitable grizzly bear habitat. The overall health and status of whitebark pine in the GYE is currently threatened by mountain pine beetle infestations and the spread of whitepine blister rust. Whitebark pine distribution (presence/absence) was mapped for the GYE using Landsat 7 Enhanced Thematic Mapper (ETM+) imagery and topographic data as part of a long-term inter-agency monitoring program. Logistic regression was compared with classification tree analysis (CTA) with and without boosting. Overall comparative classification accuracies for the central portion of the GYE covering three ETM+ images along a single path ranged from 91.6% using logistic regression to 95.8% with See5's CTA algorithm with the maximum 99 boosts. The analysis is being extended to the entire northern Rocky Mountain Ecosystem and extended over decadal time scales. The analysis is being extended to the entire northern Rocky Mountain Ecosystem and extended over decadal time scales.
Object based technique for delineating and mapping 15 tree species using VHR WorldView-2 imagery
NASA Astrophysics Data System (ADS)
Mustafa, Yaseen T.; Habeeb, Hindav N.
2014-10-01
Monitoring and analyzing forests and trees are required task to manage and establish a good plan for the forest sustainability. To achieve such a task, information and data collection of the trees are requested. The fastest way and relatively low cost technique is by using satellite remote sensing. In this study, we proposed an approach to identify and map 15 tree species in the Mangish sub-district, Kurdistan Region-Iraq. Image-objects (IOs) were used as the tree species mapping unit. This is achieved using the shadow index, normalized difference vegetation index and texture measurements. Four classification methods (Maximum Likelihood, Mahalanobis Distance, Neural Network, and Spectral Angel Mapper) were used to classify IOs using selected IO features derived from WorldView-2 imagery. Results showed that overall accuracy was increased 5-8% using the Neural Network method compared with other methods with a Kappa coefficient of 69%. This technique gives reasonable results of various tree species classifications by means of applying the Neural Network method with IOs techniques on WorldView-2 imagery.
NASA Technical Reports Server (NTRS)
Hoffer, R. M. (Principal Investigator)
1981-01-01
Training and test data sets for CAM1S from NS-001 MSS data for two dates (geometrically adjusted to 30 meter resolution) were used to evaluate wavelength band. Two sets of tapes containing digitized HH and HV polarization data were obtained. Because the SAR data on the 9 track tapes contained no meaningful data, the 7 track tapes were copied onto 9 track tapes at LARS. The LARSYS programs were modified and a program was written to reformat the digitized SAR data into a LARSYS format. The radar imagery is being qualitatively interpreted. Results are to be used to identify possible cover types, to produce a classification map to aid in the numerical evaluation classification of radar data, and to develop an interpretation key for radar imagery. The four spatial resolution data sets were analyzed. A program was developed to reduce the spatial distortions resulting from variable viewing distance, and geometrically adjusted data sets were generated. A flowchart of steps taken to geometrically adjust a data set from the NS-001 scanner is presented.
NASA Technical Reports Server (NTRS)
Ackleson, S. G.; Klemas, V.
1985-01-01
LANDSAT Thematic Mapper (TM) and Multispectral Scanner (MSS) imagery generated simultaneously over Guinea Marsh, Virginia, are assessed in the ability to detect submerged aquatic, bottom-adhering plant canopies (SAV). An unsupervised clustering algorithm is applied to both image types and the resulting classifications compared to SAV distributions derived from color aerial photography. Class confidence and accuracy are first computed for all water areas and then only shallow areas where water depth is less than 6 feet. In both the TM and MSS imagery, masking water areas deeper than 6 ft. resulted in greater classification accuracy at confidence levels greater than 50%. Both systems perform poorly in detecting SAV with crown cover densities less than 70%. On the basis of the spectral resolution, radiometric sensitivity, and location of visible bands, TM imagery does not offer a significant advantage over MSS data for detecting SAV in Lower Chesapeake Bay. However, because the TM imagery represents a higher spatial resolution, smaller SAV canopies may be detected than is possible with MSS data.
NASA Astrophysics Data System (ADS)
Ma, Weiwei; Gong, Cailan; Hu, Yong; Li, Long; Meng, Peng
2015-10-01
Remote sensing technology has been broadly recognized for its convenience and efficiency in mapping vegetation, particularly in high-altitude and inaccessible areas where there are lack of in-situ observations. In this study, Landsat Thematic Mapper (TM) images and Chinese environmental mitigation satellite CCD sensor (HJ-1 CCD) images, both of which are at 30m spatial resolution were employed for identifying and monitoring of vegetation types in a area of Western China——Qinghai Lake Watershed(QHLW). A decision classification tree (DCT) algorithm using multi-characteristic including seasonal TM/HJ-1 CCD time series data combined with digital elevation models (DEMs) dataset, and a supervised maximum likelihood classification (MLC) algorithm with single-data TM image were applied vegetation classification. Accuracy of the two algorithms was assessed using field observation data. Based on produced vegetation classification maps, it was found that the DCT using multi-season data and geomorphologic parameters was superior to the MLC algorithm using single-data image, improving the overall accuracy by 11.86% at second class level and significantly reducing the "salt and pepper" noise. The DCT algorithm applied to TM /HJ-1 CCD time series data geomorphologic parameters appeared as a valuable and reliable tool for monitoring vegetation at first class level (5 vegetation classes) and second class level(8 vegetation subclasses). The DCT algorithm using multi-characteristic might provide a theoretical basis and general approach to automatic extraction of vegetation types from remote sensing imagery over plateau areas.
A multitemporal (1979-2009) land-use/land-cover dataset of the binational Santa Cruz Watershed
2011-01-01
Trends derived from multitemporal land-cover data can be used to make informed land management decisions and to help managers model future change scenarios. We developed a multitemporal land-use/land-cover dataset for the binational Santa Cruz watershed of southern Arizona, United States, and northern Sonora, Mexico by creating a series of land-cover maps at decadal intervals (1979, 1989, 1999, and 2009) using Landsat Multispectral Scanner and Thematic Mapper data and a classification and regression tree classifier. The classification model exploited phenological changes of different land-cover spectral signatures through the use of biseasonal imagery collected during the (dry) early summer and (wet) late summer following rains from the North American monsoon. Landsat images were corrected to remove atmospheric influences, and the data were converted from raw digital numbers to surface reflectance values. The 14-class land-cover classification scheme is based on the 2001 National Land Cover Database with a focus on "Developed" land-use classes and riverine "Forest" and "Wetlands" cover classes required for specific watershed models. The classification procedure included the creation of several image-derived and topographic variables, including digital elevation model derivatives, image variance, and multitemporal Kauth-Thomas transformations. The accuracy of the land-cover maps was assessed using a random-stratified sampling design, reference aerial photography, and digital imagery. This showed high accuracy results, with kappa values (the statistical measure of agreement between map and reference data) ranging from 0.80 to 0.85.
Reese, H.M.; Lillesand, T.M.; Nagel, D.E.; Stewart, J.S.; Goldmann, R.A.; Simmons, T.E.; Chipman, J.W.; Tessar, P.A.
2002-01-01
Landsat Thematic Mapper (TM) data were the basis in production of a statewide land cover data set for Wisconsin, undertaken in partnership with U.S. Geological Survey's (USGS) Gap Analysis Program (GAP). The data set contained seven classes comparable to Anderson Level I and 24 classes comparable to Anderson Level II/III. Twelve scenes of dual-date TM data were processed with methods that included principal components analysis, stratification into spectrally consistent units, separate classification of upland, wetland, and urban areas, and a hybrid supervised/unsupervised classification called "guided clustering." The final data had overall accuracies of 94% for Anderson Level I upland classes, 77% for Level II/III upland classes, and 84% for Level II/III wetland classes. Classification accuracies for deciduous and coniferous forest were 95% and 93%, respectively, and forest species' overall accuracies ranged from 70% to 84%. Limited availability of acceptable imagery necessitated use of an early May date in a majority of scene pairs, perhaps contributing to lower accuracy for upland deciduous forest species. The mixed deciduous/coniferous forest class had the lowest accuracy, most likely due to distinctly classifying a purely mixed class. Mixed forest signatures containing oak were often confused with pure oak. Guided clustering was seen as an efficient classification method, especially at the tree species level, although its success relied in part on image dates, accurate ground troth, and some analyst intervention. ?? 2002 Elsevier Science Inc. All rights reserved.
MAPPER: A personal computer map projection tool
NASA Technical Reports Server (NTRS)
Bailey, Steven A.
1993-01-01
MAPPER is a set of software tools designed to let users create and manipulate map projections on a personal computer (PC). The capability exists to generate five popular map projections. These include azimuthal, cylindrical, mercator, lambert, and sinusoidal projections. Data for projections are contained in five coordinate databases at various resolutions. MAPPER is managed by a system of pull-down windows. This interface allows the user to intuitively create, view and export maps to other platforms.
MetalMapper Demonstration at the Former Camp Beale, CA
2012-03-01
2012 2 . REPORT TYPE 3. DATES COVERED 00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE MetalMapper Demonstration at the Former Camp Beale, CA 5a...SUMMARY REPORT MetalMapper Demonstration at the Former Camp Beale, CA March 2012 Herb Nelson Anne Andrews SERDP & ESTCP...advanced electromagnetic sensor was demonstrated at the former Camp Beale, CA in 2011. Camp Beale was also the site of the first demonstrations of
Validation of the Thematic Mapper radiometric and geometric correction algorithms
NASA Technical Reports Server (NTRS)
Fischel, D.
1984-01-01
The radiometric and geometric correction algorithms for Thematic Mapper are critical to subsequent successful information extraction. Earlier Landsat scanners, known as Multispectral Scanners, produce imagery which exhibits striping due to mismatching of detector gains and biases. Thematic Mapper exhibits the same phenomenon at three levels: detector-to-detector, scan-to-scan, and multiscan striping. The cause of these variations has been traced to variations in the dark current of the detectors. An alternative formulation has been tested and shown to be very satisfactory. Unfortunately, the Thematic Mapper detectors exhibit saturation effects suffered while viewing extensive cloud areas, and is not easily correctable. The geometric correction algorithm has been shown to be remarkably reliable. Only minor and modest improvements are indicated and shown to be effective.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sparks, Rachel, E-mail: rachel.sparks@ucl.ac.uk; Barratt, Dean; Nicolas Bloch, B.
2015-03-15
Purpose: Transrectal ultrasound (TRUS)-guided needle biopsy is the current gold standard for prostate cancer diagnosis. However, up to 40% of prostate cancer lesions appears isoechoic on TRUS. Hence, TRUS-guided biopsy has a high false negative rate for prostate cancer diagnosis. Magnetic resonance imaging (MRI) is better able to distinguish prostate cancer from benign tissue. However, MRI-guided biopsy requires special equipment and training and a longer procedure time. MRI-TRUS fusion, where MRI is acquired preoperatively and then aligned to TRUS, allows for advantages of both modalities to be leveraged during biopsy. MRI-TRUS-guided biopsy increases the yield of cancer positive biopsies. Inmore » this work, the authors present multiattribute probabilistic postate elastic registration (MAPPER) to align prostate MRI and TRUS imagery. Methods: MAPPER involves (1) segmenting the prostate on MRI, (2) calculating a multiattribute probabilistic map of prostate location on TRUS, and (3) maximizing overlap between the prostate segmentation on MRI and the multiattribute probabilistic map on TRUS, thereby driving registration of MRI onto TRUS. MAPPER represents a significant advancement over the current state-of-the-art as it requires no user interaction during the biopsy procedure by leveraging texture and spatial information to determine the prostate location on TRUS. Although MAPPER requires manual interaction to segment the prostate on MRI, this step is performed prior to biopsy and will not substantially increase biopsy procedure time. Results: MAPPER was evaluated on 13 patient studies from two independent datasets—Dataset 1 has 6 studies acquired with a side-firing TRUS probe and a 1.5 T pelvic phased-array coil MRI; Dataset 2 has 7 studies acquired with a volumetric end-firing TRUS probe and a 3.0 T endorectal coil MRI. MAPPER has a root-mean-square error (RMSE) for expert selected fiducials of 3.36 ± 1.10 mm for Dataset 1 and 3.14 ± 0.75 mm for Dataset 2. State-of-the-art MRI-TRUS fusion methods report RMSE of 3.06–2.07 mm. Conclusions: MAPPER aligns MRI and TRUS imagery without manual intervention ensuring efficient, reproducible registration. MAPPER has a similar RMSE to state-of-the-art methods that require manual intervention.« less
James W. Hoffman; Lloyd L. Coulter; Philip J Riggan
2005-01-01
The new FireMapper® 2.0 and OilMapper airborne, infrared imaging systems operate in a "snapshot" mode. Both systems feature the real time display of single image frames, in any selected spectral band, on a daylight readable tablet PC. These single frames are displayed to the operator with full temperature calibration in color or grayscale renditions. A rapid...
CosmoQuest MoonMappers: Citizen Lunar Exploration
NASA Astrophysics Data System (ADS)
Gay, P. L.; Antonenko, I.; Robbins, S. J.; Bracey, G.; Lehan, C.; Moore, J.; Huang, D.
2012-09-01
The MoonMappers citizen science project is part of CosmoQuest, a virtual research facility designed for the public. CosmoQuest seeks to take the best aspects of a research center - research, seminars, journal clubs, and community discussions - and provide them to a community of citizen scientists through a virtual facility. MoonMappers was the first citizen science project within CosmoQuest, and is being used to define best practices in getting the public to effectively learn and do science.
NASA Astrophysics Data System (ADS)
Alevizos, Evangelos; Snellen, Mirjam; Simons, Dick; Siemes, Kerstin; Greinert, Jens
2018-06-01
This study applies three classification methods exploiting the angular dependence of acoustic seafloor backscatter along with high resolution sub-bottom profiling for seafloor sediment characterization in the Eckernförde Bay, Baltic Sea Germany. This area is well suited for acoustic backscatter studies due to its shallowness, its smooth bathymetry and the presence of a wide range of sediment types. Backscatter data were acquired using a Seabeam1180 (180 kHz) multibeam echosounder and sub-bottom profiler data were recorded using a SES-2000 parametric sonar transmitting 6 and 12 kHz. The high density of seafloor soundings allowed extracting backscatter layers for five beam angles over a large part of the surveyed area. A Bayesian probability method was employed for sediment classification based on the backscatter variability at a single incidence angle, whereas Maximum Likelihood Classification (MLC) and Principal Components Analysis (PCA) were applied to the multi-angle layers. The Bayesian approach was used for identifying the optimum number of acoustic classes because cluster validation is carried out prior to class assignment and class outputs are ordinal categorical values. The method is based on the principle that backscatter values from a single incidence angle express a normal distribution for a particular sediment type. The resulting Bayesian classes were well correlated to median grain sizes and the percentage of coarse material. The MLC method uses angular response information from five layers of training areas extracted from the Bayesian classification map. The subsequent PCA analysis is based on the transformation of these five layers into two principal components that comprise most of the data variability. These principal components were clustered in five classes after running an external cluster validation test. In general both methods MLC and PCA, separated the various sediment types effectively, showing good agreement (kappa >0.7) with the Bayesian approach which also correlates well with ground truth data (r2 > 0.7). In addition, sub-bottom data were used in conjunction with the Bayesian classification results to characterize acoustic classes with respect to their geological and stratigraphic interpretation. The joined interpretation of seafloor and sub-seafloor data sets proved to be an efficient approach for a better understanding of seafloor backscatter patchiness and to discriminate acoustically similar classes in different geological/bathymetric settings.
2009-08-03
NASA Moon Minerology Mapper, a guest instrument onboard the Indian Space Research Organization Chandrayaan-1 mission to the moon, looks homeward. Australia is visible in the lower center of the image.
NASA Astrophysics Data System (ADS)
Rasel, Sikdar M. M.; Chang, Hsing-Chung; Ralph, Tim; Saintilan, Neil
2015-10-01
Saltmarsh is one of the important communities of wetlands, however, due to a range of pressures, it has been declared as an EEC (Ecological Endangered Community) in Australia. In order to correctly identify different saltmarsh species, development of spectral libraries of saltmarsh species is essential to monitor this EEC. Hyperspectral remote sensing, can explore the area of wetland monitoring and mapping. The benefits of Hyperion data to wetland monitoring have been studied at Hunter Wetland Park, NSW, Australia. After exclusion of bad bands from the original data, an atmospheric correction model was applied to minimize atmospheric effect and to retrieve apparent surface reflectance for different land cover. Large data dimensionality was reduced by Forward Minimum Noise Fraction (MNF) algorithm. It was found that first 32 MNF band contains more than 80% information of the image. Pixel Purity Index (PPI) algorithm worked properly to extract pure pixel for water, builtup area and three vegetation Casuarina sp., Phragmitis sp. and green grass. The result showed it was challenging to extract extreme pure pixel for Sporobolus and Sarcocornia from the data due to coarse resolution (30 m) and small patch size (<3 m) of those vegetation on the ground . Spectral Angle Mapper, classified the image into five classes: Casuarina, Saltmarsh (Phragmitis), Green grass, Water and Builtup area with 43.55 % accuracy. This classification also failed to classify Sporobolus as a distinct group due to the same reason. A high spatial resolution airborne hyperspectral data and a new study site with a bigger patch of Sporobolus and Sarcocornia is proposed to overcome the issue.
Hyperspectral remote sensing of wild oyster reefs
NASA Astrophysics Data System (ADS)
Le Bris, Anthony; Rosa, Philippe; Lerouxel, Astrid; Cognie, Bruno; Gernez, Pierre; Launeau, Patrick; Robin, Marc; Barillé, Laurent
2016-04-01
The invasion of the wild oyster Crassostrea gigas along the western European Atlantic coast has generated changes in the structure and functioning of intertidal ecosystems. Considered as an invasive species and a trophic competitor of the cultivated conspecific oyster, it is now seen as a resource by oyster farmers following recurrent mass summer mortalities of oyster spat since 2008. Spatial distribution maps of wild oyster reefs are required by local authorities to help define management strategies. In this work, visible-near infrared (VNIR) hyperspectral and multispectral remote sensing was investigated to map two contrasted intertidal reef structures: clusters of vertical oysters building three-dimensional dense reefs in muddy areas and oysters growing horizontally creating large flat reefs in rocky areas. A spectral library, collected in situ for various conditions with an ASD spectroradiometer, was used to run Spectral Angle Mapper classifications on airborne data obtained with an HySpex sensor (160 spectral bands) and SPOT satellite HRG multispectral data (3 spectral bands). With HySpex spectral/spatial resolution, horizontal oysters in the rocky area were correctly classified but the detection was less efficient for vertical oysters in muddy areas. Poor results were obtained with the multispectral image and from spatially or spectrally degraded HySpex data, it was clear that the spectral resolution was more important than the spatial resolution. In fact, there was a systematic mud deposition on shells of vertical oyster reefs explaining the misclassification of 30% of pixels recognized as mud or microphytobenthos. Spatial distribution maps of oyster reefs were coupled with in situ biomass measurements to illustrate the interest of a remote sensing product to provide stock estimations of wild oyster reefs to be exploited by oyster producers. This work highlights the interest of developing remote sensing techniques for aquaculture applications in coastal areas.
Estuary Data Mapper is a tool for geospatial data discovery, visualization, and data download for any of the approximately 2,000 estuaries and associated watersheds in along the five US coastal regions
NASA Technical Reports Server (NTRS)
Tucker, C. J.
1978-01-01
The first four LANDSAT-D thematic mapper sensors were evaluated and compared to: the return beam vidicon (RBV) and multispectral scanners (MSS) sensors from LANDSATS 1, 2, and 3; Colvocoresses' proposed 'operational LANDSAT' three band system; and the French SPOT three band system using simulation/intergration techniques and in situ collected spectral reflectance data. Sensors were evaluated by their ability to discriminate vegetation biomass, chlorophyll concentration, and leaf water content. The thematic mapper and SPOT bands were found to be superior in a spectral resolution context to the other three sensor systems for vegetational applications. Significant improvements are expected for most vegetational analyses from LANDSAT-D thematic mapper and SPOT imagery over MSS and RBV imagery.
Analysis of signals under compositional noise with applications to SONAR data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tucker, J. Derek; Wu, Wei; Srivastava, Anuj
2013-07-09
In this paper, we consider the problem of denoising and classification of SONAR signals observed under compositional noise, i.e., they have been warped randomly along the x-axis. The traditional techniques do not account for such noise and, consequently, cannot provide a robust classification of signals. We apply a recent framework that: 1) uses a distance-based objective function for data alignment and noise reduction; and 2) leads to warping-invariant distances between signals for robust clustering and classification. We use this framework to introduce two distances that can be used for signal classification: a) a y-distance, which is the distance between themore » aligned signals; and b) an x-distance that measures the amount of warping needed to align the signals. We focus on the task of clustering and classifying objects, using acoustic spectrum (acoustic color), which is complicated by the uncertainties in aspect angles at data collections. Small changes in the aspect angles corrupt signals in a way that amounts to compositional noise. As a result, we demonstrate the use of the developed metrics in classification of acoustic color data and highlight improvements in signal classification over current methods.« less
[Adolescent scoliosis : From deformity to treatment].
Schulze, A; Schrading, S; Betsch, M; Quack, V; Tingart, M
2015-11-01
Scoliosis affects up to 6 % of the population. The resulting spine deformity, the increasing risk of back pain, cosmetic aspects, pulmonary disorders if the Cobb angle is > 80°, and the progress of the deformity to > 50° after the end of growth indicate non-operative or operative therapy. In daily clinical practice, the classifications of scoliosis allow the therapy to be adapted. Classifications consider deformity, topography of the scoliosis, and the age at diagnosis. This publication gives an overview of the relevant and most common classifications in the treatment of adolescent scoliosis. For evaluation, the deformity measurement on the coronary radiographic projection of the total spine (Cobb angle) is relevant to therapy. The classification of topography, form, and the sagittal profile of the deformity of the spine are useful for preoperative planning of the fusion level. Classifications that take into account the age at the time of the diagnosis of scoliosis differentiate among early onset scoliosis (younger than 10 years of age), adolescent scoliosis (up to the end of growth), and adult scoliosis. Early onset scoliosis is subdivided by age and etiology. Therapy is derived from the classification of clinical and radiological findings. Classifications that take into account clinical and radiological parameters are essential components of modern scoliosis therapy.
About Estuary Data Mapper (EDM)
Estuary Data Mapper is a tool for geospatial data discovery, visualization, and data download for any of the approximately 2,000 estuaries and associated watersheds in along the five US coastal regions.
Geometric error characterization and error budgets. [thematic mapper
NASA Technical Reports Server (NTRS)
Beyer, E.
1982-01-01
Procedures used in characterizing geometric error sources for a spaceborne imaging system are described using the LANDSAT D thematic mapper ground segment processing as the prototype. Software was tested through simulation and is undergoing tests with the operational hardware as part of the prelaunch system evaluation. Geometric accuracy specifications, geometric correction, and control point processing are discussed. Cross track and along track errors are tabulated for the thematic mapper, the spacecraft, and ground processing to show the temporal registration error budget in pixel (42.5 microrad) 90%.
Land cover change of watersheds in Southern Guam from 1973 to 2001.
Wen, Yuming; Khosrowpanah, Shahram; Heitz, Leroy
2011-08-01
Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.
Satellite inventory of Minnesota forest resources
NASA Technical Reports Server (NTRS)
Bauer, Marvin E.; Burk, Thomas E.; Ek, Alan R.; Coppin, Pol R.; Lime, Stephen D.; Walsh, Terese A.; Walters, David K.; Befort, William; Heinzen, David F.
1993-01-01
The methods and results of using Landsat Thematic Mapper (TM) data to classify and estimate the acreage of forest covertypes in northeastern Minnesota are described. Portions of six TM scenes covering five counties with a total area of 14,679 square miles were classified into six forest and five nonforest classes. The approach involved the integration of cluster sampling, image processing, and estimation. Using cluster sampling, 343 plots, each 88 acres in size, were photo interpreted and field mapped as a source of reference data for classifier training and calibration of the TM data classifications. Classification accuracies of up to 75 percent were achieved; most misclassification was between similar or related classes. An inverse method of calibration, based on the error rates obtained from the classifications of the cluster plots, was used to adjust the classification class proportions for classification errors. The resulting area estimates for total forest land in the five-county area were within 3 percent of the estimate made independently by the USDA Forest Service. Area estimates for conifer and hardwood forest types were within 0.8 and 6.0 percent respectively, of the Forest Service estimates. A trial of a second method of estimating the same classes as the Forest Service resulted in standard errors of 0.002 to 0.015. A study of the use of multidate TM data for change detection showed that forest canopy depletion, canopy increment, and no change could be identified with greater than 90 percent accuracy. The project results have been the basis for the Minnesota Department of Natural Resources and the Forest Service to define and begin to implement an annual system of forest inventory which utilizes Landsat TM data to detect changes in forest cover.
Making heads turn: the effect of familiarity and stimulus rotation on a gender-classification task.
Stevenage, Sarah V; Osborne, Cara D
2006-01-01
Recent work has demonstrated that facial familiarity can moderate the influence of inversion when completing a configural processing task. Here, we examine whether familiarity interacts with intermediate angles of orientation in the same way that it interacts with inversion. Participants were asked to make a gender classification to familiar and unfamiliar faces shown at seven angles of orientation. Speed and accuracy of performance were assessed for stimuli presented (i) as whole faces and (ii) as internal features. When presented as whole faces, the task was easy, as revealed by ceiling levels of accuracy and no effect of familiarity or angle of rotation on response times. However, when stimuli were presented as internal features, an influence of facial familiarity was evident. Unfamiliar faces showed no increase in difficulty across angle of rotation, whereas familiar faces showed a marked increase in difficulty across angle, which was explained by significant linear and cubic trends in the data. Results were interpreted in terms of the benefit gained from a mental representation when face processing was impaired by stimulus rotation.
Improving the MODIS Global Snow-Mapping Algorithm
NASA Technical Reports Server (NTRS)
Klein, Andrew G.; Hall, Dorothy K.; Riggs, George A.
1997-01-01
An algorithm (Snowmap) is under development to produce global snow maps at 500 meter resolution on a daily basis using data from the NASA MODIS instrument. MODIS, the Moderate Resolution Imaging Spectroradiometer, will be launched as part of the first Earth Observing System (EOS) platform in 1998. Snowmap is a fully automated, computationally frugal algorithm that will be ready to implement at launch. Forests represent a major limitation to the global mapping of snow cover as a forest canopy both obscures and shadows the snow underneath. Landsat Thematic Mapper (TM) and MODIS Airborne Simulator (MAS) data are used to investigate the changes in reflectance that occur as a forest stand becomes snow covered and to propose changes to the Snowmap algorithm that will improve snow classification accuracy forested areas.
NASA Astrophysics Data System (ADS)
Shupe, Scott Marshall
2000-10-01
Vegetation mapping in and regions facilitates ecological studies, land management, and provides a record to which future land changes can be compared. Accurate and representative mapping of desert vegetation requires a sound field sampling program and a methodology to transform the data collected into a representative classification system. Time and cost constraints require that a remote sensing approach be used if such a classification system is to be applied on a regional scale. However, desert vegetation may be sparse and thus difficult to sense at typical satellite resolutions, especially given the problem of soil reflectance. This study was designed to address these concerns by conducting vegetation mapping research using field and satellite data from the US Army Yuma Proving Ground (USYPG) in Southwest Arizona. Line and belt transect data from the Army's Land Condition Trend Analysis (LCTA) Program were transformed into relative cover and relative density classification schemes using cluster analysis. Ordination analysis of the same data produced two and three-dimensional graphs on which the homogeneity of each vegetation class could be examined. It was found that the use of correspondence analysis (CA), detrended correspondence analysis (DCA), and non-metric multidimensional scaling (NMS) ordination methods was superior to the use of any single ordination method for helping to clarify between-class and within-class relationships in vegetation composition. Analysis of these between-class and within-class relationships were of key importance in examining how well relative cover and relative density schemes characterize the USYPG vegetation. Using these two classification schemes as reference data, maximum likelihood and artificial neural net classifications were then performed on a coregistered dataset consisting of a summer Landsat Thematic Mapper (TM) image, one spring and one summer ERS-1 microwave image, and elevation, slope, and aspect layers. Classifications using a combination of ERS-1 imagery and elevation, slope, and aspect data were superior to classifications carried out using Landsat TM data alone. In all classification iterations it was consistently found that the highest classification accuracy was obtained by using a combination of Landsat TM, ERS-1, and elevation, slope, and aspect data. Maximum likelihood classification accuracy was found to be higher than artificial neural net classification in all cases.
Downloading and Installing Estuary Data Mapper (EDM)
Estuary Data Mapper is a tool for geospatial data discovery, visualization, and data download for any of the approximately 2,000 estuaries and associated watersheds in along the five US coastal regions
Frequent Questions about Estuary Data Mapper (EDM)
Estuary Data Mapper is a tool for geospatial data discovery, visualization, and data download for any of the approximately 2,000 estuaries and associated watersheds in along the five US coastal regions
Land-cover change in the Lower Mississippi Valley, 1973-2000
Karstensen, Krista A.; Sayler, Kristi L.
2009-01-01
The Land Cover Trends is a research project focused on understanding the rates, trends, causes, and consequences of contemporary United States land-use and land-cover change. The project is coordinated by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in conjunction with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA). Using the EPA Level III ecoregions as the geographic framework, scientists process geospatial data collected between 1973 and 2000 were processed to characterize ecosystem responses to land-use changes. The 27-year study period was divided into four temporal periods: 1973 to1980, 1980 to 1986, 1986 to 1992, 1992 to 2000 and overall from 1973 to 2000. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize and evaluate land-cover change using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) for image interpretation.The rates of land-cover change were estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images were used to interpret land-cover change. The sample block data then were incorporated into statistical analyses to generate an overall change matrix for the ecoregion. These change statistics are applicable for different levels of scale, including total change for the individual sample blocks and change estimates for the entire ecoregion.
Analysis of Urban Expansion of the Resort City of Al Ain Using Remote Sensing and GIS
NASA Astrophysics Data System (ADS)
Issa, S.; Al Shuwaihi, A.
2009-12-01
The urban growth of AL Ain city has been investigated using remote sensing data for three different dates, 1972, 1990 and 2000. We used three Landsat images together with socio-economic data in a post-classification analysis to map the spatial dynamics of land use/cover changes and identify the urbanization process in Al Ain resort city, United Arab Emirates. Land use/cover statistics, extracted from Landsat Multi-spectral Scanner (MSS). Thematic Mapper (TM) and Enhanced Thematic Mapper plus (ETM +) images for 1972. 1990 and 2000 respectively, revealed that the built-up area has expanded by about 170.53km2. The city was found to have a tendency for major expansion in four different directions: along the Abu Dhabi highway, along Dubai highway, Myziad direction and Hafeet recreational area. Expansion in any direction was found to be governed by the availability of road network, suitability for construction, utilities, economic activities, geographical constraints, and legal factors (boundary with Sultanate of Oman). The road network in particular has influenced the spatial patterns and structure of urban development, so that the expansion of the built-up areas has assumed an accretive as well as linear growth along the major roads. The research concludes that the development is based on conservation of agricultural areas (oases) and reclamation of the desert for farming and agricultural activities. The integration of remote sensing and GIS was found to be effective in monitoring LULC changes and providing valuable information necessary for planning and research.
Sub-pixel image classification for forest types in East Texas
NASA Astrophysics Data System (ADS)
Westbrook, Joey
Sub-pixel classification is the extraction of information about the proportion of individual materials of interest within a pixel. Landcover classification at the sub-pixel scale provides more discrimination than traditional per-pixel multispectral classifiers for pixels where the material of interest is mixed with other materials. It allows for the un-mixing of pixels to show the proportion of each material of interest. The materials of interest for this study are pine, hardwood, mixed forest and non-forest. The goal of this project was to perform a sub-pixel classification, which allows a pixel to have multiple labels, and compare the result to a traditional supervised classification, which allows a pixel to have only one label. The satellite image used was a Landsat 5 Thematic Mapper (TM) scene of the Stephen F. Austin Experimental Forest in Nacogdoches County, Texas and the four cover type classes are pine, hardwood, mixed forest and non-forest. Once classified, a multi-layer raster datasets was created that comprised four raster layers where each layer showed the percentage of that cover type within the pixel area. Percentage cover type maps were then produced and the accuracy of each was assessed using a fuzzy error matrix for the sub-pixel classifications, and the results were compared to the supervised classification in which a traditional error matrix was used. The overall accuracy of the sub-pixel classification using the aerial photo for both training and reference data had the highest (65% overall) out of the three sub-pixel classifications. This was understandable because the analyst can visually observe the cover types actually on the ground for training data and reference data, whereas using the FIA (Forest Inventory and Analysis) plot data, the analyst must assume that an entire pixel contains the exact percentage of a cover type found in a plot. An increase in accuracy was found after reclassifying each sub-pixel classification from nine classes with 10 percent interval each to five classes with 20 percent interval each. When compared to the supervised classification which has a satisfactory overall accuracy of 90%, none of the sub-pixel classification achieved the same level. However, since traditional per-pixel classifiers assign only one label to pixels throughout the landscape while sub-pixel classifications assign multiple labels to each pixel, the traditional 85% accuracy of acceptance for pixel-based classifications should not apply to sub-pixel classifications. More research is needed in order to define the level of accuracy that is deemed acceptable for sub-pixel classifications.
2008-12-17
Different wavelengths of light provide new information about the Orientale Basin region of the moon in a composite image taken by NASA Moon Mineralogy Mapper, a guest instrument aboard the Indian Space Research Organization Chandrayaan-1 spacecraft.
A new EMI system for detection and classification of challenging targets
NASA Astrophysics Data System (ADS)
Shubitidze, F.; Fernández, J. P.; Barrowes, B. E.; O'Neill, K.
2013-06-01
Advanced electromagnetic induction (EMI) sensors currently feature multi-axis illumination of targets and tri-axial vector sensing (e.g., MetalMapper), or exploit multi-static array data acquisition (e.g., TEMTADS). They produce data of high density, quality, and diversity, and have been combined with advanced EMI models to provide superb classification performance relative to the previous generation of single-axis, monostatic sensors. However, these advances yet have to improve significantly our ability to classify small, deep, and otherwise challenging targets. Particularly, recent live-site discrimination studies at Camp Butner, NC and Camp Beale, CA have revealed that it is more challenging to detect and discriminate small munitions (with calibers ranging from 20 mm to 60 mm) than larger ones. In addition, a live-site test at the Massachusetts Military Reservation, MA highlighted the difficulties for current sensors to classify large, deep, and overlapping targets with high confidence. There are two main approaches to overcome these problems: 1) adapt advanced EMI models to the existing systems and 2) improve the detection limits of current sensors by modifying their hardware. In this paper we demonstrate a combined software/hardware approach that will provide extended detection range and spatial resolution to next-generation EMI systems; we analyze and invert EMI data to extract classification features for small and deep targets; and we propose a new system that features a large transmitter coil.
Advanced defect classification by smart sampling, based on sub-wavelength anisotropic scatterometry
NASA Astrophysics Data System (ADS)
van der Walle, Peter; Kramer, Esther; Ebeling, Rob; Spruit, Helma; Alkemade, Paul; Pereira, Silvania; van der Donck, Jacques; Maas, Diederik
2018-03-01
We report on advanced defect classification using TNO's RapidNano particle scanner. RapidNano was originally designed for defect detection on blank substrates. In detection-mode, the RapidNano signal from nine azimuth angles is added for sensitivity. In review-mode signals from individual angles are analyzed to derive additional defect properties. We define the Fourier coefficient parameter space that is useful to study the statistical variation in defect types on a sample. By selecting defects from each defect type for further review by SEM, information on all defects can be obtained efficiently.
NASA Astrophysics Data System (ADS)
Kirst, Stefan; Vielhauer, Claus
2015-03-01
In digitized forensics the support of investigators in any manner is one of the main goals. Using conservative lifting methods, the detection of traces is done manually. For non-destructive contactless methods, the necessity for detecting traces is obvious for further biometric analysis. High resolutional 3D confocal laser scanning microscopy (CLSM) grants the possibility for a detection by segmentation approach with improved detection results. Optimal scan results with CLSM are achieved on surfaces orthogonal to the sensor, which is not always possible due to environmental circumstances or the surface's shape. This introduces additional noise, outliers and a lack of contrast, making a detection of traces even harder. Prior work showed the possibility of determining angle-independent classification models for the detection of latent fingerprints (LFP). Enhancing this approach, we introduce a larger feature space containing a variety of statistical-, roughness-, color-, edge-directivity-, histogram-, Gabor-, gradient- and Tamura features based on raw data and gray-level co-occurrence matrices (GLCM) using high resolutional data. Our test set consists of eight different surfaces for the detection of LFP in four different acquisition angles with a total of 1920 single scans. For each surface and angles in steps of 10, we capture samples from five donors to introduce variance by a variety of sweat compositions and application influences such as pressure or differences in ridge thickness. By analyzing the present test set with our approach, we intend to determine angle- and substrate-dependent classification models to determine optimal surface specific acquisition setups and also classification models for a general detection purpose for both, angles and substrates. The results on overall models with classification rates up to 75.15% (kappa 0.50) already show a positive tendency regarding the usability of the proposed methods for LFP detection on varying surfaces in non-planar scenarios.
NASA Astrophysics Data System (ADS)
Huang, Xin; Chen, Huijun; Gong, Jianya
2018-01-01
Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed ADF features can effectively improve the accuracy of urban scene classification, with a significant increase in overall accuracy (3.8-11.7%) compared to using the spectral bands alone. Furthermore, the results indicated the superiority of the proposed ADFs in distinguishing between the spectrally similar and complex man-made classes, including roads and various types of buildings (e.g., high buildings, urban villages, and residential apartments).
NASA Technical Reports Server (NTRS)
1974-01-01
The optimization of a thematic mapper for earth resources application is discussed in terms of cost versus performance. Performance tradeoffs and the cost impact are analyzed. The instrument design and radiometric performance are also described. The feasibility of a radiative cooler design for a scanning spectral radiometer is evaluated along with the charge coupled multiplex operation. Criteria for balancing the cost and complexity of data acquisition instruments against the requirements of the user, and a pushbroom scanner version of the thematic mapper are presented.
NASA Astrophysics Data System (ADS)
Shumack, Samuel; Hesse, Paul; Turner, Liam
2017-12-01
This study aims to determine the common response of coastal sand dunes in Western Australia (WA) to fire on decadal time-scales, in terms of ecological-geomorphic-climatic interactions to test the hypothesis that fire plays a role in coastal dune destabilisation. Fires are commonly suggested to have contributed to widespread dune reactivation in Australia and globally, a hypothesis that is relatively untested. We used data from the Landsat Thematic Mapper, Enhanced Thematic Mapper Plus, and Operational Land Imager missions to monitor changes in surface coverage on coastal sand dunes in south-west WA after fires. We analysed 31 fire scars from 1988 to 2016 in two Landsat scenes on the west and south coast of WA. Recovery ratios derived from the Normalised Difference Vegetation Index (NDVI) were used to monitor patterns in post-fire biomass and surface cover. Recovery ratios are correlated with indices of burn severity, and meteorological data to investigate relationships. We also used Maximum Likelihood Classification to monitor changes in bare sand area. Results suggest that recovery followed a strongly consistent pattern, and is characterised by rapid vegetation cover re-establishment within six to twelve months. Prior to this, some aeolian activity may have occurred but without substantial surface changes. Initial germination and/or resprouting were followed by steady growth up to seven years, where NDVI typically neared pre-fire values. Some variation in early recovery occurred between the west and south coast, possibly owing to relative proportions of reseeding and resprouting plants. A log regression explained 75% of the recovery pattern (79% on the south coast). Precipitation had some ability to explain recovery up to nine months post-fire (r2 = 0.29 to 0.54). No relationships were observed between estimates of burn severity and recovery. After nine months, the biggest cause of spatial variation in recovery was the pre-fire community composition and related seedbank or resprouting density. Image classification did not identify any new blowout features except where fires were not the primary cause. Results suggest that fires are not presently contributing to the destabilisation of coastal dunes in south-west WA.
NASA Technical Reports Server (NTRS)
1982-01-01
Functional and design data from various thematic mapper subsystems are presented. Coarse focus, modulation transfer function, and shim requirements are addressed along with spectral matching and spatial coverage tests.
INPE LANDSAT-D thematic mapper computer compatible tape format specification
NASA Technical Reports Server (NTRS)
Parada, N. D. J. (Principal Investigator); Desouza, R. C. M.
1982-01-01
The format of the computer compatible tapes (CCT) which contain Thematic Mapper (TM) imagery data acquired from the LANDSAT D and D Prime satellites by the INSTITUTO DE PERSQUISAS ESPACIALS (CNPq-INPE/BRAZIL) is defined.
EnviroMapper for Envirofacts is a single point of access to select U.S. EPA environmental data. This Web site provides access to several EPA databases to provide you with information about environmental activities that may affect air, water, and l
Hawi, Nael; Magosch, Petra; Tauber, Mark; Lichtenberg, Sven; Martetschläger, Frank; Habermeyer, Peter
2017-02-01
A variety of measurements can be used to assess radiographic osteoarthritic changes of the shoulder. This study aimed to analyze the correlation between the radiographic humeral-sided Samilson and Prieto classification system and 3 different radiographic classifications describing the changes of the glenoid in the coronal plane. The study material included standardized radiographs of 50 patients with idiopathic osteoarthritis before anatomic shoulder replacement. On the basis of radiographic measurements, the cases were evaluated using the Samilson and Prieto grading system, angle β, inclination type, and critical shoulder angle by 2 independent observers. Classification measurements showed an excellent agreement between observers. Our results showed that the humeral-sided Samilson and Prieto grading system had a statistically significant good correlation with angle β (observer 1, r = 0.74; observer 2, r = 0.77; P < .05) and a statistically significant excellent correlation with the inclination type of the glenoid (observer 1, r = 0.86; observer 2, r = 0.8; P < .05). A poor correlation to the critical shoulder angle was observed (r = -0.14, r = 0.03; P > .05). The grade of humeral-sided osteoarthritis according to Samilson and Prieto correlates with the glenoid-sided osteoarthritic changes of the glenoid in the coronal plane described by the angle β and by the inclination type of the glenoid. Higher glenoid-sided inclination is associated with higher grade of osteoarthritis in primary shoulder osteoarthritis. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.
Liu, S; Oh, H; Chambers, D W; Baumrind, S; Xu, T
2017-08-01
To assess the validity of the American Board of Orthodontics Discrepancy Index (ABO-DI) and Peer Assessment Rating (PAR) Index in evaluating malocclusion severity in Chinese orthodontic patients. A stratified random sample of 120 orthodontic patients based on Angle classification was collected from six university orthodontic centres. Sixty-nine orthodontists rated malocclusion severity on a five-point scale by assessing a full set of pre-treatment records for each case and listed reasons for their decision. Their judgement was then compared with ABO-DI and PAR scores determined by three calibrated examiners. Excellent interexaminer reliability of clinician judgement, ABO-DI and PAR index was demonstrated by the Intraclass Correlation Coefficient (rho= 0.995, 0.990 and 0.964, respectively). Both the ABO-DI and US-PAR index showed good correlation with clinician judgement (r=.700 and r=.707, respectively). There was variability among the different Angle classifications: the ABO-DI showed the highest correlation with clinician judgement in Class II patients (r=.780), whereas the US-PAR index showed the highest correlation with clinician judgement in Class III patients (r=.710). Both indices demonstrated the lowest correlations with clinician judgement in Class I patients. With strong interexaminer agreement, the panel consensus was used for validating the ABO-DI and US-PAR index for malocclusion severity. Overall, the ABO-DI and US-PAR index were reliable for measuring malocclusion severity with significantly variable weightings for different Angle classifications. Further modification of the indices for different Angle classification may be indicated. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data
NASA Astrophysics Data System (ADS)
Churches, Christopher E.; Wampler, Peter J.; Sun, Wanxiao; Smith, Andrew J.
2014-08-01
This study uses 2010-2011 Landsat Thematic Mapper (TM) imagery to estimate total forested area in Haiti. The thematic map was generated using radiometric normalization of digital numbers by a modified normalization method utilizing pseudo-invariant polygons (PIPs), followed by supervised classification of the mosaicked image using the Food and Agriculture Organization (FAO) of the United Nations Land Cover Classification System. Classification results were compared to other sources of land-cover data produced for similar years, with an emphasis on the statistics presented by the FAO. Three global land cover datasets (GLC2000, Globcover, 2009, and MODIS MCD12Q1), and a national-scale dataset (a land cover analysis by Haitian National Centre for Geospatial Information (CNIGS)) were reclassified and compared. According to our classification, approximately 32.3% of Haiti's total land area was tree covered in 2010-2011. This result was confirmed using an error-adjusted area estimator, which predicted a tree covered area of 32.4%. Standardization to the FAO's forest cover class definition reduces the amount of tree cover of our supervised classification to 29.4%. This result was greater than the reported FAO value of 4% and the value for the recoded GLC2000 dataset of 7.0%, but is comparable to values for three other recoded datasets: MCD12Q1 (21.1%), Globcover (2009) (26.9%), and CNIGS (19.5%). We propose that at coarse resolutions, the segmented and patchy nature of Haiti's forests resulted in a systematic underestimation of the extent of forest cover. It appears the best explanation for the significant difference between our results, FAO statistics, and compared datasets is the accuracy of the data sources and the resolution of the imagery used for land cover analyses. Analysis of recoded global datasets and results from this study suggest a strong linear relationship (R2 = 0.996 for tree cover) between spatial resolution and land cover estimates.
Thematic Mapper. Volume 1: Calibration report flight model, LANDSAT 5
NASA Technical Reports Server (NTRS)
Cooley, R. C.; Lansing, J. C.
1984-01-01
The calibration of the Flight 1 Model Thematic Mapper is discussed. Spectral response, scan profile, coherent noise, line spread profiles and white light leaks, square wave response, radiometric calibration, and commands and telemetry are specifically addressed.
Thematic mapper flight model preshipment review data package. Volume 2, part C: Subsystem data
NASA Technical Reports Server (NTRS)
1982-01-01
Reference lists are provided to acceptance data for each of the major subsystems of the thematic mapper. Configuration reports, lists and copies of all failure reports, and requests for deviation/waiver are included.
Identification of invasive and expansive plant species based on airborne hyperspectral and ALS data
NASA Astrophysics Data System (ADS)
Szporak-Wasilewska, Sylwia; Kuc, Gabriela; Jóźwiak, Jacek; Demarchi, Luca; Chormański, Jarosław; Marcinkowska-Ochtyra, Adriana; Ochtyra, Adrian; Jarocińska, Anna; Sabat, Anita; Zagajewski, Bogdan; Tokarska-Guzik, Barbara; Bzdęga, Katarzyna; Pasierbiński, Andrzej; Fojcik, Barbara; Jędrzejczyk-Korycińska, Monika; Kopeć, Dominik; Wylazłowska, Justyna; Woziwoda, Beata; Michalska-Hejduk, Dorota; Halladin-Dąbrowska, Anna
2017-04-01
The aim of Natura 2000 network is to ensure the long term survival of most valuable and threatened species and habitats in Europe. The encroachment of invasive alien and expansive native plant species is among the most essential threat that can cause significant damage to protected habitats and their biodiversity. The phenomenon requires comprehensive and efficient repeatable solutions that can be applied to various areas in order to assess the impact on habitats. The aim of this study is to investigate of the issue of invasive and expansive plant species as they affect protected areas at a larger scale of Natura 2000 network in Poland. In order to determine the scale of the problem we have been developing methods of identification of invasive and expansive species and then detecting their occurrence and mapping their distribution in selected protected areas within Natura 2000 network using airborne hyperspectral and airborne laser scanning data. The aerial platform used consists of hyperspectral HySpex scanner (451 bands in VNIR and SWIR), Airborne Laser Scanner (FWF) Riegl Lite Mapper and RGB camera. It allowed to obtain simultaneous 1 meter resolution hyperspectral image, 0.1 m resolution orthophotomaps and point cloud data acquired with 7 points/m2. Airborne images were acquired three times per year during growing season to account for plant seasonal change (in May/June, July/August and September/October 2016). The hyperspectral images were radiometrically, geometrically and atmospherically corrected. Atmospheric correction was performed and validated using ASD FieldSpec 4 measurements. ALS point cloud data were used to generate several different topographic, vegetation and intensity products with 1 m spatial resolution. Acquired data (both hyperspectral and ALS) were used to test different classification methods including Mixture Tuned Matched Filtering (MTMF), Spectral Angle Mapper (SAM), Random Forest (RF), Support Vector Machines (SVM), among others. Simultaneously to airborne data acquisitions also botanical surveys were performed covering in total 5680 reference plots for 18 alien invasive and native expansive plant species (1886 in first flight campaign, 1907 in second and 1887 in third). The collected data were used to identify species characteristics such as spectral properties among others (percentage cover, growth stage, discoloration, coexisting species, land use, plant litter). The research includes 10 invasive alien species and 8 native expansive plant species. Amongst plant species selected for the purposes of this study were: Robinia pseudoacacia, Padus serotina, Rumex confertus, Erigeron annuus, Spiraea tomentosa, Solidago spp., Lupinus polyphyllus, Reynoutria spp., Echinocystis lobata and Heracleum spp. as alien invasive species, and Urtica dioica, Filipendula ulmaria, Phragmites australis, Rubus spp, Calamagrostis epigejos, Cirsium arvense, Molinia caerulea, Deschampsia caespitosa as native expansive species. In this study we present the methodology used for identification of invasive alien and expansive native plant species using hyperspectral and airborne laser data with resulting accuracies using different classification methods and exemplary distribution maps. The research within this study will be continued during growing season of the year 2017. Acknowledgements This research has been carried out under the Biostrateg Programme of the Polish National Centre for Research and Development (NCBiR), project No.: DZP/BIOSTRATEG-II/390/2015: The innovative approach supporting monitoring of non-forest Natura 2000 habitats, using remote sensing methods (HabitARS).
NASA Astrophysics Data System (ADS)
Hishe, Hadgu; Giday, Kidane; Neka, Mulugeta; Soromessa, Teshome; Van Orshoven, Jos; Muys, Bart
2015-01-01
Comprehensive and less costly forest inventory approaches are required to monitor the spatiotemporal dynamics of key species in forest ecosystems. Subpixel analysis using the earth resources data analysis system imagine subpixel classification procedure was tested to extract Olea europaea subsp. cuspidata and Juniperus procera canopies from Landsat 7 enhanced thematic mapper plus imagery. Control points with various canopy area fractions of the target species were collected to develop signatures for each of the species. With these signatures, the imagine subpixel classification procedure was run for each species independently. The subpixel process enabled the detection of O. europaea subsp. cuspidata and J. procera trees in pure and mixed pixels. Total of 100 pixels each were field verified for both species. An overall accuracy of 85% was achieved for O. europaea subsp. cuspidata and 89% for J. procera. A high overall accuracy level of detecting species at a natural forest was achieved, which encourages using the algorithm for future species monitoring activities. We recommend that the algorithm has to be validated in similar environment to enrich the knowledge on its capability to ensure its wider usage.
Mao, Xiaoyan; Fu, Xi; Niu, Feng; Chen, Ying; Jin, Qi; Qiao, Jia; Gui, Lai
2018-05-14
Reduction gonioplasty is very popular in East Asia. However, there has been little quantitative criteria for mandibular angle classification or aesthetics. The aim of this study was to investigate the quantitative differences of mandibular angle types and determine the morphologic features of mandibular angle in attractive women. We created a database of skull computed tomography and standardized frontal and lateral photographs of 96 Chinese female adults. Mandibular angle was classified into 3 groups, namely, extraversion, introversion, and healthy group, based on the position of gonion. We used a 5-point Likert scale to quantify attractiveness based on photographs. Those who scored 4 or higher were defined as attractive women. Three types of computed tomography measurements of the mandible were taken, including 4 distances, 4 angles, and 3 proportions. Discriminant analysis was applied to establish a mathematic model for mandibular angle aesthetics evaluation. Significant differences were observed between the different types of mandibular angle in lower facial width (Gol-Gor), mandibular angle (Co-Go-Me), and gonion divergence angle (Gol-Me-Gor) (P < 0.01). Chinese attractive women had a mandibular angle of 123.913 ± 2.989 degrees, a FH-MP of 27.033 ± 2.695 degrees, and a Go-Me/Co-Go index of 2.0. The "healthy" women had a mandibular angle of 116.402 ± 5.373 degrees, a FH-MP of 19.556 ± 5.999 degrees, and a Go-Me/Co-Go index of 1.6. The estimated Fisher linear discriminant function for the identification of attractive women was as follows: Y = -0.1516X1(Co-Go) + 0.128X2(Go-Me) + 0.04936X3(Co-Go-Me) +0.0218X4(FH-MP). Our study quantified the differences of mandibular angle types and identified the morphological features of mandibular angle in attractive Chinese female adults. Our results could assist plastic surgeons in presurgical designing of new aesthetic gonion and help to evaluate lower face aesthetics.
An overview of the thematic mapper geometric correction system
NASA Technical Reports Server (NTRS)
Beyer, E. P.
1983-01-01
Geometric accuracy specifications for LANDSAT 4 are reviewed and the processing concepts which form the basis of NASA's thematic mapper geometric correction system are summarized for both the flight and ground segments. The flight segment includes the thematic mapper instrument, attitude measurement devices, attitude control, and ephemeris processing. For geometric correction the ground segment uses mirror scan correction data, payload correction data, and control point information to determine where TM detector samples fall on output map projection systems. Then the raw imagery is reformatted and resampled to produce image samples on a selected output projection grid system.
Evaluation of spatial, radiometric and spectral Thematic Mapper performance for coastal studies
NASA Technical Reports Server (NTRS)
Klemas, V.; Ackleson, S. G.; Hardisky, M. A.
1985-01-01
On 31 March 1983, the University of Delaware's Center for Remote Sensing initiated a study to evaluate the spatial, radiometric and spectral performance of the LANDSAT Thematic Mapper for coastal and estuarine studies. The investigation was supported by Contract NAS5-27580 from the NASA Goddard Space Flight Center. The research was divided into three major subprojects: (1) a comparison of LANDSAT TM to MSS imagery for detecting submerged aquatic vegetation in Chesapeake Bay; (2) remote sensing of submerged aquatic vegetation - a radiative transfer approach; and (3) remote sensing of coastal wetland biomass using Thematic Mapper wavebands.
Giese, Sven H; Zickmann, Franziska; Renard, Bernhard Y
2014-01-01
Accurate estimation, comparison and evaluation of read mapping error rates is a crucial step in the processing of next-generation sequencing data, as further analysis steps and interpretation assume the correctness of the mapping results. Current approaches are either focused on sensitivity estimation and thereby disregard specificity or are based on read simulations. Although continuously improving, read simulations are still prone to introduce a bias into the mapping error quantitation and cannot capture all characteristics of an individual dataset. We introduce ARDEN (artificial reference driven estimation of false positives in next-generation sequencing data), a novel benchmark method that estimates error rates of read mappers based on real experimental reads, using an additionally generated artificial reference genome. It allows a dataset-specific computation of error rates and the construction of a receiver operating characteristic curve. Thereby, it can be used for optimization of parameters for read mappers, selection of read mappers for a specific problem or for filtering alignments based on quality estimation. The use of ARDEN is demonstrated in a general read mapper comparison, a parameter optimization for one read mapper and an application example in single-nucleotide polymorphism discovery with a significant reduction in the number of false positive identifications. The ARDEN source code is freely available at http://sourceforge.net/projects/arden/.
CisMapper: predicting regulatory interactions from transcription factor ChIP-seq data
O'Connor, Timothy; Bodén, Mikael
2017-01-01
Abstract Identifying the genomic regions and regulatory factors that control the transcription of genes is an important, unsolved problem. The current method of choice predicts transcription factor (TF) binding sites using chromatin immunoprecipitation followed by sequencing (ChIP-seq), and then links the binding sites to putative target genes solely on the basis of the genomic distance between them. Evidence from chromatin conformation capture experiments shows that this approach is inadequate due to long-distance regulation via chromatin looping. We present CisMapper, which predicts the regulatory targets of a TF using the correlation between a histone mark at the TF's bound sites and the expression of each gene across a panel of tissues. Using both chromatin conformation capture and differential expression data, we show that CisMapper is more accurate at predicting the target genes of a TF than the distance-based approaches currently used, and is particularly advantageous for predicting the long-range regulatory interactions typical of tissue-specific gene expression. CisMapper also predicts which TF binding sites regulate a given gene more accurately than using genomic distance. Unlike distance-based methods, CisMapper can predict which transcription start site of a gene is regulated by a particular binding site of the TF. PMID:28204599
PrimerMapper: high throughput primer design and graphical assembly for PCR and SNP detection
O’Halloran, Damien M.
2016-01-01
Primer design represents a widely employed gambit in diverse molecular applications including PCR, sequencing, and probe hybridization. Variations of PCR, including primer walking, allele-specific PCR, and nested PCR provide specialized validation and detection protocols for molecular analyses that often require screening large numbers of DNA fragments. In these cases, automated sequence retrieval and processing become important features, and furthermore, a graphic that provides the user with a visual guide to the distribution of designed primers across targets is most helpful in quickly ascertaining primer coverage. To this end, I describe here, PrimerMapper, which provides a comprehensive graphical user interface that designs robust primers from any number of inputted sequences while providing the user with both, graphical maps of primer distribution for each inputted sequence, and also a global assembled map of all inputted sequences with designed primers. PrimerMapper also enables the visualization of graphical maps within a browser and allows the user to draw new primers directly onto the webpage. Other features of PrimerMapper include allele-specific design features for SNP genotyping, a remote BLAST window to NCBI databases, and remote sequence retrieval from GenBank and dbSNP. PrimerMapper is hosted at GitHub and freely available without restriction. PMID:26853558
A review of future remote sensing satellite capabilities
NASA Technical Reports Server (NTRS)
Calabrese, M. A.
1980-01-01
Existing, planned and future NASA capabilities in the field of remote sensing satellites are reviewed in relation to the use of remote sensing techniques for the identification of irrigated lands. The status of the currently operational Landsat 2 and 3 satellites is indicated, and it is noted that Landsat D is scheduled to be in operation in two years. The orbital configuration and instrumentation of Landsat D are discussed, with particular attention given to the thematic mapper, which is expected to improve capabilities for small field identification and crop discrimination and classification. Future possibilities are then considered, including a multi-spectral resource sampler supplying high spatial and temporal resolution data possibly based on push-broom scanning, Shuttle-maintained Landsat follow-on missions, a satellite to obtain high-resolution stereoscopic data, further satellites providing all-weather radar capability and the Large Format Camera.
Analysis of forest disturbance using TM and AVHRR data
NASA Technical Reports Server (NTRS)
Spanner, Michael A.; Hlavka, Christine A.; Pierce, Lars L.
1989-01-01
A methodology that will be used to determine the proportions of undisturbed, successional vegetation and recently disturbed land cover within coniferous forests using remotely sensed data from the advanced very high resolution radiometer (AVHRR) is presented. The method uses thematic mapper (TM) data to determine the proportions of the three stages of forest disturbance and regrowth for each AVHRR pixel in the sample areas, and is then applied to interpret all AVHRR imagery. Preliminary results indicate that there are predictable relationships between TM spectral response and the disturbance classes. Analysis of ellipse plots from a TM classification of the disturbed forested landscape indicates that the forest classes are separable in the red (0.63-0.69 micron) and near-infrared (0.76-0.90 micron) bands, providing evidence that the proportion of disturbance classes may be determined from AVHRR data.
Sanz-Mengibar, Jose Manuel; Altschuck, Natalie; Sanchez-de-Muniain, Paloma; Bauer, Christian; Santonja-Medina, Fernando
2017-04-01
To understand whether there is a trunk postural control threshold in the sagittal plane for the transition between the Gross Motor Function Classification System (GMFCS) levels measured with 3-dimensional gait analysis. Kinematics from 97 children with spastic bilateral cerebral palsy from spine angles according to Plug-In Gait model (Vicon) were plotted relative to their GMFCS level. Only average and minimum values of the lumbar spine segment correlated with GMFCS levels. Maximal values at loading response correlated independently with age at all functional levels. Average and minimum values were significant when analyzing age in combination with GMFCS level. There are specific postural control patterns in the average and minimum values for the position between trunk and pelvis in the sagittal plane during gait, for the transition among GMFCS I-III levels. Higher classifications of gross motor skills correlate with more extended spine angles.
Cloud cover determination in polar regions from satellite imagery
NASA Technical Reports Server (NTRS)
Barry, R. G.; Maslanik, J. A.; Key, J. R.
1987-01-01
A definition is undertaken of the spectral and spatial characteristics of clouds and surface conditions in the polar regions, and to the creation of calibrated, geometrically correct data sets suitable for quantitative analysis. Ways are explored in which this information can be applied to cloud classifications as new methods or as extensions to existing classification schemes. A methodology is developed that uses automated techniques to merge Advanced Very High Resolution Radiometer (AVHRR) and Scanning Multichannel Microwave Radiometer (SMMR) data, and to apply first-order calibration and zenith angle corrections to the AVHRR imagery. Cloud cover and surface types are manually interpreted, and manual methods are used to define relatively pure training areas to describe the textural and multispectral characteristics of clouds over several surface conditions. The effects of viewing angle and bidirectional reflectance differences are studied for several classes, and the effectiveness of some key components of existing classification schemes is tested.
NASA Technical Reports Server (NTRS)
1982-01-01
The data obtained for the Band 1 thematic mapper flight full band assembly (P/N 50797) are summarized. The data were collected from half band, post amplifier, and full band acceptance test data records.
Spectroradiometric calibration of the Thematic Mapper and multispectral scanner system
NASA Technical Reports Server (NTRS)
Palmer, J. (Principal Investigator); Slater, P.
1984-01-01
Results of an analysis that relates TM saturation level to ground reflectance, calendar date, latitude, and atmospheric conditions are reported. The determination of the spectral reflectance at the entrance pupil of the LANDSAT 4 pupil of the thematic mapper is described.
LANDSAT-4 Science Characterization Early Results. Volume 3, Part 2: Thematic Mapper (TM)
NASA Technical Reports Server (NTRS)
Barker, J. L. (Editor)
1985-01-01
The calibration of the LANDSAT 4 thematic mapper is discussed as well as the atmospheric, radiometric, and geometric accuracy and correction of data obtained with this sensor. Methods are given for assessing TM band to band registration.
Liu, Xiaofeng; Ouyang, Sisheng; Yu, Biao; Liu, Yabo; Huang, Kai; Gong, Jiayu; Zheng, Siyuan; Li, Zhihua; Li, Honglin; Jiang, Hualiang
2010-01-01
In silico drug target identification, which includes many distinct algorithms for finding disease genes and proteins, is the first step in the drug discovery pipeline. When the 3D structures of the targets are available, the problem of target identification is usually converted to finding the best interaction mode between the potential target candidates and small molecule probes. Pharmacophore, which is the spatial arrangement of features essential for a molecule to interact with a specific target receptor, is an alternative method for achieving this goal apart from molecular docking method. PharmMapper server is a freely accessed web server designed to identify potential target candidates for the given small molecules (drugs, natural products or other newly discovered compounds with unidentified binding targets) using pharmacophore mapping approach. PharmMapper hosts a large, in-house repertoire of pharmacophore database (namely PharmTargetDB) annotated from all the targets information in TargetBank, BindingDB, DrugBank and potential drug target database, including over 7000 receptor-based pharmacophore models (covering over 1500 drug targets information). PharmMapper automatically finds the best mapping poses of the query molecule against all the pharmacophore models in PharmTargetDB and lists the top N best-fitted hits with appropriate target annotations, as well as respective molecule’s aligned poses are presented. Benefited from the highly efficient and robust triangle hashing mapping method, PharmMapper bears high throughput ability and only costs 1 h averagely to screen the whole PharmTargetDB. The protocol was successful in finding the proper targets among the top 300 pharmacophore candidates in the retrospective benchmarking test of tamoxifen. PharmMapper is available at http://59.78.96.61/pharmmapper. PMID:20430828
Near-infrared hyperspectral imaging of atherosclerotic tissue phantom
NASA Astrophysics Data System (ADS)
Ishii, K.; Nagao, R.; Kitayabu, A.; Awazu, K.
2013-06-01
A method to identify vulnerable plaques that are likely to cause acute coronary events has been required. The object of this study is identifying vulnerable plaques by hyperspectral imaging in near-infrared range (NIR-HSI) for an angioscopic application. In this study, NIR-HSI of atherosclerotic tissue phantoms was demonstrated under simulated angioscopic conditions. NIR-HSI system was constructed by a NIR super continuum light and a mercury-cadmium-telluride camera. Spectral absorbance values were obtained in the wavelength range from 1150 to 2400 nm at 10 nm intervals. The hyperspectral images were constructed with spectral angle mapper algorithm. As a result, detections of the lipid area in the atherosclerotic tissue phantom under angioscopic observation conditions were achieved especially in the wavelength around 1200 nm, which corresponds to the second overtone of CH stretching vibration mode.
USDA-ARS?s Scientific Manuscript database
Fisher’s linear discriminant (FLD) models for wheat variety classification were developed and validated. The inputs to the FLD models were the capacitance (C), impedance (Z), and phase angle ('), measured at two frequencies. Classification of wheat varieties was obtained as output of the FLD mod...
NASA Technical Reports Server (NTRS)
Merola, John A.
1989-01-01
The LANDSAT Thematic Mapper (TM) scanner records reflected solar energy from the earth's surface in six wavelength regions, or bands, and one band that records emitted energy in the thermal region, giving a total of seven bands. Useful research was extracted about terrain morphometry from remote sensing measurements and this information is used in an image-based terrain model for selected coastal geomorphic features in the Great Salt Lake Desert (GSLD). Technical developments include the incorporation of Aerial Profiling of Terrain System (APTS) data in satellite image analysis, and the production and use of 3-D surface plots of TM reflectance data. Also included in the technical developments is the analysis of the ground control point spatial distribution and its affects on geometric correction, and the terrain mapping procedure; using satellite data in a way that eliminates the need to degrade the data by resampling. The most common approach for terrain mapping with multispectral scanner data includes the techniques of pattern recognition and image classification, as opposed to direct measurement of radiance for identification of terrain features. The research approach in this investigation was based on an understanding of the characteristics of reflected light resulting from the variations in moisture and geometry related to terrain as described by the physical laws of radiative transfer. The image-based terrain model provides quantitative information about the terrain morphometry based on the physical relationship between TM data, the physical character of the GSLD, and the APTS measurements.
Sparse representation based SAR vehicle recognition along with aspect angle.
Xing, Xiangwei; Ji, Kefeng; Zou, Huanxin; Sun, Jixiang
2014-01-01
As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC) has attracted much attention in synthetic aperture radar (SAR) automatic target recognition (ATR) recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA), in which the correlation between the vehicle's aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA) feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle's aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.
Nitrogen Source and Loading Data for EPA Estuary Data Mapper
Nitrogen source and loading data have been compiled and aggregated at the scale of estuaries and associated watersheds of the conterminous United States, using the spatial framework in EPA's Estuary Data Mapper (EDM) to provide system boundaries. Original sources of data include...
Development of the Lunar Polar Hydrogen Mapper Mission
NASA Astrophysics Data System (ADS)
Hardgrove, C.; Bell, J. F.; Starr, R.; Colaprete, A.; Drake, D.; Lazbin, I.; West, S.; Johnson, E. B.; Christian, J.; Heffern, L.; Genova, A.; Dunham, D.; Williams, B.; Nelson, D.; Puckett, S.; Babuscia, A.; Scowen, P.; Kerner, H.; Amzler, R. J.
2018-04-01
The Lunar Polar Hydrogen Mapper is a 6U CubeSat mission launching on SLS EM-1. The spacecraft will orbit at a low altitude perlune over the lunar south pole and carries a miniature neutron spectrometer to map small scale hydrogen enrichments in PSRs.
NASA Technical Reports Server (NTRS)
1982-01-01
Data from the final performance tests of the thematic mapper flight model multiplexer at ambient temperature are presented. Results cover the power supply, the input buffer, and the A/D threshold for bands 1 through 4.
Star sensor/mapper with a self deployable, high-attenuation light shade for SAS-B
NASA Technical Reports Server (NTRS)
Schenkel, F. W.; Finkel, A.
1972-01-01
A star sensor/mapper to determine positional data for the small astronomy satellites was tested to detect stars of plus 4 visual magnitude. It utilizes two information channels with memory so that it can be used with a low-data-rate telemetry system. One channel yields star amplitude information; the other yields the time of star occurrence as the star passes across an N-slit reticle/photomultiplier detector system. Some of the features of the star sensor/mapper are its low weight of 6.5 pounds, low power consumption of 0.4 watt, bandwidth switching to match the satellite spin rate, optical equalization of sensitivity over the 5-by-10 deg field of view, and self-deployable sunshade. The attitude determination accuracy is 3 arc minutes. This is determined by such parameters as the reticle configuration, optical train, and telemetry readout. The optical and electronic design of the star sensor/mapper, its expansion capabilities, and its features are discussed.
Observer variation in the assessment of root canal curvature.
Faraj, S; Boutsioukis, C
2017-02-01
To evaluate the inter- and intra-observer agreement between training/trained endodontists regarding the ex vivo classification of root canal curvature into three categories and its measurement using three quantitative methods. Periapical radiographs of seven extracted human posterior teeth with varying degrees of curvature were exposed ex vivo. Twenty training/trained endodontists were asked to classify the root canal curvature into three categories (<10°, 10-30°, >30°), to measure the curvature using three quantitative methods (Schneider, Weine, Pruett) and to draw angles of 10° or 30°, as a control experiment. The procedure was repeated after six weeks. Inter- and intra-observer agreement was evaluated by the intraclass correlation coefficient and weighted kappa. The inter-observer agreement on the visual classification of root canal curvature was substantial (ICC = 0.65, P < 0.018), but a trend towards underestimation of the angle was evident. Participants modified their classifications both within and between the two sessions. Median angles drawn as a control experiment were not significantly different from the target values (P > 0.10), but the results of individual participants varied. When quantitative methods were used, the inter- and intra-observer agreement on the angle measurements was considerably better (ICC = 0.76-0.82, P < 0.001) than on the radius measurements (ICC = 0.16-0.19, P > 0.895). Visual estimation of root canal curvature was not reliable. The use of computer-based quantitative methods is recommended. The measurement of radius of curvature was more subjective than angle measurement. Endodontic Associations need to provide specific guidelines on how to estimate root canal curvature in case difficulty assessment forms. © 2015 International Endodontic Journal. Published by John Wiley & Sons Ltd.
Carroll, Kristen L; Murray, Kathleen A; MacLeod, Lynne M; Hennessey, Theresa A; Woiczik, Marcella R; Roach, James W
2011-06-01
Numerous studies underscore the poor intraobserver and interobserver reliability of both the center edge angle (CEA) and the Severin classification using plain film measurements. In this study, experienced observers applied a computer-assisted measurement program to determine the CEA in digital pelvic radiographs of adults who had been previously treated for dysplasia of the hip (DDH). Using a teaching aid/algorithm of the Severin classification, the observers then assigned a Severin rating to these hips. Intraobserver and interobserver errors were then calculated on both the CEA measurements and the Severin classifications. Four pediatric orthopaedic surgeons and 1 pediatric radiologist calculated the CEAs using the OrthoView TM planning system and then determined the Severin classification on 41 blinded digital pelvic radiographs. The radiographs were evaluated by each examiner twice, with evaluations separated by 2 months. All examiners reviewed a Severin classification algorithm before making their Severin assignments. The intraobserver and interobserver reliability for both the CEA and the Severin classification were calculated using the interclass correlation coefficients and Cohen and Fleiss κ scores, respectively. The intraobserver and interobserver reliability for CEA measurement was moderate to almost perfect. When we separated the Severin classification into 3 clinically relevant groups of good (Severin I and II), dysplastic (Severin III), and poor (Severin IV and above), our interobserver reliability neared almost perfect. The Severin classification is an extremely useful and oft-used radiographic measure for the success of DDH treatment. Our research found digital radiography, computer-aided measurement tools, the use of a Severin algorithm, and separating the Severin classification into 3 clinically relevant groups significantly increased the intraobserver and interobserver reliability of both the CEA and Severin classification. This finding will assist future studies using the CEA and Severin classification in the radiographic assessment of DDH treatment outcomes.
Gender classification system in uncontrolled environments
NASA Astrophysics Data System (ADS)
Zeng, Pingping; Zhang, Yu-Jin; Duan, Fei
2011-01-01
Most face analysis systems available today perform mainly on restricted databases of images in terms of size, age, illumination. In addition, it is frequently assumed that all images are frontal and unconcealed. Actually, in a non-guided real-time supervision, the face pictures taken may often be partially covered and with head rotation less or more. In this paper, a special system supposed to be used in real-time surveillance with un-calibrated camera and non-guided photography is described. It mainly consists of five parts: face detection, non-face filtering, best-angle face selection, texture normalization, and gender classification. Emphases are focused on non-face filtering and best-angle face selection parts as well as texture normalization. Best-angle faces are figured out by PCA reconstruction, which equals to an implicit face alignment and results in a huge increase of the accuracy for gender classification. Dynamic skin model and a masked PCA reconstruction algorithm are applied to filter out faces detected in error. In order to fully include facial-texture and shape-outline features, a hybrid feature that is a combination of Gabor wavelet and PHoG (pyramid histogram of gradients) was proposed to equitable inner texture and outer contour. Comparative study on the effects of different non-face filtering and texture masking methods in the context of gender classification by SVM is reported through experiments on a set of UT (a company name) face images, a large number of internet images and CAS (Chinese Academy of Sciences) face database. Some encouraging results are obtained.
Integrating remote sensing and terrain data in forest fire modeling
NASA Astrophysics Data System (ADS)
Medler, Michael Johns
Forest fire policies are changing. Managers now face conflicting imperatives to re-establish pre-suppression fire regimes, while simultaneously preventing resource destruction. They must, therefore, understand the spatial patterns of fires. Geographers can facilitate this understanding by developing new techniques for mapping fire behavior. This dissertation develops such techniques for mapping recent fires and using these maps to calibrate models of potential fire hazards. In so doing, it features techniques that strive to address the inherent complexity of modeling the combinations of variables found in most ecological systems. Image processing techniques were used to stratify the elements of terrain, slope, elevation, and aspect. These stratification images were used to assure sample placement considered the role of terrain in fire behavior. Examination of multiple stratification images indicated samples were placed representatively across a controlled range of scales. The incorporation of terrain data also improved preliminary fire hazard classification accuracy by 40%, compared with remotely sensed data alone. A Kauth-Thomas transformation (KT) of pre-fire and post-fire Thematic Mapper (TM) remotely sensed data produced brightness, greenness, and wetness images. Image subtraction indicated fire induced change in brightness, greenness, and wetness. Field data guided a fuzzy classification of these change images. Because fuzzy classification can characterize a continuum of a phenomena where discrete classification may produce artificial borders, fuzzy classification was found to offer a range of fire severity information unavailable with discrete classification. These mapped fire patterns were used to calibrate a model of fire hazards for the entire mountain range. Pre-fire TM, and a digital elevation model produced a set of co-registered images. Training statistics were developed from 30 polygons associated with the previously mapped fire severity. Fuzzy classifications of potential burn patterns were produced from these images. Observed field data values were displayed over the hazard imagery to indicate the effectiveness of the model. Areas that burned without suppression during maximum fire severity are predicted best. Areas with widely spaced trees and grassy understory appear to be misrepresented, perhaps as a consequence of inaccuracies in the initial fire mapping.
NASA Technical Reports Server (NTRS)
Seeley, M. W.; Ruschy, D. L.; Linden, D. R.
1983-01-01
A cooperative research project was initiated in 1982 to study differences in thematic mapper spectral characteristics caused by variable tillage and crop residue practices. Initial evaluations of radiometric data suggest that spectral separability of variably tilled soils can be confounded by moisture and weathering effects. Separability of bare tilled soils from those with significant amounts of corn residue is enhanced by wet conditions, but still possible under dry conditions when recent tillage operations have occurred. In addition, thematic mapper data may provide an alternative method to study the radiant energy balance at the soil surface in conjunction with variable tillage systems.
Estuary Data Mapper: A virtual portal to coastal data informing environmental management decisions
The Estuary Data Mapper (EDM) is a free, interactive graphical application under development at the US EPA that allows environmental researchers and managers to quickly and easily retrieve, view and save subsets of online US coastal estuary-related data. Accessible data include ...
LAND COVER MAPPING IN AN AGRICULTURAL SETTING USING MULTISEASONAL THEMATIC MAPPER DATA
A multiseasonal Landsat Thematic Mapper (TM) data set consisting of five image dates from a single year was used to characterize agricultural and related land cover in the Willamette River Basin (WRB) of western Oregon. Image registration was accomplished using an automated grou...
NASA Astrophysics Data System (ADS)
Wang, J.; Feng, B.
2016-12-01
Impervious surface area (ISA) has long been studied as an important input into moisture flux models. In general, ISA impedes groundwater recharge, increases stormflow/flood frequency, and alters in-stream and riparian habitats. Urban area is recognized as one of the richest ISA environment. Urban ISA mapping assists flood prevention and urban planning. Hyperspectral imagery (HI), for its ability to detect subtle spectral signature, becomes an ideal candidate in urban ISA mapping. To map ISA from HI involves endmember (EM) selection. The high degree of spatial and spectral heterogeneity of urban environment puts great difficulty in this task: a compromise point is needed between the automatic degree and the good representativeness of the method. The study tested one manual and two semi-automatic EM selection strategies. The manual and the first semi-automatic methods have been widely used in EM selection. The second semi-automatic EM selection method is rather new and has been only proposed for moderate spatial resolution satellite. The manual method visually selected the EM candidates from eight landcover types in the original image. The first semi-automatic method chose the EM candidates using a threshold over the pixel purity index (PPI) map. The second semi-automatic method used the triangle shape of the HI scatter plot in the n-Dimension visualizer to identify the V-I-S (vegetation-impervious surface-soil) EM candidates: the pixels locate at the triangle points. The initial EM candidates from the three methods were further refined by three indexes (EM average RMSE, minimum average spectral angle, and count based EM selection) and generated three spectral libraries, which were used to classify the test image. Spectral angle mapper was applied. The accuracy reports for the classification results were generated. The overall accuracy are 85% for the manual method, 81% for the PPI method, and 87% for the V-I-S method. The V-I-S EM selection method performs best in this study. This fact proves the value of V-I-S EM selection method in not only moderate spatial resolution satellite image but also the more and more accessible high spatial resolution airborne image. This semi-automatic EM selection method can be adopted into a wide range of remote sensing images and provide ISA map for hydrology analysis.
Landsat TM inventory and assessment of waterbird habitat in the southern altiplano of South America
Boyle, T.P.; Caziani, S.M.; Waltermire, R.G.
2004-01-01
The diverse set of wetlands in southern altiplano of South America supports a number of endemic and migratory waterbirds. These species include endangered endemic flamingos and shorebirds that nest in North America and winter in the altiplano. This research developed maps from nine Landsat Thematic Mapper (TM) images (254,300 km2) to provide an inventory of aquatic waterbird habitats. Image processing software was used to produce a map with a classification of wetlands according to the habitat requirements of different types of waterbirds. A hierarchical procedure was used to, first, isolate the bodies of water within the TM image; second, execute an unsupervised classification on the subsetted image to produce 300 signatures of cover types, which were further subdivided as necessary. Third, each of the classifications was examined in the light of field data and personal experience for relevance to the determination of the various habitat types. Finally, the signatures were applied to the entire image and other adjacent images to yield a map depicting the location of the various waterbird habitats in the southern altiplano. The data sets referenced with a global positioning system receiver were used to test the classification system. Multivariate analysis of the bird communities censused at each lake by individual habitats indicated a salinity gradient, and then the depth of the water separated the birds. Multivariate analysis of the chemical and physical data from the lakes showed that the variation in lakes were significantly associated with difference in depth, transparency, latitude, elevation, and pH. The presence of gravel bottoms was also one of the qualities distinguishing a group of lakes. This information will be directly useful to the Flamingo Census Project and serve as an element for risk assessment for future development.
Target-classification approach applied to active UXO sites
NASA Astrophysics Data System (ADS)
Shubitidze, F.; Fernández, J. P.; Shamatava, Irma; Barrowes, B. E.; O'Neill, K.
2013-06-01
This study is designed to illustrate the discrimination performance at two UXO active sites (Oklahoma's Fort Sill and the Massachusetts Military Reservation) of a set of advanced electromagnetic induction (EMI) inversion/discrimination models which include the orthonormalized volume magnetic source (ONVMS), joint diagonalization (JD), and differential evolution (DE) approaches and whose power and flexibility greatly exceed those of the simple dipole model. The Fort Sill site is highly contaminated by a mix of the following types of munitions: 37-mm target practice tracers, 60-mm illumination mortars, 75-mm and 4.5'' projectiles, 3.5'', 2.36'', and LAAW rockets, antitank mine fuzes with and without hex nuts, practice MK2 and M67 grenades, 2.5'' ballistic windshields, M2A1-mines with/without bases, M19-14 time fuzes, and 40-mm practice grenades with/without cartridges. The site at the MMR site contains targets of yet different sizes. In this work we apply our models to EMI data collected using the MetalMapper (MM) and 2 × 2 TEMTADS sensors. The data for each anomaly are inverted to extract estimates of the extrinsic and intrinsic parameters associated with each buried target. (The latter include the total volume magnetic source or NVMS, which relates to size, shape, and material properties; the former includes location, depth, and orientation). The estimated intrinsic parameters are then used for classification performed via library matching and the use of statistical classification algorithms; this process yielded prioritized dig-lists that were submitted to the Institute for Defense Analyses (IDA) for independent scoring. The models' classification performance is illustrated and assessed based on these independent evaluations.
Mills, Kathryn; Idris, Aula; Pham, Thu-An; Porte, John; Wiggins, Mark; Kavakli, Manolya
2017-12-18
To determine the validity and reliability of the peak frontal plane knee angle evaluated by a virtual reality (VR) netball game when landing from a drop vertical jump (DVJ). Laboratory Methods: Forty participants performed 3 DVJs evaluated by 3-dimensional (3D) motion analysis and 3 DVJs evaluated by the VR game. Limits of agreement for the peak projected frontal plane knee angle and peak knee abduction were determined. Participants were given a consensus category of "Above threshold" or "Below threshold" based on a pre-specified threshold angle of 9˚ during landing. Classification agreement was determined using kappa coefficient and accuracy was determined using specificity and sensitivity. Ten participants returned 1-week later to determine intra-rater reliability, standard error of the measure and typical error. The mean difference in detected frontal plane knee angle was 3.39˚ (1.03˚, 5.74˚). Limits of agreement were -10.27˚ (-14.36˚, -6.19˚) to 17.05˚ (12.97˚, 21.14˚). Substantial agreement, specificity and sensitivity were observed for the threshold classification (ĸ = 0.66, [0.42, 0.88] specificity= 0.96 [0.78, 1.0], sensitivity= 0.75 [0.43, 0.95]). The game exhibited acceptable reliability over time (ICC (3,1) = 0.844) and error was approximately 2˚. The VR game reliably evaluated a projected frontal plane knee angle. While the knee angle detected by the VR game is strongly related peak knee abduction, the accuracy of detecting the exact angle was limited. A threshold approach may be a more accurate approach for gaming technology to evaluate frontal plane knee angles when landing from a jump.
[The questionnaire survey on glaucoma diagnosis and treatment in China (2016)].
Zhang, Q; Cao, K; Kang, M T; Sun, Y X; Gan, J H; Tian, J X; Ran, A R; Zhang, X; Su, Y D; Li, S N
2017-02-11
Objective: To investigate the present situation of diagnosis and treatment for primary angle-closure glaucoma (PACG) and primary open-angle glaucoma (POAG) and awareness of the relevant progress among Chinese ophthalmologists. Methods: This study was a cross-sectional, non-randomized sampling survey. Participants were ophthalmologists who attended the 11st Chinese Glaucoma Society Congress during November 11 to 12, 2016. They were invited to fill out a questionnaire. The questionnaire included participants' basic information and their knowledge about glaucoma diagnosis and treatment. The data collected through questionnaire were analyzed with SAS9.4. Results: A total of 450 questionnaires were distributed and 372 valid questionnaires were retrieved, with a response rate of 82. 7%(372/450). ISGEO classification system was adopted by 58.9% (219/372) of the participants as the diagnostic criteria for PACG. Of the respondents, 48.1% (179/372) of the participants believed that "anterior chamber angle closure mechanism-based PACG classification system" was more instructive for treatment, the percentage was higher than ISGEO classification system (42.2%, 157/372). Most (72.3%, 269/372) of the participants knew the 3-minute dark room prone test, but only 27.7%(103/372) of them applied it in clinical practice. A total of 83.4%(310/372) of the participants believed that low cerebrospinal fluid pressure is a risk factor for POAG. In all, 71.8% (267/372) of the participants reported that their institutes had applied compound trabeculectomy with adjustable suture, with 76.9%(286/372) of the participants agreeing that the adjustable suture reduced the rate of complications after trabeculectomy. Conclusions: Currently, both ISGEO classification system and anterior chamber angle closure mechanism-based PACG classification system were adopted in the diagnosis and treatment of glaucoma. Low cerebrospinal fluid pressure as new risk factors for POAG has been widely acknowledged and given attentions by Chinese ophthalmologists. The 3-minute darkroom prone test and compound trabeculectomy with adjustable suture still need to be promoted. (Chin J Ophthalmol, 2017, 53: 115-120) .
The EPA Recovery Mapper is an Internet interactive mapping application that allows users to discover information about every American Recovery and Reinvestment Act (ARRA) award that EPA has funded for six programs. By integrating data reported by the recipients of Recovery Act funding and data created by EPA, this application delivers a level of transparency and public accessibility to users interested in EPA's use of Recovery Act monies. The application is relatively easy to use and builds on the same mapping model as Google, Bing, MapQuest and other commonly used mapping interfaces. EPA Recovery Mapper tracks each award made by each program and gives basic Quick Facts information for each award including award name, location, award date, dollar amounts and more. Data Summaries for each EPA program or for each state are provided displaying dollars for Total Awarded, Total Received (Paid), and Total Jobs This Quarter by Recovery for the latest quarter of data released by Recovery.gov. The data are reported to the government and EPA four times a year by the award recipients. The latest quarterly report will always be displayed in the EPA Recovery Mapper. In addition, the application provides many details about each award. Users will learn more about how to access and interpret these data later in this document. Data shown in the EPA Recovery Mapper are derived from information reported back to FederalReporting.gov from the recipients of Recovery Act funding. EPA
Classification of earth terrain using polarimetric synthetic aperture radar images
NASA Technical Reports Server (NTRS)
Lim, H. H.; Swartz, A. A.; Yueh, H. A.; Kong, J. A.; Shin, R. T.; Van Zyl, J. J.
1989-01-01
Supervised and unsupervised classification techniques are developed and used to classify the earth terrain components from SAR polarimetric images of San Francisco Bay and Traverse City, Michigan. The supervised techniques include the Bayes classifiers, normalized polarimetric classification, and simple feature classification using discriminates such as the absolute and normalized magnitude response of individual receiver channel returns and the phase difference between receiver channels. An algorithm is developed as an unsupervised technique which classifies terrain elements based on the relationship between the orientation angle and the handedness of the transmitting and receiving polariation states. It is found that supervised classification produces the best results when accurate classifier training data are used, while unsupervised classification may be applied when training data are not available.
A signature dissimilarity measure for trabecular bone texture in knee radiographs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Woloszynski, T.; Podsiadlo, P.; Stachowiak, G. W.
Purpose: The purpose of this study is to develop a dissimilarity measure for the classification of trabecular bone (TB) texture in knee radiographs. Problems associated with the traditional extraction and selection of texture features and with the invariance to imaging conditions such as image size, anisotropy, noise, blur, exposure, magnification, and projection angle were addressed. Methods: In the method developed, called a signature dissimilarity measure (SDM), a sum of earth mover's distances calculated for roughness and orientation signatures is used to quantify dissimilarities between textures. Scale-space theory was used to ensure scale and rotation invariance. The effects of image size,more » anisotropy, noise, and blur on the SDM developed were studied using computer generated fractal texture images. The invariance of the measure to image exposure, magnification, and projection angle was studied using x-ray images of human tibia head. For the studies, Mann-Whitney tests with significance level of 0.01 were used. A comparison study between the performances of a SDM based classification system and other two systems in the classification of Brodatz textures and the detection of knee osteoarthritis (OA) were conducted. The other systems are based on weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM) and local binary patterns (LBP). Results: Results obtained indicate that the SDM developed is invariant to image exposure (2.5-30 mA s), magnification (x1.00-x1.35), noise associated with film graininess and quantum mottle (<25%), blur generated by a sharp film screen, and image size (>64x64 pixels). However, the measure is sensitive to changes in projection angle (>5 deg.), image anisotropy (>30 deg.), and blur generated by a regular film screen. For the classification of Brodatz textures, the SDM based system produced comparable results to the LBP system. For the detection of knee OA, the SDM based system achieved 78.8% classification accuracy and outperformed the WND-CHARM system (64.2%). Conclusions: The SDM is well suited for the classification of TB texture images in knee OA detection and may be useful for the texture classification of medical images in general.« less
Wisconsin H-Alpha Mapper | UW-Madison Astronomy
Department of Astronomy Wisconsin H-Alpha Mapper Overview Description About WHAM Fabry-Perot Spectroscopy National Science Foundation Astronomy and... 02.20.2012 | Continue Reading » WHAM featured at Natural Astronomy Galactic Structure GALFA GLIMPSE GLIMPSE360 WHAM Extragalactic Astronomy & Cosmology Local
Spectroradiometric calibration of the thematic mapper and multispectral scanner system
NASA Technical Reports Server (NTRS)
Palmer, J. M.; Slater, P. N.
1983-01-01
The results of an analysis that relates thematic mapper (TM) saturation level to ground reflectance, calendar date, latitude, and atmospheric condition is provided. A revised version of the preprint included with the last quarterly report is also provided for publication in the IEEE Transactions on Geoscience and Remote Sensing.
Can Visualizing Document Space Improve Users' Information Foraging?
ERIC Educational Resources Information Center
Song, Min
1998-01-01
This study shows how users access relevant information in a visualized document space and determine whether BiblioMapper, a visualization tool, strengthens an information retrieval (IR) system and makes it more usable. BiblioMapper, developed for a CISI collection, was evaluated by accuracy, time, and user satisfaction. Users' navigation…
Information content of data from the LANDSAT-4 Thematic Mapper (TM) and multispectral scanner (MSS)
NASA Technical Reports Server (NTRS)
Price, J. C.
1983-01-01
The progress of an investigation to quantify the increased information content of thematic mapper (TM) data as compared to that from the LANDSAT 4 multispectral scanner (MSS) is reported. Two night infrared images were examined and compared with Heat Capacity Mapping Mission data.
Linear mixing model applied to coarse resolution satellite data
NASA Technical Reports Server (NTRS)
Holben, Brent N.; Shimabukuro, Yosio E.
1992-01-01
A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.
NASA Technical Reports Server (NTRS)
Wu, S.-T.
1985-01-01
Seasonally compatible data collected by SIR-A and by Landsat 4 TM over the lower coastal plain in Alabama were coregistered, forming a SIR-A/TM multichannel data set with 30 m x 30 m pixel size. Spectral signature plots and histogram analysis of the data were used to observe data characteristics. Radar returns from pine forest classes correlated highly with the tree ages, suggesting the potential utility of microwave remote sensing for forest biomass estimation. As compared with the TM-only data set, the use of SIR-A/TM data set improved classification accuracy of the seven land cover types studied. In addition, the SIR-A/TM classified data support previous finding by Engheta and Elachi (1982) that microwave data appear to be correlated with differing bottomland hardwood forest vegetation as associated with varying water regimens (i.e., wet versus dry).
Multi-Scale Fractal Analysis of Image Texture and Pattern
NASA Technical Reports Server (NTRS)
Emerson, Charles W.; Lam, Nina Siu-Ngan; Quattrochi, Dale A.
1999-01-01
Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images is the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimension-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.
Investigation of LANDSAT follow-on thematic mapper spatial, radiometric and spectral resolution
NASA Technical Reports Server (NTRS)
Nalepka, R. F. (Principal Investigator); Morgenstern, J. P.; Kent, E. R.; Erickson, J. D.
1976-01-01
The author has identified the following significant results. Fine resolution M7 multispectral scanner data collected during the Corn Blight Watch Experiment in 1971 served as the basis for this study. Different locations and times of year were studied. Definite improvement using 30-40 meter spatial resolution over present LANDSAT 1 resolution and over 50-60 meter resolution was observed, using crop area mensuration as the measure. Simulation studies carried out to extrapolate the empirical results to a range of field size distributions confirmed this effect, showing the improvement to be most pronounced for field sizes of 1-4 hectares. Radiometric sensitivity study showed significant degradation of crop classification accuracy immediately upon relaxation from the nominally specified values of 0.5% noise equivalent reflectance. This was especially the case for data which were spectrally similar such as that collected early in the growing season and also when attempting to accomplish crop stress detection.
Multi-Scale Fractal Analysis of Image Texture and Pattern
NASA Technical Reports Server (NTRS)
Emerson, Charles W.; Lam, Nina Siu-Ngan; Quattrochi, Dale A.
1999-01-01
Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images of the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimensional-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.
Spatio-Temporal Assessment of Margalla Hills Forest by Using Landsat Imagery for Year 2000 and 2018
NASA Astrophysics Data System (ADS)
Batool, R.; Javaid, K.
2018-04-01
Environmental imbalance due to human activities has shown serious threat to ecosystem and produced negative impacts. The main goal of this study is to identify, monitor and classify temporal changes of forest cover, build up and open spaces in Margalla Hills National Park, Islamabad. Geographic Information Sciences (GISc) and Remote Sensing (RS) techniques has been used for the assessment of analysis. LANDSAT-7 Enhanced Thematic Mapper (ETM+) and LANDSAT-8 Operational Land Imager (OLI) were utilized for obtaining data of year 2000 and 2018. Temporal changes were evaluated after applying supervised classification and discrimination was analyzed by Per-Pixel based change detection. Results depicts forest cover decrease from 87 % to 74 % whereas build up has increased from 5 % to 7 % over the span. Consequences also justify the presence of open land in study area that has been increased from 2 % to 7 % respectively.
Linear mixing model applied to AVHRR LAC data
NASA Technical Reports Server (NTRS)
Holben, Brent N.; Shimabukuro, Yosio E.
1993-01-01
A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55 - 3.93 microns channel was extracted and used with the two reflective channels 0.58 - 0.68 microns and 0.725 - 1.1 microns to run a Constraine Least Squares model to generate vegetation, soil, and shade fraction images for an area in the Western region of Brazil. The Landsat Thematic Mapper data covering the Emas National park region was used for estimating the spectral response of the mixture components and for evaluating the mixing model results. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse resolution data for global studies.
Design and Implementation of an Experimental Cataloging Advisor--Mapper.
ERIC Educational Resources Information Center
Ercegovac, Zorana; Borko, Harold
1992-01-01
Describes the design of an experimental computer-aided cataloging advisor, Mapper, that was developed to help novice users with the descriptive cataloging of single-sheet maps from U.S. publishers. The human-computer interface is considered, the use of HyperCard is discussed, the knowledge base is explained, and assistance screens are described.…
NASA Technical Reports Server (NTRS)
Ahmed, H.
1981-01-01
The format of computer compatible tapes which contain LANDSAT 4 and D Prime thematic mapper data is defined. A complete specification of the CCT-AT (radiometric corrections applied and geometric matrices appended) and the CCT-PT (radiometric and geometric corrections) data formats is provided.
The Estuary Data Mapper (EDM) is a free, interactive virtual gateway to coastal data aimed to promote research and aid in environmental management. The graphical user interface allows users to custom select and subset data based on their spatial and temporal interests giving them...
Information content of data from the LANDSAT 4 Thematic Mapper (TM) and multispectral scanner (MSS)
NASA Technical Reports Server (NTRS)
Price, J. C.
1983-01-01
Simultaneous data acquisition by the LANDSAT 4 thematic mapper and the multispectral scanner permits the comparison of the two types of image data with respect to engineering performance and data applications. Progress in the evaluation of information content of matching scenes in agricultural areas is briefly reported.
Nano Mapper: an Internet knowledge mapping system for nanotechnology development
NASA Astrophysics Data System (ADS)
Li, Xin; Hu, Daning; Dang, Yan; Chen, Hsinchun; Roco, Mihail C.; Larson, Catherine A.; Chan, Joyce
2009-04-01
Nanotechnology research has experienced rapid growth in recent years. Advances in information technology enable efficient investigation of publications, their contents, and relationships for large sets of nanotechnology-related documents in order to assess the status of the field. This paper presents the development of a new knowledge mapping system, called Nano Mapper (http://nanomapper.eller.arizona.edu), which integrates the analysis of nanotechnology patents and research grants into a Web-based platform. The Nano Mapper system currently contains nanotechnology-related patents for 1976-2006 from the United States Patent and Trademark Office (USPTO), European Patent Office (EPO), and Japan Patent Office (JPO), as well as grant documents from the U.S. National Science Foundation (NSF) for the same time period. The system provides complex search functionalities, and makes available a set of analysis and visualization tools (statistics, trend graphs, citation networks, and content maps) that can be applied to different levels of analytical units (countries, institutions, technical fields) and for different time intervals. The paper shows important nanotechnology patenting activities at USPTO for 2005-2006 identified through the Nano Mapper system.
CheS-Mapper - Chemical Space Mapping and Visualization in 3D.
Gütlein, Martin; Karwath, Andreas; Kramer, Stefan
2012-03-17
Analyzing chemical datasets is a challenging task for scientific researchers in the field of chemoinformatics. It is important, yet difficult to understand the relationship between the structure of chemical compounds, their physico-chemical properties, and biological or toxic effects. To that respect, visualization tools can help to better comprehend the underlying correlations. Our recently developed 3D molecular viewer CheS-Mapper (Chemical Space Mapper) divides large datasets into clusters of similar compounds and consequently arranges them in 3D space, such that their spatial proximity reflects their similarity. The user can indirectly determine similarity, by selecting which features to employ in the process. The tool can use and calculate different kind of features, like structural fragments as well as quantitative chemical descriptors. These features can be highlighted within CheS-Mapper, which aids the chemist to better understand patterns and regularities and relate the observations to established scientific knowledge. As a final function, the tool can also be used to select and export specific subsets of a given dataset for further analysis.
CheS-Mapper - Chemical Space Mapping and Visualization in 3D
2012-01-01
Analyzing chemical datasets is a challenging task for scientific researchers in the field of chemoinformatics. It is important, yet difficult to understand the relationship between the structure of chemical compounds, their physico-chemical properties, and biological or toxic effects. To that respect, visualization tools can help to better comprehend the underlying correlations. Our recently developed 3D molecular viewer CheS-Mapper (Chemical Space Mapper) divides large datasets into clusters of similar compounds and consequently arranges them in 3D space, such that their spatial proximity reflects their similarity. The user can indirectly determine similarity, by selecting which features to employ in the process. The tool can use and calculate different kind of features, like structural fragments as well as quantitative chemical descriptors. These features can be highlighted within CheS-Mapper, which aids the chemist to better understand patterns and regularities and relate the observations to established scientific knowledge. As a final function, the tool can also be used to select and export specific subsets of a given dataset for further analysis. PMID:22424447
Landsat-4 thematic mapper and thematic mapper simulator data for a porphyry copper deposit
NASA Technical Reports Server (NTRS)
Abrams, M. J.
1984-01-01
Aircraft thematic mapper (TM) data were analyzed to evaluate the potential utility of the Landsat-4 thematic mapper for geologic mapping and detection of hydrothermal alteration zones in the Silver Bell porphyry copper deposit in southern Arizona. The data allow a comparison between aircraft TV simulator data and the Landsat-4 TM satellite data which possess similar spectral bands. A color rationcomposite of 30-m pixels was resampled, in order to clearly define a number of hydroxyl bearing minerals, (kaolinite, sericite, white mica), pyrite and iron oxide/hydroxide minerals. The iron oxide minerals have diagnostic absorption bands in the 0.45 and 0.85 micron regions of the spectrum, and the hydrous minerals are characterized by an absorption in the 2.2 micron region. The position of the spectral bands allow the TM to identify regions of hydrothermal alteration without resorting to a data processing algorithm. The comparison of the aircraft and Landsat-4 TM data showed considerable agreement, and confirmed the utility of TM data for identifying hydrothermal alteration zones. Samples of some color TM images are provided.
Nano Mapper: an Internet knowledge mapping system for nanotechnology development
Hu, Daning; Dang, Yan; Chen, Hsinchun; Roco, Mihail C.; Larson, Catherine A.; Chan, Joyce
2008-01-01
Nanotechnology research has experienced rapid growth in recent years. Advances in information technology enable efficient investigation of publications, their contents, and relationships for large sets of nanotechnology-related documents in order to assess the status of the field. This paper presents the development of a new knowledge mapping system, called Nano Mapper (http://nanomapper.eller.arizona.edu), which integrates the analysis of nanotechnology patents and research grants into a Web-based platform. The Nano Mapper system currently contains nanotechnology-related patents for 1976–2006 from the United States Patent and Trademark Office (USPTO), European Patent Office (EPO), and Japan Patent Office (JPO), as well as grant documents from the U.S. National Science Foundation (NSF) for the same time period. The system provides complex search functionalities, and makes available a set of analysis and visualization tools (statistics, trend graphs, citation networks, and content maps) that can be applied to different levels of analytical units (countries, institutions, technical fields) and for different time intervals. The paper shows important nanotechnology patenting activities at USPTO for 2005–2006 identified through the Nano Mapper system. PMID:21170121
Mapping land cover through time with the Rapid Land Cover Mapper—Documentation and user manual
Cotillon, Suzanne E.; Mathis, Melissa L.
2017-02-15
The Rapid Land Cover Mapper is an Esri ArcGIS® Desktop add-in, which was created as an alternative to automated or semiautomated mapping methods. Based on a manual photo interpretation technique, the tool facilitates mapping over large areas and through time, and produces time-series raster maps and associated statistics that characterize the changing landscapes. The Rapid Land Cover Mapper add-in can be used with any imagery source to map various themes (for instance, land cover, soils, or forest) at any chosen mapping resolution. The user manual contains all essential information for the user to make full use of the Rapid Land Cover Mapper add-in. This manual includes a description of the add-in functions and capabilities, and step-by-step procedures for using the add-in. The Rapid Land Cover Mapper add-in was successfully used by the U.S. Geological Survey West Africa Land Use Dynamics team to accurately map land use and land cover in 17 West African countries through time (1975, 2000, and 2013).
Anolik, Rachel A; Allori, Alexander C; Pourtaheri, Navid; Rogers, Gary F; Marcus, Jeffrey R
2016-05-01
The purpose of this study was to evaluate the utility of a previously validated interfrontal angle for classification of severity of metopic synostosis and as an aid to operative decision-making. An expert panel was asked to study 30 cases ranging from minor to severe metopic synostosis. Based on computed tomographic images of the skull and clinical photographs, they classified the severity of trigonocephaly (1 = normal, 2 = mild, 3 = moderate, and 4 = severe) and management (0 = nonoperative and 1 = operative). The severity scores and management reported by experts were then pooled and matched with the interfrontal angle computed from each respective computed tomographic scan. A threshold was identified at which most experts agree on operative management. Expert severity scores were higher for more acute interfrontal angles. There was a high concordance at the extremes of classifications, severe (4) and normal (1) (p < 0.0001); however, between interfrontal angles of 114.3 and 136.1 degrees, there exists a "gray zone," with severe discordance in expert rankings. An operative threshold of 118.2 degrees was identified, with the interfrontal angle able to predict the expert panel's decision to proceed with surgery 87.6 percent of the time. The interfrontal angle has been previously validated as a simple, accurate, and reproducible means for diagnosing trigonocephaly, but must be obtained from computed tomographic data. In this article, the authors demonstrate that the interfrontal angle can be used to further characterize the severity of trigonocephaly. It also correlated with expert decision-making for operative versus nonoperative management. This tool may be used as an adjunct to clinical decision-making when the decision to proceed with surgery may not be straightforward. Diagnostic, V.
Diagnostic discrepancies in retinopathy of prematurity classification
Campbell, J. Peter; Ryan, Michael C.; Lore, Emily; Tian, Peng; Ostmo, Susan; Jonas, Karyn; Chan, R.V. Paul; Chiang, Michael F.
2016-01-01
Objective To identify the most common areas for discrepancy in retinopathy of prematurity (ROP) classification between experts. Design Prospective cohort study. Subjects, Participants, and/or Controls 281 infants were identified as part of a multi-center, prospective, ROP cohort study from 7 participating centers. Each site had participating ophthalmologists who provided the clinical classification after routine examination using binocular indirect ophthalmoscopy (BIO), and obtained wide-angle retinal images, which were independently classified by two study experts. Methods Wide-angle retinal images (RetCam; Clarity Medical Systems, Pleasanton, CA) were obtained from study subjects, and two experts evaluated each image using a secure web-based module. Image-based classifications for zone, stage, plus disease, overall disease category (no ROP, mild ROP, Type II or pre-plus, and Type I) were compared between the two experts, and to the clinical classification obtained by BIO. Main Outcome Measures Inter-expert image-based agreement and image-based vs. ophthalmoscopic diagnostic agreement using absolute agreement and weighted kappa statistic. Results 1553 study eye examinations from 281 infants were included in the study. Experts disagreed on the stage classification in 620/1553 (40%) of comparisons, plus disease classification (including pre-plus) in 287/1553 (18%), zone in 117/1553 (8%), and overall ROP category in 618/1553 (40%). However, agreement for presence vs. absence of type 1 disease was >95%. There were no differences between image-based and clinical classification except for zone III disease. Conclusions The most common area of discrepancy in ROP classification is stage, although inter-expert agreement for clinically-significant disease such as presence vs. absence of type 1 and type 2 disease is high. There were no differences between image-based grading and the clinical exam in the ability to detect clinically-significant disease. This study provides additional evidence that image-based classification of ROP reliably detects clinically significant levels of ROP with high accuracy compared to the clinical exam. PMID:27238376
NASA Astrophysics Data System (ADS)
Al-Doasari, Ahmad E.
The 1991 Gulf War caused massive environmental damage in Kuwait. Deposition of oil and soot droplets from hundreds of burning oil-wells created a layer of tarcrete on the desert surface covering over 900 km2. This research investigates the spatial change in the tarcrete extent from 1991 to 1998 using Landsat Thematic Mapper (TM) imagery and statistical modeling techniques. The pixel structure of TM data allows the spatial analysis of the change in tarcrete extent to be conducted at the pixel (cell) level within a geographical information system (GIS). There are two components to this research. The first is a comparison of three remote sensing classification techniques used to map the tarcrete layer. The second is a spatial-temporal analysis and simulation of tarcrete changes through time. The analysis focuses on an area of 389 km2 located south of the Al-Burgan oil field. Five TM images acquired in 1991, 1993, 1994, 1995, and 1998 were geometrically and atmospherically corrected. These images were classified into six classes: oil lakes; heavy, intermediate, light, and traces of tarcrete; and sand. The classification methods tested were unsupervised, supervised, and neural network supervised (fuzzy ARTMAP). Field data of tarcrete characteristics were collected to support the classification process and to evaluate the classification accuracies. Overall, the neural network method is more accurate (60 percent) than the other two methods; both the unsupervised and the supervised classification accuracy assessments resulted in 46 percent accuracy. The five classifications were used in a lagged autologistic model to analyze the spatial changes of the tarcrete through time. The autologistic model correctly identified overall tarcrete contraction between 1991--1993 and 1995--1998. However, tarcrete contraction between 1993--1994 and 1994--1995 was less well marked, in part because of classification errors in the maps from these time periods. Initial simulations of tarcrete contraction with a cellular automaton model were not very successful. However, more accurate classifications could improve the simulations. This study illustrates how an empirical investigation using satellite images, field data, GIS, and spatial statistics can simulate dynamic land-cover change through the use of a discrete statistical and cellular automaton model.
Acetabular-epiphyseal angle and hip dislocation in cerebral palsy: a preliminary study.
Alí-Morell, O J; Zurita-Ortega, F; Davó-Jiménez, I; Segura-Biedma, S
To relate, in non-ambulatory subjects with palsy, Reimers' migration percentage with standardized radiological measurements, including the acetabular-epiphyseal angle. Descriptive, observational and transversal study of 15 individuals with cerebral palsy at levels IV and V of the Gross Motor Function Classification System, aged between 3 and 9 years. Radiological measurements of the acetabular index, Hilgenreiner's epiphyseal angle, acetabular-epiphyseal angle, neck-shaft angle and Reimers' migration percentage of each of the hips were performed. Correlations between acetabular index, epiphyseal angle and acetabular-epiphyseal angle were obtained with respect to the Reimers migration percentage. For hips with a migration rate of 15% or less, a positive correlation was observed between acetabular and epiphyseal angles. In our population, the measurement between acetabular and epiphyseal inclination represents the highest association with the hip migration percentage. Copyright © 2018 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.
Variation of directional reflectance factors with structural changes of a developing alfalfa canopy
NASA Technical Reports Server (NTRS)
Kirchner, J. A.; Kimes, D. S.; Mcmurtrey, J. E., III
1982-01-01
Directional reflectance factors of an alfalfa canopy were determined and related to canopy structure, agronomic variables, and irradiance conditions at four periods during a cutting cycle. Nadir and off-nadir reflectance factors decreased with increasing biomass in Thematic Mapper band 3(0.63-0.69 micrometer) and increased with increasing biomass in band 4(0.76-0.90 micrometer). The sensor view angle had less impact on perceived reflectance as the alfalfa progressed from an erectophile canopy of stems after harvest to a near planophile canopy of leaves at maturity. Studies of directional reflectance are needed for testing and upgrading vegetation canopy models and to aid in the complex interpretation problems presented by aircraft scanners and pointable satellites where illumination and viewing geometries may vary widely. Distinct changes in the patterns of radiance observed by a sensor as structural and biomass changes occur are keys to monitoring the growth and condition of crops.
NASA Astrophysics Data System (ADS)
Ramos, Yuddy; Goïta, Kalifa; Péloquin, Stéphane
2016-04-01
This study evaluates Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Hyperion hyperspectral sensor datasets to detect advanced argillic minerals. The spectral signatures of some alteration clay minerals, such as dickite and alunite, have similar absorption features; thus separating them using multispectral satellite images is a complex challenge. However, Hyperion with its fine spectral bands has potential for good separability of features. The Spectral Angle Mapper algorithm was used in this study to map three advanced argillic alteration minerals (alunite, kaolinite, and dickite) in a known alteration zone in the Peruvian Andes. The results from ASTER and Hyperion were analyzed, compared, and validated using a Portable Infrared Mineral Analyzer field spectrometer. The alterations corresponding to kaolinite and alunite were detected with both ASTER and Hyperion (80% to 84% accuracy). However, the dickite mineral was identified only with Hyperion (82% accuracy).
Abstracts of the annual meeting of Planetary Geologic Mappers: June 21-22, 2002, Tempe, Arizona
Gregg, Tracy K. P.; Tanaka, Kenneth L.; Senske, David A.
2002-01-01
The annual meeting of planetary geologic mappers allows mappers the opportunity to exchange ideas, experiences, victories, and problems. In addition, presentations are reviewed by the Geologic Mapping Subcommittee (GEMS) to provide input to the Planetary Geology and Geophysics Mapping Program review panel’s consideration of new proposals and progress reports that include mapping tasks. Funded mappers bring both oral presentation materials (slides or viewgraphs) and map products to post for review by GEMS and fellow mappers. Additionally, the annual meetings typically feature optional field trips that offer Earth analogs and parallels to planetary mapping problems or workshops that provide information and status of current missions. The 2002 meeting of planetary geologic mappers was held June 21-22 at the Mars Flight Facility, Arizona State University, Tempe, Arizona. Dr. Phil Christensen graciously offered the use of the newly renovated facility, and Ms. Kelly Bender not only proved to be a courteous hostess, but also arranged a short workshop on June 23 regarding TES and THEMIS data. Approximately 30 people attended each day of the 2-day meeting, although not the same 30—some attended only on Thursday and others only on Friday. On Thursday, eight mappers gave oral presentations of Mars mapping, and an additional two presentations were presented as posters only. Eight oral presentations on Venus mapping were given on Friday, and an additional four presentations were posters only. Twelve people attended the TES/THEMIS workshop. Presentations of Ganymede mapping and Europa mapping (the latter not yet financially sponsored by PG&G mapping program) were also given on Friday. Aside from the regular presentations of maps-in-progress, there were some additional talks. Lisa Gaddis (USGS) presented a proposal seeking support for a new lunar mapping program in light of all the new data available; she made a good case that the GEMS panel discussed. Jim Skinner (USGS) gave a short presentation on free (or nearly so) software available for 3D viewing of planetary surfaces. Healthy discussions focused on the review time for some maps and the use of different styles of correlation charts observed on the presented maps. Next year’s meeting will be held June 19-20 at Brown University, Providence, RI.
Xu, James Y; Nan, Xiaomeng; Ebken, Victor; Wang, Yan; Pottie, Greg J; Kaiser, William J
2015-03-01
Today, the bicycle is utilized as a daily commute tool, a physical rehabilitation asset, and sporting equipment, prompting studies into the biomechanics of cycling. Of the number of important parameters that affect cycling efficiency, the foot angle profile is one of the most important as it correlates directly with the effective force applied to the bike. However, there has been no compact and portable solution for measuring the foot angle and for providing the cyclist with real-time feedback due to a number of difficulties of the current tracking and sensing technologies and the myriad types of bikes available. This paper presents a novel sensing and mobile computing system for classifying the foot angle profiles during cycling and for providing real-time guidance to the user to achieve the correct profile. Continuous foot angle tracking is firstly converted into a discrete problem requiring only recognition of acceleration profiles of the foot using a single shoe mounted tri-axial accelerometer during each pedaling cycle. A classification method is then applied to identify the pedaling profile. Finally, a mobile solution is presented to provide real-time signal processing and guidance.
NASA Technical Reports Server (NTRS)
Fielding, E. J.
1986-01-01
The Central Andes are widely used as a modern example of noncollisional mountain-building processes. The Puna is a high plateau in the Chilean and Argentine Central Andes extending southward from the altiplano of Bolivia and Peru. Young tectonic and volcanic features are well exposed on the surface of the arid Puna, making them prime targets for the application of high-resolution space imagery such as Shuttle Imaging Radar B and Landsat Thematic Mapper (TM). Two TM scene quadrants from this area are analyzed using interactive color image processing, examination, and automated classification algorithms. The large volumes of these high-resolution datasets require significantly different techniques than have been used previously for the interpretation of Landsat MSS data. Preliminary results include the determination of the radiance spectra of several volcanic and sedimentary rock units and the use of the spectra for automated classification. Structural interpretations have revealed several previously unknown folds in late Tertiary strata, and key zones have been targeted to be investigated in the field. The synoptic view of space imagery is already filling a critical gap between low-resolution geophysical data and traditional geologic field mapping in the reconnaissance study of poorly mapped mountain frontiers such as the Puna.
Integrating multisource land use and land cover data
Wright, Bruce E.; Tait, Mike; Lins, K.F.; Crawford, J.S.; Benjamin, S.P.; Brown, Jesslyn F.
1995-01-01
As part of the U.S. Geological Survey's (USGS) land use and land cover (LULC) program, the USGS in cooperation with the Environmental Systems Research Institute (ESRI) is collecting and integrating LULC data for a standard USGS 1:100,000-scale product. The LULC data collection techniques include interpreting spectrally clustered Landsat Thematic Mapper (TM) images; interpreting 1-meter resolution digital panchromatic orthophoto images; and, for comparison, aggregating locally available large-scale digital data of urban areas. The area selected is the Vancouver, WA-OR quadrangle, which has a mix of urban, rural agriculture, and forest land. Anticipated products include an integrated LULC prototype data set in a standard classification scheme referenced to the USGS digital line graph (DLG) data of the area and prototype software to develop digital LULC data sets.This project will evaluate a draft standard LULC classification system developed by the USGS for use with various source material and collection techniques. Federal, State, and local governments, and private sector groups will have an opportunity to evaluate the resulting prototype software and data sets and to provide recommendations. It is anticipated that this joint research endeavor will increase future collaboration among interested organizations, public and private, for LULC data collection using common standards and tools.
NASA Astrophysics Data System (ADS)
Nabiev, F. H.; Dobrodeev, A. S.; Libin, P. V.; Kotov, I. I.; Ovsyannikov, A. G.
2015-11-01
The paper defines the therapeutic and rehabilitation approach to the patients with Angle's classification Class II dento-facial anomalies, accompanied by obstructive sleep apnea (OSA). The proposed comprehensive approach to the diagnostics and treatment of patients with posterior occlusion, accompanied by OSA, allows for objective evaluation of intensity of a dento-facial anomaly and accompanying respiratory disorders in the nasal and oral pharynx, which allows for the pathophysiological mechanisms of OSA to be identified, and an optimal plan for surgical procedures to be developed. The proposed comprehensive approach to the diagnostics and treatment of patients with Angle's classification Class II dento-facial anomalies provides high functional and aesthetic results.
Using classified Landsat Thematic Mapper data for stratification in a statewide forest inventory
Mark H. Hansen; Daniel G. Wendt
2000-01-01
The 1998 Indiana/Illinois forest inventory (USDA Forest Service, Forest Inventory and Analysis (FIA)) used Landsat Thematic Mapper (TM) data for stratification. Classified images made by the National Gap Analysis Program (GAP) stratified FIA plots into four classes (nonforest, nonforest/ forest, forest/nonforest, and forest) based on a two pixel forest edge buffer zone...
Using Classified Landsat Thematic Mapper Data for Stratification in a Statewide Forest Inventory
Mark H. Hansen; Daniel G. Wendt
2000-01-01
The 1998 Indiana/Illinois forest inventory (USDA Forest Service, Forest Inventory and Analysis (FIA)) used Landsat Thematic Mapper (TM} data for stratification. Classified images made by the National Gap Analysis Program (GAP) stratified FIA plots into four classes (nonforest, nonforest/forest, forest/nonforest, and forest) based on a two pixel forest edge buffer zone...
Thematic Mapper Analysis of Blue Oak (Quercus douglasii) in Central California
Paul A. Lefebvre Jr.; Frank W. Davis; Mark Borchert
1991-01-01
Digital Thematic Mapper (TM) satellite data from September 1986 and December 1985 were analyzed to determine seasonal reflectance properties of blue oak rangeland in the La Panza mountains of San Luis Obispo County. Linear regression analysis was conducted to examine relationships between TM reflectance and oak canopy cover, basal area, and site topographic variables....
Thematic mapper flight model preshipment review data package. Volume 3, part A: System data
NASA Technical Reports Server (NTRS)
1982-01-01
Results of vibration, acoustical noise, and thermal vacuum are described as well as tests studies of EMI/EMC and mass properties conducted for thematic mapper systems integration. Liens are summarized and the engineering change proposal status is presented. Requests for deviation/waiver are included along with failure and nonforming material reports.
Conifer health classification for Colorado, 2008
Cole, Christopher J.; Noble, Suzanne M.; Blauer, Steven L.; Friesen, Beverly A.; Curry, Stacy E.; Bauer, Mark A.
2010-01-01
Colorado has undergone substantial changes in forests due to urbanization, wildfires, insect-caused tree mortality, and other human and environmental factors. The U.S. Geological Survey Rocky Mountain Geographic Science Center evaluated and developed a methodology for applying remotely-sensed imagery for assessing conifer health in Colorado. Two classes were identified for the purposes of this study: healthy and unhealthy (for example, an area the size of a 30- x 30-m pixel with 20 percent or greater visibly dead trees was defined as ?unhealthy?). Medium-resolution Landsat 5 Thematic Mapper imagery were collected. The normalized, reflectance-converted, cloud-filled Landsat scenes were merged to form a statewide image mosaic, and a Normalized Difference Vegetation Index (NDVI) and Renormalized Difference Infrared Index (RDII) were derived. A supervised maximum likelihood classification was done using the Landsat multispectral bands, the NDVI, the RDII, and 30-m U.S. Geological Survey National Elevation Dataset (NED). The classification was constrained to pixels identified in the updated landcover dataset as coniferous or mixed coniferous/deciduous vegetation. The statewide results were merged with a separate health assessment of Grand County, Colo., produced in late 2008. Sampling and validation was done by collecting field data and high-resolution imagery. The 86 percent overall classification accuracy attained in this study suggests that the data and methods used successfully characterized conifer conditions within Colorado. Although forest conditions for Lodgepole Pine (Pinus contorta) are easily characterized, classification uncertainty exists between healthy/unhealthy Ponderosa Pine (Pinus ponderosa), Pi?on (Pinus edulis), and Juniper (Juniperus sp.) vegetation. Some underestimation of conifer mortality in Summit County is likely, where recent (2008) cloud-free imagery was unavailable. These classification uncertainties are primarily due to the spatial and temporal resolution of Landsat, and of the NLCD derived from this sensor. It is believed that high- to moderate-resolution multispectral imagery, coupled with field data, could significantly reduce the uncertainty rates. The USGS produced a four-county follow-up conifer health assessment using high-resolution RapidEye remotely sensed imagery and field data collected in 2009.
The SkyMapper Transient Survey
NASA Astrophysics Data System (ADS)
Scalzo, R. A.; Yuan, F.; Childress, M. J.; Möller, A.; Schmidt, B. P.; Tucker, B. E.; Zhang, B. R.; Onken, C. A.; Wolf, C.; Astier, P.; Betoule, M.; Regnault, N.
2017-07-01
The SkyMapper 1.3 m telescope at Siding Spring Observatory has now begun regular operations. Alongside the Southern Sky Survey, a comprehensive digital survey of the entire southern sky, SkyMapper will carry out a search for supernovae and other transients. The search strategy, covering a total footprint area of 2 000 deg2 with a cadence of ⩽5 d, is optimised for discovery and follow-up of low-redshift type Ia supernovae to constrain cosmic expansion and peculiar velocities. We describe the search operations and infrastructure, including a parallelised software pipeline to discover variable objects in difference imaging; simulations of the performance of the survey over its lifetime; public access to discovered transients; and some first results from the Science Verification data.
The GSFC Mark-2 three band hand-held radiometer. [thematic mapper for ground truth data collection
NASA Technical Reports Server (NTRS)
Tucker, C. J.; Jones, W. H.; Kley, W. A.; Sundstrom, G. J.
1980-01-01
A self-contained, portable, hand-radiometer designed for field usage was constructed and tested. The device, consisting of a hand-held probe containing three sensors and a strap supported electronic module, weighs 4 1/2 kilograms. It is powered by flashlight and transistor radio batteries, utilizes two silicon and one lead sulfide detectors, has three liquid crystal displays, sample and hold radiometric sampling, and its spectral configuration corresponds to LANDSAT-D's thematic mapper bands. The device was designed to support thematic mapper ground-truth data collection efforts and to facilitate 'in situ' ground-based remote sensing studies of natural materials. Prototype instruments were extensively tested under laboratory and field conditions with excellent results.
Land-Cover Change in the Central Irregular Plains, 1973-2000
Karstensen, Krista A.
2009-01-01
Spearheaded by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in collaboration with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA), the Land Cover Trends is a research project focused on understanding the rates, trends, causes, and consequences of contemporary United States land-use and land-cover change. Using the EPA Level III ecoregions as the geographic framework, scientists process geospatial data collected between 1973 and 2000 to characterize ecosystem responses to land-use changes. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000 and 1973-2000. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize land-cover change and evaluate using a modified Anderson Land Use Land Cover Classification System for image interpretation. The rates of land-cover change are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change. Additionally, historical aerial photographs from similar timeframes and other ancillary data such as census statistics and published literature are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. These change statistics are applicable for different levels of scale, including total change for the individual sample blocks and change estimates for the entire ecoregion. The results illustrate that there is no single profile of land-cover change but instead point to geographic variability that results from land uses within ecoregions continuously adapting to various factors including environmental, technological, and socioeconomic.
1992-01-01
CLASSIFICATION 11. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACTI rnEHUC AGE OF ABSTRACTUNCLSIFIED UNCLASSIFIED UL NSN... ag . ;nst liquid chemical agent simulants SF96, DIMP, and DMMP on a soil surface. The crosshatched wavelengthi-angle domains are areas where the...WHITE ag WRIUT pE/pmv" I MAKE LINE DASHED "fl WRlE,(*WML1r LINE COLOR WHITE al2 ELSE 3 WIUrTE(*,jEJ/MVO MAKE LINE SOUD 244 CALL INThPr(ICOL.COL) I NEER
The First Year of Cassini RADAR Observations of Titan
NASA Astrophysics Data System (ADS)
Elachi, C.; Lorenz, R. D.
2005-12-01
Titan`s atmosphere is essentially transparent to Radar, making it an ideal technique to study Titan`s surface. Cassini`s Titan Radar Mapper operates as a passive radiometer, scatterometer, altimeter, and synthetic aperture radar (SAR). Here we review data from four fly-bys in the first year of Cassini`s tour (Ta: October 2004, T3: February 2005, T7: September 2005, and T8: October 2005.) Early SAR images from Ta and T3 (showing < 3% of Titan`s surface) reveal that Titan is geologically young and complex (see Elachi et al., 2005, Science 13, 970-4). Significant variations were seen between the range of features seen in the Ta swath (centered at ~50N, 80W) and T3 (~ 30N, 70W) : the large-scale radiometric properties also differed, with T3 being radar-brighter. A variety of features have been identified in SAR, including two large impact craters, cryovolcanic flows and a probable volcanic dome. Dendritic and braided radar-bright sinuous channels, some 180km long, are evidence of fluvial activity. `Cat scratches`, arrays of linear dark features seem most likely to be Aeolian. Radar provides unique topographic information on Titan`s landscape e.g. the depth of the 80km crater observed in T3 can be geometrically determined to be around 1300m deep. Despite the shallow large-scale slopes indicated in altimetry to date, many small hills are seen in T3. Scatterometry and radiometry maps provide large-scale classification of surface types and polarization and incidence angle coverage being assembled will constrain dielectric and scattering properties of the surface. Judging from the TA/T3 diversity, we expect further variations in the types and distribution of surface materials and geologic features in T7, which spans a wide range of Southern latitudes. T8 SAR will cover a near-equatorial dark region, including the landing site of the Huygens probe.
NASA Astrophysics Data System (ADS)
Uygur, Merve; Karaman, Muhittin; Kumral, Mustafa
2016-04-01
Çürüksu (Denizli) Graben hosts various geothermal fields such as Kızıldere, Yenice, Gerali, Karahayıt, and Tekkehamam. Neotectonic activities, which are caused by extensional tectonism, and deep circulation in sub-volcanic intrusions are heat sources of hydrothermal solutions. The temperature of hydrothermal solutions is between 53 and 260 degree Celsius. Phyllic, argillic, silicic, and carbonatization alterations and various hydrothermal minerals have been identified in various research studies of these areas. Surfaced hydrothermal alteration minerals are one set of potential indicators of geothermal resources. Developing the exploration tools to define the surface indicators of geothermal fields can assist in the recognition of geothermal resources. Thermal and hyperspectral imaging and analysis can be used for defining the surface indicators of geothermal fields. This study tests the hypothesis that hyperspectral image analysis based on EO-1 Hyperion images can be used for the delineation and definition of surfaced hydrothermal alteration in geothermal fields. Hyperspectral image analyses were applied to images covering the geothermal fields whose alteration characteristic are known. To reduce data dimensionality and identify spectral endmembers, Kruse's multi-step process was applied to atmospherically and geometrically-corrected hyperspectral images. Minimum Noise Fraction was used to reduce the spectral dimensions and isolate noise in the images. Extreme pixels were identified from high order MNF bands using the Pixel Purity Index. n-Dimensional Visualization was utilized for unique pixel identification. Spectral similarities between pixel spectral signatures and known endmember spectrum (USGS Spectral Library) were compared with Spectral Angle Mapper Classification. EO-1 Hyperion hyperspectral images and hyperspectral analysis are sensitive to hydrothermal alteration minerals, as their diagnostic spectral signatures span the visible and shortwave infrared seen in geothermal fields. Hyperspectral analysis results indicated that kaolinite, smectite, illite, montmorillonite, and sepiolite minerals were distributed in a wide area, which covered the hot spring outlet. Rectorite, lizardite, richterite, dumortierite, nontronite, erionite, and clinoptilolite were observed occasionally.
Moses, C.S.; Andrefouet, S.; Kranenburg, C.; Muller-Karger, F. E.
2009-01-01
Using imagery at 30 m spatial resolution from the most recent Landsat satellite, the Landsat 7 Enhanced Thematic Mapper Plus (ETM+), we scale up reef metabolic productivity and calcification from local habitat-scale (10 -1 to 100 km2) measurements to regional scales (103 to 104 km2). Distribution and spatial extent of the North Florida Reef Tract (NFRT) habitats come from supervised classification of the Landsat imagery within independent Landsat-derived Millennium Coral Reef Map geomorphologic classes. This system minimizes the depth range and variability of benthic habitat characteristics found in the area of supervised classification and limits misclassification. Classification of Landsat imagery into 5 biotopes (sand, dense live cover, sparse live cover, seagrass, and sparse seagrass) by geomorphologic class is >73% accurate at regional scales. Based on recently published habitat-scale in situ metabolic measurements, gross production (P = 3.01 ?? 109 kg C yr -1), excess production (E = -5.70 ?? 108 kg C yr -1), and calcification (G = -1.68 ?? 106 kg CaCO 3 yr-1) are estimated over 2711 km2 of the NFRT. Simple models suggest sensitivity of these values to ocean acidification, which will increase local dissolution of carbonate sediments. Similar approaches could be applied over large areas with poorly constrained bathymetry or water column properties and minimal metabolic sampling. This tool has potential applications for modeling and monitoring large-scale environmental impacts on reef productivity, such as the influence of ocean acidification on coral reef environments. ?? Inter-Research 2009.
Coastline complexity: A parameter for functional classification of coastal environments
Bartley, J.D.; Buddemeier, R.W.; Bennett, D.A.
2001-01-01
To understand the role of the world's coastal zone (CZ) in global biogeochemical fluxes (particularly those of carbon, nitrogen, phosphorus, and sediments) we must generalise from a limited number of observations associated with a few well-studied coastal systems to the global scale. Global generalisation must be based on globally available data and on robust techniques for classification and upscaling. These requirements impose severe constraints on the set of variables that can be used to extract information about local CZ functions such as advective and metabolic fluxes, and differences resulting from changes in biotic communities. Coastal complexity (plan-view tortuosity of the coastline) is a potentially useful parameter, since it interacts strongly with both marine and terrestrial forcing functions to determine coastal energy regimes and water residence times, and since 'open' vs. 'sheltered' categories are important components of most coastal habitat classification schemes. This study employs the World Vector Shoreline (WVS) dataset, originally developed at a scale of 1:250 000. Coastline complexity measures are generated using a modification of the Angle Measurement Technique (AMT), in which the basic measurement is the angle between two lines of specified length drawn from a selected point to the closest points of intersection with the coastline. Repetition of these measurements for different lengths at the same point yields a distribution of angles descriptive of the extent and scale of complexity in the vicinity of that point; repetition of the process at different points on the coast provides a basis for comparing both the extent and the characteristic scale of coastline variation along different reaches of the coast. The coast of northwestern Mexico (Baja California and the Gulf of California) was used as a case study for initial development and testing of the method. The characteristic angle distribution plots generated by the AMT analysis were clustered using LOICZVIEW, a high dimensionality clustering routine developed for large-scale coastal classification studies. The results show distinctive differences in coastal environments that have the potential for interpretation in terms of both biotic and hydrogeochemical environments, and that can be related to the resolution limits and uncertainties of the shoreline data used. These objective, quantitative measures of coastal complexity as a function of scale can be further developed and combined with other data sets to provide a key component of functional classification of coastal environments. ?? 2001 Elsevier Science B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
1982-01-01
Tests to verify the as-designed performance of all circuits within the thematic mapper electronics module unit are described. Specifically, the tests involved the evaluation of the scan line corrector driver, shutter drivers function, cal lamp controller function, post amplifier function, command decoder verification unit, and the temperature and actuator controllers function.
Monitoring landscape change for LANDFIRE using multi-temporal satellite imagery and ancillary data
James E. Vogelmann; Jay R. Kost; Brian Tolk; Stephen Howard; Karen Short; Xuexia Chen; Chengquan Huang; Kari Pabst; Matthew G. Rollins
2011-01-01
LANDFIRE is a large interagency project designed to provide nationwide spatial data for fire management applications. As part of the effort, many 2000 vintage Landsat Thematic Mapper and Enhanced Thematic Mapper plus data sets were used in conjunction with a large volume of field information to generate detailed vegetation type and structure data sets for the entire...
Lightning Mapper Sensor Lens Assembly S.O. 5459: Project Management Plan
NASA Technical Reports Server (NTRS)
Zeidler, Janet
1999-01-01
Kaiser Electro-Optics, Inc. (KEO) has developed this Project Management Plan for the Lightning Mapper Sensor (LMS) program. KEO has integrated a team of experts in a structured program management organization to meet the needs of the LMS program. The project plan discusses KEO's approach to critical program elements including Program Management, Quality Assurance, Configuration Management, and Schedule.
Thematic mapper flight model preshipment review data package. Volume 3, part C: System data
NASA Technical Reports Server (NTRS)
1982-01-01
Failure reports for flight model-1 of the thematic mapper are summarized showing the symptom and cause of failure as well as the corrective action taken. Each report is keyed to the major subsystem against which the failure occurred. Requests for deviation/waiver are listed by number, description, and current status. Copies of engineering proposals are included.
The OakMapper WebGIS: improved access to sudden oak death spatial data
K. Tuxen; M. Kelly
2008-01-01
Access to timely and accurate sudden oak death (SOD) location data is critical for SOD monitoring, management and research. Several websites (hereafter called the OakMapper sites) associated with sudden oak death monitoring efforts have been maintained with up-todate SOD location information for over five years, providing information and maps of the most current...
Spectroradiometric calibration of the Thematic Mapper and multispectral scanner system
NASA Technical Reports Server (NTRS)
Slater, P. N.; Palmer, J. M. (Principal Investigator)
1985-01-01
The eleventh quarterly report on Spectroradiometric Calibration of the Thematic Mapper (Contract NAS5-27832) discusses calibrations made at White Sands on 24 May 1985. An attempt is made to standardize test results. Critical values used in the final steps of the data reduction and the comparison of the results of the pre-flight and internal calibration (IC) data are summarized.
F. M. Roberts; P. E. Gessler
2000-01-01
Landsat Thematic Mapper (TM) and SPOT Satellite Imagery were used to map wetland plant species in thc Coeur d'Alene floodplain in northern Idaho. This paper discusses the methodology used to create a wetland plant species map for the floodplain. Species mapped included common cattail (Typha latifolia); water horse-tail (Equisetum...
Landsat and Thermal Infrared Imaging
NASA Technical Reports Server (NTRS)
Arvidson, Terry; Barsi, Julia; Jhabvala, Murzy; Reuter, Dennis
2012-01-01
The purpose of this chapter is to describe the collection of thermal images by Landsat sensors already on orbit and to introduce the new thermal sensor to be launched in 2013. The chapter describes the thematic mapper (TM) and enhanced thematic mapper plus (ETM+) sensors, the calibration of their thermal bands, and the design and prelaunch calibration of the new thermal infrared sensor (TIRS).
Tripp Lowe; Chris Cieszewski; Michael Zasada; Jarek Zawadzki
2005-01-01
The ability to evaluate the ecological and economical effects of proposed modifications to Georgia's best management practices is an important issue in the State. We have incorporated tabular FIA data with Landsat Thematic Mapper satellite images and other spatial data to model Georgia's forested land and assess the area, volume, age, and site quality...
The US EPA Estuary Data Mapper (EDM; http://badger.epa.gov/rsig/edm/index.html) has been designed as a free stand-alone tool for geospatial data discovery, visualization, and data download for estuaries and their associated watersheds in the conterminous United States. EDM requi...
The US EPA Estuary Data Mapper (EDM; http://badger.epa.gov/rsig/edm/index.html) has been designed as a free stand-alone tool for geospatial data discovery, visualization, and data download for estuaries and their associated watersheds in the conterminous United States. EDM requi...
High-Resolution airborne color video data were used to evaluate the accuracy of a land cover map of the upper San Pedro River watershed, derived from June 1997 Landsat Thematic Mapper data. The land cover map was interpreted and generated by Instituto del Medio Ambiente y el Bes...
Thematic mapper flight model preshipment review data package. Volume 2, part B: Subsystem data
NASA Technical Reports Server (NTRS)
1982-01-01
Summarized performance data are presented for the following major subsystems of the thematic mapper: the focal plane assembly, the radiative cooler, the radiative cooler door assembly, the top optical assembly, and the telescope assembly. Reference lists of the configurations status and of nonconforming material reports, failure reports, and requests for deviation/waiver are included.
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
Wang, Xia; Shen, Yihang; Wang, Shiwei; Li, Shiliang; Zhang, Weilin; Liu, Xiaofeng; Lai, Luhua; Pei, Jianfeng; Li, Honglin
2017-07-03
The PharmMapper online tool is a web server for potential drug target identification by reversed pharmacophore matching the query compound against an in-house pharmacophore model database. The original version of PharmMapper includes more than 7000 target pharmacophores derived from complex crystal structures with corresponding protein target annotations. In this article, we present a new version of the PharmMapper web server, of which the backend pharmacophore database is six times larger than the earlier one, with a total of 23 236 proteins covering 16 159 druggable pharmacophore models and 51 431 ligandable pharmacophore models. The expanded target data cover 450 indications and 4800 molecular functions compared to 110 indications and 349 molecular functions in our last update. In addition, the new web server is united with the statistically meaningful ranking of the identified drug targets, which is achieved through the use of standard scores. It also features an improved user interface. The proposed web server is freely available at http://lilab.ecust.edu.cn/pharmmapper/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
The influence of radiographic viewing perspective and demographics on the Critical Shoulder Angle
Suter, Thomas; Popp, Ariane Gerber; Zhang, Yue; Zhang, Chong; Tashjian, Robert Z.; Henninger, Heath B.
2014-01-01
Background Accurate assessment of the critical shoulder angle (CSA) is important in clinical evaluation of degenerative rotator cuff tears. This study analyzed the influence of radiographic viewing perspective on the CSA, developed a classification system to identify malpositioned radiographs, and assessed the relationship between the CSA and demographic factors. Methods Glenoid height, width and retroversion were measured on 3D CT reconstructions of 68 cadaver scapulae. A digitally reconstructed radiograph was aligned perpendicular to the scapular plane, and retroversion was corrected to obtain a true antero-posterior (AP) view. In 10 scapulae, incremental anteversion/retroversion and flexion/extension views were generated. The CSA was measured and a clinically applicable classification system was developed to detect views with >2° change in CSA versus true AP. Results The average CSA was 33±4°. Intra- and inter-observer reliability was high (ICC≥0.81) but decreased with increasing viewing angle. Views beyond 5° anteversion, 8° retroversion, 15° flexion and 26° extension resulted in >2° deviation of the CSA compared to true AP. The classification system was capable of detecting aberrant viewing perspectives with sensitivity of 95% and specificity of 53%. Correlations between glenoid size and CSA were small (R≤0.3), and CSA did not vary by gender (p=0.426) or side (p=0.821). Conclusions The CSA was most susceptible to malposition in ante/retroversion. Deviations as little as 5° in anteversion resulted in a CSA >2° from true AP. A new classification system refines the ability to collect true AP radiographs of the scapula. The CSA was unaffected by demographic factors. PMID:25591458
NASA Technical Reports Server (NTRS)
Toll, D. L.
1984-01-01
An airborne multispectral scanner, operating in the same spectral channels as the Landsat Thematic Mapper (TM), was used in a region east of Denver, CO, for a simulation test performed in the framework of using TM to discriminate the level I and level II classes. It is noted that at the 30-m spatial resolution of the Thematic Mapper Simulator (TMS) the overall discrimination for such classes as commercial/industrial land, rangeland, irrigated sod, irrigated alfalfa, and irrigated pasture was superior to that of the Landsat Multispectral Scanner, primarily due to four added spectral bands. For residential and other spectrally heterogeneous classes, however, the higher resolution of TMS resulted in increased variability within the class and a larger spectral overlap.
Lahmiri, Salim; Gargour, Christian S; Gabrea, Marcel
2014-10-01
An automated diagnosis system that uses complex continuous wavelet transform (CWT) to process retina digital images and support vector machines (SVMs) for classification purposes is presented. In particular, each retina image is transformed into two one-dimensional signals by concatenating image rows and columns separately. The mathematical norm of phase angles found in each one-dimensional signal at each level of CWT decomposition are relied on to characterise the texture of normal images against abnormal images affected by exudates, drusen and microaneurysms. The leave-one-out cross-validation method was adopted to conduct experiments and the results from the SVM show that the proposed approach gives better results than those obtained by other methods based on the correct classification rate, sensitivity and specificity.
Huang, Zhong-sheng; Zhao, Zhen; Ji, Ying-yao; Li, Ke-lun; Zheng, Ju-han; Ni, Jian-guang; Xu, Can-zhen; Zheng, Li-cheng
2011-10-01
To introduce and evaluate the clinical effects of percutaneous reduction and Kirschner pin fixation for the treatment of intraarticular fractures of the calcaneus in children. From March 2001 to February 2009,12 patients with intraarticular calcaneal fractures were treated by percutaneous reduction and Kirschner pin fixation (13 feet). There were 8 males and 4 females,ranging in age from 3 to 14,with an average of 8.7 years. According to Essex-Lopresti classification, among 5 feet were tongue fractures and 8 feet were compressed fractures. According to Sanders classification, 9 feet were type II and 4 feet were type III. The Biihler angle and Gissane angle of the calcaneus were obtained before and after operation. All patients were evaluated according to Maryland Foot Score. All the patients were followed up for 16-71 months (means 35.9 months),and all the incisions were healed without complications and infection. The preoperative X-ray film showed that Böhler angle was (19.7+/-5.3) degrees, Gissane angle was (137.3+/-7.5) degrees. The postoperative X-ray film demonstrated that Böhler angle was (32.6+/-3.7) degrees, Gissane angle was (125.4+/-2.9) degrees. There was a significant difference between preoperative and postoperative (P<0.01). The average Maryland score was 96.3+/-2.4 (range, 92 to 100 points). Percutaneous reduction and Kirschner pin fixation is an effective minimally invasive way to treat intraarticular fractures of the calcaneus in children, it has many advantages such as minimal invasion, reliable fixation and satisfactory effects.
Green, R.O.; Pieters, C.; Mouroulis, P.; Eastwood, M.; Boardman, J.; Glavich, T.; Isaacson, P.; Annadurai, M.; Besse, S.; Barr, D.; Buratti, B.; Cate, D.; Chatterjee, A.; Clark, R.; Cheek, L.; Combe, J.; Dhingra, D.; Essandoh, V.; Geier, S.; Goswami, J.N.; Green, R.; Haemmerle, V.; Head, J.; Hovland, L.; Hyman, S.; Klima, R.; Koch, T.; Kramer, G.; Kumar, A.S.K.; Lee, Kenneth; Lundeen, S.; Malaret, E.; McCord, T.; McLaughlin, S.; Mustard, J.; Nettles, J.; Petro, N.; Plourde, K.; Racho, C.; Rodriquez, J.; Runyon, C.; Sellar, G.; Smith, C.; Sobel, H.; Staid, M.; Sunshine, J.; Taylor, L.; Thaisen, K.; Tompkins, S.; Tseng, H.; Vane, G.; Varanasi, P.; White, M.; Wilson, D.
2011-01-01
The NASA Discovery Moon Mineralogy Mapper imaging spectrometer was selected to pursue a wide range of science objectives requiring measurement of composition at fine spatial scales over the full lunar surface. To pursue these objectives, a broad spectral range imaging spectrometer with high uniformity and high signal-to-noise ratio capable of measuring compositionally diagnostic spectral absorption features from a wide variety of known and possible lunar materials was required. For this purpose the Moon Mineralogy Mapper imaging spectrometer was designed and developed that measures the spectral range from 430 to 3000 nm with 10 nm spectral sampling through a 24 degree field of view with 0.7 milliradian spatial sampling. The instrument has a signal-to-noise ratio of greater than 400 for the specified equatorial reference radiance and greater than 100 for the polar reference radiance. The spectral cross-track uniformity is >90% and spectral instantaneous field-of-view uniformity is >90%. The Moon Mineralogy Mapper was launched on Chandrayaan-1 on the 22nd of October. On the 18th of November 2008 the Moon Mineralogy Mapper was turned on and collected a first light data set within 24 h. During this early checkout period and throughout the mission the spacecraft thermal environment and orbital parameters varied more than expected and placed operational and data quality constraints on the measurements. On the 29th of August 2009, spacecraft communication was lost. Over the course of the flight mission 1542 downlinked data sets were acquired that provide coverage of more than 95% of the lunar surface. An end-to-end science data calibration system was developed and all measurements have been passed through this system and delivered to the Planetary Data System (PDS.NASA.GOV). An extensive effort has been undertaken by the science team to validate the Moon Mineralogy Mapper science measurements in the context of the mission objectives. A focused spectral, radiometric, spatial, and uniformity validation effort has been pursued with selected data sets including an Earth-view data set. With this effort an initial validation of the on-orbit performance of the imaging spectrometer has been achieved, including validation of the cross-track spectral uniformity and spectral instantaneous field of view uniformity. The Moon Mineralogy Mapper is the first imaging spectrometer to measure a data set of this kind at the Moon. These calibrated science measurements are being used to address the full set of science goals and objectives for this mission. Copyright 2011 by the American Geophysical Union.
C. Pieters,; P. Mouroulis,; M. Eastwood,; J. Boardman,; Green, R.O.; Glavich, T.; Isaacson, P.; Annadurai, M.; Besse, S.; Cate, D.; Chatterjee, A.; Clark, R.; Barr, D.; Cheek, L.; Combe, J.; Dhingra, D.; Essandoh, V.; Geier, S.; Goswami, J.N.; Green, R.; Haemmerle, V.; Head, J.; Hovland, L.; Hyman, S.; Klima, R.; Koch, T.; Kramer, G.; Kumar, A.S.K.; Lee, K.; Lundeen, S.; Malaret, E.; McCord, T.; McLaughlin, S.; Mustard, J.; Nettles, J.; Petro, N.; Plourde, K.; Racho, C.; Rodriguez, J.; Runyon, C.; Sellar, G.; Smith, C.; Sobel, H.; Staid, M.; Sunshine, J.; Taylor, L.; Thaisen, K.; Tompkins, S.; Tseng, H.; Vane, G.; Varanasi, P.; White, M.; Wilson, D.
2011-01-01
The NASA Discovery Moon Mineralogy Mapper imaging spectrometer was selected to pursue a wide range of science objectives requiring measurement of composition at fine spatial scales over the full lunar surface. To pursue these objectives, a broad spectral range imaging spectrometer with high uniformity and high signal-to-noise ratio capable of measuring compositionally diagnostic spectral absorption features from a wide variety of known and possible lunar materials was required. For this purpose the Moon Mineralogy Mapper imaging spectrometer was designed and developed that measures the spectral range from 430 to 3000 nm with 10 nm spectral sampling through a 24 degree field of view with 0.7 milliradian spatial sampling. The instrument has a signal-to-noise ratio of greater than 400 for the specified equatorial reference radiance and greater than 100 for the polar reference radiance. The spectral cross-track uniformity is >90% and spectral instantaneous field-of-view uniformity is >90%. The Moon Mineralogy Mapper was launched on Chandrayaan-1 on the 22nd of October. On the 18th of November 2008 the Moon Mineralogy Mapper was turned on and collected a first light data set within 24 h. During this early checkout period and throughout the mission the spacecraft thermal environment and orbital parameters varied more than expected and placed operational and data quality constraints on the measurements. On the 29th of August 2009, spacecraft communication was lost. Over the course of the flight mission 1542 downlinked data sets were acquired that provide coverage of more than 95% of the lunar surface. An end-to-end science data calibration system was developed and all measurements have been passed through this system and delivered to the Planetary Data System (PDS.NASA.GOV). An extensive effort has been undertaken by the science team to validate the Moon Mineralogy Mapper science measurements in the context of the mission objectives. A focused spectral, radiometric, spatial, and uniformity validation effort has been pursued with selected data sets including an Earth-view data set. With this effort an initial validation of the on-orbit performance of the imaging spectrometer has been achieved, including validation of the cross-track spectral uniformity and spectral instantaneous field of view uniformity. The Moon Mineralogy Mapper is the first imaging spectrometer to measure a data set of this kind at the Moon. These calibrated science measurements are being used to address the full set of science goals and objectives for this mission.
C- and L-band space-borne SAR incidence angle normalization for efficient Arctic sea ice monitoring
NASA Astrophysics Data System (ADS)
Mahmud, M. S.; Geldsetzer, T.; Howell, S.; Yackel, J.; Nandan, V.
2017-12-01
C-band Synthetic Aperture Radar (SAR) has been widely used effectively for operational sea ice monitoring, owing to its greater seperability between snow-covered first-year (FYI) and multi-year (MYI) ice types, during winter. However, during the melt season, C-band SAR backscatter contrast reduces between FYI and MYI. To overcome the limitations of C-band, several studies have recommended utlizing L-band SAR, as it has the potential to significantly improve sea ice classification. Given its longer wavelength, L-band can efficiently separate FYI and MYI types, especially during melt season. Therefore, the combination of C- and L-band SAR is an optimal solution for efficient seasonal sea ice monitoring. As SAR acquires images over a range of incidence angles from near-range to far-range, SAR backscatter varies substantially. To compensate this variation in SAR backscatter, incidence angle dependency of C- and L-band SAR backscatter for different FYI and MYI types is crucial to quantify, which is the objective of this study. Time-series SAR imagery from C-band RADARSAT-2 and L-band ALOS PALSAR during winter months of 2010 across 60 sites over the Canadian Arctic was acquired. Utilizing 15 images for each sites during February-March for both C- and L-band SAR, incidence angle dependency was calculated. Our study reveals that L- and C-band backscatter from FYI and MYI decreases with increasing incidence angle. The mean incidence angle dependency for FYI and MYI were estimated to be -0.21 dB/1° and -0.30 dB/1° respectively from L-band SAR, and -0.22 dB/1° and -0.16 dB/1° from C-band SAR, respectively. While the incidence angle dependency for FYI was found to be similar in both frequencies, it doubled in case of MYI from L-band, compared to C-band. After applying the incidence angle normalization method to both C- and L-band SAR images, preliminary results indicate improved sea ice type seperability between FYI and MYI types, with substantially lower number of mixed pixels; thereby offering more reliable sea ice classification accuracies. Research findings from this study can be utilized to improve seasonal sea ice classification with higher accuracy for operational Arctic sea ice monitoring, especially in regions like the Canadian Arctic, where MYI detection is crucial for safer ship navigations.
Shifman, M. A.; Nadkarni, P.; Miller, P. L.
1992-01-01
Pulse field gel electrophoresis mapping is an important technique for characterizing large segments of DNA. We have developed two tools to aid in the construction of pulse field electrophoresis gel maps: PFGE READER which stores experimental conditions and calculates fragment sizes and PFGE MAPPER which constructs pulse field gel electrophoresis maps. PMID:1482898
NASA Technical Reports Server (NTRS)
Smith, Charles M.
2003-01-01
This report provides results of an independent assessment of the geopositional accuracy of the Earth Satellite (EarthSat) Corporation's GeoCover, Orthorectified Landsat Thematic Mapper (TM) imagery over Northeast Asia. This imagery was purchased through NASA's Earth Science Enterprise (ESE) Scientific Data Purchase (SDP) program.
NASA Technical Reports Server (NTRS)
1982-01-01
The acceptance test data package for the thematic mapper flight model power supply was reviewed and the data compared to the relevant specification. The power supply was found to be within specification. Final test data for outut voltage regulation and ripple, efficiency, over and undervoltage protection, telemetry, impedances, turn-on requirements, and input current limits are presented.
Comparison of mapping algorithms used in high-throughput sequencing: application to Ion Torrent data
2014-01-01
Background The rapid evolution in high-throughput sequencing (HTS) technologies has opened up new perspectives in several research fields and led to the production of large volumes of sequence data. A fundamental step in HTS data analysis is the mapping of reads onto reference sequences. Choosing a suitable mapper for a given technology and a given application is a subtle task because of the difficulty of evaluating mapping algorithms. Results In this paper, we present a benchmark procedure to compare mapping algorithms used in HTS using both real and simulated datasets and considering four evaluation criteria: computational resource and time requirements, robustness of mapping, ability to report positions for reads in repetitive regions, and ability to retrieve true genetic variation positions. To measure robustness, we introduced a new definition for a correctly mapped read taking into account not only the expected start position of the read but also the end position and the number of indels and substitutions. We developed CuReSim, a new read simulator, that is able to generate customized benchmark data for any kind of HTS technology by adjusting parameters to the error types. CuReSim and CuReSimEval, a tool to evaluate the mapping quality of the CuReSim simulated reads, are freely available. We applied our benchmark procedure to evaluate 14 mappers in the context of whole genome sequencing of small genomes with Ion Torrent data for which such a comparison has not yet been established. Conclusions A benchmark procedure to compare HTS data mappers is introduced with a new definition for the mapping correctness as well as tools to generate simulated reads and evaluate mapping quality. The application of this procedure to Ion Torrent data from the whole genome sequencing of small genomes has allowed us to validate our benchmark procedure and demonstrate that it is helpful for selecting a mapper based on the intended application, questions to be addressed, and the technology used. This benchmark procedure can be used to evaluate existing or in-development mappers as well as to optimize parameters of a chosen mapper for any application and any sequencing platform. PMID:24708189
A new method for shape and texture classification of orthopedic wear nanoparticles.
Zhang, Dongning; Page, Janet R; Kavanaugh, Aaron E; Billi, Fabrizio
2012-09-27
Detailed morphologic analysis of particles produced during wear of orthopedic implants is important in determining a correlation among material, wear, and biological effects. However, the use of simple shape descriptors is insufficient to categorize the data and to compare the nature of wear particles generated by different implants. An approach based on Discrete Fourier Transform (DFT) is presented for describing particle shape and surface texture. Four metal-on-metal bearing couples were tested in an orbital wear simulator under standard and adverse (steep-angled cups) wear simulator conditions. Digitized Scanning Electron Microscope (SEM) images of the wear particles were imported into MATLAB to carry out Fourier descriptor calculations via a specifically developed algorithm. The descriptors were then used for studying particle characteristics (shape and texture) as well as for cluster classification. Analysis of the particles demonstrated the validity of the proposed model by showing that steep-angle Co-Cr wear particles were more asymmetric, compressed, extended, triangular, square, and roughened at 3 Mc than after 0.25 Mc. In contrast, particles from standard angle samples were only more compressed and extended after 3 Mc compared to 0.25 Mc. Cluster analysis revealed that the 0.25 Mc steep-angle particle distribution was a subset of the 3 Mc distribution.
Hadoop-MCC: Efficient Multiple Compound Comparison Algorithm Using Hadoop.
Hua, Guan-Jie; Hung, Che-Lun; Tang, Chuan Yi
2018-01-01
In the past decade, the drug design technologies have been improved enormously. The computer-aided drug design (CADD) has played an important role in analysis and prediction in drug development, which makes the procedure more economical and efficient. However, computation with big data, such as ZINC containing more than 60 million compounds data and GDB-13 with more than 930 million small molecules, is a noticeable issue of time-consuming problem. Therefore, we propose a novel heterogeneous high performance computing method, named as Hadoop-MCC, integrating Hadoop and GPU, to copy with big chemical structure data efficiently. Hadoop-MCC gains the high availability and fault tolerance from Hadoop, as Hadoop is used to scatter input data to GPU devices and gather the results from GPU devices. Hadoop framework adopts mapper/reducer computation model. In the proposed method, mappers response for fetching SMILES data segments and perform LINGO method on GPU, then reducers collect all comparison results produced by mappers. Due to the high availability of Hadoop, all of LINGO computational jobs on mappers can be completed, even if some of the mappers encounter problems. A comparison of LINGO is performed on each the GPU device in parallel. According to the experimental results, the proposed method on multiple GPU devices can achieve better computational performance than the CUDA-MCC on a single GPU device. Hadoop-MCC is able to achieve scalability, high availability, and fault tolerance granted by Hadoop, and high performance as well by integrating computational power of both of Hadoop and GPU. It has been shown that using the heterogeneous architecture as Hadoop-MCC effectively can enhance better computational performance than on a single GPU device. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
NASA Technical Reports Server (NTRS)
Lang, Timothy; Blakeslee, R. J.; Cecil, D. J.; Christian, H. J.; Gatlin, P. N.; Goodman, S. J.; Koshak, W. J.; Petersen, W. A.; Quick, M.; Schultz, C. J.;
2018-01-01
Function: Monitor global change and thunderstorm processes through observations of Earth's high-latitude lightning. This instrument will combine long-lived sampling of individual thunderstorms with long-term observations of lightning at high latitudes: How is global change affecting thunderstorm patterns; How do high-latitude thunderstorms differ from low-latitude? Why is the Gateway the optimal facility for this instrument / research: Expected DSG (Deep Space Gateway) orbits will provide nearly continuous viewing of the Earth's high latitudes (50 degrees latitude and poleward); These regions are not well covered by existing lightning mappers (e.g., Lightning Imaging Sensor / LIS, or Geostationary Lightning Mapper / GLM); Polar, Molniya, Tundra, etc. Earth orbits have significant drawbacks related to continuous coverage and/or stable FOVs (Fields of View).
Code of Federal Regulations, 2011 CFR
2011-04-01
... and, as the patient's mouth opens, the pen records on graph paper the angle between the upper and the lower jaw. (b) Classification. Class I (general controls). The device is exempt from the premarket...
NASA Technical Reports Server (NTRS)
1982-01-01
Final performance test data for the thematic mapper flight model multiplexer are presented in tables. Aspects covered include A/D thresholds for bands 5, 6, and 7; cross talk; the thermistor; bilevel commands signal parameters; A/D threshold ambient, voltage margin low bus; serial data and bit clock parameters; and the wire check. Tests were conducted at ambient temperature.
2006-09-01
Each of these layers will be described in more detail to include relevant technologies ( Java , PDA, Hibernate , and PostgreSQL) used to implement...Logic Layer -Object-Relational Mapper ( Hibernate ) Data 35 capable in order to interface with Java applications. Based on meeting the selection...further discussed. Query List Application Logic Layer HibernateApache - Java Servlet - Hibernate Interface -OR Mapper -RDBMS Interface
Airborne Topographic Mapper Calibration Procedures and Accuracy Assessment
NASA Technical Reports Server (NTRS)
Martin, Chreston F.; Krabill, William B.; Manizade, Serdar S.; Russell, Rob L.; Sonntag, John G.; Swift, Robert N.; Yungel, James K.
2012-01-01
Description of NASA Airborn Topographic Mapper (ATM) lidar calibration procedures including analysis of the accuracy and consistancy of various ATM instrument parameters and the resulting influence on topographic elevation measurements. The ATM elevations measurements from a nominal operating altitude 500 to 750 m above the ice surface was found to be: Horizontal Accuracy 74 cm, Horizontal Precision 14 cm, Vertical Accuracy 6.6 cm, Vertical Precision 3 cm.
Thematic mapper flight model preshipment review data package. Volume 3, part B: System data
NASA Technical Reports Server (NTRS)
1982-01-01
Procedures and results are presented for performance and systems integration tests of flight model-1 thematic mapper. Aspects considered cover electronic module integration, radiometric calibration, spectral matching, spatial coverage, radiometric calibration of the calibrator, coherent noise, dynamic square wave response, band to band registration, geometric accuracy, and self induced vibration. Thermal vacuum tests, EMI/EMS, and mass properties are included. Liens are summarized.
NASA Technical Reports Server (NTRS)
Lewis, James K.
1987-01-01
Energy flow and nutrient cycling were modeled as affected by herbivory on selected intensive sites along gradients of precipitation and soils, validating the model output by monitoring selected parameters with data derived from the Thematic Mapper (TM). Herbivore production was modeled along the gradient of soils and herbivory, and validated with data derived from TM in a spatial data base.
Fitzpatrick, Megan J; Mathewson, Paul D; Porter, Warren P
2015-01-01
Mechanistic models provide a powerful, minimally invasive tool for gaining a deeper understanding of the ecology of animals across geographic space and time. In this paper, we modified and validated the accuracy of the mechanistic model Niche Mapper for simulating heat exchanges of animals with counter-current heat exchange mechanisms in their legs and animals that wade in water. We then used Niche Mapper to explore the effects of wading and counter-current heat exchange on the energy expenditures of Whooping Cranes, a long-legged wading bird. We validated model accuracy against the energy expenditure of two captive Whooping Cranes measured using the doubly-labeled water method and time energy budgets. Energy expenditure values modeled by Niche Mapper were similar to values measured by the doubly-labeled water method and values estimated from time-energy budgets. Future studies will be able to use Niche Mapper as a non-invasive tool to explore energy-based limits to the fundamental niche of Whooping Cranes and apply this knowledge to management decisions. Basic questions about the importance of counter-current exchange and wading to animal physiological tolerances can also now be explored with the model.
Fitzpatrick, Megan J.; Mathewson, Paul D.; Porter, Warren P.
2015-01-01
Mechanistic models provide a powerful, minimally invasive tool for gaining a deeper understanding of the ecology of animals across geographic space and time. In this paper, we modified and validated the accuracy of the mechanistic model Niche Mapper for simulating heat exchanges of animals with counter-current heat exchange mechanisms in their legs and animals that wade in water. We then used Niche Mapper to explore the effects of wading and counter-current heat exchange on the energy expenditures of Whooping Cranes, a long-legged wading bird. We validated model accuracy against the energy expenditure of two captive Whooping Cranes measured using the doubly-labeled water method and time energy budgets. Energy expenditure values modeled by Niche Mapper were similar to values measured by the doubly-labeled water method and values estimated from time-energy budgets. Future studies will be able to use Niche Mapper as a non-invasive tool to explore energy-based limits to the fundamental niche of Whooping Cranes and apply this knowledge to management decisions. Basic questions about the importance of counter-current exchange and wading to animal physiological tolerances can also now be explored with the model. PMID:26308207
PepMapper: a collaborative web tool for mapping epitopes from affinity-selected peptides.
Chen, Wenhan; Guo, William W; Huang, Yanxin; Ma, Zhiqiang
2012-01-01
Epitope mapping from affinity-selected peptides has become popular in epitope prediction, and correspondingly many Web-based tools have been developed in recent years. However, the performance of these tools varies in different circumstances. To address this problem, we employed an ensemble approach to incorporate two popular Web tools, MimoPro and Pep-3D-Search, together for taking advantages offered by both methods so as to give users more options for their specific purposes of epitope-peptide mapping. The combined operation of Union finds as many associated peptides as possible from both methods, which increases sensitivity in finding potential epitopic regions on a given antigen surface. The combined operation of Intersection achieves to some extent the mutual verification by the two methods and hence increases the likelihood of locating the genuine epitopic region on a given antigen in relation to the interacting peptides. The Consistency between Intersection and Union is an indirect sufficient condition to assess the likelihood of successful peptide-epitope mapping. On average from 27 tests, the combined operations of PepMapper outperformed either MimoPro or Pep-3D-Search alone. Therefore, PepMapper is another multipurpose mapping tool for epitope prediction from affinity-selected peptides. The Web server can be freely accessed at: http://informatics.nenu.edu.cn/PepMapper/
Efficient Moment-Based Inference of Admixture Parameters and Sources of Gene Flow
Levin, Alex; Reich, David; Patterson, Nick; Berger, Bonnie
2013-01-01
The recent explosion in available genetic data has led to significant advances in understanding the demographic histories of and relationships among human populations. It is still a challenge, however, to infer reliable parameter values for complicated models involving many populations. Here, we present MixMapper, an efficient, interactive method for constructing phylogenetic trees including admixture events using single nucleotide polymorphism (SNP) genotype data. MixMapper implements a novel two-phase approach to admixture inference using moment statistics, first building an unadmixed scaffold tree and then adding admixed populations by solving systems of equations that express allele frequency divergences in terms of mixture parameters. Importantly, all features of the model, including topology, sources of gene flow, branch lengths, and mixture proportions, are optimized automatically from the data and include estimates of statistical uncertainty. MixMapper also uses a new method to express branch lengths in easily interpretable drift units. We apply MixMapper to recently published data for Human Genome Diversity Cell Line Panel individuals genotyped on a SNP array designed especially for use in population genetics studies, obtaining confident results for 30 populations, 20 of them admixed. Notably, we confirm a signal of ancient admixture in European populations—including previously undetected admixture in Sardinians and Basques—involving a proportion of 20–40% ancient northern Eurasian ancestry. PMID:23709261
21 CFR 868.5780 - Tube introduction forceps.
Code of Federal Regulations, 2010 CFR
2010-04-01
...) Identification. Tube introduction forceps (e.g., Magill forceps) are a right-angled device used to grasp a tracheal tube and place it in a patient's trachea. (b) Classification. Class I (general controls). The...
21 CFR 868.5780 - Tube introduction forceps.
Code of Federal Regulations, 2011 CFR
2011-04-01
...) Identification. Tube introduction forceps (e.g., Magill forceps) are a right-angled device used to grasp a tracheal tube and place it in a patient's trachea. (b) Classification. Class I (general controls). The...
21 CFR 868.5780 - Tube introduction forceps.
Code of Federal Regulations, 2014 CFR
2014-04-01
...) Identification. Tube introduction forceps (e.g., Magill forceps) are a right-angled device used to grasp a tracheal tube and place it in a patient's trachea. (b) Classification. Class I (general controls). The...
21 CFR 868.5780 - Tube introduction forceps.
Code of Federal Regulations, 2012 CFR
2012-04-01
...) Identification. Tube introduction forceps (e.g., Magill forceps) are a right-angled device used to grasp a tracheal tube and place it in a patient's trachea. (b) Classification. Class I (general controls). The...
21 CFR 868.5780 - Tube introduction forceps.
Code of Federal Regulations, 2013 CFR
2013-04-01
...) Identification. Tube introduction forceps (e.g., Magill forceps) are a right-angled device used to grasp a tracheal tube and place it in a patient's trachea. (b) Classification. Class I (general controls). The...
NASA Astrophysics Data System (ADS)
Berlin, Cynthia Jane
1998-12-01
This research addresses the identification of the areal extent of the intertidal wetlands of Willapa Bay, Washington, and the evaluation of the potential for exotic Spartina alterniflora (smooth cordgrass) expansion in the bay using a spatial geographic approach. It is hoped that the results will address not only the management needs of the study area but provide a research design that may be applied to studies of other coastal wetlands. Four satellite images, three Landsat Multi-Spectral (MSS) and one Thematic Mapper (TM), are used to derive a map showing areas of water, low, middle and high intertidal, and upland. Two multi-date remote sensing mapping techniques are assessed: a supervised classification using density-slicing and an unsupervised classification using an ISODATA algorithm. Statistical comparisons are made between the resultant derived maps and the U.S.G.S. topographic maps for the Willapa Bay area. The potential for Spartina expansion in the bay is assessed using a sigmoidal (logistic) growth model and a spatial modelling procedure for four possible growth scenarios: without management controls (Business-as-Usual), with moderate management controls (e.g. harvesting to eliminate seed setting), under a hypothetical increase in the growth rate that may reflect favorable environmental changes, and under a hypothetical decrease in the growth rate that may reflect aggressive management controls. Comparisons for the statistics of the two mapping techniques suggest that although the unsupervised classification method performed satisfactorily, the supervised classification (density-slicing) method provided more satisfactory results. Results from the modelling of potential Spartina expansion suggest that Spartina expansion will proceed rapidly for the Business-as-Usual and hypothetical increase in the growth rate scenario, and at a slower rate for the elimination of seed setting and hypothetical decrease in the growth rate scenarios, until all potential habitat is filled.
Coban, Huseyin Oguz; Koc, Ayhan; Eker, Mehmet
2010-01-01
Previous studies have been able to successfully detect changes in gently-sloping forested areas with low-diversity and homogeneous vegetation cover using medium-resolution satellite data such as landsat. The aim of the present study is to examine the capacity of multi-temporal landsat data to identify changes in forested areas with mixed vegetation and generally located on steep slopes or non-uniform topography landsat thematic mapper (TM) and landsat enhanced thematic mapperplus (ETM+) data for the years 1987-2000 was used to detect changes within a 19,500 ha forested area in the Western Black sea region of Turkey. The data comply with the forest cover type maps previously created for forest management plans of the research area. The methods used to detect changes were: post-classification comparison, image differencing, image rationing and NDVI (Normalized Difference Vegetation Index) differencing methods. Following the supervised classification process, error matrices were used to evaluate the accuracy of classified images obtained. The overall accuracy has been calculated as 87.59% for 1987 image and as 91.81% for 2000 image. General kappa statistics have been calculated as 0.8543 and 0.9038 for 1987 and 2000, respectively. The changes identified via the post-classification comparison method were compared with other change detetion methods. Maximum coherence was found to be 74.95% at 4/3 band rate. The NDVI difference and 3rd band difference methods achieved the same coherence with slight variations. The results suggest that landsat satellite data accurately conveys the temporal changes which occur on steeply-sloping forested areas with a mixed structure, providing a limited amount of detail but with a high level of accuracy. Moreover it has been decided that the post-classification comparison method can meet the needs of forestry activities better than other methods as it provides information about the direction of these changes.
Liu, Siqi; Oh, Heesoo; Chambers, David William; Xu, Tianmin; Baumrind, Sheldon
2018-04-06
Determine optimal weightings of Peer Assessment Rating (PAR) index and Discrepancy Index (DI) for malocclusion severity assessment in Chinese orthodontic patients. Sixty-nine Chinese orthodontists assessed a full set of pre-treatment records from a stratified random sample of 120 subjects gathered from six university orthodontic centres. Using professional judgment as the outcome variable, multiple regression analyses were performed to derive customized weighting systems for the PAR index and DI, for all subjects and each Angle classification subgroup. Professional judgment was consistent, with an Intraclass Correlation Coefficient (ICC) of 0.995. The PAR index or DI can be reliably measured, with ICC = 0.959 and 0.990, respectively. The predictive accuracy of PAR index was greatly improved by the Chinese weighting process (from r = 0.431 to r = 0.788) with almost equal distribution in each Angle classification subgroup. The Chinese-weighted DI showed a higher predictive accuracy, at P = 0.01, compared with the PAR index (r = 0.851 versus r = 0.788). A better performance was found in the Class II group (r = 0.890) when compared to Class I (r = 0.736) and III (r = 0.785) groups. The Chinese-weighted PAR index and DI were capable of predicting 62 per cent and 73 per cent of total variance in the professional judgment of malocclusion severity in Chinese patients. Differential prediction across Angle classifications merits attention since different weighting formulas were found.
View angle effect in LANDSAT imagery
NASA Technical Reports Server (NTRS)
Kaneko, T.; Engvall, J. L.
1977-01-01
The view angle effect in LANDSAT 2 imagery was investigated. The LANDSAT multispectral scanner scans over a range of view angles of -5.78 to 5.78 degrees. The view angle effect, which is caused by differing view angles, could be studied by comparing data collected at different view angles over a fixed location at a fixed time. Since such LANDSAT data is not available, consecutive day acquisition data were used as a substitute: they were collected over the same geographical location, acquired 24 hours apart, with a view angle change of 7 to 8 degrees at a latitude of 35 to 45 degrees. It is shown that there is approximately a 5% reduction in the average sensor response on the second-day acquisitions as compared with the first-day acquisitions, and that the view angle effect differs field to field and crop to crop. On false infrared color pictures the view angle effect causes changes primarily in brightness and to a lesser degree in color (hue and saturation). An implication is that caution must be taken when images with different view angles are combined for classification and a signature extension technique needs to take the view angle effect into account.
NASA Astrophysics Data System (ADS)
van der Meer, Freek; Kopačková, Veronika; Koucká, Lucie; van der Werff, Harald M. A.; van Ruitenbeek, Frank J. A.; Bakker, Wim H.
2018-02-01
The final product of a geologic remote sensing data analysis using multi spectral and hyperspectral images is a mineral (abundance) map. Multispectral data, such as ASTER, Landsat, SPOT, Sentinel-2, typically allow to determine qualitative estimates of what minerals are in a pixel, while hyperspectral data allow to quantify this. As input to most image classification or spectral processing approach, endmembers are required. An alternative approach to classification is to derive absorption feature characteristics such as the wavelength position of the deepest absorption, depth of the absorption and symmetry of the absorption feature from hyperspectral data. Two approaches are presented, tested and compared in this paper: the 'Wavelength Mapper' and the 'QuanTools'. Although these algorithms use a different mathematical solution to derive absorption feature wavelength and depth, and use different image post-processing, the results are consistent, comparable and reproducible. The wavelength images can be directly linked to mineral type and abundance, but more importantly also to mineral chemical composition and subtle changes thereof. This in turn allows to interpret hyperspectral data in terms of mineral chemistry changes which is a proxy to pressure-temperature of formation of minerals. We show the case of the Rodalquilar epithermal system of the southern Spanish Gabo de Gata volcanic area using HyMAP airborne hyperspectral images.
Detection of Deforestation and Land Conversion in Rondonia, Brazil Using Change Detection Techniques
NASA Technical Reports Server (NTRS)
Guild, Liane S.; Cohen, Warren B,; Kauffman, J. Boone; Peterson, David L. (Technical Monitor)
2001-01-01
Fires associated with tropical deforestation, land conversion, and land use greatly contribute to emissions as well as the depletion of carbon and nutrient pools. The objective of this research was to compare change detection techniques for identifying deforestation and cattle pasture formation during a period of early colonization and agricultural expansion in the vicinity of Jamari, Rond6nia. Multi-date Landsat Thematic Mapper (TM) data between 1984 and 1992 was examined in a 94 370-ha area of active deforestation to map land cover change. The Tasseled Cap (TC) transformation was used to enhance the contrast between forest, cleared areas, and regrowth. TC images were stacked into a composite multi-date TC and used in a principal components (PC) transformation to identify change components. In addition, consecutive TC image pairs were differenced and stacked into a composite multi-date differenced image. A maximum likelihood classification of each image composite was compared for identification of land cover change. The multi-date TC composite classification had the best accuracy of 78.1% (kappa). By 1984, only 5% of the study area had been cleared, but by 1992, 11% of the area had been deforested, primarily for pasture and 7% lost due to hydroelectric dam flooding. Finally, discrimination of pasture versus cultivation was improved due to the ability to detect land under sustained clearing opened to land exhibiting regrowth with infrequent clearing.
An empirical study of scanner system parameters
NASA Technical Reports Server (NTRS)
Landgrebe, D.; Biehl, L.; Simmons, W.
1976-01-01
The selection of the current combination of parametric values (instantaneous field of view, number and location of spectral bands, signal-to-noise ratio, etc.) of a multispectral scanner is a complex problem due to the strong interrelationship these parameters have with one another. The study was done with the proposed scanner known as Thematic Mapper in mind. Since an adequate theoretical procedure for this problem has apparently not yet been devised, an empirical simulation approach was used with candidate parameter values selected by the heuristic means. The results obtained using a conventional maximum likelihood pixel classifier suggest that although the classification accuracy declines slightly as the IFOV is decreased this is more than made up by an improved mensuration accuracy. Further, the use of a classifier involving both spatial and spectral features shows a very substantial tendency to resist degradation as the signal-to-noise ratio is decreased. And finally, further evidence is provided of the importance of having at least one spectral band in each of the major available portions of the optical spectrum.
Hansen, M.C.; Egorov, Alexey; Roy, David P.; Potapov, P.; Ju, J.; Turubanova, S.; Kommareddy, I.; Loveland, Thomas R.
2011-01-01
Vegetation Continuous Field (VCF) layers of 30 m percent tree cover, bare ground, other vegetation and probability of water were derived for the conterminous United States (CONUS) using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data sets from the Web-Enabled Landsat Data (WELD) project. Turnkey approaches to land cover characterization were enabled due to the systematic WELD Landsat processing, including conversion of digital numbers to calibrated top of atmosphere reflectance and brightness temperature, cloud masking, reprojection into a continental map projection and temporal compositing. Annual, seasonal and monthly WELD composites for 2008 were used as spectral inputs to a bagged regression and classification tree procedure using a large training data set derived from very high spatial resolution imagery and available ancillary data. The results illustrate the ability to perform Landsat land cover characterizations at continental scales that are internally consistent while retaining local spatial and thematic detail.
Lu, Dengsheng; Batistella, Mateus; Moran, Emilio
2009-01-01
Traditional change detection approaches have been proven to be difficult in detecting vegetation changes in the moist tropical regions with multitemporal images. This paper explores the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data for vegetation change detection in the Brazilian Amazon. A principal component analysis was used to integrate TM and HRG panchromatic data. Vegetation change/non-change was detected with the image differencing approach based on the TM and HRG fused image and the corresponding TM image. A rule-based approach was used to classify the TM and HRG multispectral images into thematic maps with three coarse land-cover classes: forest, non-forest vegetation, and non-vegetation lands. A hybrid approach combining image differencing and post-classification comparison was used to detect vegetation change trajectories. This research indicates promising vegetation change techniques, especially for vegetation gain and loss, even if very limited reference data are available. PMID:19789721
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.
NASA Technical Reports Server (NTRS)
1974-01-01
The Ground System requirements for the Land Resources Management (LRM) type-A and type-B missions of the Earth Observatory Satellite (EOS) program are presented. Specifications for the Thematic Mapper data processing are provided (LRM A mission). The specifications also cover the R and D instruments (Thematic Mapper and High Resolution Pointable Imager) data processing for the LRM type-B mission.
Sadowski, Franklin G.; Covington, Steven J.
1987-01-01
Advanced digital processing techniques were applied to Landsat-5 Thematic Mapper (TM) data and SPOT highresolution visible (HRV) panchromatic data to maximize the utility of images of a nuclear powerplant emergency at Chernobyl in the Soviet Ukraine. The images demonstrate the unique interpretive capabilities provided by the numerous spectral bands of the Thematic Mapper and the high spatial resolution of the SPOT HRV sensor.
NASA Technical Reports Server (NTRS)
Ripple, W. J.; Wang, S.; Isaacson, D. L.; Paine, D. P.
1991-01-01
Digital Landsat Thematic Mapper (TM) and SPOT high-resolution visible (HRV) images of coniferous forest canopies were compared in their relationship to forest wood volume using correlation and regression analyses. Significant inverse relationships were found between softwood volume and the spectral bands from both sensors (P less than 0.01). The highest correlations were between the log of softwood volume and the near-infrared bands.
LANDSAT D to test thematic mapper, inaugurate operational system
NASA Technical Reports Server (NTRS)
1982-01-01
NASA will launch the Landsat D spacecraft on July 9, 1982 aboard a new, up-rated Delta 3920 expendable launch vehicle. LANDSAT D will incorporate two highly sophisticated sensors; the flight proven multispectral scanner; and a new instrument expected to advance considerably the remote sensing capabilities of Earth resources satellites. The new sensor, the thematic mapper, provides data in seven spectral (light) bands with greatly improved spectral, spatial and radiometric resolution.
Thematic Mapper: Design through flight evaluation
NASA Technical Reports Server (NTRS)
1984-01-01
LANDSAT 4 and 5, launched in 1982 and 1984, not only carried the Thematic Mapper, but were redesigned to handle the increased data rates associated with it, and to communicate that data to Earth via geosynchronous orbiting Tracking and Data Relay Satellites (TDRS). The TM development program is summarized. A brief historical perspective is presented of the evolution of design requirements and hardware development. The basic performance parameters that serve as sensor design guidelines are presented.
NASA Technical Reports Server (NTRS)
1982-01-01
Data from the thematic mapper scan mirror assembly (SMA) acceptance test are presented. Documentation includes: (1) a list of the acceptance test discrepancies; (2) flight 1 SMA test data book; (3) flight 1 SMA environmental report; (4) the configuration verification index; (5) the flight 1 SMA test failure reports; (6) the flight 1 data tapes log; and (7) the requests for deviation/waivers.
Table Rock Lake Water-Clarity Assessment Using Landsat Thematic Mapper Satellite Data
Krizanich, Gary; Finn, Michael P.
2009-01-01
Water quality of Table Rock Lake in southwestern Missouri is assessed using Landsat Thematic Mapper satellite data. A pilot study uses multidate satellite image scenes in conjunction with physical measurements of secchi disk transparency collected by the Lakes of Missouri Volunteer Program to construct a regression model used to estimate water clarity. The natural log of secchi disk transparency is the dependent variable in the regression and the independent variables are Thematic Mapper band 1 (blue) reflectance and a ratio of the band 1 and band 3 (red) reflectance. The regression model can be used to reliably predict water clarity anywhere within the lake. A pixel-level lake map of predicted water clarity or computed trophic state can be produced from the model output. Information derived from this model can be used by water-resource managers to assess water quality and evaluate effects of changes in the watershed on water quality.
Evaluation of spatial, radiometric and spectral thematic mapper performance for coastal studies
NASA Technical Reports Server (NTRS)
Klemas, V.
1985-01-01
The main emphasis of the research was to determine what effect different wetland plant canopies would have upon observed reflectance in Thematic Mapper bands. The three major vegetation canopy types (broadleaf, gramineous and leafless) produce unique spectral responses for a similar quantity of live biomass. Biomass estimates computed from spectral data were most similar to biomass estimates determined from harvest data when models developed for a specific canopy were used. In other words, the spectral biomass estimate of a broadleaf canopy was most similar to the harvest biomass estimate when a broadleaf canopy radiance model was used. Work is continuing to more precisely determine regression coefficients for each canopy type and to model the change in the coefficients with various combinations of canopy types. Researchers suspect that textural and spatial considerations can be used to identify canopy types and improve biomass estimates from Thematic Mapper data.
Use of laser range finders and range image analysis in automated assembly tasks
NASA Technical Reports Server (NTRS)
Alvertos, Nicolas; Dcunha, Ivan
1990-01-01
A proposition to study the effect of filtering processes on range images and to evaluate the performance of two different laser range mappers is made. Median filtering was utilized to remove noise from the range images. First and second order derivatives are then utilized to locate the similarities and dissimilarities between the processed and the original images. Range depth information is converted into spatial coordinates, and a set of coefficients which describe 3-D objects is generated using the algorithm developed in the second phase of this research. Range images of spheres and cylinders are used for experimental purposes. An algorithm was developed to compare the performance of two different laser range mappers based upon the range depth information of surfaces generated by each of the mappers. Furthermore, an approach based on 2-D analytic geometry is also proposed which serves as a basis for the recognition of regular 3-D geometric objects.
Tectonic evaluation of the Nubian shield of Northeastern Sudan using thematic mapper imagery
NASA Technical Reports Server (NTRS)
1986-01-01
Bechtel is nearing completion of a one-year program that uses digitally enhanced LANDSAT Thematic Mapper (TM) data to compile the first comprehensive regional tectonic map of the Proterozoic Nubian Shield exposed in the northern Red Sea Hills of northeastern Sudan. The status of significant objectives of this study are given. Pertinent published and unpublished geologic literature and maps of the northern Red Sea Hills to establish the geologic framework of the region were reviewed. Thematic mapper imagery for optimal base-map enhancements was processed. Photo mosaics of enhanced images to serve as base maps for compilation of geologic information were completed. Interpretation of TM imagery to define and delineate structural and lithogologic provinces was completed. Geologic information (petrologic, and radiometric data) was compiled from the literature review onto base-map overlays. Evaluation of the tectonic evolution of the Nubian Shield based on the image interpretation and the compiled tectonic maps is continuing.
NASA Astrophysics Data System (ADS)
Zambon, F.; De Sanctis, M. C.; Capaccioni, F.; Filacchione, G.; Carli, C.; Ammanito, E.; Friggeri, A.
2011-10-01
During the first two MESSENGER flybys (14th January 2008 and 6th October 2008) the Mercury Dual Imaging System (MDIS) has extended the coverage of the Mercury surface, obtained by Mariner 10 and now we have images of about 90% of the Mercury surface [1]. MDIS is equipped with a Narrow Angle Camera (NAC) and a Wide Angle Camera (WAC). The NAC uses an off-axis reflective design with a 1.5° field of view (FOV) centered at 747 nm. The WAC has a re- fractive design with a 10.5° FOV and 12-position filters that cover a 395-1040 nm spectral range [2]. The color images can be used to infer information on the surface composition and classification meth- ods are an interesting technique for multispectral image analysis which can be applied to the study of the planetary surfaces. Classification methods are based on clustering algorithms and they can be divided in two categories: unsupervised and supervised. The unsupervised classifiers do not require the analyst feedback, and the algorithm automatically organizes pixels values into classes. In the supervised method, instead, the analyst must choose the "training area" that define the pixels value of a given class [3]. Here we will describe the classification in different compositional units of the region near the Rudaki Crater on Mercury.
NASA Technical Reports Server (NTRS)
Orepoulos, Lazaros; Cahalan, Robert; Marshak, Alexander; Wen, Guoyong
1999-01-01
We suggest a new approach to cloud retrieval, using a normalized difference of nadir reflectivities (NDNR) constructed from a non-absorbing and absorbing (with respect to liquid water) wavelength. Using Monte Carlo simulations we show that this quantity has the potential of removing first order scattering effects caused by cloud side illumination and shadowing at oblique Sun angles. Application of the technique to TM (Thematic Mapper) radiance observations from Landsat-5 over the Southern Great Plains site of the ARM (Atmospheric Radiation Measurement) program gives very similar regional statistics and histograms, but significant differences at the pixel level. NDNR can be also combined with the inverse NIPA (Nonlocal Independent Pixel Approximation) of Marshak (1998) which is applied for the first time on overcast Landsat scene subscenes. We demonstrate the sensitivity of the NIPA-retrieved cloud fields on the parameters of the method and discuss practical issues related to the optimal choice of these parameters.
Landsat TM image maps of the Shirase and Siple Coast ice streams, West Antarctica
Ferrigno, Jane G.; Mullins, Jerry L.; Stapleton, Jo Anne; Bindschadler, Robert; Scambos, Ted A.; Bellisime, Lynda B.; Bowell, Jo-Ann; Acosta, Alex V.
1994-01-01
Fifteen 1: 250000 and one 1: 1000 000 scale Landsat Thematic Mapper (TM) image mosaic maps are currently being produced of the West Antarctic ice streams on the Shirase and Siple Coasts. Landsat TM images were acquired between 1984 and 1990 in an area bounded approximately by 78°-82.5°S and 120°- 160° W. Landsat TM bands 2, 3 and 4 were combined to produce a single band, thereby maximizing data content and improving the signal-to-noise ratio. The summed single band was processed with a combination of high- and low-pass filters to remove longitudinal striping and normalize solar elevation-angle effects. The images were mosaicked and transformed to a Lambert conformal conic projection using a cubic-convolution algorithm. The projection transformation was controled with ten weighted geodetic ground-control points and internal image-to-image pass points with annotation of major glaciological features. The image maps are being published in two formats: conventional printed map sheets and on a CD-ROM.
Radionuclide identification algorithm for organic scintillator-based radiation portal monitor
NASA Astrophysics Data System (ADS)
Paff, Marc Gerrit; Di Fulvio, Angela; Clarke, Shaun D.; Pozzi, Sara A.
2017-03-01
We have developed an algorithm for on-the-fly radionuclide identification for radiation portal monitors using organic scintillation detectors. The algorithm was demonstrated on experimental data acquired with our pedestrian portal monitor on moving special nuclear material and industrial sources at a purpose-built radiation portal monitor testing facility. The experimental data also included common medical isotopes. The algorithm takes the power spectral density of the cumulative distribution function of the measured pulse height distributions and matches these to reference spectra using a spectral angle mapper. F-score analysis showed that the new algorithm exhibited significant performance improvements over previously implemented radionuclide identification algorithms for organic scintillators. Reliable on-the-fly radionuclide identification would help portal monitor operators more effectively screen out the hundreds of thousands of nuisance alarms they encounter annually due to recent nuclear-medicine patients and cargo containing naturally occurring radioactive material. Portal monitor operators could instead focus on the rare but potentially high impact incidents of nuclear and radiological material smuggling detection for which portal monitors are intended.
NASA Technical Reports Server (NTRS)
Hoffer, R. M. (Principal Investigator); Latty, R. S.; Dean, E.; Knowlton, D. J.
1980-01-01
Separate holograms of horizontally (HH) and vertically (HV) polarized responses obtained by the APQ-102 side-looking radar were processed through an optical correlator and the resulting image was recorded on positive film from which black and white negative and positive prints were made. Visual comparison of the HH and HV images reveals a distinct dark band in the imagery which covers about 30% of the radar strip. Preliminary evaluaton of the flight line 1 date indicates that various features on the HH and HV images seem to have different response levels. The amount of sidelap due to the look angle between flight lines 1 and 2 is negligible. NASA mission #425 to obtain flightlines of NS-001 MSS data and supporting aerial photography was successfully flown. Flight line 3 data are of very good quality and virtually cloud-free. Results of data analysis for selection of test fields and for evaluation of waveband combination and spatial resolution are presented.
a Comprehensive Review of Pansharpening Algorithms for GÖKTÜRK-2 Satellite Images
NASA Astrophysics Data System (ADS)
Kahraman, S.; Ertürk, A.
2017-11-01
In this paper, a comprehensive review and performance evaluation of pansharpening algorithms for GÖKTÜRK-2 images is presented. GÖKTÜRK-2 is the first high resolution remote sensing satellite of Turkey which was designed and built in Turkey, by The Ministry of Defence, TUBITAK-UZAY and Turkish Aerospace Industry (TUSAŞ) collectively. GÖKTÜRK-2 was launched at 18th. December 2012 in Jinguan, China and provides 2.5 meter panchromatic (PAN) and 5 meter multispectral (MS) spatial resolution satellite images. In this study, a large number of pansharpening algorithms are implemented and evaluated for performance on multiple GÖKTÜRK-2 satellite images. Quality assessments are conducted both qualitatively through visual results and quantitatively using Root Mean Square Error (RMSE), Correlation Coefficient (CC), Spectral Angle Mapper (SAM), Erreur Relative Globale Adimensionnelle de Synthése (ERGAS), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM) and Universal Image Quality Index (UIQI).
NASA Astrophysics Data System (ADS)
Asadi Haroni, Hooshang; Hassan Tabatabaei, Seyed
2016-04-01
Muteh gold mining area is located in 160 km NW of Isfahan town. Gold mineralization is meso-thermal type and associated with silisic, seresitic and carbonate alterations as well as with hematite and goethite. Image processing and interpretation were applied on the ASTER satellite imagery data of about 400 km2 at the Muteh gold mining area to identify hydrothermal alterations and iron oxides associated with gold mineralization. After applying preprocessing methods such as radiometric and geometric corrections, image processing methods of Principal Components Analysis (PCA), Least Square Fit (Ls-Fit) and Spectral Angle Mapper (SAM) were applied on the ASTER data to identify hydrothermal alterations and iron oxides. In this research reference spectra of minerals such as chlorite, hematite, clay minerals and phengite identified from laboratory spectral analysis of collected samples were used to map the hydrothermal alterations. Finally, identified hydrothermal alteration and iron oxides were validated by visiting and sampling some of the mapped hydrothermal alterations.
Comparison of three methods for materials identification and mapping with imaging spectroscopy
NASA Technical Reports Server (NTRS)
Clark, Roger N.; Swayze, Gregg; Boardman, Joe; Kruse, Fred
1993-01-01
We are comparing three methods of mapping analysis tools for imaging spectroscopy data. The purpose of this comparison is to understand the advantages and disadvantages of each algorithm so others would be better able to choose the best algorithm or combinations of algorithms for a particular problem. The three algorithms are: (1) the spectralfeature modified least squares mapping algorithm of Clark et al (1990, 1991): programs mbandmap and tricorder; (2) the Spectral Angle Mapper Algorithm(Boardman, 1993) found in the CU CSES SIPS package; and (3) the Expert System of Kruse et al. (1993). The comparison uses a ground-calibrated 1990 AVIRIS scene of 400 by 410 pixels over Cuprite, Nevada. Along with the test data set is a spectral library of 38 minerals. Each algorithm is tested with the same AVIRIS data set and spectral library. Field work has confirmed the presence of many of these minerals in the AVIRIS scene (Swayze et al. 1992).
Land-Cover Change in the East Central Texas Plains, 1973-2000
Karstensen, Krista A.
2009-01-01
Project Background: The Geographic Analysis and Monitoring (GAM) Program of the U.S. Geological Survey (USGS) Land Cover Trends project is focused on understanding the rates, trends, causes, and consequences of contemporary U.S. land-use and land-cover change. The objectives of the study are to: (1) develop a comprehensive methodology for using sampling and change analysis techniques and Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) data for measuring regional land-cover change across the United States, (2) characterize the types, rates and temporal variability of change for a 30-year period, (3) document regional driving forces and consequences of change, and (4) prepare a national synthesis of land-cover change (Loveland and others, 1999). Using the 1999 Environmental Protection Agency (EPA) Level III ecoregions derived from Omernik (1987) as the geographic framework, geospatial data collected between 1973 and 2000 were processed and analyzed to characterize ecosystem responses to land-use changes. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000, and 1973-2000. General land-cover classes such as water, developed, grassland/shrubland, and agriculture for these periods were interpreted from Landsat MSS, TM, and Enhanced Thematic Mapper Plus imagery to categorize land-cover change and evaluate using a modified Anderson Land-Use Land-Cover Classification System for image interpretation. The interpretation of these land-cover classes complement the program objective of looking at land-use change with cover serving as a surrogate for land use. The land-cover change rates are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change for the five time periods previously mentioned. Additionally, historical aerial photographs from similar timeframes and other ancillary data such as census statistics and published literature are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. For example, the scalar statistics can show the spatial extent of change per cover type with time, as well as the land-cover transformations from one land-cover type to another type occurring with time. Field data of the sample blocks include direct measurements of land cover, particularly ground-survey data collected for training and validation of image classifications (Loveland and others, 2002). The field experience allows for additional observations of the character and condition of the landscape, assistance in sample block interpretation, ground truthing of Landsat imagery, and helps determine the driving forces of change identified in an ecoregion. Management and maintenance of field data, beyond initial use for training and validation of image classifications, is important as improved methods for image classification are developed, and as present-day data become part of the historical legacy for which studies of land-cover change in the future will depend (Loveland and others, 2002). The results illustrate that there is no single profile of land-cover change; instead, there is significant geographic variability that results from land uses within ecoregions continuously adapting to the resource potential created by various environmental, technological, and socioeconomic factors.
Su, Hong; Han, Bing; Li, Sa; Na, Bin; Ma, Wen; Xu, Tian-Min
2014-09-01
We investigated the compensatory trends of mesiodistal angulation of first molars in malocclusion cases. We compared differences in the angulation of first molars in different developmental stages, malocclusion classifications and skeletal patterns. The medical records and lateral cephalogrammes of 1403 malocclusion cases taken before treatment were measured to evaluate compensation of molar angulation in relation to the skeletal jaw. The cases were stratified by age, Angle classification and skeletal patterns. Differences in the mesiodistal angulation of the first molars were compared among the stratifications. We observed three main phenomena. First, angulation of the upper first molar varied significantly with age and tipped most distally in cases aged <12 years and least distally in cases aged >16 years. The lower first molar did not show such differences. Second, in Angle Class II or skeletal Class II cases, the upper first molar was the most distally tipped, the lower first molar was the most mesially tipped, and opposite angulation compensation was observed in Class III cases. Third, in high-angle cases, the upper and lower first molars were the most distally tipped, and opposite angulation compensation was observed in low-angle cases. These data suggest that the angulation of the molars compensated for various growth patterns and malocclusion types. Hence, awareness of molar angulation compensation would help to adjust occlusal relationships, control anchorage and increase the chances of long-term stability.
NASA Astrophysics Data System (ADS)
Dolan, B.; Rutledge, S. A.; Barnum, J. I.; Matsui, T.; Tao, W. K.; Iguchi, T.
2017-12-01
POLarimetric Radar Retrieval and Instrument Simulator (POLARRIS) is a framework that has been developed to simulate radar observations from cloud resolving model (CRM) output and subject model data and observations to the same retrievals, analysis and visualization. This framework not only enables validation of bulk microphysical model simulated properties, but also offers an opportunity to study the uncertainties associated with retrievals such as hydrometeor classification (HID). For the CSU HID, membership beta functions (MBFs) are built using a set of simulations with realistic microphysical assumptions about axis ratio, density, canting angles, size distributions for each of ten hydrometeor species. These assumptions are tested using POLARRIS to understand their influence on the resulting simulated polarimetric data and final HID classification. Several of these parameters (density, size distributions) are set by the model microphysics, and therefore the specific assumptions of axis ratio and canting angle are carefully studied. Through these sensitivity studies, we hope to be able to provide uncertainties in retrieved polarimetric variables and HID as applied to CRM output. HID retrievals assign a classification to each point by determining the highest score, thereby identifying the dominant hydrometeor type within a volume. However, in nature, there is rarely just one a single hydrometeor type at a particular point. Models allow for mixing ratios of different hydrometeors within a grid point. We use the mixing ratios from CRM output in concert with the HID scores and classifications to understand how the HID algorithm can provide information about mixtures within a volume, as well as calculate a confidence in the classifications. We leverage the POLARRIS framework to additionally probe radar wavelength differences toward the possibility of a multi-wavelength HID which could utilize the strengths of different wavelengths to improve HID classifications. With these uncertainties and algorithm improvements, cases of convection are studied in a continental (Oklahoma) and maritime (Darwin, Australia) regime. Observations from C-band polarimetric data in both locations are compared to CRM simulations from NU-WRF using the POLARRIS framework.
Tree species classification in subtropical forests using small-footprint full-waveform LiDAR data
NASA Astrophysics Data System (ADS)
Cao, Lin; Coops, Nicholas C.; Innes, John L.; Dai, Jinsong; Ruan, Honghua; She, Guanghui
2016-07-01
The accurate classification of tree species is critical for the management of forest ecosystems, particularly subtropical forests, which are highly diverse and complex ecosystems. While airborne Light Detection and Ranging (LiDAR) technology offers significant potential to estimate forest structural attributes, the capacity of this new tool to classify species is less well known. In this research, full-waveform metrics were extracted by a voxel-based composite waveform approach and examined with a Random Forests classifier to discriminate six subtropical tree species (i.e., Masson pine (Pinus massoniana Lamb.)), Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.), Slash pines (Pinus elliottii Engelm.), Sawtooth oak (Quercus acutissima Carruth.) and Chinese holly (Ilex chinensis Sims.) at three levels of discrimination. As part of the analysis, the optimal voxel size for modelling the composite waveforms was investigated, the most important predictor metrics for species classification assessed and the effect of scan angle on species discrimination examined. Results demonstrate that all tree species were classified with relatively high accuracy (68.6% for six classes, 75.8% for four main species and 86.2% for conifers and broadleaved trees). Full-waveform metrics (based on height of median energy, waveform distance and number of waveform peaks) demonstrated high classification importance and were stable among various voxel sizes. The results also suggest that the voxel based approach can alleviate some of the issues associated with large scan angles. In summary, the results indicate that full-waveform LIDAR data have significant potential for tree species classification in the subtropical forests.
Van Berkel, Gary J.; Kertesz, Vilmos
2016-11-15
An “Open Access”-like mass spectrometric platform to fully utilize the simplicity of the manual open port sampling interface for rapid characterization of unprocessed samples by liquid introduction atmospheric pressure ionization mass spectrometry has been lacking. The in-house developed integrated software with a simple, small and relatively low-cost mass spectrometry system introduced here fills this void. Software was developed to operate the mass spectrometer, to collect and process mass spectrometric data files, to build a database and to classify samples using such a database. These tasks were accomplished via the vendorprovided software libraries. Sample classification based on spectral comparison utilized themore » spectral contrast angle method. As a result, using the developed software platform near real-time sample classification is exemplified using a series of commercially available blue ink rollerball pens and vegetable oils. In the case of the inks, full scan positive and negative ion ESI mass spectra were both used for database generation and sample classification. For the vegetable oils, full scan positive ion mode APCI mass spectra were recorded. The overall accuracy of the employed spectral contrast angle statistical model was 95.3% and 98% in case of the inks and oils, respectively, using leave-one-out cross-validation. In conclusion, this work illustrates that an open port sampling interface/mass spectrometer combination, with appropriate instrument control and data processing software, is a viable direct liquid extraction sampling and analysis system suitable for the non-expert user and near real-time sample classification via database matching.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Van Berkel, Gary J.; Kertesz, Vilmos
An “Open Access”-like mass spectrometric platform to fully utilize the simplicity of the manual open port sampling interface for rapid characterization of unprocessed samples by liquid introduction atmospheric pressure ionization mass spectrometry has been lacking. The in-house developed integrated software with a simple, small and relatively low-cost mass spectrometry system introduced here fills this void. Software was developed to operate the mass spectrometer, to collect and process mass spectrometric data files, to build a database and to classify samples using such a database. These tasks were accomplished via the vendorprovided software libraries. Sample classification based on spectral comparison utilized themore » spectral contrast angle method. As a result, using the developed software platform near real-time sample classification is exemplified using a series of commercially available blue ink rollerball pens and vegetable oils. In the case of the inks, full scan positive and negative ion ESI mass spectra were both used for database generation and sample classification. For the vegetable oils, full scan positive ion mode APCI mass spectra were recorded. The overall accuracy of the employed spectral contrast angle statistical model was 95.3% and 98% in case of the inks and oils, respectively, using leave-one-out cross-validation. In conclusion, this work illustrates that an open port sampling interface/mass spectrometer combination, with appropriate instrument control and data processing software, is a viable direct liquid extraction sampling and analysis system suitable for the non-expert user and near real-time sample classification via database matching.« less
The contributions of Edward H. Angle to dental public health.
Peck, S
2009-09-01
The genius of Edward Hartley Angle, (1855-1930), the founder of the dental specialty of orthodontics, to create order from chaos in the study and treatment of positional discrepancies of the teeth, jaws and face advanced greatly the cause of dental public health. Angle's innovations that had the most public health impact were (1) his identification of dental occlusion, not simply tooth irregularity, as a prime concern, (2) his development of an uncomplicated classification system for occlusal conditions, (3) his introduction of prefabricated orthodontic appliances and (4) his framing of orthodontics as a dental specialty by organizing the world's first educational program to train orthodontists.
Underwater target classification using wavelet packets and neural networks.
Azimi-Sadjadi, M R; Yao, D; Huang, Q; Dobeck, G J
2000-01-01
In this paper, a new subband-based classification scheme is developed for classifying underwater mines and mine-like targets from the acoustic backscattered signals. The system consists of a feature extractor using wavelet packets in conjunction with linear predictive coding (LPC), a feature selection scheme, and a backpropagation neural-network classifier. The data set used for this study consists of the backscattered signals from six different objects: two mine-like targets and four nontargets for several aspect angles. Simulation results on ten different noisy realizations and for signal-to-noise ratio (SNR) of 12 dB are presented. The receiver operating characteristic (ROC) curve of the classifier generated based on these results demonstrated excellent classification performance of the system. The generalization ability of the trained network was demonstrated by computing the error and classification rate statistics on a large data set. A multiaspect fusion scheme was also adopted in order to further improve the classification performance.
Parker, Timothy J.; Tanaka, Kenneth L.; Senske, David A.
2002-01-01
The annual Planetary Geologic Mappers Meeting serves two purposes. In addition to giving mappers the opportunity to exchange ideas, experiences, victories, and problems with others, presentations are reviewed by the Geologic Mapping Subcommittee (GeMS) to provide input to the Planetary Geology and Geophysics Mapping Program review panel’s consideration of new proposals and progress reports that include mapping tasks. Funded mappers bring both oral presentation materials (slides or viewgraphs) and map products to post for review by GeMS and fellow mappers. Additionally, the annual meetings typically feature optional field trips offering earth analogs and parallels to planetary mapping problems. The 2001 Mappers Meeting, June 18-19, was convened by Tim Parker, Dave Senske, and Ken Tanaka and was hosted by Larry Crumpler and Jayne Aubele of the New Mexico Museum of Natural History and Science in Albuquerque, New Mexico. Oral presentations were given in the Museum’s Honeywell Auditorium, and maps were posted in the Sandia Room. In addition to active mappers, guests included local science teachers who had successfully competed for the right to attend and listen to the reports. It was a unique pleasure for mappers to have the opportunity to interact with and provide information to teachers responding so enthusiastically to the meeting presentation. On Sunday, June 17, Larry and Jayne conducted an optional pre-meeting field trip. The flanks of Rio Grande Rift, east and west of Albuquerque and Valles Caldera north of town presented tectonic, volcanic, and sedimentary examples of the Rift and adjoining areas analogous to observed features on Mars and Venus. The arid but volcanically and tectonically active environment of New Mexico’s rift valley enables focus on features that appear morphologically young and spectacular in satellite images and digital relief models. The theme of the trip was to see what, at orbiter resolution, "obvious" geologic features look like at lander (outcrop) scales. Trips to the top of the rift-flanking mountains (Sandia Peak, 10,600 ft) and the Valles Caldera, as well as various active spring deposits highlighted the day. After welcoming remarks from the host, Larry Crumpler, opening remarks by Tim Parker and Dave Senske and a report on mapping program status by Ken Tanaka, the mappers’ oral presentations began the morning of June 18, with a session on Venus Geologic Mapping. The afternoon continued with an exciting USGS Planetary GIS on the Web (PIGWAD) demonstration and ended with an open discussion of issues in planetary mapping. Posted maps of Venus quadrangles were viewed during the morning break. Tuesday’s Mars Geologic Mapping session began with a pep talk from Tim Parker encouraging mapping community input to the MER landing site selection committee and continued with Steve Saunders describing the potential contribution of Odyssey Mission data to the geologic mapping of Mars. A Mars map poster session was held during the morning break, and the meeting was adjourned mid-afternoon. After the mappers meeting on Tuesday, attendants were treated to a "Field trip to Mars." The Institute of Meteoritics at the University of New Mexico houses an outstanding collection of meteorites, including those that have been identified as originating from Mars. The Institute tour featured examples of most of the different lithologies exhibited by martian meteorites identified to date, as well as some of the analytical tests (scanning electron microscope) they are conducting on specimens from ALH84001. Wednesday, June 20, featured an optional post-meeting field trip to see a travertine quarry and nearby sites of travertine deposition, the Very Large Array near Socorro, and other volcanic features within the Rio Grande Rift.
21 CFR 888.4600 - Protractor for clinical use.
Code of Federal Regulations, 2011 CFR
2011-04-01
...) Identification. A protractor for clinical use is a device intended for use in measuring the angles of bones, such as on x-rays or in surgery. (b) Classification. Class I (general controls). The device is exempt from...
Removing the Shackles of Euclid: 1 Classification.
ERIC Educational Resources Information Center
Fielker, David S.
1981-01-01
A new approach to classifying quadrilaterals is presented that tries to classify all possible combinations of shapes and angles by removing the traditional Euclidean viewpoints. The document concludes with a brief look at other types of polygons. (MP)
Evidence for dust transport in Viking IR thermal mapper opacity data
NASA Technical Reports Server (NTRS)
Martin, Terry Z.
1993-01-01
Global maps of 9-micron dust opacity derived from radiometric observations made by the Viking Orbiter IR Thermal Mapper instruments have revealed a wealth of new information about the distribution of airborne dust over 1.36 Mars years from 1976-1979. In particular, the changing dust distribution during major dust storms is of interest since the data provide a point of contact with both Earth-based observations of storm growth and with global circulation models.
LANDSAT D instrument module study
NASA Technical Reports Server (NTRS)
1976-01-01
Spacecraft instrument module configurations which support an earth resource data gathering mission using a thematic mapper sensor were examined. The differences in size of these two experiments necessitated the development of two different spacecraft configurations. Following the selection of the best-suited configurations, a validation phase of design, analysis and modelling was conducted to verify feasibility. The chosen designs were then used to formulate definition for a systems weight, a cost range for fabrication and interface requirements for the thematic mapper (TM).
Moon Zoo - Examples of Interesting Lunar Morphology
NASA Astrophysics Data System (ADS)
Cook, A. C.; Wilkinson, J.
2012-09-01
The MoonMappers citizen science project is part of CosmoQuest, a virtual research facility designed for the public. CosmoQuest seeks to take the best aspects of a research center - research, seminars, journal clubs, and community discussions - and provide them to a community of citizen scientists through a virtual facility. MoonMappers was the first citizen science project within CosmoQuest, and is being used to define best practices in getting the public to effectively learn and do science.
Thematic mapper critical elements breadboard program
NASA Technical Reports Server (NTRS)
Dale, C. H., Jr.; Engel, J. L.; Harney, E. D.
1976-01-01
A 40.6 cm bidirectional scan mirror assembly, a scan line corrector and a silicon photodiode array with integral preamplifier input stages were designed, fabricated, and tested to demonstrate performance consistent with requirements of the Hughes thematic mapper system. The measured performance met or exceeded the original design goals in all cases with the qualification that well defined and well understood deficiencies in the design of the photodiode array package will require the prescribed corrections before flight use.
Hu, Fei; Cheng, Yayun; Gui, Liangqi; Wu, Liang; Zhang, Xinyi; Peng, Xiaohui; Su, Jinlong
2016-11-01
The polarization properties of thermal millimeter-wave emission capture inherent information of objects, e.g., material composition, shape, and surface features. In this paper, a polarization-based material-classification technique using passive millimeter-wave polarimetric imagery is presented. Linear polarization ratio (LPR) is created to be a new feature discriminator that is sensitive to material type and to remove the reflected ambient radiation effect. The LPR characteristics of several common natural and artificial materials are investigated by theoretical and experimental analysis. Based on a priori information about LPR characteristics, the optimal range of incident angle and the classification criterion are discussed. Simulation and measurement results indicate that the presented classification technique is effective for distinguishing between metals and dielectrics. This technique suggests possible applications for outdoor metal target detection in open scenes.
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.
The Comprehensive AOCMF Classification System: Mandible Fractures- Level 2 Tutorial
Cornelius, Carl-Peter; Audigé, Laurent; Kunz, Christoph; Rudderman, Randal; Buitrago-Téllez, Carlos H.; Frodel, John; Prein, Joachim
2014-01-01
This tutorial outlines the details of the AOCMF image-based classification system for fractures of the mandible at the precision level 2 allowing description of their topographical distribution. A short introduction about the anatomy is made. Mandibular fractures are classified by the anatomic regions involved. For this purpose, the mandible is delineated into an array of nine regions identified by letters: the symphysis/parasymphysis region anteriorly, two body regions on each lateral side, combined angle and ascending ramus regions, and finally the condylar and coronoid processes. A precise definition of the demarcation lines between these regions is given for the unambiguous allocation of fractures. Four transition zones allow an accurate topographic assignment if fractures end up in or run across the borders of anatomic regions. These zones are defined between angle/ramus and body, and between body and symphysis/parasymphysis. A fracture is classified as “confined” as long as it is located within a region, in contrast to a fracture being “nonconfined” when it extents to an adjoining region. Illustrations and case examples of mandible fractures are presented to become familiar with the classification procedure in daily routine. PMID:25489388
Adam, Asrul; Ibrahim, Zuwairie; Mokhtar, Norrima; Shapiai, Mohd Ibrahim; Mubin, Marizan; Saad, Ismail
2016-01-01
In the existing electroencephalogram (EEG) signals peak classification research, the existing models, such as Dumpala, Acir, Liu, and Dingle peak models, employ different set of features. However, all these models may not be able to offer good performance for various applications and it is found to be problem dependent. Therefore, the objective of this study is to combine all the associated features from the existing models before selecting the best combination of features. A new optimization algorithm, namely as angle modulated simulated Kalman filter (AMSKF) will be employed as feature selector. Also, the neural network random weight method is utilized in the proposed AMSKF technique as a classifier. In the conducted experiment, 11,781 samples of peak candidate are employed in this study for the validation purpose. The samples are collected from three different peak event-related EEG signals of 30 healthy subjects; (1) single eye blink, (2) double eye blink, and (3) eye movement signals. The experimental results have shown that the proposed AMSKF feature selector is able to find the best combination of features and performs at par with the existing related studies of epileptic EEG events classification.
Analysis of multispectral signatures and investigation of multi-aspect remote sensing techniques
NASA Technical Reports Server (NTRS)
Malila, W. A.; Hieber, R. H.; Sarno, J. E.
1974-01-01
Two major aspects of remote sensing with multispectral scanners (MSS) are investigated. The first, multispectral signature analysis, includes the effects on classification performance of systematic variations found in the average signals received from various ground covers as well as the prediction of these variations with theoretical models of physical processes. The foremost effects studied are those associated with the time of day airborne MSS data are collected. Six data collection runs made over the same flight line in a period of five hours are analyzed, it is found that the time span significantly affects classification performance. Variations associated with scan angle also are studied. The second major topic of discussion is multi-aspect remote sensing, a new concept in remote sensing with scanners. Here, data are collected on multiple passes by a scanner that can be tilted to scan forward of the aircraft at different angles on different passes. The use of such spatially registered data to achieve improved classification of agricultural scenes is investigated and found promising. Also considered are the possibilities of extracting from multi-aspect data, information on the condition of corn canopies and the stand characteristics of forests.
Solar-phase-angle effects on the taxonomic classification of asteroids
NASA Astrophysics Data System (ADS)
Carvano, J.; Davallos, J.
2014-07-01
Asteroid taxonomy is the effort of grouping asteroids into classes based on similarities of a number of their observational properties. The most used properties include measurements of their spectral reflectance (by means of low-resolution spectra, spectro-photometry, or colors), and geometric albedo. The usefulness of asteroid taxonomic classes derived in this way relies on the assumption that the classes bear some correspondence to the mineralogy of the asteroids, and on the fact that such classification can be made using types of observations that presently are available to a large number of asteroids. Therefore, asteroid taxonomy can be used to infer trends in the distribution of compositions in the main belt and other populations, as an additional parameter in defining asteroid families, and as a selection tool to identify candidates for more detailed observations. However, the fact that the correspondence between taxonomic class and composition is far from perfect is still sometimes overlooked in the literature. Indeed, although a taxonomic classification narrows down the possible mineralogies of a given asteroid, it will seldom point univocally to one particular mineralogy. This happens for a number of reasons, some linked to the intrinsic difficulty involved in the remote characterization of the mineralogy of an asteroid, since it depends on the presence of absorption bands in its reflectance spectrum which may be absent or not completely sampled by the observations used to derive taxonomy. Other problem here is the exposure of the material on the surface of the asteroid to space-weathering effects, such as solar wind implantation and micro-meteorite bombardment, which can change the optical properties of the material. Finally, the overall shape of the reflectance spectrum of an asteroid is also affected by the geometry of the observation, as well as by its shape. In this work, we analyze how the classification of asteroids observed by the Sloan Digital Sky Survey is affected by the solar phase angle of the observation. It is found that the number of observations assigned to several taxonomic classes has a clear dependency on the solar phase angle of the asteroid at the moment of the observation. In order to understand how variations of phase angles affect the reflectance spectra of the individual asteroids listed in the SDSS with multiple observations, we use the reflectance spectra derived from the SDSS colors to define two parameters, which measure the spectral slope in the visible and the depth of the 1-micron band, if present. It is found that most asteroids in the sample tend to be redder at higher phase angles, and that, for the classes showing a 1-μ m band, most show increasing band depth with increasing phase angle. This predominance of positive correlations for both band depth and spectral slope might suffice to explain the offsets in the distribution of classes. However, for both parameters there is a significant fraction in each sample for which there seem to be no correlation at all, and a comparable number seem to display anti-correlation between the parameters and the phase angle. Therefore, although phase-reddening effects, as currently understood in the literature, can account for the offsets in the distribution of taxonomic classes with phase angle, it cannot explain all variability seen in the SDSS data. There is also a dependency on composition and also shape effects involved, which can be reproduced using Hapke reflectance models.
Multiscale sagebrush rangeland habitat modeling in the Gunnison Basin of Colorado
Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Schell, Spencer J.
2013-01-01
North American sagebrush-steppe ecosystems have decreased by about 50 percent since European settlement. As a result, sagebrush-steppe dependent species, such as the Gunnison sage-grouse, have experienced drastic range contractions and population declines. Coordinated ecosystem-wide research, integrated with monitoring and management activities, is needed to help maintain existing sagebrush habitats; however, products that accurately model and map sagebrush habitats in detail over the Gunnison Basin in Colorado are still unavailable. The goal of this project is to provide a rigorous large-area sagebrush habitat classification and inventory with statistically validated products and estimates of precision across the Gunnison Basin. This research employs a combination of methods, including (1) modeling sagebrush rangeland as a series of independent objective components that can be combined and customized by any user at multiple spatial scales; (2) collecting ground measured plot data on 2.4-meter QuickBird satellite imagery in the same season the imagery is acquired; (3) modeling of ground measured data on 2.4-meter imagery to maximize subsequent extrapolation; (4) acquiring multiple seasons (spring, summer, and fall) of Landsat Thematic Mapper imagery (30-meter) for optimal modeling; (5) using regression tree classification technology that optimizes data mining of multiple image dates, ratios, and bands with ancillary data to extrapolate ground training data to coarser resolution Landsat Thematic Mapper; and 6) employing accuracy assessment of model predictions to enable users to understand their dependencies. Results include the prediction of four primary components including percent bare ground, percent herbaceous, percent shrub, and percent litter, and four secondary components including percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata), percent Wyoming sagebrush (Artemisia tridentata wyomingensis), and shrub height (centimeters). Results were validated with an independent accuracy assessment, with root mean square error values ranging from 3.5 (percent big sagebrush) to 10.8 (percent bare ground) at the QuickBird scale, and from 4.5 (percent Wyoming sagebrush) to 12.4 (percent herbaceous) at the full Landsat scale. These results offer significant improvement in sagebrush ecosystem quantification across the Gunnison Basin, and also provide maximum flexibility to users to employ for a wide variety of applications. Further refinement of these remote sensing component predictions in the future will be most likely achieved by focusing on more extensive ground plot sampling, employing new high and moderate-resolution satellite sensors that offer additional spectral bands for vegetation discrimination, and capturing more dates of satellite imagery to better represent phenological variation.
Effect of foot shape on the three-dimensional position of foot bones.
Ledoux, William R; Rohr, Eric S; Ching, Randal P; Sangeorzan, Bruce J
2006-12-01
To eliminate some of the ambiguity in describing foot shape, we developed three-dimensional (3D), objective measures of foot type based on computerized tomography (CT) scans. Feet were classified via clinical examination as pes cavus (high arch), neutrally aligned (normal arch), asymptomatic pes planus (flat arch with no pain), or symptomatic pes planus (flat arch with pain). We enrolled 10 subjects of each foot type; if both feet were of the same foot type, then each foot was scanned (n=65 total). Partial weightbearing (20% body weight) CT scans were performed. We generated embedded coordinate systems for each foot bone by assuming uniform density and calculating the inertial matrix. Cardan angles were used to describe five bone-to-bone relationships, resulting in 15 angular measurements. Significant differences were found among foot types for 12 of the angles. The angles were also used to develop a classification tree analysis, which determined the correct foot type for 64 of the 65 feet. Our measure provides insight into how foot bone architecture differs between foot types. The classification tree analysis demonstrated that objective measures can be used to discriminate between feet with high, normal, and low arches. Copyright (c) 2006 Orthopaedic Research Society.
NASA Astrophysics Data System (ADS)
Davis, Benjamin L.; Berrier, Joel C.; Shields, Douglas W.; Kennefick, Julia; Kennefick, Daniel; Seigar, Marc S.; Lacy, Claud H. S.; Puerari, Ivânio
2012-04-01
A logarithmic spiral is a prominent feature appearing in a majority of observed galaxies. This feature has long been associated with the traditional Hubble classification scheme, but historical quotes of pitch angle of spiral galaxies have been almost exclusively qualitative. We have developed a methodology, utilizing two-dimensional fast Fourier transformations of images of spiral galaxies, in order to isolate and measure the pitch angles of their spiral arms. Our technique provides a quantitative way to measure this morphological feature. This will allow comparison of spiral galaxy pitch angle to other galactic parameters and test spiral arm genesis theories. In this work, we detail our image processing and analysis of spiral galaxy images and discuss the robustness of our analysis techniques.
sEMG feature evaluation for identification of elbow angle resolution in graded arm movement.
Castro, Maria Claudia F; Colombini, Esther L; Aquino, Plinio T; Arjunan, Sridhar P; Kumar, Dinesh K
2014-11-25
Automatic and accurate identification of elbow angle from surface electromyogram (sEMG) is essential for myoelectric controlled upper limb exoskeleton systems. This requires appropriate selection of sEMG features, and identifying the limitations of such a system.This study has demonstrated that it is possible to identify three discrete positions of the elbow; full extension, right angle, and mid-way point, with window size of only 200 milliseconds. It was seen that while most features were suitable for this purpose, Power Spectral Density Averages (PSD-Av) performed best. The system correctly classified the sEMG against the elbow angle for 100% cases when only two discrete positions (full extension and elbow at right angle) were considered, while correct classification was 89% when there were three discrete positions. However, sEMG was unable to accurately determine the elbow position when five discrete angles were considered. It was also observed that there was no difference for extension or flexion phases.
The dynamics of human-induced land cover change in miombo ecosystems of southern Africa
NASA Astrophysics Data System (ADS)
Jaiteh, Malanding Sambou
Understanding human-induced land cover change in the miombo require the consistent, geographically-referenced, data on temporal land cover characteristics as well as biophysical and socioeconomic drivers of land use, the major cause of land cover change. The overall goal of this research to examine the applications of high-resolution satellite remote sensing data in studying the dynamics of human-induced land cover change in the miombo. Specific objectives are to: (1) evaluate the applications of computer-assisted classification of Landsat Thematic Mapper (TM) data for land cover mapping in the miombo and (2) analyze spatial and temporal patterns of landscape change locations in the miombo. Stepwise Thematic Classification, STC (a hybrid supervised-unsupervised classification) procedure for classifying Landsat TM data was developed and tested using Landsat TM data. Classification accuracy results were compared to those from supervised and unsupervised classification. The STC provided the highest classification accuracy i.e., 83.9% correspondence between classified and referenced data compared to 44.2% and 34.5% for unsupervised and supervised classification respectively. Improvements in the classification process can be attributed to thematic stratification of the image data into spectrally homogenous (thematic) groups and step-by-step classification of the groups using supervised or unsupervised classification techniques. Supervised classification failed to classify 18% of the scene evidence that training data used did not adequately represent all of the variability in the data. Application of the procedure in drier miombo produced overall classification accuracy of 63%. This is much lower than that of wetter miombo. The results clearly demonstrate that digital classification of Landsat TM can be successfully implemented in the miombo without intensive fieldwork. Spatial characteristics of land cover change in agricultural and forested landscapes in central Malawi were analyzed for the period 1984 to 1995 spatial pattern analysis methods. Shifting cultivation areas, Agriculture in forested landscape, experienced highest rate of woodland cover fragmentation with mean patch size of closed woodland cover decreasing from 20ha to 7.5ha. Permanent bare (cropland and settlement) in intensive agricultural matrix landscapes increased 52% largely through the conversion of fallow areas. Protected National Park area remained fairly unchanged although closed woodland area increased by 4%, mainly from regeneration of open woodland. This study provided evidence that changes in spatial characteristics in the miombo differ with landscape. Land use change (i.e. conversion to cropland) is the primary driving force behind changes in landscape spatial patterns. Also, results revealed that exclusion of intense human use (i.e. cultivation and woodcutting) through regulations and/or fencing increased both closed woodland area (through regeneration of open woodland) and overall connectivity in the landscape. Spatial characteristics of land cover change were analyzed at locations in Malawi (wetter miombo) and Zimbabwe (drier miombo). Results indicate land cover dynamics differ both between and within case study sites. In communal areas in the Kasungu scene, land cover change is dominated by woodland fragmentation to open vegetation. Change in private commercial lands was dominantly expansion of bare (settlement and cropland) areas primarily at the expense of open vegetation (fallow land).
The eNanoMapper database for nanomaterial safety information
Chomenidis, Charalampos; Doganis, Philip; Fadeel, Bengt; Grafström, Roland; Hardy, Barry; Hastings, Janna; Hegi, Markus; Jeliazkov, Vedrin; Kochev, Nikolay; Kohonen, Pekka; Munteanu, Cristian R; Sarimveis, Haralambos; Smeets, Bart; Sopasakis, Pantelis; Tsiliki, Georgia; Vorgrimmler, David; Willighagen, Egon
2015-01-01
Summary Background: The NanoSafety Cluster, a cluster of projects funded by the European Commision, identified the need for a computational infrastructure for toxicological data management of engineered nanomaterials (ENMs). Ontologies, open standards, and interoperable designs were envisioned to empower a harmonized approach to European research in nanotechnology. This setting provides a number of opportunities and challenges in the representation of nanomaterials data and the integration of ENM information originating from diverse systems. Within this cluster, eNanoMapper works towards supporting the collaborative safety assessment for ENMs by creating a modular and extensible infrastructure for data sharing, data analysis, and building computational toxicology models for ENMs. Results: The eNanoMapper database solution builds on the previous experience of the consortium partners in supporting diverse data through flexible data storage, open source components and web services. We have recently described the design of the eNanoMapper prototype database along with a summary of challenges in the representation of ENM data and an extensive review of existing nano-related data models, databases, and nanomaterials-related entries in chemical and toxicogenomic databases. This paper continues with a focus on the database functionality exposed through its application programming interface (API), and its use in visualisation and modelling. Considering the preferred community practice of using spreadsheet templates, we developed a configurable spreadsheet parser facilitating user friendly data preparation and data upload. We further present a web application able to retrieve the experimental data via the API and analyze it with multiple data preprocessing and machine learning algorithms. Conclusion: We demonstrate how the eNanoMapper database is used to import and publish online ENM and assay data from several data sources, how the “representational state transfer” (REST) API enables building user friendly interfaces and graphical summaries of the data, and how these resources facilitate the modelling of reproducible quantitative structure–activity relationships for nanomaterials (NanoQSAR). PMID:26425413
The eNanoMapper database for nanomaterial safety information.
Jeliazkova, Nina; Chomenidis, Charalampos; Doganis, Philip; Fadeel, Bengt; Grafström, Roland; Hardy, Barry; Hastings, Janna; Hegi, Markus; Jeliazkov, Vedrin; Kochev, Nikolay; Kohonen, Pekka; Munteanu, Cristian R; Sarimveis, Haralambos; Smeets, Bart; Sopasakis, Pantelis; Tsiliki, Georgia; Vorgrimmler, David; Willighagen, Egon
2015-01-01
The NanoSafety Cluster, a cluster of projects funded by the European Commision, identified the need for a computational infrastructure for toxicological data management of engineered nanomaterials (ENMs). Ontologies, open standards, and interoperable designs were envisioned to empower a harmonized approach to European research in nanotechnology. This setting provides a number of opportunities and challenges in the representation of nanomaterials data and the integration of ENM information originating from diverse systems. Within this cluster, eNanoMapper works towards supporting the collaborative safety assessment for ENMs by creating a modular and extensible infrastructure for data sharing, data analysis, and building computational toxicology models for ENMs. The eNanoMapper database solution builds on the previous experience of the consortium partners in supporting diverse data through flexible data storage, open source components and web services. We have recently described the design of the eNanoMapper prototype database along with a summary of challenges in the representation of ENM data and an extensive review of existing nano-related data models, databases, and nanomaterials-related entries in chemical and toxicogenomic databases. This paper continues with a focus on the database functionality exposed through its application programming interface (API), and its use in visualisation and modelling. Considering the preferred community practice of using spreadsheet templates, we developed a configurable spreadsheet parser facilitating user friendly data preparation and data upload. We further present a web application able to retrieve the experimental data via the API and analyze it with multiple data preprocessing and machine learning algorithms. We demonstrate how the eNanoMapper database is used to import and publish online ENM and assay data from several data sources, how the "representational state transfer" (REST) API enables building user friendly interfaces and graphical summaries of the data, and how these resources facilitate the modelling of reproducible quantitative structure-activity relationships for nanomaterials (NanoQSAR).
NASA Technical Reports Server (NTRS)
Erickson, J. D.; Nalepka, R. F.
1976-01-01
PROCAMS (Prototype Classification and Mensuration System) has been designed for the classification and mensuration of agricultural crops (specifically small grains including wheat, rye, oats, and barley) through the use of data provided by Landsat. The system includes signature extension as a major feature and incorporates multitemporal as well as early season unitemporal approaches for using multiple training sites. Also addressed are partial cloud cover and cloud shadows, bad data points and lines, as well as changing sun angle and atmospheric state variations.
Segmentation of human upper body movement using multiple IMU sensors.
Aoki, Takashi; Lin, Jonathan Feng-Shun; Kulic, Dana; Venture, Gentiane
2016-08-01
This paper proposes an approach for the segmentation of human body movements measured by inertial measurement unit sensors. Using the angular velocity and linear acceleration measurements directly, without converting to joint angles, we perform segmentation by formulating the problem as a classification problem, and training a classifier to differentiate between motion end-point and within-motion points. The proposed approach is validated with experiments measuring the upper body movement during reaching tasks, demonstrating classification accuracy of over 85.8%.
1983-05-01
longitudinal changes in arch width between lateral incisors, canines and second premolars or deciduous second molars at four stages of dental eruption in 22 male... dental arch or skeletal widths. Also, he made no attempt to divide his sample into normal and malocclusion groups. -J 7 Warren (1959) studying twenty...buccal crossbite of the posterior teeth Many clinicians believe that this problem is highly correlated with tfte type or classification of malocclusion
2016-04-01
Program ft foot/feet GPS Global Positioning System HE High Explosive ID Identification IDA Institute for Defense Analysis IMU Inertial Measurement Unit ISO...were replaced with two ski-shaped runners, and a new mount above the array was used to hold the Inertial Measurement Unit (IMU) and Trimble R8 Real...to collect a cued data measurement (Figure 9). The instrument’s pitch, roll , and yaw angles automatically were measured by the IMU. These angles and
Ground data handling for Landsat-D. [for thematic mapper
NASA Technical Reports Server (NTRS)
Lynch, T. J.
1977-01-01
The present plans for the Landsat-D ground data handling are described in relationship to the mission objectives and the planned spacecraft system. The end-to-end data system is presented with particular emphasis on the data handling plans for the new instrument, the Thematic Mapper. This instrument generates ten times the amount of data per scene as the present Multispectral Scanner and this resulting data rate and volume are discussed as well as possible new data techniques to handle them - such as image compression.
Thematic Mapper Protoflight Model Line Spread Function
NASA Technical Reports Server (NTRS)
Schueler, C.
1984-01-01
The Thematic Mapper (TM) Protoflight Model Spatial Line Spread Function (LSF) was not measured before launch. Therefore, methodology are developed to characterize LSF with protoflight model optics and electronics measurements that were made before launch. Direct prelaunch LSF measurements that were made from the flight model TM verified the protoflight TM LSF simulation. Results for two selected protoflight TM channels are presented here. It is shown that LSF data for the other ninety-four channels could be generated in the same fashion.
New dust opacity maps from Viking IR thermal mapper data
NASA Technical Reports Server (NTRS)
Martin, T. Z.; Richardson, M. I.
1992-01-01
Mapping of dust opacity of the Martian atmosphere, using the silicate-induced absorption of 9 micron radiation, was performed with the Viking Infrared Thermal Mapper (IRTM) data for several local dust storms and in a global sense. We present here the first results from an effort to extend the earlier mapping work to the period of the 1977b major storm, and to concentrate attention on the details of opacity behavior during the initial phases of the 1977a and b storms.
Studies of atmospheric dust from Viking IR thermal mapper data
NASA Technical Reports Server (NTRS)
Martin, T. Z.
1993-01-01
Following earlier work to map the dust opacity of the Mars atmosphere, a number of separate studies have been performed employing the radiometric measurements of the Viking IR Thermal Mappers. These efforts have resulted in a new perspective on the atmospheric dust distribution during the Viking Mission, as well as quantitative measures useful in the modeling of likely behavior at other times, and improved boundary conditions for circulation models of Mars. The significant findings from these studies are presented.
Study of Spectral/Radiometric Characteristics of the Thematic Mapper for Land Use Applications
NASA Technical Reports Server (NTRS)
Malila, W. A. (Principal Investigator); Metzler, M. D. (Principal Investigator)
1985-01-01
An investigation conducted in support of the LANDSAT 4/5 Image Data Quality Analysis (LIDQA) Program is discussed. Results of engineering analyses of radiometric, spatial, spectral, and geometric properties of the Thematic Mapper systems are summarized; major emphasis is placed on the radiometric analysis. Details of the analyses are presented in appendices, which contain three of the eight technical papers produced during this investigation; these three, together, describe the major activities and results of the investigation.
2012-05-01
tilted metamorphic rock . Typically, the surface layer of the soil is a brown gravelly silt with sand, about 4 inches thick. The subsoil is yellowish red...site setup, the placement of 200 seed items for use in measuring the capabilities of the advanced EMI sensors tested, the subsequent collection of...advanced sensors. The second team was responsible for the cued survey of 1,491 of the 2,143 targets using the MetalMapper, one of the advanced
Spectral characterization of the LANDSAT Thematic Mapper sensors
NASA Technical Reports Server (NTRS)
Markham, B. L.; Barker, J. L.
1984-01-01
The spectral coverage characteristics of the two thematic mapper instruments were determined by analyses of spectral measurements of the optics, filters, and detectors. The following results are presented: (1) band 2 and 3 flatness was slightly below specification, and band 7 flatness was below specification; (2) band 5 upper-band edge was higher than specifications; (3) band 2 band edges were shifted upward about 9 nm relative to nominal; and (4) band 4, 5, and 7 lower band edges were 16 to 18 nm higher then nominal.
MetalMapper Demonstration at the Pole Mountain Target and Maneuver Area, WY
2012-03-01
number. 1. REPORT DATE MAR 2012 2 . REPORT TYPE 3. DATES COVERED 00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE MetalMapper Demonstration at the... 2 ) The bulk of this liability is $10.0B for the 1703 sites identified in the Formerly Used Defense Sites (FUDS) program and $4.4B for the 2433...performer was able to correctly classify 2 /3 of the clutter while identifying 100% of the TOI. 2 The Strategic Environmental Research and Development
Reverse screening methods to search for the protein targets of chemopreventive compounds
NASA Astrophysics Data System (ADS)
Huang, Hongbin; Zhang, Guigui; Zhou, Yuquan; Lin, Chenru; Chen, Suling; Lin, Yutong; Mai, Shangkang; Huang, Zunnan
2018-05-01
This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.
Ramsey, Elijah W.; Rangoonwala, A.; Nelson, G.; Ehrlich, R.
2005-01-01
Our objective was to provide a realistic and accurate representation of the spatial distribution of Chinese tallow (Triadica sebifera) in the Earth Observing 1 (EO1) Hyperion hyperspectral image coverage by using methods designed and tested in previous studies. We transformed, corrected, and normalized Hyperion reflectance image data into composition images with a subpixel extraction model. Composition images were related to green vegetation, senescent foliage and senescing cypress-tupelo forest, senescing Chinese tallow with red leaves ('red tallow'), and a composition image that only corresponded slightly to yellowing vegetation. These statistical and visual comparisons confirmed a successful portrayal of landscape features at the time of the Hyperion image collection. These landscape features were amalgamated in the Landsat Thematic Mapper (TM) pixel, thereby preventing the detection of Chinese tallow occurrences in the Landsat TM classification. With the occurrence in percentage of red tallow (as a surrogate for Chinese tallow) per pixel mapped, we were able to link dominant land covers generated with Landsat TM image data to Chinese tallow occurrences as a first step toward determining the sensitivity and susceptibility of various land covers to tallow establishment. Results suggested that the highest occurrences and widest distribution of red tallow were (1) apparent in disturbed or more open canopy woody wetland deciduous forests (including cypress-tupelo forests), upland woody land evergreen forests (dominantly pines and seedling plantations), and upland woody land deciduous and mixed forests; (2) scattered throughout the fallow fields or located along fence rows separating active and non-active cultivated and grazing fields, (3) found along levees lining the ubiquitous canals within the marsh and on the cheniers near the coastline; and (4) present within the coastal marsh located on the numerous topographic highs. ?? 2005 US Government.
Reverse Screening Methods to Search for the Protein Targets of Chemopreventive Compounds.
Huang, Hongbin; Zhang, Guigui; Zhou, Yuquan; Lin, Chenru; Chen, Suling; Lin, Yutong; Mai, Shangkang; Huang, Zunnan
2018-01-01
This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.
Reverse Screening Methods to Search for the Protein Targets of Chemopreventive Compounds
Huang, Hongbin; Zhang, Guigui; Zhou, Yuquan; Lin, Chenru; Chen, Suling; Lin, Yutong; Mai, Shangkang; Huang, Zunnan
2018-01-01
This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction. PMID:29868550
Hayworth, Kenneth J.; Morgan, Josh L.; Schalek, Richard; Berger, Daniel R.; Hildebrand, David G. C.; Lichtman, Jeff W.
2014-01-01
The automated tape-collecting ultramicrotome (ATUM) makes it possible to collect large numbers of ultrathin sections quickly—the equivalent of a petabyte of high resolution images each day. However, even high throughput image acquisition strategies generate images far more slowly (at present ~1 terabyte per day). We therefore developed WaferMapper, a software package that takes a multi-resolution approach to mapping and imaging select regions within a library of ultrathin sections. This automated method selects and directs imaging of corresponding regions within each section of an ultrathin section library (UTSL) that may contain many thousands of sections. Using WaferMapper, it is possible to map thousands of tissue sections at low resolution and target multiple points of interest for high resolution imaging based on anatomical landmarks. The program can also be used to expand previously imaged regions, acquire data under different imaging conditions, or re-image after additional tissue treatments. PMID:25018701
Landsat thematic mapper (TM) soil variability analysis over Webster County, Iowa
NASA Technical Reports Server (NTRS)
Thompson, D. R.; Henderson, K. E.; Pitts, D. E.
1984-01-01
Thematic mapper simulator (TMS) data acquired June 7, June 23, and July 31, 1982, and Landsat thematic mapper (TM) data acquired August 2, September 3, and October 21, 1982, over Webster County, Iowa, were examined for within-field soil effects on corn and soybean spectral signatures. It was found that patterns displayed on various computer-generated map products were in close agreement with the detailed soil survey of the area. The difference in spectral values appears to be due to a combination of subtle soil properties and crop growth patterns resulting from the different soil properties. Bands 4 (0.76-.90 micron), 5 (1.55-1.75 micron), and 7 (2.08-2.35 micron) were found to be responding to the within-field soil variability even with increasing ground cover. While these results are preliminary, they do indicate that the soil influence on the vegetation is being detected by TM and should provide improved information relating to crop and soil properties.
Data and Information Exchange System for the "Reindeer Mapper" Project
NASA Technical Reports Server (NTRS)
Maynard, Nancy; Yurchak, Boris
2005-01-01
During this past year, the Reindeer Mapper Intranet system has been set up on the NASA system, 8 team members have been established, a Reindeer Mapper reference list containing 696 items has been entered, 6 power point presentations have been put on line for review among team members, 304 satellite images have been catalogued (including 16 Landsat images, 288 NDVI 10-day composited images and an anomaly series- May 1998 to December 2002, and 56 SAR CEOS S A R format files), schedules and meeting dates are being shared, students at the Nordic Sami Institute are experimenting with the system for reindeer herder indigenous knowledge sharing, and an "address book" is being developed. Several documents and presentations have been translated and made available in Russian for our Russian colleagues. This has enabled our Russian partners to utilize documents and presentations for use in their research (e.g., SAR imagery comparisons with Russian GIS of specific study areas) and discussion with local colleagues.
NASA Technical Reports Server (NTRS)
Westman, Walter E.; Price, Curtis V.
1988-01-01
Landsat Thematic Mapper (TM) and aircraft-borne Thematic Mapper simulator (TMS) data were collected over two areas of natural vegetation in southern California exposed to gradients of pollutant dose, particularly in photochemical oxidants: the coastal sage scrub of the Santa Monica Mountains in the Los Angeles basin, and the yellow pine forests in the southern Sierra Nevada. In both situations, natural variations in canopy closure, with subsequent exposure of understory elements (e.g.,rock or soil, chaparral, grasses, and herbs), were sufficient to cause changes in spectral variation that could obscure differences due to visible foliar injury symptoms observed in the field. TM or TMS data are therefore more likely to be successful in distinguishing pollution injury from background variation when homogeneous communities with closed canopies are subjected to more severe pollution-induced structural and/or compositional change. The present study helps to define the threshold level of vegetative injury detectable by TM data.
Design and Characterization of Optical Metamaterials Using Tunable Polarimetric Scatterometry
2012-12-01
metamaterial absorber (MMA) [33]. The MMA was found to have an incident angle depend resonance, which was captured with Mm polarimetry measurements...TERMS Dual Rotating Retarder, Polarimetry Scatterometry, Metamaterials, Near-Zero Permittivity 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF
Van Berkel, Gary J; Kertesz, Vilmos
2017-02-15
An "Open Access"-like mass spectrometric platform to fully utilize the simplicity of the manual open port sampling interface for rapid characterization of unprocessed samples by liquid introduction atmospheric pressure ionization mass spectrometry has been lacking. The in-house developed integrated software with a simple, small and relatively low-cost mass spectrometry system introduced here fills this void. Software was developed to operate the mass spectrometer, to collect and process mass spectrometric data files, to build a database and to classify samples using such a database. These tasks were accomplished via the vendor-provided software libraries. Sample classification based on spectral comparison utilized the spectral contrast angle method. Using the developed software platform near real-time sample classification is exemplified using a series of commercially available blue ink rollerball pens and vegetable oils. In the case of the inks, full scan positive and negative ion ESI mass spectra were both used for database generation and sample classification. For the vegetable oils, full scan positive ion mode APCI mass spectra were recorded. The overall accuracy of the employed spectral contrast angle statistical model was 95.3% and 98% in case of the inks and oils, respectively, using leave-one-out cross-validation. This work illustrates that an open port sampling interface/mass spectrometer combination, with appropriate instrument control and data processing software, is a viable direct liquid extraction sampling and analysis system suitable for the non-expert user and near real-time sample classification via database matching. Published in 2016. This article is a U.S. Government work and is in the public domain in the USA. Published in 2016. This article is a U.S. Government work and is in the public domain in the USA.
The BHVI-EyeMapper: peripheral refraction and aberration profiles.
Fedtke, Cathleen; Ehrmann, Klaus; Falk, Darrin; Bakaraju, Ravi C; Holden, Brien A
2014-10-01
The aim of this article was to present the optical design of a new instrument (BHVI-EyeMapper, EM), which is dedicated to rapid peripheral wavefront measurements across the visual field for distance and near, and to compare the peripheral refraction and higher-order aberration profiles obtained in myopic eyes with and without accommodation. Central and peripheral refractive errors (M, J180, and J45) and higher-order aberrations (C[3, 1], C[3, 3], and C[4, 0]) were measured in 26 myopic participants (mean [±SD] age, 20.9 [±2.0] years; mean [±SD] spherical equivalent, -3.00 [±0.90] diopters [D]) corrected for distance. Measurements were performed along the horizontal visual field with (-2.00 to -5.00 D) and without (+1.00 D fogging) accommodation. Changes as a function of accommodation were compared using tilt and curvature coefficients of peripheral refraction and aberration profiles. As accommodation increased, the relative peripheral refraction profiles of M and J180 became significantly (p < 0.05) more negative and the profile of M became significantly (p < 0.05) more asymmetric. No significant differences were found for the J45 profiles (p > 0.05). The peripheral aberration profiles of C[3, 1], C[3, 3], and C[4, 0] became significantly (p < 0.05) less asymmetric as accommodation increased, but no differences were found in the curvature. The current study showed that significant changes in peripheral refraction and higher-order aberration profiles occurred during accommodation in myopic eyes. With its extended measurement capabilities, that is, permitting rapid peripheral refraction and higher-order aberration measurements up to visual field angles of ±50 degrees for distance and near (up to -5.00 D), the EM is a new advanced instrument that may provide additional insights in the ongoing quest to understand and monitor myopia development.
The BHVI-EyeMapper: Peripheral Refraction and Aberration Profiles
Fedtke, Cathleen; Ehrmann, Klaus; Falk, Darrin; Bakaraju, Ravi C.; Holden, Brien A.
2014-01-01
ABSTRACT Purpose The aim of this article was to present the optical design of a new instrument (BHVI-EyeMapper, EM), which is dedicated to rapid peripheral wavefront measurements across the visual field for distance and near, and to compare the peripheral refraction and higher-order aberration profiles obtained in myopic eyes with and without accommodation. Methods Central and peripheral refractive errors (M, J180, and J45) and higher-order aberrations (C[3, 1], C[3, 3], and C[4, 0]) were measured in 26 myopic participants (mean [±SD] age, 20.9 [±2.0] years; mean [±SD] spherical equivalent, −3.00 [±0.90] diopters [D]) corrected for distance. Measurements were performed along the horizontal visual field with (−2.00 to −5.00 D) and without (+1.00 D fogging) accommodation. Changes as a function of accommodation were compared using tilt and curvature coefficients of peripheral refraction and aberration profiles. Results As accommodation increased, the relative peripheral refraction profiles of M and J180 became significantly (p < 0.05) more negative and the profile of M became significantly (p < 0.05) more asymmetric. No significant differences were found for the J45 profiles (p > 0.05). The peripheral aberration profiles of C[3, 1], C[3, 3], and C[4, 0] became significantly (p < 0.05) less asymmetric as accommodation increased, but no differences were found in the curvature. Conclusions The current study showed that significant changes in peripheral refraction and higher-order aberration profiles occurred during accommodation in myopic eyes. With its extended measurement capabilities, that is, permitting rapid peripheral refraction and higher-order aberration measurements up to visual field angles of ±50 degrees for distance and near (up to −5.00 D), the EM is a new advanced instrument that may provide additional insights in the ongoing quest to understand and monitor myopia development. PMID:25105690
Meeting medical terminology needs--the Ontology-Enhanced Medical Concept Mapper.
Leroy, G; Chen, H
2001-12-01
This paper describes the development and testing of the Medical Concept Mapper, a tool designed to facilitate access to online medical information sources by providing users with appropriate medical search terms for their personal queries. Our system is valuable for patients whose knowledge of medical vocabularies is inadequate to find the desired information, and for medical experts who search for information outside their field of expertise. The Medical Concept Mapper maps synonyms and semantically related concepts to a user's query. The system is unique because it integrates our natural language processing tool, i.e., the Arizona (AZ) Noun Phraser, with human-created ontologies, the Unified Medical Language System (UMLS) and WordNet, and our computer generated Concept Space, into one system. Our unique contribution results from combining the UMLS Semantic Net with Concept Space in our deep semantic parsing (DSP) algorithm. This algorithm establishes a medical query context based on the UMLS Semantic Net, which allows Concept Space terms to be filtered so as to isolate related terms relevant to the query. We performed two user studies in which Medical Concept Mapper terms were compared against human experts' terms. We conclude that the AZ Noun Phraser is well suited to extract medical phrases from user queries, that WordNet is not well suited to provide strictly medical synonyms, that the UMLS Metathesaurus is well suited to provide medical synonyms, and that Concept Space is well suited to provide related medical terms, especially when these terms are limited by our DSP algorithm.
Su, Hong; Han, Bing; Li, Sa; Na, Bin; Ma, Wen; Xu, Tian-Min
2014-01-01
We investigated the compensatory trends of mesiodistal angulation of first molars in malocclusion cases. We compared differences in the angulation of first molars in different developmental stages, malocclusion classifications and skeletal patterns. The medical records and lateral cephalogrammes of 1 403 malocclusion cases taken before treatment were measured to evaluate compensation of molar angulation in relation to the skeletal jaw. The cases were stratified by age, Angle classification and skeletal patterns. Differences in the mesiodistal angulation of the first molars were compared among the stratifications. We observed three main phenomena. First, angulation of the upper first molar varied significantly with age and tipped most distally in cases aged <12 years and least distally in cases aged >16 years. The lower first molar did not show such differences. Second, in Angle Class II or skeletal Class II cases, the upper first molar was the most distally tipped, the lower first molar was the most mesially tipped, and opposite angulation compensation was observed in Class III cases. Third, in high-angle cases, the upper and lower first molars were the most distally tipped, and opposite angulation compensation was observed in low-angle cases. These data suggest that the angulation of the molars compensated for various growth patterns and malocclusion types. Hence, awareness of molar angulation compensation would help to adjust occlusal relationships, control anchorage and increase the chances of long-term stability. PMID:24699185
Novel angle estimation for bistatic MIMO radar using an improved MUSIC
NASA Astrophysics Data System (ADS)
Li, Jianfeng; Zhang, Xiaofei; Chen, Han
2014-09-01
In this article, we study the problem of angle estimation for bistatic multiple-input multiple-output (MIMO) radar and propose an improved multiple signal classification (MUSIC) algorithm for joint direction of departure (DOD) and direction of arrival (DOA) estimation. The proposed algorithm obtains initial estimations of angles obtained from the signal subspace and uses the local one-dimensional peak searches to achieve the joint estimations of DOD and DOA. The angle estimation performance of the proposed algorithm is better than that of estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm, and is almost the same as that of two-dimensional MUSIC. Furthermore, the proposed algorithm can be suitable for irregular array geometry, obtain automatically paired DOD and DOA estimations, and avoid two-dimensional peak searching. The simulation results verify the effectiveness and improvement of the algorithm.
Unveiling the nature of the $$\\gamma$$-ray emitting active galactic nucleus PKS 0521-36
D'Ammando, F.; Orienti, M.; Tavecchio, F.; ...
2015-05-19
PKS 0521-36 is an active galactic nucleus (AGN) with uncertain classification. Here, we investigate the properties of this source from radio to γ-rays. The broad emission lines in the optical and ultraviolet bands and steep radio spectrum indicate a possible classification as an intermediate object between broad-line radio galaxies (BLRG) and steep spectrum radio quasars (SSRQ). On pc-scales PKS 0521-36 shows a knotty structure similar to misaligned AGN. The core dominance and the γ-ray properties are similar to those estimated for other SSRQ and BLRG detected in γ-rays, suggesting an intermediate viewing angle with respect to the observer. In thismore » context the flaring activity detected from this source by Fermi-Large Area Telescope between 2010 June and 2012 February is very intriguing. We discuss the γ-ray emission of this source in the framework of the structured jet scenario, comparing the spectral energy distribution (SED) of the flaring state in 2010 June with that of a low state. We present three alternative models corresponding to three different choices of the viewing angles θv = 6°, 15°, and 20°. We obtain a good fit for the first two cases, but the SED obtained with θv = 15° if observed at a small angle does not resemble that of a typical blazar since the synchrotron emission should dominate by a large factor (~100) the inverse Compton component. This suggests that a viewing angle between 6° and 15° is preferred, with the rapid variability observed during γ-ray flares favouring a smaller angle. However, we cannot rule out that PKS 0521-36 is the misaligned counterpart of a synchrotron-dominated blazar.« less
NASA Astrophysics Data System (ADS)
Jorge, Marco G.; Brennand, Tracy A.; Perkins, Andrew J.; Neudorf, Christina; Hillier, John K.; Cripps, Jonathan E.; Spagnolo, Matteo; Dinney, Meaghan; Storrar, Robert D.
2016-04-01
Mapper-dependent (subjective) differences in drumlin morphometry have received little attention even though over one-hundred thousand drumlins have been manually mapped and used to characterize drumlin morphometry and infer drumlin genesis, and several obstacles to objectivity in drumlin mapping can be identified. Due to uncertainty in drumlin genesis, drumlins remain putative morphogenetic landforms, yet still lack a complete single morphological definition. Additionally, post-formational degradation of relict subglacial landscapes challenges our ability: 1) to identify all drumlins in the landscape (some [potential] drumlins may be too degraded to be mapped and are thus excluded from the inventory), with implications for the analysis of field properties (e.g., spatial arrangement and autocorrelation); and 2) to accurately map the original footprint (i.e., shape and size). These issues (definitional ambiguity; degradation of original drumlin topography) are a problem for both manual and automated mapping. Automation is touted as the solution to the subjectivity of manual mapping, but the quality of any automated method directly depends on the quality of the operational definition (ruleset) it draws upon; if drumlin definitions are subjective (expert-dependent), so will be the automated algorithms relying on them. Additionally, recognizing highly degraded drumlins is, arguably, more difficult automatedly than manually (visually). Because a single morphologic definition is missing, mapping is expert-dependent. Therefore, quantifying the magnitude of inter-mapper differences is important for fully understanding the morphology of drumlins, constraining the robustness of drumlin morphometric inventories and assisting in the development of stricter operational definitions/mapping guidelines. We present the results of an experiment to quantify inter-mapper differences in mapped drumlin morphometry. All participants mapped 42 morphologically diverse drumlins in the Puget Lowland, WA at 2 spatial resolutions (1.8 m and 10.8 m cell size DEMs) in a GIS, using exactly the same base maps (analytical hillshade; semi-transparent elevation; contours) and informed by the same loose operational definition (e.g., drumlins delimited at their base by concave breaks in slope). Preliminary results (3 mappers) indicate that differences between manual mappers are substantial. For example, for the footprints mapped from the 10.8 m terrain data: average length ranges from 4603 m to 5454 m, and the mean absolute difference in length from 693 m to 1101 m; average elongation ratio (ER) ranges from 5.0 to 6.1; average footprint area ranges from 0.39 km2 to 0.50 km2.
Traffic Sign Recognition with Invariance to Lighting in Dual-Focal Active Camera System
NASA Astrophysics Data System (ADS)
Gu, Yanlei; Panahpour Tehrani, Mehrdad; Yendo, Tomohiro; Fujii, Toshiaki; Tanimoto, Masayuki
In this paper, we present an automatic vision-based traffic sign recognition system, which can detect and classify traffic signs at long distance under different lighting conditions. To realize this purpose, the traffic sign recognition is developed in an originally proposed dual-focal active camera system. In this system, a telephoto camera is equipped as an assistant of a wide angle camera. The telephoto camera can capture a high accuracy image for an object of interest in the view field of the wide angle camera. The image from the telephoto camera provides enough information for recognition when the accuracy of traffic sign is low from the wide angle camera. In the proposed system, the traffic sign detection and classification are processed separately for different images from the wide angle camera and telephoto camera. Besides, in order to detect traffic sign from complex background in different lighting conditions, we propose a type of color transformation which is invariant to light changing. This color transformation is conducted to highlight the pattern of traffic signs by reducing the complexity of background. Based on the color transformation, a multi-resolution detector with cascade mode is trained and used to locate traffic signs at low resolution in the image from the wide angle camera. After detection, the system actively captures a high accuracy image of each detected traffic sign by controlling the direction and exposure time of the telephoto camera based on the information from the wide angle camera. Moreover, in classification, a hierarchical classifier is constructed and used to recognize the detected traffic signs in the high accuracy image from the telephoto camera. Finally, based on the proposed system, a set of experiments in the domain of traffic sign recognition is presented. The experimental results demonstrate that the proposed system can effectively recognize traffic signs at low resolution in different lighting conditions.