3D elemental sensitive imaging using transmission X-ray microscopy.

PubMed

Liu, Yijin; Meirer, Florian; Wang, Junyue; Requena, Guillermo; Williams, Phillip; Nelson, Johanna; Mehta, Apurva; Andrews, Joy C; Pianetta, Piero

2012-09-01

Determination of the heterogeneous distribution of metals in alloy/battery/catalyst and biological materials is critical to fully characterize and/or evaluate the functionality of the materials. Using synchrotron-based transmission x-ray microscopy (TXM), it is now feasible to perform nanoscale-resolution imaging over a wide X-ray energy range covering the absorption edges of many elements; combining elemental sensitive imaging with determination of sample morphology. We present an efficient and reliable methodology to perform 3D elemental sensitive imaging with excellent sample penetration (tens of microns) using hard X-ray TXM. A sample of an Al-Si piston alloy is used to demonstrate the capability of the proposed method.

Generation of 2D Land Cover Maps for Urban Areas Using Decision Tree Classification

NASA Astrophysics Data System (ADS)

Höhle, J.

2014-09-01

A 2D land cover map can automatically and efficiently be generated from high-resolution multispectral aerial images. First, a digital surface model is produced and each cell of the elevation model is then supplemented with attributes. A decision tree classification is applied to extract map objects like buildings, roads, grassland, trees, hedges, and walls from such an "intelligent" point cloud. The decision tree is derived from training areas which borders are digitized on top of a false-colour orthoimage. The produced 2D land cover map with six classes is then subsequently refined by using image analysis techniques. The proposed methodology is described step by step. The classification, assessment, and refinement is carried out by the open source software "R"; the generation of the dense and accurate digital surface model by the "Match-T DSM" program of the Trimble Company. A practical example of a 2D land cover map generation is carried out. Images of a multispectral medium-format aerial camera covering an urban area in Switzerland are used. The assessment of the produced land cover map is based on class-wise stratified sampling where reference values of samples are determined by means of stereo-observations of false-colour stereopairs. The stratified statistical assessment of the produced land cover map with six classes and based on 91 points per class reveals a high thematic accuracy for classes "building" (99 %, 95 % CI: 95 %-100 %) and "road and parking lot" (90 %, 95 % CI: 83 %-95 %). Some other accuracy measures (overall accuracy, kappa value) and their 95 % confidence intervals are derived as well. The proposed methodology has a high potential for automation and fast processing and may be applied to other scenes and sensors.

Efficient method of image edge detection based on FSVM

NASA Astrophysics Data System (ADS)

Cai, Aiping; Xiong, Xiaomei

2013-07-01

For efficient object cover edge detection in digital images, this paper studied traditional methods and algorithm based on SVM. It analyzed Canny edge detection algorithm existed some pseudo-edge and poor anti-noise capability. In order to provide a reliable edge extraction method, propose a new detection algorithm based on FSVM. Which contains several steps: first, trains classify sample and gives the different membership function to different samples. Then, a new training sample is formed by increase the punishment some wrong sub-sample, and use the new FSVM classification model for train and test them. Finally the edges are extracted of the object image by using the model. Experimental result shows that good edge detection image will be obtained and adding noise experiments results show that this method has good anti-noise.

Extending a prototype knowledge- and object-based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

USGS Publications Warehouse

Strong, Laurence L.

2012-01-01

A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

Extending a prototype knowledge and object based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

USGS Publications Warehouse

Strong, Laurence L.

2012-01-01

A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

Impact Assessment of Mikania Micrantha on Land Cover and Maxent Modeling to Predict its Potential Invasion Sites

NASA Astrophysics Data System (ADS)

Baidar, T.; Shrestha, A. B.; Ranjit, R.; Adhikari, R.; Ghimire, S.; Shrestha, N.

2017-05-01

Mikania micrantha is one of the major invasive alien plant species in tropical moist forest regions of Asia including Nepal. Recently, this weed is spreading at an alarming rate in Chitwan National Park (CNP) and threatening biodiversity. This paper aims to assess the impacts of Mikania micrantha on different land cover and to predict potential invasion sites in CNP using Maxent model. Primary data for this were presence point coordinates and perceived Mikania micrantha cover collected through systematic random sampling technique. Rapideye image, Shuttle Radar Topographic Mission data and bioclimatic variables were acquired as secondary data. Mikania micrantha distribution maps were prepared by overlaying the presence points on image classified by object based image analysis. The overall accuracy of classification was 90 % with Kappa coefficient 0.848. A table depicting the number of sample points in each land cover with respective Mikania micrantha coverage was extracted from the distribution maps to show the impact. The riverine forest was found to be the most affected land cover with 85.98 % presence points and sal forest was found to be very less affected with only 17.02 % presence points. Maxent modeling predicted the areas near the river valley as the potential invasion sites with statistically significant Area Under the Receiver Operating Curve (AUC) value of 0.969. Maximum temperature of warmest month and annual precipitation were identified as the predictor variables that contribute the most to Mikania micrantha's potential distribution.

Floral diversity in desert ecosystems: Comparing field sampling to image analyses in assessing species cover

PubMed Central

2013-01-01

Background Developing a quick and reliable technique to estimate floral cover in deserts will assist in monitoring and management. The present attempt was to estimate plant cover in the UAE desert using both digital photography and field sampling. Digital photographs were correlated with field data to estimate floral cover in moderately (Al-Maha) and heavily (DDCR) grazed areas. The Kruskal-Wallis test was also used to assess compatibility between the two techniques within and across grazing intensities and soil substrates. Results Results showed that photographs could be a reliable technique within the sand dune substrate under moderate grazing (r = 0.69). The results were very poorly correlated (r =−0.24) or even inversely proportional (r =−0.48) when performed within DDCR. Overall, Chi-square values for Al-Maha and DDCR were not significant at P > 0.05, indicating similarities between the two methods. At the soil type level, the Kruskal-Wallis analysis was not significant (P > 0.05), except for gravel plains (P < 0.05). Across grazing intensities and soil substrates, the two techniques were in agreement in ranking most plant species, except for Lycium shawii. Conclusions Consequently, the present study has proven that digital photography could not be used reliably to asses floral cover, while further testing is required to support such claim. An image-based sampling approach of plant cover at the species level, across different grazing and substrate variations in desert ecosystems, has its uses, but results are to be cautiously interpreted. PMID:23758667

Stress Measurement by Geometrical Optics

NASA Technical Reports Server (NTRS)

Robinson, R. S.; Rossnagel, S. M.

1986-01-01

Fast, simple technique measures stresses in thin films. Sample disk bowed by stress into approximately spherical shape. Reflected image of disk magnified by amount related to curvature and, therefore, stress. Method requires sample substrate, such as cheap microscope cover slide, two mirrors, laser light beam, and screen.

ASSESSING THE ACCURACY OF SATELLITE-DERIVED LAND COVER CLASSIFICATION USING HISTORICAL AERIAL PHOTOGRAPHY DIGITAL ORTHOPHOTO QUADRANGLES, AND AIRBORNE VIDEO DATA

EPA Science Inventory

As the rapidly growing archives of satellite remote sensing imagery now span decades'worth of data, there is increasing interest in the study of long-term regional land cover change across multiple image dates. In most cases, however, temporally coincident ground sampled data are...

ASSESSING THE ACCURACY OF SATELLITE-DERIVED LAND COVER CLASSIFICATION USING HISTORICAL AERIAL PHOTOGRAPHY, DIGITAL ORTHOPHOTO QUADDRANGLES, AND AIRBORNE VIDEO DATA

EPA Science Inventory

As the rapidly growing archives of satellite remote sensing imagery now span decades'worth of data, there is increasing interest in the study of long-term regional land cover change across multiple image dates. In most cases, however, temporally coincident ground sampled data are...

ASSESSING THE ACCURACY OF SATELLITE-DERIVED LAND COVER CLASSIFICATION USING HISTORICAL AERIAL PHOTOGRAPHY, DIGITAL ORTHOPHOTO QUADRANGLES, AND AIRBORNE VIDEO DATA

EPA Science Inventory

As the rapidly growing archives of satellite remote sensing imagery now span decades' worth of data, there is increasing interest in the study of long-term regional land cover change across multiple image dates. In most cases, however, temporally coincident ground sampled data ar...

Optimal Subset Selection of Time-Series MODIS Images and Sample Data Transfer with Random Forests for Supervised Classification Modelling

PubMed Central

Zhou, Fuqun; Zhang, Aining

2016-01-01

Nowadays, various time-series Earth Observation data with multiple bands are freely available, such as Moderate Resolution Imaging Spectroradiometer (MODIS) datasets including 8-day composites from NASA, and 10-day composites from the Canada Centre for Remote Sensing (CCRS). It is challenging to efficiently use these time-series MODIS datasets for long-term environmental monitoring due to their vast volume and information redundancy. This challenge will be greater when Sentinel 2–3 data become available. Another challenge that researchers face is the lack of in-situ data for supervised modelling, especially for time-series data analysis. In this study, we attempt to tackle the two important issues with a case study of land cover mapping using CCRS 10-day MODIS composites with the help of Random Forests’ features: variable importance, outlier identification. The variable importance feature is used to analyze and select optimal subsets of time-series MODIS imagery for efficient land cover mapping, and the outlier identification feature is utilized for transferring sample data available from one year to an adjacent year for supervised classification modelling. The results of the case study of agricultural land cover classification at a regional scale show that using only about a half of the variables we can achieve land cover classification accuracy close to that generated using the full dataset. The proposed simple but effective solution of sample transferring could make supervised modelling possible for applications lacking sample data. PMID:27792152

Application of Deep Learning in GLOBELAND30-2010 Product Refinement

NASA Astrophysics Data System (ADS)

Liu, T.; Chen, X.

2018-04-01

GlobeLand30, as one of the best Global Land Cover (GLC) product at 30-m resolution, has been widely used in many research fields. Due to the significant spectral confusion among different land cover types and limited textual information of Landsat data, the overall accuracy of GlobeLand30 is about 80 %. Although such accuracy is much higher than most other global land cover products, it cannot satisfy various applications. There is still a great need of an effective method to improve the quality of GlobeLand30. The explosive high-resolution satellite images and remarkable performance of Deep Learning on image classification provide a new opportunity to refine GlobeLand30. However, the performance of deep leaning depends on quality and quantity of training samples as well as model training strategy. Therefore, this paper 1) proposed an automatic training sample generation method via Google earth to build a large training sample set; and 2) explore the best training strategy for land cover classification using GoogleNet (Inception V3), one of the most widely used deep learning network. The result shows that the fine-tuning from first layer of Inception V3 using rough large sample set is the best strategy. The retrained network was then applied in one selected area from Xi'an city as a case study of GlobeLand30 refinement. The experiment results indicate that the proposed approach with Deep Learning and google earth imagery is a promising solution for further improving accuracy of GlobeLand30.

Optimal Subset Selection of Time-Series MODIS Images and Sample Data Transfer with Random Forests for Supervised Classification Modelling.

PubMed

Zhou, Fuqun; Zhang, Aining

2016-10-25

Nowadays, various time-series Earth Observation data with multiple bands are freely available, such as Moderate Resolution Imaging Spectroradiometer (MODIS) datasets including 8-day composites from NASA, and 10-day composites from the Canada Centre for Remote Sensing (CCRS). It is challenging to efficiently use these time-series MODIS datasets for long-term environmental monitoring due to their vast volume and information redundancy. This challenge will be greater when Sentinel 2-3 data become available. Another challenge that researchers face is the lack of in-situ data for supervised modelling, especially for time-series data analysis. In this study, we attempt to tackle the two important issues with a case study of land cover mapping using CCRS 10-day MODIS composites with the help of Random Forests' features: variable importance, outlier identification. The variable importance feature is used to analyze and select optimal subsets of time-series MODIS imagery for efficient land cover mapping, and the outlier identification feature is utilized for transferring sample data available from one year to an adjacent year for supervised classification modelling. The results of the case study of agricultural land cover classification at a regional scale show that using only about a half of the variables we can achieve land cover classification accuracy close to that generated using the full dataset. The proposed simple but effective solution of sample transferring could make supervised modelling possible for applications lacking sample data.

Study on Big Database Construction and its Application of Sample Data Collected in CHINA'S First National Geographic Conditions Census Based on Remote Sensing Images

NASA Astrophysics Data System (ADS)

Cheng, T.; Zhou, X.; Jia, Y.; Yang, G.; Bai, J.

2018-04-01

In the project of China's First National Geographic Conditions Census, millions of sample data have been collected all over the country for interpreting land cover based on remote sensing images, the quantity of data files reaches more than 12,000,000 and has grown in the following project of National Geographic Conditions Monitoring. By now, using database such as Oracle for storing the big data is the most effective method. However, applicable method is more significant for sample data's management and application. This paper studies a database construction method which is based on relational database with distributed file system. The vector data and file data are saved in different physical location. The key issues and solution method are discussed. Based on this, it studies the application method of sample data and analyzes some kinds of using cases, which could lay the foundation for sample data's application. Particularly, sample data locating in Shaanxi province are selected for verifying the method. At the same time, it takes 10 first-level classes which defined in the land cover classification system for example, and analyzes the spatial distribution and density characteristics of all kinds of sample data. The results verify that the method of database construction which is based on relational database with distributed file system is very useful and applicative for sample data's searching, analyzing and promoted application. Furthermore, sample data collected in the project of China's First National Geographic Conditions Census could be useful in the earth observation and land cover's quality assessment.

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.

A multitemporal (1979-2009) land-use/land-cover dataset of the binational Santa Cruz Watershed

USGS Publications Warehouse

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.

Interactive boundary delineation of agricultural lands using graphics workstations

NASA Technical Reports Server (NTRS)

Cheng, Thomas D.; Angelici, Gary L.; Slye, Robert E.; Ma, Matt

1992-01-01

A review is presented of the computer-assisted stratification and sampling (CASS) system developed to delineate the boundaries of sample units for survey procedures. CASS stratifies the sampling units by land-cover and land-use type, employing image-processing software and hardware. This procedure generates coverage areas and the boundaries of stratified sampling units that are utilized for subsequent sampling procedures from which agricultural statistics are developed.

Sample project: establishing a global forest monitoring capability using multi-resolution and multi-temporal remotely sensed data sets

USGS Publications Warehouse

Hansen, Matt; Stehman, Steve; Loveland, Tom; Vogelmann, Jim; Cochrane, Mark

2009-01-01

Quantifying rates of forest-cover change is important for improved carbon accounting and climate change modeling, management of forestry and agricultural resources, and biodiversity monitoring. A practical solution to examining trends in forest cover change at global scale is to employ remotely sensed data. Satellite-based monitoring of forest cover can be implemented consistently across large regions at annual and inter-annual intervals. This research extends previous research on global forest-cover dynamics and land-cover change estimation to establish a robust, operational forest monitoring and assessment system. The approach integrates both MODIS and Landsat data to provide timely biome-scale forest change estimation. This is achieved by using annual MODIS change indicator maps to stratify biomes into low, medium and high change categories. Landsat image pairs can then be sampled within these strata and analyzed for estimating area of forest cleared.

Land cover mapping at Alkali Flat and Lake Lucero, White Sands, New Mexico, USA using multi-temporal and multi-spectral remote sensing data

NASA Astrophysics Data System (ADS)

Ghrefat, Habes A.; Goodell, Philip C.

2011-08-01

The goal of this research is to map land cover patterns and to detect changes that occurred at Alkali Flat and Lake Lucero, White Sands using multispectral Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Imager (ALI), and hyperspectral Hyperion and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data. The other objectives of this study were: (1) to evaluate the information dimensionality limits of Landsat 7 ETM+, ASTER, ALI, Hyperion, and AVIRIS data with respect to signal-to-noise and spectral resolution, (2) to determine the spatial distribution and fractional abundances of land cover endmembers, and (3) to check ground correspondence with satellite data. A better understanding of the spatial and spectral resolution of these sensors, optimum spectral bands and their information contents, appropriate image processing methods, spectral signatures of land cover classes, and atmospheric effects are needed to our ability to detect and map minerals from space. Image spectra were validated using samples collected from various localities across Alkali Flat and Lake Lucero. These samples were measured in the laboratory using VNIR-SWIR (0.4-2.5 μm) spectra and X-ray Diffraction (XRD) method. Dry gypsum deposits, wet gypsum deposits, standing water, green vegetation, and clastic alluvial sediments dominated by mixtures of ferric iron (ferricrete) and calcite were identified in the study area using Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), and n-D Visualization. The results of MNF confirm that AVIRIS and Hyperion data have higher information dimensionality thresholds exceeding the number of available bands of Landsat 7 ETM+, ASTER, and ALI data. ASTER and ALI data can be a reasonable alternative to AVIRIS and Hyperion data for the purpose of monitoring land cover, hydrology and sedimentation in the basin. The spectral unmixing analysis and dimensionality eigen analysis between the various datasets helped to uncover the most optimum spatial-spectral-temporal and radiometric-resolution sensor characteristics for remote sensing based on monitoring of seasonal land cover, surface water, groundwater, and alluvial sediment input changes within the basin. The results demonstrated good agreement between ground truth data and XRD analysis of samples, and the results of Matched Filtering (MF) mapping method.

Sprinkle Test by Phoenix's Robotic Arm (Movie)

NASA Technical Reports Server (NTRS)

2008-01-01

NASA's Phoenix Mars Lander used its Robotic Arm during the mission's 15th Martian day since landing (June 9, 2008) to test a 'sprinkle' method for delivering small samples of soil to instruments on the lander deck. This sequence of four images from the spacecraft's Surface Stereo Imager covers a period of 20 minutes from beginning to end of the activity.

In the single delivery of a soil sample to a Phoenix instrument prior to this test, the arm brought the scooped up soil over the instrument's opened door and turned over the scoop to release the soil. The sprinkle technique, by contrast, holds the scoop at a steady angle and vibrates the scoop by running the motorized rasp located beneath the scoop. This gently jostles some material out of the scoop to the target below.

For this test, the target was near the upper end the cover of the Microscopy, Electrochemistry and Conductivity Analyzer instrument suite, or MECA. The cover is 20 centimeters (7.9 inches) across. The scoop is about 8.5 centimeters (3.3 inches) across.

Based on the test's success in delivering a small quantity and fine-size particles, the Phoenix team plans to use the sprinkle method for delivering samples to MECA and to the Thermal and Evolved-Gas Analyzer, or TEGA. The next planned delivery is to MECA's Optical Microscope, via the port in the MECA cover visible at the bottom of these images.

The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

Flexible sample environment for high resolution neutron imaging at high temperatures in controlled atmosphere

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

Makowska, Małgorzata G.; Theil Kuhn, Luise; Cleemann, Lars N.

In high material penetration by neutrons allows for experiments using sophisticated sample environments providing complex conditions. Thus, neutron imaging holds potential for performing in situ nondestructive measurements on large samples or even full technological systems, which are not possible with any other technique. Our paper presents a new sample environment for in situ high resolution neutron imaging experiments at temperatures from room temperature up to 1100 degrees C and/or using controllable flow of reactive atmospheres. The design also offers the possibility to directly combine imaging with diffraction measurements. Design, special features, and specification of the furnace are described. In addition,more » examples of experiments successfully performed at various neutron facilities with the furnace, as well as examples of possible applications are presented. Our work covers a broad field of research from fundamental to technological investigations of various types of materials and components.« less

Flexible sample environment for high resolution neutron imaging at high temperatures in controlled atmosphere

DOE PAGES

Makowska, Małgorzata G.; Theil Kuhn, Luise; Cleemann, Lars N.; ...

2015-12-17

In high material penetration by neutrons allows for experiments using sophisticated sample environments providing complex conditions. Thus, neutron imaging holds potential for performing in situ nondestructive measurements on large samples or even full technological systems, which are not possible with any other technique. Our paper presents a new sample environment for in situ high resolution neutron imaging experiments at temperatures from room temperature up to 1100 degrees C and/or using controllable flow of reactive atmospheres. The design also offers the possibility to directly combine imaging with diffraction measurements. Design, special features, and specification of the furnace are described. In addition,more » examples of experiments successfully performed at various neutron facilities with the furnace, as well as examples of possible applications are presented. Our work covers a broad field of research from fundamental to technological investigations of various types of materials and components.« less

Theory on data processing and instrumentation. [remote sensing

NASA Technical Reports Server (NTRS)

Billingsley, F. C.

1978-01-01

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

Mapping Land Cover Types in Amazon Basin Using 1km JERS-1 Mosaic

NASA Technical Reports Server (NTRS)

Saatchi, Sassan S.; Nelson, Bruce; Podest, Erika; Holt, John

2000-01-01

In this paper, the 100 meter JERS-1 Amazon mosaic image was used in a new classifier to generate a I km resolution land cover map. The inputs to the classifier were 1 km resolution mean backscatter and seven first order texture measures derived from the 100 m data by using a 10 x 10 independent sampling window. The classification approach included two interdependent stages: 1) a supervised maximum a posteriori Bayesian approach to classify the mean backscatter image into 5 general land cover categories of forest, savannah, inundated, white sand, and anthropogenic vegetation classes, and 2) a texture measure decision rule approach to further discriminate subcategory classes based on taxonomic information and biomass levels. Fourteen classes were successfully separated at 1 km scale. The results were verified by examining the accuracy of the approach by comparison with the IBGE and the AVHRR 1 km resolution land cover maps.

Atomic force microscopy contact, tapping, and jumping modes for imaging biological samples in liquids

NASA Astrophysics Data System (ADS)

Moreno-Herrero, F.; Colchero, J.; Gómez-Herrero, J.; Baró, A. M.

2004-03-01

The capabilities of the atomic force microscope for imaging biomolecules under physiological conditions has been systematically investigated. Contact, dynamic, and jumping modes have been applied to four different biological systems: DNA, purple membrane, Alzheimer paired helical filaments, and the bacteriophage φ29. These samples have been selected to cover a wide variety of biological systems in terms of sizes and substrate contact area, which make them very appropriate for the type of comparative studies carried out in the present work. Although dynamic mode atomic force microscopy is clearly the best choice for imaging soft samples in air, in liquids there is not a leading technique. In liquids, the most appropriate imaging mode depends on the sample characteristics and preparation methods. Contact or dynamic modes are the best choices for imaging molecular assemblies arranged as crystals such as the purple membrane. In this case, the advantage of image acquisition speed predominates over the disadvantage of high lateral or normal force. For imaging individual macromolecules, which are weakly bonded to the substrate, lateral and normal forces are the relevant factors, and hence the jumping mode, an imaging mode which minimizes lateral and normal forces, is preferable to other imaging modes.

Exploring geo-tagged photos for land cover validation with deep learning

NASA Astrophysics Data System (ADS)

Xing, Hanfa; Meng, Yuan; Wang, Zixuan; Fan, Kaixuan; Hou, Dongyang

2018-07-01

Land cover validation plays an important role in the process of generating and distributing land cover thematic maps, which is usually implemented by high cost of sample interpretation with remotely sensed images or field survey. With an increasing availability of geo-tagged landscape photos, the automatic photo recognition methodologies, e.g., deep learning, can be effectively utilised for land cover applications. However, they have hardly been utilised in validation processes, as challenges remain in sample selection and classification for highly heterogeneous photos. This study proposed an approach to employ geo-tagged photos for land cover validation by using the deep learning technology. The approach first identified photos automatically based on the VGG-16 network. Then, samples for validation were selected and further classified by considering photos distribution and classification probabilities. The implementations were conducted for the validation of the GlobeLand30 land cover product in a heterogeneous area, western California. Experimental results represented promises in land cover validation, given that GlobeLand30 showed an overall accuracy of 83.80% with classified samples, which was close to the validation result of 80.45% based on visual interpretation. Additionally, the performances of deep learning based on ResNet-50 and AlexNet were also quantified, revealing no substantial differences in final validation results. The proposed approach ensures geo-tagged photo quality, and supports the sample classification strategy by considering photo distribution, with accuracy improvement from 72.07% to 79.33% compared with solely considering the single nearest photo. Consequently, the presented approach proves the feasibility of deep learning technology on land cover information identification of geo-tagged photos, and has a great potential to support and improve the efficiency of land cover validation.

Ground-Cover Measurements: Assessing Correlation Among Aerial and Ground-Based Methods

NASA Astrophysics Data System (ADS)

Booth, D. Terrance; Cox, Samuel E.; Meikle, Tim; Zuuring, Hans R.

2008-12-01

Wyoming’s Green Mountain Common Allotment is public land providing livestock forage, wildlife habitat, and unfenced solitude, amid other ecological services. It is also the center of ongoing debate over USDI Bureau of Land Management’s (BLM) adjudication of land uses. Monitoring resource use is a BLM responsibility, but conventional monitoring is inadequate for the vast areas encompassed in this and other public-land units. New monitoring methods are needed that will reduce monitoring costs. An understanding of data-set relationships among old and new methods is also needed. This study compared two conventional methods with two remote sensing methods using images captured from two meters and 100 meters above ground level from a camera stand (a ground, image-based method) and a light airplane (an aerial, image-based method). Image analysis used SamplePoint or VegMeasure software. Aerial methods allowed for increased sampling intensity at low cost relative to the time and travel required by ground methods. Costs to acquire the aerial imagery and measure ground cover on 162 aerial samples representing 9000 ha were less than 3000. The four highest correlations among data sets for bare ground—the ground-cover characteristic yielding the highest correlations (r)—ranged from 0.76 to 0.85 and included ground with ground, ground with aerial, and aerial with aerial data-set associations. We conclude that our aerial surveys are a cost-effective monitoring method, that ground with aerial data-set correlations can be equal to, or greater than those among ground-based data sets, and that bare ground should continue to be investigated and tested for use as a key indicator of rangeland health.

Subgingival calculus imaging based on swept-source optical coherence tomography

NASA Astrophysics Data System (ADS)

Hsieh, Yao-Sheng; Ho, Yi-Ching; Lee, Shyh-Yuan; Lu, Chih-Wei; Jiang, Cho-Pei; Chuang, Ching-Cheng; Wang, Chun-Yang; Sun, Chia-Wei

2011-07-01

We characterized and imaged dental calculus using swept-source optical coherence tomography (SS-OCT). The refractive indices of enamel, dentin, cementum, and calculus were measured as 1.625 +/- 0.024, 1.534 +/- 0.029, 1.570 +/- 0.021, and 2.097 +/- 0.094, respectively. Dental calculus leads strong scattering properties, and thus, the region can be identified from enamel with SS-OCT imaging. An extracted human tooth with calculus is covered with gingiva tissue as an in vitro sample for tomographic imaging.

Dental calculus image based on optical coherence tomography

NASA Astrophysics Data System (ADS)

Hsieh, Yao-Sheng; Ho, Yi-Ching; Lee, Shyh-Yuan; Chuang, Ching-Cheng; Wang, Chun-Yang; Sun, Chia-Wei

2011-03-01

In this study, the dental calculus was characterized and imaged by means of swept-source optical coherence tomography (SSOCT). The refractive indices of enamel, dentin, cementum and calculus were measured as 1.625+/-0.024, 1.534+/-0.029, 1.570+/-0.021 and 1.896+/-0.085, respectively. The dental calculus lead strong scattering property and thus the region can be identified under enamel with SSOCT imaging. An extracted human tooth with calculus was covered by gingiva tissue as in vitro sample for SSOCT imaging.

Nonlinear interferometric vibrational imaging of biological tissue

NASA Astrophysics Data System (ADS)

Jiang, Zhi; Marks, Daniel L.; Geddes, Joseph B., III; Boppart, Stephen A.

2008-02-01

We demonstrate imaging with the technique of nonlinear interferometric vibrational imaging (NIVI). Experimental images using this instrumentation and method have been acquired from both phantom and biological tissues. In our system, coherent anti-Stokes Raman scattering (CARS) signals are detected by spectral interferometry, which is able to fully restore high resolution Raman spectrum on each focal spot of a sample covering multiple Raman bands using broadband pump and Stokes laser beams. Spectral-domain detection has been demonstrated and allows for a significant increase in image acquiring speed, in signal-to-noise, and in interferometric signal stability.

Fourier Plane Image Combination by Feathering

NASA Astrophysics Data System (ADS)

Cotton, W. D.

2017-09-01

Astronomical objects frequently exhibit structure over a wide range of scales whereas many telescopes, especially interferometer arrays, only sample a limited range of spatial scales. To properly image these objects, images from a set of instruments covering the range of scales may be needed. These images then must be combined in a manner to recover all spatial scales. This paper describes the feathering technique for image combination in the Fourier transform plane. Implementations in several packages are discussed and example combinations of single dish and interferometric observations of both simulated and celestial radio emission are given.

Method and apparatus for implementing material thermal property measurement by flash thermal imaging

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

Sun, Jiangang

A method and apparatus are provided for implementing measurement of material thermal properties including measurement of thermal effusivity of a coating and/or film or a bulk material of uniform property. The test apparatus includes an infrared camera, a data acquisition and processing computer coupled to the infrared camera for acquiring and processing thermal image data, a flash lamp providing an input of heat onto the surface of a two-layer sample with an enhanced optical filter covering the flash lamp attenuating an entire infrared wavelength range with a series of thermal images is taken of the surface of the two-layer sample.

Robust, Globally Consistent, and Fully-automatic Multi-image Registration and Montage Synthesis for 3-D Multi-channel Images

PubMed Central

Tsai, Chia-Ling; Lister, James P.; Bjornsson, Christopher J; Smith, Karen; Shain, William; Barnes, Carol A.; Roysam, Badrinath

2013-01-01

The need to map regions of brain tissue that are much wider than the field of view of the microscope arises frequently. One common approach is to collect a series of overlapping partial views, and align them to synthesize a montage covering the entire region of interest. We present a method that advances this approach in multiple ways. Our method (1) produces a globally consistent joint registration of an unorganized collection of 3-D multi-channel images with or without stage micrometer data; (2) produces accurate registrations withstanding changes in scale, rotation, translation and shear by using a 3-D affine transformation model; (3) achieves complete automation, and does not require any parameter settings; (4) handles low and variable overlaps (5 – 15%) between adjacent images, minimizing the number of images required to cover a tissue region; (5) has the self-diagnostic ability to recognize registration failures instead of delivering incorrect results; (6) can handle a broad range of biological images by exploiting generic alignment cues from multiple fluorescence channels without requiring segmentation; and (7) is computationally efficient enough to run on desktop computers regardless of the number of images. The algorithm was tested with several tissue samples of at least 50 image tiles, involving over 5,000 image pairs. It correctly registered all image pairs with an overlap greater than 7%, correctly recognized all failures, and successfully joint-registered all images for all tissue samples studied. This algorithm is disseminated freely to the community as included with the FARSIGHT toolkit for microscopy (www.farsight-toolkit.org). PMID:21361958

Scanning electron microscopy of high-pressure-frozen sea urchin embryos.

PubMed

Walther, P; Chen, Y; Malecki, M; Zoran, S L; Schatten, G P; Pawley, J B

1993-12-01

High-pressure-freezing permits direct cryo-fixation of sea urchin embryos having a defined developmental state without the formation of large ice crystals. We have investigated preparation protocols for observing high-pressure-frozen and freeze-fractured samples in the scanning electron microscope. High-pressure-freezing was superior to other freezing protocols, because the whole bulk sample was reasonably well frozen and the overall three-dimensional shape of the embryos was well preserved. The samples were either dehydrated by freeze-substitution and critical-point-drying, or imaged in the partially hydrated state, using a cold stage in the SEM. During freeze-substitution the samples were stabilized by fixatives. The disadvantage of this method was that shrinking and extraction effects, caused by the removal of the water, could not be avoided. These disadvantages were avoided when the sample was imaged in the frozen-hydrated state using a cold-stage in the SEM. This would be the method of choice for morphometric studies. Frozen-hydrated samples, however, were very beam sensitive and many structures remained covered by the ice and were not visible. Frozen-hydrated samples were partially freeze-dried to make visible additional structures that had been covered by ice. However, this method also caused drying artifacts when too much water was removed.

An assessment of the resolution limitation due to radiation-damage in X-ray diffraction microscopy

DOE PAGES

Howells, M. R.; Beetz, T.; Chapman, H. N.; ...

2008-11-17

X-ray diffraction microscopy (XDM) is a new form of x-ray imaging that is being practiced at several third-generation synchrotron-radiation x-ray facilities. Nine years have elapsed since the technique was first introduced and it has made rapid progress in demonstrating high-resolution three-dimensional imaging and promises few-nm resolution with much larger samples than can be imaged in the transmission electron microscope. Both life- and materials-science applications of XDM are intended, and it is expected that the principal limitation to resolution will be radiation damage for life science and the coherent power of available x-ray sources for material science. In this paper wemore » address the question of the role of radiation damage. We use a statistical analysis based on the so-called "dose fractionation theorem" of Hegerl and Hoppe to calculate the dose needed to make an image of a single life-science sample by XDM with a given resolution. We find that for simply-shaped objects the needed dose scales with the inverse fourth power of the resolution and present experimental evidence to support this finding. To determine the maximum tolerable dose we have assembled a number of data taken from the literature plus some measurements of our own which cover ranges of resolution that are not well covered otherwise. The conclusion of this study is that, based on the natural contrast between protein and water and "Rose-criterion" image quality, one should be able to image a frozen-hydrated biological sample using XDM at a resolution of about 10 nm.« less

MODIS Snow and Ice Production

NASA Technical Reports Server (NTRS)

Hall, Dorthoy K.; Hoser, Paul (Technical Monitor)

2002-01-01

Daily, global snow cover maps, and sea ice cover and sea ice surface temperature (IST) maps are derived from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS), are available at no cost through the National Snow and Ice Data Center (NSIDC). Included on this CD-ROM are samples of the MODIS snow and ice products. In addition, an animation, done by the Scientific Visualization studio at Goddard Space Flight Center, is also included.

Possible Layers on Floor of Suzhi Crater

NASA Image and Video Library

2016-12-14

This image shows the floor of Suzhi Crater, an approximately 25-kilometer diameter impact crater located northeast of Hellas Planitia. The crater floor is mostly covered by dark-toned deposits; however some patches of the underlying light-toned bedrock are now exposed, like in this Context Camera image. This enhanced-color infrared image shows a close up of the exposed bedrock on the floor of the crater. Here we can see the lighter-toned bedrock partially covered up by darker-toned bedrock and a few wind-blown bedforms. The lighter-toned bedrock appears to lie over yet another type of bedrock in our image, which appears to be yellowish and heavily fractured. What complex tale of Martian geologic and climate history might these rocks tell us if we were able to sample them in person? Perhaps, one day we'll know. The University of Arizona, Tucson, operates HiRISE, which was http://photojournal.jpl.nasa.gov/catalog/PIA21273

Eating and Exercising: Nebraska Adolescents' Attitudes and Behaviors. Technical Report 25.

ERIC Educational Resources Information Center

Newman, Ian M.

This report describes selected eating and exercise patterns among a sample of 2,237 Nebraska youth in grades 9-12 selected from a random sample of 24 junior and senior high schools. The eating patterns reported cover food selection, body image, weight management, and weight loss methods. The exercise patterns relate to the frequency of…

Publications | Transportation Research | NREL

Science.gov Websites

Overview Thumbnail image of publication cover Sustainable TransportationPDF This overview fact sheet image of publication cover Alternative Fuels Data CenterPDF Thumbnail image of publication cover Clean CitiesPDF Thumbnail image of publication cover Fleet ToolsPDF Thumbnail image of publication cover Fuels

Subgingival calculus imaging based on swept-source optical coherence tomography.

PubMed

Hsieh, Yao-Sheng; Ho, Yi-Ching; Lee, Shyh-Yuan; Lu, Chih-Wei; Jiang, Cho-Pei; Chuang, Ching-Cheng; Wang, Chun-Yang; Sun, Chia-Wei

2011-07-01

We characterized and imaged dental calculus using swept-source optical coherence tomography (SS-OCT). The refractive indices of enamel, dentin, cementum, and calculus were measured as 1.625 ± 0.024, 1.534 ± 0.029, 1.570 ± 0.021, and 2.097 ± 0.094, respectively. Dental calculus leads strong scattering properties, and thus, the region can be identified from enamel with SS-OCT imaging. An extracted human tooth with calculus is covered with gingiva tissue as an in vitro sample for tomographic imaging.

A novel weighted-direction color interpolation

NASA Astrophysics Data System (ADS)

Tao, Jin-you; Yang, Jianfeng; Xue, Bin; Liang, Xiaofen; Qi, Yong-hong; Wang, Feng

2013-08-01

A digital camera capture images by covering the sensor surface with a color filter array (CFA), only get a color sample at pixel location. Demosaicking is a process by estimating the missing color components of each pixel to get a full resolution image. In this paper, a new algorithm based on edge adaptive and different weighting factors is proposed. Our method can effectively suppress undesirable artifacts. Experimental results based on Kodak images show that the proposed algorithm obtain higher quality images compared to other methods in numerical and visual aspects.

Food quality assessment by NIR hyperspectral imaging

NASA Astrophysics Data System (ADS)

Whitworth, Martin B.; Millar, Samuel J.; Chau, Astor

2010-04-01

Near infrared reflectance (NIR) spectroscopy is well established in the food industry for rapid compositional analysis of bulk samples. NIR hyperspectral imaging provides new opportunities to measure the spatial distribution of components such as moisture and fat, and to identify and measure specific regions of composite samples. An NIR hyperspectral imaging system has been constructed for food research applications, incorporating a SWIR camera with a cooled 14 bit HgCdTe detector and N25E spectrograph (Specim Ltd, Finland). Samples are scanned in a pushbroom mode using a motorised stage. The system has a spectral resolution of 256 pixels covering a range of 970-2500 nm and a spatial resolution of 320 pixels covering a swathe adjustable from 8 to 300 mm. Images are acquired at a rate of up to 100 lines s-1, enabling samples to be scanned within a few seconds. Data are captured using SpectralCube software (Specim) and analysed using ENVI and IDL (ITT Visual Information Solutions). Several food applications are presented. The strength of individual absorbance bands enables the distribution of particular components to be assessed. Examples are shown for detection of added gluten in wheat flour and to study the effect of processing conditions on fat distribution in chips/French fries. More detailed quantitative calibrations have been developed to study evolution of the moisture distribution in baguettes during storage at different humidities, to assess freshness of fish using measurements of whole cod and fillets, and for prediction of beef quality by identification and separate measurement of lean and fat regions.

The Land-Use and Land-Cover Change Analysis in Beijing Huairou in Last Ten Years

NASA Astrophysics Data System (ADS)

Zhao, Q.; Liu, G.; Tu, J.; Wang, Z.

2018-04-01

With eCognition software, the sample-based object-oriented classification method is used. Remote sensing images in Huairou district of Beijing had been classified using remote sensing images of last ten years. According to the results of image processing, the land use types in Huairou district of Beijing were analyzed in the past ten years, and the changes of land use types in Huairou district were obtained, and the reasons for its occurrence were analyzed.

Image Analysis for Facility Siting: a Comparison of Lowand High-altitude Image Interpretability for Land Use/land Cover Mapping

NASA Technical Reports Server (NTRS)

Borella, H. M.; Estes, J. E.; Ezra, C. E.; Scepan, J.; Tinney, L. R.

1982-01-01

For two test sites in Pennsylvania the interpretability of commercially acquired low-altitude and existing high-altitude aerial photography are documented in terms of time, costs, and accuracy for Anderson Level II land use/land cover mapping. Information extracted from the imagery is to be used in the evaluation process for siting energy facilities. Land use/land cover maps were drawn at 1:24,000 scale using commercially flown color infrared photography obtained from the United States Geological Surveys' EROS Data Center. Detailed accuracy assessment of the maps generated by manual image analysis was accomplished employing a stratified unaligned adequate class representation. Both 'area-weighted' and 'by-class' accuracies were documented and field-verified. A discrepancy map was also drawn to illustrate differences in classifications between the two map scales. Results show that the 1:24,000 scale map set was more accurate (99% to 94% area-weighted) than the 1:62,500 scale set, especially when sampled by class (96% to 66%). The 1:24,000 scale maps were also more time-consuming and costly to produce, due mainly to higher image acquisition costs.

Delivery of cosmetic covers to persons with transtibial and transfemoral amputations in an outpatient prosthetic practice.

PubMed

Highsmith, M Jason; Kahle, Jason T; Knight, Molly; Olk-Szost, Ayla; Boyd, Melinda; Miro, Rebecca M

2016-06-01

Limb loss negatively impacts body image to the extent that functional activity and societal participation are affected. Scientific literature is lacking on the subject of cosmetic covering for prostheses and the rate of cosmetic cover utilization by cover type, gender, amputation level, and type of healthcare reimbursement. To describe the delivery of cosmetic covers in lower limb prostheses in a sample of people with lower extremity amputation. Cross-sectional design Patient records from an outpatient practice were reviewed for people who received a transtibial or transfemoral prosthesis within a selected 2-year period. A total of 294 records were reviewed. Regardless of the amputation level, females were significantly (p ≤ 0.05) more likely to receive a cover. Type of insurance did not affect whether or not a cover was used, but Medicare reimbursed more pull-up skin covers. There were differences regarding cosmetic cover delivery based on gender, and Medicare reimbursed for more pull-up skin covers at the transtibial level than other reimbursors did. This analysis was conducted in a warm, tropical geographic region of the United States. Results may differ in other parts of the world based on many factors including climate and local views of body image and disability. Cosmetic covering rates are clinically relevant because they provide insight into which gender is utilizing more cosmetic covers. Furthermore, it can be determined which type of covers are being utilized with greater frequency and which insurance type is providing more coverage for them. © The International Society for Prosthetics and Orthotics 2015.

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

Makowska, Małgorzata G., E-mail: malg@dtu.dk; European Spallation Source ESS AB, P.O. Box 176, SE-221 00 Lund; Theil Kuhn, Luise

High material penetration by neutrons allows for experiments using sophisticated sample environments providing complex conditions. Thus, neutron imaging holds potential for performing in situ nondestructive measurements on large samples or even full technological systems, which are not possible with any other technique. This paper presents a new sample environment for in situ high resolution neutron imaging experiments at temperatures from room temperature up to 1100 °C and/or using controllable flow of reactive atmospheres. The design also offers the possibility to directly combine imaging with diffraction measurements. Design, special features, and specification of the furnace are described. In addition, examples of experimentsmore » successfully performed at various neutron facilities with the furnace, as well as examples of possible applications are presented. This covers a broad field of research from fundamental to technological investigations of various types of materials and components.« less

Land-Cover Trends of the Southern California Mountains Ecoregion

USGS Publications Warehouse

Soulard, Christopher E.; Raumann, Christian G.; Wilson, Tamara S.

2007-01-01

This report presents an assessment of land-use and land-cover (LU/LC) change in the Southern California Mountains ecoregion for the period 1973-2001. The Southern California Mountains is one of 84 Level-III ecoregions as defined by the U.S. Environmental Protection Agency (EPA). Ecoregions have served as a spatial framework for environmental resource management, denoting areas that contain a geographically distinct assemblage of biotic and abiotic phenomena including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The established Land Cover Trends methodology generates estimates of change for ecoregions using a probability sampling approach and change-detection analysis of thematic land-cover images derived from Landsat satellite imagery.

Reviews CD-ROM: Scientific American—The Amateur Scientist 3.0 Book: The New Resourceful Physics Teacher Equipment: DynaKar Book: The Fundamentals of Imaging Book: Teaching Secondary Physics Book: Novel Materials and Smart Applications Equipment: Cryptic disk Web Watch

NASA Astrophysics Data System (ADS)

2012-05-01

WE RECOMMEND Scientific American—The Amateur Scientist 3.0 Article collection spans the decades DynaKar DynaKar drives dynamics experiments The Fundamentals of Imaging Author covers whole imaging spectrum Teaching Secondary Physics Effective teaching is all in the approach Novel Materials and Smart Applications/Novel materials sample pack Resources kit samples smart materials WORTH A LOOK Cryptic disk Metal disk spins life into discussions about energy, surfaces and kinetics HANDLE WITH CARE The New Resourceful Physics Teacher Book brings creativity to physics WEB WATCH Apps for tablets and smartphones can aid physics teaching

A Time-Series of Surface Oil Distribution Detected by Satellite SAR During the Deepwater Horizon Blowout

NASA Astrophysics Data System (ADS)

MacDonald, I. R.; Garcia-Pineda, O. G.; Solow, A.; Daneshgar, S.; Beet, A.

2013-12-01

Oil discharged as a result of the Deepwater Horizon disaster was detected on the surface of the Gulf of Mexico by synthetic aperture radar satellites from 25 April 2010 until 4 August 2010. SAR images were not restricted by daylight or cloud-cover. Distribution of this material is a tracer for potential environmental impacts and an indicator of impact mitigation due to response efforts and physical forcing factors. We used a texture classifying neural network algorithm for semi-supervised processing of 176 SAR images from the ENVISAT, RADARSAT I, and COSMO-SKYMED satellites. This yielded an estimate the proportion of oil-covered water within the region sampled by each image with a nominal resolution of 10,000 sq m (100m pixels), which was compiled as a 5-km equal area grid covering the northern Gulf of Mexico. Few images covered the entire impact area, so analysis was required to compile a regular time-series of the oil cover. A Gaussian kernel using a bandwidth of 2 d was used to estimate oil cover percent in each grid at noon and midnight throughout the interval. Variance and confidence intervals were calculated for each grid and for the global 12-h totals. Results animated across the impact region show the spread of oil under the influence of physical factors. Oil cover reached an early peak of 17032.26 sq km (sd 460.077) on 18 May, decreasing to 27% of this total on 4 June, following by sharp increase to an overall maximum of 18424.56 sq km (sd 424.726) on 19 June. There was a significant negative correlation between average wind stress and the total area of oil cover throughout the time-series. Correlation between response efforts including aerial and subsurface application of dispersants and burning of gathered oil was negative, positive, or indeterminate at different time segments during the event. Daily totals for oil-covered surface waters of the Gulf of Mexico during 25 April - 9 August 2010 with upper and lower 0.95 confidence limits on estimate. (No oil visible after 4 August.)

Sedimentology of Martian Gravels from Mardi Twilight Imaging: Techniques

NASA Technical Reports Server (NTRS)

Garvin, James B.; Malin, Michael C.; Minitti, M. E.

2014-01-01

Quantitative sedimentologic analysis of gravel surfaces dominated by pebble-sized clasts has been employed in an effort to untangle aspects of the provenance of surface sediments on Mars using Curiosity's MARDI nadir-viewing camera operated at twilight Images have been systematically acquired since sol 310 providing a representative sample of gravel-covered surfaces since the rover departed the Shaler region. The MARDI Twilight imaging dataset offers approximately 1 millimeter spatial resolution (slightly out of focus) for patches beneath the rover that cover just under 1 m2 in area, under illumination that makes clast size and inter-clast spacing analysis relatively straightforward using semi- automated codes developed for use with nadir images. Twilight images are utilized for these analyses in order to reduce light scattering off dust deposited on the front MARDI lens element during the terminal stages of Curiosity's entry, descent and landing. Such scattering is worse when imaging bright, directly-illuminated surfaces; twilight imaging times yield diffusely-illuminated surfaces that improve the clarity of the resulting MARDI product. Twilight images are obtained between 10-30 minutes after local sunset, governed by the timing of the end of the no-heat window for the camera. Techniques were also utilized to examine data terrestrial locations (the Kau Desert in Hawaii and near Askja Caldera in Iceland). Methods employed include log hyperbolic size distribution (LHD) analysis and Delauney Triangulation (DT) inter-clast spacing analysis. This work extends the initial results reported in Yingst et al., that covered the initial landing zone, to the Rapid-Transit Route (RTR) towards Mount Sharp.

Inlet Cover On the Curiosity Rover

NASA Image and Video Library

2018-06-04

The drill bit of NASA's Curiosity Mars rover over one of the sample inlets on the rover's deck. The inlets lead to Curiosity's onboard laboratories. This image was taken on Sol 2068 by the rover's Mast Camera (Mastcam). https://photojournal.jpl.nasa.gov/catalog/PIA22327

Phase Tomography Reconstructed by 3D TIE in Hard X-ray Microscope

NASA Astrophysics Data System (ADS)

Yin, Gung-Chian; Chen, Fu-Rong; Pyun, Ahram; Je, Jung Ho; Hwu, Yeukuang; Liang, Keng S.

2007-01-01

X-ray phase tomography and phase imaging are promising ways of investigation on low Z material. A polymer blend of PE/PS sample was used to test the 3D phase retrieval method in the parallel beam illuminated microscope. Because the polymer sample is thick, the phase retardation is quite mixed and the image can not be distinguished when the 2D transport intensity equation (TIE) is applied. In this study, we have provided a different approach for solving the phase in three dimensions for thick sample. Our method involves integration of 3D TIE/Fourier slice theorem for solving thick phase sample. In our experiment, eight sets of de-focal series image data sets were recorded covering the angular range of 0 to 180 degree. Only three set of image cubes were used in 3D TIE equation for solving the phase tomography. The phase contrast of the polymer blend in 3D is obviously enhanced, and the two different groups of polymer blend can be distinguished in the phase tomography.

High-throughput Raman chemical imaging for evaluating food safety and quality

NASA Astrophysics Data System (ADS)

Qin, Jianwei; Chao, Kuanglin; Kim, Moon S.

2014-05-01

A line-scan hyperspectral system was developed to enable Raman chemical imaging for large sample areas. A custom-designed 785 nm line-laser based on a scanning mirror serves as an excitation source. A 45° dichroic beamsplitter reflects the laser light to form a 24 cm x 1 mm excitation line normally incident on the sample surface. Raman signals along the laser line are collected by a detection module consisting of a dispersive imaging spectrograph and a CCD camera. A hypercube is accumulated line by line as a motorized table moves the samples transversely through the laser line. The system covers a Raman shift range of -648.7-2889.0 cm-1 and a 23 cm wide area. An example application, for authenticating milk powder, was presented to demonstrate the system performance. In four minutes, the system acquired a 512x110x1024 hypercube (56,320 spectra) from four 47-mm-diameter Petri dishes containing four powder samples. Chemical images were created for detecting two adulterants (melamine and dicyandiamide) that had been mixed into the milk powder.

Land cover heterogeneity and soil respiration in a west Greenland tundra landscape

NASA Astrophysics Data System (ADS)

Bradley-Cook, J. I.; Burzynski, A.; Hammond, C. R.; Virginia, R. A.

2011-12-01

Multiple direct and indirect pathways underlie the association between land cover classification, temperature and soil respiration. Temperature is a main control of the biological processes that constitute soil respiration, yet the effect of changing atmospheric temperatures on soil carbon flux is unresolved. This study examines associations amongst land cover, soil carbon characteristics, soil respiration, and temperature in an Arctic tundra landscape in western Greenland. We used a 1.34 meter resolution multi-spectral WorldView2 satellite image to conduct an unsupervised multi-staged ISODATA classification to characterize land cover heterogeneity. The four band image was taken on July 10th, 2010, and captures an 18 km by 15 km area in the vicinity of Kangerlussuaq. The four major terrestrial land cover classes identified were: shrub-dominated, graminoid-dominated, mixed vegetation, and bare soil. The bare soil class was comprised of patches where surface soil has been deflated by wind and ridge-top fellfield. We hypothesize that soil respiration and soil carbon storage are associated with land cover classification and temperature. We set up a hierarchical field sampling design to directly observe spatial variation between and within land cover classes along a 20 km temperature gradient extending west from Russell Glacier on the margin of the Greenland Ice Sheet. We used the land cover classification map and ground verification to select nine sites, each containing patches of the four land cover classes. Within each patch we collected soil samples from a 50 cm pit, quantified vegetation, measured active layer depth and determined landscape characteristics. From a subset of field sites we collected additional 10 cm surface soil samples to estimate soil heterogeneity within patches and measured soil respiration using a LiCor 8100 Infrared Gas Analyzer. Soil respiration rates varied with land cover classes, with values ranging from 0.2 mg C/m^2/hr in the bare soil class to over 5 mg C/m^2/hr in the graminoid-dominated class. These findings suggest that shifts in land cover vegetation types, especially soil and vegetation loss (e.g. from wind deflation), can alter landscape soil respiration. We relate soil respiration measurements to soil, vegetation, and permafrost characteristics to understand how ecosystem properties and processes vary at the landscape scale. A long-term goal of this research is to develop a spatially explicit model of soil organic matter, soil respiration, and temperature sensitivity of soil carbon dynamics for a western Greenland permafrost tundra ecosystems.

VizieR Online Data Catalog: SL2S galaxy-scale sample of lens candidates (Gavazzi+, 2014)

NASA Astrophysics Data System (ADS)

Gavazzi, R.; Marshall, P. J.; Treu, T.; Sonnenfeld, A.

2017-06-01

The CFHTLS5 is a major photometric survey of more than 450 nights over 5 yr (started on 2003 June 1) using the MegaCam wide-field imager, which covers ~1 deg2 on the sky, with a pixel size of 0.186". The CFHTLS has two components aimed at extragalactic studies: a Deep component consisting of four pencil-beam fields of 1 deg2 and a wide component consisting of four mosaics covering 150 deg2 in total. Both surveys are imaged through five broadband filters. The data are pre-reduced at CFHT with the Elixir pipeline (http://www.cfht.hawaii.edu/Instruments/Elixir/), which removes the instrumental artifacts in individual exposures. The CFHTLS images are then astrometrically calibrated, photometrically inter-calibrated, resampled and stacked by the Terapix group at the Institut d'Astrophysique de Paris, and finally archived at the Canadian Astronomy Data Centre. (2 data files).

Land-Cover Trends of the Sierra Nevada Ecoregion, 1973-2000

USGS Publications Warehouse

Raumann, Christian G.; Soulard, Christopher E.

2007-01-01

The U.S. Geological Survey has developed and is implementing the Land Cover Trends project to estimate and describe the temporal and spatial distribution and variability of contemporary land-use and land-cover change in the United States. As part of the Land Cover Trends project, the purpose of this study was to assess land-use/land-cover change in the Sierra Nevada ecoregion for the period 1973 to 2000 using a probability sampling technique and satellite imagery. We randomly selected 36 100-km2 sample blocks to derive thematic images of land-use/land-cover for five dates of Landsat imagery (1973, 1980, 1986, 1992, 2000). We visually interpreted as many as 11 land-use/land-cover classes using a 60-meter minimum mapping unit from the five dates of imagery yielding four periods for analysis. Change-detection results from post-classification comparison of our mapped data showed that landscape disturbance from fire was the dominant change from 1973-2000. The second most-common change was forest disturbance resulting from harvest of timber resources by way of clear-cutting. The rates of forest regeneration from temporary fire and harvest disturbances coincided with the rates of disturbance from the previous period. Relatively minor landscape changes were caused by new development and reservoir drawdown. Multiple linear regression analysis suggests that land ownership and the proportion of forest and developed cover types were significant determinants of the likelihood of direct human-induced change occurring in sampling units. Driving forces of change include land ownership, land management such as fire suppression policy, and demand for natural resources.

New NASA Maps Show Flooding Changes In Aftermath of Hurricane Harvey

NASA Image and Video Library

2017-09-13

Data from NASA's Soil Moisture Active Passive (SMAP) satellite have been used to create new surface flooding maps of Southeast Texas and the Tennessee Valley following Hurricane Harvey. The SMAP observations detect the proportional cover of surface water within the satellite sensor's field of view. This sequence of images shows changes in the extent of surface flooding from successive five-day SMAP observation composite images. Widespread flooding can be seen in the Houston metropolitan area on Aug. 27 following record rainfall from the Category 4 hurricane, which made landfall on Aug. 25th, 2017 (left image). Flood waters around Houston had substantially receded by Aug. 31 (middle image), while flooding had increased across Louisiana, eastern Arkansas, and western Tennessee as then Tropical Storm Harvey passed over the area. The far right image shows the change in flooded area between Aug. 27 and Aug. 31, with regions showing the most flooding recession depicted in yellow and orange shades and those where flooding had increased depicted in blue shades. The SMAP satellite has a low-frequency (L-band) microwave radiometer with enhanced capabilities for detecting surface water changes in nearly all weather conditions and under low-to-moderate vegetation cover. SMAP provides global coverage with one-to-three-day repeat sampling that is well suited for global monitoring of inland surface water cover dynamics. https://photojournal.jpl.nasa.gov/catalog/PIA21951

Improved estimation of forest area in tropical Africa through ALOS/PALSAR 50-m orthorectified mosaic images

NASA Astrophysics Data System (ADS)

Dong, J.; Xiao, X.; Li, L.; Tenku, S. N.; Zhang, G.; Biradar, C. M.

2013-12-01

Tropical and moist Africa has one of the largest rainforests in the world. However, our knowledge about its forest area and spatial extent is still very limited. Forest area datasets from the Food and Agriculture Organization (FAO) Forest Resource Assessment (FRA) and the analyses of optical images (e.g., MODIS and MERIS) had a significant discrepancy, and they cannot meet the requirements to support the studies of forest carbon cycle and biodiversity, as well as the implementation of reducing emissions from deforestation and forest degradation (REDD+). The reasons for the large data discrepancy are complex and may attribute to the frequent cloud cover, coarse spatial resolution of images (MODIS, MERIS), diverse forest definition and classification approaches. In this study we generated a forest cover map in central Africa at 50-m resolution through the use of the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) 50-m orthorectified mosaic imagery in 2009. The resultant forest map was evaluated by the ground-reference data collected from the Geo-referenced Field Photo Library and Google Earth, and it has a reasonably high accuracy (producer's accuracy 83% and user's accuracy 94%). We also compared the PALSAR-based forest map with other three forest cover products (MCD12Q1 2009, GlobCover 2009 and VCF tree cover 2009) at the scales of (1) entire study domain and (2) selected sample regions. This new PALSAR-based 50-m forest cover map is likely to help reduce the uncertainty in forest area estimation, and better quantify and track deforestation, REDD+ implementation, and biodiversity conservation in central Africa.

Handheld microwave bomb-detecting imaging system

NASA Astrophysics Data System (ADS)

Gorwara, Ashok; Molchanov, Pavlo

2017-05-01

Proposed novel imaging technique will provide all weather high-resolution imaging and recognition capability for RF/Microwave signals with good penetration through highly scattered media: fog, snow, dust, smoke, even foliage, camouflage, walls and ground. Image resolution in proposed imaging system is not limited by diffraction and will be determined by processor and sampling frequency. Proposed imaging system can simultaneously cover wide field of view, detect multiple targets and can be multi-frequency, multi-function. Directional antennas in imaging system can be close positioned and installed in cell phone size handheld device, on small aircraft or distributed around protected border or object. Non-scanning monopulse system allows dramatically decrease in transmitting power and at the same time provides increased imaging range by integrating 2-3 orders more signals than regular scanning imaging systems.

D Land Cover Classification Based on Multispectral LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

2016-06-01

Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green), at 1064 nm near infrared (NIR) and at 1550nm intermediate infrared (IR). It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA) approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.

Redshifts for 2410 Galaxies in the Century Survey Region

NASA Astrophysics Data System (ADS)

Wegner, Gary; Thorstensen, John R.; Kurtz, Michael J.; Brown, Warren R.; Fabricant, Daniel G.; Geller, Margaret J.; Huchra, John P.; Marzke, Ronald O.; Sakai, Shoko

2001-12-01

The Century Survey strip covers 102 deg2 within the limits 8h5<=α<=16h5, 29.0d<=δ<=30.0d, equinox B1950.0. The strip passes through the Corona Borealis supercluster and the outer region of the Coma cluster. Within the Century Survey region, we have measured 2410 redshifts that constitute four overlapping complete redshift surveys: (1) 1728 galaxies with Kron-Cousins Rph<=16.13 covering the entire strip, (2) 507 galaxies with Rph<=16.4 in right ascension range 8h32m<=α<=10 h45m, equinox B1950.0, (3) 1251 galaxies with absorption- and K-corrected RCCDc<=16.2 (where ``c'' indicates ``corrected'') covering the right ascension range 8h5<=α<=13h5, equinox B1950.0, and (4) 1255 galaxies with absorption- and K-corrected VCCDc<=16.7 also covering the right ascension range 8h5<=α<=13h5, equinox B1950.0. All these redshift samples are more than 98% complete to the specified magnitude limit. We derived samples 1 and 2 from scans of the POSS1 red (E) plates calibrated with CCD photometry. We derived samples 3 and 4 from deep V and R CCD images covering the entire region. We include coarse morphological types for all the galaxies in sample 1. The distribution of (V-R)CCD for each type corresponds appropriately with the classification. Work reported here is based partly on observations obtained at the Michigan-Dartmouth-MIT Observatory.

Use of thematic mapper imagery to assess water quality, trophic state, and macrophyte distributions in Massachusetts lakes

USGS Publications Warehouse

Waldron, Marcus C.; Steeves, Peter A.; Finn, John T.

2001-01-01

During the spring and summer of 1996, 1997, and 1998, measurements of phytoplankton- chlorophyll concentration, Secchi disk transparency, and color were made at 97 Massachusetts lakes within 24 hours of Landsat Thematic Mapper imaging of the lakes in an effort to assess water quality and trophic state. Spatial distributions of floating, emergent, and submerged macrophytes were mapped in 49 of the lakes at least once during the 3-year period. The maps were digitized and used to assign pixels in the thematic mapper images to one of four vegetation cover classes-open water, 1-50 percent floating-and-emergent-vegetation cover, 51-100 percent floating-and-emergent-vegetation cover, and submerged vegetation at any density. The field data were collected by teams of U.S. Geological Survey and Massachusetts Department of Environmental Management staff and by 76 volunteers. Side-by-side sampling by U.S. Geological Survey and volunteer field teams resulted in statistically similar chlorophyll determinations, Secchi disk readings, and temperature measurements, but concurrent color determinations were not similar, possibly due to contamination of sample bottles issued to the volunteers.Attempts to develop predictive relations between phytoplankton-chlorophyll concentration, Secchi disk transparency, lake color, dissolved organic carbon, and various combinations of thematic mapper bands 1, 2, 3, and 4 digital numbers were unsuccessful, primarily because of the extremely low concentrations of chlorophyll in the lakes studied, and also because of the highly variable dissolved organic carbon concentrations.Predictive relations were developed between Secchi disk transparency and phytoplankton-chlorophyll concentration, and between color and dissolved organic carbon concentration. Phytoplankton-chlorophyll concentration was inversely correlated with Secchi disk transparency during all three sampling periods. The relations were very similar in 1996 and 1997 and indicated that 62 to 67 percent of the variability in Secchi disk transparency could be explained by the chlorophyll concentration. Analysis of color and dissolved organic carbon concentrations in water samples collected by U.S. Geological Survey field teams in 1996-98 indicated that 91 percent of the variance in color in Massachusetts lakes can be explained by variations in dissolved organic carbon.Areas of open-water, submerged vegetation, and two surface-vegetation-cover classes predicted from Thematic Mapper images acquired in the summer of 1996 closely matched the areas observed in a set of field observations. However, the same analysis applied to a set of data acquired in the summer of 1997 resulted in somewhat less reliable predictions, and an attempt to predict 1996 vegetation-cover areas using the relations developed in the 1997 analysis was unsuccessful.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Image interpreter tool: An ArcGIS tool for estimating vegetation cover from high-resolution imagery

USDA-ARS?s Scientific Manuscript database

Land managers need increased temporal and spatial resolution of rangeland assessment and monitoring data. However, with flat or declining land management and monitoring agency budgets, such increases in sampling intensity are unlikely unless new methods can be developed that capture data of key rang...

3D surface scan of biological samples with a Push-broom Imaging Spectrometer

NASA Astrophysics Data System (ADS)

Yao, Haibo; Kincaid, Russell; Hruska, Zuzana; Brown, Robert L.; Bhatnagar, Deepak; Cleveland, Thomas E.

2013-08-01

The food industry is always on the lookout for sensing technologies for rapid and nondestructive inspection of food products. Hyperspectral imaging technology integrates both imaging and spectroscopy into unique imaging sensors. Its application for food safety and quality inspection has made significant progress in recent years. Specifically, hyperspectral imaging has shown its potential for surface contamination detection in many food related applications. Most existing hyperspectral imaging systems use pushbroom scanning which is generally used for flat surface inspection. In some applications it is desirable to be able to acquire hyperspectral images on circular objects such as corn ears, apples, and cucumbers. Past research describes inspection systems that examine all surfaces of individual objects. Most of these systems did not employ hyperspectral imaging. These systems typically utilized a roller to rotate an object, such as an apple. During apple rotation, the camera took multiple images in order to cover the complete surface of the apple. The acquired image data lacked the spectral component present in a hyperspectral image. This paper discusses the development of a hyperspectral imaging system for a 3-D surface scan of biological samples. The new instrument is based on a pushbroom hyperspectral line scanner using a rotational stage to turn the sample. The system is suitable for whole surface hyperspectral imaging of circular objects. In addition to its value to the food industry, the system could be useful for other applications involving 3-D surface inspection.

Spatial Patterns of Snow Cover in North Carolina: Surface and Satellite Perspectives

NASA Technical Reports Server (NTRS)

Fuhrmann, Christopher M.; Hall, Dorothy K.; Perry, L. Baker; Riggs, George A.

2010-01-01

Snow mapping is a common practice in regions that receive large amounts of snowfall annually, have seasonally-continuous snow cover, and where snowmelt contributes significantly to the hydrologic cycle. Although higher elevations in the southern Appalachian Mountains average upwards of 100 inches of snow annually, much of the remainder of the Southeast U.S. receives comparatively little snowfall (< 10 inches). Recent snowy winters in the region have provided an opportunity to assess the fine-grained spatial distribution of snow cover and the physical processes that act to limit or improve its detection across the Southeast. In the present work, both in situ and remote sensing data are utilized to assess the spatial distribution of snow cover for a sample of recent snowfall events in North Carolina. Specifically, this work seeks to determine how well ground measurements characterize the fine-grained patterns of snow cover in relation to Moderate- Resolution Imaging Spectroradiometer (MODIS) snow cover products (in this case, the MODIS Fractional Snow Cover product).

Land cover change of watersheds in Southern Guam from 1973 to 2001.

PubMed

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.

Retrieval of land cover information under thin fog in Landsat TM image

NASA Astrophysics Data System (ADS)

Wei, Yuchun

2008-04-01

Thin fog, which often appears in remote sensing image of subtropical climate region, has resulted in the low image quantity and bad image mapping. Therefore, it is necessary to develop the image processing method to retrieve land cover information under thin fog. In this paper, the Landsat TM image near the Taihu Lake that is in the subtropical climate zone of China was used as an example, and the workflow and method used to retrieve the land cover information under thin fog have been built based on ENVI software and a single TM image. The basic step covers three parts: 1) isolating the thin fog area in image according to the spectral difference of different bands; 2) retrieving the visible band information of different land cover types under thin fog from the near-infrared bands according to the relationships between near-infrared bands and visible bands of different land cover types in the area without fog; 3) image post-process. The result showed that the method in the paper is easy and suitable, and can be used to improve the quantity of TM image mapping more effectively.

Optical detection of Trypanosoma cruzi in blood samples for diagnosis purpose

NASA Astrophysics Data System (ADS)

Alanis, Elvio; Romero, Graciela; Alvarez, Liliana; Martinez, Carlos C.; Basombrio, Miguel A.

2004-10-01

An optical method for detection of Trypanosoma Cruzi (T. cruzi) parasites in blood samples of mice infected with Chagas disease is presented. The method is intended for use in human blood, for diagnosis purposes. A thin layer of blood infected by T. cruzi parasites, in small concentrations, is examined in an interferometric microscope in which the images of the vision field are taken by a CCD camera and temporarily stored in the memory of a host computer. The whole sample is scanned displacing the microscope plate by means of step motors driven by the computer. Several consecutive images of the same field are taken and digitally processed by means of image temporal differentiation in order to detect if a parasite is eventually present in the field. Each field of view is processed in the same fashion, until the full area of the sample is covered or until a parasite is detected, in which case an acoustical warning is activated and the corresponding image is displayed permitting the technician to corroborate the result visually. A discussion of the reliability of the method as well as a comparison with other well established techniques are presented.

Handling Different Spatial Resolutions in Image Fusion by Multivariate Curve Resolution-Alternating Least Squares for Incomplete Image Multisets.

PubMed

Piqueras, Sara; Bedia, Carmen; Beleites, Claudia; Krafft, Christoph; Popp, Jürgen; Maeder, Marcel; Tauler, Romà; de Juan, Anna

2018-06-05

Data fusion of different imaging techniques allows a comprehensive description of chemical and biological systems. Yet, joining images acquired with different spectroscopic platforms is complex because of the different sample orientation and image spatial resolution. Whereas matching sample orientation is often solved by performing suitable affine transformations of rotation, translation, and scaling among images, the main difficulty in image fusion is preserving the spatial detail of the highest spatial resolution image during multitechnique image analysis. In this work, a special variant of the unmixing algorithm Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) for incomplete multisets is proposed to provide a solution for this kind of problem. This algorithm allows analyzing simultaneously images collected with different spectroscopic platforms without losing spatial resolution and ensuring spatial coherence among the images treated. The incomplete multiset structure concatenates images of the two platforms at the lowest spatial resolution with the image acquired with the highest spatial resolution. As a result, the constituents of the sample analyzed are defined by a single set of distribution maps, common to all platforms used and with the highest spatial resolution, and their related extended spectral signatures, covering the signals provided by each of the fused techniques. We demonstrate the potential of the new variant of MCR-ALS for multitechnique analysis on three case studies: (i) a model example of MIR and Raman images of pharmaceutical mixture, (ii) FT-IR and Raman images of palatine tonsil tissue, and (iii) mass spectrometry and Raman images of bean tissue.

Computerized tomography platform using beta rays

NASA Astrophysics Data System (ADS)

Paetkau, Owen; Parsons, Zachary; Paetkau, Mark

2017-12-01

A computerized tomography (CT) system using a 0.1 μCi Sr-90 beta source, Geiger counter, and low density foam samples was developed. A simple algorithm was used to construct images from the data collected with the beta CT scanner. The beta CT system is analogous to X-ray CT as both types of radiation are sensitive to density variations. This system offers a platform for learning opportunities in an undergraduate laboratory, covering topics such as image reconstruction algorithms, radiation exposure, and the energy dependence of absorption.

Time-domain terahertz spectroscopy of artificial skin

NASA Astrophysics Data System (ADS)

Corridon, Peter M.; Ascázubi, Ricardo; Krest, Courtney; Wilke, Ingrid

2006-02-01

Time-domain Terahertz (THz) spectroscopy and imaging is currently evaluated as a novel tool for medical imaging and diagnostics. The application of THz-pulse imaging of human skin tissues and related cancers has been demonstrated recently in-vitro and in-vivo. With this in mind, we present a time-domain THz-transmission study of artificial skin. The skin samples consist of a monolayer of porous matrix of fibers of cross-linked bovine tendon collagen and a glycosaminoglycan (chondroitin-6-sulfate) that is manufactured with a controlled porosity and defined degradation rate. Another set of samples consists of the collagen monolayer covered with a silicone layer. We have measured the THz-transmission and determined the index of refraction and absorption of our samples between 0.1 and 3 THz for various states of hydration in distilled water and saline solutions. The transmission of the THz-radiation through the artificial skin samples is modeled by electromagnetic wave theory. Moreover, the THz-optical properties of the artificial skin layers are compared to the THz-optical properties of freshly excised human skin samples. Based on this comparison the potential use of artificial skin samples as photo-medical phantoms for human skin is discussed.

ARC-2009-ACD09-0108-032

NASA Image and Video Library

2009-02-08

An SUV-sized Asteroid 2008TC# Impacts on October 7, 2008 in the Nubian Desert, Northern Sudan: Dr. Peter Jenniskens, NASA/SETI joined Muawia Shaddas of the University of Khartoum in leading an expedition on a search for samples. (image used as cover for March 26, 2009 journal Nature) Photo Credit: NASA/SETI/P. Jenniskens

Object-based land cover classification based on fusion of multifrequency SAR data and THAICHOTE optical imagery

NASA Astrophysics Data System (ADS)

Sukawattanavijit, Chanika; Srestasathiern, Panu

2017-10-01

Land Use and Land Cover (LULC) information are significant to observe and evaluate environmental change. LULC classification applying remotely sensed data is a technique popularly employed on a global and local dimension particularly, in urban areas which have diverse land cover types. These are essential components of the urban terrain and ecosystem. In the present, object-based image analysis (OBIA) is becoming widely popular for land cover classification using the high-resolution image. COSMO-SkyMed SAR data was fused with THAICHOTE (namely, THEOS: Thailand Earth Observation Satellite) optical data for land cover classification using object-based. This paper indicates a comparison between object-based and pixel-based approaches in image fusion. The per-pixel method, support vector machines (SVM) was implemented to the fused image based on Principal Component Analysis (PCA). For the objectbased classification was applied to the fused images to separate land cover classes by using nearest neighbor (NN) classifier. Finally, the accuracy assessment was employed by comparing with the classification of land cover mapping generated from fused image dataset and THAICHOTE image. The object-based data fused COSMO-SkyMed with THAICHOTE images demonstrated the best classification accuracies, well over 85%. As the results, an object-based data fusion provides higher land cover classification accuracy than per-pixel data fusion.

Beagle-2 landing site atlas

NASA Astrophysics Data System (ADS)

Michael, G.; Chicarro, A.; Rodionova, J.; Shevchenko, V.; Ilukhina, J.; Kozlova, K.

2003-04-01

The Beagle-2 lander of the Mars Express mission will come to rest on the surface of Isidis Planitia in late December 2003 to carry out a range of geochemistry and exobiology experi-ments. We are compiling an atlas of the presently available data products pertinent to the landing site at 11.6N 90.75E, which is intended for distribution both as a printed and an electronic resource. The atlas will include Viking and MOC-WA image mosaics, and a catalogue of high-resolution im-ages from MOC and THEMIS with location maps. There will be various MOLA topography-based products: colour-scaled, contoured, and shaded maps, slope, and detrended relief. Simulated camera panoramas from various potential landing locations may assist in determining the spacecraft’s position. Other maps, both raw, and in composites with image mosa-ics, will cover TES thermal inertia and spectroscopy, and Odyssey gamma and neutron spectroscopy. Maps at the scale of the Isidis context will additionally cover geology, tem-perature cycles, and atmospheric circulation. Sample are shown below.

Reliability and discriminatory power of methods for dental plaque quantification

PubMed Central

RAGGIO, Daniela Prócida; BRAGA, Mariana Minatel; RODRIGUES, Jonas Almeida; FREITAS, Patrícia Moreira; IMPARATO, José Carlos Pettorossi; MENDES, Fausto Medeiros

2010-01-01

Objective This in situ study evaluated the discriminatory power and reliability of methods of dental plaque quantification and the relationship between visual indices (VI) and fluorescence camera (FC) to detect plaque. Material and Methods Six volunteers used palatal appliances with six bovine enamel blocks presenting different stages of plaque accumulation. The presence of plaque with and without disclosing was assessed using VI. Images were obtained with FC and digital camera in both conditions. The area covered by plaque was assessed. Examinations were done by two independent examiners. Data were analyzed by Kruskal-Wallis and Kappa tests to compare different conditions of samples and to assess the inter-examiner reproducibility. Results Some methods presented adequate reproducibility. The Turesky index and the assessment of area covered by disclosed plaque in the FC images presented the highest discriminatory powers. Conclusions The Turesky index and images with FC with disclosing present good reliability and discriminatory power in quantifying dental plaque. PMID:20485931

Convolutional neural networks based on augmented training samples for synthetic aperture radar target recognition

NASA Astrophysics Data System (ADS)

Yan, Yue

2018-03-01

A synthetic aperture radar (SAR) automatic target recognition (ATR) method based on the convolutional neural networks (CNN) trained by augmented training samples is proposed. To enhance the robustness of CNN to various extended operating conditions (EOCs), the original training images are used to generate the noisy samples at different signal-to-noise ratios (SNRs), multiresolution representations, and partially occluded images. Then, the generated images together with the original ones are used to train a designed CNN for target recognition. The augmented training samples can contrapuntally improve the robustness of the trained CNN to the covered EOCs, i.e., the noise corruption, resolution variance, and partial occlusion. Moreover, the significantly larger training set effectively enhances the representation capability for other conditions, e.g., the standard operating condition (SOC), as well as the stability of the network. Therefore, better performance can be achieved by the proposed method for SAR ATR. For experimental evaluation, extensive experiments are conducted on the Moving and Stationary Target Acquisition and Recognition dataset under SOC and several typical EOCs.

Mapping urban impervious surface using object-based image analysis with WorldView-3 satellite imagery

NASA Astrophysics Data System (ADS)

Iabchoon, Sanwit; Wongsai, Sangdao; Chankon, Kanoksuk

2017-10-01

Land use and land cover (LULC) data are important to monitor and assess environmental change. LULC classification using satellite images is a method widely used on a global and local scale. Especially, urban areas that have various LULC types are important components of the urban landscape and ecosystem. This study aims to classify urban LULC using WorldView-3 (WV-3) very high-spatial resolution satellite imagery and the object-based image analysis method. A decision rules set was applied to classify the WV-3 images in Kathu subdistrict, Phuket province, Thailand. The main steps were as follows: (1) the image was ortho-rectified with ground control points and using the digital elevation model, (2) multiscale image segmentation was applied to divide the image pixel level into image object level, (3) development of the decision ruleset for LULC classification using spectral bands, spectral indices, spatial and contextual information, and (4) accuracy assessment was computed using testing data, which sampled by statistical random sampling. The results show that seven LULC classes (water, vegetation, open space, road, residential, building, and bare soil) were successfully classified with overall classification accuracy of 94.14% and a kappa coefficient of 92.91%.

In Situ Visualization of the Local Photothermal Effect Produced on α-Cyclodextrin Inclusion Compound Associated with Gold Nanoparticles

NASA Astrophysics Data System (ADS)

Silva, Nataly; Muñoz, Camila; Diaz-Marcos, Jordi; Samitier, Josep; Yutronic, Nicolás; Kogan, Marcelo J.; Jara, Paul

2016-04-01

Evidence of guest migration in α-cyclodextrin-octylamine (α-CD-OA) inclusion compound (IC) generated via plasmonic heating of gold nanoparticles (AuNPs) has been studied. In this report, we demonstrate local effects generated by laser-mediated irradiation of a sample of AuNPs covered with inclusion compounds on surface-derivatized glass under liquid conditions by atomic force microscopy (AFM). Functionalized AuNPs on the glass and covered by the ICs were monitored by recording images by AFM during 5 h of irradiation, and images showed that after irradiation, a drastic decrease in the height of the AuNPs occurred. The absorption spectrum of the irradiated sample showed a hypsochromic shift from 542 to 536 nm, evidence suggesting that much of the population of nanoparticles lost all of the parts of the overlay of ICs due to the plasmonic heat generated by the irradiation. Mass spectrometry matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) performed on a sample containing a collection of drops obtained from the surface of the functionalized glass provided evidence that the irradiation lead to disintegration of the ICs and therefore exit of the octylamine molecule (the guest) from the cyclodextrin cavity (the matrix).

Dual tunneling-unit scanning tunneling microscope for length measurement based on crystalline lattice

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

Zhang, H.; Higuchi, T.; Nishioki, N.

1997-01-01

A dual tunneling-unit scanning tunneling microscope (DTU STM) was developed for nm order length measurement with wide scan range. The crystalline lattice of highly oriented pyrolitic graphite (HOPG) was used as reference scale. A reference unit was set up on top of a test unit. The reference sample holder and the probe tip of test unit were attached to one single XY scanner on either surface, while the test sample holder was open. This enables simultaneous acquisition of wide images of HOPG and test sample. The length in test sample image was measured by counting the number of HOPG lattices.more » An inchworm actuator and an impact drive mechanism were introduced to roughly position probe tips. The XY scanner was designed to be elastic to eliminate image distortion. Some comparison experiments using two HOPG chips were carried out in air. The DTU STM is confirmed to be a stable and more powerful device for length measurement which has nanometer accuracy when covering a wide scan range up to several micrometers, and is capable of measuring comparatively large and heavy samples. {copyright} {ital 1997 American Vacuum Society.}« less

High speed spectral domain optical coherence tomography for retinal imaging at 500,000 A‑lines per second

PubMed Central

An, Lin; Li, Peng; Shen, Tueng T.; Wang, Ruikang

2011-01-01

We present a new development of ultrahigh speed spectral domain optical coherence tomography (SDOCT) for human retinal imaging at 850 nm central wavelength by employing two high-speed line scan CMOS cameras, each running at 250 kHz. Through precisely controlling the recording and reading time periods of the two cameras, the SDOCT system realizes an imaging speed at 500,000 A-lines per second, while maintaining both high axial resolution (~8 μm) and acceptable depth ranging (~2.5 mm). With this system, we propose two scanning protocols for human retinal imaging. The first is aimed to achieve isotropic dense sampling and fast scanning speed, enabling a 3D imaging within 0.72 sec for a region covering 4x4 mm2. In this case, the B-frame rate is 700 Hz and the isotropic dense sampling is 500 A-lines along both the fast and slow axes. This scanning protocol minimizes the motion artifacts, thus making it possible to perform two directional averaging so that the signal to noise ratio of the system is enhanced while the degradation of its resolution is minimized. The second protocol is designed to scan the retina in a large field of view, in which 1200 A-lines are captured along both the fast and slow axes, covering 10 mm2, to provide overall information about the retinal status. Because of relatively long imaging time (4 seconds for a 3D scan), the motion artifact is inevitable, making it difficult to interpret the 3D data set, particularly in a way of depth-resolved en-face fundus images. To mitigate this difficulty, we propose to use the relatively high reflecting retinal pigmented epithelium layer as the reference to flatten the original 3D data set along both the fast and slow axes. We show that the proposed system delivers superb performance for human retina imaging. PMID:22025983

High speed spectral domain optical coherence tomography for retinal imaging at 500,000 A‑lines per second.

PubMed

An, Lin; Li, Peng; Shen, Tueng T; Wang, Ruikang

2011-10-01

We present a new development of ultrahigh speed spectral domain optical coherence tomography (SDOCT) for human retinal imaging at 850 nm central wavelength by employing two high-speed line scan CMOS cameras, each running at 250 kHz. Through precisely controlling the recording and reading time periods of the two cameras, the SDOCT system realizes an imaging speed at 500,000 A-lines per second, while maintaining both high axial resolution (~8 μm) and acceptable depth ranging (~2.5 mm). With this system, we propose two scanning protocols for human retinal imaging. The first is aimed to achieve isotropic dense sampling and fast scanning speed, enabling a 3D imaging within 0.72 sec for a region covering 4x4 mm(2). In this case, the B-frame rate is 700 Hz and the isotropic dense sampling is 500 A-lines along both the fast and slow axes. This scanning protocol minimizes the motion artifacts, thus making it possible to perform two directional averaging so that the signal to noise ratio of the system is enhanced while the degradation of its resolution is minimized. The second protocol is designed to scan the retina in a large field of view, in which 1200 A-lines are captured along both the fast and slow axes, covering 10 mm(2), to provide overall information about the retinal status. Because of relatively long imaging time (4 seconds for a 3D scan), the motion artifact is inevitable, making it difficult to interpret the 3D data set, particularly in a way of depth-resolved en-face fundus images. To mitigate this difficulty, we propose to use the relatively high reflecting retinal pigmented epithelium layer as the reference to flatten the original 3D data set along both the fast and slow axes. We show that the proposed system delivers superb performance for human retina imaging.

Go For the Gold...Read! Louisiana Summer Reading Program, 1996.

ERIC Educational Resources Information Center

White, Dorothy J., Ed.

A manual for the 1996 Louisiana Summer Reading Program is presented in five sections with an Olympic and sports-related theme and illustrations. An evaluation form, a 1996 monthly calendar, and clip art images are provided. The first section covers promotion and publicity, and contains facts about the Olympics, promotion ideas, and sample news…

Micro- and nano-tomography at the DIAMOND beamline I13L imaging and coherence

NASA Astrophysics Data System (ADS)

Rau, C.; Bodey, A.; Storm, M.; Cipiccia, S.; Marathe, S.; Zdora, M.-C.; Zanette, I.; Wagner, U.; Batey, D.; Shi, X.

2017-10-01

The Diamond Beamline I13L is dedicated to imaging on the micro- and nano-lengthsale, operating in the energy range between 6 and 30keV. For this purpose two independently operating branchlines and endstations have been built. The imaging branch is fully operational for micro-tomography and in-line phase contrast imaging with micrometre resolution. Grating interferometry is currently implemented, adding the capability of measuring phase and small-angle information. For tomography with increased resolution a full-field microscope providing 50nm spatial resolution with a field of view of 100μm is being tested. The instrument provides a large working distance between optics and sample to adapt a wide range of customised sample environments. On the coherence branch coherent diffraction imaging techniques such as ptychography, coherent X-ray diffraction (CXRD) are currently developed for three dimensional imaging with the highest resolution. The imaging branch is operated in collaboration with Manchester University, called therefore the Diamond-Manchester Branchline. The scientific applications cover a large area including bio-medicine, materials science, chemistry geology and more. The present paper provides an overview about the current status of the beamline and the science addressed.

Accuracy Assessment of Satellite Derived Forest Cover Products in South and Southeast Asia

NASA Astrophysics Data System (ADS)

Gilani, H.; Xu, X.; Jain, A. K.

2017-12-01

South and Southeast Asia (SSEA) region occupies 16 % of worlds land area. It is home to over 50% of the world's population. The SSEA's countries are experiencing significant land-use and land-cover changes (LULCCs), primarily in agriculture, forest, and urban land. For this study, we compiled four existing global forest cover maps for year 2010 by Gong et al.(2015), Hansen et al. (2013), Sexton et al.(2013) and Shimada et al. (2014), which were all medium resolution (≤30 m) products based on Landsat and/or PALSAR satellite images. To evaluate the accuracy of these forest products, we used three types of information: (1) ground measurements, (2) high resolution satellite images and (3) forest cover maps produced at the national scale. The stratified random sampling technique was used to select a set of validation data points from the ground and high-resolution satellite images. Then the confusion matrix method was used to assess and rank the accuracy of the forest cover products for the entire SSEA region. We analyzed the spatial consistency of different forest cover maps, and further evaluated the consistency with terrain characteristics. Our study suggests that global forest cover mapping algorithms are trained and tested using limited ground measurement data. We found significant uncertainties in mountainous areas due to the topographical shadow effect and the dense tree canopies effects. The findings of this study will facilitate to improve our understanding of the forest cover dynamics and their impacts on the quantities and pathways of terrestrial carbon and nitrogen fluxes. Gong, P., et al. (2012). "Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data." International Journal of Remote Sensing 34(7): 2607-2654. Hansen, M. C., et al. (2013). "High-Resolution Global Maps of 21st-Century Forest Cover Change." Science 342(6160): 850-853. Sexton, J. O., et al. (2013). "Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error." International Journal of Digital Earth: 1-22. Shimada, M., et al. (2014). "New global forest/non-forest maps from ALOS PALSAR data (2007-2010)." Remote Sensing of Environment 155: 13-31.

Digital image classification approach for estimating forest clearing and regrowth rates and trends

NASA Technical Reports Server (NTRS)

Sader, Steven A.

1987-01-01

A technique is presented to monitor vegetation changes for a selected study area in Costa Rica. A normalized difference vegetation index was computed for three dates of Landsat satellite data and a modified parallelipiped classifier was employed to generate a multitemporal greenness image representing all three dates. A second-generation image was created by partitioning the intensity levels at each date into high, medium, and low and thereby reducing the number of classes to 21. A sampling technique was applied to describe forest and other land cover change occurring between time periods based on interpretation of aerial photography that closely matched the dates of satellite acquisition. Comparison of the Landsat-derived classes with the photo-interpreted sample areas can provide a basis for evaluating the satellite monitoring technique and the accuracy of estimating forest clearing and regrowth rates and trends.

Detection of rebars in concrete using advanced ultrasonic pulse compression techniques.

PubMed

Laureti, S; Ricci, M; Mohamed, M N I B; Senni, L; Davis, L A J; Hutchins, D A

2018-04-01

A pulse compression technique has been developed for the non-destructive testing of concrete samples. Scattering of signals from aggregate has historically been a problem in such measurements. Here, it is shown that a combination of piezocomposite transducers, pulse compression and post processing can lead to good images of a reinforcement bar at a cover depth of 55 mm. This has been achieved using a combination of wide bandwidth operation over the 150-450 kHz range, and processing based on measuring the cumulative energy scattered back to the receiver. Results are presented in the form of images of a 20 mm rebar embedded within a sample containing 10 mm aggregate. Copyright © 2017 Elsevier B.V. All rights reserved.

Detecting the environmental impact of off-road vehicles on Rawdat Al Shams in central Saudi Arabia by remote sensing.

PubMed

Dewidar, K; Thomas, J; Bayoumi, S

2016-07-01

Off-road vehicles can have a devastating impact on vegetation and soil. Here, we sought to quantify, through a combination of field vegetation, bulk soil, and image analyses, the impact of off-road vehicles on the vegetation and soils of Rawdat Al Shams, which is located in central Saudi Arabia. Soil compaction density was measured in the field, and 27 soil samples were collected for bulk density analysis in the lab to quantify the impacts of off-road vehicles. High spatial resolution images, such as those obtained by the satellites GeoEye-1 and IKONOS-2, were used for surveying the damage to vegetation cover and soil compaction caused by these vehicles. Vegetation cover was mapped using the Normalized Difference Vegetation Index (NDVI) technique based on high-resolution images taken at different times of the year. Vehicle trails were derived from satellite data via visual analysis. All damaged areas were determined from high-resolution image data. In this study, we conducted quantitative analyses of vegetation cover change, the impacts of vehicle trails (hereafter "trail impacts"), and a bulk soil analysis. Image data showed that both vegetation cover and trail impacts increased from 2008 to 2015, with the average percentage of trail impacts nearly equal to that of the percentage of vegetation cover during this period. Forty-six species of plants were found to be present in the study area, consisting of all types of life forms, yet trees were represented by a single species, Acacia gerrardii. Herbs composed the largest share of plant life, with 29 species, followed by perennial herbs (12 species), grasses (5 species), and shrubs (3 species). Analysis of soil bulk density for Rawdat Al Shams showed that off-road driving greatly impacts soil density. Twenty-two plant species were observed on the trails, the majority of which were ephemerals. Notoceras bicorne was the most common, with a frequency rate of 93.33 %, an abundance value of 78.47 %, and a density of 0.1 in transect 1, followed by Plantago ovata.

Body MR Imaging: Artifacts, k-Space, and Solutions

PubMed Central

Seethamraju, Ravi T.; Patel, Pritesh; Hahn, Peter F.; Kirsch, John E.; Guimaraes, Alexander R.

2015-01-01

Body magnetic resonance (MR) imaging is challenging because of the complex interaction of multiple factors, including motion arising from respiration and bowel peristalsis, susceptibility effects secondary to bowel gas, and the need to cover a large field of view. The combination of these factors makes body MR imaging more prone to artifacts, compared with imaging of other anatomic regions. Understanding the basic MR physics underlying artifacts is crucial to recognizing the trade-offs involved in mitigating artifacts and improving image quality. Artifacts can be classified into three main groups: (a) artifacts related to magnetic field imperfections, including the static magnetic field, the radiofrequency (RF) field, and gradient fields; (b) artifacts related to motion; and (c) artifacts arising from methods used to sample the MR signal. Static magnetic field homogeneity is essential for many MR techniques, such as fat saturation and balanced steady-state free precession. Susceptibility effects become more pronounced at higher field strengths and can be ameliorated by using spin-echo sequences when possible, increasing the receiver bandwidth, and aligning the phase-encoding gradient with the strongest susceptibility gradients, among other strategies. Nonuniformities in the RF transmit field, including dielectric effects, can be minimized by applying dielectric pads or imaging at lower field strength. Motion artifacts can be overcome through respiratory synchronization, alternative k-space sampling schemes, and parallel imaging. Aliasing and truncation artifacts derive from limitations in digital sampling of the MR signal and can be rectified by adjusting the sampling parameters. Understanding the causes of artifacts and their possible solutions will enable practitioners of body MR imaging to meet the challenges of novel pulse sequence design, parallel imaging, and increasing field strength. ©RSNA, 2015 PMID:26207581

Mathematical models used in segmentation and fractal methods of 2-D ultrasound images

NASA Astrophysics Data System (ADS)

Moldovanu, Simona; Moraru, Luminita; Bibicu, Dorin

2012-11-01

Mathematical models are widely used in biomedical computing. The extracted data from images using the mathematical techniques are the "pillar" achieving scientific progress in experimental, clinical, biomedical, and behavioural researches. This article deals with the representation of 2-D images and highlights the mathematical support for the segmentation operation and fractal analysis in ultrasound images. A large number of mathematical techniques are suitable to be applied during the image processing stage. The addressed topics cover the edge-based segmentation, more precisely the gradient-based edge detection and active contour model, and the region-based segmentation namely Otsu method. Another interesting mathematical approach consists of analyzing the images using the Box Counting Method (BCM) to compute the fractal dimension. The results of the paper provide explicit samples performed by various combination of methods.

Study on the Classification of GAOFEN-3 Polarimetric SAR Images Using Deep Neural Network

NASA Astrophysics Data System (ADS)

Zhang, J.; Zhang, J.; Zhao, Z.

2018-04-01

Polarimetric Synthetic Aperture Radar (POLSAR) imaging principle determines that the image quality will be affected by speckle noise. So the recognition accuracy of traditional image classification methods will be reduced by the effect of this interference. Since the date of submission, Deep Convolutional Neural Network impacts on the traditional image processing methods and brings the field of computer vision to a new stage with the advantages of a strong ability to learn deep features and excellent ability to fit large datasets. Based on the basic characteristics of polarimetric SAR images, the paper studied the types of the surface cover by using the method of Deep Learning. We used the fully polarimetric SAR features of different scales to fuse RGB images to the GoogLeNet model based on convolution neural network Iterative training, and then use the trained model to test the classification of data validation.First of all, referring to the optical image, we mark the surface coverage type of GF-3 POLSAR image with 8m resolution, and then collect the samples according to different categories. To meet the GoogLeNet model requirements of 256 × 256 pixel image input and taking into account the lack of full-resolution SAR resolution, the original image should be pre-processed in the process of resampling. In this paper, POLSAR image slice samples of different scales with sampling intervals of 2 m and 1 m to be trained separately and validated by the verification dataset. Among them, the training accuracy of GoogLeNet model trained with resampled 2-m polarimetric SAR image is 94.89 %, and that of the trained SAR image with resampled 1 m is 92.65 %.

Micro and nanocrystalline diamond formation on reticulated vitreous carbon substrate

NASA Astrophysics Data System (ADS)

Diniz, A. V.; Trava-Airoldi, V. J.; Corat, E. J.; Ferreira, N. G.

2005-10-01

High diamond nucleation and a three-dimensional growth on reticulated vitreous carbon substrate are obtained by chemical vapor deposition. Scanning electron microscopy images show continuous films covering the whole substrate including the center of 3.5 mm thick porous samples. It is evident the nanocrystalline diamond (NCD) film formation on deeper substrate regions. The grain size can vary from nano to micro scale for deposition time of 20 h. Raman spectra of sample regions closer to filaments exhibit well-defined diamond line. For central regions of sample (depth between 1.0 and 2.0 mm) Raman spectra also confirm NCD film.

Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

PubMed Central

Moran, Emilio Federico.

2010-01-01

High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervised classification, incorporation of textural images and multispectral images, spectral-spatial classifier, and segmentation-based classification are examined in a relatively new developing urban landscape, Lucas do Rio Verde in Mato Grosso State, Brazil. This research shows that use of spatial information during the image classification procedure, either through the integrated use of textural and spectral images or through the use of segmentation-based classification method, can significantly improve land cover classification performance. PMID:21643433

Visible and infrared linear detector arrays for the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

NASA Technical Reports Server (NTRS)

Bailey, Gary C.

1987-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) instrument uses four separate focal plane assemblies consisting of line array detectors that are multiplexed to a common J-FET preamp using a FET switch multiplexing (MUX) technique. A 32-element silicon line array covers the spectral range from 0.41 to 0.70 microns. Three additional 64-element indium antimonide (InSb) line arrays cover the spectral range from 0.68 to 2.45 microns. The spectral sampling interval per detector element is nominally 9.8 nm, giving a total of 224 spectral channels. All focal planes operate at liquid nitrogen temperature and are housed in separate dewars. Electrical performance characteristics include a read noise of less than 1000 e(-) in all channels, response and dark nonuniformity of 5 percent peak to peak, and quantum efficiency of greater than 60 percent.

Optimally weighted least-squares steganalysis

NASA Astrophysics Data System (ADS)

Ker, Andrew D.

2007-02-01

Quantitative steganalysis aims to estimate the amount of payload in a stego object, and such estimators seem to arise naturally in steganalysis of Least Significant Bit (LSB) replacement in digital images. However, as with all steganalysis, the estimators are subject to errors, and their magnitude seems heavily dependent on properties of the cover. In very recent work we have given the first derivation of estimation error, for a certain method of steganalysis (the Least-Squares variant of Sample Pairs Analysis) of LSB replacement steganography in digital images. In this paper we make use of our theoretical results to find an improved estimator and detector. We also extend the theoretical analysis to another (more accurate) steganalysis estimator (Triples Analysis) and hence derive an improved version of that estimator too. Experimental results show that the new steganalyzers have improved accuracy, particularly in the difficult case of never-compressed covers.

Surface Flooding from Hurricane Harvey Shown in New SMAP Imagery

NASA Image and Video Library

2017-08-30

A new series of images generated with data from NASA's Soil Moisture Active Passive (SMAP) satellite illustrate the surface flooding caused by Hurricane Harvey from before its initial landfall through August 27, 2017. The SMAP observations detect the proportion of the ground covered by surface water within the satellite's field of view. The sequence of images depicts successive satellite orbital swath observations showing the surface water conditions on August 22, before Harvey's landfall (left), and then on Aug. 27, two days after landfall (middle). The resulting increase in surface flooding from record rainfall over the three-day period, shown at right, depicts regionally heavy flooding around the Houston metropolitan area. The hardest hit areas (blue and purple shades) cover more than 23,000 square miles (about 59,600 square kilometers) and indicate a more than 1,000-fold increase in surface water cover from rainfall-driven flooding. SMAP's low-frequency (L-band) microwave radiometer features enhanced capabilities for detecting surface water changes in nearly all weather conditions and under low-to-moderate vegetation cover. The satellite provides global coverage with one to three-day repeat sampling, which is well suited for monitoring dynamic inland waters around the world. https://photojournal.jpl.nasa.gov/catalog/PIA21930

Lightdrum—Portable Light Stage for Accurate BTF Measurement on Site

PubMed Central

Havran, Vlastimil; Hošek, Jan; Němcová, Šárka; Čáp, Jiří; Bittner, Jiří

2017-01-01

We propose a miniaturised light stage for measuring the bidirectional reflectance distribution function (BRDF) and the bidirectional texture function (BTF) of surfaces on site in real world application scenarios. The main principle of our lightweight BTF acquisition gantry is a compact hemispherical skeleton with cameras along the meridian and with light emitting diode (LED) modules shining light onto a sample surface. The proposed device is portable and achieves a high speed of measurement while maintaining high degree of accuracy. While the positions of the LEDs are fixed on the hemisphere, the cameras allow us to cover the range of the zenith angle from 0∘ to 75∘ and by rotating the cameras along the axis of the hemisphere we can cover all possible camera directions. This allows us to take measurements with almost the same quality as existing stationary BTF gantries. Two degrees of freedom can be set arbitrarily for measurements and the other two degrees of freedom are fixed, which provides a tradeoff between accuracy of measurements and practical applicability. Assuming that a measured sample is locally flat and spatially accessible, we can set the correct perpendicular direction against the measured sample by means of an auto-collimator prior to measuring. Further, we have designed and used a marker sticker method to allow for the easy rectification and alignment of acquired images during data processing. We show the results of our approach by images rendered for 36 measured material samples. PMID:28241466

The relationship of field burn severity measures to satellite-derived Burned Area Reflectance Classification (BARC) maps

Treesearch

Andrew Hudak; Penelope Morgan; Carter Stone; Pete Robichaud; Terrie Jain; Jess Clark

2004-01-01

Preliminary results are presented from ongoing research on spatial variability of fire effects on soils and vegetation from the Black Mountain Two and Cooney Ridge wildfires, which burned in western Montana during the 2003 fire season. Extensive field fractional cover data were sampled to assess the efficacy of quantitative satellite image-derived indicators of burn...

MODIS tasselled cap: land cover characteristics expressed through transformed MODIS data

Treesearch

S. E. Lobser; W. B. Cohen

2007-01-01

The tasselled cap concept is extended to Moderate Resolution Imaging Spectroradiometer (MODIS) Nadir BRDF-Adjusted Reflectance (NBAR, MOD43) data. The transformation is based on a rigid rotation of principal component axes (PCAs) derived from a global sample spanning one full year of NBAR 16-day composites. To provide a standard for MODIS tasselled cap axes, we...

Effect of using different cover image quality to obtain robust selective embedding in steganography

NASA Astrophysics Data System (ADS)

Abdullah, Karwan Asaad; Al-Jawad, Naseer; Abdulla, Alan Anwer

2014-05-01

One of the common types of steganography is to conceal an image as a secret message in another image which normally called a cover image; the resulting image is called a stego image. The aim of this paper is to investigate the effect of using different cover image quality, and also analyse the use of different bit-plane in term of robustness against well-known active attacks such as gamma, statistical filters, and linear spatial filters. The secret messages are embedded in higher bit-plane, i.e. in other than Least Significant Bit (LSB), in order to resist active attacks. The embedding process is performed in three major steps: First, the embedding algorithm is selectively identifying useful areas (blocks) for embedding based on its lighting condition. Second, is to nominate the most useful blocks for embedding based on their entropy and average. Third, is to select the right bit-plane for embedding. This kind of block selection made the embedding process scatters the secret message(s) randomly around the cover image. Different tests have been performed for selecting a proper block size and this is related to the nature of the used cover image. Our proposed method suggests a suitable embedding bit-plane as well as the right blocks for the embedding. Experimental results demonstrate that different image quality used for the cover images will have an effect when the stego image is attacked by different active attacks. Although the secret messages are embedded in higher bit-plane, but they cannot be recognised visually within the stegos image.

Mapping vegetation cover and biomass on the Qinghai-Tibet-Plateau using hyperspectral measurements and multispectral satellite images

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Lehnert, Lukas W.; Wang, Yun; Reudenbach, Christoph; Nauss, Thomas; Bendix, Jörg

2016-04-01

Pastoralism is the dominant land-use on the Qinghai-Tibet-Plateau (QTP) providing the major economic resource for the local population. However, the pastures are highly supposed to be affected by ongoing degradation whose extent is still disputed. This study uses hyperspectral in situ measurements and multispectral satellite images to assess vegetation cover and above ground biomass (AGB) as proxies of pasture degradation on a regional scale. Using Random Forests in conjunction with recursive feature selection as modeling tool, it is tested whether the full hyperspectral information is needed or if multispectral information is sufficient to accurately estimate vegetation cover and AGB. To regionalize pasture degradation proxies, the transferability of the locally derived models to high resolution multispectral satellite data is assessed. For this purpose, 1183 hyperspectral measurements and vegetation records were sampled at 18 locations on the QTP. AGB was determined on 25 0.5x0.5m plots. Proxies for pasture degradation were derived from the spectra by calculating narrow-band indices (NBI). Using the NBI as predictor variables vegetation cover and AGB were modeled. Models were calculated using the hyperspectral data as well as the same data resampled to WorldView-2, QuickBird and RapidEye channels. The hyperspectral results were compared to the multispectral results. Finally, the models were applied to satellite data to map vegetation cover and AGB on a regional scale. Vegetation cover was accurately predicted by Random Forest if hyperspectral measurements were used. In contrast, errors in AGB estimations were considerably higher. Only small differences in accuracy were observed between the models based on hyper- compared to multispectral data. The application of the models to satellite images generally resulted in an increase of the estimation error. Though this reflects the challenge of applying in situ measurements to satellite data, the results still show a high potential to map pasture degradation proxies on the QTP even for larger scales.

Historical Analysis of Melt Pond Fraction on Arctic Sea Ice Through the Synthesis of High- and Medium- Resolution Optical Satellite Remote Sensing.

NASA Astrophysics Data System (ADS)

Wright, N.; Polashenski, C. M.

2017-12-01

Snow, ice, and melt ponds cover the surface of the Arctic Ocean in fractions that change throughout the seasons. These surfaces exert tremendous influence over the energy balance of the Arctic Ocean by controlling the absorption of solar radiation. Here we demonstrate the use of a newly released, open source, image classification algorithm designed to identify surface features in high resolution optical satellite imagery of sea ice. Through explicitly resolving individual features on the surface, the algorithm can determine the percentage of ice that is covered by melt ponds with a high degree of certainty. We then compare observations of melt pond fraction extracted from these images with an established method of estimating melt pond fraction from medium resolution satellite images (e.g. MODIS). Because high resolution satellite imagery does not provide the spatial footprint needed to examine the entire Arctic basin, we propose a method of synthesizing both high and medium resolution satellite imagery for an improved determination of melt pond fraction across whole Arctic. We assess the historical trends of melt pond fraction in the Arctic ocean, and address the question: Is pond coverage changing in response to changing ice conditions? Furthermore, we explore the image area that must be observed in order to get a locally representative sample (i.e. the aggregate scale), and show that it is possible to determine accurate estimates of melt pond fraction by observing sample areas significantly smaller than the typical footprint of high-resolution satellite imagery.

a Framework of Change Detection Based on Combined Morphologica Features and Multi-Index Classification

NASA Astrophysics Data System (ADS)

Li, S.; Zhang, S.; Yang, D.

2017-09-01

Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI), the differential water index (NDWI) are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

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.

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.

Inexpensive Tools To Quantify And Map Vegetative Cover For Large-Scale Research Or Management Decisions.

USDA-ARS?s Scientific Manuscript database

Vegetative cover can be quantified quickly and consistently and often at lower cost with image analysis of color digital images than with visual assessments. Image-based mapping of vegetative cover for large-scale research and management decisions can now be considered with the accuracy of these met...

BOREAS Level-3s Landsat TM Imagery Scaled At-sensor Radiance in LGSOWG Format

NASA Technical Reports Server (NTRS)

Nickeson, Jaime; Knapp, David; Newcomer, Jeffrey A.; Cihlar, Josef; Hall, Forrest G. (Editor)

2000-01-01

For BOReal Ecosystem-Atmosphere Study (BOREAS),the level-3s Landsat Thematic Mapper (TM) data, along with the other remotely sensed images,were collected in order to provide spatially extensive information over the primary study areas. This information includes radiant energy,detailed land cover, and biophysical parameter maps such as Fraction of Photosynthetically Active Radiation (FPAR) and Leaf area Index (LAI). CCRS collected and supplied the level-3s images to BOREAS for use in the remote sensing research activities. Geographically,the bulk of the level-3s images cover the BOREAS Northern Study Area (NSA) and Southern Study Area (SSA) with a few images covering the area between the NSA and SSA. Temporally,the images cover the period of 22-Jun-1984 to 30-Jul-1996. The images are available in binary,image-format files.

Formation of the Periotic Space During the Early Fetal Period in Humans.

PubMed

Ishikawa, Aoi; Ohtsuki, Sae; Yamada, Shigehito; Uwabe, Chigako; Imai, Hirohiko; Matsuda, Tetsuya; Takakuwa, Tetsuya

2018-04-01

The inner ear is a very complicated structure, composed of a bony labyrinth (otic capsule; OC), membranous labyrinth, with a space between them, named the periotic labyrinth or periotic space. We investigated how periotic tissue fluid spaces covered the membranous labyrinth three-dimensionally, leading to formation of the periotic labyrinth encapsulated in the OC during human fetal development. Digital data sets from magnetic resonance images and phase-contrast X-ray tomography images of 24 inner ear organs from 24 human fetuses from the Kyoto Collection (fetuses in trimesters 1 and 2; crown-rump length: 14.4-197 mm) were analyzed. The membranous labyrinth was morphologically differentiated in samples at the end of the embryonic period (Carnegie stage 23), and had grown linearly to more than eight times in size during the observation period. The periotic space was first detected at the 35-mm samples, around the vestibule and basal turn of the cochlea, which elongated rapidly to the tip of the cochlea and semicircular ducts, successively, and almost covered the membranous labyrinth at the 115-mm CRL stage or later. In those samples, several ossification centers were detected around the space. This article thus demonstrated that formation of the membranous labyrinth, periotic space (labyrinth), and ossification of the OC occurs successively, according to an intricate timetable. Anat Rec, 301:563-570, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

In Situ Visualization of the Local Photothermal Effect Produced on α-Cyclodextrin Inclusion Compound Associated with Gold Nanoparticles.

PubMed

Silva, Nataly; Muñoz, Camila; Diaz-Marcos, Jordi; Samitier, Josep; Yutronic, Nicolás; Kogan, Marcelo J; Jara, Paul

2016-12-01

Evidence of guest migration in α-cyclodextrin-octylamine (α-CD-OA) inclusion compound (IC) generated via plasmonic heating of gold nanoparticles (AuNPs) has been studied. In this report, we demonstrate local effects generated by laser-mediated irradiation of a sample of AuNPs covered with inclusion compounds on surface-derivatized glass under liquid conditions by atomic force microscopy (AFM). Functionalized AuNPs on the glass and covered by the ICs were monitored by recording images by AFM during 5 h of irradiation, and images showed that after irradiation, a drastic decrease in the height of the AuNPs occurred. The absorption spectrum of the irradiated sample showed a hypsochromic shift from 542 to 536 nm, evidence suggesting that much of the population of nanoparticles lost all of the parts of the overlay of ICs due to the plasmonic heat generated by the irradiation. Mass spectrometry matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) performed on a sample containing a collection of drops obtained from the surface of the functionalized glass provided evidence that the irradiation lead to disintegration of the ICs and therefore exit of the octylamine molecule (the guest) from the cyclodextrin cavity (the matrix). Graphical Abstract Atomic Force Microscopy observation of the disintegration of a cyclodextrin inclusion compound by gold nanoparticles photothermal effect.

Carbon mapping of Argentine savannas: Using fractional tree cover to scale from field to region

NASA Astrophysics Data System (ADS)

González-Roglich, M.; Swenson, J. J.

2015-12-01

Programs which intend to maintain or enhance carbon (C) stocks in natural ecosystems are promising, but require detailed and spatially explicit C distribution models to monitor the effectiveness of management interventions. Savanna ecosystems are significant components of the global C cycle, covering about one fifth of the global land mass, but they have received less attention in C monitoring protocols. Our goal was to estimate C storage across a broad savanna ecosystem using field surveys and freely available satellite images. We first mapped tree canopies at 2.5 m resolution with a spatial subset of high resolution panchromatic images to then predict regional wall-to-wall tree percent cover using 30-m Landsat imagery and the Random Forests algorithms. We found that a model with summer and winter spectral indices from Landsat, climate and topography performed best. Using a linear relationship between C and % tree cover, we then predicted tree C stocks across the gradient of tree cover, explaining 87 % of the variability. The spatially explicit validation of the tree C model with field-measured C-stocks revealed an RMSE of 8.2 tC/ha which represented ~30% of the mean C stock for areas with tree cover, comparable to studies based on more advanced remote sensing methods, such as LiDAR and RADAR. Sample spatial distribution highly affected the performance of the RF models in predicting tree cover, raising concerns regarding the predictive capabilities of the model in areas for which training data is not present. The 50,000 km2 has ~41 Tg C, which could be released to the atmosphere if agricultural pressure intensifies in this semiarid savanna.

The Enceladus Atlas

NASA Image and Video Library

2010-05-13

This map sheet covers a 15-series image set covering the entire surface of Enceladus. The map data was acquired by NASA Cassini imaging experiment. Individual images can be viewed via the Photojournal.

Developing a New North American Land Cover Product at 30m Resolution: Methods, Results and Future Plans

NASA Astrophysics Data System (ADS)

Homer, C.; Colditz, R. R.; Latifovic, R.; Llamas, R. M.; Pouliot, D.; Danielson, P.; Meneses, C.; Victoria, A.; Ressl, R.; Richardson, K.; Vulpescu, M.

2017-12-01

Land cover and land cover change information at regional and continental scales has become fundamental for studying and understanding the terrestrial environment. With recent advances in computer science and freely available image archives, continental land cover mapping has been advancing to higher spatial resolution products. The North American Land Change Monitoring System (NALCMS) remains the principal provider of seamless land cover maps of North America. Founded in 2006, this collaboration among the governments of Canada, Mexico and the United States has released two previous products based on 250m MODIS images, including a 2005 land cover and a 2005-2010 land cover change product. NALCMS has recently completed the next generation North America land cover product, based upon 30m Landsat images. This product now provides the first ever 30m land cover produced for the North American continent, providing 19 classes of seamless land cover. This presentation provides an overview of country-specific image classification processes, describes the continental map production process, provides results for the North American continent and discusses future plans. NALCMS is coordinated by the Commission for Environmental Cooperation (CEC) and all products can be obtained at their website - www.cec.org.

VizieR Online Data Catalog: NIR spectral analysis of star-forming galaxies (Genzel+, 2014)

NASA Astrophysics Data System (ADS)

Genzel, R.; Forster Schreiber, N. M.; Rosario, D.; Lang, P.; Lutz, D.; Wisnioski, E.; Wuyts, E.; Wuyts, S.; Bandara, K.; Bender, R.; Berta, S.; Kurk, J.; Mendel, J. T.; Tacconi, L. J.; Wilman, D.; Beifiori, A.; Brammer, G.; Burkert, A.; Buschkamp, P.; Chan, J.; Carollo, C. M.; Davies, R.; Eisenhauer, F.; Fabricius, M.; Fossati, M.; Kriek, M.; Kulkarni, S.; Lilly, S. J.; Mancini, C.; Momcheva, I.; Naab, T.; Nelson, E. J.; Renzini, A.; Saglia, R.; Sharples, R. M.; Sternberg, A.; Tacchella, S.; van Dokkum, P.

2017-02-01

For the analysis in this paper, we included a total of 110 SFGs at z~1-3 with near-IR integral field or slit spectroscopy covering the Hα+[NII] line emission from surveys carried out with SINFONI, KMOS, LUCI, and GNIRS. The targets for these surveys were originally drawn from rest-frame optical, UV, and near-IR selected samples in broadband imaging surveys with optical spectroscopic redshifts, and from stellar mass-selected samples with near-IR or optical spectroscopic redshifts. (2 data files).

VizieR Online Data Catalog: Galaxies and QSOs FIR size and surface brightness (Lutz+, 2016)

NASA Astrophysics Data System (ADS)

Lutz, D.; Berta, S.; Contursi, A.; Forster Schreiber, N. M.; Genzel, R.; Gracia-Carpio, J.; Herrera-Camus, R.; Netzer, H.; Sturm, E.; Tacconi, L. J.; Tadaki, K.; Veilleux, S.

2016-08-01

We use 70, 100, and 160um images from scan maps obtained with PACS on board Herschel, collecting archival data from various projects. In order to cover a wide range of galaxy properties, we first obtain an IR-selected local sample ranging from normal galaxies up to (ultra)luminous infrared galaxies. For that purpose, we searched the Herschel archive for all cz>=2000km/s objects from the IRAS Revised Bright Galaxy Sample (RBGS, Sanders et al., 2003, Cat. J/AJ/126/1607). (1 data file).

Accuracy assessment, using stratified plurality sampling, of portions of a LANDSAT classification of the Arctic National Wildlife Refuge Coastal Plain

NASA Technical Reports Server (NTRS)

Card, Don H.; Strong, Laurence L.

1989-01-01

An application of a classification accuracy assessment procedure is described for a vegetation and land cover map prepared by digital image processing of LANDSAT multispectral scanner data. A statistical sampling procedure called Stratified Plurality Sampling was used to assess the accuracy of portions of a map of the Arctic National Wildlife Refuge coastal plain. Results are tabulated as percent correct classification overall as well as per category with associated confidence intervals. Although values of percent correct were disappointingly low for most categories, the study was useful in highlighting sources of classification error and demonstrating shortcomings of the plurality sampling method.

Imaging Extended Emission-Line Regions of Obscured AGN with the Subaru Hyper Suprime-Cam Survey

NASA Astrophysics Data System (ADS)

Sun, Ai-Lei; Greene, Jenny E.; Zakamska, Nadia L.; Goulding, Andy; Strauss, Michael A.; Huang, Song; Johnson, Sean; Kawaguchi, Toshihiro; Matsuoka, Yoshiki; Marsteller, Alisabeth A.; Nagao, Tohru; Toba, Yoshiki

2018-05-01

Narrow-line regions excited by active galactic nuclei (AGN) are important for studying AGN photoionization and feedback. Their strong [O III] lines can be detected with broadband images, allowing morphological studies of these systems with large-area imaging surveys. We develop a new broad-band imaging technique to reconstruct the images of the [O III] line using the Subaru Hyper Suprime-Cam (HSC) Survey aided with spectra from the Sloan Digital Sky Survey (SDSS). The technique involves a careful subtraction of the galactic continuum to isolate emission from the [O III]λ5007 and [O III]λ4959 lines. Compared to traditional targeted observations, this technique is more efficient at covering larger samples without dedicated observational resources. We apply this technique to an SDSS spectroscopically selected sample of 300 obscured AGN at redshifts 0.1 - 0.7, uncovering extended emission-line region candidates with sizes up to tens of kpc. With the largest sample of uniformly derived narrow-line region sizes, we revisit the narrow-line region size - luminosity relation. The area and radii of the [O III] emission-line regions are strongly correlated with the AGN luminosity inferred from the mid-infrared (15 μm rest-frame) with a power-law slope of 0.62^{+0.05}_{-0.06}± 0.10 (statistical and systematic errors), consistent with previous spectroscopic findings. We discuss the implications for the physics of AGN emission-line regions and future applications of this technique, which should be useful for current and next-generation imaging surveys to study AGN photoionization and feedback with large statistical samples.

Cloud cover and solar disk state estimation using all-sky images: deep neural networks approach compared to routine methods

NASA Astrophysics Data System (ADS)

Krinitskiy, Mikhail; Sinitsyn, Alexey

2017-04-01

Shortwave radiation is an important component of surface heat budget over sea and land. To estimate them accurate observations of cloud conditions are needed including total cloud cover, spatial and temporal cloud structure. While massively observed visually, for building accurate SW radiation parameterizations cloud structure needs also to be quantified using precise instrumental measurements. While there already exist several state of the art land-based cloud-cameras that satisfy researchers needs, their major disadvantages are associated with inaccuracy of all-sky images processing algorithms which typically result in the uncertainties of 2-4 octa of cloud cover estimates with the resulting true-scoring cloud cover accuracy of about 7%. Moreover, none of these algorithms determine cloud types. We developed an approach for cloud cover and structure estimating, which provides much more accurate estimates and also allows for measuring additional characteristics. This method is based on the synthetic controlling index, namely the "grayness rate index", that we introduced in 2014. Since then this index has already demonstrated high efficiency being used along with the technique namely the "background sunburn effect suppression", to detect thin clouds. This made it possible to significantly increase the accuracy of total cloud cover estimation in various sky image states using this extension of routine algorithm type. Errors for the cloud cover estimates significantly decreased down resulting the mean squared error of about 1.5 octa. Resulting true-scoring accuracy is more than 38%. The main source of this approach uncertainties is the solar disk state determination errors. While the deep neural networks approach lets us to estimate solar disk state with 94% accuracy, the final result of total cloud estimation still isn`t satisfying. To solve this problem completely we applied the set of machine learning algorithms to the problem of total cloud cover estimation directly. The accuracy of this approach varies depending on algorithm choice. Deep neural networks demonstrated the best accuracy of more than 96%. We will demonstrate some approaches and the most influential statistical features of all-sky images that lets the algorithm reach that high accuracy. With the use of our new optical package a set of over 480`000 samples has been collected in several sea missions in 2014-2016 along with concurrent standard human observed and instrumentally recorded meteorological parameters. We will demonstrate the results of the field measurements and will discuss some still remaining problems and the potential of the further developments of machine learning approach.

GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa Watershed, Ethiopia.

PubMed

Nigatu Wondrade; Dick, Øystein B; Tveite, Havard

2014-03-01

Classifying multi-temporal image data to produce thematic maps and quantify land cover changes is one of the most common applications of remote sensing. Mapping land cover changes at the regional level is essential for a wide range of applications including land use planning, decision making, land cover database generation, and as a source of information for sustainable management of natural resources. Land cover changes in Lake Hawassa Watershed, Southern Ethiopia, were investigated using Landsat MSS image data of 1973, and Landsat TM images of 1985, 1995, and 2011, covering a period of nearly four decades. Each image was partitioned in a GIS environment, and classified using an unsupervised algorithm followed by a supervised classification method. A hybrid approach was employed in order to reduce spectral confusion due to high variability of land cover. Classification of satellite image data was performed integrating field data, aerial photographs, topographical maps, medium resolution satellite image (SPOT 20 m), and visual image interpretation. The image data were classified into nine land cover types: water, built-up, cropland, woody vegetation, forest, grassland, swamp, bare land, and scrub. The overall accuracy of the LULC maps ranged from 82.5 to 85.0 %. The achieved accuracies were reasonable, and the observed classification errors were attributable to coarse spatial resolution and pixels containing a mixture of cover types. Land cover change statistics were extracted and tabulated using the ERDAS Imagine software. The results indicated an increase in built-up area, cropland, and bare land areas, and a reduction in the six other land cover classes. Predominant land cover is cropland changing from 43.6 % in 1973 to 56.4 % in 2011. A significant portion of land cover was converted into cropland. Woody vegetation and forest cover which occupied 21.0 and 10.3 % in 1973, respectively, diminished to 13.6 and 5.6 % in 2011. The change in water body was very peculiar in that the area of Lake Hawassa increased from 91.9 km(2) in 1973 to 95.2 km(2) in 2011, while that of Lake Cheleleka whose area was 11.3 km(2) in 1973 totally vanished in 2011 and transformed into mud-flat and grass dominated swamp. The "change and no change" analysis revealed that more than one third (548.0 km(2)) of the total area was exposed to change between 1973 and 2011. This study was useful in identifying the major land cover changes, and the analysis pursued provided a valuable insight into the ongoing changes in the area under investigation.

Microfabricated endoscopic probe integrated MEMS micromirror for optical coherence tomography bioimaging.

PubMed

Wang, Ming-Fang; Xu, Yingshun; Prem, C S; Chen, Kelvin Wei Sheng; Xie, Jin; Mu, Xiaojing; Tan, Chee Wei; Yu, Aibin; Feng, Hanhua

2010-01-01

In this paper, we present a miniaturized endoscopic probe, consisted of MEMS micromirror, silicon optical bench (SiOB), grade index (GRIN) lens, single mode optical fiber (SMF) and transparent housing, for optical coherence tomography (OCT) bioimaging. Due to the use of the MEMS micromirror, the endoscopic OCT system is highly suitable for non-invasive imaging diagnosis of a wide variety of inner organs. The probe engineering and proof of concept were demonstrated by obtaining the two-dimensional OCT images with a cover slide and an onion used as standard samples and the axial resolution was around 10µm.

Potential and limitations of webcam images for snow cover monitoring in the Swiss Alps

NASA Astrophysics Data System (ADS)

Dizerens, Céline; Hüsler, Fabia; Wunderle, Stefan

2017-04-01

In Switzerland, several thousands of outdoor webcams are currently connected to the Internet. They deliver freely available images that can be used to analyze snow cover variability on a high spatio-temporal resolution. To make use of this big data source, we have implemented a webcam-based snow cover mapping procedure, which allows to almost automatically derive snow cover maps from such webcam images. As there is mostly no information about the webcams and its parameters available, our registration approach automatically resolves these parameters (camera orientation, principal point, field of view) by using an estimate of the webcams position, the mountain silhouette, and a high-resolution digital elevation model (DEM). Combined with an automatic snow classification and an image alignment using SIFT features, our procedure can be applied to arbitrary images to generate snow cover maps with a minimum of effort. Resulting snow cover maps have the same resolution as the digital elevation model and indicate whether each grid cell is snow-covered, snow-free, or hidden from webcams' positions. Up to now, we processed images of about 290 webcams from our archive, and evaluated images of 20 webcams using manually selected ground control points (GCPs) to evaluate the mapping accuracy of our procedure. We present methodological limitations and ongoing improvements, show some applications of our snow cover maps, and demonstrate that webcams not only offer a great opportunity to complement satellite-derived snow retrieval under cloudy conditions, but also serve as a reference for improved validation of satellite-based approaches.

Snow cover of the Upper Colorado River Basin from satellite passive microwave and visual imagery

USGS Publications Warehouse

Josberger, E.G.; Beauvillain, E.

1989-01-01

A comparison of passive microwave images from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and visual images from the Defense Meteorological Satellite Program (DMSP) of the Upper Colorado River Basin shows that passive microwave satellite imagery can be used to determine the extent of the snow cover. Eight cloud-free DMSP images throughout the winter of 1985-1986 show the extent of the snowpack, which, when compared to the corresponding SMMR images, determine the threshold microwave characteristics for snow-covered pixels. With these characteristics, the 27 sequential SMMR images give a unique view of the temporal history of the snow cover extent through the first half of the water year. -from Authors

Energy-filtered real- and k-space secondary and energy-loss electron imaging with Dual Emission Electron spectro-Microscope: Cs/Mo(110).

PubMed

Grzelakowski, Krzysztof P

2016-05-01

Since its introduction the importance of complementary k||-space (LEED) and real space (LEEM) information in the investigation of surface science phenomena has been widely demonstrated over the last five decades. In this paper we report the application of a novel kind of electron spectromicroscope Dual Emission Electron spectroMicroscope (DEEM) with two independent electron optical channels for reciprocal and real space quasi-simultaneous imaging in investigation of a Cs covered Mo(110) single crystal by using the 800eV electron beam from an "in-lens" electron gun system developed for the sample illumination. With the DEEM spectromicroscope it is possible to observe dynamic, irreversible processes at surfaces in the energy-filtered real space and in the corresponding energy-filtered kǁ-space quasi-simultaneously in two independent imaging columns. The novel concept of the high energy electron beam sample illumination in the cathode lens based microscopes allows chemically selective imaging and analysis under laboratory conditions. Copyright © 2015 Elsevier B.V. All rights reserved.

Global, long-term Earth Science Data Records of forest cover, change, and fragmentation from Landsat: the Global Forest Cover Change Project

NASA Astrophysics Data System (ADS)

Sexton, J.; Huang, C.; Channan, S.; Feng, M.; Song, X.; Kim, D.; Song, D.; Vermote, E.; Masek, J.; Townshend, J. R.

2013-12-01

Monitoring, analysis, and management of forests require measurements of forest cover that are both spatio-temporally consistent and resolved globally at sub-hectare resolution. The Global Forest Cover Change project, a cooperation between the University of Maryland Global Land Cover Facility and NASA Goddard Space Flight Center, is providing the first long-term, sub-hectare, globally consistent data records of forest cover, change, and fragmentation in circa-1975, -1990, -2000, and -2005 epochs. These data are derived from the Global Land Survey collection of Landsat images in the respective epochs, atmospherically corrected to surface reflectance in 1990, 2000, and 2005 using the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) implementation of the 6S radiative transfer algorithm, with ancillary information from MODIS Land products, ASTER Global Digital Elevation Model (GDEM), and climatological data layers. Forest cover and change were estimated by a novel continuous-field approach, which produced for the 2000 and 2005 epochs the world's first global, 30-m resolution database of tree cover. Surface reflectance estimates were validated against coincident MODIS measurements, the results of which have been corroborated by subsequent, independent validations against measurements from AERONET sites. Uncertainties in tree- and forest-cover values were estimated in each pixel as a compounding of within-sample uncertainty and accuracy relative to a sample of independent measurements from small-footprint lidar. Accuracy of forest cover and change estimates was further validated relative to expert-interpreted high-resolution imagery, from which unbiased estimates of forest cover and change have been produced at national and eco-regional scales. These first-of-kind Earth Science Data Records--surface reflectance in 1990, 2000, and 2005 and forest cover, change, and fragmentation in and between 1975, 1990, 2000, and 2005--are hosted at native, Landsat resolution for free public access at the Global Land Cover Facility website (www.landcover.org). Global mosaic of circa-2000, Landsat-based estimates of tree cover. Gaps due to clouds and/or snow in each scene were filled first with Landsat-based data from overlapping paths, and the remaining gaps were filled with data from the MODIS VCF Tree Cover layer in 2000.

The evaluation of alternate methodologies for land cover classification in an urbanizing area

NASA Technical Reports Server (NTRS)

Smekofski, R. M.

1981-01-01

The usefulness of LANDSAT in classifying land cover and in identifying and classifying land use change was investigated using an urbanizing area as the study area. The question of what was the best technique for classification was the primary focus of the study. The many computer-assisted techniques available to analyze LANDSAT data were evaluated. Techniques of statistical training (polygons from CRT, unsupervised clustering, polygons from digitizer and binary masks) were tested with minimum distance to the mean, maximum likelihood and canonical analysis with minimum distance to the mean classifiers. The twelve output images were compared to photointerpreted samples, ground verified samples and a current land use data base. Results indicate that for a reconnaissance inventory, the unsupervised training with canonical analysis-minimum distance classifier is the most efficient. If more detailed ground truth and ground verification is available, the polygons from the digitizer training with the canonical analysis minimum distance is more accurate.

A study on high NA and evanescent imaging with polarized illumination

NASA Astrophysics Data System (ADS)

Yang, Seung-Hune

Simulation techniques are developed for high NA polarized microscopy with Babinet's principle, partial coherence and vector diffraction for non-periodic geometries. A mathematical model for the Babinet approach is developed and interpreted. Simulation results of the Babinet's principle approach are compared with those of Rigorous Coupled Wave Theory (RCWT) for periodic structures to investigate the accuracy of this approach and its limitations. A microscope system using a special solid immersion lens (SIL) is introduced to image Blu-Ray (BD) optical disc samples without removing the protective cover layer. Aberration caused by the cover layer is minimized with a truncated SIL. Sub-surface imaging simulation is achieved by RCWT, partial coherence, vector diffraction and Babinet's Principle. Simulated results are compared with experimental images and atomic force microscopy (AFM) measurement. A technique for obtaining native and induced using a significant amount of evanescent energy is described for a solid immersion lens (SIL) microscope. Characteristics of native and induced polarization images for different object structures and materials are studied in detail. Experiments are conducted with a NA = 1.48 at lambda = 550nm microscope. Near-field images are simulated and analyzed with an RCWT approach. Contrast curve versus object spatial frequency calculations are compared with experimental measurements. Dependencies of contrast versus source polarization angles and air gap for native and induced polarization image profiles are evaluated. By using the relationship between induced polarization and topographical structure, an induced polarization image of an alternating phase shift mask (PSM) is converted into a topographical image, which shows very good agreement with AFM measurement. Images of other material structures include a dielectric grating, chrome-on-glass grating, silicon CPU structure, BD-R and BD-ROM.

Enhanced encrypted reversible data hiding algorithm with minimum distortion through homomorphic encryption

NASA Astrophysics Data System (ADS)

Bhardwaj, Rupali

2018-03-01

Reversible data hiding means embedding a secret message in a cover image in such a manner, to the point that in the midst of extraction of the secret message, the cover image and, furthermore, the secret message are recovered with no error. The goal of by far most of the reversible data hiding algorithms is to have improved the embedding rate and enhanced visual quality of stego image. An improved encrypted-domain-based reversible data hiding algorithm to embed two binary bits in each gray pixel of original cover image with minimum distortion of stego-pixels is employed in this paper. Highlights of the proposed algorithm are minimum distortion of pixel's value, elimination of underflow and overflow problem, and equivalence of stego image and cover image with a PSNR of ∞ (for Lena, Goldhill, and Barbara image). The experimental outcomes reveal that in terms of average PSNR and embedding rate, for natural images, the proposed algorithm performed better than other conventional ones.

USGS Spectral Library Version 7

USGS Publications Warehouse

Kokaly, Raymond F.; Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Hoefen, Todd M.; Pearson, Neil C.; Wise, Richard A.; Benzel, William M.; Lowers, Heather A.; Driscoll, Rhonda L.; Klein, Anna J.

2017-04-10

We have assembled a library of spectra measured with laboratory, field, and airborne spectrometers. The instruments used cover wavelengths from the ultraviolet to the far infrared (0.2 to 200 microns [μm]). Laboratory samples of specific minerals, plants, chemical compounds, and manmade materials were measured. In many cases, samples were purified, so that unique spectral features of a material can be related to its chemical structure. These spectro-chemical links are important for interpreting remotely sensed data collected in the field or from an aircraft or spacecraft. This library also contains physically constructed as well as mathematically computed mixtures. Four different spectrometer types were used to measure spectra in the library: (1) Beckman™ 5270 covering the spectral range 0.2 to 3 µm, (2) standard, high resolution (hi-res), and high-resolution Next Generation (hi-resNG) models of Analytical Spectral Devices (ASD) field portable spectrometers covering the range from 0.35 to 2.5 µm, (3) Nicolet™ Fourier Transform Infra-Red (FTIR) interferometer spectrometers covering the range from about 1.12 to 216 µm, and (4) the NASA Airborne Visible/Infra-Red Imaging Spectrometer AVIRIS, covering the range 0.37 to 2.5 µm. Measurements of rocks, soils, and natural mixtures of minerals were made in laboratory and field settings. Spectra of plant components and vegetation plots, comprising many plant types and species with varying backgrounds, are also in this library. Measurements by airborne spectrometers are included for forested vegetation plots, in which the trees are too tall for measurement by a field spectrometer. This report describes the instruments used, the organization of materials into chapters, metadata descriptions of spectra and samples, and possible artifacts in the spectral measurements. To facilitate greater application of the spectra, the library has also been convolved to selected spectrometer and imaging spectrometers sampling and bandpasses, and resampled to selected broadband multispectral sensors. The native file format of the library is the SPECtrum Processing Routines (SPECPR) data format. This report describes how to access freely available software to read the SPECPR format. To facilitate broader access to the library, we produced generic formats of the spectra and metadata in text files. The library is provided on digital media and online at https://speclab.cr.usgs.gov/spectral-lib.html. A long-term archive of these data are stored on the USGS ScienceBase data server (https://dx.doi.org/10.5066/F7RR1WDJ).

Evaluation of NinePoint Medical's Nvision VLE device for gastrointestinal applications.

PubMed

Mosko, Jeffrey D; Pleskow, Douglas

2017-07-01

The incidence of esophageal adenocarcinoma (EAC) has increased over the last few decades. With a known precursor lesion, Barrett's esophagus, this remains a target for screening and surveillance with the goal of detecting and providing curative treatment for early neoplasia. Areas covered: Current surveillance techniques rely on white light endoscopy and random tissue sampling which is time consuming, costly and prone to sampling error. Volumetric laser endomicroscopy (VLE), a second-generation optical coherence technology, has emerged as an advanced imaging modality with the potential to improve dysplasia detection, surveillance and subsequently prevent esophageal adenocarcinoma. This review will focus on the use of VLE for advanced imaging of Barrett's esophagus and summarize its current and potential uses elsewhere in the GI tract. Expert commentary: NinePoint's VLE imaging device enables imaging of large segments of BE facilitating identification of luminal and subsurface abnormalities that may have otherwise been missed. Its diagnostic accuracy is improving and laser-marking system adds the capacity for accurate VLE-histologic correlation. With the adoption of dysplasia scoring systems that utilize very few VLE imaging features, inexperienced endoscopists will likely be able to pick out areas concerning for dysplasia to target therapy.

BOREAS Level-3b Landsat TM Imagery: At-sensor Radiances in BSQ Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime; Knapp, David; Newcomer, Jeffrey A.; Cihlar, Josef

2000-01-01

For BOREAS, the level-3b Landsat TM data, along with the other remotely sensed images, were collected in order to provide spatially extensive information over the primary study areas. This information includes radiant energy, detailed land cover, and biophysical parameter maps such as FPAR and LAI. Although very similar in content to the level-3a Landsat TM products, the level-3b images were created to provide users with a directly usable at-sensor radiance image. Geographically, the level-3b images cover the BOREAS NSA and SSA. Temporally, the images cover the period of 22-Jun-1984 to 09-Jul-1996. The images are available in binary, image format files.

Urban Land Cover/use Change Detection Using High Resolution SPOT 5 and SPOT 6 Images and Urban Atlas Nomenclature

NASA Astrophysics Data System (ADS)

Akay, S. S.; Sertel, E.

2016-06-01

Urban land cover/use changes like urbanization and urban sprawl have been impacting the urban ecosystems significantly therefore determination of urban land cover/use changes is an important task to understand trends and status of urban ecosystems, to support urban planning and to aid decision-making for urban-based projects. High resolution satellite images could be used to accurately, periodically and quickly map urban land cover/use and their changes by time. This paper aims to determine urban land cover/use changes in Gaziantep city centre between 2010 and 2105 using object based images analysis and high resolution SPOT 5 and SPOT 6 images. 2.5 m SPOT 5 image obtained in 5th of June 2010 and 1.5 m SPOT 6 image obtained in 7th of July 2015 were used in this research to precisely determine land changes in five-year period. In addition to satellite images, various ancillary data namely Normalized Difference Vegetation Index (NDVI), Difference Water Index (NDWI) maps, cadastral maps, OpenStreetMaps, road maps and Land Cover maps, were integrated into the classification process to produce high accuracy urban land cover/use maps for these two years. Both images were geometrically corrected to fulfil the 1/10,000 scale geometric accuracy. Decision tree based object oriented classification was applied to identify twenty different urban land cover/use classes defined in European Urban Atlas project. Not only satellite images and satellite image-derived indices but also different thematic maps were integrated into decision tree analysis to create rule sets for accurate mapping of each class. Rule sets of each satellite image for the object based classification involves spectral, spatial and geometric parameter to automatically produce urban map of the city centre region. Total area of each class per related year and their changes in five-year period were determined and change trend in terms of class transformation were presented. Classification accuracy assessment was conducted by creating a confusion matrix to illustrate the thematic accuracy of each class.

Terahertz imaging system based on a backward-wave oscillator.

PubMed

Dobroiu, Adrian; Yamashita, Masatsugu; Ohshima, Yuichi N; Morita, Yasuyuki; Otani, Chiko; Kawase, Kodo

2004-10-20

We present an imaging system designed for use in the terahertz range. As the radiation source a backward-wave oscillator was chosen for its special features such as high output power, good wave-front quality, good stability, and wavelength tunability from 520 to 710 GHz. Detection is achieved with a pyroelectric sensor operated at room temperature. The alignment procedure for the optical elements is described, and several methods to reduce the etalon effect that are inherent in monochromatic sources are discussed. The terahertz spot size in the sample plane is 550 microm (nearly the diffraction limit), and the signal-to-noise ratio is 10,000:1; other characteristics were also measured and are presented in detail. A number of preliminary applications are also shown that cover various areas: nondestructive real-time testing for plastic tubes and packaging seals; biological terahertz imaging of fresh, frozen, or freeze-dried samples; paraffin-embedded specimens of cancer tissue; and measurement of the absorption coefficient of water by use of a wedge-shaped cell.

City of Flagstaff Project: Ground Water Resource Evaluation, Remote Sensing Component

USGS Publications Warehouse

Chavez, Pat S.; Velasco, Miguel G.; Bowell, Jo-Ann; Sides, Stuart C.; Gonzalez, Rosendo R.; Soltesz, Deborah L.

1996-01-01

Many regions, cities, and towns in the Western United States need new or expanded water resources because of both population growth and increased development. Any tools or data that can help in the evaluation of an area's potential water resources must be considered for this increasingly critical need. Remotely sensed satellite images and subsequent digital image processing have been under-utilized in ground water resource evaluation and exploration. Satellite images can be helpful in detecting and mapping an area's regional structural patterns, including major fracture and fault systems, two important geologic settings for an area's surface to ground water relations. Within the United States Geological Survey's (USGS) Flagstaff Field Center, expertise and capabilities in remote sensing and digital image processing have been developed over the past 25 years through various programs. For the City of Flagstaff project, this expertise and these capabilities were combined with traditional geologic field mapping to help evaluate ground water resources in the Flagstaff area. Various enhancement and manipulation procedures were applied to the digital satellite images; the results, in both digital and hardcopy format, were used for field mapping and analyzing the regional structure. Relative to surface sampling, remotely sensed satellite and airborne images have improved spatial coverage that can help study, map, and monitor the earth surface at local and/or regional scales. Advantages offered by remotely sensed satellite image data include: 1. a synoptic/regional view compared to both aerial photographs and ground sampling, 2. cost effectiveness, 3. high spatial resolution and coverage compared to ground sampling, and 4. relatively high temporal coverage on a long term basis. Remotely sensed images contain both spectral and spatial information. The spectral information provides various properties and characteristics about the surface cover at a given location or pixel (that is, vegetation and/or soil type). The spatial information gives the distribution, variation, and topographic relief of the cover types from pixel to pixel. Therefore, the main characteristics that determine a pixel's brightness/reflectance and, consequently, the digital number (DN) assigned to the pixel, are the physical properties of the surface and near surface, the cover type, and the topographic slope. In this application, the ability to detect and map lineaments, especially those related to fractures and faults, is critical. Therefore, the extraction of spatial information from the digital images was of prime interest in this project. The spatial information varies among the different spectral bands available; in particular, a near infrared spectral band is better than a visible band when extracting spatial information in highly vegetated areas. In this study, both visible and near infrared bands were analyzed and used to extract the desired spatial information from the images. The wide swath coverage of remotely sensed satellite digital images makes them ideal for regional analysis and mapping. Since locating and mapping highly fractured and faulted areas is a major requirement for ground water resource evaluation and exploration this aspect of satellite images was considered critical; it allowed us to stand back (actually up about 440 miles), look at, and map the regional structural setting of the area. The main focus of the remote sensing and digital image processing component of this project was to use both remotely sensed digital satellite images and a Digital Elevation Model (DEM) to extract spatial information related to the structural and topographic patterns in the area. The data types used were digital satellite images collected by the United States' Landsat Thematic Mapper (TM) and French Systeme Probatoire d'Observation de laTerre (SPOT) imaging systems, along with a DEM of the Flagstaff region. The USGS Mini Image Processing Sy

In vivo liver visualizations with magnetic particle imaging based on the calibration measurement approach

NASA Astrophysics Data System (ADS)

Dieckhoff, J.; Kaul, M. G.; Mummert, T.; Jung, C.; Salamon, J.; Adam, G.; Knopp, T.; Ludwig, F.; Balceris, C.; Ittrich, H.

2017-05-01

Magnetic particle imaging (MPI) facilitates the rapid determination of 3D in vivo magnetic nanoparticle distributions. In this work, liver MPI following intravenous injections of ferucarbotran (Resovist®) was studied. The image reconstruction was based on a calibration measurement, the so called system function. The application of an enhanced system function sample reflecting the particle mobility and aggregation status of ferucarbotran resulted in significantly improved image reconstructions. The finding was supported by characterizations of different ferucarbotran compositions with the magnetorelaxometry and magnetic particle spectroscopy technique. For instance, similar results were obtained between ferucarbotran embedded in freeze-dried mannitol sugar and liver tissue harvested after a ferucarbotran injection. In addition, the combination of multiple shifted measurement patches for a joint reconstruction of the MPI data enlarged the field of view and increased the covering of liver MPI on magnetic resonance images noticeably.

In vivo liver visualizations with magnetic particle imaging based on the calibration measurement approach.

PubMed

Dieckhoff, J; Kaul, M G; Mummert, T; Jung, C; Salamon, J; Adam, G; Knopp, T; Ludwig, F; Balceris, C; Ittrich, H

2017-05-07

Magnetic particle imaging (MPI) facilitates the rapid determination of 3D in vivo magnetic nanoparticle distributions. In this work, liver MPI following intravenous injections of ferucarbotran (Resovist ® ) was studied. The image reconstruction was based on a calibration measurement, the so called system function. The application of an enhanced system function sample reflecting the particle mobility and aggregation status of ferucarbotran resulted in significantly improved image reconstructions. The finding was supported by characterizations of different ferucarbotran compositions with the magnetorelaxometry and magnetic particle spectroscopy technique. For instance, similar results were obtained between ferucarbotran embedded in freeze-dried mannitol sugar and liver tissue harvested after a ferucarbotran injection. In addition, the combination of multiple shifted measurement patches for a joint reconstruction of the MPI data enlarged the field of view and increased the covering of liver MPI on magnetic resonance images noticeably.

Characterization of the new neutron imaging and materials science facility IMAT

NASA Astrophysics Data System (ADS)

Minniti, Triestino; Watanabe, Kenichi; Burca, Genoveva; Pooley, Daniel E.; Kockelmann, Winfried

2018-04-01

IMAT is a new cold neutron imaging and diffraction instrument located at the second target station of the pulsed neutron spallation source ISIS, UK. A broad range of materials science and materials testing areas will be covered by IMAT. We present the characterization of the imaging part, including the energy-selective and energy-dispersive imaging options, and provide the basic parameters of the radiography and tomography instrument. In particular, detailed studies on mono and bi-dimensional neutron beam flux profiles, neutron flux as a function of the neutron wavelength, spatial and energy dependent neutron beam uniformities, guide artifacts, divergence and spatial resolution, and neutron pulse widths are provided. An accurate characterization of the neutron beam at the sample position, located 56 m from the source, is required to optimize collection of radiographic and tomographic data sets and for performing energy-dispersive neutron imaging via time-of-flight methods in particular.

Generating High-Temporal and Spatial Resolution TIR Image Data

NASA Astrophysics Data System (ADS)

Herrero-Huerta, M.; Lagüela, S.; Alfieri, S. M.; Menenti, M.

2017-09-01

Remote sensing imagery to monitor global biophysical dynamics requires the availability of thermal infrared data at high temporal and spatial resolution because of the rapid development of crops during the growing season and the fragmentation of most agricultural landscapes. Conversely, no single sensor meets these combined requirements. Data fusion approaches offer an alternative to exploit observations from multiple sensors, providing data sets with better properties. A novel spatio-temporal data fusion model based on constrained algorithms denoted as multisensor multiresolution technique (MMT) was developed and applied to generate TIR synthetic image data at both temporal and spatial high resolution. Firstly, an adaptive radiance model is applied based on spectral unmixing analysis of . TIR radiance data at TOA (top of atmosphere) collected by MODIS daily 1-km and Landsat - TIRS 16-day sampled at 30-m resolution are used to generate synthetic daily radiance images at TOA at 30-m spatial resolution. The next step consists of unmixing the 30 m (now lower resolution) images using the information about their pixel land-cover composition from co-registered images at higher spatial resolution. In our case study, TIR synthesized data were unmixed to the Sentinel 2 MSI with 10 m resolution. The constrained unmixing preserves all the available radiometric information of the 30 m images and involves the optimization of the number of land-cover classes and the size of the moving window for spatial unmixing. Results are still being evaluated, with particular attention for the quality of the data streams required to apply our approach.

Object Manifold Alignment for Multi-Temporal High Resolution Remote Sensing Images Classification

NASA Astrophysics Data System (ADS)

Gao, G.; Zhang, M.; Gu, Y.

2017-05-01

Multi-temporal remote sensing images classification is very useful for monitoring the land cover changes. Traditional approaches in this field mainly face to limited labelled samples and spectral drift of image information. With spatial resolution improvement, "pepper and salt" appears and classification results will be effected when the pixelwise classification algorithms are applied to high-resolution satellite images, in which the spatial relationship among the pixels is ignored. For classifying the multi-temporal high resolution images with limited labelled samples, spectral drift and "pepper and salt" problem, an object-based manifold alignment method is proposed. Firstly, multi-temporal multispectral images are cut to superpixels by simple linear iterative clustering (SLIC) respectively. Secondly, some features obtained from superpixels are formed as vector. Thirdly, a majority voting manifold alignment method aiming at solving high resolution problem is proposed and mapping the vector data to alignment space. At last, all the data in the alignment space are classified by using KNN method. Multi-temporal images from different areas or the same area are both considered in this paper. In the experiments, 2 groups of multi-temporal HR images collected by China GF1 and GF2 satellites are used for performance evaluation. Experimental results indicate that the proposed method not only has significantly outperforms than traditional domain adaptation methods in classification accuracy, but also effectively overcome the problem of "pepper and salt".

Objective sampling design in a highly heterogeneous landscape - characterizing environmental determinants of malaria vector distribution in French Guiana, in the Amazonian region.

PubMed

Roux, Emmanuel; Gaborit, Pascal; Romaña, Christine A; Girod, Romain; Dessay, Nadine; Dusfour, Isabelle

2013-12-01

Sampling design is a key issue when establishing species inventories and characterizing habitats within highly heterogeneous landscapes. Sampling efforts in such environments may be constrained and many field studies only rely on subjective and/or qualitative approaches to design collection strategy. The region of Cacao, in French Guiana, provides an excellent study site to understand the presence and abundance of Anopheles mosquitoes, their species dynamics and the transmission risk of malaria across various environments. We propose an objective methodology to define a stratified sampling design. Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors. Such components defined new variables which could then be used in a robust k-means clustering procedure. Then, we identified five clusters that corresponded to our sampling strata and selected sampling sites in each stratum. We validated our method by comparing the species overlap of entomological collections from selected sites and the environmental similarities of the same sites. The Morisita index was significantly correlated (Pearson linear correlation) with environmental similarity based on i) the balanced environmental variable groups considered jointly (p = 0.001) and ii) land cover/use (p-value < 0.001). The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001). The results validate our sampling approach. Land cover/use maps (based on high spatial resolution satellite images) were shown to be particularly useful when studying the presence, density and diversity of Anopheles mosquitoes at local scales and in very heterogeneous landscapes.

Objective sampling design in a highly heterogeneous landscape - characterizing environmental determinants of malaria vector distribution in French Guiana, in the Amazonian region

PubMed Central

2013-01-01

Background Sampling design is a key issue when establishing species inventories and characterizing habitats within highly heterogeneous landscapes. Sampling efforts in such environments may be constrained and many field studies only rely on subjective and/or qualitative approaches to design collection strategy. The region of Cacao, in French Guiana, provides an excellent study site to understand the presence and abundance of Anopheles mosquitoes, their species dynamics and the transmission risk of malaria across various environments. We propose an objective methodology to define a stratified sampling design. Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors. Such components defined new variables which could then be used in a robust k-means clustering procedure. Then, we identified five clusters that corresponded to our sampling strata and selected sampling sites in each stratum. Results We validated our method by comparing the species overlap of entomological collections from selected sites and the environmental similarities of the same sites. The Morisita index was significantly correlated (Pearson linear correlation) with environmental similarity based on i) the balanced environmental variable groups considered jointly (p = 0.001) and ii) land cover/use (p-value << 0.001). The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001). Conclusions The results validate our sampling approach. Land cover/use maps (based on high spatial resolution satellite images) were shown to be particularly useful when studying the presence, density and diversity of Anopheles mosquitoes at local scales and in very heterogeneous landscapes. PMID:24289184

Nanometer resolution optical coherence tomography using broad bandwidth XUV and soft x-ray radiation

DOE PAGES

Fuchs, Silvio; Rödel, Christian; Blinne, Alexander; ...

2016-02-10

Optical coherence tomography (OCT) is a non-invasive technique for cross-sectional imaging. It is particularly advantageous for applications where conventional microscopy is not able to image deeper layers of samples in a reasonable time, e.g. in fast moving, deeper lying structures. However, at infrared and optical wavelengths, which are commonly used, the axial resolution of OCT is limited to about 1 μm, even if the bandwidth of the light covers a wide spectral range. Here, we present extreme ultraviolet coherence tomography (XCT) and thus introduce a new technique for non-invasive cross-sectional imaging of nanometer structures. XCT exploits the nanometerscale coherence lengthsmore » corresponding to the spectral transmission windows of, e.g., silicon samples. The axial resolution of coherence tomography is thus improved from micrometers to a few nanometers. Tomographic imaging with an axial resolution better than 18 nm is demonstrated for layer-type nanostructures buried in a silicon substrate. Using wavelengths in the water transmission window, nanometer-scale layers of platinum are retrieved with a resolution better than 8 nm. As a result, XCT as a nondestructive method for sub-surface tomographic imaging holds promise for several applications in semiconductor metrology and imaging in the water window.« less

THE LYMAN ALPHA REFERENCE SAMPLE. V. THE IMPACT OF NEUTRAL ISM KINEMATICS AND GEOMETRY ON Lyα ESCAPE

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

Rivera-Thorsen, Thøger E.; Hayes, Matthew; Östlin, Göran

2015-05-20

We present high-resolution far-UV spectroscopy of the 14 galaxies of the Lyα Reference Sample; a sample of strongly star-forming galaxies at low redshifts (0.028 < z < 0.18). We compare the derived properties to global properties derived from multi-band imaging and 21 cm H i interferometry and single-dish observations, as well as archival optical SDSS spectra. Besides the Lyα line, the spectra contain a number of metal absorption features allowing us to probe the kinematics of the neutral ISM and evaluate the optical depth and and covering fraction of the neutral medium as a function of line of sight velocity.more » Furthermore, we show how this, in combination with the precise determination of systemic velocity and good Lyα spectra, can be used to distinguish a model in which separate clumps together fully cover the background source, from the “picket fence” model named by Heckman et al. We find that no one single effect dominates in governing Lyα radiative transfer and escape. Lyα escape in our sample coincides with a maximum velocity-binned covering fraction of ≲0.9 and bulk outflow velocities of ≳50 km s{sup −1}, although a number of galaxies show these characteristics and yet little or no Lyα escape. We find that Lyα peak velocities, where available, are not consistent with a strong backscattered component, but rather with a simpler model of an intrinsic emission line overlaid by a blueshifted absorption profile from the outflowing wind. Finally, we find a strong anticorrelation between Hα equivalent width and maximum velocity-binned covering factor, and propose a heuristic explanatory model.« less

Classifying land cover from an object-oriented approach - applied to LANDSAT 8 at the regional scale of the Lake Tana Basin (Ethiopia)

NASA Astrophysics Data System (ADS)

Lemma, Hanibal; Frankl, Amaury; Poesen, Jean; Adgo, Enyew; Nyssen, Jan

2017-04-01

Object-oriented image classification has been gaining prominence in the field of remote sensing and provides a valid alternative to the 'traditional' pixel based methods. Recent studies have proven the superiority of the object-based approach. So far, object-oriented land cover classifications have been applied either at limited spatial coverages (ranging 2 to 1091 km2) or by using very high resolution (0.5-16 m) imageries. The main aim of this study is to drive land cover information for large area from Landsat 8 OLI surface reflectance using the Estimation of Scale Parameter (ESP) tool and the object oriented software eCognition. The available land cover map of Lake Tana Basin (Ethiopia) is about 20 years old with a courser spatial scale (1:250,000) and has limited use for environmental modelling and monitoring studies. Up-to-date and basin wide land cover maps are essential to overcome haphazard natural resources management, land degradation and reduced agricultural production. Indeed, object-oriented approach involves image segmentation prior to classification, i.e. adjacent similar pixels are aggregated into segments as long as the heterogeneity in the spectral and spatial domains is minimized. For each segmented object, different attributes (spectral, textural and shape) were calculated and used for in subsequent classification analysis. Moreover, the commonly used error matrix is employed to determine the quality of the land cover map. As a result, the multiresolution segmentation (with parameters of scale=30, shape=0.3 and Compactness=0.7) produces highly homogeneous image objects as it is observed in different sample locations in google earth. Out of the 15,089 km2 area of the basin, cultivated land is dominant (69%) followed by water bodies (21%), grassland (4.8%), forest (3.7%) and shrubs (1.1%). Wetlands, artificial surfaces and bare land cover only about 1% of the basin. The overall classification accuracy is 80% with a Kappa coefficient of 0.75. With regard to individual classes, the classification show higher Producer's and User's accuracy (above 84%) for cultivated land, water bodies and forest, but lower (less than 70%) for shrubs, bare land and grassland. Key words: accuracy assessment, eCognition, Estimation of Scale Parameter, land cover, Landsat 8, remote sensing

Non-Cartesian Parallel Imaging Reconstruction

PubMed Central

Wright, Katherine L.; Hamilton, Jesse I.; Griswold, Mark A.; Gulani, Vikas; Seiberlich, Nicole

2014-01-01

Non-Cartesian parallel imaging has played an important role in reducing data acquisition time in MRI. The use of non-Cartesian trajectories can enable more efficient coverage of k-space, which can be leveraged to reduce scan times. These trajectories can be undersampled to achieve even faster scan times, but the resulting images may contain aliasing artifacts. Just as Cartesian parallel imaging can be employed to reconstruct images from undersampled Cartesian data, non-Cartesian parallel imaging methods can mitigate aliasing artifacts by using additional spatial encoding information in the form of the non-homogeneous sensitivities of multi-coil phased arrays. This review will begin with an overview of non-Cartesian k-space trajectories and their sampling properties, followed by an in-depth discussion of several selected non-Cartesian parallel imaging algorithms. Three representative non-Cartesian parallel imaging methods will be described, including Conjugate Gradient SENSE (CG SENSE), non-Cartesian GRAPPA, and Iterative Self-Consistent Parallel Imaging Reconstruction (SPIRiT). After a discussion of these three techniques, several potential promising clinical applications of non-Cartesian parallel imaging will be covered. PMID:24408499

Fluorescence imaging to quantify crop residue cover

NASA Technical Reports Server (NTRS)

Daughtry, C. S. T.; Mcmurtrey, J. E., III; Chappelle, E. W.

1994-01-01

Crop residues, the portion of the crop left in the field after harvest, can be an important management factor in controlling soil erosion. Methods to quantify residue cover are needed that are rapid, accurate, and objective. Scenes with known amounts of crop residue were illuminated with long wave ultraviolet (UV) radiation and fluorescence images were recorded with an intensified video camera fitted with a 453 to 488 nm band pass filter. A light colored soil and a dark colored soil were used as background for the weathered soybean stems. Residue cover was determined by counting the proportion of the pixels in the image with fluorescence values greater than a threshold. Soil pixels had the lowest gray levels in the images. The values of the soybean residue pixels spanned nearly the full range of the 8-bit video data. Classification accuracies typically were within 3(absolute units) of measured cover values. Video imaging can provide an intuitive understanding of the fraction of the soil covered by residue.

Benchmark of Machine Learning Methods for Classification of a SENTINEL-2 Image

NASA Astrophysics Data System (ADS)

Pirotti, F.; Sunar, F.; Piragnolo, M.

2016-06-01

Thanks to mainly ESA and USGS, a large bulk of free images of the Earth is readily available nowadays. One of the main goals of remote sensing is to label images according to a set of semantic categories, i.e. image classification. This is a very challenging issue since land cover of a specific class may present a large spatial and spectral variability and objects may appear at different scales and orientations. In this study, we report the results of benchmarking 9 machine learning algorithms tested for accuracy and speed in training and classification of land-cover classes in a Sentinel-2 dataset. The following machine learning methods (MLM) have been tested: linear discriminant analysis, k-nearest neighbour, random forests, support vector machines, multi layered perceptron, multi layered perceptron ensemble, ctree, boosting, logarithmic regression. The validation is carried out using a control dataset which consists of an independent classification in 11 land-cover classes of an area about 60 km2, obtained by manual visual interpretation of high resolution images (20 cm ground sampling distance) by experts. In this study five out of the eleven classes are used since the others have too few samples (pixels) for testing and validating subsets. The classes used are the following: (i) urban (ii) sowable areas (iii) water (iv) tree plantations (v) grasslands. Validation is carried out using three different approaches: (i) using pixels from the training dataset (train), (ii) using pixels from the training dataset and applying cross-validation with the k-fold method (kfold) and (iii) using all pixels from the control dataset. Five accuracy indices are calculated for the comparison between the values predicted with each model and control values over three sets of data: the training dataset (train), the whole control dataset (full) and with k-fold cross-validation (kfold) with ten folds. Results from validation of predictions of the whole dataset (full) show the random forests method with the highest values; kappa index ranging from 0.55 to 0.42 respectively with the most and least number pixels for training. The two neural networks (multi layered perceptron and its ensemble) and the support vector machines - with default radial basis function kernel - methods follow closely with comparable performance.

High Resolution Land Use Land Cover Classification using Landsat Earth Observation Data for the Continental Africa

NASA Astrophysics Data System (ADS)

Midekisa, A.; Bennet, A.; Gething, P. W.; Holl, F.; Andrade-Pacheco, R.; Savory, D. J.; Hugh, S. J.

2016-12-01

Spatially detailed and temporally dynamic land use land cover data is necessary to monitor the state of the land surface for various applications. Yet, such data at a continental to global scale is lacking. Here, we developed high resolution (30 meter) annual land use land cover layers for the continental Africa using Google Earth Engine. To capture ground truth training data, high resolution satellite imageries were visually inspected and used to identify 7, 212 sample Landsat pixels that were comprised entirely of one of seven land use land cover classes (water, man-made impervious surface, high biomass, low biomass, rock, sand and bare soil). For model validation purposes, 80% of points from each class were used as training data, with 20% withheld as a validation dataset. Cloud free Landsat 7 annual composites for 2000 to 2015 were generated and spectral bands from the Landsat images were then extracted for each of the training and validation sample points. In addition to the Landsat spectral bands, spectral indices such as normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used as covariates in the model. Additionally, calibrated night time light imageries from the National Oceanic and Atmospheric Administration (NOAA) were included as a covariate. A decision tree classification algorithm was applied to predict the 7 land cover classes for the periods 2000 to 2015 using the training dataset. Using the validation dataset, classification accuracy including omission error and commission error were computed for each land cover class. Model results showed that overall accuracy of classification was high (88%). This high resolution land cover product developed for the continental Africa will be available for public use and can potentially enhance the ability of monitoring and studying the state of the Earth's surface.

Optimal use of land surface temperature data to detect changes in tropical forest cover

NASA Astrophysics Data System (ADS)

van Leeuwen, Thijs T.; Frank, Andrew J.; Jin, Yufang; Smyth, Padhraic; Goulden, Michael L.; van der Werf, Guido R.; Randerson, James T.

2011-06-01

Rapid and accurate assessment of global forest cover change is needed to focus conservation efforts and to better understand how deforestation is contributing to the buildup of atmospheric CO2. Here we examined different ways to use land surface temperature (LST) to detect changes in tropical forest cover. In our analysis we used monthly 0.05° × 0.05° Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations of LST and Program for the Estimation of Deforestation in the Brazilian Amazon (PRODES) estimates of forest cover change. We also compared MODIS LST observations with an independent estimate of forest cover loss derived from MODIS and Landsat observations. Our study domain of approximately 10° × 10° included the Brazilian state of Mato Grosso. For optimal use of LST data to detect changes in tropical forest cover in our study area, we found that using data sampled during the end of the dry season (˜1-2 months after minimum monthly precipitation) had the greatest predictive skill. During this part of the year, precipitation was low, surface humidity was at a minimum, and the difference between day and night LST was the largest. We used this information to develop a simple temporal sampling algorithm appropriate for use in pantropical deforestation classifiers. Combined with the normalized difference vegetation index, a logistic regression model using day-night LST did moderately well at predicting forest cover change. Annual changes in day-night LST decreased during 2006-2009 relative to 2001-2005 in many regions within the Amazon, providing independent confirmation of lower deforestation levels during the latter part of this decade as reported by PRODES.

A Preliminary Analysis of LANDSAT-4 Thematic Mapper Radiometric Performance

NASA Technical Reports Server (NTRS)

Justice, C.; Fusco, L.; Mehl, W.

1984-01-01

Analysis was performed to characterize the radiometry of three Thematic Mapper (TM) digital products of a scene of Arkansas. The three digital products examined were the NASA raw (BT) product, the radiometrically corrected (AT) product and the radiometrically and geometrically corrected (PT) product. The frequency distribution of the digital data; the statistical correlation between the bands; and the variability between the detectors within a band were examined on a series of image subsets from the full scene. The results are presented from one 1024 x 1024 pixel subset of Realfoot Lake, Tennessee which displayed a representative range of ground conditions and cover types occurring within the full frame image. Bands 1, 2 and 5 of the sample area are presented. The subsets were extracted from the three digital data products to cover the same geographic area. This analysis provides the first step towards a full appraisal of the TM radiometry being performed as part of the ESA/CEC contribution to the NASA/LIDQA program.

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

NASA Technical Reports Server (NTRS)

Mcgwire, K.; Friedl, M.; Estes, J. E.

1993-01-01

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Near-Infrared Fluorescent Materials for Sensing of Biological Targets

PubMed Central

Amiot, Carrie L.; Xu, Shuping; Liang, Song; Pan, Lingyun; Zhao, Julia Xiaojun

2008-01-01

Near-infrared fluorescent (NIRF) materials are promising labeling reagents for sensitive determination and imaging of biological targets. In the near-infrared region biological samples have low background fluorescence signals, providing high signal to noise ratio. Meanwhile, near-infrared radiation can penetrate into sample matrices deeply due to low light scattering. Thus, in vivo and in vitro imaging of biological samples can be achieved by employing the NIRF probes. To take full advantage of NIRF materials in the biological and biomedical field, one of the key issues is to develop intense and biocompatible NIRF probes. In this review, a number of NIRF materials are discussed including traditional NIRF dye molecules, newly developed NIRF quantum dots and single-walled carbon nanotubes, as well as rare earth metal compounds. The use of some NIRF materials in various nanostructures is illustrated. The enhancement of NIRF using metal nanostructures is covered as well. The fluorescence mechanism and bioapplications of each type of the NIRF materials are discussed in details. PMID:27879867

Characterization of a small CsI(Na)-WSF-SiPM gamma camera prototype using 99mTc

NASA Astrophysics Data System (ADS)

Castro, I. F.; Soares, A. J.; Moutinho, L. M.; Ferreira, M. A.; Ferreira, R.; Combo, A.; Muchacho, F.; Veloso, J. F. C. A.

2013-03-01

A small field of view gamma camera is being developed, aiming for applications in scintimammography, sentinel lymph node detection or small animal imaging and research. The proposed wavelength-shifting fibre (WSF) gamma camera consists of two perpendicular sets of WSFs covering both sides of a CsI(Na) crystal, such that the fibres positioned at the bottom of the crystal provide the x coordinate and the ones on top the y coordinate of the gamma photon interaction point. The 2D position is given by highly sensitive photodetectors reading out each WSF and the energy information is provided by PMTs that cover the full detector area. This concept has the advantage of using N+N instead of N × N photodetectors to cover an identical imaging area, and is being applied using for the first time SiPMs. Previous studies carried out with 57Co have proved the feasibility of this concept using SiPM readout. In this work, we present experimental results from true 2D image acquisitions with a 10+10 SiPMs prototype, i.e. 10 × 10 mm2, using a parallel-hole collimator and different samples filled with 99mTc solution. The performance of the small prototype in these conditions is evaluated through the characterization of different gamma camera parameters, such as energy and spatial resolution. Ongoing advances towards a larger prototype of 100+100 SiPMs (10 × 10 cm2) are also presented.

Flexible conformable hydrophobized surfaces for turbulent flow drag reduction

NASA Astrophysics Data System (ADS)

Brennan, Joseph C.; Geraldi, Nicasio R.; Morris, Robert H.; Fairhurst, David J.; McHale, Glen; Newton, Michael I.

2015-05-01

In recent years extensive work has been focused onto using superhydrophobic surfaces for drag reduction applications. Superhydrophobic surfaces retain a gas layer, called a plastron, when submerged underwater in the Cassie-Baxter state with water in contact with the tops of surface roughness features. In this state the plastron allows slip to occur across the surface which results in a drag reduction. In this work we report flexible and relatively large area superhydrophobic surfaces produced using two different methods: Large roughness features were created by electrodeposition on copper meshes; Small roughness features were created by embedding carbon nanoparticles (soot) into Polydimethylsiloxane (PDMS). Both samples were made into cylinders with a diameter under 12 mm. To characterize the samples, scanning electron microscope (SEM) images and confocal microscope images were taken. The confocal microscope images were taken with each sample submerged in water to show the extent of the plastron. The hydrophobized electrodeposited copper mesh cylinders showed drag reductions of up to 32% when comparing the superhydrophobic state with a wetted out state. The soot covered cylinders achieved a 30% drag reduction when comparing the superhydrophobic state to a plain cylinder. These results were obtained for turbulent flows with Reynolds numbers 10,000 to 32,500.

Application of Visible and Near-Infrared Hyperspectral Imaging to Determine Soluble Protein Content in Oilseed Rape Leaves

PubMed Central

Zhang, Chu; Liu, Fei; Kong, Wenwen; He, Yong

2015-01-01

Visible and near-infrared hyperspectral imaging covering spectral range of 380–1030 nm as a rapid and non-destructive method was applied to estimate the soluble protein content of oilseed rape leaves. Average spectrum (500–900 nm) of the region of interest (ROI) of each sample was extracted, and four samples out of 128 samples were defined as outliers by Monte Carlo-partial least squares (MCPLS). Partial least squares (PLS) model using full spectra obtained dependable performance with the correlation coefficient (rp) of 0.9441, root mean square error of prediction (RMSEP) of 0.1658 mg/g and residual prediction deviation (RPD) of 2.98. The weighted regression coefficient (Bw), successive projections algorithm (SPA) and genetic algorithm-partial least squares (GAPLS) selected 18, 15, and 16 sensitive wavelengths, respectively. SPA-PLS model obtained the best performance with rp of 0.9554, RMSEP of 0.1538 mg/g and RPD of 3.25. Distribution of protein content within the rape leaves were visualized and mapped on the basis of the SPA-PLS model. The overall results indicated that hyperspectral imaging could be used to determine and visualize the soluble protein content of rape leaves. PMID:26184198

Imaging of Norway spruce early somatic embryos with the ESEM, Cryo-SEM and laser scanning microscope.

PubMed

Neděla, Vilém; Hřib, Jiří; Havel, Ladislav; Hudec, Jiří; Runštuk, Jiří

2016-05-01

This article describes the surface structure of Norway spruce early somatic embryos (ESEs) as a typical culture with asynchronous development. The microstructure of extracellular matrix covering ESEs were observed using the environmental scanning electron microscope as a primary tool and using the scanning electron microscope with cryo attachment and laser electron microscope as a complementary tool allowing our results to be proven independently. The fresh samples were observed in conditions of the air environment of the environmental scanning electron microscope (ESEM) with the pressure from 550Pa to 690Pa and the low temperature of the sample from -18°C to -22°C. The samples were studied using two different types of detector to allow studying either the thin surface structure or material composition. The scanning electron microscope with cryo attachment was used for imaging frozen extracellular matrix microstructure with higher resolution. The combination of both electron microscopy methods was suitable for observation of "native" plant samples, allowing correct evaluation of our results, free of error and artifacts. Copyright © 2016 Elsevier Ltd. All rights reserved.

High Throughput Determination of Plant Height, Ground Cover, and Above-Ground Biomass in Wheat with LiDAR

PubMed Central

Jimenez-Berni, Jose A.; Deery, David M.; Rozas-Larraondo, Pablo; Condon, Anthony (Tony) G.; Rebetzke, Greg J.; James, Richard A.; Bovill, William D.; Furbank, Robert T.; Sirault, Xavier R. R.

2018-01-01

Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labor-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data. Here we demonstrate the capacity of Light Detection and Ranging (LiDAR), mounted on a lightweight, mobile, ground-based platform, for rapid multi-temporal and non-destructive estimation of canopy height, ground cover and above-ground biomass. Field validation of LiDAR measurements is presented. For canopy height, strong relationships with LiDAR (r2 of 0.99 and root mean square error of 0.017 m) were obtained. Ground cover was estimated from LiDAR using two methodologies: red reflectance image and canopy height. In contrast to NDVI, LiDAR was not affected by saturation at high ground cover, and the comparison of both LiDAR methodologies showed strong association (r2 = 0.92 and slope = 1.02) at ground cover above 0.8. For above-ground biomass, a dedicated field experiment was performed with destructive biomass sampled eight times across different developmental stages. Two methodologies are presented for the estimation of biomass from LiDAR: 3D voxel index (3DVI) and 3D profile index (3DPI). The parameters involved in the calculation of 3DVI and 3DPI were optimized for each sample event from tillering to maturity, as well as generalized for any developmental stage. Individual sample point predictions were strong while predictions across all eight sample events, provided the strongest association with biomass (r2 = 0.93 and r2 = 0.92) for 3DPI and 3DVI, respectively. Given these results, we believe that application of this system will provide new opportunities to deliver improved genotypes and agronomic interventions via more efficient and reliable phenotyping of these important traits in large experiments. PMID:29535749

High Throughput Determination of Plant Height, Ground Cover, and Above-Ground Biomass in Wheat with LiDAR.

PubMed

Jimenez-Berni, Jose A; Deery, David M; Rozas-Larraondo, Pablo; Condon, Anthony Tony G; Rebetzke, Greg J; James, Richard A; Bovill, William D; Furbank, Robert T; Sirault, Xavier R R

2018-01-01

Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labor-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data. Here we demonstrate the capacity of Light Detection and Ranging (LiDAR), mounted on a lightweight, mobile, ground-based platform, for rapid multi-temporal and non-destructive estimation of canopy height, ground cover and above-ground biomass. Field validation of LiDAR measurements is presented. For canopy height, strong relationships with LiDAR ( r 2 of 0.99 and root mean square error of 0.017 m) were obtained. Ground cover was estimated from LiDAR using two methodologies: red reflectance image and canopy height. In contrast to NDVI, LiDAR was not affected by saturation at high ground cover, and the comparison of both LiDAR methodologies showed strong association ( r 2 = 0.92 and slope = 1.02) at ground cover above 0.8. For above-ground biomass, a dedicated field experiment was performed with destructive biomass sampled eight times across different developmental stages. Two methodologies are presented for the estimation of biomass from LiDAR: 3D voxel index (3DVI) and 3D profile index (3DPI). The parameters involved in the calculation of 3DVI and 3DPI were optimized for each sample event from tillering to maturity, as well as generalized for any developmental stage. Individual sample point predictions were strong while predictions across all eight sample events, provided the strongest association with biomass ( r 2 = 0.93 and r 2 = 0.92) for 3DPI and 3DVI, respectively. Given these results, we believe that application of this system will provide new opportunities to deliver improved genotypes and agronomic interventions via more efficient and reliable phenotyping of these important traits in large experiments.

Snow Cover Mapping and Ice Avalanche Monitoring from the Satellite Data of the Sentinels

NASA Astrophysics Data System (ADS)

Wang, S.; Yang, B.; Zhou, Y.; Wang, F.; Zhang, R.; Zhao, Q.

2018-04-01

In order to monitor ice avalanches efficiently under disaster emergency conditions, a snow cover mapping method based on the satellite data of the Sentinels is proposed, in which the coherence and backscattering coefficient image of Synthetic Aperture Radar (SAR) data (Sentinel-1) is combined with the atmospheric correction result of multispectral data (Sentinel-2). The coherence image of the Sentinel-1 data could be segmented by a certain threshold to map snow cover, with the water bodies extracted from the backscattering coefficient image and removed from the coherence segment result. A snow confidence map from Sentinel-2 was used to map the snow cover, in which the confidence values of the snow cover were relatively high. The method can make full use of the acquired SAR image and multispectral image under emergency conditions, and the application potential of Sentinel data in the field of snow cover mapping is exploited. The monitoring frequency can be ensured because the areas obscured by thick clouds are remedied in the monitoring results. The Kappa coefficient of the monitoring results is 0.946, and the data processing time is less than 2 h, which meet the requirements of disaster emergency monitoring.

Design of an Airborne Portable Remote Imaging Spectrometer (PRISM) for the Coastal Ocean

NASA Technical Reports Server (NTRS)

Mouroulis, P.; vanGorp, B.; Green, R. O.; Cohen, D.; Wilson, D.; Randall, D.; Rodriguez, J.; Polanco, O.; Dierssen, H.; Balasubramanian, K.;

Optical design of a CubeSat-compatible imaging spectrometer

NASA Astrophysics Data System (ADS)

Mouroulis, Pantazis; Van Gorp, Byron; Green, Robert O.; Wilson, Daniel W.

2014-09-01

We describe a fast, uniform, low-polarization imaging spectrometer and telescope system that can be integrated in a 6U CubeSat. The spectral range is 350-1700 nm, with 5.7 nm sampling. The telescope and spectrometer operate at F/1.8. At 100 mm focal length, the telescope is the highest resolution form that can fit in the CubeSat frame without deployable mirrors. The field of view is 10° with 600 cross-track pixels. The spectrometer is designed for the new Teledyne CHROMA detector array with 30μm pixel size for maximizing throughput. The primary intended applications are coastal ocean and snow cover monitoring.

Cover estimation and payload location using Markov random fields

NASA Astrophysics Data System (ADS)

Quach, Tu-Thach

2014-02-01

Payload location is an approach to find the message bits hidden in steganographic images, but not necessarily their logical order. Its success relies primarily on the accuracy of the underlying cover estimators and can be improved if more estimators are used. This paper presents an approach based on Markov random field to estimate the cover image given a stego image. It uses pairwise constraints to capture the natural two-dimensional statistics of cover images and forms a basis for more sophisticated models. Experimental results show that it is competitive against current state-of-the-art estimators and can locate payload embedded by simple LSB steganography and group-parity steganography. Furthermore, when combined with existing estimators, payload location accuracy improves significantly.

Environmental High-content Fluorescence Microscopy (e-HCFM) of Tara Oceans Samples Provides a View of Global Ocean Protist Biodiversity

NASA Astrophysics Data System (ADS)

Coelho, L. P.; Colin, S.; Sunagawa, S.; Karsenti, E.; Bork, P.; Pepperkok, R.; de Vargas, C.

2016-02-01

Protists are responsible for much of the diversity in the eukaryotic kingdomand are crucial to several biogeochemical processes of global importance (e.g.,the carbon cycle). Recent global investigations of these organisms have reliedon sequence-based approaches. These methods do not, however, capture thecomplex functional morphology of these organisms nor can they typically capturephenomena such as interactions (except indirectly through statistical means).Direct imaging of these organisms, can therefore provide a valuable complementto sequencing and, when performed quantitatively, provide measures ofstructures and interaction patterns which can then be related back to sequencebased measurements. Towards this end, we developed a framework, environmentalhigh-content fluorescence microscopy (e-HCFM) which can be applied toenvironmental samples composed of mixed communities. This strategy is based ongeneral purposes dyes that stain major structures in eukaryotes. Samples areimaged using scanning confocal microscopy, resulting in a three-dimensionalimage-stack. High-throughput can be achieved using automated microscopy andcomputational analysis. Standard bioimage informatics segmentation methodscombined with feature computation and machine learning results in automatictaxonomic assignments to the objects that are imaged in addition to severalbiochemically relevant measurements (such as biovolumes, fluorescenceestimates) per organism. We provide results on 174 image acquisition from TaraOcean samples, which cover organisms from 5 to 180 microns (82 samples in the5-20 fraction, 96 in the 20-180 fraction). We show a validation of the approachboth on technical grounds (demonstrating the high accuracy of automatedclassification) and provide results obtain from image analysis and fromintegrating with other data, such as associated environmental parametersmeasured in situ as well as perspectives on integration with sequenceinformation.

Optical Observation, Image-processing, and Detection of Space Debris in Geosynchronous Earth Orbit

NASA Astrophysics Data System (ADS)

Oda, H.; Yanagisawa, T.; Kurosaki, H.; Tagawa, M.

2014-09-01

We report on optical observations and an efficient detection method of space debris in the geosynchronous Earth orbit (GEO). We operate our new Australia Remote Observatory (ARO) where an 18 cm optical telescope with a charged-coupled device (CCD) camera covering a 3.14-degree field of view is used for GEO debris survey, and analyse datasets of successive CCD images using the line detection method (Yanagisawa and Nakajima 2005). In our operation, the exposure time of each CCD image is set to be 3 seconds (or 5 seconds), and the time interval of CCD shutter open is about 4.7 seconds (or 6.7 seconds). In the line detection method, a sufficient number of sample objects are taken from each image based on their shape and intensity, which includes not only faint signals but also background noise (we take 500 sample objects from each image in this paper). Then we search a sequence of sample objects aligning in a straight line in the successive images to exclude the noise sample. We succeed in detecting faint signals (down to about 1.8 sigma of background noise) by applying the line detection method to 18 CCD images. As a result, we detected about 300 GEO objects up to magnitude of 15.5 among 5 nights data. We also calculate orbits of objects detected using the Simplified General Perturbations Satellite Orbit Model 4(SGP4), and identify the objects listed in the two-line-element (TLE) data catalogue publicly provided by the U.S. Strategic Command (USSTRATCOM). We found that a certain amount of our detections are new objects that are not contained in the catalogue. We conclude that our ARO and detection method posse a high efficiency detection of GEO objects despite the use of comparatively-inexpensive observation and analysis system. We also describe the image-processing specialized for the detection of GEO objects (not for usual astronomical objects like stars) in this paper.

Pornographic image recognition and filtering using incremental learning in compressed domain

NASA Astrophysics Data System (ADS)

Zhang, Jing; Wang, Chao; Zhuo, Li; Geng, Wenhao

2015-11-01

With the rapid development and popularity of the network, the openness, anonymity, and interactivity of networks have led to the spread and proliferation of pornographic images on the Internet, which have done great harm to adolescents' physical and mental health. With the establishment of image compression standards, pornographic images are mainly stored with compressed formats. Therefore, how to efficiently filter pornographic images is one of the challenging issues for information security. A pornographic image recognition and filtering method in the compressed domain is proposed by using incremental learning, which includes the following steps: (1) low-resolution (LR) images are first reconstructed from the compressed stream of pornographic images, (2) visual words are created from the LR image to represent the pornographic image, and (3) incremental learning is adopted to continuously adjust the classification rules to recognize the new pornographic image samples after the covering algorithm is utilized to train and recognize the visual words in order to build the initial classification model of pornographic images. The experimental results show that the proposed pornographic image recognition method using incremental learning has a higher recognition rate as well as costing less recognition time in the compressed domain.

A land-cover map for South and Southeast Asia derived from SPOT-VEGETATION data

USGS Publications Warehouse

Stibig, H.-J.; Belward, A.S.; Roy, P.S.; Rosalina-Wasrin, U.; Agrawal, S.; Joshi, P.K.; ,; Beuchle, R.; Fritz, S.; Mubareka, S.; Giri, C.

2007-01-01

Aim  Our aim was to produce a uniform ‘regional’ land-cover map of South and Southeast Asia based on ‘sub-regional’ mapping results generated in the context of the Global Land Cover 2000 project.Location  The ‘region’ of tropical and sub-tropical South and Southeast Asia stretches from the Himalayas and the southern border of China in the north, to Sri Lanka and Indonesia in the south, and from Pakistan in the west to the islands of New Guinea in the far east.Methods  The regional land-cover map is based on sub-regional digital mapping results derived from SPOT-VEGETATION satellite data for the years 1998–2000. Image processing, digital classification and thematic mapping were performed separately for the three sub-regions of South Asia, continental Southeast Asia, and insular Southeast Asia. Landsat TM images, field data and existing national maps served as references. We used the FAO (Food and Agriculture Organization) Land Cover Classification System (LCCS) for coding the sub-regional land-cover classes and for aggregating the latter to a uniform regional legend. A validation was performed based on a systematic grid of sample points, referring to visual interpretation from high-resolution Landsat imagery. Regional land-cover area estimates were obtained and compared with FAO statistics for the categories ‘forest’ and ‘cropland’.Results  The regional map displays 26 land-cover classes. The LCCS coding provided a standardized class description, independent from local class names; it also allowed us to maintain the link to the detailed sub-regional land-cover classes. The validation of the map displayed a mapping accuracy of 72% for the dominant classes of ‘forest’ and ‘cropland’; regional area estimates for these classes correspond reasonably well to existing regional statistics.Main conclusions  The land-cover map of South and Southeast Asia provides a synoptic view of the distribution of land cover of tropical and sub-tropical Asia, and it delivers reasonable thematic detail and quantitative estimates of the main land-cover proportions. The map may therefore serve for regional stratification or modelling of vegetation cover, but could also support the implementation of forest policies, watershed management or conservation strategies at regional scales.

A user-friendly LabVIEW software platform for grating based X-ray phase-contrast imaging.

PubMed

Wang, Shenghao; Han, Huajie; Gao, Kun; Wang, Zhili; Zhang, Can; Yang, Meng; Wu, Zhao; Wu, Ziyu

2015-01-01

X-ray phase-contrast imaging can provide greatly improved contrast over conventional absorption-based imaging for weakly absorbing samples, such as biological soft tissues and fibre composites. In this study, we introduced an easy and fast way to develop a user-friendly software platform dedicated to the new grating-based X-ray phase-contrast imaging setup at the National Synchrotron Radiation Laboratory of the University of Science and Technology of China. The control of 21 motorized stages, of a piezoelectric stage and of an X-ray tube are achieved with this software, it also covers image acquisition with a flat panel detector for automatic phase stepping scan. Moreover, a data post-processing module for signals retrieval and other custom features are in principle available. With a seamless integration of all the necessary functions in one software package, this platform greatly facilitate users' activities during experimental runs with this grating based X-ray phase contrast imaging setup.

Snow survey and vegetation growth in high mountains (Swiss Alps) and additional ERTS investigations in Switzerland

NASA Technical Reports Server (NTRS)

Haefner, H. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Two different methods, an analog and a digital one, have been developed for rapid and accurate mapping of the areal extent and changes in snow cover in high mountains. The quick-look method is based on individual visual control of each image using a photo quantizer which provides exact references for density slicing with high resolution lith-film. The digital snow classification system is based on discriminant analysis with the data of the four multispectral bands as variables and contains all preprocessing, feature extraction, and mapping steps for an operational application. Two different sets of sampling groups were established which apply to different conditions of snow cover. The first one serves for the normal situation with a uniform dry and new cover. The second one serves for situations with partly thawing and/or frozen snow.

Producing Information for Corine Database by Using Classification Method: a Case Study of Sazlidere Basin, Istanbul

NASA Astrophysics Data System (ADS)

Sarıyılmaz, F. B.; Musaoğlu, N.; Uluğtekin, N.

2017-11-01

The Sazlidere Basin is located on the European side of Istanbul within the borders of Arnavutkoy and Basaksehir districts. The total area of the basin, which is largely located within the province of Arnavutkoy, is approximately 177 km2. The Sazlidere Basin is faced with intense urbanization pressures and land use / cover change due to the Northern Marmara Motorway, 3rd airport and Channel Istanbul Projects, which are planned to be realized in the Arnavutkoy region. Due to the mentioned projects, intense land use /cover changes occur in the basin. In this study, 2000 and 2012 dated LANDSAT images were supervised classified based on CORINE Land Cover first level to determine the land use/cover classes. As a result, four information classes were identified. These classes are water bodies, forest and semi-natural areas, agricultural areas and artificial surfaces. Accuracy analysis of the images were performed following the classification process. The supervised classified images that have the smallest mapping units 0.09 ha and 0.64 ha were generalized to be compatible with the CORINE Land Cover data. The image pixels have been rearranged by using the thematic pixel aggregation method as the smallest mapping unit is 25 ha. These results were compared with CORINE Land Cover 2000 and CORINE Land Cover 2012, which were obtained by digitizing land cover and land use classes on satellite images. It has been determined that the compared results are compatible with each other in terms of quality and quantity.

Curiosity’s robotic arm-mounted Mars Hand Lens Imager (MAHLI): Characterization and calibration status

USGS Publications Warehouse

Edgett, Kenneth S.; Caplinger, Michael A.; Maki, Justin N.; Ravine, Michael A.; Ghaemi, F. Tony; McNair, Sean; Herkenhoff, Kenneth E.; Duston, Brian M.; Wilson, Reg G.; Yingst, R. Aileen; Kennedy, Megan R.; Minitti, Michelle E.; Sengstacken, Aaron J.; Supulver, Kimberley D.; Lipkaman, Leslie J.; Krezoski, Gillian M.; McBride, Marie J.; Jones, Tessa L.; Nixon, Brian E.; Van Beek, Jason K.; Krysak, Daniel J.; Kirk, Randolph L.

2015-01-01

MAHLI (Mars Hand Lens Imager) is a 2-megapixel, Bayer pattern color CCD camera with a macro lens mounted on a rotatable turret at the end of the 2-meters-long robotic arm aboard the Mars Science Laboratory rover, Curiosity. The camera includes white and longwave ultraviolet LEDs to illuminate targets at night. Onboard data processing services include focus stack merging and data compression. Here we report on the results and status of MAHLI characterization and calibration, covering the pre-launch period from August 2008 through the early months of the extended surface mission through February 2015. Since landing in Gale crater in August 2012, MAHLI has been used for a wide range of science and engineering applications, including distinction among a variety of mafic, siliciclastic sedimentary rocks; investigation of grain-scale rock, regolith, and eolian sediment textures and structures; imaging of the landscape; inspection and monitoring of rover and science instrument hardware concerns; and supporting geologic sample selection, extraction, analysis, delivery, and documentation. The camera has a dust cover and focus mechanism actuated by a single stepper motor. The transparent cover was coated with a thin film of dust during landing, thus MAHLI is usually operated with the cover open. The camera focuses over a range from a working distance of 2.04 cm to infinity; the highest resolution images are at 13.9 µm per pixel; images acquired from 6.9 cm show features at the same scale as the Mars Exploration Rover Microscopic Imagers at 31 µm/pixel; and 100 µm/pixel is achieved at a working distance of ~26.5 cm. The very highest resolution images returned from Mars permit distinction of high contrast silt grains in the 30–40 µm size range. MAHLI has performed well; the images need no calibration in order to achieve most of the investigation’s science and engineering goals. The positioning and repeatability of robotic arm placement of the MAHLI camera head have been excellent on Mars, often with the hardware arriving within millimeters of expectation. Stability while imaging is usually such that the images are sharply focused; some exceptions—thought to result from motion induced by wind—have occurred during longer exposure LED-illuminated night imaging. Image calibration includes relative radiometric correction by removal of dark current and application of a flat field. Dark current is negligible to minor for typical daytime exposure durations and temperatures at the Gale field site. A pre-launch flat field product is usually applied to the data but new products created from images acquired by MAHLI of the Martian sky are superior and can provide a relative radiometric accuracy of ~6%. The camera lens imparts negligible distortion to its images; camera models derived from pre-launch data, with CAHV and CAHVOR parameters captured in their archived labels, can be applied to the images for analysis. MAHLI data and derived products, including pre-launch images, are archived with the NASA Planetary Data System (PDS). This report includes supplementary calibration and characterization data that are not available in the PDS archive (see supplement file MAHLITechRept0001_Supplement.zip).

First laboratory high-temperature emissivity measurements of Venus analog measurements in the near-infrared atmospheric windows

NASA Astrophysics Data System (ADS)

Helbert, J.; Maturilli, A.; Ferrari, S.; Dyar, M. D.; Smrekar, S. E.

2014-12-01

The permanent cloud cover of Venus prohibits observation of the surface with traditional imaging techniques over most of the visible spectral range. Venus' CO2 atmosphere is transparent exclusively in small spectral windows near 1 μm. The Visible and Infrared Thermal Imaging Spectrometer (VIRTIS) team on the European Space Agency Venus-Express mission have recently used these windows successfully to map the southern hemisphere from orbit. VIRTIS is showing variations in surface brightness, which can be interpreted as variations in surface emissivity. Deriving surface composition from these variations is a challenging task. Comparison with laboratory analogue spectra are complicated by the fact that Venus has an average surface temperature of 730K. Mineral crystal structures and their resultant spectral signatures are notably affected by temperature, therefore any interpretations based on room temperature laboratory spectra database can be misleading. In order to support the interpretation of near-infrared data from Venus we have started an extensive measurement campaign at the Planetary Emissivity Laboratory (PEL, Institute of Planetary Research of the German Aerospace Center, Berlin). The PEL facility, which is unique in the world, allows emission measurements covering the 1 to 2 μm wavelength range at sample temperatures of up to 770K. Conciliating the expected emissivity variation between felsic and mafic minerals with Venera and VEGA geochemical data we have started with a set of five analog samples. This set includes basalt, gneiss, granodiorite, anorthosite and hematite, thus covering the range of mineralogies. Preliminary results show significant spectral contrast, thus allowing different samples to be distinguished with only 5 spectral points and validating the use of thermal emissivity for investigating composition. This unique new dataset from PEL not only allows interpretation of the Venus Express VIRTIS data but also provide a baseline for considering new instrument designs for future Venus missions.

Quantification of land cover and land use within the rural complex of the Democratic Republic of Congo

NASA Astrophysics Data System (ADS)

Molinario, G.; Hansen, M. C.; Potapov, P. V.; Tyukavina, A.; Stehman, S.; Barker, B.; Humber, M.

2017-10-01

The rural complex is the inhabited agricultural land cover mosaic found along the network of rivers and roads in the forest of the Democratic Republic of Congo. It is a product of traditional small-holder shifting cultivation. To date, thanks to its distinction from primary forest, this area has been mapped as relatively homogenous, leaving the proportions of land cover heterogeneity within it unknown. However, the success of strategies for sustainable development, including land use planning and payment for ecosystem services, such as Reduced Emissions from Deforestation and Degradation, depends on the accurate characterization of the impacts of land use on natural resources, including within the rural complex. We photo-interpreted a simple random sample of 1000 points in the established rural complex, using 3106 high resolution satellite images obtained from the National Geospatial-Intelligence Agency, together with 406 images from Google Earth, spanning the period 2008-2016. Results indicate that nationally the established rural complex includes 5% clearings, 10% active fields, 26% fallows, 34% secondary forest, 2% wetland forest, 11% primary forest, 6% grasslands, 3% roads and settlements and 2% commercial plantations. Only a small proportion of sample points were plantations, while other commercial dynamics, such as logging and mining, were not detected in the sample. The area of current shifting cultivation accounts for 76% of the established rural complex. Added to primary forest (11%), this means that 87% of the rural complex is available for shifting cultivation. At the current clearing rate, it would take ~18 years for a complete rotation of the rural complex to occur. Additional pressure on land results in either the cultivation of non-preferred land types within the rural complex (such as wetland forest), or expansion of agriculture into nearby primary forests, with attendant impacts on emissions, habitat loss and other ecosystems services.

Nondestructive corrosion detection in concrete through integrated heat induction and IR thermography

NASA Astrophysics Data System (ADS)

Kwon, Seung-Jun; Xue, Henry; Feng, Maria Q.; Baek, Seunghoon

2011-04-01

Steel corrosion in concrete is a main cause of deterioration and early failure of concrete structures. A novel integration of electromagnetic heat induction and infrared (IR) thermography is proposed for nondestructive detection of steel corrosion in concrete, by taking advantage of the difference in thermal characteristics of corroded and non-corroded steel. This paper focuses on experimental investigation of the concept. An inductive heater is developed to remotely heat the steel rebar from concrete surface, which is integrated with an IR camera. Bare rebar and concrete samples with different cover depths are prepared. Each concrete sample is embedded with a single steel rebar in the middle, resulting an identical cover depth from the front and the back surfaces, which enables heat induction from one surface and IR thermogrphay from the other simultaneously. The impressed current method is adopted to induce accelerated corrosion on the rebar. IR video images are recorded during both heating and cooling periods. The test results demonstrate a clear difference in thermal characteristics between corroded and non-corroded samples. The corroded samples show higher rates of heating and cooling as well as a higher peak IR intensity than those of the non-corroded samples. This study demonstrates a potential for nondestructive detection of rebar corrosion in concrete.

Georectification and snow classification of webcam images: potential for complementing satellite-derrived snow maps over Switzerland

NASA Astrophysics Data System (ADS)

Dizerens, Céline; Hüsler, Fabia; Wunderle, Stefan

2016-04-01

The spatial and temporal variability of snow cover has a significant impact on climate and environment and is of great socio-economic importance for the European Alps. Satellite remote sensing data is widely used to study snow cover variability and can provide spatially comprehensive information on snow cover extent. However, cloud cover strongly impedes the surface view and hence limits the number of useful snow observations. Outdoor webcam images not only offer unique potential for complementing satellite-derived snow retrieval under cloudy conditions but could also serve as a reference for improved validation of satellite-based approaches. Thousands of webcams are currently connected to the Internet and deliver freely available images with high temporal and spatial resolutions. To exploit the untapped potential of these webcams, a semi-automatic procedure was developed to generate snow cover maps based on webcam images. We used daily webcam images of the Swiss alpine region to apply, improve, and extend existing approaches dealing with the positioning of photographs within a terrain model, appropriate georectification, and the automatic snow classification of such photographs. In this presentation, we provide an overview of the implemented procedure and demonstrate how our registration approach automatically resolves the orientation of a webcam by using a high-resolution digital elevation model and the webcam's position. This allows snow-classified pixels of webcam images to be related to their real-world coordinates. We present several examples of resulting snow cover maps, which have the same resolution as the digital elevation model and indicate whether each grid cell is snow-covered, snow-free, or not visible from webcams' positions. The procedure is expected to work under almost any weather condition and demonstrates the feasibility of using webcams for the retrieval of high-resolution snow cover information.

Regional Climate Modeling over the Marmara Region, Turkey, with Improved Land Cover Data

NASA Astrophysics Data System (ADS)

Sertel, E.; Robock, A.

2007-12-01

Land surface controls the partitioning of available energy at the surface between sensible and latent heat,and controls partitioning of available water between evaporation and runoff. Current land cover data available within the regional climate models such as Regional Atmospheric Modeling System (RAMS), the Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) and Weather Research and Forecasting (WRF) was obtained from 1- km Advanced Very High Resolution Radiometer satellite images spanning April 1992 through March 1993 with an unsupervised classification technique. These data are not up-to-date and are not accurate for all regions and some land cover types such as urban areas. Here we introduce new, up-to-date and accurate land cover data for the Marmara Region, Turkey derived from Landsat Enhanced Thematic Mapper images into the WRF regional climate model. We used several image processing techniques to create accurate land cover data from Landsat images obtained between 2001 and 2005. First, all images were atmospherically and radiometrically corrected to minimize contamination effects of atmospheric particles and systematic errors. Then, geometric correction was performed for each image to eliminate geometric distortions and define images in a common coordinate system. Finally, unsupervised and supervised classification techniques were utilized to form the most accurate land cover data yet for the study area. Accuracy assessments of the classifications were performed using error matrix and kappa statistics to find the best classification results. Maximum likelihood classification method gave the most accurate results over the study area. We compared the new land cover data with the default WRF land cover data. WRF land cover data cannot represent urban areas in the cities of Istanbul, Izmit, and Bursa. As an example, both original satellite images and new land cover data showed the expansion of urban areas into the Istanbul metropolitan area, but in the WRF land cover data only a limited area along the Bosporus is shown as urban. In addition, the new land cover data indicate that the northern part of Istanbul is covered by evergreen and deciduous forest (verified by ground truth data), but the WRF data indicate that most of this region is croplands. In the northern part of the Marmara Region, there is bare ground as a result of open mining activities and this class can be identified in our land cover data, whereas the WRF data indicated this region as woodland. We then used this new data set to conduct WRF simulations for one main and two nested domains, where the inner-most domain represents the Marmara Region with 3 km horizontal resolution. The vertical domain of both main and nested domains extends over 28 vertical levels. Initial and boundary conditions were obtained from National Centers for Environmental Prediction-Department of Energy Reanalysis II and the Noah model was selected as the land surface model. Two model simulations were conducted; one with available land cover data and one with the newly created land cover data. Using detailed meteorological station data within the study area, we find that the simulation with the new land cover data set produces better temperature and precipitation simulations for the region, showing the value of accurate land cover data and that changing land cover data can be an important influence on local climate change.

Optimization of Immobilization of Nanodiamonds on Graphene

NASA Astrophysics Data System (ADS)

Pille, A.; Lange, S.; Utt, K.; Eltermann, M.

2015-04-01

We report using simple dip-coating method to cover the surface of graphene with nanodiamonds for future optical detection of defects on graphene. Most important part of the immobilization process is the pre-functionalization of both, nanodiamond and graphene surfaces to obtain the selectiveness of the method. This work focuses on an example of using electrostatic attraction to confine nanodiamonds to graphene. Raman spectroscopy, microluminescence imaging and scanning electron microscopy were applied to characterize obtained samples.

Vapor deposition routes to conformal polymer thin films

PubMed Central

Moni, Priya; Al-Obeidi, Ahmed

2017-01-01

Vapor phase syntheses, including parylene chemical vapor deposition (CVD) and initiated CVD, enable the deposition of conformal polymer thin films to benefit a diverse array of applications. This short review for nanotechnologists, including those new to vapor deposition methods, covers the basic theory in designing a conformal polymer film vapor deposition, sample preparation and imaging techniques to assess film conformality, and several applications that have benefited from vapor deposited, conformal polymer thin films. PMID:28487816

Mapping land cover from satellite images: A basic, low cost approach

NASA Technical Reports Server (NTRS)

Elifrits, C. D.; Barney, T. W.; Barr, D. J.; Johannsen, C. J.

1978-01-01

Simple, inexpensive methodologies developed for mapping general land cover and land use categories from LANDSAT images are reported. One methodology, a stepwise, interpretive, direct tracing technique was developed through working with university students from different disciplines with no previous experience in satellite image interpretation. The technique results in maps that are very accurate in relation to actual land cover and relative to the small investment in skill, time, and money needed to produce the products.

Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues

NASA Astrophysics Data System (ADS)

Lazaridou, M. A.; Karagianni, A. Ch.

2016-06-01

Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM - Landsat 8) is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion - pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

Celebrity chefs put their left cheek forward: Cover image orientation in celebrity cookbooks.

PubMed

Lindell, Annukka K

2017-09-01

Portrait pose orientations influence perception: the left cheek is more emotionally expressive; females' right cheeks appear more attractive. Posing biases are established in paintings, photographs, and advertisements, however, book covers have not previously been examined. This paper assesses cover image orientation in a book genre that frequently features a cover portrait: the celebrity cookbook. If marketers intuitively choose to enhance chefs' emotional expressivity, left cheek poses should predominate; if attractiveness is more important, right cheek poses will be more frequent for females, with a left or no cheek bias for males. Celebrity cookbook covers (N = 493) were sourced online; identity, portrait orientation, photo type, and sex were coded. For celebrity cookbooks, left cheek covers (39.6%) were more frequent than right cheek (31.6%) or midline covers (28.8%); sex did not predict pose orientation. An interaction between photo type and sex bordered on significance: photo type did not influence females' pose orientation; for males, the left cheek bias present for head and torso images was absent for full body and head only photos. Overall, the left cheek bias for celebrity cookbook covers implies that marketers intuitively select images that make the chefs appear happier and/or more emotionally expressive, enhancing engagement with the audience.

Quantification of liver fibrosis via second harmonic imaging of the Glisson's capsule from liver surface.

PubMed

Xu, Shuoyu; Kang, Chiang Huen; Gou, Xiaoli; Peng, Qiwen; Yan, Jie; Zhuo, Shuangmu; Cheng, Chee Leong; He, Yuting; Kang, Yuzhan; Xia, Wuzheng; So, Peter T C; Welsch, Roy; Rajapakse, Jagath C; Yu, Hanry

2016-04-01

Liver surface is covered by a collagenous layer called the Glisson's capsule. The structure of the Glisson's capsule is barely seen in the biopsy samples for histology assessment, thus the changes of the collagen network from the Glisson's capsule during the liver disease progression are not well studied. In this report, we investigated whether non-linear optical imaging of the Glisson's capsule at liver surface would yield sufficient information to allow quantitative staging of liver fibrosis. In contrast to conventional tissue sections whereby tissues are cut perpendicular to the liver surface and interior information from the liver biopsy samples were used, we have established a capsule index based on significant parameters extracted from the second harmonic generation (SHG) microscopy images of capsule collagen from anterior surface of rat livers. Thioacetamide (TAA) induced liver fibrosis animal models was used in this study. The capsule index is capable of differentiating different fibrosis stages, with area under receiver operating characteristics curve (AUC) up to 0.91, making it possible to quantitatively stage liver fibrosis via liver surface imaging potentially with endomicroscopy. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mapping spatial patterns with morphological image processing

Treesearch

Peter Vogt; Kurt H. Riitters; Christine Estreguil; Jacek Kozak; Timothy G. Wade; James D. Wickham

2006-01-01

We use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover pattern is classified as 'perforated,' 'edge,' 'patch,' and 'core' with higher spatial precision and thematic accuracy compared to a previous approach based on image convolution, while retaining the...

Structural and Functional Biomedical Imaging Using Polarization-Based Optical Coherence Tomography

NASA Astrophysics Data System (ADS)

Black, Adam J.

Biomedical imaging has had an enormous impact in medicine and research. There are numerous imaging modalities covering a large range of spatial and temporal scales, penetration depths, along with indicators for function and disease. As these imaging technologies mature, the quality of the images they produce increases to resolve finer details with greater contrast at higher speeds which aids in a faster, more accurate diagnosis in the clinic. In this dissertation, polarization-based optical coherence tomography (OCT) systems are used and developed to image biological structure and function with greater speeds, signal-to-noise (SNR) and stability. OCT can image with spatial and temporal resolutions in the micro range. When imaging any sample, feedback is very important to verify the fidelity and desired location on the sample being imaged. To increase frame rates for display as well as data throughput, field-programmable gate arrays (FPGAs) were used with custom algorithms to realize real-time display and streaming output for continuous acquisition of large datasets of swept-source OCT systems. For spectral domain (SD) OCT systems, significant increases in signal-to-noise ratios were achieved from a custom balanced detection (BD) OCT system. The BD system doubled measured signals while reducing common term. For functional imaging, a real-time directed scanner was introduced to visualize the 3D image of a sample to identify regions of interest prior to recording. Elucidating the characteristics of functional OCT signals with the aid of simulations, novel processing methods were also developed to stabilize samples being imaged and identify possible origins of functional signals being measured. Polarization-sensitive OCT was used to image cardiac tissue before and after clearing to identify the regions of vascular perfusion from a coronary artery. The resulting 3D image provides a visualization of the perfusion boundaries for the tissue that would be damaged from a myocardial infarction to possibly identity features that lead to fatal cardiac arrhythmias. 3D functional imaging was used to measure functional retinal activity from a light stimulus. In some cases, single trial responses were possible; measured at the outer segment of the photoreceptor layer. The morphology and time-course of these signals are similar to the intrinsic optical signals reported from phototransduction. Assessing function in the retina could aid in early detection of degenerative diseases of the retina, such as glaucoma and macular degeneration.

Forest Resource Information System (FRIS)

NASA Technical Reports Server (NTRS)

1983-01-01

The technological and economical feasibility of using multispectral digital image data as acquired from the LANDSAT satellites in an ongoing operational forest information system was evaluated. Computer compatible multispectral scanner data secured from the LANDSAT satellites were demonstrated to be a significant contributor to ongoing information systems by providing the added dimensions of synoptic and repeat coverage of the Earth's surface. Major forest cover types of conifer, deciduous, mixed conifer-deciduous and non-forest, were classified well within the bounds of the statistical accuracy of the ground sample. Further, when overlayed with existing maps, the acreage of cover type retains a high level of positional integrity. Maps were digitized by a graphics design system, overlayed and registered onto LANDSAT imagery such that the map data with associated attributes were displayed on the image. Once classified, the analysis results were converted back to map form as a cover type of information. Existing tabular information as represented by inventory is registered geographically to the map base through a vendor provided data management system. The notion of a geographical reference base (map) providing the framework to which imagery and tabular data bases are registered and where each of the three functions of imagery, maps and inventory can be accessed singly or in combination is the very essence of the forest resource information system design.

Enhancement of spectral quality of archival aerial photographs using satellite imagery for detection of land cover

NASA Astrophysics Data System (ADS)

Siok, Katarzyna; Jenerowicz, Agnieszka; Woroszkiewicz, Małgorzata

2017-07-01

Archival aerial photographs are often the only reliable source of information about the area. However, these data are single-band data that do not allow unambiguous detection of particular forms of land cover. Thus, the authors of this article seek to develop a method of coloring panchromatic aerial photographs, which enable increasing the spectral information of such images. The study used data integration algorithms based on pansharpening, implemented in commonly used remote sensing programs: ERDAS, ENVI, and PCI. Aerial photos and Landsat multispectral data recorded in 1987 and 2016 were chosen. This study proposes the use of modified intensity-hue-saturation and Brovey methods. The use of these methods enabled the addition of red-green-blue (RGB) components to monochrome images, thus enhancing their interpretability and spectral quality. The limitations of the proposed method relate to the availability of RGB satellite imagery, the accuracy of mutual orientation of the aerial and the satellite data, and the imperfection of archival aerial photographs. Therefore, it should be expected that the results of coloring will not be perfect compared to the results of the fusion of recent data with a similar ground sampling resolution, but still, they will allow a more accurate and efficient classification of land cover registered on archival aerial photographs.

Relationship between refractive index and mineral content of enamel and dentin using SS-OCT and TMR

NASA Astrophysics Data System (ADS)

Hariri, Ilnaz; Sadr, Alireza; Shimada, Yasushi; Nakashima, Syozi; Sumi, Yasunori; Tagami, Junji

2012-01-01

The aim of this work was to investigate relationship between refractive index (n) and mineral content (MC) (vol %) of enamel and dentin using swept-source optical coherence tomography (SS-OCT) and transverse microradiography (TMR). Enamel and dentin blocks were partitioned into three regions. The middle partition of each sample was covered with a nail polish to protect the sound area during exposure to the treatment solutions. Samples were demineralized in a demineralizing solution, which was refreshed once a week, for 2 months. One window was covered with acid-resistant varnish, leaving the other window exposed; the samples were placed in a solution for remineralization. Samples then were sliced into disks with thickness of 300 μm to 400 μm and placed on metal plate in order to capture cross-sectional images of sound, demineralized and remineralized regions by OCT at 1319 nm center wavelength. The n then was calculated via formula using image analysis software. Following n measurement, these specimens were further polished for the TMR analysis. Correlation between OCT n and TMR MC was examined. A significant and highly positive correlation was found between the measured n and the actual MC at the corresponding locations (Pearson correlation coefficients (r) were 0.94 and 0.97 in enamel and 0.95 and 0.91 in dentin after de-/remineralization process, respectively p < 0.05). OCT showed a potential for quantitative analysis of the mineral loss or gain by measuring of the n in vitro. Supported by the grant from the Japanese Ministry of Education, Global Center of Excellence (GCOE) Program, "International Research Center for Molecular Science in Tooth and Bone Diseases."

Color separation in forensic image processing using interactive differential evolution.

PubMed

Mushtaq, Harris; Rahnamayan, Shahryar; Siddiqi, Areeb

2015-01-01

Color separation is an image processing technique that has often been used in forensic applications to differentiate among variant colors and to remove unwanted image interference. This process can reveal important information such as covered text or fingerprints in forensic investigation procedures. However, several limitations prevent users from selecting the appropriate parameters pertaining to the desired and undesired colors. This study proposes the hybridization of an interactive differential evolution (IDE) and a color separation technique that no longer requires users to guess required control parameters. The IDE algorithm optimizes these parameters in an interactive manner by utilizing human visual judgment to uncover desired objects. A comprehensive experimental verification has been conducted on various sample test images, including heavily obscured texts, texts with subtle color variations, and fingerprint smudges. The advantage of IDE is apparent as it effectively optimizes the color separation parameters at a level indiscernible to the naked eyes. © 2014 American Academy of Forensic Sciences.

Whole-Brain Microscopy Meets In Vivo Neuroimaging: Techniques, Benefits, and Limitations.

PubMed

Aswendt, Markus; Schwarz, Martin; Abdelmoula, Walid M; Dijkstra, Jouke; Dedeurwaerdere, Stefanie

2017-02-01

Magnetic resonance imaging, positron emission tomography, and optical imaging have emerged as key tools to understand brain function and neurological disorders in preclinical mouse models. They offer the unique advantage of monitoring individual structural and functional changes over time. What remained unsolved until recently was to generate whole-brain microscopy data which can be correlated to the 3D in vivo neuroimaging data. Conventional histological sections are inappropriate especially for neuronal tracing or the unbiased screening for molecular targets through the whole brain. As part of the European Society for Molecular Imaging (ESMI) meeting 2016 in Utrecht, the Netherlands, we addressed this issue in the Molecular Neuroimaging study group meeting. Presentations covered new brain clearing methods, light sheet microscopes for large samples, and automatic registration of microscopy to in vivo imaging data. In this article, we summarize the discussion; give an overview of the novel techniques; and discuss the practical needs, benefits, and limitations.

Cover Image, Volume 119, Number 1, January 2018.

PubMed

Rubio-Infante, Nestor; Ilhuicatzi-Alvarado, Damaris; Torres-Martínez, Marilu; Reyes-Grajeda, Juan Pablo; Nava-Acosta, Raúl; González-González, Edith; Moreno-Fierros, Leticia

2018-01-01

Cover: The cover image, by Nestor Rubio-Infante et al., is based on the Article The Macrophage Activation Induced by Bacillus thuringiensis Cry1Ac Protoxin Involves ERK1/2 and p38 Pathways and the Interaction with Cell-Surface-HSP70, DOI: 10.1002/jcb.26216. © 2017 Wiley Periodicals, Inc.

The managed clearing: An overlooked land-cover type in urbanizing regions?

PubMed Central

Madden, Marguerite; Gray, Josh; Meentemeyer, Ross K.

2018-01-01

Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type–semi-natural, vegetated land surfaces with varying degrees of management practices–for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area– 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and mapping of managed clearings in urbanizing landscapes. Our findings also demonstrate the need to more carefully consider managed clearings and their critical ecological functions in landscape- to regional-scale studies of urbanizing ecosystems. PMID:29432442

The managed clearing: An overlooked land-cover type in urbanizing regions?

PubMed

Singh, Kunwar K; Madden, Marguerite; Gray, Josh; Meentemeyer, Ross K

2018-01-01

Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type-semi-natural, vegetated land surfaces with varying degrees of management practices-for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area- 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and mapping of managed clearings in urbanizing landscapes. Our findings also demonstrate the need to more carefully consider managed clearings and their critical ecological functions in landscape- to regional-scale studies of urbanizing ecosystems.

Application of Machine Learning in Urban Greenery Land Cover Extraction

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

High-quality JPEG compression history detection for fake uncompressed images

NASA Astrophysics Data System (ADS)

Zhang, Rong; Wang, Rang-Ding; Guo, Li-Jun; Jiang, Bao-Chuan

2017-05-01

Authenticity is one of the most important evaluation factors of images for photography competitions or journalism. Unusual compression history of an image often implies the illicit intent of its author. Our work aims at distinguishing real uncompressed images from fake uncompressed images that are saved in uncompressed formats but have been previously compressed. To detect the potential image JPEG compression, we analyze the JPEG compression artifacts based on the tetrolet covering, which corresponds to the local image geometrical structure. Since the compression can alter the structure information, the tetrolet covering indexes may be changed if a compression is performed on the test image. Such changes can provide valuable clues about the image compression history. To be specific, the test image is first compressed with different quality factors to generate a set of temporary images. Then, the test image is compared with each temporary image block-by-block to investigate whether the tetrolet covering index of each 4×4 block is different between them. The percentages of the changed tetrolet covering indexes corresponding to the quality factors (from low to high) are computed and used to form the p-curve, the local minimum of which may indicate the potential compression. Our experimental results demonstrate the advantage of our method to detect JPEG compressions of high quality, even the highest quality factors such as 98, 99, or 100 of the standard JPEG compression, from uncompressed-format images. At the same time, our detection algorithm can accurately identify the corresponding compression quality factor.

Sparsity prediction and application to a new steganographic technique

NASA Astrophysics Data System (ADS)

Phillips, David; Noonan, Joseph

2004-10-01

Steganography is a technique of embedding information in innocuous data such that only the innocent data is visible. The wavelet transform lends itself to image steganography because it generates a large number of coefficients representing the information in the image. Altering a small set of these coefficients allows embedding of information (payload) into an image (cover) without noticeably altering the original image. We propose a novel, dual-wavelet steganographic technique, using transforms selected such that the transform of the cover image has low sparsity, while the payload transform has high sparsity. Maximizing the sparsity of the payload transform reduces the amount of information embedded in the cover, and minimizing the sparsity of the cover increases the locations that can be altered without significantly altering the image. Making this system effective on any given image pair requires a metric to indicate the best (maximum sparsity) and worst (minimum sparsity) wavelet transforms to use. This paper develops the first stage of this metric, which can predict, averaged across many wavelet families, which of two images will have a higher sparsity. A prototype implementation of the dual-wavelet system as a proof of concept is also developed.

Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data

NASA Astrophysics Data System (ADS)

Hamedianfar, Alireza; Shafri, Helmi Zulhaidi Mohd

2016-04-01

This paper integrates decision tree-based data mining (DM) and object-based image analysis (OBIA) to provide a transferable model for the detailed characterization of urban land-cover classes using WorldView-2 (WV-2) satellite images. Many articles have been published on OBIA in recent years based on DM for different applications. However, less attention has been paid to the generation of a transferable model for characterizing detailed urban land cover features. Three subsets of WV-2 images were used in this paper to generate transferable OBIA rule-sets. Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. The developed DT algorithm was applied to object-based classifications in the first study area. After this process, we validated the capability and transferability of the classification rules into second and third subsets. Detailed ground truth samples were collected to assess the classification results. The first, second, and third study areas achieved 88%, 85%, and 85% overall accuracies, respectively. Results from the investigation indicate that DM was an efficient method to provide the optimal and transferable classification rules for OBIA, which accelerates the rule-sets creation stage in the OBIA classification domain.

Minimal resin embedding of multicellular specimens for targeted FIB-SEM imaging.

PubMed

Schieber, Nicole L; Machado, Pedro; Markert, Sebastian M; Stigloher, Christian; Schwab, Yannick; Steyer, Anna M

2017-01-01

Correlative light and electron microscopy (CLEM) is a powerful tool to perform ultrastructural analysis of targeted tissues or cells. The large field of view of the light microscope (LM) enables quick and efficient surveys of the whole specimen. It is also compatible with live imaging, giving access to functional assays. CLEM protocols take advantage of the features to efficiently retrace the position of targeted sites when switching from one modality to the other. They more often rely on anatomical cues that are visible both by light and electron microscopy. We present here a simple workflow where multicellular specimens are embedded in minimal amounts of resin, exposing their surface topology that can be imaged by scanning electron microscopy (SEM). LM and SEM both benefit from a large field of view that can cover whole model organisms. As a result, targeting specific anatomic locations by focused ion beam-SEM (FIB-SEM) tomography becomes straightforward. We illustrate this application on three different model organisms, used in our laboratory: the zebrafish embryo Danio rerio, the marine worm Platynereis dumerilii, and the dauer larva of the nematode Caenorhabditis elegans. Here we focus on the experimental steps to reduce the amount of resin covering the samples and to image the specimens inside an FIB-SEM. We expect this approach to have widespread applications for volume electron microscopy on multiple model organisms. Copyright © 2017 Elsevier Inc. All rights reserved.

Land use change analysis using spectral similarity and vegetation indices and its effect on runoff and sediment yield in tropical environment

NASA Astrophysics Data System (ADS)

Christanto, N.; Sartohadi, J.; Setiawan, M. A.; Shrestha, D. B. P.; Jetten, V. G.

2018-04-01

Land use change influences the hydrological as well as landscape processes such as runoff and sediment yields. The main objectives of this study are to assess the land use change and its impact on the runoff and sediment yield of the upper Serayu Catchment. Land use changes of 1991 to 2014 have been analyzed. Spectral similarity and vegetation indices were used to classify the old image. Therefore, the present and the past images are comparable. The influence of the past and present land use on runoff and sediment yield has been compared with field measurement. The effect of land use changes shows the increased surface runoff which is the result of change in the curve number (CN) values. The study shows that it is possible to classify previously obtained image based on spectral characteristics and indices of major land cover types derived from recently obtained image. This avoids the necessity of having training samples which will be difficult to obtain. On the other hand, it also demonstrates that it is possible to link land cover changes with land degradation processes and finally to sedimentation in the reservoir. The only condition is the requirement for having the comparable dataset which should not be difficult to generate. Any variation inherent in the data which are other than surface reflectance has to be corrected.

Low-cost Assessment for Early Vigor and Canopy Cover Estimation in Durum Wheat Using RGB Images.

NASA Astrophysics Data System (ADS)

Fernandez-Gallego, J. A.; Kefauver, S. C.; Aparicio Gutiérrez, N.; Nieto-Taladriz, M. T.; Araus, J. L.

2017-12-01

Early vigor and canopy cover is an important agronomical component for determining grain yield in wheat. Estimates of the canopy cover area at early stages of the crop cycle may contribute to efficiency of crop management practices and breeding programs. Canopy-image segmentation is complicated in field conditions by numerous factors, including soil, shadows and unexpected objects, such as rocks, weeds, plant remains, or even part of the photographer's boots (many times it appears in the scene); and the algorithms must be robust to accommodate these conditions. Field trials were carried out in two sites (Aranjuez and Valladolid, Spain) during the 2016/2017 crop season. A set of 24 varieties of durum wheat in two growing conditions (rainfed and support irrigation) per site were used to create the image database. This work uses zenithal RGB images taken from above the crop in natural light conditions. The images were taken with Canon IXUS 320HS camera in Aranjuez, holding the camera by hand, and with a Nikon D300 camera in Valladolid, using a monopod. The algorithm for early vigor and canopy cover area estimation uses three main steps: (i) Image decorrelation (ii) Colour space transformation and (iii) Canopy cover segmentation using an automatic threshold based on the image histogram. The first step was chosen to enhance the visual interpretation and separate the pixel colors into the scene; the colour space transformation contributes to further separate the colours. Finally an automatic threshold using a minimum method allows for correct segmentation and quantification of the canopy pixels. The percent of area covered by the canopy was calculated using a simple algorithm for counting pixels in the final binary segmented image. The comparative results demonstrate the algorithm's effectiveness through significant correlations between early vigor and canopy cover estimation compared to NDVI (Normalized difference vegetation index) and grain yield.

Decorrelation of L-band and C-band interferometry to volcanic risk prevention

NASA Astrophysics Data System (ADS)

Malinverni, E. S.; Sandwell, D.; Tassetti, A. N.; Cappelletti, L.

2013-10-01

SAR has several strong key features: fine spatial resolution/precision and high temporal pass frequency. Moreover, the InSAR technique allows the accurate detection of ground deformations. This high potential technology can be invaluable to study volcanoes: it provides important information on pre-eruption surface deformation, improving the understanding of volcanic processes and the ability to predict eruptions. As a downside, SAR measurements are influenced by artifacts such as atmospheric effects or bad topographic data. Correlation gives a measure of these interferences, quantifying the similarity of the phase of two SAR images. Different approaches exists to reduce these errors but the main concern remain the possibility to correlate images with different acquisition times: snow-covered or heavily-vegetated areas produce seasonal changes on the surface. Minimizing the time between passes partly limits decorrelation. Though, images with a short temporal baseline aren't always available and some artifacts affecting correlation are timeindependent. This work studies correlation of pairs of SAR images focusing on the influence of surface and climate conditions, especially snow coverage and temperature. Furthermore, the effects of the acquisition band on correlation are taken into account, comparing L-band and C-band images. All the chosen images cover most of the Yellowstone caldera (USA) over a span of 4 years, sampling all the seasons. Interferograms and correlation maps are generated. To isolate temporal decorrelation, pairs of images with the shortest baseline are chosen. Correlation maps are analyzed in relation to snow depth and temperature. Results obtained with ENVISAT and ERS satellites (C-band) are compared with the ones from ALOS (L-band). Results show a good performance during winter and a bad attitude towards wet snow (spring and fall). During summer both L-band and C-band maintain a good coherence with L-band performing better over vegetation.

Investigating Mars: Ascraeus Mons

NASA Image and Video Library

2017-08-28

This image shows part of the southeastern flank of Ascraeus Mons. The narrow flows of the volcano dominate the top of the image, while younger volcanic plains cover the bottom of the image. The relative age designation is based on the fact that the brighter plains flows lap up against and cover the flank flows of Ascraeus Mons. The Odyssey spacecraft has spent over 15 years in orbit around Mars, circling the planet more than 69000 times. It holds the record for longest working spacecraft at Mars. THEMIS, the IR/VIS camera system, has collected data for the entire mission and provides images covering all seasons and lighting conditions. Over the years many features of interest have received repeated imaging, building up a suite of images covering the entire feature. From the deepest chasma to the tallest volcano, individual dunes inside craters and dune fields that encircle the north pole, channels carved by water and lava, and a variety of other feature, THEMIS has imaged them all. For the next several months the image of the day will focus on the Tharsis volcanoes, the various chasmata of Valles Marineris, and the major dunes fields. We hope you enjoy these images! Orbit Number: 10339 Latitude: 9.01699 Longitude: 257.294 Instrument: VIS Captured: 2004-04-13 17:23 https://photojournal.jpl.nasa.gov/catalog/PIA21820

Mapping Secondary Forest Succession on Abandoned Agricultural Land in the Polish Carpathians

NASA Astrophysics Data System (ADS)

Kolecka, N.; Kozak, J.; Kaim, D.; Dobosz, M.; Ginzler, Ch.; Psomas, A.

2016-06-01

Land abandonment and secondary forest succession have played a significant role in land cover changes and forest cover increase in mountain areas in Europe over the past several decades. Land abandonment can be easily observed in the field over small areas, but it is difficult to map over the large areas, e.g., with remote sensing, due to its subtle and spatially dispersed character. Our previous paper presented how the LiDAR (Light Detection and Ranging) and topographic data were used to detect secondary forest succession on abandoned land in one commune located in the Polish Carpathians by means of object-based image analysis (OBIA) and GIS (Kolecka et al., 2015). This paper proposes how the method can be applied to efficiently map secondary forest succession over the entire Polish Carpathians, incorporating spatial sampling strategy supported by various ancillary data. Here we discuss the methods of spatial sampling, its limitations and results in the context of future secondary forest succession modelling.

[Fractional vegetation cover of invasive Spartina alterniflora in coastal wetland using unmanned aerial vehicle (UAV)remote sensing].

PubMed

Zhou, Zai Ming; Yang, Yan Ming; Chen, Ben Qing

2016-12-01

The effective management and utilization of resources and ecological environment of coastal wetland require investigation and analysis in high precision of the fractional vegetation cover of invasive species Spartina alterniflora. In this study, Sansha Bay was selected as the experimental region, and visible and multi-spectral images obtained by low-altitude UAV in the region were used to monitor the fractional vegetation cover of S. alterniflora. Fractional vegetation cover parameters in the multi-spectral images were then estimated by NDVI index model, and the accuracy was tested against visible images as references. Results showed that vegetation covers of S. alterniflora in the image area were mainly at medium high level (40%-60%) and high level (60%-80%). Root mean square error (RMSE) between the NDVI model estimation values and true values was 0.06, while the determination coefficient R 2 was 0.92, indicating a good consistency between the estimation value and the true value.

Analysis of interstellar cloud structure based on IRAS images

NASA Technical Reports Server (NTRS)

Scalo, John M.

1992-01-01

The goal of this project was to develop new tools for the analysis of the structure of densely sampled maps of interstellar star-forming regions. A particular emphasis was on the recognition and characterization of nested hierarchical structure and fractal irregularity, and their relation to the level of star formation activity. The panoramic IRAS images provided data with the required range in spatial scale, greater than a factor of 100, and in column density, greater than a factor of 50. In order to construct densely sampled column density maps of star-forming clouds, column density images of four nearby cloud complexes were constructed from IRAS data. The regions have various degrees of star formation activity, and most of them have probably not been affected much by the disruptive effects of young massive stars. The largest region, the Scorpius-Ophiuchus cloud complex, covers about 1000 square degrees (it was subdivided into a few smaller regions for analysis). Much of the work during the early part of the project focused on an 80 square degree region in the core of the Taurus complex, a well-studied region of low-mass star formation.

Satellite images for land cover monitoring - Navigating through the maze

USGS Publications Warehouse

Künzer, Claudia; Fosnight, Gene

2001-01-01

The focus of this publication is satellite systems for land cover monitoring. On the reverse is a table that compares a selection of these systems, whose data are globally available in a form suitable for land cover analysis. We hope the information presented will help you assess the utility of remotely sensed image to meet your needs.

BOREAS Level-3s SPOT Imagery: Scaled At-sensor Radiance in LGSOWG Format

NASA Technical Reports Server (NTRS)

Strub, Richard; Nickeson, Jaime; Newcomer, Jeffrey A.; Hall, Forrest G. (Editor); Cihlar, Josef

2000-01-01

For BOReal Ecosystem-Atmosphere Study (BOREAS), the level-3s Satellite Pour l'Observation de la Terre (SPOT) data, along with the other remotely sensed images, were collected in order to provide spatially extensive information over the primary study areas. This information includes radiant energy, detailed land cover, and biophysical parameter maps such as Fraction of Photosynthetically Active Radiation (FPAR) and Leaf Area Index (LAI). The SPOT images acquired for the BOREAS project were selected primarily to fill temporal gaps in the Landsat Thematic Mapper (TM) image data collection. CCRS collected and supplied the level-3s images to BOREAS Information System (BORIS) for use in the remote sensing research activities. Spatially, the level-3s images cover 60- by 60-km portions of the BOREAS Northern Study Area (NSA) and Southern Study Area (SSA). Temporally, the images cover the period of 17-Apr-1994 to 30-Aug-1996. The images are available in binary image format files. Due to copyright issues, the SPOT images may not be publicly available.

Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery

NASA Technical Reports Server (NTRS)

Estes, John E.; Gebelein, Jennifer

1999-01-01

This report is produced in accordance with the requirements outlined in the NASA Research Grant NAG9-1032 titled "Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery". This grant funds the Remote Sensing Research Unit of the University of California, Santa Barbara. This document summarizes the research progress and accomplishments to date and describes current on-going research activities. Even though this grant has technically expired, in a contractual sense, work continues on this project. Therefore, this summary will include all work done through and 5 May 1999. The principal goal of this effort is to test the accuracy of a sub-regional portion of an AVHRR-based land cover product. Land cover mapped to three different classification systems, in the southwestern United States, have been subjected to two specific accuracy assessments. One assessment utilizing astronaut acquired photography, and a second assessment employing Landsat Thematic Mapper imagery, augmented in some cases, high aerial photography. Validation of these three land cover products has proceeded using a stratified sampling methodology. We believe this research will provide an important initial test of the potential use of imagery acquired from Shuttle and ultimately the International Space Station (ISS) for the operational validation of the Moderate Resolution Imaging Spectrometer (MODIS) land cover products.

Multitemporal Snow Cover Mapping in Mountainous Terrain for Landsat Climate Data Record Development

NASA Technical Reports Server (NTRS)

Crawford, Christopher J.; Manson, Steven M.; Bauer, Marvin E.; Hall, Dorothy K.

2013-01-01

A multitemporal method to map snow cover in mountainous terrain is proposed to guide Landsat climate data record (CDR) development. The Landsat image archive including MSS, TM, and ETM+ imagery was used to construct a prototype Landsat snow cover CDR for the interior northwestern United States. Landsat snow cover CDRs are designed to capture snow-covered area (SCA) variability at discrete bi-monthly intervals that correspond to ground-based snow telemetry (SNOTEL) snow-water-equivalent (SWE) measurements. The June 1 bi-monthly interval was selected for initial CDR development, and was based on peak snowmelt timing for this mountainous region. Fifty-four Landsat images from 1975 to 2011 were preprocessed that included image registration, top-of-the-atmosphere (TOA) reflectance conversion, cloud and shadow masking, and topographic normalization. Snow covered pixels were retrieved using the normalized difference snow index (NDSI) and unsupervised classification, and pixels having greater (less) than 50% snow cover were classified presence (absence). A normalized SCA equation was derived to independently estimate SCA given missing image coverage and cloud-shadow contamination. Relative frequency maps of missing pixels were assembled to assess whether systematic biases were embedded within this Landsat CDR. Our results suggest that it is possible to confidently estimate historical bi-monthly SCA from partially cloudy Landsat images. This multitemporal method is intended to guide Landsat CDR development for freshwaterscarce regions of the western US to monitor climate-driven changes in mountain snowpack extent.

Using Google Earth to Assess Shade for Sun Protection in Urban Recreation Spaces: Methods and Results.

PubMed

Gage, R; Wilson, N; Signal, L; Barr, M; Mackay, C; Reeder, A; Thomson, G

2018-05-16

Shade in public spaces can lower the risk of and sun burning and skin cancer. However, existing methods of auditing shade require travel between sites, and sunny weather conditions. This study aimed to evaluate the feasibility of free computer software-Google Earth-for assessing shade in urban open spaces. A shade projection method was developed that uses Google Earth street view and aerial images to estimate shade at solar noon on the summer solstice, irrespective of the date of image capture. Three researchers used the method to separately estimate shade cover over pre-defined activity areas in a sample of 45 New Zealand urban open spaces, including 24 playgrounds, 12 beaches and 9 outdoor pools. Outcome measures included method accuracy (assessed by comparison with a subsample of field observations of 10 of the settings) and inter-rater reliability. Of the 164 activity areas identified in the 45 settings, most (83%) had no shade cover. The method identified most activity areas in playgrounds (85%) and beaches (93%) and was accurate for assessing shade over these areas (predictive values of 100%). Only 8% of activity areas at outdoor pools were identified, due to a lack of street view images. Reliability for shade cover estimates was excellent (intraclass correlation coefficient of 0.97, 95% CI 0.97-0.98). Google Earth appears to be a reasonably accurate and reliable and shade audit tool for playgrounds and beaches. The findings are relevant for programmes focused on supporting the development of healthy urban open spaces.

Transmissive liquid-crystal device correcting primary coma aberration and astigmatism in laser scanning microscopy

NASA Astrophysics Data System (ADS)

Tanabe, Ayano; Hibi, Terumasa; Ipponjima, Sari; Matsumoto, Kenji; Yokoyama, Masafumi; Kurihara, Makoto; Hashimoto, Nobuyuki; Nemoto, Tomomi

2016-03-01

Laser scanning microscopy allows 3D cross-sectional imaging inside biospecimens. However, certain aberrations produced can degrade the quality of the resulting images. We previously reported a transmissive liquid-crystal device that could compensate for the predominant spherical aberrations during the observations, particularly in deep regions of the samples. The device, inserted between the objective lens and the microscope revolver, improved the image quality of fixed-mouse-brain slices that were observed using two-photon excitation laser scanning microscopy, which was originally degraded by spherical aberration. In this study, we developed a transmissive device that corrects primary coma aberration and astigmatism, motivated by the fact that these asymmetric aberrations can also often considerably deteriorate image quality, even near the sample surface. The device's performance was evaluated by observing fluorescent beads using single-photon excitation laser scanning microscopy. The fluorescence intensity in the image of the bead under a cover slip tilted in the y-direction was increased by 1.5 times after correction by the device. Furthermore, the y- and z-widths of the imaged bead were reduced to 66% and 65%, respectively. On the other hand, for the imaged bead sucked into a glass capillary in the longitudinal x-direction, correction with the device increased the fluorescence intensity by 2.2 times compared to that of the aberrated image. In addition, the x-, y-, and z-widths of the bead image were reduced to 75%, 53%, and 40%, respectively. Our device successfully corrected several asymmetric aberrations to improve the fluorescent signal and spatial resolution, and might be useful for observing various biospecimens.

The Ad Hoc Mars Airplane science working group. [remotely piloted airplane as a Mars exploration vehicle

NASA Technical Reports Server (NTRS)

Clarke, V. C., Jr.

1978-01-01

The capability of a remotely piloted airplane as a Mars exploration vehicle in the aerial survey mode is assessed. Specific experiment areas covered include: visual imaging; gamma ray and infrared reflectance spectroscopy; gravity field; magnetic field and electromagnetic sounding; and atmospheric composition and dynamics. It is concluded that (1) the most important use of a plane in the aerial survey mode would be in topical studies and returned sample site characterization; (2) the airplane offers the unique capability to do high resolution, oblique imaging, and repeated profile measurements in the atmospheric boundary layer; and (3) it offers the best platform from which to do electromagnetic sounding.

Hydrometric, Hydrochemical, and Hydrogeophysical Runoff Characterization Across Multiple Land Covers in the Agua Salud Project, Panama

NASA Astrophysics Data System (ADS)

Litt, Guy Finley

As the Panama Canal Authority faces sensitivity to water shortages, managing water resources becomes crucial for the global shipping industry's security. These studies address knowledge gaps in tropical water resources to aid hydrological model development and validation. Field-based hydrological investigations in the Agua Salud Project within the Panama Canal Watershed employed multiple tools across a variety of land covers to investigate hydrological processes. Geochemical tracers informed where storm runoff in a stream comes from and identified electrical conductivity (EC) as an economical, high sample frequency tracer during small storms. EC-based hydrograph separation coupled with hydrograph recession rate analyses identified shallow and deep groundwater storage-discharge relationships that varied by season and land cover. A series of plot-scale electrical resistivity imaging geophysical experiments coupled with rainfall simulation characterized subsurface flow pathway behavior and quantified respectively increasing infiltration rates across pasture, 10 year old secondary succession forest, teak (tectona grandis), and 30 year old secondary succession forest land covers. Additional soil water, groundwater, and geochemical studies informed conceptual model development in subsurface flow pathways and groundwater, and identified future research needs.

Dual-resolution image reconstruction for region-of-interest CT scan

NASA Astrophysics Data System (ADS)

Jin, S. O.; Shin, K. Y.; Yoo, S. K.; Kim, J. G.; Kim, K. H.; Huh, Y.; Lee, S. Y.; Kwon, O.-K.

2014-07-01

In ordinary CT scan, so called full field-of-view (FFOV) scan, in which the x-ray beam span covers the whole section of the body, a large number of projections are necessary to reconstruct high resolution images. However, excessive x-ray dose is a great concern in FFOV scan. Region-of-interest (ROI) scan is a method to visualize the ROI in high resolution while reducing the x-ray dose. But, ROI scan suffers from bright-band artifacts which may hamper CT-number accuracy. In this study, we propose an image reconstruction method to eliminate the band artifacts in the ROI scan. In addition to the ROI scan with high sampling rate in the view direction, we get FFOV projection data with much lower sampling rate. Then, we reconstruct images in the compressed sensing (CS) framework with dual resolutions, that is, high resolution in the ROI and low resolution outside the ROI. For the dual-resolution image reconstruction, we implemented the dual-CS reconstruction algorithm in which data fidelity and total variation (TV) terms were enforced twice in the framework of adaptive steepest descent projection onto convex sets (ASD-POCS). The proposed method has remarkably reduced the bright-band artifacts at around the ROI boundary, and it has also effectively suppressed the streak artifacts over the entire image. We expect the proposed method can be greatly used for dual-resolution imaging with reducing the radiation dose, artifacts and scan time.

Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss

USGS Publications Warehouse

Potapov, P.; Hansen, Matthew C.; Stehman, S.V.; Loveland, Thomas R.; Pittman, K.

2008-01-01

Estimation of forest cover change is important for boreal forests, one of the most extensive forested biomes, due to its unique role in global timber stock, carbon sequestration and deposition, and high vulnerability to the effects of global climate change. We used time-series data from the MODerate Resolution Imaging Spectroradiometer (MODIS) to produce annual forest cover loss hotspot maps. These maps were used to assign all blocks (18.5 by 18.5 km) partitioning the boreal biome into strata of high, medium and low likelihood of forest cover loss. A stratified random sample of 118 blocks was interpreted for forest cover and forest cover loss using high spatial resolution Landsat imagery from 2000 and 2005. Area of forest cover gross loss from 2000 to 2005 within the boreal biome is estimated to be 1.63% (standard error 0.10%) of the total biome area, and represents a 4.02% reduction in year 2000 forest cover. The proportion of identified forest cover loss relative to regional forest area is much higher in North America than in Eurasia (5.63% to 3.00%). Of the total forest cover loss identified, 58.9% is attributable to wildfires. The MODIS pan-boreal change hotspot estimates reveal significant increases in forest cover loss due to wildfires in 2002 and 2003, with 2003 being the peak year of loss within the 5-year study period. Overall, the precision of the aggregate forest cover loss estimates derived from the Landsat data and the value of the MODIS-derived map displaying the spatial and temporal patterns of forest loss demonstrate the efficacy of this protocol for operational, cost-effective, and timely biome-wide monitoring of gross forest cover loss.

Space Radar Image of Raco, Michigan

NASA Image and Video Library

1999-05-01

These are two false-color composites of Raco, Michigan, located at the eastern end of Michigan upper peninsula, west of Sault Ste. Marie and south of Whitefish Bay on Lake Superior. The two images (centered at 46.39 degrees north latitude, 84.88 degrees west longitude) show significant seasonal changes in the mid-latitude region of mixed deciduous and coniferous forests. The images were acquired by the Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) aboard the shuttle Endeavour on the sixth orbit of each mission. In these images, red is L-band (23 cm) with horizontal/vertical polarization; green is C-band (6 cm) with horizontal/vertical polarization; blue is C-band with horizontal/horizontal polarization. The region shown is largely forested and includes a large portion of Hiawatha National Forest, as well as an agricultural region near the bottom of each image. In early April, the area was snow-covered with up to 50 centimeters (19.5 inches) of snow in forest clearings and agricultural fields. Buds had not yet broken on deciduous trees, but the trees were not frozen and sap was generally flowing. Lake Superior, in the upper right, and the small inland lakes were frozen and snow-covered on April 9, 1994. By the end of September, deciduous trees were just beginning to change color after a relatively wet period. Leaf loss was estimated at about 30 percent, depending on the species, and the soil was moist to wet after a heavy rainfall on September 28, 1994. Most agricultural fields were covered with grasses of up to 60 centimeters (23 inches) in height. In the two images the colors are related to the types of land cover (i.e. vegetation type) and the brightness is related to the amount of plant material and its relative moisture content. Significant seasonal changes between early spring and early fall are illustrated by this pair of images. For the agricultural region near the bottom of the images, the change from snow-cover to moist soil with short vegetation cover is shown by the color change from blue to green and blue. The green color corresponds to significant increases in vegetation cover and field-to-field differences in blue are the result of differences in surface roughness and soil moisture. In the forested areas, many of the conifer forests appear similar in both images (red pine forests appear red in both images). However, there is more blue and green in the September 30, 1994 image as a consequence of greater foliage and more moisture in the forest crowns. Lowland conifer forests (spruce and northern white cedars) appear as bright green in both images. Deciduous forests produce very strong radar returns at these frequencies and polarization combinations, resulting in a nearly white appearance on the images (the specific color mix is related to the local species mix). In the September 30, 1994 image, the areas of deciduous forest appear darker than in the April image because of the weaker radar signal from the foliage in the crown layer. The clear-cut areas (shown in April by the irregularly shaped dark areas in the center) change dramatically in appearance due to loss of snow cover and increases in soil moisture and vegetation cover by the end of September. http://photojournal.jpl.nasa.gov/catalog/PIA01730

An improved image alignment procedure for high-resolution transmission electron microscopy.

PubMed

Lin, Fang; Liu, Yan; Zhong, Xiaoyan; Chen, Jianghua

2010-06-01

Image alignment is essential for image processing methods such as through-focus exit-wavefunction reconstruction and image averaging in high-resolution transmission electron microscopy. Relative image displacements exist in any experimentally recorded image series due to the specimen drifts and image shifts, hence image alignment for correcting the image displacements has to be done prior to any further image processing. The image displacement between two successive images is determined by the correlation function of the two relatively shifted images. Here it is shown that more accurate image alignment can be achieved by using an appropriate aperture to filter the high-frequency components of the images being aligned, especially for a crystalline specimen with little non-periodic information. For the image series of crystalline specimens with little amorphous, the radius of the filter aperture should be as small as possible, so long as it covers the innermost lattice reflections. Testing with an experimental through-focus series of Si[110] images, the accuracies of image alignment with different correlation functions are compared with respect to the error functions in through-focus exit-wavefunction reconstruction based on the maximum-likelihood method. Testing with image averaging over noisy experimental images from graphene and carbon-nanotube samples, clear and sharp crystal lattice fringes are recovered after applying optimal image alignment. Copyright 2010 Elsevier Ltd. All rights reserved.

Adaptive AFM scan speed control for high aspect ratio fast structure tracking

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

Ahmad, Ahmad; Schuh, Andreas; Rangelow, Ivo W.

2014-10-15

Improved imaging rates in Atomic Force Microscopes (AFM) are of high interest for disciplines such as life sciences and failure analysis of semiconductor wafers, where the sample topology shows high aspect ratios. Also, fast imaging is necessary to cover a large surface under investigation in reasonable times. Since AFMs are composed of mechanical components, they are associated with comparably low resonance frequencies that undermine the effort to increase the acquisition rates. In particular, high and steep structures are difficult to follow, which causes the cantilever to temporarily loose contact to or crash into the sample. Here, we report on amore » novel approach that does not affect the scanner dynamics, but adapts the lateral scanning speed of the scanner. The controller monitors the control error signal and, only when necessary, decreases the scan speed to allow the z-piezo more time to react to changes in the sample's topography. In this case, the overall imaging rate can be significantly increased, because a general scan speed trade-off decision is not needed and smooth areas are scanned fast. In contrast to methods trying to increase the z-piezo bandwidth, our method is a comparably simple approach that can be easily adapted to standard systems.« less

Modulus design multiwavelength polarization microscope for transmission Mueller matrix imaging

NASA Astrophysics Data System (ADS)

Zhou, Jialing; He, Honghui; Chen, Zhenhua; Wang, Ye; Ma, Hui

2018-01-01

We have developed a polarization microscope based on a commercial transmission microscope. We replace the halogen light source by a collimated LED light source module of six different colors. We use achromatic polarized optical elements that can cover the six different wavelength ranges in the polarization state generator (PSG) and polarization state analyzer (PSA) modules. The dual-rotating wave plate method is used to measure the Mueller matrix of samples, which requires the simultaneous rotation of the two quarter-wave plates in both PSG and PSA at certain angular steps. A scientific CCD detector is used as the image receiving module. A LabView-based software is developed to control the rotation angels of the wave plates and the exposure time of the detector to allow the system to run fully automatically in preprogrammed schedules. Standard samples, such as air, polarizers, and quarter-wave plates, are used to calibrate the intrinsic Mueller matrix of optical components, such as the objectives, using the eigenvalue calibration method. Errors due to the images walk-off in the PSA are studied. Errors in the Mueller matrices are below 0.01 using air and polarizer as standard samples. Data analysis based on Mueller matrix transformation and Mueller matrix polarization decomposition is used to demonstrate the potential application of this microscope in pathological diagnosis.

Flexible conformable hydrophobized surfaces for turbulent flow drag reduction

PubMed Central

Brennan, Joseph C; Geraldi, Nicasio R; Morris, Robert H; Fairhurst, David J; McHale, Glen; Newton, Michael I

2015-01-01

In recent years extensive work has been focused onto using superhydrophobic surfaces for drag reduction applications. Superhydrophobic surfaces retain a gas layer, called a plastron, when submerged underwater in the Cassie-Baxter state with water in contact with the tops of surface roughness features. In this state the plastron allows slip to occur across the surface which results in a drag reduction. In this work we report flexible and relatively large area superhydrophobic surfaces produced using two different methods: Large roughness features were created by electrodeposition on copper meshes; Small roughness features were created by embedding carbon nanoparticles (soot) into Polydimethylsiloxane (PDMS). Both samples were made into cylinders with a diameter under 12 mm. To characterize the samples, scanning electron microscope (SEM) images and confocal microscope images were taken. The confocal microscope images were taken with each sample submerged in water to show the extent of the plastron. The hydrophobized electrodeposited copper mesh cylinders showed drag reductions of up to 32% when comparing the superhydrophobic state with a wetted out state. The soot covered cylinders achieved a 30% drag reduction when comparing the superhydrophobic state to a plain cylinder. These results were obtained for turbulent flows with Reynolds numbers 10,000 to 32,500. PMID:25975704

Optimizing the Attitude Control of Small Satellite Constellations for Rapid Response Imaging

NASA Astrophysics Data System (ADS)

Nag, S.; Li, A.

2016-12-01

Distributed Space Missions (DSMs) such as formation flight and constellations, are being recognized as important solutions to increase measurement samples over space and time. Given the increasingly accurate attitude control systems emerging in the commercial market, small spacecraft now have the ability to slew and point within few minutes of notice. In spite of hardware development in CubeSats at the payload (e.g. NASA InVEST) and subsystems (e.g. Blue Canyon Technologies), software development for tradespace analysis in constellation design (e.g. Goddard's TAT-C), planning and scheduling development in single spacecraft (e.g. GEO-CAPE) and aerial flight path optimizations for UAVs (e.g. NASA Sensor Web), there is a gap in open-source, open-access software tools for planning and scheduling distributed satellite operations in terms of pointing and observing targets. This paper will demonstrate results from a tool being developed for scheduling pointing operations of narrow field-of-view (FOV) sensors over mission lifetime to maximize metrics such as global coverage and revisit statistics. Past research has shown the need for at least fourteen satellites to cover the Earth globally everyday using a LandSat-like sensor. Increasing the FOV three times reduces the need to four satellites, however adds image distortion and BRDF complexities to the observed reflectance. If narrow FOV sensors on a small satellite constellation were commanded using robust algorithms to slew their sensor dynamically, they would be able to coordinately cover the global landmass much faster without compensating for spatial resolution or BRDF effects. Our algorithm to optimize constellation satellite pointing is based on a dynamic programming approach under the constraints of orbital mechanics and existing attitude control systems for small satellites. As a case study for our algorithm, we minimize the time required to cover the 17000 Landsat images with maximum signal to noise ratio fall-off and minimum image distortion among the satellites, using Landsat's specifications. Attitude-specific constraints such as power consumption, response time, and stability were factored into the optimality computations. The algorithm can integrate cloud cover predictions, specific ground and air assets and angular constraints.

CMOS sensors for atmospheric imaging

NASA Astrophysics Data System (ADS)

Pratlong, Jérôme; Burt, David; Jerram, Paul; Mayer, Frédéric; Walker, Andrew; Simpson, Robert; Johnson, Steven; Hubbard, Wendy

2017-09-01

Recent European atmospheric imaging missions have seen a move towards the use of CMOS sensors for the visible and NIR parts of the spectrum. These applications have particular challenges that are completely different to those that have driven the development of commercial sensors for applications such as cell-phone or SLR cameras. This paper will cover the design and performance of general-purpose image sensors that are to be used in the MTG (Meteosat Third Generation) and MetImage satellites and the technology challenges that they have presented. We will discuss how CMOS imagers have been designed with 4T pixel sizes of up to 250 μm square achieving good charge transfer efficiency, or low lag, with signal levels up to 2M electrons and with high line rates. In both devices a low noise analogue read-out chain is used with correlated double sampling to suppress the readout noise and give a maximum dynamic range that is significantly larger than in standard commercial devices. Radiation hardness is a particular challenge for CMOS detectors and both of these sensors have been designed to be fully radiation hard with high latch-up and single-event-upset tolerances, which is now silicon proven on MTG. We will also cover the impact of ionising radiation on these devices. Because with such large pixels the photodiodes have a large open area, front illumination technology is sufficient to meet the detection efficiency requirements but with thicker than standard epitaxial silicon to give improved IR response (note that this makes latch up protection even more important). However with narrow band illumination reflections from the front and back of the dielectric stack on the top of the sensor produce Fabry-Perot étalon effects, which have been minimised with process modifications. We will also cover the addition of precision narrow band filters inside the MTG package to provide a complete imaging subsystem. Control of reflected light is also critical in obtaining the required optical performance and this has driven the development of a black coating layer that can be applied between the active silicon regions.

Classification of surface types using SIR-C/X-SAR, Mount Everest Area, Tibet

USGS Publications Warehouse

Albright, Thomas P.; Painter, Thomas H.; Roberts, Dar A.; Shi, Jiancheng; Dozier, Jeff; Fielding, Eric

1998-01-01

Imaging radar is a promising tool for mapping snow and ice cover in alpine regions. It combines a high-resolution, day or night, all-weather imaging capability with sensitivity to hydrologic and climatic snow and ice parameters. We use the spaceborne imaging radar-C/X-band synthetic aperture radar (SIR-C/X-SAR) to map snow and glacial ice on the rugged north slope of Mount Everest. From interferometrically derived digital elevation data, we compute the terrain calibration factor and cosine of the local illumination angle. We then process and terrain-correct radar data sets acquired on April 16, 1994. In addition to the spectral data, we include surface slope to improve discrimination among several surface types. These data sets are then used in a decision tree to generate an image classification. This method is successful in identifying and mapping scree/talus, dry snow, dry snow-covered glacier, wet snow-covered glacier, and rock-covered glacier, as corroborated by comparison with existing surface cover maps and other ancillary information. Application of the classification scheme to data acquired on October 7 of the same year yields accurate results for most surface types but underreports the extent of dry snow cover.

Using hyperspectral remote sensing for land cover classification

NASA Astrophysics Data System (ADS)

Zhang, Wendy W.; Sriharan, Shobha

2005-01-01

This project used hyperspectral data set to classify land cover using remote sensing techniques. Many different earth-sensing satellites, with diverse sensors mounted on sophisticated platforms, are currently in earth orbit. These sensors are designed to cover a wide range of the electromagnetic spectrum and are generating enormous amounts of data that must be processed, stored, and made available to the user community. The Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) collects data in 224 bands that are approximately 9.6 nm wide in contiguous bands between 0.40 and 2.45 mm. Hyperspectral sensors acquire images in many, very narrow, contiguous spectral bands throughout the visible, near-IR, and thermal IR portions of the spectrum. The unsupervised image classification procedure automatically categorizes the pixels in an image into land cover classes or themes. Experiments on using hyperspectral remote sensing for land cover classification were conducted during the 2003 and 2004 NASA Summer Faculty Fellowship Program at Stennis Space Center. Research Systems Inc.'s (RSI) ENVI software package was used in this application framework. In this application, emphasis was placed on: (1) Spectrally oriented classification procedures for land cover mapping, particularly, the supervised surface classification using AVIRIS data; and (2) Identifying data endmembers.

Analysis of land cover/use changes using Landsat 5 TM data and indices.

PubMed

Ettehadi Osgouei, Paria; Kaya, Sinasi

2017-04-01

Urban expansion and unprecedented rural to urban transition, along with a huge population growth, are major driving forces altering land cover/use in metropolitan areas. Many of the land cover classes such as farmlands, wetlands, forests, and bare soils have been transformed during the past years into human settlements. Identification of the city growth trends and the impact of it on the vegetation cover of an area is essential for a better understanding of the sustainability of urban development processes, both planned and unplanned. Analyzing the causes and consequences of land use dynamics helps local government, urban planners, and managers for the betterment of future plans and minimizing the negative effects.This study determined temporal changes in vegetation cover and built-up area in Istanbul (Turkey) using the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and built-up area index (BUAI). The temporal data were based on Landsat 5 Thematic Mapper (TM) images acquired in June of 1984, 2002, 2007, 2009, and 2011. The NDVI was applied to all the Landsat images, and the resulting NDVI images were overlaid to generate an NDVI layer stack image. The same procedure was repeated using the SAVI and BUAI images. The layer stack images revealed those areas that had changed in terms of the different indices over the years. To determine temporal change trends, the values of 150 randomly selected control points were extracted from the same locations in the NDVI, SAVI, and BUAI layer stack images. The results obtained from these control points showed that vegetation cover decreased considerably because of a remarkable increase in the built-up area.

The Slope Imaging Multi-Polarization Photon-Counting Lidar: Development and Performance Results

NASA Technical Reports Server (NTRS)

Dabney, Phillip

2010-01-01

The Slope Imaging Multi-polarization Photon-counting Lidar is an airborne instrument developed to demonstrate laser altimetry measurement methods that will enable more efficient observations of topography and surface properties from space. The instrument was developed through the NASA Earth Science Technology Office Instrument Incubator Program with a focus on cryosphere remote sensing. The SIMPL transmitter is an 11 KHz, 1064 nm, plane-polarized micropulse laser transmitter that is frequency doubled to 532 nm and split into four push-broom beams. The receiver employs single-photon, polarimetric ranging at 532 and 1064 nm using Single Photon Counting Modules in order to achieve simultaneous sampling of surface elevation, slope, roughness and depolarizing scattering properties, the latter used to differentiate surface types. Data acquired over ice-covered Lake Erie in February, 2009 are documenting SIMPL s measurement performance and capabilities, demonstrating differentiation of open water and several ice cover types. ICESat-2 will employ several of the technologies advanced by SIMPL, including micropulse, single photon ranging in a multi-beam, push-broom configuration operating at 532 nm.

Video processing of remote sensor data applied to uranium exploration in Wyoming. [Roll-front U deposits

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

Levinson, R.A.; Marrs, R.W.; Crockell, F.

1979-06-30

LANDSAT satellite imagery and aerial photography can be used to map areas of altered sandstone associated with roll-front uranium deposits. Image data must be enhanced so that alteration spectral contrasts can be seen, and video image processing is a fast, low-cost, and efficient tool. For LANDSAT data, the 7/4 ratio produces the best enhancement of altered sandstone. The 6/4 ratio is most effective for color infrared aerial photography. Geochemical and mineralogical associations occur in unaltered, altered, and ore roll-front zones. Samples from Pumpkin Buttes show that iron is the primary coloring agent which makes alteration visually detectable. Eh and pHmore » changes associated with passage of a roll front cause oxidation of magnetite and pyrite to hematite, goethite, and limonite in the host sandstone, thereby producing the alteration. Statistical analysis show that the detectability of geochemical and color zonation in host sands is weakened by soil-forming processes. Alteration can only be mapped in areas of thin soil cover and moderate to sparse vegetative cover.« less

Analysis of energy dispersive x-ray diffraction profiles for material identification, imaging and system control

NASA Astrophysics Data System (ADS)

Cook, Emily Jane

2008-12-01

This thesis presents the analysis of low angle X-ray scatter measurements taken with an energy dispersive system for substance identification, imaging and system control. Diffraction measurements were made on illicit drugs, which have pseudo- crystalline structures and thus produce diffraction patterns comprising a se ries of sharp peaks. Though the diffraction profiles of each drug are visually characteristic, automated detection systems require a substance identification algorithm, and multivariate analysis was selected as suitable. The software was trained with measured diffraction data from 60 samples covering 7 illicit drugs and 5 common cutting agents, collected with a range of statistical qual ities and used to predict the content of 7 unknown samples. In all cases the constituents were identified correctly and the contents predicted to within 15%. Soft tissues exhibit broad peaks in their diffraction patterns. Diffraction data were collected from formalin fixed breast tissue samples and used to gen erate images. Maximum contrast between healthy and suspicious regions was achieved using momentum transfer windows 1.04-1.10 and 1.84-1.90 nm_1. The resulting images had an average contrast of 24.6% and 38.9% compared to the corresponding transmission X-ray images (18.3%). The data was used to simulate the feedback for an adaptive imaging system and the ratio of the aforementioned momentum transfer regions found to be an excellent pa rameter. Investigation into the effects of formalin fixation on human breast tissue and animal tissue equivalents indicated that fixation in standard 10% buffered formalin does not alter the diffraction profiles of tissue in the mo mentum transfer regions examined, though 100% unbuffered formalin affects the profile of porcine muscle tissue (a substitute for glandular and tumourous tissue), though fat is unaffected.

Debris Disk Dust Characterization through Spectral Types: Deep Visible-Light Imaging of Nine Systems

NASA Astrophysics Data System (ADS)

Choquet, Elodie

2017-08-01

We propose STIS coronagraphy of 9 debris disks recently seen in the near-infrared from our re-analysis of archival NICMOS data. STIS coronagraphy will provide complementary visible-light images that will let us characterize the disk colors needed to place constraints on dust grain sizes, albedos, and anisotropy of scattering of these disks. With 3 times finer angular resolution and much better sensitivity, our STIS images will dramatically surpass the NICMOS discovery images, and will more clearly reveal disk local structures, cleared inner regions, and test for large-scale asymmetries in the dust distributions possibly triggered by associated planets in these systems. The exquisite sensitivity to visible-light scattering by submicron particles uniquely offered by STIS coronagraphy will let us detect and spatially characterize the diffuse halo of dust blown out of the systems by the host star radiative pressure. Our sample includes disks around 3 low-mass stars, 3 solar-type stars, and 3 massive A stars; together with our STIS+NICMOS imaging of 6 additional disks around F and G stars, our sample covers the full range of spectral types and will let us perform a comparative study of dust distribution properties as a function of stellar mass and luminosity. Our sample makes up more than 1/3 of all debris disks imaged in scattered light to date, and will offer the first homogeneous characterization of the visible-light to near-IR properties of debris disk systems over a large range of spectral types. Our program will let us analyze how the dynamical balance is affected by initial conditions and star properties, and how it may be perturbed by gas drag or planet perturbations.

A high-resolution combined scanning laser and widefield polarizing microscope for imaging at temperatures from 4 K to 300 K.

PubMed

Lange, M; Guénon, S; Lever, F; Kleiner, R; Koelle, D

2017-12-01

Polarized light microscopy, as a contrast-enhancing technique for optically anisotropic materials, is a method well suited for the investigation of a wide variety of effects in solid-state physics, as, for example, birefringence in crystals or the magneto-optical Kerr effect (MOKE). We present a microscopy setup that combines a widefield microscope and a confocal scanning laser microscope with polarization-sensitive detectors. By using a high numerical aperture objective, a spatial resolution of about 240 nm at a wavelength of 405 nm is achieved. The sample is mounted on a 4 He continuous flow cryostat providing a temperature range between 4 K and 300 K, and electromagnets are used to apply magnetic fields of up to 800 mT with variable in-plane orientation and 20 mT with out-of-plane orientation. Typical applications of the polarizing microscope are the imaging of the in-plane and out-of-plane magnetization via the longitudinal and polar MOKE, imaging of magnetic flux structures in superconductors covered with a magneto-optical indicator film via the Faraday effect, or imaging of structural features, such as twin-walls in tetragonal SrTiO 3 . The scanning laser microscope furthermore offers the possibility to gain local information on electric transport properties of a sample by detecting the beam-induced voltage change across a current-biased sample. This combination of magnetic, structural, and electric imaging capabilities makes the microscope a viable tool for research in the fields of oxide electronics, spintronics, magnetism, and superconductivity.

A high-resolution combined scanning laser and widefield polarizing microscope for imaging at temperatures from 4 K to 300 K

NASA Astrophysics Data System (ADS)

Lange, M.; Guénon, S.; Lever, F.; Kleiner, R.; Koelle, D.

2017-12-01

Polarized light microscopy, as a contrast-enhancing technique for optically anisotropic materials, is a method well suited for the investigation of a wide variety of effects in solid-state physics, as, for example, birefringence in crystals or the magneto-optical Kerr effect (MOKE). We present a microscopy setup that combines a widefield microscope and a confocal scanning laser microscope with polarization-sensitive detectors. By using a high numerical aperture objective, a spatial resolution of about 240 nm at a wavelength of 405 nm is achieved. The sample is mounted on a 4He continuous flow cryostat providing a temperature range between 4 K and 300 K, and electromagnets are used to apply magnetic fields of up to 800 mT with variable in-plane orientation and 20 mT with out-of-plane orientation. Typical applications of the polarizing microscope are the imaging of the in-plane and out-of-plane magnetization via the longitudinal and polar MOKE, imaging of magnetic flux structures in superconductors covered with a magneto-optical indicator film via the Faraday effect, or imaging of structural features, such as twin-walls in tetragonal SrTiO3. The scanning laser microscope furthermore offers the possibility to gain local information on electric transport properties of a sample by detecting the beam-induced voltage change across a current-biased sample. This combination of magnetic, structural, and electric imaging capabilities makes the microscope a viable tool for research in the fields of oxide electronics, spintronics, magnetism, and superconductivity.

On locating steganographic payload using residuals

NASA Astrophysics Data System (ADS)

Quach, Tu-Thach

2011-02-01

Locating steganographic payload usingWeighted Stego-image (WS) residuals has been proven successful provided a large number of stego images are available. In this paper, we revisit this topic with two goals. First, we argue that it is a promising approach to locate payload by showing that in the ideal scenario where the cover images are available, the expected number of stego images needed to perfectly locate all load-carrying pixels is the logarithm of the payload size. Second, we generalize cover estimation to a maximum likelihood decoding problem and demonstrate that a second-order statistical cover model can be used to compute residuals to locate payload embedded by both LSB replacement and LSB matching steganography.

Epi-detected quadruple-modal nonlinear optical microscopy for label-free imaging of the tooth

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

Wang, Zi; Zheng, Wei; Huang, Zhiwei, E-mail: biehzw@nus.edu.sg

2015-01-19

We present an epi-detected quadruple-modal nonlinear optical microscopic imaging technique (i.e., coherent anti-Stokes Raman scattering (CARS), second-harmonic generation (SHG), third-harmonic generation (THG), and two-photon excited fluorescence (TPEF)) based on a picosecond (ps) laser-pumped optical parametric oscillator system for label-free imaging of the tooth. We demonstrate that high contrast ps-CARS images covering both the fingerprint (500–1800 cm{sup −1}) and high-wavenumber (2500–3800 cm{sup −1}) regions can be acquired to uncover the distributions of mineral and organic biomaterials in the tooth, while high quality TPEF, SHG, and THG images of the tooth can also be acquired under ps laser excitation without damaging the samples. Themore » quadruple-modal nonlinear microscopic images (CARS/SHG/THG/TPEF) acquired provide better understanding of morphological structures and biochemical/biomolecular distributions in the dentin, enamel, and the dentin-enamel junction of the tooth without labeling, facilitating optical diagnosis and characterization of the tooth in dentistry.« less

Deep Spitzer/IRAC Imaging of the Subaru Deep Field

NASA Astrophysics Data System (ADS)

Jiang, Linhua; Egami, Eiichi; Cohen, Seth; Fan, Xiaohui; Ly, Chun; Mechtley, Matthew; Windhorst, Rogier

2013-10-01

The last decade saw great progress in our understanding of the distant Universe as a number of objects at z > 6 were discovered. The Subaru Deep Field (SDF) project has played an important role on study of high-z galaxies. The SDF is unique: it covers a large area of 850 sq arcmin; it has extremely deep optical images in a series of broad and narrow bands; it has the largest sample of spectroscopically-confirmed galaxies known at z >= 6, including ~100 Lyman alpha emitters (LAEs) and ~50 Lyman break galaxies (LBGs). Here we propose to carry out deep IRAC imaging observations of the central 75% of the SDF. The proposed observations together with those from our previous Spitzer programs will reach a depth of ~10 hours, and enable the first complete census of physical properties and stellar populations of spectroscopically-confirmed galaxies at the end of cosmic reionization. IRAC data is the key to measure stellar masses and constrain stellar populations in high-z galaxies. From SED modeling with secure redshifts, we will characterize the physical properties of these galaxies, and trace their mass assembly and star formation history. In particular, it allows us, for the first time, to study stellar populations in a large sample of z >=6 LAEs. We will also address some critical questions, such as whether LAEs and LBGs represent physically different galaxy populations. All these will help us to understand the earliest galaxy formation and evolution, and better constrain the galaxy contribution to reionization. The IRAC data will also cover 10,000 emission-line selected galaxies at z < 1.5, 50,000 UV and mass selected LBGs at 1.5 < z < 3, and more than 5,000 LBGs at 3 < z < 6. It will have a legacy value for SDF-related programs.

A virtual image chain for perceived image quality of medical display

NASA Astrophysics Data System (ADS)

Marchessoux, Cédric; Jung, Jürgen

2006-03-01

This paper describes a virtual image chain for medical display (project VICTOR: granted in the 5th framework program by European commission). The chain starts from raw data of an image digitizer (CR, DR) or synthetic patterns and covers image enhancement (MUSICA by Agfa) and both display possibilities, hardcopy (film on viewing box) and softcopy (monitor). Key feature of the chain is a complete image wise approach. A first prototype is implemented in an object-oriented software platform. The display chain consists of several modules. Raw images are either taken from scanners (CR-DR) or from a pattern generator, in which characteristics of DR- CR systems are introduced by their MTF and their dose-dependent Poisson noise. The image undergoes image enhancement and comes to display. For soft display, color and monochrome monitors are used in the simulation. The image is down-sampled. The non-linear response of a color monitor is taken into account by the GOG or S-curve model, whereas the Standard Gray-Scale-Display-Function (DICOM) is used for monochrome display. The MTF of the monitor is applied on the image in intensity levels. For hardcopy display, the combination of film, printer, lightbox and viewing condition is modeled. The image is up-sampled and the DICOM-GSDF or a Kanamori Look-Up-Table is applied. An anisotropic model for the MTF of the printer is applied on the image in intensity levels. The density-dependent color (XYZ) of the hardcopy film is introduced by Look-Up-tables. Finally a Human Visual System Model is applied to the intensity images (XYZ in terms of cd/m2) in order to eliminate nonvisible differences. Comparison leads to visible differences, which are quantified by higher order image quality metrics. A specific image viewer is used for the visualization of the intensity image and the visual difference maps.

Optimal use of land surface temperature data to detect changes in tropical forest cover

NASA Astrophysics Data System (ADS)

Van Leeuwen, T. T.; Frank, A. J.; Jin, Y.; Smyth, P.; Goulden, M.; van der Werf, G.; Randerson, J. T.

2011-12-01

Rapid and accurate assessment of global forest cover change is needed to focus conservation efforts and to better understand how deforestation is contributing to the build up of atmospheric CO2. Here we examined different ways to use remotely sensed land surface temperature (LST) to detect changes in tropical forest cover. In our analysis we used monthly 0.05×0.05 degree Terra MODerate Resolution Imaging Spectroradiometer (MODIS) observations of LST and PRODES (Program for the Estimation of Deforestation in the Brazilian Amazon) estimates of forest cover change. We also compared MODIS LST observations with an independent estimate of forest cover loss derived from MODIS and Landsat observations. Our study domain of approximately 10×10 degree included most of the Brazilian state of Mato Grosso. For optimal use of LST data to detect changes in tropical forest cover in our study area, we found that using data sampled during the end of the dry season (~1-2 months after minimum monthly precipitation) had the greatest predictive skill. During this part of the year, precipitation was low, surface humidity was at a minimum, and the difference between day and night LST was the largest. We used this information to develop a simple temporal sampling algorithm appropriate for use in pan-tropical deforestation classifiers. Combined with the normalized difference vegetation index (NDVI), a logistic regression model using day-night LST did moderately well at predicting forest cover change. Annual changes in day-night LST difference decreased during 2006-2009 relative to 2001-2005 in many regions within the Amazon, providing independent confirmation of lower deforestation levels during the latter part of this decade as reported by PRODES. The use of day-night LST differences may be particularly valuable for use with satellites that do not have spectral bands that allow for the estimation of NDVI or other vegetation indices.

Using Landsat satellite data to support pesticide exposure assessment in California.

PubMed

Maxwell, Susan K; Airola, Matthew; Nuckols, John R

2010-09-16

The recent U.S. Geological Survey policy offering Landsat satellite data at no cost provides researchers new opportunities to explore relationships between environment and health. The purpose of this study was to examine the potential for using Landsat satellite data to support pesticide exposure assessment in California. We collected a dense time series of 24 Landsat 5 and 7 images spanning the year 2000 for an agricultural region in Fresno County. We intersected the Landsat time series with the California Department of Water Resources (CDWR) land use map and selected field samples to define the phenological characteristics of 17 major crop types or crop groups. We found the frequent overpass of Landsat enabled detection of crop field conditions (e.g., bare soil, vegetated) over most of the year. However, images were limited during the winter months due to cloud cover. Many samples designated as single-cropped in the CDWR map had phenological patterns that represented multi-cropped or non-cropped fields, indicating they may have been misclassified. We found the combination of Landsat 5 and 7 image data would clearly benefit pesticide exposure assessment in this region by 1) providing information on crop field conditions at or near the time when pesticides are applied, and 2) providing information for validating the CDWR map. The Landsat image time-series was useful for identifying idle, single-, and multi-cropped fields. Landsat data will be limited during the winter months due to cloud cover, and for years prior to the Landsat 7 launch (1999) when only one satellite was operational at any given time. We suggest additional research to determine the feasibility of integrating CDWR land use maps and Landsat data to derive crop maps in locations and time periods where maps are not available, which will allow for substantial improvements to chemical exposure estimation.

Mapping land cover and estimating forest structure using satellite imagery and coarse resolution lidar in the Virgin Islands

Treesearch

T.A. Kennaway; E.H. Helmer; M.A. Lefsky; T.A. Brandeis; K.R. Sherill

2008-01-01

Current information on land cover, forest type and forest structure for the Virgin Islands is critical to land managers and researchers for accurate forest inventory and ecological monitoring. In this study, we use cloud free image mosaics of panchromatic sharpened Landsat ETM+ images and decision tree classification software to map land cover and forest type for the...

Mapping land cover and estimating forest structure using satellite imagery and coarse resolution lidar in the Virgin Islands

Treesearch

Todd Kennaway; Eileen Helmer; Michael Lefsky; Thomas Brandeis; Kirk Sherrill

2009-01-01

Current information on land cover, forest type and forest structure for the Virgin Islands is critical to land managers and researachers for accurate forest inverntory and ecological monitoring. In this study, we use cloud free image mosaics of panchromatic sharpened Landsat ETM+ images and decision tree classification software to map land cover and forest type for the...

Examination of the semi-automatic calculation technique of vegetation cover rate by digital camera images.

NASA Astrophysics Data System (ADS)

Takemine, S.; Rikimaru, A.; Takahashi, K.

The rice is one of the staple foods in the world High quality rice production requires periodically collecting rice growth data to control the growth of rice The height of plant the number of stem the color of leaf is well known parameters to indicate rice growth Rice growth diagnosis method based on these parameters is used operationally in Japan although collecting these parameters by field survey needs a lot of labor and time Recently a laborsaving method for rice growth diagnosis is proposed which is based on vegetation cover rate of rice Vegetation cover rate of rice is calculated based on discriminating rice plant areas in a digital camera image which is photographed in nadir direction Discrimination of rice plant areas in the image was done by the automatic binarization processing However in the case of vegetation cover rate calculation method depending on the automatic binarization process there is a possibility to decrease vegetation cover rate against growth of rice In this paper a calculation method of vegetation cover rate was proposed which based on the automatic binarization process and referred to the growth hysteresis information For several images obtained by field survey during rice growing season vegetation cover rate was calculated by the conventional automatic binarization processing and the proposed method respectively And vegetation cover rate of both methods was compared with reference value obtained by visual interpretation As a result of comparison the accuracy of discriminating rice plant areas was increased by the proposed

Intra- and interspecific variation in tropical tree and liana phenology derived from Unmanned Aerial Vehicle images

NASA Astrophysics Data System (ADS)

Bohlman, S.; Park, J.; Muller-Landau, H. C.; Rifai, S. W.; Dandois, J. P.

2017-12-01

Phenology is a critical driver of ecosystem processes. There is strong evidence that phenology is shifting in temperate ecosystems in response to climate change, but tropical tree and liana phenology remains poorly quantified and understood. A key challenge is that tropical forests contain hundreds of plant species with a wide variety of phenological patterns. Satellite-based observations, an important source of phenology data in northern latitudes, are hindered by frequent cloud cover in the tropics. To quantify phenology over a large number of individuals and species, we collected bi-weekly images from unmanned aerial vehicles (UAVs) in the well-studied 50-ha forest inventory plot on Barro Colorado Island, Panama. Between October 2014 and December 2015 and again in May 2015, we collected a total of 35 sets of UAV images, each with continuous coverage of the 50-ha plot, where every tree ≥ 1 cm DBH is mapped. Spectral, texture, and image information was extracted from the UAV images for individual tree crowns, which was then used as inputs for a machine learning algorithm to predict percent leaf and branch cover. We obtained the species identities of 2000 crowns in the images via field mapping. The objectives of this study are to (1) determined if machine learning algorithms, applied to UAV images, can effectively quantify changes in leaf cover, which we term "deciduousness; (2) determine how liana cover effects deciduousness and (3) test how well UAV-derived deciduousness patterns match satellite-derived temporal patterns. Machine learning algorithms trained on a variety of image parameters could effectively determine leaf cover, despite variation in lighting and viewing angles. Crowns with higher liana cover have less overall deciduousness (tree + liana together) than crowns with lower liana cover. Individual crown deciduousness, summed over all crowns measured in the 50-ha plot, showed a similar seasonal pattern as MODIS EVI composited over 10 years. However, MODIS EVI phenology was "greened" up earlier than UAV-based deciduousness, perhaps reflecting the new late dry season leaf flush that increases EVI but not overall leaf cover. We discuss how the potential mechanisms that explain variation among species and between trees and lianas and the consequences for these variation for ecosystem processes and modeling.

Noise in NC-AFM measurements with significant tip–sample interaction

PubMed Central

Lübbe, Jannis; Temmen, Matthias

2016-01-01

The frequency shift noise in non-contact atomic force microscopy (NC-AFM) imaging and spectroscopy consists of thermal noise and detection system noise with an additional contribution from amplitude noise if there are significant tip–sample interactions. The total noise power spectral density D Δ f(f m) is, however, not just the sum of these noise contributions. Instead its magnitude and spectral characteristics are determined by the strongly non-linear tip–sample interaction, by the coupling between the amplitude and tip–sample distance control loops of the NC-AFM system as well as by the characteristics of the phase locked loop (PLL) detector used for frequency demodulation. Here, we measure D Δ f(f m) for various NC-AFM parameter settings representing realistic measurement conditions and compare experimental data to simulations based on a model of the NC-AFM system that includes the tip–sample interaction. The good agreement between predicted and measured noise spectra confirms that the model covers the relevant noise contributions and interactions. Results yield a general understanding of noise generation and propagation in the NC-AFM and provide a quantitative prediction of noise for given experimental parameters. We derive strategies for noise-optimised imaging and spectroscopy and outline a full optimisation procedure for the instrumentation and control loops. PMID:28144538

Noise in NC-AFM measurements with significant tip-sample interaction.

PubMed

Lübbe, Jannis; Temmen, Matthias; Rahe, Philipp; Reichling, Michael

2016-01-01

The frequency shift noise in non-contact atomic force microscopy (NC-AFM) imaging and spectroscopy consists of thermal noise and detection system noise with an additional contribution from amplitude noise if there are significant tip-sample interactions. The total noise power spectral density D Δ f ( f m ) is, however, not just the sum of these noise contributions. Instead its magnitude and spectral characteristics are determined by the strongly non-linear tip-sample interaction, by the coupling between the amplitude and tip-sample distance control loops of the NC-AFM system as well as by the characteristics of the phase locked loop (PLL) detector used for frequency demodulation. Here, we measure D Δ f ( f m ) for various NC-AFM parameter settings representing realistic measurement conditions and compare experimental data to simulations based on a model of the NC-AFM system that includes the tip-sample interaction. The good agreement between predicted and measured noise spectra confirms that the model covers the relevant noise contributions and interactions. Results yield a general understanding of noise generation and propagation in the NC-AFM and provide a quantitative prediction of noise for given experimental parameters. We derive strategies for noise-optimised imaging and spectroscopy and outline a full optimisation procedure for the instrumentation and control loops.

LANDSAT 4 band 6 data evaluation

NASA Technical Reports Server (NTRS)

1984-01-01

A series of images of a portion of a TM frame of Lake Ontario are presented. The top left frame is the TM Band 6 image, the top right image is a conventional contrast stretched image. The bottom left image is a Band 5 to Band 3 ratio image. This image is used to generate a primitive land cover classificaton. Each land cover (Water, Urban, Forest, Agriculture) is assigned a Band 6 emissivity value. The ratio image is then combined with the Band 6 image and atmospheric propagation data to generate the bottom right image. This image represents a display of data whose digital count can be directly related to estimated surface temperature. The resolution appears higher because the process cell is the size of the TM shortwave pixels.

False-color composite image of Prince Albert, Canada

NASA Technical Reports Server (NTRS)

1994-01-01

This is a false color composite of Prince Albert, Canada, centered at 53.91 north latitude and 104.69 west longitude. This image was acquired by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) on the 20th orbit of the Shuttle Endeavour. The area is located 40 km north and 30 km east of the town of Prince Albert in the Saskatchewan province of Canada. The image covers the area east of the Candle Lake, between gravel surface highways 120 and 106 and west of 106. The area in the middle of the image covers the entire Nipawin (Narrow Hills) provincial park. The look angle of the radar is 30 degrees and the size of the image is approximately 20 kilometers by 50 kilometers (12 by 30 miles). Most of the dark areas in the image are the ice-covered lakes in the region. The dark area on the top right corner of the image is the White Gull Lake north of the intersection of Highway 120 and 913. The right middle part of the image shows Lake Ispuchaw and Lower Fishing Lake

Three frequency false-color image of Prince Albert, Canada

NASA Technical Reports Server (NTRS)

1994-01-01

This is a three-frequency, false color image of Prince Albert, Canada, centered at 53.91 north latitude and 104.69 west longitude. It was produced using data from the X-band, C-band and L-band radars that comprise the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR). SIR-C/X-SAR acquired this image on the 20th orbit of the Shuttle Endeavour. The area is located 40 km north and 30 km east of the town of Prince Albert in the Saskatchewan province of Canada. The image covers the area east of the Candle Lake, between gravel surface highways 120 and 106 and west of 106. The area in the middle of the image covers the entire Nipawin (Narrow Hills) provincial park. Most of the dark blue areas in the image are the ice covered lakes. The dark area on the top right corner of the image is the White Gull Lake north of the intersection of highway 120 and 913. The right middle part of the image shows Lake Ispuchaw and Lower Fishing Lake. The deforested areas are shown by light

Estimating accuracy of land-cover composition from two-stage cluster sampling

USGS Publications Warehouse

Stehman, S.V.; Wickham, J.D.; Fattorini, L.; Wade, T.D.; Baffetta, F.; Smith, J.H.

2009-01-01

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), root mean square error (RMSE), and correlation (CORR) to quantify accuracy of land-cover composition for a general two-stage cluster sampling design, and for the special case of simple random sampling without replacement (SRSWOR) at each stage. The bias of the estimators for the two-stage SRSWOR design is evaluated via a simulation study. The estimators of RMSE and CORR have small bias except when sample size is small and the land-cover class is rare. The estimator of MAD is biased for both rare and common land-cover classes except when sample size is large. A general recommendation is that rare land-cover classes require large sample sizes to ensure that the accuracy estimators have small bias. ?? 2009 Elsevier Inc.

High-frame-rate full-vocal-tract 3D dynamic speech imaging.

PubMed

Fu, Maojing; Barlaz, Marissa S; Holtrop, Joseph L; Perry, Jamie L; Kuehn, David P; Shosted, Ryan K; Liang, Zhi-Pei; Sutton, Bradley P

2017-04-01

To achieve high temporal frame rate, high spatial resolution and full-vocal-tract coverage for three-dimensional dynamic speech MRI by using low-rank modeling and sparse sampling. Three-dimensional dynamic speech MRI is enabled by integrating a novel data acquisition strategy and an image reconstruction method with the partial separability model: (a) a self-navigated sparse sampling strategy that accelerates data acquisition by collecting high-nominal-frame-rate cone navigator sand imaging data within a single repetition time, and (b) are construction method that recovers high-quality speech dynamics from sparse (k,t)-space data by enforcing joint low-rank and spatiotemporal total variation constraints. The proposed method has been evaluated through in vivo experiments. A nominal temporal frame rate of 166 frames per second (defined based on a repetition time of 5.99 ms) was achieved for an imaging volume covering the entire vocal tract with a spatial resolution of 2.2 × 2.2 × 5.0 mm 3 . Practical utility of the proposed method was demonstrated via both validation experiments and a phonetics investigation. Three-dimensional dynamic speech imaging is possible with full-vocal-tract coverage, high spatial resolution and high nominal frame rate to provide dynamic speech data useful for phonetic studies. Magn Reson Med 77:1619-1629, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

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

PubMed

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

2012-09-01

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

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

PubMed Central

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

2013-01-01

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

A patch-based convolutional neural network for remote sensing image classification.

PubMed

Sharma, Atharva; Liu, Xiuwen; Yang, Xiaojun; Shi, Di

2017-11-01

Availability of accurate land cover information over large areas is essential to the global environment sustainability; digital classification using medium-resolution remote sensing data would provide an effective method to generate the required land cover information. However, low accuracy of existing per-pixel based classification methods for medium-resolution data is a fundamental limiting factor. While convolutional neural networks (CNNs) with deep layers have achieved unprecedented improvements in object recognition applications that rely on fine image structures, they cannot be applied directly to medium-resolution data due to lack of such fine structures. In this paper, considering the spatial relation of a pixel to its neighborhood, we propose a new deep patch-based CNN system tailored for medium-resolution remote sensing data. The system is designed by incorporating distinctive characteristics of medium-resolution data; in particular, the system computes patch-based samples from multidimensional top of atmosphere reflectance data. With a test site from the Florida Everglades area (with a size of 771 square kilometers), the proposed new system has outperformed pixel-based neural network, pixel-based CNN and patch-based neural network by 24.36%, 24.23% and 11.52%, respectively, in overall classification accuracy. By combining the proposed deep CNN and the huge collection of medium-resolution remote sensing data, we believe that much more accurate land cover datasets can be produced over large areas. Copyright © 2017 Elsevier Ltd. All rights reserved.

77 FR 15298 - Rule Concerning Disclosures Regarding Energy Consumption and Water Use of Certain Home Appliances...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-15

... manufacturers make images of their labels available on a Web site for linking and downloading by both paper... rather than using the images provided by the manufacturers, as long as the labels conform to all the... the covered product and its price,'' rather than alongside every image of a covered product on the...

Evaluation of different esthetic smile criteria.

PubMed

Al-Johany, Sulieman S; Alqahtani, Abdulaziz S; Alqahtani, Fahd Y; Alzahrani, Adel H

2011-01-01

The aim of this study was to evaluate the existence of different esthetic smile criteria as determined on the smiles of celebrities, which were considered by lay people to be beautiful. An Internet search for "best smile" and "female celebrities" in the years 2007 and 2008 identified 50 celebrities who were voted to have beautiful smiles. Another search was made for images of these celebrities that showed the entire face with an open smile. The images were analyzed using Digimizer image analysis software for different esthetic smile criteria. Eighty percent of the sample was classified as having an average upper lip position, 62% showed upward upper lip curvature, and 78% had a parallel smile line. Forty-two percent of the images showed the maxillary anterior teeth not touching the lower lip, while 34% were touching, and 24% slightly covered it. Sixty percent displayed up to the second premolar, and 32% displayed up to the first molar when smiling. Midline deviation was detected in 36% of the sample. Diastema and golden proportion were not seen in any of the subjects. Female celebrities voted to have the best smile by lay people showed most of the esthetic smile criteria with slight variations, except for the golden proportion. The opinions and perceptions of lay people about beauty should be studied and evaluated.

Landcover Classification Using Deep Fully Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Wang, J.; Li, X.; Zhou, S.; Tang, J.

2017-12-01

Land cover classification has always been an essential application in remote sensing. Certain image features are needed for land cover classification whether it is based on pixel or object-based methods. Different from other machine learning methods, deep learning model not only extracts useful information from multiple bands/attributes, but also learns spatial characteristics. In recent years, deep learning methods have been developed rapidly and widely applied in image recognition, semantic understanding, and other application domains. However, there are limited studies applying deep learning methods in land cover classification. In this research, we used fully convolutional networks (FCN) as the deep learning model to classify land covers. The National Land Cover Database (NLCD) within the state of Kansas was used as training dataset and Landsat images were classified using the trained FCN model. We also applied an image segmentation method to improve the original results from the FCN model. In addition, the pros and cons between deep learning and several machine learning methods were compared and explored. Our research indicates: (1) FCN is an effective classification model with an overall accuracy of 75%; (2) image segmentation improves the classification results with better match of spatial patterns; (3) FCN has an excellent ability of learning which can attains higher accuracy and better spatial patterns compared with several machine learning methods.

Automated Visibility & Cloud Cover Measurements with a Solid State Imaging System

DTIC Science & Technology

1989-03-01

GL-TR-89-0061 SIO Ref. 89-7 MPL-U-26/89 AUTOMATED VISIBILITY & CLOUD COVER MEASUREMENTS WITH A SOLID-STATE IMAGING SYSTEM C) to N4 R. W. Johnson W. S...include Security Classification) Automated Visibility & Cloud Measurements With A Solid State Imaging System 12. PERSONAL AUTHOR(S) Richard W. Johnson...based imaging systems , their ics and control algorithms, thus they ar.L discussed sepa- initial deployment and the preliminary application of rately

Transvaginal 3D Image-Guided High Intensity Focused Ultrasound Array

NASA Astrophysics Data System (ADS)

Held, Robert; Nguyen, Thuc Nghi; Vaezy, Shahram

2005-03-01

The goal of this project is to develop a transvaginal image-guided High Intensity Focused Ultrasound (HIFU) device using piezocomposite HIFU array technology, and commercially-available ultrasound imaging. Potential applications include treatment of uterine fibroids and abnormal uterine bleeding. The HIFU transducer was an annular phased array, with a focal length range of 30-60 mm, an elliptically-shaped aperture of 35×60 mm, and an operating frequency of 3 MHz. A pillow-shaped bag with water circulation will be used for coupling the HIFU energy into the tissue. An intra-cavity imaging probe (C9-5, Philips) was integrated with the HIFU array such that the focal axis of the HIFU transducer was within the image plane. The entire device will be covered by a gel-filled condom when inserted in the vaginal cavity. To control it, software packages were developed in the LabView programming environment. An imaging algorithm processed the ultrasound image to remove noise patterns due to the HIFU signal. The device will be equipped with a three-dimensional tracking system, using a six-degrees-of-freedom articulating arm. Necrotic lesions were produced in a tissue-mimicking phantom and a turkey breast sample for all focal lengths. Various HIFU doses allow various necrotic lesion shapes, including thin ellipsoidal, spherical, wide cylindrical, and teardrop-shaped. Software control of the device allows multiple foci to be activated sequentially for desired lesion patterns. Ultrasound imaging synchronization can be achieved using hardware signals obtained from the imaging system, or software signals determined empirically for various imaging probes. The image-guided HIFU device will provide a valuable tool in visualization of uterine fibroid tumors for the purposes of planning and subsequent HIFU treatment of the tumor, all in a 3D environment. The control system allows for various lesions of different shapes to be optimally positioned in the tumor to cover the entire tumor volume. Real-time ultrasound imaging for guidance and monitoring of HIFU treatment provides an effective method for outpatient-based procedures.

Mapping stand-age distribution of Russian forests from satellite data

NASA Astrophysics Data System (ADS)

Chen, D.; Loboda, T. V.; Hall, A.; Channan, S.; Weber, C. Y.

2013-12-01

Russian boreal forest is a critical component of the global boreal biome as approximately two thirds of the boreal forest is located in Russia. Numerous studies have shown that wildfire and logging have led to extensive modifications of forest cover in the region since 2000. Forest disturbance and subsequent regrowth influences carbon and energy budgets and, in turn, affect climate. Several global and regional satellite-based data products have been developed from coarse (>100m) and moderate (10-100m) resolution imagery to monitor forest cover change over the past decade, record of forest cover change pre-dating year 2000 is very fragmented. Although by using stacks of Landsat images, some information regarding the past disturbances can be obtained, the quantity and locations of such stacks with sufficient number of images are extremely limited, especially in Eastern Siberia. This paper describes a modified method which is built upon previous work to hindcast the disturbance history and map stand-age distribution in the Russian boreal forest. Utilizing data from both Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS), a wall-to-wall map indicating the estimated age of forest in the Russian boreal forest is created. Our previous work has shown that disturbances can be mapped successfully up to 30 years in the past as the spectral signature of regrowing forests is statistically significantly different from that of mature forests. The presented algorithm ingests 55 multi-temporal stacks of Landsat imagery available over Russian forest before 2001 and processes through a standardized and semi-automated approach to extract training and validation data samples. Landsat data, dating back to 1984, are used to generate maps of forest disturbance using temporal shifts in Disturbance Index through the multi-temporal stack of imagery in selected locations. These maps are then used as reference data to train a decision tree classifier on 50 MODIS-based indices. The resultant map provides an estimate of forest age based on the regrowth curves observed from Landsat imagery. The accuracy of the resultant map is assessed against three datasets: 1) subset of the disturbance maps developed within the algorithm, 2) independent disturbance maps created by the Northern Eurasia Land Dynamics Analysis (NELDA) project, and 3) field-based stand-age distribution from forestry inventory units. The current version of the product presents a considerable improvement on the previous version which used Landsat data samples at a set of randomly selected locations, resulting a strong bias of the training samples towards the Landsat-rich regions (e.g. European Russia) whereas regions such as Siberia were under-sampled. Aiming at improving accuracy, the current method significantly increases the number of training Landsat samples compared to the previous work. Aside from the previously used data, the current method uses all available Landsat data for the under-sampled regions in order to increase the representativeness of the total samples. The finial accuracy assessment is still ongoing, however, the initial results suggested an overall accuracy expressed in Kappa > 0.8. We plan to release both the training data and the final disturbance map of the Russian boreal forest to the public after the validation is completed.

An algorithm for encryption of secret images into meaningful images

NASA Astrophysics Data System (ADS)

Kanso, A.; Ghebleh, M.

2017-03-01

Image encryption algorithms typically transform a plain image into a noise-like cipher image, whose appearance is an indication of encrypted content. Bao and Zhou [Image encryption: Generating visually meaningful encrypted images, Information Sciences 324, 2015] propose encrypting the plain image into a visually meaningful cover image. This improves security by masking existence of encrypted content. Following their approach, we propose a lossless visually meaningful image encryption scheme which improves Bao and Zhou's algorithm by making the encrypted content, i.e. distortions to the cover image, more difficult to detect. Empirical results are presented to show high quality of the resulting images and high security of the proposed algorithm. Competence of the proposed scheme is further demonstrated by means of comparison with Bao and Zhou's scheme.

Image processing methods in two and three dimensions used to animate remotely sensed data. [cloud cover

NASA Technical Reports Server (NTRS)

Hussey, K. J.; Hall, J. R.; Mortensen, R. A.

1986-01-01

Image processing methods and software used to animate nonimaging remotely sensed data on cloud cover are described. Three FORTRAN programs were written in the VICAR2/TAE image processing domain to perform 3D perspective rendering, to interactively select parameters controlling the projection, and to interpolate parameter sets for animation images between key frames. Operation of the 3D programs and transferring the images to film is automated using executive control language and custom hardware to link the computer and camera.

Demonstration of Imaging Fourier Transform Spectrometer (FTS) Performance for Planetary and Geostationary Earth Observing

NASA Technical Reports Server (NTRS)

Revercomb, Henry E.; Sromovsky, Lawrence A.; Fry, Patrick M.; Best, Fred A.; LaPorte, Daniel D.

2001-01-01

The combination of massively parallel spatial sampling and accurate spectral radiometry offered by imaging FTS makes it extremely attractive for earth and planetary remote sensing. We constructed a breadboard instrument to help assess the potential for planetary applications of small imaging FTS instruments in the 1 - 5 micrometer range. The results also support definition of the NASA Geostationary Imaging FTS (GIFTS) instrument that will make key meteorological and climate observations from geostationary earth orbit. The Planetary Imaging FTS (PIFTS) breadboard is based on a custom miniaturized Bomen interferometer that uses corner cube reflectors, a wishbone pivoting voice-coil delay scan mechanism, and a laser diode metrology system. The interferometer optical output is measured by a commercial infrared camera procured from Santa Barbara Focalplane. It uses an InSb 128x128 detector array that covers the entire FOV of the instrument when coupled with a 25 mm focal length commercial camera lens. With appropriate lenses and cold filters the instrument can be used from the visible to 5 micrometers. The delay scan is continuous, but slow, covering the maximum range of +/- 0.4 cm in 37.56 sec at a rate of 500 image frames per second. Image exposures are timed to be centered around predicted zero crossings. The design allows for prediction algorithms that account for the most recent fringe rate so that timing jitter produced by scan speed variations can be minimized. Response to a fixed source is linear with exposure time nearly to the point of saturation. Linearity with respect to input variations was demonstrated to within 0.16% using a 3-point blackbody calibration. Imaging of external complex scenes was carried out at low and high spectral resolution. These require full complex calibration to remove background contributions that vary dramatically over the instrument FOV. Testing is continuing to demonstrate the precise radiometric accuracy and noise characteristics.

Experimental study on the 3D image reconstruction in a truncated Archimedean-like spiral geometry with a long-rectangular detector and its image characteristics

NASA Astrophysics Data System (ADS)

Hong, Daeki; Cho, Heemoon; Cho, Hyosung; Choi, Sungil; Je, Uikyu; Park, Yeonok; Park, Chulkyu; Lim, Hyunwoo; Park, Soyoung; Woo, Taeho

2015-11-01

In this work, we performed a feasibility study on the three-dimensional (3D) image reconstruction in a truncated Archimedean-like spiral geometry with a long-rectangular detector for application to high-accurate, cost-effective dental x-ray imaging. Here an x-ray tube and a detector rotate together around the rotational axis several times and, concurrently, the detector moves horizontally in the detector coordinate at a constant speed to cover the whole imaging volume during the projection data acquisition. We established a table-top setup which mainly consists of an x-ray tube (60 kVp, 5 mA), a narrow CMOS-type detector (198-μm pixel resolution, 184 (W)×1176 (H) pixel dimension), and a rotational stage for sample mounting and performed a systematic experiment to demonstrate the viability of the proposed approach to volumetric dental imaging. For the image reconstruction, we employed a compressed-sensing (CS)-based algorithm, rather than a common filtered-backprojection (FBP) one, for more accurate reconstruction. We successfully reconstructed 3D images of considerably high quality and investigated the image characteristics in terms of the image value profile, the contrast-to-noise ratio (CNR), and the spatial resolution.

Target recognition of log-polar ladar range images using moment invariants

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jie; Yu, Haoyong

2017-01-01

The ladar range image has received considerable attentions in the automatic target recognition field. However, previous research does not cover target recognition using log-polar ladar range images. Therefore, we construct a target recognition system based on log-polar ladar range images in this paper. In this system combined moment invariants and backpropagation neural network are selected as shape descriptor and shape classifier, respectively. In order to fully analyze the effect of log-polar sampling pattern on recognition result, several comparative experiments based on simulated and real range images are carried out. Eventually, several important conclusions are drawn: (i) if combined moments are computed directly by log-polar range images, translation, rotation and scaling invariant properties of combined moments will be invalid (ii) when object is located in the center of field of view, recognition rate of log-polar range images is less sensitive to the changing of field of view (iii) as object position changes from center to edge of field of view, recognition performance of log-polar range images will decline dramatically (iv) log-polar range images has a better noise robustness than Cartesian range images. Finally, we give a suggestion that it is better to divide field of view into recognition area and searching area in the real application.

Imaging brain tumour microstructure.

PubMed

Nilsson, Markus; Englund, Elisabet; Szczepankiewicz, Filip; van Westen, Danielle; Sundgren, Pia C

2018-05-08

Imaging is an indispensable tool for brain tumour diagnosis, surgical planning, and follow-up. Definite diagnosis, however, often demands histopathological analysis of microscopic features of tissue samples, which have to be obtained by invasive means. A non-invasive alternative may be to probe corresponding microscopic tissue characteristics by MRI, or so called 'microstructure imaging'. The promise of microstructure imaging is one of 'virtual biopsy' with the goal to offset the need for invasive procedures in favour of imaging that can guide pre-surgical planning and can be repeated longitudinally to monitor and predict treatment response. The exploration of such methods is motivated by the striking link between parameters from MRI and tumour histology, for example the correlation between the apparent diffusion coefficient and cellularity. Recent microstructure imaging techniques probe even more subtle and specific features, providing parameters associated to cell shape, size, permeability, and volume distributions. However, the range of scenarios in which these techniques provide reliable imaging biomarkers that can be used to test medical hypotheses or support clinical decisions is yet unknown. Accurate microstructure imaging may moreover require acquisitions that go beyond conventional data acquisition strategies. This review covers a wide range of candidate microstructure imaging methods based on diffusion MRI and relaxometry, and explores advantages, challenges, and potential pitfalls in brain tumour microstructure imaging. Copyright © 2018. Published by Elsevier Inc.

Cover Image, Volume 176A, Number 3, March 2018.

PubMed

Tamai, Kei; Tada, Katsuhiko; Takeuchi, Akihito; Nakamura, Makoto; Marunaka, Hidenori; Washio, Yosuke; Tanaka, Hiroyuki; Miya, Fuyuki; Okamoto, Nobuhiko; Kageyama, Misao

2018-03-01

The cover image, by Kei Tamai et al., is based on the Clinical Report Fetal ultrasonographic findings including cerebral hyperechogenicity in a patient with non-lethal form of Raine syndrome, DOI: 10.1002/ajmg.a.38598. © 2018 Wiley Periodicals, Inc.

Mapping Soil Organic Matter with Hyperspectral Imaging

NASA Astrophysics Data System (ADS)

Moni, Christophe; Burud, Ingunn; Flø, Andreas; Rasse, Daniel

2014-05-01

Soil organic matter (SOM) plays a central role for both food security and the global environment. Soil organic matter is the 'glue' that binds soil particles together, leading to positive effects on soil water and nutrient availability for plant growth and helping to counteract the effects of erosion, runoff, compaction and crusting. Hyperspectral measurements of samples of soil profiles have been conducted with the aim of mapping soil organic matter on a macroscopic scale (millimeters and centimeters). Two soil profiles have been selected from the same experimental site, one from a plot amended with biochar and another one from a control plot, with the specific objective to quantify and map the distribution of biochar in the amended profile. The soil profiles were of size (30 x 10 x 10) cm3 and were scanned with two pushbroomtype hyperspectral cameras, one which is sensitive in the visible wavelength region (400 - 1000 nm) and one in the near infrared region (1000 - 2500 nm). The images from the two detectors were merged together into one full dataset covering the whole wavelength region. Layers of 15 mm were removed from the 10 cm high sample such that a total of 7 hyperspectral images were obtained from the samples. Each layer was analyzed with multivariate statistical techniques in order to map the different components in the soil profile. Moreover, a 3-dimensional visalization of the components through the depth of the sample was also obtained by combining the hyperspectral images from all the layers. Mid-infrared spectroscopy of selected samples of the measured soil profiles was conducted in order to correlate the chemical constituents with the hyperspectral results. The results show that hyperspectral imaging is a fast, non-destructive technique, well suited to characterize soil profiles on a macroscopic scale and hence to map elements and different organic matter quality present in a complete pedon. As such, we were able to map and quantify biochar in our profile. Smaller interesting regions can also easily be selected from the hyperspectral images for more detailed study at microscopic scale.

Propagation-based phase-contrast tomography for high-resolution lung imaging with laboratory sources

NASA Astrophysics Data System (ADS)

Krenkel, Martin; Töpperwien, Mareike; Dullin, Christian; Alves, Frauke; Salditt, Tim

2016-03-01

We have performed high-resolution phase-contrast tomography on whole mice with a laboratory setup. Enabled by a high-brilliance liquid-metal-jet source, we show the feasibility of propagation-based phase contrast in local tomography even in the presence of strongly absorbing surrounding tissue as it is the case in small animal imaging of the lung. We demonstrate the technique by reconstructions of the mouse lung for two different fields of view, covering the whole organ, and a zoom to the local finer structure of terminal airways and alveoli. With a resolution of a few micrometers and the wide availability of the technique, studies of larger biological samples at the cellular level become possible.

Securing quality of camera-based biomedical optics

NASA Astrophysics Data System (ADS)

Guse, Frank; Kasper, Axel; Zinter, Bob

2009-02-01

As sophisticated optical imaging technologies move into clinical applications, manufacturers need to guarantee their products meet required performance criteria over long lifetimes and in very different environmental conditions. A consistent quality management marks critical components features derived from end-users requirements in a top-down approach. Careful risk analysis in the design phase defines the sample sizes for production tests, whereas first article inspection assures the reliability of the production processes. We demonstrate the application of these basic quality principles to camera-based biomedical optics for a variety of examples including molecular diagnostics, dental imaging, ophthalmology and digital radiography, covering a wide range of CCD/CMOS chip sizes and resolutions. Novel concepts in fluorescence detection and structured illumination are also highlighted.

A system for tracking and recognizing pedestrian faces using a network of loosely coupled cameras

NASA Astrophysics Data System (ADS)

Gagnon, L.; Laliberté, F.; Foucher, S.; Branzan Albu, A.; Laurendeau, D.

2006-05-01

A face recognition module has been developed for an intelligent multi-camera video surveillance system. The module can recognize a pedestrian face in terms of six basic emotions and the neutral state. Face and facial features detection (eyes, nasal root, nose and mouth) are first performed using cascades of boosted classifiers. These features are used to normalize the pose and dimension of the face image. Gabor filters are then sampled on a regular grid covering the face image to build a facial feature vector that feeds a nearest neighbor classifier with a cosine distance similarity measure for facial expression interpretation and face model construction. A graphical user interface allows the user to adjust the module parameters.

The fragmented nature of tundra landscape

NASA Astrophysics Data System (ADS)

Virtanen, Tarmo; Ek, Malin

2014-04-01

The vegetation and land cover structure of tundra areas is fragmented when compared to other biomes. Thus, satellite images of high resolution are required for producing land cover classifications, in order to reveal the actual distribution of land cover types across these large and remote areas. We produced and compared different land cover classifications using three satellite images (QuickBird, Aster and Landsat TM5) with different pixel sizes (2.4 m, 15 m and 30 m pixel size, respectively). The study area, in north-eastern European Russia, was visited in July 2007 to obtain ground reference data. The QuickBird image was classified using supervised segmentation techniques, while the Aster and Landsat TM5 images were classified using a pixel-based supervised classification method. The QuickBird classification showed the highest accuracy when tested against field data, while the Aster image was generally more problematic to classify than the Landsat TM5 image. Use of smaller pixel sized images distinguished much greater levels of landscape fragmentation. The overall mean patch sizes in the QuickBird, Aster, and Landsat TM5-classifications were 871 m2, 2141 m2 and 7433 m2, respectively. In the QuickBird classification, the mean patch size of all the tundra and peatland vegetation classes was smaller than one pixel of the Landsat TM5 image. Water bodies and fens in particular occur in the landscape in small or elongated patches, and thus cannot be realistically classified from larger pixel sized images. Land cover patterns vary considerably at such a fine-scale, so that a lot of information is lost if only medium resolution satellite images are used. It is crucial to know the amount and spatial distribution of different vegetation types in arctic landscapes, as carbon dynamics and other climate related physical, geological and biological processes are known to vary greatly between vegetation types.

Analysis of urban area land cover using SEASAT Synthetic Aperture Radar data

NASA Technical Reports Server (NTRS)

Henderson, F. M. (Principal Investigator)

1980-01-01

Digitally processed SEASAT synthetic aperture raar (SAR) imagery of the Denver, Colorado urban area was examined to explore the potential of SAR data for mapping urban land cover and the compatability of SAR derived land cover classes with the United States Geological Survey classification system. The imagery is examined at three different scales to determine the effect of image enlargement on accuracy and level of detail extractable. At each scale the value of employing a simplistic preprocessing smoothing algorithm to improve image interpretation is addressed. A visual interpretation approach and an automated machine/visual approach are employed to evaluate the feasibility of producing a semiautomated land cover classification from SAR data. Confusion matrices of omission and commission errors are employed to define classification accuracies for each interpretation approach and image scale.

Simulation of the hybrid Tunka Advanced International Gamma-ray and Cosmic ray Astrophysics (TAIGA)

NASA Astrophysics Data System (ADS)

Kunnas, M.; Astapov, I.; Barbashina, N.; Beregnev, S.; Bogdanov, A.; Bogorodskii, D.; Boreyko, V.; Brückner, M.; Budnev, N.; Chiavassa, A.; Chvalaev, O.; Dyachok, A.; Epimakhov, S.; Eremin, T.; Gafarov, A.; Gorbunov, N.; Grebenyuk, V.; Gress, O.; Gress, T.; Grinyuk, A.; Grishin, O.; Horns, D.; Ivanova, A.; Karpov, N.; Kalmykov, N.; Kazarina, Y.; Kindin, V.; Kirichkov, N.; Kiryuhin, S.; Kokoulin, R.; Kompaniets, K.; Konstantinov, E.; Korobchenko, A.; Korosteleva, E.; Kozhin, V.; Kuzmichev, L.; Lenok, V.; Lubsandorzhiev, B.; Lubsandorzhiev, N.; Mirgazov, R.; Mirzoyan, R.; Monkhoev, R.; Nachtigall, R.; Pakhorukov, A.; Panasyuk, M.; Pankov, L.; Perevalov, A.; Petrukhin, A.; Platonov, V.; Poleschuk, V.; Popescu, M.; Popova, E.; Porelli, A.; Porokhovoy, S.; Prosin, V.; Ptuskin, V.; Romanov, V.; Rubtsov, G. I.; Müger; Rybov, E.; Samoliga, V.; Satunin, P.; Saunkin, A.; Savinov, V.; Semeney, Yu; Shaibonov (junior, B.; Silaev, A.; Silaev (junior, A.; Skurikhin, A.; Slunecka, M.; Spiering, C.; Sveshnikova, L.; Tabolenko, V.; Tkachenko, A.; Tkachev, L.; Tluczykont, M.; Veslopopov, A.; Veslopopova, E.; Voronov, D.; Wischnewski, R.; Yashin, I.; Yurin, K.; Zagorodnikov, A.; Zirakashvili, V.; Zurbanov, V.

2015-08-01

Up to several 10s of TeV, Imaging Air Cherenkov Telescopes (IACTs) have proven to be the instruments of choice for GeV/TeV gamma-ray astronomy due to their good reconstrucion quality and gamma-hadron separation power. However, sensitive observations at and above 100 TeV require very large effective areas (10 km2 and more), which is difficult and expensive to achieve. The alternative to IACTs are shower front sampling arrays (non-imaging technique or timing-arrays) with a large area and a wide field of view. Such experiments provide good core position, energy and angular resolution, but only poor gamma-hadron separation. Combining both experimental approaches, using the strengths of both techniques, could optimize the sensitivity to the highest energies. The TAIGA project plans to combine the non-imaging HiSCORE [8] array with small (∼10m2) imaging telescopes. This paper covers simulation results of this hybrid approach.

The BioImage Database Project: organizing multidimensional biological images in an object-relational database.

PubMed

Carazo, J M; Stelzer, E H

1999-01-01

The BioImage Database Project collects and structures multidimensional data sets recorded by various microscopic techniques relevant to modern life sciences. It provides, as precisely as possible, the circumstances in which the sample was prepared and the data were recorded. It grants access to the actual data and maintains links between related data sets. In order to promote the interdisciplinary approach of modern science, it offers a large set of key words, which covers essentially all aspects of microscopy. Nonspecialists can, therefore, access and retrieve significant information recorded and submitted by specialists in other areas. A key issue of the undertaking is to exploit the available technology and to provide a well-defined yet flexible structure for dealing with data. Its pivotal element is, therefore, a modern object relational database that structures the metadata and ameliorates the provision of a complete service. The BioImage database can be accessed through the Internet. Copyright 1999 Academic Press.

Application of Hyperspectral Imaging to Detect Sclerotinia sclerotiorum on Oilseed Rape Stems

PubMed Central

Kong, Wenwen; Zhang, Chu; Huang, Weihao

2018-01-01

Hyperspectral imaging covering the spectral range of 384–1034 nm combined with chemometric methods was used to detect Sclerotinia sclerotiorum (SS) on oilseed rape stems by two sample sets (60 healthy and 60 infected stems for each set). Second derivative spectra and PCA loadings were used to select the optimal wavelengths. Discriminant models were built and compared to detect SS on oilseed rape stems, including partial least squares-discriminant analysis, radial basis function neural network, support vector machine and extreme learning machine. The discriminant models using full spectra and optimal wavelengths showed good performance with classification accuracies of over 80% for the calibration and prediction set. Comparing all developed models, the optimal classification accuracies of the calibration and prediction set were over 90%. The similarity of selected optimal wavelengths also indicated the feasibility of using hyperspectral imaging to detect SS on oilseed rape stems. The results indicated that hyperspectral imaging could be used as a fast, non-destructive and reliable technique to detect plant diseases on stems. PMID:29300315

Steganography and Steganalysis in Digital Images

DTIC Science & Technology

2012-01-01

Nonetheless, to hide a message in a BMP using this algorithm it would require a large image used as a cover. STEGANOGRAPHY TOOLS There were eight tools in...REPORT Steganography and Steganalysis in Digital Images 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: Steganography (from the Greek for "covered writing...12211 Research Triangle Park, NC 27709-2211 15. SUBJECT TERMS Least Significant Bit ( LSB ), steganography , steganalysis, stegogramme. Dr. Jeff Duffany

Megahertz ultra-wide-field swept-source retina optical coherence tomography compared to current existing imaging devices.

PubMed

Reznicek, Lukas; Klein, Thomas; Wieser, Wolfgang; Kernt, Marcus; Wolf, Armin; Haritoglou, Christos; Kampik, Anselm; Huber, Robert; Neubauer, Aljoscha S

2014-06-01

To investigate the image quality of wide-angle cross-sectional and reconstructed fundus images based on ultra-megahertz swept-source Fourier domain mode locking (FDML) OCT compared to current generation diagnostic devices. A 1,050 nm swept-source FDML OCT system was constructed running at 1.68 MHz A-scan rate covering approximately 70° field of view. Twelve normal eyes were imaged with the device applying an isotropically dense sampling protocol (1,900 × 1,900 A-scans) with a fill factor of 100 %. Obtained OCT scan image quality was compared with two commercial OCT systems (Heidelberg Spectralis and Stratus OCT) of the same 12 eyes. Reconstructed en-face fundus images from the same FDML-OCT data set were compared to color fundus, infrared and ultra-wide-field scanning laser images (SLO). Comparison of cross-sectional scans showed a high overall image quality of the 15× averaged FDML images at 1.68 MHz [overall quality grading score: 8.42 ± 0.52, range 0 (bad)-10 (excellent)] comparable to current spectral-domain OCTs (overall quality grading score: 8.83 ± 0.39, p = 0.731). On FDML OCT, a dense 3D data set was obtained covering also the central and mid-peripheral retina. The reconstructed FDML OCT en-face fundus images had high image quality comparable to scanning laser ophthalmoscope (SLO) as judged from retinal structures such as vessels and optic disc. Overall grading score was 8.36 ± 0.51 for FDML OCT vs 8.27 ± 0.65 for SLO (p = 0.717). Ultra-wide-field megahertz 3D FDML OCT at 1.68 MHz is feasible, and provides cross-sectional image quality comparable to current spectral-domain OCT devices. In addition, reconstructed en-face visualization of fundus images result in a wide-field view with high image quality as compared to currently available fundus imaging devices. The improvement of >30× in imaging speed over commercial spectral-domain OCT technology enables high-density scan protocols leading to a data set for high quality cross-sectional and en-face images of the posterior segment.

A rapid-screening approach to detect and quantify microplastics based on fluorescent tagging with Nile Red

NASA Astrophysics Data System (ADS)

Maes, Thomas; Jessop, Rebecca; Wellner, Nikolaus; Haupt, Karsten; Mayes, Andrew G.

2017-03-01

A new approach is presented for analysis of microplastics in environmental samples, based on selective fluorescent staining using Nile Red (NR), followed by density-based extraction and filtration. The dye adsorbs onto plastic surfaces and renders them fluorescent when irradiated with blue light. Fluorescence emission is detected using simple photography through an orange filter. Image-analysis allows fluorescent particles to be identified and counted. Magnified images can be recorded and tiled to cover the whole filter area, allowing particles down to a few micrometres to be detected. The solvatochromic nature of Nile Red also offers the possibility of plastic categorisation based on surface polarity characteristics of identified particles. This article details the development of this staining method and its initial cross-validation by comparison with infrared (IR) microscopy. Microplastics of different sizes could be detected and counted in marine sediment samples. The fluorescence staining identified the same particles as those found by scanning a filter area with IR-microscopy.

Application LANDSAT imagery to geologic mapping in the ice-free valleys of Antarctica

NASA Technical Reports Server (NTRS)

Houston, R. S. (Principal Investigator); Marrs, R. W.; Smithson, S. B.

1976-01-01

The author has identified the following significant results. Studies in the Ice-Free Valleys are resulted in the compilation of a sizeable library of maps and publications. Rock reflectance measurements were taken during the Antarctic summer of 1973. Spectral reflectance of rocks (mostly mafic lava flows) in the McMurdo and Ice-Free Valleys areas were measured using a filter wheel photometer equipped to measure reflectances in the four Landsat bands. A series of samples were collected at regular intervals across a large differentiated, mafic sill near Lake Vida. Chemical analyses of the sample suggest that the tonal variations in this sill are controlled by changes in the iron content of the rock. False color images were prepared for a number of areas by the diazo method and with an optical multispectral biviewer. These images were useful in defining boundaries of sea ice, snow cover, and in the study of ablating glaciers, but were not very useful for rock discrimination.

A rapid-screening approach to detect and quantify microplastics based on fluorescent tagging with Nile Red

PubMed Central

Maes, Thomas; Jessop, Rebecca; Wellner, Nikolaus; Haupt, Karsten; Mayes, Andrew G.

2017-01-01

A new approach is presented for analysis of microplastics in environmental samples, based on selective fluorescent staining using Nile Red (NR), followed by density-based extraction and filtration. The dye adsorbs onto plastic surfaces and renders them fluorescent when irradiated with blue light. Fluorescence emission is detected using simple photography through an orange filter. Image-analysis allows fluorescent particles to be identified and counted. Magnified images can be recorded and tiled to cover the whole filter area, allowing particles down to a few micrometres to be detected. The solvatochromic nature of Nile Red also offers the possibility of plastic categorisation based on surface polarity characteristics of identified particles. This article details the development of this staining method and its initial cross-validation by comparison with infrared (IR) microscopy. Microplastics of different sizes could be detected and counted in marine sediment samples. The fluorescence staining identified the same particles as those found by scanning a filter area with IR-microscopy. PMID:28300146

Three-dimensional scanning force/tunneling spectroscopy at room temperature.

PubMed

Sugimoto, Yoshiaki; Ueda, Keiichi; Abe, Masayuki; Morita, Seizo

2012-02-29

We simultaneously measured the force and tunneling current in three-dimensional (3D) space on the Si(111)-(7 × 7) surface using scanning force/tunneling microscopy at room temperature. The observables, the frequency shift and the time-averaged tunneling current were converted to the physical quantities of interest, i.e. the interaction force and the instantaneous tunneling current. Using the same tip, the local density of states (LDOS) was mapped on the same surface area at constant height by measuring the time-averaged tunneling current as a function of the bias voltage at every lateral position. LDOS images at negative sample voltages indicate that the tip apex is covered with Si atoms, which is consistent with the Si-Si covalent bonding mechanism for AFM imaging. A measurement technique for 3D force/current mapping and LDOS imaging on the equivalent surface area using the same tip was thus demonstrated.

Characterization of non-conductive materials using field emission scanning electron microscopy

NASA Astrophysics Data System (ADS)

Cao, Cong; Gao, Ran; Shang, Huayan; Peng, Tingting

2016-01-01

With the development of science and technology, field emission scanning electron microscope (FESEM) plays an important role in nano-material measurements because of its advantages of high magnification, high resolution and easy operation. A high-quality secondary electron image is a significant prerequisite for accurate and precise length measurements. In order to obtain high-quality secondary electron images, the conventional treatment method for non-conductive materials is coating conductive films with gold, carbon or platinum to reduce charging effects, but this method will cover real micro structures of materials, change the sample composition properties and meanwhile introduce a relatively big error to nano-scale microstructure measurements. This paper discusses how to reduce or eliminate the impact of charging effects on image quality to the greatest extent by changing working conditions, such as voltage, stage bias, scanning mode and so on without treatment of coating, to obtain real and high-quality microstructure information of materials.

Single lens system for forward-viewing navigation and scanning side-viewing optical coherence tomography

NASA Astrophysics Data System (ADS)

Tate, Tyler H.; McGregor, Davis; Barton, Jennifer K.

2017-02-01

The optical design for a dual modality endoscope based on piezo scanning fiber technology is presented including a novel technique to combine forward-viewing navigation and side viewing OCT. Potential applications include navigating body lumens such as the fallopian tube, biliary ducts and cardiovascular system. A custom cover plate provides a rotationally symmetric double reflection of the OCT beam to deviate and focus the OCT beam out the side of the endoscope for cross-sectional imaging of the tubal lumen. Considerations in the choice of the scanning fiber are explored and a new technique to increase the divergence angle of the scanning fiber to improve system performance is presented. Resolution and the necessary scanning density requirements to achieve Nyquist sampling of the full image are considered. The novel optical design lays the groundwork for a new approach integrating side-viewing OCT into multimodality endoscopes for small lumen imaging. KEYWORDS:

An all-optronic synthetic aperture lidar

NASA Astrophysics Data System (ADS)

Turbide, Simon; Marchese, Linda; Terroux, Marc; Babin, François; Bergeron, Alain

2012-09-01

Synthetic Aperture Radar (SAR) is a mature technology that overcomes the diffraction limit of an imaging system's real aperture by taking advantage of the platform motion to coherently sample multiple sections of an aperture much larger than the physical one. Synthetic Aperture Lidar (SAL) is the extension of SAR to much shorter wavelengths (1.5 μm vs 5 cm). This new technology can offer higher resolution images in day or night time as well as in certain adverse conditions. It could be a powerful tool for Earth monitoring (ship detection, frontier surveillance, ocean monitoring) from aircraft, unattended aerial vehicle (UAV) or spatial platforms. A continuous flow of high-resolution images covering large areas would however produce a large amount of data involving a high cost in term of post-processing computational time. This paper presents a laboratory demonstration of a SAL system complete with image reconstruction based on optronic processing. This differs from the more traditional digital approach by its real-time processing capability. The SAL system is discussed and images obtained from a non-metallic diffuse target at ranges up to 3m are shown, these images being processed by a real-time optronic SAR processor origiinally designed to reconstruct SAR images from ENVISAT/ASAR data.

DEEP U BAND AND R IMAGING OF GOODS-SOUTH: OBSERVATIONS, DATA REDUCTION AND FIRST RESULTS ,

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

Nonino, M.; Cristiani, S.; Vanzella, E.

2009-08-01

We present deep imaging in the U band covering an area of 630 arcmin{sup 2} centered on the southern field of the Great Observatories Origins Deep Survey (GOODS). The data were obtained with the VIMOS instrument at the European Southern Observatory (ESO) Very Large Telescope. The final images reach a magnitude limit U {sub lim} {approx} 29.8 (AB, 1{sigma}, in a 1'' radius aperture), and have good image quality, with full width at half-maximum {approx}0.''8. They are significantly deeper than previous U-band images available for the GOODS fields, and better match the sensitivity of other multiwavelength GOODS photometry. The deepermore » U-band data yield significantly improved photometric redshifts, especially in key redshift ranges such as 2 < z < 4, and deeper color-selected galaxy samples, e.g., Lyman break galaxies at z {approx} 3. We also present the co-addition of archival ESO VIMOS R-band data, with R {sub lim} {approx} 29 (AB, 1{sigma}, 1'' radius aperture), and image quality {approx}0.''75. We discuss the strategies for the observations and data reduction, and present the first results from the analysis of the co-added images.« less

Forest Cover Mapping in Iskandar Malaysia Using Satellite Data

NASA Astrophysics Data System (ADS)

Kanniah, K. D.; Mohd Najib, N. E.; Vu, T. T.

2016-09-01

Malaysia is the third largest country in the world that had lost forest cover. Therefore, timely information on forest cover is required to help the government to ensure that the remaining forest resources are managed in a sustainable manner. This study aims to map and detect changes of forest cover (deforestation and disturbance) in Iskandar Malaysia region in the south of Peninsular Malaysia between years 1990 and 2010 using Landsat satellite images. The Carnegie Landsat Analysis System-Lite (CLASlite) programme was used to classify forest cover using Landsat images. This software is able to mask out clouds, cloud shadows, terrain shadows, and water bodies and atmospherically correct the images using 6S radiative transfer model. An Automated Monte Carlo Unmixing technique embedded in CLASlite was used to unmix each Landsat pixel into fractions of photosynthetic vegetation (PV), non photosynthetic vegetation (NPV) and soil surface (S). Forest and non-forest areas were produced from the fractional cover images using appropriate threshold values of PV, NPV and S. CLASlite software was found to be able to classify forest cover in Iskandar Malaysia with only a difference between 14% (1990) and 5% (2010) compared to the forest land use map produced by the Department of Agriculture, Malaysia. Nevertheless, the CLASlite automated software used in this study was found not to exclude other vegetation types especially rubber and oil palm that has similar reflectance to forest. Currently rubber and oil palm were discriminated from forest manually using land use maps. Therefore, CLASlite algorithm needs further adjustment to exclude these vegetation and classify only forest cover.

Influence of meniscus on cartilage and subchondral bone features of knees from older individuals: A cadaver study

PubMed Central

Touraine, Sébastien; Bouhadoun, Hamid; Engelke, Klaus; Laredo, Jean Denis; Chappard, Christine

2017-01-01

Objective Cartilage and subchondral bone form a functional unit. Here, we aimed to examine the effect of meniscus coverage on the characteristics of this unit in knees of older individuals. Methods We assessed the hyaline cartilage, subchondral cortical plate (SCP), and subchondral trabecular bone in areas covered or uncovered by the meniscus from normal cadaver knees (without degeneration). Bone cores harvested from the medial tibial plateau at locations uncovered (central), partially covered (posterior), and completely covered (peripheral) by the meniscus were imaged by micro-CT. The following were measured on images: cartilage volume (Cart.Vol, mm3) and thickness (Cart.Th, mm); SCP thickness (SCP.Th, μm) and porosity (SCP.Por, %); bone volume to total volume fraction (BV/TV, %); trabecular thickness (Tb.Th, μm), spacing (Tb.Sp, μm), and number (Tb.N, 1/mm); structure model index (SMI); trabecular pattern factor (Tb.Pf); and degree of anisotropy (DA). Results Among the 28 specimens studied (18 females) from individuals with mean age 82.8±10.2 years, cartilage and SCP were thicker at the central site uncovered by the meniscus than the posterior and peripheral sites, and Cart.Vol was greater. SCP.Por was highest in posterior samples. In the upper 1–5 mm of subchondral bone, central samples were characterized by higher values for BV/TV, Tb.N, Tb.Th, and connectivity (Tb.Pf), a more plate-like trabecular structure and lower anisotropy than with other samples. Deeper down, at 6–10 mm, the differences were slightly higher for Tb.Th centrally, DA peripherally and SMI posteriorly. Conclusions The coverage or not by meniscus in the knee of older individuals is significantly associated with Cart.Th, SCP.Th, SCP.Por and trabecular microarchitectural parameters in the most superficial 5 mm and to a lesser extent the deepest area of subchondral trabecular bone. These results suggest an effect of differences in local loading conditions. In subchondral bone uncovered by the meniscus, the trabecular architecture resembles that of highly loaded areas. PMID:28797093

NALC/MEXICO LAND-COVER MAPPING RESULTS: IMPLICATIONS FOR ASSESSING LANDSCAPE CONDITION

EPA Science Inventory

An inventory of land-cover conditions throughout Mexico was performed using North American Landscap Characterization ( NALC) Landsat Multi-Spectral Scanner (MSS) 'triplicate' images, corresponding to the 1970s, 1980s and1990s epoch periods. The equivalent of 300 image scenes were...

IMPACTS OF PATCH SIZE AND LAND COVER HETEROGENEITY ON THEMATIC IMAGE CLASSIFICATION ACCURACY

EPA Science Inventory

Landscape characteristics such as small patch size and land cover heterogeneity have been hypothesized to increase the likelihood of miss-classifying pixels during thematic image classification. However, there has been a lack of empirical evidence to support these hypotheses,...

NALC/MEXICO LAND-COVER MAPPING RESULTS: IMPLICATIONS FOR ASSESSING LANDSCAPE CHANGE

EPA Science Inventory

An inventory of land-cover conditions throughout Mexico was performed using North American Landscape Characterization (NALC) Landsat Multi-Spectral Scanner (MSS) 'triplicate' images, corresponding to the 1970s, 1980s, and 1990s epoch periods. The equivalent of 300 image scenes we...

NALC/MEXICO LAND-COVER MAPPING RESULTS: IMPLICATIONS FOR ASSESSING LANDSCAPE CONDITION

EPA Science Inventory

An inventory of land-cover conditions throughout Mexico was performed using North American Landscape Characterization (NLAC) Landsat Mult-Spectral Scann (MSS) 'triplicate' images, corresponding to the 1970s, 1980s and 1990s epoch periods. The equivalents of 300 image scenes were...

Snow extent measurements from geostationary satellites using an interactive computer system. [Salt and Verde River Basins, Arizona

NASA Technical Reports Server (NTRS)

Gird, R. S. (Principal Investigator)

1980-01-01

The author has identified the following significant results. A time series of GOES full resolution visible image sectors was viewed on the McIDAS video component in chronological order and registered to within plus or minus 1 image pixel to compute real time snow melting rates. Synoptic scale clouds were eliminated to create a snow covered area from a composite image. Results show good agreement with NESS products although a significant difference was noted for one two-day period when the NESS products showed an increase in the snow cover for the Verde Basin, while the GOES/McIDAS product implied no change in the snow cover for approximately the same period. A check of NWS radar reports indicated no precipitation had occurred within the Verde basin. The use of the registered image sequence eliminates instrument error since small changes in the snow cover between any two days are easily detected.

Extracting Features of Acacia Plantation and Natural Forest in the Mountainous Region of Sarawak, Malaysia by ALOS/AVNIR2 Image

NASA Astrophysics Data System (ADS)

Fadaei, H.; Ishii, R.; Suzuki, R.; Kendawang, J.

2013-12-01

The remote sensing technique has provided useful information to detect spatio-temporal changes in the land cover of tropical forests. Land cover characteristics derived from satellite image can be applied to the estimation of ecosystem services and biodiversity over an extensive area, and such land cover information would provide valuable information to global and local people to understand the significance of the tropical ecosystem. This study was conducted in the Acacia plantations and natural forest situated in the mountainous region which has different ecological characteristic from that in flat and low land area in Sarawak, Malaysia. The main objective of this study is to compare extract the characteristic of them by analyzing the ALOS/AVNIR2 images and ground truthing obtained by the forest survey. We implemented a ground-based forest survey at Aacia plantations and natural forest in the mountainous region in Sarawak, Malaysia in June, 2013 and acquired the forest structure data (tree height, diameter at breast height (DBH), crown diameter, tree spacing) and spectral reflectance data at the three sample plots of Acacia plantation that has 10 x 10m area. As for the spectral reflectance data, we measured the spectral reflectance of the end members of forest such as leaves, stems, road surface, and forest floor by the spectro-radiometer. Such forest structure and spectral data were incorporated into the image analysis by support vector machine (SVM) and object-base/texture analysis. Consequently, land covers on the AVNIR2 image were classified into three forest types (natural forest, oil palm plantation and acacia mangium plantation), then the characteristic of each category was examined. We additionally used the tree age data of acacia plantation for the classification. A unique feature was found in vegetation spectral reflectance of Acacia plantations. The curve of the spectral reflectance shows two peaks around 0.3μm and 0.6 - 0.8μm that can be assumed to be corresponded to the reflectance from the bare land part (soil) and forest crown in the Acacia forest, respectively. In accordance with this spectral characteristic, we can estimate the proportional areas of the bare land and crown cover of the tree in the acacia plantation forest that will provide essential information for evaluating the forest ecosystem. We will define Bare land and Tree Crown Ratio Index (BTRI) that represent ratio of the areas of tree crown to areas of their access roads. Such information will delineate the characteristics of Acacia plantation and natural forest in mountainous region, and enable us to compare them with the plantation and forest in flat and low land.

Measurement of breast-tissue x-ray attenuation by spectral mammography: solid lesions

NASA Astrophysics Data System (ADS)

Fredenberg, Erik; Kilburn-Toppin, Fleur; Willsher, Paula; Moa, Elin; Danielsson, Mats; Dance, David R.; Young, Kenneth C.; Wallis, Matthew G.

2016-04-01

Knowledge of x-ray attenuation is essential for developing and evaluating x-ray imaging technologies. For instance, techniques to distinguish between cysts and solid tumours at mammography screening would be highly desirable to reduce recalls, but the development requires knowledge of the x-ray attenuation for cysts and tumours. We have previously measured the attenuation of cyst fluid using photon-counting spectral mammography. Data on x-ray attenuation for solid breast lesions are available in the literature, but cover a relatively wide range, likely caused by natural spread between samples, random measurement errors, and different experimental conditions. In this study, we have adapted a previously developed spectral method to measure the linear attenuation of solid breast lesions. A total of 56 malignant and 5 benign lesions were included in the study. The samples were placed in a holder that allowed for thickness measurement. Spectral (energy-resolved) images of the samples were acquired and the image signal was mapped to equivalent thicknesses of two known reference materials, which can be used to derive the x-ray attenuation as a function of energy. The spread in equivalent material thicknesses was relatively large between samples, which is likely to be caused mainly by natural variation and only to a minor extent by random measurement errors and sample inhomogeneity. No significant difference in attenuation was found between benign and malignant solid lesions. The separation between cyst-fluid and tumour attenuation was, however, significant, which suggests it may be possible to distinguish cystic from solid breast lesions, and the results lay the groundwork for a clinical trial. In addition, the study adds a relatively large sample set to the published data and may contribute to a reduction in the overall uncertainty in the literature.

Photoacoustic tomography using a fiber based Fabry-Perot interferometer as an integrating line detector and image reconstruction by model-based time reversal method

NASA Astrophysics Data System (ADS)

Grün, H.; Paltauf, G.; Haltmeier, M.; Burgholzer, P.

2007-07-01

Photoacoustic imaging is based on the generation of acoustic waves in a semitransparent sample (e.g. soft tissue) after illumination with short pulses of light or radio waves. The goal is to recover the spatial distribution of absorbed energy density inside the sample from acoustic pressure signals measured outside the sample (photoacoustic inverse problem). If the acoustic pressure outside the illuminated sample is measured with a large-aperture detector, the signal at a certain time is given by an integral of the generated acoustic pressure distribution over an area that is determined by the shape of the detector. For example a planar detector measures the projections of the initial pressure distribution over planes parallel to the detector plane, which is the Radon transform of the initial pressure distribution. Stable and exact three-dimensional imaging with planar integrating detector requires measurements in all directions of space and so the receiver plane has to be rotated to cover the entire detection surface. We have recently presented a simpler set-up for exact imaging which requires only a single rotation axis and therefor the fragmentation of the area detector into line detectors perpendicular to the rotation axis. Using a two-dimensional reconstruction method and applying the inverse two-dimensional Radon transform afterwards gives an exact reconstruction of the three-dimensional sample with this set-up. In order to achieve high resolution, a fiber based Fabry-Perot interferometer is used. It is a single mode fiber with two fiber bragg gratings on both ends of the line detector. Thermal shifts and vibrations are compensated by frequency locking of the laser. The high resolution and the good performance of this integrating line detector has been demonstrated by photoacoustic measurements with line grid samples and phantoms using a model-based time reversal method for image reconstruction. The time reversed pressure field can be calculated directly by retransmitting the measured pressure on the detector positions in a reversed temporal order.

Nanoscale NMR spectroscopy and imaging of multiple nuclear species.

PubMed

DeVience, Stephen J; Pham, Linh M; Lovchinsky, Igor; Sushkov, Alexander O; Bar-Gill, Nir; Belthangady, Chinmay; Casola, Francesco; Corbett, Madeleine; Zhang, Huiliang; Lukin, Mikhail; Park, Hongkun; Yacoby, Amir; Walsworth, Ronald L

2015-02-01

Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance imaging (MRI) provide non-invasive information about multiple nuclear species in bulk matter, with wide-ranging applications from basic physics and chemistry to biomedical imaging. However, the spatial resolution of conventional NMR and MRI is limited to several micrometres even at large magnetic fields (>1 T), which is inadequate for many frontier scientific applications such as single-molecule NMR spectroscopy and in vivo MRI of individual biological cells. A promising approach for nanoscale NMR and MRI exploits optical measurements of nitrogen-vacancy (NV) colour centres in diamond, which provide a combination of magnetic field sensitivity and nanoscale spatial resolution unmatched by any existing technology, while operating under ambient conditions in a robust, solid-state system. Recently, single, shallow NV centres were used to demonstrate NMR of nanoscale ensembles of proton spins, consisting of a statistical polarization equivalent to ∼100-1,000 spins in uniform samples covering the surface of a bulk diamond chip. Here, we realize nanoscale NMR spectroscopy and MRI of multiple nuclear species ((1)H, (19)F, (31)P) in non-uniform (spatially structured) samples under ambient conditions and at moderate magnetic fields (∼20 mT) using two complementary sensor modalities.

"Tools For Analysis and Visualization of Large Time- Varying CFD Data Sets"

NASA Technical Reports Server (NTRS)

Wilhelms, Jane; vanGelder, Allen

1999-01-01

During the four years of this grant (including the one year extension), we have explored many aspects of the visualization of large CFD (Computational Fluid Dynamics) datasets. These have included new direct volume rendering approaches, hierarchical methods, volume decimation, error metrics, parallelization, hardware texture mapping, and methods for analyzing and comparing images. First, we implemented an extremely general direct volume rendering approach that can be used to render rectilinear, curvilinear, or tetrahedral grids, including overlapping multiple zone grids, and time-varying grids. Next, we developed techniques for associating the sample data with a k-d tree, a simple hierarchial data model to approximate samples in the regions covered by each node of the tree, and an error metric for the accuracy of the model. We also explored a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH (Association for Computing Machinery Special Interest Group on Computer Graphics) '96. In our initial implementation, we automatically image the volume from 32 approximately evenly distributed positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation.

Forest cover type analysis of New England forests using innovative WorldView-2 imagery

NASA Astrophysics Data System (ADS)

Kovacs, Jenna M.

For many years, remote sensing has been used to generate land cover type maps to create a visual representation of what is occurring on the ground. One significant use of remote sensing is the identification of forest cover types. New England forests are notorious for their especially complex forest structure and as a result have been, and continue to be, a challenge when classifying forest cover types. To most accurately depict forest cover types occurring on the ground, it is essential to utilize image data that have a suitable combination of both spectral and spatial resolution. The WorldView-2 (WV2) commercial satellite, launched in 2009, is the first of its kind, having both high spectral and spatial resolutions. WV2 records eight bands of multispectral imagery, four more than the usual high spatial resolution sensors, and has a pixel size of 1.85 meters at the nadir. These additional bands have the potential to improve classification detail and classification accuracy of forest cover type maps. For this reason, WV2 imagery was utilized on its own, and in combination with Landsat 5 TM (LS5) multispectral imagery, to evaluate whether these image data could more accurately classify forest cover types. In keeping with recent developments in image analysis, an Object-Based Image Analysis (OBIA) approach was used to segment images of Pawtuckaway State Park and nearby private lands, an area representative of the typical complex forest structure found in the New England region. A Classification and Regression Tree (CART) analysis was then used to classify image segments at two levels of classification detail. Accuracies for each forest cover type map produced were generated using traditional and area-based error matrices, and additional standard accuracy measures (i.e., KAPPA) were generated. The results from this study show that there is value in analyzing imagery with both high spectral and spatial resolutions, and that WV2's new and innovative bands can be useful for the classification of complex forest structures.

Application of spectrometer cropscan MSR 16R and Landsat imagery for identification the spectral characteristics of land cover

NASA Astrophysics Data System (ADS)

Tampubolon, Togi; Abdullah, Khiruddin bin; San, Lim Hwee

2013-09-01

The spectral characteristics of land cover are basic references in classifying satellite image for geophysics analysis. It can be obtained from the measurements using spectrometer and satellite image processing. The aims of this study to investigate the spectral characteristics of land cover based on the results of measurement using Spectrometer Cropscan MSR 16R and Landsat satellite imagery. The area of study in this research is in Medan, (Deli Serdang, North Sumatera) Indonesia. The scope of this study is the basic survey from the measurements of spectral land cover which is covered several type of land such as a cultivated and managed terrestrial areas, natural and semi-natural, cultivated aquatic or regularly flooded areas, natural and semi-natural aquatic, artificial surfaces and associated areas, bare areas, artificial waterbodies and natural waterbodies. The measurement and verification were conducted using a spectrometer provided their spectral characteristics and Landsat imagery, respectively. The results of the spectral characteristics of land cover shows that each type of land cover have a unique characteristic. The correlation of spectral land cover based on spectrometer Cropscan MSR 16R and Landsat satellite image are above 90 %. However, the land cover of artificial waterbodiese have a correlation under 40 %. That is because the measurement of spectrometer Cropscan MSR 16R and acquisition of Landsat satellite imagery has a time different.

Snow cover retrieval over Rhone and Po river basins from MODIS optical satellite data (2000-2009).

NASA Astrophysics Data System (ADS)

Dedieu, Jean-Pierre, ,, Dr.; Boos, Alain; Kiage, Wiliam; Pellegrini, Matteo

2010-05-01

Estimation of the Snow Covered Area (SCA) is an important issue for meteorological application and hydrological modeling of runoff. With spectral bands in the visible, near and middle infrared, the MODIS optical satellite sensor can be used to detect snow cover because of large differences between reflectance from snow covered and snow free surfaces. At the same time, it allows separation between snow and clouds. Moreover, the sensor provides a daily coverage of large areas (2,500 km range). However, as the pixel size is 500m x 500m, a MODIS pixel may be partially covered by snow, particularly in Alpine areas, where snow may not be present in valleys lying at lower altitudes. Also, variation of reflectance due to differential sunlit effects as a function of slope and aspect, as well as bidirectional effects may be present in images. Nevertheless, it is possible to estimate snow cover at the Sub-Pixel level with a relatively good accuracy and with very good results if the sub-pixel estimations are integrated for a few pixels relative to an entire watershed. Integrated into the EU-FP7 ACQWA Project (www.acqwa.ch), this approach was first applied over Alpine area of Rhone river basin upper Geneva Lake: Canton du Valais, Switzerland (5 375 km²). In a second step over Alps, rolling hills and plain areas in Po catchment for Val d'Aosta and Piemonte regions, Italy (37 190 km²). Watershed boundaries were provided respectively by GRID (Ch) and ARPA (It) partners. The complete satellite images database was extracted from the U.S. MODIS/NASA website (http://modis.gsfc.nasa.gov/) for MOD09_B1 Reflectance images, and from the MODIS/NSIDC website (http://nsidc.org/index.html) for MOD10_A2 snow cover images. Only the Terra platform was used because images are acquired in the morning and are therefore better correlated with dry snow surface, avoiding cloud coverage of the afternoon (Aqua Platform). The MOD9 Image reflectance and MOD10_A2 products were respectively analyzed to retrieve (i) Fractional Snow cover at sub-pixel scale, and (ii) maximum snow cover. All products were retrieved at 8-days over a complete time period of 10 years (2000-2009), giving 500 images for each river basin. Digital Model Elevation was given by NASA/SRTM database at 90-m resolution and used (i) for illumination versus topography correction on snow cover, (ii) geometric rectification of images. Geographic projection is WGS84, UTM 32. Fractional Snow cover mapping was derived from the NDSI linear regression method (Salomonson et al., 2004). Cloud mask was given by MODIS-NASA library (radiometric threshold) and completed by inverse slope regression to avoid lowlands fog confusing with thin snow cover (Po river basin). Maximum Snow Cover mapping was retrieved from the NSIDC database classification (Hall et al., 2001). Validation step was processed using comparison between MODIS Snow maps outputs and meteorological data provided by network of 87 meteorological stations: temperature, precipitation, snow depth measurement. A 0.92 correlation was observed for snow/non snow cover and can be considered as quite satisfactory, given the radiometric problems encountered in mountainous areas, particularly in snowmelt season. The 10-years time period results indicates a main difference between (i) regular snow accumulation and depletion in Rhone and (ii) the high temporal and spatial variability of snow cover for Po. Then, a high sensitivity to low variation of air temperature, often close to 1° C was observed. This is the case in particular for the beginning and the end of the winter season. The regional snow cover depletion is both influenced by thermal positives anomalies (e.g. 2000 and 2006), and the general trend of rising atmospheric temperatures since the late 1980s, particularly for Po river basin. Results will be combined with two hydrological models: Topkapi and Fest.

Search for evidence of low energy protons in solar flares

NASA Technical Reports Server (NTRS)

Metcalf, Thomas R.; Wuelser, Jean-Pierre; Canfield, Richard C.; Hudson, Hugh S.

1992-01-01

We searched for linear polarization in the H alpha line using the Stokes Polarimeter at Mees Solar Observatory and present observations of a flare from NOAA active region 6659 which began at 01:30 UT on 14 Jun. 1991. Our dataset also includes H alpha spectra from the Mees charge coupled device (MCCD) imaging spectrograph as well as hard x ray observations from the Burst and Transient Source Experiment (BATSE) instrument on board the Gamma Ray Observatory (GRO). The polarimeter scanned a 40 x 40 inch field of view using 16 raster points in a 4 x 4 grid. Each scan took about 30 seconds with 2 seconds at each raster point. The polarimeter stopped 8.5 inches between raster points and each point covered a 6 inch region. This sparse sampling increased the total field of view without reducing the temporal cadence. At each raster point, an H alpha spectrum with 20 mA spectral sampling is obtained covering 2.6 A centered on H alpha line center. The preliminary conclusions from the research are presented.

Computer-aided boundary delineation of agricultural lands

NASA Technical Reports Server (NTRS)

Cheng, Thomas D.; Angelici, Gary L.; Slye, Robert E.; Ma, Matt

1989-01-01

The National Agricultural Statistics Service of the United States Department of Agriculture (USDA) presently uses labor-intensive aerial photographic interpretation techniques to divide large geographical areas into manageable-sized units for estimating domestic crop and livestock production. Prototype software, the computer-aided stratification (CAS) system, was developed to automate the procedure, and currently runs on a Sun-based image processing system. With a background display of LANDSAT Thematic Mapper and United States Geological Survey Digital Line Graph data, the operator uses a cursor to delineate agricultural areas, called sampling units, which are assigned to strata of land-use and land-cover types. The resultant stratified sampling units are used as input into subsequent USDA sampling procedures. As a test, three counties in Missouri were chosen for application of the CAS procedures. Subsequent analysis indicates that CAS was five times faster in creating sampling units than the manual techniques were.

OH/H2O Detection Capability Evaluation on Chang'e-5 Lunar Mineralogical Spectrometer (LMS)

NASA Astrophysics Data System (ADS)

Liu, Bin; Ren, Xin; Liu, Jianjun; Li, Chunlai; Mu, Lingli; Deng, Liyan

2016-10-01

The Chang'e-5 (CE-5) lunar sample return mission is scheduled to launch in 2017 to bring back lunar regolith and drill samples. The Chang'e-5 Lunar Mineralogical Spectrometer (LMS), as one of the three sets of scientific payload installed on the lander, is used to collect in-situ spectrum and analyze the mineralogical composition of the samplingsite. It can also help to select the sampling site, and to compare the measured laboratory spectrum of returned sample with in-situ data. LMS employs acousto-optic tunable filters (AOTFs) and is composed of a VIS/NIR module (0.48μm-1.45μm) and an IR module (1.4μm -3.2μm). It has spectral resolution ranging from 3 to 25 nm, with a field of view (FOV) of 4.24°×4.24°. Unlike Chang'e-3 VIS/NIR Imaging Spectrometer (VNIS), the spectral coverage of LMS is extended from 2.4μm to 3.2μm, which has capability to identify H2O/OH absorption features around 2.7μm. An aluminum plate and an Infragold plate are fixed in the dust cover, being used as calibration targets in the VIS/NIR and IR spectral range respectively when the dust cover is open. Before launch, a ground verification test of LMS needs to be conducted in order to: 1) test and verify the detection capability of LMS through evaluation on the quality of image and spectral data collected for the simulated lunar samples; and 2) evaluate the accuracy of data processing methods by the simulation of instrument working on the moon. The ground verification test will be conducted both in the lab and field. The spectra of simulated lunar regolith/mineral samples will be collected simultaneously by the LMS and two calibrated spectrometers: a FTIR spectrometer (Model 102F) and an ASD FieldSpec 4 Hi-Res spectrometer. In this study, the results of the LMS ground verification test will be reported, and OH/H2O Detection Capability will be evaluated especially.

Regional melt-pond fraction and albedo of thin Arctic first-year drift ice in late summer

NASA Astrophysics Data System (ADS)

Divine, D. V.; Granskog, M. A.; Hudson, S. R.; Pedersen, C. A.; Karlsen, T. I.; Divina, S. A.; Renner, A. H. H.; Gerland, S.

2015-02-01

The paper presents a case study of the regional (≈150 km) morphological and optical properties of a relatively thin, 70-90 cm modal thickness, first-year Arctic sea ice pack in an advanced stage of melt. The study combines in situ broadband albedo measurements representative of the four main surface types (bare ice, dark melt ponds, bright melt ponds and open water) and images acquired by a helicopter-borne camera system during ice-survey flights. The data were collected during the 8-day ICE12 drift experiment carried out by the Norwegian Polar Institute in the Arctic, north of Svalbard at 82.3° N, from 26 July to 3 August 2012. A set of > 10 000 classified images covering about 28 km2 revealed a homogeneous melt across the study area with melt-pond coverage of ≈ 0.29 and open-water fraction of ≈ 0.11. A decrease in pond fractions observed in the 30 km marginal ice zone (MIZ) occurred in parallel with an increase in open-water coverage. The moving block bootstrap technique applied to sequences of classified sea-ice images and albedo of the four surface types yielded a regional albedo estimate of 0.37 (0.35; 0.40) and regional sea-ice albedo of 0.44 (0.42; 0.46). Random sampling from the set of classified images allowed assessment of the aggregate scale of at least 0.7 km2 for the study area. For the current setup configuration it implies a minimum set of 300 images to process in order to gain adequate statistics on the state of the ice cover. Variance analysis also emphasized the importance of longer series of in situ albedo measurements conducted for each surface type when performing regional upscaling. The uncertainty in the mean estimates of surface type albedo from in situ measurements contributed up to 95% of the variance of the estimated regional albedo, with the remaining variance resulting from the spatial inhomogeneity of sea-ice cover.

Versatile variable temperature and magnetic field scanning probe microscope for advanced material research

NASA Astrophysics Data System (ADS)

Jung, Jin-Oh; Choi, Seokhwan; Lee, Yeonghoon; Kim, Jinwoo; Son, Donghyeon; Lee, Jhinhwan

2017-10-01

We have built a variable temperature scanning probe microscope (SPM) that covers 4.6 K-180 K and up to 7 T whose SPM head fits in a 52 mm bore magnet. It features a temperature-controlled sample stage thermally well isolated from the SPM body in good thermal contact with the liquid helium bath. It has a 7-sample-holder storage carousel at liquid helium temperature for systematic studies using multiple samples and field emission targets intended for spin-polarized spectroscopic-imaging scanning tunneling microscopy (STM) study on samples with various compositions and doping conditions. The system is equipped with a UHV sample preparation chamber and mounted on a two-stage vibration isolation system made of a heavy concrete block and a granite table on pneumatic vibration isolators. A quartz resonator (qPlus)-based non-contact atomic force microscope (AFM) sensor is used for simultaneous STM/AFM operation for research on samples with highly insulating properties such as strongly underdoped cuprates and strongly correlated electron systems.

Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks

PubMed Central

Xu, Xin; Gui, Rong; Pu, Fangling

2018-01-01

Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods. PMID:29510499

BOREAS Level-3a Landsat TM Imagery: Scaled At-sensor Radiance in BSQ Format

NASA Technical Reports Server (NTRS)

Nickerson, Jaime; Hall, Forrest G. (Editor); Knapp, David; Newcomer, Jeffrey A.; Cihlar, Josef

2000-01-01

For BOREAS, the level-3a Landsat TM data, along with the other remotely sensed images, were collected in order to provide spatially extensive information over the primary study areas. This information includes radiant energy, detailed land cover, and biophysical parameter maps such as FPAR and LAI. Although very similar in content to the level-3s Landsat TM products, the level-3a images were created to provide users with a more usable BSQ format and to provide information that permitted direct determination of per-pixel latitude and longitude coordinates. Geographically, the level-3a images cover the BOREAS NSA and SSA. Temporally, the images cover the period of 22-Jun-1984 to 30-Jul-1996. The images are available in binary, image-format files. With permission from CCRS and RSI, several of the full-resolution images are included on the BOREAS CD-ROM series. Due to copyright issues, the images not included on the CD-ROM may not be publicly available. See Sections 15 and 16 for information about how to acquire the data. Information about the images not on the CD-ROMs is provided in an inventory listing on the CD-ROMs.

Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks.

PubMed

Wang, Lei; Xu, Xin; Dong, Hao; Gui, Rong; Pu, Fangling

2018-03-03

Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods.

BOREAS Level-3p Landsat TM Imagery: Geocoded and Scaled At-sensor Radiance

NASA Technical Reports Server (NTRS)

Nickeson, Jaime; Knapp, David; Newcomer, Jeffrey A.; Hall, Forrest G. (Editor); Cihlar, Josef

2000-01-01

For BOReal Ecosystem-Atmosphere Study (BOREAS), the level-3p Landsat Thematic Mapper (TM) data were used to supplement the level-3s Landsat TM products. Along with the other remotely sensed images, the Landsat TM images were collected in order to provide spatially extensive information over the primary study areas. This information includes radiant energy, detailed land cover, and biophysical parameter maps such as Fraction of Photosynthetically Active Radiation (FPAR) and Leaf Area Index (LAI). Although very similar to the level-3s Landsat TM products, the level-3p images were processed with ground control information, which improved the accuracy of the geographic coordinates provided. Geographically, the level-3p images cover the BOREAS Northern Study Area (NSA) and Southern Study Area (SSA). Temporally, the four images cover the period of 20-Aug-1988 to 07-Jun-1994. Except for the 07-Jun-1994 image, which contains seven bands, the other three contain only three bands.

LAND COVER MAPPING IN AN AGRICULTURAL SETTING USING MULTISEASONAL THEMATIC MAPPER DATA

EPA Science Inventory

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...

Temporal optimisation of image acquisition for land cover classification with Random Forest and MODIS time-series

NASA Astrophysics Data System (ADS)

Nitze, Ingmar; Barrett, Brian; Cawkwell, Fiona

2015-02-01

The analysis and classification of land cover is one of the principal applications in terrestrial remote sensing. Due to the seasonal variability of different vegetation types and land surface characteristics, the ability to discriminate land cover types changes over time. Multi-temporal classification can help to improve the classification accuracies, but different constraints, such as financial restrictions or atmospheric conditions, may impede their application. The optimisation of image acquisition timing and frequencies can help to increase the effectiveness of the classification process. For this purpose, the Feature Importance (FI) measure of the state-of-the art machine learning method Random Forest was used to determine the optimal image acquisition periods for a general (Grassland, Forest, Water, Settlement, Peatland) and Grassland specific (Improved Grassland, Semi-Improved Grassland) land cover classification in central Ireland based on a 9-year time-series of MODIS Terra 16 day composite data (MOD13Q1). Feature Importances for each acquisition period of the Enhanced Vegetation Index (EVI) and Normalised Difference Vegetation Index (NDVI) were calculated for both classification scenarios. In the general land cover classification, the months December and January showed the highest, and July and August the lowest separability for both VIs over the entire nine-year period. This temporal separability was reflected in the classification accuracies, where the optimal choice of image dates outperformed the worst image date by 13% using NDVI and 5% using EVI on a mono-temporal analysis. With the addition of the next best image periods to the data input the classification accuracies converged quickly to their limit at around 8-10 images. The binary classification schemes, using two classes only, showed a stronger seasonal dependency with a higher intra-annual, but lower inter-annual variation. Nonetheless anomalous weather conditions, such as the cold winter of 2009/2010 can alter the temporal separability pattern significantly. Due to the extensive use of the NDVI for land cover discrimination, the findings of this study should be transferrable to data from other optical sensors with a higher spatial resolution. However, the high impact of outliers from the general climatic pattern highlights the limitation of spatial transferability to locations with different climatic and land cover conditions. The use of high-temporal, moderate resolution data such as MODIS in conjunction with machine-learning techniques proved to be a good base for the prediction of image acquisition timing for optimal land cover classification results.

Modulus design multiwavelength polarization microscope for transmission Mueller matrix imaging.

PubMed

Zhou, Jialing; He, Honghui; Chen, Zhenhua; Wang, Ye; Ma, Hui

2018-01-01

We have developed a polarization microscope based on a commercial transmission microscope. We replace the halogen light source by a collimated LED light source module of six different colors. We use achromatic polarized optical elements that can cover the six different wavelength ranges in the polarization state generator (PSG) and polarization state analyzer (PSA) modules. The dual-rotating wave plate method is used to measure the Mueller matrix of samples, which requires the simultaneous rotation of the two quarter-wave plates in both PSG and PSA at certain angular steps. A scientific CCD detector is used as the image receiving module. A LabView-based software is developed to control the rotation angels of the wave plates and the exposure time of the detector to allow the system to run fully automatically in preprogrammed schedules. Standard samples, such as air, polarizers, and quarter-wave plates, are used to calibrate the intrinsic Mueller matrix of optical components, such as the objectives, using the eigenvalue calibration method. Errors due to the images walk-off in the PSA are studied. Errors in the Mueller matrices are below 0.01 using air and polarizer as standard samples. Data analysis based on Mueller matrix transformation and Mueller matrix polarization decomposition is used to demonstrate the potential application of this microscope in pathological diagnosis. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Non-destructive evaluation of polymer coating structures on pharmaceutical pellets using full-field optical coherence tomography.

PubMed

Li, Chen; Zeitler, J Axel; Dong, Yue; Shen, Yao-Chun

2014-01-01

Full-field optical coherence tomography (FF-OCT) using a conventional light-emitting diode and a complementary metal-oxide semiconductor camera has been developed for characterising coatings on small pellet samples. A set of en-face images covering an area of 700 × 700 μm(2) was taken over a depth range of 166 μm. The three-dimensional structural information, such as the coating thickness and uniformity, was subsequently obtained by analysis of the recorded en-face images. Drug-loaded pharmaceutical sustained-release pellets with two coating layers and of a sub-millimetre diameter were studied to demonstrate the usefulness of the developed system. We have shown that both coatings can be clearly resolved and the thickness was determined to be 40 and 50 μm for the outer and inner coating layers, respectively. It was also found that the outer coating layer is relatively uniform, whereas the inner coating layer has many particle-like features. X-ray computed microtomography measurements carried out on the same pellet sample confirmed all these findings. The presented FF-OCT approach is inexpensive and has better spatial resolution compared with other non-destructive analysis techniques such as terahertz pulsed imaging, and is thus considered advantageous for the quantitative analysis of thin coatings on small pellet samples. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

Land cover mapping of North and Central America—Global Land Cover 2000

USGS Publications Warehouse

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

Determining land use changes by radar-optic fused images and monitoring its environmental impacts in Edremit region of western Turkey.

PubMed

Balik Sanli, Fusun; Kurucu, Yusuf; Esetlili, Mustafa Tolga

2009-04-01

Rapid and unplanned urbanization and industrialization are the main reasons of environmental problems. If urban growth is not based on resource sustainability criteria and urban plans are not applied, natural and human resources are damaged dramatically. In this study, land use change and urban expansion in Edremit region of Turkey is determined by means of remote sensing techniques between 1971 and 2002. To improve the accuracy of land use/cover maps, the contribution of SAR images to optic images in defining land cover types was investigated. To determine the situation of land use/cover types in 2002 accurately, Landsat-5 images and Radarsat-1 images were fused, and the land use/cover types were defined from the fused images. Comparisons with the ground truth reveal that land use maps generated using the fuse technique are improved about 6% with an accuracy of 81.20%. To define land use types and urban expansion, screen digitizing and classification methods were used. The results of the study indicate that the urban areas have been increased 1,826 ha across the agricultural fields which are in land use capability classes of I and II, and significant environmental changes such as land degradation and degeneration of ground water quality occurred.

Land cover in the Guayas Basin using SAR images from low resolution ASAR Global mode to high resolution Sentinel-1 images

NASA Astrophysics Data System (ADS)

Bourrel, Luc; Brodu, Nicolas; Frappart, Frédéric

2016-04-01

Remotely sensed images allow a frequent monitoring of land cover variations at regional and global scale. Recently launched Sentinel-1 satellite offers a global cover of land areas at an unprecedented spatial (20 m) and temporal (6 days at the Equator). We propose here to compare the performances of commonly used supervised classification techniques (i.e., k-nearest neighbors, linear and Gaussian support vector machines, naive Bayes, linear and quadratic discriminant analyzes, adaptative boosting, loggit regression, ridge regression with one-vs-one voting, random forest, extremely randomized trees) for land cover applications in the Guayas Basin, the largest river basin of the Pacific coast of Ecuator (area ~32,000 km²). The reason of this choice is the importance of this region in Ecuatorian economy as its watershed represents 13% of the total area of Ecuador where 40% of the Ecuadorian population lives. It also corresponds to the most productive region of Ecuador for agriculture and aquaculture. Fifty percents of the country shrimp farming production comes from this watershed, and represents with agriculture the largest source of revenue of the country. Similar comparisons are also performed using ENVISAT ASAR images acquired in global mode (1 km of spatial resolution). Accuracy of the results will be achieved using land cover map derived from multi-spectral images.

Using Unmanned Helicopters to Assess Vegetation Cover in Sagebrush Steppe Ecosystems

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

Robert P. Breckenridge; Maxine Dakins; Stephen Bunting

2012-07-01

Evaluating vegetation cover is an important factor in understanding the sustainability of many ecosystems. Methods that have sufficient accuracy and improved cost efficiency could dramatically alter how biotic resources are monitored on both public and private lands. This will be of interest to land managers because there are rarely enough resource specialists or funds available for comprehensive ground evaluations. In this project, unmanned helicopters were used to collect still-frame imagery to assess vegetation cover during May, June, and July in 2005. The images were used to estimate percent cover for six vegetative cover classes (shrub, dead shrub, grass, forbs, litter,more » and bare ground). The field plots were located on the INL site west of Idaho Falls, Idaho. Ocular assessments of digital imagery were performed using a software program called SamplePoint, and the results were compared against field measurements collected using a point-frame method to assess accuracy. The helicopter imagery evaluation showed a high degree of agreement with field cover class values for litter, bare ground, and grass, and reasonable agreement for dead shrubs. Shrub cover was often overestimated and forbs were generally underestimated. The helicopter method took 45% less time than the field method to set plots and collect and analyze data. This study demonstrates that UAV technology provides a viable method for monitoring vegetative cover on rangelands in less time and with lower costs. Tradeoffs between cost and accuracy are critical management decisions that are important when managing vegetative conditions across vast sagebrush ecosystems throughout the Intermountain West.« less

Toward Automatic Georeferencing of Archival Aerial Photogrammetric Surveys

NASA Astrophysics Data System (ADS)

Giordano, S.; Le Bris, A.; Mallet, C.

2018-05-01

Images from archival aerial photogrammetric surveys are a unique and relatively unexplored means to chronicle 3D land-cover changes over the past 100 years. They provide a relatively dense temporal sampling of the territories with very high spatial resolution. Such time series image analysis is a mandatory baseline for a large variety of long-term environmental monitoring studies. The current bottleneck for accurate comparison between epochs is their fine georeferencing step. No fully automatic method has been proposed yet and existing studies are rather limited in terms of area and number of dates. State-of-the art shows that the major challenge is the identification of ground references: cartographic coordinates and their position in the archival images. This task is manually performed, and extremely time-consuming. This paper proposes to use a photogrammetric approach, and states that the 3D information that can be computed is the key to full automation. Its original idea lies in a 2-step approach: (i) the computation of a coarse absolute image orientation; (ii) the use of the coarse Digital Surface Model (DSM) information for automatic absolute image orientation. It only relies on a recent orthoimage+DSM, used as master reference for all epochs. The coarse orthoimage, compared with such a reference, allows the identification of dense ground references and the coarse DSM provides their position in the archival images. Results on two areas and 5 dates show that this method is compatible with long and dense archival aerial image series. Satisfactory planimetric and altimetric accuracies are reported, with variations depending on the ground sampling distance of the images and the location of the Ground Control Points.

Remote sensing with simulated unmanned aircraft imagery for precision agriculture applications

USGS Publications Warehouse

Hunt, E. Raymond; Daughtry, Craig S.T.; Mirsky, Steven B.; Hively, W. Dean

2014-01-01

An important application of unmanned aircraft systems (UAS) may be remote-sensing for precision agriculture, because of its ability to acquire images with very small pixel sizes from low altitude flights. The objective of this study was to compare information obtained from two different pixel sizes, one about a meter (the size of a small vegetation plot) and one about a millimeter. Cereal rye (Secale cereale) was planted at the Beltsville Agricultural Research Center for a winter cover crop with fall and spring fertilizer applications, which produced differences in biomass and leaf chlorophyll content. UAS imagery was simulated by placing a Fuji IS-Pro UVIR digital camera at 3-m height looking nadir. An external UV-IR cut filter was used to acquire true-color images; an external red cut filter was used to obtain color-infrared-like images with bands at near-infrared, green, and blue wavelengths. Plot-scale Green Normalized Difference Vegetation Index was correlated with dry aboveground biomass ( ${mbi {r}} = 0.58$ ), whereas the Triangular Greenness Index (TGI) was not correlated with chlorophyll content. We used the SamplePoint program to select 100 pixels systematically; we visually identified the cover type and acquired the digital numbers. The number of rye pixels in each image was better correlated with biomass ( ${mbi {r}} = 0.73$ ), and the average TGI from only leaf pixels was negatively correlated with chlorophyll content ( ${mbi {r}} = -0.72$ ). Thus, better information for crop requirements may be obtained using very small pixel sizes, but new algorithms based on computer vision are needed for analysis. It may not be necessary to geospatially register large numbers of photographs with very small pixel sizes. Instead, images could be analyzed as single plots along field transects.

Evaluating rapid ground sampling and scaling estimated plant cover using UAV imagery up to Landsat for mapping arctic vegetation

NASA Astrophysics Data System (ADS)

Nelson, P.; Paradis, D. P.

2017-12-01

The small stature and spectral diversity of arctic plant taxa presents challenges in mapping arctic vegetation. Mapping vegetation at the appropriate scale is needed to visualize effects of disturbance, directional vegetation change or mapping of specific plant groups for other applications (eg. habitat mapping). Fine spatial grain of remotely sensed data (ca. 10 cm pixels) is often necessary to resolve patches of many arctic plant groups, such as bryophytes and lichens. These groups are also spectrally different from mineral, litter and vascular plants. We sought to explore method to generate high-resolution spatial and spectral data to explore better mapping methods for arctic vegetation. We sampled ground vegetation at seven sites north or west of tree-line in Alaska, four north of Fairbanks and three northwest of Bethel, respectively. At each site, we estimated cover of plant functional types in 1m2 quadrats spaced approximately every 10 m along a 100 m long transect. Each quadrat was also scanned using a field spectroradiometer (PSR+ Spectral Evolution, 400-2500 nm range) and photographed from multiple perspectives. We then flew our small UAV with a RGB camera over the transect and at least 50 m on either side collecting on imagery of the plot, which were used to generate a image mosaic and digital surface model of the plot. We compare plant functional group cover ocular estimated in situ to post-hoc estimation, either automated or using a human observer, using the quadrat photos. We also compare interpolated lichen cover from UAV scenes to estimated lichen cover using a statistical models using Landsat data, with focus on lichens. Light and yellow lichens are discernable in the UAV imagery but certain lichens, especially dark colored lichens or those with spectral signatures similar to graminoid litter, present challenges. Future efforts will focus on integrating UAV-upscaled ground cover estimates to hyperspectral sensors (eg. AVIRIS ng) for better combined spectral and spatial resolution.

39 CFR 233.3 - Mail covers.

Code of Federal Regulations, 2011 CFR

2011-07-01

... transcription, photograph, photocopy or any other facsimile of the image of the outside cover, envelope, wrapper... Postal Inspection Service to transmit mail cover reports directly to the requesting authority. (j) Review...

39 CFR 233.3 - Mail covers.

Code of Federal Regulations, 2010 CFR

2010-07-01

... transcription, photograph, photocopy or any other facsimile of the image of the outside cover, envelope, wrapper... Postal Inspection Service to transmit mail cover reports directly to the requesting authority. (j) Review...

39 CFR 233.3 - Mail covers.

Code of Federal Regulations, 2013 CFR

2013-07-01

... transcription, photograph, photocopy or any other facsimile of the image of the outside cover, envelope, wrapper... Postal Inspection Service to transmit mail cover reports directly to the requesting authority. (j) Review...

39 CFR 233.3 - Mail covers.

Code of Federal Regulations, 2012 CFR

2012-07-01

... transcription, photograph, photocopy or any other facsimile of the image of the outside cover, envelope, wrapper... Postal Inspection Service to transmit mail cover reports directly to the requesting authority. (j) Review...

39 CFR 233.3 - Mail covers.

Code of Federal Regulations, 2014 CFR

2014-07-01

... transcription, photograph, photocopy or any other facsimile of the image of the outside cover, envelope, wrapper... Postal Inspection Service to transmit mail cover reports directly to the requesting authority. (j) Review...

a Spiral-Based Downscaling Method for Generating 30 M Time Series Image Data

NASA Astrophysics Data System (ADS)

Liu, B.; Chen, J.; Xing, H.; Wu, H.; Zhang, J.

2017-09-01

The spatial detail and updating frequency of land cover data are important factors influencing land surface dynamic monitoring applications in high spatial resolution scale. However, the fragmentized patches and seasonal variable of some land cover types (e. g. small crop field, wetland) make it labor-intensive and difficult in the generation of land cover data. Utilizing the high spatial resolution multi-temporal image data is a possible solution. Unfortunately, the spatial and temporal resolution of available remote sensing data like Landsat or MODIS datasets can hardly satisfy the minimum mapping unit and frequency of current land cover mapping / updating at the same time. The generation of high resolution time series may be a compromise to cover the shortage in land cover updating process. One of popular way is to downscale multi-temporal MODIS data with other high spatial resolution auxiliary data like Landsat. But the usual manner of downscaling pixel based on a window may lead to the underdetermined problem in heterogeneous area, result in the uncertainty of some high spatial resolution pixels. Therefore, the downscaled multi-temporal data can hardly reach high spatial resolution as Landsat data. A spiral based method was introduced to downscale low spatial and high temporal resolution image data to high spatial and high temporal resolution image data. By the way of searching the similar pixels around the adjacent region based on the spiral, the pixel set was made up in the adjacent region pixel by pixel. The underdetermined problem is prevented to a large extent from solving the linear system when adopting the pixel set constructed. With the help of ordinary least squares, the method inverted the endmember values of linear system. The high spatial resolution image was reconstructed on the basis of high spatial resolution class map and the endmember values band by band. Then, the high spatial resolution time series was formed with these high spatial resolution images image by image. Simulated experiment and remote sensing image downscaling experiment were conducted. In simulated experiment, the 30 meters class map dataset Globeland30 was adopted to investigate the effect on avoid the underdetermined problem in downscaling procedure and a comparison between spiral and window was conducted. Further, the MODIS NDVI and Landsat image data was adopted to generate the 30m time series NDVI in remote sensing image downscaling experiment. Simulated experiment results showed that the proposed method had a robust performance in downscaling pixel in heterogeneous region and indicated that it was superior to the traditional window-based methods. The high resolution time series generated may be a benefit to the mapping and updating of land cover data.

Assessment of Classification Accuracies of SENTINEL-2 and LANDSAT-8 Data for Land Cover / Use Mapping

NASA Astrophysics Data System (ADS)

Hale Topaloğlu, Raziye; Sertel, Elif; Musaoğlu, Nebiye

2016-06-01

This study aims to compare classification accuracies of land cover/use maps created from Sentinel-2 and Landsat-8 data. Istanbul metropolitan city of Turkey, with a population of around 14 million, having different landscape characteristics was selected as study area. Water, forest, agricultural areas, grasslands, transport network, urban, airport- industrial units and barren land- mine land cover/use classes adapted from CORINE nomenclature were used as main land cover/use classes to identify. To fulfil the aims of this research, recently acquired dated 08/02/2016 Sentinel-2 and dated 22/02/2016 Landsat-8 images of Istanbul were obtained and image pre-processing steps like atmospheric and geometric correction were employed. Both Sentinel-2 and Landsat-8 images were resampled to 30m pixel size after geometric correction and similar spectral bands for both satellites were selected to create a similar base for these multi-sensor data. Maximum Likelihood (MLC) and Support Vector Machine (SVM) supervised classification methods were applied to both data sets to accurately identify eight different land cover/ use classes. Error matrix was created using same reference points for Sentinel-2 and Landsat-8 classifications. After the classification accuracy, results were compared to find out the best approach to create current land cover/use map of the region. The results of MLC and SVM classification methods were compared for both images.

Flood Extent Delineation by Thresholding Sentinel-1 SAR Imagery Based on Ancillary Land Cover Information

NASA Astrophysics Data System (ADS)

Liang, J.; Liu, D.

2017-12-01

Emergency responses to floods require timely information on water extents that can be produced by satellite-based remote sensing. As SAR image can be acquired in adverse illumination and weather conditions, it is particularly suitable for delineating water extent during a flood event. Thresholding SAR imagery is one of the most widely used approaches to delineate water extent. However, most studies apply only one threshold to separate water and dry land without considering the complexity and variability of different dry land surface types in an image. This paper proposes a new thresholding method for SAR image to delineate water from other different land cover types. A probability distribution of SAR backscatter intensity is fitted for each land cover type including water before a flood event and the intersection between two distributions is regarded as a threshold to classify the two. To extract water, a set of thresholds are applied to several pairs of land cover types—water and urban or water and forest. The subsets are merged to form the water distribution for the SAR image during or after the flooding. Experiments show that this land cover based thresholding approach outperformed the traditional single thresholding by about 5% to 15%. This method has great application potential with the broadly acceptance of the thresholding based methods and availability of land cover data, especially for heterogeneous regions.

Remote sensing and GIS-based integrated analysis of land cover change in Duzce plain and its surroundings (north western Turkey).

PubMed

Ikiel, Cercis; Ustaoglu, Beyza; Dutucu, Ayse Atalay; Kilic, Derya Evrim

2013-02-01

The aim of this study is to research natural land cover change caused by the permanent effects of human activities in Duzce plain and its surroundings, and to determine the current status of the land cover. For this purpose, two Landsat TM images were used in the study for the years 1987 and 2010. These images are analysed by using data image processing techniques in ERDAS Imagine©10.0 and ArcGIS©10.0 software. Land cover change nomenclature is classified according to the Coordination of Information on the Environment Level 2 Classification (1--urban fabric, 2--industrial, commercial and transport units, 3--heterogeneous agricultural areas, 4--forests, and 5--inland wetlands). Furthermore, the image analysis results are confirmed by the field research. According to the results, a decrease of 33.5 % was recorded in forest areas from 24,840.7 to 16,529.0 ha; an increase of 11.2 % was recorded in heterogeneous agricultural areas from 47,702.7 to 53,051.7 ha. Natural vegetation, which is the large part of land cover in the research area, has been changing rapidly because of rapid urbanisation and agricultural activities. As a result, it is concluded that significant changes have occurred on the natural land cover between the years 1987 and 2010 in the Duzce plain and its surroundings.

Chemical resistivity of self-assembled monolayer covalently attached to silicon substrate to hydrofluoric acid and ammonium fluoride

NASA Astrophysics Data System (ADS)

Saito, N.; Youda, S.; Hayashi, K.; Sugimura, H.; Takai, O.

2003-06-01

Self-assembled monolayers (SAMs) were prepared on hydrogen-terminated silicon substrates through chemical vapor deposition using 1-hexadecene (HD) as a precursor. The HD-SAMs prepared in an atmosphere under a reduced pressure (≈50 Pa) showed better chemical resistivities to hydrofluoric acid and ammonium fluoride (NH 4F) solutions than that of an organosilane SAM formed on oxide-covered silicon substrates. The surface covered with the HD-SAM was micro-patterned by vacuum ultraviolet photolithography and consequently divided into two areas terminated with HD-SAM or silicon dioxide. This micro-patterned sample was immersed in a 40 vol.% NH 4F aqueous solution. Surface images obtained by an optical microscopy clearly show that the micro-patterns of HD-SAM/silicon dioxide were successfully transferred into the silicon substrate.

Urban Heat Island ın Ankara

NASA Astrophysics Data System (ADS)

Yılmaz, Erkan

2016-04-01

In this study, the seasonal variation of the surface temperature of Ankara urban area and its enviroment have been analyzed by using Landsat 7 image. The Landsat 7 images of each month from 2007 to 2011 have been used to analyze the annually changes of the surface temperature. The land cover of the research area was defined with supervised classification method on the basis of the satellite image belonging to 2008 July. After determining the surface temperatures from 6-1 bands of satellite images, the monthly mean surface temperatures were calculated for land cover classification for the period between 2007 and 2011. According to the results obtained, the surface temperatures are high in summer and low in winter from the airtemperatures. all satellite images were taken at 10:00 am, it is found that urban areas are cooler than rural areas at 10:00 am. Regarding the land cover classification, the water surfaces are the coolest surfaces during the whole year.The warmest areas are the grasslands and dry farming areas. While the parks are warmer than the urban areas during the winter, during the summer they are cooler than artificial land covers. The urban areas with higher building density are the cooler surfaces after water bodies.

A comparison of traffic estimates of nocturnal flying animals using radar, thermal imaging, and acoustic recording.

PubMed

Horton, Kyle G; Shriver, W Gregory; Buler, Jeffrey J

2015-03-01

There are several remote-sensing tools readily available for the study of nocturnally flying animals (e.g., migrating birds), each possessing unique measurement biases. We used three tools (weather surveillance radar, thermal infrared camera, and acoustic recorder) to measure temporal and spatial patterns of nocturnal traffic estimates of flying animals during the spring and fall of 2011 and 2012 in Lewes, Delaware, USA. Our objective was to compare measures among different technologies to better understand their animal detection biases. For radar and thermal imaging, the greatest observed traffic rate tended to occur at, or shortly after, evening twilight, whereas for the acoustic recorder, peak bird flight-calling activity was observed just prior to morning twilight. Comparing traffic rates during the night for all seasons, we found that mean nightly correlations between acoustics and the other two tools were weakly correlated (thermal infrared camera and acoustics, r = 0.004 ± 0.04 SE, n = 100 nights; radar and acoustics, r = 0.14 ± 0.04 SE, n = 101 nights), but highly variable on an individual nightly basis (range = -0.84 to 0.92, range = -0.73 to 0.94). The mean nightly correlations between traffic rates estimated by radar and by thermal infrared camera during the night were more strongly positively correlated (r = 0.39 ± 0.04 SE, n = 125 nights), but also were highly variable for individual nights (range = -0.76 to 0.98). Through comparison with radar data among numerous height intervals, we determined that flying animal height above the ground influenced thermal imaging positively and flight call detections negatively. Moreover, thermal imaging detections decreased with the presence of cloud cover and increased with mean ground flight speed of animals, whereas acoustic detections showed no relationship with cloud cover presence but did decrease with increased flight speed. We found sampling methods to be positively correlated when comparing mean nightly traffic rates across nights. The strength of these correlations generally increased throughout the night, peaking 2-3 hours before morning twilight. Given the convergence of measures by different tools at this time, we suggest that researchers consider sampling flight activity in the hours before morning twilight when differences due to detection biases among sampling tools appear to be minimized.

S-SIMS and MetA-SIMS study of organic additives in thin polymer coatings

NASA Astrophysics Data System (ADS)

Adriaensen, L.; Vangaever, F.; Lenaerts, J.; Gijbels, R.

2006-07-01

In the present study a methodology for TOF-S-SIMS measurements is developed to gain information on the distribution of molecules on and in polymer coatings (thickness ˜100 μm). Experiments were carried out on model systems consisting of one or more additive-containing polyvinylbutyral coatings. Several organic additives were selected: carbocyanine dyes, basonyl blue and the pharmaceutical risperidone. The additives have been measured as pure compounds on a Si substrate to obtain good reference spectra. After optimisation of the sample preparation method, the coatings were embedded in epoxy resin and stored in an oven (60 °C) for 24 h. Cross-sections were made by means of a microtome. S-SIMS spectra were taken on the prepared cross-sections before and after Au was deposited on the sample surface. Compared to the untreated samples, the Au covered samples give rise to more intense secondary ion signals. Generally, signals of the intact cations were more intense than those of the fragment ions. Apart from mass spectra, images of the additive distribution in the coatings could also be acquired by recording structural ion signals. It was possible to make secondary ion images of the additive molecule ions with a (sub)-micrometer lateral resolution.

Using vegetation cover type to predict and scale peatland methane dynamics.

NASA Astrophysics Data System (ADS)

McArthur, K. J.; McCalley, C. K.; Palace, M. W.; Varner, R. K.; Herrick, C.; DelGreco, J. L.

2015-12-01

Permafrost ecosystems contain about 50% of the global soil carbon. As these northern ecosystems experience warmer temperature, permafrost thaws and may result in an increase in atmospheric methane. We examined a thawing and discontinuous permafrost boundary at Stordalen Mire, in Northern Sweden, in an effort to better understand methane emissions. Stable isotope analysis of methane in peatland porewater can give insights into the pathway of methane production. By measuring δ13CH4 we can predict whether a system is dominated by either hydrogenotrophic or acetaclastic methane production. Currently, it is a challenge to scale these isotopic patterns, thus, atmospheric inversion models simply assume that acetoclastic production dominates. We analyzed porewater samples collected across a range of vegetation cover types for δ13CH4 using a QCL (Quantum Cascade Laser Spectrometer) in conjunction with highly accurate GPS (3-10cm) measurements and high-resolution UAV imaging. We found δ13CH4 values ranging from -88‰ to -41‰, with averages based on cover type and other vegetation features showing differences of up to -15‰. We then used a computer neural network to predict cover types across Stordalen Mire from UAV imagery based on field-based plot measurements and training samples.. This prediction map was used to scale methane flux and isotope measurements. Our results suggest that the current values used in atmospheric inversion studies may oversimplify the relationship between plant and microbial communities in complex permafrost landscapes. As we gain a deeper understanding of how vegetation relates to methanogenic communities, understanding the spatial component of ecosystem methane metabolism and distribution will be increasingly valuable.

An Iterative Inference Procedure Applying Conditional Random Fields for Simultaneous Classification of Land Cover and Land Use

NASA Astrophysics Data System (ADS)

Albert, L.; Rottensteiner, F.; Heipke, C.

2015-08-01

Land cover and land use exhibit strong contextual dependencies. We propose a novel approach for the simultaneous classification of land cover and land use, where semantic and spatial context is considered. The image sites for land cover and land use classification form a hierarchy consisting of two layers: a land cover layer and a land use layer. We apply Conditional Random Fields (CRF) at both layers. The layers differ with respect to the image entities corresponding to the nodes, the employed features and the classes to be distinguished. In the land cover layer, the nodes represent super-pixels; in the land use layer, the nodes correspond to objects from a geospatial database. Both CRFs model spatial dependencies between neighbouring image sites. The complex semantic relations between land cover and land use are integrated in the classification process by using contextual features. We propose a new iterative inference procedure for the simultaneous classification of land cover and land use, in which the two classification tasks mutually influence each other. This helps to improve the classification accuracy for certain classes. The main idea of this approach is that semantic context helps to refine the class predictions, which, in turn, leads to more expressive context information. Thus, potentially wrong decisions can be reversed at later stages. The approach is designed for input data based on aerial images. Experiments are carried out on a test site to evaluate the performance of the proposed method. We show the effectiveness of the iterative inference procedure and demonstrate that a smaller size of the super-pixels has a positive influence on the classification result.

GLCF: About GLCF

Science.gov Websites

on determining land cover and land cover change around the world. Land cover is the discernible imagery. Land cover change can be assessed by comparing one area with two images taken at different dates . Determining where, when, how much and why change occurs with land cover is a crucial scientific concern. It is

Acquisition and visualization techniques for narrow spectral color imaging.

PubMed

Neumann, László; García, Rafael; Basa, János; Hegedüs, Ramón

2013-06-01

This paper introduces a new approach in narrow-band imaging (NBI). Existing NBI techniques generate images by selecting discrete bands over the full visible spectrum or an even wider spectral range. In contrast, here we perform the sampling with filters covering a tight spectral window. This image acquisition method, named narrow spectral imaging, can be particularly useful when optical information is only available within a narrow spectral window, such as in the case of deep-water transmittance, which constitutes the principal motivation of this work. In this study we demonstrate the potential of the proposed photographic technique on nonunderwater scenes recorded under controlled conditions. To this end three multilayer narrow bandpass filters were employed, which transmit at 440, 456, and 470 nm bluish wavelengths, respectively. Since the differences among the images captured in such a narrow spectral window can be extremely small, both image acquisition and visualization require a novel approach. First, high-bit-depth images were acquired with multilayer narrow-band filters either placed in front of the illumination or mounted on the camera lens. Second, a color-mapping method is proposed, using which the input data can be transformed onto the entire display color gamut with a continuous and perceptually nearly uniform mapping, while ensuring optimally high information content for human perception.

In-situ X-ray CT results of damage evolution in L6 ordinary chondrite meteorites

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

Cuadra, Jefferson A.; Hazeli, Kavan; Ramesh, K. T.

2016-06-17

These are slides about in-situ X-ray CT results of damage evolution in L6 ordinary chondrite meteorites. The following topics are covered: mechanical and thermal damage characterization, list of Grosvenor Mountain (GRO) meteorite samples, in-situ x-ray compression test setup, GRO-chipped reference at 0 N - existing cracks, GRO-chipped loaded at 1580 N, in-situ x-ray thermal fatigue test setup, GRO-B14 room temperature reference, GRO-B14 Cycle 47 at 200°C, GRO-B14 Cycle 47 at room temperature, conclusions from qualitative analysis, future work and next steps. Conclusions are the following: Both GRO-Chipped and GRO-B14 had existing voids and cracks within the volume. These sites withmore » existing damage were selected for CT images from mechanically and thermally loaded scans since they are prone to damage initiation. The GRO-Chipped sample was loaded to 1580 N which resulted in a 14% compressive engineering strain, calculated using LVDT. Based on the CT cross sectional images, the GRO-B14 sample at 200°C has a thermal expansion of approximately 96 μm in height (i.e. ~1.6% engineering strain).« less

Mapping Surface Soil Organic Carbon for Crop Fields with Remote Sensing

NASA Technical Reports Server (NTRS)

Chen, Feng; Kissel, David E.; West, Larry T.; Rickman, Doug; Luvall, J. C.; Adkins, Wayne

2004-01-01

The organic C concentration of surface soil can be used in agricultural fields to vary crop production inputs. Organic C is often highly spatially variable, so that maps of soil organic C can be used to vary crop production inputs using precision farming technology. The objective of this research was to demonstrate the feasibility of mapping soil organic C on three fields, using remotely sensed images of the fields with a bare surface. Enough soil samples covering the range in soil organic C must be taken from each field to develop a satisfactory relationship between soil organic C content and image reflectance values. The number of soil samples analyzed in the three fields varied from 22 to 26. The regression equations differed between fields, but gave highly significant relationships with R2 values of 0.93, 0.95, and 0.89 for the three fields. A comparison of predicted and measured values of soil organic C for an independent set of 2 soil samples taken on one of the fields gave highly satisfactory results, with a comparison equation of % organic C measured + 1.02% organic C predicted, with r2 = 0.87.

VIS: the visible imager for Euclid

NASA Astrophysics Data System (ADS)

Cropper, Mark; Pottinger, S.; Niemi, S.; Azzollini, R.; Denniston, J.; Szafraniec, M.; Awan, S.; Mellier, Y.; Berthe, M.; Martignac, J.; Cara, C.; Di Giorgio, A.-M.; Sciortino, A.; Bozzo, E.; Genolet, L.; Cole, R.; Philippon, A.; Hailey, M.; Hunt, T.; Swindells, I.; Holland, A.; Gow, J.; Murray, N.; Hall, D.; Skottfelt, J.; Amiaux, J.; Laureijs, R.; Racca, G.; Salvignol, J.-C.; Short, A.; Lorenzo Alvarez, J.; Kitching, T.; Hoekstra, H.; Massey, R.; Israel, H.

2016-07-01

Euclid-VIS is the large format visible imager for the ESA Euclid space mission in their Cosmic Vision program, scheduled for launch in 2020. Together with the near infrared imaging within the NISP instrument, it forms the basis of the weak lensing measurements of Euclid. VIS will image in a single r+i+z band from 550-900 nm over a field of view of ~0.5 deg2. By combining 4 exposures with a total of 2260 sec, VIS will reach to deeper than mAB=24.5 (10σ) for sources with extent ~0.3 arcsec. The image sampling is 0.1 arcsec. VIS will provide deep imaging with a tightly controlled and stable point spread function (PSF) over a wide survey area of 15000 deg2 to measure the cosmic shear from nearly 1.5 billion galaxies to high levels of accuracy, from which the cosmological parameters will be measured. In addition, VIS will also provide a legacy dataset with an unprecedented combination of spatial resolution, depth and area covering most of the extra-Galactic sky. Here we will present the results of the study carried out by the Euclid Consortium during the period up to the Critical Design Review.

Predicting the amount of coke deposition on catalyst pellets through image analysis and soft computing

NASA Astrophysics Data System (ADS)

Zhang, Jingqiong; Zhang, Wenbiao; He, Yuting; Yan, Yong

2016-11-01

The amount of coke deposition on catalyst pellets is one of the most important indexes of catalytic property and service life. As a result, it is essential to measure this and analyze the active state of the catalysts during a continuous production process. This paper proposes a new method to predict the amount of coke deposition on catalyst pellets based on image analysis and soft computing. An image acquisition system consisting of a flatbed scanner and an opaque cover is used to obtain catalyst images. After imaging processing and feature extraction, twelve effective features are selected and two best feature sets are determined by the prediction tests. A neural network optimized by a particle swarm optimization algorithm is used to establish the prediction model of the coke amount based on various datasets. The root mean square error of the prediction values are all below 0.021 and the coefficient of determination R 2, for the model, are all above 78.71%. Therefore, a feasible, effective and precise method is demonstrated, which may be applied to realize the real-time measurement of coke deposition based on on-line sampling and fast image analysis.

An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis.

PubMed

Stewart, Ethan L; Hagerty, Christina H; Mikaberidze, Alexey; Mundt, Christopher C; Zhong, Ziming; McDonald, Bruce A

2016-07-01

Zymoseptoria tritici causes Septoria tritici blotch (STB) on wheat. An improved method of quantifying STB symptoms was developed based on automated analysis of diseased leaf images made using a flatbed scanner. Naturally infected leaves (n = 949) sampled from fungicide-treated field plots comprising 39 wheat cultivars grown in Switzerland and 9 recombinant inbred lines (RIL) grown in Oregon were included in these analyses. Measures of quantitative resistance were percent leaf area covered by lesions, pycnidia size and gray value, and pycnidia density per leaf and lesion. These measures were obtained automatically with a batch-processing macro utilizing the image-processing software ImageJ. All phenotypes in both locations showed a continuous distribution, as expected for a quantitative trait. The trait distributions at both sites were largely overlapping even though the field and host environments were quite different. Cultivars and RILs could be assigned to two or more statistically different groups for each measured phenotype. Traditional visual assessments of field resistance were highly correlated with quantitative resistance measures based on image analysis for the Oregon RILs. These results show that automated image analysis provides a promising tool for assessing quantitative resistance to Z. tritici under field conditions.

Highest Resolution Image of Dust and Sand Yet Acquired on Mars

NASA Technical Reports Server (NTRS)

2008-01-01

[figure removed for brevity, see original site] [figure removed for brevity, see original site] [figure removed for brevity, see original site] Click on image for Figure 1Click on image for Figure 2Click on image for Figure 3

This mosaic of four side-by-side microscope images (one a color composite) was acquired by the Optical Microscope, a part of the Microscopy, Electrochemistry, and Conductivity Analyzer (MECA) instrument suite on NASA's Phoenix Mars Lander. Taken on the ninth Martian day of the mission, or Sol 9 (June 3, 2008), the image shows a 3 millimeter (0.12 inch) diameter silicone target after it has been exposed to dust kicked up by the landing. It is the highest resolution image of dust and sand ever acquired on Mars. The silicone substrate provides a sticky surface for holding the particles to be examined by the microscope.

Martian Particles on Microscope's Silicone Substrate In figure 1, the particles are on a silcone substrate target 3 millimeters (0.12 inch) in diameter, which provides a sticky surface for holding the particles while the microscope images them. Blow-ups of four of the larger particles are shown in the center. These particles range in size from about 30 microns to 150 microns (from about one one-thousandth of an inch to six one-thousandths of an inch).

Possible Nature of Particles Viewed by Mars Lander's Optical Microscope In figure 2, the color composite on the right was acquired to examine dust that had fallen onto an exposed surface. The translucent particle highlighted at bottom center is of comparable size to white particles in a Martian soil sample (upper pictures) seen two sols earlier inside the scoop of Phoenix's Robotic Arm as imaged by the lander's Robotic Arm Camera. The white particles may be examples of the abundant salts that have been found in the Martian soil by previous missions. Further investigations will be needed to determine the white material's composition and whether translucent particles like the one in this microscopic image are found in Martian soil samples.

Scale of Phoenix Optical Microscope Images This set of pictures in figure 3 gives context for the size of individual images from the Optical Microscope on NASA's Mars Phoenix Lander.

The picture in the upper left was taken on Mars by the Surface Stereo Imager on Phoenix. It shows a portion of the microscope's sample stage exposed to accept a sample. In this case, the sample was of dust kicked up by the spacecraft thrusters during landers. Later samples will include soil delivered by the Robotic Arm.

The other pictures were taken on Earth. They show close-ups of circular substrates on which the microscopic samples rest when the microscope images them. Each circular substrate target is 3 millimeters (about one-tenth of an inch) in diameter. Each image taken by the microscope covers and area 2 millimeters by 1 millimeter (0.08 inch by 0.04 inch), the size of a large grain of sand.

The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

Usefulness of LANDSAT data for monitoring plant development and range conditions in California's annual grassland

NASA Technical Reports Server (NTRS)

Carneggie, D. M.; Degloria, S. D.; Colwell, R. N.

1977-01-01

A network of sampling sites throughout the annual grassland region was established to correlate plant growth in stages and forage production to climatic and other environmental factors. Plant growth and range conditions were further related to geographic location and seasonal variations. A sequence of LANDSAT data was obtained covering critical periods in the growth cycle. Data were analyzed by both photointerpretation and computer aided techniques. Image characteristics and spectral reflectance data were then related to forage production, range condition, range site, and changing growth conditions.

VizieR Online Data Catalog: CARMENES radial velocity curves of 7 M-dwarf (Trifonov+, 2018)

NASA Astrophysics Data System (ADS)

Trifonov, T.; Kuerster, M.; Zechmeister, M.; Tal-Or, L.; Caballero, J. A.; Quirrenbach, A.; Amado, P. J.; Ribas, I.; Reiners, A.; Reffert, S.; Dreizler, S.; Hatzes, A. P.; Kaminski, A.; Launhardt, R.; Henning, T.; Montes, D.; Bejar, V. J. S.; Mundt, R.; Pavlov, A.; Schmitt, J. H. M. M.; Seifert, W.; Morales, J. C.; Nowak, G.; Jeffers, S. V.; Rodriguez-Lopez, C.; Del Burgo, C.; Anglada-Escude, G.; Lopez-Santiago, J.; Mathar, R. J.; Ammler-von Eiff, M.; Guenther, E. W.; Barrado, D.; Gonzalez Hernandez, J. I.; Mancini, L.; Stuermer, J.; Abril, M.; Aceituno, J.; Alonso-Floriano, F. J.; Antona, R.; Anwand-Heerwart, H.; Arroyo-Torres, B.; Azzaro, M.; Baroch, D.; Bauer, F. F.; Becerril, S.; Benitez, D.; Berdinas, Z. M.; Bergond, G.; Bluemcke, M.; Brinkmoeller, M.; Cano, J.; Cardenas Vazquez, M. C.; Casal, E.; Cifuentes, C.; Claret, A.; Colome, J.; Cortes-Contreras, M.; Czesla, S.; Diez-Alonso, E.; Feiz, C.; Fernandez, M.; Ferro, I. M.; Fuhrmeister, B.; Galadi-Enriquez, D.; Garcia-Piquer, A.; Garcia Vargas, M. L.; Gesa, L.; Gomez Galera, V.; Gonzalez-Peinado, R.; Groezinger, U.; Grohnert, S.; Guardia, J.; Guijarro, A.; de Guindos, E.; Gutierrez-Soto, J.; Hagen, H.-J.; Hauschildt, P. H.; Hedrosa, R. P.; Helmling, J.; Hermelo, I.; Hernandez Arabi, R.; Hernandez Castano, L.; Hernandez Hernando, F.; Herrero, E.; Huber, A.; Huke, P.; Johnson, E.; de Juan, E.; Kim, M.; Klein, R.; Klueter, J.; Klutsch, A.; Lafarga, M.; Lampon, M.; Lara, L. M.; Laun, W.; Lemke, U.; Lenzen, R.; Lopez Del Fresno, M.; Lopez-Gonzalez, J.; Lopez-Puertas, M.; Lopez Salas, J. F.; Luque, R.; Magan Madinabeitia, H.; Mall, U.; Mandel, H.; Marfil, E.; Marin Molina, J. A.; Maroto Fernandez, D.; Martin, E. L.; Martin-Ruiz, S.; Marvin, C. J.; Mirabet, E.; Moya, A.; Moreno-Raya, M. E.; Nagel, E.; Naranjo, V.; Nortmann, L.; Ofir, A.; Oreiro, R.; Palle, E.; Panduro, J.; Pascual, J.; Passegger, V. M.; Pedraz, S.; Perez-Calpena, A.; Perez Medialdea, D.; Perger, M.; Perryman, M. A. C.; Pluto, M.; Rabaza, O.; Ramon, A.; Rebolo, R.; Redondo, P.; Reinhardt, S.; Rhode, P.; Rix, H.-W.; Rodler, F.; Rodriguez, E.; Rodriguez Trinidad, A.; Rohlo, R.-R.; Rosich, A.; Sadegi, S.; Sanchez-Blanco, E.; Sanchez Carrasco, M. A.; Sanchez-Lopez, A.; Sanz-Forcada, J.; Sarkis, P.; Sarmiento, L. F.; Schaefer, S.; Schiller, J.; Schoefer, P.; Schweitzer, A.; Solano, E.; Stahl, O.; Strachan, J. B. P.; Suarez, J. C.; Tabernero, H. M.; Tala, M.; Tulloch, S. M.; Veredas, G.; Vico Linares, J. I.; Vilardel, F.; Wagner, K.; Winkler, J.; Woltho, V.; Xu, W.; Yan, F.; Zapatero Osorio, M. R.

2017-10-01

The two CARMENES spectrographs are grism cross-dispersed, white pupil, echelle spectrograph working in quasi-Littrow mode using a two-beam, two-slice image slicer. The visible spectrograph covers the wavelength range from 0.52um to 1.05um with 61 orders, a resolving power of R=94600, and a mean sampling of 2.8 pixels per resolution element. The data presented in this paper were taken during the early phase of operation of the CARMENES visible-light spectrograph. (8 data files).

An approach to optimize sample preparation for MALDI imaging MS of FFPE sections using fractional factorial design of experiments.

PubMed

Oetjen, Janina; Lachmund, Delf; Palmer, Andrew; Alexandrov, Theodore; Becker, Michael; Boskamp, Tobias; Maass, Peter

2016-09-01

A standardized workflow for matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI imaging MS) is a prerequisite for the routine use of this promising technology in clinical applications. We present an approach to develop standard operating procedures for MALDI imaging MS sample preparation of formalin-fixed and paraffin-embedded (FFPE) tissue sections based on a novel quantitative measure of dataset quality. To cover many parts of the complex workflow and simultaneously test several parameters, experiments were planned according to a fractional factorial design of experiments (DoE). The effect of ten different experiment parameters was investigated in two distinct DoE sets, each consisting of eight experiments. FFPE rat brain sections were used as standard material because of low biological variance. The mean peak intensity and a recently proposed spatial complexity measure were calculated for a list of 26 predefined peptides obtained by in silico digestion of five different proteins and served as quality criteria. A five-way analysis of variance (ANOVA) was applied on the final scores to retrieve a ranking of experiment parameters with increasing impact on data variance. Graphical abstract MALDI imaging experiments were planned according to fractional factorial design of experiments for the parameters under study. Selected peptide images were evaluated by the chosen quality metric (structure and intensity for a given peak list), and the calculated values were used as an input for the ANOVA. The parameters with the highest impact on the quality were deduced and SOPs recommended.

A Markov random field based approach to the identification of meat and bone meal in feed by near-infrared spectroscopic imaging.

PubMed

Jiang, Xunpeng; Yang, Zengling; Han, Lujia

2014-07-01

Contaminated meat and bone meal (MBM) in animal feedstuff has been the source of bovine spongiform encephalopathy (BSE) disease in cattle, leading to a ban in its use, so methods for its detection are essential. In this study, five pure feed and five pure MBM samples were used to prepare two sets of sample arrangements: set A for investigating the discrimination of individual feed/MBM particles and set B for larger numbers of overlapping particles. The two sets were used to test a Markov random field (MRF)-based approach. A Fourier transform infrared (FT-IR) imaging system was used for data acquisition. The spatial resolution of the near-infrared (NIR) spectroscopic image was 25 μm × 25 μm. Each spectrum was the average of 16 scans across the wavenumber range 7,000-4,000 cm(-1), at intervals of 8 cm(-1). This study introduces an innovative approach to analyzing NIR spectroscopic images: an MRF-based approach has been developed using the iterated conditional mode (ICM) algorithm, integrating initial labeling-derived results from support vector machine discriminant analysis (SVMDA) and observation data derived from the results of principal component analysis (PCA). The results showed that MBM covered by feed could be successfully recognized with an overall accuracy of 86.59% and a Kappa coefficient of 0.68. Compared with conventional methods, the MRF-based approach is capable of extracting spectral information combined with spatial information from NIR spectroscopic images. This new approach enhances the identification of MBM using NIR spectroscopic imaging.

Unusually Low Snow Cover in the U.S.

NASA Technical Reports Server (NTRS)

2002-01-01

New maps of snow cover produced by NASA's Terra satellite show that this year's snow line stayed farther north than normal. When combined with land surface temperature measurements, the observations confirm earlier National Oceanic and Atmospheric Administration reports that the United States was unusually warm and dry this past winter. The above map shows snow cover over the continental United States from February 2002 and is based on data acquired by the Moderate-Resolution Imaging Spectroradiometer (MODIS). The amount of land covered by snow during this period was much lower than usual. With the exception of the western mountain ranges and the Great Lakes region, the country was mostly snow free. The solid red line marks the average location of the monthly snow extent; white areas are snow-covered ground. Snow was mapped at approximately 5 kilometer pixel resolution on a daily basis and then combined, or composited, every eight days. If a pixel was at least 50 percent snow covered during all of the eight-day periods that month, it was mapped as snow covered for the whole month. For more information, images, and animations, read: Terra Satellite Data Confirm Unusually Warm, Dry U.S. Winter Image by Robert Simmon, based on data from the MODIS Snow/Ice Global Mapping Project

Land use and land cover mapping: City of Palm Bay, Florida

NASA Technical Reports Server (NTRS)

Barile, D. D.; Pierce, R.

1977-01-01

Two different computer systems were compared for use in making land use and land cover maps. The Honeywell 635 with the LANDSAT signature development program (LSDP) produced a map depicting general patterns, but themes were difficult to classify as specific land use. Urban areas were unclassified. The General Electric Image 100 produced a map depicting eight land cover categories classifying 68 percent of the total area. Ground truth, LSDP, and Image 100 maps were all made to the same scale for comparison. LSDP agreed with the ground truth 60 percent and 64 percent within the two test areas compared and Image 100 was in agreement 70 percent and 80 percent.

Spatiotemporal Change Detection Using Landsat Imagery: the Case Study of Karacabey Flooded Forest, Bursa, Turkey

NASA Astrophysics Data System (ADS)

Akay, A. E.; Gencal, B.; Taş, İ.

2017-11-01

This short paper aims to detect spatiotemporal detection of land use/land cover change within Karacabey Flooded Forest region. Change detection analysis applied to Landsat 5 TM images representing July 2000 and a Landsat 8 OLI representing June 2017. Various image processing tools were implemented using ERDAS 9.2, ArcGIS 10.4.1, and ENVI programs to conduct spatiotemporal change detection over these two images such as band selection, corrections, subset, classification, recoding, accuracy assessment, and change detection analysis. Image classification revealed that there are five significant land use/land cover types, including forest, flooded forest, swamp, water, and other lands (i.e. agriculture, sand, roads, settlement, and open areas). The results indicated that there was increase in flooded forest, water, and other lands, while the cover of forest and swamp decreased.

Generating land cover boundaries from remotely sensed data using object-based image analysis: overview and epidemiological application

PubMed Central

Maxwell, Susan K.

2010-01-01

Satellite imagery and aerial photography represent a vast resource to significantly enhance environmental mapping and modeling applications for use in understanding spatio-temporal relationships between environment and health. Deriving boundaries of land cover objects, such as trees, buildings, and crop fields, from image data has traditionally been performed manually using a very time consuming process of hand digitizing. Boundary detection algorithms are increasingly being applied using object-based image analysis (OBIA) technology to automate the process. The purpose of this paper is to present an overview and demonstrate the application of OBIA for delineating land cover features at multiple scales using a high resolution aerial photograph (1 m) and a medium resolution Landsat image (30 m) time series in the context of a pesticide spray drift exposure application. PMID:21135917

Synergy of Optical and SAR Data for Mapping and Monitoring Mangroves

NASA Astrophysics Data System (ADS)

Monzon, A. K.; Reyes, S. R.; Veridiano, R. K.; Tumaneng, R.; De Alban, J. D.

2016-06-01

Quantitative information on mangrove cover extents is essential in producing relevant resource management plans and conservation strategies. In the Philippines, mangrove rehabilitation was made a priority in relation to disaster risk response and mitigation following the calamities in the coastal communities during typhoon Haiyan/Yolanda; hence, baseline information on the extent of remaining mangrove cover was essential for effective site interventions. Although mangrove cover maps for the country already exists, analysis of mangrove cover changes were limited to the application of fixed annual deforestation rates due to the challenge of acquiring consistent temporal cloud-free optical satellite data over large landscapes. This study presents an initial analysis of SAR and optical imagery combined with field-based observations for detecting mangrove cover extent and changes through a straightforward graphical approach. The analysis is part of a larger study evaluating the synergistic use of time-series L-band SAR and optical data for mapping and monitoring of mangroves. Image segmentation was implemented on the 25-meter ALOS/PALSAR image mosaics, in which the generated objects were subjected to statistical analysis using the software R. In combination with selected Landsat bands, the class statistics from the image bands were used to generate decision trees and thresholds for the hierarchical image classification. The results were compared with global mangrove cover dataset and validated using collected ground truth data. This study developed an integrated replicable approach for analyzing future radar and optical datasets, essential in national level mangrove cover change monitoring and assessment for long-term conservation targets and strategies.

Spectroscopic Confirmation of Two Massive Red-sequence-selected Galaxy Clusters at Z Approximately Equal to 1.2 in the Sparcs-North Cluster Survey

NASA Technical Reports Server (NTRS)

Muzzin, Adam; Wilson, Gillian; Yee, H.K.C.; Hoekstra, Henk; Gilbank, David; Surace, Jason; Lacy, Mark; Blindert, Kris; Majumdar, Subhabrata; Demarco, Ricardo;

A Novel Quantum Image Steganography Scheme Based on LSB

NASA Astrophysics Data System (ADS)

Zhou, Ri-Gui; Luo, Jia; Liu, XingAo; Zhu, Changming; Wei, Lai; Zhang, Xiafen

2018-06-01

Based on the NEQR representation of quantum images and least significant bit (LSB) scheme, a novel quantum image steganography scheme is proposed. The sizes of the cover image and the original information image are assumed to be 4 n × 4 n and n × n, respectively. Firstly, the bit-plane scrambling method is used to scramble the original information image. Then the scrambled information image is expanded to the same size of the cover image by using the key only known to the operator. The expanded image is scrambled to be a meaningless image with the Arnold scrambling. The embedding procedure and extracting procedure are carried out by K 1 and K 2 which are under control of the operator. For validation of the presented scheme, the peak-signal-to-noise ratio (PSNR), the capacity, the security of the images and the circuit complexity are analyzed.

Bloodstain detection and discrimination impacted by spectral shift when using an interference filter-based visible and near-infrared multispectral crime scene imaging system

NASA Astrophysics Data System (ADS)

Yang, Jie; Messinger, David W.; Dube, Roger R.

2018-03-01

Bloodstain detection and discrimination from nonblood substances on various substrates are critical in forensic science as bloodstains are a critical source for confirmatory DNA tests. Conventional bloodstain detection methods often involve time-consuming sample preparation, a chance of harm to investigators, the possibility of destruction of blood samples, and acquisition of too little data at crime scenes either in the field or in the laboratory. An imaging method has the advantages of being nondestructive, noncontact, real-time, and covering a large field-of-view. The abundant spectral information provided by multispectral imaging makes it a potential presumptive bloodstain detection and discrimination method. This article proposes an interference filter (IF) based area scanning three-spectral-band crime scene imaging system used for forensic bloodstain detection and discrimination. The impact of large angle of views on the spectral shift of calibrated IFs is determined, for both detecting and discriminating bloodstains from visually similar substances on multiple substrates. Spectral features in the visible and near-infrared portion employed by the relative band depth method are used. This study shows that 1 ml bloodstain on black felt, gray felt, red felt, white cotton, white polyester, and raw wood can be detected. Bloodstains on the above substrates can be discriminated from cola, coffee, ketchup, orange juice, red wine, and green tea.

Validation of Special Sensor Ultraviolet Limb Imager (SSULI) Ionospheric Tomography using ALTAIR Incoherent Scatter Radar Measurements

NASA Astrophysics Data System (ADS)

Dymond, K.; Nicholas, A. C.; Budzien, S. A.; Stephan, A. W.; Coker, C.; Hei, M. A.; Groves, K. M.

2015-12-01

The Special Sensor Ultraviolet Limb Imager (SSULI) instruments are ultraviolet limb scanning sensors flying on the Defense Meteorological Satellite Program (DMSP) satellites. The SSULIs observe the 80-170 nanometer wavelength range covering emissions at 91 and 136 nm, which are produced by radiative recombination of the ionosphere. We invert these emissions tomographically using newly developed algorithms that include optical depth effects due to pure absorption and resonant scattering. We present the details of our approach including how the optimal altitude and along-track sampling were determined and the newly developed approach we are using for regularizing the SSULI tomographic inversions. Finally, we conclude with validations of the SSULI inversions against ALTAIR incoherent scatter radar measurements and demonstrate excellent agreement between the measurements.

Near-Field Scanning Optical Microscopy of Soft, Biological, or Rough Objects in Aqueous Environment: Challenges and some Remedies to Circumvent

NASA Technical Reports Server (NTRS)

Vikram, C. S.; Witherow, W. K.

1999-01-01

Near-field scanning optical microscopy is an established technique for sub-wavelength spatial resolution in imaging, spectroscopy, material science, surface chemistry, polarimetry, etc. A significant amount of confidence has been established for thin hard specimens in air. However when soft, biological, rough, in aqueous environment object, or a combination is involved, the progress has been slow. The tip-sample mechanical interaction, heat effects to sample, drag effects to the probe, difficulty in controlling tip-sample separation in case of rough objects, light scattering from sample thickness, etc. create problems. Although these problems are not even fully understood, there have been attempts to study them with the aim of performing reliable operations. In this review we describe these attempts. Starting with general problems encountered, various effects like polarization, thermal, and media are covered. The roles of independent tip-sample distance control tools in the relevant situations are then described. Finally progress in fluid cell aspect has been summarized.

Point force singularities outside a drop covered with an incompressible surfactant: Image systems and their applications

NASA Astrophysics Data System (ADS)

Shaik, Vaseem A.; Ardekani, Arezoo M.

2017-11-01

In this work we derive the image flow fields for point force singularities placed outside a stationary drop covered with an insoluble, nondiffusing, and incompressible surfactant. We assume the interface to be Newtonian and use the Boussinesq-Scriven constitutive law for the interfacial stress tensor. We use this analytical solution to investigate two different problems. First, we derive the mobility matrix for two drops of arbitrary sizes covered with an incompressible surfactant. In the second example, we calculate the velocity of a swimming microorganism (modeled as a Stokes dipole) outside a drop covered with an incompressible surfactant.

A novel quantum steganography scheme for color images

NASA Astrophysics Data System (ADS)

Li, Panchi; Liu, Xiande

In quantum image steganography, embedding capacity and security are two important issues. This paper presents a novel quantum steganography scheme using color images as cover images. First, the secret information is divided into 3-bit segments, and then each 3-bit segment is embedded into the LSB of one color pixel in the cover image according to its own value and using Gray code mapping rules. Extraction is the inverse of embedding. We designed the quantum circuits that implement the embedding and extracting process. The simulation results on a classical computer show that the proposed scheme outperforms several other existing schemes in terms of embedding capacity and security.

Satellite radars for geologic mapping in tropical regions

NASA Technical Reports Server (NTRS)

Ford, J. P.; Sabins, F. F.

1987-01-01

This paper presents interpretations of the satellite radar images of cloud-covered portions of Indonesia and Amazonia obtained from NASA's Shuttle imaging radar experiments in 1981 (SIR-A) and 1984 (SIR-B). It was found that different terrain categories observed from distinctive image textures correlate well with major lithologic associations. The images show geologic structures at regional and local scales. The SIR-B images of East Kalimantan, Indonesia, reveal structural features and terrain distributions that had been overlooked or not perceived in previous surface mapping. Variability in radar response from the vegetation cover is interpretable only in coastal areas or alluvial areas that are relatively level.

A PCA-based hyperspectral approach to detect infections by mycophilic fungi on dried porcini mushrooms (boletus edulis and allied species).

PubMed

Bagnasco, Lucia; Zotti, Mirca; Sitta, Nicola; Oliveri, Paolo

2015-11-01

Mycophilic fungi of anamorphic genus Sepedonium (telomorphs in Hypomyces, Hypocreales, Ascomycota) infect and parasitize sporomata of boletes. The obligated hosts such as Boletus edulis and allied species (known as "porcini mushrooms") are among the most valued and prized edible wild mushrooms in the world. Sepedonium infections have a great morphological variability: at the initial state, contaminated mushrooms present a white coating covering tubes and pores; at the final state, Sepedonium forms a deep and thick hyphal layer that eventually leads to the total necrosis of the host. Up to date, Sepedonium infections in porcini mushrooms have been evaluated only through macroscopic and microscopic visual analysis. In this study, in order to implement the infection evaluation as a routine methodology for industrial purposes, the potential application of Hyperspectral Imaging (HSI) and Principal Component Analysis (PCA) for detection of Sepedonium presence on sliced and dried B. edulis and allied species was investigated. Hyperspectral images were obtained using a pushbroom line-scanning HSI instrument, operating in the wavelength range between 400 and 1000 nm with 5 nm resolution. PCA was applied on normal and contaminated samples. To reduce the spectral variability caused by factors unrelated to Sepedonium infection, such as scattering effects and differences in sample height, different spectral pre-treatments were applied. A supervised rule was then developed to assign spectra recorded on new test samples to each of the two classes, based on the PC scores. This allowed to visualize directly - within false-color images of test samples - which points of the samples were contaminated. The results achieved may lead to the development of a non-destructive monitoring system for a rapid on-line screening of contaminated mushrooms. Copyright © 2015 Elsevier B.V. All rights reserved.

LAND COVER ASSESSMENT OF INDIGENOUS COMMUNITIES IN THE BOSAWAS REGION OF NICARAGUA

EPA Science Inventory

Data derived from remotely sensed images were utilized to conduct land cover assessments of three indigenous communities in northern Nicaragua. Historical land use, present land cover and land cover change processes were all identified through the use of a geographic informat...

Commentary: A cautionary tale regarding use of the National Land Cover Dataset 1992

USGS Publications Warehouse

Thogmartin, Wayne E.; Gallant, Alisa L.; Knutson, Melinda G.; Fox, Timothy J.; Suarez, Manuel J.

2004-01-01

Digital land-cover data are among the most popular data sources used in ecological research and natural resource management. However, processes for accurate land-cover classification over large regions are still evolving. We identified inconsistencies in the National Land Cover Dataset 1992, the most current and available representation of land cover for the conterminous United States. We also report means to address these inconsistencies in a bird-habitat model. We used a Geographic Information System (GIS) to position a regular grid (or lattice) over the upper midwestern United States and summarized the proportion of individual land covers in each cell within the lattice. These proportions were then mapped back onto the lattice, and the resultant lattice was compared to satellite paths, state borders, and regional map classification units. We observed mapping inconsistencies at the borders between mapping regions, states, and Thematic Mapper (TM) mapping paths in the upper midwestern United States, particularly related to grass I and-herbaceous, emergent-herbaceous wetland, and small-grain land covers. We attributed these discrepancies to differences in image dates between mapping regions, suboptimal image dates for distinguishing certain land-cover types, lack of suitable ancillary data for improving discrimination for rare land covers, and possibly differences among image interpreters. To overcome these inconsistencies for the purpose of modeling regional populations of birds, we combined grassland-herbaceous and pasture-hay land-cover classes and excluded the use of emergent-herbaceous and small-grain land covers. We recommend that users of digital land-cover data conduct similar assessments for other regions before using these data for habitat evaluation. Further, caution is advised in using these data in the analysis of regional land-cover change because it is not likely that future digital land-cover maps will repeat the same problems, thus resulting in biased estimates of change.

Analysis On Land Cover In Municipality Of Malang With Landsat 8 Image Through Unsupervised Classification

NASA Astrophysics Data System (ADS)

Nahari, R. V.; Alfita, R.

2018-01-01

Remote sensing technology has been widely used in the geographic information system in order to obtain data more quickly, accurately and affordably. One of the advantages of using remote sensing imagery (satellite imagery) is to analyze land cover and land use. Satellite image data used in this study were images from the Landsat 8 satellite combined with the data from the Municipality of Malang government. The satellite image was taken in July 2016. Furthermore, the method used in this study was unsupervised classification. Based on the analysis towards the satellite images and field observations, 29% of the land in the Municipality of Malang was plantation, 22% of the area was rice field, 12% was residential area, 10% was land with shrubs, and the remaining 2% was water (lake/reservoir). The shortcoming of the methods was 25% of the land in the area was unidentified because it was covered by cloud. It is expected that future researchers involve cloud removal processing to minimize unidentified area.

Automatic mapping of event landslides at basin scale in Taiwan using a Montecarlo approach and synthetic land cover fingerprints

NASA Astrophysics Data System (ADS)

Mondini, Alessandro C.; Chang, Kang-Tsung; Chiang, Shou-Hao; Schlögel, Romy; Notarnicola, Claudia; Saito, Hitoshi

2017-12-01

We propose a framework to systematically generate event landslide inventory maps from satellite images in southern Taiwan, where landslides are frequent and abundant. The spectral information is used to assess the pixel land cover class membership probability through a Maximum Likelihood classifier trained with randomly generated synthetic land cover spectral fingerprints, which are obtained from an independent training images dataset. Pixels are classified as landslides when the calculated landslide class membership probability, weighted by a susceptibility model, is higher than membership probabilities of other classes. We generated synthetic fingerprints from two FORMOSAT-2 images acquired in 2009 and tested the procedure on two other images, one in 2005 and the other in 2009. We also obtained two landslide maps through manual interpretation. The agreement between the two sets of inventories is given by the Cohen's k coefficients of 0.62 and 0.64, respectively. This procedure can now classify a new FORMOSAT-2 image automatically facilitating the production of landslide inventory maps.

Best Hiding Capacity Scheme for Variable Length Messages Using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Bajaj, Ruchika; Bedi, Punam; Pal, S. K.

Steganography is an art of hiding information in such a way that prevents the detection of hidden messages. Besides security of data, the quantity of data that can be hidden in a single cover medium, is also very important. We present a secure data hiding scheme with high embedding capacity for messages of variable length based on Particle Swarm Optimization. This technique gives the best pixel positions in the cover image, which can be used to hide the secret data. In the proposed scheme, k bits of the secret message are substituted into k least significant bits of the image pixel, where k varies from 1 to 4 depending on the message length. The proposed scheme is tested and results compared with simple LSB substitution, uniform 4-bit LSB hiding (with PSO) for the test images Nature, Baboon, Lena and Kitty. The experimental study confirms that the proposed method achieves high data hiding capacity and maintains imperceptibility and minimizes the distortion between the cover image and the obtained stego image.

Land Cover Monitoring for Water Resources Management in Angola

NASA Astrophysics Data System (ADS)

Miguel, Irina; Navarro, Ana; Rolim, Joao; Catalao, Joao; Silva, Joel; Painho, Marco; Vekerdy, Zoltan

2016-08-01

The aim of this paper is to assess the impact of improved temporal resolution and multi-source satellite data (SAR and optical) on land cover mapping and monitoring for efficient water resources management. For that purpose, we developed an integrated approach based on image classification and on NDVI and SAR backscattering (VV and VH) time series for land cover mapping and crop's irrigation requirements computation. We analysed 28 SPOT-5 Take-5 images with high temporal revisiting time (5 days), 9 Sentinel-1 dual polarization GRD images and in-situ data acquired during the crop growing season. Results show that the combination of images from different sources provides the best information to map agricultural areas. The increase of the images temporal resolution allows the improvement of the estimation of the crop parameters, and then, to calculate of the crop's irrigation requirements. However, this aspect was not fully exploited due to the lack of EO data for the complete growing season.

Radiative forcing over the conterminous United States due to contemporary land cover land use albedo change

USGS Publications Warehouse

Barnes, Christopher; Roy, David P.

2008-01-01

Recently available satellite land cover land use (LCLU) and albedo data are used to study the impact of LCLU change from 1973 to 2000 on surface albedo and radiative forcing for 36 ecoregions covering 43% of the conterminous United States (CONUS). Moderate Resolution Imaging Spectroradiometer (MODIS) snow-free broadband albedo values are derived from Landsat LCLU classification maps located using a stratified random sampling methodology to estimate ecoregion estimates of LCLU induced albedo change and surface radiative forcing. The results illustrate that radiative forcing due to LCLU change may be disguised when spatially and temporally explicit data sets are not used. The radiative forcing due to contemporary LCLU albedo change varies geographically in sign and magnitude, with the most positive forcings (up to 0.284 Wm−2) due to conversion of agriculture to other LCLU types, and the most negative forcings (as low as −0.247 Wm−2) due to forest loss. For the 36 ecoregions considered a small net positive forcing (i.e., warming) of 0.012 Wm−2 is estimated.

DOE workshop: Sedimentary systems, aqueous and organic geochemistry

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

Not Available

1993-07-01

A DOE workshop on sedimentary systems, aqueous and organic geochemistry was held July 15-16, 1993 at Lawrence Berkeley Laboratory. Papers were organized into several sections: Fundamental Properties, containing papers on the thermodynamics of brines, minerals and aqueous electrolyte solutions; Geochemical Transport, covering 3-D imaging of drill core samples, hydrothermal geochemistry, chemical interactions in hydrocarbon reservoirs, fluid flow model application, among others; Rock-Water Interactions, with presentations on stable isotope systematics of fluid/rock interaction, fluid flow and petotectonic evolution, grain boundary transport, sulfur incorporation, tracers in geologic reservoirs, geothermal controls on oil-reservoir evolution, and mineral hydrolysis kinetics; Organic Geochemistry covered new methodsmore » for constraining time of hydrocarbon migration, kinetic models of petroleum formation, mudstones in burial diagenesis, compound-specific carbon isotope analysis of petroleums, stability of natural gas, sulfur in sedimentary organic matter, organic geochemistry of deep ocean sediments, direct speciation of metal by optical spectroscopies; and lastly, Sedimentary Systems, covering sequence stratigraphy, seismic reflectors and diagenetic changes in carbonates, geochemistry and origin of regional dolomites, and evidence of large comet or asteroid impacts at extinction boundaries.« less

Detection of irradiated quail meat by using DNA comet assay and evaluation of comets by image analysis

NASA Astrophysics Data System (ADS)

Erel, Yakup; Yazici, Nizamettin; Özvatan, Sumer; Ercin, Demet; Cetinkaya, Nurcan

2009-09-01

A simple technique of microgel electrophoresis of single cells (DNA comet assay) was used to detect DNA comets in irradiated quail meat samples. Obtained DNA comets were evaluated by both photomicrographic and image analysis. Quail meat samples were exposed to radiation doses of 0.52, 1.05, 1.45, 2.00, 2.92 and 4.00 kGy in gamma cell (gammacell 60Co, dose rate 1.31 kGy/h) covering the permissible limits for enzymatic decay and stored at 2 °C. The cells isolated from muscle (chest, thorax) in cold PBS were analyzed using the DNA comet assay on 1, 2, 3, 4, 7, 8 and 11 day post irradiation. The cells were lysed between 2, 5 and 9 min in 2.5% SDS and electrophorosis was carried out at a voltage of 2 V/cm for 2 min. After propidium iodide staining, the slides were evaluated through a fluorescent microscope. In all irradiated samples, fragmented DNA stretched towards the anode and damaged cells appeared as a comet. All measurement data were analyzed using BS 200 ProP with software image analysis (BS 200 ProP, BAB Imaging System, Ankara, Turkey). The density of DNA in the tails increased with increasing radiation dose. However, in non-irradiated samples, the large molecules of DNA remained relatively intact and there was only minor or no migration of DNA; the cells were round or had very short tails only. The values of tail DNA%, tail length and tail moment were significantly different and identical between 0.9 and 4.0 kGy dose exposure, and also among storage times on day 1, 4 and 8. In conclusion, the DNA Comet Assay EN 13784 standard method may be used not only for screening method for detection of irradiated quail meat depending on storage time and condition but also for the quantification of applied dose if it is combined with image analysis. Image analysis may provide a powerful tool for the evaluation of head and tail of comet intensity related with applied doses.

The Lyman Alpha Reference Sample. V. The Impact of Neutral ISM Kinematics and Geometry on Lyα Escape

NASA Astrophysics Data System (ADS)

Rivera-Thorsen, Thøger E.; Hayes, Matthew; Östlin, Göran; Duval, Florent; Orlitová, Ivana; Verhamme, Anne; Mas-Hesse, J. Miguel; Schaerer, Daniel; Cannon, John M.; Otí-Floranes, Héctor; Sandberg, Andreas; Guaita, Lucia; Adamo, Angela; Atek, Hakim; Herenz, E. Christian; Kunth, Daniel; Laursen, Peter; Melinder, Jens

2015-05-01

We present high-resolution far-UV spectroscopy of the 14 galaxies of the Lyα Reference Sample; a sample of strongly star-forming galaxies at low redshifts (0.028 < z < 0.18). We compare the derived properties to global properties derived from multi-band imaging and 21 cm H i interferometry and single-dish observations, as well as archival optical SDSS spectra. Besides the Lyα line, the spectra contain a number of metal absorption features allowing us to probe the kinematics of the neutral ISM and evaluate the optical depth and and covering fraction of the neutral medium as a function of line of sight velocity. Furthermore, we show how this, in combination with the precise determination of systemic velocity and good Lyα spectra, can be used to distinguish a model in which separate clumps together fully cover the background source, from the “picket fence” model named by Heckman et al. We find that no one single effect dominates in governing Lyα radiative transfer and escape. Lyα escape in our sample coincides with a maximum velocity-binned covering fraction of ≲0.9 and bulk outflow velocities of ≳50 km s-1, although a number of galaxies show these characteristics and yet little or no Lyα escape. We find that Lyα peak velocities, where available, are not consistent with a strong backscattered component, but rather with a simpler model of an intrinsic emission line overlaid by a blueshifted absorption profile from the outflowing wind. Finally, we find a strong anticorrelation between Hα equivalent width and maximum velocity-binned covering factor, and propose a heuristic explanatory model. Based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with programs GO 11522, GO 11727, GO 12027, and GO 12583.

Calibration and Validation of Tundra Plant Functional Type Fractional Cover Mapping

NASA Astrophysics Data System (ADS)

Macander, M. J.; Nelson, P.; Frost, G. V., Jr.

2017-12-01

Fractional cover maps are being developed for selected tundra plant functional types (PFTs) across >500,000 sq. km of arctic Alaska and adjacent Canada at 30 m resolution. Training and validation data include a field-based training dataset based on point-intercept sampling method at hundreds of plots spanning bioclimatic and geomorphic gradients. We also compiled 50 blocks of 1-5 cm resolution RGB image mosaics in Alaska (White Mountains, North Slope, and Yukon-Kuskokwim Delta) and the Yukon Territory. The mosaics and associated surface and canopy height models were developed using a consumer drone and structure from motion processing. We summarized both the in situ measurements and drone imagery to determine cover of two PFTs: Low and Tall Deciduous Shrub, and Light Fruticose/Foliose Lichen. We applied these data to train 2 m (limited extent) and 30 m (wall to wall) maps of PFT fractional cover for shrubs and lichen. Predictors for 2 m models were commercial satellite imagery such as WorldView-2 and Worldview-3, analyzed on the ABoVE Science Cloud. Predictors for 30 m models were primarily reflectance composites and spectral metrics developed from Landsat imagery, using Google Earth Engine. We compared the performance of models developed from the in situ and drone-derived training data and identify best practices to improve the performance and efficiency of arctic PFT fractional cover mapping.

Mystery #6 Answer

Atmospheric Science Data Center

2013-04-22

... title:  MISR Mystery Image Quiz #6: Brazil's Duck Lagoon     View Larger Image ... Imaging SpectroRadiometer (MISR) image of Brazil's Duck Lagoon covers an area of about 298 kilometers x 358 kilometers, and was ...

Comparison of AIS Versus TMS Data Collected over the Virginia Piedmont

NASA Technical Reports Server (NTRS)

Bell, R.; Evans, C. S.

1985-01-01

The Airborne Imaging Spectrometer (AIS, NS001 Thematic Mapper Simlulator (TMS), and Zeiss camera collected remotely sensed data simultaneously on October 27, 1983, at an altitude of 6860 meters (22,500 feet). AIS data were collected in 32 channels covering 1200 to 1500 nm. A simple atmospheric correction was applied to the AIS data, after which spectra for four cover types were plotted. Spectra for these ground cover classes showed a telescoping effect for the wavelength endpoints. Principal components were extracted from the shortwave region of the AIS (1200 to 1280 nm), full spectrum AIS (1200 to 1500 nm) and TMS (450 to 12,500 nm) to create three separate three-component color image composites. A comparison of the TMS band 5 (1000 to 1300 nm) to the six principal components from the shortwave AIS region (1200 to 1280 nm) showed improved visual discrimination of ground cover types. Contrast of color image composites created from principal components showed the AIS composites to exhibit a clearer demarcation between certain ground cover types but subtle differences within other regions of the imagery were not as readily seen.

Thrips (Thysanoptera: Thripidae) mitigation in seedling cotton using strip tillage and winter cover crops.

PubMed

Toews, Michael D; Tubbs, R Scott; Wann, Dylan Q; Sullivan, Dana

2010-10-01

Thrips are the most consistent insect pests of seedling cotton in the southeastern United States, where symptoms can range from leaf curling to stand loss. In a 2 year study, thrips adults and immatures were sampled at 14, 21 and 28 days after planting on cotton planted with a thiamethoxam seed treatment in concert with crimson clover, wheat or rye winter cover crops and conventional or strip tillage to investigate potential differences in thrips infestations. Densities of adult thrips, primarily Frankliniella fusca (Hinds), peaked on the first sampling date, whereas immature densities peaked on the second sampling date. Regardless of winter cover crop, plots that received strip tillage experienced significantly fewer thrips at each sampling interval. In addition, assessment of percentage ground cover 42 days after planting showed that there was more than twice as much ground cover in the strip-tilled plots compared with conventionally tilled plots. Correlation analyses showed that increased ground cover was inversely related to thrips densities that occurred on all three sampling dates in 2008 and the final sampling date in 2009. Growers who utilize strip tillage and a winter cover crop can utilize seed treatments for mitigation of early-season thrips infestation.

Heat Capacity Mapping Mission (HCMM): Interpretation of imagery over Canada

NASA Technical Reports Server (NTRS)

Cihlar, J. (Principal Investigator); Dixon, R. G.

1981-01-01

Visual analysis of HCMM images acquired over two sites in Canada and supporting aircraft and ground data obtained at a smaller subsite in Alberta show that nightime surface temperature distribution is primarily related to the near-surface air temperature; the effects of topography, wind, and land cover were low or indirect through air temperature. Surface cover and large altitudinal differences were important parameters influencing daytime apparent temperature values. A quantitative analysis of the relationship between the antecedent precipitation index and the satellite thermal IR measurements did not yield statistically significant correlation coefficients, but the correlations had a definite temporal trend which could be related to the increasing uniformity of vegetation cover. The large pixel size (resulting in a mixture of cover types and soil/canopy temperatures measured by the satellite) and high cloud cover frequency found in images covering both Canadian sites and northern U.S. were considered the main deficiencies of the thermal satellite data.

Generating land cover boundaries from remotely sensed data using object-based image analysis: overview and epidemiological application.

PubMed

Maxwell, Susan K

2010-12-01

Satellite imagery and aerial photography represent a vast resource to significantly enhance environmental mapping and modeling applications for use in understanding spatio-temporal relationships between environment and health. Deriving boundaries of land cover objects, such as trees, buildings, and crop fields, from image data has traditionally been performed manually using a very time consuming process of hand digitizing. Boundary detection algorithms are increasingly being applied using object-based image analysis (OBIA) technology to automate the process. The purpose of this paper is to present an overview and demonstrate the application of OBIA for delineating land cover features at multiple scales using a high resolution aerial photograph (1 m) and a medium resolution Landsat image (30 m) time series in the context of a pesticide spray drift exposure application. Copyright © 2010. Published by Elsevier Ltd.

BOREAS TE-18 Landsat TM Physical Classification Image of the NSA

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Knapp, David

2000-01-01

The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the NSA. A Landsat-5 TM image from 21-Jun-1995 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used in a way that is similar to training data to classify the image into the different land cover classes. The data are provided in a binary, image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

BOREAS TE-18 Landsat TM Physical Classification Image of the SSA

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Knapp, David

2000-01-01

The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the SSA. A Landsat-5 TM image from 02-Sep-1994 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used as training data to classify the image into the different land cover classes. These data are provided in a binary image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

Reversible integer wavelet transform for blind image hiding method

PubMed Central

Bibi, Nargis; Mahmood, Zahid; Akram, Tallha; Naqvi, Syed Rameez

2017-01-01

In this article, a blind data hiding reversible methodology to embed the secret data for hiding purpose into cover image is proposed. The key advantage of this research work is to resolve the privacy and secrecy issues raised during the data transmission over the internet. Firstly, data is decomposed into sub-bands using the integer wavelets. For decomposition, the Fresnelet transform is utilized which encrypts the secret data by choosing a unique key parameter to construct a dummy pattern. The dummy pattern is then embedded into an approximated sub-band of the cover image. Our proposed method reveals high-capacity and great imperceptibility of the secret embedded data. With the utilization of family of integer wavelets, the proposed novel approach becomes more efficient for hiding and retrieving process. It retrieved the secret hidden data from the embedded data blindly, without the requirement of original cover image. PMID:28498855

BOREAS TE-18 Landsat TM Maximum Likelihood Classification Image of the SSA

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Knapp, David

2000-01-01

The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the SSA. A Landsat-5 TM image from 02-Sep- 1994 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used as training data to classify the image into the different land cover classes. These data are provided in a binary image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC).

A Comparison of Local Variance, Fractal Dimension, and Moran's I as Aids to Multispectral Image Classification

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Sig-NganLam, Nina; Quattrochi, Dale A.

2004-01-01

The accuracy of traditional multispectral maximum-likelihood image classification is limited by the skewed statistical distributions of reflectances from the complex heterogenous mixture of land cover types in urban areas. This work examines the utility of local variance, fractal dimension and Moran's I index of spatial autocorrelation in segmenting multispectral satellite imagery. Tools available in the Image Characterization and Modeling System (ICAMS) were used to analyze Landsat 7 imagery of Atlanta, Georgia. Although segmentation of panchromatic images is possible using indicators of spatial complexity, different land covers often yield similar values of these indices. Better results are obtained when a surface of local fractal dimension or spatial autocorrelation is combined as an additional layer in a supervised maximum-likelihood multispectral classification. The addition of fractal dimension measures is particularly effective at resolving land cover classes within urbanized areas, as compared to per-pixel spectral classification techniques.

Development of an Independent Global Land Cover Validation Dataset

NASA Astrophysics Data System (ADS)

Sulla-Menashe, D. J.; Olofsson, P.; Woodcock, C. E.; Holden, C.; Metcalfe, M.; Friedl, M. A.; Stehman, S. V.; Herold, M.; Giri, C.

2012-12-01

Accurate information related to the global distribution and dynamics in global land cover is critical for a large number of global change science questions. A growing number of land cover products have been produced at regional to global scales, but the uncertainty in these products and the relative strengths and weaknesses among available products are poorly characterized. To address this limitation we are compiling a database of high spatial resolution imagery to support international land cover validation studies. Validation sites were selected based on a probability sample, and may therefore be used to estimate statistically defensible accuracy statistics and associated standard errors. Validation site locations were identified using a stratified random design based on 21 strata derived from an intersection of Koppen climate classes and a population density layer. In this way, the two major sources of global variation in land cover (climate and human activity) are explicitly included in the stratification scheme. At each site we are acquiring high spatial resolution (< 1-m) satellite imagery for 5-km x 5-km blocks. The response design uses an object-oriented hierarchical legend that is compatible with the UN FAO Land Cover Classification System. Using this response design, we are classifying each site using a semi-automated algorithm that blends image segmentation with a supervised RandomForest classification algorithm. In the long run, the validation site database is designed to support international efforts to validate land cover products. To illustrate, we use the site database to validate the MODIS Collection 4 Land Cover product, providing a prototype for validating the VIIRS Surface Type Intermediate Product scheduled to start operational production early in 2013. As part of our analysis we evaluate sources of error in coarse resolution products including semantic issues related to the class definitions, mixed pixels, and poor spectral separation between classes.

Mangroves in peril: unprecedented degradation rates of peri-urban mangroves in Kenya

NASA Astrophysics Data System (ADS)

Bosire, J. O.; Kaino, J. J.; Olagoke, A. O.; Mwihaki, L. M.; Ogendi, G. M.; Kairo, J. G.; Berger, U.; Macharia, D.

2014-05-01

Marine ecosystems are experiencing unprecedented degradation rates higher than any other ecosystem on the planet, which in some instances are up to 4 times those of rainforests. Mangrove ecosystems have especially been impacted by compounded anthropogenic pressures leading to significant cover reductions of between 35 and 50% (equivalent to 1-2% loss pa) for the last half century. The main objective of this study was to test the hypothesis that peri-urban mangroves suffering from compounded and intense pressures may be experiencing higher degradation rates than the global mean (and/or national mean for Kenya) using Mombasa mangroves (comprising Tudor and Mwache creeks) as a case study. Stratified sampling was used to sample along 22 and 10 belt transects in Mwache and Tudor respectively, set to capture stand heterogeneity in terms of species composition and structure in addition to perceived human pressure gradients using proximity to human habitations as a proxy. We acquired SPOT (HRV/ HRVIR/ HRS) images of April 1994, May 2000 and January 2009 and a vector mangrove map of 1992 at a scale of 1:50 000 for cover change and species composition analysis. Results from image classification of the 2009 image had 80.23% overall accuracy and Cohen's kappa of 0.77, thus proving satisfactory for use in this context. Structural data indicate that complexity index (CI) which captures stand structural development was higher in Mwache at 1.80 compared to Tudor at 1.71. From cover change data, Tudor lost 86.9% of the forest between 1992 and 2009, compared to Mwache at 45.4%, representing very high hitherto undocumented degradation rates of 5.1 and 2.7% pa, respectively. These unprecedentedly high degradation rates, which far exceed not only the national mean (for Kenya of 0.7% pa) but the global mean as well, strongly suggest that these mangroves are highly threatened due to compounded pressures. Strengthening of governance regimes through enforcement and compliance to halt illegal wood extraction, improvement of land-use practices upstream to reduce soil erosion, restoration in areas where natural regeneration has been impaired, provision of alternative energy sources/building materials and a complete moratorium on wood extraction especially in Tudor Creek to allow recovery are some of the suggested management interventions.

Managed Clearings: an Unaccounted Land-cover in Urbanizing Regions

NASA Astrophysics Data System (ADS)

Singh, K. K.; Madden, M.; Meentemeyer, R. K.

2016-12-01

Managed clearings (MC), such as lawns, public parks and grassy transportation medians, are a common and ecologically important land cover type in urbanizing regions, especially those characterized by sprawl. We hypothesize that MC is underrepresented in land cover classification schemes and data products such as NLCD (National Land Cover Database) data, which may impact environmental assessments and models of urban ecosystems. We visually interpreted and mapped fine scale land cover with special attention to MC using 2012 NAIP (National Agriculture Imagery Program) images and compared the output with NLCD data. Areas sampled were 50 randomly distributed 1*1km blocks of land in three cities of the Char-lanta mega-region (Atlanta, Charlotte, and Raleigh). We estimated the abundance of MC relative to other land cover types, and the proportion of land-cover types in NLCD data that are similar to MC. We also assessed if the designations of recreation, transportation, and utility in MC inform the problem differently than simply tallying MC as a whole. 610 ground points, collected using the Google Earth, were used to evaluate accuracy of NLCD data and visual interpretation for consistency. Overall accuracy of visual interpretation and NLCD data was 78% and 58%, respectively. NLCD data underestimated forest and MC by 14.4km2 and 6.4km2, respectively, while overestimated impervious surfaces by 10.2km2 compared to visual interpretation. MC was the second most dominant land cover after forest (40.5%) as it covered about 28% of the total area and about 13% higher than impervious surfaces. Results also suggested that recreation in MC constitutes up to 90% of area followed by transportation and utility. Due to the prevalence of MC in urbanizing regions, the addition of MC to the synthesis of land-cover data can help delineate realistic cover types and area proportions that could inform ecologic/hydrologic models, and allow for accurate prediction of ecological phenomena.

A Practical and Automated Approach to Large Area Forest Disturbance Mapping with Remote Sensing

PubMed Central

Ozdogan, Mutlu

2014-01-01

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions. PMID:24717283

A practical and automated approach to large area forest disturbance mapping with remote sensing.

PubMed

Ozdogan, Mutlu

2014-01-01

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions.

Renewable Portfolio Standards: Understanding Costs and Benefits | Energy

Science.gov Websites

considering the highest cost and lowest benefit outcomes. More Information: Fact Sheet Image of a report cover | Presentation Image of a report cover for A Survey of State-Level Cost and Benefit Estimates of Renewable Portfolio Standards: Understanding Costs and Benefits State policymakers, public utilities commissions, and

Image-based change estimation for land cover and land use monitoring

Treesearch

Jeremy Webb; C. Kenneth Brewer; Nicholas Daniels; Chris Maderia; Randy Hamilton; Mark Finco; Kevin A. Megown; Andrew J. Lister

2012-01-01

The Image-based Change Estimation (ICE) project resulted from the need to provide estimates and information for land cover and land use change over large areas. The procedure uses Forest Inventory and Analysis (FIA) plot locations interpreted using two different dates of imagery from the National Agriculture Imagery Program (NAIP). In order to determine a suitable...

Evaluation of search strategies for microcalcifications and masses in 3D images

NASA Astrophysics Data System (ADS)

Eckstein, Miguel P.; Lago, Miguel A.; Abbey, Craig K.

2018-03-01

Medical imaging is quickly evolving towards 3D image modalities such as computed tomography (CT), magnetic resonance imaging (MRI) and digital breast tomosynthesis (DBT). These 3D image modalities add volumetric information but further increase the need for radiologists to search through the image data set. Although much is known about search strategies in 2D images less is known about the functional consequences of different 3D search strategies. We instructed readers to use two different search strategies: drillers had their eye movements restricted to a few regions while they quickly scrolled through the image stack, scanners explored through eye movements the 2D slices. We used real-time eye position monitoring to ensure observers followed the drilling or the scanning strategy while approximately preserving the percentage of the volumetric data covered by the useful field of view. We investigated search for two signals: a simulated microcalcification and a larger simulated mass. Results show an interaction between the search strategy and lesion type. In particular, scanning provided significantly better detectability for microcalcifications at the cost of 5 times more time to search while there was little change in the detectability for the larger simulated masses. Analyses of eye movements support the hypothesis that the effectiveness of a search strategy in 3D imaging arises from the interaction of the fixational sampling of visual information and the signals' visibility in the visual periphery.

Imaging of shoulder instability

PubMed Central

Martínez Martínez, Alberto; Tomás Muñoz, Pablo; Pozo Sánchez, José; Zarza Pérez, Antonio

2017-01-01

This extended review tries to cover the imaging findings of the wide range of shoulder injuries secondary to shoulder joint instability. Usefulness of the different imaging methods is stressed, including radiography, computed tomography (CT) and magnetic resonance. The main topics to be covered include traumatic, atraumatic and minor instability syndromes. Radiography may show bone abnormalities associated to instability, including developmental and post-traumatic changes. CT is the best technique depicting and quantifying skeletal changes. MR-arthrography is the main tool in diagnosing the shoulder instability injuries. PMID:28932699

Optically Sectioned Imaging of Microvasculature of In-Vivo and Ex-Vivo Thick Tissue Models with Speckle-illumination HiLo Microscopy and HiLo Image Processing Implementation in MATLAB Architecture

NASA Astrophysics Data System (ADS)

Suen, Ricky Wai

The work described in this thesis covers the conversion of HiLo image processing into MATLAB architecture and the use of speckle-illumination HiLo microscopy for use of ex-vivo and in-vivo imaging of thick tissue models. HiLo microscopy is a wide-field fluorescence imaging technique and has been demonstrated to produce optically sectioned images comparable to confocal in thin samples. The imaging technique was developed by Jerome Mertz and the Boston University Biomicroscopy Lab and has been implemented in our lab as a stand-alone optical setup and a modification to a conventional fluorescence microscope. Speckle-illumination HiLo microscopy combines two images taken under speckle-illumination and standard uniform-illumination to generate an optically sectioned image that reject out-of-focus fluorescence. The evaluated speckle contrast in the images is used as a weighting function where elements that move out-of-focus have a speckle contrast that decays to zero. The experiments shown here demonstrate the capability of our HiLo microscopes to produce optically-sectioned images of the microvasculature of ex-vivo and in-vivo thick tissue models. The HiLo microscope were used to image the microvasculature of ex-vivo mouse heart sections prepared for optical histology and the microvasculature of in-vivo rodent dorsal window chamber models. Studies in label-free surface profiling with HiLo microscopy is also presented.

Space Shuttle Columbia views the world with imaging radar: The SIR-A experiment

NASA Technical Reports Server (NTRS)

Ford, J. P.; Cimino, J. B.; Elachi, C.

1983-01-01

Images acquired by the Shuttle Imaging Radar (SIR-A) in November 1981, demonstrate the capability of this microwave remote sensor system to perceive and map a wide range of different surface features around the Earth. A selection of 60 scenes displays this capability with respect to Earth resources - geology, hydrology, agriculture, forest cover, ocean surface features, and prominent man-made structures. The combined area covered by the scenes presented amounts to about 3% of the total acquired. Most of the SIR-A images are accompanied by a LANDSAT multispectral scanner (MSS) or SEASAT synthetic-aperture radar (SAR) image of the same scene for comparison. Differences between the SIR-A image and its companion LANDSAT or SEASAT image at each scene are related to the characteristics of the respective imaging systems, and to seasonal or other changes that occurred in the time interval between acquisition of the images.

A RONI Based Visible Watermarking Approach for Medical Image Authentication.

PubMed

Thanki, Rohit; Borra, Surekha; Dwivedi, Vedvyas; Borisagar, Komal

2017-08-09

Nowadays medical data in terms of image files are often exchanged between different hospitals for use in telemedicine and diagnosis. Visible watermarking being extensively used for Intellectual Property identification of such medical images, leads to serious issues if failed to identify proper regions for watermark insertion. In this paper, the Region of Non-Interest (RONI) based visible watermarking for medical image authentication is proposed. In this technique, to RONI of the cover medical image is first identified using Human Visual System (HVS) model. Later, watermark logo is visibly inserted into RONI of the cover medical image to get watermarked medical image. Finally, the watermarked medical image is compared with the original medical image for measurement of imperceptibility and authenticity of proposed scheme. The experimental results showed that this proposed scheme reduces the computational complexity and improves the PSNR when compared to many existing schemes.

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.

PubMed

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

Enhanced Deforestation Mapping in North Korea using Spatial-temporal Image Fusion Method and Phenology-based Index

NASA Astrophysics Data System (ADS)

Jin, Y.; Lee, D.

2017-12-01

North Korea (the Democratic People's Republic of Korea, DPRK) is known to have some of the most degraded forest in the world. The characteristics of forest landscape in North Korea is complex and heterogeneous, the major vegetation cover types in the forest are hillside farm, unstocked forest, natural forest, and plateau vegetation. Better classification of types in high spatial resolution of deforested areas could provide essential information for decisions about forest management priorities and restoration of deforested areas. For mapping heterogeneous vegetation covers, the phenology-based indices are helpful to overcome the reflectance value confusion that occurs when using one season images. Coarse spatial resolution images may be acquired with a high repetition rate and it is useful for analyzing phenology characteristics, but may not capture the spatial detail of the land cover mosaic of the region of interest. Previous spatial-temporal fusion methods were only capture the temporal change, or focused on both temporal change and spatial change but with low accuracy in heterogeneous landscapes and small patches. In this study, a new concept for spatial-temporal image fusion method focus on heterogeneous landscape was proposed to produce fine resolution images at both fine spatial and temporal resolution. We classified the three types of pixels between the base image and target image, the first type is only reflectance changed caused by phenology, this type of pixels supply the reflectance, shape and texture information; the second type is both reflectance and spectrum changed in some bands caused by phenology like rice paddy or farmland, this type of pixels only supply shape and texture information; the third type is reflectance and spectrum changed caused by land cover type change, this type of pixels don't provide any information because we can't know how land cover changed in target image; and each type of pixels were applied different prediction methods. Results show that both STARFM and FSDAF predicted in low accuracy in second type pixels and small patches. Classification results used spatial-temporal image fusion method proposed in this study showed overall classification accuracy of 89.38%, with corresponding kappa coefficients of 0.87.

The Hyperspectral Imager for the Coastal Ocean (HICO): Four Years Operating on the International Space Station (Invited)

NASA Astrophysics Data System (ADS)

Davis, C. O.; Nahorniak, J.; Tufillaro, N.; Kappus, M.

2013-12-01

The Hyperspectral Imager for the Coastal Ocean (HICO) is the first spaceborne imaging spectrometer designed to sample the coastal ocean. HICO images selected coastal regions at 92 m spatial resolution with full spectral coverage (88 channels covering 400 to 900 nm) and a high signal-to-noise ratio to resolve the complexity of the coastal ocean. Under sponsorship of the Office of Naval Research, HICO was built by the Naval Research Laboratory, which continues to operate the sensor. HICO has been operating on the International Space Station since October 2009 and has collected over 8000 scenes for more than 50 users. As Project Scientist I have been the link to the international ocean optics community primarily through our OSU HICO website (http://hico.oregonstate.edu). HICO operations are now under NASA support and HICO data is now also be available through the NASA Ocean Color Website (http://oceancolor.gsfc.nasa.gov ). Here we give a brief overview of HICO data and operations and discuss the unique challenges and opportunities that come from operating on the International Space Station.

[Presentation of age(ing) and elderly people in TV commercials].

PubMed

Hoppe, Theresa; Tischer, Ulrike; Philippsen, Christine; Hartmann-Tews, Ilse

2016-06-01

From the results of different studies it is known that stereotyped images about ageing and elderly people frame and influence the attitudes, beliefs and activities of elderly people and also influence the interaction of others with elderly people. The purpose of this study was to assess the currently portrayed images of elderly people, age and ageing in television (TV) advertisements. The study was based on a qualitative and quantitative content analysis of commercials presented on four major TV networks, two private and two public TV broadcasting networks in Germany. The sample covered 114 different commercials which included 131 elderly actors (approximately 50 + years). The results show that the products most often portrayed in commercials with elderly people are related to food, followed by prescription drugs and health, insurance and hygiene products. Elderly people are still underrepresented in TV commercials. Their characters are portrayed with overwhelmingly positive attributes and traits. The findings suggest that TV advertisements create an ideal image of active and healthy ageing. Further research might explore to what extent elderly people take this ideal image of ageing as their own interpretive frame of orientation.

On the Role of Urban and Vegetative Land Cover in the Identification of Tornado Damage Using Dual-Resolution Multispectral Satellite Imagery

NASA Astrophysics Data System (ADS)

Kingfield, D.; de Beurs, K.

2014-12-01

It has been demonstrated through various case studies that multispectral satellite imagery can be utilized in the identification of damage caused by a tornado through the change detection process. This process involves the difference in returned surface reflectance between two images and is often summarized through a variety of ratio-based vegetation indices (VIs). Land cover type plays a large contributing role in the change detection process as the reflectance properties of vegetation can vary based on several factors (e.g. species, greenness, density). Consequently, this provides the possibility for a variable magnitude of loss, making certain land cover regimes less reliable in the damage identification process. Furthermore, the tradeoff between sensor resolution and orbital return period may also play a role in the ability to detect catastrophic loss. Moderate resolution imagery (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS)) provides relatively coarse surface detail with a higher update rate which could hinder the identification of small regions that underwent a dynamic change. Alternatively, imagery with higher spatial resolution (e.g. Landsat) have a longer temporal return period between successive images which could result in natural recovery underestimating the absolute magnitude of damage incurred. This study evaluates the role of land cover type and sensor resolution on four high-end (EF3+) tornado events occurring in four different land cover groups (agriculture, forest, grassland, urban) in the spring season. The closest successive clear images from both Landsat 5 and MODIS are quality controlled for each case. Transacts of surface reflectance across a homogenous land cover type both inside and outside the damage swath are extracted. These metrics are synthesized through the calculation of six different VIs to rank the calculated change metrics by land cover type, sensor resolution and VI.

Design, Development and Testing of Web Services for Multi-Sensor Snow Cover Mapping

NASA Astrophysics Data System (ADS)

Kadlec, Jiri

This dissertation presents the design, development and validation of new data integration methods for mapping the extent of snow cover based on open access ground station measurements, remote sensing images, volunteer observer snow reports, and cross country ski track recordings from location-enabled mobile devices. The first step of the data integration procedure includes data discovery, data retrieval, and data quality control of snow observations at ground stations. The WaterML R package developed in this work enables hydrologists to retrieve and analyze data from multiple organizations that are listed in the Consortium of Universities for the Advancement of Hydrologic Sciences Inc (CUAHSI) Water Data Center catalog directly within the R statistical software environment. Using the WaterML R package is demonstrated by running an energy balance snowpack model in R with data inputs from CUAHSI, and by automating uploads of real time sensor observations to CUAHSI HydroServer. The second step of the procedure requires efficient access to multi-temporal remote sensing snow images. The Snow Inspector web application developed in this research enables the users to retrieve a time series of fractional snow cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) for any point on Earth. The time series retrieval method is based on automated data extraction from tile images provided by a Web Map Tile Service (WMTS). The average required time for retrieving 100 days of data using this technique is 5.4 seconds, which is significantly faster than other methods that require the download of large satellite image files. The presented data extraction technique and space-time visualization user interface can be used as a model for working with other multi-temporal hydrologic or climate data WMTS services. The third, final step of the data integration procedure is generating continuous daily snow cover maps. A custom inverse distance weighting method has been developed to combine volunteer snow reports, cross-country ski track reports and station measurements to fill cloud gaps in the MODIS snow cover product. The method is demonstrated by producing a continuous daily time step snow presence probability map dataset for the Czech Republic region. The ability of the presented methodology to reconstruct MODIS snow cover under cloud is validated by simulating cloud cover datasets and comparing estimated snow cover to actual MODIS snow cover. The percent correctly classified indicator showed accuracy between 80 and 90% using this method. Using crowdsourcing data (volunteer snow reports and ski tracks) improves the map accuracy by 0.7--1.2%. The output snow probability map data sets are published online using web applications and web services. Keywords: crowdsourcing, image analysis, interpolation, MODIS, R statistical software, snow cover, snowpack probability, Tethys platform, time series, WaterML, web services, winter sports.

Collecting and Animating Online Satellite Images.

ERIC Educational Resources Information Center

Irons, Ralph

1995-01-01

Describes how to generate automated classroom resources from the Internet. Topics covered include viewing animated satellite weather images using file transfer protocol (FTP); sources of images on the Internet; shareware available for viewing images; software for automating image retrieval; procedures for animating satellite images; and storing…

Spectral signature of alpine snow cover from the Landsat Thematic Mapper

NASA Technical Reports Server (NTRS)

Dozier, Jeff

1989-01-01

In rugged terrain, snow in the shadows can appear darker than soil or vegetation in the sunlight, making it difficult to interpret satellite data images of rugged terrains. This paper discusses methods for using Thematic Mapper (TM) and SPOT data for automatic analyses of alpine snow cover. Typical spectral signatures of the Landsat TM are analyzed for a range of snow types, atmospheric profiles, and topographic illumination conditions. A number of TM images of Sierra Nevada are analyzed to distinguish several classes of snow from other surface covers.

Automated image processing of Landsat II digital data for watershed runoff prediction

NASA Technical Reports Server (NTRS)

Sasso, R. R.; Jensen, J. R.; Estes, J. E.

1977-01-01

Digital image processing of Landsat data from a 230 sq km area was examined as a possible means of generating soil cover information for use in the watershed runoff prediction of Kern County, California. The soil cover information included data on brush, grass, pasture lands and forests. A classification accuracy of 94% for the Landsat-based soil cover survey suggested that the technique could be applied to the watershed runoff estimate. However, problems involving the survey of complex mountainous environments may require further attention

ASTER First Views of Rift Valley, Ethiopia - Thermal-Infrared TIR Image color

NASA Image and Video Library

2000-03-11

This image is a color composite covering the Rift Valley inland area of Ethiopia (south of the region shown in PIA02452). The color difference of this image reflects the distribution of different rocks with different amounts of silicon dioxide. It is inferred that the area with whitish color is covered with basalt and the pinkish area in the center contain sandesite. This is the first spaceborne, multi-band TIR image in history that enables geologists to distinguish between rocks with similar compositions. The size of image: 60 km x 60 km approx., ground resolution 90 m x 90 m approximately. http://photojournal.jpl.nasa.gov/catalog/PIA02453

Analysing land cover and land use change in the Matobo National Park and surroundings in Zimbabwe

NASA Astrophysics Data System (ADS)

Scharsich, Valeska; Mtata, Kupakwashe; Hauhs, Michael; Lange, Holger; Bogner, Christina

2016-04-01

Natural forests are threatened worldwide, therefore their protection in National Parks is essential. Here, we investigate how this protection status affects the land cover. To answer this question, we analyse the surface reflectance of three Landsat images of Matobo National Park and surrounding in Zimbabwe from 1989, 1998 and 2014 to detect changes in land cover in this region. To account for the rolling countryside and the resulting prominent shadows, a topographical correction of the surface reflectance was required. To infer land cover changes it is not only necessary to have some ground data for the current satellite images but also for the old ones. In particular for the older images no recent field study could help to reconstruct these data reliably. In our study we follow the idea that land cover classes of pixels in current images can be transferred to the equivalent pixels of older ones if no changes occurred meanwhile. Therefore we combine unsupervised clustering with supervised classification as follows. At first, we produce a land cover map for 2014. Secondly, we cluster the images with clara, which is similar to k-means, but suitable for large data sets. Whereby the best number of classes were determined to be 4. Thirdly, we locate unchanged pixels with change vector analysis in the images of 1989 and 1998. For these pixels we transfer the corresponding cluster label from 2014 to 1989 and 1998. Subsequently, the classified pixels serve as training data for supervised classification with random forest, which is carried out for each image separately. Finally, we derive land cover classes from the Landsat image in 2014, photographs and Google Earth and transfer them to the other two images. The resulting classes are shrub land; forest/shallow waters; bare soils/fields with some trees/shrubs; and bare light soils/rocks, fields and settlements. Subsequently the three different classifications are compared and land changes are mapped. The main changes are observable in the surroundings of the National Park, especially the common lands have lost their clear boundaries with time. In the National Park, the area of forest increases from 1989 to 2014 from 58% to 61% whereas the area of shrub land decreases by the same amount. The amount of each of the other two classes remains constant. These changes indicate an actual effect of the protection status of the National Park. In our study remote sensing data are the main source to evaluate the effects and the benefits of a protected area without on-side studies. This could be important for regions, where field studies are not possible because of insecure political conditions and only remote sensing data are available.

Spiral Imaging in fMRI

PubMed Central

Glover, Gary H.

2011-01-01

T2*-weighted Blood Oxygen Level Dependent (BOLD) functional magnetic resonance imaging (fMRI) requires efficient acquisition methods in order to fully sample the brain in a several second time period. The most widely used approach is Echo Planar Imaging (EPI), which utilizes a Cartesian trajectory to cover k-space. This trajectory is subject to ghosts from off-resonance and gradient imperfections and is intrinsically sensitive to cardiac-induced pulsatile motion from substantial first- and higher order moments of the gradient waveform near the k-space origin. In addition, only the readout direction gradient contributes significant energy to the trajectory. By contrast, the Spiral method samples k-space with an Archimedean or similar trajectory that begins at the k-space center and spirals to the edge (Spiral-out), or its reverse, ending at the origin (Spiral-in). Spiral methods have reduced sensitivity to motion, shorter readout times, improved signal recovery in most frontal and parietal brain regions, and exhibit blurring artifacts instead of ghosts or geometric distortion. Methods combining Spiral-in and Spiral-out trajectories have further advantages in terms of diminished susceptibility-induced signal dropout and increased BOLD signal. In measurements of temporal signal to noise ratio measured in 8 subjects, Spiral-in/out exhibited significant increases over EPI in voxel volumes recovered in frontal and whole brain regions (18% and 10%, respectively). PMID:22036995

Wide spectral-range imaging spectroscopy of photonic crystal microbeads for multiplex biomolecular assay applications

NASA Astrophysics Data System (ADS)

Li, Jianping

2014-05-01

Suspension assay using optically color-encoded microbeads is a novel way to increase the reaction speed and multiplex of biomolecular detection and analysis. To boost the detection speed, a hyperspectral imaging (HSI) system is of great interest for quickly decoding the color codes of the microcarriers. Imaging Fourier transform spectrometer (IFTS) is a potential candidate for this task due to its advantages in HSI measurement. However, conventional IFTS is only popular in IR spectral bands because it is easier to track its scanning mirror position in longer wavelengths so that the fundamental Nyquist criterion can be satisfied when sampling the interferograms; the sampling mechanism for shorter wavelengths IFTS used to be very sophisticated, high-cost and bulky. In order to overcome this handicap and take better usage of its advantages for HSI applications, a new wide spectral range IFTS platform is proposed based on an optical beam-folding position-tracking technique. This simple technique has successfully extended the spectral range of an IFTS to cover 350-1000nm. Test results prove that the system has achieved good spectral and spatial resolving performances with instrumentation flexibilities. Accurate and fast measurement results on novel colloidal photonic crystal microbeads also demonstrate its practical potential for high-throughput and multiplex suspension molecular assays.

Continuous Grading of Early Fibrosis in NAFLD Using Label-Free Imaging: A Proof-of-Concept Study.

PubMed

Pirhonen, Juho; Arola, Johanna; Sädevirta, Sanja; Luukkonen, Panu; Karppinen, Sanna-Maria; Pihlajaniemi, Taina; Isomäki, Antti; Hukkanen, Mika; Yki-Järvinen, Hannele; Ikonen, Elina

2016-01-01

Early detection of fibrosis is important in identifying individuals at risk for advanced liver disease in non-alcoholic fatty liver disease (NAFLD). We tested whether second-harmonic generation (SHG) and coherent anti-Stokes Raman scattering (CARS) microscopy, detecting fibrillar collagen and fat in a label-free manner, might allow automated and sensitive quantification of early fibrosis in NAFLD. We analyzed 32 surgical biopsies from patients covering histological fibrosis stages 0-4, using multimodal label-free microscopy. Native samples were visualized by SHG and CARS imaging for detecting fibrillar collagen and fat. Furthermore, we developed a method for quantitative assessment of early fibrosis using automated analysis of SHG signals. We found that the SHG mean signal intensity correlated well with fibrosis stage and the mean CARS signal intensity with liver fat. Little overlap in SHG signal intensities between fibrosis stages 0 and 1 was observed. A specific fibrillar SHG signal was detected in the liver parenchyma outside portal areas in all samples histologically classified as having no fibrosis. This signal correlated with immunohistochemical location of fibrillar collagens I and III. This study demonstrates that label-free SHG imaging detects fibrillar collagen deposition in NAFLD more sensitively than routine histological staging and enables observer-independent quantification of early fibrosis in NAFLD with continuous grading.

Design considerations for highly effective fluorescence excitation and detection optical systems for molecular diagnostics

NASA Astrophysics Data System (ADS)

Kasper, Axel; Van Hille, Herbert; Kuk, Sola

2018-02-01

Modern instruments for molecular diagnostics are continuously optimized for diagnostic accuracy, versatility and throughput. The latest progress in LED technology together with tailored optics solutions allows developing highly efficient photonics engines perfectly adapted to the sample under test. Super-bright chip-on-board LED light sources are a key component for such instruments providing maximum luminous intensities in a multitude of narrow spectral bands. In particular the combination of white LEDs with other narrow band LEDs allows achieving optimum efficiency outperforming traditional Xenon light sources in terms of energy consumption, heat dissipation in the system, and switching time between spectral channels. Maximum sensitivity of the diagnostic system can only be achieved with an optimized optics system for the illumination and imaging of the sample. The illumination beam path must be designed for optimum homogeneity across the field while precisely limiting the angular distribution of the excitation light. This is a necessity for avoiding spill-over to the detection beam path and guaranteeing the efficiency of the spectral filtering. The imaging optics must combine high spatial resolution, high light collection efficiency and optimized suppression of excitation light for good signal-to-noise ratio. In order to achieve minimum cross-talk between individual wells in the sample, the optics design must also consider the generation of stray light and the formation of ghost images. We discuss what parameters and limitations have to be considered in an integrated system design approach covering the full path from the light source to the detector.

Net Changes in Above Ground Woody Carbon Stock in Western Juniper Woodlands using Wavelet Techniques and Multi-temporal Aerial Photography

NASA Astrophysics Data System (ADS)

Strand, E. K.; Bunting, S. C.; Smith, A. M.

2006-12-01

Expansion of woody plant cover in semi-arid ecosystems previously occupied primarily by grasses and forbs has been identified as an important land cover change process affecting the global carbon budget. Although woody encroachment occurs worldwide, quantifying changes in carbon pools and fluxes related to this phenomenon via remote sensing is challenging because large areas are affected at a fine spatial resolution (1- 10 m) and, in many cases, at slow temporal rates. Two-dimensional spatial wavelet analysis (SWA) represents a novel image processing technique that has been successful in automatically and objectively quantifying ecologically relevant features at multiple scales. We apply SWA to current and historic 1-m resolution black and white aerial photography to quantify changes in above ground woody biomass and carbon stock of western juniper (Juniperus occidentalis subsp. occidentalis) expanding into sagebrush (Artemisia spp.) steppe on the Owyhee Plateau in southwestern Idaho. Due to the large land area (330,000 ha) and variable availability of historical photography, we sampled forty-eight 100-ha blocks situated across the area, stratified using topographic, soil, and land stewardship variables. The average juniper plant cover increased one-fold (from 5.3% to 10.4% total cover) at the site during the time period of 1939-1946 to 1998-2004. Juniper plant density has increased by 128% with a higher percentage of the plant population in the smaller size classes compared to the size distribution 60 years ago. After image-based SWA delineation of tree crown sizes, we computed the change in above ground woody plant biomass and carbon stock between the two time periods using allometry. Areas where the shrub steppe is dominated by low sagebrush (Artemisia arbuscula) has experienced little to no expansion of western juniper. However, on deeper, more well drained soils capable of supporting mountain big sagebrush (Artemisia tridentata subsp. vaseyana), the above ground carbon stock has increased on average 4.1 ±0.6 gCm-2yr-1, with rates varying spatially from 0.3 to 9.9 gCm- 2yr-1. Within the sampled elevation range (1500-1900 m) we found no significant effect of altitude or topographic position on the accumulation of biomass and carbon over the time period of investigation. The research presented here demonstrates the considerable potential for this remote sensing technique in decadal- scale monitoring of change in vegetation structure, cover, and biogeochemical properties from the scale of the plant to the landscape.

Point Intercept (PO)

Treesearch

John F. Caratti

2006-01-01

The FIREMON Point Intercept (PO) method is used to assess changes in plant species cover or ground cover for a macroplot. This method uses a narrow diameter sampling pole or sampling pins, placed at systematic intervals along line transects to sample within plot variation and quantify statistically valid changes in plant species cover and height over time. Plant...

Determining the best phenological state for accurate mapping of Phragmites australis in wetlands using time series multispectral satellite data

NASA Astrophysics Data System (ADS)

Rupasinghe, P. A.; Markle, C. E.; Marcaccio, J. V.; Chow-Fraser, P.

2017-12-01

Phragmites australis (European common reed), is a relatively recent invader of wetlands and beaches in Ontario. It can establish large homogenous stands within wetlands and disperse widely throughout the landscape by wind and vehicular traffic. A first step in managing this invasive species includes accurate mapping and quantification of its distribution. This is challenging because Phragimtes is distributed in a large spatial extent, which makes the mapping more costly and time consuming. Here, we used freely available multispectral satellite images taken monthly (cloud free images as available) for the calendar year to determine the optimum phenological state of Phragmites that would allow it to be accurately identified using remote sensing data. We analyzed time series, Landsat-8 OLI and Sentinel-2 images for Big Creek Wildlife Area, ON using image classification (Support Vector Machines), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). We used field sampling data and high resolution image collected using Unmanned Aerial Vehicle (UAV; 8 cm spatial resolution) as training data and for the validation of the classified images. The accuracy for all land cover classes and for Phragmites alone were low at both the start and end of the calendar year, but reached overall accuracy >85% by mid to late summer. The highest classification accuracies for Landsat-8 OLI were associated with late July and early August imagery. We observed similar trends using the Sentinel-2 images, with higher overall accuracy for all land cover classes and for Phragmites alone from late July to late September. During this period, we found the greatest difference between Phragmites and Typha, commonly confused classes, with respect to near-infrared and shortwave infrared reflectance. Therefore, the unique spectral signature of Phragmites can be attributed to both the level of greenness and factors related to water content in the leaves during late summer. Landsat-8 OLI or Sentinel-2 images acquired in late summer can be used as a cost effective approach to mapping Phragmites at a large spatial scale without sacrificing accuracy.

Temperature dependent BRDF facility

NASA Astrophysics Data System (ADS)

Airola, Marc B.; Brown, Andrea M.; Hahn, Daniel V.; Thomas, Michael E.; Congdon, Elizabeth A.; Mehoke, Douglas S.

2014-09-01

Applications involving space based instrumentation and aerodynamically heated surfaces often require knowledge of the bi-directional reflectance distribution function (BRDF) of an exposed surface at high temperature. Addressing this need, the Johns Hopkins University Applied Physics Laboratory (JHU/APL) developed a BRDF facility that features a multiple-port vacuum chamber, multiple laser sources covering the spectral range from the longwave infrared to the ultraviolet, imaging pyrometry and laser heated samples. Laser heating eliminates stray light that would otherwise be seen from a furnace and requires minimal sample support structure, allowing low thermal conduction loss to be obtained, which is especially important at high temperatures. The goal is to measure the BRDF of ceramic-coated surfaces at temperatures in excess of 1000°C in a low background environment. Most ceramic samples are near blackbody in the longwave infrared, thus pyrometry using a LWIR camera can be very effective and accurate.

Developed land cover of Puerto Rico

Treesearch

William A. Gould; Sebastian Martinuzzi; Olga M. Ramos Gonzalez

2008-01-01

This map shows the distribution of developed land cover in Puerto Rico (Martinuzzi et al. 2007). Developed land cover refers to urban, built-up and non-vegetated areas that result from human activity. These typically include built structures, concrete, asphalt, and other infrastructure. The developed land cover was estimated using Landsat 7 ETM+ satellite images pan...

Is the hijab protective? An investigation of body image and related constructs among British Muslim women.

PubMed

Swami, Viren; Miah, Jusnara; Noorani, Nazerine; Taylor, Donna

2014-08-01

Previous studies have reported equivocal findings concerning the impact of wearing a hijab, or Islamic head- and body-cover, on Muslim women's body image. Here, we sought to examine that impact using a larger sample of Muslim women than has been relied upon and a wider range of body image measures. A total of 587 British Muslim women completed a battery of scales assessing their frequency and conservativeness of hijab use, body image variables, attitudes towards the media and beauty ideals, importance of appearance, and religiosity. Preliminary results indicated that 218 women never used the hijab and 369 women used some form of the hijab at least rarely. Controlling for religiosity, women who wore the hijab had more positive body image, lower internalization of media messages about beauty standards, and placed less importance on appearance than women who did not wear the hijab. Among women who wore the hijab, hijab use significantly predicted weight discrepancy and body appreciation over and above religiosity. These results are discussed in terms of the possible protective impact among British Muslim women of wearing the hijab. © 2013 The British Psychological Society.

Estimation of canopy attributes in beech forests using true colour digital images from a small fixed-wing UAV

NASA Astrophysics Data System (ADS)

Chianucci, Francesco; Disperati, Leonardo; Guzzi, Donatella; Bianchini, Daniele; Nardino, Vanni; Lastri, Cinzia; Rindinella, Andrea; Corona, Piermaria

2016-05-01

Accurate estimates of forest canopy are essential for the characterization of forest ecosystems. Remotely-sensed techniques provide a unique way to obtain estimates over spatially extensive areas, but their application is limited by the spectral and temporal resolution available from these systems, which is often not suited to meet regional or local objectives. The use of unmanned aerial vehicles (UAV) as remote sensing platforms has recently gained increasing attention, but their applications in forestry are still at an experimental stage. In this study we described a methodology to obtain rapid and reliable estimates of forest canopy from a small UAV equipped with a commercial RGB camera. The red, green and blue digital numbers were converted to the green leaf algorithm (GLA) and to the CIE L*a*b* colour space to obtain estimates of canopy cover, foliage clumping and leaf area index (L) from aerial images. Canopy attributes were compared with in situ estimates obtained from two digital canopy photographic techniques (cover and fisheye photography). The method was tested in beech forests. UAV images accurately quantified canopy cover even in very dense stand conditions, despite a tendency to not detecting small within-crown gaps in aerial images, leading to a measurement of a quantity much closer to crown cover estimated from in situ cover photography. Estimates of L from UAV images significantly agreed with that obtained from fisheye images, but the accuracy of UAV estimates is influenced by the appropriate assumption of leaf angle distribution. We concluded that true colour UAV images can be effectively used to obtain rapid, cheap and meaningful estimates of forest canopy attributes at medium-large scales. UAV can combine the advantage of high resolution imagery with quick turnaround series, being therefore suitable for routine forest stand monitoring and real-time applications.

Investigating Mars: Coprates Chasma

NASA Image and Video Library

2017-09-29

Coprates Chasma is one of the numerous canyons that make up Valles Marineris. The chasma stretches for 960 km (600 miles) from Melas Chasma to the west and Capri Chasma to the east. Landslide deposits, layered materials and sand dunes cover a large portion of the chasma floor. This image is located in central Coprates Chasma. The floor of the chasma is covered by a complex deposit of material. This chaotic surface differs from most of the floor of the canyon and indicate a local process, perhaps a very large landslide or failure of the cliff face. The Odyssey spacecraft has spent over 15 years in orbit around Mars, circling the planet more than 69000 times. It holds the record for longest working spacecraft at Mars. THEMIS, the IR/VIS camera system, has collected data for the entire mission and provides images covering all seasons and lighting conditions. Over the years many features of interest have received repeated imaging, building up a suite of images covering the entire feature. From the deepest chasma to the tallest volcano, individual dunes inside craters and dune fields that encircle the north pole, channels carved by water and lava, and a variety of other feature, THEMIS has imaged them all. For the next several months the image of the day will focus on the Tharsis volcanoes, the various chasmata of Valles Marineris, and the major dunes fields. We hope you enjoy these images! Orbit Number: 27086 Latitude: -13.564 Longitude: 300.618 Instrument: VIS Captured: 2008-01-22 12:04 https://photojournal.jpl.nasa.gov/catalog/PIA21994

Phenopix: a R package to process digital images of a vegetation cover

NASA Astrophysics Data System (ADS)

Filippa, Gianluca; Cremonese, Edoardo; Migliavacca, Mirco; Galvagno, Marta; Morra di Cella, Umberto; Richardson, Andrew

2015-04-01

Plant phenology is a globally recognized indicator of the effects of climate change on the terrestrial biosphere. Accordingly, new tools to automatically track the seasonal development of a vegetation cover are becoming available and more and more deployed. Among them, near-continuous digital images are being collected in several networks in the US, Europe, Asia and Australia in a range of different ecosystems, including agricultural lands, deciduous and evergreen forests, and grasslands. The growing scientific interest in vegetation image analysis highlights the need of easy to use, flexible and standardized processing techniques. In this contribution we illustrate a new open source package called "phenopix" written in R language that allows to process images of a vegetation cover. The main features include: (i) define of one or more areas of interest on an image and process pixel information within them, (ii) compute vegetation indexes based on red green and blue channels, (iii) fit a curve to the seasonal trajectory of vegetation indexes and extract relevant dates (aka thresholds) on the seasonal trajectory; (iv) analyze image pixels separately to extract spatially explicit phenological information. The utilities of the package will be illustrated in detail for two subalpine sites, a grassland and a larch stand at about 2000 m in the Italian Western Alps. The phenopix package is a cost free and easy-to-use tool that allows to process digital images of a vegetation cover in a standardized, flexible and reproducible way. The software is available for download at the R forge web site (r-forge.r-project.org/projects/phenopix/).

Analysis of MODIS snow cover time series over the alpine regions as input for hydrological modeling

NASA Astrophysics Data System (ADS)

Notarnicola, Claudia; Rastner, Philipp; Irsara, Luca; Moelg, Nico; Bertoldi, Giacomo; Dalla Chiesa, Stefano; Endrizzi, Stefano; Zebisch, Marc

2010-05-01

Snow extent and relative physical properties are key parameters in hydrology, weather forecast and hazard warning as well as in climatological models. Satellite sensors offer a unique advantage in monitoring snow cover due to their temporal and spatial synoptic view. The Moderate Resolution Imaging Spectrometer (MODIS) from NASA is especially useful for this purpose due to its high frequency. However, in order to evaluate the role of snow on the water cycle of a catchment such as runoff generation due to snowmelt, remote sensing data need to be assimilated in hydrological models. This study presents a comparison on a multi-temporal basis between snow cover data derived from (1) MODIS images, (2) LANDSAT images, and (3) predictions by the hydrological model GEOtop [1,3]. The test area is located in the catchment of the Matscher Valley (South Tyrol, Northern Italy). The snow cover maps derived from MODIS-images are obtained using a newly developed algorithm taking into account the specific requirements of mountain regions with a focus on the Alps [2]. This algorithm requires the standard MODIS-products MOD09 and MOD02 as input data and generates snow cover maps at a spatial resolution of 250 m. The final output is a combination of MODIS AQUA and MODIS TERRA snow cover maps, thus reducing the presence of cloudy pixels and no-data-values due to topography. By using these maps, daily time series starting from the winter season (November - May) 2002 till 2008/2009 have been created. Along with snow maps from MODIS images, also some snow cover maps derived from LANDSAT images have been used. Due to their high resolution (< 30 m) they have been considered as an evaluation tool. The snow cover maps are then compared with the hydrological GEOtop model outputs. The main objectives of this work are: 1. Evaluation of the MODIS snow cover algorithm using LANDSAT data 2. Investigation of snow cover, and snow cover duration for the area of interest for South Tyrol 3. Derivation and interpretation of the snow line for the seven winter seasons 4. An evaluation of the model outputs in order to determine the situations in which the remotely sensed data can be used to improve the model prediction of snow coverage and related variables References [1] Rigon R., Bertoldi G. and Over T.M. 2006. GEOtop: A Distributed Hydrological Model with Coupled Water and Energy Budgets, Journal of Hydrometeorology, 7: 371-388. [2] Rastner P., Irsara L., Schellenberger T., Della Chiesa S., Bertoldi G., Endrizzi S., Notarnicola C., Steurer C., Zebisch M. 2009. Monitoraggio del manto nevoso in aree alpine con dati MODIS multi-temporali e modelli idrologici, 13th ASITA National Conference, 1-4.12.2009, Bari, Italy. [3] Zanotti F., Endrizzi S., Bertoldi G. and Rigon R. 2004. The GEOtop snow module. Hydrological Processes, 18: 3667-3679. DOI:10.1002/hyp.5794.

Sampling supraglacial debris thickness using terrestrial photogrammetry

NASA Astrophysics Data System (ADS)

Nicholson, Lindsey; Mertes, Jordan

2017-04-01

The melt rate of debris-covered ice differs to that of clean ice primarily as a function of debris thickness. The spatial distribution of supraglacial debris thickness must therefore be known in order to understand how it is likely to impact glacier behaviour, and meltwater contribution to local hydrological resources and global sea level rise. However, practical means of determining debris cover thickness remain elusive. In this study we explore the utility of terrestrial photogrammetry to produce high resolution, scaled and texturized digital terrain models of debris cover exposures above ice cliffs as a means of quantifying and characterizing debris thickness. Two Nikon D5000 DSLRs with Tamron 100mm lenses were used to photograph a sample area of the Ngozumpa glacier in the Khumbu Himal of Nepal in April 2016. A Structure from Motion workflow using Agisoft Photoscan software was used to generate a surface models with <10cm resolution. A Trimble Geo7X differential GPS with Zephyr antenna, along with a local base station, was used to precisely measure marked ground control points to scale the photogrammetric surface model. Measurements of debris thickness along the exposed cliffline were made from this scaled model, assuming that the ice surface at the debris-ice boundary is horizontal, and these data are compared to 50 manual point measurements along the same clifftops. We conclude that sufficiently high resolution photogrammetry, with precise scaling information, provides a useful means to determine debris thickness at clifftop exposures. The resolution of the possible measurements depends on image resolution, the accuracy of the ground control points and the computational capacity to generate centimetre scale surface models. Application of such techniques to sufficiently high resolution imagery from UAV-borne cameras may offer a powerful means of determining debris thickness distribution patterns over debris covered glacier termini.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Research on the Construction of Remote Sensing Automatic Interpretation Symbol Big Data

NASA Astrophysics Data System (ADS)

Gao, Y.; Liu, R.; Liu, J.; Cheng, T.

2018-04-01

Remote sensing automatic interpretation symbol (RSAIS) is an inexpensive and fast method in providing precise in-situ information for image interpretation and accuracy. This study designed a scientific and precise RSAIS data characterization method, as well as a distributed and cloud architecture massive data storage method. Additionally, it introduced an offline and online data update mode and a dynamic data evaluation mechanism, with the aim to create an efficient approach for RSAIS big data construction. Finally, a national RSAIS database with more than 3 million samples covering 86 land types was constructed during 2013-2015 based on the National Geographic Conditions Monitoring Project of China and then annually updated since the 2016 period. The RSAIS big data has proven to be a good method for large scale image interpretation and field validation. It is also notable that it has the potential to solve image automatic interpretation with the assistance of deep learning technology in the remote sensing big data era.

Classification of Land Cover and Land Use Based on Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Yang, Chun; Rottensteiner, Franz; Heipke, Christian

2018-04-01

Land cover describes the physical material of the earth's surface, whereas land use describes the socio-economic function of a piece of land. Land use information is typically collected in geospatial databases. As such databases become outdated quickly, an automatic update process is required. This paper presents a new approach to determine land cover and to classify land use objects based on convolutional neural networks (CNN). The input data are aerial images and derived data such as digital surface models. Firstly, we apply a CNN to determine the land cover for each pixel of the input image. We compare different CNN structures, all of them based on an encoder-decoder structure for obtaining dense class predictions. Secondly, we propose a new CNN-based methodology for the prediction of the land use label of objects from a geospatial database. In this context, we present a strategy for generating image patches of identical size from the input data, which are classified by a CNN. Again, we compare different CNN architectures. Our experiments show that an overall accuracy of up to 85.7 % and 77.4 % can be achieved for land cover and land use, respectively. The classification of land cover has a positive contribution to the classification of the land use classification.

Manhole Cover Detection Using Vehicle-Based Multi-Sensor Data

NASA Astrophysics Data System (ADS)

Ji, S.; Shi, Y.; Shi, Z.

2012-07-01

A new method combined wit multi-view matching and feature extraction technique is developed to detect manhole covers on the streets using close-range images combined with GPS/IMU and LINDAR data. The covers are an important target on the road traffic as same as transport signs, traffic lights and zebra crossing but with more unified shapes. However, the different shoot angle and distance, ground material, complex street scene especially its shadow, and cars in the road have a great impact on the cover detection rate. The paper introduces a new method in edge detection and feature extraction in order to overcome these difficulties and greatly improve the detection rate. The LIDAR data are used to do scene segmentation and the street scene and cars are excluded from the roads. And edge detection method base on canny which sensitive to arcs and ellipses is applied on the segmented road scene and the interesting areas contain arcs are extracted and fitted to ellipse. The ellipse are then resampled for invariance to shooting angle and distance and then are matched to adjacent images for further checking if covers and . More than 1000 images with different scenes are used in our tests and the detection rate is analyzed. The results verified our method have its advantages in correct covers detection in the complex street scene.

Near-infrared properties of quasar and Seyfert host galaxies

NASA Astrophysics Data System (ADS)

McLeod, Kim Katris

1994-01-01

We present near-infrared images of nearly 100 host galaxies of Active Galactic Nuclei (AGN). Our quasar sample is comprised of the 50 quasars from the Palomar Green Bright Quasar Survey with redshifts z less than or equal to 0.3. We have restricted the redshift range to ensure adequate spatial resolution, galaxy detectability, and minimal distance-dependent effects, while still giving a large sample of objects. For lower-luminosity AGN we have chosen to image the CfA Seyfert sample. This sample is composed of 48 Seyferts, roughly equally divided among types 1, 1.5-1.9, and 2. This sample was spectroscopically selected, and, therefore, is not biased towards Seyferts with significant star formation. Taken together, these samples allow a statistical look at the continuity of host galaxy properties over a factor of 10,000 in nuclear luminosity. We find the near-infrared light to be a good tracer of luminous mass in these galaxies. The Seyferts are found in galaxies of type SO to Sc. The radio quiet quasars live in similar kinds of galaxies spanning the same range of mass centered around L(*). However, for the most luminous quasars, there is a correlation between the minimum host galaxy mass and the luminosity of the active nucleus. Radio-loud quasars are generally found in hosts more massive than an L(*) galaxy. We also detect a population of low mass host galaxies with very low luminosity Seyfert nuclei. The low luminosity quasars and the Seyferts both tend to lie in host galaxies seen preferentially face-on, which suggests there is a substantial amount of obscuration coplanar with the galaxian disk. The obscuration must be geometrically thick (thickness-to-radius approximately 1) and must cover a significant fraction of the narrow line region (r greater than 100 pc). We have examined our images for signs of perturbations that could drive fuel toward the galaxy nucleus, but there are none we can identify at a significant level. The critical element for fueling is evidently not reflected clearly in the large scale distribution of luminous mass in the galaxy. We also present an infrared image of the jet of SC 273 and compare it to optical and radio images from the literature.

Near-Infrared Properties of Quasar and Seyfert Host Galaxies

NASA Astrophysics Data System (ADS)

McLeod, Kim Katris

1995-01-01

We present near-infrared images of nearly 100 host galaxies of Active Galactic Nuclei (AGN). Our quasar sample is comprised of the 50 quasars from the Palomar Green Bright Quasar Survey with redshifts z\\<= 0.3. We have restricted the redshift range to ensure adequate spatial resolution, galaxy detectability, and minimal distance-dependent effects, while still giving a large sample of objects. For lower-luminosity AGN we have chosen to image the CfA Seyfert sample. This sample is composed of 48 Seyferts, roughly equally divided among types 1, 1.5-1.9, and 2. This sample was spectroscopically selected, and, therefore, is not biased towards Seyferts with significant star formation. Taken together, these samples allow a statistical look at the continuity of host-galaxy properties over a factor of 10,000 in nuclear luminosity. We find the near-infrared light to be a good tracer of luminous mass in these galaxies. The Seyferts are found in galaxies of type S0 to Sc. The radio quiet quasars live in similar kinds of galaxies spanning the same range of mass centered around L*. However, for the most luminous quasars, there is a correlation between the minimum host-galaxy mass and the luminosity of the active nucleus. Radio-loud quasars are generally found in hosts more massive than an L* galaxy. We also detect a population of low-mass host galaxies with very low-luminosity Seyfert nuclei. The low luminosity quasars and the Seyferts both tend to lie in host galaxies seen preferentially face-on, which suggests there is a substantial amount of obscuration coplanar with the galaxian disk. The obscuration must be geometrically thick (thickness-to-radius ~1) and must cover a significant fraction of the narrow line region (r>100 pc). We have examined our images for signs of perturbations that could drive fuel toward the galaxy nucleus, but there are none we can identify at a significant level. The critical element for fueling is evidently not reflected clearly in the large scale distribution of luminous mass in the galaxy. We also present an infrared image of the jet of 3C 273 and compare it to visible and radio images from the literature. (SECTION: Dissertation Summaries)

NASA IMAGESEER: NASA IMAGEs for Science, Education, Experimentation and Research

NASA Technical Reports Server (NTRS)

Le Moigne, Jacqueline; Grubb, Thomas G.; Milner, Barbara C.

2012-01-01

A number of web-accessible databases, including medical, military or other image data, offer universities and other users the ability to teach or research new Image Processing techniques on relevant and well-documented data. However, NASA images have traditionally been difficult for researchers to find, are often only available in hard-to-use formats, and do not always provide sufficient context and background for a non-NASA Scientist user to understand their content. The new IMAGESEER (IMAGEs for Science, Education, Experimentation and Research) database seeks to address these issues. Through a graphically-rich web site for browsing and downloading all of the selected datasets, benchmarks, and tutorials, IMAGESEER provides a widely accessible database of NASA-centric, easy to read, image data for teaching or validating new Image Processing algorithms. As such, IMAGESEER fosters collaboration between NASA and research organizations while simultaneously encouraging development of new and enhanced Image Processing algorithms. The first prototype includes a representative sampling of NASA multispectral and hyperspectral images from several Earth Science instruments, along with a few small tutorials. Image processing techniques are currently represented with cloud detection, image registration, and map cover/classification. For each technique, corresponding data are selected from four different geographic regions, i.e., mountains, urban, water coastal, and agriculture areas. Satellite images have been collected from several instruments - Landsat-5 and -7 Thematic Mappers, Earth Observing-1 (EO-1) Advanced Land Imager (ALI) and Hyperion, and the Moderate Resolution Imaging Spectroradiometer (MODIS). After geo-registration, these images are available in simple common formats such as GeoTIFF and raw formats, along with associated benchmark data.

SparseBeads data: benchmarking sparsity-regularized computed tomography

NASA Astrophysics Data System (ADS)

Jørgensen, Jakob S.; Coban, Sophia B.; Lionheart, William R. B.; McDonald, Samuel A.; Withers, Philip J.

2017-12-01

Sparsity regularization (SR) such as total variation (TV) minimization allows accurate image reconstruction in x-ray computed tomography (CT) from fewer projections than analytical methods. Exactly how few projections suffice and how this number may depend on the image remain poorly understood. Compressive sensing connects the critical number of projections to the image sparsity, but does not cover CT, however empirical results suggest a similar connection. The present work establishes for real CT data a connection between gradient sparsity and the sufficient number of projections for accurate TV-regularized reconstruction. A collection of 48 x-ray CT datasets called SparseBeads was designed for benchmarking SR reconstruction algorithms. Beadpacks comprising glass beads of five different sizes as well as mixtures were scanned in a micro-CT scanner to provide structured datasets with variable image sparsity levels, number of projections and noise levels to allow the systematic assessment of parameters affecting performance of SR reconstruction algorithms6. Using the SparseBeads data, TV-regularized reconstruction quality was assessed as a function of numbers of projections and gradient sparsity. The critical number of projections for satisfactory TV-regularized reconstruction increased almost linearly with the gradient sparsity. This establishes a quantitative guideline from which one may predict how few projections to acquire based on expected sample sparsity level as an aid in planning of dose- or time-critical experiments. The results are expected to hold for samples of similar characteristics, i.e. consisting of few, distinct phases with relatively simple structure. Such cases are plentiful in porous media, composite materials, foams, as well as non-destructive testing and metrology. For samples of other characteristics the proposed methodology may be used to investigate similar relations.

Local X-ray Computed Tomography Imaging for Mineralogical and Pore Characterization

NASA Astrophysics Data System (ADS)

Mills, G.; Willson, C. S.

2015-12-01

Sample size, material properties and image resolution are all tradeoffs that must be considered when imaging porous media samples with X-ray computed tomography. In many natural and engineered samples, pore and throat sizes span several orders of magnitude and are often correlated with the material composition. Local tomography is a nondestructive technique that images a subvolume, within a larger specimen, at high resolution and uses low-resolution tomography data from the larger specimen to reduce reconstruction error. The high-resolution, subvolume data can be used to extract important fine-scale properties but, due to the additional noise associated with the truncated dataset, it makes segmentation of different materials and mineral phases a challenge. The low-resolution data of a larger specimen is typically of much higher-quality making material characterization much easier. In addition, the imaging of a larger domain, allows for mm-scale bulk properties and heterogeneities to be determined. In this research, a 7 mm diameter and ~15 mm in length sandstone core was scanned twice. The first scan was performed to cover the entire diameter and length of the specimen at an image voxel resolution of 4.1 μm. The second scan was performed on a subvolume, ~1.3 mm in length and ~2.1 mm in diameter, at an image voxel resolution of 1.08 μm. After image processing and segmentation, the pore network structure and mineralogical features were extracted from the low-resolution dataset. Due to the noise in the truncated high-resolution dataset, several image processing approaches were applied prior to image segmentation and extraction of the pore network structure and mineralogy. Results from the different truncated tomography segmented data sets are compared to each other to evaluate the potential of each approach in identifying the different solid phases from the original 16 bit data set. The truncated tomography segmented data sets were also compared to the whole-core tomography segmented data set in two ways: (1) assessment of the porosity and pore size distribution at different scales; and (2) comparison of the mineralogical composition and distribution. Finally, registration of the two datasets will be used to show how the pore structure and mineralogy details at the two scales can be used to supplement each other.

Developing consistent Landsat data sets for large area applications: the MRLC 2001 protocol

USGS Publications Warehouse

Chander, G.; Huang, Chengquan; Yang, Limin; Homer, Collin G.; Larson, C.

2009-01-01

One of the major efforts in large area land cover mapping over the last two decades was the completion of two U.S. National Land Cover Data sets (NLCD), developed with nominal 1992 and 2001 Landsat imagery under the auspices of the MultiResolution Land Characteristics (MRLC) Consortium. Following the successful generation of NLCD 1992, a second generation MRLC initiative was launched with two primary goals: (1) to develop a consistent Landsat imagery data set for the U.S. and (2) to develop a second generation National Land Cover Database (NLCD 2001). One of the key enhancements was the formulation of an image preprocessing protocol and implementation of a consistent image processing method. The core data set of the NLCD 2001 database consists of Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images. This letter details the procedures for processing the original ETM+ images and more recent scenes added to the database. NLCD 2001 products include Anderson Level II land cover classes, percent tree canopy, and percent urban imperviousness at 30-m resolution derived from Landsat imagery. The products are freely available for download to the general public from the MRLC Consortium Web site at http://www.mrlc.gov.

Evaluating remotely sensed plant count accuracy with differing unmanned aircraft system altitudes, physical canopy separations, and ground covers

NASA Astrophysics Data System (ADS)

Leiva, Josue Nahun; Robbins, James; Saraswat, Dharmendra; She, Ying; Ehsani, Reza

2017-07-01

This study evaluated the effect of flight altitude and canopy separation of container-grown Fire Chief™ arborvitae (Thuja occidentalis L.) on counting accuracy. Images were taken at 6, 12, and 22 m above the ground using unmanned aircraft systems. Plants were spaced to achieve three canopy separation treatments: 5 cm between canopy edges, canopy edges touching, and 5 cm of canopy edge overlap. Plants were placed on two different ground covers: black fabric and gravel. A counting algorithm was trained using Feature Analyst®. Total counting error, false positives, and unidentified plants were reported for images analyzed. In general, total counting error was smaller when plants were fully separated. The effect of ground cover on counting accuracy varied with the counting algorithm. Total counting error for plants placed on gravel (-8) was larger than for those on a black fabric (-2), however, false positive counts were similar for black fabric (6) and gravel (6). Nevertheless, output images of plants placed on gravel did not show a negative effect due to the ground cover but was impacted by differences in image spatial resolution.

The EO-1 hyperion and advanced land imager sensors for use in tundra classification studies within the Upper Kuparuk River Basin, Alaska

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.

Computer generated maps from digital satellite data - A case study in Florida

NASA Technical Reports Server (NTRS)

Arvanitis, L. G.; Reich, R. M.; Newburne, R.

1981-01-01

Ground cover maps are important tools to a wide array of users. Over the past three decades, much progress has been made in supplementing planimetric and topographic maps with ground cover details obtained from aerial photographs. The present investigation evaluates the feasibility of using computer maps of ground cover from satellite input tapes. Attention is given to the selection of test sites, a satellite data processing system, a multispectral image analyzer, general purpose computer-generated maps, the preliminary evaluation of computer maps, a test for areal correspondence, the preparation of overlays and acreage estimation of land cover types on the Landsat computer maps. There is every indication to suggest that digital multispectral image processing systems based on Landsat input data will play an increasingly important role in pattern recognition and mapping land cover in the years to come.

Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

NASA Astrophysics Data System (ADS)

Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

2016-06-01

The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

Strong-lensing analysis of a complete sample of 12 MACS clusters at z > 0.5: mass models and Einstein radii

NASA Astrophysics Data System (ADS)

Zitrin, Adi; Broadhurst, Tom; Barkana, Rennan; Rephaeli, Yoel; Benítez, Narciso

2011-01-01

We present the results of a strong-lensing analysis of a complete sample of 12 very luminous X-ray clusters at z > 0.5 using HST/ACS images. Our modelling technique has uncovered some of the largest known critical curves outlined by many accurately predicted sets of multiple images. The distribution of Einstein radii has a median value of ≃28 arcsec (for a source redshift of zs˜ 2), twice as large as other lower z samples, and extends to 55 arcsec for MACS J0717.5+3745, with an impressive enclosed Einstein mass of 7.4 × 1014 M⊙. We find that nine clusters cover a very large area (>2.5 arcmin2) of high magnification (μ > 10×) for a source redshift of zs˜ 8, providing primary targets for accessing the first stars and galaxies. We compare our results with theoretical predictions of the standard Λ cold dark matter (ΛCDM) model which we show systematically fall short of our measured Einstein radii by a factor of ≃1.4, after accounting for the effect of lensing projection. Nevertheless, a revised analysis, once arc redshifts become available, and similar analyses of larger samples, is needed in order to establish more precisely the level of discrepancy with ΛCDM predictions.

Imaging spectrometer measurement of water vapor in the 400 to 2500 nm spectral region

NASA Technical Reports Server (NTRS)

Green, Robert O.; Roberts, Dar A.; Conel, James E.; Dozier, Jeff

1995-01-01

The Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) measures the total upwelling spectral radiance from 400 to 2500 nm sampled at 10 nm intervals. The instrument acquires spectral data at an altitude of 20 km above sea level, as images of 11 by up to 100 km at 17x17 meter spatial sampling. We have developed a nonlinear spectral fitting algorithm coupled with a radiative transfer code to derive the total path water vapor from the spectrum, measured for each spatial element in an AVIRIS image. The algorithm compensates for variation in the surface spectral reflectance and atmospheric aerosols. It uses water vapor absorption bands centered at 940 nm, 1040 nm, and 1380 nm. We analyze data sets with water vapor abundances ranging from 1 to 40 perceptible millimeters. In one data set, the total path water vapor varies from 7 to 21 mm over a distance of less than 10 km. We have analyzed a time series of five images acquired at 12 minute intervals; these show spatially heterogeneous changes of advocated water vapor of 25 percent over 1 hour. The algorithm determines water vapor for images with a range of ground covers, including bare rock and soil, sparse to dense vegetation, snow and ice, open water, and clouds. The precision of the water vapor determination approaches one percent. However, the precision is sensitive to the absolute abundance and the absorption strength of the atmospheric water vapor band analyzed. We have evaluated the accuracy of the algorithm by comparing several surface-based determinations of water vapor at the time of the AVIRIS data acquisition. The agreement between the AVIRIS measured water vapor and the in situ surface radiometer and surface interferometer measured water vapor is 5 to 10 percent.

Patterns of fire activity over Indonesia and Malaysia from polar and geostationary satellite observations

NASA Astrophysics Data System (ADS)

Hyer, Edward J.; Reid, Jeffrey S.; Prins, Elaine M.; Hoffman, Jay P.; Schmidt, Christopher C.; Miettinen, Jukka I.; Giglio, Louis

2013-03-01

Biomass burning patterns over the Maritime Continent of Southeast Asia are examined using a new active fire detection product based on application of the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) to data from the imagers on the MTSAT geostationary satellites operated by the Japanese space agency JAXA. Data from MTSAT-1R and MTSAT-2 covering 34 months from September 2008 to July 2011 are examined for a study region consisting of Indonesia, Malaysia, and nearby environs. The spatial and temporal distributions of fires detected in the MTSAT WF_ABBA product are described and compared with active fire observations from MODIS MOD14 data. Land cover distributions for the two instruments are examined using a new 250 m land cover product from the National University of Singapore. The two products show broadly similar patterns of fire activity, land cover distribution of fires, and pixel fire radiative power (FRP). However, the MTSAT WF_ABBA data differ from MOD14 in important ways. Relative to MODIS, the MTSAT WF_ABBA product has lower overall detection efficiency, but more fires detected due to more frequent looks, a greater relative fraction of fires in forest and a lower relative fraction of fires in open areas, and significantly higher single-pixel retrieved FRP. The differences in land cover distribution and FRP between the MTSAT and MODIS products are shown to be qualitatively consistent with expectations based on pixel size and diurnal sampling. The MTSAT WF_ABBA data are used to calculate coverage-corrected diurnal cycles of fire for different regions within the study area. These diurnal cycles are preliminary but demonstrate that the fraction of diurnal fire activity sampled by the two MODIS sensors varies significantly by region and vegetation type. Based on the results from comparison of the two fire products, a series of steps is outlined to account for some of the systematic biases in each of these satellite products in order to produce a successful merged fire detection product.

Attempt at quantifying human-induced land-cover change during the Holocene in central eastern China

NASA Astrophysics Data System (ADS)

Li, Furong; Gaillard, Marie-José; Mazier, Florence; Sugita, Shinya; Xu, Qinghai; Li, Yuecong; Zhou, Zhongze

2016-04-01

China is one of the key regions of the world where agricultural civilizations already flourished several millennia ago. However, the role of human activity in vegetation change is not yet fully understood. As a contribution to the PAGES LandCover6k initiative, this study aims to achieve a first attempt at Holocene land-cover reconstructions in the temperate zone of China using the REVEALS model (Sugita, 2007). Pollen productivity estimates (PPEs) are key parameters required for the model and were lacking so far for major taxa characteristic of ancient cultural landscapes in that part of the world. Remains of traditional agricultural structures and practices are still found in the low mountain ranges of the Shandong province located in central-eastern China. The area was chosen for a study of pollen-vegetation relationships and calculation of pollen productivity estimates. Pollen counts and vegetation data from 37 random sites within an area of 200 x 100 km are used for calculation. The vegetation inventory within 100 meters from the pollen sampling site follows the standard methods of Bunting et al. (2013). Vegetation data beyond 100 meters up to 1.5 km from the pollen sampling site is extracted from satellite images. The PPEs are calculated using the three sub-models of the Extended R-value model and compared with existing PPEs from northern China's biomes and temperate Europe. The PPEs' relevance for reconstruction of past human-induced land-cover change in temperate China are evaluated. Key words China, traditional agricultural landscape, ERV model, pollen productivity estimates References Bunting, M. J., et al. (2013). "Palynological perspectives on vegetation survey: a critical step for model-based reconstruction of Quaternary land cover." Quaternary Science Reviews 82: 41-55. Sugita, S. (2007). "Theory of quantitative reconstruction of vegetation I: pollen from large sites REVEALS regional vegetation composition." The Holocene 17(2): 229-241.

Fabrication of imaging X-ray optics

NASA Astrophysics Data System (ADS)

Catura, R. C.; Joki, E. G.; Brookover, W. J.

The design, fabrication, and performance of optics for X-ray astronomy and laboratory applications are described and illustrated with diagrams, drawings, graphs, photographs, and sample images. Particular attention is given to the Wolter I telescope developed for spectroscopic observation of 8-30-A cosmic X-ray sources from a rocketborne X-ray Objective Grating Spectrometer; this instrument employs three nested paraboloid-hyperboloid mirrors of 5083 Al alloy, figured by diamond turning and covered with a thin coating of acrylic lacquer prior to deposition of a 40-nm-thick layer of Sn. In calibration tests at NASA Marshall, the FWHM of the line-spread function at 1.33 nm was found to be 240 microns, corresponding to 21 arcsec. Also presented are the results of reflectivity measurements on C and W multilayers sputtered on Si and fusion glass substrates.

VizieR Online Data Catalog: GCs in 27 nearby ETGs from the SLUGGS survey (Forbes+, 2017)

NASA Astrophysics Data System (ADS)

Forbes, D. A.; Alabi, A.; Brodie, J. P.; Romanowsky, A. J.; Strader, J.; Foster, C.; Usher, C.; Spitler, L.; Bellstedt, S.; Pastorello, N.; Villaume, A.; Wasserman, A.; Pota, V.

2018-04-01

Our sample consists of GC systems associated with 25 early-type galaxies from the SLUGGS survey (Brodie et al. 2014ApJ...796...52B) plus two of the three bonus galaxies (NGC 3607 and NGC 5866) that were observed with the same setup. We have obtained wide-field multi-filter imaging of the SLUGGS galaxies using the Subaru telescope under =<1 arcsec seeing conditions. This is supplemented by HST and CFHT imaging. Spectroscopic observations of GC candidates were obtained over the last decade using the DEIMOS spectrograph (Faber et al. 2003SPIE.4841.1657F) on the Keck II 10 m telescope. The DEIMOS instrument is used in multi-slit mode, with each slit mask covering an area of ~16x5 arcmin2. (5 data files).

Processing and Probability Analysis of Pulsed Terahertz NDE of Corrosion under Shuttle Tile Data

NASA Technical Reports Server (NTRS)

Anastasi, Robert F.; Madaras, Eric I.; Seebo, Jeffrey P.; Ely, Thomas M.

2009-01-01

This paper examines data processing and probability analysis of pulsed terahertz NDE scans of corrosion defects under a Shuttle tile. Pulsed terahertz data collected from an aluminum plate with fabricated corrosion defects and covered with a Shuttle tile is presented. The corrosion defects imaged were fabricated by electrochemically etching areas of various diameter and depth in the plate. In this work, the aluminum plate echo signal is located in the terahertz time-of-flight data and a threshold is applied to produce a binary image of sample features. Feature location and area are examined and identified as corrosion through comparison with the known defect layout. The results are tabulated with hit, miss, or false call information for a probability of detection analysis that is used to identify an optimal processing threshold.

Data-Driven Multiresolution Camera Using the Foveal Adaptive Pyramid

PubMed Central

González, Martin; Sánchez-Pedraza, Antonio; Marfil, Rebeca; Rodríguez, Juan A.; Bandera, Antonio

2016-01-01

There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a relatively small region, but covering a wide field of view. This is the aim of foveal vision systems. Briefly, they propose to sense a large field of view at a spatially-variant resolution: one relatively small region, the fovea, is mapped at a high resolution, while the rest of the image is captured at a lower resolution. In these systems, this fovea must be moved, from one region of interest to another one, to scan a visual scene. It is interesting that the part of the scene that is covered by the fovea should not be merely spatial, but closely related to perceptual objects. Segmentation and attention are then intimately tied together: while the segmentation process is responsible for extracting perceptively-coherent entities from the scene (proto-objects), attention can guide segmentation. From this loop, the concept of foveal attention arises. This work proposes a hardware system for mapping a uniformly-sampled sensor to a space-variant one. Furthermore, this mapping is tied with a software-based, foveal attention mechanism that takes as input the stream of generated foveal images. The whole hardware/software architecture has been designed to be embedded within an all programmable system on chip (AP SoC). Our results show the flexibility of the data port for exchanging information between the mapping and attention parts of the architecture and the good performance rates of the mapping procedure. Experimental evaluation also demonstrates that the segmentation method and the attention model provide results comparable to other more computationally-expensive algorithms. PMID:27898029

Data-Driven Multiresolution Camera Using the Foveal Adaptive Pyramid.

PubMed

González, Martin; Sánchez-Pedraza, Antonio; Marfil, Rebeca; Rodríguez, Juan A; Bandera, Antonio

2016-11-26

There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a relatively small region, but covering a wide field of view. This is the aim of foveal vision systems. Briefly, they propose to sense a large field of view at a spatially-variant resolution: one relatively small region, the fovea, is mapped at a high resolution, while the rest of the image is captured at a lower resolution. In these systems, this fovea must be moved, from one region of interest to another one, to scan a visual scene. It is interesting that the part of the scene that is covered by the fovea should not be merely spatial, but closely related to perceptual objects. Segmentation and attention are then intimately tied together: while the segmentation process is responsible for extracting perceptively-coherent entities from the scene (proto-objects), attention can guide segmentation. From this loop, the concept of foveal attention arises. This work proposes a hardware system for mapping a uniformly-sampled sensor to a space-variant one. Furthermore, this mapping is tied with a software-based, foveal attention mechanism that takes as input the stream of generated foveal images. The whole hardware/software architecture has been designed to be embedded within an all programmable system on chip (AP SoC). Our results show the flexibility of the data port for exchanging information between the mapping and attention parts of the architecture and the good performance rates of the mapping procedure. Experimental evaluation also demonstrates that the segmentation method and the attention model provide results comparable to other more computationally-expensive algorithms.

Infrared Sky Imager (IRSI) Instrument Handbook

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

Morris, Victor R.

2016-04-01

The Infrared Sky Imager (IRSI) deployed at the Atmospheric Radiation Measurement (ARM) Climate Research Facility is a Solmirus Corp. All Sky Infrared Visible Analyzer. The IRSI is an automatic, continuously operating, digital imaging and software system designed to capture hemispheric sky images and provide time series retrievals of fractional sky cover during both the day and night. The instrument provides diurnal, radiometrically calibrated sky imagery in the mid-infrared atmospheric window and imagery in the visible wavelengths for cloud retrievals during daylight hours. The software automatically identifies cloudy and clear regions at user-defined intervals and calculates fractional sky cover, providing amore » real-time display of sky conditions.« less

Atmospheric imaging results from the Mars Exploration Rovers

NASA Astrophysics Data System (ADS)

Lemmon, M.; Athena Science Team

The Athena science payload of the Spirit and Opportunity Mars Exploration Rovers contains instruments capable of measuring radiometric properties of the Martian atmosphere in the visible and the thermal infrared. Remote sensing instruments include Pancam, a color panoramic camera covering 0.4-1.0 microns, and Mini-TES, a thermal infrared spectrometer covering 5-29 microns. Results from atmospheric imaging by Pancam will be covered here. Visible and near-infrared aerosol opacity is monitored by direct solar imaging. Early results show dust opacity near 1 when both rovers landed. Both Spirit and Opportunity have seen dust opacity fall with time, somewhat faster at Spirit's Gusev crater landing site. Diurnal variations are also being monitored at both sites. There is no direct probe of the dust's vertical distribution, but images of the Sun near the horizon and of the twilight will provide constraints on the dust distribution. Dust optical properties and a cross-section weighted aerosol size will be estimated from Pancam images of the sky at varying geometries and times of day. A series of sky imaging sequences has been run with varying illumination geometry. The observations are similar to those reported for Mars Pathfinder.

Is there a real danger of concealing gunshot residue (GSR) particles by skin debris using the tape-lift method for sampling GSR from hands?

PubMed

Zeichner, A

2001-11-01

Experiments were carried out to assess the danger of concealing GSR particles by skin debris using the tape-lift method for sampling GSR from hands. Thirty discrete spherical particles (from GSR and from the debris of oxygen cutting of steel) sized from 8 to 30 microns were mounted on a double-side adhesive coated stubs in known locations using a stereomicroscope. These stubs were then used for dabbing hands 50 times. Some of the particles or parts thereof were covered by skin flakes, however, all particles could be detected using the backscattered electron image (BEI) in the scanning electron microscope (SEM). Also, all could be identified by the energy dispersive X-ray spectroscopy (EDX).

Comparison of the Spectral Properties of Pansharpened Images Generated from AVNIR-2 and Prism Onboard Alos

NASA Astrophysics Data System (ADS)

Matsuoka, M.

2012-07-01

A considerable number of methods for pansharpening remote-sensing images have been developed to generate higher spatial resolution multispectral images by the fusion of lower resolution multispectral images and higher resolution panchromatic images. Because pansharpening alters the spectral properties of multispectral images, method selection is one of the key factors influencing the accuracy of subsequent analyses such as land-cover classification or change detection. In this study, seven pixel-based pansharpening methods (additive wavelet intensity, additive wavelet principal component, generalized Laplacian pyramid with spectral distortion minimization, generalized intensity-hue-saturation (GIHS) transform, GIHS adaptive, Gram-Schmidt spectral sharpening, and block-based synthetic variable ratio) were compared using AVNIR-2 and PRISM onboard ALOS from the viewpoint of the preservation of spectral properties of AVNIR-2. A visual comparison was made between pansharpened images generated from spatially degraded AVNIR-2 and original images over urban, agricultural, and forest areas. The similarity of the images was evaluated in terms of the image contrast, the color distinction, and the brightness of the ground objects. In the quantitative assessment, three kinds of statistical indices, correlation coefficient, ERGAS, and Q index, were calculated by band and land-cover type. These scores were relatively superior in bands 2 and 3 compared with the other two bands, especially over urban and agricultural areas. Band 4 showed a strong dependency on the land-cover type. This was attributable to the differences in the observing spectral wavelengths of the sensors and local scene variances.

Measuring the nonlinear elastic properties of tissue-like phantoms.

PubMed

Erkamp, Ramon Q; Skovoroda, Andrei R; Emelianov, Stanislav Y; O'Donnell, Matthew

2004-04-01

A direct mechanical system simultaneously measuring external force and deformation of samples over a wide dynamic range is used to obtain force-displacement curves of tissue-like phantoms under plain strain deformation. These measurements, covering a wide deformation range, then are used to characterize the nonlinear elastic properties of the phantom materials. The model assumes incompressible media, in which several strain energy potentials are considered. Finite-element analysis is used to evaluate the performance of this material characterization procedure. The procedures developed allow calibration of nonlinear elastic phantoms for elasticity imaging experiments and finite-element simulations.

A novel biosensor array with a wheel-like pattern for glucose, lactate and choline based on electrochemiluminescence imaging.

PubMed

Zhou, Zhenyu; Xu, Linru; Wu, Suozhu; Su, Bin

2014-10-07

Electrochemiluminescence (ECL) imaging provides a superior approach to achieve array detection because of its ability for ultrasensitive multiplex analysis. In this paper, we reported a novel ECL imaging biosensor array modified with an enzyme/carbon nanotubes/chitosan composite film for the determination of glucose, choline and lactate. The biosensor array was constructed by integrating a patterned indium tin oxide (ITO) glass plate with six perforated poly(dimethylsiloxane) (PDMS) covers. ECL is generated by the electrochemical reaction between luminol and hydrogen peroxide that is produced by the enzyme catalysed oxidation of different substrates with molecular oxygen, and ECL images were captured by a charge-coupled device (CCD) camera. The separated electrochemical micro-cells enabled simultaneous assay of six samples at different concentrations. From the established calibration curves, the detection limits were 14 μM for glucose, 40 μM for lactate and 97 μM for choline, respectively. Moreover, multicomponent assays and cross reactivity were also studied, both of which were satisfied for the analysis. This biosensing platform based on ECL imaging shows many distinct advantages, including miniaturization, low cost, and multi-functionalization. We believe that this novel ECL imaging biosensor platform will have potential applications in clinical diagnostics, medicine and food inspection.

Shade images of forested areas obtained from LANDSAT MSS data

NASA Technical Reports Server (NTRS)

Shimabukuro, Yosio Edemir; Smith, James A.

1989-01-01

The pixel size in the present day Remote Sensing systems is large enough to include different types of land cover. Depending upon the target area, several components may be present within the pixel. In forested areas, generally, three main components are present: tree canopy, soil (understory), and shadow. The objective is to generate a shade (shadow) image of forested areas from multispectral measurements of LANDSAT MSS (Multispectral Scanner) data by implementing a linear mixing model, where shadow is considered as one of the primary components in a pixel. The shade images are related to the observed variation in forest structure, i.e., the proportion of inferred shadow in a pixel is related to different forest ages, forest types, and tree crown cover. The Constrained Least Squares (CLS) method is used to generate shade images for forest of eucalyptus and vegetation of cerrado using LANDSAT MSS imagery over Itapeva study area in Brazil. The resulted shade images may explain the difference on ages for forest of eucalyptus and the difference on three crown cover for vegetation of cerrado.

Eolian Features Provide a Glimpse of Candor Chasma Mineralology

NASA Technical Reports Server (NTRS)

2008-01-01

This image of Candor Chasma's eastern end was taken by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) at 0655 UTC (2:55 a.m. EDT) on March 24, 2007. CRISM's image captured 544 colors covering 0.36-3.92 micrometers, and shows features as small as 100 meters (330 feet) across. The region covered is roughly 10 kilometers (6.2 miles) at its narrowest point. Designed to look for a variety of materials on the walls and floor of Candor Chasma, this CRISM observation is somewhat unique in that it is extended along an extended path across the chasma floor to capture extra territory at the expense of spatial resolution.

Candor Chasma is a deep, elongated, steep-sided depression some 813 kilometers (505 miles) in length. It is one of two large chasmata that make up the northern end of the Valles Marineris system. The top image, which illustrates the long path CRISM's cameras scanned to extend the observation in the along-track direction, shows the CRISM image on top of a mosaic of images from the Thermal Emission Imaging System (THEMIS) on Mars Odyssey. The lower two false-color images offer a glimpse of the topography and mineralogy contained within this large chasma. These views were constructed by draping the CRISM images over topography, and viewing the surface in perspective from the northeast. The southern part of CRISM's swath (to the left) covers interior layered deposits along with low ridges (far left) that are an erosional remnant of the chasma wall. The northern end (to the right) reveals the older, eroded chasma wall material, as well as the chasma floor. White lines in the images represent gaps in the data due to the stretching of the image.

The erosive Martian wind appears to have removed dust and debris covering monohydrated sulfate-rich mineral deposits (bright green). Wind-abraded ridges of layered sediments (image center) reveal these deposits more readily, while ridges to the north and south also appear to retain more of a cover of obscuring dust.

CRISM is one of six science instruments on NASA's Mars Reconnaissance Orbiter. Led by The Johns Hopkins University Applied Physics Laboratory, Laurel, Md., the CRISM team includes expertise from universities, government agencies and small businesses in the United States and abroad. NASA's Jet Propulsion Laboratory, a division of the California Institute of Technology in Pasadena, manages the Mars Reconnaissance Orbiter and the Mars Science Laboratory for NASA's Science Mission Directorate, Washington. Lockheed Martin Space Systems, Denver, built the orbiter.

Land use/land cover mapping using multi-scale texture processing of high resolution data

NASA Astrophysics Data System (ADS)

Wong, S. N.; Sarker, M. L. R.

2014-02-01

Land use/land cover (LULC) maps are useful for many purposes, and for a long time remote sensing techniques have been used for LULC mapping using different types of data and image processing techniques. In this research, high resolution satellite data from IKONOS was used to perform land use/land cover mapping in Johor Bahru city and adjacent areas (Malaysia). Spatial image processing was carried out using the six texture algorithms (mean, variance, contrast, homogeneity, entropy, and GLDV angular second moment) with five difference window sizes (from 3×3 to 11×11). Three different classifiers i.e. Maximum Likelihood Classifier (MLC), Artificial Neural Network (ANN) and Supported Vector Machine (SVM) were used to classify the texture parameters of different spectral bands individually and all bands together using the same training and validation samples. Results indicated that texture parameters of all bands together generally showed a better performance (overall accuracy = 90.10%) for land LULC mapping, however, single spectral band could only achieve an overall accuracy of 72.67%. This research also found an improvement of the overall accuracy (OA) using single-texture multi-scales approach (OA = 89.10%) and single-scale multi-textures approach (OA = 90.10%) compared with all original bands (OA = 84.02%) because of the complementary information from different bands and different texture algorithms. On the other hand, all of the three different classifiers have showed high accuracy when using different texture approaches, but SVM generally showed higher accuracy (90.10%) compared to MLC (89.10%) and ANN (89.67%) especially for the complex classes such as urban and road.

Geospatial mapping of Antarctic coastal oasis using geographic object-based image analysis and high resolution satellite imagery

NASA Astrophysics Data System (ADS)

Jawak, Shridhar D.; Luis, Alvarinho J.

2016-04-01

An accurate spatial mapping and characterization of land cover features in cryospheric regions is an essential procedure for many geoscientific studies. A novel semi-automated method was devised by coupling spectral index ratios (SIRs) and geographic object-based image analysis (OBIA) to extract cryospheric geospatial information from very high resolution WorldView 2 (WV-2) satellite imagery. The present study addresses development of multiple rule sets for OBIA-based classification of WV-2 imagery to accurately extract land cover features in the Larsemann Hills, east Antarctica. Multilevel segmentation process was applied to WV-2 image to generate different sizes of geographic image objects corresponding to various land cover features with respect to scale parameter. Several SIRs were applied to geographic objects at different segmentation levels to classify land mass, man-made features, snow/ice, and water bodies. We focus on water body class to identify water areas at the image level, considering their uneven appearance on landmass and ice. The results illustrated that synergetic usage of SIRs and OBIA can provide accurate means to identify land cover classes with an overall classification accuracy of ≍97%. In conclusion, our results suggest that OBIA is a powerful tool for carrying out automatic and semiautomatic analysis for most cryospheric remote-sensing applications, and the synergetic coupling with pixel-based SIRs is found to be a superior method for mining geospatial information.

Chemical imaging analysis of the brain with X-ray methods

NASA Astrophysics Data System (ADS)

Collingwood, Joanna F.; Adams, Freddy

2017-04-01

Cells employ various metal and metalloid ions to augment the structure and the function of proteins and to assist with vital biological processes. In the brain they mediate biochemical processes, and disrupted metabolism of metals may be a contributing factor in neurodegenerative disorders. In this tutorial review we will discuss the particular role of X-ray methods for elemental imaging analysis of accumulated metal species and metal-containing compounds in biological materials, in the context of post-mortem brain tissue. X-rays have the advantage that they have a short wavelength and can penetrate through a thick biological sample. Many of the X-ray microscopy techniques that provide the greatest sensitivity and specificity for trace metal concentrations in biological materials are emerging at synchrotron X-ray facilities. Here, the extremely high flux available across a wide range of soft and hard X-rays, combined with state-of-the-art focusing techniques and ultra-sensitive detectors, makes it viable to undertake direct imaging of a number of elements in brain tissue. The different methods for synchrotron imaging of metals in brain tissues at regional, cellular, and sub-cellular spatial resolution are discussed. Methods covered include X-ray fluorescence for elemental imaging, X-ray absorption spectrometry for speciation imaging, X-ray diffraction for structural imaging, phase contrast for enhanced contrast imaging and scanning transmission X-ray microscopy for spectromicroscopy. Two- and three-dimensional (confocal and tomographic) imaging methods are considered as well as the correlation of X-ray microscopy with other imaging tools.

Image analysis used to count and measure etched tracks from ionizing radiation

NASA Technical Reports Server (NTRS)

Blanford, George E.; Schulz, Cindy K.

1995-01-01

We have developed techniques to use digitized scanning electron micrographs and computer image analysis programs to measure track densities in lunar soil grains and plastic dosimeters. Tracks in lunar samples are formed by highly ionizing solar energetic particles and cosmic rays during near surface exposure on the Moon. The track densities are related to the exposure conditions (depth and time). Distributions of the number of grains as a function of their track densities can reveal the modality of soil maturation. We worked on two samples identified for a consortium study of lunar weathering effects, 61221 and 67701. They were prepared by the lunar curator's staff as polished grain mounts that were etched in boiling 1 N NaOH for 6 h to reveal tracks. We determined that backscattered electron images taken at 10 percent contrast and approximately 50 percent brightness produced suitable high contrast images for analysis. We used the NIH Image program to cut out areas that were unsuitable for measurement such as edges, cracks, etc. We ascertained a gray-scale threshold of 25 to separate tracks from background. We used the computer to count everything that was two pixels or greater in size and to measure the area to obtain track densities. We found an excellent correlation with manual measurements for track densities below 1 x 10(exp 8) cm(exp -2). For track densities between 1 x 10(exp 8) cm(exp -2) to 1 x 10(exp 9) cm(exp -2) we found that a regression formula using the percentage area covered by tracks gave good agreement with manual measurements. We determined the track density distributions for 61221 and 67701. Sample 61221 is an immature sample, but not pristine. Sample 67701 is a submature sample that is very close to being fully mature. Because only 10 percent of the grains have track densities less than 10(exp 9) cm(exp -2), it is difficulty to determine whether the sample matured in situ or is a mixture of a mature and a submature soil. Although our analysis of plastic dosimeters is at an early stage of development, results are encouraging. The dosimeter was etched in 6.25 N NaOH at 70 deg C for 16 h. We took 200x secondary electron images of the sample and used the NIH Image software to count and measure major and minor diameters of the etched tracks. We calculated the relative track etch rate from a formula that relates it to the major and minor diameters. We made a histogram of the number of tracks versus their relative etch rate. The relative track etching rate is proportional to the linear energy transfer of the particle. With appropriate calibration experiments, the histogram could be used to calculate the radiation dose.

Image analysis used to count and measure etched tracks from ionizing radiation

NASA Astrophysics Data System (ADS)

Blanford, George E.; Schulz, Cindy K.

1995-07-01

We have developed techniques to use digitized scanning electron micrographs and computer image analysis programs to measure track densities in lunar soil grains and plastic dosimeters. Tracks in lunar samples are formed by highly ionizing solar energetic particles and cosmic rays during near surface exposure on the Moon. The track densities are related to the exposure conditions (depth and time). Distributions of the number of grains as a function of their track densities can reveal the modality of soil maturation. We worked on two samples identified for a consortium study of lunar weathering effects, 61221 and 67701. They were prepared by the lunar curator's staff as polished grain mounts that were etched in boiling 1 N NaOH for 6 h to reveal tracks. We determined that backscattered electron images taken at 10 percent contrast and approximately 50 percent brightness produced suitable high contrast images for analysis. We used the NIH Image program to cut out areas that were unsuitable for measurement such as edges, cracks, etc. We ascertained a gray-scale threshold of 25 to separate tracks from background. We used the computer to count everything that was two pixels or greater in size and to measure the area to obtain track densities. We found an excellent correlation with manual measurements for track densities below 1 x 10(exp 8) cm(exp -2). For track densities between 1 x 10(exp 8) cm(exp -2) to 1 x 10(exp 9) cm(exp -2) we found that a regression formula using the percentage area covered by tracks gave good agreement with manual measurements. We determined the track density distributions for 61221 and 67701. Sample 61221 is an immature sample, but not pristine. Sample 67701 is a submature sample that is very close to being fully mature. Because only 10 percent of the grains have track densities less than 10(exp 9) cm(exp -2), it is difficulty to determine whether the sample matured in situ or is a mixture of a mature and a submature soil. Although our analysis of plastic dosimeters is at an early stage of development, results are encouraging. The dosimeter was etched in 6.25 N NaOH at 70 deg C for 16 h.

Cloud cover detection combining high dynamic range sky images and ceilometer measurements

NASA Astrophysics Data System (ADS)

Román, R.; Cazorla, A.; Toledano, C.; Olmo, F. J.; Cachorro, V. E.; de Frutos, A.; Alados-Arboledas, L.

2017-11-01

This paper presents a new algorithm for cloud detection based on high dynamic range images from a sky camera and ceilometer measurements. The algorithm is also able to detect the obstruction of the sun. This algorithm, called CPC (Camera Plus Ceilometer), is based on the assumption that under cloud-free conditions the sky field must show symmetry. The symmetry criteria are applied depending on ceilometer measurements of the cloud base height. CPC algorithm is applied in two Spanish locations (Granada and Valladolid). The performance of CPC retrieving the sun conditions (obstructed or unobstructed) is analyzed in detail using as reference pyranometer measurements at Granada. CPC retrievals are in agreement with those derived from the reference pyranometer in 85% of the cases (it seems that this agreement does not depend on aerosol size or optical depth). The agreement percentage goes down to only 48% when another algorithm, based on Red-Blue Ratio (RBR), is applied to the sky camera images. The retrieved cloud cover at Granada and Valladolid is compared with that registered by trained meteorological observers. CPC cloud cover is in agreement with the reference showing a slight overestimation and a mean absolute error around 1 okta. A major advantage of the CPC algorithm with respect to the RBR method is that the determined cloud cover is independent of aerosol properties. The RBR algorithm overestimates cloud cover for coarse aerosols and high loads. Cloud cover obtained only from ceilometer shows similar results than CPC algorithm; but the horizontal distribution cannot be obtained. In addition, it has been observed that under quick and strong changes on cloud cover ceilometers retrieve a cloud cover fitting worse with the real cloud cover.

Shade images of forested areas obtained from Landsat MSS data

NASA Technical Reports Server (NTRS)

Shimabukuro, Yosio Edemir; Smith, James A.

1989-01-01

The objective of this report is to generate a shade (shadow) image of forested areas from Landsat MSS data by implementing a linear mixing model, where shadow is considered as one of the primary components in a pixel. The shade images are related to the observed variation in forest structure; i.e., the proportion of inferred shadow in a pixel is related to different forest ages, forest types, and tree crown cover. The constrained least-squares method is used to generate shade images for forest of eucalyptus and vegetation of 'cerrado' over the Itapeva study area in Brazil. The resulted shade images may explain the difference on ages for forest of eucalyptus and the difference on tree crown cover for vegetation of cerrado.

Object-based land-cover classification for metropolitan Phoenix, Arizona, using aerial photography

NASA Astrophysics Data System (ADS)

Li, Xiaoxiao; Myint, Soe W.; Zhang, Yujia; Galletti, Chritopher; Zhang, Xiaoxiang; Turner, Billie L.

2014-12-01

Detailed land-cover mapping is essential for a range of research issues addressed by the sustainability and land system sciences and planning. This study uses an object-based approach to create a 1 m land-cover classification map of the expansive Phoenix metropolitan area through the use of high spatial resolution aerial photography from National Agricultural Imagery Program. It employs an expert knowledge decision rule set and incorporates the cadastral GIS vector layer as auxiliary data. The classification rule was established on a hierarchical image object network, and the properties of parcels in the vector layer were used to establish land cover types. Image segmentations were initially utilized to separate the aerial photos into parcel sized objects, and were further used for detailed land type identification within the parcels. Characteristics of image objects from contextual and geometrical aspects were used in the decision rule set to reduce the spectral limitation of the four-band aerial photography. Classification results include 12 land-cover classes and subclasses that may be assessed from the sub-parcel to the landscape scales, facilitating examination of scale dynamics. The proposed object-based classification method provides robust results, uses minimal and readily available ancillary data, and reduces computational time.

Estimating Achievable Accuracy for Global Imaging Spectroscopy Measurement of Non-Photosynthetic Vegetation Cover

NASA Astrophysics Data System (ADS)

Dennison, P. E.; Kokaly, R. F.; Daughtry, C. S. T.; Roberts, D. A.; Thompson, D. R.; Chambers, J. Q.; Nagler, P. L.; Okin, G. S.; Scarth, P.

2016-12-01

Terrestrial vegetation is dynamic, expressing seasonal, annual, and long-term changes in response to climate and disturbance. Phenology and disturbance (e.g. drought, insect attack, and wildfire) can result in a transition from photosynthesizing "green" vegetation to non-photosynthetic vegetation (NPV). NPV cover can include dead and senescent vegetation, plant litter, agricultural residues, and non-photosynthesizing stem tissue. NPV cover is poorly captured by conventional remote sensing vegetation indices, but it is readily separable from substrate cover based on spectral absorption features in the shortwave infrared. We will present past research motivating the need for global NPV measurements, establishing that mapping seasonal NPV cover is critical for improving our understanding of ecosystem function and carbon dynamics. We will also present new research that helps determine a best achievable accuracy for NPV cover estimation. To test the sensitivity of different NPV cover estimation methods, we simulated satellite imaging spectrometer data using field spectra collected over mixtures of NPV, green vegetation, and soil substrate. We incorporated atmospheric transmittance and modeled sensor noise to create simulated spectra with spectral resolutions ranging from 10 to 30 nm. We applied multiple methods of NPV estimation to the simulated spectra, including spectral indices, spectral feature analysis, multiple endmember spectral mixture analysis, and partial least squares regression, and compared the accuracy and bias of each method. These results prescribe sensor characteristics for an imaging spectrometer mission with NPV measurement capabilities, as well as a "Quantified Earth Science Objective" for global measurement of NPV cover. Copyright 2016, all rights reserved.

Deep convolutional neural network training enrichment using multi-view object-based analysis of Unmanned Aerial systems imagery for wetlands classification

NASA Astrophysics Data System (ADS)

Liu, Tao; Abd-Elrahman, Amr

2018-05-01

Deep convolutional neural network (DCNN) requires massive training datasets to trigger its image classification power, while collecting training samples for remote sensing application is usually an expensive process. When DCNN is simply implemented with traditional object-based image analysis (OBIA) for classification of Unmanned Aerial systems (UAS) orthoimage, its power may be undermined if the number training samples is relatively small. This research aims to develop a novel OBIA classification approach that can take advantage of DCNN by enriching the training dataset automatically using multi-view data. Specifically, this study introduces a Multi-View Object-based classification using Deep convolutional neural network (MODe) method to process UAS images for land cover classification. MODe conducts the classification on multi-view UAS images instead of directly on the orthoimage, and gets the final results via a voting procedure. 10-fold cross validation results show the mean overall classification accuracy increasing substantially from 65.32%, when DCNN was applied on the orthoimage to 82.08% achieved when MODe was implemented. This study also compared the performances of the support vector machine (SVM) and random forest (RF) classifiers with DCNN under traditional OBIA and the proposed multi-view OBIA frameworks. The results indicate that the advantage of DCNN over traditional classifiers in terms of accuracy is more obvious when these classifiers were applied with the proposed multi-view OBIA framework than when these classifiers were applied within the traditional OBIA framework.

quanTLC, an online open-source solution for videodensitometric quantification.

PubMed

Fichou, Dimitri; Morlock, Gertrud E

2018-07-27

The image is the key feature of planar chromatography. Videodensitometry by digital image conversion is the fastest way of its evaluation. Instead of scanning single sample tracks one after the other, only few clicks are needed to convert all tracks at one go. A minimalistic software was newly developed, termed quanTLC, that allowed the quantitative evaluation of samples in few minutes. quanTLC includes important assets such as open-source, online, free of charge, intuitive to use and tailored to planar chromatography, as none of the nine existent software for image evaluation covered these aspects altogether. quanTLC supports common image file formats for chromatogram upload. All necessary steps were included, i.e., videodensitogram extraction, preprocessing, automatic peak integration, calibration, statistical data analysis, reporting and data export. The default options for each step are suitable for most analyses while still being tunable, if needed. A one-minute video was recorded to serve as user manual. The software capabilities are shown on the example of a lipophilic dye mixture separation. The quantitative results were verified by comparison with those obtained by commercial videodensitometry software and opto-mechanical slit-scanning densitometry. The data can be exported at each step to be processed in further software, if required. The code was released open-source to be exploited even further. The software itself is online useable without installation and directly accessible at http://shinyapps.ernaehrung.uni-giessen.de/quanTLC. Copyright © 2018 Elsevier B.V. All rights reserved.

Surface plasmon-assisted microscope.

PubMed

Borejdo, Julian; Gryczynski, Zygmunt; Fudala, Rafal; Joshi, Chaitanya R; Borgmann, Kathleen; Ghorpade, Anuja; Gryczynski, Ignacy

2018-06-01

Total internal reflection microscopy (TIRF) has been a powerful tool in biological research. The most valuable feature of the method has been the ability to image 100- to 200-nm-thick layer of cell features adjacent to a coverslip, such as membrane lipids, membrane receptors, and structures proximal-to-basal membranes. Here, we demonstrate an alternative method of imaging thin-layer proximal-to-basal membranes by placing a sample on a high refractive index coverslip covered by a thin layer of gold. The sample is illuminated using the Kretschmann method (i.e., from the top to an aqueous medium). Fluorophores that are close to the metal surface induce surface plasmons in the metal film. Fluorescence from fluorophores near the metal surface couple with surface plasmons allowing them to penetrate the metal surface and emerge at a surface plasmon coupled emission angle. The thickness of the detection layer is further reduced in comparison with TIRF by metal quenching of fluorophores at a close proximity (below 10 nm) to a surface. Fluorescence is collected by a high NA objective and imaged by EMCCD or converted to a signal by avalanche photodiode fed by a single-mode optical fiber inserted in the conjugate image plane of the objective. The system avoids complications of through-the-objective TIRF associated with shared excitation and emission light path, has thin collection thickness, produces excellent background rejection, and is an effective method to study molecular motion. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Bamboo Classification Using WorldView-2 Imagery of Giant Panda Habitat in a Large Shaded Area in Wolong, Sichuan Province, China.

PubMed

Tang, Yunwei; Jing, Linhai; Li, Hui; Liu, Qingjie; Yan, Qi; Li, Xiuxia

2016-11-22

This study explores the ability of WorldView-2 (WV-2) imagery for bamboo mapping in a mountainous region in Sichuan Province, China. A large area of this place is covered by shadows in the image, and only a few sampled points derived were useful. In order to identify bamboos based on sparse training data, the sample size was expanded according to the reflectance of multispectral bands selected using the principal component analysis (PCA). Then, class separability based on the training data was calculated using a feature space optimization method to select the features for classification. Four regular object-based classification methods were applied based on both sets of training data. The results show that the k -nearest neighbor ( k -NN) method produced the greatest accuracy. A geostatistically-weighted k -NN classifier, accounting for the spatial correlation between classes, was then applied to further increase the accuracy. It achieved 82.65% and 93.10% of the producer's and user's accuracies respectively for the bamboo class. The canopy densities were estimated to explain the result. This study demonstrates that the WV-2 image can be used to identify small patches of understory bamboos given limited known samples, and the resulting bamboo distribution facilitates the assessments of the habitats of giant pandas.

Structural characterization of semicrystalline polymer morphologies by imaging-SANS

NASA Astrophysics Data System (ADS)

Radulescu, A.; Fetters, L. J.; Richter, D.

2012-02-01

Control and optimization of polymer properties require the global knowledge of the constitutive microstructures of polymer morphologies in various conditions. The microstructural features can be typically explored over a wide length scale by combining pinhole-, focusing- and ultra-small-angle neutron scattering (SANS) techniques. Though it proved to be a successful approach, this involves major efforts related to the use of various scattering instruments and large amount of samples and the need to ensure the same crystallization kinetics for the samples investigated at various facilities, in different sample cell geometries and at different time intervals. With the installation and commissioning of the MgF2 neutron lenses at the KWS-2 SANS diffractometer installed at the Heinz Maier-Leibnitz neutron source (FRMII reactor) in Garching, a wide Q-range, between 10-4Å-1 and 0.5Å-1, can be covered at a single instrument. This enables investigation of polymer microstructures over a length scale from lnm up to 1μm, while the overall polymer morphology can be further examined up to 100μm by optical microscopy (including crossed polarizers). The study of different semi-crystalline polypropylene-based polymers in solution is discussed and the new imaging-SANS approach allowing for an unambiguous and complete structural characterization of polymer morphologies is presented.

A search for moderate-redshift survivors from the population of luminous compact passive galaxies at high redshift

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

Stockton, Alan; Shih, Hsin-Yi; Larson, Kirsten

2014-01-10

From a search of a ∼2400 deg{sup 2} region covered by both the Sloan Digital Sky Survey and UKIRT Infrared Deep Sky Survey databases, we have attempted to identify galaxies at z ∼ 0.5 that are consistent with their being essentially unmodified examples of the luminous passive compact galaxies found at z ∼ 2.5. After isolating good candidates via deeper imaging, we further refine the sample with Keck moderate-resolution spectroscopy and laser guide star adaptive-optics imaging. For four of the five galaxies that so far remain after passing through this sieve, we analyze plausible star-formation histories based on our spectramore » in order to identify galaxies that may have survived with little modification from the population formed at high redshift. We find two galaxies that are consistent with having formed ≳ 95% of their mass at z > 5. We attempt to estimate masses both from our stellar population determinations and from velocity dispersions. Given the high frequency of small axial ratios, both in our small sample and among samples found at high redshifts, we tentatively suggest that some of the more extreme examples of passive compact galaxies may have prolate morphologies.« less

Recent micro-CT scanner developments at UGCT

NASA Astrophysics Data System (ADS)

Dierick, Manuel; Van Loo, Denis; Masschaele, Bert; Van den Bulcke, Jan; Van Acker, Joris; Cnudde, Veerle; Van Hoorebeke, Luc

2014-04-01

This paper describes two X-ray micro-CT scanners which were recently developed to extend the experimental possibilities of microtomography research at the Centre for X-ray Tomography (www.ugct.ugent.be) of the Ghent University (Belgium). The first scanner, called Nanowood, is a wide-range CT scanner with two X-ray sources (160 kVmax) and two detectors, resolving features down to 0.4 μm in small samples, but allowing samples up to 35 cm to be scanned. This is a sample size range of 3 orders of magnitude, making this scanner well suited for imaging multi-scale materials such as wood, stone, etc. Besides the traditional cone-beam acquisition, Nanowood supports helical acquisition, and it can generate images with significant phase-contrast contributions. The second scanner, known as the Environmental micro-CT scanner (EMCT), is a gantry based micro-CT scanner with variable magnification for scanning objects which are not easy to rotate in a standard micro-CT scanner, for example because they are physically connected to external experimental hardware such as sensor wiring, tubing or others. This scanner resolves 5 μm features, covers a field-of-view of about 12 cm wide with an 80 cm vertical travel range. Both scanners will be extensively described and characterized, and their potential will be demonstrated with some key application results.

Using the Landsat Archive to Estimate and Map Changes in Agriculture, Forests, and other Land Cover Types in East Africa

NASA Astrophysics Data System (ADS)

Healey, S. P.; Oduor, P.; Cohen, W. B.; Yang, Z.; Ouko, E.; Gorelick, N.; Wilson, S.

2017-12-01

Every country's land is distributed among different cover types, such as: agriculture; forests; rangeland; urban areas; and barren lands. Changes in the distribution of these classes can inform us about many things, including: population pressure; effectiveness of preservation efforts; desertification; and stability of the food supply. Good assessment of these changes can also support wise planning, use, and preservation of natural resources. We are using the Landsat archive in two ways to provide needed information about land cover change since the year 2000 in seven East African countries (Ethiopia, Kenya, Malawi, Rwanda, Tanzania, Uganda, and Zambia). First, we are working with local experts to interpret historical land cover change from historical imagery at a probabilistic sample of 2000 locations in each country. This will provide a statistical estimate of land cover change since 2000. Second, we will use the same data to calibrate and validate annual land cover maps for each country. Because spatial context can be critical to development planning through the identification of hot spots, these maps will be a useful complement to the statistical, country-level estimates of change. The Landsat platform is an ideal tool for mapping land cover change because it combines a mix of appropriate spatial and spectral resolution with unparalleled length of service (Landsat 1 launched in 1972). Pilot tests have shown that time series analysis accessing the entire Landsat archive (i.e., many images per year) improves classification accuracy and stability. It is anticipated that this project will meet the civil needs of both governmental and non-governmental users across a range of disciplines.

New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods.

PubMed

Boushey, C J; Spoden, M; Zhu, F M; Delp, E J; Kerr, D A

2017-08-01

For nutrition practitioners and researchers, assessing dietary intake of children and adults with a high level of accuracy continues to be a challenge. Developments in mobile technologies have created a role for images in the assessment of dietary intake. The objective of this review was to examine peer-reviewed published papers covering development, evaluation and/or validation of image-assisted or image-based dietary assessment methods from December 2013 to January 2016. Images taken with handheld devices or wearable cameras have been used to assist traditional dietary assessment methods for portion size estimations made by dietitians (image-assisted methods). Image-assisted approaches can supplement either dietary records or 24-h dietary recalls. In recent years, image-based approaches integrating application technology for mobile devices have been developed (image-based methods). Image-based approaches aim at capturing all eating occasions by images as the primary record of dietary intake, and therefore follow the methodology of food records. The present paper reviews several image-assisted and image-based methods, their benefits and challenges; followed by details on an image-based mobile food record. Mobile technology offers a wide range of feasible options for dietary assessment, which are easier to incorporate into daily routines. The presented studies illustrate that image-assisted methods can improve the accuracy of conventional dietary assessment methods by adding eating occasion detail via pictures captured by an individual (dynamic images). All of the studies reduced underreporting with the help of images compared with results with traditional assessment methods. Studies with larger sample sizes are needed to better delineate attributes with regards to age of user, degree of error and cost.

Gold nanoparticle contrast agents in advanced X-ray imaging technologies.

PubMed

Ahn, Sungsook; Jung, Sung Yong; Lee, Sang Joon

2013-05-17

Recently, there has been significant progress in the field of soft- and hard-X-ray imaging for a wide range of applications, both technically and scientifically, via developments in sources, optics and imaging methodologies. While one community is pursuing extensive applications of available X-ray tools, others are investigating improvements in techniques, including new optics, higher spatial resolutions and brighter compact sources. For increased image quality and more exquisite investigation on characteristic biological phenomena, contrast agents have been employed extensively in imaging technologies. Heavy metal nanoparticles are excellent absorbers of X-rays and can offer excellent improvements in medical diagnosis and X-ray imaging. In this context, the role of gold (Au) is important for advanced X-ray imaging applications. Au has a long-history in a wide range of medical applications and exhibits characteristic interactions with X-rays. Therefore, Au can offer a particular advantage as a tracer and a contrast enhancer in X-ray imaging technologies by sensing the variation in X-ray attenuation in a given sample volume. This review summarizes basic understanding on X-ray imaging from device set-up to technologies. Then this review covers recent studies in the development of X-ray imaging techniques utilizing gold nanoparticles (AuNPs) and their relevant applications, including two- and three-dimensional biological imaging, dynamical processes in a living system, single cell-based imaging and quantitative analysis of circulatory systems and so on. In addition to conventional medical applications, various novel research areas have been developed and are expected to be further developed through AuNP-based X-ray imaging technologies.

Monitoring fungal growth on brown rice grains using rapid and non-destructive hyperspectral imaging.

PubMed

Siripatrawan, U; Makino, Y

2015-04-16

This research aimed to develop a rapid, non-destructive, and accurate method based on hyperspectral imaging (HSI) for monitoring spoilage fungal growth on stored brown rice. Brown rice was inoculated with a non-pathogenic strain of Aspergillus oryzae and stored at 30 °C and 85% RH. Growth of A. oryzae on rice was monitored using viable colony counts, expressed as colony forming units per gram (CFU/g). The fungal development was observed using scanning electron microscopy. The HSI system was used to acquire reflectance images of the samples covering the visible and near-infrared (NIR) wavelength range of 400-1000 nm. Unsupervised self-organizing map (SOM) was used to visualize data classification of different levels of fungal infection. Partial least squares (PLS) regression was used to predict fungal growth on rice grains from the HSI reflectance spectra. The HSI spectral signals decreased with increasing colony counts, while conserving similar spectral pattern during the fungal growth. When integrated with SOM, the proposed HSI method could be used to classify rice samples with different levels of fungal infection without sample manipulation. Moreover, HSI was able to rapidly identify infected rice although the samples showed no symptoms of fungal infection. Based on PLS regression, the coefficient of determination was 0.97 and root mean square error of prediction was 0.39 log (CFU/g), demonstrating that the HSI technique was effective for prediction of fungal infection in rice grains. The ability of HSI to detect fungal infection at early stage would help to prevent contaminated rice grains from entering the food chain. This research provides scientific information on the rapid, non-destructive, and effective fungal detection system for rice grains. Copyright © 2015 Elsevier B.V. All rights reserved.

The brightest galaxies in the first 700 Myr: Building Hubble's legacy of large area IR imaging for JWST and beyond

NASA Astrophysics Data System (ADS)

Trenti, Michele

2017-08-01

Hubble's WFC3 has been a game changer for the study of early galaxy formation in the first 700 Myr after the Big Bang. Reliable samples of sources to redshift z 11, which can be discovered only from space, are now constraining the evolution of the galaxy luminosity function into the epoch of reionization. Unexpectedly but excitingly, the recent spectroscopic confirmations of L>L* galaxies at z>8.5 demonstrate that objects brighter than our own Galaxy are already present 500 Myr after the Big Bang, creating a challenge to current theoretical/numerical models that struggle to explain how galaxies can grow so luminous so quickly. Yet, the existing HST observations do not cover sufficient area, nor sample a large enough diversity of environments to provide an unbiased sample of sources, especially at z 9-11 where only a handful of bright candidates are known. To double this currently insufficient sample size, to constrain effectively the bright-end of the galaxy luminosity function at z 9-10, and to provide targets for follow-up imaging and spectroscopy with JWST, we propose a large-area pure-parallel survey that will discover the Brightest of Reionizing Galaxies (BoRG[4JWST]). We will observe 580 arcmin^2 over 125 sightlines in five WFC3 bands (0.35 to 1.7 micron) using high-quality pure-parallel opportunities available in the cycle (3 orbits or longer). These public observations will identify more than 80 intrinsically bright galaxies at z 8-11, investigate the connection between halo mass, star formation and feedback in progenitors of groups and clusters, and build HST lasting legacy of large-area, near-IR imaging.

Analysis of landscape fragmentation in the Peloncillo Mountains in relation to wildfire, prescribed burning, and cattle grazing

Treesearch

John Rogan; Kelley O' Neal; Stephen Yool

2005-01-01

This paper examined the application of state-of-the-art remote sensing image enhancement and classification techniques for mapping land cover change in the Peloncillo Mountains of Arizona and New Mexico. Spectrally enhanced images acquired August 1985, 1991, 1996, and 2000 were combined with environmental variables such as slope and aspect to map land cover...

Large area mapping of southwestern forest crown cover, canopy height, and biomass using the NASA Multiangle Imaging Spectro-Radiometer

Treesearch

Mark Chopping; Gretchen G. Moisen; Lihong Su; Andrea Laliberte; Albert Rango; John V. Martonchik; Debra P. C. Peters

2008-01-01

A rapid canopy reflectance model inversion experiment was performed using multi-angle reflectance data from the NASA Multi-angle Imaging Spectro-Radiometer (MISR) on the Earth Observing System Terra satellite, with the goal of obtaining measures of forest fractional crown cover, mean canopy height, and aboveground woody biomass for large parts of south-eastern Arizona...

An evaluation of new high resolution image collection and processing techniques for estimating shrub cover and detecting landscape changes associated with military training in arid lands

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

Hansen, D.J.; Ostler, W.K.

2000-02-01

Research funded by the US Department of Defense, US Department of Energy, and the US Environmental Protection Agency as part of Project CS-1131 of the Strategic Environmental Research and Development Program evaluated novel techniques for collecting high-resolution images in the Mojave Desert using helicopters, helium-filled blimps, kites, and hand-held telescoping poles at heights from 1 to 150 meters. Several camera types, lens, films, and digital techniques were evaluated on the basis of their ability to correctly estimate canopy cover of shrubs. A high degree of accuracy was obtained with photo scales of 1:4,000 or larger and flatbed scanning rates frommore » films or prints of 300 lines per inch or larger. Smaller scale images were of value in detecting retrospective changes in cover of large shrubs, but failed to detect smaller shrubs. Excellent results were obtained using inexpensive 35-millimeter cameras and new super-fine grain film such as Kodak's Royal Gold{trademark} (ASA 100) film or megapixel digital cameras. New image-processing software, such as SigmaScan Pro{trademark}, makes it possible to accurately measure areas up to 1 hectare in size for total cover and density in 10 minutes compared to several hours or days of field work. In photographs with scales of 1:1,000 and 1:2,000, it was possible to detect cover and density of up to four dominant shrub species. Canopy cover and other parameters such as width, length, feet diameter, and shape factors can be nearly instantaneously measured for each individual shrub yielding size distribution histograms and other statistical data on plant community structure. Use of the technique is being evaluated in a four-year study of military training impacts at Fort Irwin, California, and results compared with image processing using conventional aerial photography and satellite imagery, including the new 1-meter pixel IKONOS images. The technique is a valuable new emerging tool to accurately assess vegetation structure and landscape changes due to military or other land-use disturbances.« less

Space Radar Image of Safsaf Oasis, Egypt

NASA Image and Video Library

1999-04-15

This three-frequency space radar image of south-central Egypt demonstrates the unique capability of imaging radar to penetrate thin sand cover in arid regions to reveal hidden details below the surface.

Impacts of LUCC on soil properties in the riparian zones of desert oasis with remote sensing data: a case study of the middle Heihe River basin, China.

PubMed

Jiang, Penghui; Cheng, Liang; Li, Manchun; Zhao, Ruifeng; Duan, Yuewei

2015-02-15

Large-scale changes in land use and land cover over long timescales can induce significant variations in soil physicochemical properties, particularly in the riparian zones of arid regions. Frequent reclamation of wetlands and grasslands and intensive agricultural activity have induced significant changes in both land use/cover and soil physicochemical properties in the riparian zones of the middle Heihe River basin of China. The present study aims to explore whether land use/land cover change (LUCC) can well explain the variations in soil properties in the riparian zones of the middle Heihe River basin. To achieve this, we mapped LUCC and quantified the type of land use change using remote sensing images, topographic maps, and GIS analysis techniques. Forty-two sites were selected for soil and vegetation sampling. Then, physical and chemical experiments were employed to determine soil moisture, soil bulk density, soil pH, soil organic carbon, total nitrogen, total potassium, total phosphorous, available nitrogen, available potassium, and available phosphorous. The Independent-Samples Kruskal-Wallis Test, principal component analysis, and a scatter matrix were used to analyze the effects of LUCC on soil properties. The results indicate that the majority of the parameters investigated were affected significantly by LUCC. In particular, soil moisture and soil organic carbon can be explained well by land cover change and land use change, respectively. Furthermore, changes in soil moisture could be attributed primarily to land cover changes. Changes in soil organic carbon were correlated closely with the following land use change types: wetlands-arable, forest-grasslands, and grasslands-desert. Other parameters, including pH and total K, were also found to exhibit significant correlations with LUCC. However, changes in soil nutrients were shown to be induced most probably by human agricultural activity (i.e. fertilize, irrigation, tillage, etc.), rather than by simple conversions from one land use/cover types to the others. Copyright © 2014 Elsevier B.V. All rights reserved.

MODIS Measures Total U.S. Leaf Area

NASA Technical Reports Server (NTRS)

2002-01-01

This composite image over the continental United States was produced with data acquired by the Moderate-resolution Imaging Spectroradiometer (MODIS) during the period March 24 - April 8, 2000. The image is a map of the density of the plant canopy covering the ground. It is the first in a series of images over the continental U.S. produced by the MODIS Land Discipline Group (refer to this site June 2 and 5 for the next two images in the series). The image is a MODIS data product called 'Leaf Area Index,' which is produced by radiometrically measuring the visible and near infrared energy reflected by vegetation. The Leaf Area Index provides information on the structure of plant canopy, showing how much surface area is covered by green foliage relative to total land surface area. In this image, dark green pixels indicate areas where more than 80 percent of the land surface is covered by green vegetation, light green pixels show where leaves cover about 10 to 50 percent of the land surface, and brown pixels show virtually no leaf coverage. The more leaf area a plant has, the more sunlight it can absorb for photosynthesis. Leaf Area Index is one of a new suite of measurements that scientists use to understand how the Earth's land surfaces are changing over time. Their goal is to use these measurements to refine computer models well enough to simulate how the land biosphere influences the natural cycles of water, carbon, and energy throughout the Earth system. This image is the first of its kind from the MODIS instrument, which launched in December 1999 aboard the Terra spacecraft. MODIS began acquiring scientific data on February 24, 2000, when it first opened its aperture door. The MODIS instrument and Terra spacecraft are both managed by NASA's Goddard Space Flight Center, Greenbelt, MD. Image courtesy Steven Running, MODIS Land Group Member, University of Montana

ASTER Images the Island of Hawaii

NASA Image and Video Library

2000-04-26

These images of the Island of Hawaii were acquired on March 19, 2000 by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA's Terra satellite. With its 14 spectral bands from the visible to the thermal infrared wavelength region, and its high spatial resolution of 15 to 90 meters (about 50 to 300 feet), ASTER will image Earth for the next 6 years to map and monitor the changing surface of our planet. Data are shown from the short wavelength and thermal infrared spectral regions, illustrating how different and complementary information is contained in different parts of the spectrum. Left image: This false-color image covers an area 60 kilometers (37 miles) wide and 120 kilometers (75 miles) long in three bands of the short wavelength infrared region. While, much of the island was covered in clouds, the dominant central Mauna Loa volcano, rising to an altitude of 4115 meters (13,500 feet), is cloud-free. Lava flows can be seen radiating from the central crater in green and black tones. As they reach lower elevations, the flows become covered with vegetation, and their image color changes to yellow and orange. Mauna Kea volcano to the north of Mauna Loa has a thin cloud-cover, producing a bluish tone on the image. The ocean in the lower right appears brown due to the color processing. Right image: This image is a false-color composite of three thermal infrared bands. The brightness of the colors is proportional to the temperature, and the hues display differences in rock composition. Clouds are black, because they are the coldest objects in the scene. The ocean and thick vegetation appear dark green because they are colder than bare rock surfaces, and have no thermal spectral features. Lava flows are shades of magenta, green, pink and yellow, reflecting chemical changes due to weathering and relative age differences. http://photojournal.jpl.nasa.gov/catalog/PIA02604

Robust image watermarking using DWT and SVD for copyright protection

NASA Astrophysics Data System (ADS)

Harjito, Bambang; Suryani, Esti

2017-02-01

The Objective of this paper is proposed a robust combined Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The RGB image is called a cover medium, and watermark image is converted into gray scale. Then, they are transformed using DWT so that they can be split into several subbands, namely sub-band LL2, LH2, HL2. The watermark image embeds into the cover medium on sub-band LL2. This scheme aims to obtain the higher robustness level than the previous method which performs of SVD matrix factorization image for copyright protection. The experiment results show that the proposed method has robustness against several image processing attacks such as Gaussian, Poisson and Salt and Pepper Noise. In these attacks, noise has average Normalized Correlation (NC) values of 0.574863 0.889784, 0.889782 respectively. The watermark image can be detected and extracted.

Camouflaging in Digital Image for Secure Communication

NASA Astrophysics Data System (ADS)

Jindal, B.; Singh, A. P.

2013-06-01

The present paper reports on a new type of camouflaging in digital image for hiding crypto-data using moderate bit alteration in the pixel. In the proposed method, cryptography is combined with steganography to provide a two layer security to the hidden data. The novelty of the algorithm proposed in the present work lies in the fact that the information about hidden bit is reflected by parity condition in one part of the image pixel. The remaining part of the image pixel is used to perform local pixel adjustment to improve the visual perception of the cover image. In order to examine the effectiveness of the proposed method, image quality measuring parameters are computed. In addition to this, security analysis is also carried by comparing the histograms of cover and stego images. This scheme provides a higher security as well as robustness to intentional as well as unintentional attacks.

Land use and land cover data changes in Indian Ocean Islands: Case study of Unguja in Zanzibar Island.

PubMed

Mwalusepo, Sizah; Muli, Eliud; Faki, Asha; Raina, Suresh

2017-04-01

Land use and land cover changes will continue to affect resilient human communities and ecosystems as a result of climate change. However, an assessment of land use and land cover changes over time in Indian Ocean Islands is less documented. The land use/cover data changes over 10 years at smaller geographical scale across Unguja Island in Zanzibar were analyzed. Downscaling of the data was obtained from SERVIR through partnership with Kenya-based Regional Centre for Mapping of Resources for Development (RCMRD) database (http://www.servirglobal.net), and clipped down in ArcMap (Version 10.1) to Unguja Island. SERVIR and RCMRD Land Cover Dataset are mainly 30 m multispectral images include Landsat TM and ETM+Multispectral Images. Landscape ecology Statistics tool (LecoS) was used to analysis the land use and land cover changes. The data provide information on the status of the land use and land cover changes along the Unguja Island in Zanzibar. The data is of great significance to the future research on global change.

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders.

PubMed

Tapia-McClung, Horacio; Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology.

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders

PubMed Central

Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology. PMID:27902724

Echographic detectability of optoacoustic signals from low-concentration PEG-coated gold nanorods

PubMed Central

Conversano, Francesco; Soloperto, Giulia; Greco, Antonio; Ragusa, Andrea; Casciaro, Ernesto; Chiriacò, Fernanda; Demitri, Christian; Gigli, Giuseppe; Maffezzoli, Alfonso; Casciaro, Sergio

2012-01-01

Purpose: To evaluate the diagnostic performance of gold nanorod (GNR)-enhanced optoacoustic imaging employing a conventional echographic device and to determine the most effective operative configuration in order to assure optoacoustic effectiveness, nanoparticle stability, and imaging procedure safety. Methods: The most suitable laser parameters were experimentally determined in order to assure nanoparticle stability during the optoacoustic imaging procedures. The selected configuration was then applied to a novel tissue-mimicking phantom, in which GNR solutions covering a wide range of low concentrations (25–200 pM) and different sample volumes (50–200 μL) were exposed to pulsed laser irradiation. GNR-emitted optoacoustic signals were acquired either by a couple of single-element ultrasound probes or by an echographic transducer. Off-line analysis included: (a) quantitative evaluation of the relationships between GNR concentration, sample volume, phantom geometry, and amplitude of optoacoustic signals propagating along different directions; (b) echographic detection of “optoacoustic spots,” analyzing their intensity, spatial distribution, and clinical exploitability. MTT measurements performed on two different cell lines were also used to quantify biocompatibility of the synthesized GNRs in the adopted doses. Results: Laser irradiation at 30 mJ/cm2 for 20 seconds resulted in the best compromise among the requirements of effectiveness, safety, and nanoparticle stability. Amplitude of GNR-emitted optoacoustic pulses was proportional to both sample volume and concentration along each considered propagation direction for all the tested boundary conditions, providing an experimental confirmation of isotropic optoacoustic emission. Average intensity of echographically detected spots showed similar behavior, emphasizing the presence of an “ideal” GNR concentration (100 pM) that optimized optoacoustic effectiveness. The tested GNRs also exhibited high biocompatibility over the entire considered concentration range. Conclusion: An optimal configuration for GNR-enhanced optoacoustic imaging was experimentally determined, demonstrating in particular its feasibility with a conventional echographic device. The proposed approach can be easily extended to quantitative performance evaluation of different contrast agents for optoacoustic imaging. PMID:22927756